rtm phase b 2007-2011

Report

TransLink’s Regional Transit ModelFinal Model Development Report – Phase B: 2007 and 2011

Vancouver, B.C. / Wilmington, DE, December 2008

PTV America Inc.

408-675 West Hastings Street Vancouver, BC, V6B 1N2

(604) 435-2895

South Coast British Columbia

Transportation Authority 4720 Kingsway, Suite 1600

Burnaby, B.C., V5H 4N2 (604) 453 3058

Regional Transit Model, Phase B

TransLink / PTV December, 2008

Table of Contents

1. Introduction .............................................................................................................. 10

2. Network and Service Data Model ............................................................................ 12

2.1. Integrated Network Topology ........................................................................................ 12

2.1.1. General Network and Time Settings 13 2.1.2. Transport Systems 14 2.1.3. Node and Link Network 15 2.1.4. Territories 17 2.1.5. Transit Stops 18

2.2. Transit Service and Operations Data ........................................................................... 22

2.2.1. Operators 22 2.2.2. Vehicle Units and Vehicle Combinations 24 2.2.3. Main Lines 26 2.2.4. Lines, Routes and Schedules 26

2.2.4.1. Bus Schedules 27 2.2.4.2. SkyTrain Schedules 32 2.2.4.3. West Coast Express Schedules 34 2.2.4.4. Ferry Schedules 34

3. Operations Model 2007 ............................................................................................ 35

3.1. Analysis Based on Network and Schedule .................................................................. 35

3.1.1. Travel Time Isochrone 35 3.1.2. Service Frequency and Average Operating Speed 37 3.1.3. Service Statistics per System, Main Line and Territory 39

3.2. Analysis Based on Line Blocking ................................................................................. 41

3.2.1. Procedure Settings 41 3.2.2. Validation of Line Blocking 45

3.2.2.1. Rapid Transit Lines 46 3.2.2.2. CMBC Bus Lines 46 3.2.2.3. Non-CMBC Bus Lines and Ferry 52 3.2.2.4. System Wide Fleet Utilization 52

3.2.3. Results: Operations and Capacity Statistics 54

3.3. Cost-Revenue Analysis ................................................................................................. 57



3.3.1. Fare and Revenue Model Set-Up 57 3.3.1.1. TransLink’s Zone-Based Fare 57 3.3.1.2. WCE Fare Rules 58 3.3.1.3. Ticket Modeling and Average Fare 60

3.3.2. Cost Model Set-Up 61 3.3.3. Validation of the Cost-Revenue Model 65

3.3.3.1. Equivalent Annual Cost and Revenue 65 3.3.3.2. Revenue Validation Results 67 3.3.3.3. Cost Validation Results 67

3.3.4. Summary and Recommendations 71

4. Travel Demand Model 2007 ..................................................................................... 72

4.1. Model Architecture and Applied Methods ................................................................... 72

4.2. Zones and Districts ........................................................................................................ 72

4.2.1. Zone Definition 72 4.2.2. District Definition 73

4.3. Travel Demand Calibration ............................................................................................ 75

4.3.1. Ridership Data 75 4.3.1.1. Data Sources 75 4.3.1.2. Processing of SkyTrain Counts 76 4.3.1.3. Processing of APC Data 76

4.3.2. Trip Table Development and Model Calibration 77 4.3.2.1. Transit Network Calibration 78 4.3.2.2. Processing and 24-Hour Completion of emme/2 Matrices 79 4.3.2.3. Trip Table Correction with TFlowFuzzy and FlowBundles 80

4.3.3. Time of Day Distribution of Travel Demand 82 4.3.4. Passenger Flow-Model and Path Choice 84

4.3.4.1. Timetable-Based Assignment Settings 84 4.3.4.2. Rapid Transit Bonus Coefficients 85

4.4. Validation and Proof of Calibration .............................................................................. 86

4.4.1. Total System Ridership - Linked and Unlinked 86 4.4.2. SkyTrain Boardings and Transfers 89 4.4.3. SeaBus Boardings and Loads 91 4.4.4. West Coast Express Boardings and Loads 92 4.4.5. CMBC Bus Boardings and Loading Curves 93 4.4.6. 24-Hour Time Distribution of Demand 98



5. Network and Ridership Scenario 2011 ................................................................. 106

5.1. Network Model and Transit Service ............................................................................ 106

5.1.1. Network Topology (Links, Stops, Connectors) 106 5.1.2. New Transit Lines and Service Adjustments 2011 109 5.1.3. SkyTrain Operations 2011 111

5.2. Future Travel Demand 2011 ........................................................................................ 112

5.2.1. Development of Future Trip Tables 112 5.2.1.1. Processing of emme/2 Matrices 112 5.2.1.2. Delta-Matrix Development and Application 113 5.2.1.3. Trip Table Symmetrization 113 5.2.1.4. Airport Demand 114

5.2.2. Results 115

5.3. Model Results 2011 and Validation ............................................................................ 117

5.3.1. Model Results 2011 117 5.3.2. Ridership Validation 123 5.3.3. Line Blocking 124

5.3.3.1. Number of Blocks per Rapid Transit Line 124 5.3.3.2. Number of Blocks for All CMBC Services 125 5.3.3.3. Number of Blocks for Non-CMBC and Ferry Services 130

6. Data Management and Scenario Organization .................................................... 131

6.1. Management of Scenarios and Model Runs .............................................................. 131

6.1.1. The Master Network File – Scenario Selection in VISUM 131 6.1.2. Model Run Components (VISUM Procedure Settings) 133 6.1.3. Evaluations and Graphical Display 134

6.2. File Organization .......................................................................................................... 135

7. Conclusions and Future Directions ...................................................................... 136

Appendices ................................................................................................................... 137

List of Abbreviations and Symbols 137 Appendix A: Automated Schedule Data Import from CMBC to VISUM 138 Appendix B: User Defined Attributes in the RTM 148



Tables

Table 1: Transport Systems and Basic Operating Statistics (Base Year 2007) ............................. 14

Table 2: Node Numbering Ranges ................................................................................................. 15

Table 3: Link types ......................................................................................................................... 16

Table 4: Stop Types and Numbering Ranges for Stop Points and Stop Areas .............................. 20

Table 5: Stop Numbering Ranges .................................................................................................. 21

Table 6: Operators in the RTM - Overview ..................................................................................... 22

Table 7: Transit Lines per Operator and Transport System ........................................................... 23

Table 8: Vehicle Combinations (Consists) in the RTM ................................................................... 24

Table 9: Vehicle Units in the RTM .................................................................................................. 25

Table 10: Main Lines ...................................................................................................................... 26

Table 11: Number of Lines, Routes, Time Profiles and Vehicle Journeys per System .................. 27

Table 12: Fundamental Service Statistics for all B-Line Time-Profiles ........................................... 29

Table 13: Fundamental Service Statistics for the SkyTrain Time-Profiles ...................................... 32

Table 14: Fundamental Service Statistics for the West Coast Express Time-Profiles ................... 34

Table 15: Fundamental Service Statistics for the Ferry Lines and their Time-Profiles ................... 34

Table 16: Fundamental Service Statistics per Transport System ................................................... 39

Table 17: Fundamental Service Statistics per Main Line ............................................................... 39

Table 18: Fundamental Service Statistics per Rapid Transit Line .................................................. 39

Table 19: Fundamental Service Statistics per Territory .................................................................. 40

Table 20: Line Blocking Validation – Rapid Transit Lines .............................................................. 46

Table 21: Line Blocking Validation – CMBC, Burnaby Transit Centre ............................................ 47

Table 22: Line Blocking Validation – CMBC, North Vancouver Transit Centre .............................. 48

Table 23: Line Blocking Validation – CMBC, Port Coquitlam Transit Centre ................................. 48

Table 24: Line Blocking Validation – CMBC, Richmond Transit Centre ......................................... 49

Table 25: Line Blocking Validation – CMBC, Surrey Transit Centre .............................................. 49

Table 26: Line Blocking Validation – CMBC, Trolley Bus Use, Vancouver Transit Centre ............ 50

Table 27: Line Blocking Validation – CMBC, Diesel Bus, Vancouver Transit Centre ..................... 50

Table 28: Line Blocking Validation – CMBC Community Shuttle ................................................... 51

Table 29: Number of Blocks for Non-CMBC Buses ........................................................................ 52



Table 30: Number of Blocks for Ferries .......................................................................................... 52

Table 31: Line Blocking: Total Vehicle and Train Use and Spare Rates (AM Peak) ...................... 53

Table 32: Line Blocking: Total Vehicle and Train Use and Spare Rates (PM Peak) ...................... 53

Table 33: Rapid Transit Service Statistics ..................................................................................... 54

Table 34: Main Line Service Statistics ............................................................................................ 54

Table 35: TransLink Average Fare ................................................................................................. 60

Table 36: WCE Average Fare ........................................................................................................ 60

Table 37: VISUM Cost Model Inputs .............................................................................................. 63

Table 38: Vehicle Types used by Each Operator – RTM 2007 ...................................................... 64

Table 39: Performance Statistics – Comparison of NTD Terms and VISUM Terms ...................... 65

Table 40: Daily Revenue KM versus Annual Service KM and Expansion Factors ......................... 66

Table 41: Daily and Annual Ticket Revenue 2007 - Validation Results ......................................... 67

Table 42: Average Fare Validation Results .................................................................................... 67

Table 43: Cost Validation Results – Model 1 .................................................................................. 68



Table 46: District Definition and Relationship to Fare Zones ......................................................... 74

Table 47: Total Number of Trips in the Four Demand Segments for 2007 ..................................... 81

Table 48: Time Series Used by Area and Zone Type for AM ......................................................... 83

Table 49: Network-Wide Connector Speeds, Capture Distance and Time Bonus Assumptions .... 85

Table 50: Total System Ridership 2007 ......................................................................................... 86

Table 51: Total Unlinked Ridership per Mode/System 2007 .......................................................... 87

Table 52: Total Linked Ridership between Fare Zones 2007 ......................................................... 88

Table 53: SkyTrain Daily Boardings, Alightings and Transfers at Major Transfer Stations ............ 91

Table 54: SeaBus Ridership 2007 for Four Time Periods .............................................................. 91

Table 55: B-Line Ridership 2007 for Four Time Periods ................................................................ 93

Table 56: New Links in Year 2011 ................................................................................................ 107

Table 57: Year 2011 Transit Stop Settings ................................................................................... 108

Table 58: SkyTrain 2010: Number of Blocks per Train Type ........................................................ 111

Table 59: Year 2011PM One-Hour Demand Adjustment ............................................................. 112



Table 60: Year 2007 and 2011 Demand Total Comparison ......................................................... 115

Table 61: Year 2011 Demand Growth at Fare Zone Level ........................................................... 115

Table 62: Year 2011 Demand Growth at 10-District Level ........................................................... 116

Table 63: Total System Ridership Statistics, RTM 2007 versus 2011 .......................................... 118

Table 64: Total Unlinked Ridership per Mode/System, RTM 2007 versus 2011 .......................... 118

Table 65: B-Line Ridership, RTM 2007 versus 2011 .................................................................... 119

Table 66: Canada Line: Comparison of VISUM and emme/2 ridership totals .............................. 123

Table 67: Canada Line Boardings by Time of Day (Phase A vs. Phase B) .................................. 123

Table 68: Line Blocking 2011 versus 2007 – Rapid Transit Lines ................................................ 125

Table 69: Line Blocking 2011 versus 2007 – CMBC Transit Lines .............................................. 125

Table 70: Line Blocking 2011 versus 2007 – CMBC Burnaby Transit Centre .............................. 126

Table 71: Line Blocking 2011 versus 2007 – CMBC North Vancouver Transit Centre ................ 126

Table 72: Line Blocking 2011 versus 2007 – CMBC Port Coquitlam ........................................... 126

Table 73: Line Blocking 2011 versus 2007 – CMBC, Richmond Transit Centre .......................... 127

Table 74: Line Blocking 2011 versus 2007 – CMBC, Surrey Transit Centre ................................ 127

Table 75: Line Blocking 2011 versus 2007 – CMBC Trolley Bus (Van. Transit Centre) .............. 128

Table 76: Line Blocking 2011 versus 2007 – CMBC Diesel Bus (Van. Transit Centre) ............... 128

Table 77: Line Blocking 2011 versus 2007 – CMBC Community Shuttles ................................... 129

Table 78: Number of Blocks for Ferries 2011 ............................................................................... 130

Table 79: Number of Blocks for Non-CMBC Buses 2011 ............................................................. 130

Table 80: User Defined Attributes for the Various VISUM Object Classes .................................. 148

Table 81: User Defined Attributes for the Various VISUM Object Classes (continued) ............... 149



Figures

Figure 1: Transit Network in VISUM for the Base Year 2007 – Downtown Vancouver .................. 12

Figure 2: Transit Network in VISUM for the Base Year 2007 – City of Vancouver ......................... 13

Figure 3: Rail-Only Links in the Network (Base Year 2007 and Future Networks) ......................... 17

Figure 4: Territories (Fare Zones and Municipalities) ..................................................................... 18

Figure 5: Three-Tier Stop Model for Broadway-Commercial .......................................................... 19

Figure 6: Data Object Correspondence between VISUM’s and CMBC .......................................... 28

Figure 7: SkyTrain Schedule with Short-Turn Trips between Broadway and Waterfront ............... 33

Figure 8: User Settings for Travel Time Isochrone in VISUM ......................................................... 36

Figure 9: Map - Travel Time Isochrone from Waterfront SkyTrain-Station (2007) ......................... 36

Figure 10: Map – Average Operating Speed on Network Links (Region, 2007) ............................ 37

Figure 11: Map – Average Operating Speed on Network Links (Downtown, 2007) ....................... 38

Figure 12: Line Blocking Settings in VISUM ................................................................................... 43

Figure 13: Line Blocking Procedure Overview in VISUM ............................................................... 45

Figure 14: Time-Distribution of Selected Link Capacities ............................................................... 55

Figure 15: Time-Distribution of Selected Link Capacities (Continued) ........................................... 56

Figure 16: TransLink’s Fare Zones in VISUM ................................................................................ 57

Figure 17: Average “Ticket” for Zone-Based Fare in the RTM ....................................................... 58

Figure 18: West Coast Express Fare Modeling as Supplement ..................................................... 59

Figure 19: Editing of Vehicle Cost Rates and Operator Cost (Model 3) ......................................... 62

Figure 20: Districts for Travel Demand Analysis ............................................................................ 74

Figure 21: APC Loading Data for Line 99 and 98 Visualized with VISUM. .................................... 77

Figure 22: Subareas for the Application of Different Time Series .................................................. 82

Figure 23: Desired Departure Time Distribution – Four Different Types ........................................ 83

Figure 24: Path Choice Utility Function (Perceived Journey Time Function) ................................. 84

Figure 25: SkyTrain Daily Station Boardings, Alightings and Transfers ......................................... 89

Figure 26: SkyTrain Daily Station Boardings - Goodness of Fit ..................................................... 90

Figure 27: West-Coast Express Ridership 2007 AM and PM ......................................................... 92

Figure 28: CMBC Buses Daily Boardings 2007 (VSUM versus APC) ............................................ 94

Figure 29: B-Line 98 Daily Loading Curves (VISUM versus APC) ................................................. 95





Figure 32: Time Distribution of SkyTrain Morning Peak Loads, Broadway Inbound ...................... 98

Figure 33: Time Distribution of SeaBus Boardings ......................................................................... 99

Figure 34: Time Distribution of SkyTrain Boardings for Waterfront and Granville Stations .......... 100

Figure 35: Time Distribution of SkyTrain Boardings for Commercial Drive and Broadway .......... 101

Figure 36: Time Distribution of SkyTrain Boardings for Main Street and Metrotown Stations ...... 102

Figure 37: Time Distribution of SkyTrain Boardings Columbia and BD Stations .......................... 103

Figure 38: Time Distribution of SkyTrain Boardings Lougheed and Production Way Stations ..... 104

Figure 39: Time Distribution of Suburban Bus Boardings – Selected Lines in Surrey ................. 105

Figure 40: Time Distribution of Suburban Bus Boardings – Selected Lines in Coquitlam ............ 105

Figure 41: Rail Transit Daily Assignment Volumes 2011 ............................................................. 117

Figure 42: Visual Comparison of Average Network Speed 2011 versus 2007 ............................. 120

Figure 43: Visual Comparison of Travel Time from/to YVR Airport 2011 versus 2007 ................ 121

Figure 44: Visual Comparison of 24-Hour Passenger Volumes 2011 versus 2007 ..................... 122

Figure 45: Scenario Definition as a Sub-Set of LineRoutes ......................................................... 132

Figure 46: Selection of OD matrices for the scenario. .................................................................. 133

Figure 47: The Model Run Components under VISUM – Calculate – Procedures ...................... 134



1. Introduction

TransLink has contracted with PTV for the development of the Regional Transit Model (RTM) to support operations planning and service planning decisions in Metro Vancouver. The RTM provides an integrated picture of transit operations and transit ridership in the region, including all modes: commuter rail, ALRT, ferry, B-Lines, standard bus, community shuttle. This report documents the model development and explains the process of calibration and validation. The current state of the model is referred to as “Phase B”. It is a significant extension of the “Phase A” model, which was finished in 2006 and which included all rail lines but no bus and ferry services. The new Phase-B model development and calibration is based on 2007 data and was finished in September 2008.

Applications of the RTM

The Regional Transit Model serves to study operations scenarios that include variations of route alignments and route patterns, schedule changes and fleet assignment. In addition, the model supports service planning and the analysis of future network extensions such as the Canada Line or the Evergreen Line and their impacts on the transit system as a whole. The model is able to compute performance measures for the operations side and for the passenger side. It allows creating graphical representations and animations that can easily be understood by a non-technical audience.

PTV and TransLink have collaborated closely during the development of the 2011 scenario. PTV has conducted several training classes and workshops to transfer the know-how to TransLink. By the time of this report, TransLink staff has adopted the model and has started to apply it in several studies.

Architecture and Coverage of the RTM

The RTM intentionally uses off-the-shelf technology and is built under the VISUM software platform, using the current release version 10.0. The model represents 24 hours of an average weekday, starting at 5:00 AM and ending around 3:00 AM the next morning. The model integrates existing data sources from within TransLink and from the operating companies – BCRTC, CMBC and WCE – on both the supply and the demand sides of the transit system. The integration of these databases into one planning platform is new to the Vancouver area.

On the supply side, the Regional Transit Model incorporates schedules, fleet and line blocking of all rail, bus and ferry lines. On the demand side the model is based on trip tables that were calibrated based on data from automated passenger count system (APC) and recent boarding surveys. The passenger flow model is based on a time-dynamic and timetable-based assignment. Model calibration has been focused on rapid transit and on those bus lines that belong to the Frequent Transit Network (FTN). A detailed calibration has not been pursued for individual



suburban bus lines or community shuttles.

The calibration of the RTM has been based on extensive ridership boarding data, which covered almost all transit routes and all major stations of the rapid transit service. Moreover, the calibration process used methods such as automated matrix calibration to achieve high levels in goodness of fit, not only for the ridership totals but also for their temporal distribution over 24 hours. The authors of the report believe that this kind of calibration approach is appropriate given the model purpose of transit operations analysis.

At the time of this report, the model includes two complete scenarios: 2007 and 2011. Existing and future transit services, as well as existing and future travel demand are integrated into one consistent master network file.

Organization of the Report

Chapter 2 of this report describes the supply side of the model. The first component of supply is the network topology (section 2.1), which stands for the geographic representation of streets, intersections and stops. The section also describes how the topology data model has been populated by integrating data from existing databases such as NAVTEQ, CMBC stop database, BCRTC network data. Section 2.2 describes the second supply component, which are the service and operations data, such as fleet, routes and schedules. Most schedules have been imported from CMBC service schedule using an automated interface, which is also documented.

Chapter 3 describes three levels of operations analysis in VISUM: network and schedule analysis (3.1); line blocking (3.2); cost/revenue model (3.3). For all three levels, the methods are described and results are presented and validated.

The travel demand model and its calibration is the topic of chapter 4. The sections of this chapter cover zones and districts (4.1), the demand model architecture (4.2), the integration of ridership data from various sources (surveys and APC) and the calibration process (4.3) and an extensive presentation of the results and their validation (4.4). Most validations are based on boarding and transfer statistics, which are analyzed as daily or part-of-day totals and in their time-distribution per hour or half-hour.

Chapter 5 presents the development of a 2011 future model case, including supply (5.1) and demand (5.2). The last section of the chapter (5.3) covers model results for 2011 and the validation of these results.

Chapter 6 documents the organization of the model data, which includes the concept of the master network, the selection of scenarios and model runs. Section 6.2 describes the organization of data in files and folders.

The conclusions, the current status and the future directions are outlined in the closing chapter 7.



2. Network and Service Data Model

The supply side of the model describes the network and the transit service. The two components of the supply model are the network topology (section 2.1), such as streets and stops, and data of transit service and operations (section 2.2), such as fleet, routes and schedules. The overall objective of this chapter is on one hand to describe how the supply side of the model was built for the existing case 2007, by integrating data from various sources. On the other hand, it is explained how these data can be updated to account for future network and schedule changes.

2.1. Integrated Network Topology

The RTM is based on a network model that integrates a detailed street network (derived from the NAVTEQ data set) with rail links and transit stops which were imported from CMBC’s and BCRTC’s data bases. This section of the report describes how these data were integrated in VISUM and what assumptions the integrated model is based on.

Figure 1: Transit Network in VISUM for the Base Year 2007 – Downtown Vancouver



Figure 2: Transit Network in VISUM for the Base Year 2007 – City of Vancouver

2.1.1. General Network and Time Settings

The model uses a UTM coordinate system (UTM zone 10N), with the coordinate unit being the metre. Length unit in the model is the kilometre or metre, speed unit is km/h.

The model covers “24 hours” of an average weekday, which corresponds to VISUM “Analysis Period” (AP). The day starts around 5:00 AM and continues to the end of transit operations around 3:00 AM the next day. The results for the AP are always expanded into values for the AH (Analysis Horizon), which is defined as the year in the RTM. The expansion factor is a very simple constant for all modes and all types of statistics. AH results have not yet been used in applications of the RTM.

To model the transition from one day to the next morning, RTM Phase B uses simpler and more efficient approach than Phase A which applied VISUM’s calendar module. Now in Phase B, schedules are entered first from 5:00 to 24:00 and then for times after mid-night by numbers



greater then 24:00, for example “25:15”. On the demand side, departure-time-distributions are defined from 5:00 to 24:00 and then again from 0:00 to 3:00. It was found that this approach works best for the computation of passenger assignment, line blocking and operations statistics.

The model computes all outputs (ridership and operations statistics for all network objects) in 30-minute intervals during the day. These “Analysis Intervals” are defined from 0:00 to 24:00. A trips that goes from 23:15 on the first day to 0:45 the next morning will affect the results of several analysis intervals: 23:00-23:30, 23:30-24:00, 0:00-0:30 and 0:30-0:45.

2.1.2. Transport Systems

The selection and definition of “Transport Systems” (TSys) is a fundamental decision on model architecture in VISUM. For the RTM, the following TSys have been defined:

Table 1: Transport Systems and Basic Operating Statistics (Base Year 2007)

Code Name Type Lines Line Routes

Time Profiles

Vehicle Journeys

Stop Points

R Rail PuT 3 7 15 950 83 B Bus PuT 214 1021 3022 15824 8371 TB Trolley Bus PuT 15 158 696 3379 953 F Ferry PuT 2 4 4 159 4 W Walk PuTWalk 0 PR Drive Access PuTAux 0 C Car PrT 0 TOTAL 234 1190 3737 20312 9411 PuT: Public Transportation PrT: Private Transportation PuTWalk: Walk mode to transfer and walk-access, PuTAux: Additional access mode.

Note that the world of buses has been divided only by the type of energy they use. Trolley buses depend on streets equipped with a trolleybus overhead contact system and therefore cannot use the entire street network, where all other bus services can use the entire street network, subject to street and lane widths, turning radii and other geometric constraints.

The number of transport systems has been kept low to minimize memory use during the passenger assignment. For this reason, BRT or community shuttles have not been represented as separate transport systems. Also, the different rail systems (SkyTrain, West Coast Express commuter rail, Canada Line, LRT) have not been represented as separate transport systems. To allow analysis of such major service categories, the RTM applies the concept of main lines, which



will be explained later in this report.

Network objects are assigned to transport systems (TSys). For example, each links, turn and stop point is either permitted or prohibited for each individual TSys. A transit line has been assigned exactly one TSys. Vehicle types are defined per transport system too; in exceptional cases, some vehicle types can use several TSys, for example: busses can run on B and TB lines (that way it is possible that standard buses “help out” on trolley lines).

Car is a dummy mode which was originally defined for the NAVTEQ data set. The RTM is however strictly a PuT model that is not used for highway analysis (PrT).

2.1.3. Node and Link Network

The node/link network has been created from two sources: NAVTEQ sheet network plus complementary transit links, like rail tracks or bus lanes. The following table shows how node numbers and node types allow tracking the original data source.

Table 2: Node Numbering Ranges

Description Numbering Range VISUM TypeNo

SkyTrain station 1 … 43 0

SkyTrain switch/junction 500 … 600 0

Evergreen Line station 601 … 614 0

Canada Line Station 616 … 674 0

West Coast Express station 675 … 682 0

Intersection (NAVTEQ) 147467545 … 148011656 * 99

Ferry terminal 57960, 57961, 147512574, 147495775 * 10

Additional bus nodes ** 53014 …60809, 527901… 5843612 88 * The numbering of intersections is based on the NAVTEQ system with very high numbers that are unique world-wide. ** Nodes not included in original NAVTEQ but necessary to complete bus network.

Reducing the NAVTEQ Node and Link Data Set

In early test of the memory need and computation time for the RTM, Phase B, it became clear that the model with full NAVTEQ streets (45,000 nodes and 118,000 links) and high resolution in time-dynamics (15-minute or 30-minute intervals over 24 hours) will exceed the standard computer technology available not only at TransLink, but also in PTV’s Wilmington and Vancouver offices. For that reason it was decided to reduce the NAVTEQ streets by excluding the majority of nodes and links from the standard RTM files and keep them in a separate VISUM VER file for eventual



need in defining future transit services.

The selection of links and nodes to remain in the standard RTM files followed these criteria:

• Keep all links that are used by 2007 transit services.

• Keep all links and street segments where CMBC has bus stops defined even if there is no service in 2007.

• Keep major infrastructure like expressways and their ramps.

• Keep all streets where plans for future lines are known.

As a result, the total node and link data base (NAVTEQ and rail links) has been split as follows:

• Included in RTM model files: 26,996 links, 11,934 nodes (not including isolated nodes imported from shape file).

• Full NAVTEQ streets: 44,620 nodes and 118,108 links (can be found in RTM_full_Navteq_Streets.ver)

Link Types

Link types have been defined for the RTM to distinguish between functional street classes and between the different data sources. Table 3 summarizes the RTM link types:

Table 3: Link types

LinkType Number Name

0 Unused 11-19 Major freeway 21-29 Freeway 31-38 Ramp

39 Rest area 41-49 Principal arterial 51-59 Major arterial 61-69 Minor arterial 71-79 Collector 81-89 Local road

92 Ferry 93 SkyTrain Track 94 Canada Line Track 95 Rail Track 96 LRT-only track 97 Bus only link 99 Blocked for traffic



Most link types are maintained the link type definition provided by PTV in NAVTEQ networks. These links represent the street network and carry type numbers from 11 through 89. Link type 0 represents technical links (like the closed direction of a one-way street) that are unused. Links with types 91 through 99 have been added to the NAVTEQ data set to represent transit links, like rail tracks or bus-bays that are not included in NAVTEQ.

Figure 3: Rail-Only Links in the Network (Base Year 2007 and Future Networks)

2.1.4. Territories

The territory object in VISUM allows us to analyze transportation statistics by subarea or district. Territories also serve to highlight, for example, fare zones by colour.

The RTM currently has 29 territories, including:

• Three fare zones (TypeNo 1, 2, 3)

• 23 Municipalities (TypeNo = 9)

A major application is to compute performance statistics like passenger km and seat km by municipality. An example of territory evaluation is given in Section 3.1.3 of this report.



The following map shows the territories in the RTM:

Figure 4: Territories (Fare Zones and Municipalities)

2.1.5. Transit Stops

VISUM allows modeling transit stops with three levels which allow integrating operational detail with the passenger’s point of view. The three levels or tiers are:

1. Stop Point: Stop points are the most detailed level, representing the physical stop locations for vehicles; stop points are equivalent to the stop representation in AVL or APC systems.

2. Stop Area: stop areas represent groups of stop points like transfer points at a normal intersection; stop areas are important to define transfer walking times.

3. Stop: The stop can include several stop areas that are known to the passenger under the same name, as at off-street bus exchanges; the stop object also allows defining transfer walking times between stop areas as a matrix.

The following picture shows how all stop points in and around the Broadway-Commercial stations



have been grouped to several stop areas and one stop.

Figure 5: Three-Tier Stop Model for Broadway-Commercial

In the RTM, most stops have only one stop area – this is the case for typical bus stops that group several stop points at an intersection. In other cases a stop which serves as an intermodal hub in the network will include several stop areas, typically separating the different transit modes; for multi-stop-area stops transfer walk times have been defined as a walking time matrix.

The advantage of VISUM’s stop model is that the RTM now integrates intermodal stop data, which have been derived from data provided by the various operating companies. While remaining consistent with the operators’ stop numbering scheme on the stop point and stop area levels, the stops have allowed the integration of different transit systems.

As the following table shows, most stops points represent bus stops and have been imported from CMBC’s bus stop management system (BSMS). The RTM includes all CMBC “stops” as stop points. These bus stop points have then been merged into the NAVTEQ street network by attaching them to the correct link and the correct street side. During this action, the x and y coordinates have been slightly modified. For some stops points in the CMBC system that do not have x and y (like “flag stops”), a reasonable location has been defined for the model. The user-defined attribute “BSMS_Accuracy” documents for each stop point if it was imported with exact



geo-code or only with an approximate intersection or with no information at all. Another user-defined attribute “FlagStop” indicated flag stops.

Table 4: Stop Types and Numbering Ranges for Stop Points and Stop Areas

Description Stop point numbering range

Stop point TypeNo

Stop area TypeNo

Stop area symbol

Stop TypeNo

Bus 50001 … 61007 10000 … 10328

0 0 = default 1 = time

point

0 = Bus, no transfer

5 = Bus transfer

10 Ferry-Bus

30 = Rail-Bus

90 = Intermodal hub with several

rail modes

Ferry 57960, 57961 7001, 7002

10 10

Commuter Rail

675 … 682 20 20

TrainBus 8675 … 8682 inb. 9675 … 9682 outb.

5 0

SkyTrain 100 … 4309 30 30 Canada Line 5100 … 5130 40 40 LRT, BRT, B-Lines

6000 … 6025 50 50

Bus stop points have been grouped to the same stop area (and same stop) if they belong to the same intersection.

The numbering of stop points follows the rules listed below:

• Stop point number (bus) = original CMBC BSMS • Stop area number (bus) = minimum(stop point number) • Stop number (bus) = minimum(stop area number) • Stop area number (SkyTrain)= original numbering by BCRTC • Stop point number (SkyTrain) = stop area number * 100 + 1, 2, 3

(for example stop area 11 has the stop points 1101, 1102, 1103) • Stop number = minimum (stop area number) • All other modes: numbering ranges have been defined by PTV

Stop names on all three levels have been derived from operator data or following their conventions as closely as possible. Then all remaining names and codes have been completed consistently. Bus stop codes (short name in VISUM) have been defined as the first 3 letters from the “on” and the first three letters from the “at” street separated by “/”.



User defined attributes on the stop data include:

• Timepoint (Boolean) indicates whether stop area is a time point (applied to CMBC stops areas only)

• ON/OFF_count_YEAR_24hr holds the real count data. Zero represents that there is no data available.

Table 5: Stop Numbering Ranges

Description Numbering Range

Expo Stations 1-20

Millennium Stations 31-43

Canada 102-116

LRT 201-211

WCE 675-682

Bus Flagstop 10000-10328

Bus 50001-61002

Transfer Walk Times

VISUM allows the definition of transfer opportunities and transfer walking times on the stop level. To contain the complexity of the path search tree during the passenger assignment, transfer has been allowed only on selected stops being served by at least two different bus lines (stop type>0).

VISUM’s stop data models transfer walk times as an editable matrix with matrix cells representing the time between two stop areas of the same stop. For the RTM, transfer walk times have been determined as follows:

• Transfer is blocked for stop type 0

• All other stops:

o Bus-to-bus transfer at an intersection stop = 90s (stop type 1) o Ideal transfer walk time = 30 seconds (SkyTrain centre platform) o Intermodal transfers within large stations as a function of distance with a walking

speed of 3 km/h: time = 90s + distance /(50 metre/minute)

o Elevator or stairs add 120s per direction (results in 240 seconds = 4 minutes to switch directions on a SkyTrain side platform station)



2.2. Transit Service and Operations Data

The RTM describes service and operations of all transit modes in the Vancouver region. This integrating approach made it necessary to merge data sets from several operating companies (mainly from CMBC and BCRTC) and from TransLink into one integrated system. The data integration has been performed under the goals to remain compatible with the existing service data sources and to enable regular updates of the RTM with schedule and service data. This section of the report describes what transit operations and service data have been integrated and how they have been matched with VISUM’s model architecture.

2.2.1. Operators

The following operating companies (in VISUM’s terminology: “operators”) have been included in the model. Note that CMBC (Coast Mountain Bus Company) and West Vancouver was split into several “operators”, which allows applying different fix cost coefficients in the cost model (see section 3.3 of this report):

Table 6: Operators in the RTM - Overview

Number Name Services operated

1 BCRTC (BC Rapid Transit Company) SkyTrain lines

21 CMBC Bus Three B-Lines, standard bus lines and 15 trolley bus lines

22 CMBC Shuttle Most community shuttle lines except C3, C4, C10, C11, C12, C60, through C64

23 CMBC SeaBus One ferry line (SeaBus)

3 WCE (West Coast Express) One commuter rail line.

4 TransLink** Place holder for future transit services where the operating company has not yet been defined.

5 InTransitBC Future operator of the Canada Line.

6 West-Vancouver “Blue Bus” - Bus 11 bus lines in West Vancouver. 10 West-Vancouver “Blue Bus” - Shuttle

7 Bowen Island Bus Two community shuttle lines on Bowen Island.

8 Langley Community Shuttles Five bus lines in Langley.

9 New Westminster Community Shuttles Two bus lines.

11 BC Ferries One ferry line (to/from Bowen Island).



Table 7 shows which lines are operated by which operator and it gives an overview of the lines and services that are included in the model. Note that Fraser River Marine Transportation runs two ferries across the Fraser River that have not been included in this model because the Fort Langley terminal is 1600 m from the nearest bus stop and the service will be discontinued in 2009 when it is replaced by a bridge.

Table 7: Transit Lines per Operator and Transport System

Operator Number Operator Name Main Line/

System Lines

1 BCRTC SkyTrain Expo, Millennium

3

WCE

WCE

West Coast Express

TrainBus *

2

CMBC

Ferries SeaBus (passenger-only ferry)

B-Lines 99, 98, 97

Standard Bus All bus lines except 250 through 259,

Trolley bus Bus lines 3 through 20 and N6,N8,N20

Community Shuttle

Most Community Shuttle Lines except C3, C4, C10, C11, C12, C60, through C64.

6 West Vancouver Blue Bus

Standard Bus, Community

Shuttle

Bus lines 250, 251 … 259. Community Shuttle C12

7 Bowen Island Community Shuttles

Community Shuttle

Community Shuttles C10, C11

8 Langley Community Shuttles

Community Shuttle

C60 - C64

9 New Westminster Community Shuttles

Community Shuttle

C3, C4

11 BC Ferries Ferries Bowen Island Ferry (cars and passengers)

5 InTransitBC Canada Line Canada Line: under construction, opening in 2009

4 TransLink** n/a Future services where the operating company has not yet been defined.

* Shoulder period bus service serving WCE train station. ** TransLink as placeholder until future operating company is defined.



2.2.2. Vehicle Units and Vehicle Combinations

Vehicle combinations contain the basic data for capacity and operating cost. To become effective in VISUM’s operations analysis, the vehicle combinations have to be assigned to vehicle journeys and will then contribute after line blocking to fleet, cost and capacity analysis. This section documents which vehicle units and vehicle combinations have been defined and what capacities have been assumed.

Table 8: Vehicle Combinations (Consists) in the RTM

Number TSys Code Name Number of veh. units

Seat capacity

Total capacity

12 R 2MkI 2 car Mark I 2 72 150 14 R 4MkI 4 car Mark I 4 144 300 16 R 6MkI 6 car Mark I 6 216 450 22 R 2MkII 2 car Mark II 2 84 240 24 R 4MkII 4 car Mark II 4 168 480 25 R 5MkII 5 car Mark II 5 210 600 52 R 2Rotem 2 car Rotem Metro 2 84 334 74 R 4WCE 4 car West Coast Train 5 592 1432 77 R 7WCE 7 car West Coast Train 8 1036 2506 79 R 9WCE 9 car West Coast Train 10 1332 3222 91 R 1LRT 1 car LRT 1 64 210 92 R 2LRT 2 car LRT 2 128 420

901 B,TB RLB New Flyer articulated 1 55 120 902 B,TB RHB New Flyer articulated 1 60 115 903 TB TRL New Flyer low-floor artic. trolley 1 45 77 912 B, TB AB 40-foot high-floor, no lift 1 41 77 915 TB T New Flyer high-floor Trolley 1 38 76 916 TB TAB Low-floor trolley access - rack 1 31 77 922 B,TB LAB 40-foot low-floor 1 36 77 942 B,TB AB 40-foot high-floor 1 41 77 943 B,TB ABO Orion V highway coach 1 47 60 950 B,TB CA Ford Polar 5 1 20 24 951 B,TB CAB GMC Eldorado 1 24 24

1000 F QoC Queen of Capilano 1 0 462 1001 F SeaBus SeaBus 1 400 400



In the case of buses, each vehicle combination corresponds to exactly one vehicle unit. In the case of rail however, one combination corresponds to a train composed of several vehicles. In the case of WCE, each vehicle combination includes one locomotive plus several cars.

Table 9: Vehicle Units in the RTM

Number TSys Code Name Seat Capacity

Total Capacity

1 R MK I SkyTrain Mark I 36 75

2 R MK II SkyTrain Mark II 42 120

5 R Rotem Rotem Metro 42 167

7 R GM Loc GM Locomotive 0 0

8 R WCE WCE Car 148 358

9 R LRT LRT car 64 210

901 B,TB RLB New Flyer articulated 55 120

902 B,TB RHB New Flyer articulated 60 115

903 TB TRL New Flyer low-floor artic. trolley 45 77

912 B, TB AB 40-foot high-floor, no lift 41 77

915 TB T New Flyer high-floor Trolley 38 76

916 TB TAB Low-floor trolley access - rack 31 77

922 B,TB LAB 40-foot low-floor 36 77

942 B,TB AB 40-foot high-floor 41 77

943 B,TB ABO Orion V highway coach 47 60

950 B,TB CA ford Polar 5 55 120

951 B,TB CAB GMC Eldorado 60 115

1000 F QoC Queen of Capilano 0 462

1001 F SB SeaBus 400 400

The numbering as well as the names of vehicle units and combinations for the bus system is derived from CMBC’s numbering and naming conventions. The vehicle type number in the RTM has been derived as follows:

RTM_number = 900 + CMBC_number



2.2.3. Main Lines

To distinguish different service categories without creating additional transport systems, the following main lines have been defined for the RTM. The advantage of these main lines is to obtain automated summary statistics and mapping styles for the different bus categories, like B-Lines or Community shuttles.

Table 10: Main Lines

Main Line Transport System

Number of Lines

SkyTrain S 2

B-Lines B 3

Canada Line R (1)

Evergreen Line R (1)

SeaBus F 1

Bowen Island Ferry F 1

West Coast Express R 2

Trolley Bus Lines TB 15

Standard Bus Lines B 150

Community Shuttles B 62

* The Canada Line will be operating in the 2011 scenario. The Evergreen Line is currently included as LRT – the current plan assumes it will be built as ALRT (not LRT) in 2014.

2.2.4. Lines, Routes and Schedules

The service and schedule data include four levels:

• Definition of lines as a service product (VISUM’s object class “Line”)

• Service patterns and their alignments (VISUM’s object class “LineRoute”)

• Run and dwell times along a line route (VISUM’s object class “TimeProfile”, short “TP”)

• Schedules or vehicle trips (VISUM’s object class “Vehicle Journey”)

This section of the report describes how all these object classes and their data tables have been populated. As the methods of data import differ according to the operating companies, this report section is divided in sub-sections for SkyTrain, WCE, Bus and Ferry.



Table 11: Number of Lines, Routes, Time Profiles and Vehicle Journeys per System

Code Name Type Lines Line Routes

Time Profiles

Vehicle Journeys

Stop Points

R Rail PuT 3 7 15 950 83 B Bus PuT 214 1021 3022 15824 8371* TB Trolley Bus PuT 15 158 696 3379 953* F Ferry PuT 2 4 4 159 4 TOTAL 234 1190 3737 20312 9411 * Bus: stop points served by bus only. Trolley bus: stop points might be served by bus and trolley.

2.2.4.1. Bus Schedules

The source for all bus line data used in the RTM is CMBC’s database of service schedules. The CMBC database includes its own lines and all transit lines in the region that are operated by other companies. Note that the CMBC data was not used to populate rail networks and rail schedules, as the operators have provided data with more detail than CMBC’s database.

Automated Import from CMBC into the VISUM Data Model

The transit schedule data for the Vancouver region includes approximately 200 lines, 1000 routes, 9,000 stop points and 20,000 vehicle trips. To import such a large amount of data, it is necessary to use automated routines. PTV has created an import routine based on Microsoft Access 2000, using standard database operations like queries and joins and uses VBA as the scripting language.

This import routine has been used for the January 2008 schedule, which is described in this report. An important feature of the import routine is that it can be applied again every year to update the RTM with the current schedule. During a schedule update, the import needs to distinguish two data parts:

• The data that should not be overwritten: stop points, line and route IDs and route alignments. These components are specific to the RTM implementation in VISUM.

• The data that will be updated: all time-profiles, vehicle journeys, IDs and alignments for new lines or routes, and new transit stops.

The import routine has been applied to the spring 2008 schedule, with extensive testing, error checking and validation, to make sure that the routine can be applied to future schedule updates. A detailed description of the import routine and instructions to use it can be found in Appendix A. Figure 6 shows how CMBC’s data objects correspond to VISUM’s object classes.



Figure 6: Data Object Correspondence between VISUM’s and CMBC

Manual Post-Processing and Validation

For this version of the RTM, bus services have been included in the model for the first time. The integration of nodes, links, stops, routes and schedules was a combination of automated and manual data processing. The end result has gone through extensive error-checking and validations and consequently data corrections:

• The alignment has been error-checked by visual validation and comparison of CMBC’s GIS layers and published transit maps. Also VISUM’s automated network checking routine was applied.

• The route alignment was adjusted manually if between two CMBC stops several paths through the network exist and VISUM’s automated path search used an alternative route.

• The position of stop points in the NAVTEQ network has been corrected if it was the cause of wrong route alignment.

• Additional links were added to the NAVTEQ network if bus routes leave the public street network that is included in NAVTEQ (for example in case of bus bays at large stations).

CMBC Data table

VISUM ObjectLegend:

Stop Stop Point

Stop Area

Stop Transfer

Line

Pattern Stop

Line Route

Line Route Item

Line

Schedule

Time Profile

Time Profile Item

Trip Veh-Journey



Results: Bus Lines and Bus Schedules in the RTM

The following table summarizes basic schedule statistics for the three B-Lines:

Table 12: Fundamental Service Statistics for all B-Line Time-Profiles

Line Route Dir Time

Profile Name

# Stop points served

Length [km]

Total stop time [min]

Total run time [min]

Total run & stop time [min]

Average operating

Speed [km/h]

Number of

service trips in

24h 97 EB1 < 1740 19 12.40 0.00 29.00 29.00 25.7 1797 EB1 < 1860 19 12.40 0.00 31.00 31.00 24.0 4897 EB1 < 1920 19 12.40 0.00 32.00 32.00 23.3 1497 EB1 < 1980 19 12.40 0.00 33.00 33.00 22.6 997 EB1 < 2040 19 12.40 0.00 34.00 34.00 21.9 497 EB1 < 2100 19 12.40 0.00 35.00 35.00 21.3 1597 EB1 < 2160 19 12.40 0.00 36.00 36.00 20.7 897 EB1 < 2280 19 12.40 0.00 38.00 38.00 19.6 297 WB1 > 1620 19 12.21 0.00 27.00 27.00 27.1 1597 WB1 > 1680 19 12.21 0.00 28.00 28.00 26.2 1097 WB1 > 1800 19 12.21 0.00 30.00 30.00 24.4 1397 WB1 > 1860 19 12.21 0.00 31.00 31.00 23.6 1997 WB1 > 1920 19 12.21 0.00 32.00 32.00 22.9 297 WB1 > 1980 19 12.21 0.00 33.00 33.00 22.2 3797 WB1 > 2040 19 12.21 0.00 34.00 34.00 21.5 997 WB1 > 2100 19 12.21 0.00 35.00 35.00 20.9 897 WB1 > 2160 19 12.21 0.00 36.00 36.00 20.4 597 WB1 > 2280 19 12.21 0.00 38.00 38.00 19.3 297 WB2S > 895 8 4.33 0.00 14.92 14.92 17.4 198 NB1Z < 2220 20 16.98 0.00 37.00 37.00 27.5 1498 NB1Z < 2280 20 16.98 0.00 38.00 38.00 26.8 598 NB1Z < 2520 20 16.98 0.00 42.00 42.00 24.3 198 NB1Z < 2580 20 16.98 0.00 43.00 43.00 23.7 798 NB1Z < 2640 20 16.98 0.00 44.00 44.00 23.2 698 NB1Z < 2700 20 16.98 0.00 45.00 45.00 22.6 698 NB1Z < 2760 20 16.98 0.00 46.00 46.00 22.2 1198 NB1Z < 2820 20 16.98 0.00 47.00 47.00 21.7 298 NB1Z < 2880 20 16.98 0.00 48.00 48.00 21.2 698 NB1Z < 2940 20 16.98 0.00 49.00 49.00 20.8 198 NB1Z < 3000 20 16.98 0.00 50.00 50.00 20.4 2198 NB1Z < 3060 20 16.98 0.00 51.00 51.00 20.0 2598 NB1Z < 3180 20 16.98 0.00 53.00 53.00 19.2 2898 NB2SHZ < 2940 41 22.68 0.00 49.00 49.00 27.8 498 NB2SHZ < 3060 41 22.68 0.00 51.00 51.00 26.7 198 NB2SHZ < 3120 41 22.68 0.00 52.00 52.00 26.2 298 NB2SHZ < 3180 41 22.68 0.00 53.00 53.00 25.7 198 NB2SHZ < 3240 41 22.68 0.00 54.00 54.00 25.2 198 NB2SHZ < 3480 41 22.68 0.00 58.00 58.00 23.5 2



Line Route Dir Time

Profile Name


Length [km]




Average operating

Speed [km/h]

Number of

service trips in

24h 98 NB2SHZ < 3540 41 22.68 0.00 59.00 59.00 23.1 598 NB2SHZ < 3660 41 22.68 0.00 61.00 61.00 22.3 398 NB2SHZ < 4080 41 22.68 0.00 68.00 68.00 20.0 498 NB2SHZ < 4200 41 22.68 0.00 70.00 70.00 19.4 298 SB1 > 2280 20 16.72 0.00 38.00 38.00 26.4 498 SB1 > 2400 20 16.72 0.00 40.00 40.00 25.1 1598 SB1 > 2460 20 16.72 0.00 41.00 41.00 24.5 298 SB1 > 2520 20 16.72 0.00 42.00 42.00 23.9 198 SB1 > 2580 20 16.72 0.00 43.00 43.00 23.3 198 SB1 > 2640 20 16.72 0.00 44.00 44.00 22.8 198 SB1 > 2700 20 16.72 0.00 45.00 45.00 22.3 1498 SB1 > 2820 20 16.72 0.00 47.00 47.00 21.3 298 SB1 > 2940 20 16.72 0.00 49.00 49.00 20.5 1198 SB1 > 3000 20 16.72 0.00 50.00 50.00 20.1 398 SB1 > 3060 20 16.72 0.00 51.00 51.00 19.7 298 SB1 > 3180 20 16.72 0.00 53.00 53.00 18.9 1198 SB1 > 3240 20 16.72 0.00 54.00 54.00 18.6 598 SB1 > 3420 20 16.72 0.00 57.00 57.00 17.6 4198 SB1 > 3540 20 16.72 0.00 59.00 59.00 17.0 2298 SB1 > 3600 20 16.72 0.00 60.00 60.00 16.7 198 SB2RTC > 3000 41 22.09 0.00 50.00 50.00 26.5 398 SB2RTC > 3120 41 22.09 0.00 52.00 52.00 25.5 198 SB2RTC > 3420 41 22.09 0.00 57.00 57.00 23.3 198 SB2RTC > 3480 41 22.09 0.00 58.00 58.00 22.9 198 SB2RTC > 3540 41 22.09 0.00 59.00 59.00 22.5 198 SB2RTC > 3660 41 22.09 0.00 61.00 61.00 21.7 198 SB2RTC > 3780 41 22.09 0.00 63.00 63.00 21.0 298 SB2RTC > 3900 41 22.09 0.00 65.00 65.00 20.4 298 SB2RTC > 3960 41 22.09 0.00 66.00 66.00 20.1 298 SB2RTC > 4140 41 22.09 0.00 69.00 69.00 19.2 398 SB2RTC > 4260 41 22.09 0.00 71.00 71.00 18.7 498 SB2RTC > 4320 41 22.09 0.00 72.00 72.00 18.4 199 EB1 < 1800 11 13.80 0.00 30.00 30.00 27.6 299 EB1 < 1860 11 13.80 0.00 31.00 31.00 26.7 1199 EB1 < 1980 11 13.80 0.00 33.00 33.00 25.1 1299 EB1 < 2160 11 13.80 0.00 36.00 36.00 23.0 1099 EB1 < 2280 11 13.80 0.00 38.00 38.00 21.8 899 EB1 < 2340 11 13.80 0.00 39.00 39.00 21.2 1999 EB1 < 2400 11 13.80 0.00 40.00 40.00 20.7 1399 EB1 < 2460 11 13.80 0.00 41.00 41.00 20.2 2099 EB1 < 2520 11 13.80 0.00 42.00 42.00 19.7 1699 EB1PK < 1800 11 13.80 0.00 30.00 30.00 27.6 299 EB1PK < 1860 11 13.80 0.00 31.00 31.00 26.7 399 EB1PK < 2160 11 13.80 0.00 36.00 36.00 23.0 11



Line Route Dir Time

Profile Name


Length [km]




Average operating

Speed [km/h]

Number of

service trips in

24h 99 EB1PK < 2280 11 13.80 0.00 38.00 38.00 21.8 299 EB1PK < 2400 11 13.80 0.00 40.00 40.00 20.7 1399 EB1PK < 2460 11 13.80 0.00 41.00 41.00 20.2 3399 EB1PK < 2520 11 13.80 0.00 42.00 42.00 19.7 1399 EB2 < 1304 8 8.75 0.00 21.73 21.73 24.2 299 EB3 < 2280 16 16.98 0.00 38.00 38.00 26.8 799 EB3 < 2400 16 16.98 0.00 40.00 40.00 25.5 399 EB3 < 2760 16 16.98 0.00 46.00 46.00 22.2 299 EB3PK < 2640 16 16.98 0.00 44.00 44.00 23.2 399 EB3PK < 2760 16 16.98 0.00 46.00 46.00 22.2 399 EB3PK < 2820 16 16.98 0.00 47.00 47.00 21.7 299 EB3PK < 2880 16 16.98 0.00 48.00 48.00 21.2 599 WB1 > 1980 11 13.68 0.00 33.00 33.00 24.9 2299 WB1 > 2100 11 13.68 0.00 35.00 35.00 23.5 499 WB1 > 2220 11 13.68 0.00 37.00 37.00 22.2 399 WB1 > 2340 11 13.68 0.00 39.00 39.00 21.1 599 WB1 > 2400 11 13.68 0.00 40.00 40.00 20.5 199 WB1 > 2460 11 13.68 0.00 41.00 41.00 20.0 2499 WB1 > 2520 11 13.68 0.00 42.00 42.00 19.6 2599 WB1 > 2580 11 13.68 0.00 43.00 43.00 19.1 3599 WB1AL > 1080 8 8.73 0.00 18.00 18.00 29.1 299 WB1PK > 1920 11 13.68 0.00 32.00 32.00 25.7 399 WB1PK > 2100 11 13.68 0.00 35.00 35.00 23.5 199 WB1PK > 2220 11 13.68 0.00 37.00 37.00 22.2 499 WB1PK > 2280 11 13.68 0.00 38.00 38.00 21.6 1199 WB1PK > 2340 11 13.68 0.00 39.00 39.00 21.1 3499 WB1PK > 2460 11 13.68 0.00 41.00 41.00 20.0 699 WB1PK > 2520 11 13.68 0.00 42.00 42.00 19.6 1799 WB2 > 2220 16 16.72 0.00 37.00 37.00 27.1 399 WB2 > 2340 16 16.72 0.00 39.00 39.00 25.7 399 WB2 > 2580 16 16.72 0.00 43.00 43.00 23.3 299 WB2 > 2640 16 16.72 0.00 44.00 44.00 22.8 199 WB2 > 2700 16 16.72 0.00 45.00 45.00 22.3 499 WB2PK > 2580 16 16.72 0.00 43.00 43.00 23.3 199 WB2PK > 2640 16 16.72 0.00 44.00 44.00 22.8 199 WB2PK > 2700 16 16.72 0.00 45.00 45.00 22.3 899 WB2PK > 2940 16 16.72 0.00 49.00 49.00 20.5 1



2.2.4.2. SkyTrain Schedules

SkyTrain lines and schedule data have already been developed in Phase A of the RTM project. The data needed to be taken over for Phase B and adjusted to reflect the latest changes in SkyTrain operations.

The source of all SkyTrain service data has been BCRTC directly and not the CMBC’s service schedule or TRAPEZE passenger information module. There is no automated import routine for BCRTC data. During Phase A, BCRTC provided detailed information on stations, stop and run times and schedules that were replicated accurately in the RTM.

Table 13: Fundamental Service Statistics for the SkyTrain Time-Profiles

Line Route Dir Time

Profile Name


Length [km]



Total run &

stop time [min]

Average operating

Speed [km/h]

Number of

service trips in

24h

Expo S0 > AM 20 28.95 4.77 35.78 40.55 42.8 80

Expo S0 > Mid 20 28.95 4.57 35.78 40.35 43.1 121

Expo S0 > PM 20 28.95 5.70 35.78 41.48 41.9 78

Expo S0 < AM 20 28.81 5.67 36.33 42.00 41.2 75

Expo S0 < Mid 20 28.81 4.57 36.33 40.90 42.3 91

Expo S0 < PM 20 28.81 4.87 36.33 41.20 42.0 95

Expo S0-WFBW < AM 7 7.78 2.12 11.60 13.72 34.0 8

Millennium S0 > AM 28 42.03 7.28 52.62 59.90 42.1 41

Millennium S0 > Mid 28 42.03 6.62 52.62 59.23 42.6 119

Millennium S0 > PM 28 42.03 8.13 52.62 60.75 41.5 38

Millennium S0 < AM 28 42.06 7.85 52.88 60.73 41.6 35

Millennium S0 < Mid 28 42.06 6.78 52.88 59.67 42.3 122

Millennium S0 < PM 28 42.06 7.13 52.88 60.02 42.1 37

Since 2006, the SkyTrain operations have changed as additional trains are now running during the morning peak hour to increase inbound capacity between Broadway and Waterfront. Altogether eight additional BW-WF “short-turn” vehicle journeys are operated. They have been included in the RTM as Expo route “S0-WFBW <”, so they fit exactly in between two Expo or Millennium journeys



that maintain their 108 headway on the main branch. In Figure 7, the “short-turn” journeys are highlighted in red among the black normal SkyTrain journeys.

Figure 7: SkyTrain Schedule with Short-Turn Trips between Broadway and Waterfront



2.2.4.3. West Coast Express Schedules

WCE has been modeled in VISUM as part of Phase A, using run times and time-tables as they are published in the internet. The 2006 schedule is still valid in 2007, so the WCE model has been transferred from the Phase-A model to Phase-B without modifications. One difference to SkyTrain is that WCE is modeled in the RTM without differentiating stop and run times. The following table shows the key service statistics for the WCE rail line:

Table 14: Fundamental Service Statistics for the West Coast Express Time-Profiles

Line Route Dir Time

Profile Name


Length [km]




Average operating

Speed [km/h]

Number of

service trips in

24h

West Coast Express S0 > Std 8 67.59 0.00 73.00 73.00 55.6 5

West Coast Express S0 < Std 8 67.59 0.00 73.00 73.00 55.6 5

2.2.4.4. Ferry Schedules

The ferry schedules have been entered manually from data published on the internet. The scheduled run times do not include stop time at the ferry dock. The following table summarizes key operating assumptions that are implicit to the schedule:

Table 15: Fundamental Service Statistics for the Ferry Lines and their Time-Profiles

Line Route Dir Time

Profile Name


Length [km]




Average operating

Speed [km/h]

Number of

service trips in

24h

Bowen Island Ferry BI > HB > 1 2 5.31 0.00 20.00 20.00 15.9 16

Bowen Island Ferry HB > BI < 1 2 5.31 0.00 20.00 20.00 15.9 15

Sea Bus S0 > 1 2 3.08 0.00 12.00 12.00 15.4 64

Sea Bus S0 < 1 2 3.08 0.00 12.00 12.00 15.4 64



3. Operations Model 2007

VISUM’s strength is to provide automated operations analysis on several levels. This chapter of the report describes three levels of analysis that do not require the ridership model:

1. Analysis based on network and schedule only – this functionality helps to understand speeds and accessibilities and can be used right after a schedule import for example, without any model runs (section 3.1).

2. Analysis based on schedule and line-blocking – this evaluation needs to run the fleet- and line-blocking model but not the passenger model (section 3.2).

3. Analysis of cost and revenue (section 3.2) – it should be noted that the ridership model is necessary for the revenue part.

The fourth level if analysis will be described in chapter 4:

4. Analysis involving the passenger model which allows forecasting ridership and forecasting volume-capacity measures.

In this section of the report we give examples for analysis categories 1, 2 and 3 for the existing schedule (Winter 2007/2008). These examples can be performance statistics or visualizations and maps. Where necessary, reasonableness checks and validations are given also.

3.1. Analysis Based on Network and Schedule

Some evaluations can be performed without application of either the line-blocking or passenger models. These kinds of evaluations do certainly not use the full potential of VISUM’s operational analysis, but are practical as all they need for input are a schedule import into a consistent network model. These types of analysis include: travel time isochrones, mapping of service quality measures such as speeds and frequencies, and aggregated performance measures.

3.1.1. Travel Time Isochrone

An isochrone is a graphical analysis of travel times. Space is colour-coded according to how long the travel time is from a given starting point. Stop points are reached based on a shortest-path search using scheduled services and given transfer walking times. Then from a reached stop point the “empty space” is coloured assuming walkability in all directions with a constant walking speed. The most important user interaction is selecting a starting point (zone or stop area) and under “parameters” make sure that only active vehicle journeys are selected (see also Figure 8).

The isochrone in Figure 9 is computed based on a January 2008 service schedule, with Waterfront- SkyTrain Station as the starting point and a walking speed of 3 km/h up to 15 minutes maximum walk time. The colours red and orange mark the area that is in 30-minute reach; yellow



and green extend to the 60-minute reach. The map shows how rail lines and limited-stop bus lines create “accessibility islands”, while local buses create “accessibility branches”.

Figure 8: User Settings for Travel Time Isochrone in VISUM

Figure 9: Map - Travel Time Isochrone from Waterfront SkyTrain-Station (2007)



3.1.2. Service Frequency and Average Operating Speed

Once the schedule is given, it is easy to compute average speeds over the entire network. For the RTM, PTV has created a calculation procedure within VISUM which performs the following computations:

1. Average operating speed for each time profile segment (user defined attribute “avg_op_speed”).

2. Average all time-profiles using the same link weighted by the number of vehicle journeys (i.e. the schedule frequency).

3. Store the result in a user defined link attribute which is also called “avg_op_speed”.

Once this script has run, the following mapping of operating speed is available. Note that the thickness of link bars represents the number of service trips while the colour depends on the average speed of all services on that link (here average over 24 hours).

Figure 10: Map – Average Operating Speed on Network Links (Region, 2007)



Figure 11: Map – Average Operating Speed on Network Links (Downtown, 2007)



3.1.3. Service Statistics per System, Main Line and Territory

Already in section 2.2.4 of this report, basic operating statistics were given for each time profile of the rapid transit lines. In addition, these basic statistics can be developed on aggregated levels like lines, main lines, transport systems and territories. The following tables display these aggregated statistics for a single weekday.

Table 16: Fundamental Service Statistics per Transport System

TSys

# of Lines

# of service

trips

Avg run length [km]

Avg run time [min]

Avg Speed

Service* KM

Service* Hours

Stops served

Bus 214 15,824 12.9 31.6 24.5 204,332 8,345 4,212Ferry 2 159 3.5 13.6 15.6 559 36 4Rail 3 950 34.5 48.9 42.4 32,817 774 62Trolley 15 3,379 10.3 40.0 15.5 34,828 2,250 493

*Service KM and Hours are the same as Revenue KM and Hours defined by TransLink

Table 17: Fundamental Service Statistics per Main Line

Main Line

# of Lines

# of service

trips

Avg run length [km]

Avg run time [min]

Avg Speed

Service* KM

Service* Hours

Stops served

B-Lines 3 990 14.8 41.4 21.4 14,630 683 91Community Shuttle 61 3,628 8.1 18.8 25.8 29,372 1,139 1,458Ferries 2 159 3.5 13.6 15.6 559 36 4Standard Bus 149 11,201 14.3 34.9 24.6 159,975 6,515 3,484SkyTrain 2 940 34.2 48.6 42.2 32,141 762 32Trolley Bus 15 3,379 10.3 40.0 15.5 34,828 2,250 493WCE 2 15 68.8 82.4 50.1 1,031 21 9


Table 18: Fundamental Service Statistics per Rapid Transit Line

Line TSys # of

service trips

Avg run length [km]

Avg run time [min]

Avg Speed

Service* KM

Service* Hours

Stops served

97 B 238 12.3 31.8 23.2 2,921 125.9 2198 B 316 17.7 51.3 20.7 5,585 270.2 5499 B 436 14.0 39.4 21.4 6,124 286.5 17Expo R 548 28.6 40.6 42.2 15,660 371.0 20Millennium R 392 42.0 59.8 42.2 16,481 390.6 28Sea Bus F 128 3.1 12.0 15.4 394 25.6 2Train Bus B 5 71.1 101.2 42.1 355 8.4 8West Coast Express R 10 67.6 73.0 55.6 676 12.2 8




Table 19: Fundamental Service Statistics per Territory

Territory

# of service

trips Avg

Speed Service*

KM Service* Hours

Stops served

1 Fare zone 1 10034 19.85 101076 5093 19912 Fare zone 2 10214 26.49 90614 3421 30633 Fare zone 3 6838 28.19 78116 2771 379820011944 Anmore 57 32.18 255 8 1720012011 Belcarra 34 56.02 234 4 1220011946 Bowen Island 50 21.09 388 18 4920011973 Burnaby 5012 27.69 37288 1346 97520012018 Coquitlam 2096 25.38 13533 533 57820011990 Delta 1500 36.43 11606 319 49620011986 Langley City 569 26.20 1749 67 11420012000 Langley Township 619 31.43 4251 135 33820011932 Lions Bay 30 47.74 44 1 220012017 Maple Ridge 527 29.14 4901 168 38420012006 New Westminster 3137 29.06 11809 406 27920012012 North Vancouver City 1132 18.42 4210 229 16020012021 North Vancouver District 1808 23.45 8847 377 44120011961 Pitt Meadows 314 25.84 1390 54 5420011966 Port Coquitlam 872 25.27 4856 192 23220011930 Port Moody 751 27.08 4655 172 17920011999 Richmond 2874 26.68 22164 831 73020012002 Surrey 3127 27.53 30097 1093 131420011972 UEL 1994 28.14 7401 263 7220012003 Vancouver 9909 19.40 93675 4830 191920012020 West Vancouver 812 27.04 5367 198 40820011975 White Rock 360 25.31 936 37 99

*Service KM and Service Hours are VISUM terms that correspond to “Revenue KM” and “Revenue Hours” as defined by APTA and TransLink. **Service allocated to routes that follow streets that are also municipal boundaries may be allocated to one or both municipalities, depending on the geographic registration of the routes and boundary in VISUM.



3.2. Analysis Based on Line Blocking

This section describes the calibration of the line blocking process in VISUM for the RTM. This task is based on the network model, which has been described in chapter 2. VISUM’s schedule data are a highly accurate description of revenue service. The line blocking routine however is a model of reality that is designed for planning purposes. Consequently RTM’s line blocking has a sketch planning character. It is very useful for comparing and selecting operational alternatives. It can however not substitute the detailed scheduling and run-cutting process as it is performed by the operating companies.

3.2.1. Procedure Settings

The Line blocking settings for the rail modes have already been calibrated in Phase A of the RTM project. The various bus services, that have been added in Phase B, are highly complex in their operations as CMBC uses complex interlining techniques, which will not be replicated in every detail by the RTM.

During the development of VISUM line blocking parameters for the RTM, two major options were tested:

• Blocking of all lines in one batch. In theory, this method would allow best to replicate all the interlining and line changes that is going on in CMBC’s operations. However it turned out that VISUM would make too much use of line change and therefore the results were complex and less transparent. Another downside of this method is the increased need of computer memory.

• Blocking according to groups of lines in several consecutive batches. This method appeared to be more comprehensive, efficient and practical. Also the results appeared to be closer to CMBC’s operations.

Terminology and basic definitions in VISUM

• Interlining: It allows the bus to be re-deployed to a different stop after the last vehicle trip (known as a “vehicle journey section” in VISUM). Interlining is often considered as a means to minimize vehicle requirements as well as a method to provide transfer enhancement for passengers.

• Line change: It allows a bus to run a line route which belongs to line B from the same stop point after finishing vehicle trips of line A.

• Recovery Time (also known as pre-preparation time /post-preparation time in VISUM): A



vehicle run of a bus includes journeys and times that do not directly serve the purpose of a passenger transport. Recovery time is preparation time a bus needs before it starts the next vehicle journey or after it finishes the current vehicle journey. Taking into consideration recovery time will change the line blocking results.

Grouping of lines

Overall the line blocking is run in the following groups that follow mainly the different modes, operators and various depots within CMBC:

• Rail modes (SkyTrain, WCE)

• Ferries (SeaBus, Bowen Island Ferry)

• B-Lines

• CMBC Lines operated out of North Vancouver Depot(NVT)

• CMBC Lines operated out of Vancouver Depot(VTC)

• CMBC Lines operated out of Burnaby Depot(BTC)

• CMBC Lines operated out of Richmond Depot(RTC)

• CMBC Lines operated out of Surrey Depot(STC)

• CMBC Lines operated out of Port Coquitlam Depot (PCT)

• Non CMBC Buses

Line Blocking Settings in VISUM

Line blocking settings in VISUM take the following situations into consideration:

1. If line change or interlining is allowed for succeeding vehicle journey, if yes, how much time penalty is imposed

2. If a bus can serve the line route that is managed by different bus operator

3. If regular bus can serve the line route that is normally run by trolley bus.

4. If recovery time is considered.

5. If a maximum layover time limit is enforced.



Figure 12: Line Blocking Settings in VISUM



For this study, the following settings were chosen for most line groups’ line blocking:

1. Line change is allowed for succeeding vehicle journey and time penalty for each line change is 15 minutes.

2. Same operator and same TSys for next vehicle journey.

3. Interlining is allowed, with a time penalty of 15 to 20 minutes.

4. For each line, recovery time before a bus starts the next vehicle journey and after it finishes the current vehicle journey are the same.

5. No maximum layover time is enforced.

Line blocking is an iterative process which involves engineering judgment besides software application. Different settings were tested in order to improve the final results. Following rules were applied to certain lines:

• Line change is not allowed for rail blocking.

• Three minutes of recovery time is given to line 97, 98 and 99.

• Line group 601 from Richmond Depot has recovery time of 5 min, and rest of line groups from this depot all have recovery time equal to 2 min.

• Line blocking for Line Group 320 from Surrey Depot was performed separately and recovery time of 3 min was considered.

• All trolley buses from Vancouver Transit Centre have recovery time of 1 min, except for Line group 4 which uses 3 min.

• All Diesel buses from Vancouver Transit Centre have recovery time of 2 min.

The line blocking is not run for all lines at once. Instead it is applied to groups of lines with a different parameter set for each group. The grouping is also important to impose constraints to interlining and line change. The following Figure 13 shows how the line blocking in VISUM is composed of 40 steps, always alternating between setting a new filter and then starting the line blocking for that particular group. It can be seen that each bus depot has at least one line blocking group.



Figure 13: Line Blocking Procedure Overview in VISUM

3.2.2. Validation of Line Blocking

The validation of line blocking is done using Python script which is delivered as part of the final RTM model data. The validation process is based on the vehicle need in the morning and afternoon peak operations and during mid-day operations. As an individual block can stretch over many hours of the day, our evaluation has counted the number of blocks in VISUM as follows:

• AM peak: all blocks operating any time between 6:00AM and 9:00 AM



• Mid-day: all blocks operating at noon.

• PM peak: all blocks operating any time between 3:00PM and 6:00 PM.

• If a block is shared by several lines, it is split according how often each line appears on this block’s revenue runs over the entire duration of the block.

3.2.2.1. Rapid Transit Lines

SkyTrain and WCE line blocking results were compared against the operations data collected for RTM phase A. Note that the SkyTrain blocks have one small change as there is one additional train during the AM peak which increases the number of blocks to 33 from 32 in phase A, which represented the 2006 schedule. The RTM model matches the number of blocks for both SkyTrain and WCE perfectly. B-Line blocking result showed difference of 1-2 for AM and Midday, and 0-4 for PM peak. This difference is from different layover time as well as line change/interlining setting. The result will be further improved once the more detailed B-Line operating information is available.

Table 20: Line Blocking Validation – Rapid Transit Lines

Group Line Number of Blocks-Phase A Number of Blocks- VISUM AM MD PM AM MD PM

BCRTC 203 Expo 33 15 32 33.0 15.0 32.0 204 Millennium 23 21 23 23.0 21.0 23.0

Total 56 36 55 56 36 55 WCE 219 WCE 5 0 5 5.0 0.0 5.0 218 TrainBus 1 0 1 1.0 0.0 1.0

Total 6 0 6 6 0 6 B-Line Group Line

Number of Blocks-CMBC Number of Blocks- VISUM AM MD PM AM MD PM

97 97 11 7 8 12.0 8.0 12.0 99 99 33 24 35 31.0 22.0 33.0 98 098 19 21 25 21.0 20.0 25.0

Total 63 52 68 64 50 70 Notes:

* First TrainBus run starts after 9am. AM peak definition is revised accordingly. * WCE AM peak period is 5-10AM, PM peak period is 3 PM to 7PM.

3.2.2.2. CMBC Bus Lines

The tables in this section compare the line blocking results of all CMBC buses by transit centre. CMBC transit centres include Burnaby (BTC), North Vancouver (NVT), Richmond (RTC), Surrey (STC), Port Coquitlam (PCT) and Vancouver (VTC). The underlying assumption is that no line



change or interlining among transit lines from different transit centres is allowed. This rule applies to most of the cases but is not strictly followed in real transit operation. It simplifies the line blocking procedure greatly. This assumption could explain some minor differences between fleet schedule data and VISUM results.

Some routes are operated from more than one Line Group, or even more than one depot, especially in the case of some North Vancouver routes and a few others .Sometimes this is done not for efficiency reasons but because the closest depot has enough space to park the buses needed for base service but not enough to park peak service buses, so they come from another depot. In this case, for line blocking purpose, the line route will only be included in the group which has biggest number of fleets.

In Table 21, the number of blocks are compared between RTM and CMBC reports. The total number of buses that are needed to operate all lines from this depot is very closely matched. Line group 43 is not included for comparison purpose due to the fact that line 43 has only one bus assigned to it in the AM peak and other trips are provided by buses in line group 27, 41 and 99. More information is needed if blocking setting needs to be updated.

Table 21: Line Blocking Validation – CMBC, Burnaby Transit Centre

BTC Group Line


27 27,28,26,29,210,211,212,292 35 16 26 40.4 24.0 36.6 44 44 7 3 6 8.3 3.0 5.7

106 106 13 11 15 10.4 9.0 11.8 110 110, 116, 144 19 12 20 17.2 11.0 17.5 123 123 8 6 7 7.6 6.0 8.9 129 129, 112 13 9 15 12.4 9.0 13.2 130 130 12 7 11 9.9 6.0 11.0 134 136, 134 8 6 8 8.0 6.0 7.9 135 135, 145 26 14 21 28.8 19.0 21.3

Total 141 84 129 143 93 134 Notes: *Line 99 results are not included – they are shown in Table 20.

Table 22 shows the comparison at North Vancouver Transit Centre. Since bus line 210, 211, 212 and 292 are included in BTC line group 27 for line blocking, line blocking for these four lines was not performed here and line group 211 line blocking result was not included in the total for this comparison. Also bus lines 246, 247 were not included in line group 239 but included in line group 246 and 247 respectively.



Table 22: Line Blocking Validation – CMBC, North Vancouver Transit Centre

NVT Group Line


211 211,212,214,290 16 6 12 6.1 1.0 5.5 228 228 3 2 4 4.0 2.0 4.0 229 229,230 6 5 9 7.6 5.0 7.4 232 232,236 8 7 8 7.5 7.0 10.7 239 239, 246, 247 11 10 12 9.7 7.0 9.8 240 240,241,242,N24 15 6 10 14.3 6.0 11.1 246 246 7 2 8 9.0 3.0 9.9 247 247 2 0 4 3.0 0.0 1.7

Total 52 32 55 55 30 55

In Table 23, the total number of blocks from VISUM does not include group 143 because bus line 135 and 145 are already included in BTC line group 135.

Table 23: Line Blocking Validation – CMBC, Port Coquitlam Transit Centre

Group Line Number of Blocks-CMBC Number of Blocks- VISUM

AM MD PM AM MD PM 143 135, 143, 145 13 7 13 4.5 4.0 4.8 151 151, 156 9 7 9 8.6 6.0 7.3 152 101, 152 10 6 11 9.4 6.0 10.3

154 104, 153, 154, 155, 157, 159, 169, 177 28 21 35 29.2 23.0 29.0

160 160, 190 9 5 6 10.4 7.0 9.1 179 179, 189 2 0 0 2.5 0.0 2.3 701 701 ,791 10 8 14 12.4 9.0 13.2

Total 68 47 75 73 51 71 Notes: * Line 97 line blocking results are not included – they are shown in Table 20



Line blocking at Richmond Transit Centre (Table 24) and Surrey Transit Centre (Table 25) again demonstrate that the model produced very good numbers and the minor differences result from different line change, interlining and layover time settings.

Table 24: Line Blocking Validation – CMBC, Richmond Transit Centre

RTC Group Line


401 104, 401, 410 23 16 25 21.2 16.0 22.4 402 402,404,407,430 15 11 19 18.2 15.0 20.8 403 403 3 3 6 4.0 4.0 7.5 405 405 4 2 4 4.6 2.0 3.9 480 480 9 6 10 9.5 6.0 10.2 490 049, 490 26 14 24 19.3 13.0 22.6 491 491,496 20 0 14 21.9 0.0 13.7 492 488,492 14 0 12 13.3 0.0 11.8

601 351,601,602,603,604, 606,

608 40 13 37 39.0 15.0 39.0 620 620 2 2 2 2.0 2.0 2.0

Total 156 67 153 153 73 154 Notes:

* Line 98 line blocking data is in Table 20.

Table 25: Line Blocking Validation – CMBC, Surrey Transit Centre

STC Group Line


301 301 4 4 4 4.0 4.0 4.0 311 311 8 7 8.0 0.0 7.3 312 312,314,319,329,391,640,N19 18 10 16 18.8 14.7 17.7

320 314,316,320,321,323,324,325,326, 332, 335,345,393, 395, 501, 509,

590 61 41 61 59.0 53.0 65.0

340 340 11 5 9 6.9 4.0 6.1 341 341,375 7 7 7 7.0 8.0 7.3 352 352 7 8 6.0 0.0 5.0 394 394 5 5 2.3 0.0 2.7 502 502 7 4 12 11.0 9.3 12.9

Total 128 71 129 123 93 128 Notes: *Line group 374 from STC is used for assigning full-size buses to the C74 community shuttle route during peak periods. Line blocking result is not included in this table but combined with line group 970 data in The final line blocking for CMBC are the community shuttles, which are shown in the following table: Table 28.



Table 26 and Table 27 summarize the Vancouver Transit Centre trolley bus and diesel bus line blocking comparison results. Given that line group 4 and 8 are run by both trolley and diesel buses and line blocking does not differentiate these two vehicle types, CMBC data were consolidated for these two line groups.

Table 26: Line Blocking Validation – CMBC, Trolley Bus Use, Vancouver Transit Centre

VTC Trolley Line Number of Blocks-CMBC Number of Blocks- VISUM

AM MD PM AM MD PM 3 3 19 14 19 17.2 14.0 17.6 4 4,7 22 21 26+3 21.7 21.0 27.8 5 5,6 19 16 21 19.4 18.0 21.7 8 8,20 40 33 35+7 40.1 34.0 44.2 9 9 25 18 26 23.2 19.0 26.1 10 10 14 10 16 14.2 11.0 15.3 16 16 17 12 18 15.3 12.0 18.7 17 17 20 16 22 21.1 17.0 24.0 19 19 12 12 12+2 11.9 13.0 13.7

Total 188 152 207 184 159 209 Notes: *Group 4,8,19 CMBC data include Trolley and Diesel buses

Table 27: Line Blocking Validation – CMBC, Diesel Bus, Vancouver Transit Centre VTC

(Diesel) Line Number of Blocks-CMBC Number of Blocks- VISUM AM MD PM AM MD PM

15 15 16 12 17 16.5 14.0 17.7 22 2,22 27 15 33 34.4 16.0 29.7 25 25 26 13 19 25.6 18.0 21.5 32 32 4 0 4 3.3 0.0 2.3 41 41 32 18 25 23.3 17.0 22.6 50 50 5 5 6 6.0 6.0 7.8 84 84 10 8 10 10.0 8.0 10.0

100 100,424 10 10 10 11.8 10.0 11.5 Total 130 81 124 131 89 123



The final line blocking for CMBC are the community shuttles, which are shown in the following table:

Table 28: Line Blocking Validation – CMBC Community Shuttle Community

Shuttle Group Line Number of Blocks-CMBC Number of Blocks- VISUM AM MD PM AM MD PM

BTC 901 C1, C2 2 2 2 2.0 3.0 2.3 905 C5-C7 4 3 4 5.0 4.0 5.2 915 C15, 214 3 3 3 3.0 2.0 3.0 920 C20, C22 2 2 2 2.0 2.0 2.0 921 C21,C23 10 8 10 9.0 6.0 9.5

Total 21 18 21 21 17 22 PCT 925 C24-C30 22 11 22 20.4 14.0 21.5 930 C35-C40 14 9 16 16.8 10.0 14.0 940 C41-C49 12 9 11 10.8 11.0 10.5

Total 48 29 49 48 35 46 RTC 984 C84, C89 1 1 1 0.0 2.0 1.2 986 C86-C88 2 2 2 3.0 2.0 3.2 990 C90,C92 1 0 1 1.6 0.0 1.0 993 C93 3 3 3 2.4 3.0 3.6 994 C95, C96 3 2 3 2.0 2.0 3.0

Total 10 8 10 9 9 12 STC 950 C50-C53 5 6 6 4.3 6.0 6.0 970 C71,C73,C74 6+4 4 5+4 10.0 4.0 8.9 975 C70, C75,C76 7 6 7 7.7 8.0 7.1

Total 22 16 22 22 18 22 Notes: *CMBC line blocking numbers for group 970 include line group 374 data



3.2.2.3. Non-CMBC Bus Lines and Ferry

For Non-CMBC bus services, no line blocking reports were available for calibration. Therefore Table 29 only shows the model results. Further validation can be made when more information is available.

Table 29: Number of Blocks for Non-CMBC Buses

Group Line Number of Blocks- VISUM AM MD PM

West Vancouver Blue Bus 250 250-259,C12 25.0 21.0 27.0

Bowen Island Community Shuttles 9910 C10,C11 2.0 2.0 2.0

Langley Community Shuttles 9960 C60-C64 9.0 7.0 7.0

New Westminster Community Shuttles 9903 C3,C4 3.0 4.0 3.0 Total 39 34 39

The following table shows that the number of blocks for ferry services matches exactly the number of vessels used in the respective ferry lines.

Table 30: Number of Blocks for Ferries

Ferry Group Line

Number of Blocks- VISUM

AM MD PM 141 Bowen Island Ferry 1.0 1.0 1.0 217 SeaBus 2.0 2.0 2.0

3.2.2.4. System Wide Fleet Utilization

This section summarizes the total fleet usage in comparison between real operations and VISUM line blocking results. Such a system-wide validation provides a big picture of VISUM line blocking performance and the differences imply how the line blocking global settings can be fine-tuned.



Table 31: Line Blocking: Total Vehicle and Train Use and Spare Rates (AM Peak)

Rapid Transit Total Fleet

AM – Real World AM - VISUM Fleet Usage Spare Rate Fleet Usage Spare Rate

SkyTrain cars 210 194 7% 194 7%

WCE 5 5 0% 5 0%

CMBC B-Lines 1204

63 64

Other CMBC Busses 868 862

CMBC Community Shuttles 130 101 100

Total CMBC 1334 1032 23% 1026 23% *To be consistent with Phase A report, Sky train fleet usage calculation is based on number of cars. The current SkyTrain fleet includes 150 Mark-I cars and 60 Mark-II cars.

Table 32: Line Blocking: Total Vehicle and Train Use and Spare Rates (PM Peak)

Rapid Transit Total Fleet

PM - Real World PM - VISUM Fleet Usage Spare Rate Fleet Usage Spare Rate

SkyTrain cars 210 194 7% 194 7%

WCE 5 5 0% 5 0%

CMBC B-Lines 1204

68 70

Other CMBC Busses 878 873

CMBC Community Shuttles 130 102 102

Total CMBC 1334 1048 21% 1045 22% *To be consistent with Phase A report, Sky train fleet usage calculation is based on number of cars. The current SkyTrain fleet includes 150 Mark-I cars and 60 Mark-II cars.

Line blocking in the real world is a fairly complex process. Not only the basic operating data such as vehicle type, time table information, and layover time are considered, but also the operating cost, labor cost, work rules, constraints for line change and interlining, as well as the depot capacity. While the model should aims at simulating the reality as much as possible, some assumptions have to be made and some situations have to be simplified to make sure that the line blocking in the RTM or in VISUM in general are valid and applicable for scenario analysis. It is noteworthy that the 2007-case of the RTM has assigned exactly the same vehicle combination on each vehicle journey, as it was given in the service schedule that was imported from CMBC. As a result, special cases are taken into account in the model: for example that an individual bus helps out once per day on another line which is otherwise operated with a totally different vehicle type. As can been seen from the tables shown in the previous sections, overall line blocking results demonstrate the satisfactory consistency between model results and the real world statistics.



3.2.3. Results: Operations and Capacity Statistics

The following two tables show some of the key operations statistics that VISUM provides based on line blocking.

Table 33: Rapid Transit Service Statistics

Line Name Seat Capacity* Total Capacity* Seat KM Total Capacity KM

97 8,625 18,455 105,688 226,123

98 17,380 37,920 307,187 670,227

99 24,230 52,070 340,269 731,472

Expo 80,232 177,420 2,303,247 5,084,134

Millennium 43,188 104,340 1,815,809 4,386,898

Sea Bus 51,200 51,200 157,750 157,750

West Coast Express 10,656 25,776 720,277 1,742,292 Note: *Seat capacity/total capacity is equal to seat capacity/total capacity per vehicle multiplied by number of service trips in 24 hours.

Table 34: Main Line Service Statistics

Line Name Seat Capacity* Total Capacity* Seat KM Total Capacity KM

B-Lines 50,235 108,445 753,144 1,627,823

Community Shuttles 74,210 91,312 598,988 734,301

Ferries 51,200 65,522 157,750 233,760

SkyTrain 123,420 281,760 4,119,057 9,471,033

Standard Bus Lines 437,634 887,753 634,1362 12,580,347

Trolley Buses 108,539 259,709 1,114,141 2,677,511

West Coast Express 10,656 25,776 720,277 1,742,292 Note: *Seat capacity/total capacity is equal to seat capacity/total capacity per vehicle multiplied by number of service trips in 24 hours.



Figure 14: Time-Distribution of Selected Link Capacities

Broadway inbound: 30-minute link capacities over 24 hours

0

1000

2000

3000

4000

5000

6000

7000

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

SeaBus inbound: 30-minute link capacities over 24 hours

0100200300400500600700800900

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Lions Gate Bridge inbound: 30-minute link capacities over 24 hours

0200400600800

10001200140016001800

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23



Figure 15: Time-Distribution of Selected Link Capacities (Continued)

Granville Bridge inbound: 30-minute link capacities over 24 hours

0500

10001500200025003000350040004500

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Cambie Bridge inbound: 30-minute link capacities over 24 hours

050

100150200250300350400450500

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23

Burrard Bridge inbound: 30-minute link capacities over 24 hours

0100200300400500600700800900

1000

5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23



3.3. Cost-Revenue Analysis

This section of the report provides a concise description of the RTM’s cost and revenue model. It describes the methodology, data sources and assumptions applied in the development of the coast and the revenue models. It also presents a validation procedure and the results, discusses model limitations and makes recommendations for future improvement.

3.3.1. Fare and Revenue Model Set-Up

In VISUM, the revenue of a public transit (PuT) network is calculated from the fare model and distributed over the lines. The fare model allows modeling of fare zones and fare subzones. The stops within the PuT network are assigned to one or several fare zones and fare subzones. Then the number of traversed fare zones can be determined by VISUM, and the fares are calculated on the basis of basic fares by number of zones (or distance) traversed and possible supplements.

3.3.1.1. TransLink’s Zone-Based Fare

Figure 16: TransLink’s Fare Zones in VISUM

TransLink has defined three fare zones throughout Metro Vancouver, and the number of zones being touched during a trip determines the fare. This fare system can be directly replicated in VISUM by defining corresponding fare zones and associated stops as adopted by TransLink. The assignment of stops to fare zones can be automatically calculated from GIS operations in VISUM,



after the boundary of fare zones are defined (as territories). Stops need to be first assigned to fare subzones, and then fare subzones are grouped to fare zones. Fare subzones are typically used for modeling short-haul fare. In the RTM, each fare zone includes only one fare subzone (i.e. fare zones and fare subzones are the same).

After defining fare zones in VISUM, tickets are defined to specify the basic fare levels for travelling within the fare zones. Different ticket types can be defined for different demand segments. This allows to model such as discount fares for the weekday off-peak period and weekends. Since it is not feasible to separate demand matrices for different ticket types, a virtual “combined ticket” type is used in the RTM to present the average fare of different ticket types. The calculation of average fare will be explained later.

Figure 17: Average “Ticket” for Zone-Based Fare in the RTM

3.3.1.2. WCE Fare Rules

West Coast Express (WCE) fares are essentially separate from the TransLink zone-based fares, and the fare is determined by the distance of travel. In addition, the WCE line may share stops with other TransLink service lines and discounts are given for transfers between WCE and other TransLink services. To account for these factors, the WCE fare system is modeled as distance-



based supplements, which reflect additional cost for using specific transit systems (WCE train and train bus). In VISUM, the distance of travel (or other distance-related factors) can be counted by fare points, which can be defined directly in the time profile of a transit line route (or added to a link). To present the WCE fare rules, different numbers of fare points are added to different segments of the WCE line routes to account for different fare levels for traveling between different stops. The supplement is then determined on the basis of the number of fare points traversed by the WCE service.

Figure 18: West Coast Express Fare Modeling as Supplement



It is important to note that the fare values used for supplements are not direct values of the WCE fares. That is because in the model the WCE stops are also a part of the TransLink zone-based fare system and a trip using the WCE line will be first charged for a basic fare based on the number of zones traversed. For example, a trip from Waterfront to Mission will be counted for a basic fare of two zones ($3.75 for regular cash fare) if it is by WCE trains or a basic fare of three zones ($5.0 for regular cash fare) if it is by WCE train buses. Therefore, the supplements for this WCE trip (18000 fare points) are the difference between the WCE fare ($11.25 for one-way cash fare) and the TransLink basic fares (i.e. $7.5 for train and $6.25 for bus). Average fares for the WCE service are also calculated to account for different ticket types in reality, as it is not feasible to separate them in demand matrices.

3.3.1.3. Ticket Modeling and Average Fare

As explained earlier, a virtual “combined ticket” type is defined to present the average fare of different ticket types used in reality. This virtual ticket preservers (and combines) the zone-based fare structure used by TransLink (as basic fares) and the distance-based fare structure used by WCE (as supplements). Average fares are calculated for TransLink and WCE respectively, based on the shares of the annual sales by various fare media. It is to be noted that only 2007 statistics of the TransLink fare sales by ticket type are provided and the average fares of WCE are estimated based on 2006 statistics found online. The following tables list the average fares calculated from the fare sale statistics, and they results a close estimate of the annual ticket revenue (to be discussed late in the validation section). The adjust fares are input values that are further adjusted from the average fare that can produce a perfect match of the annual ticket revenue.

Table 35: TransLink Average Fare

Average Fare Adjusted Fare

1 Zone 1.20 1.22

2 Zone 1.70 1.73

3 Zone 2.30 2.35

Table 36: WCE Average Fare

Average Fare Adjusted Fare

0 – 5,000 Fare Points 3.60 4.05

5,000 – 12,000 Fare Points 4.70 5.30

12,000 – 15,000 Fare Points 5.80 6.50

15,000 – 18,000 Fare Points 7.90 8.85



It is also known from TransLink statistics that the average fare paid per trip is $1.83 for TransLink (non-WCE) services and $5.94 for WCE services, giving the annual fare revenue and number of linked trips for TransLink (excludes WCE) and WCE respectively. These values are compared when estimating the average fares (they will be revisited during validation in section 3.3.3).

3.3.2. Cost Model Set-Up

• In VISUM, the total operating cost of a line or a line services can be computed based on several components:

• Vehicle cost

o Hourly cost: time-dependent cost for personal service time (used in RTM)

o Kilometre cost: KM-dependent cost for fuel, maintenance, etc. (used in RTM)

o Fixed cost: cost for debt service and insurance (not used)

• Infrastructure cost

o Operator cost: cost for operating infrastructure, administration, etc. (used in RTM)

o Stop point cost: cost for the use of stop points (unused)

o Link cost: cost for the use of links (unused)

TransLink statistics include expenditure breakdowns for different transit services (e.g. SeaBus vs. SkyTrain) and different expense categories (e.g. fixed vs. variable and fuel vs. wage), along with annual service hours and annual service kilometres. Based on the data availability, the cost model can be constructed in different ways with different cost inputs:

• Model 1: vehicle cost per kilometre

• Model 2: vehicle cost per hour and vehicle cost per kilometre

• Model 3: operator cost, vehicle cost per hour, and vehicle cost per kilometre

Model 1 is the simplest construct by calculating the vehicle cost per kilometre based on the total annual expenditures and annual service kilometres. It will also be the easiest one to validate against the annual statistics.

Mode 2 is designed to distinguish between kilometre-dependent cost and time-dependent cost so



that the model can better predict the change of operating cost in response to the change of service (or schedule) of different services. For example, the operating cost of SkyTrain depends on car kilometres but not on vehicle hours, as it is operated without onboard personnel. The vehicle cost per hour is calculated from the annual expenditure for wage and annual service hours, and the vehicle cost per kilometres is calculated from the total of rest expenditures and annual service kilometres.

Model 3 is extended to the highest level of complexity. The fixed and semi-variable annual cost (e.g. depreciation and administration) is separated from other variable cost and is defined as the operator cost in VISUM. Among other variable cost items, wage is used to calculate the vehicle cost per hour, and the rest is account for the vehicle cost per kilometre. The operator cost can be distributed to lines or vehicle journeys based on different indicators including service kilometres, service time, vehicle journeys, passenger kilometres and passenger trips.

Figure 19: Editing of Vehicle Cost Rates and Operator Cost (Model 3)



The table below summarizes the data inputs of different cost models. The operator cost listed in the table is the annual cost, referring to the analysis horizon (AH) of the RTM, where the analysis period (AP) in the RTM represents an average weekday.

Table 37: VISUM Cost Model Inputs

Model 1 Model 2 Model 3

Service vehicle cost per km

vehicle cost per km

vehicle cost per hr

vehicle cost per km

vehicle cost per hr

operator cost (AH)

CMBC Bus 5.95 2.62 62.46 0.95 62.46

119,082,495CMBC Trolley1 5.48 2.15 62.46 0.54 62.46

CMBC Shuttle 2.36 0.54 35.71 0.36 35.71 1,450,936

CMBC SeaBus 56.18 16.92 530.65 7.69 530.65 1,333,033

BCRTC SkyTrain2 2.22 0.00 2.22 0.00 1.53 24,082,377

WCE Train2 12.92 11.29 61.53 8.18 61.53

3,851,569 WCE

Train Bus1 5.06 2.43 61.53 0.95 61.53

West Van Bus 4.58 2.15 49.25 1.72 49.25 995,217

Contracted Shuttle3 2.12 1.02 25.93 0.65 25.93 518,651

1 No separate statistics are available for these services, and estimates are used for model inputs. 2 The vehicle cost refers to car cost per kilometre (or per hour) instead of train cost. 3 It includes West Vancouver, Bowen Island, Langley, and New Westminster Community Shuttles.

The vehicle cost is assigned to each vehicle type (unit combination) according to its classification of service as used in Table 37. Table 38 below summarizes the list of vehicle combination numbers by service classification.



Table 38: Vehicle Types used by Each Operator – RTM 2007

Service Vehicle Type

CMBC Bus 900, 901, 902, 912, 922, 942, 950

CMBC Trolley 915, 916

CMBC Shuttle 950, 951, 922, 942

CMBC SeaBus 1001

BCRTC SkyTrain 12, 14, 16, 22, 24, 25

WCE Train 74, 77, 79

WCE Train Bus 943

West Van Bus 942, 950

Contracted Shuttle1 950

1 Includes West Vancouver, Bowen Island, Langley, and New Westminster Community Shuttle.

The above table shows that one vehicle type (unit combination) may be used for different services (or lines). For example, vehicle No. 942 (and 950) services for both CMBC bus lines and West Vancouver bus lines. It requests a tradeoff in determining the vehicle cost for that vehicle type. To account for this, an average cost is calculated by the share of the vehicle’s service kilometres for different services (e.g. CMBC bus vs. West Vancouver bus). However, due to this tradeoff, the model estimates of the operating cost may be inevitably higher for one operator but lower for another. In addition, it shows that several vehicle unit combinations may be used for same service (or lines), and they share same cost rates in the model. Ideally, they should be differentiated to account for the difference in fuel efficiency etc in reality, if relevant data is provided. This is another limitation of the current cost model.

It is also to note that in Table 37 two services (e.g. CMBC conventional bus and CMBC trolley bus) may not be differentiated from each other in terms of operator cost. Thus, in VISUM, operators are defined only if relevant data is provided. The model outputs will also be validated on the basis of aggregates by operators.



3.3.3. Validation of the Cost-Revenue Model

The RTM represents transit operations and ridership of an average weekday. Accordingly, outputs of the cost and revenue models are estimates of the average daily operating cost and ticket revenue. These cost and revenue estimates can be aggregated for individual lines or operators. For model validation purposes, real-world cost and revenue data were not available for the average weekday. Therefore, the validation is conducted against annual statistics.

Performance Terminology

The cost and revenue validation is also based on performance measures. In this context, some terms used in VISUM are different from the typical American definitions as used by the NTD or APTA. Table 39 compares different terms (and their compositions). Identical items are coded in the same colour to show the correspondence between NTD and VISUM.

Table 39: Performance Statistics – Comparison of NTD Terms and VISUM Terms

NTD1 VISUM

Vehicle hours/km

(aka “Service

hours”)

Running or load time/km = Service time/km

Revenue hours/km

Layover time = Stand

time/km Empty

time/km

Recovery time

Operating time/km

Deadhead time

Pull-in/out time/km = Pull-in/out

time/km

Change-route time/km = Interlining2

time/km 1 Other terms defined in NTD including service interruption, maintenance testing/training, school bus service and charter service are not included in VISUM. 2 Line change in VISUM is different from interlining time/km, as no additional km is resulted from that.

It is important for the understanding of this validation that Translink’s statistics in terms of annual service hours/km include both revenue and non-revenue hours/km, while the RTM can not estimate deadhead km to the full extend. As a result, the level of validation achievable is limited and varies by service type and operator, depending on the percentage of non-revenue service hours/km included in the annual statistics.

3.3.3.1. Equivalent Annual Cost and Revenue

To estimate the annual cost and revenue from the RTM model, an expansion factor is required to extend the model outputs on the basis of average day to equivalent annual values (from AP to AH). In VISUM, the expansion factor is by default set to 365. This global factor is applied to all



transit services (or operators). For the RTM model, a factor of 340 is used as determined from the following Table 40. It is important to note that in reality the expansion factors may be different from one service (or operator) to another and the expansion factors may also be different for cost estimation and revenue estimation. Table 40 compares the daily service (revenue) kilometres from VISUM with the annual service kilometres from the TransLink statistics for different operators. These annual service km include revenue km, and also deadhead km, weekend km, events and other non-scheduled service. The expansion factors are calculated as the ratio between those two different statistics. The calculated expansion factors may be more reasonable for some operators such as SkyTrain and WCE as they have very little deadhead kilometres, but for other operators such as West Van Bus the expansion is quite high because of significant deadhead km.

Table 40: Daily Revenue KM versus Annual Service KM and Expansion Factors

Operator VISUM Daily Revenue KM

TransLink Annual Service KM

Theoretical Expansion Factor

CMBC Bus1 202,794 71,943,289 355

CMBC Shuttle 24,798 7,959,052 321

CMBC SeaBus 394 144,355 366

BCRTC SkyTrain 109,855 34,992,756 319

WCE 4,867 1,214,062 249

West Van Bus 6,341 2,334,857 368

Contracted Shuttle2 4,592 1,424,410 310

All Operators 353,641 120,012,781 340 1 It includes CMBC conventional bus and trolley bus. 2 It includes West Vancouver, Bowen Island, Langley, and New Westminster Community Shuttles. Data are TransLink statistics for 2007. Note that the term “service KM” used here corresponds to “revenue KM” in APTA’s terms.

Table 40 also illustrates the fact that the expansion factors vary by operators. It is best to apply the operator-specific expansion factors for annual cost/revenue estimates in order to achieve a perfect match to the annual statistics. For the RTM, one average projection factor, 340, has been determined based on TransLink’s service kilometres statistics for 2007 by operating company. This average expansion factor is used as the global factor in VISUM. It is to be noted that a different set of expansion factors may be obtained based on the ratio of the annual service hours to the daily service hours. However, the service-kilometre-based expansion factors are recommended as the service-hour-based projection factors turn to be higher and more deviated by operators (which makes it even more difficult to determine a global projection factor). Moreover, the statistic of service kilometre is generally more accurate.



3.3.3.2. Revenue Validation Results

In VISUM, the revenue is calculated for each trip from the fare model, and then distributed to individual path legs of a trip weighted by the number of path legs. The revenue can be further aggregated for individual lines and operators. For validation purposes, Table 41 compares the VISUM estimates of the annual ticket revenue with the 2007 TransLink statistics. The revenue for the WCE service is separated from other TransLink services in comparison.

Table 41: Daily and Annual Ticket Revenue 2007 - Validation Results

2007 TransLink Ticket Revenue ($)

VISUM Estimates ($)

Daily Annual1 Annual2

WCE 13,531,803 52,821 13,152,412 17,959,116

TransLink - others3 314,077,577 915,877 314,467,286 311,398,0241 Different projection factors (from Table 40) are used for different operators (calculated explicitly). 2 A global projection factor (=340) is used for all operators (direct VISUM output, from AP to AH). 3 It includes all other TransLink services except WCE.

The VISUM estimates present a perfect match to the 2007 statistics, if different projection factors are applied to different operators. Using one global factor, the estimate of the WCE revenue turns to be higher, as a much lower projection factor is obtained in Table 40 (249 vs. 340). Based on the VISUM outputs, the average fare per trip may be calculated and compared with the model input (average fare). Table 42 compares the VISUM estimate with the TransLink statistics (based on the 2007 ticket revenue and the number of unlinked trips)

Table 42: Average Fare Validation Results

2007 TransLink ($ per trip) VISUM Output ($ per trip)

WCE 5.94 4.83

TransLink – others1 1.83 1.54

1It includes all other TransLink services except WCE.

3.3.3.3. Cost Validation Results

In VISUM, the total cost is summed up from the calculated individual costs including infrastructure cost and vehicle cost. The operator cost is distributed to individual vehicle journeys weighted by service km. The vehicle cost is a sum of km cost and hourly cost. The km cost is calculated on the basis of vehicle km and the hourly cost is calculated on the basis of operating time.



Model 1 (not used)

The following table compares the VISUM estimates of the total cost (Model 1) with the 2007 TransLink operating cost.

Table 43: Cost Validation Results – Model 1

2007 TransLink Operating Cost ($)

VISUM Estimates ($)


CMBC Bus3 422,382,142 1,169,664 415,230,654 396,685,689

CMBC Shuttle 18,770,126 63,714 20,452,107 21,662,668

CMBC SeaBus 8,109,663 22,155 8,108,803 7,532,768

BCRTC SkyTrain 77,664,438 244,319 77,693,569 83,068,596

WCE 15,531,065 64,676 16,104,356 21,989,884

West Van Bus 10,685,312 36,176 13,312,831 12,299,898

Contracted Shuttle4 3,023,873 11,487 3,561,091 3,905,713

Σ Total 556,593,619 1,616,192 554,463,403 548,145,215

1Different projection factors (from Table 40) are used for different operators (calculated explicitly). 2A global projection factor (=340) is used for all operators (direct VISUM output, from AP to AH). 3It includes CMBC conventional bus and trolley bus. 4It includes West Vancouver, Bowen Island, Langley, and New Westminster Community Shuttles.

The Model 1 calculates the total cost on the basis of cost rate per kilometre. As one would expect, the estimates of equivalent annual cost present a perfect match to the TransLink statistics for major operators, when different projection factors are applied. For example, the difference between the VISUM estimates and the TransLink statistics is less than 2% for CMBC bus. Since the projection factors are calculated on the basis of the service kilometres, this is the most viable and appropriate case to apply different projection factors. Some larger difference presents between the VISUM estimates and the target values for some operators (e.g. West Vancouver Bus), and that is a result of the tradeoff in assigning the vehicle cost to the vehicle combinations that serve for more than one operator, as discussed in section 2.2.2. Otherwise, the difference is a result of rounding in calculation (e.g. CMBC SeaBus). When a global projection factor is used, the difference between the model estimates and the targets are varied by operators, but the estimated total cost is still within 2% from the reported total expenditures for TransLink.



Model 2 (not used)

Table 44 below further compare the VISUM estimates of the total operating cost from Model 2 with the TransLink statistics.



VISUM Estimates ($)


CMBC Bus3 422,382,142 1,116,336 396,299,372 379,554,328

CMBC Shuttle 18,770,126 54,032 17,344,224 18,370,829

CMBC SeaBus 8,109,663 20,257 7,414,234 6,887,540

BCRTC SkyTrain 77,664,438 243,880 77,553,830 82,919,190

WCE 15,531,065 61,719 15,368,146 20,984,616

West Van Bus 10,685,312 30,913 11,376,061 10,510,491


Σ Total 556,593,619 1,536,312 528,199,683 522,346,019


The results show again that using different project factors for different operators match the model estimates to the annual statistics better than using a global project factor. In comparison with Model 1, Model 1 matches the targets better than Model 2. This is because that Model 2 considers different cost rates on the basis of service kilometres and service hours, but the projection factors are derived on the basis of service kilometres. The distance-based projection factors are different from the time-based projection factors, if calculated. Overall, the model estimates match the target reasonably (within 10% for most operators and within 5% for the total), when different projection factors (from Table 40) are used. If one global projection factor is used, the difference between the model estimate and the TransLink statistics is still within 10% at the system level.



Model 3 (used for RTM)

Table 45 below compare the VISUM estimates of the total operating cost from Model 3 with the TransLink statistics.



VISUM Estimates ($)


CMBC Bus3 422,382,142 1,125,109 399,413,780 387,568,696

CMBC Shuttle 18,770,126 51,143 16,416,855 17,302,692

CMBC SeaBus 8,109,663 20,259 7,414,933 6,982,944

BCRTC SkyTrain 77,664,438 243,810 77,531,720 81,229,386

WCE 15,531,065 61,525 15,319,735 19,510,961

West Van Bus 10,685,312 24,302 8,943,173 8,338,571


Σ Total 556,593,619 1,535,742 528,013,924 524,144,252


The estimates from Model 3 are close to that from Model 2, and even match the target slightly better for major operators and at the system level. It is shown in the input data that the operator cost is relatively a small portion of the total cost, and thus it does not make much difference when the operator cost is separated from the vehicle cost in this case. However, in general, it helps in account for the difference of service kilometres and service hours between the model and the real data, as well as the issue in selecting the projection factors. As shown in the Table 45, the total cost for all operators from the VISUM estimates is about 6% deviated from the target.



3.3.4. Summary and Recommendations

Cost and revenue analysis is now enabled in the RTM and parameters and assumptions are set so that it is now fully functional. The calibration of the revenue model obtained very good results, where the cost model can still be improved with more detailed data and estimations for individual vehicle models.

The revenue is calculated from a zone-based fare model on the basis of basic zone-based fare plus – in the case of WCE - supplements based on travel distance. The average fare is calculated from the share of ticket sales of different types. The revenue estimates match the real-world data very well at the system level.

Three different cost models have been constructed and tested with three different sets of inputs, using data provided by TransLink. Model 1 using single cost rate by vehicle per service kilometre presents the closest match to the reported expenditures for major operators and at the system level, since it is simplest design and the easiest case for validation by nature. The other two models, which take into account the cost rate by vehicle per service hour and the operator cost in addition to Model 1, also shows good match to the real data at the system level. Model 3 is recommended for future analysis due to its advantage in model structure (more cost factors being modeled). There are still opportunities to improve the cost model in the following aspects so that it will provide better estimates and analysis results at different levels:

Differentiate vehicle cost per kilometre among different vehicle types that serve under same operator and the classification of service. Statistics of fuel economics for different bus types from TransLink can provide that information and improve the model estimates at the line level.

Differentiate vehicles that serve for different lines (or operators). In the current model, one vehicle type may be used by more than one operator. It raises an issue in determining the appropriate vehicle cost to these vehicle types. If different vehicles are defined for different services in the model, the data input will be more accurate so as the model outputs.

Select appropriate projection factor(s) in determining the equivalent annual cost and revenue. It shows that the model outputs can match the statistics best if different projection factors are used, but it is more desirable to use a global projection factor.



4. Travel Demand Model 2007

This chapter summarizes the methodology applied and results achieved in calibration and validation of the ridership model.

Section 4.1 summarizes the demand model’s architecture. Section 4.2 describes the zone system and districts used for travel demand analysis. Section 4.3 describes the methodology used to build and calibrate the travel demand matrices, time-distributions and the assignment model. Section 4.4 summarizes the results of model calibration and validation by comparing the model outputs to the survey data and counts.

4.1. Model Architecture and Applied Methods

The demand model represents the 24-hour ridership of an average weekday. In VISUM the entire demand is represented by four trip tables – corresponding to four demand segments:

• AM – the morning peak from 5:00 to 9:00

• Mid – the off peak time from 9:00 to 15:00

• PM – the afternoon peak from 15:00 to 18:00

• Eve – the evening from 18:00 to the end of the operating day, 3:00 in this model.

The passenger assignment of the model, which determines the path choice of the transit riders, is a time-table based assignment based on the winter schedules 2007/2008. VISUM’s time-table based assignment method is time-dynamic as it explains how demand and flow change over time and it computes passenger volumes over 24 hours. These volumes have been calibrated for the year 2007, with most passenger counts received for the fall 2007.

4.2. Zones and Districts

4.2.1. Zone Definition

The current travel demand model for the Vancouver Metro Area that runs on the emme/2 platform has an established system of traffic analysis zones for many years. It has a basis of 641 zones that are sometimes split into subzones, with a numbering scheme that can trace the mother zone from any child zone. The zone structure in the RTM are derived from this zone system, using the same refinement (split) as in the Evergreen line studies performed in 2005, with a total of 889 zones in emme/2. From these 889, 83 are deleted because they are irrelevant to transit (11



external cordon zones, PnR zones 123 through 130, and zones 9000 through 9810 which are located in the far-East out of reach for TransLink’s transit services).

The zone system is further refined for computational and analysis purposes. For example, it was found that trips from far away zones (e.g. east of the WCE Mission station) cannot be assigned to the network because the trips cannot be completed within the assignment time interval. If appropriate, the demand from far-away zones was assigned to a PnR zone.

Finally, the RTM has 806 zones, which can be divided as follows: • 784 internal zones (ID range: 1000 - 8840) • 22 P&R zones (ID range: 101 - 122) • 0 external cordon zones

All zones use multiple connectors to feed the passenger demand into the network. The connectors have been developed and refined as part of the RTM calibration.

A definition of four zone types has been introduced to better model the time-dynamics of travel demand across the region. The methodology is explained in section 4.3.3 of this report and illustrated in Figure 22. The four types represent:

• Type 1 = Core of the urban area (City of Vancouver, Vancouver CBD, and UBC)

• Type 2 = Near suburbs: Burnaby, New Westminster

• Type 4 = Near suburbs: West Vancouver, North Vancouver, Bowen Island, Lions Bay.

• Type 3 = Distant suburbs – rest of the zones

4.2.2. District Definition

The zones were grouped into 10 districts in order to analyze aggregated flows and compare them with surveys. A second system of three districts is used which corresponds to the 3 fare zones.

One major reason to use the 10-to-10 district flow matrix is to compare VISUM’s matrices with the 2004 trip diary. The 2004 trip diary districts can be combined to get the same 10-district structure. The districts are relatively homogenous in terms of transit service options available to the population and many district boundaries follow significant geographic dividers. An example is Surrey, Delta and White Rock. All travelers from this area will take SkyTrain across the river to the northwest area or transfer at Columbia Station to Burnaby. Therefore, the district analysis is also used to compare aggregated flows in VISUM’s matrices with transit volumes at major screen lines. Sometimes it was necessary to further group the 10 districts to obtain more trips for each district-to-district pair, in particular if the number of observations in the travel survey were too small.



Figure 20: Districts for Travel Demand Analysis

Note: District 2 (CBD) and district 10 (PnR) not visible.

Table 46: District Definition and Relationship to Fare Zones

District Numbering Fare zone

Zones

Report Altern.

North Shore (North Vancouver, West Vancouver)

1 1000 Zone 2 1000 - 1199, 1200 - 1290 1500 - 1719, 1900 1910

Vancouver CBD 2 30000 Zone 1 2000 – 2399

Vancouver & UBC (w/o CBD) 3 40000 Zone 1 2900 - 2929 3000 – 3999

Burnaby, New Westminster 4 50000 Zone 2 4000 - 4599, 4700 - 4899

North-East (Coquitlam, Port Moody, Amore, Belcarra)

5 60000 Zone 3 5000 - 5699 1920

Richmond 6 70000 Zone 2 6000 – 6499

Surrey & Delta & White Rock 7 80000 Zone 3 6700 - 6999, 7000 –- 7999, 1930, 8000

- 8299

Maple Ridge, Pitt Meadows 8 110000 Zone 3 5000 – 5699, 1920

Langley 9 12000 Zone 3 8300 – 8899

Park and Ride 10 n/a n/a 101 - 122



4.3. Travel Demand Calibration

This section describes how the RTM’s travel demand data has been developed and calibrated for the base year 2007. The main components of the travel demand in the RTM consist of:

• Trip tables for four time-of-day periods: AM, Mid, PM, Eve

• Desired departure time distributions over 24 hours

• Parameters of the time-table based assignment

• Zone connectors and transfer-walk times within stops

The following sections of the report describe the methodology used to derive travel demand data for AM, PM, Mid and Eve time periods.

4.3.1. Ridership Data

4.3.1.1. Data Sources

Data considered for RTM model calibration and validation are from different sources listed as below:

• emme/2 trip matrices, 2004, AM and PM peak from transit priority corridor study

• Trip diary 2004 aggregated trip matrices (between fare zones and districts)

• TransLink website trip planner service

• SkyTrain station boarding counts by time-of-day 2006, for some stations collected in 2005 or 2003

• SkyTrain 2006 transfer counts at Broadway, Commercial Drive and Columbia stations

• WCE boarding counts collected in September/October 2007

• SeaBus boarding counts collected in September 2007

• APC boarding data by bus line by time period (CMBC)

• APC on/off/load data for the B-Line and other selected lines (CMBC)



• GVRD customer service performance survey 2006 and 2007

• WCE customer service performance survey 2007

• SkyTrain load survey, AM, Broadway inbound, 2007 (BCRTC)

• Total monthly revenue ridership for all operators (TransLink estimates from ticket sales)

Since the focus of the project is on Regional Transit lines in the study area, the SkyTrain, WCE, SeaBus and B-Lines boarding counts are considered as the most important source for calibration purposes. Other counts (CMBC bus boardings) and system-wide surveys (trip diary, customer service performance survey, and revenue ridership) are used mainly for validation purposes.

4.3.1.2. Processing of SkyTrain Counts

Most survey data are considered to be a good representation of 2007 weekday ridership. However, as SkyTrain boarding counts are dated from 2006 and for some stations from 2003 and 2005, they have been factored up with growth factors derived from the revenue ridership estimates to represent the 2007 ridership. The following growth factors were applied:

• 2006 – 2007: 3%

• 2005 - 2007: 5%

• 2003 - 2007: 10% (average over all stations)

4.3.1.3. Processing of APC Data

Over the fall of 2007 CMBC's APC equipment and evaluation software made the transition from the test phase to application in planning. To use the APC data for the RTM calibration and other applications at TransLink, adjustments were still necessary and contradictions in the APC output needed to be clarified. Currently it is agreed that the total boarding statistics per line (24 hour or per time of day) are reliable. The on/off/load statistics per line route that were received for calibration did however not match the total boarding statistics. The on/off boardings were too high, sometimes up to 100%. Unfortunately, PTV had started to calibrate based on on/off data. Finally, on/off/load data have been scaled down with a global factor for all day, so that they can only be considered as a rough approximation of bus loading. Overall the experience with APC was good especially as they provide a very high coverage of bus ridership in the region.



APC data contains the boarding, alighting and leave load data at each stop by line route for four time periods. Since the APC data format is already very close to VISUM line route item listing format, with very limited data formatting, VISUM can bring in all these data and store them as line route item attributes and visualize the data at different aggregation level. For example, VISUM can show boardings at a stop only for B-Line #99 EB, or all the EB line routes that use this stop. This feature facilitates B-line calibration and validation process greatly. Figure 21 displays the B-Line 99 EB and 98 NB daily boardings as well as loadings along the line route. Red pie charts represent the number of boardings at each stop and green bars are daily loads between two adjacent stops.

Figure 21: APC Loading Data for Line 99 and 98 Visualized with VISUM.

4.3.2. Trip Table Development and Model Calibration

The RTM model calibration involves four major steps which interact with each other and make the whole calibration an iterative process:

1. Processing of emme/2 matrices and 24-hour completion

2. Network checking before and after assignment

3. K-factor correction of trip tables

4. Automated trip table calibration



The main outputs of the model calibration are four trips tables: AM, Mid, PM and Eve, which together represent the entire ridership as linked trips over 24 hours.

4.3.2.1. Transit Network Calibration

The network has been adjusted to make sure that the choice of alternative paths and routes in the model fits best with the choices that are implicitly reported in the counts. Network calibration was performed with and without assignment.

Network checking without assignment

Network checking without assignment is based on the shortest path search and analysis of alternative paths. This step is independent of any trip table. The shortest path search result in terms of bus routes taken, transfers, and total travel time were compared against the result from TransLink’s website trip planner service. This initial network checking was very helpful to discover connectivity problems such as transfers are not allowed at where they could occur or zone connectors are missing.

Network calibration based on assignment

Analyzing the assignment results is important in the case of parallel routes. If a particular route is overloaded while the parallel lines have low ridership, the trip table cannot be adjusted based on assignment results. Therefore, the network was revised after each assignment and station transfer times, zone-station connectors and connector access time will be changed.

After the initial assignment, it was found that B-Lines didn’t have enough boardings because these lines don’t have many stops for travelers to access, and sometimes the travel time savings from using the B-Line is not significant compared with the competing standard bus routes. In reality however, B-Lines are much more favored over other options because of marketing, visibility, fleet. To solve this issue and to make the model reflect the reality, certain rules were applied to B-Lines as well as other rapid transit lines in terms of maximum access walk distance, walk speed and perceived transit running time bonus. The reasonable initial parameters were first applied to the model. The idea behind these parameters is that people are willing to walk longer distances to reach rapid transit modes. This higher attractiveness of rapid transit is caused by convenience, visibility and marketing, higher comfort level and higher service frequencies. In the model the running time of these modes has then a reduced impact. During calibration process, these parameters were fine-tuned and special cases were created for certain stations. The final settings are presented in Table 49 in section 4.3.4.2 on page 85.

Station transfer times were calculated based on stop point coordinates and a constant walking speed. On some key stations such as Broadway-Commercial and Waterfront the transfer walk times were adjusted during calibration to reduce the impedance of attractive connections.



4.3.2.2. Processing and 24-Hour Completion of emme/2 Matrices

Processing of emme/2 Matrices

The regional planning model in emme/2 produced AM and PM peak hour matrices as input for RTM. These two matrices represent the year 2004 with total numbers of 64,500 trips in AM and 71,700 trips in PM. These matrices were processed in several steps to obtain 24-hour demand in four trip tables (AM, Mid, PM and Eve).

Since midday and evening trip tables are not available from the regional demand model, they are estimated based on AM and PM trip tables.

1. AM, PM hourly trip tables are scaled up to match 2004 trip dairy totals, which are 155,000 for the AM period and 181,000 for the PM period. As a first step, the emme/2 hourly matrices were scaled up to have the same total as the trip diary. However such an operation does not guarantee that trip tables have the same district level trip pattern. For this reason the trip tables in VISUM were later aggregated and calibrated on a district to district basis. The side-by-side comparison with the trip diary and boarding counts and correction of K-factors were also applied (see below).

2. Midday and evening trip tables are assumed to be the linear combinations of AM demand and PM demand. The criterion is that the output and survey data have reasonably close row totals and column totals. This criterion is consistent with double constraint (2D balancing) trip distribution method used widely. It was found that 0.5 * (AM Calibrated Matrix + PM Calibrated Matrix) provides good estimation of Midday matrix, and 0.45 * PM Calibrated Matrix matches Evening survey results well.

3. Intra-zonal trips were set to Zero

4. AM Park and Ride trips are transposed in order to obtain PM Park and Ride trips in reverse direction (as the PM emme/2 matrix did not include the transit part of the P&R trips, where the AM matrix did include it).

K-Factor Correction of Trip Tables

With the help of district to district K-factors, the trip tables have been adjusted to better match the 2004 trip diary matrices as well as screen-line loads of SkyTrain, WCE, SeaBus. In a first step, AM and PM trip tables were calibrated based on boarding surveys. In a second step, midday and evening trip tables were estimated based on the calibrated AM and PM trip tables and refined with off-peak counts.

Based on SkyTrain boarding/alighting counts at 43 stations, the CBD inbound and outbound demand were estimated based on the counts at Waterfront, Burrard, Granville and Stadium stations by assuming that most of trips entering or leaving the CBD area use these three stations



as their access/egress points. In a similar fashion, the Expo tail across the river and the boarding/alighting counts at King George, Surrey Central, Gateway and Scott Road stations provide a good estimate of the total number of inbound trips to and outbound trips from the districts across the river.

Boarding and alighting data at four SkyTrain transfer stations, when combined with 2004 trip diary information, provided very important information about trip patterns among districts. For example, the number of boardings at Commercial drive station tells how many trips come from district North Vancouver area, CBD and the rest of the city to destinations along SkyTrain’s upper branch (Millennium Line). Similarly, boarding counts at Broadway station show how many trips coming from Vancouver area, as well as SkyTrain loop upper branch area, take SkyTrain to the area along SkyTrain’s lower branch (Expo Line), such as New Westminster and the area south of Pattullo Bridge. Boarding/ alighting data at Columbia station would suggest very clearly how many trips from the area south of Pattullo Bridge enter the Burnaby area, and vice versa.

When the above information was extracted from SkyTrain counts, it was compared with district level survey data to adjust K-factors created at OD estimation stage. The assignment was performed, and the VISUM results were compared against observed data. This is an iterative process and even though 2004 trip diary is based on a small number of observations, the trip pattern should be respected as much as possible when no obvious conflicts exist.

4.3.2.3. Trip Table Correction with TFlowFuzzy and FlowBundles

TFlowFuzzy

TFlowFuzzy is VISUM’s method to calibrate OD matrices based on counts. The method’s inputs include counts associated with margins of variation, the original OD matrix and the assignment model. The output is a modified OD matrix that will fit the counts within the “fuzzy” margin. TFlowFuzzy has been applied to adjust the RTM passenger assignment in regards to boarding counts on three modes: SkyTrain, WCE and SeaBus. As the current version of TFlowFuzzy only allows link, turn or zone counts as inputs, the boarding counts for these three modes were translated into link counts. It should be noted that CMBC APC counts – as they consist of boarding totals - could not be used with the TFlowFuzzy version in the current VISUM release. It is however planned for one of the next releases of VISUM, probably in 2009, to extend the model to the use of station boarding counts or route total boarding counts. A future re-calibration of the RTM will then be able to use APC data as direct input.

The Phase-A model served to translate 2007 boarding counts for SkyTrain and WCE into link counts. The computed link volumes were then brought to the Phase B model for TFlowFuzzy calibration.



Fine-Tuning based on Flow-Bundle

Flow bundles on specific stations were used to improve the calibration. In VISUM, path information is saved after assignment, therefore it is very easy to trace the trips that board, alight or transfer at a particular station. These trips can then be saved and scaled up or down to fine tune the number of boardings and alightings locally.

This method has been applied with caution so that the trip pattern was not distorted and data at other stations were not negatively affected.

Final Trip Table Symmetrization

In theory, daily trip are symmetric meaning that one outgoing trip corresponds to one returning trip. However the methodology used to derive trip tables for four time periods does not guarantee the total daily trips are perfectly symmetric. To overcome this, the following formulas were applied:

1. Original daily trips = Sum of four time-period trip tables

2. Symmetric daily trips = Original daily trips*0.5 +Transpose(Original daily trips)*0.5

3. Adjustment factor =Symmetric daily trips/Original daily trips

4. Symmetric trip table for each time period= Original trip table for each time period *Adjustment factor

The following table shows the matrix totals for all four demand segments at the end of calibration for the year 2007:

Table 47: Total Number of Trips in the Four Demand Segments for 2007

Demand Segment Number of trips in the OD Matrix

AM 140,300

Mid 209,200

PM 184,700

Eve 92,900

Total (24-Hour Demand) 627,200 Note: numbers in this table are rounded to the nearest 100, so that they might not sum up to the rounded total.



4.3.3. Time of Day Distribution of Travel Demand

A very important component of the RTM is the time-dynamic passenger flow model, based on VISUM’s time-table based assignment. It computes time-dependent route choices and passenger flow specifically for every minute during the day. Together with the 24-hour schedule and the trip tables, 24-hour departure time distributions are key inputs for the assignment model. VISUM allows to specify several departure time curves and to assign them to different groups or OD pairs in the system. In the RTM, four areas of the region have been defined based on the travel time analysis and calibration (see Figure 22). The four areas correspond to zone types and are:

1. Core urban area - City of Vancouver, Vancouver CBD and UBC (TypeNo = 1)

2. Near suburbs

a. West Vancouver, Bowen Island, Lions Bay, North Vancouver (TypeNo = 4)

b. Burnaby, New Westminster (TypeNo = 2)

3. Distant suburbs - Rest of the Modeling Area (TypeNo = 3)

Figure 22: Subareas for the Application of Different Time Series

The calibration of different time series for the subareas appeared to be most reasonable for the time period of AM. In several iterations, the original time series of AM has been modified until the results of validation were close. The general assumption is that trips from zone 2 or 3 which end in the core area start approximately 30 min and 60 min earlier, respectively, than intrazonal trips of the core area. Specific time series were also defined for intrazonal trips in area 3 as well as for



trips between the areas 2 and 3. All assumptions were used symmetrically for opposite directions. The following table shows the assignment of time-curves to subarea-relations.

Table 48: Time Series Used by Area and Zone Type for AM

Core Urban Near Suburbs A Near Suburbs B Distant Suburb

Core Urban 11 21 21 31

Near Suburbs A 21 11 31 31

Near Suburbs B 21 31 11 41

Distant Suburbs 31 31 41 41

Figure 23 shows how the desired departure time of linked trips is distributed during the day. The distributions in the chart are a combination of the two relevant inputs in VISUM: OD matrices and time-series. It can be seen that the peak of demand during PM is equal for all curves. During AM however, people start to travel the earlier, the farther they are from the core area:

Figure 23: Desired Departure Time Distribution – Four Different Types

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4.3.4. Passenger Flow-Model and Path Choice

4.3.4.1. Timetable-Based Assignment Settings

The time-table based assignment in VISUM combines network, transit schedules and trip tables to compute 24-hour passenger flows. As a result of assignment, passenger volumes are provided in small time intervals for links, stops, routes and lines, and on aggregated levels like territories and transport systems. Furthermore, flow bundle analysis can be performed to find out where those trips of interest are coming from and where they go.

Figure 24: Path Choice Utility Function (Perceived Journey Time Function)

An important assumption for the assignment model is the general cost function or in VISUM’s jargon, the perceived journey time, which can be seen in Figure 24. Transit Journey time perceived by a traveler weights various travel time components such as in-vehicle time and out-of-vehicle time, number of transfers and fare. Figure 24 displays the attributes considered and the weight given to each item. These weights have been adjusted during calibration.



4.3.4.2. Rapid Transit Bonus Coefficients

In addition, two kinds of bonuses have been applied to increase the attractiveness of certain rapid transit modes:

• Connector speed (rapid transit stations can be reached faster than other stops)

• Bonus to in-vehicle time – assigned to individual vehicle journey items. Each rapid transit line except WCE has a discount/bonus value that is applied to in-vehicle time. This bonus reflects the attractiveness and the level of public acceptance of rapid transit service quality. The default value equals to 1.0, which corresponds to “no bonus”.

Table 49: Network-Wide Connector Speeds, Capture Distance and Time Bonus Assumptions

Line Name Maximum Connector

Distance (Stop Catchment)

Connector Speed Perceived Running

Time Bonus

SkyTrain 2 km 8 km/h 0.8

Canada Line 2 km 8 km/h 0.8

WCE 2 km 8 km/h 1.0

SeaBus 4 km 12 km/h 0.8

Vancouver Street Car 1 km 4 km/h 1.0

B-Lines 1 km 4 km/h 0.8

Other Lines 1 km 4 km/h 1.0 Note: * B-Line connector speeds in downtown area vary as a result of calibration process. * Connector speeds for SkyTrain stations in downtown area as well as south of Fraser River vary as a result of calibration process. * Perceived running time bonus was set to 1.0 for WCE after trying 0.8 as well – it should be noted that there are almost no other services competing with WCE.



4.4. Validation and Proof of Calibration

For calibration validation purpose we have differentiated several levels of ridership statistics: from network-wide statistics over aggregates of high-capacity services down to individual station or line statistics. The calibration has generally not used these statistics as direct input. Instead, the modelers have adjusted OD flows and then compared ridership statistics with corresponding model results to analyze the effectiveness of the last calibration steps.

4.4.1. Total System Ridership - Linked and Unlinked

The system-wide statistics used to validate the 2007 model results are:

• Total number of unlinked trips, differentiated per transit mode

• Total number of linked trips on aggregated flows

• The relationship between linked and unlined trips which shows the relative transfer rate

These statistics are summarized in Table 50. For the transfer frequency there is no perfect empirical source available. The emme/2 calibration of 1998 assumed 1.6 boardings per trip, probably based on evidence from a household survey. The current RTM calibration shows 1.77, which is close to the transfer frequency assumed in TransLink’s revenue ridership estimations (1.71).

Table 50: Total System Ridership 2007

RTM 2007 Validation and Source

Total number of unlinked trips 1,113,000

Total number of linked trips 627,200

Total number of transfers 485,800

Average number of boardings per trip

1.77

1.71 (revenue ridership estimation 2006)

1.6 (emme/2 calibration 1998)



System-Wide Unlinked Trips

The total number of unlinked trips (equivalent to the number of boardings) could be estimated relatively close, as most modes have either had recent boarding surveys or system wide automated passenger count statistics. Table 51 shows the total number of boardings per mode. These numbers are either aggregates from a 2007 survey or results from a survey prior to 2007 that has been adjusted with a growth factor. The growth factors are derived from TransLink’s monthly revenue ridership reports. VISUM replicates the system-wide ridership very closely with approximately 1.0 million boardings for the counted part of the system. The RTM demand estimated that the total ridership (counted and uncounted services) is in the order of 1.1 million. VISUM also matches the totals for the individual modes or sub-systems very closely.

Table 51: Total Unlinked Ridership per Mode/System 2007

Source of the Count

Original source/count

Count factored for 2007

RTM 2007

SkyTrain Survey 2003, 2005, 2006 249,100 271,078 276,956

West Coast Express Boarding count Sept 2007 10,060 10,060 10,940

WCE TrainBus n/a n/a n/a 1,209

SeaBus Boarding count Sept 2007 15,728 15,728 14,292

Other Ferry n/a n/a n/a 10

B-lines APC fall 2007 81,536 81,536 87,897

Other APC Buses APC fall 2007 653,395 653,395 664,907

Non APC Buses n/a n/a n/a 157

Shuttles (no APC) n/a n/a n/a 55,016

TOTAL counted 1,009,819 1,031,797 1,054,992

TOTAL overall n/a 1,111,384



Linked Trips between Fare Zones

The best source for linked trips is the trip diary (household survey) from 2004. Note that the survey had around 2,800 observed transit trips in the sample. The totals shown in Table 52 are the 2800 observed trips expanded with weights to represent the total population. Given the sample size, it appeared to be appropriate to aggregate all trips to a three-by-three matrix based on TransLink's fare zones. As a result, the sample per aggregate is large enough to allow to estimate the number of real-world trips. During the calibration, the number of trips within fare zone one (which is Vancouver and UBC) had to be increased significantly in comparison to the emme/2 matrices. The aggregated trip diary matrix as well as the bus boarding statistics pointed our calibration consistently to the same conclusion. Overall the order of magnitude is approximately 650,000 linked trips in the region.

Table 52: Total Linked Ridership between Fare Zones 2007 Observed-Trip Diary 2004

Zone 1 Zone 2 Zone 3 TOTAL Zone 1 258,500 69,500 26,200 354,300 Zone 2 67,400 75,100 23,300 165,700 Zone 3 30,000 21,600 37,800 89,500 TOTAL 355,900 166,200 87,300 609,400

Trip Diary factored up to 2007 (11% growth 2004-2007)


VISUM 2007


Note: Average weekday travel. Trip diary sample size is of only 2,800 trips which is why the expanded number of trips needs to be interpreted with caution. The growth factor from 2004 to 2007 of 11% is based on the annual TransLink ridership estimates based on fare box statistics. Numbers are rounded to the nearest 100 and might not sum up to the rounded total.



4.4.2. SkyTrain Boardings and Transfers

Figure 25: SkyTrain Daily Station Boardings, Alightings and Transfers

Note: * Number of boarding trips includes direct boarding trips entering the station, as well as the transfer boarding trips within the station. * Number of alighting trips includes trips leaving the station, as well as transfer boarding trips within the station.



SkyTrain is the backbone of the transit network with over 250,000 boardings per day. The station boardings and alightings have been surveyed several times in recent years. Note that our numbers in Figure 25 and Figure 26 represent 24-hour boardings plus 24-hour alighting including all transfers happening at each station. In the case of a bus-SkyTrain transfer, the transfer is counted once. In the case of a SkyTrain-SkyTrain transfer, the transfer is counted twice. The statistics include only what happened on the platforms; they do not include boardings that happened at bus stops that belong to the station. Overall, VISUM shows a very good approximation of the station statistics. We believe that this level of goodness of fit is the maximum reasonable given the variation of boarding counts. Also it has to be considered that some stations have not been counted since 2003 and some 2007 numbers rely largely on a growth rate assumption over 4 years. The growth rates were derived from TransLink’s revenue ridership estimates.

Figure 26 shows the same statistics as a scattergramm. The correlation coefficient is 95% and the RMSE is 16%. Later in the report in section 4.4.6, 24-hour distributions of boardings at some stations will be shown.

Figure 26: SkyTrain Daily Station Boardings - Goodness of Fit

Note: total number of boardings is the 24-hour sum of boardings, alights resulting from star of a trip or from transfer. The “Survey 2007” represents numbers from 2006 surveys (or 2005, 2003 if not surveyed in 2006) and factored up to represent 2007.



SkyTrain-to-SkyTrain Transfers

Transfers from SkyTrain to SkyTrain have been surveyed at the three stations Broadway (BW), Commercial Drive (CM) and Columbia (CO). This is the only survey provided information on transfer activity in the network. To avoid misunderstanding, the comparisons for the three stations show both transfers and direct boardings and direct alightings. Note that transfers between SkyTrain and Bus are included in either boardings or alightings. As Table 53 shows, the model replicates the transfer pattern very closely.

Table 53: SkyTrain Daily Boardings, Alightings and Transfers at Major Transfer Stations

Boarding, w/o rail transfer

Alighting, w/o rail transfer

Rail-to-Rail Transfer Boarding

Rail-to-Rail

Transfer Alighting

Total Boarding

Total Alighting

Total B+A+T

Survey 2007

BW 17,700 17,600 9,500 7,900 27,200 25,500 52,700

CM 5,600 5,300 7,900 9,500 13,500 14,800 28,300

CO 3,200 3,500 7,500 7,500 10,700 11,000 21,700

Total 26,500 26,400 24,900 24,900 51,400 51,300 102,700

RTM 2007

BW 17,027 18,597 8,946 7,861 25,973 26,458 52,431

CM 6,941 7,680 7,861 8,946 14,802 16,626 31,428

CO 4,782 5,981 6,183 6,183 10,965 12,164 23,129

Total 28,750 32,258 22,990 22,990 51,740 55,248 106,988Note: * Direct boardings are those boarding trips from outside the same station. *Leaving alightings are those alighting trips going out of the same station.

4.4.3. SeaBus Boardings and Loads

Table 54 compares the SeaBus ridership between VISUM estimation and survey. VISUM matches the total number of SeaBus boardings very well.

Table 54: SeaBus Ridership 2007 for Four Time Periods

Direction AM Midday PM Evening Total

Survey VISUM Survey VISUM Survey VISUM Survey VISUM Survey VISUM

NB 1326 1117 2269 1734 2580 2227 1934 1428 8109 7070

SB 2150 2294 2240 1854 2120 1822 1109 713 7619 7220



4.4.4. West Coast Express Boardings and Loads

WCE has very reliable load statistics, which have been used for calibration and validation. VISUM's ridership replicates the loading curve very well, as shown in Figure 27.

Figure 27: West-Coast Express Ridership 2007 AM and PM



4.4.5. CMBC Bus Boardings and Loading Curves

Total Boardings (Unlined Trips) per Route

Table 55 summarizes B-Line daily boardings of lines 97, 98 and 99. These three lines get most attention among the bus lines, but there are some other routes that have ridership in the order of magnitude of B-Lines. Figure 28 shows that VISUM replicates the CMBC 24-hour boardings very well. Note that there have been issues with determining the real ridership based on APC data. Unfortunately, our calibration was for some time misled by APC loading data to try to achieve B-line boardings almost two times as high as the current calibration outcome. Later in the calibration, we have introduced the lower number shown in the tables. The original APC loading data have been down-factored to meet the 24-hour total.

The boarding data show different groups of busses in different colours. It can be seen that the big bus lines are all green squares (B-lines) or blue dots (inside of Vancouver). VISUM replicates the total ridership per line pretty well.

Table 55: B-Line Ridership 2007 for Four Time Periods

Direction AM Midday PM Evening Total

APC VISUM APC VISUM APC VISUM APC VISUM APC VISUM

97 2,242 2178 3,239 4445 2,704 2680 1,788 2,076 10,148 11,379

98 5,712 6474 10,174 11147 6,430 9616 4,947 6,508 27,534 33,745

99 9,526 8150 14,836 13764 11,687 13765 7,662 6,338 43,856 42,017



Figure 28: CMBC Buses Daily Boardings 2007 (VSUM versus APC)

Bus Loading Curves

VISUM replicates the general pattern of the loading curve for each of the three B-Lines very well. It should be mentioned again that the empirical curved were obtained APC data, but were factored with a very simple factor that is constant over 24 hours. The following three figures show the loading curves for B-Lines 98, 97 and 99.



Figure 29: B-Line 98 Daily Loading Curves (VISUM versus APC)

NB:

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4.4.6. 24-Hour Time Distribution of Demand

Once the matrices were calibrated, we adjusted the distribution of departure time so that the ridership fits on major facilities that could provide 24 hour boardings or loading data. It can be seen that the VISUM matches all curves very well. The first two are located in proximity to downtown: SeaBus and the SkyTrain link BWI. It should be noted that the two links are otherwise very different: SeaBus has relatively local demand where BWI represents the most heavily loaded and the most congested link in the entire network. During the calibration it could be seen, that BWI is sensitive to adjustments in other areas of the model, which underlines its critical role in the system.

Figure 32: Time Distribution of SkyTrain Morning Peak Loads, Broadway Inbound

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Figure 33: Time Distribution of SeaBus Boardings

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The SkyTrain stations in downtown such as WF, MN and BW have very similar patterns, with the exception of GV which has a somewhat unique curve. All downtown stations are replicated pretty well in the model on both the boarding and alighting sides. The suburban stations CO and CM clearly show that the boarding in the AM period starts earlier than at the downtown stations. The model achieves a good replication of this time shift, thanks to a differentiation of departure time distributions over the region. Metrotown (MT) has a very individual curve that is better replicated on the alighting than on the boardings side. This suburban location enjoys an urban character with a combination of business and residential, and therefore it is not surprising that it shows a unique ridership pattern. PW, LH and BD are the most outlying SkyTrain stations that were available for this validation with year-2007 24-hour boardings data. It can be seen that VISUM fits the pattern of the distribution very well. It should be noted that the CO alighting counts are incomplete – they do probably not include transfers.



Figure 34: Time Distribution of SkyTrain Boardings for Waterfront and Granville Stations

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Figure 35: Time Distribution of SkyTrain Boardings for Commercial Drive and Broadway

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Figure 36: Time Distribution of SkyTrain Boardings for Main Street and Metrotown Stations

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Figure 37: Time Distribution of SkyTrain Boardings Columbia and BD Stations

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To analyze boarding time distribution in the outlying suburbs, aggregated data of several bus lines have been used. Analyzing the goodness of fit of individual bus lines would overstretch VISUM's calibration goals but also the reliability of the APC data. In the following, the two groups of buses from Coquitlam and Surrey have helped to adjust the time distribution in the model to reflect the earlier start of trips in the morning in these areas.

Figure 39: Time Distribution of Suburban Bus Boardings – Selected Lines in Surrey

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Note: The curve is the cumulated total boarding of lines 323, 324, 325, 326 and 335

Figure 40: Time Distribution of Suburban Bus Boardings – Selected Lines in Coquitlam

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Note: The curve is the cumulated total boarding of lines 151, 152, 153, 159, 169 and 177



5. Network and Ridership Scenario 2011

This chapter summarizes the development of the year 2011 network and operations models, the methodology for demand forecasting, as well as a validation of the 2011 results. The network and operations models were derived from the 2007 model, as described in chapter 2. The RTM network is organized as a master network, that contains 2007 and 2011 networks and demand data. The version file can be used to compute year 2007 and 2011 scenarios.

Section 5.1 describes the development of the 2011 network and the results of the operations model. Section 5.2 elaborates on the demand forecasting for 2011, including demand growth assumptions and time-of-day formulas. Section 5.3 presents key results of assignment and line blocking, and validates the results by comparing them to 2007 and to previous forecasts.

5.1. Network Model and Transit Service

The 2011 transit network in Metro Vancouver will undergo significant changes from the existing year condition. The differences include, but are not limited to: the Canada line will be part of the rapid transit system, the #98 B-Line will be discontinued and the third SeaBus will operate. Many bus routes in Richmond will be adjusted to serve the Canada Line stations at Richmond-Brighouse and Bridgeport, replacing direct express bus services. Several South of Fraser bus routes will be shortened to terminate at the Canada Line’s Bridgeport station to reduce duplication and improve efficiency and service levels. Granville Street construction will also be complete, allowing many detoured local Vancouver routes to return to this street downtown.

This section of the report describes the network editing which has been performed to develop the year 2011 transit network model starting from the year 2007 network as described in chapter 2.

5.1.1. Network Topology (Links, Stops, Connectors)

New Links

The existing year model was first checked and new nodes and links that are needed for the new bus routes were identified. This step is the basis for new routes to be added or for the existing routes to be realigned. The following table summarizes all the new links added to the network that had not been included in 2007.



Table 56: New Links in Year 2011 Link No. Location 32926999 Westminster Hwy at Garden City 32927132 Buswell - Westminster to Saba 32905772 Davie - Richards to Homer 32905862 Davie - Homer to Hamilton 32905956 Davie - Hamilton to Mainland 32906043 Davie - Mainland to Pacific 32906276 Davie - Pacific to Marinaside 32906332 Davie - Marinaside circle 32971897 Davie - Marinaside circle 32971898 Davie - Marinaside circle 32922865 W 71 Av - Hudson to Selkirk 32908281 Links N of Cambie and Broadway for routing flexibility 32908550 Links N of Cambie and Broadway for routing flexibility 32908721 Links N of Cambie and Broadway for routing flexibility 32908773 Links N of Cambie and Broadway for routing flexibility 32908824 Links N of Cambie and Broadway for routing flexibility 32908825 Links N of Cambie and Broadway for routing flexibility 32908977 Links N of Cambie and Broadway for routing flexibility 32909029 Links N of Cambie and Broadway for routing flexibility 32909073 Links N of Cambie and Broadway for routing flexibility 32909074 Links N of Cambie and Broadway for routing flexibility 32909233 Links N of Cambie and Broadway for routing flexibility 32909282 Links N of Cambie and Broadway for routing flexibility 32904599 Hamilton - Dunsmuir to Pender, TSys TB NB only 32904994 Hamilton - Robson to Georgia, TSys TB NB only

Stops

In the VISUM model, a line route is integrated into the regional transit network through the stop point/stop area/stop settings as specified by the modeler. Due to the hierarchical structure of the stop model in VISUM, when a new route is created, each stop point along the route needs to be carefully checked and properly assigned to the nearby existing stop area/stop. This step is crucial because walking is not allowed on the roadway links in the model. It is determined at the stop data if transfer between different routes is allowed and how much time it takes. Errors in the stop transfer settings could misrepresent the real situation and lead to unreasonable assignment results.



Table 57 lists the stop points that have been added to or deleted from the network and shows how the new stop points have been allocated to the existing or the newly created stop areas.

Table 57: Year 2011 Transit Stop Settings Stop Area

Number New /

Existing Stop Area Name Stop

Points Note Added

50023 New Davie St/Mainland St 50023 Reinstate stop, reuse CMBC number 61215 Reinstate stop, reuse CMBC number

50016 Existing Davie St/Pacific Blvd 50085 Reinstate stop, reuse CMBC number 50412 New Cambie/ W 7 Av 50412 Reinstate stop, reuse CMBC number 50617 Existing Granville/Robson 58326 Reinstate stop, reuse CMBC number 50976 Existing Granville/Georgia 50223 Reinstate & move stop, reuse CMBC number50976 Existing Granville/Georgia 50531 Reinstate & move stop, reuse CMBC number50976 Existing Granville/Georgia 60980 New stop, use proposed CMBC number 60993 New Granville/Dunsmuir 60993 New stop, use proposed CMBC number 50077 Existing Granville/Pender 50526 Reinstate & move stop, reuse CMBC number50078 Existing Granville/Pender 50226 Reinstate & move stop, reuse CMBC number50034 New Granville/Hastings 50034 Reinstate stop, reuse CMBC number 50035 New Granville/Hastings 51374 Reinstate stop, reuse CMBC number 50619 Existing Hamilton/Robson 50486 Reinstate stop, reuse CMBC number 50487 New Hamilton/Georgia 50487 Reinstate stop, reuse CMBC number 50488 New Hamilton/Dunsmuir 50488 Reinstate stop, reuse CMBC number 50016 Existing Davie St/Pacific Blvd 59398 Reinstate stop, reuse CMBC number

Deleted

50221 Existing Granville at Helmcken 50221 Cancelled as part of Granville Mall redesign 50534 Cancelled as part of Granville Mall redesign

Connectors

The line routes added to the network in year 2011 include the Canada Line and new bus lines. Connectors were set up based on the rules used to create connectors in the existing year model. It is assumed that, like the SkyTrain system, the maximum access (walk or drop-off) distance for the Canada Line is 2 km and connector speed is 8 km/h. Perceived travel time bonus reflects the preference that passengers have over other lines. A value less than 1.0 represents a travel time discount and will make the line more attractive to passenger during the assignment. The value of perceived running time bonus is equal to 0.8 for Canada Line, and thus leads to a 20% perceived time saving than actual running time to reflect its attractiveness along the Richmond-Vancouver Corridor. Connector settings for #33 and #388 are the same as what were used for normal bus lines. An overview of connector speeds for different transit modes is given in section 4.3.4, in particular Table 49.



5.1.2. New Transit Lines and Service Adjustments 2011

As mentioned earlier, many existing line routes will have their alignments changed. The list below provides the full picture of the line route additions, removals or alignment changes:

1) Canada Line will be running with the service characteristics defined in Phase A

2) Bus system adjustments to be made around Canada Line

• Richmond

- Replace all express routes (488, 491, 492 and 496) with improved local service to Canada Line stations

- Discontinue #98 B-Line service

- Discontinue 424 bus service to the Airport

- Line Routes 401-410 (excl. 403) will terminate at Richmond-Brighouse Station

- Line Route 403 will terminate at Bridgeport Station

South of Fraser

- All highway 99 routes (311, 351, 352, 354, 601, 602, 603, 604, and 620) will terminate at Bridgeport Station

East-West Vancouver

- New route 33 from 29th Ave Station to UBC via E 33rd Ave, Cambie Street and W 16th Ave

- New Community Shuttle C17, linking Oakridge-41st Ave Station with King Edward Station, to serve Oak Street hospitals.

North-South Vancouver

- Granville (#10) and Main(#3) trolley routes will be extended to Marine Dr. Station

- #10 to run between Marine Dr. Station and Downtown

- # 15 to terminate at Broadway and Cambie

- #17 over Cambie Bridge and will extend to Marine Dr. Station

3) The new Vancouver Streetcar will connect Canada Line and Granville Island (demonstration line in 2010, may continue after.)

4) New Bus Line #388

5) The third SeaBus (a third vessel) will be put in service to increase frequency and capacity.



6) Bus System Adjustments after Construction on Granville

- #4 , #5, #6,#7, #10, #16, #17, #50

Bus Run Times

The CMBC winter 2007 schedule data was brought into the existing year model, so that the run time for each vehicle trip (also referred to as vehicle journey in VISUM) reflects the real situation. However, detailed bus schedules for new line routes or realigned line routes in year 2011 have not been developed. The following bus run time assumptions were made:

• If a bus route is rerouted locally and the difference is minor compared with year 2007 condition, then the total run time specified for year 2007 is used and VISUM will adjust the run time between adjacent stops automatically. Routes in this category include those that are shifted to Granville Street from Seymour Street.

• If a new line route is added to the network in year 2011, then the bus run time is calculated based on the link attribute "op_avg_spd" from the existing model and this attribute is the average speed of all traversing line routes weighted by their service frequencies – see section 3.1.2 of this report.

• If a link is not traversed by any existing year line route, the calculated average values of "op_avg_spd" by facility type are considered: 50 km/h for freeways, 40 km/h for principal arterial streets, 30 km/h for major arterial streets, and 20km/h for all other facility types.

• Run time information for Canada line comes from the official website www.canadaline.ca.

Bus Timetable Development

Timetable development was the most time-consuming part of the year 2011 transit network and operations model development. When constructing the time table for each future year line route, 24-hour vehicle journey time-space diagrams were first developed based on the time of day headway information provided by TransLink. Meanwhile, proper vehicle types were assigned to vehicle journeys. It is important to assign reasonable bus run time to each vehicle journey based on time of day as this will have a big impact on transit assignment and fleet requirement results. When working on the existing year line routes with realignment, the current time of day run time settings were used to maintain consistency.

New Vehicle Type

Vehicle Type 903 will be added in year 2011, which is for the low-floor articulated trolley. It will be used for lines 3, 8 and 20. For all community shuttles, the vehicle type will be changed from 950CA to 951CAB due to fleet replacement.



5.1.3. SkyTrain Operations 2011

In year 2011, it is assumed that 150 Mark-I train cars and 108 Mark-II train cars will be available for SkyTrain system. The key idea behind the SkyTrain fleet assignment is to avoid running 2-car Mark-II trains due to their low capacity, and put the larger trains on the Expo line as much as possible. Millennium Line will only use 4-car Mark-I trains. Table 58 shows the SkyTrain Line blocking results and train car usage. (This projection will change if TransLink exercises its option for an additional 24 Mark II cars in 2009.).

It should be noted that the 2011 fleet assignment shown in Table 58 is different from the one assumed for RTM Phase A.

Table 58: SkyTrain 2010: Number of Blocks per Train Type

Line Expo Millennium

From - To WF – KG WF – VC Headway AM Peak 162 s in avg. (2 min 42 s) 324 s (5 min 24 s) # of blocks/trains AM Peak 32 23 # of blocks per train type

4-car Mark I -- 23 6-car Mark I 7 -- 2-car Mark II -- -- 4-car Mark II 25 --

Total fleet used, AM Peak: 134 Mark I (11% spare) and 100 Mark II (7% spare)



5.2. Future Travel Demand 2011

Future year demand is calculated based on the following formula, which is also referred to as the "Difference Method":

Future Year Calibrated OD = Δ + Existing Year Calibrated OD

where:

Δ = Demand growth in the original model (EMME/2 model in this case)

It can be seen from the above formula that the assumption behind the Difference Method is that the demand growth in the original model is also the difference between future year demand and the existing year calibrated demand. The next section elaborates the methodology for demand forecasting by looking at each step.

5.2.1. Development of Future Trip Tables

5.2.1.1. Processing of emme/2 Matrices

emme/2 PM One-Hour Matrix Adjustment

It was found that the PM peak hour matrix from emme/2 model has an unreasonably high number of trips, which would correspond to a 52% growth from 2004 to 2011 (see Table 59). Assuming that the annual transit demand growth in Vancouver Metro Area is no more than 3%, AM demand increases seem to be much more reasonable. 18.5% will used as the growth rate between 2004 and 2011 for PM as well. Table 59 shows the adjusted 2011 PM peak hour demand with adjusted growth.

Table 59: Year 2011PM One-Hour Demand Adjustment

emme/2 AM emme/2 PM PM -Adjusted

Year 2004 62,387 71,501 71,501

Year 2011 73,937 108,558 84,684

Growth 11,550 37,057 13,183

Growth Rate 18.5% 52% 18.5%



Demand Growth Assumption

It should also be noted that emme/2 model existing year is referring to year 2004, and the RTM existing year is calibrated to year 2007 conditions. For the RTM forecasting purpose, the demand growth should be four-sevenths of the emme/2 model output (based on the formula (2011-2007)/(2011-2004) = 4/7). This consideration will be reflected in the formulas presented in the next section.

5.2.1.2. Delta-Matrix Development and Application

AM peak period factor of 2.36 and PM peak factor of 2.33 are used to convert the hourly demand to the AM and PM peak period demand. These two values are derived from the ratio of 2004 trip diary to emme/2 hourly demand and have been used for model calibration purpose.

In the following formulas, "demand growth" refers to peak period demand growth and factors 4/7 and peak factor 2.33/2.36 have been taken into consideration. "PM hourly demand growth" is the adjusted PM hourly demand growth (refer to Table 59).

Forecasted 2011AM demand =2007 AM calibrated+ AM hourly demand growth*2.36*4/7 = 2007 AM calibrated+ AM demand growth Forecasted 2011PM demand: =2007 PM calibrated +PM hourly demand growth*2.33*4/7 = 2007 PM calibrated + PM demand growth

In the regional emme/2 planning model, midday and evening demand are not available. During the existing year calibration process, based on 2004 trip diary, midday demand was estimated to be the average of AM and PM demand, and evening demand was estimated to be 45% of the PM demand. These factors and relationships are used for future year forecasting as well.

Forecasted MD demand: =2007 calibrated MD demand +[0.5*(2011 AM hourly demand*2.36+2011 PM hourly demand*2.33)] - [0.5*(2004 AM hourly demand*2.36+2004 PM hourly demand*2.33)] =2007 calibrated MD demand +0.5*[(2011 AM demand growth)+(2011 PM demand growth)] Forecasted EV demand: =2007 Calibrated EV demand+(PM Demand Growth)*0.45

5.2.1.3. Trip Table Symmetrization

It is assumed that daily trips need to be symmetric. That means that one outgoing trip at any time



of day has a corresponding return trip at another time of the day. Also during the calibration of the existing demand (section 4.3), the methodology used to derive the individual demands for the four time periods does not guarantee the symmetry of the daily demand. To overcome this, the following formulas are used:

• Original daily trips = Sum of demand for four time periods based on the difference method

• Symmetric daily trips = Original daily trips*0.5 +Transpose(Original daily trips)*0.5

• Adjustment factor =Symmetric daily trips/Original daily trips

• Symmetric trip table for each time period= Original trip table for each time period *Adjustment factor

5.2.1.4. Airport Demand

Year 2011 airport daily transit demand at YVR is assumed to be 4,600 (RTM Phase A), including deplaning and enplaning passengers. These trips were not explicitly modeled in an emme/2 model, and need to be added. As has been shown in "Richmond/Airport/Vancouver Rapid Transit Project Definition Phase Final Report on Ridership & Revenues" (Halcrow&TSi, 2003), more than 50% of the air passengers are currently coming from or going to the CBD area. To simplify the post-processing but also maintain the reasonableness of the result, the following methodology was developed for adding airport demand to the demand total:

1. First perform daily assignment using the matrices obtained from the difference method.

2. Flow bundle analysis was performed to obtain airport trips that use Canada Line. Save the flow bundle result as a matrix and assume these trips are employee trips or other non-air passenger trips.

3. Expand the flow bundle matrix to the target demand of 4,600 to obtain the total air passenger demand. It is assumed that the airport passenger trips follow the same pattern as the flow bundle trips obtained in step 1.

4. Apply the same time of day distribution used for Phase A to obtain time of day airport demand. The time of day factors are 30%, 24%, 36% and 10% for AM, MD, PM and EV, respectively (refer to "future demand" Excel spreadsheet for Phase A).

5. Assume that deplaning and enplaning air passenger trips are the same for each time period.



5.2.2. Results

Existing year demand and 2011 demand are first compared at different aggregate level. First the totals are compared. Then the demand at fare zone level and 10-district level are compared and the results are shown in Table 60 through Table 61.

Table 60: Year 2007 and 2011 Demand Total Comparison

Year AM MD PM EV

2007 140,343 209,191 184,742 92,921

2011 158,314 227,887 204,523 101,579

Growth + 13% + 9% + 11% + 9%

Table 61: Year 2011 Demand Growth at Fare Zone Level VISUM 2007


VISUM 2011 Zone 1 Zone 2 Zone 3 TOTAL

Zone 1 276,800 79,600 28,600 384,900 Zone 2 80,400 87,000 25,000 192,400 Zone 3 28,500 25,500 60,900 115,000 TOTAL 385,700 192,100 114,500 692,300

Growth (2007-2011) Zone 1 Zone 2 Zone 3 Total

Zone 1 13,600 7,400 2,000 22,900 Zone 2 8,200 10,300 3,500 22,000 Zone 3 2,300 4,000 13,900 20,200 TOTAL 24,100 21,700 19,400 65,100

Note: Numbers are rounded to the nearest 100, so that they might not sum up to the rounded total.

The demand comparison at 10-district level is presented in Table 61.



Table 62: Year 2011 Demand Growth at 10-District Level Year 2007 1 2 3 4 5 6 7 8 9 10 Total

1 13,500 9,300 4,300 2,300 300 600 900 0 0 0 31,200

2 9,300 14,500 44,700 22,000 3,900 3,900 6,600 700 500 4,400 110,500

3 4,300 44,600 158,800 24,000 2,700 7,900 7,000 400 700 700 251,100

4 2,300 22,000 24,100 42,100 6,700 1,900 8,900 300 900 1,000 110,200

5 300 4,000 2,700 6,700 11,000 200 700 800 0 100 26,500

6 400 3,700 8,200 2,000 200 11,600 2,300 0 0 0 28,400

7 900 6,500 6,900 9,000 700 2,200 25,100 0 2,000 0 53,300

8 0 700 400 300 800 0 0 1,300 0 0 3,500

9 0 500 700 900 0 0 2,000 0 2,400 0 6,500

10 0 4,300 600 1,000 100 0 0 0 0 0 6,000 Total 31,000 110,100 251,400 110,300 26,400 28,300 53,500 3,500 6,500 6,200 627,200

Year 2011 1 2 3 4 5 6 7 8 9 10 Total

1 16,400 10,100 4,900 2,500 300 700 900 0 0 0 35,800

2 9,900 15,300 48,200 22,700 4,300 4,900 6,800 600 500 4,400 117,600

3 5,000 48,000 164,900 25,800 3,300 10,500 7,700 400 700 800 267,100

4 2,600 23,100 26,300 46,500 7,700 2,800 9,900 300 1,000 1,100 121,300

5 300 4,400 3,400 7,900 14,300 500 1,200 900 0 100 33,000

6 700 4,800 10,500 2,700 500 12,000 3,000 0 100 0 34,300

7 900 7,000 7,400 10,200 1,100 3,000 32,800 0 2,400 0 64,800

8 0 700 400 300 700 0 0 1,600 0 0 3,700

9 0 500 700 1,000 0 100 2,400 0 3,100 0 7,800

10 0 4,300 700 1,200 100 0 0 0 0 0 6,300 Total 35,800 118,200 267,400 120,800 32,300 34,500 64,700 3,800 7,800 6,400 692,300

Growth 1 2 3 4 5 6 7 8 9 10 Total

1 2,900 800 600 200 0 100 0 0 0 0 4,600

2 600 800 3,500 700 400 1,000 200 -100 0 0 7,100

3 700 3,400 6,100 1,800 600 2,600 700 0 0 100 16,000

4 300 1,100 2,200 4,400 1,000 900 1,000 0 100 100 11,100

5 0 400 700 1,200 3,300 300 500 100 0 0 6,500

6 300 1,100 2,300 700 300 400 700 0 100 0 5,900

7 0 500 500 1,200 400 800 7,700 0 400 0 11,500

8 0 0 0 0 -100 0 0 300 0 0 200

9 0 0 0 100 0 100 400 0 700 0 1,300

10 0 0 100 200 0 0 0 0 0 0 300 Total 4,800 8,100 16,000 10,500 5,900 6,200 11,200 300 1,300 200 65,100

Note: The definition of 10 districts used for demand aggregation follows the 2004 trip diary definition (see section 4.2, in particular Figure 20 and Table 46). Numbers are rounded to the nearest 100, so that they might not sum up to the rounded total.



5.3. Model Results 2011 and Validation

For validation purposes, the model results are compared either to 2007 ridership statistics or to previous forecasts from RTM Phase A.

5.3.1. Model Results 2011

Number of Boardings

Figure 41 shows the year 2011 assignment volumes in the system, focusing on the rapid transit system. Overall there is a 10% increase of SkyTrain ridership and the segment volumes are very close to Phase A. It is worth mentioning that during existing year model calibration, the APC daily boarding total for 98 B-Line, which is used as control total, are much lower than the boarding totals aggregated from the stop level data. This led to the reduction of ridership on line 98, and hence affects the Canada Line forecasted ridership. The daily link volumes on the Canada line are sometimes lower in the Phase B model compared to Phase A.

Figure 41: Rail Transit Daily Assignment Volumes 2011

System ridership statistics are compared with the existing year model calibration results and are



listed in Table 63. There is no major change in average number of transfers.

Table 63: Total System Ridership Statistics, RTM 2007 versus 2011

RTM 2007 RTM 2011

Total number of unlinked trips 1,113,000 1,233,400

Total number of linked trips 627,200 692,300

Total number of transfers 485,800 541,100

Average number of boardings per trip 1.77 1.78

Total unlinked ridership by system is compared with the RTM 2007 calibrated results and displayed in the following two tables. Note that the category "All other APC equipped" in Table 64 includes future year line route 33 and 388 assuming the APC equipment will be deployed on these two bus routes. Table 65 shows that Line #99 number of boardings for year 2011 is slightly higher than year 2007. The shortest path analysis shows this is partly due to the Canada Line serving trips to Central Broadway. Some Passengers who today take SkyTrain then transferred at Broadway Station to #99 WB will be able to take SkyTrain to Downtown then transfer to the Canada Line. In addition, many passengers can reach SkyTrain without taking line 99 by using line 33 connecting UBC and SkyTrain 29th-Ave Station.

Table 64: Total Unlinked Ridership per Mode/System, RTM 2007 versus 2011

RTM 2007 RTM 2011

SkyTrain 276,956 301,261

West Coast Express 10,940 12,397

Canada Line n/a 134,069

WCE TrainBus 1,209 1,552

SeaBus 14,292 15,938

Other Ferry 10 13

B-lines 87,897 57,490

Other APC Buses 664,907 640,923

Non-APC Buses 157 256

Shuttles (no APC) 55,016 67,501

TOTAL All Lines 1,111,384 1,231,400



Table 65: B-Line Ridership, RTM 2007 versus 2011

RTM 2007 RTM 2011

97 11,525 14,028

98 34,171 0

99 42,201 43,462

Total B-Lines 87,897 57,490

Scenario comparison: 2011 versus 2007

The following three maps put the 2011 scenario in contrast with 2007, using VISUM’s automated visualizations with identical graphic parameters. The three evaluations try to show the effect of Canada Line, using average speed, travel time and passenger volumes for comparison. Major effects that can be seen are:

• In terms of average operating speed or average travel speed on the Canada Line corridor, there is a clear improvement from the B-Line to the ALRT: while the bus is never faster than 35 km/h, Canada Line will reach 40 km/ and higher. See Figure 42.

• Figure 43 shows a comparison of travel time isochrones starting at the airport: It shows that the accessibility of the airport has improved along the Canada Line corridor up to Vancouver’s CBD. However, due to the limited connectivity of Canada Line with SkyTrain, these travel time advantages are not extended much beyond Downtown Vancouver.

• Figure 44 compares passenger volumes. The Canada Line will clearly become the major North-South carrier between Richmond and Downtown and its passenger volumes will exceed the volumes observed on the B-Line today.



Figure 42: Visual Comparison of Average Network Speed 2011 versus 2007

2011

2007



Figure 43: Visual Comparison of Travel Time from/to YVR Airport 2011 versus 2007

2011

2007



Figure 44: Visual Comparison of 24-Hour Passenger Volumes 2011 versus 2007

2011

2007



5.3.2. Ridership Validation

Validation of the assignment results have been performed mainly for the Canada Line by comparing RTM’s results to previous forecasts. The following table shows the number of boardings during the AM peak-hour for the Canada Line and maximum loads per section. The comparison shows that Phase A and Phase B results are very similar.

Table 66: Canada Line: Comparison of VISUM and emme/2 ridership totals

AM peak hour Phase A Year 2010

emme/Halcrow Year 2010

Phase B Year 2011

excl. airport hourly demand 8,820 9,020 n/a incl. airport hourly demand 9,868 n/a 10,195* Section max. link loads 2010(2011):

Waterfront – Bridgeport excl. airport demand 4,450 4,230 incl. airport demand 4,854 n/a 4,483 Airport – Bridgeport excl. airport demand 960 1,050 incl. airport demand 1,238 n/a 1,077 Richmond – Bridgeport excl. airport demand 1,680 1,800 incl. airport demand 1,863 n/a 1,736

Notes: * AM Peak hour total number of boardings is the maximum of 60-min values based on 15-min interval data in Phase A model. In Phase B model, the maximum of 60-min values from the 30-min interval data is used.

The Canada Line number of boardings by time period is compared between Phase A and Phase B and the result is shown in the next table.

Table 67: Canada Line Boardings by Time of Day (Phase A vs. Phase B)

Scenario Canada Line Number of Boardings

AM MD PM EV Total

Phase A 2010 20,944 40,173 36,866 26,997 124,980

Phase B 2011 26,836 42,651 42,118 21,229 132,834



5.3.3. Line Blocking

Line blocking was performed for the Rapid transit system, ferries, CMBC buses, etc. This task serves two important purposes: 1) It is an efficient tool to catch errors that might have occurred during time schedule updates, line route creation or removal, given the complexity of the service pattern changes in many areas; 2) It provides a big picture of the fleet requirement change for each transit depot; 3) Line blocking analysis can also assist in the future year bus schedule optimization.

The line blocking settings are consistent with those used for Phase B existing year line blocking (chapter 3.2 of this report). A preparation time of 2 min is used for Canada Line, consistent with RTM Phase A.

The results are all compared with Phase B model existing year numbers which have been validated.

5.3.3.1. Number of Blocks per Rapid Transit Line

Table 68 shows the line blocking result for rapid transit line system. There is one fewer block for Expo AM because the short-turn service between Waterfront and Broadway will be removed in year 2011 since new fleet will allow longer trains with higher capacity. There is minimal change in the number of blocks for B-Line 99 because the link run time has been updated based on existing year average operating speed in order to obtain time profiles for new line routes. This will have some impact on empty vehicle travel time during interlining. 18 trains are needed for Canada Line which is consistent with Phase A result. The Vancouver street car will operate on a 3-minute headway using two trains.



Table 68: Line Blocking 2011 versus 2007 – Rapid Transit Lines

Group Line Phase B 2007 Phase B 2011 AM MD PM AM MD PM

BCRTC 203 Expo 33 15 32 32 15 32 204 Millennium 23 21 23 23 21 23

201 Canada

Line n/a n/a n/a 18 18 18 Total 56 36 55 55 36 55 WCE 219 WCE 5 0 5 5 0 5 218 TrainBus 1 0 1 1 0 1

Total 6 0 6 6 0 6

1000 Vancouver Street Car 0 0 0 2 2 2

B-Line Line


97 97 12 8 12 12 8 12 99 99 31 22 33 33 21 34 98 098 21 20 25 0 0 0

Total 64 50 70 45 29 46

5.3.3.2. Number of Blocks for All CMBC Services

Table 69 summarizes the year 2011 CMBC number of blocks. All other tables in this section compare the line blocking results of all CMBC buses by transit centre. CMBC transit centres include Burnaby (BTC), North Vancouver (NVT), Richmond (RTC), Surrey (STC), Port Coquitlam (PCT) and Vancouver (VTC).

Table 69: Line Blocking 2011 versus 2007 – CMBC Transit Lines Phase B 2007 Phase 2011

CMBC AM PM AM PM B-Lines 64 70 45 46

Other Buses 862 878 904 918 Community Shuttles 100 102 114 114

Total 1,026 1,050 1,063 1,078



Table 70: Line Blocking 2011 versus 2007 – CMBC Burnaby Transit Centre

BTC Group Line

Phase B 2007 Phase B 2011 AM MD PM AM MD PM

27 27,28,26,29,210,211,212,292 40 24 37 42 24 36 43* 43 8 0 7 13 0 14 44 44 8 3 6 8 3 6

106 106 10 9 12 10 9 12 110 110, 116, 144 17 11 17 18 11 18 123 123 8 6 9 8 6 8 129 129, 112 12 9 13 13 9 14 130 130 10 6 11 10 6 11 134 136, 134 8 6 8 9 6 8 135 135, 145 29 19 21 29 19 22

Total 143 93 134 146 93 135 Notes:

* Line 33 will be added in year 2009. * Line 43 (UBC to Joyce Station) will provide high frequency service during the peak hours in year 2011.

Table 71: Line Blocking 2011 versus 2007 – CMBC North Vancouver Transit Centre

NVT Group Line


211 211,212,214,290 6 1 5 6 1 6 228 228 4 2 4 4 2 4 229 229,230 8 5 7 8 5 9 232 232,236 8 7 11 8 7 10 239 239, 246, 247 10 7 10 10 7 10 240* 240,241,242,N24 14 6 11 16 6 15 246 246 9 3 10 9 3 10 247 247 3 0 2 4 0 3

Total 55 30 55 59 30 60 Notes:

* Line 242 will be removed in 2011.

Table 72: Line Blocking 2011 versus 2007 – CMBC Port Coquitlam

PCT Group Line Phase B 2007 Phase B 2011 AM MD PM AM MD PM

143 135, 143, 145 5 4 5 5 4 6 151 151, 156 9 6 7 8 6 8 152 101, 152 9 6 10 11 6 11

154 104, 153, 154, 155, 157, 159, 169, 177 29 23 29 29 23 29

160 160, 190 10 7 9 12 7 11 179 179, 189 3 0 2 3 0 3 701 701 ,791 12 9 13 13 9 13

Total 73 51 71 76 51 74



Table 73: Line Blocking 2011 versus 2007 – CMBC, Richmond Transit Centre

RTC Group Line


401 104, 401, 410 21 16 22 45 25 44 402 402,404,407,430 18 15 21 29 24 35 403 403 4 4 8 10 6 11 405 405 5 2 4 8 6 10 480 480 10 6 10 11 9 15 490 49, 490 19 13 23 23 13 25 491* 491,496 22 0 14 0 0 0 492* 488,492 13 0 12 0 0 0

601 351,601,602,603,604, 606,

608 39 15 39 53 20 49 620 620 2 2 2 2 2 2

Total 153 73 154 181 105 192 Notes:

* Line routes 488,491,492,496 will be removed in year 2011. *Drastic changes of line route alignments as well as schedules for most of lines from RTC.

Table 74: Line Blocking 2011 versus 2007 – CMBC, Surrey Transit Centre

STC Group Line


388* 388 0 0 0 6 6 6 301 301 4 4 4 4 4 4 311* 311 8 0 7 6 0 6 312 312,314,319,329,391,640,N19 19 15 18 20 15 18

320 314,316,320,321,323,324,325,326, 332, 335,345,393, 395, 501, 509,

590 59 53 65 63 54 68

340 340 7 4 6 6 4 6 341 341,375 7 8 7 8 8 8 352* 352 6 0 5 6 0 5 374 Run C74 0 0 0 0 0 0 394 394 2 0 3 2 0 3 502 502 11 9 13 12 9 13

Total 123 93 128 132 100 137 Notes:

* Line 388 will be added in year 2011. * Line 311 and 352 will have different schedules in year 2011.



Table 75: Line Blocking 2011 versus 2007 – CMBC Trolley Bus (Van. Transit Centre) VTC

Trolley Line Phase B 2007 Phase B 2011 AM MD PM AM MD PM

3* 3 17 14 18 13 11 14 4* 4,7 22 21 28 20 25 31 5* 5,6 19 18 22 21 17 21 8 8,20 40 34 44 37 32 36 9 9 23 19 26 23 19 26

10* 10 14 11 15 15 14 18 16* 16 15 12 19 16 12 17 17* 17 21 17 24 23 18 26 19 19 12 13 14 13 12 13

Total 184 159 209 180 160 202 Notes:

* Line 3 ,4,5,6,7,10,16,17 will have different line route alignments or schedules. * Line 8 and 20 will have different line route alignments and use vehicle type 903 in year 2011.

Table 76: Line Blocking 2011 versus 2007 – CMBC Diesel Bus (Van. Transit Centre)

VTC (Diesel) Line Phase B 2007 Phase B 2011

AM MD PM AM MD PM 15 15 17 14 18 6 5 6 22 2,22 34 16 30 35 16 31 25 25 26 18 21 26 19 21 32 32 3 0 2 3 0 3

33* 33 0 0 0 13 7 13 41 41 23 17 23 24 16 20 50 50 6 6 8 5 5 6 84 84 10 8 10 10 8 10

100* 100,424 12 10 12 8 6 8 Total 131 89 123 130 82 118

Notes: * Line 33 will be added in year 2011. * Line 15 ,41,50,100 will have different line route alignments or schedules in year 2011. * Line 424 will be removed in year 2011



Table 77: Line Blocking 2011 versus 2007 – CMBC Community Shuttles Community

Shuttle Group Line Phase B 2007 Phase B 2011 AM MD PM AM MD PM

BTC 917 C17 0 0 0 2 2 2 901 C1, C2 2 3 2 2 3 2 905 C5-C7 5 4 5 5 4 5 915 C15, 214 3 2 3 3 2 3 920 C20, C22 2 2 2 2 2 2 921 C21,C23 9 6 9 19 13 19

Total 21 17 22 33 26 33 PCT 925 C24-C30 20 14 22 21 14 22 930 C35-C40 17 10 14 16 9 15 940 C41-C49 11 11 10 13 11 11

Total 48 35 46 50 34 48 RTC 984 C84, C89 0 2 1 0 2 1 986 C86-C88 3 2 3 3 2 4 990 C90,C92 2 0 1 2 0 1 993 C93 2 3 4 3 4 3 994 C95, C96 2 2 3 2 2 2

Total 9 9 12 10 10 11 STC 950 C50-C53 4 6 6 4 7 6 970 C71,C73,C74 10 4 9 10 5 9 975 C70, C75,C76 8 8 7 7 8 7

Total 22 18 22 21 20 22 Notes:

* Line C17 will be added in year 2011. * C90,C92,C93 and C96 will have different line route alignments and schedules in year 2011. * C95 will be removed in year 2011.



5.3.3.3. Number of Blocks for Non-CMBC and Ferry Services

As mentioned earlier, the third SeaBus will be put into service by 2011. The peak hour headway will be 10 min, with the off-peak headway being 15 min. Based on these two target values, revised SeaBus schedules were developed. The line blocking result is shown in Table 78 with three blocks for the peak service:

Table 78: Number of Blocks for Ferries 2011

Ferry Group Line


141 Bowen Island Ferry 1 1 1 1 1 1

217 SeaBus 2 2 2 3 2 3

The following Table 79 shows line blocking results for non-CBMC buses.

Table 79: Number of Blocks for Non-CMBC Buses 2011

Group Line Phase B 2007 Phase B 2011

AM MD PM AM MD PM

West Vancouver Blue Bus

250 250-259,C12 25 21 27 29 21 30

Bowen Island Community Shuttles

9910 C10,C11 2 2 2 2 2 2

Langley Community Shuttles

9960 C60-C64 9 7 7 9 7 7

New Westminster Community Shuttles

9903 C3,C4 3 4 3 3 4 3

Total 39 34 39 43 34 42



6. Data Management and Scenario Organization

This chapter documents how the model data and model runs are organized by the time of this report. The term “master network” stands for an approach of model data organization where several scenarios are stored in one file while multiple scenarios can be run from this same data set. Section 6.2 describes how the final model data are organized as they were compiled by PTV and delivered to TransLink by the time of this report.

6.1. Management of Scenarios and Model Runs

To use RTM for scenario analysis or to reproduce results from previous model runs, the following steps need to be performed in VISUM:

1. Select a set of line routes (These routes together represent the complete regional transit service. This selection activates all operations data needed: route scheme, timetables, train assignment)

2. Select a set of OD matrices for the four DSeg: AM, Mid, PM, Eve (The choices at this time are: 2007 and 2011 - in the future there will be more)

3. Run models (Typically line blocking, passenger assignment , PuT operations statistics)

4. Store the version file under a new name to secure your results

5. Perform evaluation (graphical display, maps, listings, reports…)

In the following the principles of using the RTM during those 5 steps will be explained in more detail.

6.1.1. The Master Network File – Scenario Selection in VISUM

The scenario typically is defined by a set of line routes and a set of OD matrices that need to be selected as inputs for the model runs. Obviously, these inputs need to have been prepared or developed first, a lengthy process that is not described at this time.

The Master Network: Scenario Definition Based on Sets of LineRoutes

The VISUM network in the RTM is setup in such a way that one line can have several ways of operating. Each way of operation is stored in several LineRoutes that belong to the same Line. It is important that the selection of a route also selects the subsequent TimeProfiles and VehicleJourneys – and thus the schedule and the train assignment – as well.

The example of the Expo line – shown in Figure 45 – can illustrate this principle: A few possible



complete operating scenarios that are available would be:

o 2006 operations, with two routes: “S0 >” and “S0 <”

o 2007, containing three routes: “S0 >”, “S0 <” and “S0-WFBW <” (in other words, the 2007 operations are almost the same as 2006 but they add a short-turn route that operates only in one direction).

o 2011 operations, with two routes: “S0-xl >” and “S0-xl <”.

o Many more scenarios, most of them consisting of between two and four routes.

Figure 45: Scenario Definition as a Sub-Set of LineRoutes

Step 1: Selection of LineRoutes

In the final report of RTM Phase-A, manual selection of line routes was proposed as the way to define scenarios in VISUM. Now, in Phase B, where the model covers the entire region, manual selection would be tedious. So it is proposed to make scenario selections with the help of LineRoute attributes. The new master network concept proposed to have variables for each major network scenario that defines if a certain line route is part of this particular scenario of not. Currently, three attributes have been defined and populated:

o Available2007 – is set to 1 for all LineRoutes that are operated in 2007 and 0 for all other LineRoutes



o Available2011 – is set to 1 for all LineRoutes that are operated in 2011 and 0 for all other LineRoutes

o CurrentScenario – this attribute will be directly used by VISUM’s model procedure and - before starting the model run - CurrentScenario should be set equal to Available2007 or to Available2011 or to any other future scenario selection.

In short, the user needs to make sure that the attribute “CurrentScenario” is set to 1 for all LineRoutes that are part of the current scenario and set to 0 for everything else.

Step 2: Selection of OD Matrices

Currently there are basically two sets of OD matrices available: one for 2007 and one for 2011. In the future, there will be additional demand scenarios being developed for the RTM and therefore more choices available. The following figure illustrates the selection of matrices in VISUM under Demand – Demand Data …

Figure 46: Selection of OD matrices for the scenario.

Once LineRoutes and OD Matrices have been selected, the model run can be started.

6.1.2. Model Run Components (VISUM Procedure Settings)

The Model Run Components under VISUM – Calculate – Procedures

Currently one model run can consist of up to 96 operations, which are grouped into 10 groups. The user can choose to run everything or a set of operations only. A typical scenario will not run the group “calibration” not “Link Speed Update”. Typically it will include:

• A passenger assignment – operations 3 – 5 (using the selected OD matrices)

• Line blocking – groups 2 – 9, operations 7 – 48

• Evaluations – operations 50 – 58



Figure 47: The Model Run Components under VISUM – Calculate – Procedures

6.1.3. Evaluations and Graphical Display

Evaluations can be performed as reports or maps.

Reports

Reports can be generated using VISUM Listings menu. There the user can compose report tables by selecting rows and columns. After the model run, the version file contains a huge amount of operations and ridership statistics for each network object. Several list layouts that have been used for this report or during model calibration have been added to the final data delivery (*.LLA files, see section 6.2).

Maps

Many model results can be displayed graphically in maps. Several maps that have been created for this report, during model calibration or for one of the presentation of the RTM. They can be easily reproduced for new scenarios by applying a previous *.GPA file. Several GPA files have been included in the final data delivery (see section 6.2).



6.2. File Organization

The final data set summarizing the major results of the RTM Phase B model development project is organized in the following folders:

• VISUM – all VISUM input files

o VER – all version files (master network files and model runs)

o PAR – procedure parameter files

o GPA – all graphic parameter files for automated maps and visualizations

o List Layouts – list layouts for standard reports

o Filter – filter files to select groups of network objects

o Scripts – all python scripts used for different model purposes

• DemandModel – files and tools that were useful to calibrate demand

o MuuliCOD – all code files for VISUM’s matrix editor (mainly district aggregation)

o TimeSeries – development of departure time distributions

o ODMatrixCalibration2007 – development of 2007 matrices

o ODMatrixDevelopment2011 – development of 2011 matrices

o OriginalEmmeMatrices – 2007&2011 emme matrices (emme and VISUM formats)

• Evaluations – post-processing tools that had been useful, mainly for validation purpose

o Assignment Validation – Spreadsheets, all validations 2007&2011 from this report

o LineBlocking Validation – Spreadsheets with validation 2007&2011

o CostRevenue Validation – Spreadsheets with validation 2007

o Animations – Time-dynamic animations created from serial screenshots

• Reports&Presentations

o Report – DOC and PDF files of the final report

o PPT – presentations

• ScheduleImport – tools for the import of CMBC service schedule



7. Conclusions and Future Directions

The Regional Transit Model (RTM) has become a key resource within the TransLink organization for operations analysis – at a time when many projects are started and the demand for service and operations analysis is great.

One major achievement in the transition from Phase A to Phase B is certainly the inclusion of all bus services and the automated interface to CMBC’s data systems (schedule, stop database, APC). As a result the RTM has become a truly regional tool and can be used to analyze all transit not just the rapid transit. Also intermodal trips and transfers can now be estimated. Another interface that has been improved is the one to the regional travel forecasting model in emme/2, which can now supply trip tables to the RTM; both models are compatible because they are based on the same zone system.

The RTM has already contributed to several studies, sometimes still using the Phase-A version, more often now by applying the Phase-B version. These studies include:

• Operating scenarios for SkyTrain, based on the 2006 fleet (2006)

• Maximum capacity for the future SkyTrain (2008)

• Operations analysis for the Evergreen Line as ALRT (2008)

• Fleet strategy SkyTrain – When and if to add 3-car units to the fleet? (2008)

• Rapid transit scenario analysis for the UBC Line - operating analysis (2008)

• Canada Line bus network adjustment – operating analysis (2008, ongoing).

Several members of TransLink’s staff have been trained in the use of VISUM and the RTM data model. TransLink has taken ownership of the model, while PTV still assists as consultant with model update and model application.

Future directions of the model will include:

• an extension to include additional planning years (2014, 2021),

• continued application in rapid transit studies such as the UBC Line project, and

• the application of the RTM in area transit plans.



Appendices

List of Abbreviations and Symbols

AH Analysis Horizon in VISUM (a year in the RTM)

AP Analysis Period in VISUM (a single average weekday in the RTM)

APC Automated Passenger Count System

APTA American Public Transportation Association

AVL Automated Vehicle Location System

B Bus - as transport system in the RTM

BCRTC BC Rapid Transit Company

BRT Bus Rapid Transit

CBD Central Business District

CMBC Coast Mountain Bus Company

CUTA Canadian Urban Transit Association

DSeg Demand Segment

F Ferry - as transport system in the RTM

LRT Light Rail Transit

NTD National Transit Database

PnR Park and Ride

POI Point of Interest (geography object in VISUM)

PrT Private Transportation

PuT Public Transportation

R Rail - as transport system in the RTM

RTM Regional Transit Model

SCBCTA South Coast British Columbia Transportation Authority

TB Trolley Bus - as transport system in the RTM

TP Time Profile

TSys Transport System

V/C Volume/capacity ratio

Veh Vehicle

WCE West Coast Express



Appendix A: Automated Schedule Data Import from CMBC to VISUM

This appendix documents the automated import of CMBC’s service schedule data to VISUM. First the import is explained step by step. Then the internal mechanics of the MS Access import routine are documented.

A.1 Preparations in VISUM before a Schedule Import or a Schedule Update

Before the actual schedule import, it is necessary to check if any new bus stops are used by the schedule and to add these stops into the VISUM network.

To find out which stops are new, a stop SHP file can be obtained from CMBC to perform a graphical comparison in VISUM or ArcGIS. Another method is to compare the stop table from the schedule data base (likely file name: “ts_stop.csv”) with a stop point listing form VISUM.

Note that schedule data for SkyTrain, WCE and SeaBus are part of CMBC’s schedule data, but for VISUM they are derived from different sources. Thus the stop point numbering is different from the CMBC schedule data.

Create a stop point attribute such as “08NewData” (for 2008 schedule update) and assign value 1 to all new stop points. Add the VISUM header information, then copy and paste the list into a VISUM stop point listing. A GPA called NewStopPoints2008.gpa has been created to show where these stops are located. Reading a shape file of the new bus routes into VISUM as a POI of category “BusRoute” will help identify on which side of the street the stop point should be located. In VISUM, it is possible to automatically attach a node to a link and convert the node to the stop point. However in the case of a schedule update, it is recommended to add and merge the new stops manually into the network. The efforts needed for checking and repairing the results from the automated merge would be at least the same as adding stop points manually.

For most new stop points, the next step will be to assign the new stop points to a nearby existing stop area. In the RTM, walking is not allowed on the links, and transfers are permitted within the stop between stop areas. While assigning the new stop points to stop areas it is important to make sure that all desired transfer opportunities are created.



A.2 Step by Step Import Process

The import of CMBC service schedule databases to VISUM is implemented in Microsoft Access.

There are four csv tables that CMBC staff will provide for a schedule update. All schedule data need to be cleaned and all [NULL]s need to be replaced by a single space. The importer will look for files with exactly the following names (rename the files if necessary):

• ts_stop • ts_patternstop • ts_schedule • ts_trip

The import goes in several steps as follows:

1. Make a copy of “schedule importer.mdb” with a new name, for example “Spring2008.mdb”

(otherwise you will lose the original file during the process).

2. Open four tables using text editor and replace all Null values with a single SPACE character.



3. Open the new database file with MS Access 2003 or 2007. Note that these two versions have

different interfaces.

4. Specify where the schedule data files are that you want to import

Using “Linked Table Manager” in MS Access:

office 2007:

office 2003:

With “Linked Table Manager”, each of the four tables has to be updated separately.

Select a table and check “Always prompt for new location”:

In the open file dialog, select new location for the linked table:

Repeat these steps for each table separately!



5. Launch the translation into VISUM format

This step is highly automated with a macro in MS Access. The macro will perform several queries, joins and other database operations.

office 2007:

office 2003:

Run the macro with a double click (you may have to enable this Macro in Access first). When the VISUM tables are created, a confirmation message box will pop up. It is recommended that the macro file be run step by step so that each intermediate output can be reviewed and it can be made sure that each step starts with complete input.

After step 5, the MS Access data base will contain all schedule data in VISUM’s table format ready to be read into VISUM.

6. Open the resulting database in VISUM

In a first try you can read everything into an empty VISUM network.

The final run will consist of reading the new schedule database additionally into the RTM network.

In VISUM’s main menu go to File > Import > Database and open the new database created in steps 1 through 5.

VISUM asks you to select which database tables to import :



You can load the parameter file “schedule import access updated July08.anrp” in order to select correct tables in the following dialog box.

For an update you need the following tables:

• Direction • Line • LineRoute • LineRouteItem • TimeProfile • TimeProfileItem • VehJourney • VehJourneySection

Note that the conflict handling for LineRouteItem and TimeProfileItem needs to be set as "overwrite course" .This is important in the case of a schedule update, when the VISUM network already has most of the line routes and time profiles and we want only the new or changed pieces to be created in VISUM. Only when "overwrite course" is selected, VISUM will be able to read LineRouteItems properly from the database without showing any error message.

For error checking purpose, the user can also choose to bring in the data piece by piece. The rule of thumb is that the LineRoute table, LineRouteItem table, TimeProfile table and TimeProfileItem table must be brought in at the same time for maintaining internal data consistency. For the same reason, the vehicle journey table and the vehicle journey section table must be brought in at the same time.



VISUM will now try to fit transit routes into the links and stops of the network. The routing options have to be set as shown in the figure below.

These options have to be set for all transport systems so click “Apply to all transport systems”.

VISUM will give error messages for all routes that cannot fit into the network. CMBC’s lines 996 through 999 (representing SkyTrain, WCE and SeaBus) will create such error messages and will not be accepted by VISUM, because the RTM has different stop IDs than CMBC.

Under “Read Network (Completing Lineroute / SystemRoute) dialog box, make sure to check “the course of existing line routes is to be used first”, this will guarantee that most of the line routes that are already in the network will have the same line course, so that line route alignment checking only needs to be done for those newly added line routes.

During Vehicle journey section import, an error message may show up

complaining about missing vehicle combinations because of the incomplete information provided by the schedule data. In this case, write down all the missing combinations and add them to VISUM manually. When this step is done, read in vehicle journeys and vehicle journey sections again.

A.3 Suggested Quality Control and Data Completion after Import

Stop Point Checking

After an import, the location of all new stop points should be verified, to find out if they are on the correct street side or if they cause for another reason the wrong line route alignment. Here are a few ways to identify such problems:



• Run average link speed computation in the model procedure. All links with extremely high speed indicate line route alignment problems because the same line route segment was traversed more than once. This step can’t however catch line routes with wrong alignment.

• Visually check the alignment of the line routes, especially of all new routes or of those using new stops.

Schedule Data Checking

The following checks should be performed for all line routes other than SkyTrain, WCE and Ferry.

• Compare LineRoute length (in a LineRoute listing) between the old and the new version file. Compute the length difference in Excel. If there is a difference, it indicates that the line route alignment has been changed and the line route alignment needs to be verified.

• When the import is done, delete all line routes with the Minimum of the number of TimeProfileItems is equal to zero. Any route that meets this criterion does not exist anymore in the new schedule.

• After the import of the TimeProfileItems, set up a filter and delete those TimeProfiles with Count:Vehjourney=0. This means that they are not used by any vehicle journey in the new schedule.

Data Completion

• Copy all line attributes such as OperatorNo, Mainline, BlockingGroup from the old version file. These attributes for new lines do not contain any data and need to be filled with the correct information.

• Reset Vehicle Journey item attribute "Bonus" for all line routes for assignment purpose. Refer to the report for values used for different transit systems.

• Re-Create the TimeProfileItem attribute “avg_op_speed” and rerun the calculation procedure to obtain the average operating speed.

• Line Blocking preparation:

o Values need to be assigned to line UDA "LineGroup" and "BlockID" for new lines.

o The lookup table which contains "LineGroup" and "BlockID" in the line blocking Excel file needs to be updated accordingly.



A.4 Internal Organization of the Importer

To import the CMBC service schedule into VISUM all provided tables have to be reformatted and reorganized. A database platform like MS Access is the ideal tool for such an undertaking. CMBC’s service schedule is provided in three tables.

• The table ts_patternstops contains all information about the stop sequence, the name and number of the route, the line it belongs to and the direction. This file is the major data for the lineroute tables in VISUM.

• The table ts_trip provides additional information for each trip, but this table was not used to import the schedule into VISUM. It will be used later on to add the vehicle combination for every bus trip.

• The last table, ts_schedule includes all trips in Metro Vancouver. This table plays an important role in the import routine, because it provides the time information.

To acquire the LINEROUTE table for VISUM all pattern numbers with its direction and name have to be listed. This is done by a query, which lists all records where the stop sequence entry is equal to one. This table has to be formatted for the input in VISUM, then

To construct the LINE table, a copy of the LINEROUTE table is created. This table is then sorted by the line column. With a short macro, written in VBA, every record, which has the same entry for the line column as his predecessor, is deleted. Removing the unnecessary information and adding the TSYSCODE finishes the work on this VISUM table.

For the LINEROUTEITEM table the provided ts_patternstop table has to be modified. Spare information again has to be removed and the direction name has to be replaced by the direction code. This again is done by a simple query in Access. Then VISUM’s Directioncode table is also added.



The most complex part of the import process is the creation of the TIMEPROFILE and TIMEPROFILEITEMS. The creation process of these tables is divided into different parts. First a temporary helping table is created. This table links the tripID to several things, like the departure at the first and last stop, the number of stoppoints served on the trip, the name of the pattern to which the trip belongs and the TimeProfileName attribute. This attribute needs to be populated, which is done using the trip duration in seconds. The duration is computed by the difference between the departure at the first and the last stop.

This table again has to be “cleaned” the same way it was done with the LINE table described earlier. The only difference is that the macro decides depending on the TimeProfileName. The result of this cleaning procedure is a table which holds a trip example for every timeprofile. With this table and a query it is easy to combine the TIMEPROFILE and TIMEPROFILEITEM table for VISUM.



In a very similar way the VEHJOUNREY and the VEHJOURNEYSECTION tables are created.

At the end of the reformatting process all tables have to get the correct column names and the correct time format. This is again achieved by a short macro.

It is important that the queries and the VBA scripts are run in the correct order, because of inter-dependencies.

One master macro called “run” will perform all queries and all the individual VBA macros in the right order. For a new schedule import, the user only has to replace the raw data and launch the “run” macro as described in A.1.



Appendix B: User Defined Attributes in the RTM

Table 80: User Defined Attributes for the Various VISUM Object Classes

Object Class Attribute ID Data Type Definition

LINK NETLEVEL Int Street Category from NAVTEQ LINK SPEED_CATEGORY Int Street Type from NAVTEQ LINK SLOW_ROAD Int Street Attribute from NAVTEQ LINK URBAN_ROAD Int Street Attribute from NAVTEQ LINK BRUNNEL Int Street Attribute from NAVTEQ LINK WALKWAY Int Street Attribute from NAVTEQ LINK PEDESTRIAN_ZONE Int Street Attribute from NAVTEQ LINK RAMP Int Street Attribute from NAVTEQ LINK ROUNDABOUT Int Street Attribute from NAVTEQ LINK LinksToKeep Int Links to keep during network clean-up(1/0) LINK AVG_OP_SPEED Double Weighted Average Transit Operating Speed LINK TYPE Text Type of rail track: elevated, tunnel or at-grade LINK AM_COUNT2 Int AM SkyTrain volume target for TFlowFuzzy LINK MD_COUNT2 Int MD SkyTrain volume target for TFlowFuzzy LINK PM_COUNT2 Int PM SkyTrain volume target for TFlowFuzzy LINK EV_COUNT2 Int EV SkyTrain volume target for TFlowFuzzy LINK Canada_SegName Text Canada Line segm. name to compute max load LINEROUTE Available2007 Int Line Route operates in 2007 (1 = yes, 0= no) LINEROUTE Available2011 Int Line Route operates in 2011 (1 = yes, 0= no) LINEROUTE CurrentScenario Int Is the line route part of the current selection (1/0) LINEROUTEITEM AM_ON_2007 Int APC AM number of boardings in 2007 LINEROUTEITEM MD_ON_2007 Int APC MD number of boardings in 2007 LINEROUTEITEM PM_ON_2007 Int APC PM number of boardings in 2007 LINEROUTEITEM EV_ON_2007 Int APC EV number of boardings in 2007 LINEROUTEITEM AM_LEAVE_2007 Int APC AM leave load in 2007 LINEROUTEITEM MD_LEAVE_2007 Int APC AM leave load in 2007 LINEROUTEITEM PM_LEAVE_2007 Int APC AM leave load in 2007 LINEROUTEITEM EV_LEAVE_2007 Int APC AM leave load in 2007 LINEROUTEITEM Daily_ON_2007 Int APC Daily number of boardings in 2007 LINEROUTEITEM Daily_LEAVE_2007 Int APC Daily leave load in 2007 TIMEPROFILEITEM AVG_OP_SPEED Double Transit Operating Speed at Time Profile Level VEHCOMB ACCESSIBLE Bool Wheel chair accessible VEHCOMB RACK Bool Bike Rack available on bus vehicle



Table 81: User Defined Attributes for the Various VISUM Object Classes (continued)

Object Class Attribute ID Data Type Definition

STOPPOINT BSMS_ACCURACY Text Quality of the coordinates in CMBC data STOPPOINT FLAGSTOP Bool Stop is flag stop STOPPOINT Year08 Int StopPoint added in Winter 07/08 schedule update STOPPOINT MINDWELLAM Int Min dwell AM (SkyTrain) STOPPOINT MINDWELLPM Int Min dwell time PM (SkyTrain) STOPPOINT MINDWELLMID Int Min dwell time Mid (SkyTrain) STOPPOINT ONTIMEDWELLAM Int On time dwell AM (SkyTrain) STOPPOINT ONTIMEDWELLPM Int On time dwell PM (SkyTrain) STOPPOINT ONTIMEDWELLMID Int On time dwell Mid (SkyTrain) STOPPOINT MAXDWELLAM Int Max dwell AM (SkyTrain) STOPPOINT MAXDWELLPM Int Max dwell PM (SkyTrain) STOPPOINT MAXDWELLMID Int Max dwell Mid (SkyTrain) STOPPOINT NOMDWELLAM Int Nom dwell AM (SkyTrain) STOPPOINT NOMDWELLPM Int Nom dwell PM (SkyTrain) STOPPOINT NOMDWELLMID Int Nom dwell Mid (SkyTrain) STOPAREA STATIONTYPE Text Station Type (SkyTrain) STOPAREA PLATFORMTYPE Text Platform Type (SkyTrain) STOPAREA PLATFORMWIDTH Double Platform Width (SkyTrain) STOPAREA ELEVATORS Int Elevators (SkyTrain) STOPAREA ESCALATORS Int Escalators (SkyTrain) STOPAREA TIMEPOINT Bool Time point for at least one bus line STOPAREA TIMEPOINTCODE Text CMBC 4-letter code for time points STOPAREA AM_ON_2003 Int Ridership count 2003 STOPAREA MID_ON_2003 Int Ridership count 2003 STOPAREA PM_ON_2003 Int Ridership count 2003 STOPAREA EVE_ON_2003 Int Ridership count 2003 STOPAREA AM_OFF_2003 Int Ridership count 2003 STOPAREA MID_OFF_2003 Int Ridership count 2003 STOPAREA PM_OFF_2003 Int Ridership count 2003 STOPAREA EVE_OFF_2003 Int Ridership count 2003 STOPAREA AM_ON_2005 Int Ridership count 2005 STOPAREA MID_ON_2005 Int Ridership count 2005 STOPAREA PM_ON_2005 Int Ridership count 2005 STOPAREA EVE_ON_2005 Int Ridership count 2005 STOPAREA AM_OFF_2005 Int Ridership count 2005 STOPAREA MID_OFF_2005 Int Ridership count 2005 STOPAREA PM_OFF_2005 Int Ridership count 2005 STOPAREA EVE_OFF_2005 Int Ridership count 2005 STOPAREA ON_COUNT_2007_24H Int Ridership estimate 2007 – ADT STOPAREA OFF_COUNT_2007_24H Int Ridership estimate 2007 – ADT STOPAREA ON_COUNT_2006_24H Int Ridership count 2006 – ADT STOPAREA OFF_COUNT_2006_24H Int Ridership count 2006 – ADT STOPAREA ON_COUNT_2005_24H Int Ridership count 2005 – ADT STOPAREA OFF_COUNT_2005_24H Int Ridership count 2005 – ADT STOPAREA ON_COUNT_2003_24H Int Ridership count 2003 – ADT STOPAREA OFF_COUNT_2003_24H Int Ridership count 2003 – ADT

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