shrp2 c10a
DESCRIPTION
SHRP2 C10A . Sensitivity Testing of an Integrated Regional Travel Demand and Traffic Microsimulation Model. TRB Planning Applications Conference May 8 - 12, 2011 Reno, NV Joe Castiglione, Brian Grady & Stephen Lawe Resource Systems Group John Bowman Bowman Research and Consulting - PowerPoint PPT PresentationTRANSCRIPT
SHRP2 C10A
Sensitivity Testing of an Integrated Regional Travel Demand and Traffic Microsimulation Model
TRB PlanningApplications ConferenceMay 8 - 12, 2011Reno, NV
Joe Castiglione, Brian Grady & Stephen LaweResource Systems Group
John BowmanBowman Research and Consulting
Mark BradleyMark Bradley Research & Consulting
David Roden & Krishna PatnamAECOM
2
Overview
C10A project DaySim-TRANSIMS-MOVES model system Initial Sensitivity tests
Pricing (freeway tolling, auto operating costs) Travel demand management Operational improvements
3
C10A Project Objectives
Address limited sensitivity of models to dynamic interplay between network conditions and behavior
Temporal detail (reflect variations in supply and demand) Behavioral detail (VOTs, reliability) Spatial detail (small scale improvements)
Exploit advances in activity-based demand modeling and DTA
Capacity expansion Variable road pricing / tolling Operational improvements Travel demand management Travel time reliability Time-of-day shifting
4
Jacksonville, FL
4-counties 3,100 sq.miles 525,000
households 5 million daily
trips
C10A: Two Distinct Project Geographies
Burlington, VT test-bed
1-county 620 sq.miles 55,000 households 525,000 daily trips
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C10A Integrated Model System
Develop a integrated model in Jacksonville, FL and Burlington, VT
DaySim: Provides detailed estimates of travel demand TRANSIMS: Provides detailed estimates of network
performance MOVES: Provides estimates of air quality
Impedance Skims
Demand FileTRANSIMS STUDIO
Iteration/ConvergenceFile Manager
DaySim Exogenous Trips
TRANSIMS
MOVESMOEs / Indicators
6
DaySim TRANSIMS Integration
DaySim Spatial resolution of parcels Temporal resolution of half-
hours, disaggregated to minutes
TRANSIMS Spatial resolution of activity
locations Temporal resolution of
minutes and seconds DaySim provides an
activity list (trips are linked as tours) to TRANSIMS at the level of minutes and activity locations
7
TRANSIMS DaySim: Temporal Resolution
Current skim resolution: 22 time periods, TAZ-level Future skim resolution: 48 time periods, “activity-level”
resolution Microsimulated network and TRANSIMS tools easily and
flexibly support skim development
1 overnight skim 9 hourly midday & shoulder skims 12 30-min peak period skims
EV PM EVAM MD
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% o
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Convergence
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Convergence is necessary to:
ensure the behavioral integrity of the model system
ensure that the model system will be useful as an analysis tool
FHWA-funded Sacramento DaySim-TRANSIMS project is investigating convergence measures and methods
Preliminary results have informed this effort
Use of disaggregate “trip gap”
Identifying sufficient numbers of assignment and system iterations
Network temporal resolution
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Initial Sensitivity Testing Scenarios
Initial tests performed using the Burlington testbed
Smaller region allows for more rapid testing and debugging
Burlington demand increased to reflect more congestion
Pricing Freeway tolling by time-of-day Auto operating costs
Travel Demand Management Flexible work schedule
Operation Improvements Signal progression
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Freeway Tolling
Costs may be imposed on travelers using certain roads traversing certain screenlines travelling to certain areas
Costs may be either fixed, or vary by time-of-day or in response to congestion
3 freeway tolling by time-of-day scenarios tested
ScenarioFreeway Tolls (7am-10am)
Freeway Tolls (10am-3pm)
Freeway Tolls (3pm-6pm)
Base none none nonePricing_3 $0.25 / mile none $0.25 / milePricing_4 $0.25 / mile $0.10 / mile $0.25 / milePricing_5 $1.00 / mile $0.50 / mile $1.00 / mile
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Freeway Tolling: Demand Impacts
Trips shift out of peaks and midday and into evening and early AM
Higher tolls increases the magnitude of this shift
Time shifting varies by purpose
Work trips shift into early AM and out of AM peak
Social/recreation trips shift significantly out of peaks and primarily into the evening
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Work & Soc/Rec Trips by Time of DayBASE-WORK
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Difference in Trips by Time of Day
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Freeway Tolling: Supply Impacts
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Major Arterial VHT
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Minor Arterial VHT
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Freeway VHT significantly affected by time varying toll scenarios
VHT on minor arterials impacted significantly more than major arterials
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Freeway Tolling: Supply Impacts
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Total Delay (hours)
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Total Delay (hours) - Major Arterials
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Total Delay (hours) - Minor Arterials
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Increased delay on non-freeway facilities leads to higher overall system delay
No sustained congestion in Burlington, even with increases in assumed pop / emp
No optimization of tolls to address peak congestion
14
Auto Operating Costs
Auto Operating Costs Costs associated with operating the vehicle (gas,
maintenance) Assessed on a per mile basis
In DaySim, long-term and short-term models affected by changes in costs
Long-term: Auto ownership, usual work and school location
Short-term: Day pattern, tour/stop destination, mode choice
Scenarios tested Base ($0.12/mile) 0.5x ($0.06/mile) 2x ($0.24/mile) 5x ($0.60/mile)
15
Auto Operating Costs: Demand Impacts
BASE AOC_X05 AOC_X2 AOC_X50 5.5% 5.3% 5.7% 6.5%1 36.7% 36.8% 36.7% 36.3%2 39.5% 39.6% 39.5% 39.3%3 13.1% 13.1% 13.0% 12.9%4+ 5.2% 5.2% 5.2% 5.0%
BASE AOC_X05 AOC_X2 AOC_X5 AOC_X05 AOC_X2 AOC_X5Work 116,928 117,475 115,898 114,321 1.00 0.99 0.99School 44,011 44,246 43,449 41,906 1.01 0.98 0.96Escort 41,982 42,022 41,610 41,028 1.00 0.99 0.99PersBus 45,877 45,756 45,549 45,635 1.00 1.00 1.00Shop 38,841 39,432 38,210 37,525 1.02 0.97 0.98Meal 15,908 16,001 16,021 15,794 1.01 1.00 0.99SocRec 47,181 47,436 46,999 47,076 1.01 0.99 1.00Total 350,728 352,368 347,736 343,285 1.00 0.99 0.99
Auto ownership decreases with higher costs
Overall tour-making decreases slightly with higher costs
16
Auto Operating Costs: Demand & Supply Impacts
Trip lengths decrease slightly with higher costs
VMT, VHT and Delay also decline with higher costs
But time-of-day is largely unaffected 0.0%
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Trip Length Frequency Distribution
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VMT VHT VHD
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Difference in Trips by Time of Day
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Auto Operating Costs: Change in Per Capita VMT
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Travel Demand Management
Strategies to change travel behavior in order to reduce congestion and improve mobility
Work-at-home Flexible work schedules (off-peak) Shared ride
Advanced integrated model system captures interaction between demand and supply models
Scenario-based approaches necessary Model system captures the effects of TDM policy
outcomes Cannot identify which policies will affect flexible work
schedules But can estimate the impact on transportation system
performance of shift from a 5-day 8-hour work week to a 4-day 9+ hour work week
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Travel Demand Management
“Flexible Schedule” scenario Asserted assumptions about:
Fewer individual work activities Longer individual work durations Aggregate work durations
constant Target: Fulltime Workers
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% o
f Tou
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Work Tour Duration Distribution
Original
Adjusted
Tours by Purpose (Fulltime Workers)Original Adjusted Adj/Orig
Work 94,408 78,472 0.83School 115 140 1.22Escort 8,070 9,023 1.12Pers Bus 13,519 16,848 1.25Shop 10,531 12,938 1.23Meal 3,817 3,842 1.01Soc/Rec 13,076 14,360 1.10Workbased 27,949 23,211 0.83Total 171,485 158,834 0.93
20
Travel Demand Management: Demand Impacts
~4% Reduction in overall trips
Reduced peak period and midday travel
More early AM travel and evening travel
Fewer, and earlier, work trips
More nonwork trips in morning and evening with fewer in midday
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Difference in Trips by Time of Day
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Travel Demand Management: Supply Impacts
Total VMT declines slightly Reduced peak period and midday
VMT, increased VMT in evening Reduced peak period and midday
delay across all facility types, additional delay in the evening
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VMT by 30 Minute Period
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Hours of Delay - Major Arterials
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Hours of Delay - Minor Arterials
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Hours of Delay - Collectors
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Operational Improvements
Cost-effective strategies to address congestion and mobility challenges
Travel demand forecasting models typically cannot represent TSM improvements or impacts
Bottleneck improvements: intersection controls, signal timing and phasing, ramp metering
Corridor improvements: Coordinated signal systems, speed harmonization
Parking: Supply, pricing, subsidies
Signal progression implemented in 3 corridors
Route 7 Main Street Colchester Ave
Signal progression corridors in downtown Burlington, VT
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Operational Improvements: Demand Impacts
Signal progression on a limited number of corridors has little impact on regional tripmaking by time-of-day
Marginal differences in AM peak nonwork trips
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Difference in Trips by Time of Day
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Operational Improvements: Supply Impacts
Total VMT unaffected by local signal progression improvements
AM peak delay reduced across all facility types
PM delay largely unaffected, though changes are observable by facility type
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Operational Improvements: Supply Impacts
Improvements (or lack of) in speed can be observed at the level of individual link directions and corridors
Results are from fully linked model system with no additional post-processing
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Route 7 Speeds (out)
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Route 7 Speeds (in)
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Main Street Speeds (in)
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0:00
1:00
2:00
3:00
4:00
5:00
6:00
7:00
8:00
9:00
10:0
011
:00
12:0
013
:00
14:0
015
:00
16:0
017
:00
18:0
019
:00
20:0
021
:00
22:0
023
:00
Colchester Ave Speeds (out)
BASE
PROGRESSED
26
Lessons Learned
Convergence is key Runtimes are still a challenge Consistency between demand and supply
assumptions is essential Evaluating operational improvements requires
significant care
27
Next Steps
Incorporate enhanced DaySim Incorporate TRANSIMS v5 Address new sensitivities (reliability) Improve model runtimes Policy testing in Jacksonville