trimet cad / avl system data
DESCRIPTION
Dave Crout and Steve Callas, TriMet TriMet has used a computer aided dispatch (CAD)/automatic vehicle location (AVL) system to manage bus and rail operations since the late 1990s. TriMet is currently in the process of updating the CAD/AVL system, and anticipates improvements in bus tracking and performance monitoring. This presentation will show how TriMet uses data from the system to support intelligent transportation systems (ITS) such as TransitTracker and automatic stop announcements in buses and trains, as well as to analyze transit operations such as on time performance and passenger loads.TRANSCRIPT
1
TriMet CAD/AVL Data for Operations
Steve Callas, TriMet Dave Crout, TriMet
Portland State University
Center for Transportation Studies Fall 2012 Transportation Seminar Series
November 2, 2012
2
CAD/AVL Primary Functions • Improved Dispatch Capabilities
• Real Time Vehicle Location – Headway Management • Digital Voice/Data Communications
• Enhanced Security • Provide Real Time Information to Other Systems
• Transit Tracker • Automatic Stop Announcements • Signal Priority
• Collects Operating Data
3
New CAD/AVL Features
Screenshots
4
5
6
7
8
9
10
11
CAD/AVL Data
Real Time • 30 second polling data • Packet data
Vehicle Log • Stop data • 5 second bread crumb
12
400,000 Daily Stop Records (Vehicle Log) • Route Number • Direction • Trip Number • Service Date • Vehicle Number • Operator ID • Bus Stop Location • Actual Arrive Time • Actual Leave Time
• Scheduled Time • Ons & Offs (APCs) • Passenger Load • Door Opened • Door Opened Time • Lift Usage • Speed • Longitude • Latitude
13
14
15
16
Capacity and Passenger Load Analysis
17
Length Passenger Capacity Load Vehicle Type (feet) Seated Design Achie
vable Factor
Small Bus 30 28 35 28 100%
Bus – High Floor Bus – Low Floor
40 40
43 39
64 64
51 51
119% 131%
Light Rail Vehicle 88 64 166 133 208%
Achievable Capacity – 80 Percent of Design Capacity
18
Overloads
Underloads
19
20
21
22
Schedule Reliability and Running Time Data
23
Actual Running Time Data
Line 4 St. Johns to Gresham Run Times (PM Peak)
24
25
Other Operational Analyses
26
27
• Increase person trips through selected traffic corridors while minimizing impacts on minor movements.
• Reduce transit running times. • Improve transit schedule reliability:
• Reduce running time variability. • Reduce excess time built into schedule to offset variability.
• Defer providing additional transit capacity.
TriMet’s Transit Signal Priority (TSP)
28
• Automatic Vehicle Location System tracks bus location and schedule status.
• If conditions are met, bus emitter (Opticom) communicates priority request to signal.
• Signal controller then grants priority request.
TSP Process
29
TSP and Relationship to CAD/AVL Data
• Real time location and schedule deviation
• Vehicle Log Data for Analysis
30 30
Scheduled Run Time 84 Minutes
(30th Percentile)
Existing Recovery 20 (104) Minutes (99th percentile)
31 31
Scheduled Run Time 84 Minutes
(30th Percentile)
Existing Recovery 20 (104) Minutes (99th percentile)
New Run Time 83 Minutes
(40th Percentile)
New Recovery 10 (93) Minutes (95th Percentile)
32
Drive Train – Maintenance Data Throttle Position
Fuel Mileage Coolant Temperature
ABS (Anti-lock Brake System) activation Oil Pressure
Transmission Fluid Level Turbo Boost Pressure
Engine RPM Vehicle Speed
33
• Figliozzi, et al. A Study of Headway Maintenance for Bus Routes: Causes and Effects of "Bus Bunching" in Extensive and Congested Service Areas, OTREC-RR-12-09. July 2012.
• Li, Bertini. Assessing a Model for Optimal Bus Stop Spacing with High-Resolution Archived Stop-Level Data. May 2009.
• Strathman, et al. Headway Deviation Effects on Bus Passenger Loads: Analysis of TriMet’s Archived AVL-APC Data. January 2003.
• Strathman, et al. Analysis of Bus Collision and Non-Collision Inicents using Transit ITS and other Archived Operations Data. November 2010
Selected PSU-Sponsored Studies Using TriMet CAD/AVL Data