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Atlanta Travel Forecasting Methods: Traditional Trip-Based & Activity-Based Model AMPO Travel Modeling Work Group, Nov. 4, 2010 Guy Rousseau, Modeling Manager, Atlanta Regional Commission ARC Model Applications: Using Radar Graphs to Visualize Performance Measures Scenario 1 Scenario 1a Demand Accessibility Demand Mode Share Accessibility Congestion Mode Share Congestion Scenario 2 Scenario 2b Demand Demand Accessibility Mode Share Congestion Accessibility Mode Share Congestion ARC Activity-Based Modeling System Based on the CT-RAMP1 family of ABMs developed in New York, NY, Columbus OH (MORPC) and others - Explicit intra-household interactions • - Continuous temporal dimension (Hourly time periods) - Integration of location, time-of-day, and mode choice models - Java-based package for AB model implementation • Implemented with the existing Cube-based networks, GUI and ancillary models (external model, truck model, assignments, etc) • Households: 1.7 million in 2005, 2.7 million in 2030 • Model development parallel effort with MTC 1Coordinated Travel-Regional Activity-Based Modeling Platform The ARC CT-RAMP Cluster 4 8-processor dual-core Dell servers with 32 GB RAM each ARC Activtiy-Based Model Hardware and Software Setup • Three Windows Server 2003 64bit Machines: • Two Dual Quad Core Intel Xeon X570 2.93 GHz Processors 16 threads • 32 GB of RAM • Cube Voyager + 8 seat Cube Cluster license • Total cost ~ $30,000 in 2009 ARC Activity-Based Model Hardware and Software Setup • • • • • 64 bit OS for large memory addresses 64 bit Java for CT-RAMP 32 bit Java to integrate with Cube’s native matrix I/O DLL Cube Base for the GUI Cube Voyager + Cluster for running the model, assignment, etc • Java CT-RAMP software • 64 bit R for reporting/visualization ARC’s Activity-Based Model • Provides results similar to 4-step trip based model • Ok, so then why bother with an ABM? • Because ARC’s ABM provides additional details, more info about travel patterns & market segments • ABM allows to answer questions the 4step model is not capable to provide • For internal use only, not for official purposes, hence dual/parallel track of models Synthesized Population: Person Age Share Age 80+ 2030 Age 65-79 2005 Age 50-64 Age 35-49 Age 25-34 Age 18-24 Age 16-17 Age 12-15 Age 6-11 Age 0-5 0% 5% 10% 15% Share 20% 25% 30% Trip-Based Model Mode Share Compared to ABM Mode Share 90% 80% 70% 60% 50% HBW HBO 40% NHB 30% 20% 10% 0% WLKL WLKP DRVL DRVP SOV Trip-Based Model HOV WLKL WLKP DRVL DRVP Activity-Based Model SOV HOV Line Boardings: Trip Based Model Versus ABM AM SOV Free: Trip Length Frequency Distributions 450000 400000 350000 TBM 300000 Frequency ABM 250000 200000 150000 100000 50000 0 1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 Distance 31 33 35 37 39 41 43 45 47 49 51 VMT by Time Period 80,000,000 70,000,000 60,000,000 VMT 50,000,000 Trip Concept3 40,000,000 ABM Concept 3 30,000,000 20,000,000 10,000,000 0 AM MD PM NT ARC’s ABM Year 2005 Volume/Count Scatterplot Line Boardings (Routes > 10,000 Boards) Station Boardings By Number of Boards External Model Results Passenger Work Non-Work Passenger Cars Truck Trucks Trucks Trucks TBM ABM 2030HOV2HOT 2030HOV2HOT ODRelation Trips Trips IE 390,787 388,150 IE 510,557 507,103 EE 80,219 80,563 II IE EE 2,518,171 234,545 25,573 2,518,837 233,478 40,793 What Sort of Performance Measures & Visuals are Possible with an Activity-Based Model? ABM results in a complete activity diary for all ARC residents •A wealth of activity/travel results •Just about any custom report/query/visual is now possible •Performance Measures also available by Age, Gender & Household Types Mean Delay, Peak Period Travel Travelers By Age Persons Not At Home By TAZ and Hour Persons By TAZ and Hour Conclusions • Overall, the ARC ABM model appears to be displaying appropriate sensitivities when compared to the base year results and the existing trip based model runs. • Compared with the trip based model run, the ABM required increased prices in the peak periods in order to provide 1600 vphpl performance given the significant amount of toll eligible demand that could use the facilities • VMT results by time-of-day suggest that the addition of a trip time-of-day departure choice model would help reduce the over predicted night period demand Potential Improvements • The population synthesizer works at the household level. Adding more explicit functionality for person level information and controls would be useful. • The ABM does not have a model to calculate the departure hour for each trip within the tour time window. Adding a model, or simply a distribution of probabilities by tour purpose and hour, would be an improvement Questions / Comments Guy Rousseau (404 463-3274) [email protected] Atlanta Regional Commission 40 Courtland Street, NE Atlanta, Georgia 30303 www.atlantaregional.com Acknowledgements: PBS&J, AECOM, Parsons Brinckerhoff, John Bowman, Mark Bradley, Bill Allen