|
Title: Large-Scale Agent-Based Transport Simulation in Shanghai, China
Accession Number: 01476788
Record Type: Component
Record URL: Availability: Transportation Research Board Business Office 500 Fifth Street, NW Find a library where document is available Abstract: The activity-based model system is being coined as the next-generation demand-forecasting model. The agent-based transport simulation toolkit MATSIM is a fully integrated system that models decisions from the long term to the short term, and these decisions in MATSIM are activity-based models. This paper describes the application of MATSIM in a large-scale multiagent-based transport simulation for Shanghai, China. First, algorithms for integrating new data in Shanghai with MATSIM inputs such as synthetic population, facilities, and network are separately designed according to data characteristics. Then activity-based modeling is introduced to generate population plans, and activity replanning is employed to learn the better travel plans; a utility-based approach is used to model scoring for a plan. Finally, a full MATSIM-based simulation platform for the Shanghai scenario is built in detail. The scenario contains 200,000 synthetic persons simulated on a network with 50,000 links. The relaxed state of the simulation system is reached after 100 iterations of replanning procedures, and the mode choice, route choice, and activity time allocation modules are used to optimize agents’ activity plans. The feasibility of transport simulation in Shanghai by MATSIM is validated against the mode split and the observed counts. Extensive simulation results for the designed Shanghai simulation scenarios indicate that most of the observed counts match quite well with the traffic simulation volumes and demonstrate the potential of MATSIM for large-scale dynamic transport simulation.
Monograph Title: Information Systems, Geospatial Information, State Data, and Advanced Computing 2013 Monograph Accession #: 01517323
Report/Paper Numbers: 13-4405
Language: English
Authors: Zhang, LunYang, WenchenWang, JiameiRao, QianPagination: pp 34–43
Publication Date: 2013
ISBN: 9780309294843
Media Type: Print
Features: Figures
(5)
; References
(24)
; Tables
(2)
TRT Terms: Identifier Terms: Geographic Terms: Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; Planning and Forecasting; I70: Traffic and Transport; I72: Traffic and Transport Planning
Files: TRIS, TRB, ATRI
Created Date: Feb 5 2013 12:51PM
More Articles from this Serial Issue:
|