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Title:

Large-Scale Agent-Based Transport Simulation in Shanghai, China

Accession Number:

01476788

Record Type:

Component

Availability:

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Washington, DC 20001 United States
Order URL: http://www.trb.org/Main/Blurbs/170345.aspx

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Order URL: http://worldcat.org/isbn/9780309294843

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 Accession #:

01517323

Report/Paper Numbers:

13-4405

Language:

English

Authors:

Zhang, Lun
Yang, Wenchen
Wang, Jiamei
Rao, Qian

Pagination:

pp 34–43

Publication Date:

2013

Serial:

Transportation Research Record: Journal of the Transportation Research Board

Issue Number: 2399
Publisher: Transportation Research Board
ISSN: 0361-1981

ISBN:

9780309294843

Media Type:

Print

Features:

Figures (5) ; References (24) ; Tables (2)

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

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