Operational Evaluation of Traffic Guidance Systems Based on Multi-Agent-Based Simulation

Authors

Keshuang Tang, Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China;
Hengjia Zhang, Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China;
Yixie Bowen, Key Laboratory of Road and Traffic Engineering of Ministry of Education, Tongji University, Shanghai 201804, China;

Abstract

Abstract: To study the optimization effect of variable message sign-based traffic guidance system on the utilization efficiency of transportation resource, the multi-agent-based model is used to develop simulation and evaluation platform. The simulation experiments of three typical traffic guidance strategies are carried out. The effect of guidance is evaluated by the indexes as average driving time, average searching time for parking lot and parking failure rate. The result shows that the driving and parking guidance can help reduce the average driving time and the parking failure rate respectively. The influence of the traffic guidance system on the traffic operation status and the utilization of parking resource is different under different traffic demand levels, so the distribution of guidance information needs comprehensive consideration of traffic demand level and guiding strategy.

Recommended Citation

Tang, Keshuang; Zhang, Hengjia; and Bowen, Yixie (2019) "Operational Evaluation of Traffic Guidance Systems Based on Multi-Agent-Based Simulation," Journal of System Simulation: Vol. 30: Iss. 7, Article 25.
DOI: 10.16182/j.issn1004731x.joss.201807025
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss7/25

First Page

2630

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201807025

Last Page

2639

CLC

U491.1

Recommended Citation

Tang Keshuang, Zhang Hengjia, Yixie Bowen. Operational Evaluation of Traffic Guidance Systems Based on Multi-Agent-Based Simulation[J]. Journal of System Simulation, 2018, 30(7): 2630-2639.

DOI

10.16182/j.issn1004731x.joss.201807025