Optimization of signal timing schedule of traffic network based on CTM

Xiaolin Ai, Jianqiao Yu*, Shengqing Yang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

In order to relieve current urban traffic congestion, this study proposes a new model of network based on cell transmission model (CTM). A typical model of network with four three-line intersections is established by analyzing the confluence phenomenon, the divergence phenomenon and the extern dynamic input phenomenon, which appears in the actual traffic flow movement. The model depicts a transmission relation of traffic flow between different intersections efficiently. The timing schedule of traffic signal of the intersections can be optimized dynamically to reduce the average network delay and enhance the road capacity. In this study, a genetic algorithm (GA) is applied to optimize the timing schedule where the average network delay is considered as the objective of optimization. The simulation result shows that the proposed model of network can deal with the signal timing schedule of obstructed and unobstructed traffic phenomenon and the average network delay can be reduced efficiently.

Original languageEnglish
Title of host publicationProceedings of the 33rd Chinese Control Conference, CCC 2014
EditorsShengyuan Xu, Qianchuan Zhao
PublisherIEEE Computer Society
Pages3367-3372
Number of pages6
ISBN (Electronic)9789881563842
DOIs
Publication statusPublished - 11 Sept 2014
EventProceedings of the 33rd Chinese Control Conference, CCC 2014 - Nanjing, China
Duration: 28 Jul 201430 Jul 2014

Publication series

NameProceedings of the 33rd Chinese Control Conference, CCC 2014
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

ConferenceProceedings of the 33rd Chinese Control Conference, CCC 2014
Country/TerritoryChina
CityNanjing
Period28/07/1430/07/14

Keywords

  • CTM
  • intelligent transportation
  • network
  • timing schedule optimization

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