Critical Path Identification for Network Signal Coordination Control Using Connected Vehicle Data Based on Analytic Hierarchy Process Method

Conference Paper (2024)
Author(s)

Jiarong Yao (Nanyang Technological University)

Chaopeng Tan (TU Delft - Traffic Systems Engineering)

Hao Wu (Tongji University)

Yumin Cao (Tongji University)

Keshuang Tang (Tongji University)

Research Group
Traffic Systems Engineering
DOI related publication
https://doi.org/10.1109/ICARCV63323.2024.10821709
More Info
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Publication Year
2024
Language
English
Research Group
Traffic Systems Engineering
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
7-12
ISBN (electronic)
9798331518493
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Abstract

Network signal coordination control is a crucial means to improve the traffic operation efficiency of the overall roadway network. Accurate identification of critical paths does play an important role in determining the scope of network coordination control. Therefore, this paper proposed the definition of critical path from the perspective of traffic control and management. Under the detection environment of connected vehicle (CV), a comprehensive quantitative indicator system for path criticality evaluation from three aspects, supply side, demand side and operation side, which are arranged in the form of a tower structure. A critical path identification method (CPIM) was then proposed based on the analytic hierarchy process (AHP) theory, which was hereinafter referred to as AHP-CPIM. In order to evaluate the feasibility and effectiveness of the proposed method, a case study set in an urban network in Tongxiang, Zhejiang Province in China, is conducted through simulation models built through VISSIM and Synchro. Two scenarios were set, one is coordination control based on the coordination subarea obtained from Synchro (namely without critical path identification), and another one is coordination control with critical paths obtained from AHP-CPIM. Results showed that, compared with the control of Synchro and Multiband method under the scenario of coordination control without critical path identification, network signal coordination control optimization based on AHP-CPIM improved about 37.9% and 35.9% in average delay, respectively, justifying the effectiveness of CV-driven critical path identification for network signal coordination control.

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