An agile vehicle-based dynamic user equilibrium scheme for urban traffic signal control

Liu, Wei-Li ORCID: 0000-0003-0725-3759, Gong, Yue-Jiao ORCID: 0000-0002-5648-1160, Chen, Wei-Neng ORCID: 0000-0003-0843-5802, Zhang, Jun ORCID: 0000-0001-7835-9871 and Dou, Zhi (2021) An agile vehicle-based dynamic user equilibrium scheme for urban traffic signal control. IET Intelligent Transport Systems, 15 (5). pp. 619-634. ISSN 1751-956X

Abstract

Traffic Signal Control (TSC) is a fundamental task in modern intelligent transport systems. TSC is often formulated as a bi-level optimization problem, comprised by the signal timing at the upper level and the Dynamic User Equilibrium (DUE) traffic assignment at the lower level. Since DUE is non-convex, existing methods either formulate approximation models or adopt traffic simulators. However, approximation models may oversimplify the practical situations, while traffic simulators are usually time-consuming. This paper formulates a vehicle-based DUE (vDUE) model and proposes an agile method that can simultaneously maintain the computational simplicity and the traffic dynamics for the traffic assignment. Further, an agile TSC system is built by combining the vDUE at the lower level for the traffic assignment with an adaptive differential evolution algorithm at the upper level for the signal timing optimization. To enhance the effectiveness of optimization, the TSC problem formulation is also improved to make it better characterize the practical requirements. In the experiments undertaken, comparisons of different TSC methods are carried out on both real-world and synthetic transportation networks. The experimental results validate the effectiveness of the proposed agile TSC system in various traffic situations.

Dimensions Badge

Altmetric Badge

Item type Article
URI https://vuir.vu.edu.au/id/eprint/45261
DOI 10.1049/itr2.12049
Official URL https://ietresearch.onlinelibrary.wiley.com/doi/10...
Subjects Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > FOR (2020) Classification > 4605 Data management and data science
Current > Division/Research > Institute for Sustainable Industries and Liveable Cities
Keywords traffic signal control, TSC, traffic simulator, intelligent transport systems, computing, data engineering
Citations in Scopus 5 - View on Scopus
Download/View statistics View download statistics for this item

Search Google Scholar

Repository staff login