Intersection multi-objective optimization on signal setting and lane assignment

Xiang Li and Jian-Qiao Sun

Physica A: Statistical Mechanics and its Applications, 2019, vol. 525, issue C, 1233-1246

Abstract: Increasing traffic volumes result in congestion especially at intersections in urban areas. Effective regulation of vehicle flows at intersections has always been an important issue in the traffic control system. This paper presents a multi-objective optimization method for improving traffic performance at intersections. Vehicle conflicts and pedestrian interference are considered in the microscopic simulation of the traffic system. Three categories of the traffic performance are studied including transportation efficiency, energy consumption and road safety. The signal timing and lane assignment are optimized for different traffic flows. The multi-objective optimization problem is solved with the cell mapping method. The optimization results with constant traffic demands show the conflicting nature of different performance objectives. The influence of different traffic variables on the intersection performance is investigated. We further propose a dynamic optimization algorithm to handle the varying traffic demands. It is observed that the proposed optimization method is effective in controlling the traffic at the intersection to meet multiple objectives. Different control demands can be satisfied and optimal performance can be obtained.

Keywords: Multi-objective optimization; Cell mapping algorithm; Intersection optimization; Intelligent control; Cellular automata (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:525:y:2019:i:c:p:1233-1246

DOI: 10.1016/j.physa.2019.04.223

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