A genetic timing scheduling model for urban traffic signal control

As urban traffic condition is diverse and complicated, maximizing the use of urban traffic signal control system to solve traffic issues becomes one of the hot and promising topics. Especially, how to control traffic signals at multiple intersections is a key challenge. To speed up urban traffic flow, this research presents a genetic timing scheduling model (GTSM) for urban traffic signal control. GTSM constructs cellular automata to update the timing cycles of traffic signals at multiple intersections, where state update functions are formulated to coordinate traffic signals. In addition, a proposed genetic optimization algo-rithm (GOA) in GTSM optimizes the timing cycles of traffic signals at multiple intersections in the dynamic timing optimization. The experimental results on urban road networks show that the performance of our model is excellent in various scenarios to control traffic signals to speed up urban traffic flow. (c) 2021 Published by Elsevier Inc.

Automated summary

The research presents a genetic timing scheduling model (GTSM) for urban traffic signal control, utilizing cellular automata and genetic optimization algorithm to coordinate and optimize traffic signals at multiple intersections to speed up urban traffic flow. The experimental results show that the model performs excellently in various scenarios.