Bat-based algorithm for intelligent regulation of traffic light eco-intersection design

A bat algorithm based traffic light intelligent regulation ecological intersection is designed. In order to solve the intersection vehicle congestion problem and implement reasonable and efficient traffic light control, this paper uses the Python-based VISSIM interface to realize the data interaction between the algorithm and simulation, deploys the bat algorithm on the simulation platform, and conducts simulation experiments on intersection traffic light control. The simulation results show that the signal timing algorithm based on vehicle congestion improves intersection throughput, reduces average vehicle waiting time and achieves the goal of preventing and alleviating traffic congestion compared with the traditional time-phased traffic light control method and the main road control method (ATL). Tests show that the average queue length decreased by 33.8% compared to the non-deployed algorithm, the maximum queue length decreased by 38.9%, delay decreased by 22.2%, intersection throughput increased by 14.8% and average vehicle carbon emissions decreased by 57.2%. This shows that the bat-based algorithm for intelligent signal modulation is effective in reducing traffic congestion at intersections and reducing total emissions at intersections.