Multi-objective optimization Control and Data Analysis of Intersection Considering Vehicle Exhaust Emission

Abstract

Considering the influence of traffic efficiency indicators on vehicle exhaust emission at urban intersection, firstly, the single-objective optimization function of vehicle delay, number of stops and traffic capacity was established respectively. By calculating the contribution rate of the above indicators to vehicle exhaust emission at intersection, and taking the minimum influence of vehicle exhaust emission as the optimization objective, Pareto multi-objective optimization function was further established, then the contribution rate was used as the weight to transform the multi-objective function into an objective function, and the particle swarm optimization (PSO) algorithm was used to solve the optimal value. The video traffic volume collection system and environmental monitoring system were set up at the actual intersection of Hefei city to collect the data of traffic volume and vehicle exhaust emission in real time, the effectiveness of the solution method of Pareto multi-objective optimization function is further verified. The data analysis results showed that, the single-objective optimization could only make one indicator optimal, and the performance indicator of influence on vehicle exhaust emission was not optimal, while the multi-objective optimization enabled multiple indicators to be optimized within a reasonable scope, and the performance indicator of influence on vehicle exhaust emission was optimal.