Dynamic Multi-objective Optimization for Mixed Traffic Flow Based on Partial Least Squares Prediction Model

Abstract

A dynamic multi-objective genetic algorithm based on partial least squares prediction model DNSGA-II-PLS is presented in this paper to solve the mix traffic flow multi-objective timing optimization problem with time-varying traffic demand. Take motor vehicle delay, non-motor vehicle delay and urban road service level as objectives to solve the problem. Then, the algorithm is tested under the simulation environment. And making comparation with three improved dynamic multi-objective genetic algorithms based on prediction strategy, the results show that the proposed DNSGA-II-PLS algorithm can effectively reduce the delay of motor vehicles, non-motor vehicles and pedestrian waiting time.