Double quintic polynomial ecological lane change trajectory optimization for intelligent vehicles based on multi-objective genetic algorithm

This paper aims to study the ecological trajectory optimization of intelligent vehicle during lane change, so as to realize the energy saving and emission reduction of vehicle lane change process. Based on VT-Micro model and double quintic polynomial lane-changing trajectory algorithm, multi-objective genetic algorithm was used to calculate the eco-type vehicle speed trajectory during lane-changing. The feasibility of eco-lane-change trajectory optimization was verified by Matlab and Carsim co-simulation. The results show that the optimized lane-change trajectory reduces fuel consumption by 10.1%, NOX emission by 18.2%, HC emission by 9.5%, but CO emission increases by 2.9%.The simulation results verify the feasibility of eco-lane change trajectory optimization, and provide a basis for the ecological planning of intelligent vehicle lane change.