| With the rapid development of social economy,automobile has gradually become the daily walking tool of tens and ordinary people.At the same time,the incidence of traffic accidents is also increasing,and traffic accidents caused by human factors account for more than 90% of the total number of accidents,which indicates that traffic accidents are not only related to the car itself,but also closely related to people's driving manipulation behavior.Therefore,this paper studies the driving control mode of pure electric vehicle under the traffic scene at the intersection of Urban Trunk road,analyzes the types of cross conflict existing by pure electric vehicle under the urban intersection scene,and establishes the multi-objective optimization model of driving safety,economy and comfort of pure electric vehicle,with speed,acceleration,road width,lane number,The mean square root value of the total weighted acceleration is the optimization decision variable,and the optimal path solution set under the urban intersection scene is obtained.A pure electric vehicle control strategy based on NSGA-? genetic algorithm is proposed,and the accuracy and feasibility of multi-objective optimization model under driving control mode of pure electric vehicle are verified.Firstly,In this paper,using the existing model of Advisor2002 automobile simulation software,according to the simulation condition of this paper,the whole vehicle dynamic model,the mathematical model of transmission system and the mathematical model of driving resistance are constructed by setting different parameters of a pure electric vehicle selected.It provides theoretical support for the establishment of the objective function of economy and comfort of pure electric vehicle,and provides a theoretical basis for the research of driving control system of pure electric vehicle.Then,taking the crossroads of urban arterial road as the background,the severity of the conflict type is clarified.The multi-objective optimization model of safety,economy and comfort of pure electric vehicles is established by using multi-objective optimization theory and weighting method,and the non-dominant sorting genetic algorithm(NSGA-II)with elite strategy is used to optimize its safety,economy and comfort,and the effects of different driving paths,different left-turn speeds and different single lane widths on its safety,economy and comfort are described in detail.The optimization results show that with the increase of the driving trajectory of the left-turn vehicle,the straight-through speed increases by 9.4%,the mean square root value of the total weighted acceleration increases by 30.6%,the acceleration increased by 24.1%,and the safety,economy and comfort of pure electric vehicles increases by 10.15% in two-way four lanes.With the increase of the driving trajectory of the left-turn vehicle,the straight-through speed increased by 10.26%,the mean square root value of the total weighted acceleration increased by 82.11%,the acceleration increased by 0.81%,and the safety,economy and comfort of pure electric vehicles increased by 6.3% in the two-way six lanes,and the research results achieve the goal of improving the comprehensive performance of safety,economy and comfort of pure electric vehicles.Finally,based on the optimization result and constraint condition obtained by NSGA-II optimization algorithm,this paper designs the driving control system of pure electric vehicles,expounds the control strategy of speed and acceleration in detail,and gets the speed and acceleration curve through the fuzzy controller.The results show that the speed and acceleration curve of the control strategy are smoother,there is no crest or trough,and the validity of multi-objective optimization of pure electric vehicle is verified,whether it is driving in two-way four lanes or six lanes in two directions.And the fuzzy control method proposed in this paper can control the vehicle safe driving on the road and the operation stability is better,and has good robustness. |
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