摘要
针对站点车辆时空分布不均衡制约共享模式快速发展的问题,提出基于用户激励的共享电动汽车自适应调度成本最优模型,引入共享单车调度与价格激励手段,通过遗传算法求解获得最优价格优惠、初始站点车辆数、多时段可变最优阈值.实例仿真结果表明,通过用户激励策略,企业调度成本降低60%以上,峰值用户取、还车允许率超过95%,极大提升了用户满意度与车辆使用率,充分证明该模型的有效性.
Car-sharing is a very important development direction of urban transportation in the future.However,the unbalanced distribution of site vehicles caused by the tidal characteristics of user travel restricts the rapid development of the model.This paper presents an optimal model of adaptive relocation cost for shared electric vehicles based on user incentive,in which the sharing bicycle and price discount as adjustment strategies are introduced. The genetic algorithm is used to solve the model.The optimal price discount,the initial vehicle numbers,and the multi period variable optimal threshold allocated of each site are obtained.The simulation results based on real data show that the relocation cost of enterprise is reduced by more than 60%through the user incentive scheduling strategy,and the peak order fill rate is more than 95%.The validity of the model is proved to improve customer satisfaction and vehicle utilization rate.
作者
王宁
郑文晖
刘向
郭家辉
WANG Ning;ZHENG Wenhui;LIU Xiang;GUO Jiahui(School of Automotive Studies,Tongji University,Shanghai 201804,China;College of Transportation Engineering,Tongji University,Shanghai 201804,China)
出处
《同济大学学报(自然科学版)》
EI
CAS
CSCD
北大核心
2018年第12期1668-1675,1721,共9页
Journal of Tongji University:Natural Science
基金
国家科技支撑计划(2015BAG11B00)
中央高校基本科研业务经费专项资金(kx0170020172681)
上海市科学技术委员会软科学基金(18692109400)
关键词
电动汽车共享
用户激励
自适应调度模型
遗传算法
可变阈值
electric vehicle-sharing
user incentive
adaptive relocation model
genetic algorithm
variable threshold