摘要
近年来,中国纯电动公交车占比逐年提高,2019年已超过46.8%,北上广深等多个城市已实现100%。通过深入分析纯电动公交车行驶过程中的耗能组成,由此建立电能能耗成本函数;构建同时考虑乘客出行与公交企业运营成本的纯电动公交车调度排班模型;将公交场站车辆数作为约束条件引入模型,真实反映实际车辆运行情况;为严格做好疫情防控,将车辆满载率纳入模型约束以保证乘客安全距离;通过分析发现该模型属于NP-hard问题,提出利用遗传算法对其进行求解。利用广州市105路公交线路的运行和OD需求数据进行仿真验证,表明该模型和算法具有一定的有效性。
In recent years,the proportion of pure electric buses in China has increased year by year.In 2019,it has exceeded 46.8%,and many cities such as Beijing,Shanghai,Guangzhou and Shenzhen have reached 100%.Therefore,through in-depth analysis of the energy consumption,this article first establishes the functional relationship between the energy consumption of pure electric buses and passenger capacity.Based on this,a pure electric bus scheduling model is constructed,which takes into account both passenger travel and the operating costs of public transportation companies.To further reflect the actual vehicle operation conditions,the number of vehicles at the bus station is introduced into the model as a constraint.In order to prevent and control the epidemic situation strictly,the full load rate of vehicles is included in the model constraint to ensure the safety distance of passengers.It is found that this model is an NP-hard problem which can be solved by a genetic algorithm.Finally,the effectiveness of the model and algorithm is verified by the operation and OD demand data of No.105 bus line in Guangzhou.
作者
张颖
邹亮
ZHANG Ying;ZOU Liang(College of Civil and Transportation Engineering, Shenzhen University, Shenzhen Guangdong 518060, China)
出处
《大连民族大学学报》
2021年第1期45-53,共9页
Journal of Dalian Minzu University
基金
深圳市科技计划项目(JCYJ20170818142947240)。
关键词
公交调度
纯电动公交
能耗组成分析
实时排班
遗传算法
bus dispatch
pure electric bus
analysis of power consumption
real-time scheduling genetic algorithm