融合客流大数据和成本最优化的公交动态排班方法  

Bus Dynamic Scheduling Method Based on Passenger Flow Big Data and Cost Optimization

作　　者：罗建平 陈欢 欧勇辉 李慧玲 林德勇 LUO Jianping;CHEN Huan;OU Yonghui;LI Huiling;LIN Deyong(Guangdong Province Urban Intelligent Transportation Internet of Things Engineering Technology Research Center,Guangzhou 510000,China;Guangzhou Jiaoxintou Technology Co.,Ltd,Guangzhou 510000,China;Guangzhou Public Transport Group Co.,Ltd,Guangzhou 510000,China)

机构地区：[1]广东省城市智能交通物联网工程技术研究中心,广州510000 [2]广州交信投科技股份有限公司,广州510000 [3]广州市公共交通集团有限公司,广州510000

出　　处：《交通与运输》2021年第5期87-92,共6页Traffic & Transportation

基　　金：交通部行业重点科技项目(2019-ZD7-045);广州市科技计划项目(201902010043)。

摘　　要：为提高公交排班效率和准确性,提出一种基于客流OD数据的动态排班模型。首先,模型将影响公交车辆排班的因素划分为静态因素、可变因素和动态因素,给出每日客流变化情况下动态影响因素计算方法;其次,以满足乘客需求减少公交企业运营成本为目标,探索多目标最优排班方案求解方法,实现公交运营效益最大化;最后,以广州560路公交线路为例进行模型仿真验证。仿真结果表明:模型求解结果可以在不降低乘客服务质量的同时有效减少车辆使用量,提升车辆满载率,工作日减少车辆13.3%,非工作日减少车辆26.6%。在满足社会效益的情况下节约企业运营成本。In order to improve the efficiency and accuracy of bus scheduling,this paper proposes a dynamic scheduling model based on OD data of passenger flow.Firstly,the factors that affect bus scheduling are divided into static factors,variable factors and dynamic factors.By studying the influence of passenger flow on automatic scheduling,the calculation method of dynamic factors under the change of daily passenger flow is proposed;Secondly,in order to meet the needs of passengers and reduce the operating costs of public transport enterprises,the solution method of multi-objective optimal scheduling scheme is explored to maximize the benefits of public transport operation;Finally,taking Guangzhou 560 bus line as an example,the simulation results show that under the premise of ensuring the quality of passenger service,the model can effectively reduce the use of vehicles,which can reduce vehicles by 13.3% on working days and 26.6%on non-working days.The model can not only save the enterprise operation cost but also meet the social benefits.

关 键 词：城市交通 动态排班 公交客流 公交调度 大数据 

分 类 号：U491[交通运输工程—交通运输规划与管理]