站点需求响应的电动模块公交车重组调度优化  

Formation and Scheduling Optimization of Electric Modular Buses with Station-based Demand-responsive Model

作　　者：高虹 刘锴[1] 姚恩建[2] GAO Hong;LIU Kai;YAO En-jian(School of Transportation and Logistics,Dalian University of Technology,Dalian 116024,Liaoning,China;School of Traffic and Transportation,Beijing Jiaotong University,Beijing 100044,China)

机构地区：[1]大连理工大学交通运输学院,辽宁大连116024 [2]北京交通大学交通运输学院,北京100044

出　　处：《中国公路学报》2024年第4期24-36,共13页China Journal of Highway and Transport

基　　金：国家自然科学基金项目(71871043);辽宁省科技厅2022揭榜挂帅重点项目(2022JH1,10800098)。

摘　　要：传统的电动公交系统受到固定车辆容量等限制,难以通过灵活地调度应对时空不均衡的站点需求。为突破这一瓶颈,基于一种采用耦合/解离操作实现容量动态调整的电动模块车技术,提出考虑站点需求响应的模块化公交重组调度优化模型,可以较好解决乘客在车站的滞留问题。模型以单公交线路为研究对象,通过优化电动模块车在组合站点的容量重组操作和不同班次间的序列决策,旨在最小化包括车辆派遣、运营能耗等多项成本在内的总成本。特别考虑到模块车电池容量较小等特点,调度模型强调了车辆个体的能耗限制和充电计划。针对提出的混合整数非线性规划模型,引入辅助变量将约束中所涵盖的非线性部分转化为线性约束,增强模型的可求解性。采用郑州市电动公交实际运营数据提取的多项参数作为模型输入,将优化后的车辆使用数、系统总成本、未服务乘客的惩罚成本以及充电成本等多项指标与其他2种调度策略进行对比。结果表明:相较于传统电动公交,考虑站点需求响应的模块车调度策略可使系统总成本降低约26.6%,特别是站点间动态容量调整的优势可以使滞留乘客的人数降低95.4%,提高公共交通服务的便民性;与非站点响应的模块车调度模式相比,总成本也降低约7.3%,其中运营和充电成本的减少最为显著。最后展开敏感性分析为实际运营中关于车型选择、电池容量配置以及寻找乘客服务水平和运营经济性二者的均衡点提供了决策依据。Restricted by various conditions, such as fixed vehicle capacity, conventional electric transit systems are struggling to cope with spatially and temporally uneven station demands through flexible dispatch. To overcome this bottleneck, we proposed a station-based demand responsive model for formation and scheduling optimization based on electric modular vehicle technology that enables dynamic capacity adjustment via coupling/decoupling actions. Taking a single bus route as the modeling object, the model optimizes the vehicle capacity reformation and trip sequences for electric modular vehicles to minimize the total cost, including the vehicle dispatch cost, charging cost, and other items. Considering the low battery capacity of modular vehicles, individual energy constraints and charging plans were emphasized in the scheduling model. Because the proposed model is a mixed-integer nonlinear programming problem, auxiliary variables were introduced to further transform the nonlinear part covered in the constraints into linear constraints to improve the tractability of the model. Using the parameters extracted from real operation data of electric buses in Zhengzhou City as model inputs, a variety of optimization indicators with respect to the number of vehicles employed, total system costs, penalty costs for unserved passengers, and charging costs were compared with the other two scheduling strategies. The results show that compared with the traditional electric bus, the modular vehicle scheduling strategy considering station-based demand-response can reduce the total system costs by approximately 26.6%. In particular, the dynamic capacity advantage among stations allows for a 95.4% reduction in the number of stranded passengers, increasing the accessibility of public transport services. In addition, the total cost is reduced by approximately 7.3% compared to that of the non-station demand-responsive modular vehicle scheduling mode, achieving the most significant savings in operating and charging costs. Sensitivity an

关 键 词：交通工程 电动模块车 调度优化 站点需求响应 乘客滞留 充电决策 

分 类 号：U491.17[交通运输工程—交通运输规划与管理]