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一种基于时空棱柱的乘车行程可拼性判断模型

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拼车是城市共享出行的重要组成部分,量化分析行程间的可拼性程度对推广拼车服务和提高乘客的出行效率具有重要意义.现有研究大多依据车辆在多个上、下车点间是否满足特定时空约束条件下的先后到达顺序来判断可否拼车,缺少有效建模行程可拼性强度的手段,在应对大规模拼车请求时无法快速全面地发现所有潜在可拼机会.提出了一种基于时空棱柱的乘车行程可拼性判断模型,首先基于时间地理学中的时空棱柱建模方法和乘客共乘意愿的时空表达,构建行程的潜在时空可达范围表达模型;然后,基于行程时空棱柱间的拓扑关系判断行程的可拼性,量化行程的可拼性强度;最后,提出两种拼车匹配策略,模拟真实出行环境下的拼车匹配结果.实验结果表明,所提模型能够准确和有效地发现潜在可拼行程.对美国纽约市曼哈顿岛内行程可拼性能力的可视化分析结果呈现出明显的时空分布规律,能为车辆资源调度和乘客拼车出行规划提供一定的决策支持.
A Ridesharing Model Based on Space-Time Prism for Shared Mobility
Objectives:Ridesharing is an essential part of shared mobility for improving passengers'travel ef-ficiency in cities.The existing studies usually determine shareable trips based on whether the arrival se-quence of vehicles in more than one pick-up and drop-off points can meet the predefined spatiotemporal constraints.Such a simple approach cannot quickly and comprehensively find all the potential shareable trips under scenarios involving large-scale car-sharing requests.Methods:Based on the modeling method of space-time prism and the spatial-temporal expression of passengers'sharing willing,we first propose a po-tential spatiotemporal path area model of travel.Then,we apply the topological relation between the space-time prisms of trips for ridesharing identification,and quantify the strength of ridesharing of trips.Finally,two ridesharing matching strategies are proposed to simulate the ridesharing matching process in real-world transport environment.Results:The proposed ridesharing identification model can accurately delineate the potential space-time accessibility of vehicular travel,which makes it easier to discover all potential share-able trips and to realize the accurate and effective ridesharing identification.Conclusions:This study can be helpful for vehicle dispatching and passengers'travel planning in shared urban mobility system.

shared mobilityspace-time prismroad networkridesharing modelmatching strategy

李杰文、康朝贵

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武汉大学遥感信息工程学院,湖北 武汉,430079

中国地质大学(武汉)国家地理信息系统工程技术研究中心,湖北 武汉,430078

共享出行 时空棱柱 道路网络 可拼性判断模型 拼车匹配策略

2024

武汉大学学报(信息科学版)
武汉大学

武汉大学学报(信息科学版)

CSTPCD北大核心
影响因子:1.072
ISSN:1671-8860
年,卷(期):2024.49(9)