Dynamic On-Demand Vehicle Services for Small or Medium-sized Cities based on the E-CARGO Model

基于E-CARGO模式的中小城市动态按需用车服务

• 批准号: RGPIN-2018-04818
• 负责人: Zhu, Haibin
• 金额: $ 2.26万
• 依托单位: Nipissing University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=683835
• 关键词: Dynamic; Demand; Vehicle; Services; Small

Title: Dynamic On-Demand Vehicle Services for Small or Medium-sized Cities based on the E-CARGO Model***The public transit system is an essential and very expensive service provided to the residents of a small or medium-sized city. A city like North Bay, Ontario needs to subsidize almost $3 million to this service. During daily operations, there can be times when there are only two, one or even zero riders. This situation demonstrates a need to investigate possibilities for operational improvements to public transit systems.***To this end, we propose a dynamic on-demand vehicle service. This service offers rapid responses to rider requests in real-time or at periodic intervals. Based on these requests, the transit authority sets up on-demand vehicle services. This service aims at decreasing the number of scheduled vehicles and their sizes, lowers the operation cost, increases the vehicle utilization, and finally, provides an improved and more economical service to the residents.***Dynamic rider-to-vehicle assignment and efficient route planning are the major challenges to be addressed in this investigation. Solutions to these two challenges will affect the degree of rider satisfaction and the transit system's costs.***Such problems involve many factors and include many parameters. They can be categorized as multi-objective optimization problems and are very complex. An optimal solution can be difficult or impossible to find. My research aims at overcoming complexity issues and offering practical solutions. To achieve these objectives, we need to formalize the related problems with a well-defined model. A simulation system is required for the evaluation of alternative scheduling methods. Finally, practical vehicle routing algorithms are needed for optimal fleet deployment based on dynamic rider requests.***A solid theoretical foundation for this research comes from the results of my past NSERC research on Role-Based Collaboration (RBC), Group Role Assignment (GRA) and the Environments - Classes, Agents, Roles, Groups, and Objects (E-CARGO) model. The simulation maps the proposed service into an RBC system that includes rider/vehicle matching, rider/vehicle assignment, and vehicle routing. ***This research is to provide: 1) an effective evaluation algorithm to acquire pertinent rider-vehicle matching values; 2) a practical assignment algorithm based on the above evaluation and required constraints; 3) a practical routing algorithm in a dynamic situation; 4) practical reference values to set up the proposed services; and 5) a simulation system for facilitating the proposed service. ***This research conducts a thorough investigation of these innovative services. The outcomes will offer considerable savings in public transportation costs for small or medium-sized cities. The proposed solutions can be applied to similarly sized cities throughout Canada and around the world.

职务名称：基于E-CARGO模型的中小城市动态按需车辆服务 * 公共交通系统是为中小城市居民提供的必不可少且非常昂贵的服务。像安大略的北湾这样的城市需要为这项服务补贴近300万美元。在日常运营中，有时可能只有两个，一个甚至零个骑手。这种情况表明，有必要研究改进公共交通系统运营的可能性。为此，我们提出了一个动态的按需车辆服务。该服务可实时或定期对骑手请求做出快速响应。根据这些请求，过境当局按需提供车辆服务。这项服务旨在减少预定车辆的数量和尺寸，降低运营成本，提高车辆利用率，最终为居民提供更好和更经济的服务。动态的人车分配和有效的路线规划是本研究中要解决的主要挑战。这两个挑战的解决方案将影响乘客的满意度和交通系统的成本。*这些问题涉及许多因素，包括许多参数。它们可以被归类为多目标优化问题，并且非常复杂。最佳解决方案可能很难或不可能找到。我的研究旨在克服复杂性问题并提供实用的解决方案。为了实现这些目标，我们需要用一个定义良好的模型来形式化相关的问题。一个模拟系统是必要的替代调度方法的评估。最后，需要实用的车辆路径算法，以根据动态乘客请求进行最佳车队部署。*本研究的坚实的理论基础来自于我过去NSERC对基于角色的协作（RBC），组角色分配（GRA）和环境-类，代理，角色，组和对象（E-CARGO）模型的研究结果。模拟将建议的服务映射到RBC系统中，该系统包括骑手/车辆匹配、骑手/车辆分配和车辆路由。* 本研究旨在提供：1）有效的评估算法，以获取相关的乘用车匹配值; 2）基于上述评估和所需约束的实用分配算法; 3）动态情况下的实用路由算法; 4）设置建议服务的实用参考值;以及5）促进建议服务的模拟系统。* 本研究对这些创新服务进行了深入调查。这些成果将为中小城市节省大量公共交通费用。所提出的解决方案可以适用于加拿大和世界各地类似规模的城市。