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Optimal Routing Design of Feeder Transit With Stop Selection Using Aggregated Cell Phone Data and Open Source GIS Tool

机译:使用聚合手机数据和开源GIS工具停止选择的馈线过境的最佳路由设计

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A novel bilevel programming model for designing feeder bus routes to simultaneously consider bus stop selection, bus routing, and passenger route/trip choice behavior is developed in this work. The objective of the upper-level model is to minimize the total in-vehicle travel time of passengers. The objective of the lower-level model is to determine bus stop locations and assign passenger demand to stops by minimizing the total passenger walking time. An ant colony optimization-based two-stage heuristic algorithm is developed to solve the bilevel programming model within an acceptance computation time. Different from conventional methods, the proposed methodology benefits from using real temporal and spatial characteristic datasets of travel demand aggregated from cellular data and traveling time and distance matrices under actual traffic conditions resulted from an open geographic information system (GIS) tool. Results of a real-life case study in Chongqing municipality, China, show that the proposed methodology could achieve a significant reduction of 2.9% total passenger travel time compared with a traditional method. Finally, sensitivity analyses are conducted to further understand the performance of the model. It is anticipated that the proposed methodology could be very useful in designing attractive and cost-effective feeder transit service in practice.
机译:一种用于设计馈线总线路线的新型贝里尔编程模型,以便在这项工作中开发了总线停止选择,总线路由和客线/旅行选择行为。上层模型的目的是最小化乘客的总车载行程时间。下层模型的目的是确定总线停止位置,并通过最小化总乘客步行时间来分配乘客需求来停止。基于蚁群优化的两级启发式算法是开发的,以解决验收计算时间内的Bilevel编程模型。与传统方法不同,所提出的方法效益来自使用从蜂窝数据和行进时间和距离矩阵聚合的旅行需求的实际时间和空间特征数据集由开放地理信息系统(GIS)工具产生的实际交通状况。中国重庆市的真实案例研究结果表明,与传统方法相比,拟议的方法可能会达到2.9%总客车时间的显着减少。最后,进行敏感性分析以进一步了解模型的性能。预计该方法在实践中设计有吸引力和经济高效的馈线过境服务非常有用。

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