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城郊公交线网hub站点和milk?run线路设计
引用本文:罗孝羚,蒋阳升,吴奇,赵斌,姚志洪.城郊公交线网hub站点和milk?run线路设计[J].哈尔滨工业大学学报,2019,51(3):135-140.
作者姓名:罗孝羚  蒋阳升  吴奇  赵斌  姚志洪
作者单位:西南交通大学 交通运输与物流学院,成都610031;综合交通大数据应用技术国家工程实验室(西南交通大学) ,成都610031;西南交通大学 交通运输与物流学院,成都610031;综合交通大数据应用技术国家工程实验室(西南交通大学) ,成都610031;西南交通大学 交通运输与物流学院,成都610031;综合交通大数据应用技术国家工程实验室(西南交通大学) ,成都610031;西南交通大学 交通运输与物流学院,成都610031;综合交通大数据应用技术国家工程实验室(西南交通大学) ,成都610031;西南交通大学 交通运输与物流学院,成都610031;综合交通大数据应用技术国家工程实验室(西南交通大学) ,成都610031
基金项目:国家自然科学基金(5,9);重庆市应用开发计划重点项目 (cstc2014yykfB3,5H01373)
摘    要:为解决现有的常规公交线网设计方法没有考虑实际城郊客流需求的特殊性,造成乘客出行时间过长的问题.构建基于milk-run和hub-spoke的设计理念,且同时考虑载客能力的城郊公交线网优化模型,并提出相应的遗传算法实现模型的求解.在所提出的方法中,能够得到hub站点的数量及具体位置、milk-run线路的结构、和车辆分配方案.不同于常规公交线路运营方式,所提出的城郊公交线网通过milk-run线路将分散的客流聚集到各线路的hub站点,从而形成大客流的规模效应,到达hub站点的大客流可以通过直达线路从hub站点到达相应的目的地,以此减少乘客总的出行时间.最后,为验证所提出的方法的有效性,将其应用到位于香港天水围的实际城郊公交线网中,并对比了优化后的公交服务和现有的公交服务水平.对比结果表明:在现有的公交车辆配置数量不变的条件下,所提出的方法,可以减少16.26%总的乘客出行时间,说明所提出的方法能够有效提高现有公交服务水平,增加乘客出行满意度,吸引更多乘客采用公交出行,减少交通拥堵.

关 键 词:交通工程  城市公交  城郊公交线网优化  hub-spoke站点  milk-run线路  遗传算法
收稿时间:2017/11/7 0:00:00

Design of hub stops and milk-run routes in transit network between urban area and suburb
LUO Xiaoling,JIANG Yangsheng,WU Qi,ZHAO Bin and YAO Zhihong.Design of hub stops and milk-run routes in transit network between urban area and suburb[J].Journal of Harbin Institute of Technology,2019,51(3):135-140.
Authors:LUO Xiaoling  JIANG Yangsheng  WU Qi  ZHAO Bin and YAO Zhihong
Affiliation:School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China ;National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University, Chengdu 610031, China,School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China ;National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University, Chengdu 610031, China,School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China ;National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University, Chengdu 610031, China,School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China ;National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University, Chengdu 610031, China and School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China ;National Engineering Laboratory of Integrated Transportation Big Data Application TechnologySouthwest Jiaotong University, Chengdu 610031, China
Abstract:Current normal transit network results in long passenger travel time because it does not consider the particularity of the travel demand in transit network between urban area and suburb. To solve this problem, a novel transit network model was proposed based on principles of milk-run and hub-spoke, which considers the capacity constraint for the travel demand in transit network between urban area and suburb. Then the corresponding genetic algorithm was developed to solve this model. In this model, the number and locations of the hub stops, the route structure of milk-run route, and the vehicle assignment can be determined. Different from normal transit network, decentralized passenger flow can be aggregated at hub stops to form scale effect through milk-run routes in this network. In addition, massive passenger flow can complete their travels by express routes from hub stops, which can reduce their travel time. Finally, the proposed approach was applied to a real network in Tin Shui Wai of Hong Kong to verify its effectiveness. The comparisons of the proposed network and the existing network show that when the proposed network was applied, the total travel time was reduced by 16.26% with existing available fleet size. It suggests that the proposed network can improve the existing transit service level and travel satisfaction, as well as attract more passengers to travel by public transit, thereby mitigating traffic jam.
Keywords:transportation engineering  urban transit  optimization of transit network between urban area and suburb  hub stop  milk-run route  genetic algorithm
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