考虑智轨列车行驶时间不确定性的接运公交设计研究  

Feeder Bus Design under Travel Time Uncertainty of Autonomous-rail Rapid Transit Train

作　　者：殷勇[1,2,3] 岳梦凡 陈卓 张帆[1,2] 陈锦渠 YIN Yong;YUE Mengfan;HEN Zhuo;HANG Fan;HEN Jinqu(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 611756,China;Yibin Research Institute,Southwest Jiaotong University,Yibin 644000,China;National United Engineering Laboratory of Integrated and Intelligent Transportation,Southwest Jiaotong University,Chengdu 611756,China)

机构地区：[1]西南交通大学交通运输与物流学院,四川成都611756 [2]西南交通大学宜宾研究院,四川宜宾644000 [3]西南交通大学综合交通运输智能化国家地方联合工程实验室,四川成都611756

出　　处：《综合运输》2024年第7期59-65,共7页China Transportation Review

基　　金：宜宾市双城协议保障科研经费科技项目(SWJTU2021020006)。

摘　　要：为改善以智能轨道快运(Autonomous-rail Rapid Transit, ART)系统为骨干的城市公共交通系统的运输服务水平,本文研究考虑ART列车行驶时间不确定性的接运公交设计问题。首先,考虑出行需求,基于ART站点及城市公交站点的空间关系选定备选接运公交站点,其次,考虑ART列车不确定的行驶时间,以乘客出行成本最小为目标,接运公交连通性、车队规模及发车频率等为约束,构建模型用于设计接运公交的线路及发车间隔。最后,选用粒子群算法实现模型的求解。以宜宾智轨T1线为例的研究表明,本文所提出的方案能够显著提升乘客出行效率,相较于无接运公交情况,乘客的期望出行成本节省了9.8%。To improve the transportation service level of the urban public transportation system with Autonomous-rail Rapid Transit(ART)as the backbone,this paper studies the design problem of feeder bus considering the uncertain ART train travel time.First,considering travel demand,alternative feeder bus stops are selected based on the spatial relationship between ART and bus stops.Second,considering the impact of uncertain ART train travel time,a model is formulated to optimize the route direction and departure interval of feeder bus with the objective of minimizing the passengers'travel cost with constraints such as route connectivity,fleet size and headway of feeder bus.Finally,a solution algorithm based on the particle swarm optimization algorithm is proposed to solve the model.The numerical experiment based on the Yibin ART Line 1 shows that the scheme proposed in this paper can great improve the eficiency of passenger travel and save 9.8%of passenger travel cost compared to the case without feeder bus.

关 键 词：智能轨道快运系统 接运公交设计 发车频率 时间不确定性 粒子群算法 

分 类 号：U298[交通运输工程—交通运输规划与管理]