DEPART: Dynamic Route Planning in Stochastic Time-Dependent Public Transit Networks

被引:4
|
作者
Ni, Peng [1 ]
Vo, Hoang Tam [1 ]
Dahlmeier, Daniel [1 ]
Cai, Wentong [2 ]
Ivanchev, Jordan [3 ]
Aydt, Heiko [3 ]
机构
[1] SAP Innovat Ctr, Dynam RoutE plAnning tRansit neTworks, Potsdam, Germany
[2] Nanyang Technol Univ, Singapore 639798, Singapore
[3] TUM CREATE, Singapore, Singapore
关键词
PATHS;
D O I
10.1109/ITSC.2015.271
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
While providing intelligent urban transportation services is one of the key enablers for realizing smart cities, existing transit route planners mainly rely on static schedules and hence fall short in dealing with uncertain and time-dependent traffic situations. In this paper, by leveraging a large set of historical travel smart card data, we propose a method to build a stochastic time-dependent model for public transit networks. In addition, we develop DEPART1-a dynamic route planner that takes the stochastic models of both bus travel time and waiting time into account and optimizes both the speediness and reliability of routes. Experiments on real bus data set for the entire city confirm the quality and accuracy of the routes returned by DEPART in comparison to state-of-the-practice route planners.
引用
收藏
页码:1672 / 1677
页数:6
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