Arxiv:1605.08390V1 [Cs.AI] 19 Apr 2016 Corresponding Author: Fan Zhang (Email: [email protected])
1 Estimation of Passenger Route Choice Pattern Using Smart Card Data for Complex Metro Systems Juanjuan Zhao, Fan Zhang, Member, IEEE, Lai Tu, Chengzhong Xu, Fellow, IEEE, Dayong Shen, Chen Tian, Xiang-Yang Li, Fellow, IEEE, and Zhengxi Li Nowadays, metro systems play an important role in meeting the urban transportation demand in large cities. The understanding of passenger route choice is critical for public transit management. The wide deployment of Automated Fare Collection(AFC) systems opens up a new opportunity. However, only each trip’s tap-in and tap-out timestamp and stations can be directly obtained from AFC system records; the train and route chosen by a passenger are unknown, which are necessary to solve our problem. While existing methods work well in some specific situations, they don’t work for complicated situations. In this paper, we propose a solution that needs no additional equipment or human involvement than the AFC systems. We develop a probabilistic model that can estimate from empirical analysis how the passenger flows are dispatched to different routes and trains. We validate our approach using a large scale data set collected from the Shenzhen metro system. The measured results provide us with useful inputs when building the passenger path choice model. Index Terms—Metro systems, Smart card, Data mining, Intelligent transportation systems. I. INTRODUCTION HengGang g OWADAYS, metro systems play an important role in n QingHu TangKeng o L HeAo LiuYue g AiLian DaYun LongHua n JiXiang YongHu NanLian a meeting the urban transportation demand in large cities. LongSheng DanZhuTou u h N DaFen S ShangTang Due to its fast speed, high efficiency, large volume and HongLangBei XingDong LiuXianDong XiLi DaXueCheng TangLang ZhangLingPo HongShan MuMianWan JiChangDong BuJi HouRui BaiShiLong CaoPu punctuality, the urban metro has become the first choice of ShuiBei LongChengGuangChang GuShu LingZhi MinLe WuHe MinZhi BanTian TianBei XiXiang ShangMeiLin YangMei ZhangLong CuiZhu many people.
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