Estimating Train Choices of Rail Transit Passengers with Real Timetable and Automatic Fare Collection Data
Estimating Train Choices of Rail Transit Passengers with Real Timetable and Automatic Fare Collection Data
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DOI：
10.1155/2017/5824051
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发表时间：
2017-08
影响因子：
2.3
通讯作者：
Wei Zhu;Wei Wang;Zhaodong Huang
中科院分区：
文献类型：
--
作者：
Wei Zhu;Wei Wang;Zhaodong Huang
An urban rail transit (URT) system is operated according to relatively punctual schedule, which is one of the most important constraints for a URT passenger’s travel. Thus, it is the key to estimate passengers’ train choices based on which passenger route choices as well as flow distribution on the URT network can be deduced. In this paper we propose a methodology that can estimate individual passenger’s train choices with real timetable and automatic fare collection (AFC) data. First, we formulate the addressed problem using Manski’s paradigm on modelling choice. Then, an integrated framework for estimating individual passenger’s train choices is developed through a data-driven approach. The approach links each passenger trip to the most feasible train itinerary. Initial case study on Shanghai metro shows that the proposed approach works well and can be further used for deducing other important operational indicators like route choices, passenger flows on section, load factor of train, and so forth.
