Estimating Train Choices of Rail Transit Passengers with Real Timetable and Automatic Fare Collection Data

Wei Zhu,Zhaodong Huang,Wei Wang

doi:10.1155/2017/5824051

Wei Zhu, Zhaodong Huang + Show 1 more

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https://doi.org/10.1155/2017/5824051

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Abstract

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.

Highlights

Passenger flow is the foundation of making and coordinating operation plans for an urban rail transit (URT) system, while assigning passenger flows on the URT network plays a paramount role in analyzing passenger flows
Different from urban road traffic systems, a URT system is operated according to relatively punctual schedule, which is an important constraint for a URT passenger’s travel
For better understanding of passenger flows on network, the objective of this paper is to propose a methodology that can estimate passenger train choices with real timetable and automatic fare collection (AFC) data

Summary

Introduction

Passenger flow is the foundation of making and coordinating operation plans for an urban rail transit (URT) system, while assigning passenger flows on the URT network plays a paramount role in analyzing (calculating, predicting, and simulating) passenger flows. The passenger flow distribution on the network is subjected to passengers’ physical route choices and their individual train choices especially in peak hours (Figure 1), which may be a more important issue [4]. For analyzing passenger flows on a schedule-based URT network, it is the key to estimate passengers’ train choices for threefold reasons:. (1) On a schedule-based URT network, passenger route choices as well as flow distribution on the network can be deduced if the train choices of passengers are obtained, but that is not so either. URT companies can check how passengers select trains after timetable improvements

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