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

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Wei Zhu ◽  
Wei Wang ◽  
Zhaodong Huang
Keyword(s):  
Flow Distribution ◽  
Urban Rail Transit ◽  
Load Factor ◽  
Rail Transit ◽  
Urban Rail ◽  
Collection Data ◽  
Data Driven Approach ◽  
Passenger Flows ◽  
Route Choices ◽  
Shanghai Metro

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.

Influence of Emergency Passenger Flow Distribution in Urban Rail Network

2012 ◽  
Vol 450-451 ◽  
pp. 295-301 ◽  
Author(s):  
Ling Hong ◽  
Jia Gao ◽  
Rui Hua Xu
Keyword(s):  
Flow Distribution ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Abstract Model ◽  
Flow Volume ◽  
Rail Network ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Flows ◽  
Urban Rail Transit Network

The emergency disposal of urban rail transit needs to accurately estimate the emergency range and total affected passenger flow volume. The urban rail transit network could be simplified to an abstract model which is easy to be analyst based on the graph theory method. Considering the actual network back-turning lines and vehicle storage tracks of urban rail network, the emergency range could be estimated effectively. The affected passenger flow could be classified as different kinds based on the different paths of passenger flow. The classification of passenger flow mainly includes “delay passenger flow”, “detour passenger flow” and “loss passenger flow”. Considering the emergency range, the different affected passenger flows could be superposed over time based on the abstract model, then the affected passenger flow volume and virtual loss time could be calculated out. The results could provide basis for the emergency disposal in urban rail transit. The example analysis is verified the feasibility of this method.

Optimal Train Size and Headway for Urban Rail Transit System

2012 ◽  
Vol 253-255 ◽  
pp. 2020-2023
Author(s):  
Xue Jun Liu ◽  
Chuan Min Mi ◽  
Yuan Yuan Wang ◽  
Wei Vivien Shi
Keyword(s):  
Solution Procedure ◽  
Urban Rail Transit ◽  
Level Of Service ◽  
Load Factor ◽  
Rail Transit ◽  
Total System ◽  
Transit System ◽  
Demand Distribution ◽  
Urban Rail ◽  
Subway System

An analytical model and a solution procedure are proposed to optimize train size and headway for an urban rail transit system wherein passengers demand is assumed to be sensitive to fare and the level of service, in terms of load factor and waiting time. It is found that an optimal temporal headway and train size for different demand distribution that maximizes profit and minimize total system cost for the studied subway system can be efficiently solved.

Short-Time Calculation Method of Passenger Flows on Urban Rail Transit Island Platform

2014 ◽  
Vol 644-650 ◽  
pp. 2133-2136
Author(s):  
Tian Shi Li
Keyword(s):  
Probability Theory ◽  
Calculation Method ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Numerical Examples ◽  
Passenger Flow ◽  
Urban Rail ◽  
Time Calculation ◽  
Passenger Flows ◽  
Short Time

Because urban tail transit becomes the preferred way to travel for more travelers, the passenger flow of rail transit is increasing fast. Due to the increased passenger, the congestion on platform reduces the comfort and puts passengers in danger. This article analyses the model of island platform short-time arrivals based on the probability theory and historical statistics. The calculation method is studied and the Feasibility and algorithm is testified by setting numerical examples.

scholarly journals RANDOM COEFFICIENT MODELING RESEARCH ON SHORT-TERM FORECAST OF PASSENGER FLOW INTO AN URBAN RAIL TRANSIT STATION

Transport ◽  
2016 ◽  
Vol 31 (1) ◽  
pp. 94-99 ◽  
Author(s):  
Xuesong Feng ◽  
Hemeizi Zhang ◽  
Tiantian Gan ◽  
Qipeng Sun ◽  
Fei Ma ◽  
...  
Keyword(s):  
Estimation Procedure ◽  
Random Coefficient ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Short Term ◽  
Metro Station ◽  
Factors Affecting ◽  
Urban Rail ◽  
Passenger Flows ◽  
Transit Station

Taking a representative metro station in Beijing as example, this research has newly developed a random coefficient model to predict the short-term passenger flows with sudden increases sometimes into an urban rail transit station. The hierarchical Bayesian approach is iteratively applied in this work to estimate the new model and the estimation outcomes in each of the iterative calibrations are improved by sequential Bayesian updating. It has been proved that the estimation procedure is able to effectively converge to rational results with satisfying accuracies. In addition, the model application study reveals that besides sufficient preparations in manpower, devices, etc.; the information of the factors affecting the passenger flows into an urban rail transit station should be timely transferred in advance from important buildings, road intersections, squares and so on in neighborhood to this station. In this way, this station is able to cope with the unexpectedly sharp increases of the passenger flows into the station to ensure its operation safety.

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