scholarly journals Research on Passenger Flow Assignment of High-Speed Trains Based on Personalized Itinerary Choice

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jinzi Zheng
Keyword(s):  
High Speed ◽  
Ticket Sale ◽  
Passenger Flow ◽  
Assignment Method ◽  
Assignment Model ◽  
Proposed Model ◽  
Flow Assignment ◽  
High Speed Trains ◽  
Time Minimization ◽  
Passenger Flow Assignment

Under the condition that ticket fare for high-speed train could fluctuate around a benchmark price in China, aimed at predicting how the passengers will distribute among different trains given a ticket fare, the passenger flow assignment method for high-speed trains is studied. Different from the classical researches on the passenger flow assignment, by introducing a variable that represents the value of time, this research allows passengers to make their personalized choice between the principles of time minimization and expense minimization, so as to demonstrate how the passengers holding different time values respond to each ticket fare scheme. An equilibrium passenger flow assignment model based on personalized choice is built and an improved Monte-Carlo random simulation algorithm is designed for solving the model. The actual ticket sale data for Beijing-Shanghai high-speed railway are used to verify the feasibility of the proposed model and algorithm. The passenger flow assignment results under various fare schemes show how the distribution of passenger flow changes with the adjustment of ticket fare.

scholarly journals Operational Impacts of Using Restricted Passenger Flow Assignment in High-Speed Train Stop Scheduling Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Huiling Fu ◽  
Benjamin R. Sperry ◽  
Lei Nie
Keyword(s):  
High Speed ◽  
Impact Analysis ◽  
Stochastic Approach ◽  
High Speed Rail ◽  
Rail Network ◽  
Passenger Flow ◽  
Travel Path ◽  
Flow Assignment ◽  
Passenger Flow Assignment ◽  
Low Efficiency

One key decision basis to the train stop scheduling process is the passenger flow assignment, that is, the estimated passengers’ travel path choices from origins to destinations. Many existing assignment approaches are stochastic in nature, which causes unbalanced problems such as low efficiency in train capacity occupancy or an irrational distribution of transfer passengers among stations. The purpose of this paper is to propose a train stop scheduling approach. It combines a passenger flow assignment procedure that routes passenger travel paths freely within a train network and is particularly capable of incorporating additional restrictions on generating travel paths that better resemble the rail planner’s purpose of utilizing capacity resources by introducing four criteria to define the feasibility of travel path used by a traveler. Our approach also aims at ensuring connectivity and rapidity, the two essential characteristics of train service increasingly required by modern high-speed rails. The effectiveness of our approach is tested using the Chinese high-speed rail network as a real-world example. It works well in finding a train stop schedule of good quality whose operational indicators dominate those of an existing stochastic approach. The paper concludes with a comprehensive operational impact analysis, further demonstrating the value of our proposed approach.

scholarly journals An Enhanced Dynamic User Optimal Passenger Flow Assignment Model for Metro Networks

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Hanchuan Pan ◽  
Zhigang Liu ◽  
Hua Hu
Keyword(s):  
Choice Behavior ◽  
Route Choice ◽  
Urban Rail Transit ◽  
Passenger Flow ◽  
Route Choice Behavior ◽  
Assignment Model ◽  
Flow Assignment ◽  
Train Operation ◽  
Metro Networks ◽  
Passenger Flow Assignment

By considering the difference between a car driver’s route choice behavior on the road and a passenger’s route choice behavior in urban rail transit (URT), this paper proposes an enhanced Dynamic User Optimal (DUO) passenger flow assignment model for metro networks. To capture realistic URT phenomena, the model has integrated the train operation disturbance constraint. Real passenger and train data are used to verify the proposed model and algorithm. The results indicate that the DUO-based model is more suitable for describing passenger route choice behavior under uncertain conditions compared to a static model. Moreover, this paper found that passengers under oversaturated conditions are more sensitive to train operation disturbances compared to undersaturated passengers.

scholarly journals A Method to Estimate URT Passenger Spatial-Temporal Trajectory with Smart Card Data and Train Schedules

2020 ◽  
Vol 12 (6) ◽  
pp. 2574
Author(s):  
Taoyuan Yang ◽  
Peng Zhao ◽  
Xiangming Yao
Keyword(s):  
Urban Rail Transit ◽  
Passenger Flow ◽  
Precise Estimation ◽  
Smart Card Data ◽  
Urban Rail ◽  
Flow Assignment ◽  
The Difference ◽  
Passenger Flow Assignment ◽  
Temporal Trajectory ◽  
Beijing Subway

Precise estimation of passenger spatial-temporal trajectory is the basis for urban rail transit (URT) passenger flow assignment and ticket fare clearing. Inspired by the correlation between passenger tap-in/out time and train schedules, we present a method to estimate URT passenger spatial-temporal trajectory. First, we classify passengers into four types according to the number of their routes and transfers. Subsequently, based on the characteristic that passengers tap-out in batches at each station, the K-means algorithm is used to assign passengers to trains. Then, we acquire passenger access, egress, and transfer time distribution, which are used to give a probability estimation of passenger trajectories. Finally, in a multi-route case of the Beijing Subway, this method presents an estimation result with 91.2% of the passengers choosing the same route in two consecutive days, and the difference of route choice ratio in these two days is 3.8%. Our method has high accuracy and provides a new method for passenger microcosmic behavior research.

scholarly journals A Hybrid Short-Term Forecasting Model of Passenger Flow on High-Speed Rail considering the Impact of Train Service Frequency

2017 ◽  
Vol 2017 ◽  
pp. 1-9 ◽  
Author(s):  
Qingying Lai ◽  
Jun Liu ◽  
Yongji Luo ◽  
Minshu Ma
Keyword(s):  
Hybrid Model ◽  
Traffic Management ◽  
High Speed ◽  
Short Term ◽  
High Speed Rail ◽  
Passenger Flow ◽  
Proposed Model ◽  
Service Frequency ◽  
Short Term Forecasting ◽  
The Impact

Short-term forecasting of OD (origin to destination) passenger flow on high-speed rail (HSR) is one of the critical tasks in rail traffic management. This paper proposes a hybrid model to explore the impact of the train service frequency (TSF) of the HSR on the passenger flow. The model is composed of two parts. One is the Holt-Winters model, which takes advantage of time series characteristics of passenger flow. The other part considers the changes of TSF for the OD in different time during a day. The two models are integrated by the minimum absolute value method to generate the final hybrid model. The operational data of Beijing-Shanghai high-speed railway from 2012 to 2016 are used to verify the effectiveness of the model. In addition to the forecasting ability, with a definite formation, the proposed model can be further used to forecast the effects of the TSF.

Research on the Modeling Methods of the Service Network Meeting the Requirements of Passenger Flow Assignment in Urban Rail Transit

2013 ◽  
Vol 779-780 ◽  
pp. 815-820
Author(s):  
Jian Yu ◽  
Xing Chen Zhang ◽  
Bin Xu
Keyword(s):  
Urban Rail Transit ◽  
Service Networks ◽  
Service Network ◽  
Passenger Flow ◽  
Construction Methods ◽  
Network Meeting ◽  
Urban Rail ◽  
Flow Assignment ◽  
Passenger Flow Assignment ◽  
Network Type

The conceptual introduction of the service network and its function in passenger flow assignment are given. Based on the summary of the related research results, the service networks are divided into two classes as the matrix type and the network type according to the different construction methods. The modeling principles and methods of the network type service network are then proposed. The methods are explained in three aspects including node modeling, segment (or arc) modeling, and partial network modeling, which can, for a certain physical network and a certain line plan, construct the virtual service network that is required by the passenger flow assignment process. Corresponding modifications are required when using these methods in specific researches.

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