scholarly journals Dynamic Origin-Destination Matrix Estimation Based on Urban Rail Transit AFC Data: Deep Optimization Framework with Forward Passing and Backpropagation Techniques

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yuedi Yang ◽  
Jun Liu ◽  
Pan Shang ◽  
Xinyue Xu ◽  
Xuchao Chen
Keyword(s):  
Travel Demand ◽  
Urban Rail Transit ◽  
Estimation Methods ◽  
Accurate Estimation ◽  
Rail Transit ◽  
Travel Demand Management ◽  
Transit System ◽  
Passenger Flow ◽  
Urban Rail ◽  
Proposed Model

At present, the existing dynamic OD estimation methods in an urban rail transit network still need to be improved in the factors of the time-dependent characteristics of the system and the estimation accuracy of the results. This study focuses on predicting the dynamic OD demand for a time of period in the future for an urban rail transit system. We propose a nonlinear programming model to predict the dynamic OD matrix based on historic automatic fare collection (AFC) data. This model assigns the passenger flow to the hierarchical flow network, which can be calibrated by backpropagation of the first-order gradients and reassignment of the passenger flow with the updated weights between different layers. The proposed model can predict the time-varying OD matrix, the number of passengers departing at each time, and the travel time spent by passengers, of which the results are shown in the case study. Finally, the results indicate that the proposed model can effectively obtain a relatively accurate estimation result. The proposed model can integrate more traffic characteristics than traditional methods and provides an effective and hierarchical passenger flow estimation framework. This study can provide a rich set of passenger demand for advanced transit planning and management applications, for instance, passenger flow control, adaptive travel demand management, and real-time train scheduling.

scholarly journals Holiday Destination Choice Behavior Analysis Based on AFC Data of Urban Rail Transit

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Chang-jun Cai ◽  
En-jian Yao ◽  
Sha-sha Liu ◽  
Yong-sheng Zhang ◽  
Jun Liu
Keyword(s):  
Behavior Analysis ◽  
Choice Behavior ◽  
Travel Demand ◽  
Choice Model ◽  
Urban Rail Transit ◽  
Destination Choice ◽  
Rail Transit ◽  
Transit System ◽  
Passenger Flow ◽  
Urban Rail

For urban rail transit, the spatial distribution of passenger flow in holiday usually differs from weekdays. Holiday destination choice behavior analysis is the key to analyze passengers’ destination choice preference and then obtain the OD (origin-destination) distribution of passenger flow. This paper aims to propose a holiday destination choice model based on AFC (automatic fare collection) data of urban rail transit system, which is highly expected to provide theoretic support to holiday travel demand analysis for urban rail transit. First, based on Guangzhou Metro AFC data collected on New Year’s day, the characteristics of holiday destination choice behavior for urban rail transit passengers is analyzed. Second, holiday destination choice models based on MNL (Multinomial Logit) structure are established for each New Year’s days respectively, which takes into account some novel explanatory variables (such as attractiveness of destination). Then, the proposed models are calibrated with AFC data from Guangzhou Metro using WESML (weighted exogenous sample maximum likelihood) estimation and compared with the base models in which attractiveness of destination is not considered. The results show that theρ2values are improved by 0.060, 0.045, and 0.040 for January 1, January 2, and January 3, respectively, with the consideration of destination attractiveness.

scholarly journals Passengers Flow Forecasting Model of Urban Rail Transit Based on the Macro-Factors

2012 ◽  
Vol 6-7 ◽  
pp. 688-693 ◽  
Author(s):  
Bin Shang ◽  
Xiao Ning Zhang
Keyword(s):  
Real Data ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Estimation Model ◽  
Population Total ◽  
Transit System ◽  
The Real ◽  
Passenger Flow ◽  
Urban Rail ◽  
Multiple Variables

In China, many cities are planning urban rail transit system, but a comprehensive passenger flow estimation model is still lacking. The total passenger flow of urban rail transit in a city depends on many factors, such as urban population, total length of rail lines, gross domestic production of the city etc. To estimate the total passenger flow of urban rail transit, a linear regression model with multiple variables is established in the paper, based on the real data collected in many cities with urban rail transit operating. The comparison of the estimated flow and the real flow in many cities shows that the model is very accurate in passenger flow forecasting.

scholarly journals Optimum Equilibrium Passenger Flow Control Strategies with Delay Penalty Functions under Oversaturated Condition on Urban Rail Transit

2021 ◽  
Vol 2021 ◽  
pp. 1-27
Author(s):  
Yonghao Yin ◽  
Dewei Li ◽  
Kai Zhao ◽  
Ruixia Yang
Keyword(s):  
Flow Control ◽  
Simulated Annealing Algorithm ◽  
Control Strategies ◽  
Penalty Functions ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit System ◽  
Passenger Flow ◽  
Urban Rail ◽  
Linear Delay

When passengers are oversaturated in the urban rail transit system and a further increase of train frequency is impossible, passenger flow control strategy is an indispensable approach to avoid congestion and ensure safety. To make the best use of train capacity and reduce the passenger waiting time, coordinative flow control is necessary at each station on a line. In most published studies, the equilibrium of passenger distributions among different stations and periods is not considered. As a result, two issues occur making it hard to implement in practical. First, a large number of passengers are held up outside a small number of stations for very long time. Second, there is a large variation of controlled flows for successive time intervals. To alleviate this problem, a single-line equilibrium passenger flow control model is constructed, which minimizes the total passenger delay. By applying different forms of the delay penalty function (constant and linear), flow control strategies such as independent flow control and equilibrium flow control can be reproduced. An improved simulated annealing algorithm is proposed to solve the model. A numerical case is studied to analyze the sensitivity of the functions, and the best parameter relationship in different functions could be confirmed. A real-world case from Batong Line corridor in Beijing subway is used to test the applicability of the model and algorithm, and the result shows that the solution with linear delay penalty functions can not only reduce the total passenger delay but also equilibrate the number of flow control passengers on spatial and temporal.

A cooperative evacuation strategy for mass passenger flow in urban rail transit transfer stations

2020 ◽  
pp. 2150007
Author(s):  
Jia Hong-Fei ◽  
Sang Heng ◽  
Luo Qing-Yu ◽  
Yang Jin-Ling ◽  
Miao Hong-Zhi
Keyword(s):  
Real Life ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Nsga Ii ◽  
Transit System ◽  
Passenger Flow ◽  
Evacuation Strategy ◽  
Urban Rail ◽  
The Status ◽  
Transfer Stations

In reviewing the evacuation problem of mass passenger flow in urban rail transit transfer stations, the cooperative evacuation strategy considering urban rail transit and emergency bus simultaneously is found to be an efficient way. In this work, firstly, the dynamic characteristics of mass passenger flow are analyzed based on the abstraction and simplification of major entities of urban rail transit, including passengers, stations and trains. Then, the operations of the urban rail transit system are modeled, including the boarding, landing and transferring processes of the passengers and the status updating flows of the trains and stations. To realize the cooperative evacuation, a multi-objective optimization model considering the evacuation speed, the number of passengers transferred, and the amount of emergency buses is proposed. The NSGA-II algorithm is adopted to solve the proposed model, which can balance the theoretical validity and computational convenience. Last, the proposed strategy is applied in a real-life case based on the Shanghai Metro line, and the results verify its effectiveness and efficiency.

scholarly journals Forecasting Passenger Flow Distribution on Holidays for Urban Rail Transit Based on Destination Choice Behavior Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Enjian Yao ◽  
Junyi Hong ◽  
Long Pan ◽  
Binbin Li ◽  
Yang Yang ◽  
...  
Keyword(s):  
Public Transportation ◽  
Choice Model ◽  
Flow Distribution ◽  
Urban Rail Transit ◽  
Destination Choice ◽  
Rail Transit ◽  
Efficient Operation ◽  
Passenger Flow ◽  
Urban Rail ◽  
Proposed Model

Passenger travel flows of urban rail transit during holidays usually show distinct characteristics different from normal days. To ensure efficient operation management, it is essential to accurately predict the distribution of holiday passenger flow. Based on Automatic Fare Collection (AFC) data, this paper explores the passengers’ destination choice differences between normal days and holidays, as well as one-way tickets and public transportation cards, which provides support for variable selection in modeling. Then, a forecasting model of holiday travel distribution is proposed, in which the destination choice model is established for representing local and nonlocal passengers. Meanwhile, explanatory variables such as land matching degree, scenic spot dummy, and level of service variables are introduced to deal with the particularity of holiday passengers’ travel behavior. The parameters calibrated by the improved weighted exogenous sampling maximum likelihood (WESML) method are applied to predict passenger flow distribution in different holiday cases with annual changes in the metro network, using the data collected from Guangzhou Metro, China. The results show that the proposed model is valid and performs better than the other comparable models in terms of forecasting accuracy. The proposed model has the capability to provide a more universal and accurate passenger flow distribution prediction method for urban rail transit in different holiday scenarios with network changes.

scholarly journals Data-Driven Approaches to Mining Passenger Travel Patterns: “Left-Behinds” in a Congested Urban Rail Transit Network

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Xing Chen ◽  
Leishan Zhou ◽  
Zixi Bai ◽  
Yixiang Yue ◽  
Bin Guo ◽  
...  
Keyword(s):  
Travel Demand ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Travel Patterns ◽  
Train Control ◽  
Left Behind ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Time Parameters

The “left-behind” phenomenon occurs frequently in Urban Rail Transit (URT) networks with booming travel demand, especially during peak hours in a complex URT network, which makes passenger travel patterns more complicated. This paper proposes a methodology to mine passenger travel patterns based on fare transaction records from automatic fare collection (AFC) systems and Automatic Vehicle Location (AVL) data from Communication Based Train Control (CBTC) Systems or tracking systems. By introducing the concept of a sequence, a space-time-sequence trajectory model is proposed to simulate a passenger’s travel activities, including when they are left-behind. The paper analyzes passenger travel trajectory links and estimates the weight of each feasible trajectory under tap-in/tap-out constraints. The station time parameters, including access/egress and transfer walking-time parameters, are important inputs for the model. The paper also presents a maximum-likelihood approach to estimate these parameters from AFC transaction data and AVL data. The methodology is applied to a case study using AFC and AVL data from the Beijing URT network during peak hours to test the proposed model and algorithm. The estimation results are consistent with the results obtained from the authorities, and this finding verifies the feasibility of our approach.

scholarly journals Timetable Optimization of Rail Transit Loop Line with Transfer Coordination

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Rui-Jia Shi ◽  
Bao-Hua Mao ◽  
Yong Ding ◽  
Yun Bai ◽  
Yao Chen
Keyword(s):  
Waiting Time ◽  
Performance Indicators ◽  
Waiting Times ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit System ◽  
Urban Rail ◽  
Proposed Model ◽  
Timetable Optimization

In an urban rail transit system, it is important to coordinate the timetable of a loop line with its connecting lines so as to reduce the waiting time of passengers. This is particularly essential because transfer passengers usually account for the majority of the total passengers in loop lines. In this paper, a timetable optimization model is developed for loop line in order to minimize the average waiting time of access passengers and transfer passengers. This is performed by adjusting the headways and dwell times of trains on the loop line. A genetic algorithm is applied to solve the proposed model, and a numerical example is used to verify its effectiveness. Finally, a case study of a loop line in the Beijing urban rail transit system is conducted. Waiting times of the passengers and the number of waiting passengers are used as performance indicators to verify the optimization results in rush hours and non-rush hours. The results show that the average waiting times for the up-track and down-track are reduced by 3.69% and 2.89% during rush hours and by 11.60% and 11.47% during non-rush hours, respectively.

Urban Rail Transit Operation during World Expo 2010 Shanghai

2012 ◽  
Vol 178-181 ◽  
pp. 1797-1801
Author(s):  
Wei Zhu
Keyword(s):  
Management Practices ◽  
Travel Demand ◽  
Demand Management ◽  
Urban Rail Transit ◽  
Transport Systems ◽  
Rail Transit ◽  
Transit System ◽  
Transportation Demand ◽  
Urban Rail ◽  
Transport Modes

This paper presents the operation practices of Urban Rail Transit during the Word Expo 2010 period in Shanghai. The overall traffic strategy of the Expo and the role of urban rail transit system are first introduced. The focal points of this paper are operation schemes during the Expo, such as train arrangement, passenger flow organization, emergency response, and the coordination with other transport modes. The paper concludes that the Expo travel demand can be met well without sacrificing local urban daily traffic. To have a good linkage with other transport modes as well as the Expo, urban rail transit should play its role in the framework of overall traffic strategy. And in today’s international events, guidance measures including various media are more and more important in the transportation demand management. Practices in Shanghai also show that management of transit stations and information sharing among different public transport systems should be improved.

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