Estimating Distributions of Walking Speed, Walking Distance, and Waiting Time with Automated Fare Collection Data for Rail Transit

2017 ◽  
Vol 2648 (1) ◽  
pp. 134-141 ◽  
Author(s):  
Xiaoyan Xie ◽  
Fabien Leurent
Keyword(s):  
Stochastic Model ◽  
Travel Time ◽  
Waiting Time ◽  
Walking Speed ◽  
Urban Rail Transit ◽  
Walking Distance ◽  
Rail Transit ◽  
Journey Time ◽  
Urban Rail ◽  
Collection Data

Journey time is one of the key factors of public transport quality of service that is of concern to passengers. The variability in passenger journey time stems from the variability of in-vehicle travel time, walking time, and waiting time. A better understanding of passenger walking and waiting behavior along an urban rail transit line, especially in mass transit hubs and stations, is thus of much relevance. However, the estimation of passengers’ walking speed, walking distance, and waiting time is still a complicated and difficult task: individual walking speed and waiting time keep changing throughout the interindividual journey. A novel stochastic model that uses automated fare collection data and automatic vehicle location data is proposed to estimate the distributions of walking speed, walking distance, and waiting time indirectly. The stochastic model relates tap-out time to tap-in time on an individual basis and with respect to train circulation on the basis of statistical distributions for the individual’s cruise walking speed, in-station walking distance, and waiting time. Analytical formulas are provided, first conditional to an individual walking speed and waiting time and then without conditions. The model is applied to the maximum likelihood estimate (MLE) of the parameters with constrained numerical optimization. A case study of the urban rail transit line Réseau Express Régional [Regional Express Network (RER)] A in the Paris region yielded reasonable parameter values and factor mean values. This study paves the way for estimating passenger elementary travel time along a journey.

scholarly journals Stop Plan of Express and Local Train for Regional Rail Transit Line

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Qin Luo ◽  
Yufei Hou ◽  
Wei Li ◽  
Xiongfei Zhang
Keyword(s):  
Energy Consumption ◽  
Travel Time ◽  
Programming Model ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Long Distance ◽  
Passenger Travel ◽  
Urban Rail ◽  
Proposed Model ◽  
Rail Line

The urban rail transit line operating in the express and local train mode can solve the problem of disequilibrium passenger flow and space and meet the rapid arrival demand of long-distance passengers. In this paper, the Logit model is used to analyze the behavior of passengers choosing trains by considering the sensitivity of travel time and travel distance. Then, based on the composition of passenger travel time, an integer programming model for train stop scheme, aimed at minimizing the total passenger travel time, is proposed. Finally, combined with a certain regional rail line in Shenzhen, the plan is solved by genetic algorithm and evaluated through the time benefit, carrying capacity, and energy consumption efficiency. The simulation result shows that although the capacity is reduced by 6 trains, the optimized travel time per person is 10.34 min, and the energy consumption is saved by about 16%, which proves that the proposed model is efficient and feasible.

scholarly journals First Train Timetabling for Urban Rail Transit Networks with Maximum Passenger Transfer Satisfaction

2020 ◽  
Vol 12 (10) ◽  
pp. 4166 ◽  
Author(s):  
Xuan Li ◽  
Toshiyuki Yamamoto ◽  
Tao Yan ◽  
Lili Lu ◽  
Xiaofei Ye
Keyword(s):  
Waiting Time ◽  
Stated Preference ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Transit Network ◽  
Transit Networks ◽  
Bee Colony ◽  
Passenger Satisfaction ◽  
Urban Rail ◽  
Urban Rail Transit Network

This paper proposes a novel model to optimize the first train timetables for urban rail transit networks, with the goal of maximizing passengers’ transfer waiting time satisfaction. To build up the relationship of transfer waiting time and passenger satisfaction, a reference-based piecewise function is formulated with the consideration of passengers’ expectations, tolerances and dissatisfaction on “just miss”. In order to determine the parameters of zero waiting satisfaction rating, the most comfortable waiting time, and the maximum tolerable waiting time in time satisfaction function, a stated preference survey is conducted in rail transit transfer stations in Shanghai. An artificial bee colony algorithm is developed to solve the timetabling model. Through a real-world case study on Shanghai’s urban rail transit network and comparison with the results of minimizing the total transfer time, we demonstrate that our approach performs better in decreasing extremely long wait and “just miss” events and increasing the number of passengers with a relatively comfortable waiting time in [31s, 5min). Finally, four practical suggestions are proposed for urban rail transit network operations.

Study of the Influencing Factors of Urban Rail Transit Travel Behavior: A Case Study of Xi'an

2015 ◽  
Vol 744-746 ◽  
pp. 2049-2052
Author(s):  
Yao Wu ◽  
Jian Lu ◽  
Yue Chen
Keyword(s):  
Travel Time ◽  
Influencing Factors ◽  
Travel Behavior ◽  
Family Income ◽  
Binary Logistic Regression ◽  
Travel Distance ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Binary Logistic Regression Model ◽  
Urban Rail

In order to study the factors influencing urban rail transit travel behavior, a questionnaire was conducted for residents’ selection of rail transit in Xi'an. Based on the collected data from 1105 valid questionnaires, a binary logistic regression model was established to analyze the influencing factors quantitatively. The results showed that seven factors have statistically significant for rail transit travel behavior including age, occupation, family income, average monthly household transportation costs (T-cost), travel purpose, travel distance, and travel time. Odds ratio analysis revealed that young people and staff were more likely to choose rail transit; the probability of selecting rail transit increased with the increase of family income and the T-cost. In addition, more and more people tend to rail travel with the increase of travel distance and travel time.

The Optimization of Arriving and Departing Time of Trains in Urban Rail Transit Based on Passenger Transfer

2014 ◽  
Vol 587-589 ◽  
pp. 1958-1962
Author(s):  
Jie Ping Sun
Keyword(s):  
Travel Time ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Operation Process ◽  
Urban Rail ◽  
Practical Operation ◽  
Time Extension ◽  
Transfer Stations ◽  
Important Significance ◽  
Beijing Subway

In this paper, there is a study on the effect of the lack of coordination between trains in the network, such as waiting aggravation, travel time extension. Through the study of the practical operation process and passenger transfer characteristics of urban rail transit, according to the types of line crossing, taking the minimized waiting time of all transfer passengers in station as the object function, the optimization model was designed for three lines with two intersections, solve the model by using the Lingo, and transfer stations, Xidan and Dongdan station, from lines No.1 No.4 and No.5 of Beijing Subway Network are chosen as an example to validate its rationality and availability. The result shows that the model is of important significance to reduce the travel time for transfer passengers.

scholarly journals Application of Regenerative Braking with Optimized Speed Profiles for Sustainable Train Operation

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Leon Allen ◽  
Steven Chien
Keyword(s):  
Energy Saving ◽  
Travel Time ◽  
Transmission Lines ◽  
Urban Rail Transit ◽  
Regenerative Braking ◽  
Rail Transit ◽  
Time Step ◽  
Urban Rail ◽  
Train Operation ◽  
Storage Limit

This paper presents a method for synergizing the energy-saving strategies of integrated coasting and regenerative braking in urban rail transit operations. Coasting saves energy by maintaining motion with propulsion disabled, but it induces longer travel time. Regenerative braking captures and reuses the braking energy of the train and could shorten travel time but reduces the time available for coasting, indicating a tradeoff between the two strategies. A simulation model was developed based on fundamental kinematic equations for assessing sustainable train operation with Wayside Energy-Saving Systems (WESSs). The objective of this study is to optimize speed profiles that minimize energy consumption, considering the train schedule and specifications, track alignment, speed limit, and the WESS parameters such as storage limit and energy losses in the transmission lines. The decision variables are the acceleration at each time step of the respective motion regimes. Since the study optimization problem is combinatorial, a Genetic Algorithm was developed to search for the solution. A case study was conducted which examined various scenarios with and without WESS on a segment of an urban rail transit line to test the applicability of the proposed model and to provide a platform for the application of ideas developed in this study. It was determined that synergizing the energy-saving strategies of coasting and regenerative braking yielded the greatest efficiency of the scenarios examined.

Disruption Management in Urban Rail Transit System

2018 ◽  
pp. 18-48
Author(s):  
Erfan Hassannayebi ◽  
Arman Sajedinejad ◽  
Soheil Mardani
Keyword(s):  
Waiting Time ◽  
Recovery Time ◽  
Control Strategies ◽  
Discrete Event ◽  
Urban Rail Transit ◽  
Disruption Management ◽  
Rail Transit ◽  
Transit Systems ◽  
Urban Rail ◽  
Proposed Model

The process of disruption management in rail transit systems faces challenging issues such as the unpredictable occurrence time, the consequences and the uncertain duration of disturbance or recovery time. The objective of this chapter is to adopt a discrete-event object-oriented simulation system, which applies the optimization algorithms in order to compensate the system performance after disruption. A line blockage disruption is investigated. The uncertainty associated with blockage recovery time is considered with several probabilistic scenarios. The disruption management model presented here combines short-turning and station-skipping control strategies with the objective to decrease the average passengers' waiting time. A variable neighborhood search (VNS) algorithm is proposed to minimize the average waiting time. The computational experiments on real instances derived from Tehran Metropolitan Railway are applied in the proposed model and the advantages of the implementing the optimized single and combined short-turning and stop-skipping strategies are listed.

scholarly journals Estimation Method of Path-Selecting Proportion for Urban Rail Transit Based on AFC Data

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Feng Zhou ◽  
Jun-gang Shi ◽  
Rui-hua Xu
Keyword(s):  
Travel Time ◽  
Estimation Method ◽  
Urban Rail Transit ◽  
Rail Transit ◽  
Time Data ◽  
Travel Time Data ◽  
Urban Rail ◽  
Distribution Parameters ◽  
The Cost ◽  
Walking Time

With the successful application of automatic fare collection (AFC) system in urban rail transit (URT), the information of passengers’ travel time is recorded, which provides the possibility to analyze passengers’ path-selecting by AFC data. In this paper, the distribution characteristics of the components of travel time were analyzed, and an estimation method of path-selecting proportion was proposed. This method made use of single path ODs’ travel time data from AFC system to estimate the distribution parameters of the components of travel time, mainly including entry walking time (ewt), exit walking time (exwt), and transfer walking time (twt). Then, for multipath ODs, the distribution of each path’s travel time could be calculated under the condition of its components’ distributions known. After that, each path’s path-selecting proportion can be estimated. Finally, simulation experiments were designed to verify the estimation method, and the results show that the error rate is less than 2%. Compared with the traditional models of flow assignment, the estimation method can reduce the cost of artificial survey significantly and provide a new way to calculate the path-selecting proportion for URT.

scholarly journals A Timetable Optimization Model for Urban Rail Transit with Express/Local Mode

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Renjie Zhang ◽  
Shisong Yin ◽  
Mao Ye ◽  
Zhiqiang Yang ◽  
Shanglu He
Keyword(s):  
Waiting Time ◽  
Optimization Model ◽  
Urban Rail Transit ◽  
Local Mode ◽  
Rail Transit ◽  
Long Distance ◽  
Urban Rail ◽  
Proposed Model ◽  
Distance Travel ◽  
Timetable Optimization

Nowadays, an express/local mode has be studied and applied in the operation of urban rail transit, and it has been proved to be beneficial for the long-distance travel. The optimization of train patterns and timetables is vital in the application of the express/local mode. The former one has been widely discussed in the various existing works, while the study on the timetable optimization is limited. In this study, a timetable optimization model is proposed by minimizing the total passenger waiting time at platforms. Further, a genetic algorithm is used to solve the minimization problems in the model. This study uses the data collected from Guangzhou Metro Line 14 and finds that the total passenger waiting time at platforms is reduced by 9.3%. The results indicate that the proposed model can reduce the passenger waiting time and improve passenger service compared with the traditional timetable.

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