Coordination of last train transfers using automated fare collection (AFC) system data

Li, Wei; Xu, Ruihua; Luo, Qin; Jones, Steven

doi:10.1002/atr.1455

Cited by 16 publications

(11 citation statements)

References 16 publications

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“…e AFCS data has been widely applied in public transit systems for OD demand estimation [12], timetable design [13], passenger flow assignment [14,15], passenger behavior analysis [16], and transfer coordination [17][18][19]. Since passengers swipe the metro card only at the gates of origin and destination stations, detailed information, such as the location where a passenger makes a transfer, is unknown.…”

Section: Literature Reviewmentioning

confidence: 99%

Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach

Xiaoyue

Chien

2020

Journal of Advanced Transportation

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The service quality of public transit, such as comfort and convenience, is an important factor influencing ridership and fare revenue, which also reflects the passengers’ perception to the transit performance. Passengers are frustrated while waiting to board a crowded train especially during the peak hours, while the fail-to-board (FtB) situation commonly exists. The service performance measures determined by deterministic passenger demand and service frequency cannot reflect the perceived service of passengers. With the automatic fare collection system data provided by Chengdu Metro, we develop a data-driven approach considering the joint probability of spatiotemporal passenger demand at stations based on posted train schedule to approximate passenger travel time (e.g., in-vehicle and out-of-vehicle times). It was found that the estimated wait time can reflect the actual situation as passengers FtB. The proposed modeling approach and analysis results would be useful and beneficial for transit providers to improve system performance and service planning.

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Section: Literature Reviewmentioning

confidence: 99%

Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach

Xiaoyue

Chien

2020

Journal of Advanced Transportation

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“…Li. et al [24] considered the last train problem with an objective to maximize the total number of passengers successfully reaching their destination. Chen et al [25] developed a mixed integer programming model to consider the passenger rerouting in the network and multiple transfers in the routes.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The transfer accessibility can thus be approximately calculated as the linear equation (24), as shown in Figure 2. The smaller the time interval is, the more accurate result can be attained.…”

Section: Model (C)mentioning

confidence: 99%

Optimal Coordination of Last Trains for Maximum Transfer Accessibility with Heterogeneous Walking Time

Chen

Mao

Bai

et al. 2019

Journal of Advanced Transportation

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Last train coordination aims to synchronize the arrival and departure times of the last feeder trains and the last connecting trains at transfer stations to improve the transfer accessibility of urban rail networks. This study focuses on the transfer accessibility between last trains with considering heterogeneous transfer walking time. Three mathematical models are developed on the last train timetable optimization. The first model fine-tunes the last train timetable under the given bound of the dwell time. The second one aims to allow the mutual transfers with the prolonged dwell time to maximize the transfer accessibility. A biobjective function is proposed to seek the trade-off between the maximal transfer accessibility and the minimal extension of dwell time. The third model considers the heterogeneity of transfer walking time that is represented as a random variable following a probability distribution. A discrete approximation method is proposed to reformulate the nonlinear model. The embedded Branch & Cut algorithm of CPLEX is applied to solve the models. A real case on the Shenzhen metro network is conducted to demonstrate the performance of the models. The three models all provide better last train timetable than the current timetable in practice. The sensitivity analysis manifests that the third model are always advantageous in the optimization of successful transfer passengers.

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“…On the other hand, the hypothetical O-D demand used in real-life cases may lead to completely different results compared to realistic situations. Li et al 17 applied actual arrivals and O-D pairs from AFC system data as the passenger demand data of last trains, but they didn't consider the potential passenger demand. Thus, it is necessary to study the forecast on potential passenger demand of last trains in the metro.…”

Section: Last Trains Coordinationmentioning

confidence: 99%

A data-driven estimation method for potential passenger demand of last trains in metro based on external traffic data

Luo

2019

Advances in Mechanical Engineering

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The last train problem for metro is especially important because the last trains are the last chances for many passengers to travel by metro; otherwise, they have to choose other traffic modes like taxis or buses. Among the problems, the passenger demand is a vital input condition for the optimization of last train transfers. This study proposes a data-driven estimation method for the potential passenger demand of last trains. Through the geographic information, external traffic data including taxi and bus are first analyzed separately to match the origin–destination passenger flow during the last train period. A solving solution for taxi and bus is then developed to estimate the potential passenger flow for all the transfer directions of the target stations. Combining the estimated potential passenger flow and the actual passenger flow obtained by metro smart card data, the total potential passenger demand of last trains is obtained. The effectiveness of the proposed method is evaluated using a real-world metro network. This research can provide important guidance and act as a technical reference for the metro operations on when to optimize the last train transfers.

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Coordination of last train transfers using automated fare collection (AFC) system data

Cited by 16 publications

References 16 publications

Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach

Estimating Wait Time and Passenger Load in a Saturated Metro Network: A Data-Driven Approach

Optimal Coordination of Last Trains for Maximum Transfer Accessibility with Heterogeneous Walking Time

A data-driven estimation method for potential passenger demand of last trains in metro based on external traffic data

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