Route-choice support system for passengers in the face of unexpected disturbance of train operations

Tsuchiya, Ryosuke; Sugiyama, Yoichi; Yamauchi, Kana; Fujinami, Kohei; Arisawa, Riichiro; Nakagawa, Takeshi

doi:10.2495/cr060191

Cited by 17 publications

(12 citation statements)

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“…While the subjects did feel irritation at the trains arriving in the opposite order to what had been predicted, they still rated satisfaction with their own choices highly, and did not give low ratings to the information service. These results are consistent with the result of the previous study which revealed that passengers appreciated being able to make their own decisions even if they had received incorrect prognostic information [3].…”

Section: When the Predicted Information Is Incorrectsupporting

confidence: 83%

Provision of Forecast Train Information and Consequential Impact on Decision Making for Train-choice

Fukasawa¹,

Yamauchi

Murakoshi

et al. 2012

QR of RTRI

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Keywords: train information provision, train choice, passengers' behavioral mode, travel delaytrains, their reasons for choosing them, the level of difficulty in choosing trains, and also passenger reactions to being given information about arrival sequences, which turned out to be incorrect. Providing detailed information about individual trains Attitude to train traffic information in the case of disruptionsPrevious research [1, 2] has already examined and highlighted the specific types of information that passengers need when train operations are disrupted. In order to understand passengers' attitudes to traffic information and choosing trains, and to help decide how best to provide that information, the following survey was conducted: Passengers were asked to consider two ways of thinking, A and B. They were then asked to indicate which best reflected their own way of thinking, on a scale of 1 to 7 (1: very similar to A; 2: similar to A; 3: somewhat similar to A; 4: neutral; 5: somewhat similar to B; 6: similar to B; 7: very similar to B).A: Rather than reading detailed information about the trains, I want to be told exactly which train I should ride. (For example, to arrive quickly at my destination I should take this train; to avoid congestion I should ride that train, etc.) B: I will choose which train to take myself, so I want to be provided with detailed traffic information to enable me to make my own decision.

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Section: When the Predicted Information Is Incorrectsupporting

confidence: 83%

Provision of Forecast Train Information and Consequential Impact on Decision Making for Train-choice

Fukasawa¹,

Yamauchi

Murakoshi

et al. 2012

QR of RTRI

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“…In addition, the travel time is estimated under disruptions before calculating the utility function, as in Tsuchiya et al . [7]. Bouman et al .…”

Section: Literature Reviewmentioning

confidence: 99%

Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network

Yin

Han

et al. 2016

PLoS ONE

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A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0–1 integer programming to describe passengers’ responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated.

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“…Because escalator, staircase, and platform are bottleneck of station [21,28], passengers on the facility are more crowded than those on passages. Passengers have to come to halt because it is too crowded during rush hours.…”

Section: Examplementioning

confidence: 99%

Route Choice in Subway Station during Morning Peak Hours: A Case of Guangzhou Subway

Yao

Wei

et al. 2015

Discrete Dynamics in Nature and Society

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This paper is aimed at crowding phenomenon in the subway. As passengers are inclined to choose the route with minimum disutility, we put forward a route choice model which is constructed to achieve minimum objective function of feasibility for the optimal solution. Meanwhile we set passenger volume threshold values according to capacity of facilities. In the case of actual capacity exceeding the threshold, the decision node of constrained route will be selected; computing procedure about searching decision points will be presented. Then we should set rational restrictions at the decision node of the minimum utility function route to prevent too many passengers' access to platform. Through certification, this series of methods can effectively ensure the safety of the station efficient operation. Hindawi Publishing Corporation

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Route-choice support system for passengers in the face of unexpected disturbance of train operations

Cited by 17 publications

References 0 publications

Provision of Forecast Train Information and Consequential Impact on Decision Making for Train-choice

Provision of Forecast Train Information and Consequential Impact on Decision Making for Train-choice

Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network

Route Choice in Subway Station during Morning Peak Hours: A Case of Guangzhou Subway

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