2019
DOI: 10.3390/sym11060780
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A Time-Space Network Model Based on a Train Diagram for Predicting and Controlling the Traffic Congestion in a Station Caused by an Emergency

Abstract: Timely predicting and controlling the traffic congestion in a station caused by an emergency is an important task in railway emergency management. However, traffic forecasting in an emergency is subject to a dynamic service network, with uncertainty surrounding elements such as the capacity of the transport network, schedules, and plans. Accurate traffic forecasting is difficult. This paper proposes a practical time-space network model based on a train diagram for predicting and controlling the traffic congest… Show more

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Cited by 7 publications
(7 citation statements)
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“…This is confirmed by a number of publications, for example, [34][35][36][37]. It has been proven that the synergistic effect of a large LS, which is characteristic, for example, of logistics centers, is a consequence of the centralization and concentration of operations of an informational and analytical nature [18]. However, there are very few works where such an effect was reflected in models and was reproduced under different flow conditions and external disturbances.…”
Section: Analysis and Arrangement Of Information Flowsmentioning
confidence: 58%
See 1 more Smart Citation
“…This is confirmed by a number of publications, for example, [34][35][36][37]. It has been proven that the synergistic effect of a large LS, which is characteristic, for example, of logistics centers, is a consequence of the centralization and concentration of operations of an informational and analytical nature [18]. However, there are very few works where such an effect was reflected in models and was reproduced under different flow conditions and external disturbances.…”
Section: Analysis and Arrangement Of Information Flowsmentioning
confidence: 58%
“…Ukrainian carriers, for example, are trying to reduce the useless mileage of trucks. Carriers use various information systems for forecasting demand, planning the schedule of individual crews [18][19][20]. However, the information service will not work if it does not have a functional connection with cargo flows.…”
Section: Chaptermentioning
confidence: 99%
“…Additionally, Qu and He used the spatiotemporal network model to predict and control station traffic congestion caused by emergencies. At the same time, they also verified the feasibility of the model [22]. Kang et al conducted many long-term studies on the mechanism of how the temporal and spatial characteristics of traffic accidents for the elderly in Seoul change over time [23].…”
Section: Introductionmentioning
confidence: 75%
“…Hetrakul and Cirillo [27,28] first formulated latent class and mixed logit models by internet booking data to analyze railway passenger choice behavior, then proposed a joint optimization model for pricing and seat allocation with the assumption of deterministic demand. All studies of railway revenue management are based on prepared line planning [29], train diagrams [30], and timetables [31]. However, group reservations were not considered in the above literature.…”
Section: Literature Reviewmentioning
confidence: 99%