2022
DOI: 10.1007/s40864-022-00170-1
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Research on Rail Transit Dispatcher Emergency Decision Support Based on Case Similarity Matching

Abstract: To alleviate decision-making pressure on rail transit dispatchers in the emergency handling process, this work sorts out the scenario elements of rail transit emergency cases, establishes a scenario element system, and uses the information weight method to determine the weight of each scenario element. Based on the information of the key decision points, the complete process of emergencies is divided into various scenarios, and an emergency case representation model is constructed. The model establishes a data… Show more

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Cited by 5 publications
(2 citation statements)
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References 31 publications
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“…Wang S C et al significantly improved the detection method of railway foreign body intrusion by using the YOLO v3 network and improved the operational efficiency of railway detection [1]; Huang Tao et al applied machine vision technology to the speed measurement and positioning system of urban rail transit, and its efficiency was significantly higher than the existing equipment [2]; Cheng S et al loaded the inertial navigation system and global navigation satellite system onto the train motion model and conducted simulation experiments [3]; Liu X K et al proposed a fiber optic positioning speed measurement system, which uses fiber Bragg grating sensors to locate and measure train speed [4].The above methods have the advantages of high positioning accuracy, but the disadvantages are high cost and difficult implementation. This paper proposes a high-speed maglev positioning system based on image recognition, which uses deep learning technology to locate the train and can directly locate the train through the monitoring system on both sides of the track.…”
Section: Introductionmentioning
confidence: 99%
“…Wang S C et al significantly improved the detection method of railway foreign body intrusion by using the YOLO v3 network and improved the operational efficiency of railway detection [1]; Huang Tao et al applied machine vision technology to the speed measurement and positioning system of urban rail transit, and its efficiency was significantly higher than the existing equipment [2]; Cheng S et al loaded the inertial navigation system and global navigation satellite system onto the train motion model and conducted simulation experiments [3]; Liu X K et al proposed a fiber optic positioning speed measurement system, which uses fiber Bragg grating sensors to locate and measure train speed [4].The above methods have the advantages of high positioning accuracy, but the disadvantages are high cost and difficult implementation. This paper proposes a high-speed maglev positioning system based on image recognition, which uses deep learning technology to locate the train and can directly locate the train through the monitoring system on both sides of the track.…”
Section: Introductionmentioning
confidence: 99%
“…Subway stations have also begun to adopt facilities and equipment such as intelligent lighting, intelligent security, intelligent comfort service, intelligent entertainment system, and intelligent passenger flow statistics and analysis. Through the use of various facilities, passengers can share and exchange information with the subway operation and dispatch center [1][2][3][4][5][6] . At present, many cities in China have begun the construction of smart transportation systems in urban rail transit networks.…”
Section: Introductionmentioning
confidence: 99%