China Safety Science Journal ›› 2022, Vol. 32 ›› Issue (6): 186-192.doi: 10.16265/j.cnki.issn1003-3033.2022.06.2189

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Study on location of medical rescue points in subway stations considering risk of accidents

PAN Hengyan1(), LIANG Tingting2, GAO Zhixiang3, SHEN Weiyu3, WANG Yonggang1,**()   

  1. 1 College of Transportation Engineering, Chang'an University, Xi'an Shaanxi 710064, China
    2 School of Civil Engineering, Xi'an Traffic Engineering Institute,Xi'an Shaanxi 710300, China
    3 School of Traffic and Transportation, Northeast Forestry University, Harbin Heilongjiang 150040, China
  • Received:2022-01-15 Revised:2022-04-16 Online:2022-06-28 Published:2022-12-28
  • Contact: WANG Yonggang

Abstract:

In order to address issues of emergency rescue points under subway station accidents, an evaluation model of station accident risk was established based on TOPSIS method starting from four aspects: passenger flow, equipment, environment, and management. The improved P-median site selection model, which achieved the least total time spent to complete the rescue task, and the improved MCLP site selection model, which maximized the rescue volume per unit time, were established by combining the accident risk level of a subway station, actual rescue demand, rescue point's capacity for emergency rescue, and actual operation of vehicles during the rescue process. The simulated annealing algorithm was applied to obtain the results. The results are as follows: the improved P-median model and the improved MCLP model have more advantages compared with the traditional model. The stations with high accident potential were given priority for rescue considering the station accident risk. The improved MCLP model is preferred when the rescue demand is unknown, while the improved P-median model is preferred when the casualty situation is relatively well understood and the rescue task is clear.

Key words: risk of accidents, medical rescue site, technique for order preference by similarity to an ideal solution(TOPSIS), improved P-median model, maximum covering location problem(MCLP) model