|Table of Contents|

Epidemic risk assessment and active protection strategy of high-speed train(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2020年03期
Page:
110-119
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Epidemic risk assessment and active protection strategy of high-speed train
Author(s):
XIE Guo1;  JIN Yong-ze1;  JI Wen-jiang1;  HEI Xin-hong1;  MA Wei-gang1;  WANG Dan1;  CHEN Pang1;  YE Min-ying2
(1. Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an 710048, Shaanxi, China; 2. School of Engineering, University of Fukui, Fukui 910-8507, Fukui, Japan)
Keywords:
high-speed train;  infection risk assessment;  hybrid heuristic algorithm;  active protection strategy;  epidemic prevention and control;  long- and short-distance passenger
PACS:
U293.1
DOI:
10.19818/j.cnki.1671-1637.2020.03.010
Abstract:
Considering the danger of infectious disease in closed train compartment, the spatial distribution characteristics of the virus were studied. Combined with the correlation analysis result of the distances between passengers, the infection prediction model of passenger was constructed, and the risk of each passenger infected with virus in the case of existing multiple infections was evaluated. In order to reduce the infected risk of passenger, the active protection strategies for train passengers were formulated, and a hybrid heuristic algorithm based on greedy algorithm and variable neighborhood local search algorithm was proposed to optimize and solve the passenger seat arrangement problem. Through the distance-based greedy algorithm, the arrangement of passenger seats in the fixed coordinate was converted into the problem of the maximum number of passengers and the minimum number of virus overlapping areas, and the feasible solution of the seat was obtained. The feasible region was obtained by summing up the feasible solutions, the feasible solution of the seats was improved based on variable neighborhood local search algorithm, and the optimal scheme of seat arrangement was obtained. Research result shows that the risk of passengers infected with virus can be predicted effectively by the infection probability evaluation model, and the infection risk of passengers can be reduced effectively by the active protection measures combined with the hybrid heuristic algorithm. For the short-distance passengers, with the increase of the number of passengers and the number of people infected in the compartments, the number of people with high risk infection increases from 1 to 7, the number of people with medium risk infection increases from 0 to 3, and the number of people with low risk of infection increases from 47 to 83. Compared with the disordered sitting without control, the risk of passenger infection can be eliminated by the seat arrangement strategy. 4 tabs, 7 figs, 30 refs.

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Last Update: 2020-07-10