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高速列车疫情风险评估与主动防护策略
引用本文:谢国,金永泽,姬文江,黑新宏,马维纲,王丹,陈庞,叶闽英.高速列车疫情风险评估与主动防护策略[J].交通运输工程学报,2020,20(3):110-119.
作者姓名:谢国  金永泽  姬文江  黑新宏  马维纲  王丹  陈庞  叶闽英
作者单位:1.西安理工大学 陕西省复杂系统控制与智能信息处理重点实验室, 陕西 西安 7100482.福井大学 工学研究科, 福井 福井 910-8507
摘    要:考虑到列车密闭车厢内传染病的危害性, 研究了车厢内病毒的空间分布特性; 结合乘客间距离相关性分析结果, 构建了乘客感染预测模型, 对车厢内存在多感染者情况下每个乘客感染病毒的风险进行了评估; 为降低乘客乘车感染风险, 制定了列车乘客主动防护策略, 提出基于贪婪算法和变邻域局部搜索算法的混合启发式算法, 对车厢乘客布座问题进行优化求解; 通过基于距离的贪婪算法, 将列车固定坐标的乘客布座问题转换为最多乘客数最少病毒重叠区问题, 得到座位可行解, 并汇总各可行解得到可行域, 再基于变邻域的局部搜索算法改进座位可行解, 得到最优乘客布座方案。研究结果表明: 本文建立的感染概率评估模型可有效预测乘客感染病毒的风险, 结合基于混合启发式算法的主动防护措施可有效降低乘客乘车的感染风险; 针对短途旅客, 随着乘车人数和车厢内感染者的增加, 高风险感染者由1人增加至7人, 中风险感染者由0人增加至3人, 低风险感染者由47人增加至83人; 相较于无序就坐, 采用本文制定的布座策略可消除乘客感染风险。 

关 键 词:高速列车    感染风险评估    混合启发式算法    主动防护策略    疫情防控    长短途旅客
收稿时间:2020-03-20

Epidemic risk assessment and active protection strategy of high-speed train
XIE Guo,JIN Yong-ze,JI Wen-jiang,HEI Xin-hong,MA Wei-gang,WANG Dan,CHEN Pang,YE Min-ying.Epidemic risk assessment and active protection strategy of high-speed train[J].Journal of Traffic and Transportation Engineering,2020,20(3):110-119.
Authors:XIE Guo  JIN Yong-ze  JI Wen-jiang  HEI Xin-hong  MA Wei-gang  WANG Dan  CHEN Pang  YE Min-ying
Institution:1.Key Laboratory of Shaanxi Province for Complex System Control and Intelligent Information Processing, Xi'an University of Technology, Xi'an 710048, Shaanxi, China2.School of Engineering, University of Fukui, Fukui 910-8507, Fukui, Japan
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. 
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