施工环境下高速公路应急车辆资源配置
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摘要
提出了一种施工环境下的高速公路应急车辆资源配置方法。通过分析高速公路施工区域对高速公路通行能力的影响,构建了施工环境下高速公路路段危险程度计算模型,求解各路段的危险程度;根据现有的高速公路应急资源的配置模型,充分考虑施工区域影响下的路段危险程度、最佳救援时间、资源需求等参数的影响,采用数学规划的方法构建了基于施工区通行能力与历史事故数据的应急资源配置模型,采用粒子群算法求解模型。并以山东高速济青高速段施工区域路段为例进行了应急车辆资源配置。结果表明:在保证各路段资源需求的前提下,应急车辆的资源利用效率最高,实现了施工环境下高速公路应急车辆的合理配置。
A resource allocation method of expressway emergency vehicle under construction environment was proposed.According to the analysis on the influence of construction area on highway capacity,the expressway risk degree calculation model under construction environment was established to get the risk degree of each section. According to the current expressway emergency resource allocation models,the influence of factors such as risk degree,the best rescue time and resource demands in the construction area was fully taken into account; the emergency resource allocation model based on the traffic capacity and historical accident data of the construction area was established and the particle swarm optimization algorithm was used to solve the proposed model. Taking the construction area of Ji'nan-Qinghai section of Shandong expressway as an example,the emergency vehicle resource allocation was carried out. The results show that under the premise of guaranteeing the resource demand of each section,the utilization efficiency of emergency vehicle is the highest,which realizes the reasonable allocation of expressway emergency vehicle under the construction environment.
A resource allocation method of expressway emergency vehicle under construction environment was proposed.According to the analysis on the influence of construction area on highway capacity,the expressway risk degree calculation model under construction environment was established to get the risk degree of each section. According to the current expressway emergency resource allocation models,the influence of factors such as risk degree,the best rescue time and resource demands in the construction area was fully taken into account; the emergency resource allocation model based on the traffic capacity and historical accident data of the construction area was established and the particle swarm optimization algorithm was used to solve the proposed model. Taking the construction area of Ji'nan-Qinghai section of Shandong expressway as an example,the emergency vehicle resource allocation was carried out. The results show that under the premise of guaranteeing the resource demand of each section,the utilization efficiency of emergency vehicle is the highest,which realizes the reasonable allocation of expressway emergency vehicle under the construction environment.
引文
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[2]TUFEKCI S,WALLACE W A.The emerging area of emergency management and engineering[J].IEEE Transactions on Engineering Management,1998,45(2):103-105.
[3]CHU S C K,CHU L.A modeling framework for hospital location and service allocation[J].International Transactions in Operational Research,2000,7(6):539-568.
[4]于英,于慧,田晋跃.公路应急救援系统分析及模型仿真[J].中国安全科学学报,2006,16(7):13-17.YU Ying,YU Hui,TIAN Jinyue.Study on simulation model for highway emergency service system[J].China Safety Science Journal,2006,16(7):13-18.
[5]张子亮.基于GIS的集中式高速公路紧急救援指挥系统研究[D].镇江:江苏大学,2007.ZHANG Ziliang.Study of Centralized Type Freeway Emergency Rescue Command System Based on GIS[D].Zhenjiang:Jiangsu University,2007.
[6]柴干,赵倩,黄琪,等.高速公路交通应急救援资源的配置[J].中国安全科学学报,2010,20(1):165-170.CHAI Gan,ZHAO Qian,HUANG Qi,et al.Allocation of emergency rescue resources for freeway traffic[J].China Safety Science Journal,2010,20(1):165-170.
[7]范宝文,向红艳.山区高速公路路段危险度计算模型[J].长沙理工大学学报(自然科学版),2013,10(3):39-43.FAN Baowen,XIANG Hongyan.Calculation model of mountainous highway risk[J].Journal of Changsha University of Science&Technology(Natural Science),2013,10(3):39-43.
[8]陈旭哲.高速公路应急车辆资源需求预测与配置[D].北京:北京交通大学,2014.CHEN Xuzhe.Study on Demand Forecasting and Allocation of Expressway Emergency Vehicle Resource[D].Beijing:Beijing Jiaotong University,2014.
[9]杨惠敏,陈雨人,方守恩,等.高速公路交通事故救援时间与生存率关系模型研究[J].交通信息与安全,2015,33(4):82-86.YANG Huimin,CHEN Yuren,FANG Shouen,et al.A study of the relationship between rescue time and survival rate of traffic accidents on freeways using acox regression model[J].Journal of Transport Information and Safety,2015,33(4):82-86.