| 地铁应急救援车辆配置绩效评估模型 |
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| 引用本文： | 张勇,伏紫妍.地铁应急救援车辆配置绩效评估模型[J].交通运输工程学报,2019,19(2):156-166. |
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| 作者姓名： | 张勇 伏紫妍 |
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| 作者单位： | 1.苏州大学 轨道交通学院, 江苏 苏州 2151312.苏州工业园区测绘地理信息有限公司, 江苏 苏州 215027 |
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| 基金项目： | 国家自然科学基金项目51778386国家社科基金重大项目13 & ZD175 |
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| 摘 要： | 分析了地铁应急救援车辆对地铁灾害事故实施救援的排队过程, 定义了救援车辆响应地铁灾害事故的状态空间, 基于随机生灭过程理论建立了救援车辆的联合排队模型, 得到救援状态平衡方程; 为了减小平衡方程求解的运算量与存储空间, 提出了基于稀疏矩阵压缩的联合排队状态概率改进求解算法, 给出了包括救援响应时间、救援车辆工作强度、跨区救援概率等地铁救援系统各项绩效评价指标计算方法; 为了验证模型与求解算法, 以实际的地铁线网为例, 研究了路轨两用救援车、履带式救援车和便携式救援车的性能指标。计算结果表明: 算法迭代7次以后, 收敛精度数量级达到了10-8; 路轨两用救援车、履带式救援车和便携式救援车的平均响应时间分别约为14、20、10 min; 路轨两用救援车、履带式救援车跨区救援概率分别约为0.85、0.75, 便携式救援车跨区救援概率数量级为10-5; 在各小区接收外部救援车方面, 路轨两用救援车和履带式救援车跨区救援概率约为0.7, 而便携式救援车跨区救援概率的数量级约为10-6; 在救援强度的均衡性方面, 路轨两用救援车、履带式救援车和便携式救援车依次降低。
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| 关 键 词： | 地铁应急救援 联合排队模型 救援概率 救援车辆配置 便携式救援车 |
| 收稿时间： | 2018-09-05 |
Evaluating model of deployment performance of metro emergency rescue vehicles |
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| ZHANG Yong,FU Zi-yan.Evaluating model of deployment performance of metro emergency rescue vehicles[J].Journal of Traffic and Transportation Engineering,2019,19(2):156-166. |
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| Authors: | ZHANG Yong FU Zi-yan |
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| Affiliation: | 1.School of Rail Transportation, Soochow University, Suzhou 215131, Jiangsu, China2.Suzhou Industrial Park Surveying, Mapping and Geoinformation Co., Ltd., Suzhou 215027, Jiangsu, China |
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| Abstract: | The rescue operation queue process of metro emergency rescue vehicles (MERVs) responding to metro disasters was analyzed. By defining the state space of MERVs in response to metro disasters, the joint queuing model of MERVs' rescue states was established based on the random birth-death process theory and obtained balance equations. In order to reduce the computation amount and storage space of balance equations, an improved solving algorithm of joint queuing state probability based on the sparse matrix compression was developed. The calculation methods of various performance evaluation indexes of metro rescue system, including the rescue response time, MERVs working intensity and cross-district rescue probability, were given. In order to verify the model and algorithm, the actual metro network was taken as an example, and the performance indexes of three types of MERVs, including the road-rail rescue vehicle, crawler rescue vehicle and portable rescue vehicle, were studied. Calculation result shows that the magnitude of convergence precision reaches 10-8 after the algorithm iterates 7 times. The average response times of road-rail rescue vehicle, crawler rescue vehicle and portable rescue vehicle are about 14, 20 and 10 min, respectively. The cross-district rescue probabilities of road-rail rescue vehicle and crawler rescue vehicle are about 0.85 and 0.75, respectively, and the magnitude of portable rescue vehicle is 10-5. For the regions receiving external rescues, the rescue probabilities of road-rail rescue vehicle and crawler rescue vehicle both are about 0.7, while the magnitude of portable rescue vehicle is about 10-6. For the balance of rescue intensity, they are sequentially decline the road-rail rescue vehicle, crawler rescue vehicle and portable rescue vehicle. |
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