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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. doi: 10.19818/j.cnki.1671-1637.2019.02.014
Citation: 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. doi: 10.19818/j.cnki.1671-1637.2019.02.014
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Evaluating model of deployment performance of metro emergency rescue vehicles

doi: 10.19818/j.cnki.1671-1637.2019.02.014
  • 1.

    School of Rail Transportation, Soochow University, Suzhou 215131, Jiangsu, China

  • 2.

    Suzhou Industrial Park Surveying, Mapping and Geoinformation Co., Ltd., Suzhou 215027, Jiangsu, China

More Information
  • Author Bio:

    ZHANG Yong (1978-), male, associate professor, PhD, sinkey@126.com

    FU Zi-yan (1993-), female, engineer, 1542533384@qq.com

  • Received Date: 2018-09-05
  • Publish Date: 2019-04-25
    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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