Volume 39 Issue 6
Dec.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(6): 19-26,53
HUANG Min, WU Zhaoju, LI Yetao, WANG Lingli. A Study of Prioritized Routing Strategy of Emergency Vehicles over Small-scale Emergency Scenes[J]. Journal of Transport Information and Safety, 2021, 39(6): 19-26,53. doi: 10.3963/j.jssn.1674-4861.2021.06.003
Citation: HUANG Min, WU Zhaoju, LI Yetao, WANG Lingli. A Study of Prioritized Routing Strategy of Emergency Vehicles over Small-scale Emergency Scenes[J]. Journal of Transport Information and Safety, 2021, 39(6): 19-26,53. doi: 10.3963/j.jssn.1674-4861.2021.06.003
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A Study of Prioritized Routing Strategy of Emergency Vehicles over Small-scale Emergency Scenes

doi: 10.3963/j.jssn.1674-4861.2021.06.003
  • 1.

    School of Intelligent Systems Engineering, Sun Yat-sen University, Guangzhou 510006, China

  • 2.

    Guangdong Provincial Key Laboratory of Intelligent Transportation System, Sun Yat-sen University, Guangzhou 510006, China

  • 3.

    Zhejiang Dahua Technology Co., Ltd., Hangzhou 310051, China

  • Received Date: 2021-08-18
    Available Online: 2022-01-12
    Abstract
  • For small-scale emergency scenes that take place during peak hours, the priority of emergency vehicle may cause traffic delays. And signal strategy to ensure the priority of emergency vehicle affects the reliability of route selection. A priority strategy of emergency vehicles based on a bi-level programming model is proposed, considering the efficiency of emergency vehicles and the delays to the traffic system. Path selection is affected by physical conditions and traffic status. Signal control changes traffic status. The lane group saturation is used as a parameter to characterize the traffic status, and a bi-level programming model for the priority of emergency vehicles is constructed. The upper-level is path selection, which can minimize the travel time of emergency vehicles. The lower level is signal control, which can maximize the social benefit caused by signal control. It is solved by an improved multi-labels algorithm for N-shortest paths problem. The result shows that the travel time of emergency vehicles is increased by 8.7%, but the delays of social vehicles are reduced by 261%. An increase of 1% in the travel time of emergency vehicles leads to a decrease of 30% in delays to the traffic system. This strategy can reduce larger delays to the traffic system at the cost of smaller delays to emergency vehicles.

     

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