China Safety Science Journal ›› 2024, Vol. 34 ›› Issue (7): 178-185.doi: 10.16265/j.cnki.issn1003-3033.2024.07.0153

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Allocation of traffic police resources based on queuing theory

HU Zhenghua1(), ZHOU Jibiao2,3, GUO Xu1, MA Changxi4   

  1. 1 School of Cyber Science and Engineering, Ningbo University of Technology, Ningbo Zhejiang 315211, China
    2 Ningbo Highway Construction & Management Center, Ningbo Zhejiang 315199, China
    3 School of Transportation Engineering, Tongji University, Shanghai 201804, China
    4 School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhou Gansu 730070, China
  • Received:2024-01-15 Revised:2024-04-16 Online:2024-07-28 Published:2025-01-28

Abstract:

To alleviate the contradiction between limited traffic police resources and the untimely handling of road traffic accidents, a traffic police resource optimization allocation approach was proposed based on a queuing theory model under a grid management mode of roads. Firstly, license plate recognition data obtained from the city's road network bayonet system was used to extract historical travel trajectories of vehicles and develop a similarity model between road segments. Secondly, the spectral clustering algorithm was adopted to cluster the road segments and form a set with the highest association between the segments, serving as the result of the road network division. Then, for the real-time traffic accidents within the grid, a queuing theory model was further proposed to calculate the minimum number of police officers required for each grid, along with an optimized allocation scheme for police resources. Finally, the proposed method was validated in Yinzhou District of Ningbo City. The results showed that the proposed optimization method for police allocation reduced the number of police officers by 18.18% and patrol mileage by 10.87% compared to the traditional method of dispatching police officers as soon as an accident occurs. Furthermore, the proposed method increased the accident handling response speed by 10.68%, demonstrating excellent optimization performance.

Key words: queuing theory, traffic police, resource allocation, traffic accidents, grid-based management

CLC Number: