An ALNS-based approach for the traffic-police-routine-patrol-vehicle assignment problem in resource allocation analysis of traffic crashes

Abstract

Objectives

Imbalances between limited police resource allocations and the timely handling of road traffic crashes are prevalent. To optimize resource allocations and route choices for traffic police routine patrol vehicle (RPV) assignments, a dynamic crash handling response model was developed.

Methods

This approach was characterized by two objective functions: the minimum waiting time and the minimum number of RPVs. In particular, an adaptive large neighborhood search (ALNS) was designed to solve the model. Then, the proposed ALNS-based approach was examined using comprehensive traffic and crash data from Ningbo, China.

Results

Finally, a sensitivity analysis was conducted to evaluate the bi-objective of the proposed model and simultaneously demonstrate the efficiency of the obtained solutions. Two resolution methods, the global static resolution mode, and real-time dynamic resolution mode, were applied to explore the optimal solution.

Conclusions

The results show that the optimal allocation scheme for traffic police is 13 RPVs based on the global static resolution mode. Specifically, the average waiting time for traffic crash handling can be reduced to 5.5 min, with 53.8% less than 5.0 min and 90.0% less than 10.0 min.

Keywords:

• Traffic safety
• traffic crash
• routine patrol vehicles (RPVs;), adaptive large neighborhood search (ALNS;), traffic police

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was supported by National Natural Science Foundation of China (No. 52002282), Basic Public Welfare Research Project of Zhejiang Province (LGF20F030004). Also, we are grateful to thank Dr. Jiyan Wu from Tongji University and Dr. Xinhua Mao from Chang’an University for their contributions to the problem description and solving algorithms.