Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots
Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots
- New search for: Siliang Luan
- New search for: Qingfang Yang
- New search for: Wei Wang
- New search for: Zhongtai Jiang
- New search for: Ruru Xing
- New search for: Ruijuan Chu
- New search for: Siliang Luan
- New search for: Qingfang Yang
- New search for: Wei Wang
- New search for: Zhongtai Jiang
- New search for: Ruru Xing
- New search for: Ruijuan Chu
The preallocation of emergency resources is a mechanism increasing preparedness for uncertain traffic accidents under different weather conditions. This paper introduces the concept of accident probability of black spots and an improved accident frequency method to identify accident black spots and obtain the accident probability. At the same time, we propose a three-stage random regret-minimization (RRM) model to minimize the regret value of the attribute of overall response time, cost, and demand, which allocates limited emergency resources to more likely to happen accident spots. Due to the computational complexity of our model, a genetic algorithm is developed to solve a large-scale instance of the problem. A case study focuses on three-year rainy accidents’ data in Weifang, Linyi, and Rizhao of China to test the correctness and validity of the application of the model.
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Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots
2018
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Electronic Resource
Unknown
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