Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Siliang Luan, Qingfang Yang, Wei Wang, Zhongtai Jiang, Ruru Xing, Ruijuan Chu
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2018/3513058
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:0197-6729
2042-3195