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...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Journal of Advanced Transportation |
| Online Access: | http://dx.doi.org/10.1155/2018/3513058 |
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| _version_ | 1849683414841556992 |
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| author | Siliang Luan Qingfang Yang Wei Wang Zhongtai Jiang Ruru Xing Ruijuan Chu |
| author_facet | Siliang Luan Qingfang Yang Wei Wang Zhongtai Jiang Ruru Xing Ruijuan Chu |
| author_sort | Siliang Luan |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-d749dce5d0c841edbdb9670d4ded9613 |
| institution | DOAJ |
| issn | 0197-6729 2042-3195 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Advanced Transportation |
| spelling | doaj-art-d749dce5d0c841edbdb9670d4ded96132025-08-20T03:23:55ZengWileyJournal of Advanced Transportation0197-67292042-31952018-01-01201810.1155/2018/35130583513058Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black SpotsSiliang Luan0Qingfang Yang1Wei Wang2Zhongtai Jiang3Ruru Xing4Ruijuan Chu5School of Transportation, Jilin University, Changchun 130022, Jilin, ChinaSchool of Transportation, Jilin University, Changchun 130022, Jilin, ChinaSchool of Transportation, Jilin University, Changchun 130022, Jilin, ChinaSchool of Transportation, Jilin University, Changchun 130022, Jilin, ChinaSchool of Transportation, Jilin University, Changchun 130022, Jilin, ChinaSchool of Transportation, Jilin University, Changchun 130022, Jilin, ChinaThe 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.http://dx.doi.org/10.1155/2018/3513058 |
| spellingShingle | Siliang Luan Qingfang Yang Wei Wang Zhongtai Jiang Ruru Xing Ruijuan Chu Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots Journal of Advanced Transportation |
| title | Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots |
| title_full | Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots |
| title_fullStr | Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots |
| title_full_unstemmed | Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots |
| title_short | Random Regret-Minimization Model for Emergency Resource Preallocation at Freeway Accident Black Spots |
| title_sort | random regret minimization model for emergency resource preallocation at freeway accident black spots |
| url | http://dx.doi.org/10.1155/2018/3513058 |
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