2016 Fiscal Year Final Research Report
Development of a real-time crash prediction and prevention system for urban expressways
| Project/Area Number |
25420535
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Civil engineering project/Traffic engineering
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| Research Institution | Tokyo Institute of Technology |
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Principal Investigator |
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| Research Collaborator |
HOSSAIN Moinul
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| Project Period (FY) |
2013-04-01 – 2017-03-31
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| Keywords | 交通事故 / 都市高速道路 / リアルタイム |
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| Outline of Final Research Achievements |
In this research, we develop a real-time crash prediction and prevention system for urban expressways that can detect traffic conditions that are likely to occur in real time in traffic accidents, and can select and implement prevention measures highly effective in improving traffic conditions. With regard to the crash prediction system, we introduced Dynamic Bayesian Network to improve the prediction performance of the real-time crash prediction model, and the expectation maximization algorithm and adaptive algorithm to improve the robustness of the model. With regard to the crash prevention system, we developed a system that can examine the effect of improving traffic conditions by vehicle control on the whole route, using the real-time crash prediction and prevention system and simulation.
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| Free Research Field |
都市交通計画
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