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http://dx.doi.org/10.5391/JKIIS.2014.24.4.392

Novel Collision Warning System using Neural Networks  

Kim, Beomseong (School of Electrical & Electronics Engineering, Yonsei University)
Choi, Baehoon (School of Electrical & Electronics Engineering, Yonsei University)
An, Jhonghyun (School of Electrical & Electronics Engineering, Yonsei University)
Hwang, Jaeho (Advanced Research Team, Hyundai Mobis Co., Ltd.)
Kim, Euntai (School of Electrical & Electronics Engineering, Yonsei University)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.24, no.4, 2014 , pp. 392-397 More about this Journal
Abstract
Recently, there are many researches on active safety system of intelligent vehicle. To reduce the probability of collision caused by driver's inattention and mistakes, the active safety system gives warning or controls the vehicle toward avoiding collision. For the purpose, it is necessary to recognize and analyze circumstances around. In this paper, we will treat the problem about collision risk assessment. In general, it is difficult to calculate the collision risk before it happens. To consider the uncertainty of the situation, Monte Carlo simulation can be employed. However it takes long computation time and is not suitable for practice. In this paper, we apply neural networks to solve this problem. It efficiently computes the unseen data by training the results of Monte Carlo simulation. Furthermore, we propose the features affects the performance of the assessment. The proposed algorithm is verified by applications in various crash scenarios.
Keywords
Collision Risk Assessment; Monte Calro Simulation; Neural Networks; Time-to-Collision(TTC);
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
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