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http://dx.doi.org/10.5391/JKIIS.2011.21.4.475

Recursive Probabilistic Approach to Collision Risk Assessment for Pedestrians' Safety  

Park, Seong-Keun (연세대학교 전기전자공학부)
Kim, Beom-Seong (연세대학교 전기전자공학부)
Kim, Eun-Tai (연세대학교 전기전자공학부)
Lee, Hee-Jin (한경대학교 정보제어공학부)
Kang, Hyung-Jin ((주)만도 중앙연구소)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.21, no.4, 2011 , pp. 475-480 More about this Journal
Abstract
In this paper, we propose a collision risk assesment system. First, using Kalman Filter, we estimate the information of pedestrian, and second, we compute the collision probability using Monte Carlo Simulations(MCS) and neural network(NN). And we update the collision risk using time history which is called belief. Belief update consider not only output of Kalman Filter of only current time step but also output of Kalman Filter up to the first time step to current time step. The computer simulations will be shown the validity of our proposed method.
Keywords
Probabilistic Collision Risk Assessment; Neural Network; Belief; Monte Carlo Simulation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
연도 인용수 순위
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