Journal of Institute of Control, Robotics and Systems (제어로봇시스템학회논문지)

Institute of Control, Robotics and Systems (제어로봇시스템학회)
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Collision Risk Assessment for Pedestrians' Safety Using Neural Network

신경 회로망을 이용한 보행자와의 충돌 위험 판단 방법

  • 김범성 (연세대학교 전기전자공학부) ;
  • 박성근 (연세대학교 전기전자공학부) ;
  • 최배훈 (연세대학교 전기전자공학부) ;
  • 김은태 (연세대학교 전기전자공학부) ;
  • 이희진 (한경대학교 정보제어공학과) ;
  • 강형진 ((주)만도 중앙연구소)
  • Received : 2010.06.17
  • Accepted : 2010.12.14
  • Published : 2011.01.01
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Abstract

This paper proposes a new collision risk assessment system for pedestrians's safety. Monte Carlo Simulation (MCS) method is a one of the most popular method that rely on repeated random sampling to compute their result, and this method is also proper to get the results when it is unfeasible or impossible to compute an exact result. Nevertheless its advantages, it spends much time to calculate the result of some situation, we apply not only MCS but also Neural Networks in this problem. By Monte carlo method, we make some sample data for input of neural networks and by using this data, neural networks can be trained for computing collision probability of whole area where can be measured by sensors. By using this trained networks, we can estimate the collision probability at each positions and velocities with high speed and low error rate. Computer simulations will be shown the validity of our proposed method.

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References

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