Collision risk assessment for pedestrians' safety: Neural network with interacting multiple model apporach

Seongkeun Park, Bumsung Kim, Baehoon Choi, Euntai Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

In this paper, we propose a alarm system for pedestrian protection. We usually do not know that pedestrians may or may not be in dangerous situation, and to know whether pedestrians are in dangerous situation or not. In this paper, we construct collision probability system between vehicle and pedestrian. By using monte carlo simulation, we calculate the collision probability, and it is hard to know collision probability of all area, we recover collision probability of all area using neural networks. And, the collision probabilities are different according to tendency of pedestrian movement, we understand the tendency of pedestrian movement using interacting multiple model tracking method. Computer simulation will be show the validity of our proposed method.

Original languageEnglish
Title of host publicationProceedings of SICE Annual Conference 2010, SICE 2010 - Final Program and Papers
PublisherSociety of Instrument and Control Engineers (SICE)
Pages2897-2900
Number of pages4
ISBN (Print)9784907764364
Publication statusPublished - 2010

Publication series

NameProceedings of the SICE Annual Conference

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

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