DocumentCode :
558857
Title :
A soft computing approach for collision risk assessments
Author :
Park, Seongkeun ; Kim, Beomsung ; Choi, Baehoon ; Kim, Eunati ; Lee, Heejin ; Kang, Hyung-Jin
Author_Institution :
Dept. of Electr. Eng., Yonsei Univ., Seoul, South Korea
fYear :
2011
fDate :
26-29 Oct. 2011
Firstpage :
1908
Lastpage :
1910
Abstract :
In this paper, we propose a collision risk assessment system using soft computing method. By using Monte Carlo Method, we make some samples for collision risk, and we recover collision risk of whole area using neural network. Multi-layer perceptron neural network will be applied to proposed algorithm. And fuzzy system will decide the final collision risk by considering not only collision risk but also time for collision. Simulation results will show the validity of our proposed method.
Keywords :
Monte Carlo methods; automated highways; fuzzy set theory; multilayer perceptrons; road traffic; traffic engineering computing; Monte Carlo Method; collision risk assessment; fuzzy system; multilayer perceptron; neural network; soft computing; Accidents; Computational modeling; Electronic mail; Fuzzy systems; Risk management; Safety; Vehicles; Intelligent vehicle system; collision risk; fuzzy system; neural network; pedestrian protection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems (ICCAS), 2011 11th International Conference on
Conference_Location :
Gyeonggi-do
ISSN :
2093-7121
Print_ISBN :
978-1-4577-0835-0
Type :
conf
Filename :
6106192
Link To Document :
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