DocumentCode
529535
Title
Collision risk assessment for pedestrians´ safety : Neural network with interacting multiple model apporach
Author
Park, Seongkeun ; Choi, Baehoon ; Baehoon Choi ; Kim, Euntai
Author_Institution
Dept. of Electr. & Electron. Eng., Comput. Intell. Lab., Seoul, South Korea
fYear
2010
fDate
18-21 Aug. 2010
Firstpage
2897
Lastpage
2900
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.
Keywords
Monte Carlo methods; alarm systems; collision avoidance; neural nets; risk management; road safety; traffic engineering computing; alarm system; collision probability system; collision risk assessment; interacting multiple model tracking method; monte carlo simulation; neural network; pedestrian movement; pedestrian protection; pedestrian safety; Artificial neural networks; Computational modeling; Driver circuits; Legged locomotion; Monte Carlo methods; Probability; Safety; Collision probability; Intelligent vehicle; Pedestrian protection system;
fLanguage
English
Publisher
ieee
Conference_Titel
SICE Annual Conference 2010, Proceedings of
Conference_Location
Taipei
Print_ISBN
978-1-4244-7642-8
Type
conf
Filename
5602858
Link To Document