JRM Vol.27 No.1 pp. 5-11
doi: 10.20965/jrm.2015.p0005


Study on Autonomous Intelligent Drive System Based on Potential Field with Hazard Anticipation

Ryosuke Matsumi*, Pongsathorn Raksincharoensak**, and Masao Nagai***

*Department of Mechanical Engineering, Tokyo University of Science
6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585, Japan

**Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology
2-24-16 Naka-cho, Koganei, Tokyo 184-8588, Japan

***Japan Automobile Research Institute
1-1-30 Shiba Daimon, Minato-ku, Tokyo 105-0012, Japan

April 16, 2014
October 9, 2014
February 20, 2015
active safety, autonomous intelligent driving, pedestrian, potential fields, hazard-anticipatory knowledge
Risk potential estimation
Pedestrians darting out from blind spots in driver vision are typical scenarios in urban street environments, and conventional autonomous emergency braking systems reach safety limits if sensors do not detect the pedestrian in time to prevent accident or injury. The system must be able to anticipate such potential hazards and to anticipate such pedestrian action. This paper focuses on a pedestrian collision avoidance system that has a “driving-intelligence" model. The model was designed by applying potential field theory using hazard-anticipatory knowledge. The effectiveness of the proposed system is confirmed by computer simulation.
Cite this article as:
R. Matsumi, P. Raksincharoensak, and M. Nagai, “Study on Autonomous Intelligent Drive System Based on Potential Field with Hazard Anticipation,” J. Robot. Mechatron., Vol.27 No.1, pp. 5-11, 2015.
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