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
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.
-  Traffic Bureau, National Police Agency, “Statistics 2007 road accidents Japan," International Association of Traffic and Safety Sciences (IATSS), 2008.
-  National Police Agency, “The White Paper on Police 2011 (Digest edition), Chapter 3: Ensuring Safe and Comfortable Transportation," pp. 31-33, 2011.
-  Y. Satomi, T. Murano, M. Aga, and T. Yonekawa, “A characteristic analysis of driving behavior to rear-end collision warning using a driving simulator," Proc. of 18th JSME Conf. on Transportation and Logistics (TRANSLOG), pp. 283-286, 2009.
-  P. Raksincharoensak, “Autonomous Driving System to Enhance Safe and Secured Traffic Society for Elderly Drivers," 18th World Congress on ITS (Invited talk), Special Interest Session No.30, Orlando, USA, 2011.
-  P. Raksincharoensak, M. Shino, and M. Nagai, “Enhancing Active Safety of Small-Scale Electric Vehicle “NOVEL” by Utilizing In-Wheel-Motor," Proc. of the 20th Int. Electric Vehicle Symposium and Exposition, CD-ROM (5B-Raksincharoensak), Long Beach, USA, 2003.
-  P. Raksincharoensak, M. Shino, and M. Nagai, “Vehicle Motion Control Issues Using Micro Electric Vehicle “NOVEL"," WEVA-Journal, Vol.1, WEVA-043, 2007.
-  M. Nagai, Y. Michitsuji, M. Kamata, and M. Shino, “Research on Near-miss Incident Analysis using Drive Recorder (First Report): Drive Recorder Specifications and Incident Capturing Trigger Algorithm," Trans. of the Society of Automative Engineers of Japan, Vol.38, No.2, pp. 219-224, 2007.
-  M. Fujita, Y. Michitsuji, M. Shino, M. Kamata, and M. Nagai, “Research on Near-miss Incident Analysis using Drive Recorders (Second Report): Analysis Methodology by Collected Data and Database Construction," Trans. of the Society of Automative Engineers of Japan, Vol.38, No.4, pp. 145-150, 2007.
-  O. Khatib, “Real-time obstacle avoidance for manipulators and mobile robotsm," Int. J. of Robotics Research, Vol.5, pp. 90-98, 1986.
-  J. C. Gerdes, U. Saur, and E. J. Rossetter, “Combining Lanekeeping and Vehicle Following with Hazard Maps," Proc. of the 2000 Int. Symposium on Advanced Vehicle Control, Michigan, USA, 2000.
-  D. Reichardt and J. Schick, “Collision Avoidance in Dynamic Environments Applied to Autonomous Vehicle Guidance on the Motorway," Proc. of the IEEE Intelligent Vehicles Symposium, Paris, France, 1994.
-  T. Sattel and T. Brandt, “From robotics to automotive: lane-keeping and collision avoidance based on elastic bands," Vehicle System Dynamics, Vol.46, Issue 7, pp. 597-619, 2008.