Proceedings of the Korean Institute of Intelligent Systems Conference (한국지능시스템학회:학술대회논문집)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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Intention Recognition Using Case-base Learning in Human Vehicle

  • Yamaguchi, Toru (PRESTO, Japan Science and Technology Corporation (JST)) ;
  • Dayaong, Chen (Department of Electronic System Engineering, Tokyo Metropolitan Institute Technology) ;
  • Takeda, Yasuhiro (Department of Electronic System Engineering, Tokyo Metropolitan Institute Technology) ;
  • Jing, Jianping (Department of Electronic System Engineering, Tokyo Metropolitan Institute Technology)
  • Published : 2003.09.01
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Abstract

Most traffic accidents are caused by drivers' carelessness and lack of information on the surrounding objects. In this paper we proposed a model of human intention recognition through case-base learning and to build up an experiment system. The system can help us recognize object's intention (e.g. turn left, turn right or straight) by using detected data about human's motion, speed of the car and the distance between the car and the intersection. Furthermore, we included an example using case-base learning in this paper to improve the precision of recognition as well as an example to explain the use of the system. PC can be used to predict the driving reaction beforehand and send a warning signal to the driver in time if there is any danger.

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