Understanding driving situations using a network model

Toshio Ito, Kenichi Yamada, Kunio Nishioka

Research output: Contribution to conferencePaper

13 Citations (Scopus)

Abstract

In the rear-end collision avoidance system (RCAS), which incorporates the functions of detecting and reporting distance headway as well as of collision avoidance through the use of automatic braking, the development of the technique to integrate the advanced characteristic of each sensors becomes important. In this paper, we propose the uniting processing technique which uses the network as a trial. We classify the recognition system into some modules from the software point of view, link these modules as the network and make the states of the network correspond to the driving environment. We referred to a immune network when making the network. The immune network is a technological model of the immune mechanism in the living body. We applied this network mechanism to fuse functions of the distance headway, the road lane position and the position of the preceding vehicle obtained by the laser radar and image processing. These three functions are transferred to modules, each module tests mutually, and each certainty degree is changed continuously. This paper describes this network technique and the experimental results.

Original languageEnglish
Pages48-53
Number of pages6
Publication statusPublished - 1995
EventProceedings of the 1995 Intelligent Vehicles Symposium - Detroit, MI, USA
Duration: 1995 Sep 251995 Sep 26

Other

OtherProceedings of the 1995 Intelligent Vehicles Symposium
CityDetroit, MI, USA
Period95/9/2595/9/26

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Ito, T., Yamada, K., & Nishioka, K. (1995). Understanding driving situations using a network model. 48-53. Paper presented at Proceedings of the 1995 Intelligent Vehicles Symposium, Detroit, MI, USA, .