Understanding driving situations using a network model

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