A new Car-Following model based on Fuzzy Neural Networks is proposed in this study. First, extremely precise data on 16 test drivers of different attributes are collected by using GPS receiving apparatus. Next, the Car-Following model is built by use of Fuzzy Neural Networks. The collected data from the travel investigation of the drivers are provided as teaching data. Consequently, the developed models were adapted to actual states better than the previous. Although there are differences among the groups of drivers such as in awareness of the distance between two vehicles, the authors believe that it is possible to solve the mechanism of traffic problems as well as to evaluate the traffic policy amendments more accurately by incorporating these models into the microscopic road traffic simulation. (A*)
Samenvatting