車両感知器情報を用いた幹線道路における旅行時間予測

抄録

Accurate prediction of travel time is useful for car drivers, and thus it is critical to develop a prediction system to provide the information. AVI (Automatic Vehicle Identification) system has been developed as a direct and precise measurement tool, however, because of the constrains of the installation points, a few dozen systems have been installed so far. On the other hand, we have more than eighty thousand vehicle detectors which collect traffic volumes at each point every five minutes. We note that vehicle detectors are not quite adequate for the prediction of travel time since the traffic volume alone does not lead to the travel time. This paper proposes a new method of predicting travel time in real time using efficiently the data collected from the detectors. The route is divided into several sections. Then, the travel time of each section is estimated by the approximated velocity where the approximation is done via the time-varying coefficients autoregressive model. In order to evaluate this approach, several field experiments were carried out. The results show that predicted travel time closely approximates the measured value.