Prediction of Meta-stability Phase through Analysis of Driving Behavior
Toshio Ito, Ryohei Kaneyasu
Traffic congestion comes from three phases order: the free travel phase, the meta-stability phase,and the traffic jam phase. Therefore, it can be considered that if the meta-stability phase can be detected, forecasting traffic jams becomes possible. This paper proposes a driver model that forecasts traffic congestion based on changes in driving behavior and that does not rely on traffic flow monitoring infrastructure. As a result of evaluation in driving simulators, it was understood that the distribution of steering and throttle input frequency changes based on changes in the travel phase. It is possible to distinguish these changes using neural networks or support vector machines,and it is possible to make this into a driver model that forecasts traffic congestion.