Prediction of moving bottleneck through the use of probe vehicles: a simulation approach in the framework of three-phase traffic theory

Abstract

Based on simulations in the framework of Kerner’s three-phase traffic theory, we present a methodology for the prediction of a moving bottleneck (MB) with the use of a small share of probe vehicles (floating car data – FCD) randomly distributed in traffic flow. In this methodology, a conclusion of the three-phase traffic theory has been used that in the vicinity of any bottleneck there can be observed phase transitions between free flow and synchronized flow. The presented methodology is based on the recognition of phase transition points from synchronized flow to free flow on probe vehicle trajectories. For the simulations, we have used the Kerner–Klenov microscopic stochastic traffic flow model. It has been found that the MB can be predicted even if about 1% of probe vehicles are in traffic flow. The time-function of the probability of MB prediction in dependence of the share of probe vehicles in traffic flow has been calculated. We have found that the time-dependence of the probability of MB prediction as well as the accuracy of the estimation of MB location depend considerably on the occurrence of sequences of phase transitions from free flow to synchronized flow and back from synchronized flow to free flow occurring before traffic breakdown at the MB as well as speed oscillations in synchronized flow at the MB. The methodology of MB prediction presented in the paper can be used by either automated driving vehicles or other ITS-applications for speed harmonization, collision avoidance that should increase traffic safety and comfort.