Prediction of moving and unexpected motionless bottlenecks based on three-phase traffic theory

We present a simulation methodology for the prediction of “unexpected” bottlenecks, i.e., the bottlenecks that occur suddenly and unexpectedly for drivers on a highway. Such unexpected bottlenecks can be either a moving bottleneck (MB) caused by a slow moving vehicle or a motionless bottleneck caused by a stopped vehicle (SV). Based on simulations of a stochastic microscopic traffic flow model in the framework of Kerner's three-phase traffic theory, we show that through the use of a small share of probe vehicles (FCD) randomly distributed in traffic flow the reliable prediction of “unexpected” bottlenecks is possible. We have found that the time dependence of the probability of MB and SV prediction as well as the accuracy of the estimation of MB and SV location depend considerably on sequences of phase transitions from free flow (F) to synchronized flow (S) (F$\to$S transition) and back from synchronized flow to free flow (S$\to$F transition) as well as on speed oscillations in synchronized flow at the bottleneck. In the simulation approach, the identification of F$\to$S and S$\to$F transitions at an unexpected bottleneck has been made in accordance with Kerner's three-phase traffic theory. The presented simulation methodology allows us both the prediction of the unexpected bottleneck that suddenly occurs on a highway and the distinguishing of the origin of the unexpected bottleneck, i.e., whether the unexpected bottleneck has occurred due to a MB or a SV.