Identifying Traffic Hysteresis Based on Driver Asymmetric Behavior Model: Before and After Traffic Oscillation

Identifying Stop and go traffic results in traffic oscillation on freeway. because of scarce vehicle trajectories data and aggregated sensor data not only identifying stop and go traffic still limits but also our understanding of this type of the oscillations in congested traffic is still limited. In this paper, analyzing stop and go traffic based on trajectory data of NGSIM presents car following model that not only is able to reproduce the spontaneous formation and ensuing propagation of stop and-go waves in congested traffic, but also based on a behavioral car following model studies microscopic traffic hysteresis from a behavioral perspective. The statistical analysis of the model’s parameters reveals that there is a strong correlation between driver behaviors before and during the oscillation, and that this correlation should not be ignored if one is interested in microscopic output. Also, statistical results of traffic hysteresis based on driver asymmetric behavior reveals that generation and type of traffic hysteresis patterns depending on driver behavior of position along the oscillation. In other word, when driver meets traffic oscillation and deceleration wave starts, traffic hysteresis depends on driver behavioral of patterns and group and scenarios inside the different stages of an oscillation generation.