ABSTRACT: Conflict severity is the outcome of complex interactions between roadway and environmental characteristics, and vehicle motion. Understanding how and to what extent a vehicle is influenced by roadway and surrounding road users during a conflict can help to analyze the causal mechanisms of collisions, thus providing insights into roadway safety improvement countermeasures. This study utilized the NGSIM Peachtree Street vehicle trajectory dataset to achieve the objective of investigating causal factors of conflicts at intersections by exploring roadway-to-vehicle and vehicle-to-vehicle interactions. In order to remove the outliers and white noise existing in the raw data, vehicle trajectories were reconstructed by discrete wavelet transform and Kalman filtering. The generalized time-to-collision was adopted to detect and measure the severity of conflicts, and 423 conflict events were finally extracted. Path analysis models were then established to explore in exactly which ways the roadway-to-vehicle and vehicle-to-vehicle interactions were related to conflict severity. Various roadway and environmental characteristics such as traffic flow’s average speed, percentage of trucks and intersection skew angle were included in the models. The results indicate the roadway and environmental characteristics have both direct and indirect effects on conflict severity; while for the indirect effects, the conflict vehicle’s kinematics such as the average and standard deviation of speed play an intermediate role in linking roadway factors and conflict outcome. The framework of this study can be applied to assessing roadway readiness for both human-driven and automated vehicles.
Ping Sun, Xuesong Wang*, Omar Hassanin, Meixin Zhu. Modeling Car-following Behavior on Freeways Considering Driving Style. Transportation Research Board 100th Annual Meeting, Washington D.C., USA, 2021. 1.25-29.