Uncovering Variability in Human Driving Behavior Through Automatic Extraction of Similar Traffic Scenes from Large Naturalistic Datasets

Recently, multiple naturalistic traffic datasets of human-driven trajectories have been published (e.g., highD, NGSim, and pNEUMA). These datasets have been used in studies that investigate variability in human driving behavior, for example for scenario-based validation of autonomous vehicle (AV) behavior, modeling driver behavior, or...

Interactive Merging Behavior in a Coupled Driving Simulator: Experimental Framework and Case Study

Human highway-merging behavior is an important aspect when developing autonomous vehicles (AVs) that can safely and successfully interact with other road users. To design safe and acceptable human-AV interactions, the underlying mechanisms in human-human interactive behavior need to be understood. Exposing and understanding these mechanisms can...