Modeling Human Driver Behavior During Highway Merging Using the Communication - Enabled Interaction Framework

Abstract

Understanding how human drivers handle inter-actions with each other can aid the development of automated vehicles capable of operating in mixed traffic. Interactions between human drivers are often complex, so driver behavior models are needed to better understand them. However, existing models mostly focus on the behavior of one driver, which limits their ability to explain complex reciprocal interactions between multiple drivers. At the same time, the prior research that does focus on interactive behaviors of two or more drivers is typically limited to describing drivers' tactical decisions, limiting the understanding of how these decisions are related to operational aspects of behavior (safety margins and control inputs). In this work, we address this gap, focusing specif-ically on highway merging interactions. We build upon the Communication-Enabled Interactions (CEI) framework - a previously proposed holistic approach to interaction modeling. We develop a CEI-based model of highway merging that captures both tactical and operational aspects of the behavior of two drivers interacting in a highway merging scenario. Our model exhibits human-like behavior aligned with empirical observations of high-level decisions (i.e., who goes first?), safety margins (headways), and position and velocity profiles. Based on our model, we identify key mechanisms regarding drivers' beliefs, velocity perception, and planning, which can potentially generalize beyond highway merging to other interactive human driving behaviors. Our findings highlight the potential of the CEI framework in modeling reciprocal traffic interactions in realistic traffic scenarios, and contribute to understanding the complexities of interactions between human drivers.