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Driving automation holds significant potential for enhancing traffic safety.However, effectively handling interactions with human drivers in mixed trafficremains a challenging task. Several models exist that attempt to capture humanbehavior in traffic interactions, often focusing on gap acceptance. However, itis not clear how models of an individual driver's gap acceptance can betranslated to dynamic human-AV interactions in the context of high-speedscenarios like overtaking. In this study, we address this issue by employing acognitive process approach to describe the dynamic interactions by the oncomingvehicle during overtaking maneuvers. Our findings reveal that by incorporatingan initial decision-making bias dependent on the initial velocity into existingdrift-diffusion models, we can accurately describe the qualitative patterns ofovertaking gap acceptance observed previously. Our results demonstrate thepotential of the cognitive process approach in modeling human overtakingbehavior when the oncoming vehicle is an AV. To this end, this studycontributes to the development of effective strategies for ensuring safe andefficient overtaking interactions between human drivers and AVs.

A cognitive process approach to modeling gap acceptance in overtaking