There is currently no established method for evaluating human response timing across a
range of naturalistic traffic conflict types. Traditional notions derived from controlled …

Understanding adaptive human driving behavior, in particular how drivers manage
uncertainty, is of key importance for develo** simulated human driver models that can be …

For cyclists, being overtaken represents a safety risk of possibly being side-swiped or cut in
by overtaking drivers. For drivers, such maneuvers are challenging–not only do they need to …

Although latent hazard notification for highly automated driving is expected to enhance traffic
safety, its practical effects have yet to be verified. This study systemically investigated the …

There is currently no established method for evaluating human response timing across a
range of naturalistic traffic conflict types. Traditional notions derived from controlled …

The quantitative measurement of how and when we experience surprise has mostly
remained limited to laboratory studies, and its extension to naturalistic settings has been …

Active inference proposes a unifying principle for perception and action as jointly minimizing
the free energy of an agent's internal world model. In the active inference literature, world …

Driver process models play a central role in the testing, verification, and development of
automated and autonomous vehicle technologies. Prior models developed from control …

Autonomous vehicles face challenges in ensuring cyber-physical security due to their
reliance on image data from cameras processed by machine learning. These algorithms …

Objective Our objectives were to assess the efficacy of active inference models for capturing
driver takeovers from automated vehicles and to evaluate the links between model …