Modelling drivers' adaptation to assistance systems

Abstract

Human factors research and engineering of advanced driving assistance systems (ADAS) must consider how drivers adapt to their presence. The major obstruction to this at the moment is poor understanding of the details of the adaptive processes that the human cognition undergoes when faced with such changes. This paper presents a simulation model that predicts how drivers adapt to a steering assistance system. Our approach is based on computational rationality, and demonstrates how task interleaving strategies adapt to the task environment and the driver's goals and cognitive limitations. A supervisor controls eye movements between the driving and non-driving tasks, making this choice on the basis of maximising expected joint task utility. The model predicts that with steering assistance, drivers' in car glance durations increase. We also show that this adaptation leads to risky driving in cases where the reliability of the system is compromised.