Are you sure? Modelling the Confidence of a Driver in Left-Turn Gap Acceptance Decisions

Are you sure? Modelling the Confidence of a Driver in Left-Turn Gap Acceptance Decisions

Bontje, Floor (TU Delft Mechanical, Maritime and Materials Engineering)

Zgonnikov, A. (mentor)
de Winter, J.C.F. (graduation committee)
George, A. (graduation committee)

Delft University of Technology

Mechanical Engineering | Vehicle Engineering | Cognitive Robotics

2023-05-30

When a person makes a decision, it is automatically accompanied by a subjective probability judgement of the decision being correct, in other words, a (local) confidence judgement. Confidence judgements have, among other things, an
effect on justifications of future decisions and behaviour. A better understanding of the metacognitive processes responsible for these confidence judgements could improve behaviour models. To date, confidence judgements are mostly studied in a fundamental manner. Little to no research has been done into confidence in more dynamic tasks. Such applied research could render insights on whether fundamental principles also hold for real-life tasks. It could also have practical relevance for several applications. Driving is amongst the areas for which an improved understanding of the decision making and accompanied confidence judgements can be useful, for instance in order to improve driving assistance systems. However, current studies on driving behaviour are merely focused on decision making and do not take confidence into account.
In this study, we made a first attempt of connecting these two fields of research by investigating the confidence of drivers in left-turn gap acceptance decisions in a driver simulator experiment (N=17). The study showed that confidence can be related to the gap size with respect to the oncoming vehicle, described by the time-to-arrival and the distance gap. Confidence increases with the gap size for gap accepting decisions and decreases with the gap size for gap rejecting decisions. In addition, we concluded that confidence can be related to the driving behaviour, and that confidence is negatively related to the decision response time. Moreover, we found that confidence judgements can best be captured with the use of an extended dynamic drift diffusion decision model of which the drift rate of the evidence accumulator as well as the decision boundaries are functions of the time-to-arrival and distance gap. Furthermore, we demonstrated that allowing for post-decision evidence accumulation in the model increases its ability to describe confidence judgements in gap rejecting decisions. Overall, the study confirmed that principles known from fundamental confidence research can be used to describe confidence judgements in a dynamic and applied task.

confidence
Decision Making
Driving Behaviour
Metacognition
Evidence accumulation
Drift-diffusion model

http://resolver.tudelft.nl/uuid:27a1e1e8-a76c-40b8-961c-08655ea7d506

Student theses

master thesis

© 2023 Floor Bontje