Drivers' decision-making when attempting to cross an intersection results from choice between affordances

Abstract

In theory, a safe approach to an intersection implies that drivers can simultaneously manage two scenarios: they either choose to cross or to give way to an oncoming vehicle. In this article we formalize the critical time for safe crossing (CTcross) and the critical time for safe stopping (CTstop) to represent crossing and stopping possibilities, respectively. We describe these critical times in terms of affordances and empirically test their respective contribution to the driver's decision-making process. Using a driving simulator, three groups of participants drove cars with identical acceleration capabilities and different braking capabilities. They were asked to try to cross an intersection where there was an oncoming vehicle, if they deemed the maneuver to be safe. If not, they could decide to stop or, as a last resort, make an emergency exit. The intersections were identical among groups. Results showed that although the crossing possibilities (CTcross) were the same for all groups, there were between-group differences in crossing frequency. This suggests that stopping possibilities (CTstop) play a role in the driver's decision-making process, in addition to the crossing possibilities. These results can be accounted for by a behavioral model of decision making, and provide support for the hypothesis of choice between affordances.

Information–Movement Coupling in The Control of Driver Approach to an Intersection

“…Not only is this mechanism based on the consideration of an informational support that allows the agent to access, at any time, the state of their relationship with the environment, but task-related variables such as TTA and AC also modulate the effect of the coupling and consequently the adjustments that are produced. We believe our results also provide a useful complement to recent studies that put action capabilities at the heart of the control process in goal-directed action (e.g., Fajen, 2005Fajen, , 2007Morice, Diaz, Fajen, Basilio & Montagne, 2015;Marti, Morice & Montagne, 2015). A goal of studies that aim to formalize control laws could therefore be to consider the capacity for action in the operationalization of the information-movement relation.…”

An Affordance-Based Approach to Visually Guided Overtaking

“…In other words, in addition to perceiving overtake-ability, the driver may also need to perceive whether bailing out is still within his or her capabilities. In this regard, a more complete account of drivers' behavior during overtaking may be possible by considering overtaking in terms of a competition between two affordances (Marti, Morice, & Montagne, 2014).…”

A Mental Simulation Approach for Learning Neural-Network Predictive Control (in Self-Driving Cars)

“…For example, the features that most contribute to the steering action can be visualized [19]. However, human actions are often a superintended choice between different affordances [20], [21]. This explanation level is missing.…”