Spare visual capacity and driver inattention in lateral vehicle control

• A method was developed to measure situational spare visual capacity (SVC) in a lateral vehicle control task. • Assessing situational SVC allows for proactive and accurate detection of driver inattention against a reliable benchmark. • The measure was able to accurately predict all lane excursions in advance in a driving simulator study with 32 participants. • Re-evaluation of static buffer times for permissible off-road glance durations is necessary. • Possibility should be prioritized over probability in safety–critical measures and applications. Drivers often possess spare visual capacity (SVC), which allows them to occasionally shift their gaze from the road for both driving-task related and non-related reasons without significantly compromising safety. This creates the need to quantify SVC from a normative perspective to understand its limits in a context-sensitive manner, which can help in the timely detection of potential driver inattention and the prevention of possible mishaps. We developed a mathematical formula that generates situational estimates of available SVC by considering the relevant environmental, mechanical, and cognitive factors, enabling us to objectively identify driver inattention against a valid reference point during a lateral vehicle control task. A driving simulator study ( N = 32) was conducted to implement and evaluate the effectiveness of our methodology and to examine drivers’ visual sampling behavior in a lane-keeping task. We successfully predicted all lane excursions in advance. While the likelihood of inattention towards lane position during occluded driving is small, it exists and increases with speed. The time required to avoid lane excursions varies with speed, side of lane boundary, and individual driver differences. Quantifying situational SVC can aid in detecting driver inattention by providing a more accurate assessment in advance of safety–critical outcomes, thereby reducing false positives. Our approach offers potential for developing improved safety standards and designing proactive adaptive systems to monitor driver inattention based on contextual and driver-specific factors.