Underload on the Road: Measuring Vigilance Decrements During Partially Automated Driving

Abstract

Partially automated vehicle technology is increasingly common on-road. While this technology can provide safety benefits to drivers, it also introduces new concerns about driver attention. In particular, during partially automated driving (PAD), drivers are expected to stay vigilant so they can readily respond to important events in their environment. However, using partially automated vehicles on the highway places drivers in monotonous situations and requires them to do very little. This can place the driver in a state of cognitive underload in which they experience a very small amount of cognitive demand. In this situation, drivers can exhibit vigilance decrements which impact their ability to respond to on-road threats. This is of particular concern in situations when the partially automated vehicle fails to respond to a potentially critical situation and leaves all responsibility to safely navigate to the driver. This paper reviews situations that lead to vigilance decrements and characterizes the different methodologies of measuring driver vigilance during PAD, highlighting their advantages and limitations. Based on our reading of the literature, we summarize several factors future research on vigilance decrements in PAD should consider.

(Mis-)use of standard Autopilot and Full Self-Driving (FSD) Beta: Results from interviews with users of Tesla's FSD Beta

“…Respondents in the present study were early adopters with a strong technical or professional background and a high level of technology savviness, which may also explain the low subjective workload. Studies have shown that cognitive underload can be detrimental to drivers' take over performance (McWilliams and Ward, 2021). Hence, it is debatable whether the expected improved ability to take over, as reported by our respondents, is realistic.…”

“…It is assumed that automated cars will improve traffic safety, eliminating human error (Ye and Yamamoto, 2019;Tafidis et al, 2022). These assumptions tend to remain speculative and untested, ignoring the emergence of new types of unintended safety risks, which may offset the expected safety benefits (Casner and Hutchins, 2019;McWilliams and Ward, 2021;Malin et al, 2022;Tafidis et al, 2022). Except for social media content (e.g., anecdotes and YouTube videos) (Reddit, 2022a), little is known about the unintended and intended changes of driver state and (travel) behavior with FSD Beta engaged and how these compare to standard Autopilot.…”

Driver Vigilance Decrement is More Severe During Automated Driving than Manual Driving

“…This is concerning because the consequences of missing or failing to respond appropriately to vehicle automation failures can be lethal, as demonstrated by recent automationinvolved collisions (e.g., NHTSA, 2017;NTSB, 2019). The research on driver vigilance in automated vehicles suggests that the risk of such collisions will likely grow as a function of time spent driving with automation engaged (Greenlee et al, 2018(Greenlee et al, , 2019Körber, Cingel, Zimmermann, & Bengler, 2015;Körber, Schneider, & Zimmermann, 2015;Mok et al, 2015;McWilliams & Ward, 2021;Saxby et al, 2008;Saxby et al, 2013). Research has shown that driver vigilance is further hindered as monitoring demands are increased by increasing the frequency or reducing the predictability of roadway events that must be inspected for their potential to induce an automation failure (Greenlee et al, 2019).…”

On validating a generic camera‐based blink detection system for cognitive load assessment

“…For example, completing activities like driving or product assembly under high cognitive load often leads to poorer task performance and a greater risk of collisions or work injuries [2][3][4][5]. Likewise, cognitive underload resulting from, for example, boredom, are associated with performance declines in tasks requiring prolonged attentive engagement [6,7].…”