Effects of training and display content on Level 2 driving automation interface usability

IntroductionLevel 2 driving automation features, such as adaptive cruise control (ACC) combined with lane centering, primarily communicate their operating statuses through the instrument cluster. It remains unclear how interface-specific training and display content influence the ability to understand Level 2 activity in production vehicles.MethodsEighty participants viewed videos recorded from the driver’s point of view in a variety of driving scenarios with Level 2 activity displayed in the instrument cluster of a 2017 Mercedes-Benz E-Class. Half viewed one of two instrument cluster layouts (simple or complex), and half received an orientation to the interface before the experiment. After each video, they were asked about the scenario they had just seen. We then examined what information in the displays participants used to identify Level 2 activity and the usability of the displays.ResultsTraining improved recognition accuracy of when lane centering was temporarily inactive and understanding of why it was inactive. Neither training nor display content affected the ability to recognize when ACC had adjusted the vehicle’s speed or detected a vehicle ahead, or when ACC initially did not detect a lead vehicle and understanding of why it had not detected it. Both factors influenced which sources of information participants used to determine Level 2 activity. Recognition accuracy of system activity improved when participants used valid sources of information. Training, but not display content, improved lane centering usability, but not ACC usability.DiscussionBasic training improves detection of notifications that potentially require further driver action, but not of those that display persistent status information. Training does not result in full understanding of all system notifications or functional limitations, which reinforces the need for intuitive, salient communication about system behavior and its limitations.     

The influence of road familiarity on distracted driving activities and driving operation using naturalistic driving study data

This paper analyzed the influence of familiarity on the involvement of secondary tasks and driving operation using naturalistic driving study (NDS) data. Distracted driving activities were extracted from face videos captured in 557 trips, including 501 trips on familiar roads and 56 trips on unfamiliar roads. These trips were completed by 155 drivers using their own vehicles during daytime hours under good weather conditions. The data showed the frequency of distracted driving activities and duration time were higher on familiar roads compared to unfamiliar roads. More types of secondary tasks were found on familiar roads. Focusing on objects was the most common distracted driving activity on familiar roads. The average time drivers used to eat or drink was highest (8.67 s) on familiar roads. The time drivers spent checking their cell phone was high on both familiar roads and unfamiliar roads. Since driving operation is directly related to crash risk, this paper also analyzed the difference of driving operation on familiar roads and unfamiliar roads. The speed profiles were generated on well-known versus unfamiliar roads. It was shown that drivers were more likely to be speeding and select a short distance to deceleration near the intersections. The findings indicated that distracted driving phenomenon was more serious on familiar roads.     

Bears in our midst: Familiarity with Level 2 driving automation and attending to surprise on-road events

This study presents an on-road paradigm to measure the effect of Level 2 (L2) system familiarity on attention strategies to salient, but non-hazardous, driving-related events when using the driving automation. A vehicle with an oversized pink teddy bear on the back overtook participants three times while they drove a 2019 Mercedes-Benz C300 equipped with a L2 system for 1 h. This L2 system requires drivers to keep their hands on the wheel while activated. The L2 system was turned on or off, depending on the assigned condition, and participants varied in their familiarity with L2 systems. Cameras recorded participant eye glance behavior. After the drive, participants were asked to recall the bear and the number of times their mind had wandered from the driving task during the drive. Results show that the driving automation support gave only participants familiar with L2 systems an advantage for greater bear recall. Unfamiliar participants were at a relative disadvantage when assisted by the L2 system, with generally poorer bear recall than unfamiliar participants who drove with the system off. Better bear recall corresponded with wider on-road gaze dispersion and more instances of mind wandering. Our findings support the effectiveness of this paradigm to measure driver attention when using a L2 system under real-world conditions and highlight the need to consider the role of driving automation familiarity in future research.     

Differential effects of driver sleepiness and sleep inertia on driving behavior

ObjectivesDriver sleepiness is one of the major safety issues in conventional driving and sleep inertia emerges as a driver state in automated driving. The aim of the present study was to assess the differential impacts of sleepiness and sleep inertia on driving behavior.Method61 participants completed a 10-min manual driving task during an otherwise automated drive. They completed the task (a) under an alert state, (b) under a sleepy state, and (c) after EEG-confirmed sleep. Driving performance was assessed with the parameters lane-keeping, speed choice, and speed-keeping. The eye-blink-based sleepiness measure PERCLOS (the proportion of time with eyes closed) was compared for the three driver states.ResultsLane- and speed-keeping performance were impaired under the sleepy state and after sleep, relative to the alert state. After sleep, lane-keeping behavior recovered rapidly and speed-keeping recovered by trend. Under the sleepy state, performance deteriorated. After sleep, the mean speed was lower than in the sleepy state and in the alert state. PERCLOS was increased after sleep and under the sleepy state, relative to the alert state.ConclusionsAlthough sleep inertia had detrimental effects on driving parameters similar to sleepiness, this effect rapidly vanished. Hence, while brief naps might be suitable to restore alertness in general, the minimal time needed to regain full capacity after napping should be a focus of future research.     

Effects of a driver assistance system with foresighted deceleration control on the driving performance of elderly and younger drivers

It is imperative to enhance the safety of elderly individuals on the roads to ensure the quality of their daily life. Near-miss incidents or accidents at blind intersections often result from a conflict between the behaviors of the driver and of other road users (pedestrians and cyclists). The failure to search for potential conflict in the context of blind intersections is a concern pertaining to road safety. The proposed assistance system performs a proactive braking intervention to achieve a referenced velocity in uncertain situations, such as one in which an unobserved pedestrian might initiate a road crossing. The proactive braking intervention attempts to manage the potential risk of crashing with respect to covert hazards. Because an automated system may impair a human’s ability to perceive and respond to hazardous situations while driving, this study was designed to examine the effects of proactive braking intervention and visual support cues on elderly and younger drivers’ ability to respond to information about potentially hazardous situations. We conducted a public-road driving experiment involving 108 elderly and younger drivers from two non-overlapping age groups. It was observed that the vehicle slowdown realized through the proactive braking intervention enabled the drivers to perform safety confirmation near blind spots and caused them to be more sensitive to and wary of potential hazards. This approach could be effective not only for elderly drivers, but also for young or inexperienced ones.     

Evaluating the impact of adaptive signal control technology on driver stress and behavior using real-world experimental data

While the operational and crash reduction benefits of adaptive signal control technology (ASCT) have long been investigated, the impact of this technology on driver behavior and stress is still uncertain. This study evaluated the impact of ASCT on driver behavior and stress in a real-world environment. Participants travelled through two arterial corridors, one equipped with ASCT and the other having traditional time-of-day coordinated signals. Driver stress was measured using a heart rate detector and a perceived stress scale while driver behavior was examined using vehicular trajectory data. Overall, driving behavior improved on the ASCT as compared to the non-ASCT corridor, as indicated by higher speeds and a fewer number of stops on the ASCT corridor relative to the non-ASCT corridor. Repeated measures ANOVA showed a statistically significant reduction in driver heart rate by −10 beats per minute over the ASCT corridor. A similar trend was observed for drivers’ perceived stress, analyzed by Wilcoxon sign ranked test. Driving behavior also showed significant improvement with ASCT presence, and speed was found to be negatively correlated with stress. Furthermore, the participants’ speed was controlled by the two systems i.e. ASCT and non-ASCT as expected. This study provides a significant proof of concept that ASCT can create positive improvements in driver stress and behavior that can be further investigated in the future.