Stereoscopic 3D dashboards: an investigation of performance, workload, and gaze behavior during take-overs in semi-autonomous driving

When operating a conditionally automated vehicle, humans occasionally have to take over control. If the driver is out of the loop, a certain amount of time is necessary to gain situation awareness. This work evaluates the potential of stereoscopic 3D (S3D) dashboards for presenting smart S3D take-over-requests (TORs) to support situation assessment. In a driving simulator study with a 4 × 2 between-within design, we presented 3 smart TORs showing the current traffic situation and a baseline TOR in 2D and S3D to 52 participants doing the n-back task. We further investigate if non-standard locations affect the results. Take-over performance indicates that participants looked at and processed the TORs' visual information and by that, could perform more safe take-overs. S3D warnings in general, as well as warnings appearing at the participants’ focus of attention and warnings at the instrument cluster, performed best. We conclude that visual warnings, presented on an S3D dashboard, can be a valid option to support take-over while not increasing workload. We further discuss participants’ gaze behavior in the context of visual warnings for automotive user interfaces

Spatial and temporal EEG dynamics of dual-task driving performance

<p>Abstract</p> <p>Background</p> <p>Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions.</p> <p>Methods</p> <p>We designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains.</p> <p>Results</p> <p>Power increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA.</p> <p>Conclusions</p> <p>This study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations.</p

Among substance-abusing traffic offenders, poor sleep and poor general health predict lower driving skills but not slower reaction times

Traffic accidents are a significant health issue in Iran. Explanations for such accidents have included single consideration of the role of poor sleep and negative psychological trait and state variables. In this study, we examined whether and to what extent sleep, general health, and aggression can concomitantly predict driving behavior.; A total of 360 male traffic offenders (driving under substance use; mean age: 31 years) participated in this study. They completed the questionnaires covering sociodemographic, sleep-related, and behavior-related variables. In addition, their visual and acoustic reaction times were objectively tested.; Poor sleep, poor general health, and higher aggression scores were associated with self-rated poor driving behavior. Poor sleep was directly associated with poor driving behavior and indirectly via poor general health and aggression. In contrast, visual and acoustic reaction times were unrelated to sleep, general health, aggression, or self-rated driving behavior.; To our knowledge, this is the first study in Iran to assess concomitantly poor sleep, poor general health, and higher aggression scores as independent predictors of poor driving behavior among a larger sample of substance-abusing traffic offenders. Furthermore, visual and acoustic reaction times were unrelated to sleep, general health, aggression, and driving behavior. Finally, importantly, poor sleep predicted both directly and indirectly poor driving behavior

Examination of Driver Visual and Cognitive Responses to Billboard Elicited Passive Distraction Using Eye-Fixation Related Potential

Distractions external to a vehicle contribute to visual attention diversion that may cause traffic accidents. As a low-cost and efficient advertising solution, billboards are widely installed on side of the road, especially the motorway. However, the effect of billboards on driver distraction, eye gaze, and cognition has not been fully investigated. This study utilises a customised driving simulator and synchronised electroencephalography (EEG) and eye tracking system to investigate the cognitive processes relating to the processing of driver visual information. A distinction is made between eye gaze fixations relating to stimuli that assist driving and others that may be a source of distraction. The study compares the driver’s cognitive responses to fixations on billboards with fixations on the vehicle dashboard. The measured eye-fixation related potential (EFRP) shows that the P1 components are similar; however, the subsequent N1 and P2 components differ. In addition, an EEG motor response is observed when the driver makes an adjustment of driving speed when prompted by speed limit signs. The experimental results demonstrate that the proposed measurement system is a valid tool in assessing driver cognition and suggests the cognitive level of engagement to the billboard is likely to be a precursor to driver distraction. The experimental results are compared with the human information processing model found in the literature