Post-Takeover Proficiency in Conditionally Automated Driving: Understanding Stabilization Time with Driving and Physiological Signals.

In the realm of conditionally automated driving, understanding the crucial transition phase after a takeover is paramount. This study delves into the concept of post-takeover stabilization by analyzing data recorded in two driving simulator experiments. By analyzing both driving and physiological signals, we investigate the time required for the driver to regain full control and adapt to the dynamic driving task following automation. Our findings show that the stabilization time varies between measured parameters. While the drivers achieved driving-related stabilization (winding, speed) in eight to ten seconds, physiological parameters (heart rate, phasic skin conductance) exhibited a prolonged response. By elucidating the temporal and cognitive dynamics underlying the stabilization process, our results pave the way for the development of more effective and user-friendly automated driving systems, ultimately enhancing safety and driving experience on the roads.

Electrogastrogram-Derived Features for Automated Sickness Detection in Driving Simulator.

The rapid development of driving simulators for the evaluation of automated driving experience is constrained by the simulator sickness-related nausea. The electrogastrogram (EGG)-based approach may be promising for immediate, objective, and quantitative nausea assessment. Given the relatively high EGG sensitivity to noises associated with the relatively low amplitude and frequency spans, we introduce an automated procedure comprising statistical analysis and machine learning techniques for EGG-based nausea detection in relation to the noise contamination during automated driving simulation. We calculate the root mean square of EGG amplitude, median and dominant frequencies, magnitude of Power Spectral Density (PSD) at dominant frequency, crest factor of PSD, and spectral variation distribution along with newly introduced parameters: sample and spectral entropy, autocorrelation zero-crossing, and parameters derived from the Poincaré diagram of consecutive EGG samples. Results showed outstanding robustness of sample entropy with moderate robustness of autocorrelation zero-crossing, dominant frequency, and its median. Machine learning reached an accuracy of 88.2% and revealed sample entropy as one of the most relevant and robust parameters, while linear analysis highlighted spectral entropy, spectral variation distribution, and crest factor of PSD. This study clearly indicates the need for customized feature selection in noisy environments, as well as a complementary approach comprising machine learning and statistical analysis for efficient nausea detection.

Electrogastrography in Autonomous Vehicles-An Objective Method for Assessment of Motion Sickness in Simulated Driving Environments.

Autonomous vehicles are expected to take complete control of the driving process, enabling the former drivers to act as passengers only. This could lead to increased sickness as they can be engaged in tasks other than driving. Adopting different sickness mitigation techniques gives us unique types of motion sickness in autonomous vehicles to be studied. In this paper, we report on a study where we explored the possibilities of assessing motion sickness with electrogastrography (EGG), a non-invasive method used to measure the myoelectric activity of the stomach, and its potential usage in autonomous vehicles (AVs). The study was conducted in a high-fidelity driving simulator with a virtual reality (VR) headset. There separate EGG measurements were performed: before, during and after the driving AV simulation video in VR. During the driving, the participants encountered two driving environments: a straight and less dynamic highway road and a highly dynamic and curvy countryside road. The EGG signal was recorded with a proprietary 3-channel recording device and Ag/AgCl cutaneous electrodes. In addition, participants were asked to signalize whenever they felt uncomfortable and nauseated by pressing a special button. After the drive they completed also the Simulator Sickness Questionnaire (SSQ) and reported on their overall subjective perception of sickness symptoms. The EGG results showed a significant increase of the dominant frequency (DF) and the percentage of the high power spectrum density (FSD) as well as a significant decrease of the power spectrum density Crest factor (CF) during the AV simulation. The vast majority of participants reported nausea during more dynamic conditions, accompanied by an increase in the amplitude and the RMS value of EGG. Reported nausea occurred simultaneously with the increase in EGG amplitude. Based on the results, we conclude that EGG could be used for assessment of motion sickness in autonomous vehicles. DF, CF and FSD can be used as overall sickness indicators, while the relative increase in amplitude of EGG signal and duration of that increase can be used as short-term sickness indicators where the driving environment may affect the driver.

Lessons Learned: Gastric Motility Assessment During Driving Simulation.

In the era of technological advances and innovations in transportation technologies, application of driving simulators for the investigation and assessment of the driving process provides a safe and suitable testing environment. Although driving simulators are crucial for further improvements in transportation, it is important to resolve one of their main disadvantages-simulator sickness. Therefore, suitable methods for the assessment of simulator sickness are required. The main aim of this paper was to present a non-invasive method for assessing simulator sickness by recording gastric myoelectrical activity-electrogastrography. Open-source hardware for electrogastrography together with recordings obtained in 13 healthy volunteers is presented, and the main aspects of signal processing for artifact cancellation and feature extraction were discussed. Based on the obtained results, it was concluded that slow-wave electrical gastric activity can be recorded during driving simulation by following adequate recommendations and that proposed features could be beneficial in describing non-ordinary electrogastrography signals.

Exploring direct 3D interaction for full horizontal parallax light field displays using leap motion controller.

This paper reports on the design and evaluation of direct 3D gesture interaction with a full horizontal parallax light field display. A light field display defines a visual scene using directional light beams emitted from multiple light sources as if they are emitted from scene points. Each scene point is rendered individually resulting in more realistic and accurate 3D visualization compared to other 3D displaying technologies. We propose an interaction setup combining the visualization of objects within the Field Of View (FOV) of a light field display and their selection through freehand gesture tracked by the Leap Motion Controller. The accuracy and usefulness of the proposed interaction setup was also evaluated in a user study with test subjects. The results of the study revealed high user preference for free hand interaction with light field display as well as relatively low cognitive demand of this technique. Further, our results also revealed some limitations and adjustments of the proposed setup to be addressed in future work.

An analysis of the precision and reliability of the leap motion sensor and its suitability for static and dynamic tracking.

We present the results of an evaluation of the performance of the Leap Motion Controller with the aid of a professional, high-precision, fast motion tracking system. A set of static and dynamic measurements was performed with different numbers of tracking objects and configurations. For the static measurements, a plastic arm model simulating a human arm was used. A set of 37 reference locations was selected to cover the controller's sensory space. For the dynamic measurements, a special V-shaped tool, consisting of two tracking objects maintaining a constant distance between them, was created to simulate two human fingers. In the static scenario, the standard deviation was less than 0.5 mm. The linear correlation revealed a significant increase in the standard deviation when moving away from the controller. The results of the dynamic scenario revealed the inconsistent performance of the controller, with a significant drop in accuracy for samples taken more than 250 mm above the controller's surface. The Leap Motion Controller undoubtedly represents a revolutionary input device for gesture-based human-computer interaction; however, due to its rather limited sensory space and inconsistent sampling frequency, in its current configuration it cannot currently be used as a professional tracking system.

A user study of directional tactile and auditory user interfaces for take-over requests in conditionally automated vehicles.

General introduction of unconditionally and conditionally automated vehicles is expected to have a highly positive impact on the society, from increased accessibility to mobility and road traffic safety, to decreased environmental and economic negative impacts. However, there are several obstacles and risks slowing down the adoption of this technology, which are primarily related to the human-machine interaction (HMI) and exchange of control between the vehicle and the human driver. In this article, we present key takeaways for HMI design of take-over requests (TOR) that the vehicle issues to inform the driver to take over control of the vehicle. The key takeaways were developed based on the results of a user study, where directional tactile-ambient (visual) and auditory-ambient (visual) TOR user interfaces (UI) were evaluated with regards to commonly used take-over quality aspects (attention redirection, take-over time, correct interpretation of stimuli, off-road drive, brake application, lateral acceleration, minimal time-to-collision and occurrence of collision). 36 participants took part in the mixed design study, which was conducted in a driving simulator. The results showed that drivers' attention was statistically significantly faster redirected with the auditory-ambient UI, however using the tactile-ambient UI resulted in less off-road driving and slightly less collisions. The results also revealed that drivers correctly interpreted the directional TOR stimuli more often than the non-directional one. Based on the study results, a list of key takeaways was developed and is presented in the conclusion of the paper. The results from this study are especially relevant to the TOR UI designers and the automotive industry, which tend to provide the most usable UI for ensuring safer end efficient human-vehicle interaction during the TOR task.

Consistency of neuropsychological and driving simulator assessment after neurological impairment.

Deficits in attentional and executive functioning may interfere with driving ability and result in a lower level of fitness to drive. Studies show mixed results in relation to the consistency of neuropsychological and driving simulator assessment. The objective of this study was to investigate the consistency of both types of assessment. Ninety-nine patients with various neurological impairments (72 males; M = 48.98 years; SD = 17.27) performed a 30-minute drive in a driving simulation in three different road settings; a (non-)residential rural area, a highway and an urban area. They also underwent neuropsychological assessment of attention and executive function. An exploratory correlational analysis was conducted. We found weak, but significant correlations between attention and executive function measures and more efficient driving in the driving simulator. Distractibility was associated with the most simulator variables in all three simulated road settings. Participants who were better at maintaining attention, eliminating irrelevant information and suppressing inappropriate responses, were less likely to drive above the speed limit, produced a less jerky ride, and used the rearview mirror more regularly. A lack of moderate or strong significant correlations (inconsistency) between traditional neuropsychological and simulator assessment variables may indicate that they don't evaluate the same cognitive processes.

An analysis of the suitability of a low-cost eye tracker for assessing the cognitive load of drivers.

This paper presents a driving simulator study in which we investigated whether the Eye Tribe eye tracker (ET) is capable of assessing changes in the cognitive load of drivers through oculography and pupillometry. In the study, participants were asked to drive a simulated vehicle and simultaneously perform a set of secondary tasks with different cognitive complexity levels. We measured changes in eye properties, such as the pupil size, blink rate and fixation time. We also performed a measurement with a Detection Response Task (DRT) to validate the results and to prove a steady increase of cognitive load with increasing secondary task difficulty. The results showed that the ET precisely recognizes an increasing pupil diameter with increasing secondary task difficulty. In addition, the ET shows increasing blink rates, decreasing fixation time and narrowing of the attention field with increasing secondary task difficulty. The results were validated with the DRT method and the secondary task performance. We conclude that the Eye Tribe ET is a suitable device for assessing a driver's cognitive load.

Sensitivity evaluation of the visual, tactile, and auditory detection response task method while driving.

OBJECTIVES: In this article, we evaluate the sensitivity to cognitive load of 3 versions of the Detection Response Task method (DRT), proposed in ISO Draft Standard DIS-17488. METHODS: We present a user study with 30 participants in which we compared the sensitivity to cognitive load of visual, audio, and tactile DRT in a simulated driving environment. The amount of cognitive load was manipulated with secondary n-back tasks at 2 levels of difficulty (0-back and 1-back). We also explored whether the DRT method is least sensitive to cognitive load when the stimuli and secondary task are of the same modality. For this purpose, we used 3 forms to present the n-back task stimuli: visual, audio, and tactile. Responses to the task were always vocal. The experiment was based on a between-subject design (the DRT modalities) with 2 levels of within-subject design study (modalities and difficulty of the secondary n-back tasks). The participants' primary task in the study was to drive safely, and a second priority was to answer to DRT stimuli and perform secondary tasks. RESULTS: The results indicate that all 3 versions of the DRT tested were sensitive to detecting the difference in cognitive load between the reference driving period and driving and engaging in the secondary tasks. Only the visual DRT discriminated between the 0-back and 1-back conditions on mean response time. Contrary to expectations, no interaction was observed between DRT modality and the stimuli modality used for presentation of the secondary tasks. CONCLUSIONS: None of the 3 methods of presenting DRT stimuli showed a consistent advantage in sensitivity in differentiating multiple levels of cognitive load if all response times, hit rates, and secondary task performance are considered. If only response time is considered, the visual presentation of the DRT stimulus used in this study showed some advantages. In interpreting these data, it should be noted that the methods of DRT stimulus presentation varied somewhat from the currently proposed draft ISO standard and it is possible that the relative salience level of the visual DRT stimulus influenced the findings. It is further suggested that more than 2 levels of difficulty of the n-back task should be considered for further investigation of the relative sensitivity of different DRT stimuli modalities. Parameters that indicate change in cognitive load (response time, hit rate, task performance) should be analyzed together in assessing the overall impact on the driver and not individually, in order to obtain a fuller insight of the assessed cognitive load.

A user study of auditory, head-up and multi-modal displays in vehicles.

This paper describes a user study on the interaction with an in-vehicle information system (IVIS). The motivation for conducting this research was to investigate the subjectively and objectively measured impact of using a single- or multi-modal IVIS while driving. A hierarchical, list-based menu was presented using a windshield projection (head-up display), auditory display and a combination of both interfaces. The users were asked to navigate a vehicle in a driving simulator and simultaneously perform a set of tasks of varying complexity. The experiment showed that the interaction with visual and audio-visual head-up displays is faster and more efficient than with the audio-only display. All the interfaces had a similar impact on the overall driving performance. There was no significant difference between the visual only and audio-visual displays in terms of their efficiency and safety; however, the majority of test subjects clearly preferred to use the multi-modal interface while driving.