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The paper presents a study on motion sickness mitigation while driving with a fully automated vehicle on a test track. 31 participants who were susceptible to motion sickness experienced a 25-minuntes drive with multiple motion sickness provoking decelerations and accelerations while reading a text on a tablet. The participants experienced three different conditions in separate sessions: 1) control condition without countermeasure, 2) drive with active seat belt tensioner, 3) drive with a two-step driving profile. The participants rated their motion sickness on the MSTT Scale (during the drive; Kaß et al., 2022) and on the MSAQ (pre and post drive; Gianaros et al., 2001). After each drive, drivers rated their subjective experience of vehicle behavior and the countermeasures. On MSTT, the results showed no significant differences in the development of motion sickness across the three conditions. However, the two-step driving profile reduced the development of motion sickness assessed via MSAQ. Furthermore, both countermeasures seem to have the potential to positively influence the perception of the automation as safer, more trustworthy and more reliable.
The presented simulator study compared two different driver-in-the-loop strategies on driver's eye glances and intervention behavior at system limits in partial automated driving with a control condition without any strategy: A state-dependent strategy achieved by a driver monitoring system and a situation-dependent strategy by using a monitoring request. The results showed visible differences in gaze reaction times and intervention times. However, the effects were overlaid by strong individual differences in monitoring behavior during partial automated driving, so that none of these differences reached statistical significance. The qualitative analysis of single critical events indicated that those could be successfully avoided by the strategies. The subjective evaluations revealed that a monitoring request was perceived as more helpful in preparing for a system limit.
The presented method describes a standardized test procedure for the evaluation of takeover performance of drivers during automated driving. It was primarily developed to be used for evaluating Level 3 systems (conditional automated driving). It should be applied in a driving simulator environment during the development phase of a system. The method consists of a test course on a three-lane highway with 12 test scenarios where the driver repeatedly has to take over control from the automated system. Each scenario requires the driver to build up an adequate situation awareness in order to take the decision for the correct action. The method was explicitly designed to map the four relevant steps in the takeover process of automated driving: Perception – Awareness – Decision – Action and is therefore called PADA-AD Test for automated driving. The method description contains guidelines with regard to the specification of the test course and the included test scenarios, the design and duration of the automated drives, the non-driving related task to be performed during the automated drives, the instructions to be given to the subjects and finally the measures for evaluating takeover performance of the drivers.
• A test procedure for the evaluation of takeover performance of drivers during automated driving was developed for usage in a driving simulator during the development phase of a system/HMI
• The test course enables the assessment of the driver's takeover performance in various test scenarios including higher cognitive processes
• The method is highly standardized and thus replicable through use of a predetermined test course with clearly defined scenarios, reduced environmental conditions and "popping up” of situational elements
In the automotive domain, head-up displays (HUD) are well established to present information in the driver’s natural line of sight. Comparable display concepts for motorcyclists would be promising as obtaining riding relevant information from the dashboard typically requires head down gazes away from the forward road scene. Further, depending on powered two-wheeler (PTW) ergonomics and type of helmet, the dashboard is not even within the peripheral field of view.
As there is typically no windscreen in motorcycles that can appropriately be used as projection surface, an alternative transparent display technology is needed. For this purpose, so-called data glasses can be used. The presented user study compared the issuing of riding relevant information (i.e., turn-by-turn instructions) in data glasses and a typical dashboard. N = 24 riders completed a standardized riding task (ISO Lane Change Test) on a dynamic motorcycle riding simulator. In parallel, riders had to react to changing information on the different display concepts. Besides vehicle dynamics data, questionnaire data was gathered and rider workload was measured with the Detection Response Task (DRT). It was observed that information displayed in the data glasses while riding was detected faster and more reliably. The primary riding task performance showed no difference between the two display concepts. Same holds true for the DRT measures, while the subjectively perceived workload was reduced when wearing the data glasses.
Consequently, the study was able to show a benefit of data glasses when it comes to the perception and recognition of time-critical information, such as warnings. Obviously, before providing a potential safety benefit to a broad range of riders, some other questions need to be addressed (e.g., fitting under full face helmet, interface to motorcycle). Yet, this study on innovative display concepts for motorcyclists shows promising results regarding PTW safety of the future.
Relevant riding information such as speed or navigation instructions are typically displayed in head down dashboards on Powered Two-Wheelers. Data glasses provide information directly in the field of view and could, therefore, reduce glances away from the roadway ahead to focus on the dashboard. This study aimed to examine whether providing information in data glasses while riding as compared to classical head down displays makes a difference. Therefore, a total of N = 24 riders completed the ISO lane change test on a motorcycle riding simulator. Meanwhile, riders had to react to changing turn-by-turn indications which were either displayed in the dashboard, in the data glasses or redundantly in both display technologies. The performance in the lane change test and the reaction times achieved in the secondary task were examined along with riders’ workload by means of the Detection Response Task (DRT) and questionnaire data. Results revealed that riders’ lane change performances did not differ between the conditions ‘data glasses’ and ‘dashboard’. Information displayed in the data glasses was recognized faster and fewer turn-by-turn indications were missed. The performance in the DRT remained unchanged throughout the test conditions, while the subjective workload experience decreased with the use of data glasses. Overall, the results suggest that data glasses did not provoke an attentional capture effect and were, therefore, not inferior compared to dashboards regarding riding performance. However, data glasses did reduce the perceived workload and may in particular provide a safety benefit when time-critical information, such as warnings, need to be displayed.
Human Factors Fragestellungen sind ein wachsendes Forschungsfeld im Kontext des automatisierten Fahrens. Trotz der großen Anzahl an neu veröffentlichten Studien zu verschiedenen Themengebieten fällt auf, dass die meisten Studien kein standardisiertes Vorgehen beispielsweise bei der Untersuchung von Übernahmesituationen verwenden, was die Vergleichbarkeit der Ergebnisse untereinan-der erschwert. Ziel des Projekts war die Entwicklung einer standardisierten Prüfanordnung für die Bewertung der Übernahmeleistung, die bei der Untersuchung einer Vielzahl von Fragestellungen zum Einsatz kommen kann. Anwendungsschwerpunkt sollte das hochautomatisierte Fahren (SAE L3) sein, eine Anwendung auf Fragestellungen zum teilautomatisierten Fahren (SAE L2) sollte aber möglich sein. Die Prüfanordnung wurde speziell für den Einsatz im Fahrsimulator entwickelt, sollte aber auch auf der Teststrecke eingesetzt werden können. Sie kann zu verschiedenen Zeitpunkten im Entwicklungsprozess angewendet werden (z.B. entwicklungsbegleitende Studien oder finale Validierung).Die Prüfanordnung wurde nach theoretischer Herleitung entworfen, iterativ weiterentwickelt und in einer Vielzahl an Studien überprüft und validiert. Sie besteht aus einem dreistreifigen Prüfparcours,
in dem der Fahrer mehrmals übernehmen muss. Bei jeder Übernahmesituation muss er neu entscheiden, ob er (1) den Fahrstreifen wechseln muss (weil sein Fahrstreifen durch ein Hindernis blockiert ist), (2) in welche Richtung er den Fahrstreifen wechseln muss (in Abhängigkeit des Ausgangsfahrstreifens), (3) ob ein Wechsel ausreichend ist oder ob zwei Fahrstreifen gewechselt werden müssen, weil beide blockiert sind und (4) ob er vor erforderlichem Fahrstreifenwechsel bremsen muss, da sich Verkehr von hinten nähert oder nicht. Der Fahrer soll sich mit einer visuellen fahrfremden Tätigkeit beschäftigen, um vor der Übernahme vollständig aus dem Loop zu sein. Um einen vorzeitigen Aufbau von Situationsbewusstsein auch bei durchgeführten Kontrollblicken zu verhindern, er-
scheint das Hindernis und der Verkehr erst im Moment der Übernahmeaufforderung.
Der vorliegende Bericht beschreibt den Entwicklungsprozess der Methode auf Basis der theoretischen Überlegungen und der Durchführung mehrerer Simulatorstudien. Über eine Reihe von Vorstudien wurde zunächst der Ablauf des Prüfparcours und die Art und Anzahl der eingesetzten Szenarien definiert. In einer ersten und zweiten Validierungsstudie wurde anschließend die Sensitivität der Prüfanordnung im Hinblick auf HMI-Unterschiede bestätigt. Zudem wurden in diesen Studien weitere Einflussfaktoren auf die Sensitivität der Prüfanordnung, wie das Zeitbudget für die Übernahme sowie die Art der verwendeten fahrfremden Tätigkeit, evaluiert. In einer dritten Validierungs-studie konnte gezeigt werden, dass die Versuchsanordnung auch für Level 2 Fragestellungen, wie die Gestaltung von Driver Monitoring Systemen, geeignet ist. In Form eines „Proof-of-Concepts“ wurde die Prüfanordnung zudem auf die Teststrecke übertragen.
Dazu waren einige Anpassungen notwendig, um die besonderen Gegebenheiten der Prüfanordnung aus dem Simulator abbilden zu können (z. B. hinsichtlich des Erscheinens des Hindernisses und des Verkehrs im Moment der Übernahmeaufforderung). Eine Gruppe von Experten aus dem Bereich der Human Factors Forschung bewertete die verschiedenen Ansätze. Die Ergebnisse dieser Expertenbewertung sowie weiterer Evaluationen des Proof-of-Concepts im Hinblick auf den Implementierungsaufwand und das Übernahmeverhalten lassen die Schlussfolgerung zu, dass die Methode mit be-
stimmten Einschränkungen auf die Teststrecke übertragbar ist.
Human factors issues in automated driving continue to be a growing field of research. Despite the large number of newly published studies on various topics of the field, it is noticeable that most studies do not use a standardized procedure, for example, when investigating takeover situations. This makes it difficult to compare the results with one another. The aim of the project was therefore to develop a standardized test environment for evaluating takeover performance that can be used to investigate a wide range of research questions. The application was supposed to be focused on highly
automated driving (SAE L3), but it should also be applicable to partially automated driving (SAE L2). The test was developed specifically for use in the driving simulator, but its use on the test track should also be possible. It can be applied at various points in the development process (e.g. studies accompanying development or final validation).
The test was designed based on theoretical considerations, iteratively developed and tested and validated in numerous studies. It consists of a three-lane test course in which the driver has to take over several times. In each takeover situation, they have to decide anew whether (1) they have to change lanes (because their lane is blocked by an obstacle), (2) in which direction they have to change lanes (depending on the initial lane), (3) whether one lane change is sufficient or whether two lanes have to be changed (depending on the number of lanes blocked), and (4) whether they have to brake before
a lane change because traffic is approaching from behind or not. The driver should engage in a visual non-driving related activity to be completely out of the loop before taking over. To prevent premature buildup of situational awareness when control glances are performed, the obstacle and traffic do not appear until the moment of the takeover request.This report describes the development process of the method based on the theoretical considerations and the execution of several simulator studies. Through a series of preliminary studies, the sequence of the test course and the type and number of scenarios were first defined. A first and second validation study were then conducted to confirm the sensitivity of the test set-up with respect to HMI differences. In addition, these studies evaluated other factors influencing the sensitivity of the test, such
as the time budget for the takeover and the type of non-driving activity. In a third validation study, it was shown that the test is also suitable for Level 2 research questions, such as the design of driver monitoring systems. The method was also transferred to the test track in the form of a "proof of concept". This required some adjustments in order to be able to reproduce the special conditions of the test in the simulator (e.g. with regard to the appearance of the obstacle and the traffic at the moment of the takeover
request). For this purpose, a group of experts from the field of human factors research evaluated different approaches. The results of this expert evaluation as well as further evaluations of the proof-of-concept with regard to implementation effort and takeover behavior lead to the conclusion that the method is transferable to the test track with certain limitations.
... Interestingly, even participants susceptible to motion sickness did not report differing experiences based on the vehicle deceleration pattern. Tomzig et al. (2023) found that a deceleration style similar to the Two-Step Versions applied in this study could even help to reduce motion sickness symptoms. Future research should systematically investigate how different driving parameters such as acceleration and jerk, and different driving profiles can impact or improve motion sickness symptoms and passengers' feelings of comfort. ...
... A customized airbag west with a rope mechanism is used to cue proprioception of the accelerations and wind forces and can generate forces up to 300N. To simulate the vibrations a shaker is placed beneath the seat (Pless, 2023;Ghafarian et al., 2023;Pless et al., 2016;Will et al., 2016;Delgado Ojeda, 2019;Merkel et al., 2019;Scherer et al., 2020;Westerhof et al., 2020;Grottoli, 2021;Hammer et al., 2021;Will et al., 2022;Merkel et al., 2022). This simulator has been developed to investigate human-machine interfaces on motorcycles (Scherer et al., 2020). ...