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More warning Advanced Driver Assistance Systems (ADAS) will be integrated into the European vehicles in the coming years, due to the ongoing progress on the way to automated driving and Euro NCAP requirements. Furthermore, upcoming technologies like Car-2-X will extend the sensory horizon of ADAS and enable the possibility to warn drivers earlier against various hazards than today. Regarding this progress, increasing numbers of different ADAS warnings will be communicated to the driver. In this context, an important question is how multiple ADAS warnings can be integrated into the Human Machine Interface (HMI) of vehicles and which warning elements are needed to ensure warning acceptance, efficiency and understandability seen from the driver’s point of view.
Two driving simulator studies were conducted and the effects of specific warning elements examined to develop a concept for the integration of upcoming warning ADAS, which focuses on early collision warnings. The implemented early warnings were defined with a warning onset of approximately two seconds before the last possible warning onset. Main questions were whether and how drivers profit from warning direction cues and/or warning object cues for their response to a hazard, and how these cues affect the acceptance of an integrated warning ADAS approach. Furthermore, it was analyzed whether a generalized warning can be used for a cluster of different ADAS concerning the group “warning of collisions”. Therefore critical scenarios in rural and urban surroundings were evaluated, including frontal and lateral (intersections) scenarios. Unnecessary warnings and false alarms have also been taken into account.
The results indicate that early warning direction cues have a high potential to assist drivers with an ADAS warning cluster which covers warning of collisions. In contrast, warning object cues seem to be less important for the drivers’ performance and acceptance regarding early collision warnings. According to these findings, this thesis provides recommendations which warning elements should be included into future ADAS warnings in favor of an integrated warning approach.
Social life is organized around rules and norms. The present experiments investigate the cognitive architecture of rule violations. To do so, a setting with arbitrary rules that had to be followed or broken was developed, and breaking these rules did not have any negative consequences. Removed from any social influences that might further encourage or hinder the rule breaker, results suggest that simply labeling a behavior as a rule violation comes with specific costs: They are more difficult to plan and come with specific behavioral markers during execution. In essence, rule violations resemble rule negations, but they also trigger additional processes.
The question of what makes rule violations more difficult than rule inversions is the major focus of the remaining experiments. These experiments revealed negative affective consequences of rule violation and rule inversions alike, while rule violations additionally prime authority-related concepts, thus sensitizing towards authority related stimuli.
Next, the question how these burdens of non-conformity can be mitigated was investigated, and the influence of having executed the behavior in question frequently and recently was tested in both negations and rule violations. The burdens of non-conformity can best be reduced by a combination of having violated/negated a rule very frequently and very recently. Transfer from another task, however, could not be identified.
To conclude, a model that accounts for the data that is currently presented is proposed. As a variant of a task switching model, it describes the cognitive processes that were investigated and highlights unique processing steps that rule violations seem to require.
Driving simulators are powerful research tools. Countless simulator studies have contributed to traffic safety over the last decades. Constant improvements in simulator technology call for a measureable scale to assess driving simulators with regard to their utility in human factors research. A promising psychological construct to do so is presence. It is commonly defined as the feeling of being located in a remote or virtual environment that seems to be real. Another aspect of presence describes the ability to act there successfully.
The main aim of this thesis is to develop a presence model dedicated to the application in driving simulators. Established models have been combined and extended in order to gain a comprehensive model of presence that allows understanding its emergence and deriving recommendations on how to design or improve driving simulators. The five studies presented in this thesis investigate specific postulated model components and their interactions. All studies deal with motorcycling or a motorcycle riding simulator as exemplary field of application.
The first study used a speed estimation task to investigate the contribution of different sensory cues to presence. While visualization plays a particularly important role, further improvements could be achieved by adding more consistent sensory stimuli to the virtual environment. Auditory, proprioceptive and vestibular cues have been subject to investigation. In the second study, the speed production method was applied. It confirmed the positive contribution of action to presence as predicted by psychocybernetic models. The third study dealt with the effect of training on presence. Hence, no positive effect was observed. The fourth study aimed at replicating previous findings on sensory fidelity and diversity in a more complex riding situation than only longitudinal vehicle control. The riders had to cross an unexpectedly appearing deep pit with the virtual motorcycle. The contribution of more consistent sensory stimulation on presence was successfully shown in this scenario, too. The final study was a real riding experiment that delivered reference values for the speed estimation capabilities of motorcycle riders. Besides higher variations in the simulator data, the general speed estimation performance was on a comparable level. Different measures, such as subjective ratings, behavioral responses, performance, and physiological reactions, have been applied as presence indicators.
These studies’ findings deliver evidence for the meaningful application of the proposed presence model in driving simulator settings. The results suggest that presence can be interpreted as a quality measure for perception in virtual environments. In line with psychocybernetic models, taking action, which is seen as controlling perception, enhances this quality even further. Describing the psychological construct of presence in a theoretical framework that takes the diversity of perception and action in driving simulator settings into account closes a gap in traffic psychological research.
Fahrzeughersteller haben die Verfügbarkeit sogenannter hochautomatisierter Fahrfunktionen (SAE Level 3; SAE, 2018) in ihren Modellen angekündigt. Hierdurch wird der Fahrer in der Lage sein, sich permanent von der Fahraufgabe abzuwenden und fahrfremden Tätigkeiten nachzugehen. Allerdings muss er immer noch als Rückfallebene zur Verfügung stehen, um im Fall von Systemgrenzen oder -fehlern (siehe Gold, Naujoks, Radlmayr, Bellem & Jarosch, 2017), die Fahrzeugkontrolle zu übernehmen. Das Übernahmeerfordernis wird dem Fahrer durch die Ausgabe einer Übernameaufforderung vermittelt. Die Übernahme der manuellen Fahrzeugführung aus dem hochautomatisierten Fahren stellt aus psychologischer Sicht einen Aufgabenwechsel dar. Bei der Untersuchung von Aufgabenwechseln im Bereich der kognitiven und angewandten Psychologie zeigte sich vielfach, dass Aufgabenwechsel mit verlängerten Reaktionszeiten und erhöhten Fehlerraten assoziiert sind. Für den Anwendungsfall des automatisierten Fahrens liegen ebenfalls eine Reihe empirischer Studien vor, die darauf hinweisen, dass der Wechsel zum manuellen Fahren mit einer Verschlechterung der Fahrleistung gegenüber dem manuellen Fahren verbunden ist. Da Erkenntnisse vorliegen, dass eine Vorbereitung auf den Aufgabenwechsel die zu erwartenden Kosten verringern kann, ist das Ziel dieser Arbeit die Konzeption und empirische Evaluation einer Mensch-Maschine-Schnittstelle, die Nutzer hochautomatisierter Fahrzeuge durch frühzeitige Vorinformationen über Systemgrenzen auf die Kontrollübernahme vorbereitet.
Drei Experimente im Fahrsimulator mit Bewegungssystem betrachteten jeweils unterschiedliche Aspekte frühzeitiger Vorinformationen über bevorstehende Übernahmen. Das erste Experiment untersuchte, ob Fahrer überhaupt von frühzeitigen Situationsankündigungen, beispielsweise im Sinne einer verbesserten Übernahmeleistung, profitieren. Das zweite Experiment befasste sich mit der Frage, wie solche Ankündigungen zeitlich und inhaltlich zu gestalten sind (d. h. wann sie präsentiert werden und welche Informationen sie enthalten sollten), und welchen Einfluss deren Gestaltung auf die Aufgabenbearbeitung (insbesondere deren Unterbrechung und spätere Wiederaufnahme) während der automatisierten Fahrt hat. Um herauszufinden, wie ein Anzeigekonzept zur längerfristigen Planung von fahrfremden Tätigkeiten während des automatisierten Fahrens beitragen könnte, fand im dritten Experiment ein Vergleich von Situationsankündigungen, die vor dem Erreichen einer Übernahmesituation ausgegeben wurden, mit kontinuierlich präsentierten Informationen über die verbleibende Distanz zur nächsten Systemgrenze statt. In allen Studien wurde neben den Auswirkungen frühzeitiger Vorinformationen auf die Übernahmeleistung und Bearbeitung von fahrfremden Tätigkeiten auch untersucht, welche Auswirkungen ein erweitertes Übernahmekonzept auf die Fahrerreaktion in Grenz- und Fehlerfällen, in denen Vorinformationen entweder nicht oder fehlerhaft angezeigt wurden, hat.
Für die Gestaltung zukünftiger Übernahmekonzepte für hochautomatisierte Fahrzeuge kann basierend auf den Ergebnissen empfohlen werden, frühzeitige Anzeigen von Systemgrenzen zur Ermöglichung eines sicheren und komfortablen Wechsels zwischen dem manuellen und dem automatisierten Fahren in die Mensch-Maschine-Schnittstelle zu integrieren. Basierend auf den Ergebnissen dieser Arbeit liegt der empfohlene Zeitpunkt für diskrete Ankündigungen bei einer Reisegeschwindigkeit von 120 km/h bei etwa 1000 Meter (d. h. ca. 30 Sekunden) vor der Ausgabe der Übernahmeaufforderung. Zudem wird empfohlen zur Abschätzung der verbleibenden Zeit im automatisierten Modus eine Anzeige der Entfernung zur nächsten Systemgrenze in das Konzept zu integrieren, die dem Fahrer eine längerfristige Aufgabenplanung ermöglicht. Neben der reinen Anzeige des Übernahmeerfordernisses sollten dem Fahrer auch Informationen über das erforderliche Fahrmanöver nach der Kontrollübernahme übermittelt werden.
Human actions are generally not determined by external stimuli, but by internal goals and by the urge to evoke desired effects in the environment. To reach these effects, humans typically have to act. But at times, deciding not to act can be better suited or even the only way to reach a desired effect. What mental processes are involved when people decide not to act to reach certain effects? From the outside it may seem that nothing remarkable is happening, because no action can be observed. However, I present three studies which disclose the cognitive processes that control nonactions.
The present experiments address situations where people intentionally decide to omit certain actions in order to produce a predictable effect in the environment. These experiments are based on the ideomotor hypothesis, which suggests that bidirectional associations can be formed between actions and the resulting effects. Because of these associations, anticipating the effects can in turn activate the respective action. The results of the present experiments show that associations can be formed between nonactions (i.e., the intentional decision not to act) and the resulting effects. Due to these associations, perceiving the nonaction effects encourages not acting (Exp. 1–3). What is more, planning a nonaction seems to come with an activation of the effects that inevitably follow the nonaction (Exp. 4–5). These results suggest that the ideomotor hypothesis can be expanded to nonactions and that nonactions are cognitively represented in terms of their sensory effects. Furthermore, nonaction effects can elicit a sense of agency (Exp. 6–8). That is, even though people refrain from acting, the resulting nonaction effects are perceived as self-produced effects.
In a nutshell, these findings demonstrate that intentional nonactions include specific mechanisms and processes, which are involved, for instance, in effect anticipation and the sense of agency. This means that, while it may seem that nothing remarkable is happening when people decide not to act, complex processes run on the inside, which are also involved in intentional actions.
The rise of automated driving will fundamentally change our mobility in the near future. This thesis specifically considers the stage of so called highly automated driving (Level 3, SAE International, 2014). At this level, a system carries out vehicle guidance in specific application areas, e.g. on highway roads. The driver can temporarily suspend from monitoring the driving task and might use the time by engaging in so called non-driving related tasks (NDR-tasks). However, the driver is still in charge to resume vehicle control when prompted by the system. This new role of the driver has to be critically examined from a human factors perspective.
The main aim of this thesis was to systematically investigate the impact of different NDR-tasks on driver behavior and take-over performance. Wickens’ (2008) architecture of multiple resource theory was chosen as theoretical framework, with the building blocks of multiplicity (task interference due to resource overlap), mental workload (task demands), and aspects of executive control or self-regulation. Specific adaptations and extensions of the theory were discussed to account for the context of NDR-task interactions in highly automated driving.
Overall four driving simulator studies were carried out to investigate the role of these theoretical components. Study 1 showed that drivers focused NDR-task engagement on sections of highly automated compared to manual driving. In addition, drivers avoided task engagement prior to predictable take-over situations. These results indicate that self-regulatory behavior, as reported for manual driving, also takes place in the context of highly automated driving. Study 2 specifically addressed the impact of NDR-tasks’ stimulus and response modalities on take-over performance. Results showed that particularly visual-manual tasks with high motoric load (including the need to get rid of a handheld object) had detrimental effects. However, drivers seemed to be aware of task specific distraction in take-over situations and strictly canceled visual-manual tasks compared to a low impairing auditory-vocal task. Study 3 revealed that also the mental demand of NDR-tasks should be considered for drivers’ take-over performance. Finally, different human-machine-interfaces were developed and evaluated in Simulator Study 4. Concepts including an explicit pre-alert (“notification”) clearly supported drivers’ self-regulation and achieved high usability and acceptance ratings.
Overall, this thesis indicates that the architecture of multiple resource theory provides a useful framework for research in this field. Practical implications arise regarding the potential legal regulation of NDR-tasks as well as the design of elaborated human-machine-interfaces.
Cognitive control is what makes goal-directed actions possible. Whenever the environment or our impulses strongly suggests a response that is incompatible with our goals, conflict arises. Such conflicts are believed to cause negative affect. Aversive consequences of conflict may be registered in a conflict monitoring module, which subsequently initiates attentional changes and action tendencies to reduce negative affect. This association suggests that behavioral adaptation might be a reflection of emotion regulation. The theoretical cornerstone of current research on emotion regulation is the process model of emotion regulation, which postulates the regulation strategies situation selection, situation modification, attentional deployment, cognitive change, and response modulation. Under the assumption that conflict adaptation and affect regulation share common mechanisms, I derived several predictions regarding cognitive control from the process model of emotion regulation and tested them in 11 experiments (N = 509). Participants engaged in situation selection towards conflict, but only when they were explicitly pointed to action-outcome contingencies (Experiments 1 to 3). I found support for a mechanism resembling situation modification, but no evidence for a role of affect (Experiments 4 to 10). Changing the evaluation of conflict had no impact on the extent of conflict adaptation (Experiment 11). Overall, there was evidence for an explicit aversiveness of cognitive conflict, but less evidence for implicit aversiveness, suggesting that conflict may trigger affect regulation processes, particularly when people explicitly have affect regulation goals in mind.
Die aktuellen Veränderungen der Arbeitswelt erfordern eine stetige Anpassung an immer neue Herausforderungen seitens der Arbeitgeber und Arbeitnehmer. Lebenslanges Lernen und damit eine kontinuierliche Weiterbildung der Mitarbeiter ist essentiell für Unternehmen, um auf dem schnelllebigen Arbeitsmarkt wettbewerbsfähig zu sein. Die Bereitschaft und die Motivation von Menschen, dazuzulernen, ist jedoch sehr unterschiedlich. Eine mögliche Erklärung dafür liefert die dispositionelle Zielorientierung, welche der Achievement-Goal-Theorie entstammt. Das Konstrukt beschreibt, ob Menschen eine individuelle Präferenz für Lernziele (z.B. Kompetenzzuwachs) oder Leistungsziele (z.B. gute Beurteilungen bekommen oder schlechte Beurteilungen vermeiden) haben. Neben den Persönlichkeitsaspekten konzentriert sich die Forschung im Rahmen der Achievement-Goal-Theorie auch auf den Einfluss der Umgebung auf Lern- und Leistungsprozesse. Die sogenannte arbeitsplatzbezogene Zielorientierung beschreibt die wahrgenommene Zielstruktur der Arbeitsumgebung und stellt das situationsbedingte Gegenstück der Dispositionen dar. Zahlreiche Befunde aus dem Bereich der pädagogischen Psychologie zu Zielstrukturen der Umgebung zeigen einen Einfluss auf beispielsweise Lernerfolg, Motivation, Selbstregulationsprozesse oder Leistung. Zielstrukturen im Arbeitskontext stellen hingegen ein bisher wenig beachtetes Konstrukt dar. Ausgehend von den aktuellen Befunden zu Zielstrukturen, könnte die arbeitsplatzbezogene Zielorientierung jedoch einen wichtigen Beitrag leisten, wenn es um die Frage geht, wie Mitarbeiter unterstützt und zu Lernprozessen angeregt werden können. Die Identifizierung von lern- und leistungsförderlichen Zielstrukturen der Arbeitsumgebung würde wertvolle Ansatzpunkte für die Mitarbeiterentwicklung in der betrieblichen Praxis liefern.
Im Rahmen von drei empirischen Studien wird der Relevanz der Zielorientierung im Arbeits-kontext nachgegangen. Neben der Überprüfung eines ins Deutsche übertragenen und angepassten Mess-instruments zur Erhebung der arbeitsplatzbezogenen Zielorientierung (Studie 1) steht vor allem die Untersuchung möglicher Einflüsse des Konstrukts auf arbeitsrelevante Variablen im Vordergrund, um förderliche Zielstrukturen zu identifizieren (Studie 1 & 2). Darüber hinaus werden erstmalig mögliche Person-Situation-Interaktionen in diesem Zusammenhang untersucht (Studie 2). Abschließend erfolgt eine Untersuchung möglicher Antezedenten der arbeitsplatzbezogenen Zielorientierung, woraus sich erste wichtige Anhaltspunkte für Interventionsmaßnahmen am Arbeitsplatz ableiten lassen (Studie 3).
Die Ergebnisse der Studien zeigen, dass insbesondere ein lernzielorientierter Arbeitsplatz förderlich für die untersuchten Variablen wie Lernerfolg, Leistung oder auch berufliche Selbstwirksamkeit ist. In Bezug auf die Interaktion von Person und Situation ergaben sich gemischte Befunde, die kein eindeutiges Interaktionsmuster aufweisen. Bei der Frage, wie ein lernzielorientierter Arbeitsplatz gefördert werden kann, erwies sich vor allem die Art und Weise, wie Führungskräfte mit Fehlern umgehen, als relevant. Die Studien liefern demnach wichtige erste Ansätze für theoretische und praktische Implikationen, wie Mitarbeiter in Lern- und Leistungsprozessen unterstützt werden können.
Errors in Prospective Memory
(2019)
Prospective memory is the ability to implement intentions at a later point in time in response to a specified cue. Such prospective memory tasks often occur in daily living and workplace situations. However, in contrast to retrospective memory there has been relatively little research on prospective memory. The studies by Harris (1984) and Einstein and MacDaniel (1990) served as a starting point for a now steadily growing area of research. Based on this emerging field of study this dissertation presents and connects and five journal articles, which further explore prospective memory by focusing on its potential errors.
The first article addresses the question if additional cognitive resources are needed after a prospective memory cue occurs to keep the intention active until it is implemented. The theory by Einstein, McDaniel, Williford, Pagan and Dismukes (2003), which suggested this active maintenance, could not be replicated. The second article demonstrated that interruptions between cue and the window of opportunity to implement the intention reduce prospective memory performance, especially if the interruption is tied with a change of context. Article three to five were focused on the erroneous implementation of a no longer active prospective memory task, so called commission errors. The suggested mechanism for their occurrence, the dual-mechanism account (Bugg, Scullin, & Rauvola, 2016), was not suited to explain the present results. A modification for the dual-mechanism account was formulated, which can account for prior work, as well as for the present data.
The results of all five articles also indicate that the moment of cue retrieval is even more relevant for prospective memory and its errors than previously accounted for.
The increasing importance of environmental friendly and efficient transportation guides the interest of researchers and car manufacturers towards the development of technologies that support an efficient driving style.
This thesis presents the development of a traffic light assistance system with the focus on human factors. The system aims on supporting drivers in approaching traffic light intersections efficiently. In three driving simulator studies, the content related research covered the investigation of the unassisted driving task, the influence of the system on the driver’s perception of the interaction with other road users and the information strategy of the human machine interface. When the traffic light phase changes or when visibility is limited, drivers prepare driving behaviour that is not appropriate for the traffic light phase at arrival at the intersection. These situations offer the greatest potential for the assistance system. The traffic light assistant is able to change driving behaviour. However, the expectation of other road user’s emotional reactions influences driver compliance. In situations in which drivers expected to bother others with their driving behaviour, compliance to the traffic light assistant was low. Further, the deviations of driver behaviour from the target strategy of the traffic light assistant are lowest when the HMI includes the two information units target speed and action recommendations. Traffic light phase information in the HMI is a subjectively important information for drivers. The results point towards the presentation of all three information units.
The method related research covered the development of a method for measuring drivers’ information demand for dynamic stimuli. While driving, specific stimuli are action relevant for drivers, i.e. they need to be processed in order to decide on the appropriate driving behaviour. Eye tracking has been the standard method for measuring information demand while driving. The novel MARS (Masking Action Relevant Stimuli) method measures information demand by masking the dynamic action relevant stimulus in the driving environment or in the vehicle. To unmask the stimulus for a fixed interval, drivers press a button at the steering wheel. In the present thesis, two driving simulator studies evaluated the MARS method. They included measuring information demand for the traffic light phasing and the in-vehicle display of the traffic light assistant. The analyses demonstrate that variations in the experimental conditions influence the information demand measured with the MARS method qualitatively similar to the influences on fixations measured by eye tracking. Due to its simple application, the MARS method represents a promising tool for transportation research.