Vibrotactile pedals : provision of haptic feedback to support economical driving

The use of haptic feedback is currently an underused modality in the driving environment, especially with respect to vehicle manufacturers. This exploratory study evaluates the effects of a vibrotactile (or haptic) accelerator pedal on car driving performance and perceived workload using a driving simulator. A stimulus was triggered when the driver exceeded a 50% throttle threshold, past which is deemed excessive for economical driving. Results showed significant decreases in mean acceleration values, and maximum and excess throttle use when the haptic pedal was active as compared to a baseline condition. As well as the positive changes to driver behaviour, subjective workload decreased when driving with the haptic pedal as compared to when drivers were simply asked to drive economically. The literature suggests that the haptic processing channel offers a largely untapped resource in the driving environment, and could provide information without overloading the other attentional resource pools used in driving

Smart driving aids and their effects on driving performance and driver distraction

In-vehicle information systems have been shown to increase driver workload and cause distraction; both of which are causal factors for accidents. This simulator study evaluates the impact that two designs for a smart driving aid, and scenario complexity have on workload, distraction and driving performance. Results showed that real-time delivery of smart driving information did not increase driver workload or adversely effect driver distraction, while having the effect of decreasing mean driving speed in both the simple and complex driving scenarios. Subjective workload was shown to increase with task difficulty, as well as revealing important differences between the two interface designs

Holistic Approach for Authoring Immersive and Smart Environments for the Integration in Engineering Education

Die vierte industrielle Revolution und der rasante technologische Fortschritt stellen die etablierten Bildungsstrukturen und traditionellen Bildungspraktiken in Frage. Besonders in der Ingenieurausbildung erfordert das lebenslange Lernen, dass man sein Wissen und seine Fähigkeiten ständig verbessern muss, um auf dem Arbeitsmarkt wettbewerbsfähig zu sein. Es besteht die Notwendigkeit eines Paradigmenwechsels in der Bildung und Ausbildung hin zu neuen Technologien wie virtueller Realität und künstlicher Intelligenz. Die Einbeziehung dieser Technologien in ein Bildungsprogramm ist jedoch nicht so einfach wie die Investition in neue Geräte oder Software. Es müssen neue Bildungsprogramme geschaffen oder alte von Grund auf umgestaltet werden. Dabei handelt es sich um komplexe und umfangreiche Prozesse, die Entscheidungsfindung, Design und Entwicklung umfassen. Diese sind mit erheblichen Herausforderungen verbunden, die die Überwindung vieler Hindernisse erfordert. Diese Arbeit stellt eine Methodologie vor, die sich mit den Herausforderungen der Nutzung von Virtueller Realität und Künstlicher Intelligenz als Schlüsseltechnologien in der Ingenieurausbildung befasst. Die Methodologie hat zum Ziel, die Hauptakteure anzuleiten, um den Lernprozess zu verbessern, sowie neuartige und effiziente Lernerfahrungen zu ermöglichen. Da jedes Bildungsprogramm einzigartig ist, folgt die Methodik einem ganzheitlichen Ansatz, um die Erstellung maßgeschneiderter Kurse oder Ausbildungen zu unterstützen. Zu diesem Zweck werden die Wechselwirkung zwischen verschiedenen Aspekten berücksichtigt. Diese werden in den drei Ebenen - Bildung, Technologie und Management zusammengefasst. Die Methodik betont den Einfluss der Technologien auf die Unterrichtsgestaltung und die Managementprozesse. Sie liefert Methoden zur Entscheidungsfindung auf der Grundlage einer umfassenden pädagogischen, technologischen und wirtschaftlichen Analyse. Darüber hinaus unterstützt sie den Prozess der didaktischen Gestaltung durch eine umfassende Kategorisierung der Vor- und Nachteile immersiver Lernumgebungen und zeigt auf, welche ihrer Eigenschaften den Lernprozess verbessern können. Ein besonderer Schwerpunkt liegt auf der systematischen Gestaltung immersiver Systeme und der effizienten Erstellung immersiver Anwendungen unter Verwendung von Methoden aus dem Bereich der künstlichen Intelligenz. Es werden vier Anwendungsfälle mit verschiedenen Ausbildungsprogrammen vorgestellt, um die Methodik zu validieren. Jedes Bildungsprogramm hat seine eigenen Ziele und in Kombination decken sie die Validierung aller Ebenen der Methodik ab. Die Methodik wurde iterativ mit jedem Validierungsprojekt weiterentwickelt und verbessert. Die Ergebnisse zeigen, dass die Methodik zuverlässig und auf viele Szenarien sowie auf die meisten Bildungsstufen und Bereiche übertragbar ist. Durch die Anwendung der in dieser Arbeit vorgestellten Methoden können Interessengruppen immersiven Technologien effektiv und effizient in ihre Unterrichtspraxis integrieren. Darüber hinaus können sie auf der Grundlage der vorgeschlagenen Ansätze Aufwand, Zeit und Kosten für die Planung, Entwicklung und Wartung der immersiven Systeme sparen. Die Technologie verlagert die Rolle des Lehrenden in eine Moderatorrolle. Außerdem bekommen die Lehrkräfte die Möglichkeit die Lernenden individuell zu unterstützen und sich auf deren kognitive Fähigkeiten höherer Ordnung zu konzentrieren. Als Hauptergebnis erhalten die Lernenden eine angemessene, qualitativ hochwertige und zeitgemäße Ausbildung, die sie qualifizierter, erfolgreicher und zufriedener macht

A Testing and Experimenting Environment for Microscopic Traffic Simulation Utilizing Virtual Reality and Augmented Reality

Microscopic traffic simulation (MTS) is the emulation of real-world traffic movements in a virtual environment with various traffic entities. Typically, the movements of the vehicles in MTS follow some predefined algorithms, e.g., car-following models, lane changing models, etc. Moreover, existing MTS models only provide a limited capability of two- and/or three-dimensional displays that often restrict the user’s viewpoint to a flat screen. Their downscaled scenes neither provide a realistic representation of the environment nor allow different users to simultaneously experience or interact with the simulation model from different perspectives. These limitations neither allow the traffic engineers to effectively disseminate their ideas to various stakeholders of different backgrounds nor allow the analysts to have realistic data about the vehicle or pedestrian movements. This dissertation intends to alleviate those issues by creating a framework and a prototype for a testing environment where MTS can have inputs from user-controlled vehicles and pedestrians to improve their traffic entity movement algorithms as well as have an immersive M3 (multi-mode, multi-perspective, multi-user) visualization of the simulation using Virtual Reality (VR) and Augmented Reality (AR) technologies. VR environments are created using highly realistic 3D models and environments. With modern game engines and hardware available on the market, these VR applications can provide a highly realistic and immersive experience for a user. Different experiments performed by real users in this study prove that utilizing VR technology for different traffic related experiments generated much more favorable results than the traditional displays. Moreover, using AR technologies for pedestrian studies is a novel approach that allows a user to walk in the real world and the simulation world at a one-to-one scale. This capability opens a whole new avenue of user experiment possibilities. On top of that, the in-environment communication chat system will allow researchers to perform different Advanced Driver Assistance System (ADAS) studies without ever needing to leave the simulation environment. Last but not least, the distributed nature of the framework enables users to participate from different geographic locations with their choice of display device (desktop, smartphone, VR, or AR). The prototype developed for this dissertation is readily available on a test webpage, and a user can easily download the prototype application without needing to install anything. The user also can run the remote MTS server and then connect their client application to the server

Validation of driving behaviour as a step towards the investigation of Connected and Automated Vehicles by means of driving simulators

Connected and Automated Vehicles (CAVs) are likely to become an integral part of the traffic stream within the next few years. Their presence is expected to greatly modify mobility behaviours, travel demands and habits, traffic flow characteristics, traffic safety and related external impacts. Tools and methodologies are needed to evaluate the effects of CAVs on traffic streams, as well as the impact on traffic externalities. This is particularly relevant under mixed traffic conditions, where human-driven vehicles and CAVs will interact. Understanding technological aspects (e.g. communication protocols, control algorithms, etc.) is crucial for analysing the impact of CAVs, but the modification induced in human driving behaviours by the presence of CAVs is also of paramount importance. For this reason, the definition of appropriate CAV investigations methods and tools represents a key (and open) issue. One of the most promising approaches for assessing the impact of CAVs is operator in the loop simulators, since having a real driver involved in the simulation represents an advantageous approach. However, the behaviour of the driver in the simulator must be validated and this paper discusses the results of some experiments concerning car-following behaviour. These experiments have included both driving simulators and an instrumented vehicle, and have observed the behaviours of a large sample of drivers, in similar conditions, in different experimental environments. Similarities and differences in driver behaviour will be presented and discussed with respect to the observation of one important quantity of car-following, the maintained spacing

Eye Tracking in the Wild: the Good, the Bad and the Ugly

Modelling human cognition and behaviour in rich naturalistic settings and under conditions of free movement of the head and body is a major goal of visual science. Eye tracking has turned out to be an excellent physiological means to investigate how we visually interact with complex 3D environments, real and virtual. This review begins with a philosophical look at the advantages (the Good) and the disadvantages (the Bad) in approaches with different levels of ecological naturalness (traditional tightly controlled laboratory tasks, low- and high-fidelity simulators, fully naturalistic real-world studies). We then discuss in more technical terms the differences in approach required “in the wild”, compared to “received” lab-based methods. We highlight how the unreflecting application of lab-based analysis methods, terminology, and tacit assumptions can lead to poor experimental design or even spurious results (the Ugly). The aim is not to present a “cookbook” of best practices, but to raise awareness of some of the special concerns that naturalistic research brings about. References to helpful literature are provided along the way. The aim is to provide an overview of the landscape from the point of view of a researcher planning serious basic research on the human mind and behaviou

The impact of background and context on car distance estimation

It is well established that people underestimate the distance to objects depicted in virtual environments and two-dimensional (2D) displays. The reasons for the underestimation are still not fully understood. It is becoming more common to use virtual environment displays for driver training and testing and so understanding the distortion of perceived space that occurs in these displays is vital. We need to know what aspects of the display cause the observer to misperceive the distance to objects in the simulated environments. The research reported in this thesis investigated how people estimate distance between themselves and a car in front of them, within a number of differing environmental contexts. Four experiments were run using virtual environment displays of various kinds and a fifth experiment was run in a real-world setting. It was found that distance underestimation when viewing 2D displays is very common, even when familiar objects such as cars are used as the targets. The experiments also verified that people have a greater underestimation of distance in a virtual environment compared to a real-world setting. A surprising and somewhat counterintuitive result was that people underestimate distance more when the scene depicts forward motion of the observer compared to a static view. The research also identified a number of visual features in the display (e.g., texture information) and aspects of the display (e.g., field of view) that affected the perception of distance or that had no effect. The findings should help the designers of driver-training simulators and testing equipment to better understand the types of errors that can potentially occur when humans view two-dimensional virtual environment displays