User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system's status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers' expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone. [Abstract copyright: Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.

User expectations of partial driving automation capabilities and their effect on information design preferences in the vehicle

Partially automated vehicles present interface design challenges in ensuring the driver remains alert should the vehicle need to hand back control at short notice, but without exposing the driver to cognitive overload. To date, little is known about driver expectations of partial driving automation and whether this affects the information they require inside the vehicle. Twenty-five participants were presented with five partially automated driving events in a driving simulator. After each event, a semi-structured interview was conducted. The interview data was coded and analysed using grounded theory. From the results, two groupings of driver expectations were identified: High Information Preference (HIP) and Low Information Preference (LIP) drivers; between these two groups the information preferences differed. LIP drivers did not want detailed information about the vehicle presented to them, but the definition of partial automation means that this kind of information is required for safe use. Hence, the results suggest careful thought as to how information is presented to them is required in order for LIP drivers to safely using partial driving automation. Conversely, HIP drivers wanted detailed information about the system’s status and driving and were found to be more willing to work with the partial automation and its current limitations. It was evident that the drivers’ expectations of the partial automation capability differed, and this affected their information preferences. Hence this study suggests that HMI designers must account for these differing expectations and preferences to create a safe, usable system that works for everyone

Agentengestützte Verkehrssteuerung an Straßenkreuzungen unter Berücksichtigung der Wertschätzung der Fahrer

Verkehrsteilnehmer besitzen unterschiedliche Wertschätzungen für eine geringe Reisezeit. Klassische Verfahren zur Verkehrssteuerung an Straßenkreuzungen berücksichtigen diese Wertschätzungen nur unzureichend. In dieser Arbeit werden agentengestützte Mechanismen für die Verkehrssteuerung an Straßenkreuzungen entwickelt, die die individuelle Wertschätzung der Verkehrsteilnehmer berücksichtigen. Dabei zeigt sich, dass solche Mechanismen klassischen Verfahren überlegen sind

Automation and transition in motor vehicles - User-centered design of take-over situations within a multilevel automation approach

Die Arbeit beschäftigt sich mit der nutzerzentrierten Gestaltung von Übergabe- und Übernahmesituationen im Fahrkontext. Diese beziehen sich auf einen vierstufigen Automationsansatz, der sich vom manuellen über das assistierte, teilautomatisierte bis hin zum hochautomatisierten Fahren erstreckt. Im Kern der betrachteten Transitionen zwischen Fahrer und Automation stand die Frage, ob dem Fahrer zu jeder Zeit transparent ist, welcher Systemmodus gerade aktiv ist und wie dessen Abhängigkeiten zu den anderen Fahrfunktionen definiert sind. Das Augenmerk lag auf Übergangsszenarien die mit hoher Wahrscheinlichkeit zu einem geminderten Systemmodusbewusstsein führen und Effekte wie Modusverwechslungen oder Handlungsfehler forcieren können. In dieser Arbeit waren sie durch unterschiedliche Grade der Kontrollverschiebung charakterisiert, gingen mit indirekten Transitionen auf Zwischenstufen der Automation einher, berücksichtigten einander funktional ähnliche Systemmodi und schlossen Aktivierungs- als auch Deaktivierungssituationen ein. Die Untersuchung jener Übergänge erfolgte in zwei Studien. Während einer realen sowie simulierten Autobahnfahrt konnte der Fahrer hier neben manuellen Anteilen ein Adaptive Cruise Control und integrierte Systemauslegungen mit zusätzlich assistierter oder automatisierter Querführung nutzen. Die Ergebnisse zeigen, dass weniger das Ausmaß an Automatisierung Einfluss auf die Güte des Modusbewusstseins des Fahrers hat, sondern eher der kognitive Aufwand bei der Differenzierung noch zu übernehmender Anteile der Fahraufgabe. Ist der Fahrer noch in den Regelkreis Fahrer-Fahrzeug-Straße eingekoppelt, wird eine hierarchische (De-)Aktivierung von Systemen empfohlen. Ist dies nicht mehr der Fall, passt hingegen eine Entweder-oder-Logik besser zur mentalen Fahrerrepräsentation. Weicht das tatsächliche Systemverhalten von dem Erwarteten ab, lassen sich diese Inkonsistenzen im mentalen Nutzermodell anhand verzögerter Fahrerreaktionen, höherer Fahrerbeanspruchungen und nutzerseitigen Angaben zur Intransparenz der Transition nachweisen. Handlungsfehler treten ausschließlich nur dann auf, wenn sich einander funktional ähnliche Systeme in der verfügbaren Automationsbandbreite befinden. So bewirkt die Verwechslung der Systemmodi in diesem Fall falsche Annahmen über den Systemstatus und bedingt eine inadäquate Informationsaufnahme sowie Reaktion der Fahrer. Die Arbeit zeigt, dass vor allem Aktivierungsszenarien für diese Automation Surprises sensitiv sind.The present thesis deals with the user-centered design of handover and takeover situations in the context of driving. These relate to four stages of an automation concept, which ranges from manual and assisted driving to partly autonomous and highly autonomous driving. The central question regarding the considered transitions between driver and automation is whether it is transparent to the driver which system mode is active at the moment, what the active system does and how it depends on other driving functionalities. Particular attention was paid to transition scenarios, which, referring to aviation research, are most likely to cause reduced system mode awareness and unintended effects like mode confusion and mode errors. Those transitions were characterized by different levels of control allocation and included indirect transitions to intermediate levels of automation. They also included functionally similar system modes, and both activation and deactivation situations. The evaluation of these transitions happened in two empirical studies. During a real and a simulated highway drive, the driver could use an Adaptive Cruise Control and integrated system conceptions including assisted or automated lateral control next to manual portions of the drive. The results of this thesis demonstrate that it is not the level of automation that affects the driver’s awareness about the system mode. His awareness level is rather affected by the cognitive effort to differentiate parts of the driving tasks that still need to be controlled manually. Is the driver still a part of the control loop between “driver-vehicle-road”, a hierarchical (de-)activation of systems is recommended. If this is not the case anymore, an “either-or” logic fits better to the mental representation of the driver. If there is a difference between the expected and the actual behavior of the system, delayed driver reactions, higher driver workload and statements about lack of system transparency during transitions are the consequence. However, mistakes in action execution solely occur when functionally similar systems are located in the available automation range. In that case, mode confusion results in false assumptions about the current system status, inadequate assimilation of information as well as false driver reaction. The present thesis shows that these automation surprises primarily arise during activation scenarios