Abstract
As the first automated driving functions are now finding their way into serial production vehicles, the focus of research and development has shifted from purely automated capabilities to cooperative systems, i.e. cooperation between vehicles, and vehicle automation with drivers. Especially in partially and highly automated cooperative driving the driver should be able to take over the driving task or adapt the driving behavior. This paper presents the pattern approach to cooperation as a method to recognize and solve reoccurring problems. As an example, the pattern approach is applied to the use case of a takeover request on a highway. The concept of Confidence Horizons, which balance the capabilities of the driver and the automation based on cooperative interaction patterns, is introduced. To estimate the human capabilities for this Confidence Horizon, a Diagnostic Takeover Request is used, in which the automation analyzes the driver’s orientation reaction to a takeover request. This allows the early detection of potentially unsafe takeovers reducing possible transitions to a Minimum Risk Maneuver (MRM).
Zusammenfassung
Mit Einzug der ersten automatisierten Fahrfunktionen in die Serienproduktion von Fahrzeugen hat sich der Schwerpunkt der Forschung und Entwicklung von der reinen Automatisierung hin zu kooperativen Systemen verlagert, d.h. zur Zusammenarbeit zwischen Fahrzeugen, sowie von Fahrzeugautomatisierung und Fahrenden. Speziell im hoch- und teilautomatisierten Fahren sollten Fahrende die Möglichkeit haben, die Fahraufgabe zu übernehmen bzw. das Fahrverhalten anzupassen.
Dieser Artikel präsentiert einen Musteransatz als Methode zur Erkennung und Lösung wiederkehrender Probleme im Bereich der Kooperation. Der Musteransatz wird beispielhaft auf einen Anwendungsfall einer Übernahmeaufforderung (TOR) auf der Autobahn angewendet.
Mit dem Konfidenzhorizontkonzept lassen sich die Fähigkeiten von Fahrerinnen und Fahrern und der Automation basierend auf kooperativen Interaktionsmustern ausbalancieren. Um die menschlichen Fähigkeiten für den Konfidenzhorizont abzuschätzen, wird eine diagnostische Übernahmeaufforderung eingesetzt. Diese erlaubt eine frühe Detektion potenziell unsicherer Übernahmen und die Reduzierung von nötigen Transitionen in ein minimalriskantes Manöver (MRM).
About the authors
Frank Flemisch studied aerospace engineering at the University of the German Armed Forces in Munich, where he also gained his Ph.D./Dr.-Ing. His doctoral thesis dealt with the interaction between cockpit assistance systems and human gaze behavior. As a research associate at NASA, he worked on cooperative control of highly automated airplanes with the goal of “making flying as easy as driving a car.” From 2004 to 2011, he led a research team for system ergonomics and the design of automated cars and trucks at DLR-IST in Braunschweig, where he and his team transferred the concept of high automation to the ground vehicle domain. He was a member of the BASt group “Legal Consequences of Increasing Vehicle Automation” and is a technical expert in ISO WG 204 (Intelligent Transport Systems). Since 2011, he has been working as a department head at Fraunhofer FKIE (Wachtberg) and is professor for system ergonomics at RWTH Aachen University.
Marcel Usai has studied Electrical Engineering with specialization in systems and automation at RWTH Aachen University, Germany. Since 2018 he has worked as a research assistant and Ph.D. candidate at the Institute of Industrial Engineering and Ergonomics (IAW) at RWTH Aachen University. His current research focus is fluid human-machine cooperation in cooperative driving.
Gina Wessel is a research assistant at the department of Human Systems Integration at the RWTH Aachen University. Her research focuses on naturalistic arbitration patterns and nudging in the context of automated driving.
Nicolas Herzberger is research group manager for system ergonomics at the Institute of Industrial Engineering and Ergonomics (IAW) at the RWTH Aachen University and research group manager for balanced Human Systems Integration at the Fraunhofer FKIE. His current research focus is human-machine interaction, especially in the context of partially and highly automated driving. In this context, he focuses on the topics of cooperative guidance and control, operator monitoring, and user-centered evaluation of new vehicle concepts.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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