Towards a dynamic balance between humans and automation: authority, ability, responsibility and control in shared and cooperative control situations

Progress enables the creation of more automated and intelligent machines with increasing abilities that open up new roles between humans and machines. Only with a proper design for the resulting cooperative human–machine systems, these advances will make our lives easier, safer and enjoyable rather than harder and miserable. Starting from examples of natural cooperative systems, the paper investigates four cornerstone concepts for the design of such systems: ability, authority, control and responsibility, as well as their relationship to each other and to concepts like levels of automation and autonomy. Consistency in the relations between these concepts is identified as an important quality for the system design. A simple graphical tool is introduced that can help to visualize the cornerstone concepts and their relations in a single diagram. Examples from the automotive domain, where a cooperative guidance and control of highly automated vehicles is under investigation, demonstrate the application of the concepts and the tool. Transitions in authority and control, e.g. initiated by changes in the ability of human or machine, are identified as key challenges. A sufficient consistency of the mental models of human and machines, not only in the system use but also in the design and evaluation, can be a key enabler for a successful dynamic balance between humans and machines.

[1]  Ernst Dieter Dickmanns.  VISION FOR GROUND VEHICLES: HISTORY AND PROSPECTS , 2002 .

[2]  R. Bruder,et al.  Conduct-by-Wire - ein neues Paradigma für die Entwicklung der Fahrerassistenz , 2006 .

[3]  Kenneth H. Goodrich,et al.  Application of the H-Mode, A Design and Interaction Concept for Highly Automated Vehicles, to Aircraft , 2006, 2006 ieee/aiaa 25TH Digital Avionics Systems Conference.

[4]  Robert Karasek,et al.  Job decision latitude and mental strain: Implications for job redesign , 1979 .

[5]  John R. Wilson,et al.  Mental Models: Theory and Application in Human Factors , 1989 .

[6]  Frank Flemisch,et al.  The search for pilot's ideal complement: experimental results with the crew assistant military Aircraft CAMA , 1999, HCI.

[7]  Frank Flemisch,et al.  Some Bridging Methods towards a Balanced Design of Human-Machine Systems, Applied to Highly Automated Vehicles , 2008 .

[8]  Angelos Amditis,et al.  Highly Automated Vehicles for Intelligent Transport: Have-It Approach , 2008 .

[9]  Kenneth H. Goodrich,et al.  A Design and Interaction Concept for Aircraft with Variable Autonomy: Application of the H-Mode , 2006 .

[10]  Sidney W A Dekker,et al.  Reconstructing human contributions to accidents: the new view on error and performance. , 2002, Journal of safety research.

[11]  Frank Köster,et al.  How to interact with a highly automated vehicle. Generic interaction design schemes and test results of a usability assessment , 2011 .

[12]  Raja Parasuraman,et al.  Designing for Flexible Interaction Between Humans and Automation: Delegation Interfaces for Supervisory Control , 2007, Hum. Factors.

[13]  David E. Cox,et al.  The Naturalistic Flight Deck System: An Integrated System Concept for Improved Single-Pilot Operations , 2007 .

[14]  Paul C. Schutte,et al.  The H-Metaphor as a Guideline for Vehicle Automation and Interaction , 2005 .

[15]  Markus Maurer,et al.  Stadtpilot: Driving autonomously on Braunschweig's inner ring road , 2010, 2010 IEEE Intelligent Vehicles Symposium.

[16]  Richard I. Cook,et al.  Nine Steps to Move Forward from Error , 2002, Cognition, Technology & Work.

[17]  Sebastian Thrun,et al.  Stanley: The robot that won the DARPA Grand Challenge , 2006, J. Field Robotics.

[18]  Lisanne Bainbridge,et al.  Ironies of automation , 1982, Autom..

[19]  Michael A. Goodrich,et al.  Multiple mental models, automation strategies, and intelligent vehicle systems , 1999, Proceedings 199 IEEE/IEEJ/JSAI International Conference on Intelligent Transportation Systems (Cat. No.99TH8383).

[20]  Colin Potts,et al.  Design of Everyday Things , 1988 .

[21]  Sebastian Thrun,et al.  Junior: The Stanford entry in the Urban Challenge , 2008, J. Field Robotics.

[22]  Mica R. Endsley,et al.  The Out-of-the-Loop Performance Problem and Level of Control in Automation , 1995, Hum. Factors.

[23]  Charles E. Billings,et al.  Aviation Automation: The Search for A Human-centered Approach , 1996 .

[24]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[25]  Christian Löper,et al.  Links oder rechts, schneller oder langsamer? Grundlegende Fragestellungen beim Cognitive Systems Engineering von hochautomatisierter Fahrzeugführung , 2006 .

[26]  Earl L. Wiener,et al.  Human factors of advanced technology (glass cockpit) transport aircraft , 1989 .

[27]  Chris Miller.  Using Delegation as an Architecture for Adaptive Automation , 2005 .

[28]  Toshiyuki Inagaki,et al.  Automation and the Cost of Authority , 2003 .

[29]  Roland Siegwart,et al.  From Aviation down to Vehicles - Integration of a Motions-Envelope as Safety Technology , 2006 .

[30]  Benoit Vanholme,et al.  Towards Highly Automated Driving: Intermediate report on the HAVEit-Joint System , 2010 .

[31]  Christian Löper,et al.  Haptisch-multimodale Interaktion für hochautomatisierte, kooperative Fahrzeugführung bei Fahrstreifenwechsel-, Brems- und Ausweichmanövern , 2010 .

[32]  W. Brian Arthur,et al.  The Nature of Technology: What it Is and How it Evolves , 2009 .