Human factors of transitions in automated driving: A general framework and literature survey |
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| Institution: | 1. Department of BioMechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, The Netherlands;2. Future Resilient Systems Singapore-ETH Centre, ETH Zurich, Singapore;1. VEDECOM (Institute for Decarbonized, Connected Vehicles and New Mobility Solutions), France;2. Virtual Reality and Immersive Simulation Center, Renault, Technocentre, France;3. Laboratory of Driver Psychology, IFSTTAR, France;4. Renault, Technocentre, France;1. Institute for Transport Studies, University of Leeds, UK;2. Seeing Machines, Canberra, Australia;1. Department of BioMechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Mekelweg 2, 2628 CD Delft, The Netherlands;2. Centre for Transport Studies, University of Twente, Drienerlolaan 5, 7522 NB Enschede, The Netherlands;3. TNO Human Factors, Kampweg 5, 3769 DE Soesterberg, The Netherlands;4. Transportation Research Group, Civil, Maritime, Environmental Engineering and Science, Engineering and the Environment, University of Southampton, United Kingdom;1. Wuerzburg Institute for Traffic Sciences (WIVW GmbH), Robert-Bosch-Str. 4, Veitshoechheim, 97209, Germany;2. Interdisciplinary Center for Traffic Sciences (IZVW), University of Wuerzburg, Wuerzburg, 97070, Germany;3. Interdisciplinary Center for Traffic Sciences (IZVW), University of Wuerzburg, Wuerzburg, 97070, Germany;4. Institute of Psychology, University of Wuerzburg, Wuerzburg, 97070, Germany;1. Daimler AG, Research and Development, Hanns-Klemm-Str. 45, D-71032 Böblingen, Germany;2. Heinrich Heine University Düsseldorf, Department of Experimental Psychology, Universitätsstr. 1, D-40225 Düsseldorf, Germany;1. Department of BioMechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Delft, The Netherlands;2. Swedish National Road and Transport Research Institute, Linköping, Sweden |
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| Abstract: | The topic of transitions in automated driving is becoming important now that cars are automated to ever greater extents. This paper proposes a theoretical framework to support and align human factors research on transitions in automated driving. Driving states are defined based on the allocation of primary driving tasks (i.e., lateral control, longitudinal control, and monitoring) between the driver and the automation. A transition in automated driving is defined as the process during which the human-automation system changes from one driving state to another, with transitions of monitoring activity and transitions of control being among the possibilities. Based on ‘Is the transition required?’, ‘Who initiates the transition?’, and ‘Who is in control after the transition?’, we define six types of control transitions between the driver and automation: (1) Optional Driver-Initiated Driver-in-Control, (2) Mandatory Driver-Initiated Driver-in-Control, (3) Optional Driver-Initiated Automation-in-Control, (4) Mandatory Driver-Initiated Automation-in-Control, (5) Automation-Initiated Driver-in-Control, and (6) Automation-Initiated Automation-in-Control. Use cases per transition type are introduced. Finally, we interpret previous experimental studies on transitions using our framework and identify areas for future research. We conclude that our framework of driving states and transitions is an important complement to the levels of automation proposed by transportation agencies, because it describes what the driver and automation are doing, rather than should be doing, at a moment of time. |
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| Keywords: | Human factors Automated driving Transitions Transition classification |
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