Take-over requests in highly automated driving: A crowdsourcing survey on auditory,vibrotactile, and visual displays |
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| Institution: | 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;1. Department for Ergonomics, Faculty of Mechanical Engineering, Technical University Munich, Boltzmannstraße 15, 85747 Garching, Germany;2. Department of BioMechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Mekelweg 2, 2628 CD Delft, The Netherlands;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. VEDECOM Institute, France;2. PSA Group, France;3. Renault Group, France;1. Chair of Ergonomics, Technical University of Munich, Munich, Germany;2. Department Intelligent Vehicles, Delft University of Technology, Delft, The Netherlands;1. Centre for Transport Studies, University of Twente, Enschede, the Netherlands;2. Department of Cognitive Robotics, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Delft, the Netherlands;3. Transport & Planning, Faculty of Civil Engineering and Geoscience, Delft University of Technology, Delft, the Netherlands;4. SWOV Institute for Road Safety Research, The Hague, the Netherlands;5. TNO Traffic & Transport, The Hague, the Netherlands;1. Lehrstuhl für Ergonomie, Fakultät für Maschinenwesen, Technische Universität München, Boltzmannstraße 15, 85747, Garching, Germany;2. Division Interior, Interior Electronics Solutions, Continental Automotive, Babenhausen, Germany;3. Department of Biomechanical Engineering, Faculty of Mechanical, Maritime and Materials Engineering, Delft University of Technology, Delft, The Netherlands |
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| Abstract: | An important research question in the domain of highly automated driving is how to aid drivers in transitions between manual and automated control. Until highly automated cars are available, knowledge on this topic has to be obtained via simulators and self-report questionnaires. Using crowdsourcing, we surveyed 1692 people on auditory, visual, and vibrotactile take-over requests (TORs) in highly automated driving. The survey presented recordings of auditory messages and illustrations of visual and vibrational messages in traffic scenarios of various urgency levels. Multimodal TORs were the most preferred option in high-urgency scenarios. Auditory TORs were the most preferred option in low-urgency scenarios and as a confirmation message that the system is ready to switch from manual to automated mode. For low-urgency scenarios, visual-only TORs were more preferred than vibration-only TORs. Beeps with shorter interpulse intervals were perceived as more urgent, with Stevens’ power law yielding an accurate fit to the data. Spoken messages were more accepted than abstract sounds, and the female voice was more preferred than the male voice. Preferences and perceived urgency ratings were similar in middle- and high-income countries. In summary, this international survey showed that people’s preferences for TOR types in highly automated driving depend on the urgency of the situation. |
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| Keywords: | Multimodal interfaces Automated driving Crowdsourcing |
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