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Challenges for automated vehicle driver training: A thematic analysis from manual and automated driving
Institution: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. Industrial and Systems Engineering Department, Texas A&M University, College Station, TX, United States;2. Texas A&M Transportation Institute, College Station, TX, United States;1. University of Michigan Transportation Research Institute, United States;2. University of Michigan Institute for Social Research, United States
Abstract:Considerable research and resources are going into the development and testing of Automated Vehicles. They are expected to bring society a huge number of benefits (such as: improved safety, increased capacity, reduced fuel use and emissions). Notwithstanding these potential benefits, there have also been a number of high-profile collisions involving Automated Vehicles on the road. In the majority of these cases, the driver’s inattention to the vehicle and road environment was blamed as a significant causal factor. This suggests that solutions need to be developed in order to enhance the benefits and address the challenges associated with Automated Vehicles. One such solution is driver training. As drivers still require manual driving skills when operating Automated Vehicles on the road, this paper applied the grounded theory approach to identify eight “key” themes and interconnections that exist in current manual vehicle driver training. These themes were then applied to the limited literature available on Automated Vehicle driver training, and a ninth theme of trust emerged. This helped to identify a set of training requirements for drivers of Automated Vehicles, which suggests that a multifaceted approach (covering all nine themes and manual and Automated Vehicle driving skills) to driver training is required. This framework can be used to develop and test a training programme for drivers of Automated Vehicles.
Keywords:Automated Vehicles  Driver Training  Attention  Situation Awareness  Trust  Mental Models
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