Assessing driver acceptance of Intelligent Transport Systems in the context of railway level crossings |
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| Institution: | 1. University of Southampton, University Road, Highfield, Southampton SO17 1BJ, United Kingdom;2. University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom;1. Centre for Accident Research and Road Safety – Queensland, Queensland University of Technology, Brisbane 4059, Australia;2. Australasian Centre for Rail Innovation, Canberra 2601, Australia;3. CRC for Rail Innocation, Brisbane 4000, Australia;1. Monash University Accident Research Centre, Monash University, Clayton, Victoria, Australia;2. Research School of Psychology, The Australian National University, Canberra, ACT, Australia;3. University of the Sunshine Coast Accident Research, Maroochydore, QLD, Australia;4. University of Southampton, Highfield, Southampton, UK;1. Centre for Human Factors and Sociotechnical Systems, University of the Sunshine Coast, Sippy Downs, QLD, Australia;2. Monash University Accident Research Centre, Monash University, Clayton, VIC, Australia;3. Loughborough Design School, Loughborough University, Loughborough, United Kingdom;4. Transportation Research Group, Civil, Maritime, Environmental Engineering & Science Unit, University of Southampton, Southampton, United Kingdom;1. Department of Cognitive and Learning Sciences, Michigan Technological University, Houghton, MI 49931, United States;2. Department of Industrial and Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, United States;3. Department of Civil and Environmental Engineering, Michigan Technological University, Houghton, MI 49931, United States;1. Monash University Accident Research Centre, Monash University, Melbourne, Australia;2. University of the Sunshine Coast Accident Research, Maroochydore, QLD, Australia;3. University of Southampton, Highfield, Southampton, UK |
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| Abstract: | Intelligent Transport Systems (ITS) have the potential to substantially reduce the number of crashes caused by human errors at railway levels crossings. Such systems, however, will only exert an influence on driving behaviour if they are accepted by the driver. This study aimed at assessing driver acceptance of different ITS interventions designed to enhance driver behaviour at railway crossings. Fifty-eight participants, divided into three groups, took part in a driving simulator study in which three ITS devices were tested: an in-vehicle visual ITS, an in-vehicle audio ITS, and an on-road valet system. Driver acceptance of each ITS intervention was assessed in a questionnaire guided by the Technology Acceptance Model and the Theory of Planned Behaviour. Overall, results indicated that the strongest intentions to use the ITS devices belonged to participants exposed to the road-based valet system at passive crossings. The utility of both models in explaining drivers’ intention to use the systems is discussed, with results showing greater support for the Theory of Planned Behaviour. Directions for future studies, along with strategies that target attitudes and subjective norms to increase drivers’ behavioural intentions, are also discussed. |
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| Keywords: | Intelligent Transport Systems (ITS) Drivers Railway level crossings (RLXs) User acceptance Intentions |
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