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Effects of apparent image velocity and complexity on the dynamic visual field using a high-speed train driving simulator
Affiliation:1. Beijing Jiaotong University, Beijing 100044, China;2. Cornell University, Ithaca, NY, USA;1. Edward P. Fitts Department of Industrial & Systems Engineering, North Carolina State University, United States;2. Department of Civil, Construction, and Environmental Engineering, North Carolina State University, United States;3. Department of Civil & Environmental Engineering, Wayne State University, United States;1. Department of Psychology, University of Utah, UT, USA;4. School of Computing, University of Utah, UT, USA;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
Abstract:Train driving is a highly visual task. The visual capabilities of the train driver affects driving safety and driving performance. Understanding the effects of train speed and background image complexity on the visual behavior of the high-speed train driver is essential for optimizing performance and safety. This study investigated the role of the apparent image velocity and complexity on the dynamic visual field of drivers. Participants in a repeated-measures experiment drove a train at nine different speeds in a state-of-the-art high-speed train simulator. Eye movement analysis indicated that the effect of image velocity on the dynamic visual field of high-speed train driver was significant while image complexity had no effect on it. The fixation range was increasingly concentrated on the middle of the track as the speed increased, meanwhile there was a logarithmic decline in fixation range for areas surrounding the track. The extent of the visual search field decreased gradually, both vertically and horizontally, as the speed of train increased, and the rate of decrease was more rapid in the vertical direction. A model is proposed that predicts the extent of this tunnel vision phenomenon as a function of the train speed.Relevance to industryThis finding can be used as a basis for the design of high-speed railway system and as a foundation for improving the operational procedures of high-speed train driver for safety.
Keywords:High-speed train driver  Eye movements  Dynamic visual field  Tunnel vision
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