Capturing the effects of texting on young drivers behaviour based on copula and Gaussian Mixture Models |
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| Affiliation: | 1. Lab. for Transport Engineering, Department of Civil and Environmental Engineering, University of Cyprus, 75 Kallipoleos Str., P.O. Box 20537, 1678 Nicosia, Cyprus;2. Department of Transportation Planning and Engineering, School of Civil Engineering, National Technical University of Athens, 5, Heroon Polytechniou Str., 15773, Zographou Campus, Greece;1. Dept. of Intelligent Mechanical Systems, Okayama University, Japan;2. Dept. of Industrial Engineering and Management Systems, University of Central Florida, United States;1. Traffic and Engineering Psychology, Technische Universität Braunschweig, Gaußstraße 23, 38106 Braunschweig, Germany;2. Institute of Transportation Systems, German Aerospace Center (DLR), Lilienthalplatz 7, 38108 Braunschweig, Germany;3. Department of Psychology and Ergonomics, Technische Universität Berlin, Marchstraße 23, 10587 Berlin, Germany;1. RBG Labs, Department of Engineering Design, IIT Madras, Chennai 600036, India;2. Harita Seating Systems Limited, Belagondapalli, Thally Road, Hosur 635114, Krishnagiri District, Tamil Nadu, India;1. Universitat Rovira i Virgili (URV, Tarragona, España), Faculty of Education Sciences and Psychology, Campus Sescelades, Ctra Valls, s/n, 43005 Tarragona, Spain;2. Universitat Rovira i Virgili (URV, Reus, España), Faculty of Economics and Business, Av. de la Universitat, 1, 43204 Reus, Spain;3. EADA, Business School (EADA, Barcelona, España), Strategy, Leadership & People, Carrer Querol, S/N, 08293 Collbató, Barcelona, Spain |
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| Abstract: | This research effort aims to investigate the impact of texting on young drivers' behavior and safety based on data from driving simulator experiments, for different driving contexts, like motorways, urban and rural roads, during daytime and night, and for alternative weather conditions (‘clear sky’ and rain). The study offers a complete and comprehensive investigation of the effects of texting on driving behavior, able to provide evidence on policy-making. For the purposes of this study, a driving simulator experiment was carried out where 34 young participants drove predefined driving scenarios. Initially, multivariate copula analysis was used in order to explore statistical inferences among variables, especially since it retains a parametric specification for bivariate dependencies and allows testing of several parametric structures to characterize them. Secondly, alternative copula configurations were tested, which showed that texting and other road and environmental characteristics affect young drivers behavior and in particular more than one outcome can occur at the same time. Finally, Gaussian Mixture Modeling (GMM) was employed, demonstrating that the variables' pairs that presented the strongest correlations were lane departure and speed, as well as speed and reaction time. GMMs application showed that drivers using mobile phones who were involved in a collision presented a different driving behavior compared to the drivers who were occupied but were not involved in a collision. |
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| Keywords: | Young drivers Driving behavior Texting Driving simulator Multivariate copula analysis Gaussian mixture models |
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