Correlations of multiple rider behaviors with self-reported attitudes,perspectives on traffic rule strictness and social desirability |
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| Institution: | 1. Queensland University of Technology (QUT), Centre for Accident Research and Road Safety - Queensland (CARRS-Q), Australia;2. Queensland University of Technology (QUT), Australia;1. Knowledge Centre Road Safety, Vias Institute, Haachtsesteenweg 1405, BE-1130 Brussels, Belgium;2. University of Liège, ArGEnCo/UEE – Local Environment Management & Analysis (LEMA), Quartier Polytech 1, Allée de la Découverte 9, BE-4000 Liège, Belgium;1. National Technical University of Athens, Department of Transportation Planning & Engineering, Athens, Greece;2. IFSTTAR – Institut Français des Sciences et Technologies des Transports, de l’Aménagement et des Réseaux, France;1. Vietnamese-German Transport Research Centre (VGTRC), Vietnamese-German University, Binh Duong, Viet Nam;2. UHasselt, School of Transportation Sciences, Transportation Research Institute (IMOB), Agoralaan, 3590 Diepenbeek, Belgium |
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| Abstract: | Powered Two-Wheeler (PTW) riders constitute a very vulnerable group of road users, while riding a PTW is considerably more dangerous than using any other motor vehicle. Behavioral issues have been identified major moderating factors to PTW crashes, as riders display great variability in their attitudes towards road safety. Τhe aim of this paper is to present a thorough, overarching structure of relationships correlating various unsafe stated PTW rider behaviors (riding after alcohol consumption, speeding, helmet use and texting) with several self-reported attitude parameters and factors regarding rider perspectives on traffic rule strictness and social desirability. A structural equation model (SEM) was developed using data from the ESRA2 survey, which provided a broad sample encompassing 5,958 respondent riders from 32 countries. Numerous statistical relationships were discovered and quantified correlating the four examined unsafe rider behaviors with eight latent unobserved variables. All covariances between unsafe behaviors were found to be positive and statistically significant, indicating that a rider who will engage more frequently in every single one of the four examined unsafe riding behaviors is more likely to also engage in all the others as well. |
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| Keywords: | Rider behavior Drinking and riding Speeding while riding Texting while riding Helmet use Structural equation model |
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