Contents lists available at ScienceDirect Accident Analysis and Prevention journal homepage: www.elsevier.com/locate/aap Structural equations modelling of drivers' speed selection using environmental, driver, and risk factors Reut Sadia ⁎ , Shlomo Bekhor, Abishai Polus Department of Civil and Environmental Engineering, Technion – Israel Institute of Technology, Haifa 32000, Israel ARTICLE INFO Key words: Driving behaviour Speed selection Structural equations Driving simulator ABSTRACT Drivers’ speed has significant implications on road users’ safety in general, and particularly so if a crash occurs. This paper explores the influence of environmental and road characteristics, situational factors, and individual characteristics on drivers’ observed speed selection in a simulator experiment. The paper presents a theoretical framework for drivers’ speed selection, and applies structural equation modeling for the various factors ex- amined. The simulator experiments collected data of 111 drivers driving in 4 different scenarios composed of 22 segments for each scenario. The dataset was analyzed in several resolutions: Driver level, Trip level, and Segment level. The three models revealed that gender, age, and driving frequency are all significant in determining drivers’ perceptions and attitudes, which in turn influence speed selection. Situational factors such as traffic speed, enforcement, and time-saving-benefits are also related to speed selection, as well as infrastructure characteristics. These findings demonstrate that structural equations provide a flexible modeling tool able to concurrently analyze the variety of factors that relate to speed selection. As a result, Structural Equations Modeling provides more accurate and refined explanations for the combined effects of various factors on drivers’ speed selection than previous research so far. These tools can be useful in developing speed management strategies to improve road safety. 1. Introduction The long-time research interest in drivers’ speed has risen mainly from the effect of driving speed on road safety - the faster the speed, the harsher the resulting impact in case of a crash (Aarts and van Schagen, 2006). Speed dispersion and variations were also found in some studies to be related to crash risk (Aarts and van Schagen, 2006; Sadia et al., 2016). Thus, a great interest remains in understanding how drivers select their speeds, and how those speeds can be managed. A wide variety of factors has been studied in relations to drivers’ speed selection, which can be generally divided into three categories: (i) Environmental Characteristics - such as infrastructure and traffic conditions, (ii) Driver Characteristics - such as personality traits and subjective perceptions, and (iii) Situational factors, defined here as Additional Risk/Benefit - such as being late to work or spotting a police car. All of these influence the driver’s individually selected speed, which may change during a specific trip as a result of changes in these factors. Research on Environmental Characteristics related to speed was mostly collected from aggregate on-road observations, field studies, and simulated driving conditions such as driving simulators and virtual reality (De Waard et al., 1997; Fildes et al., 1987; Polus et al., 2000; Stamatiadis et al., 2009; Tarko, 2009; Van der Horst and de Ridder, 2007). Design consistency studies also reveal how variations in road infrastructure relate to selection of operating speeds and crash risk (Mattar-Habib et al., 2008). Specific Environmental Characteristics that relate to infrastructure and influence selected speeds include horizontal curves and cross-section elements - such as road, lane, and shoulder width, the presence of a median, and barrier type (De Waard et al., 1997; Gitelman et al., 2014; Polus et al., 2000; Stamatiadis et al., 2009; Tarko, 2009; Van der Horst and de Ridder, 2007). Road-side elements and road classification also influence speed selection (De Waard et al., 1997; Fildes et al., 1987; Tarko, 2009; Van der Horst and de Ridder, 2007). In addition, Traffic characteristics may also be perceived as environmental characteristics related to speed selection; it was found that in free flow conditions, some driver explain exceeding the speed limit as an adaption to the speed of other surrounding vehicles (SWOV, 2012). Posted speed limits are assumed also to influence drivers’ speed selection, but their interpretation varies greatly between drivers (Mannering, 2009). Research on driver characteristics was conducted mostly by using questionnaires and interviews, especially research involving latent http://dx.doi.org/10.1016/j.aap.2017.08.034 Received 4 February 2017; Received in revised form 8 July 2017; Accepted 24 August 2017 ⁎ Corresponding author. E-mail addresses: reut.sadia@gmail.com (R. Sadia), sbekhor@technion.ac.il (S. Bekhor), polus@technion.ac.il (A. Polus). Accident Analysis and Prevention 116 (2018) 21–29 Available online 20 September 2017 0001-4575/ © 2017 Elsevier Ltd. All rights reserved. T