The influence of middle-aged male driver profile on driving performance and the effects of three perceptual countermeasures: A simulator study.

The human-environment-vehicle triad and how it relates to crashes has long been a topic of discussion, in which the human factor is consistently seen as the leading cause. Recently, more sophisticated approaches to Road Safety have advocated for a road-driver interaction view, in which human characteristics influence road perception and road environment affects driver behavior. This study focuses on road-driver interaction by using a driving simulator. The objective is to investigate how the driver profile influences driving performance and the effects of three countermeasures (peripheral transverse lines before and after the beginning of the curves and roadside poles in the curves). Fifty-six middle-aged male participants drove a non-challenging rural highway simulated scenario based on a real road where many single-vehicle crashes occurred. The drivers' profiles were assessed through their behavioral history measured by a validated version of the Driver Behavior Questionnaire (DBQ) comprising three dimensions: Errors (E), Ordinary Violations (OV), and Aggressive Violations (AV). The relationship between speed and trajectory measures and drivers' profiles was investigated using random-parameter models with heterogeneity in the means. The models' results showed that the DBQ subscale scores in OV explained a considerable part of the heterogeneity found in drivers' performance. Furthermore, the heterogeneity in the means caused by the DBQ subscale scores in OV and E in the presence of peripheral transverse lines indicates a difference in how drivers react to the countermeasures. The peripheral lines were more efficient than roadside poles to moderate speed but did not positively influence all drivers' trajectories. Although the peripheral lines could be seen as an alternative to change driver behavior in a non-challenging or monotonous road environment, the design used in this study should be reviewed.

A novel approach to set driving simulator experiments based on traffic crash data.

Several studies have often cited crash occurrences as a motivation to perform a driving simulator experiment and test driver behavior to understand their causal relations. However, decisions regarding the simulated scenario and participants' requirements do not often rely directly on traffic crash data. To fill the gap between simulation and real data, we have proposed a new framework based on Clustering Analysis (K-medoids) to support the definition of driving simulator experiments when the purpose is to investigate the driver behavior under real risky road conditions to improve road safety. The suggested approach was tested with data of three years of police records regarding loss-of-control crashes and information on three Brazilian rural highways' geometry and traffic volume. The results showed the good suitability of the method to compile the data's diversity into four clusters, representing and summarizing the crashes' main characteristics in the region of study. Drivers' attributes (age and gender) were initially intended to integrate the clustering analysis; however, due to the sample's homogeneity of these characteristics, they did not contribute to the cluster definition. Hence, they were used simply to identify the target population for all scenarios. Therefore, we concluded that driving simulator experiments could benefit from the new approach since it identifies scenarios characterized by many variables connected to real risky situations and orients participants' recruitment leading to efficient safety analysis.

Driving simulators to evaluate road geometric design effects on driver behaviour: A systematic review.

Several factors can influence driver behaviour, and road geometry is one of them. A better understanding of driver-roadway interaction can enhance road design to create a safer traffic system. In this context, driving simulators are powerful tools that combine convenience and effectiveness in identifying drivers' responses to different geometry factors. In this paper, a systematic review following a Prisma guideline was conducted on driving simulator studies that examined the effects of road geometry on driver behaviour to reveal the current procedures adopted in this field and their main findings. A systematic search of eleven databases was performed covering six years of research results. Inclusion of relevant studies focused on horizontal curves, a topic identified as the most cited, extended this period. The results revealed significant heterogeneity in relation to the measured variables and deficiencies when reporting the experiment, which prevented a meta-analysis of the studies' outcomes. Despite this, a discussion of the potential of driving simulators to contribute to several road safety research gaps is presented. In addition, problems of a lack of standardisation in the performance of the experiments were detected, potentially influencing the findings of the studies. However, the results also suggest that experiments that followed good experimental practices observed effects on driver performances not detected by other studies.