Abstract
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 randomparameter 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.

Abstract
Driver distraction is a major problem nowadays, contributing to many deaths, injuries, and economic losses. Despite the effort that has been made to minimize these impacts, considering the technological evolution, distraction at the wheel has tended to increase. Not only tech-related tasks but every task that captures a driver's attention has impacts on road safety. Moreover, driver behavior and characteristics are known to be heterogeneous, leading to a distinct driving performance, which is a challenge in the road safety perspective. This study aimed to capture the effects of drivers' personal aspects and habits on their distraction behavior. Following a within-subjects approach, a convenience sample of 50 drivers was exposed to three unexpected events reproduced in a driving simulator. Drivers' reactions were evaluated through three distinct models: a Lognormal Model to make analyze the visual distraction, a Binary Logit Model to explore the adopted type of reaction, and a Parametric Survival Model to study the reaction times. The research outcomes revealed that drivers' behavior and perceived workload were distinct when they were engaged in specific secondary tasks and for distinct drivers' personal attributes and habits. Age and type of distraction showed statistical significance regarding the visual behavior. Moreover, reaction times were consistently related to gender, BMI, sleep patterns, speed, habits while driving, and type of distraction. The habit of engaging in secondary tasks while driving resulted in a cumulative better performance.