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
Conducting scientific experiments in driving simulators requires the modeling of reliable and complete road environments. These environments must provide extensive landscapes with the artifacts and natural element that can be usually found in the real world. This paper presents a method to efficiently produce models of natural vegetation. The produced models are then applied to populate existing terrain definitions, allowing the fast preparation of extensive environments with realistic landscapes. The human supervisor can interact in this generation process, in order to obtain custom landscapes definitions. After the landscape generation process, the road network definition can be then generated, producing a complete driving environment, in an integrated modeling process. The proposed method allows modeling a wide range of drive environments, with the realism and quality required to the realization of virtual training or experimental work in many terrain based activities, such driving simulators.

Abstract

Abstract
Driving simulators require extensive road environments, with roads correctly modeled and similar to those found in real world. The modeling of extensive road environments, with the specific characteristics required by driving simulators, may result in a long time consuming process. This paper presents a procedural method to the modeling of large road environments. The proposed method can produce a road network design to populate an empty terrain and produce all the related road environment models. The terrain model can also be edited to produce well-constructed road environments. The road and terrain models are optimized to interactive visualization in real time, applying all the stet-of-art techniques like the level of detail selection. The proposed method allows modeling large road environments, with the realism and quality required to the realization of experimental work in driving simulators.

Abstract
Virtual environments for driving simulation aimed to scientific purposes require three-dimensional models of realistic road networks. The generation of these networks according to the requirements, if done manually by road design specialists, results in a time consuming task. Procedural generation of road networks comes as a solution to this problem with the creation of complete road networks definition adequate to simulation. This paper proposes a method to automatically generate an optimized definition of very large roads network, in an integrated process, from the selection of nodes in a terrain area, to the network topological definition. The human supervisor can interact with this generation process at any stage, in order to obtain custom road networks definitions. The proposed method reduces the use of specialists for preparing large road networks definitions. These definitions are suitable to integrate into a broader process to create road environments, with different road types, appropriate to conducting scientific experiments in driving simulation.