Carlos Campos

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. © 2019 AISTI.

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.

Abstract
Virtual environments for driving simulations aimed to scientific purposes require three-dimensional road models that must obey to detailed standards of specification and realism. The creation of road models with this level of quality requires previous definition of the road networks and the road paths. Each road path is usually obtained through the dedicated work of roadway design specialists, resulting in a long time consuming process. The driving simulation for scientific purposes also requires a semantic description of all elements within the environment in order to provide the parameterization of actors during the simulation and the production of simulation reports. This paper presents a methodology to automatically generate road environments suitable to the implementation of driving simulation experiences. This methodology integrates every required step for modelling road environments, from the determination of interchanges nodes to the generation of the geometric and the semantic models. The human supervisor can interact with the model generation process at any stage, in order to meet every specific requirement of the experimental work. The proposed methodology reduces workload involved in the initial specification of the road network and significantly reduces the use of specialists for preparing the road paths of all roadways. The generated semantic description allows procedural placing of actors in the simulated environment. The models are suitable for conducting scientific work in a driving simulator. Copyright