The need for efficient and reproducible development processes for sensor and perception systems is growing with their increased use in modern vehicles. Such processes can be achieved by using virtual test environments and virtual sensor models. In the context of this, the present paper documents the development of a sensor model for depth estimation of virtual three-dimensional scenarios. For this purpose, the geometric and algorithmic principles of stereoscopic camera systems are recreated in a virtual form. The model is implemented as a subroutine in the Epic Games Unreal Engine, which is one of the most common Game Engines. Its architecture consists of several independent procedures that enable a local depth estimation, but also a reconstruction of a whole three-dimensional scenery. In addition, a separate programme for calibrating the model is presented. In addition to the basic principles, the architecture and the implementation, this work also documents the evaluation of the model created. It is shown that the model meets specifically defined requirements for real-time capability and the accuracy of the evaluation. Thus, it is suitable for the virtual testing of common algorithms and highly automated driving functions.
The need to find alternative urban mobility solutions for delivery and transport has led mobility companies to devote enormous resources for researchbased solutions to increase vehicle safety. This paper documents a virtual approach to investigate the influences of different load states to the vehicle dynamic of light electric vehicle. A model basing on a three-dimensional multibody system was used, which consists of five bodies. By applying methods of multibody modelling the generalized equations of motion were generated. To include the behavior within the contact point between road and vehicle a simplified tire models was added. The implementation of the equations allowed a first validation of the model via simulations. In a final modeling step the simulation results were interpreted in respect of plausibility. Afterwards, the model was simulated numerically to investigate different load states of the vehicle, by applying constant steering stimuli and variable velocities. In sum, the investigated model approach is useful to identify safety relevant parameters and shows the effects of load states to the vehicle dynamics. Furthermore, it behaves plausibly regarding general vehicle dynamics. These results prove the general usability of the model for the development controllers and estimators in driver assistances systems.
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