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Driving simulators allow the testing of driving functions, vehicle models and acceptance assessment at an early stage. For a real driving experience, it's necessary that all immersions are depicted as realistically as possible. When driving manually, the perceived haptic steering wheel torque plays a key role in conveying a realistic steering feel. To ensure this, complex multi-body systems are used with numerous of parameters that are difficult to identify. Therefore, this study shows a method how to generate a realistic steering feel with a nonlinear open-loop model which only contains significant parameters, particularly the friction of the steering gear. This is suitable for the steering feel in the most driving on-center area. Measurements from test benches and real test drives with an Electric Power Steering (EPS) were used for the Identification and Validation of the model.

Due to manifold benefits compared to proprietary software solutions, free and open source software (FOSS) in general, and Linux especially becomes more and more relevant for embedded solutions in the automotive domain, especially in High Performance Computing Platforms (HPC). However, taking over liability and warranty for a FOSS software-based problem raises the problem of software quality assurance, and thus respectively risk control. In order to control and minimize the residual risk of a product or service, the traditional and well-accepted measure in the automotive domain is to assess the engineering processes and resulting work products via a process assessment model given by the ASPICE maturity model, as well as requirements from functional safety standards for safety related functions. The underlying process reference model of ASPICE assumes software development performed and controlled by an organization.

The optimization and further development of automated driving functions offers great potential to relieve the driver in various driving situations and increase road safety. Simulative testing in particular is an indispensable tool in this process, allowing conclusions to be drawn about the design of automated driving functions at a very early stage of development. In this context, the use of driving simulators provides support so that the driving functions of tomorrow can be experienced in a very safe and reproducible environment. The focus of the acceptance and optimization of automated driving functions is particularly on vehicle lateral control functions. As part of this paper, a test person study was carried out regarding manual vehicle lateral control on the dynamic vehicle road simulator at the Institute of Automotive Engineering.

Autonomous driving is a hot topic in the automotive domain, and there is an increasing need to prove its reliability. They use machine learning techniques, which are themselves stochastic techniques based on some kind of statistical inference. The occurrence of incorrect decisions is part of this approach and often not directly related to correctable errors. The quality of the systems is indicated by statistical key figures such as accuracy and precision. Numerous driving tests and simulations in simulators are extensively used to provide evidence. However, the basis of all descriptive statistics is a random selection from a probability space. The difficulty in testing or constructing the training and test data set is that this probability space is usually not well defined. To systematically address this shortcoming, ontologies have been and are being developed to capture the various concepts and properties of the operational design domain.

The automotive industry is continuously evolving, demanding innovative approaches to enhance testing methodologies and preventive identify potential issues. This paper proposes an advancement test approach in the area of the overall vehicle system included steering system and power train on a “Road to Rig” test bench. The research aims to revolutionize the conventional testing process by identifying faults at an early stage and eliminating the need to rely solely on field tests. The motivation behind this research is to optimize the test bench setup and bring it even closer to real field tests. Key highlights of the publication include the introduction of an expanded load spectrum, incorporating both steering angle and speed parameters along the test track. The load includes different route and driving profiles like on a freeway, overland and city drive in combination with the steering angles.

EU legislation provides for only local CO2 emission-free vehicles to be allowed in individual passenger transport by 2035. In addition, the directive provides for fuels from renewable sources, i.e. defossilised fuels. This development leads to three possible energy sources or forms of energy for use in individual transport. The first possibility is charging with electricity generated from renewable sources, the second possibility is hydrogen generated from renewable sources or blue production path. The third possibility is the use of renewable fuels, also called e-fuels. These fuels are produced from atmospheric CO2 and renewable hydrogen. Possible processes for this are, for example, methanol or Fischer-Tropsch synthesis. The production of these fuels is very energy-intensive and large amounts of renewable electricity are needed.