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The field of vision of the driver during wet road conditions is essential for safety at all times. Additionally, the safe use of the increasing number of sensors integrated in modern cars for autonomous driving and intelligent driver assistant systems has to be ensured even under challenging weather conditions. To fulfil these requirements during the development process of new cars, experimental and numerical investigations of vehicle soiling are performed. This paper presents the surface contamination of self- and foreign-soiling tested in the wind tunnel. For these type of tests, the fluorescence method is state-of-the-art and widely used for visualizing critical areas. In the last years, the importance of parameters like the contact angle have been identified when designing the experimental setup. In addition, new visualization techniques have been introduced.

In the automotive industry, there is a continued need to improve the development process and handle the increasing complexity of the overall vehicle system. One major step in this process is a comprehensive and complementary approach to both simulation and testing. Knowledge of the overall dynamic vehicle behavior is becoming increasingly important for the development of new control concepts such as integrated vehicle dynamics control aiming to improve handling quality and ride comfort. However, with current well-established test systems, only separated and isolated aspects of vehicle dynamics can be evaluated. To address these challenges and further merge the link between simulation and testing, the Institute of Internal Combustion Engines and Automotive Engineering (IVK), University of Stuttgart is introducing a new Handling Roadway (HRW) Test System in cooperation with The Research Institute of Automotive Engineering and Vehicle Engines Stuttgart (FKFS) and MTS Systems Corporation.

This paper presents an autonomous cruise control for battery electric vehicles. The presented approach is based on the usage of predictive route data which is extracted out of a digital map and a wide range radar system in order to capture vehicles in front. By using the predictive route data and the information of the radar system, the autonomous cruise control can control the vehicle's speed over a wide range of driving situations without any driver interaction. The main aim of the presented autonomous cruise control is to optimize the battery electric vehicle's energy consumption. The main idea is to use predictive route data in order to calculate a consumption optimal vehicle speed trajectory by means of online optimization. The benefits of the autonomous cruise control are shown by means of real test drives and measured data evaluation.

This paper addresses the performance and potential of using electric vehicles in the Gulf Arab states. Based on a survey executed in Salalah, Oman, a representative test driving cycle has been set up. This cycle is the first of its kind for this region, where it is driven with a vehicle provided with special measurement equipment to log important values, e.g. vehicle's speed and position, temperatures and solar irradiance. More than 40 test drives are performed to obtain a representative driver profile. The driving cycle and driver profile are used in a simulation model which is capable of simulating the energy consumption for internal combustion engine or electric motor propulsion systems. The simulation model which contains detailed models for the driver, driving cycle, vehicle components and its dynamics is validated and used to compare the consumed energy for the two different propulsion systems.

Natural wind, roadside obstacles, terrain roughness, and traffic influence the incident flow of a vehicle driven on public roads. These transient on-road conditions differ from the idealized statistical steady-state flow environment utilized in CFD simulations and wind tunnel experiments. To understand these transient on-road conditions better, measurements were performed on German public highways and on a test site. A compact car was equipped with a measurement system that is capable of determining the transient airflow around the vehicle and the vehicle’s actual driving state. This vehicle was driven several times on a predefined 200 km long route to investigate different traffic densities on public highways in southern Germany. During the tests the transient incident flow and pressure distribution on the vehicle surface were measured.

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.

Typical automotive research in wind tunnels is conducted under idealized, stationary, low turbulence flow conditions. This does not necessarily reflect the actual situation in traffic. Thus, there is a considerable interest to simulate the actual flow conditions. Because of this, a system for the simulation of the turbulence intensity I, the integral linear scale L and the transient angle of incidence β measured in full-scale tests in the inflow of a test vehicle was developed and installed in a closed-loop, closed test section wind tunnel. The system consists of four airfoils with movable flaps and is installed in the beginning of the test section. Time-series of the flow velocity vector are measured in the empty test section to analyze the system’s envelope in terms of the turbulence intensity and the integral length scales.

In addition to the analysis of human driving behavior or the development of new advanced driver assistance systems, the high simulation quality of today’s driving simulators enables investigations of selected topics pertaining to driving dynamics. With high reproducibility and fast generation of vehicle variants the subjective evaluation process leads to a better system understanding in the early development stages. The transfer of the original on-road test run to the virtual reality of the driving simulator includes the full flexibility of the vehicle model, the maneuver and the test track, which allows new possibilities of investigation. With the opportunity of a realistic whole-vehicle simulation provided by the Stuttgart Driving Simulator new analysis of the human’s thresholds of perception are carried out.

With the law on autonomous driving and the associated ordinance, it has been possible in Germany since June 2022 to grant operating permission to vehicles with automated driving function and to admit them to road traffic. For public transport, automated shuttle buses offer the opportunity to maintain the existing service despite a shortage of personnel and to close gaps in supply. The safety of vehicle occupants, other road users and third parties is a key concern in the operation of automated shuttle buses. As part of the project RABus “Real laboratory for automated bus operation in public transport in urban and rural areas”, which is funded by the Ministry of Transport Baden-Württemberg, the operational reliability of automated shuttle buses (SAE Level 4) in public transport is being scientifically investigated. In the implementation of automated driving, obstacle detection/avoidance is a safety-critical driving function.