Peter E. Pfeffer

Rapid developing driving simulator technologies enable the possibility of assisting the human-centered development of Advanced Driver Assistance Systems and Autonomous Driving. It boosts the efficiency of functional testing and professional subjective assessment of the system under test and thus greatly shortens the development cycles of ADAS functions. Furthermore, standardized and transparent assessment procedures contribute to the robustness and transferability of the test results. However, the application of driving simulators in the practical development process is based upon the validity of the test results in the virtual environment. The aim of this study is to determine the subjective validity of a high-fidelity dynamic driving simulator. A back-to-back study was designed to subjectively evaluate two lateral guidance systems on an objectively validated simulator and in a real vehicle respectively. The results show that the professional drivers evaluate the system characteristics similarly in the aspects of driver interaction, perceived safety and functional performance as well as in most of their sub-aspects in the virtual and in the physical test environment and that absolute subjective validity can be established. Although the intervention intensity of the lane departure avoidance system and the general reproducibility of the lane keeping assist system show significant differences between the test environments, relative subjective validity can also be confirmed. In addition, the results of regression analysis reveal the influencing factors of driver’s subjective evaluation of the three main system characteristics and confirm the effectiveness of the evaluation methods.

Simulation-based development is the general trend in the automotive industry, especially for the development of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving (AD) functions. Driving simulators play an essential role in this by providing a reproducible, safe yet realistic environment for research and development, with the ability to rapidly generate almost infinite system and scenario variants. In this paper, a study has been designed to investigate the suitability of a static driving simulator for characterizing a safety-oriented Lane Departure Avoidance (LDA) system through both subjective and objective assessment. The study comprises two components: a subjective assessment conducted with participants and a standardized driver-in-the-loop test drive to objectively assess the system on the simulator. The research endeavors to determine the most suitable test maneuvers for objectively characterizing the system while also identifying target ranges for relevant objective metrics for an optimal subjective assessment. The results show that the professional drivers give a more reproducible subjective rating than the normal drivers. Notably, both groups consistently evaluate subjective criteria that are based on the perception of the steering wheel movement as well as the change in ego position and heading angle. However, the perception of the absolute ego position does not lead to a consistent subjective assessment. This study suggests that the characterization of Lane Departure Avoidance (LDA) systems on a static driving simulator is generally feasible, with potential for improvement of characterizing aspects based on absolute positions such as maximum lane overshoot.

A safe, comfortable and intelligent Lane Keeping Assistance System (LKAS) is fundamental on the way to realizing full automated driving. In spite of the current high market penetration of LKAS, vehicle manufacturers, suppliers and researchers are still working on improving the system to reach a higher customer acceptance. To achieve this goal more efficiently, a systematic and ideally objective assessment procedure of the system needs to be established. Till date, a thorough review study of the assessment procedures of LKAS does not exist, especially of those which also take the subjective impression of the driver into consideration. The motivation of this paper is to benchmark the state-of-the-art assessment methods of LKAS and identify where problems and research potentials lie. The paper summarizes the relevant characteristics of LKAS based on representative research in the past decades. It also compares the characterization of LKAS with the field of steering feel and vehicle handling in the aspects of procedure, strategy, as well as their advantages and disadvantages. This paper contributes to transferring the know-hows and valuable experiences from other well-developed fields of vehicle dynamics into the rapid-evolving branch of Advanced Driver Assistance System (ADAS), in order to help standardizing its assessment procedure and give insights on system design from a human-centered perspective in the early development phase, thus shortening the ADAS development cycles.

Advanced Driver Assistance Systems (ADAS) such as Lane Keeping Assistance (LKA) systems are in the focus of current vehicle developments. Of special interest is the calibration task, which plays an increasingly decisive role in early development stages. At this point it is essential to analyze the pre-calibrated controller concepts by appropriate simulation methods. A software toolchain is introduced, using Model-in-the-Loop (MiL) for the evaluation and calibration of the LKA system. Within, a Design-of-Experiment (DoE) tool is integrated together with the simulation environment. This enables the examination of the two different lateral controller concepts Steer-by-Angle (SbA) and Steer-by-Torque (SbT). Their lateral guidance performance is characterized by Key Performance Indicators (KPI), which are derived from simulation quantities of straight-line and cornering maneuvers. Further, statistical behavior models are generated based on those KPI and controller design variables (DV). The subsequent optimization process leads to high performances of both controllers. In particular, the SbA controller shows higher efficiency under the impact of disturbances as well as the reference reaction with lower settling times. Overall, the achieved lateral guidance performances indicate the potential of both control algorithms in an early development stage. With the software toolchain, a platform for further LKA system calibration and lateral guidance performance optimization is established.

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