Die Funktionen des autonomen Fahrens könnten in Zukunft den gesamten Straßenverkehr grundlegend verändern; dafür müssen diese in einer großen Stückzahl und somit als Serienprodukte zum Einsatz kommen. Im Allgemeinen ist für den Übergang eines technischen Systems von der Entwicklungsphase in die Serienproduktion die Freigabe dieses Systems notwendig [1]. Nach den Grundsätzen des Projektmanagements erfolgt die Freigabe erst dann, wenn die zuvor definierten Anforderungen von diesem technischen System erfüllt werden. Diese Anforderungen haben unterschiedlichste Ursprünge, wie beispielsweise Kunden, Normen oder Gesetze.

Passenger car disc brakes are a source of ultrafine, fine, and coarse particles. It is estimated that 21% of total traffic-related PM₁₀ emissions in urban environments originate from airborne brake wear particles. Particle number emission factors are in the magnitude of 10¹⁰ km⁻¹ wheel brake during real-world driving conditions. Due to the complexity of the tribological processes and the limited observability of the friction zone between brake disc and pad, the phenomena causing particle emission of disc brakes are only partially understood. To generate a basis for understanding the emission process and, based on this, to clarify which influencing variables have how much potential for reduction measures, one approach consists in the identification and quantification of influencing variables in the form of emission maps. The subject of this publication is the influence of disc brake temperature on ultrafine, fine, and coarse particle emissions, which was investigated with a systematic variation of temperature during single brake events on an enclosed brake dynamometer. The systematic variation of temperature was achieved by increasing or decreasing the disc temperature stepwise which leads to a triangular temperature variation. Two types of brake pads were used with the main distinction in its chemical composition being organic and inorganic binder materials. The critical disc brake temperature for the generation of ultrafine particles based on nucleation is at approximately 180 °C for pads with an organic binder and at approximately 240 °C for pads with inorganic binder materials. Number concentration during those nucleation events decreased for successive events, probably due to aging effects. PM₁₀ emissions increased by factor 2 due to an increase in temperature from 80 °C to 160 °C. The influence of temperature could be only repeatable measured for disc brake temperatures below 180 °C. Above this temperature, the emission behavior was dependent on the temperature history, which indicates also a critical temperature for PM₁₀ relevant emissions but not in an increasing rather than a decreasing manner.

Safety validation of automated driving functions is a major challenge that is partly tackled by means of simulation-based testing. The virtual validation approach always entails the modeling of automotive perception sensors and their environment. In the real world, these sensors are exposed to adverse influences by environmental conditions such as rain, fog, snow, etc. Therefore, such influences need to be reflected in the simulation models. In this publication, a novel data set is introduced and analyzed. This data set contains lidar data with synchronized reference measurements of weather conditions from a stationary long-term experiment. Recorded weather conditions comprise fog, rain, snow, and direct sunlight. The data are analyzed by pairing lidar values, such as the number of detections in the atmosphere, with weather parameters such as rain rate in mm/h. This results in expectation values, which can directly be utilized for stochastic modeling or model calibration and validation. The results show vast differences in the number of atmospheric detections, range distribution, and attenuation between the different sensors of the data set.

This paper presents a taxonomy that allows defining the fault tolerance regimes fail-operational , fail-degraded , and fail-safe in the context of automotive systems. Fault tolerance regimes such as these are widely used in recent publications related to automated driving, yet without definitions. This largely holds true for automotive safety standards, too. We show that fault tolerance regimes defined in scientific publications related to the automotive domain are partially ambiguous as well as taxonomically unrelated. The presented taxonomy is based on terminology stemming from ISO 26262 as well as from systems engineering. It uses four criteria to distinguish fault tolerance regimes. In addition to fail-operational , fail-degraded , and fail-safe , the core terminology consists of operational and fail-unsafe . These terms are supported by definitions of available performance , nominal performance , functionality , and a concise definition of the safe state . For verification, we show by means of two examples from the automotive domain that the taxonomy can be applied to hierarchical systems of different complexity.

Objective: Particular testing by functional decomposition of the automated driving function can potentially contribute to reducing the effort of validating highly automated driving functions. In this study, the required size of test suites for scenario-based testing and the potential to reduce it by functional decomposition are quantified for the first time. Methods: The required size of test suites for scenario-based approval of a so-called Autobahn-Chauffeur (SAE Level 3) is analyzed for an exemplary set of scenarios. Based on studies of data from failure analyses in other domains, the possible range for the required test coverage is narrowed down and suitable discretization steps, as well as ranges for the influence parameters, are assumed. Based on those assumptions, the size of the test suites for testing the complete system is quantified. The effects that lead to a reduction in the parameter space for particular testing of the decomposed driving function are analyzed and the potential to reduce the validation effort is estimated by comparing the resulting test suite sizes for both methods. Results: The combination of all effects leads to a reduction in the test suites’ size by a factor between 20 and 130, depending on the required test coverage. This means that the size of the required test suite can be reduced by 95–99% by particular testing compared to scenario-based testing of the complete system. Conclusions: The reduction potential is a valuable contribution to overcome the parameter space explosion during the validation of highly automated driving. However, this study is based on assumptions and only a small set of exemplary scenarios. Thus, the findings have to be validated in further studies.