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Entwicklung von Testauswahlmethoden für die Absicherung von Änderungen auf Gesamtfahrzeugebene
(2016)
Die wachsende Anzahl von Funktionen sowie die erhöhte Varianten- und Ausstattungsvielfalt heutiger Fahrzeuge führen zu einer gesteigerten Komplexität automobiler Systeme. Begleitet wird dies von stetig wachsenden Anforderungen an die Qualität und Zuverlässigkeit der Fahrzeuge. Daraus folgt ein enormer Anstieg des Aufwands für die Gesamtfahrzeugabsicherung. Der hohe Innovationsdruck führt zudem dazu, dass der effiziente Umgang mit Änderungen ein entscheidender Wettbewerbsfaktor geworden ist. Um sicherzustellen, dass die Qualität und Sicherheit des Systems durch die Modifikation nicht beeinträchtigt wird, muss der Absicherungsprozess revidiert werden. Die Ermittlung der benötigten Wiederholungstests ist dabei die zentrale Herausforderung. Gegenstand dieser Arbeit ist daher die Untersuchung der Fragestellung, ob eine Testauswahlmethode existiert, die eine Identifikation der erforderlichen Tests im Fall von Änderungen in der Gesamtfahrzeugabsicherung ermöglicht.
This fundamental work explains in detail systems for active safety and driver assistance, considering both their structure and their function. These include the well-known standard systems such as Anti-lock braking system (ABS), Electronic Stability Control (ESC) or Adaptive Cruise Control (ACC). But it includes also new systems for protecting collisions protection, for changing the lane, or for convenient parking.
The book aims at giving a complete picture focusing on the entire system. First, it describes the components which are necessary for assistance systems, such as sensors, actuators, mechatronic subsystems, and control elements. Then, it explains key features for the user-friendly design of human-machine interfaces between driver and assistance system. Finally, important characteristic features of driver assistance systems for particular vehicles are presented: Systems for commercial vehicles and motorcycles.
The VAL-Project, ‘Vollautomatische Abdrück Lokomotive’, is a research and development project of Nuremberg Institute of Technology Georg Simon Ohm (THN) in collaboration with DB Cargo, that seeks to automate shunting operations. As part of this project, the THN is developing a test methodology to validate the decision-making of the automated railway driving system. Therefore, a scenario-based testing approach is chosen. [1] Based on the large number of possible test scenarios, a hybrid test strategy combining virtual simulation (LAB) and real-world (FIELD) tests is discussed. The aim is to run the majority of the required test runs in the LAB, i.e. a photorealistic virtual simulation environment developed at THN [2]. To handle the virtual testing scope, formalised scenario descriptions and a dedicated test case set-up methodology are used [1]. For test run rating, evaluation criteria derived from project specifications, driving service regulations, and other relevant sources are considered and subsequently specific rules defined. To automatically determine the outcome of a virtual test run, a methodology for monitoring compliance with these criteria is required. A crucial element of this monitoring process involves detecting collisions within the Unreal® Engine virtual environment, which is the focus of this paper.
For this purpose, the native collision detection capabilities of the Unreal® Engine are outlined, while the Separating Axis Theorem (SAT), as well as the ray casting algorithm are introduced for mathematical collision detection. In order to apply these mathematical methods to this explicit engineering purpose, a methodical multistep filtering procedure is developed, to consider objects based on their distance to the locomotive and their proximity to the track, i.e. their relevance to the safe vehicle movement.
The handling of changes in automotive release processes is a fundamental challenge of today’s development projects. This chapter examines strategies for the identification of the effects of changes and evaluates concepts for the estimation of resulting retest effort. It is determined that there exists no approach that is applicable for large systems at vehicle level and that allows a reliable selection of all tests necessary to analyze the impact of the change. To solve this problem, two general concepts for test selection techniques are proposed. Inclusion-based approaches identify tests from the set of not executed tests whereas exclusion-based approaches eliminate tests from the set of performed tests. The two concepts are compared via receiver operating characteristic and cost estimation. Furthermore, the exclusion-based test selection is described in detail. It offers the opportunity to reduce the automotive release effort without drawbacks in test quality.