Schneider, Stefan-Alexander
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In the early phase of new vehicle system developments, it is crucial to fully define and optimize working system and functional architectures. Architecture definition and validation in turn requires a quick and accurate evaluation of a system‟s overall performance. Modeling and simulating a complete vehicle system, however, is complex and in many cases was either technically not achievable or simply has been omitted within the development process. It is the utmost challenge in system modeling and simulation to realistically reflect interaction of various electrical, mechanical, thermal, and software elements as attributed to individual system modules and their relations. State-of-the-art tools meanwhile bear this capability. In this paper we present an approach how they may effectively and efficiently be incorporated into a car system development process. To accomplish this target, we „virtualize‟ all system entities while defining and reflecting all relevant system aspects. Our proposed development flow allows simulating, evaluating, and validating complete vehicle systems and their behavior. The proposed flow will sustainably change car system development processes.
The following paper points out the key role of IT in the future of car development. At the moment a fundamental change in the structure of automotive IT organizations can be observed. The fact that software update cycle in automotive, about 1 year, in comparison with Apple, Google or Tesla is too much. The entertainment industry is constantly proceeding ahead much faster than the automotive industry. On top of this, new emerging platforms like Apple CarPlay and Android Auto are providing the look and the feel of a mobile phone regarding the control of the car. The vehicle itself is getting more and more as an “ultimate mobile application or app”. This shows the need of speeding up the Time-to-Market of new innovations in automotive industry.
The structure of IT departments has to support these process. No wonder that CIOs of car manufacturers are looking for new structures in their IT departments that enable faster cycle update for automotive applications taking in consideration safety and security requirements.
This only represents a particular interest, as for Apple and Google, we can see that Google has already a fleet of 23 self-driving cars in place which has already autonomously driven more than one million miles with only 12 accidents on public roads and Apple is said to work under the project name "Titan" on its own electric car.
Another important aspect is the software running in the car itself, e.g. the software that “fuses” data from sensors into a comprehensible form: objects have to be accurately located in the environment model of the socalled ego vehicle as a basis for decisions making either by the driver himself or even by the software that can determine within a fraction of a second what the car is going to do. High definition maps also play a very important role in enabling autonomous driving, being developed and maintained by companies such as Nokia HERE, with accuracy of only a few centimeters are thought to be of strategic importance for Advanced Driver Assistance Systems and Self Driving Cars.
“We’re the engine room of the system,” says Mr. Ristevski, vice president of reality capture and processing for former Nokia’s mapping unit named HERE. To be independent from Apple and Google maps and with that from possible competitors, it is said to be the main reason why the German premium car manufacturer Audi, BMW and Daimler bought the online map service for about € 2.5 bn. This is only the first step in the restructuring of the automotive industry.
Trajectory Modelling for Autonomous Driving: Investigating the Artificial Potential Field Method
(2024)
Although the focus of autonomous driving is on maximizing safety and efficiency, comfort and familiarity will play a key role in the adoption of autonomous driving. Therefore, it is important to develop algorithms that can mimic human driving skills and adapt to individual driving styles. The potential field method (PFM) is an obstacle avoidance algorithm for autonomous driving that uses a repulsive potential field, as a environment model, to navigate the vehicle to the lowest risk potential. In this paper, the PFM is used in a overtake scenario at high speed, to test the impact of using prediction when calculating the ideal yaw rate. Analysis is done on how the potential field can be used for lane keeping while following a car and then for overtaking it. A driving simulator is used to record human driving data and compare it with automated driving using a PFM as is proposed by [3], with modifications to enable future prediction.
Infrastructure-cooperated autonomous driving systems are attracting attention as a method for promoting the practical application of highly functional autonomous driving. We focused on the part where recognition processing on the infrastructure side can be advanced, which is not possible with in-vehicle processing. Using a fixed-point camera and recognition of the situation behind a vehicle or object in which multiple cameras are linked are such examples. In this paper, we selected a difficult situation such as a curved road, focused on the scene where the vehicle is running while deforming its shape, and examined a method of accurately recognizing the vehicle using a fixed-point camera. It is a study of the criteria for dividing the vehicle shape class. Recognition of the general vehicle class of autonomous driving also needs to identify unknown objects and non-vehicles. In his article, we have excluded the identification of unknown objects and focused on recognizing known vehicles using deep learning. Consider six different vehicle shapes on curved roads. We investigated the impact of vehicle shape class integration and performance, and found that the integration of the two classes reduced the number of vehicle shape classes and increased recognition accuracy.
In this paper, we derive intermediate frequency (IF) level analytical formulation of radio frequency (RF) group delay for automotive frequency-modulated continuous-wave (FMCW) radar waveform under quasi-static approximation. To the best of our knowledge, this paper is the first to develop and simulate an IF-level analytical form ulation of RF group delay, including random and deterministic variation for the FMCW radar waveform. Theoretical limitation for the tolerable RF group delay can be derived based on the proposed model. We demonstrated the impact of RF group delay on the FMCW radar sensor's range spectrum in dynamic virtual traffic scenarios. The proposed model is integrated into a virtual FMCW radar sensor model implemented as a functional mock-up unit (FMU) using the standardized interfaces functional mock-up interface (FMI) 2 .0 and the open simulation interface (OSI) 3. 0. 0. A virtual test scenario is implemented in an industry-standard simulation tool, CarMaker, to demonstrate the effect.
Der allgemeine technologische Fortschritt, insbesondere in der Halbleitertechnik, beschert allen Industriezweigen bisher ungeahnte Entwicklungsschübe, die ganz allgemein auch auf die Software-Entwicklung ausstrahlen und sich somit auch auf die Software-Entwicklungsmethoden auswirken. Die Entwicklungsmethoden für Steuergeräte-Software, befinden sich daher in dem Übergang von manueller C-Code Programmierung hin zu einem graphischen Entwurf. Diese Entwurfsmöglichkeiten bringen viele Vorteile mit sich, wie z.B. Verringerung der Komplexität, Verkürzung der Software-Entwicklungszeit, Verbesserung der Software-Qualität und Automatisierung des Software-Produktionsprozesses.
Allerdings wirft dieser Abstraktionsschritt eine wesentliche Frage auf: Wie lässt sich überprüfen und sicherstellen, dass die eingesetzten Software-Entwicklungswerkezeuge für die Transformation vom graphischen Modell zum generierten C-Code und darüber hinaus zum Objektcode fehlerfrei arbeiten? Typische Methoden, um das notwendige Vertrauen in diese Transformationen zu erhalten sind: Betriebsbewährtheit, Audit des Entwicklungsprozesses des Werkzeuges sowie das Validieren der Entwicklungswerkzeuge. Insbesondere beim Validieren der Entwicklungswerkzeuge fehlte ein Leitfaden wie ein solcher Validierungsprozess aussehen könnte und in welchem Umfang - Stichwort Testtiefe - ein Entwicklungswerkzeug zu testen wäre.
In diesem Beitrag wird gezeigt, wie diese Lücke methodisch geschlossen werden konnte: Die Anforderungen an einem Validierungsprozess wurden ganz allgemein für Entwicklungswerkzeuge hergeleitet und entsprechende Validierungssuite zur Qualifizierung von C-Codegeneratoren und Target-Compilern umgesetzt und angewendet. Die Ergebnisse fließen in die entsprechenden Entwicklungsprozesse in Form von Modellierungsrichtlinien ein. Dieses Vorgehen setzt damit den Stand der Technik.
Die Herleitungsbasis für die Anforderungen an eine Validierungssuite bildeten die Anforderungen an Software-Entwicklungswerkzeuge (Das Entwicklungswerkzeug soll die "Eigenschaft X" haben). Dazu wurden einschlägige Normen und Standards, wie DIN EN 61508, RTCA DO-178B, IEC 60880, PTB-Softwareprüfstelle und MOD EDF Std 00-55, sorgfältig analysiert und entsprechend kategorisiert. Dieser Anforderungskatalog wurde dann in einen in sich stimmigen Anforderungskatalog für eine Validierungssuite (Die Validierungssuite soll validieren, dass das Entwicklungswerkzeug die "Eigenschaft X" hat) umformuliert und veröffentlicht und können beim TÜV Nord bezogen werden.
Der Validierungsprozess ist zweistufig vorgesehen. In einem ersten Schrott wird ein Gutachten für die prinzipielle Eignung der Modellierungssprache eingeholt. Diese Vorprüfung der Eingabeelemente eines Entwicklungswerkzeuges dient dazu, das Entwicklungswerkzeug hinsichtlich all jener Anforderungen zu prüfen, deren Erfüllung von einer weitgehend automatisierten Validierungssuite nicht geprüft werden können. Auf diese Weise kann auch frühzeitig sichergestellt werden, ob grundsätzliche Abweichungen zu den Anforderungen einer Qualifizierung eines Entwicklungswerkzeuges im Wege stehen und ermöglicht somit eine frühzeitige Behebung. Die sich daran anschließende Hauptprüfung des Entwicklungswerkzeuges durch eine Validierungssuite prüft das Entwicklungswerkzeug ausführungsbasiert um die notwendige Testtiefe zu erreichen.
Im Ausblick wird diskutiert, ob und wie die Anforderungen zur prinzipiellen Eignung einer Modellierungssprache beim Entwurf neuer Modellierungssprachen für sicherheitsrelevante Entwicklungsprojekte an dem Beispiel der Modellierungssprache Modelica wegweisend sein können.
Sparse grids are a recently introduced new technique for discretizing partial differential equations having a very favorable complexity in the number of unknowns for higher dimensional problems. Therefore, sparse grids are especially attractive for instationary equations when time is treated as an additional dimension. The paper will introduce the sparse grid finite element technique and the sparse grid combination technique which can be interpreted as a multivariate extrapolation method. The conceps are closely related to the multilevel principle so that multigrid methods and multilevel preconditioning strategies are the natural solvers. Thus the overall solution process has optimal complexity. Furthermore, the combination technique is easily parallelizable and applicable to nonlinear problems, like the Richardson equation. Besides an introduction of the algorithms with their basic analysis we will present numerical tests for a suite of characteristic model problems.