Abstract

In the last decades, vehicles have evolved from mechanical machines to sophisticated hardware and software (HW/SW) dominated systems. This digital paradigm shift can be explained with the rise of Advanced Driver Assistance Systems (ADAS), as well as applications of highly automated driving. However, such features require a nearly exponential amount of additional SW functionalities. To support the performance demands of such applications, powerful multi and many-processor HW platforms have been employed, exhibiting a trend toward more integrated architectures. Yet, as a consequence, the design and validation, as well as safety assessment of the digital in-vehicle infrastructure of modern cars has become immensely complex.Several techniques arose to bridge this gap, e.g., system engineering strategies, and model-based design and validation methods. In this thesis, it is proposed to augment such traditional approaches with purely simulation-driven techniques to improve and accelerate overall system design. Firstly, the utilization of driving simulators is suggested to conduct virtual road tests in an early application design stage. Furthermore, virtual prototyping is proposed to perform system exploration and extend the simulation scope of ADAS to the embedded HW/SW implementation.However, the main research contributions of the thesis are two techniques that enable efficient full-vehicle modeling. Firstly, multi-scale simulation, an approach to integrate submodels of a top-level simulation system on different design abstractions. Its main benefit is providing a tunable resolution for models, thus enabling a trade-off between the execution performance and the required simulation accuracy. Secondly, multi-domain co-simulation is proposed, a standardized method to interconnect and jointly utilize multiple vehicular simulation ecosystems. This approach addresses the multi-disciplinary nature of vehicles, requiring specialized simulators that are best suited to implement a formalism representing an individual domain.Putting all aforementioned concepts in practice, a comprehensive fully virtual ADAS prototyping ecosystem is presented in this thesis. The proposed framework assembly covers various phases of the ADAS development flow, such as model-based design, virtual system integration, virtual system testing and verification, as well as application refinement. To highlight its potentials, a multitude of ADAS applications are rapidly prototyped via the proposed system. Lastly, insights into application and system-level analyses are presented, while simulation performance evaluation is provided to highlight the acceleration potential of the virtual ecosystems.

Abstract

EuCAP 2016 - 10th European Conference on Antennas and Propagation, Davos, SUISSE, 10-/04/2016 - 15/04/2016; With Advanced Driver Assistance Systems (ADAS) getting always more sophisticated, the related Virtual Prototyping platforms have to propose a very high level of accuracy with improved flexibility regarding vehicles, sensors, environments and scenarios. In this paper a new strategy is introduced for RADAR sensors modeling aimed at allowing high accuracy while limiting the related development efforts.

Abstract

In-vehicle systems that assist the driver with his driving task are developed and introduced to the market at increasing rate. Drivers may be supported during congested traffic conditions by a so-called Congestion Assistant consisting of a mix of informing, assisting and controlling functions. This paper describes the impacts of the Congestion Assistant on the driver in terms of driving behaviour and acceptance. Thirty-seven participants took part in a driving simulator study. The observed driving behaviour showed promising improvements in traffic safety when approaching the traffic jam. Moreover, positive effects of the system on traffic efficiency can be expected in the jam. The participants stated to appreciate the Congestion Assistant, although not all functions were equally rated. To increase the performance and acceptance of the total system, some refinements were suggested. Keywords: Congestion Assistant; Driving simulator; Integrated system; Driving behaviour; Acceptance