Model-Based Design for the Development and System-Level Testing of ADAS

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Abstract

Advanced driver assistance systems (ADAS) are becoming ubiquitous, and the safety of these systems is more important than ever. Engineers are incorporating new technologies—including different sensing modalities, data processing and fusion algorithms, as well as enhanced control and automation systems—leading to increased system complexity. In order to manage the complexity of these systems and address the issue of safety via extensive testing, it is vital to have an integrated environment so that different technological components can be incorporated and tested at a system level. We present such a solution in this paper. The proposed framework is based on Model-Based Design, enabling vision algorithms and control strategies to be developed using the same platform. Furthermore, software-in-the-loop (SIL) testing can be achieved via automatic C/C++ code generation. To close the loop at a system level, the environment must also be modeled. Environmental conditions include the weather conditions, the type of sensor used which affects the input data for the vision algorithms, as well as the vehicle dynamics model. This aspect is also addressed in this paper. We focus on lane-keeping as an example to illustrate different aspects of the framework.

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Kim, A., Otani, T., & Leung, V. (2016). Model-Based Design for the Development and System-Level Testing of ADAS. In Lecture Notes in Mobility (pp. 39–48). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-19818-7_5

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