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ADAS Virtual Prototyping with the OpenMETA Toolchain
- Masahiro Yamaura - Toyota Info Technology Center USA ,
- Nikos Arechiga - Toyota Info Technology Center USA ,
- Shinichi Shiraishi - Toyota Info Technology Center USA ,
- Scott Eisele - Vanderbilt University ,
- Joseph Hite - Vanderbilt University ,
- Jason Scott - Vanderbilt University ,
- Sandeep Neema - Vanderbilt University ,
- Theodore Bapty - Vanderbilt University
ISSN: 1946-4614, e-ISSN: 1946-4622
Published April 05, 2016 by SAE International in United States
Citation: Eisele, S., Yamaura, M., Arechiga, N., Shiraishi, S. et al., "ADAS Virtual Prototyping with the OpenMETA Toolchain," SAE Int. J. Passeng. Cars – Electron. Electr. Syst. 9(1):22-29, 2016, https://doi.org/10.4271/2016-01-0002.
Complex systems, such as modern advanced driver assistance systems (ADAS), consist of many interacting components. The number of options promises considerable flexibility for configuring systems with many cost-performance-value tradeoffs; however the potential unique configurations are exponentially many prohibiting a build-test-fix approach. Instead, engineering analysis tools for rapid design-space navigation and analysis can be applied to find feasible options and evaluate their potential for correct system behavior and performance subject to functional requirements.
The OpenMETA toolchain is a component-based, design space creation and analysis tool for rapidly defining and analyzing systems with large variability and cross-domain requirements. The tool supports the creation of compositional, multi-domain components, based on a user-defined ontology, which captures the behavior and structure of components and the allowable interfaces. Design spaces in OpenMETA allow product families to be defined in a single model, with component/subsystem alternatives and parametric variation. Using this system design space, OpenMETA then enables analysis of the system, via composition of the system and environment/scenario models into engineering tools, and executing simulations to compute metrics.
System models can be created and executed in many abstractions based on the required accuracy, phenomena, and execution speed. This paper explores use cases from simulations with high fidelity components, to a gamified environment using Unity with a simple model of vehicle physics. This allows for user-in-the-loop analysis of controllers and components. This approach benefits ADAS by allowing for rapid prototyping across an array of candidate designs while evaluating the requirements of the vehicle at the appropriate fidelity level.
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