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This paper presents a virtual validation and testing framework for ADAS (Advanced Driver Assistant System) planning and control development based on a co-simulation platform of vehicle dynamics and traffic environment tools. One of the main challenges in ADAS development is validating the planning and control algorithms in a closed-loop fashion, where both vehicle dynamics characteristics and a wide variety of traffic scenarios are taken into account. The designs should also guarantee optimal performance toward precise trajectory tracking, and time/fuel optimality with respect to various constraints. This work focuses on simulation-based approaches to frontload control design verification during the early phases of ADAS development involving two software: LMS Imagine.Lab Amesim and PreScan. The requirements for an interface that help to facilitate the co-simulation development are studied. The approach is demonstrated with three different use cases: adaptive cruise control, green wave technology, and autonomous parking.
ADAS, autonomous vehicles, control, co-simulation.
ADAS, autonomous vehicles, control, co-simulation.
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