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Advanced driver assistance system (ADAS) technology offers potentially transformative societal impacts, including significant mobility, road safety, and environmental benefits. ADAS systems can cut-down the number of road accidents by adopting active safety systems in vehicles to be operated on motorways or in urban traffic environments. Given this, today the race is on to deliver safe and reliable autonomous vehicles (AVs) in the market at scale. Advanced technologies such as smart sensors, modern electronics, and computing algorithms are adopted in vehicle electrical and electronic (E/E) architectures. However, this leads to growing system complexity. The development process includes sensors finalization, integration, and validation against simulated dynamic environments. While progressing through the development process several key engineering challenges arise, thus the automotive industry is turning towards 'modelling and simulation' to overcome them at the early design stages. ADAS development is possible by balancing safety, comfort, and economical fuel efficiency with a simulation-based testing and validation framework. The simulation can be placed within a complete dynamic AV simulation loop, controlling the simulated environment. This paper overviews modelling and simulation-based design approaches in ADAS and automated driving (AD) systems and their verification during the early phases of ADAS/AD development using simulation software tools. It also explains the crucial role of modelling and simulation tools in today's ADAS/AD system design and development process.
Thorat et al. (Tue,) studied this question.
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