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Vehicle Performance Engineering for Autonomous Driving

The multi-disciplinary challenge to develop and validate automated driving functions is increasing and shows no signs of slowing down. This requires far more efficient design, verification and validation of advanced driver-assistance systems (ADAS) and autonomous driving systems at the full vehicle level.

Siemens PLM Software integrated and comprehensive solutions support the creation and implementation of mature product development processes that will enable the industry to move autonomous vehicles from concept to reality.

The multi-disciplinary challenge to develop and validate automated driving functions is increasing and shows no signs of slowing down. This requires far more efficient design, verification and validation of advanced driver-assistance systems (ADAS) and autonomous driving systems at the full vehicle level.

Siemens PLM Software integrated and comprehensive solutions support the creation and implementation of mature product development processes that will enable the industry to move autonomous vehicles from concept to reality.

Vehicle Performance Engineering for Autonomous Driving

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Autonomous vehicles are revolutionizing the way we develop and engineer cars, and are reshaping the competitive landscape. The increase in software and hardware complexity, the required massive validation and verification cycles, and the growing number and variety of sensors, require manufacturers to rethink today's vehicle development processes. When it comes to the integration of advanced driver assistance systems (ADAS) and autonomous driving systems into vehicle platforms, a critical challenge is to optimize and verify full vehicle performance. Balancing safety, comfort, and fuel economy for automated driving functions requires insight into the interaction between the different attributes.

Siemens PLM Software solutions for vehicle, sensor, and traffic simulation connect mechanical, electrical, and software development that enables the performance optimization required for automakers to deliver on the increasing demands for autonomous vehicles today, and tomorrow.

Vehicle Performance Engineering for Autonomous Driving

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Engineering best practices for algorithms virtual validation of autonomous vehicles

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Leverage virtual models and scenarios, from a robust perception of the driving scene to the definition of optimal trajectories and control strategies.

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