With higher levels of automation and the exploding complexity of autonomous driving systems, proving that an autonomous vehicle (AV) or system meets safety requirements will require a model-based development approach in virtual verification cycles. With advanced verification and validation solutions in a simulation environment, automotive manufacturers will be able to replace a lot of the costly and time-consuming conventional testing on roads.
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Increasing levels of automation bring new challenges for automotive manufacturers to meet industry standards and regulations. Extensively testing the safety and reliability of autonomous driving systems against these standards will be vital to creating the trust consumers need. To be able to do that, AV systems should be tested against a massive number of critical scenarios. Simulation is the only way to reach the test coverage required to feel confident these systems are ready to go to market.
Siemens offers solutions to capture, store and analyze real-life raw sensor data to establish a comprehensive scenario database. Critical scenarios or corner cases can be created Using AI technology and combing physics-based static and dynamic world information. By leveraging comprehensive world models, engineers can optimize autonomous driving system designs, train neural networks, and perform extensive verification and validation using physics-based, high fidelity level simulation tools.
Using performance data to drive smarter decisions, Siemens offers advanced verification and validation solutions for AV development. It provides an integrated tool suite of simulation, test, and engineering services supporting a continuous, closed-loop development process in a comprehensive digital twin. With Siemens Autonomous Vehicle Development solution, development teams are enabled to stay integrated from start to finish, enhancing efficiency, productivity, and innovation across the enterprise.
Download the eBook to learn more about how advanced verification and validation solutions leverage performance data to drive smarter decisions in autonomous vehicle development.