To train autonomous driving systems for critical collision scenarios, the DeepSafe project aims to address the “reality gap” in these simulated scenarios. A crucial component of these scenarios is the realistic behavior of pedestrians interacting with their environment. AV elevate uses states-of-the-art computational biomechanical modelling to generate realistic human...
Claytex continues to invest in the important development of automated testing methodologies for autonomous vehicles, as well as researching how to define safety and quantify it. Both topics are crucial to define and optimise AV testing. However, in many cases, having a fully automated test series generation can mean...
The Simulation Manager tool, developed by Claytex, offers a wide range of methods to help engineers set up and test anything from sensor hardware in the loop to full autonomous driving. However, testing is useless unless the relevant data can be extracted from the simulation. This blog covers the...
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