The need for a multidisciplinary approach in advanced automotive development. The importance of visualization to assess performance. Developing the right testing workflow for autonomous vehicles.

For design engineers, an artificial intelligence (AI) workflow encompasses four steps: data preparation, modeling, simulation and testing, and deployment. While all steps are important, many engineers ...

Engineers are increasingly seeking to integrate AI into their projects, both to improve their results and remain ahead of their profession’s digital curve. To successfully integrate AI, engineers ...

Engineers without signal-processing expertise can now employ reusable artificial intelligence (AI) models to quickly and accurately extract and select features for audio processing, predictive ...

Electronic control units (ECUs) are vital embedded systems in vehicles; as such they impact numerous functions in a car and therefore must undergo rigorous testing. In any test workflow, ...

Manufacturers can benefit from AI in a variety of ways, such as improving production, quality control and efficiency. Although AI offers manufacturers several new applications, to get the most value ...