Watch this on-demand webinar to learn more about functional testing and understand the benefits of a HV integration testing approach.

Scenario-based testing is established as an efficient method to test critical traffic situations in a reproducible way. The AVL SCENIUS™ toolchain for scenario-based testing ensures end-to-end consistency and traceability, from the requirements to test reports, enabling a thorough safety argumentation and type approval process.

Our simulation expert will give you a free training where he will walk you through all the typical steps necessary to integrate and test an Advanced Driver Assistance System (ADAS) or Automated Driving (AD) software in a virtual environment.

Vehicle and sensor soiling is becoming an increasingly important aspect of vehicle design. The focus is clearly shifting from pure aesthetics to challenges related to safety improvement and cost reduction. 

Discover how AVL and AVES Reality are revolutionizing the verification and validation of automated driving systems in urban areas.

Solid oxide fuel cells are a promising technology for power generation within the context of renewable energy systems. This is mainly due to their high efficiency, fuel flexibility and environmental compatibility.

We will dive deep into the complexities of fast charging, and we are going to introduce you an approach to analyze fast-charging behavior, leveraging AVL's software tools.

While electric vehicles dominate the conversation of sustainable mobility, electrification is not on the horizon for certain sectors anytime soon. For heavy-duty transport, heavy machinery and aviation, alternative fuels like ammonia or green hydrogen provide sustainable mobility solutions.

The new AVL Scenario Simulator™ is a cost-optimized solution for fully automated, large-scale ADAS/AD testing. Build the optimal virtual prototype for each test purpose.

The ADAS promise - to make our streets safer - pushes regulators around the world to adopt ADAS features into the legislation and make them compulsory. As a result, the effort and complexity of ADAS feature validation is increasing tremendously.