Skip to Main Content

 

White Paper

An Integrated Simulation Platform to Validate Autonomous Vehicle Safety

Autonomous driving systems rely upon sensors and embedded software for localization, perception, motion planning and execution. Autonomous driving systems can only be released to the public after developers have demonstrated their ability to achieve extremely high levels of safety.

Today’s hands-off autonomous driving systems are largely built with deep learning algorithms that can be trained to make the right decision for nearly every driving situation. These systems, however, lack the detailed requirements and architecture that have been used up to now to validate safety-critical software, such as that which controls commercial airliners.

Road testing is clearly an essential part of the development process, but billions of miles of road testing would be required to validate the safety of autonomous driving systems and software. Simulation is needed to make verification and validation of the operation of autonomous vehicles a practical endeavor.

 

You might be interested in

Struggling with PCB Modeling? Try Trace Reinforcements
Blog

Struggling with PCB Modeling? Try Trace Reinforcements

Learn how Ansys’ trace reinforcement workflow can significantly improve printed circuit board (PCB) model fidelity at the board level.

Tackling Component Swapping Reliability Concerns in Current Supply Chain Environments
Webinar

Tackling Component Swapping Reliability Concerns in Current Supply Chain Environments

How can manufacturers adjust their processes for improved product reliability in current supply chain environments? Register for our webinar to learn more.

Electronics Reliability Using Ansys Sherlock | Ansys Webinar
Webinar

Electronics Reliability Using Ansys Sherlock | Ansys Webinar

This webinar explores Ansys Sherlock automated design analysis software, reliability physics-based electronics design software.