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Ansys at Autonomous Vehicles Online 2022

We help you push the limits

Autonomy’s limitless potential requires unprecedented engineering innovation. Simulation can solve the critical design challenges in record time, increasing speed-to-market whilst reducing cost.

May 25-26, 2022


Level 5 Autonomy through Simulation 

Critical market demands such as safety, complexity, cost, and time-to-market must be overcome by those who want to win the race to market. And to meet these market needs presents critical engineering challenges.

  • Autonomy System Definition
    Hazards caused by malfunctions, safety analysis methods, industry standard compliance, and cyberattacks
  • Autonomy System Validation
    Scenario definition, selection, creation and edge cases, sensor models, camera systems, and real-world variability such as weather and lighting conditions
  • Autonomy Hardware Development
    sensors, industry regulations, HMI complexity, and optimization of emitter and receiver design
  • Autonomy Software Development
    Scalable testing, industry standard compliance, closed-loop simulation, and testing at various levels – MIL, SIL, and HIL

Simulation enables 1,000 times more scenarios to be examined, collecting enormous amount of high-value data more quickly and economically than ever. Automotive leaders know they can win the race to Level 5 autonomy through simulation. 


Ansys Presentation

Making Autonomous Vehicles Safer Using Physics-Based Sensor Simulation at Scale

Time: May 25, 2022| 9:10am - 10:00am EDT                      

Speaker: Emmanuel Follin, Senior Manager Product Management, Ansys

The primary engineering challenge in developing ADAS and Autonomous Vehicles is ensuring that they will operate safely under all situations encountered. Since they are likely to encounter many millions of different driving situations throughout the course of their operation, engineering of ADAS and AVs must comprehensively address the design and validation of their software and hardware components over millions of driving scenarios. This is a massive task involving thousands of engineers working collaboratively at OEMs as well as Tier 1 and 2 suppliers.

With high-fidelity, physics-based simulation of radar, lidar, camera, and other sensors, 1000 times more autonomous vehicle scenarios can be examined than could be assessed through physical road testing. This presentation will explore how to make autonomous driving safer and expedite the design and validation of all aspects of an automated driving system using proven physics solutions [from Ansys], including:

  • Bridging the gap between component design and system V&V
  • Generating synthetic sensor data for Machine Learning as well as for testing
  • Using physics-based Real-Time Radar, Camera and Lidar models within driving scenarios in XiL use-cases
  • Reducing field operation testing by using physics-based sensor simulation