Ansys VRXPERIENCE Sensors
Test and Validate Sensors for Self-Driving Cars

Ansys VRXPERIENCE realistic sensor testing and validation enables you to test your autonomous vehicles, ADAS and sensors faster than with physical prototypes.

Ansys VRXPERIENCE Sensors

Virtually Experiment with Your Sensors to Meet Physical Needs

To reduce the need for costly physical prototypes while speeding the design process, the Ansys VRXPERIENCE Sensors solution offers the opportunity to virtually experience sensors to test and analyze their performance. In the virtual world, use realistic driving scenarios to investigate radar, lidar and camera sensors perception in a Mil Sil or Hil context.

  • Realistic Driving Scenarios
    Realistic Driving Scenarios
  • HiL, MiL and SiL Connectivity
    HiL, MiL and SiL Connectivity
  • Radar, Lidar and Camera Sensors
    Radar, Lidar and Camera Sensors
Ansys VRXPERIENCE Sensors

Quick Specs

Discover high-fidelity physics-based sensor simulation with ground truth information for autonomous vehicles. Enable the use of multiple sensor simulations amidst realistic driving scenarios to ensure the physical prototype meets expectations.

  • Driving Scenarios
  • Radar Sensor
  • HiL Connectivity
  • GPU Radar
  • Ground-Truth Sensors
  • Multi-Sensor Simulation
  • MiL Connectivity
  • Camera Sensor
  • Lidar Sensor
  • SiL Connectivity

Validate Autonomous Vehicle Safety

Integrated simulation scenarios speed and improve the ability to confirm safety features across vehicle creation, including autonomous vehicles.

Autonomous vehicles combine sensors and software to control, navigate and drive safely. To ensure prototype vehicles are real-world ready, sensors must be designed with an immense variety of test cases.

Autonomous driving systems rely upon sensors and embedded software for localization, perception, motion planning and execution. They can only be released to the public after developers have demonstrated their ability to achieve 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 until now to validate safety-critical software, such as the kind that control 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 serves the need to make verification and validation of the operation of autonomous vehicles a practical effort. 

Applications

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Autonomy System Development

Model-based safety and cybersecurity assessments using Ansys simulation help to accelerate autonomous system development and certification.

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Autonomy Sensors

Ansys provides a comprehensive autonomous vehicle sensor simulation capability that includes lidar, radar and camera design and development.

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High-Performance Simulation Solutions for Realistic Sensor Testing and Validation

Test faster with VRXPERIENCE. The solution eliminates any risk that real-world tests pose to other drivers and pedestrians, allowing the virtual world to stretch the limits of sensors. Customize your drive tests with a variety of scenarios and road conditions, guaranteeing that the autonomous vehicles and ADAS are all tested on edge scenarios.

VRXPERIENCE Sensors readily integrates the simulation of ground-truth sensors and camera, radar, lidar and ultrasonic sensor types while accurate outputs enable you to assess your complex ADAS systems and autonomous vehicles virtually by connecting perception, fusion and control function in a single drive simulator.

 

Key Features

Benefit from powerful ray-tracing capabilities to recreate sensor behavior and easily retrieve sensor outputs through a dedicated interface.

  • Driving Scenarios 
  • Ray Casting Ideal Sensor
  • Camera Sensor
  • Lidar Sensor
  • Radar Sensor
  • HiL, SiL and MiL Connectivity 

To test sensors in scenarios, add several cars to create complex situations, such as following a car and monitoring the path of a crossing car simultaneously. Each vehicle in a scenario can be either static or automatic, enabling evaluation at a specific point of interest or along a predefined trajectory. Sensor simulation follows ego-vehicle dynamic motion.

Sensor data output, such as lightning strike hit points, material properties, etc., and vehicle parameter input or output, such as position, orientation, speed, and steering wheel, are all available. Thanks to the consistent combination of data from multiple sensors, the simulation enables you to validate the model of a smart sensor’s behavior or its fusion algorithms. Deterministic and real-time modes are both supported.

Software allows you to simulate the actual camera model in edge case driving situations. It simulates all components of a camera, such as the lens system, imager and pre-processor. For automotive front-facing cameras, the windshield can also be considered in simulation. Consider the optical and spectral properties of the environment in visible range, along with the optical properties of the lens system and optoelectronic properties of the imager. With the addition of plugins, the simulation can manage dynamic adaption. Camera simulation creates raw images, which are used to test and validate perception algorithms either as models-in-the-loop, software-in-the-loop or hardware-in-the-loop. 

You will benefit from powerful ray-tracing capabilities to recreate sensor behavior and be able to easily retrieve sensor results through a dedicated interface. IR emitter world model IR properties (is this “The IR emitter will model IR properties?” and receiver electronics are considered in the simulation which can output from raw signals – waveforms – to point clouds. This solution provides a unique way to collect virtual sensor information during real-time drives and use the information to develop autopilot code. 

VRXPERIENCE’s GPU Radar feature provides the capability to perform full physics-based radar scenario simulations in real time at frame rates greater than 30 frames per second. The simulations consider multi-bounce reflections and transmissions from dielectric surfaces. Multichannel and MIMO radars can be simulated using the linear scalability of GPU Radar. With the addition of GPU radar, VRXPERIENCE now provides the ability to perform ADAS and Autonomy scenario simulation with full-physics models of all key sensors - cameras, radars and lidars. The data collected out of the radar model is used to efficiently stimulate the algorithm of radar ECU digital signal processing to quickly improve the accuracy and robustness of automotive radars in edge cases. Ansys VRXPERIENCE comes with a library of objects with dielectric properties defined.

Model-and Software-in-the-Loop (MiL,Sil): Perform massive scenario variation by leveraging cutting-edge testing — on-premise and in the cloud. Assess perception performance by varying parameters across countless driving scenarios.

VRXPERIENCE SENSOR RESOURCES & EVENTS

Featured Webinars

On Demand Webinar
Ansys On Demand Webinar

Simulation Toolchain for Advanced Driver Assistance Systems / Autonomous Driving Functions

Join us for this free webinar which spotlights how Ansys VRXPERIENCE will help you efficiently and cost-effectively create your ADAS and AV products, expediting their path to market faster than ever. Receive expert tips for implementing your simulation toolchain for ADAS/AVs.

On Demand Webinar
Ansys On Demand Webinar

Speed Development of Safe Autonomous Driving

Join Ansys and AVSimulation for a demonstration of ANSYS VRXPERIENCE Simulator powered by SCANeR™.


White Papers & Articles

Ansys Whitepaper autonomous safety

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. 


Videos


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