AD/ADAS - AVSimulation

AD/ADAS

AD/ADAS

The AD/ADAS Pack is made for engineers in charge of advanced driver-assistance systems testing and validation and/or researchers who want to study human factors behavior when using ADAS.

DISCOVER AD/ADAS

Unlock the potential of SCANeR to revolutionize your testing process!

Our advanced simulation platform empowers you to replicate any road environment and create complex scenarios with ease. Validate your Advanced Driver Assistance Systems (ADAS) efficiently by covering millions of kilometers through simulation. With access to manufacturers’ product data, our engineers can precisely define sensor capabilities and tailor noise and error models for unparalleled realism. Don’t settle for less – experience the future of ADAS validation with SCANeR today!

Benefits

Enhanced Target Recognition

Optimized performance and easy handling

Improved flexibility

Features

Simulate any functional sensor (L1) from its product sheet

(Ex: LiDAR; Radar; Ultra-sonic; Lighting; E-horizon; Camera)

More details

The default data set of SCANeR studio comes with sensors’ samples for camera, GPS, lidar, radar and ultrasonic.

Camera sensor

Any number of focal, for each focal: field of view, resolution, distortion, max range and detection functions
Range and visibility percentage per target type
Image output (access to each frame with the SCANeR studio SDK)
Lane and marking detection
Linear object detection
3D Bounding boxes
Targets detection: vehicles, pedestrians, objects, road signs, road lanes/lines
Target detections attributes: anchor point, bounding box, traffic state, many attributes
Occlusion computation on complete scene
Effects: apply distortion, DOF
Image segmentation output
Statistical noise models

Lidar sensor

Simulates many different Lidar types and configurations, including rotating lidar. It gives the possibility to describe rays layouts, rotation speed, scan patterns, sequence duration, etc.
Compute points cloud using a 3D ray casting: intersection between laser rays and 3D scene
3D point position, normal, intensity and targets identification
Debug view of the sensor

Radar sensor

Any number of beams, for each beam:
- Horizontal and vertical FoV
- Minimum and maximum range
Range and visibility percentage per target type
Targets detection: vehicles, pedestrians, objects, road signs
Target detections attributes: anchor point, bounding box, many attributes
Occlusion computation on complete scene
Complex beam shapes can be imported
Statistical noise models

Ultrasonic sensor

Any number of beams, for each beam:
- Horizontal and vertical FoV
- Min and max range
- Complex beam geometry
3D computation on whole scene
Compute nearest objects (detection of target in the beams). For each target: distance, azimuth, elevation …
Road filtering and debug view of the sensor

These models can also be fully customized using python scripting: anchor point selection, custom noise models, detection errors, etc.

Visualize the sensors detection in real time

Each sensor has a full graphical interface allowing an easy customization

Uses Cases

Test and validate ADAS

Engineers working on ADAS such as AEB, ACC, LKA or many others, are able to test and validate their systems in an unlimited amount of known and unknown situations created in SCANeR (e.g. SOTIF). Through its ability to model a large number of sensors, it enables the validation of any driving automation level (1 to 5).

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