Automated Driving Toolbox

 

Automated Driving Toolbox

Design, simulate, and test ADAS and autonomous driving systems

Reference Applications

Reference applications form a basis for designing and testing ADAS applications.

Lane Following Systems

AEB Euro NCAP Testing with RoadRunner Scenario

Automated Parking Systems

Traffic Negotiations at Intersections

Product Highlights

Scenario Simulation

Simulation using realistic driving scenarios and sensor models is a crucial part of testing automated driving algorithms. Automated Driving Toolbox provides various options such as cuboid simulation environment, Unreal engine simulation environment, and integration with RoadRunner Scenario to test these algorithms. This application supports import and export of scenes and scenarios to ASAM OpenDRIVE and ASAM OpenSCENARIO® formats.

Generate Scenes and Scenarios from Recorded Sensor Data

Create virtual driving scenarios from vehicle data recorded using various sensors, such as a global positioning system (GPS), inertial measurement unit (IMU), camera, and lidar. Use raw sensor data, recorded actor track lists, or lane detections.

Test Suite for Euro NCAP Protocols

Automatically generate seed scenario and its variants for the assessment of various Euro NCAP protocols. Visualize the generated variants or export them to the ASAM OpenSCENARIO® file format. Using Test Bench, run simulations and get Euro NCAP Test Metrics.

Planning and Control

Plan driving paths with vehicle costmaps and motion-planning algorithms. Use lateral and longitudinal controllers to follow a planned trajectory.

Detection, Tracking, and Ground Truth Labeling

Develop and test vision and lidar processing algorithms for automated driving. Perform multi-sensor fusion and multi-object tracking framework with Kalman. Automate labeling of ground truth data and compare output from an algorithm under test. Using Ground Truth Labeler app, label multiple signals like videos, image sequences, and lidar signals representing the same scene.

Localization and Mapping

Use simultaneous localization and mapping (SLAM) algorithms to build maps surrounding the ego vehicle based on visual or lidar data. Access and visualize high-definition map data from the HERE HD Live Map service. Display vehicle and object locations on streaming map viewers.