Automated Driving Toolbox provides algorithms and tools for designing, simulating, and testing ADAS and automated driving features. These ADAS features include forward collision warning, autonomous emergency braking, adaptive cruise control, lane keeping assist, and parking valet.
The toolbox integrates scenarios, sensors, and vehicle dynamics for validating ADAS algorithms for model-in-the-loop (MIL), software-in-the-loop (SIL), and hardware-in-the-loop (HIL) simulations. You can programmatically author and simulate scenarios in Cuboid and RoadRunner environments. It offers visualization tools, such as bird's-eye-view plots, video, lidar, and map displays, and connects with Unreal Engine®.
The Test Suite for Euro NCAP® Protocols add-on supports standards-based testing by providing scenarios, metrics, and reports. The Scenario Builder add-on enables you to recreate real-world driving conditions from recorded sensor data, including camera, lidar, Global Positioning Systems (GPS), and Inertial Measurement Units (IMU).
Reference Applications
Reference applications form a basis for designing and testing ADAS applications.
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.
Product Resources:
Automated Driving Toolbox FAQs
Automated Driving Toolbox™ provides algorithms and tools for designing, simulating, and testing ADAS and automated driving features. These ADAS features include applications like forward collision warning, autonomous emergency braking, adaptive cruise control, lane keeping assist, and parking valet and algorithms including vision and lidar perception, sensor fusion, path planning, and vehicle controllers.
The toolbox includes a bird's-eye-view plot and scope for sensor coverage, detections and tracks, and displays for video, lidar, and maps. It also provides tools for 3D visualizations with RoadRunner Scenario and Unreal Engine.
The toolbox provides ideal ground truth sensor, probabilistic sensors: Vision detection generator, Driving radar data generator, Lidar point cloud generator, INS, and Ultrasonic detection generator. It also provides sensors like Simulation 3D Camera, Simulation 3D Probabilistic Radar, and Simulation 3D Lidar that provide output from a photorealistic 3D environment like Unreal Engine.
Yes, Automated Driving Toolbox supports C/C++ code generation for rapid prototyping and HIL testing, with support for scenario reader, sensor fusion, tracking, path planning, and vehicle controller algorithms.
The toolbox provides reference test benches and workflows for autonomous emergency braking, adaptive cruise control, lane keeping assist, highway lane following, highway lane change, traffic light negotiation, intersection movement assist using V2V and V2X, truck platooning, and truck lane keep assist systems.
Yes, the toolbox lets you import and work with HERE HD Live Map data and OpenDRIVE road networks, and supports import and export of scenes and scenarios to ASAM OpenDRIVE and ASAM OpenSCENARIO formats.
Yes, you can create virtual driving scenarios from vehicle data recorded using GPS, IMU, camera, and lidar sensors, using raw sensor data, recorded actor track lists, or lane detections.
The toolbox includes a Euro NCAP test suite that generates NCAP protocol‑compliant scenarios, provides Simulink driving simulation test bench, evaluation metrics, and reports to assess ADAS performance against Euro NCAP requirements.
Yes. The SUMO Interface support package provides Simulink blocks that enable co‑simulation between Simulink and Eclipse SUMO to model traffic flow, spawn actors, and exchange vehicle states for large‑scale traffic scenario testing.
Automated Driving Toolbox includes algorithms and reference workflows for lane level path planning, behavior planning, vehicle control, multi‑object tracking, and sensor fusion to support end‑to‑end ADAS development.
Automated Driving Toolbox provides APIs and apps to author scenarios in both cuboid and RoadRunner environments. You can use drivingScenario and the Driving Scenario Designer for cuboid simulations, and roadrunner and roadrunnerAPI to create and simulate scenarios in RoadRunner Scenario.
