Automated Driving Toolbox

 

Automated Driving Toolbox

Design, simulate, and test ADAS and autonomous driving systems

Simulink lane following simulation with a highway driving scenario, vehicle sensors, lane detections, surrounding traffic, and a bird’s-eye view of tracked objects and lane boundaries.

Reference Applications

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

Lane Following Systems

AEB Car to Car simulation with Euro NCAP metrics.

AEB Euro NCAP Testing with RoadRunner Scenario

Parking lot with two cars parked side by side and a visualization of the automated parking valet.

Automated Parking Systems

Image on left shows two cars headed toward a four-way traffic light stop on different roads. Image on right plots the cars with V 2 X communication.

Traffic Negotiations at Intersections

Product Highlights

Scenario Simulation

Simulate realistic driving scenarios and sensor models to test automated driving algorithms in cuboid or Unreal Engine simulation environments, or via integration with RoadRunner Scenario. Import and export scenes and scenarios to ASAM OpenDRIVE® and ASAM OpenSCENARIO® formats.

Scenario generated from real-world camera and lidar data.

Generate Scenes and Scenarios from Recorded Sensor Data

Create virtual driving scenarios using vehicle data recorded from a GPS, IMU, camera, lidar, and other sensors. Use raw sensor data, recorded actor track lists, or lane detections.

Euro NCAP scenario with metrics.

Test Suite for Euro NCAP Protocols

Automatically generate a seed scenario and its variants to assess automated driving systems against Euro NCAP protocols. Visualize the generated variants or export them to the ASAM OpenSCENARIO file format. Use Driving Simulation Test Bench to run simulations and obtain Euro NCAP test metrics.

Diagram of Simulink cosimulation with Eclipse SUMO showing traffic flow and vehicle dynamics integration for A D testing.

Cosimulate Simulink and Eclipse 
SUMO Traffic Simulator

Use Eclipse SUMO™ with Simulink to simulate traffic interactions and test automated driving functions. Combine traffic flow modeling with vehicle dynamics for system-level validation in realistic scenarios. 

Planning and Control

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

Map of streets and highways using latitude and longitude points.

Localization and Mapping

Use simultaneous localization and mapping (SLAM) algorithms to build maps of the environment 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.

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 such as 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 an ideal ground truth sensor, probabilistic sensors, including Vision Detection Generator, Driving Radar Data Generator, Lidar Point Cloud Generator, INS, and Ultrasonic Detection Generator. It also provides sensors such as 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 as well as 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 in ASAM OpenDRIVE and ASAM OpenSCENARIO formats.

Yes, you can create virtual driving scenarios using vehicle data recorded from GPS, IMU, camera, and lidar sensors in the form of raw sensor data, recorded actor track lists, or lane detections.

The toolbox includes a Euro NCAP test suite that generates NCAP protocol–compliant scenarios and provides a 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 cosimulation 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.

You can create cuboid-based scenarios with the Driving Scenario Designer app, or create and simulate scenarios with RoadRunner Scenario through an interactive interface or APIs.

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