Automated Driving with MATLAB

Day 1 of 2

Labeling of Ground Truth Data

Objective: Label ground truth data in a video or sequence of images interactively. Automate the labeling with detection and tracking algorithms.

• Overview of the Ground Truth Labeler app
• Label regions of interest (ROIs) and scenes
• Automate labeling
• View and export ground truth results

Visualizing Sensor Data

Objective: Visualize camera frames, radar, and lidar detections. Use appropriate coordinate systems to transform image coordinates to vehicle coordinates and vice versa.

• Create a bird’s-eye plot
• Plot sensor coverage areas
• Visualize detections and lanes
• Convert from vehicle to image coordinates
• Annotate video with detections and lane boundaries

Detecting Lanes and Vehicles

Objective: Segment and model parabolic lane boundaries. Use pretrained object detectors to detect vehicles.

• Perform a bird’s-eye view transform
• Detect lane features
• Compute lane model
• Validate lane detection with ground truth
• Detect vehicles with pretrained object detectors

Processing Lidar Point Clouds

Objective: Work with lidar data stored as 3-D point clouds. Import, visualize, and process point clouds by segmenting them into clusters. Register point clouds to align and build an accumulated point cloud map.

• Import and visualize point clouds
• Preprocess point clouds
• Segment objects from lidar sensor data
• Build a map from lidar sensor data

Day 2 of 2

Fusing Sensor Detections and Tracking

Objective: Create a multi-object tracker to fuse information from multiple sensors such as camera, radar and lidar.

• Track multiple objects
• Preprocess detections
• Utilize Kalman filters
• Manage multiple tracks
• Track with multi-object tracker

Tracking Extended Objects

Objective: Create a probability hypothesis density tracker to track extended objects and estimate their spatial extent.

• Define sensor configurations
• Track extended objects
• Estimate spatial extent

Generating Driving Scenarios and Modeling Sensors

Objective: Create driving scenarios and synthetic radar and camera sensor detections interactively to test automated driving perception algorithms.

• Overview of the Driving Scenario Designer app
• Create scenarios with roads, actors, and sensors
• Simulate and visualize scenarios
• Generate detections and export scenarios
• Test algorithms with scenarios