ADAS and autonomous driving systems are redefining the automotive industry and changing all aspects of transportation, from daily commutes to long-haul trucking. MATLAB® and Simulink® provide the ability to develop the perception, planning, and control components used in these systems.
In this talk, you will learn about these tools through examples that ship in R2019a, including:
- Perception: Design LIDAR, vision, radar, and sensor fusion algorithms with recorded and live data
- Planning: Visualize street maps, design path planners, and generate C/C++ code
- Controls: Design a model-predictive controller for traffic jam assist, test with synthetic scenes and sensors, and generate C/C++ code
- Deep learning: Label data, train networks, and generate GPU code
- Systems: Simulate perception and control algorithms, as well as integrate and test hand code