Lilly Tech Systems
Learn Autonomous Vehicles
Master self-driving car technology from the ground up. Explore perception systems, path planning, vehicle control, and simulation — the complete autonomous driving stack.
Your Learning Path
Follow these lessons in order, or jump to any topic that interests you.
1. Introduction
What are autonomous vehicles? Explore SAE autonomy levels, the self-driving technology stack, and the current state of the industry.
2. Perception
Build perception pipelines with cameras, LiDAR, and radar for object detection, lane detection, and 3D scene understanding.
3. Planning
Implement route planning, behavior planning, and trajectory generation for safe autonomous navigation in traffic.
4. Control
Design vehicle controllers for steering, throttle, and braking using PID, Stanley, MPC, and learning-based approaches.
5. Simulation
Use CARLA, LGSVL, and AirSim to test autonomous driving algorithms in realistic virtual environments.
6. Best Practices
Safety validation, regulatory compliance, edge case handling, and production deployment strategies for autonomous vehicles.
What You'll Learn
By the end of this course, you'll be able to:
Understand the AV Stack
Navigate the complete autonomous vehicle technology stack from sensors and perception through planning and control.
Build Perception Systems
Process camera, LiDAR, and radar data to detect objects, lanes, and traffic signs for safe driving decisions.
Plan Safe Trajectories
Generate safe, comfortable driving trajectories that respect traffic rules, avoid obstacles, and handle complex scenarios.
Simulate & Validate
Test autonomous driving algorithms in industry-standard simulators and understand the path to real-world deployment.