Intermediate
Core Skill
Programming
Lane Detection and Vehicle Dynamics
This course covers two critical pillars of autonomous navigation: lane detection and vehicle dynamics. Participants will learn to implement computer vision techniques to detect lane boundaries from camera feeds and understand various models (kinematic, dynamic) to predict vehicle behavior. The course combines theoretical knowledge with practical programming exercises to build a robust lane-keeping system.
Course Curriculum
- Introduction to Lane Detection
- Overview of AV Software and Hardware Architecture
- Sensor Principles: Camera, Odometry, GPS
- Practical Lane Detection: Image Transforms, Thresholding, Edge Detection
- Vehicle Dynamics Modeling (Kinematic & Dynamic)
- State-Space Analysis and Control Theory
Course Information
Learning Outcomes
- Understand sensor principles for cameras and vehicle state estimation.
- Apply image transformations and filtering for lane detection.
- Develop software pipelines to identify lane lines in images and video.
- Model lateral and longitudinal vehicle dynamics.
- Grasp the fundamentals of model predictive control.
Target Audience
Aspiring AV engineers, software developers, and researchers looking to specialize in perception and control systems.
Prerequisites
Basic knowledge of Python or C++ and an understanding of linear algebra is required.