Studies in Computational Intelligence

In this chapter, we discuss one of the most popular machine vision applications in the automotive industry: lane detection and tracking. Model-based lane detection algorithms can be separated into lane modeling, feature extraction and model parameter estimation. Each of these steps is discussed in detail with examples and results. A recently proposed lane feature extraction approach, which is called the Global Lane Feature Refinement Algorithm (GLFRA), is also introduced. It provides a generalized framework to significantly improve various types of gradient-based lane feature maps by utilizing the global shape information and subsequently improves the parameter estimation and the tracking performance. Another…