Lane detection and tracking using a layered approach

Abstract

A new night-time lane detection system that extends the idea of a Layered Approach [1] is presented in this document. The extension includes the incorporation of (1) Inverse Perspective Mapping (IPM) to generate a bird's-eye view of the road surface, (2) application of Random Sample Consensus (RANSAC) to rid outliers from the data, and (3) Kalman filtering to smooth the output of the lane tracker. Videos of driving scenarios on local city roads and highways were used to test the new system. Quantitative analysis shows higher accuracy in detecting lane markers in comparison to other approaches. © 2009 Springer Berlin Heidelberg.