New Lane Model and Distance Transform for Lane Detection and Tracking

Authors:
Ruyi Jiang;Reinhard Klette;Tobi Vaudrey;Shigang Wang
Affiliations:
Shanghai Jiao Tong University, Shanghai, China;The University of Auckland, Auckland, New Zealand;The University of Auckland, Auckland, New Zealand;Shanghai Jiao Tong University, Shanghai, China
Venue:
CAIP '09 Proceedings of the 13th International Conference on Computer Analysis of Images and Patterns
Year:
2009

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Abstract

Particle filtering of boundary points is a robust way to estimate lanes. This paper introduces a new lane model in correspondence to this particle filter-based approach, which is flexible to detect all kinds of lanes. A modified version of an Euclidean distance transform is applied to an edge map of a road image from a birds-eye view to provide information for boundary point detection. An efficient lane tracking method is also discussed. The use of this distance transform exploits useful information in lane detection situations, and greatly facilitates the initialization of the particle filter, as well as lane tracking. Finally, the paper validates the algorithm with experimental evidence for lane detection and tracking.