Robust Lane Detection and Tracking for Real-Time Applications

An effective lane-detection algorithm is a fundamental component of an advanced driver assistant system, as it provides important information that supports driving safety. The challenges faced by the lane detection and tracking algorithm include the lack of clarity of lane markings, poor visibility...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems Vol. 19; no. 12; pp. 4043 - 4048
Main Authors: Lee, Chanho, Moon, Ji-Hyun
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Automobile industry
Automobile safety
Clustering
Embedded systems
Gray-scale
Image color analysis
Image edge detection
Image segmentation
Kalman filter
Lane detection
lane tracking
Light reflection
line clustering
Noise reduction
Real time operation
real-time
Real-time systems
region of interest
Road transportation
Robustness
Tracking
Vehicle safety
Visibility
ISSN:1524-9050, 1558-0016
Online Access:Get full text
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Summary:An effective lane-detection algorithm is a fundamental component of an advanced driver assistant system, as it provides important information that supports driving safety. The challenges faced by the lane detection and tracking algorithm include the lack of clarity of lane markings, poor visibility due to bad weather, illumination and light reflection, shadows, and dense road-based instructions. In this paper, a robust and real-time vision-based lane detection algorithm with an efficient region of interest is proposed to reduce the high noise level and the calculation time. The proposed algorithm also processes a gradient cue and a color cue together and a line clustering with scan-line tests to verify the characteristics of the lane markings. It removes any false lane markings and tracks the real lane markings using the accumulated statistical data. The experiment results show that the proposed algorithm gives accurate results and fulfills the real-time operation requirement on embedded systems with low computing power.
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ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2018.2791572