Abstract
This paper proposes a lane detection algorithm using a laser range finder (LRF) for the autonomous navigation of a mobile robot. There are many technologies for ensuring the safety of vehicles, such as airbags, ABS, and EPS. Further, lane detection is a fundamental requirement for an automobile system that utilizes the external environment information of automobiles. Representative methods of lane recognition are vision-based and LRF-based systems. In the case of a vision-based system, the recognition of the environment of a three-dimensional space becomes excellent only in good conditions for capturing images. However, there are so many unexpected barriers, such as bad illumination, occlusions, vibrations, and thick fog, that the vision-based method cannot be used for satisfying the abovementioned fundamental requirement. In this paper, a three-dimensional lane detection algorithm using LRF that is very robust against illumination is proposed. For the three-dimensional lane detection, the laser reflection difference between the asphalt and the lane according to color and distance has been utilized with the extraction of feature points. Further, a stable tracking algorithm is introduced empirically in this research. The performance of the proposed algorithm of lane detection and tracking has been experimentally verified.
Highlights
There has been considerable progress in the field of vehicle safety systems in the last few decades—from safety belts in the 60s to electrical systems such as air bags, anti-lock brake systems (ABSs), and electric power steering (EPS) in the 90s; this progress has been aimed at increasing passenger safety
This paper proposed a real time lane detection algorithm using laser range finder (LRF)
There are so many unexpected barriers, such as bad illumination, occlusions, and vibrations that the vision cannot be used for satisfying the fundamental requirement, and conventional lane detection has mainly been carried out by using vision-based methods, but such methods have a serious drawback of showing substantially diminished performance in driving environments where reliable vision-based information is not obtained, such as under conditions of dense fog
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. When LRF is used as an auxiliary tool, it is used for determining the position of a lane by comparing it with that recognized by a vision-based system at a measurement point or within its scope, or for detecting the location of a curb. In such cases, different sensors should be fused to build a system, which is inevitably expensive. Continuous lines can be recognized and tracked with a 3D road map and the feature point extraction algorithm When these lines become faded or broken over time, lane recognition becomes difficult and accidents are more likely to occur.
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