Accurate and Detailed Transversal Road Section Characteristics Extraction Using Laser Scanner

The incorporation of sensors in vehicles for the perception of the environment for safety functions and autonomous driving (such as LiDAR—e.g., [11,12,13], computer vision—e.g., [14,15], radar—e.g., [16], or sensor fusion of some of them—e.g., [17,18]) has opened another field to improve positioning...

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Bibliographic Details
Published in:Applied sciences 2018-05, Vol.8 (5), p.724
Main Authors: Jiménez, Felipe, Clavijo, Miguel, Castellanos, Fernando, Álvarez, Carlos
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Clustering
Computer vision
Digital maps
Driving ability
Global positioning systems
GPS
Image contrast
International conferences
Lane keeping
Lasers
Localization
Mapping
Obstacle avoidance
Odometers
Perception
Roads
Roads & highways
Scanners
Sensors
Simultaneous localization and mapping
Urban areas
Vehicles
Vision systems
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Summary:The incorporation of sensors in vehicles for the perception of the environment for safety functions and autonomous driving (such as LiDAR—e.g., [11,12,13], computer vision—e.g., [14,15], radar—e.g., [16], or sensor fusion of some of them—e.g., [17,18]) has opened another field to improve positioning. [...]different methods of visual odometry and SLAM (Simultaneous Localization and Mapping), based on computer vision and laser scanners, have emerged in recent years (e.g., [19,20,21,22]). In this way, the sensors used for obstacle detection are also used as primary or secondary sensors for positioning and road mapping [23,24]. [...]lane keeping systems are based, generally, on computer vision systems, and base their correct operation on the perception of the lines that delimit the lanes. The solution proposed in the method is to try to identify areas with constant radius differences within a predefined tolerance, which allows determining the roadway area. Since it is possible to accept points on the road that do not correspond to it, two additional filters are applied on the set of points detected: a height filter with which the points of each layer that differ significantly from the average height of the rest are discarded from points identified as roadway (potentially), and DBSCAN clustering algorithm. 2.2. [...]integration of computer vision could be used to enhance the extracted information, because of the capacity of managing other kinds of image properties (such as colors, contrast, etc.), and limitations of this technology could be mitigated by sensor fusion with the current laser scanners.
ISSN:2076-3417
2076-3417
DOI:10.3390/app8050724