Developing a Method to Automatically Extract Road Boundary and Linear Road Markings from a Mobile Mapping System Point Cloud Using Oriented Bounding Box Collision-Detection Techniques

Advancements in data-acquisition technology have led to the increasing demand for high-precision road data for autonomous driving. Specifically, road boundaries and linear road markings, like edge and lane markings, provide fundamental guidance for various applications. Unfortunately, their extracti...

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Vydáno v:Remote sensing (Basel, Switzerland) Ročník 15; číslo 19; s. 4656
Hlavní autoři: Kang, Seokchan, Lee, Jeongwon, Lee, Jiyeong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.10.2023
Témata:
Algorithms
automatic extraction
Boundaries
Data acquisition
data collection
Deep learning
Electronic data processing
extracts
ground MMS survey
Horizontal orientation
Image processing
Methods
OBB collision-detection algorithm
point cloud data
remote sensing
road boundary
road marking
Roads
Roads & highways
Sensors
South Korea
Streets
South Korea
ISSN:2072-4292, 2072-4292
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Shrnutí:Advancements in data-acquisition technology have led to the increasing demand for high-precision road data for autonomous driving. Specifically, road boundaries and linear road markings, like edge and lane markings, provide fundamental guidance for various applications. Unfortunately, their extraction usually requires labor-intensive manual work, and the automatic extraction, which can be applied universally for diverse curved road types, presents a challenge. Given this context, this study proposes a method to automatically extract road boundaries and linear road markings by applying an oriented bounding box (OBB) collision-detection algorithm. The OBBs are generated from a reference line using the point cloud data’s position and intensity values. By applying the OBB collision-detection algorithm, road boundaries and linear road markings can be extracted efficiently and accurately in straight and curved roads by adjusting search length and width to detect OBB collision. This study assesses horizontal position accuracy using automatically extracted and manually digitized data to verify this method. The resulting RMSE for extracted road boundaries is +4.8 cm and +5.3 cm for linear road markings, indicating that high-accuracy road boundary and road marking extraction was possible. Therefore, our results demonstrate that the automatic extraction adjusting OBB detection parameters and integrating the OBB collision-detection algorithm enables efficient and precise extraction of road boundaries and linear road markings in various curving types of roads. Finally, this enhances its practicality and simplifies the implementation of the extraction process.
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ISSN:2072-4292
2072-4292
DOI:10.3390/rs15194656