COMPLEX ROAD INTERSECTION MODELLING BASED ON LOW-FREQUENCY GPS TRACK DATA
It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing images. At present, a large number of GPS...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2017-09-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W7/23/2017/isprs-archives-XLII-2-W7-23-2017.pdf |
| Summary: | It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are
produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing
images. At present, a large number of GPS trajectory data collected by floating vehicles makes it a reality to extract high-detailed and
up-to-date road network information. Road intersections are often accident-prone areas and very critical to route planning and the
connectivity of road networks is mainly determined by the topological geometry of road intersections. <b>A few studies paid attention
on detecting complex road intersections and mining the attached traffic information</b> (e.g., connectivity, topology and turning
restriction) from massive GPS traces. To the authors’ knowledge, recent studies mainly used high frequency (1 s sampling rate)
trajectory data to detect the crossroads regions or extract rough intersection models. <b>It is still difficult to make use of low frequency
(20–100 s) and easily available trajectory data to modelling complex road intersections geometrically and semantically</b>. The
paper thus attempts to construct precise models for complex road intersection by using low frequency GPS traces. We propose to
firstly extract the complex road intersections by a LCSS-based (Longest Common Subsequence) trajectory clustering method, then
delineate the geometry shapes of complex road intersections by a K-segment principle curve algorithm, and finally infer the traffic
constraint rules inside the complex intersections. |
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| ISSN: | 1682-1750 2194-9034 |