AUTOMATED MODELLING OF ROAD FOR HIGH-DEFINITION MAPS WITH OPENDRIVE FORMAT UTILIZING MOBILE MAPPING MEASUREMENTS

High-definition maps (HD Maps) becomes a trend supporting autonomous vehicles (AVs) which provides accurate auxiliary information about geometries of road, such as center lines of lanes, geometries of roads, traffic signs, etc. It is not restricted by the severe environment, lack of Global Navigatio...

Full description

Saved in:
Bibliographic Details
Main Authors: Pai, H.-Y., Zeng, J.-C., Tsai, M.-L., Cheng, K.-W.
Format: Conference Proceeding
Language:English
Subjects:
Algorithms
Automation
Geographic information systems
Geographical information systems
Global navigation satellite system
High definition
Human resources
Information systems
Modelling
Navigation
Navigational satellites
Operating costs
Production costs
Remote sensing
Roads
Roads & highways
Traffic signs
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:High-definition maps (HD Maps) becomes a trend supporting autonomous vehicles (AVs) which provides accurate auxiliary information about geometries of road, such as center lines of lanes, geometries of roads, traffic signs, etc. It is not restricted by the severe environment, lack of Global Navigation Satellite System (GNSS) signal, or torrential rain, for Avs; furthermore, the standard of HD Maps is defined as tens of centimeters positioning level. However, the production cost of HD Maps is enormous involving human resources and time. The general way of producing HD Maps is to vectorize the roads from point clouds to shapefiles and import them into Geographic Information System (GIS) software to generate HD Maps. In order to simplify this complicated process, this article purposes an algorithm to automated generate high-definition maps from road marks’ data which is extracted from point clouds. The methodology in this article is mainly dived into three steps, extraction of road marks, classify lane lines, and modelling OpenDRIVE files. The achieved 2D and 3D accuracies of proposed algorithm in first fields are about 0.069 m in 2D and 0.107 m, respectively.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLIII-B1-2022-263-2022