Augmenting cartographic resources for autonomous driving

Young-Woo Seo, Christopher Urmson, David Wettergreen, and Jin-Woo Lee
Proceedings of ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS-2009), November, 2009, pp. 13-22.


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Abstract
In this paper we present algorithms for automatically generating a road network description from aerial imagery. The road network inforamtion (RNI) produced by our algorithm includes a composite topoloigical and spatial representation of the roads visible in an aerial image. We generate this data for use by autonomous vehicles operating on-road in urban environments. This information is used by the vehicles to both route plan and determine appropriate tactical behaviors. RNI can provide important contextual cues that influence driving behaviors, such as the curvature of the road ahead, the location of traffic signals, or pedestrian dense areas. The value of RNI was demonstrated compellingly in the DARPA Urban Challenge , where the vehicles relied on this information to drive quickly, safely and efficiently. The current best methods for generating RNI are manual, labor intensive and error prone. Automation of this process could thus provide an important capability. As a step toward this goal, we present algorithms that automatically build the skeleton of drivable regions in a parking lot from a single orthoimage. As a first step , in extracting structure, our algorithm detects the parking spots visible in an image. It then combines this information with the detected parking lot boundary and information from other detected road-markings to extract a skeleton of the the drivable regions within the lot.

Keywords
aerial image analysis, roadmap building for autonomous driving, computer vision, machine learning

Notes
Sponsor: GM-CMU Autonomous Driving Collaborative Research Lab
Associated Center(s) / Consortia: Field Robotics Center
Associated Project(s): Enhanced Road Network Data from Overhead Imagery
Number of pages: 10

Text Reference
Young-Woo Seo, Christopher Urmson, David Wettergreen, and Jin-Woo Lee, "Augmenting cartographic resources for autonomous driving," Proceedings of ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS-2009), November, 2009, pp. 13-22.

BibTeX Reference
@inproceedings{Seo_2009_6479,
   author = "Young-Woo Seo and Christopher Urmson and David Wettergreen and Jin-Woo Lee",
   title = "Augmenting cartographic resources for autonomous driving",
   booktitle = "Proceedings of ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (GIS-2009)",
   pages = "13-22",
   publisher = "ACM",
   month = "November",
   year = "2009",
}