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Carnegie Mellon Robotics Institute

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Abstract

Highway driving can be more safe and reliable when maps contain lane-level detailed cartographic information. Such maps are a resource for driving-assistance systems, enabling them to provide human drivers with precise lane-by-lane advice. This paper proposes new aerial image analysis algorithms that, from highway ortho-images, produce lane-level detailed maps. We analyze screenshots of road vectors to obtain the relevant spatial and photometric patterns of road image-regions. We then refine the obtained patterns to generate hypotheses about the true road-lanes. A road-lane hypothesis, since it explains only a part of the true road-lane, is then linked to other hypotheses to completely delineate boundaries of the true road-lanes. Finally, some of the refined image cues about the underlying road network are used to guide a linking process of road-lane hypotheses. We tested the accuracy and robustness of our algorithms with high-resolution, inter-city highway ortho-images. Experimental results show promise in producing lane-level detailed highway maps from ortho-image analysis – 89% of the true road-lane boundary pixels were successfully detected and 337 out of 417 true road-lanes were correctly recovered.

Keywords

Ortho-Image Analysis, Cartographic Information Extraction, Computer Vision, Machine Learning,

Notes

Sponsor: GM-CMU AD CRL

Associated Center(s) / Consortia: Field Robotics Center

Text Reference

Young-Woo Seo, Christopher Urmson, and David Wettergreen, "Ortho-Image Analysis for Producing Lane-Level Highway Maps ," tech. report CMU-RI-TR-12-26, Robotics Institute, Carnegie Mellon University, September, 2012

BibTeX Reference

@techreport{Seo_2012_7278,
   author = "Young-Woo Seo and Christopher Urmson and David Wettergreen",
   title = "Ortho-Image Analysis for Producing Lane-Level Highway Maps ",
   booktitle = "",
   institution = "Robotics Institute",
   month = "September",
   year = "2012",
   number= "CMU-RI-TR-12-26",
   address= "Pittsburgh, PA",
}

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