Lane boundary and curb estimation with lateral uncertainties
Author(s)Huang, Albert S.; Teller, Seth
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This paper describes an algorithm for estimating lane boundaries and curbs from a moving vehicle using noisy observations and a probabilistic model of curvature. The primary contribution of this paper is a curve model we call lateral uncertainty, which describes the uncertainty of a curve estimate along the lateral direction at various points on the curve, and does not attempt to capture uncertainty along the longitudinal direction of the curve. Additionally, our method incorporates expected road curvature information derived from an empirical study of a real road network. Our method is notable in that it accurately captures the geometry of arbitrarily complex lane boundary curves that are not well approximated by straight lines or low-order polynomial curves. Our method operates independently of the direction of travel of the vehicle, and incorporates sensor uncertainty associated with individual observations. We analyze the benefits and drawbacks of the approach, and show results of our algorithm applied to real world data sets.
DepartmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
IEEE/RSJ International Conference on Intelligent Robots and Systems, 2009. IROS 2009.
Institute of Electrical and Electronics Engineers
Huang, A.S., and S. Teller. “Lane boundary and curb estimation with lateral uncertainties.” Intelligent Robots and Systems, 2009. IROS 2009. IEEE/RSJ International Conference on. 2009. 1729-1734. © 2009 IEEE
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INSPEC Accession Number: 11010176