Lane boundary and curb estimation with lateral uncertainties

— 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. It is independent of the direction of travel of the vehicle, and is also able to incorporate sensor uncertainty associated with individual observations. We analyze the benefits and drawbacks of this approach, and show result...

• Type: Conference
• Year: 2009
• Where: IROS
• Authors: Albert S. Huang, Seth J. Teller
• Keywords: Curve Estimate, Curve Model, IROS 2009, Lateral Uncertainty, Robotics