LaneMatch: A Practical Real-Time Localization Method Via Lane-Matching

Mengwen He, Ragunathan Raj Rajkumar

Abstract: This letter presents <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LaneMatch,</i> a localization method for use in autonomous vehicles (AVs). It utilizes lane matching to obtain an AV’s lane occupancy and current pose estimation. Matching is performed on a compact low-resolution road map generated from satellite images. Our approach addresses the following challenges for AVs using this map: (1) misalignment between roads on the satellite images and their global coordinates, and (2) incomplete or incorrect lane detection outputs. First, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LaneMatch</i> estimates the offset between the AV’s global pose in the global coordinate system and its local map pose on the map. Secondly, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LaneMatch</i> utilizes a spatio-temporal integration of a particle filter and a factor graph to resolve lane-matching ambiguities. It strategically constrains the dimensionality of variables to obtain real-time performance. We use highway experiments to evaluate the processing time, occupancy accuracy, lateral/longitudinal and position/heading errors. These experiments show that <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">LaneMatch</i> localizes our AV rather precisely on the road map in real-time and can be used for navigation and planning purposes even in GNSS-unfriendly areas.