動的制御点ブレンディングによる自動運転車の経路追従：実験的研究
Path Tracking with Dynamic Control Point Blending for Autonomous Vehicles: An Experimental Study
前輪と後輪の制御点を動的に補間し、Stanley法と曲率ベースの幾何学制御を融合することで、低速・後退を含む経路追従の精度と操舵の滑らかさを向上させる手法を提案し、実車実験で検証した。
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著者: Alexandre Lombard, Florent Perronnet, Nicolas Gaud, Abdeljalil Abbas-Turki
分類: cs.RO, cs.SY, eess.SY
原文アブストラクト
This paper presents an experimental study of a path-tracking framework for autonomous vehicles in which the lateral control command is applied to a dynamic control point along the wheelbase. Instead of enforcing a fixed reference at either the front or rear axle, the proposed method continuously interpolates between both, enabling smooth adaptation across driving contexts, including low-speed maneuvers and reverse motion. The lateral steering command is obtained by barycentric blending of two complementary controllers: a front-axle Stanley formulation and a rear-axle curvature-based geometric controller, yielding continuous transitions in steering behavior and improved tracking stability. In addition, we introduce a curvature-aware longitudinal control strategy based on virtual track borders and ray-tracing, which converts upcoming geometric constraints into a virtual obstacle distance and regulates speed accordingly. The complete approach is implemented in a unified control stack and validated in simulation and on a real autonomous vehicle equipped with GPS-RTK, radar, odometry, and IMU. The results in closed-loop tracking and backward maneuvers show improved trajectory accuracy, smoother steering profiles, and increased adaptability compared to fixed control-point baselines.
