見通し外へ：視覚とV2X通信を活用した協調自己位置推定
Beyond Line-of-Sight: Cooperative Localization Using Vision and V2X Communication
車載カメラとV2X通信を用い、遮蔽物の多い交差点でも車両が自車位置・姿勢を推定できる分散型協調測位アルゴリズムを提案し、実機実験と大規模シミュレーションで検証した。
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著者: Annika Wong, Zhiqi Tang, Frank J. Jiang, Karl H. Johansson, Jonas Mårtensson
分類: eess.SY, cs.RO, cs.SY
原文アブストラクト
Accurate and robust localization is critical for the safe operation of Connected and Automated Vehicles (CAVs), especially in complex urban environments where Global Navigation Satellite System (GNSS) signals are unreliable. This paper presents a novel vision-based cooperative localization algorithm that leverages onboard cameras and Vehicle-to-Everything (V2X) communication to enable CAVs to estimate their poses, even in occlusion-heavy scenarios such as busy intersections. In particular, we propose a novel decentralized observer for a group of connected agents that includes landmark agents (static or moving) in the environment with known positions and vehicle agents that need to estimate their poses (both positions and orientations). Assuming that (i) there are at least three landmark agents in the environment, (ii) each vehicle agent can measure its own angular and translational velocities as well as relative bearings to at least three neighboring landmarks or vehicles, and (iii) neighboring vehicles can communicate their pose estimates, each vehicle can estimate its own pose using the proposed decentralized observer. We prove that the origin of the estimation error is locally exponentially stable under the proposed observer, provided that the minimal observability conditions are satisfied. Moreover, we evaluate the proposed approach through experiments with real 1/10th-scale connected vehicles and large-scale simulations, demonstrating its scalability and validating the theoretical guarantees in practical scenarios.
