Advancements in LiDAR technology have led to more cost-effective production while simultaneously improving precision and resolution. As a result, LiDAR has become integral to vehicle localization, achieving centimeter-level accuracy through techniques like Normal Distributions Transform (NDT) and other advanced 3D registration algorithms. Nonetheless, these approaches are reliant on high-definition 3D point cloud maps, the creation of which involves significant expenditure. When such maps are unavailable or lack sufficient features for 3D registration algorithms, localization accuracy diminishes, posing a risk to road safety. To address this, we proposed to use LiDAR-equipped roadside unit and Vehicle-to-Infrastructure (V2I) communication to accurately estimate the connected autonomous vehicle's position and help the vehicle when its self-localization is not accurate enough. Our simulation results indicate that this method outperforms traditional NDT scan matching-based approaches in terms of localization accuracy.

翻译：随着LiDAR技术的进步，其生产成本日益降低，同时精度与分辨率不断提升。因此，LiDAR已成为车辆定位的关键组成部分，通过正态分布变换（NDT）等先进的三维配准算法可实现厘米级定位精度。然而，这些方法依赖于高精度的三维点云地图，而此类地图的构建需要高昂的成本。当此类地图不可用或缺乏足够特征供三维配准算法匹配时，定位精度会下降，从而对道路安全构成威胁。为解决这一问题，我们提出利用配备LiDAR的路侧单元与车路协同（V2I）通信技术，在车辆自主定位精度不足时，精确估计网联自动驾驶车辆的位置并为其提供辅助。仿真结果表明，该方法在定位精度方面优于传统的基于NDT扫描匹配的定位方法。