Sadli Rahmad, Afkir Mohamed, Hadid Abdenour, Rivenq Atika, Taleb-Ahmed Abdelmalik
Institut d'Électronique de Microélectronique et de Nanotechnologie (IEMN), UMR 8520, Université Polytechnique Hauts de France, University of Lille, CNRS, Centrale Lille, F-59313 Valenciennes, France.
Transalley Technopole, 59300 Famars, France.
Sensors (Basel). 2022 Mar 22;22(7):2434. doi: 10.3390/s22072434.
For self-driving systems or autonomous vehicles (AVs), accurate lane-level localization is a important for performing complex driving maneuvers. Classical GNSS-based methods are usually not accurate enough to have lane-level localization to support the AV's maneuvers. LiDAR-based localization can provide accurate localization. However, the price of LiDARs is still one of the big issues preventing this kind of solution from becoming wide-spread commodity. Therefore, in this work, we propose a low-cost solution for lane-level localization using a vision-based system and a low-cost GPS to achieve high precision lane-level localization. Experiments in real-world and real-time demonstrate that the proposed method achieves good lane-level localization accuracy, outperforming solutions based on only GPS.
对于自动驾驶系统或自动驾驶车辆（AV）而言，精确的车道级定位对于执行复杂的驾驶操作至关重要。基于经典全球导航卫星系统（GNSS）的方法通常不够精确，无法实现支持自动驾驶车辆操作所需的车道级定位。基于激光雷达的定位可以提供精确的定位。然而，激光雷达的价格仍然是阻碍这种解决方案广泛应用成为商品的重大问题之一。因此，在这项工作中，我们提出了一种低成本的解决方案，利用基于视觉的系统和低成本全球定位系统（GPS）来实现高精度的车道级定位。在真实场景和实时环境中的实验表明，所提出的方法实现了良好的车道级定位精度，优于仅基于GPS的解决方案。
