论文标题
使用3D LIDAR在高速公路隧道中基于隧道设施的车辆定位
Tunnel Facility-based Vehicle Localization in Highway Tunnel using 3D LIDAR
论文作者
论文摘要
在高速公路隧道中的车辆定位是自动驾驶汽车导航的具有挑战性的问题。由于无法在高速公路隧道内接收来自卫星的GPS信号，因此必须进行地图辅助定位。但是，隧道周围的环境主要由椭圆壁组成。因此，与户外的情况不同，匹配地图匹配的独特功能点很少。结果，在现有地图辅助本地化的隧道中进行车辆导航非常困难。在本文中，我们建议使用3D激光雷达在高速公路隧道中基于隧道设施的精确车辆定位。对于在高速公路隧道中的车辆定位，使用隧道设施中心点的点地标图和使用途径分布的概率分布图。如果只能提取对象的代表点，则可以进行基于点标记的本地化。因此，这是用于特征点很少的高速公路隧道的合适定位方法。使用3D激光雷达提取隧道设施点。位置估计是使用基于EKF的导航过滤器进行的。通过使用实际的高速公路驾驶数据实验来验证所提出的本地化算法。实验结果验证了基于隧道设施的车辆定位是否可以实时产生精确的结果。
Vehicle localization in highway tunnels is a challenging issue for autonomous vehicle navigation. Since GPS signals from satellites cannot be received inside a highway tunnel, map-aided localization is essential. However, the environment around the tunnel is composed mostly of an elliptical wall. Thereby, the unique feature points for map matching are few unlike the case outdoors. As a result, it is a very difficult condition to perform vehicle navigation in the tunnel with existing map-aided localization. In this paper, we propose tunnel facility-based precise vehicle localization in highway tunnels using 3D LIDAR. For vehicle localization in a highway tunnel, a point landmark map that stores the center points of tunnel facilities and a probability distribution map that stores the probability distributions of the lane markings are used. Point landmark-based localization is possible regardless of the number of feature points, if only representative points of an object can be extracted. Therefore, it is a suitable localization method for highway tunnels where the feature points are few. The tunnel facility points were extracted using 3D LIDAR. Position estimation is conducted using an EKF-based navigation filter. The proposed localization algorithm is verified through experiments using actual highway driving data. The experimental results verify that the tunnel facility-based vehicle localization yields precise results in real time.
