Gottschalg Grischa, Leinen Stefan
Chair of Physical and Satellite Geodesy, Institute of Geodesy, Technical University of Darmstadt, Franziska-Braun-Straße 7, 64287 Darmstadt, Germany.
Sensors (Basel). 2021 Feb 19;21(4):1458. doi: 10.3390/s21041458.
High-integrity information about the vehicle's dynamic state, including position and heading (yaw angle), is required in order to implement automated driving functions. In this work, a comparison of three integrity algorithms for the vehicle dynamic state estimation of a research vehicle for an application in automated driving is presented. Requirements for this application are derived from the literature. All implemented integrity algorithms output a protection level for the position and heading solution. In the comparison, four measurement data sets obtained for the vehicle dynamic state estimation, which is based on a Global Navigation Satellite Signal receiver, inertial measurement units and odometry information (wheel speeds and steering angles), are used. The data sets represent four driving scenarios with different environmental conditions, especially regarding the satellite signal reception. All in all, the Kalman Integrated Protection Level demonstrated the best performance out of the three implemented integrity algorithms. Its protection level bounds the position error within the specified integrity risk in all four chosen scenarios. For the heading error, this also holds true, with a slight exception in the very challenging urban scenario.
为了实现自动驾驶功能，需要有关车辆动态状态的高完整性信息，包括位置和航向（偏航角）。在这项工作中，对用于自动驾驶应用的研究车辆的车辆动态状态估计的三种完整性算法进行了比较。该应用的要求源自文献。所有实现的完整性算法都会输出位置和航向解的保护级别。在比较中，使用了基于全球导航卫星信号接收器、惯性测量单元和里程计信息（车轮速度和转向角）获得的四个用于车辆动态状态估计的测量数据集。这些数据集代表了四种具有不同环境条件的驾驶场景，特别是关于卫星信号接收情况。总体而言，卡尔曼综合保护级别在三种实现的完整性算法中表现最佳。在所有四个选定场景中，其保护级别将位置误差限制在指定的完整性风险范围内。对于航向误差，情况也是如此，在极具挑战性的城市场景中略有例外。
