Vehicle Position Estimation using Tire Model
Vehicle Position Estimation using Tire Model
复制标题
使用轮胎模型估计车辆位置
DOI：
10.1007/978-3-662-46578-3_90
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Byeong
中科院分区：
文献类型：
--
作者：
Jaewoo Yoon;Byeong
GPS在位置估计技术中得到了广泛的应用，而位置估计技术对自动驾驶车辆的稳定行驶至关重要。然而，GPS存在着高速车辆突然行为时定位精度降低以及隧道和市中心信号中断等限制。为了克服这一问题，需要一种结合各种传感器信息和纵向/横向滑动的算法。提出了一种基于Dugoff轮胎模型的三自由度车辆动力学模型，并提出了一种利用扩展卡尔曼滤波对车内各种传感器信息进行融合的算法。通过仿真对所提出的位置估计算法的性能进行了分析和评估。结果表明，即使在运动突变的情况下，该算法的位置估计结果也比GPS方法的位置估计结果更准确。
GPS is being widely used in the location estimation technology, which is essential for stable driving of autonomous vehicle. However, GPS has problems such as reduction in location accuracy during abrupt vehicle behavior at high speed, and limitations such as signal interruption in tunnels and downtown areas. To overcome this problem, an algorithm that combines various sensor information and longitudinal/lateral slip is required. This paper proposes a three-degree of freedom (3-DoF) vehicle dynamics model, in which DugofFs tire model is applied, and an algorithm, which combines various sensor information inside the vehicle by using extended Kalman filter. The performance of proposed location estimation algorithm was analyzed and evaluated through simulations. As a result, it is confirmed that the location estimation result of proposed algorithm is more accurate than that of method using GPS even during abrupt changes in motion.