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GPS/DR Error Estimation for Autonomous Vehicle Localization

机译:用于自动车辆定位的GPS / DR误差估计

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Autonomous vehicles require highly reliable navigation capabilities. For example, a lane-following method cannot be applied in an intersection without lanes, and since typical lane detection is performed using a straight-line model, errors can occur when the lateral distance is estimated in curved sections due to a model mismatch. Therefore, this paper proposes a localization method that uses GPS/DR error estimation based on a lane detection method with curved lane models, stop line detection, and curve matching in order to improve the performance during waypoint following procedures. The advantage of using the proposed method is that position information can be provided for autonomous driving through intersections, in sections with sharp curves, and in curved sections following a straight section. The proposed method was applied in autonomous vehicles at an experimental site to evaluate its performance, and the results indicate that the positioning achieved accuracy at the sub-meter level.
机译:自动驾驶汽车需要高度可靠的导航功能。例如,不能在没有车道的交叉路口中应用车道跟踪方法,并且由于典型的车道检测是使用直线模型进行的,因此由于模型不匹配而在弯曲部分中估计横向距离时会发生误差。因此,本文提出了一种基于GPS / DR误差估计的定位方法,该方法基于具有弯曲车道模型,停车线检测和曲线匹配的车道检测方法,以提高航路点跟随程序的性能。使用所提出的方法的优点在于,可以提供位置信息以通过交叉点,在具有尖锐曲线的部分以及在直线部分之后的弯曲部分中进行自主驾驶。该方法在实验现场的自动驾驶汽车上进行了性能评估,结果表明该定位方法在亚米级达到了精度。

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