基于多普勒原理的自动驾驶态势感知方法

Y. Hu
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引用次数: 0

摘要

态势感知是自动驾驶的关键环节,而自动驾驶现在是基于多种技术的结合。相机、激光雷达、雷达和超声波传感器是这项任务最常用的方式。其中,激光雷达在200米以内的精度最高,成为环境感知的主要输入模块。但激光雷达存在体积大、成本高、能耗大、精度受天气环境影响等缺点。为了克服这一挑战,本文提出了一种基于多普勒原理的自动驾驶态势感知方法,作为对车载雷达的辅助和补充。具体而言,使用5个24 GHz速度传感器测量车辆在水平路面上相对运动的多普勒速度,通过联合观测可计算出车辆的三维位置坐标和水平面的二维速度。另一个24 GHz速度传感器有助于区分每个目标,判断车辆模型,并预测附近车辆可能的运动。实验结果表明,根据本文设计的原型系统测量误差符合实验预期,证明了多普勒雷达用于态势感知的可行性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Doppler Principle Based Situational Awareness Method for Autonomous Driving
Situational awareness is a critical connection in autonomous driving, which is now based on a combination of technologies. Camera, lidar, radar and ultrasonic sensors are the most commonly used modality for this task. Among them, lidar has the highest accuracy within 200 m and becomes the main input module for environmental perception. Nevertheless, lidar has defects of large size, high cost, high energy consumption, and accuracy is affected by the weather environment. To overcome the challenge, this paper proposes a situational awareness method for autonomous driving based on the Doppler principle, which is a help and supplement to the onboard radar. Specifically, five 24 GHz speed sensors are used to measure the Doppler speed of the vehicle in relative motion on the horizontal road surface, and the three-dimensional position coordinates of the vehicle and the two-dimensional speed of the horizontal plane can be calculated by a joint observation. Another 24 GHz speed sensor assists in distinguishing each target, judging the vehicle model, and predicting the possible movement of nearby vehicles. Experiment results illustrate that the measurement errors of the prototype system designed according to this paper are in line with experiment expectations, which proves the feasibility of Doppler radar for situational awareness.
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