摘要
为了获取汽车行驶过程中微观、详细的运行轨迹,利用高采样率的二维加速度数据,根据Ackermann运动模型,提出重构汽车运动二维轨迹的算法。通过设计高采样率的汽车惯性数据采集系统和真车上路试验,同步采集了汽车GPS、加速度数据等,实验数据验证了本文的汽车轨迹重构算法有效、可靠。该算法可以解决汽车行驶过程中单纯依靠GPS记录汽车轨迹采集率过低、数据漂移等问题,可在汽车轨迹重现分析和危险行驶预警等领域有独特的应用价值。
In order to obtain the movement track of vehicles in microscopic detail,this paper proposes an algorithm for reconstructing the two-dimensional track of vehicles based on the Ackermann motion model by using the two-dimensional acceleration data with high sampling rate.The GPS and acceleration data were collected synchronously through designing of automobile inertial data acquisition systema with high sampling rate in real road test.The experimental data verify that the reconstruction algorithm of vehicles'track in this paper is effective and reliable.The proposed algorithm can solve the problems such as low acquisition rate and data drift of vehicle trajectory recorded only by GPS during driving.It has application value in the fields of analysis of vehicle track reconstruction and dangerous driving warning.
作者
伍洪俊
张辉
Wu Hongjun;Zhang Hui(Guangzhou Railway Polytechnic,Guangzhou 510430,Guangdong,China;Intelligent Transportation Research Center,Sun Yat-Sen University,Guangzhou 510275,Guangdong,China)
出处
《计算机应用与软件》
北大核心
2026年第1期296-301,共6页
Computer Applications and Software
基金
中国高校产学研创新基金——新一代信息技术创新项目(2023IT031)
广东省普通高校特色创新类项目(2021KTSCX270)
广州市高等教育教学质量与教学改革工程项目(2022JSJXCXTD012)。
