视觉与单路侧单元辅助的车辆定位方法  被引量:4

Vision and Single RSU Assisted Vehicle Positioning Method

在线阅读下载全文

作  者:盛树轩 荆崇波[1] 蒋朝阳 Sheng Shuxuan;Jing Chongbo;Jiang Chaoyang(School of Mechanical Engineering,Beijing Institute of Technology,Beijing 100081)

机构地区:[1]北京理工大学机械与车辆学院,北京100081

出  处:《汽车工程》2022年第7期1009-1017,1026,共10页Automotive Engineering

基  金:国家自然科学基金(52002026)资助。

摘  要:为准确获取在城市峡谷等GNSS定位受限环境下的车辆位置,提出了一种视觉与单路侧单元(RSU)辅助的车辆定位方法。利用相机观测车辆到车道线的横向距离,利用单RSU与车辆进行测距与通信,通过误差状态卡尔曼滤波算法对GNSS、IMU、RSU和相机观测信息进行融合,实现对车辆位姿的准确估计。针对上述方法进行了实车测试,分析了单RSU测距信息和横向距离观测对定位结果的影响。结果表明:单RSU测距信息可有效降低纵向定位误差,但对横向定位误差的修正作用随着远离RSU逐渐降低,横向距离观测可有效弥补这一不足。二者优势互补,水平定位均方根误差小于10 cm,验证了所提出方法的有效性。To accurately acquire the vehicle location in the GNSS restricted environment such as urban canyon,a visual vehicle locating method is proposed with single road side unit(RSU)assisted.A camera is used to measure the lateral distance from the vehicle to the lane lines,and the RSU and vehicle are interacted for the distance measurement and communications.The information of GNSS,IMU,RSU and camera observed are fused through the error state Kalman filtering algorithm to fulfill the accurate estimation of the location and orientation of vehicle.Real vehicle tests are conducted to analyze the effects of the ranging information of single RSU and the lateral distance measured on positioning results.The results show that the ranging information of single RSU can effectively reduce the longitudinal positioning error,but its correction effects of lateral positioning error gradually reduce with the increase of the distance from RSU.This defect can be effectively remedied by lateral distance measurement,and complementing both advantages results in a root mean square error in horizontal positioning less than 10 cm,verifying the effectiveness of the method proposed.

关 键 词:车辆定位 视觉测距 路侧单元 误差状态卡尔曼滤波 

分 类 号:U495[交通运输工程—交通运输规划与管理]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象