On-line Measurement and Prediction Technology for Vehicle Motion State

LIU Jun, DONG Jing-jing, SHI Xiao-peng, HE Guo-guo

China Journal of Highway and Transport ›› 2011, Vol. 24 ›› Issue (4) : 114-121.

PDF Full Text Download(829 KB)
PDF Full Text Download(829 KB)
China Journal of Highway and Transport ›› 2011, Vol. 24 ›› Issue (4) : 114-121.
Original Article

On-line Measurement and Prediction Technology for Vehicle Motion State

  • LIU Jun, DONG Jing-jing, SHI Xiao-peng, HE Guo-guo
Author information +
History +

Abstract

In order to predict vehicle motion state and potential danger effectively, on-line measurement and prediction technology for vehicle motion state was developed. Micro inertial measurement unit (MIMU) was designed independently in order to realize on-line measurement of vehicle motion state parameters. Vehicle attitude solution and its velocity integration algorithm were presented and Kalman filter was designed. Through fusion of sensor signals, optimal estimation values of motion state parameters were achieved. Auto-regressive modeling method was built. On-line measurement and prediction software of vehicle motion state was developed. The road test was carried out based on vehicle loading test platform. Results show that on-line measurement and prediction technology for vehicle motion state which can provide an theoretical reference and technical way for future development of active safety warning systems of vehicle has good predicted effect.

Key words

automotive engineering / vehicle motion state parameter / road test / on-line measurement and prediction / micro inertial measurement unit / auto-regressive model

Cite this article

Download Citations
LIU Jun, DONG Jing-jing, SHI Xiao-peng, HE Guo-guo. On-line Measurement and Prediction Technology for Vehicle Motion State[J]. China Journal of Highway and Transport, 2011, 24(4): 114-121

References

[1] 薄大明,王元海,王军利,等.公安交通安全管理现状分析与对策研究[J].中国人民公安大学学报:自然科学版,2008,14(1):82-85.
BO Da-ming,WANG Yuan-hai,WANG Jun-li,et al.Analysis and Countermeasures Research of Public Security Traffic Current Management Situation[J].Journal of Chinese People's Public Security Univer-sity:Science and Technology,2008,14(1):82-85.
[2]National Transportation Safety Board.Vehicle-and Infrastructure-based Technology for the Prevention of Rear-end Collisions[R].Washington DC:National Transportation Board,2001.
[3]KOUREPENIS A,BORENSTEIN J,CONNELLY J,et al.Performance of MEMS Inertial Sensors[C]//IEEE Aerospace & Electronic Systems Society.Pos-ition,Location,and Navigation Symposium (Plans)Proceedings.New York:IEEE,1998:1-8.
[4]VERMA R,GOGOI B P,MLADENOVIC D.MEMS Pressure and Acceleration Sensors for Automotive Applications[J].SAE Paper 2003-01-0204.
[5]宋丽君.基于MEMS器件的航向姿态测量系统的研究[D].西安:西北工业大学,2007.
SONG Li-jun.Research of Inertial Systems of Heading and Attitude of MEMS Machine Piece[D].Xi'an:Northwestern Polytechnical University,2007.
[6]ROBINETT R D,PARKER G G.Spacecraft Euler Parameter Tracking of Large-angle Maneuvers via Sliding Mode Control[J].Journal of Guidance,Control and Dynamics,1996,19(3):702-703.
[7]BILIMORIA K D,WIE B.Time-optimal Three-axis Reorientation of a Rigid Spacecraft[J].Journal of Guidance,Control, and Dynamics,1993,16(3):446-452.
[8]刘 忠,梁晓庚,贾晓洪,等.基于四元数的导弹反步控制及全方位算法应用[J].系统仿真学报,2006,18(10):2734-2737.
LIU Zhong,LIANG Xiao-geng,JIA Xiao-hong,et al.Omnidirectional Quaternion Algorithm and Missile Attitude Control Based on Backstepping Method in Quaternion[J].Journal of System Simulation,2006,18(10):2734-2737.
[9]张再勇.车载GPS/MIMU/DM组合导航系统研究[D].重庆:重庆大学,2005.
ZHANG Zai-yong.Research on GPS/MIMU/DM Integrated System to Vehicle Navigation[D].Chongqing:Chongqing University,2005.
[10]刘付强.基于MEMS器件的捷联姿态测量系统技术研究[D].哈尔滨:哈尔滨工程大学,2007.
LIU Fu-qiang.Research on the Technology of Strapdown Attitude Measurement System Based on MEMS Sensors[D].Harbin:Harbin Engineering University,2007.
[11]付梦印,邓志红,张继伟.Kalman滤波理论及其在导航系统中的应用[M].北京:科学出版社,2003.
FU Meng-yin,DENG Zhi-hong,ZHANG Ji-wei.Kalman Filtering Theory and Application in the Navigation System[M].Beijing:Science Press,2003.
[12]李 晗,武奇生,罗向龙.基于改进几何活动轮廓模型和Kalman滤波的目标跟踪方法[J].长安大学学报:自然科学版,2011,31(3):90-94.
LI Han,WU Qi-sheng,LUO Xiang-long.Motion Object Tracking Algorithm Using an Improved Geometric Active Contour Model and Kalman Filtering[J].Journal of Chang'an University:Natural Science Edition,2011,31(3):90-94.
[13]聂佩林,余 志,何兆成.基于约束卡尔曼滤波的短时交通流量组合预测模型[J].交通运输工程学报,2008,8(5):86-90.
NIE Pei-lin,YU Zhi,HE Zhao-cheng.Constrained Kalman Filter Combined Predictor for Short-term Traffic Flow[J].Journal of Traffic and Transportation Engineering,2008,8(5):86-90.
[14]于德新,杨兆升,刘雪杰.基于卡尔曼滤波的GPS/DR导航信息融合方法[J].交通运输工程学报,2006,6(2):65-69.
YU De-xin,YANG Zhao-sheng,LIU Xue-jie.GPS/DR Navigation Data Fusion Method Based on Kalman Filter[J].Journal of Traffic and Transportation En-gineering,2006,6(2):65-69.
[15]杨叔子,吴 雅,轩建平,等.时间序列分析的工程应用[M].2版.武汉:华中科技大学出版社,2007.
YANG Shu-zi,WU Ya,XUAN Jian-ping,et al.Time Series Analysis in Engineering Application[M].2nd ed.Wuhan:Huazhong University of Science and Technology Press,2007.
[16]邓自立,王 欣,高 媛.建模与估计[M].北京:科学出版社,2007.
DENG Zi-li,WANG Xin, GAO Yuan.Modeling and Estimation[M].Beijing:Science Press,2007.
PDF Full Text Download(829 KB)

1546

Accesses

0

Citation

Detail

Sections
Recommended

/