Research on Positioning Fusion and Verification Algorithm Based on UKF

被引：0
|
作者：
Li X. [1 ]
Li J. [1 ]
Zhu M. [1 ]
Peng N. [1 ]
Zuo S. [1 ]
机构：
[1] Zhengzhou Yutong Bus Co., Ltd., Zhengzhou
来源：
Qiche Gongcheng/Automotive Engineering | 2021年 / 43卷 / 06期
关键词：
Active collision avoidance control; Autonomous driving; Positioning prediction; Positioning verification; Track calculation;
D O I：
10.19562/j.chinasae.qcgc.2021.06.005
中图分类号：
学科分类号：
摘要：
For the problem that the positioning accuracy of the sensor is greatly affected by the environment and it has great impact on the driving safety of autonomous vehicles, a positioning fusion and verification algorithm is proposed. The short-term short-range track calculation model is established for positioning prediction. And the UKF (Unscented Kalman Filter) is used to realize the nonlinear fusion between the predicted positioning result and the actual positioning result so as to improve the positioning accuracy. Whether the actual positioning has shifted can be judged by the positioning verification algorithm. And an active risk avoidance algorithm is studied to enable the vehicle to maintain the trajectory before positioning failure and continue to run until it stops, so as to improve the driving safety of the vehicle. Simulation and experimental results show that the algorithm can not only improve the positioning accuracy, but also effectively judge whether the positioning has offset, and ensure the vehicle to continue to run safely according to the saved reference trajectory after the positioning failure occurs at the same time. © 2021, Society of Automotive Engineers of China. All right reserved.
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页码：825 / 832
页数：7
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