A Novel Rollover Warning Approach for Commercial Vehicles Using Unscented Kalman Filter

Junjian Hou, Haizhu Lei, Zhijun Fu, Peixin Yuan, Yuming Yin, Heyang Feng, Zihao Li, Mingxu Zhang, Minghui Cui, Yuqing Xu and Xianjian Jin

Mathematical Problems in Engineering, 2022, vol. 2022, 1-13

Abstract: Roll responses of the semitrailer and the tractor provide higher lead time and characterise the roll instability of the commercial vehicles subjected to directional manoeuvres at highway speeds. This paper proposes a novel rollover index based on the synthesized roll angles of the tractor and trailer. Owing to the poor measurability, the unscented Kalman filter (UKF) algorithm is used to estimate the roll angle of the track and trailer, respectively. Meanwhile, different weight coefficients are considered in the rollover index to eliminate the influence of mutual coupling between the tractor and the trailer and improve the accuracy of the warning. For the practical implementation of the algorithm, a two-stage rollover warning method triggered by the video and audio is finally proposed to reduce the possibilities of false warnings. Co-simulation is presented to prove the validity of the proposed rollover warning approach.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:7503715

DOI: 10.1155/2022/7503715

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