Braking intention recognition algorithm based on electronic braking system in commercial vehicles. (29th July 2019)

• Record Type: Journal Article
• Authors: Zheng, Hongyu; Ma, Shenao; Fang, Lingxiao; Zhao, Weiqiang; Zhu, Tianjun
• Is Part Of: International journal of heavy vehicle systems. Volume 26:Number 3/4(2019)
• Page Start: 268
• Page End: 290
• Publication Date: 2019-07-29
• Subjects: commercial vehicle -- braking intention identification -- neural network -- fuzzy logic -- electronic brake system -- emergency braking -- active safety -- braking performance -- road transportation -- brake-by-wire -- hardware-in-the-loop test bench; Motor vehicles -- Design and construction -- Periodicals; Commercial vehicles -- Design and construction -- Periodicals; Motor vehicles -- Design and construction; Periodicals; 629.224
• Languages: English
• ISSNs: 1744-232X

Abstract

The aim of this research is to investigate the braking intention identification method adaptive to the electronic braking system (EBS) in commercial vehicles. Based on the neural network, a braking intention identification model is established which takes both emergency braking and general braking into account. Then, considering the complex transportation environment, a multi-condition identification model with respect to four typical braking conditions is developed using the fuzzy logic. The experimental results of the two models demonstrate that the proposed strategy can make good use of driver braking intention. The proposed method provides theoretical guidelines on driver behaviour adaptation on the longitudinal active safety system, which promotes vehicle safety and braking performance.