Title: Braking intention recognition algorithm based on electronic braking system in commercial vehicles

Authors: Hongyu Zheng; Shenao Ma; Lingxiao Fang; Weiqiang Zhao; Tianjun Zhu

Addresses: State Key Laboratory of Automotive Simulation and Control, Jilin University, No. 5988, Renmin Street, Changchun, 130022, China ' State Key Laboratory of Automotive Simulation and Control, Jilin University, No. 5988, Renmin Street, Changchun, 130022, China ' State Key Laboratory of Automotive Simulation and Control, Jilin University, No. 5988, Renmin Street, Changchun, 130022, China ' State Key Laboratory of Automotive Simulation and Control, Jilin University, No. 5988, Renmin Street, Changchun, 130022, China ' State Key Laboratory of Automotive Simulation and Control, Jilin University, No. 5988, Renmin Street, Changchun, 130022, China

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.

Keywords: 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.

DOI: 10.1504/IJHVS.2019.101464

International Journal of Heavy Vehicle Systems, 2019 Vol.26 No.3/4, pp.268 - 290

Received: 30 Dec 2016
Accepted: 19 May 2017

Published online: 11 Aug 2019 *

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