Braking Intention Recognition Algorithm Based on Electronic Braking System in Commercial Vehicles

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 behavior adaptation on the longitudinal active safety system, which promotes vehicle safety and braking performance.

• Record URL:
  • https://doi.org/10.1504/IJHVS.2019.101464
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/1744232X
• Supplemental Notes:
  • Copyright © 2018 Inderscience Enterprises Ltd.
• Authors:
  • Zheng, Hongyu
  • Ma, Shenao
  • Fang, Lingxiao
  • Zhao, Weiqiang
  • Zhu, Tianjun
• Publication Date: 2019

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: pp 268-290
• Serial:
  • International Journal of Heavy Vehicle Systems
  • Volume: 26
  • Issue Number: 3-4
  • Publisher: Inderscience Enterprises Limited
  • ISSN: 1744-232X
  • EISSN: 1741-5152
  • Serial URL: http://www.inderscience.com/jhome.php?jcode=IJHVS

Subject/Index Terms

• TRT Terms: Active safety systems; Automatic braking; Commercial vehicles; Driver vehicle interfaces; Dynamic braking; Mathematical models; Vehicle safety
• Subject Areas: Design; Motor Carriers; Safety and Human Factors;

Filing Info

• Accession Number: 01717053
• Record Type: Publication
• Files: TRIS
• Created Date: Sep 18 2019 9:17AM