Distracted Driver Behavior Detection Based-on An Improved YOLOX Framework

Yajuan Wei, Zhaoli Guo, Chuan Dai, Minsi Chen, Zhijie Xu, Ying Liu, Jiulun Fan

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

With the surge of the number of cars, road traffic accidents occur frequently because of drivers' distracted attention and abnormal behaviors, which causes huge losses to people's lives and property. To alleviate this issue, an improved deep learning algorithm based on YOLOX framework was proposed in this research to detect driving behavior changes in live. An attention mechanism - Convolutional Block Attention Module (CBAM) - was introduced in multiple scales of feature layers to form the backbone of YOLOX network. A widely used data science competition platform was adopted for distracted behavior model training. The State Farm Distracted Driver Detection Dataset was used for model validation and performance benchmarking. Experimental results have indicated promising performance gain using the devised model over the original YOLOX framework in terms of mAP and inference time.

Original languageEnglish
Title of host publication2022 27th International Conference on Automation and Computing
Subtitle of host publicationSmart Systems and Manufacturing, ICAC 2022
EditorsChenguang Yang, Yuchun Xu
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665498074
DOIs
Publication statusPublished - 2022
Externally publishedYes
Event27th International Conference on Automation and Computing, ICAC 2022 - Bristol, United Kingdom
Duration: 1 Sept 20223 Sept 2022

Publication series

Name2022 27th International Conference on Automation and Computing: Smart Systems and Manufacturing, ICAC 2022

Conference

Conference27th International Conference on Automation and Computing, ICAC 2022
Country/TerritoryUnited Kingdom
CityBristol
Period1/09/223/09/22

Keywords

  • CBAM module
  • Distracted driving behavior
  • mAP
  • YOLOX

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