Inattentive Driving Behavior Detection Based on Portable FMCW Radar

Chuanwei Ding, Rachel Chae, Jing Wang, Li Zhang, Hong Hong, Xiaohua Zhu, Changzhi Li

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Monitoring driver's attentiveness is crucial for transportation safety. In this article, inattentive driving behavior detection based on frequency-modulated continuous-wave (FMCW) radar systems is proposed for this purpose. Seven typical driving behaviors which result in reduced attentiveness are involved in this study. Time-Doppler spectrogram and range-Doppler trajectory are utilized to analyze their features in multiple domains, including time, Doppler, range, and radar cross-section (RCS). These features are extracted as inputs to a machine learning classifier to obtain recognition results. Extensive experiments on a real car environment have been conducted to show its feasibility and superiority by obtaining an average accuracy rate of around 95%. The influences of radar center frequency, individual diversity, and radar view angle are also investigated.

Original languageEnglish
Article number8815861
Pages (from-to)4031-4041
Number of pages11
JournalDefault journal
Volume67
Issue number10
DOIs
StatePublished - Oct 2019

Keywords

  • Driving behavior monitoring
  • frequency-modulated continuous-wave (FMCW) radar
  • machine learning
  • range-Doppler
  • time-Doppler

Fingerprint

Dive into the research topics of 'Inattentive Driving Behavior Detection Based on Portable FMCW Radar'. Together they form a unique fingerprint.

Cite this