Non-Contact In-Vehicle Occupant Monitoring System Based on Point Clouds from FMCW Radar

Author:

Chen Yixuan1,Luo Yunlong12ORCID,Ma Jianhua3,Qi Alex2,Huang Runhe3ORCID,De Paulis Francesco4ORCID,Qi Yihong12ORCID

Affiliation:

1. School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610032, China

2. Pontosense Inc., Waterloo, ON N2J 4G8, Canada

3. Faculty of Computer and Information Sciences, Hosei University, Chiyoda City 102-8160, Japan

4. UAq EMC Laboratory, University of L’Aquila, 67100 L’Aquila, Italy

Abstract

In order to reduce the probability of automobile safety incidents, the in-vehicle occupant monitoring is indispensable. However, occupant monitoring using frequency-modulated continuous wave (FMCW) radar can be challenging due to the interference from passengers’ posture, movement, and the presence of multiple people. This paper proposes an improved method for generating point clouds using FMCW radar. The approach involves point cloud clustering, post-processing operations such as segmentation, merging, and filtering of the clustered point cloud to match the actual in-vehicle environment, and a state machine combination step. Experimental results show that the proposed method can achieve high recognition accuracy in scenarios with multiple passengers who are moving and sitting in a relaxed manner.

Publisher

MDPI AG

Subject

Computer Science (miscellaneous)

Reference28 articles.

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2. (2021, October 05). Child Hot Car Deaths Data Analysis. Available online: https://www.kidsandcars.org/wp-content/uploads/2020/07/Child-Hot-Car-Deaths-Data-Analysis.pdf.

3. Automotive Active Safety Systems [Introduction to the special section];Sun;IEEE Control Syst.,2010

4. Leuven, B. (2020, October 03). Euro NCAP 2025 Roadmap. Available online: https://cdn.euroncap.com/media/30700/euroncap-roadmap-2025-v4.pdf.

5. Graphene-Paper Pressure Sensor for Detecting Human Motions;Tao;ACS Nano,2017

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