Driver State Monitoring Technology for Conditionally Automated Vehicles: Review and Future Prospects-Reference-Cited by-同舟云学术

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Driver State Monitoring Technology for Conditionally Automated Vehicles: Review and Future Prospects

Published:2023 Issue: Volume:72 Page:1-20
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Qu You¹^ORCID,Hu Hongyu¹^ORCID,Liu Jiarui²^ORCID,Zhang Zhengguang¹^ORCID,Li Yechen³^ORCID,Ge Xiaojun⁴^ORCID

Affiliation:

1. State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun, China

2. School of Control and Computer Engineering, North China Electric Power University, Beijing, China

3. College of Automotive Engineering, Jilin University, Changchun, China

4. College of Transportation, Shandong University of Science and Technology, Qingdao, China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jilin Province

Science and Technology Development Project of Jilin Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10201931.pdf?arnumber=10201931

Reference159 articles.

1. Driving posture recognition by convolutional neural networks

2. Driver’s posture detection based on centroid coordinates of two-hand(arm) region;wu;Proc IEEE 3rd Int Conf Commun Inf Syst (ICCIS),2018

3. Foot placement during error and pedal applications in naturalistic driving

4. Depth video-based two-stream convolutional neural networks for driver fatigue detection

5. Naturalistic observations of driver hand positions

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1. Real-Time Safety Driving Advisory System Utilizing a Vision-Based Driving Monitoring Sensor;IEICE Transactions on Information and Systems;2024-07-01

2. WISDOM: WiFi Improved Safe Driver Operation Monitoring With CSI;IEEE Sensors Letters;2024-01

3. Driver Distraction Behavior Detection Framework Based on the DWPose Model, Kalman Filtering, and Multi-Transformer;IEEE Access;2024

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