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In this paper, we propose a method for detecting dangerous behaviors based on frequency-modulated continuous-wave radar (mm-DSF). The highly packaged millimeter-wave radar chip has good in-vehicle emotion recognition capability. The acquired millimeter-wave differential frequency signal is Fourier-transformed to obtain the intermediate frequency signal. The physiological decomposition of the local micro-Doppler feature spectrum of the target action is then used as the eigenvalue. Matrix signal intensity and clutter filtering are performed by analyzing the signal echo model of the input channel. The signal classification is based on the estimation and variety of the feature vectors of the target key actions using a modified and optimized level fusion method of the SlowFast dual-channel network. Nine typical risky driving behaviors were set up by the Dula Hazard Questionnaire and TEIQue-SF, and the accuracy of the classification results of the self-built dataset was analyzed to verify the high robustness of the method. The recognition accuracy of this method increased by 1.97% compared with the traditional method.<\/jats:p>","DOI":"10.3390\/s22228929","type":"journal-article","created":{"date-parts":[[2022,11,18]],"date-time":"2022-11-18T06:22:28Z","timestamp":1668752548000},"page":"8929","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["mm-DSF: A Method for Identifying Dangerous Driving Behaviors Based on the Lateral Fusion of Micro-Doppler Features Combined"],"prefix":"10.3390","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9740-0988","authenticated-orcid":false,"given":"Zhanjun","family":"Hao","sequence":"first","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"},{"name":"Gansu Province Internet of Things Engineering Research Center, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zepei","family":"Li","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochao","family":"Dang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"},{"name":"Gansu Province Internet of Things Engineering Research Center, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhongyu","family":"Ma","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yue","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Northwest Normal University, Lanzhou 730070, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"10346","DOI":"10.1109\/TVT.2017.2737553","article-title":"CSI-Based Device-Free Wireless Localization and Activity Recognition Using Radio Image Features","volume":"66","author":"Gao","year":"2017","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2100","DOI":"10.1109\/TSP.2014.2307283","article-title":"Interference alignment with partial CSI feedback in MIMO cellular networks","volume":"62","author":"Rao","year":"2014","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1700889","DOI":"10.1002\/adhm.201700889","article-title":"Nanomaterial-Enabled Wearable Sensors for Healthcare","volume":"7","author":"Yao","year":"2018","journal-title":"Adv. Health Mater."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1109\/MWC.2015.7096294","article-title":"Enabling always on service discovery: Wifi neighbor awareness networking","volume":"22","author":"Loureiro","year":"2015","journal-title":"IEEE Wirel. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"458","DOI":"10.26599\/TST.2019.9010018","article-title":"Survey of pedestrian action recognition techniques for autonomous driving","volume":"25","author":"Chen","year":"2020","journal-title":"Tsinghua Sci. Technol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"100406","DOI":"10.1109\/ACCESS.2019.2929795","article-title":"Architecture of Vehicle Trajectories Extraction with Roadside LiDAR Serving Connected Vehicles","volume":"7","author":"Chen","year":"2019","journal-title":"IEEE Access"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"8889008","DOI":"10.1155\/2020\/8889008","article-title":"Accurate Recognition and Simulation of 3D Visual Image of Aerobics Movement","volume":"2020","author":"Fan","year":"2020","journal-title":"Complexity"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1109\/TWC.2014.011714.130846","article-title":"Spatially sparse precoding in millimeter wave MIMO systems","volume":"13","author":"Rajagopal","year":"2014","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Cardillo, E., Sapienza, G., Li, C., and Caddemi, A. (2021, January 12\u201314). Head Motion and Eyes Blinking Detection: A mm-Wave Radar for Assisting People with Neurodegenerative Disorders. Proceedings of the 2020 50th European Microwave Conference (EuMC), Utrecht, The Netherlands.","DOI":"10.23919\/EuMC48046.2021.9338116"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"10637","DOI":"10.1109\/JSEN.2021.3060428","article-title":"High Angular Resolution for 77GHz FMCW Radar via a Sparse Weighted Quadratic Minimization","volume":"21","author":"Zheng","year":"2021","journal-title":"IEEE Sens. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"160643","DOI":"10.1109\/ACCESS.2020.3021362","article-title":"High Fidelity Physics Simulation of 128 Channel MIMO Sensor for 77GHz Automotive Radar","volume":"8","author":"Chipengo","year":"2020","journal-title":"IEEE Access"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1109\/JSTSP.2014.2334278","article-title":"Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems","volume":"8","author":"Alkhateeb","year":"2014","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1038\/nphoton.2013.275","article-title":"Wireless sub-THz communication system with high data rate","volume":"7","author":"Koenig","year":"2013","journal-title":"Nat. Photon."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"4876","DOI":"10.1038\/ncomms5876","article-title":"High-capacity millimetre-wave communications with orbital angular momentum multi-plexing","volume":"5","author":"Yan","year":"2014","journal-title":"Nat. Commun."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"998","DOI":"10.1109\/JSAC.2016.2549418","article-title":"Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems with Large Antenna Arrays","volume":"34","author":"Gao","year":"2016","journal-title":"IEEE J. Sel. Areas Commun."},{"key":"ref_16","first-page":"1","article-title":"FMCW Radar-Based Hand Gesture Recognition Using Spatiotemporal Deformable and Context-Aware Convolutional 5-D Feature Representation","volume":"60","author":"Dong","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","first-page":"8000117","article-title":"MRPT: Millimeter-Wave Radar-Based Pedestrian Trajectory Tracking for Autonomous Urban Driving","volume":"71","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"105008","DOI":"10.1109\/ACCESS.2020.2999829","article-title":"Detecting human driver inattentive and aggressive driving behavior using deep learning: Recent advances, requirements and open challenges","volume":"8","author":"Alkinani","year":"2020","journal-title":"IEEE Access"},{"key":"ref_19","first-page":"1162","article-title":"The Progress of Human Action Recognition in Videos Based on Deep Learning: A Review","volume":"47","author":"Luo","year":"2019","journal-title":"Acta Electron. Sin."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Li, X., Tao, X., Zhu, B., and Deng, W. (2020). Research on a Simulation Method of the Millimeter Wave Radar Virtual Test Environment for Intelligent Driving. Sensors, 20.","DOI":"10.3390\/s20071929"},{"key":"ref_21","first-page":"217","article-title":"Threshold design method of CFAR for millimeter-wave collision warning radar","volume":"24","author":"Jiang","year":"2005","journal-title":"J. Infrared Millim. Waves-Chin. Ed."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Kim, S., and Yun, J.-H. (2020). Motion-Aware Interplay between WiGig and WiFi for Wireless Virtual Reality. Sensors, 20.","DOI":"10.3390\/s20236782"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.geoderma.2019.06.016","article-title":"Convolutional neural network for simultaneous prediction of several soil properties using visible\/near-infrared, mid-infrared, and their combined spectra","volume":"352","author":"Ng","year":"2019","journal-title":"Geoderma"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.neucom.2018.03.032","article-title":"A hybrid spatio-temporal model for detection and severity rating of Parkinson\u2019s disease from gait data","volume":"315","author":"Zhao","year":"2018","journal-title":"Neurocomputing"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Balal, Y., Balal, N., Richter, Y., and Pinhasi, Y. (2020). Time-Frequency Spectral Signature of Limb Movements and Height Estimation Using Mi-cro-Doppler Millimeter-Wave Radar. Sensors, 20.","DOI":"10.3390\/s20174660"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1094","DOI":"10.1109\/LGRS.2020.2991405","article-title":"Spectral\u2013Spatial Hyperspectral Image Classification Using Dual-Channel Capsule Networks","volume":"18","author":"Jiang","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1016\/j.media.2016.10.004","article-title":"Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation","volume":"36","author":"Kamnitsas","year":"2017","journal-title":"Med. Image Anal."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1002\/ab.21712","article-title":"Effects of trait anger, driving anger, and driving experience on dangerous driving behavior: A moderated mediation analysis","volume":"43","author":"Ge","year":"2017","journal-title":"Aggress. Behav."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Li, J., Ge, Y., Yu, T., and Qu, W. (2022). Social exclusion and dangerous driving behavior: The mediating role of driving anger and moderating role of cognitive reappraisal. Curr. Psychol., 1\u201314.","DOI":"10.1007\/s12144-022-03259-9"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/j.aap.2016.04.025","article-title":"Validation of the Driver\u2019s Angry Thoughts Questionnaire (DATQ) in a Chinese sample","volume":"95","author":"Ge","year":"2016","journal-title":"Accid. Anal. Prev."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"409","DOI":"10.1080\/15472450.2017.1305271","article-title":"Dangerous driving behavior detection using video-extracted vehicle trajectory histograms","volume":"21","author":"Chen","year":"2017","journal-title":"J. Intell. Transp. Syst."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1007\/s00231-010-0631-5","article-title":"Experimental investigation of parameters effect on heat transfer of spray cooling","volume":"46","author":"Cheng","year":"2010","journal-title":"Heat Mass Transf."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1007\/s11220-022-00383-5","article-title":"DSSEMFF: A Depthwise Separable Squeeze-and-excitation Based on Multi-feature Fusion for Image Classification","volume":"23","author":"Liu","year":"2022","journal-title":"Sens. Imaging"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1117\/1.JEI.28.6.063007","article-title":"Attention module-based spatial\u2013temporal graph convolutional networks for skeleton-based action recognition","volume":"28","author":"Kong","year":"2019","journal-title":"J. Electron. Imaging"},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Jang, H.B., Kim, D., and Lee, C.W. (2020, January 17\u201319). Human Action Recognition based on ST-GCN using Opticalflow and Image Gradient. Proceedings of the 9th International Conference on Smart Media and Applications, Jeju, Korea.","DOI":"10.1145\/3426020.3426075"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/22\/8929\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:21:02Z","timestamp":1760145662000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/22\/22\/8929"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,18]]},"references-count":35,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2022,11]]}},"alternative-id":["s22228929"],"URL":"https:\/\/doi.org\/10.3390\/s22228929","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2022,11,18]]}}}