Passenger Occupancy Estimation in Vehicles: A Review of Current Methods and Research Challenges
Open accessAbstract
Passenger detection and occupancy estimation are vital tasks in many fields. The existing literature emphasises that the increasing demand for such systems will continue to grow. This paper reviews the existing literature specializing in the field of transportation safety and efficiency concerning occupancy estimation in vehicles and passenger detection at public transport stations. A comparison between different approaches to passenger estimation is presented. Discussion on the advantages and disadvantages is highlighted. Hence, this paper provides an analysis of 146 papers on the current state of the field. This review paper concludes that invasive methods provide high accuracy with relatively cheap implementation, while noninvasive systems do not violate passenger privacy but lack state-of-the-art accuracy. Future work will include a systematic literature review and a comparative analysis of systems considering the existing window tinting and solar windshields heavily blocking certain parts of the electromagnetic spectrum. Moreover, future work will investigate the critical challenges of noninvasive passenger estimation in different types of vehicles: trucks, buses, or even motorcycles.
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The integration of morphological operations, color conversion, and histogram equalization further enhances the quality of images for subsequent analysis.
“Additionally, the integration of morphological operations, color conversion, and histogram equalization further enhances the quality of the images for subsequent analysis [92].”
From A Review of Passenger Counting in Public Transport Concepts with Solution Proposal Based on Image Processing and Machine Learning (2024) · cites this paper as [92]
Cites
Rapid object detection using a boosted cascade of simple features
Viola, P., & Jones, M. (2005) · Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001 · doi:10.1109/cvpr.2001.990517 · Cited by 18,300 · see citing works
Looking-In and Looking-Out of a Vehicle: Computer-Vision-Based Enhanced Vehicle Safety
Trivedi, M. M., Gandhi, T., & McCall, J. (2007) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2006.889442 · Cited by 317 · see citing works
People Counting and Human Detection in a Challenging Situation
Hou, Y.-L., & Pang, G. K. H. (2010) · IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans · doi:10.1109/tsmca.2010.2064299 · Cited by 238 · see citing works
The smart car seat: personalized monitoring of vital signs in automotive applications
Walter, M., Eilebrecht, B., Wartzek, T., & Leonhardt, S. K. (2011) · Personal and Ubiquitous Computing · doi:10.1007/s00779-010-0350-4 · Cited by 139 · see citing works
Driver cell phone usage detection on Strategic Highway Research Program (SHRP2) face view videos
Seshadri, K., Juefei-Xu, F., Pal, D. K., Savvides, M., & Thor, C. P. (2015) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2015.7301397 · Cited by 119 · see citing works
A Combined Inductive–Capacitive Proximity Sensor for Seat Occupancy Detection
George, B., Zangl, H., Bretterklieber, T., & Brasseur, G. (2010) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2010.2040910 · Cited by 111 · see citing works
Trivedi, M. M., Cheng, S., Childers, E. M. C., & Krotosky, S. J. (2004) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2004.835526 · Cited by 80 · see citing works
Wu, L., & Wang, Y. (2018) · IEEE Sensors Journal · doi:10.1109/jsen.2018.2875659 · Cited by 74 · see citing works
Seat Occupancy Detection Based on Capacitive Sensing
George, B., Zangl, H., Bretterklieber, T., & Brasseur, G. (2009) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2009.2009411 · Cited by 71 · see citing works
Driver Cell Phone Usage Detection from HOV/HOT NIR Images
Artan, Y. O., Bulan, O., Loce, R. P., & Paul, P. (2014) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2014.42 · Cited by 64 · see citing works
Tiny YOLO Optimization Oriented Bus Passenger Object Detection
Zhang, S., Wu, Y., Men, C., & Li, X. (2020) · Chinese Journal of Electronics · doi:10.1049/cje.2019.11.002 · Cited by 62 · see citing works
People Counting System for Getting In/Out of a Bus Based on Video Processing
Chen, C.-H., Chang, Y.-C., Chen, T.-Y., & Wang, D.-J. (2008) · 2008 Eighth International Conference on Intelligent Systems Design and Applications · doi:10.1109/isda.2008.335 · Cited by 58 · see citing works
Occupancy Detection and People Counting Using WiFi Passive Radar
Tang, C., Li, W., Vishwakarma, S., Chetty, K., Julier, S., & Woodbridge, K. (2020) · IEEE Radar Conference (RadarConf) · doi:10.1109/radarconf2043947.2020.9266493 · Cited by 58 · see citing works
Accurate seat belt detection in road surveillance images based on CNN and SVM
Chen, Y., Tao, G., Ren, H., Lin, X., & Zhang, L. (2017) · Neurocomputing · doi:10.1016/j.neucom.2016.06.098 · Cited by 57 · see citing works
Automated people-counting by using low-resolution infrared and visual cameras
Amin, I. J., Taylor, A. J., Junejo, F., Al‐Habaibeh, A., & Parkin, R. M. (2007) · Measurement · doi:10.1016/j.measurement.2007.02.010 · Cited by 56 · see citing works
Lázaro, A., Lázaro, M., Villarino, R., & Girbau, D. (2021) · IEEE Access · doi:10.1109/access.2021.3105390 · Cited by 54 · see citing works
RF-based child occupation detection in the vehicle interior
Diewald, A. R., Landwehr, J., Tatarinov, D., Cola, P. D. M., Watgen, C., Mica, C., Lu-Dac, M., Larsen, P., Gómez, O., & Goniva, T. (2016) · International Radar Symposium · doi:10.1109/irs.2016.7497352 · Cited by 54 · see citing works
Low-cost low-power in-vehicle occupant detection with mm-wave FMCW radar
Alizadeh, M., Abedi, H., & Shaker, G. (2019) · Proceedings of IEEE Sensors/Proceedings of IEEE Sensors ... · doi:10.1109/sensors43011.2019.8956880 · Cited by 54 · see citing works
HEAD DETECTION IN STEREO DATA FOR PEOPLE COUNTING AND SEGMENTATION
van Oosterhout, T., Bakkes, S. C. J., & Kröse, B. (2011) · International Conference on Computer Vision Theory and Applications · doi:10.5220/0003362806200625 · Cited by 50 · see citing works
Image-based seat belt detection
Guo, H., Lin, H., Zhang, S., & Shutao Li, A. (2011) · IEEE International Conference on Vehicular Electronics and Safety (ICVES) · doi:10.1109/icves.2011.5983807 · Cited by 49 · see citing works
Occupant classification system for automotive airbag suppression
Farmer, M. E., & Jain, A. K. (2003) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2003.1211429 · Cited by 47 · see citing works
A Pattern Recognition System for Detecting Use of Mobile Phones While DrivingPreprint
Berri, R. A., Silva, A. G., Parpinelli, R. S., Girardi, E., & Arthur, R. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1408.0680 · Cited by 47 · see citing works
Passenger Compartment Violation Detection in HOV/HOT Lanes
Artan, Y. O., Bulan, O., Loce, R. P., & Paul, P. (2015) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2475721 · Cited by 44 · see citing works
Anovel framework for automatic passenger counting
Mukherjee, S., Saha, B., Jamal, I., Leclerc, R., & Ray, N. (2011) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2011.6116284 · Cited by 40 · see citing works
Detection and classification of passenger seat occupancy using stereovision
Devy, M., Giralt, A., & Marı́n-Hernández, A. (2002) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2000.898433 · Cited by 40 · see citing works
In-Vehicle Occupancy Detection With Convolutional Networks on Thermal Images
Nowruzi, F. E., Ahmar, W. E., Laganière, R., & Ghods, A. H. (2019) · IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2019.00124 · Cited by 39 · see citing works
Occupancy Estimation using WiFi: A Case Study for Counting Passengers on Busses
Mehmood, U., Moser, I., Jayaraman, P. P., & Banerjee, A. (2019) · 2019 IEEE 5th World Forum on Internet of Things (WF-IoT) · doi:10.1109/wf-iot.2019.8767350 · Cited by 39 · see citing works
Real-time passenger counting in buses using dense stereovision
Yahiaoui, T., Khoudour, L., & Meurie, C. (2010) · Journal of Electronic Imaging · doi:10.1117/1.3455989 · Cited by 37 · see citing works
Video occupant detection for airbag deployment
Krumm, J. C., & Kirk, G. P. (2002) · Proceedings · doi:10.1109/acv.1998.732854 · Cited by 36 · see citing works
Seat Belt Fastness Detection Based on Image Analysis from Vehicle In-abin Camera
Kashevnik, A. M., Ali, A., Lashkov, I., & Shilov, N. G. (2020) · Conference of Open Innovations Association (FRUCT) · doi:10.23919/fruct48808.2020.9087474 · Cited by 36 · see citing works
The design and implementation of a vision-based people counting system in buses
Perng, J., Wang, T.-Y., Hsu, Y.-W., & Wu, B. (2016) · International Conference on System Science and Engineering · doi:10.1109/icsse.2016.7551620 · Cited by 35 · see citing works
An embedded system for counting passengers in public transportation vehicles
Bernini, N., Bombini, L., Buzzoni, M., Cerri, P., & Grisleri, P. (2014) · IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications · doi:10.1109/mesa.2014.6935562 · Cited by 33 · see citing works
Pavlidis, I. T., Morellas, V., & Papanikolopoulos, N. (2000) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2000.880964 · Cited by 33 · see citing works
Automatic Passenger Counting System Using Image Processing Based on Skin Colour Detection Approach
Nasir, A. S. A., Gharib, N. K. A., & Jaafar, H. (2018) · 2018 International Conference on Computational Approach in Smart Systems Design and Applications (ICASSDA) · doi:10.1109/icassda.2018.8477628 · Cited by 33 · see citing works
Human Occupancy Detection via Passive Cognitive Radio
Liu, J., Mu, H., Vakil, A., Ewing, R. L., Shen, X., Blasch, E., & Li, J. (2020) · Sensors · doi:10.3390/s20154248 · Cited by 32 · see citing works
Analysis of Predictive Maintenance for Tunnel Systems
Tichý, T., Brož, J., Bělinová, Z., & Pirník, R. (2021) · Sustainability · doi:10.3390/su13073977 · Cited by 32 · see citing works
Self-citationHead detection inside vehicles with a modified SVM for safer airbags
Reyna, R. A., Giralt, A., & Esteve, D. (2002) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2001.948667 · Cited by 32 · see citing works
Smart Automotive Airbags: Occupant Classification and Tracking
Farmer, M. E., & Jain, A. K. (2007) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2006.883768 · Cited by 32 · see citing works
Automatic detection of vehicle occupants: the imaging problemand its solution
Pavlidis, I. T., Symosek, P. F., Fritz, B. S., Bazakos, M. E., & Papanikolopoulos, N. (2000) · Machine Vision and Applications · doi:10.1007/s001380050116 · Cited by 31 · see citing works
Passenger Counter Based on Random Forest Regressor Using Drive Recorder and Sensors in Buses
Nakashima, H., Arai, I., & Fujikawa, K. (2019) · IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) · doi:10.1109/percomw.2019.8730761 · Cited by 31 · see citing works
Evaluation of stereo matching algorithms for occupant detection
Gautama, S., Lacroix, S., & Devy, M. (2003) · Analysis and Modeling of Faces and Gestures · doi:10.1109/ratfg.1999.799242 · Cited by 29 · see citing works
Usage of V2X Applications in Road Tunnels
Brož, J., Tichý, T., Angelakis, V., & Bělinová, Z. (2022) · Applied Sciences · doi:10.3390/app12094624 · Cited by 29 · see citing works
In-Vehicle Passenger Detection Using FMCW Radar
Song, H., Yoo, Y., & Shin, H. (2021) · International Conference on Information Networking · doi:10.1109/icoin50884.2021.9334014 · Cited by 28 · see citing works
Clustering method for counting passengers getting in a bus with single camera
Yang, T., Zhang, Y., Shao, D., & Li, Y. (2010) · Optical Engineering · doi:10.1117/1.3374439 · Cited by 27 · see citing works
Elihoş, A., Alkan, B., Balcı, B., & Artan, Y. O. (2018) · IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) · doi:10.1109/avss.2018.8639447 · Cited by 27 · see citing works
Capacitive passenger detection utilizing dielectric dispersion in human tissues
Satz, A., Hammerschmidt, D., & Tumpold, D. (2009) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2009.03.005 · Cited by 26 · see citing works
Applied Internet of Things (IoT): The Prototype Bus Passenger Monitoring System Using PIR Sensor
Rahmatulloh, A., Nursuwars, F. M. S., Darmawan, I., & Febrizki, G. (2020) · doi:10.1109/icoict49345.2020.9166420 · Cited by 26 · see citing works
A Novel Seat Occupancy Detection System based on Capacitive Sensing
George, B., Zangl, H., Bretterklieber, T., & Brasseur, G. (2008) · Conference proceedings - IEEE Instrumentation/Measurement Technology Conference · doi:10.1109/imtc.2008.4547283 · Cited by 25 · see citing works
Vehicle occupancy monitoring with optical range-sensors
Fritzsche, M., Becker, C., Castillo-Franco, M., & Mirbach, B. (2004) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2004.1336361 · Cited by 25 · see citing works
Ma, Y., Zeng, Y., & Jain, V. (2020) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3411820 · Cited by 25 · see citing works
Doppler radar sensor for occupancy monitoring
Yavari, E., Jou, H., Lubecke, V. M., & Borić-Lubecke, O. (2013) · IEEE Topical Conference on RF/Microwave Power Amplifiers for Radio and Wireless Applications (PAWR) · doi:10.1109/pawr.2013.6490217 · Cited by 25 · see citing works
Application Of Computer Vision Systems For Passenger Counting In Public Transport
Lengvenis, P., Simutis, R., Vaitkus, V., & Maskeliūnas, R. (2013) · Elektronika ir Elektrotechnika · doi:10.5755/j01.eee.19.3.1232 · Cited by 24 · see citing works
Driver’s Seat Belt Detection Using CNN
Naik, G. S. L. D. B. (2021) · Türk bilgisayar ve matematik eğitimi dergisi · doi:10.17762/turcomat.v12i5.1483 · Cited by 24 · see citing works
Noninvasive Passenger Detection Comparison Using Thermal Imager and IP Cameras
Kuchár, P., Pirník, R., Tichý, T., Rástočný, K., Skuba, M., & Tettamanti, T. (2021) · Sustainability · doi:10.3390/su132212928 · Cited by 23 · see citing works
Self-citationSeatbelt detection based on cascade Adaboost classifier
Li, W., Lu, J., Li, Y., Zhang, Y., Wang, J., & Li, H. (2013) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp.2013.6745271 · Cited by 23 · see citing works
On the Use of Low-Cost Radars and Machine Learning for In-Vehicle Passenger Monitoring
Abedi, H., Luo, S., & Shaker, G. S. A. (2020) · IEEE Topical Meeting on Silicon Monolithic Integrated Circuits in RF Systems (SiRF) · doi:10.1109/sirf46766.2020.9040191 · Cited by 21 · see citing works
A combined inductive-capacitive proximity sensor and its application to seat occupancy sensing
George, B., Zangl, H., Bretterklieber, T., & Brasseur, G. (2009) · Conference proceedings - IEEE Instrumentation/Measurement Technology Conference · doi:10.1109/imtc.2009.5168409 · Cited by 21 · see citing works
In-Vehicle Occupancy Detection And Classification Using Machine Learning
Vamsi, M., & Soman, K. P. (2020) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt49239.2020.9225661 · Cited by 20 · see citing works
Predictive diagnostics usage for telematic systems maintenance
Tichý, T., Brož, J., Bělinová, Z., & Kouba, P. (2020) · Smart City Symposium Prague (SCSP) · doi:10.1109/scsp49987.2020.9134051 · Cited by 20 · see citing works
ViPED: On-road vehicle passenger detection for autonomous vehicles
Amanatiadis, A., Karakasis, E., Bampis, L., Ploumpis, S., & Gasteratos, A. (2019) · Robotics Auton. Syst. · doi:10.1016/j.robot.2018.12.002 · Cited by 20 · see citing works
Thermal Feature Detection of Vehicle Categories in the Urban Area
Tichý, T., Švorc, D., Růžička, M., & Bělinová, Z. (2021) · Sustainability · doi:10.3390/su13126873 · Cited by 18 · see citing works
Big Data Application for Urban Transport Solutions
Růžička, J., Tichý, T., & Hajčiarová, E. (2022) · Smart City Symposium Prague (SCSP) · doi:10.1109/scsp54748.2022.9792538 · Cited by 18 · see citing works
Real-time stereo-based vehicle occupant posture determination for intelligent airbag deployment
Schoenmackers, T. D., & Trivedi, M. M. (2004) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2003.1212975 · Cited by 18 · see citing works
Passenger Detection and Counting Inside Vehicles For eCall- a Review on Current Possibilities
Bonyár, A., Géczy, A., Harsányi, G., & Hanák, P. (2018) · IEEE International Symposium for Design and Technology in Electronic Packaging (SIITME) · doi:10.1109/siitme.2018.8599285 · Cited by 17 · see citing works
A machine learning approach to vehicle occupancy detection
Xu, B., Paul, P., Artan, Y. O., & Perronnin, F. (2014) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2014.6957856 · Cited by 17 · see citing works
Image sequence analysis for counting in real time people getting in and out of a bus
Mecocci, A., Bartolini, F., & Cappellini, V. (1994) · Signal Processing · doi:10.1016/0165-1684(94)90039-6 · Cited by 17 · see citing works
Automatic Passenger Counting System for Bus Based on RGB-D Video
Li, F., Yang, F.-W., Liang, H.-W., & Yang, W. (2017) · Annual International Conference on Electronics, Electrical Engineering and Information Science (EEEIS) · doi:10.2991/eeeis-16.2017.29 · Cited by 17 · see citing works
Passenger estimation system using Wi-Fi probe request
Pattanusorn, W., Nilkhamhang, I., Kittipiyakul, S., Ekkachai, K., & Takahashi, A. (2016) · International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES) · doi:10.1109/ictemsys.2016.7467124 · Cited by 16 · see citing works
A cascade detector approach applied to vehicle occupant monitoring with an omni directional camera
Wender, S., & Löhlein, O. (2004) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2004.1336407 · Cited by 16 · see citing works
Development of an Antenna Sensor for Occupant Detection in Passenger Transportation
Sterner, H., Aichholzer, W., & Haselberger, M. (2012) · Procedia Engineering · doi:10.1016/j.proeng.2012.09.113 · Cited by 15 · see citing works
THE NEW GENERATION OF THE BMW CHILD SEAT AND OCCUPANT DETECTION SYSTEM SBE 2
Lu, Y., Marschner, C., Eisenmann, L., & Sauer, S. (2002) · International Journal of Automotive Technology · Cited by 15 · see citing works
Seat occupation detection inside vehicles
Faber, P. (2002) · IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) · doi:10.1109/iai.2000.839597 · Cited by 14 · see citing works
Application of Cybersecurity Approaches within Smart Cities and ITS
Tichý, T., Brož, J., Šmerda, T., & Lokaj, Z. (2022) · Smart City Symposium Prague (SCSP) · doi:10.1109/scsp54748.2022.9792554 · Cited by 14 · see citing works
An Automatic Vehicle Occupant Counting Algorithm Based on Face Detection
Hao, X., Chen, H., & Li, J. (2006) · doi:10.1109/icosp.2006.345797 · Cited by 14 · see citing works
Automated vehicle occupancy monitoring
Birch, P. M., Young, R. C., Claret-Tournier, F., & Chatwin, C. R. (2004) · Optical Engineering · doi:10.1117/1.1766300 · Cited by 14 · see citing works
Contactless seat occupation detection system based on electric field sensing
Tumpold, D., & Satz, A. (2009) · Annual Conference of the IEEE Industrial Electronics Society (IECON) · doi:10.1109/iecon.2009.5414836 · Cited by 14 · see citing works
A novel approach of counting people based on stereovision and DSP
Qiuyu, Z., Li, T., Yiping, J., & Deng, W. (2010) · International Conference on Computer and Automation Engineering · doi:10.1109/iccae.2010.5451996 · Cited by 13 · see citing works
Seat Belt Reminder System In Vehicle Using IR-UWB Radar
Huh, J. H., & Cho, S. H. (2018) · IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC) · doi:10.1109/icnidc.2018.8525708 · Cited by 13 · see citing works
VPDS: An AI-Based Automated Vehicle Occupancy and Violation Detection System
Kumar, A., Gupta, A., Santra, B., Lalitha, K. R., Kolla, M., Gupta, M., & Singh, R. D. (2019) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v33i01.33019498 · Cited by 13 · see citing works
Passenger detection in cars with small form-factor IR sensors (Grid-eye)
Géczy, A., Melgar, R. D. J., Bonyár, A., & Harsányi, G. (2020) · Electronic System-Integration Technology Conference (ESTC) · doi:10.1109/estc48849.2020.9229693 · Cited by 12 · see citing works
An Intelligent RGB-D Video System for Bus Passenger Counting
Liciotti, D., Cenci, A., Frontoni, E., Mancini, A., & Zingaretti, P. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-48036-7_34 · Cited by 12 · see citing works
A four-channel radar system for rear seat occupancy detection in the 24 GHz ISM band
Hoffmann, M. M., Tatarinov, D., Landwehr, J., & Diewald, A. R. (2018) · German Microwave Conference · doi:10.23919/gemic.2018.8335037 · Cited by 12 · see citing works
Automatic head detection for passenger flow analysis in bus surveillance videos
Chen, J., Wen, Q., Zhuo, C., & Mete, M. (2012) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp.2012.6469669 · Cited by 11 · see citing works
A near-infrared imaging method for capturing the interior of a vehicle through windshield
Hao, X., Chen, H., Yao, C., Yang, N., Hong-jun, B., & Wang, C. (2010) · IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) · doi:10.1109/ssiai.2010.5483907 · Cited by 11 · see citing works
Occupant Sensing Utilizing Perturbation of Electric Fields
Jinno, K., Ofuji, M., SAITO, T. K., & 関戸, 才. (1997) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/971051 · Cited by 11 · see citing works
Occupant Detection using Computer Vision
Klomark, M. (2000) · Cited by 11 · see citing works
Deep learning architectures for domain adaptation in HOV/HOT lane enforcement
Wshah, S., Xu, B., Bulan, O., Kumar, J., & Paul, P. (2016) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2016.7477599 · Cited by 11 · see citing works
Occupant Detection through Near-Infrared Imaging
Hao, X., Chen, H., Yang, Y., Yao, C., Yang, H., & Yang, N. (2011) · Journal of Applied Science and Engineering · doi:10.6180/jase.2011.14.3.11 · Cited by 11 · see citing works
Front Seat Child Occupancy Detection Using Road Surveillance Camera Images
Balcı, B., Alkan, B., Elihoş, A., & Artan, Y. O. (2018) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2018.8451582 · Cited by 11 · see citing works
A machine learning approach for detecting cell phone usage
Xu, B., & Loce, R. P. (2015) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2083126 · Cited by 10 · see citing works
Lumentut, J. S., GUNAWAN, F. E., & Diana, D. (2015) · Procedia Computer Science · doi:10.1016/j.procs.2015.07.565 · Cited by 10 · see citing works
Research on Counting Method of Bus Passenger Flow Based on Kinematics of Human Body and SVM
Zhu, F., Gu, J., Yang, R., & Zhao, Z. (2008) · 2008 Second International Symposium on Intelligent Information Technology Application · doi:10.1109/iita.2008.319 · Cited by 10 · see citing works
Artan, Y. O., Paul, P., Perronnin, F., & Burry, A. (2014) · IEEE Winter Conference on Applications of Computer Vision · doi:10.1109/wacv.2014.6835994 · Cited by 10 · see citing works
Research on Counting Method of Bus Passenger Flow Based on Kinematics of Human Body
Zhu, F., Song, J., Yang, R., & Gu, J. (2008) · doi:10.1109/csse.2008.611 · Cited by 10 · see citing works
IMAGE-BASED PASSENGER DETECTION AND LOCALIZATION INSIDE VEHICLES
Faber, P. (2000) · Cited by 9 · see citing works
A TOF-based automatic passenger counting approach in public transportation systems
Klauser, D., Bärwolff, G., & Schwandt, H. (2015) · AIP conference proceedings · doi:10.1063/1.4913168 · Cited by 9 · see citing works
The passenger flow counting research of subway video based on image processing
Qian, X., Xiao, Y., & Chen, F. (2017) · Chinese Control and Decision Conference (CCDC) · doi:10.1109/ccdc.2017.7979418 · Cited by 9 · see citing works
Detection of People Boarding/Alighting a Metropolitan Train using Computer Vision
Belloc, M., Velastín, S. A., Fernández, R., & Jara, M. (2018) · International Conference on Pattern Recognition Systems (ICPRS) · doi:10.1049/cp.2018.1281 · Cited by 9 · see citing works
Gerland, H., & Sutter, K. (1999) · Cited by 8 · see citing works
Sensors help make air bags safer
Paula, G. (1997) · Mechanical Engineering · Cited by 8 · see citing works
A Framework for Detecting Vehicle Occupancy Based on the Occupant Labeling Method
Lee, J., Byun, J., Lim, J., & Lee, J. (2020) · Journal of Advanced Transportation · doi:10.1155/2020/8870211 · Cited by 8 · see citing works
Comparison of Early and Late Information Fusion for Multi-camera HOV Lane Enforcement
Xu, B., Bulan, O., Kumar, J., Wshah, S., Kozitsky, V., & Paul, P. (2015) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2015.153 · Cited by 7 · see citing works
Car-seat occupancy detection using a monocular 360° NIR camera and advanced template matching
Makrushin, A., Langnickel, M., Schott, M., Vielhauer, C., Dittmann, J., & Seifert, K. (2009) · IEEE International Conference on Digital Signal Processing (DSP) · doi:10.1109/icdsp.2009.5201199 · Cited by 7 · see citing works
Ruby, M., Bolme, D. S., Brogan, J., Cornett, D., Delgado, B., Jager, G., Johnson, C., Martinez-Mendoza, J., Santos-Villalobos, H., & Srinivas, N. (2020) · Autonomous Systems: Sensors, Processing, and Security for Ground, Air, Sea, and Space Vehicles and Infrastructure · doi:10.1117/12.2566765 · Cited by 7 · see citing works
Vehicle Occupancy Detection for HOV/HOT Lanes Enforcement
Silva, B., Martins, P., & Batista, J. P. (2019) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc.2019.8917378 · Cited by 7 · see citing works
Passenger detection for subway transportation based on video
Chen, Y., Zhang, L., & Wang, J. (2014) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2014.6975925 · Cited by 6 · see citing works
A method of location the vehicle windshield region for vehicle occupant detection system
Yuan, X., Meng, Y., & Wei, X. (2012) · International Conference on Signal Processing · doi:10.1109/icosp.2012.6491586 · Cited by 6 · see citing works
Covert camera for screening of vehicle interiors and HOV enforcement
Wood, J. W., Gimmestad, G. G., & Roberts, D. W. (2003) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.498755 · Cited by 6 · see citing works
An Indirect Occupancy Detection and Occupant Counting System Using Motion Sensors
Luo, D., Lǚ, J., & Guo, G. (2017) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2017-01-1442 · Cited by 6 · see citing works
An optical method for automated roadside detection and counting of vehicle occupants
Tyrer, J. R., & Lobo, L. M. (2008) · Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering · doi:10.1243/09544070jauto562 · Cited by 6 · see citing works
Detection of persons in a vehicle using IR cameras and RFID technologies
Kalikova, J., Krcal, J., & Koukol, M. (2015) · Smart City Symposium Prague (SCSP) · doi:10.1109/scsp.2015.7181563 · Cited by 5 · see citing works
Nakashima, H., Arai, I., & Fujikawa, K. (2018) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata.2018.8621983 · Cited by 5 · see citing works
Leejiwon, Lee, D., Jin, J. S., Choi, D., & Jang, J.-W. (2021) · The Journal of the Korean Institute of Information and Communication Engineering · Cited by 4 · see citing works
AUTOMATIC PASSENGER COUNTING IN THE HIGH OCCUPANCY VEHICLE (HOV) LANES
Pavlidis, I. T. (1999) · Cited by 4 · see citing works
A vehicle occupant counting system using near-infrared (NIR) image
Xue, Yifei, Xiaoli, Houjin, & Xueye (2012) · International Conference on Signal Processing · doi:10.1109/icosp.2012.6491587 · Cited by 4 · see citing works
Through the windshield driver recognition
Cornett, D., Yen, A., Nayola, G., Montez, D., Johnson, C., Baird, S., Santos-Villalobos, H., & Bolme, D. S. (2019) · Electronic Imaging · doi:10.2352/issn.2470-1173.2019.13.coimg-140 · Cited by 4 · see citing works
Occupant Monitoring System for Traffic Control Based on Visual Categorization
Yebes, J. J., Alcantarilla, P. F., & Bergasa, L. M. (2011) · IEEE Intelligent Vehicles Symposium · doi:10.1109/ivs.2011.5940420 · Cited by 4 · see citing works
Occupant Pose and Location Detect for Intelligent Airbag System Based on Computer Vision
Yang, Y., Zao, G., & Sheng, J. (2008) · International Conference on Natural Computation (ICNC) · doi:10.1109/icnc.2008.599 · Cited by 3 · see citing works
New Modeling & Evaluation Approach for Capacitive Occupant Detection in Vehicles
Satz, A., & Hammerschmidt, D. (2008) · IEEE International Behavioral Modeling and Simulation Workshop (BMAS) · doi:10.1109/bmas.2008.4751234 · Cited by 3 · see citing works
Daley, W. D. R., Usher, C. T., Arif, O., Stewart, J., Wood, J. W., Turgeson, J., & Hanson, E. (2013) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.2008518 · Cited by 2 · see citing works
A device for counting passengers making use of two active linear cameras: comparison of algorithms
Deparis, J.-P., Khoudour, L., Meunier, B., & Duvieubourg, L. (2002) · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics · doi:10.1109/icsmc.1996.565339 · Cited by 2 · see citing works
An Vision System for Automatic Detection of Vehicle Passenger
Lee, Y.-S., & Bae, C.-S. (2005) · The Journal of the Korean Institute of Information and Communication Engineering · Cited by 1 · see citing works
Flagged first, then by citations
1 of the 123 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Pronello, C., & Garzón Ruiz, X. R. (2023) · Sensors · doi:10.3390/s23187719 · Cited by 24 · see citing works
Nalin, A., Vignali, V., Lantieri, C., Cappellari, D., Zamengo, B., & Simone, A. (2024) · Journal of Transport Geography · doi:10.1016/j.jtrangeo.2024.103930 · Cited by 20 · see citing works
Radovan, A., Mršić, L., Đambić, G., & Mihaljević, B. (2024) · Eng · doi:10.3390/eng5040172 · Cited by 24 · see citing works
PointNet-Transformer Fusion Network for In-Cabin Occupancy Monitoring With mm-Wave Radar
Xiao, Z., Ye, K., & Cui, G. (2024) · IEEE Sensors Journal · doi:10.1109/jsen.2023.3347893 · Cited by 18 · see citing works
Video-based automatic people counting for public transport: On-bus versus off-bus deployment
McCarthy, C., Ghaderi, H., Martí, F., Jayaraman, P., & Dia, H. (2025) · Computers in Industry · doi:10.1016/j.compind.2024.104195 · Cited by 14 · see citing works
SCAN: Surveillance Camera Array Network for Enhanced Passenger Detection
Kuchár, P., Pirník, R., Kafková, J., Tichý, T., Ďurišová, J., & Skuba, M. (2024) · IEEE Access · doi:10.1109/access.2024.3443638 · Cited by 9 · see citing works
Self-citationReal-Time Vehicle Passenger Detection Through Deep Learning
Gu, Y., & Sinnott, R. (2023) · IEEE International Conference on eScience · doi:10.1109/e-science58273.2023.10254927 · Cited by 6 · see citing works
Sharara, L., Thelen, K., Gillner, J., Wolf, J., Syed, H., Syed, H., Taylor, R., Shankar, L., Berger, M., Forta, D., et al. (2024) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2024.3408842 · Cited by 5 · see citing works
Dynamic Management Tool for Improving Passenger Experience at Transport Interchanges
Fernández-Lobo, A., Benavente, J., & de Cáceres, A. M. (2025) · Future Transportation · doi:10.3390/futuretransp5020059 · Cited by 4 · see citing works
Smartphone-Based Wi-Fi Analysis for Bus Passenger Counting
Alatiyyah, M. H. (2024) · Computers, materials & continua/Computers, materials & continua (Print) · doi:10.32604/cmc.2024.047790 · Cited by 4 · see citing works
Bus Priority Procedure for Signalized Intersections Based on Bus Occupancy and Delay
Schmidt, K. J., Steinmetz, N., & Margreiter, M. (2024) · SUMO Conference Proceedings · doi:10.52825/scp.v5i.1111 · Cited by 4 · see citing works
Liu, Y., Lyu, Q., Zhang, J., Suo, X., Hong, C., Lin, L., & Wang, D. (2023) · IEEE Conference on Cybernetics and Intelligent Systems · doi:10.1109/cis-ram55796.2023.10370009 · Cited by 3 · see citing works
Context-Aware Automated Passenger Counting Data Denoising
Cherrier, N., Rérolle, B., Graive, M., Dib, A., & Schmitt, É. (2023) · IEEE International Conference on Intelligent Transportation Systems (ITSC) · doi:10.1109/itsc57777.2023.10422561 · Cited by 3 · see citing works
Real-Time AI-Powered Occupancy Monitoring for Modern Jeepneys in Bacolod City, Philippines
Daba-ay, M. A., Bibangco, E. J. P., Javier, R. K. T., & Moncera, C. J. A. (2025) · International Conference on Data Science and Its Applications (ICoDSA) · doi:10.1109/icodsa67155.2025.11157597 · Cited by 2 · see citing works
Hyperparameter Tuning for Effective Passenger Detection
Kafková, J., Pirník, R., Janota, A., & Kuchár, P. (2025) · International Carpathian Control Conference · doi:10.1109/iccc65605.2025.11022848 · Cited by 2 · see citing works
Self-citationeCall Systems: Enhancing Safety and Accessibility
Kuchár, P., Pirník, R., Kafková, J., Janota, A., Kekelák, J., Skuba, M., & Fatura, R. (2024) · International Carpathian Control Conference · doi:10.1109/iccc62069.2024.10569195 · Cited by 1 · see citing works
Self-citationPlakhtii, A. D., & Сергеевич, К. Д. (2025) · The Russian Automobile and Highway Industry Journal · doi:10.26518/2071-7296-2025-22-2-238-247 · Cited by 1 · see citing works
Design and Implementation of Safety Functions for the CNC Milling Machine
Brtiš, J., Ždánsky, J., & Pirník, R. (2024) · ELEKTRO · doi:10.1109/elektro60337.2024.10556865 · Cited by 1 · see citing works
Self-citationAutomatic Passenger Counting (APC) for Online Event Data Recorder (EDR)
Ibnugraha, P. D., Sani, M. I., Sari, M. I., Rizal, M. F., Hanifa, F. H., & Kurniawan, A. P. (2023) · International Conference on Artificial Intelligence, Blockchain, Cloud Computing, and Data Analytics (ICoABCD) · doi:10.1109/icoabcd59879.2023.10390960 · Cited by 1 · see citing works
Smart Occupancy Monitoring System Using Iot Technologies for South African Minibus TaxisPreprint
Maepa, M. R., & Moeti, M. N. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4663206
Temporal and Spatial Characteristics of Passenger Occupancy for Different Travel Modes in Delhi
Gupta, A., & Errampalli, M. (2024) · Lecture notes in civil engineering · doi:10.1007/978-981-97-6071-8_24
An Automated Approach to Determine the People Occupancy in Two Wheeler using Deep Learning
Anuchandana, V. R., Soni, P., & Joby, N. J. (2025) · International Conference on Advances in Computing, Communication, Embedded and Secure Systems (ACCESS) · doi:10.1109/access65134.2025.11135909
Leveraging Machine Learning for Occupant Body Size Estimation via B-Pillar Seatbelt Systems
Wang, D., Ahmed, J., Rowe, O. M., & Bråse, D. (2026) · SAE technical papers on CD-ROM/SAE technical paper series · doi:10.4271/2026-01-0559
Dwelling and Speed Advisory Enhanced Max-Pressure Control With Transit Signal Priority
Tan, C., Laskaris, G., Sun, D., Abohariri, R., Rinaldi, M., & van Lint, H. (2026) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2026.3695849
Ma, J., Hu, Z., & Guo, M. (2026) · Vehicles · doi:10.3390/vehicles8070149
Bongiovi, G., Dias, T. G., Nauri, J., & Ferreira, M. C. (2026) · Transportation Letters · doi:10.1080/19427867.2026.2698817
People Counting Using YOLO-Based Detection and Clustering for a Mobile Robot
Gomulka, K., Woźniak, P., & Krzeszowski, T. (2026) · Sensors · doi:10.3390/s26154664
Weigh-in-motion sensors: an underutilized source for inferring occupancy trend
Akbari, P., & Demissie, M. G. (2026) · Travel Behaviour and Society · doi:10.1016/j.tbs.2026.101397
Köra lätt motorcykel med B-körkort
Forsman, Å., Vadeby, A., Jansson, J., & Kjeldgård, L. (2026) · VTI Rapport · doi:10.65151/vti143608
Prunean, G., Varga, B. O., Oargă, I.-T., Borzan, A. I., & Bara, A.-M. (2026) · Urban Science · doi:10.3390/urbansci10100557
- Authors
- Kuchár, P., Pirník, R., Janota, A., Malobický, B., Kubík, J., & Šišmišová, D.
- Affiliations
- University of Žilina (SK)
- Comenius University Bratislava (SK)
- Slovak University of Technology in Bratislava (SK)
- Corresponding author
- Kuchár, Pavol
- Venue
- Sustainability
- Publisher
- MDPI AG
- Published
- 2023-01-10
- Volume
- 15
- Issue
- 2
- Pages
- 1332
- ISSN
- 2071-1050 (ISSN-L)
- OpenAlex
- W4315566253
- Cited by
- 30
- References
- 123
- Citations by year
- 2026: 8 · 2025: 5 · 2024: 11 · 2023: 6
- FWCI
- 2.23
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Sustainability (publishedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Mobile robotic systems for support during crisis situations (VEGA 1/0241/22)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Indoor and Outdoor Localization Technologies
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Engineering › Mechanical Engineering › Transport Systems and Technology
- Keywords
- passenger detection, vehicle occupancy, transit stations, transport safety, passenger privacy, window tinting, electromagnetic spectrum, trucks, buses, motorcycles
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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