{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T04:18:19Z","timestamp":1780373899936,"version":"3.54.1"},"reference-count":31,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2017,11,22]],"date-time":"2017-11-22T00:00:00Z","timestamp":1511308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","award":["EP\/N012089\/1"],"award-info":[{"award-number":["EP\/N012089\/1"]}],"id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Although at present legislation does not allow drivers in a Level 3 autonomous vehicle to engage in a secondary task, there may become a time when it does. Monitoring the behaviour of drivers engaging in various non-driving activities (NDAs) is crucial to decide how well the driver will be able to take over control of the vehicle. One limitation of the commonly used face-based head tracking system, using cameras, is that sufficient features of the face must be visible, which limits the detectable angle of head movement and thereby measurable NDAs, unless multiple cameras are used. This paper proposes a novel orientation sensor based head tracking system that includes twin devices, one of which measures the movement of the vehicle while the other measures the absolute movement of the head. Measurement error in the shaking and nodding axes were less than 0.4\u00b0, while error in the rolling axis was less than 2\u00b0. Comparison with a camera-based system, through in-house tests and on-road tests, showed that the main advantage of the proposed system is the ability to detect angles larger than 20\u00b0 in the shaking and nodding axes. Finally, a case study demonstrated that the measurement of the shaking and nodding angles, produced from the proposed system, can effectively characterise the drivers\u2019 behaviour while engaged in the NDAs of chatting to a passenger and playing on a smartphone.<\/jats:p>","DOI":"10.3390\/s17112692","type":"journal-article","created":{"date-parts":[[2017,11,22]],"date-time":"2017-11-22T10:47:38Z","timestamp":1511347658000},"page":"2692","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["An Orientation Sensor-Based Head Tracking System for Driver Behaviour Monitoring"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2383-5724","authenticated-orcid":false,"given":"Yifan","family":"Zhao","sequence":"first","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lorenz","family":"G\u00f6rne","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Iek-Man","family":"Yuen","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongpu","family":"Cao","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Sullman","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6199-4251","authenticated-orcid":false,"given":"Daniel","family":"Auger","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chen","family":"Lv","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaji","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Aerospace, Transport and Manufacturing, Cranfield University, Cranfield MK43 0AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Rebecca","family":"Matthias","sequence":"additional","affiliation":[{"name":"Jaguar Land Rover Limited, University Road, University of Warwick, Coventry CV4 7AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lee","family":"Skrypchuk","sequence":"additional","affiliation":[{"name":"Jaguar Land Rover Limited, University Road, University of Warwick, Coventry CV4 7AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandros","family":"Mouzakitis","sequence":"additional","affiliation":[{"name":"Jaguar Land Rover Limited, University Road, University of Warwick, Coventry CV4 7AL, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2017,11,22]]},"reference":[{"key":"ref_1","unstructured":"SAE-International (2014). J3016: Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems, SAE International."},{"key":"ref_2","unstructured":"Sivak, M., and Schoettle, B. (2015). UMTRI-2015\u201312: Motion Sickness in Self-Driving Vehicles, The University of Michigan Transportation Research Institute."},{"key":"ref_3","unstructured":"Wang, Y., Zhao, T., Ding, X., Bian, J., and Fu, X. (2017, January 13\u201316). Head pose-free eye gaze prediction for driver attention study. Proceedings of the 2017 IEEE International Conference on Big Data and Smart Computing (BigComp), Jeju, Korea."},{"key":"ref_4","unstructured":"Liu, X., Xu, F., and Fujimura, K. (2002, January 17\u201321). Real-time eye detection and tracking for driver observation under various light conditions. Proceedings of the Intelligent Vehicle Symposium, Versailles, France."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1006\/rtim.2002.0279","article-title":"Real-Time Eye, Gaze, and Face Pose Tracking for Monitoring Driver Vigilance","volume":"8","author":"Ji","year":"2002","journal-title":"Real-Time Imaging"},{"key":"ref_6","unstructured":"Smith, P., Shah, M., and da Vitoria Lobo, N. (2000, January 3\u20137). Monitoring head\/eye motion for driver alertness with one camera. Proceedings of the 15th International Conference on Pattern Recognition, ICPR-2000, Barcelona, Spain."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1109\/TITS.2010.2044241","article-title":"Head Pose Estimation and Augmented Reality Tracking: An Integrated System and Evaluation for Monitoring Driver Awareness","volume":"11","author":"Trivedi","year":"2010","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Murphy-Chutorian, E., and Trivedi, M.M. (2008, January 4\u20136). HyHOPE: Hybrid Head Orientation and Position Estimation for vision-based driver head tracking. Proceedings of the 2008 IEEE Intelligent Vehicles Symposium, Eindhoven, The Netherlands.","DOI":"10.1109\/IVS.2008.4621320"},{"key":"ref_9","unstructured":"Hartley, L. (1995). Detecting fatigued drivers with vehicle simulators. Driver Impairment, Driver Fatigue and Driving Simulation, Taylor & Francis."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1109\/TITS.2006.889442","article-title":"Looking-In and Looking-Out of a Vehicle: Computer-Vision-Based Enhanced Vehicle Safety","volume":"8","author":"Trivedi","year":"2007","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Ba, S.O., and Odobez, J.M. (April, January 23). Visual focus of attention estimation from head pose posterior probability distributions. Proceedings of the 2008 IEEE International Conference on Multimedia and Expo, Hannover, Germany.","DOI":"10.1109\/ICME.2008.4607369"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Asteriadis, S., Karpouzis, K., and Kollias, S. (2011, January 4\u20136). The Importance of Eye Gaze and Head Pose to Estimating Levels of Attention. Proceedings of the 2011 Third International Conference on Games and Virtual Worlds for Serious Applications, Athens, Greece.","DOI":"10.1109\/VS-GAMES.2011.38"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1462","DOI":"10.1109\/TITS.2013.2262098","article-title":"Visual Analysis of Eye State and Head Pose for Driver Alertness Monitoring","volume":"14","author":"Mbouna","year":"2013","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MPRV.2006.88","article-title":"Turn-Intent Analysis Using Body Pose for Intelligent Driver Assistance","volume":"5","author":"Cheng","year":"2006","journal-title":"IEEE Pervasive Comput."},{"key":"ref_15","unstructured":"McCall, J.C., Trivedi, M.M., Wipf, D., and Rao, B. (2005, January 21\u201323). Lane Change Intent Analysis Using Robust Operators and Sparse Bayesian Learning. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR\u201905)-Workshops, San Diego, CA, USA."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1109\/TPAMI.2008.106","article-title":"Head Pose Estimation in Computer Vision: A Survey","volume":"31","author":"Trivedi","year":"2009","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/34.982883","article-title":"Detecting faces in images: A survey","volume":"24","author":"Yang","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/S0736-0266(01)00079-1","article-title":"Active range of motion of the head and cervical spine: A three-dimensional investigation in healthy young adults","volume":"20","author":"Ferrario","year":"2002","journal-title":"J. Orthop. Res."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Martin, S., Tawari, A., and Trivedi, M.M. (2013, January 6\u20139). Monitoring head dynamics for driver assistance systems: A multi-perspective approach. Proceedings of the 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, The Netherlands.","DOI":"10.1109\/ITSC.2013.6728568"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.trc.2017.03.014","article-title":"Driving analytics using smartphones: Algorithms, comparisons and challenges","volume":"79","author":"Vlahogianni","year":"2017","journal-title":"Transp. Res. Part C Emerg. Technol."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Chakravarty, T., Ghose, A., Bhaumik, C., and Chowdhury, A. (2013, January 3\u20135). MobiDriveScore\u2014A system for mobile sensor based driving analysis: A risk assessment model for improving one\u2019s driving. Proceedings of the 2013 Seventh International Conference on Sensing Technology (ICST), Wellington, New Zealand.","DOI":"10.1109\/ICSensT.2013.6727671"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ghose, A., Chowdhury, A., Chandel, V., Banerjee, T., and Chakravarty, T. (2016, January 4\u20137). An enhanced automated system for evaluating harsh driving using smartphone sensors. Proceedings of the 17th International Conference on Distributed Computing and Networking-ICDCN\u201916, Singapore.","DOI":"10.1145\/2833312.2849555"},{"key":"ref_23","unstructured":"Intersense (2017, July 10). InertiaCube4. Available online: http:\/\/www.intersense.com\/pages\/18\/234\/."},{"key":"ref_24","first-page":"1755","article-title":"Dlib-ml: A Machine Learning Toolkit","volume":"10","author":"King","year":"2009","journal-title":"J. Mach. Learn. Res."},{"key":"ref_25","unstructured":"Marku\u0161, N., Frljak, M., Pand\u017ei\u0107, I.S., Ahlberg, J., and Forchheimer, R. (arXiv, 2013). Object Detection with Pixel Intensity Comparisons Organized in Decision Trees, arXiv."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1023\/B:VISI.0000013087.49260.fb","article-title":"Robust Real-Time Face Detection","volume":"57","author":"Viola","year":"2004","journal-title":"Int. J. Comput. Vis."},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Baltrusaitis, T., Robinson, P., and Morency, L.-P. (2013, January 1\u20138). Constrained Local Neural Fields for Robust Facial Landmark Detection in the Wild. Proceedings of the 2013 IEEE International Conference on Computer Vision Workshops, Sydney, Australia.","DOI":"10.1109\/ICCVW.2013.54"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Baltrusaitis, T., Robinson, P., and Morency, L.-P. (2016, January 7\u201310). OpenFace: An open source facial behavior analysis toolkit. Proceedings of the 2016 IEEE Winter Conference on Applications of Computer Vision (WACV), Lake Placid, NY, USA.","DOI":"10.1109\/WACV.2016.7477553"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Cristinacce, D., and Cootes, T.F. (2006, January 4\u20137). Feature Detection and Tracking with Constrained Local Models. Proceedings of the British Machine Vision Conference 2006, Edinburgh, UK.","DOI":"10.5244\/C.20.95"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Baltrusaitis, T., Robinson, P., and Morency, L. (2012, January 16\u201321). 3D Constrained Local Model for rigid and non-rigid facial tracking. Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition, Providence, RI, USA.","DOI":"10.1109\/CVPR.2012.6247980"},{"key":"ref_31","unstructured":"Bussone, W.R. (2005). Linear and Angular Head Accelerations in Daily Life. [Master\u2019s Thesis, Virginia Polytechnic Institute and State University]."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2692\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:50:41Z","timestamp":1760208641000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/17\/11\/2692"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,11,22]]},"references-count":31,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2017,11]]}},"alternative-id":["s17112692"],"URL":"https:\/\/doi.org\/10.3390\/s17112692","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,11,22]]}}}