{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T13:31:34Z","timestamp":1780493494931,"version":"3.54.1"},"reference-count":39,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,2,5]],"date-time":"2024-02-05T00:00:00Z","timestamp":1707091200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Open Access Funding by TU Wien"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Human behaviour detection is relevant in many fields. During navigational tasks it is an indicator for environmental conditions. Therefore, monitoring people while they move along the street network provides insights on the environment. This is especially true for motorcyclists, who have to observe aspects such as road surface conditions or traffic very careful. We thus performed an experiment to check whether IMU data is sufficient to classify motorcyclist behaviour as a data source for later spatial and temporal analysis. The classification was done using XGBoost and proved successful for four out of originally five different types of behaviour. A classification accuracy of approximately 80% was achieved. Only overtake manoeuvrers were not identified reliably.<\/jats:p>","DOI":"10.3390\/s24031042","type":"journal-article","created":{"date-parts":[[2024,2,6]],"date-time":"2024-02-06T03:22:31Z","timestamp":1707189751000},"page":"1042","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Classifying Motorcyclist Behaviour with XGBoost Based on IMU Data"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2978-5724","authenticated-orcid":false,"given":"Gerhard","family":"Navratil","sequence":"first","affiliation":[{"name":"Department for Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr. 8-10, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2556-5230","authenticated-orcid":false,"given":"Ioannis","family":"Giannopoulos","sequence":"additional","affiliation":[{"name":"Department for Geodesy and Geoinformation, TU Wien, Wiedner Hauptstr. 8-10, 1040 Vienna, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1016\/j.patcog.2015.02.019","article-title":"Human behaviour recognition in data-scarce domains","volume":"48","author":"Baxter","year":"2015","journal-title":"Pattern Recognit."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Azor\u00edn-L\u00f3pez, J., Saval-Calvo, M., Fuster-Guill\u00f3, A., and Garc\u00eda-Rodr\u00edguez, J. (2013, January 4\u20139). Human behaviour recognition based on trajectory analysis using neural networks. Proceedings of the 2013 International Joint Conference on Neural Networks (IJCNN), Dallas, TX, USA.","DOI":"10.1109\/IJCNN.2013.6706724"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladeni\u010d, D., and Skowron, A. (2007, January 17\u201321). Feature Extraction from Sensor Data Streams for Real-Time Human Behaviour Recognition. Proceedings of the Knowledge Discovery in Databases: PKDD 2007, Warsaw, Poland.","DOI":"10.1007\/978-3-540-74976-9"},{"key":"ref_4","unstructured":"Sun, C., Stirling, D., and Naghdy, F. (2006, January 6\u20138). Human Behaviour Recognition with Segmented Inertial Data. Proceedings of the 2006 Australasian Conference on Robotics and Automation, ACRA 2006, Auckland, New Zealand."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Huggins, C.J., Clarke, R., Abasolo, D., Gil-Rey, E., Tobias, J.H., Deere, K., and Allison, S.J. (2022). Machine Learning Models for Weight-Bearing Activity Type Recognition Based on Accelerometry in Postmenopausal Women. Sensors, 22.","DOI":"10.3390\/s22239176"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Riglet, L., Nicol, F., Leonard, A., Eby, N., Claquesin, L., Orliac, B., Ornetti, P., Laroche, D., and Gueugnon, M. (2023). The Use of Embedded IMU Insoles to Assess Gait Parameters: A Validation and Test-Retest Reliability Study. Sensors, 23.","DOI":"10.3390\/s23198155"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Khan, D.A., Razak, S., Raj, B., and Singh, R. (2019, January 12\u201317). Human Behaviour Recognition Using Wifi Channel State Information. Proceedings of the ICASSP 2019\u20142019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brighton, UK.","DOI":"10.1109\/ICASSP.2019.8682821"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Fayad, M., Hachani, M.Y., Ghoumid, K., Mostefaoui, A., Chouali, S., Picaud, F., Herlem, G., Lajoie, I., and Yahiaoui, R. (2023). Fall Detection Approaches for Monitoring Elderly HealthCare Using Kinect Technology: A Survey. Appl. Sci., 13.","DOI":"10.3390\/app131810352"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"355","DOI":"10.1080\/00140139.2014.967310","article-title":"Eye-tracking measurements and their link to a normative model of monitoring behaviour","volume":"58","author":"Hasse","year":"2015","journal-title":"Ergonomics"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1007\/BF01386390","article-title":"A note on two problems in connexion with graphs","volume":"1","author":"Dijkstra","year":"1959","journal-title":"Numer. Math."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1109\/TSSC.1968.300136","article-title":"A Formal Basis for the Heuristic Determination of Minimum Cost Paths","volume":"4","author":"Hart","year":"1968","journal-title":"IEEE Trans. Syst. Sci. Cybern."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Kuhn, W., Worboys, M.F., and Timpf, S. (2003). Spatial Information Theory. Foundations of Geographic Information Science, Springer.","DOI":"10.1007\/b13481"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s00779-003-0248-5","article-title":"Pedestrian navigation aids: Information requirements and design implications","volume":"7","author":"May","year":"2003","journal-title":"Pers. Ubiquitous Comput."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2012","DOI":"10.1109\/TIM.2014.2381356","article-title":"Improved Cycling Navigation Using Inertial Sensors Measurements From Portable Devices With Arbitrary Orientation","volume":"64","author":"Chang","year":"2015","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TVT.2006.883731","article-title":"Fusion of Sensor Data in Siemens Car Navigation System","volume":"56","author":"Obradovic","year":"2007","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Gartner, G., Cartwright, W., and Peterson, M.P. (2007). Location Based Services and TeleCartography, Springer.","DOI":"10.1007\/978-3-540-36728-4"},{"key":"ref_17","first-page":"2:1","article-title":"I Can Tell by Your Eyes! Continuous Gaze-Based Turn-Activity Prediction Reveals Spatial Familiarity","volume":"Volume 2400","author":"Ishikawa","year":"2022","journal-title":"Proceedings of the 15th International Conference on Spatial Information Theory (COSIT 2022)"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.trpro.2014.09.018","article-title":"Wayfinding Search Strategies and Matching Familiarity in the Built Environment through Virtual Navigation","volume":"2","author":"Dijkstra","year":"2014","journal-title":"Transp. Res. Procedia"},{"key":"ref_19","first-page":"219","article-title":"Preliminary investigation on the dynamics of motorcycle fall behavior: Influence of a simple airbag jacket system on rider safety","volume":"24","author":"Bellati","year":"2006","journal-title":"Forschungshefte Zweiradsicherh"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Diop, M., Boubezoul, A., Oukhellou, L., and Espi\u00e9, S. (2020). Powered Two-Wheeler Riding Profile Clustering for an In-Depth Study of Bend-Taking Practices. Sensors, 20.","DOI":"10.3390\/s20226696"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1953","DOI":"10.1080\/13658816.2020.1740999","article-title":"Why did a vehicle stop? A methodology for detection and classification of stops in vehicle trajectories","volume":"34","author":"Rehrl","year":"2020","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"113240","DOI":"10.1016\/j.eswa.2020.113240","article-title":"Driver behavior detection and classification using deep convolutional neural networks","volume":"149","author":"Shahverdy","year":"2020","journal-title":"Expert Syst. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Maceira, D., Luaces, A., Lugr\u00eds, U., Naya, M.A., and Sanjurjo, E. (2021). Roll Angle Estimation of a Motorcycle through Inertial Measurements. Sensors, 21.","DOI":"10.3390\/s21196626"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.aap.2014.11.011","article-title":"The relationship between the travelling speed and motorcycle styles in urban settings: A case study in Belgrade","volume":"75","author":"Lipovac","year":"2015","journal-title":"Accid. Anal. Prev."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1016\/j.aap.2019.04.009","article-title":"Examining correlations between motorcyclist\u2019s conspicuity, apparel related factors and injury severity score: Evidence from new motorcycle crash causation study","volume":"131","author":"Wali","year":"2019","journal-title":"Accid. Anal. Prev."},{"key":"ref_26","unstructured":"Effendi, L., and Syadiah, T. (2018, January 20\u201321). Analysis of Factors Associated with Subjective Fatigue Among Motorcycle Drivers in Online Ojek. Proceedings of the Internationalization of Islamic Higher Education Institutions Toward Global Competitiveness, Semarang, Indonesia."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"142","DOI":"10.1016\/j.iatssr.2019.12.001","article-title":"A review of behavioural issues contribution to motorcycle safety","volume":"44","author":"Yousif","year":"2020","journal-title":"IATSS Res."},{"key":"ref_28","unstructured":"Sexton, B.F., Baughan, C.J., Elliott, M.A., and Maycock, G. (2004). The Accident Risk of Motorcyclists, TRL."},{"key":"ref_29","unstructured":"Xsens Technologies, B.V. (2024, January 24). MTi and MTx User Manual and Technical Documentation. Available online: https:\/\/docplayer.net\/18829118-Mti-and-mtx-user-manual-and-technical-documentation.html."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Chen, T., and Guestrin, C. (2016, January 13\u201317). XGBoost: A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, New York, NY, USA.","DOI":"10.1145\/2939672.2939785"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"107382","DOI":"10.1016\/j.aap.2023.107382","article-title":"Who might encounter hard-braking while speeding? Analysis for regular speeders using low-frequency taxi trajectories on arterial roads and explainable AI","volume":"195","author":"Zhou","year":"2024","journal-title":"Accid. Anal. Prev."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Shevchenko, Y., and Reips, U.D. (2023). Geofencing in location-based behavioral research: Methodology, challenges, and implementation. Behav. Res. Methods, 29.","DOI":"10.3758\/s13428-023-02213-2"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/s10708-007-9111-y","article-title":"Citizens as sensors: The world of volunteered geography","volume":"69","author":"Goodchild","year":"2007","journal-title":"GeoJournal"},{"key":"ref_34","unstructured":"Vogler, R., Car, A., Strobl, J., and Griesebner, G. (2014). GI_Forum 2014. Geospatial Innovation for Society, Wichmann Verlag."},{"key":"ref_35","unstructured":"Jekel, T., Car, A., Strobl, J., and Griesebner, G. (2012). GI_Forum 2012. Geovizualisation, Society and Learning, Herbert Wichmann Verlag."},{"key":"ref_36","unstructured":"Sohr, A., Brockfeld, E., and Krieg, S. (2010, January 11\u201315). Quality of Floating Car Data. Proceedings of the 12th World Conference on Transport Research (WCTR), Lisbon, Portugal."},{"key":"ref_37","unstructured":"Lang, A., and K\u00fchn, M. (2020). Motorrad fahren in Gruppen, Technical report; Unfallforschung der Versicherer."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ray, K., Sharma, T.K., Rawat, S., Saini, R.K., and Bandyopadhyay, A. (2019). Soft Computing: Theories and Applications, Springer.","DOI":"10.1007\/978-981-13-0589-4"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Kyriakidis, P., Hadjimitsis, D., Skarlatos, D., and Mansourian, A. (2019). Geospatial Technologies for Local and Regional Development, Springer.","DOI":"10.1007\/978-3-030-14745-7"}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/3\/1042\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T13:55:24Z","timestamp":1760104524000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/3\/1042"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,5]]},"references-count":39,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["s24031042"],"URL":"https:\/\/doi.org\/10.3390\/s24031042","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,5]]}}}