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In this paper, we extend previous work in the field of autonomous vehicles on snow-covered roads and present a novel approach for side-slip angle estimation that combines perception with a hybrid artificial neural network pushing the prediction horizon beyond existing approaches. We exploited the feature extraction capabilities of convolutional neural networks and the dynamic time series relationship learning capabilities of gated recurrent units and combined them with a motion model to estimate the side-slip angle. Subsequently, we evaluated the model using the 3DCoAutoSim simulation platform, where we designed a suitable simulation environment with snowfall, friction, and car tracks in snow. The results revealed that our approach outperforms the baseline model for prediction horizons \u2a7e 2 seconds. This extended prediction horizon has practical implications, by providing drivers and autonomous systems with more time to make informed decisions, thereby enhancing road safety.<\/jats:p>","DOI":"10.3233\/ica-230727","type":"journal-article","created":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T12:03:12Z","timestamp":1704801792000},"page":"117-137","source":"Crossref","is-referenced-by-count":7,"title":["Vehicle side-slip angle estimation under snowy conditions using machine learning"],"prefix":"10.1177","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8990-2622","authenticated-orcid":false,"given":"Georg","family":"Novotny","sequence":"first","affiliation":[{"name":"Department Intelligent Transport Systems, Johannes Kepler University, Upper Austria, Austria"},{"name":"Industrial Engineering, UAS Technikum Wien, Vienna, Vienna, Austria"}]},{"given":"Yuzhou","family":"Liu","sequence":"additional","affiliation":[{"name":"Department Intelligent Transport Systems, Johannes Kepler University, Upper Austria, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6912-4130","authenticated-orcid":false,"given":"Walter","family":"Morales-Alvarez","sequence":"additional","affiliation":[{"name":"Department Intelligent Transport Systems, Johannes Kepler University, Upper Austria, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0881-205X","authenticated-orcid":false,"given":"Wilfried","family":"W\u00f6ber","sequence":"additional","affiliation":[{"name":"Industrial Engineering, UAS Technikum Wien, Vienna, Vienna, Austria"},{"name":"Institute for Integrative Nature Conservation Research, University of Natural Resources and Life Sciences, Vienna, Vienna, Austria"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5211-3598","authenticated-orcid":false,"given":"Cristina","family":"Olaverri-Monreal","sequence":"additional","affiliation":[{"name":"Department Intelligent Transport Systems, Johannes Kepler University, Upper Austria, Austria"}]}],"member":"179","reference":[{"key":"10.3233\/ICA-230727_ref2","doi-asserted-by":"crossref","unstructured":"Chindamo D, Lenzo B, Gadola M. 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