Mahmoud, Abdulrahman A. ORCID: https://orcid.org/0000-0002-1617-0579, Ahmad, Zahir, Onyekpe, Uche ORCID: https://orcid.org/0000-0001-8033-9394, Almadani, Yousef ORCID: https://orcid.org/0000-0001-8190-1684, Ijaz, Muhammad ORCID: https://orcid.org/0000-0002-0050-9435, Haas, Olivier C. L. ORCID: https://orcid.org/0000-0002-4665-2894 and Rajbhandari, Sujan ORCID: https://orcid.org/0000-0001-8742-118X (2021) Vehicular Visible Light Positioning Using Receiver Diversity with Machine Learning. Electronics, 10 (23). p. 3023. Downloaded from: http://ray.yorksj.ac.uk/id/eprint/5779/ The version presented here may differ from the published version or version of record. If you intend to cite from the work you are advised to consult the publisher's version: http://dx.doi.org/10.3390/electronics10233023 Research at York St John (RaY) is an institutional repository. It supports the principles of open access by making the research outputs of the University available in digital form. Copyright of the items stored in RaY reside with the authors and/or other copyright owners. Users may access full text items free of charge, and may download a copy for private study or non-commercial research. For further reuse terms, see licence terms governing individual outputs. Institutional Repository Policy Statement RaY Research at the University of York St John For more information please contact RaY at ray@yorksj.ac.uk