Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/27676

Title: Fully Informed Vulnerable Road Users - Simpler, Maybe Better
Authors: Fernandes, Bruno
Vicente, Henrique
Ribeiro, Jorge
Capita, António
Analide, César
Neves, José
Editors: Indrawan-Santiago, Maria
Pardede, Eric
Salvadori, Ivan
Steinbauer, Matthias
Khalil, Ismail
Anderst-Kotsis, Gabriele
Keywords: Vulnerable Road Users
Knowledge Representation and Reasoning
Logic Programming
Artificial Neural Networks
Issue Date: 2019
Publisher: ACM - Association for Computing Machinery
Citation: Fernandes, B., Vicente, H., Ribeiro J., Capita, A., Analide, C. & Neves J., Fully Informed Vulnerable Road Users - Simpler, Maybe Better. In M. Indrawan-Santiago, E. Pardede, I.L. Salvadori, M. Steinbauer, I. Khalil & G. Anderst-Kotsis Eds., Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services (iiWAS2019), pp. 598–602, Association for Computing Machinery, New York, United States of America, 2019.
Abstract: Vulnerable Road Users (VRUs) are all those with an increased vulnerability on the road, in particular non-motorised ones. Until now, the emphasis has been in politics more focused on drivers, vehicles and infrastructures. However, recent developments show a shift in other directions, with researchers now devoting efforts to improve VRUs' safety. Hence, this work focuses on pedestrian walking and crossing behaviour, attitudes, motivations and habits, being grounded on an approach to Knowledge Representation and Reasoning centred on logic programming, which establishes a formal logical inference engine that is complemented with an Artificial Neural Network line to computation.
URI: https://dl.acm.org/doi/abs/10.1145/3366030.3366089
http://hdl.handle.net/10174/27676
ISBN: 978-1-4503-7179-7
Type: article
Appears in Collections:QUI - Artigos em Livros de Actas/Proceedings

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