Author, as appears in the article.: Juan AA; Freixes A; Panadero J; Serrat C; Estrada-Moreno A
Department: Enginyeria Informàtica i Matemàtiques
e-ISSN: 2352-1465
URV's Author/s: Estrada Moreno, Alejandro
Keywords: Unmanned aerial vehicles Team orienteering problem Smart cities
Abstract: © 2020 The Authors. Published by Elsevier B.V. The concepts of unmanned aerial vehicles and self-driving vehicles are gaining relevance inside the smart city environment. This type of vehicles might use ultra-reliable telecommunication systems, Internet-based technologies, and navigation satellite services to decide about the routes they must follow to efficiently accomplish their mission and reach their destinations in due time. When working in teams of vehicles, there is a need to coordinate their routing operations. When some unexpected events occur in the city (e.g., after a traffic accident, a natural disaster, or a terrorist attack), coordination among vehicles might need to be done in real-time. Using the team orienteering problem as an illustrative case scenario, this paper analyzes how the combined use of extremely fast biased-randomized heuristics and parallel computing allows for 'agile' optimization of routing plans for drones and other autonomous vehicles.
Thematic Areas: Transportation Interdisciplinar Engenharias iv Engenharias iii Ciências biológicas ii Administração pública e de empresas, ciências contábeis e turismo
licence for use: https://creativecommons.org/licenses/by/3.0/es/
Author's mail: alejandro.estrada@urv.cat
Author identifier: 0000-0001-9767-2177
Record's date: 2024-07-27
Papper version: info:eu-repo/semantics/publishedVersion
Link to the original source: https://www.sciencedirect.com/science/article/pii/S2352146520302908
Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
Papper original source: Transportation Research Procedia. 47 243-250
APA: Juan AA; Freixes A; Panadero J; Serrat C; Estrada-Moreno A (2020). Routing Drones in Smart Cities: A Biased-Randomized Algorithm for Solving the Team Orienteering Problem in Real Time. Amsterdam: Elsevier
Article's DOI: 10.1016/j.trpro.2020.03.095
Entity: Universitat Rovira i Virgili
Journal publication year: 2020
Publication Type: Proceedings Paper
Repositori URV