Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/75563
Title: Data-driven optimization for transportation logistics and smart mobility applications
Authors: Osaba, Eneko
Sánchez Medina, Javier J. 
Vlahogianni, Eleni I.
Yang, Xin She
Masegosa, Antonio D.
Perez Rastelli, Joshué
Del Ser, Javier
UNESCO Clasification: 332703 Sistemas de transito urbano
Issue Date: 2020
Journal: IEEE Intelligent Transportation Systems Magazine 
Abstract: The articles in this special section focus on data driven optimization for transportation and smart mobility applications. We live in an era of major societal and technological changes. Transportation de-carbonization and postindustrial demographic trends, such as massive migrations and an aging society, generate new challenges for cities, making the efficient and sustainable management of services and resources more necessary than ever. Cities must evolve, transform, and become smart to cope with these realities. According to the literature, a city can be referred to as smart when investments in human and social capital and traditional (transportation) and modern [information and communications technology (ICT)] communication infrastructure fuel sustainable economic growth and high quality of life, with a wise management of natural resources, through participatory government.
URI: http://hdl.handle.net/10553/75563
ISSN: 1939-1390
DOI: 10.1109/MITS.2020.3017033
Source: IEEE Intelligent Transportation Systems Magazine [ISSN 1939-1390], v. 12 (4), p. 6-9, (Diciembre 2020)
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