Guest Editorial Artificial Intelligence and Deep Learning for Intelligent and Sustainable Traffic and Vehicle Management (VANETs)

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ISSN: 1524-9050
DOI: 10.1109/TITS.2022.3208785
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2022-10-01
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Abstract
Intelligence and sustainability are two essential drivers for the development of current and future Intelligent Transportation Systems. On one hand, the complexity of vehicular ecosystems and the inherently risk-prone circumstances under which pedestrian and vehicles coexist call for the endowment of intelligent functionalities in almost all systems and processes participating in such ecosystems. On the other hand, risk may be the most important objective to be guaranteed by the provision of intelligence in ITS, but it is not certainly the only one: when safety is assured, sustainability comes into play, seeking to convey intelligence to the distinct parts composing the ITS landscape with efficiency, minimum carbon footprint, wastage of resources or any other factor affected by the technological empowerment itself.
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Intelligent Transportation Systems , Carbon footprint , Vehicular ecosystems , Intelligent Transportation Systems , Carbon footprint , Vehicular ecosystems , Automotive Engineering , Mechanical Engineering , Computer Science Applications
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journal article
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Gupta , B B , Agrawal , D P , Sajjad , M , Sheng , M & Del Ser , J 2022 , ' Guest Editorial Artificial Intelligence and Deep Learning for Intelligent and Sustainable Traffic and Vehicle Management (VANETs) ' , IEEE Transactions on Intelligent Transportation Systems , vol. 23 , no. 10 , pp. 19575-19577 . https://doi.org/10.1109/TITS.2022.3208785