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Study of Different Seat Allocation Strategies to Reduce the Risk of Contagion Among Passengers in a Public Road Transport System
14th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2022 ; 594 LNNS:209-220, 2023.
Article in English | Scopus | ID: covidwho-2173796
ABSTRACT
As a result of the COVID-19 pandemic, public transport systems suffered a significant reduction in passengers due to the suppression of services and reduced vehicle capacity. This reduction jeopardized their role as facilitators of sustainable mobility, causing large economic losses to public transport operators. Therefore, an intelligent management aimed at reducing the risk of contagion among its users is an aspect of interest for public transport operators and a challenge from a scientific point of view. This paper presents the results of a study aimed at analyzing the effect of different seat allocation strategies on the risk of contagion among passengers. Starting from a formalization of the problem based on epidemiological and public transport entities, the methodology employed, based on Data Mining, makes use of simulation processes to analyze the effect of these strategies. The paper presents the results obtained by analyzing a route of a public road passenger transport operator. The results allow us to evaluate the risk of contagion of different seat allocation strategies and to evaluate how this risk varies according to the number of passengers who have traveled on a vehicle journey. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 14th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2022 Year: 2023 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Type of study: Prognostic study Language: English Journal: 14th International Conference on Ubiquitous Computing and Ambient Intelligence, UCAmI 2022 Year: 2023 Document Type: Article