Dynamics of particulate emissions in the presence of autonomous vehicles
Around one third of CO2{{\rm{CO}}}_{2} emissions in the atmosphere are linked to vehicular traffic. Pollutant agents have an impact on the environment, in particular, the increased presence of particulate matter (PM) creates negative effects on human health. This article examines how autonomy could...
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| Format: | Article |
| Language: | English |
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De Gruyter
2025-01-01
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| Series: | Open Mathematics |
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| Online Access: | https://doi.org/10.1515/math-2024-0126 |
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| author | Briani Maya Denaro Christopher Anthony Piccoli Benedetto Rarità Luigi |
| author_facet | Briani Maya Denaro Christopher Anthony Piccoli Benedetto Rarità Luigi |
| author_sort | Briani Maya |
| collection | DOAJ |
| description | Around one third of CO2{{\rm{CO}}}_{2} emissions in the atmosphere are linked to vehicular traffic. Pollutant agents have an impact on the environment, in particular, the increased presence of particulate matter (PM) creates negative effects on human health. This article examines how autonomy could positively reduce the emission of air pollutants due to traffic. The methodology involves the analyses of PM emissions as a function of traffic conditions, especially in the presence of autonomous vehicles (AVs) dampening traffic waves. The starting point is traffic measurements that, gathered from real experiments involving a fleet of vehicles moving on a ring track, exhibit the presence of stop-and-go waves that are dampened by control strategies implemented on a unique AV. Using a system of ordinary differential equations modeling the principal chemical reactions in the atmosphere, it is proved that wave dampening implies a significant decrease in PM emissions at ground level. The horizontal diffusion of the pollutants is estimated by partial differential equations combined with the model for chemical reactions. The obtained outcomes show advantages given by the improvements in traffic flows and the mitigation effect of green barriers. |
| format | Article |
| id | doaj-art-86dcfe61f698451d8a8848a63b3b0d04 |
| institution | Kabale University |
| issn | 2391-5455 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Open Mathematics |
| spelling | doaj-art-86dcfe61f698451d8a8848a63b3b0d042025-01-20T11:09:00ZengDe GruyterOpen Mathematics2391-54552025-01-01231S213S21410.1515/math-2024-0126Dynamics of particulate emissions in the presence of autonomous vehiclesBriani Maya0Denaro Christopher Anthony1Piccoli Benedetto2Rarità Luigi3Consiglio Nazionale delle Ricerche, Istituto per le Applicazioni del Calcolo Mauro Picone, Via dei Taurini, 19, Rome, 00185, ItalyCenter for Computational and Integrative Biology, Rutgers University-Camden, 201 S. Broadway, Camden, 08102, New Jersey, USADepartment of Mathematical Sciences, Rutgers University-Camden, 311 N. Fifth Street, Camden, 08102, New Jersey, USADipartimento di Scienze Aziendali-Management and Information Systems, University of Salerno, Via Giovanni Paolo II, 132, Fisciano (SA), 84084, ItalyAround one third of CO2{{\rm{CO}}}_{2} emissions in the atmosphere are linked to vehicular traffic. Pollutant agents have an impact on the environment, in particular, the increased presence of particulate matter (PM) creates negative effects on human health. This article examines how autonomy could positively reduce the emission of air pollutants due to traffic. The methodology involves the analyses of PM emissions as a function of traffic conditions, especially in the presence of autonomous vehicles (AVs) dampening traffic waves. The starting point is traffic measurements that, gathered from real experiments involving a fleet of vehicles moving on a ring track, exhibit the presence of stop-and-go waves that are dampened by control strategies implemented on a unique AV. Using a system of ordinary differential equations modeling the principal chemical reactions in the atmosphere, it is proved that wave dampening implies a significant decrease in PM emissions at ground level. The horizontal diffusion of the pollutants is estimated by partial differential equations combined with the model for chemical reactions. The obtained outcomes show advantages given by the improvements in traffic flows and the mitigation effect of green barriers.https://doi.org/10.1515/math-2024-0126road trafficemissionsparticulate matterordinary and partial differential equations34a3435k5762p12 |
| spellingShingle | Briani Maya Denaro Christopher Anthony Piccoli Benedetto Rarità Luigi Dynamics of particulate emissions in the presence of autonomous vehicles Open Mathematics road traffic emissions particulate matter ordinary and partial differential equations 34a34 35k57 62p12 |
| title | Dynamics of particulate emissions in the presence of autonomous vehicles |
| title_full | Dynamics of particulate emissions in the presence of autonomous vehicles |
| title_fullStr | Dynamics of particulate emissions in the presence of autonomous vehicles |
| title_full_unstemmed | Dynamics of particulate emissions in the presence of autonomous vehicles |
| title_short | Dynamics of particulate emissions in the presence of autonomous vehicles |
| title_sort | dynamics of particulate emissions in the presence of autonomous vehicles |
| topic | road traffic emissions particulate matter ordinary and partial differential equations 34a34 35k57 62p12 |
| url | https://doi.org/10.1515/math-2024-0126 |
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