Estimation of NO$ _{x} $ and O$ _{3} $ reduction by dissipating traffic waves

Maya Briani; Rosanna Manzo; Benedetto Piccoli; Luigi Rarità; Maya Briani; Rosanna Manzo; Benedetto Piccoli; Luigi Rarità

doi:10.3934/nhm.2024037

Networks and Heterogeneous Media

2024, Volume 19, Issue 2: 822-841. doi: 10.3934/nhm.2024037

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Estimation of NO$ _{x} $ and O$ _{3} $ reduction by dissipating traffic waves

1.
Consiglio Nazionale delle Ricerche, Istituto per le Applicazioni del Calcolo "Mauro Picone", Via dei Taurini, 19, Rome, 00185, Italy
2.
Dipartimento di Scienze Politiche e della Comunicazione, University of Salerno, Via Giovanni Paolo II, 132, Fisciano (SA), 84084, Italy
3.
Department of Mathematical Sciences, Rutgers University-Camden, 311 N. Fifth Street, Camden, New Jersey, USA
4.
Dipartimento di Scienze Aziendali-Management & Information Systems, University of Salerno, Via Giovanni Paolo II, 132, Fisciano (SA), 84084, Italy

Received: 15 May 2024 Revised: 12 August 2024 Accepted: 19 August 2024 Published: 22 August 2024

Current research directions indicate that vehicles with autonomous capabilities will increase in traffic contexts. Starting from data analyzed in R. E. Stern et al. (2018), this paper shows the benefits due to the traffic control exerted by a unique autonomous vehicle circulating on a ring track with more than 20 human-driven vehicles. Considering different traffic experiments with high stop-and-go waves and using a general microscopic model for emissions, it was first proved that emissions reduces by about 25%. Then, concentrations for pollutants at street level were found by solving numerically a system of differential equations with source terms derived from the emission model. The results outline that ozone and nitrogen oxides can decrease, depending on the analyzed experiment, by about 10% and 30%, respectively. Such findings suggest possible management strategies for traffic control, with emphasis on the environmental impact for vehicular flows.
- road traffic modeling,
- traffic waves,
- emissions,
- Nitrogen oxides,
- ozone production
Citation: Maya Briani, Rosanna Manzo, Benedetto Piccoli, Luigi Rarità. Estimation of NO$ _{x} $ and O$ _{3} $ reduction by dissipating traffic waves[J]. Networks and Heterogeneous Media, 2024, 19(2): 822-841. doi: 10.3934/nhm.2024037

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Abstract

Current research directions indicate that vehicles with autonomous capabilities will increase in traffic contexts. Starting from data analyzed in R. E. Stern et al. (2018), this paper shows the benefits due to the traffic control exerted by a unique autonomous vehicle circulating on a ring track with more than 20 human-driven vehicles. Considering different traffic experiments with high stop-and-go waves and using a general microscopic model for emissions, it was first proved that emissions reduces by about 25%. Then, concentrations for pollutants at street level were found by solving numerically a system of differential equations with source terms derived from the emission model. The results outline that ozone and nitrogen oxides can decrease, depending on the analyzed experiment, by about 10% and 30%, respectively. Such findings suggest possible management strategies for traffic control, with emphasis on the environmental impact for vehicular flows.

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