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Potential pollutant emission effects of connected and automated vehicles in a mixed traffic flow context for different road types

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posted on 2021-09-15, 18:28 authored by Jorge BandeiraJorge Bandeira, Eloisa Macedo,, Paulo Fernandes, Monica Rodrigues, Mario Andrade, Margarida C. Coelho

The environmental impact of connected and autonomous vehicles (CAVs) is still uncertain. Little is known about how CAVs operational behavior influences the environmental performance of network traffic, including conventional vehicles (CVs). In this paper, a microscopic traffic and emission modeling platform was applied to simulate CAVs operation in Motorway, Rural, and Urban road sections of a medium-sized European city, assuming different configurations of the car-following model parameters associated with a pre-determined or cooperative adaptative behavior of the CAVs. The main contribution is to evaluate the impact of the CAVs operation on the distribution of accelerations, Vehicle Specific Power (VSP) modal distribution, carbon dioxide (CO2) and nitrogen oxides (NOx) emissions for different road types and Market Penetration Rates (MPR). Results suggest CAVs operational behavior can affect CVs environmental performance either positively or negatively, depending on the driving settings and road type. It was found network-wide CO2 varies between savings of 18% and an increase of 4%, depending on the road type and MPR. CAVs adjusted driving settings allowed minimization of system NOx up to 13-23% for MPR ranging between 10 and 90%. These findings may support policymakers and traffic planners in developing strategies to better accommodate CAVs in a sustainable way.


1 This work was supported by the projects: UIDB/00481/2020 and UIDP/00481/2020 FCT – Fundação para a Ciência e a Tecnologia; CENTRO-01-0145-FEDER-022083 - Centro2020 Regional Operational Programme, under the PORTUGAL2020 Partnership Agreement, through the European Regional Development Fund; MobiWise (P2020 SAICTPAC/0011/2015); DICA-VE (POCI-01-0145-FEDER-029463); and InFLOWence (POCI-01-0145-FEDER-029679


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Submitting Author's Institution

University of Aveiro

Submitting Author's Country

  • Portugal