| Autor: |
Seyed Mohammad Hossein Toliyat, Catherine Remfry, Isaac Levi |
| Rok vydání: |
2023 |
| Zdroj: |
Proceedings of the International Conference on Evolving Cities. :25-31 |
| ISSN: |
2754-5768 |
| DOI: |
10.55066/proc-icec.2022.58 |
| Popis: |
Rapid development of Connected and Automated Vehicles (CAVs) besides the urgency of cutting down carbon emissions in the next three decades raise a question about the impact of CAVs deployment on carbon emissions from transport sector. The uncertainties around this question are grave due to the complex interactions between technological capabilities, policy interventions and public travel behaviour. Previous modelling and simulation studies suggest a wide variation in how CAVs may contribute to carbon saving strategies or worsen CO2 emissions. This indicates a necessity for breaking the technology down into the mechanisms as well as features that directly or indirectly affect emissions at vehicular and/or network levels. This paper aims to investigate the mechanisms and different ways that CAVs may decrease or increase road carbon emissions in order to constrain the uncertainties. A semi-systematic literature review was designed and conducted which resulted in identification of 40 relevant publications and documents. Subsequently, 38 levers were ascertained and classified across five major categories: i) emissions per mile; ii) emissions per vehicle; iii) emissions from infrastructure; iv) vehicle miles travelled (VMT); and v) emissions per manufactured vehicle. The estimates for potential impacts of the most significant levers on key performance indicators (KPIs) such as VMT, vehicle occupancy rate and number of manufactured vehicles are provided. Some of the plausible policy interventions are discussed. The findings are also closely related to energy consumption (other than carbon emissions). Therefore, the results can be used for studying potential implications for mass adoption of automated and electric vehicles (AEVs). |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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