| Title | Quantitative Assessment of CCAM Applications on Greenhouse Gas Emissions |
|---|---|
| ID_Doc | 43279 |
| Authors | Partani, S; Qiu, A; Sattiraju, R; Tayade, S; Schotten, HD |
| Title | Quantitative Assessment of CCAM Applications on Greenhouse Gas Emissions |
| Year | 2022 |
| Published | |
| Abstract | With the climate change high on the priority list, reduction of Greenhouse Gas (GHG) emissions with new and intelligent technologies in the transportation sector has been a widely discussed research topic. Conventional combustion engines of today will not achieve the long-term goal of zero emissions by 2050 in the European Union (EU). In this era of automation and digitization, the transportation sector is introducing a new dimension - connectivity. With the release of Vehicle-to-everything (V2X) technology, the number of devices that can potentially connect to the automobile is increasing at a rapid pace. Thus, with connected mobility, vehicles can talk to other vehicles, the infrastructure and pedestrians, thereby making the cities not only safer, but also potentially greener and more efficient. In this regard, it is important to study and analyze the benefits of Connected, Cooperative and Automated Mobility (CCAM). Therefore, in this paper, we provide a methodology to quantitatively assess the different CCAM applications and study its effects on the GHG emissions. This study shows that introduction and usage of CCAM applications, both individually and as a group, helps in reducing GHG emissions in different cities of Germany. |
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