Addressing EU climate targets: Reducing CO2 emissions using cooperative and automated vehicles
Open accessAbstract
The European Union (EU) has set rather ambitious goals for reducing emissions and improving related environmental concerns. The majority of EU effort towards reducing emissions is aimed at vehicle manufacturers, mandating development of more efficient engines in order to reduce emissions. We propose a complementary approach to help reach the EU goals. Due to the need for motorists to repeatedly stop and accelerate while driving in urban areas, overall emission rates are observed to be higher in these environments than on open motorways. As a result, management algorithms that focus on harmonising the flow of traffic in urban centres have the potential to greatly reduce urban emission rates. In this paper, we propose a set of functionalities in form of ”use cases” in order to illustrate the inefficiencies of urban traffic flow by utilising cooperation between vehicles and infrastructure. The major contribution of this paper is in addressing the potential positive impact of such measures. The results and the expected effects of the algorithms were determined using a microscopic traffic simulation model. Importantly, this approach also addresses the transition phase, when only a limited number of cooperative and automated vehicles1 (CAVs) will be introduced into traffic, resulting in a mix of automated and non-automated vehicles on the roadways. We demonstrate that introducing CAVs into traffic can lead to significant progress towards EU emissions targets, even for lower penetration levels. According to our models, full use of CAVs on roadways would lead to a CO2 emissions decrease of 10–19%.
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Sorted by citations
A Review of Trustworthy and Explainable Artificial Intelligence (XAI)
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- Authors
- Pribyl, O., Blokpoel, R., & Matowicki, M.
- Affiliations
- Dynniq (Netherlands) (NL)
- Czech Technical University in Prague (CZ)
- ORCID
- Matowicki, Michal
- Venue
- Transportation Research Part D: Transport and Environment
- Publisher
- Elsevier BV
- Published
- 2020-09
- Volume
- 86
- Pages
- 102437
- ISSN
- 1361-9209 (ISSN-L)
- OpenAlex
- W3038658573
- Cited by
- 41
- References
- 44
- Citations by year
- 2025: 6 · 2024: 6 · 2023: 12 · 2022: 10 · 2021: 6 · 2020: 1
- FWCI
- 3.58
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Transportation Research Part D Transport and Environment (publishedVersion, cc-by)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Automotive Engineering › Vehicle emissions and performance
- Physical Sciences › Engineering › Automotive Engineering › Transportation and Mobility Innovations
- Keywords
- CO2 emission reduction, urban traffic flow, vehicle-infrastructure cooperation, EU climate targets, microscopic traffic simulation
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