The impact of automation and connectivity on traffic flow and CO2 emissions. A detailed microsimulation study
arXiv:1912.02273 · doi:10.1016/j.atmosenv.2020.117399
Abstract
Many of the anticipated advantages of connected and automated vehicles or automated vehicles without connectivity (CAVs and AVs respectively) on congestion and energy consumption are questionable. Some studies provide quantitative answers to the above questions through microsimulation but they systematically ignore the realistic simulation of vehicle dynamics, driver behaviour or instantaneous emissions estimates, mostly due to the overall increased complexity of the transport systems and the need for low computational demand on large-scale simulations. However, recent studies question the capability of common car-following models to produce realistic vehicle dynamics or driving behaviour, which directly impacts emissions estimations as well. This work presents a microsimulation study that contributes on the topic, using a scenario-based approach to give insights regarding the impact of CAVs and AVs on the evolution of emissions over a highway network. The motivation here is to answer whether the different driving behaviours produce significant differences in emissions during rush hours, and how significant is the impact of detailed vehicle dynamics simulation and instantaneous emissions in the outcome.
References in corpus (1)
Cited by in corpus (3)
- openACC. An open database of car-following experiments to study the properties of commercial ACC systems
- Are Work Zones and Connected Automated Vehicles Ready for a Harmonious Coexistence? A Scoping Review and Research Agenda
- Energy-based Assessment and Driving Behavior of ACC Systems and Humans Inside Platoons