Scenario creation of Shared Autonomous Vehicles Penetration Rate, a Quantitative Environmental Analysis

Abstract

In 2022, the air pollution levels in Iranian cities increased by an average of 35% compared to 2019, which is concerning considering the growing transportation needs due to population growth. However, alternative travel methods with better environmental performance can help reduce the role of transportation in creating pollution. One potential solution is the use of shared autonomous vehicles, which have the potential to significantly reduce greenhouse gas emissions. However, estimating the exact effects of this travel method on climate change can be challenging due to various factors that come into play. To address this issue, a study was conducted using the SUMO software and random travel demand to quantitatively analysis the environmental impact of shared autonomous vehicles in a specific section of Tehran city. The analysis considered different scenarios related to the penetration rate, fleet size, and sharing policies. Simulation-based approaches were employed to assess the environmental impact, with a particular focus on greenhouse gas emissions. The results of the study indicated that simultaneous service to two users, compared to other sharing scenarios, can reduce greenhouse gas emissions by up to 10%. This suggests that efficient sharing policies can have a positive impact on the environment. Moreover, the study found that in scenarios where both autonomous car-sharing and private car modes exist, increasing the fleet size of shared autonomous vehicles can lead to increased congestion, resulting in higher pollutant emissions. Additionally, the penetration rate of these vehicles is crucial, as a penetration rate of 100% tends to result in almost zero greenhouse gas emissions. Regarding the impact of the fleet size of shared autonomous vehicles on fuel consumption, it can be said that increasing the fleet size in scenarios where both modes exist would lead to an increase in fossil fuel consumption and a decrease in electric fuel consumption. Overall, this study highlights the potential environmental benefits of shared autonomous vehicles in reducing greenhouse gas emissions. By implementing efficient sharing policies, increasing fleet size and density, and aiming for high penetration rates, we can strive towards a greener and more sustainable transportation system.

Keywords

• simulation of shared autonomous vehicles (sav)
• ride-sharing
• electric cars
• environmental pollutants
• intelligent transportation