| Popis: |
As global efforts to combat climate change intensify, transitioning to sustainable transportation is crucial. This study explores decarbonization strategies for urban traffic in downtown Toronto through microsimulation, evaluating the environmental and economic impacts of vehicle technologies, traffic management strategies (eco-routing), and driving behaviours (eco-driving). The study analyzes 140 decarbonization scenarios involving different fuel types, Connected and Automated Vehicle (CAV) penetration rates, and anticipatory routing strategies. Using transformer-based prediction models, we forecast Greenhouse Gas (GHG) and Nitrogen Oxides (NOx) emissions, along with average speed and travel time. The key findings show that 100% Battery Electric Vehicles (BEVs) reduce GHG emissions by 75%, but face challenges related to cost and infrastructure. Hybrid Electric Vehicles (HEVs) achieve GHG reductions of 35-40%, while e-fuels result in modest reductions of 5%. Integrating CAVs with anticipatory routing strategies significantly reduces GHG emissions. Additionally, eco-driving practices and eco-routing strategies have a notable impact on NOx emissions and travel time. By incorporating a comprehensive cost analysis, the study offers valuable insights into the economic feasibility of these strategies. The findings provide practical guidance for policymakers and stakeholders in developing effective decarbonization policies and supporting sustainable transportation systems. |
