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Fuel Consumption and Emissions Analysis of a Connected Automated Vehicle Platoon in Unstable Traffic

  • Pengcheng Wang,
  • Simiao Gao,
  • Zhonghao Li,
  • Xinkai Wu,
  • Xiaozheng He

摘要

Traffic is becoming a significant source of air pollution for the local and global environment. The current study aims to design novel vehicle control strategies, such as adaptive cruise control (ACC) and cooperative ACC (CACC), to reduce fuel consumption and transportation emissions. Unlike the current study, this research explores how driving behavior could decrease fuel consumption and emissions for a given vehicle control strategy. Our previous study found that the resonance frequency could amplify the vibration amplitude. This study presents the impact of the resonance frequency of a vehicle platoon on fuel consumption and emissions. For better illustration, this study introduces a realistic CACC model validated by the PATH program to characterize the CAV’s driving behavior and fuel consumption and transportation emission model, i.e., the VT-Micro model, to describe the platoon’s fuel consumption and emissions. Numerical analysis results show that a periodic perturbation with the resonance frequency will amplify fuel consumption and pollutant emissions. These findings emphasize that preventing CAV traffic oscillations from resonance frequency could help in reaping the expected benefits of CAVs in environmental protection and improving transportation sustainability.