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A Comprehensive Emissions Model Combining Autonomous Vehicles with Park and Ride and Electric Vehicle Transportation Policies

Author

Listed:
  • Mohammed Obaid

    (Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp, 3 1111 Budapest, Hungary)

  • Arpad Torok

    (Department of Automotive Technologies, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp, 3 1111 Budapest, Hungary)

  • Jairo Ortega

    (Department of Transport Technology and Economics, Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, Műegyetem rkp, 3 1111 Budapest, Hungary)

Abstract

Several transport policies reduce pollution levels caused by private vehicles by introducing autonomous or electric vehicles and encouraging mode shift from private to public transport through park and ride (P&R) facilities. However, combining the policies of introducing autonomous vehicles with the implementation of electric vehicles and using the P&R system could amplify the decrease of transport sector emissions. The COPERT software has been used to calculate the emissions. This article aims to study these policies and determine which combinations can better reduce pollution. The result shows that each combination of autonomous vehicles reduces pollution to different degrees. In conclusion, the shift to more sustainable transport modes through autonomous electric vehicles and P&R systems reduces pollution in the urban environment to a higher percentage. In contrast, the combination of autonomous vehicles has lower emission reduction but is easier to implement with the currently available infrastructure.

Suggested Citation

  • Mohammed Obaid & Arpad Torok & Jairo Ortega, 2021. "A Comprehensive Emissions Model Combining Autonomous Vehicles with Park and Ride and Electric Vehicle Transportation Policies," Sustainability, MDPI, vol. 13(9), pages 1-15, April.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4653-:d:541007
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    3. Isam Mashhour Al Jawarneh & Luca Foschini & Paolo Bellavista, 2023. "Efficient Integration of Heterogeneous Mobility-Pollution Big Data for Joint Analytics at Scale with QoS Guarantees," Future Internet, MDPI, vol. 15(8), pages 1-28, August.
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