Forecasting the Passenger Car Demand Split from Public Perceptions of Electric, Hybrid, and Hydrogen-Fueled Cars in Greece

Efforts to reduce greenhouse gas emissions from the land transport sector revolve around replacing the Internal Combustion Engine with alternative power units. Indeed, governments within the European Union and beyond move to ban the sale of new internal combustion engine vehicles in the near future. A number of technologies are proposed as alternatives, such as electric motors powered by batteries or hydrogen fuel cells, and hybrid power units. These new technologies rely on new infrastructure (charging stations, electrical grid upgrades, hydrogen production, storage and fueling facilities), which will need to be put in place to meet the needs of a transforming vehicle fleet. As such, forecasting the demand for the different technologies will be crucial in planning investments. The authors use machine learning techniques, specifically a Multilayer Perceptron and an Adaptive Neural Fuzzy Inference System, to forecast the demand split from public perceptions as captured through an online survey.

• Record URL:
  • https://doi.org/10.1007/978-3-031-23721-8_6
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/isbn/9783031237201
• Supplemental Notes:
  • © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
• Corporate Authors:

  Springer Nature Switzerland

  ,    
• Authors:
  • Christidis, Konstantinos
  • Profillidis, Vassilios
  • Botzoris, George
  • Iliadis, Lazaros
• Conference:
  • 6th Conference on Sustainable Urban Mobility (CSUM2022)
  • Location: Skiathos Island , Greece
  • Date: 2022-8-31 to 2022-9-2
• Publication Date: 2023

Language

• English

Media Info

• Media Type: Web
• Edition: 1
• Features: References;
• Pagination: pp 77-90
• Monograph Title: Smart Energy for Smart Transport: Proceedings of the 6th Conference on Sustainable Urban Mobility, CSUM2022, August 31-September 2, 2022, Skiathos Island, Greece
• Serial:
  • Lecture Notes in Intelligent Transportation and Infrastructure
  • Publisher: Springer Cham
  • ISSN: 2523-3440
  • EISSN: 2523-3459
  • Serial URL: https://www.springer.com/series/15991

Subject/Index Terms

• TRT Terms: Electric vehicle charging; Electric vehicles; Fuel cell vehicles; Hybrid vehicles; Infrastructure; Machine learning; Service stations; Technological forecasting
• Geographic Terms: European Union
• Subject Areas: Data and Information Technology; Energy; Highways; Planning and Forecasting; Terminals and Facilities;

Filing Info

• Accession Number: 01940439
• Record Type: Publication
• ISBN: 9783031237201
• Files: TRIS
• Created Date: Dec 20 2024 10:27AM