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Trends in Swiss Passenger Vehicles Based on Machine Learning Segmentation

Author

Listed:
  • Miriam Elser

    (Chemical Energy Carriers and Vehicle Systems Laboratory, Empa, CH-8600 Dübendorf, Switzerland)

  • Pirmin Sigron

    (Chemical Energy Carriers and Vehicle Systems Laboratory, Empa, CH-8600 Dübendorf, Switzerland)

  • Betsy Sandoval Guzman

    (Chemical Energy Carriers and Vehicle Systems Laboratory, Empa, CH-8600 Dübendorf, Switzerland)

  • Naghmeh Niroomand

    (Chemical Energy Carriers and Vehicle Systems Laboratory, Empa, CH-8600 Dübendorf, Switzerland
    Department of Information Technology and Electrical Engineering, ETH, CH-8092 Zürich, Switzerland)

  • Christian Bach

    (Chemical Energy Carriers and Vehicle Systems Laboratory, Empa, CH-8600 Dübendorf, Switzerland)

Abstract

Road transport represents a major contributor to air pollution, energy consumption, and carbon dioxide emissions in Switzerland. In response, stringent emission regulations, penalties for non-compliance, and incentives for electric vehicles have been introduced. This study investigates how these policies, along with shifting consumer preferences and vehicle design advancements, have influenced the composition of the Swiss new passenger car fleet. Using machine learning techniques, we segment passenger vehicles to analyze trends over time. Our findings reveal a decline in micro and small vehicles, alongside an increase in lower- and upper-middle-class vehicles, sport utility vehicles, and alternative powertrains across all segments. Additionally, steady increases in vehicle width, length, and weight are observed in all classes since 1995. While technological advancements led to reductions in energy consumption and carbon dioxide emissions until 2016, an increase has since been observed, driven by higher engine power, greater vehicle weight, and changes in certification schemes.

Suggested Citation

  • Miriam Elser & Pirmin Sigron & Betsy Sandoval Guzman & Naghmeh Niroomand & Christian Bach, 2025. "Trends in Swiss Passenger Vehicles Based on Machine Learning Segmentation," Sustainability, MDPI, vol. 17(8), pages 1-21, April.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:8:p:3550-:d:1635235
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    References listed on IDEAS

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