<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Autonomous Vehicles (AVs) are anticipated to bring forth a multitude of advantages for upcoming mobility.These potential benefits and many others vary substantially by the market share of AVs. There are several articles that investigated AV market share with a variety of methods, however, they show a huge variation depending on the market specifications. The aim of this research is to calculate private AV adoption rates over time depending on the Hungarian automobile market characteristics. The research empirically estimates, using the Gompertz function, the projected growth rates of private autonomous passenger vehicles in Hungary using historical patterns of human-driven vehicle ownership data on the basis of projected per capita GDP.The study's findings suggest that, in an optimistic and moderate scenario, the Hungarian car market is projected to become saturated due to AVs by 2067 and 2076, respectively. However, a pessimistic estimation indicates that saturation is unlikely to occur before 2100. This study’s contribution to the literature is through a mathematical approach that predicts AVs market penetration rate and saturation year, in which the assumptions and the used parameters of the model can be modified depending on different case studies, or they can be updated due to the advancement in technology and improvement in knowledge of the studied market.</p>
</abstract>

Autonomous Vehicles (AVs) are anticipated to bring forth a multitude of advantages for upcoming mobility.These potential benefits and many others vary substantially by the market share of AVs. There are several articles that investigated AV market share with a variety of methods, however, they show a huge variation depending on the market specifications. The aim of this research is to calculate private AV adoption rates over time depending on the Hungarian automobile market characteristics. The research empirically estimates, using the Gompertz function, the projected growth rates of private autonomous passenger vehicles in Hungary using historical patterns of human-driven vehicle ownership data on the basis of projected per capita GDP.The study's findings suggest that, in an optimistic and moderate scenario, the Hungarian car market is projected to become saturated due to AVs by 2067 and 2076, respectively. However, a pessimistic estimation indicates that saturation is unlikely to occur before 2100. This study’s contribution to the literature is through a mathematical approach that predicts AVs market penetration rate and saturation year, in which the assumptions and the used parameters of the model can be modified depending on different case studies, or they can be updated due to the advancement in technology and improvement in knowledge of the studied market.

Potential autonomous vehicle ownership growth in Hungary using the Gompertz model

Budapest University of Technology and Economics

Production Engineering Archives

This work is licensed under the Creative Commons Attribution 4.0 International License.

Autonomous Vehicles (AVs) are anticipated to bring forth a multitude of advantages for upcoming mobility.These potential benefits and many others vary...

Potential autonomous vehicle ownership growth in Hungary using the Gompertz model

Online veröffentlicht: 26. Apr. 2023

Seitenbereich: 155 - 161

Eingereicht: 20. Nov. 2022

Akzeptiert: 15. März 2023

DOI: https://doi.org/10.30657/pea.2023.29.18

Schlüsselwörter
Autonomous Vehicles, Gompertz, Adoption, GDP, Forecasting

© 2023 Anas Alatawneh et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Potential autonomous vehicle ownership growth in Hungary using the Gompertz model

Online veröffentlicht: 26. Apr. 2023

Seitenbereich: 155 - 161

Eingereicht: 20. Nov. 2022

Akzeptiert: 15. März 2023

DOI: https://doi.org/10.30657/pea.2023.29.18

SchlüsselwörterAutonomous Vehicles, Gompertz, Adoption, GDP, Forecasting

© 2023 Anas Alatawneh et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Autonomous Vehicles, Gompertz, Adoption, GDP, Forecasting