Modeling cross-national differences in automated vehicle acceptance

Shelly Etzioni, Jamil Hamadneh, Arnór B. Elvarsson, Domokos Esztergár-Kiss, Milena Djukanovic, Stelios N. Neophytou, Jaka Sodnik, Amalia Polydoropoulou, Ioannis Tsouros, Cristina Pronello, Nikolas Thomopoulos, Yoram Shiftan

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The technology that allows fully automated driving already exists and it may gradually enter the market over the forthcoming decades. Technology assimilation and automated vehicle acceptance in different countries is of high interest to many scholars, manufacturers, and policymakers worldwide. We model the mode choice between automated vehicles and conventional cars using a mixed multinomial logit heteroskedastic error component type model. Specifically, we capture preference heterogeneity assuming a continuous distribution across individuals. Different choice scenarios, based on respondents’ reported trip, were presented to respondents from six European countries: Cyprus, Hungary, Iceland, Montenegro, Slovenia, and the UK. We found that large reservations towards automated vehicles exist in all countries with 70% conventional private car choices, and 30% automated vehicles choices. We found that men, under the age of 60, with a high income who currently use private car, are more likely to be early adopters of automated vehicles. We found significant differences in automated vehicles acceptance in different countries. Individuals from Slovenia and Cyprus show higher automated vehicles acceptance while individuals from wealthier countries, UK, and Iceland, show more reservations towards them. Nontrading mode choice behaviors, value of travel time, and differences in model parameters among the different countries are discussed.

Original languageEnglish
Article number9765
Pages (from-to)1-24
Number of pages24
JournalSustainability (Switzerland)
Volume12
Issue number22
DOIs
Publication statusPublished - 2 Nov 2020

Keywords

  • Automated vehicles
  • Cross-national survey
  • Discrete choice
  • Mixed logit model
  • Panel data
  • User acceptance
  • User preferences

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