Unintended Effects of Autonomous Driving: A Study on Mobility Preferences in the Future

  • Innovations in the mobility industry such as automated and connected cars could significantly reduce congestion and emissions by allowing the traffic to flow more freely and reducing the number of vehicles according to some researchers. However, the effectiveness of these sustainable product and service innovations is often limited by unexpected changes in consumption: some researchers thus hypothesize that the higher comfort and improved quality of time in driverless cars could lead to an increase in demand for driving with autonomous vehicles. So far, there is a lack of empirical evidence supporting either one or other of these hypotheses. To analyze the influence of autonomous driving on mobility behavior and to uncover user preferences, which serve as indicators for future travel mode choices, we conducted an online survey with a paired comparison of current and future travel modes with 302 participants in Germany. The results do not confirm the hypothesis that ownership will become an outdated model in the future. Instead they suggest that private cars, whether conventional or fully automated, will remain the preferred travel mode. At the same time, carsharing will benefit from full automation more than private cars. However, the findings indicate that the growth of carsharing will mainly be at the expense of public transport, showing that more emphasis should be placed in making public transport more attractive if sustainable mobility is to be developed.

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Metadaten
Document Type:Article
Language:English
Parent Title (English):Sustainability
Volume:10
Issue:7
First Page:2404
ISSN:2071-1050
DOI:10.3390/su10072404
Publisher:MDPI
Date of first publication:2018/07/10
Tag:autonomous driving; consumption shifting; indirect rebound effects; preference migration; rebound effects; shared autonomous vehicles; travel mode choice; user preferences
Departments, institutes and facilities:Fachbereich Wirtschaftswissenschaften
Dewey Decimal Classification (DDC):300 Sozialwissenschaften / 380 Handel, Kommunikation, Verkehr / 380 Handel, Kommunikation, Verkehr
Entry in this database:2018/07/14

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