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Integrating Autonomous Busses as Door-to-Door and First-/Last-Mile Service into Public Transport: Findings from a Stated Choice Experiment

Klinkhardt, Christian ORCID iD icon 1; Kandler, Kim 1; Kostorz, Nadine 1; Heilig, Michael 1; Kagerbauer, Martin 1; Vortisch, Peter 1
1 Institut für Verkehrswesen (IFV), Karlsruher Institut für Technologie (KIT)

Abstract:

Autonomous busses and on-demand (OD) services have the potential to improve the public transport system. However, research on potential traffic impacts is still ongoing, mainly because of a lack of existing use cases of autonomous driving as part of public transport. The availability of revealed preference data for mode choice decisions is thus very limited. Therefore, we conducted a stated choice experiment to assess mode choice preferences with regard to use cases as the main mode of transport and as the solution for the first and last mile. We also distinguished between OD and schedule-based (sched.) services. The target population of the survey is the population of Baden-Württemberg, a state in southwestern Germany. The responses of 1,434 people were analyzed using a nested logit approach. On this basis, we established exemplary utility functions and descriptively derived recommendations for efficient forms of deploying autonomous busses in addition to already existing well-developed public transport systems. It was found that, under the given conditions, public transport pass owners without a car in their household would be the most interested in using autonomous busses. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000160476
Veröffentlicht am 12.07.2023
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Verkehrswesen (IFV)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2023
Sprache Englisch
Identifikator ISSN: 0361-1981, 2169-4052
KITopen-ID: 1000160476
Erschienen in Transportation Research Record: Journal of the Transportation Research Board
Verlag SAGE Publications
Vorab online veröffentlicht am 23.06.2023
Schlagwörter planning and analysis, transportation demand forecasting, demand estimation, mode choices, preference survey data analysis
Nachgewiesen in Dimensions
Web of Science
Scopus
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