Ride experience in automated minibuses: measuring users' transport mode preferences before and after a test ride

Research output: Contribution to journalConference articleScientificpeer-review

24 Downloads (Pure)

Abstract

In the present study, we explored the influence of ride experience in automated minibuses (AmBs) on transport mode choice that includes the automated shuttles as well as conventional transport options (car, bus and bicycle) on the first-/ last-mile stage of rail trips. We used the case study of the connection between Brandevoort train station and the newly developing working and living area in Helmond (the Netherlands) where an AmB was tested in the February-March period of 2021. We conducted a two-wave stated preference experiment wherein data was gathered both before and after the participants had a test ride in the AmB. The results of the joint hybrid mixed logit model indicate a clear preference towards flexible-service AmBs, particularly in relation to travel time and costs. While preferences for less favoured regular-service AmBs experienced a noteworthy shift in travel time and costs, waiting and walking time parameters influenced by participants' ride experience in this pilot and by prior ride experience from other pilots. This reinforces the idea that the ride experience in AmBs even in a short pilot trial like the one conducted in Helmond has a significant impact on preferences for AmBs in comparison with car, bus and bicycle alternatives. Hence, panel studies can provide a more comprehensive understanding of how attitudes and preferences of potential users evolve over time.

Original languageEnglish
Pages (from-to)335-344
Number of pages10
JournalTransportation Research Procedia
Volume78
DOIs
Publication statusPublished - 2024
Event25th Euro Working Group on Transportation Meeting, EWGT 2023 - Santander, Spain
Duration: 6 Sept 20238 Sept 2023

Keywords

  • automated minibus
  • ride experience
  • stated choice experiment

Fingerprint

Dive into the research topics of 'Ride experience in automated minibuses: measuring users' transport mode preferences before and after a test ride'. Together they form a unique fingerprint.

Cite this