Capacity Management in an Automated Shuttle Bus: Findings from a Lab Study

Driverless shuttles bear different and novel challenges for passengers. One of these is related to capacity management, as such shuttles are often smaller (usually from 6 to 12 seats) with limited capacities to (re-)assign seating, control reservations, or arrange travels for groups that exceed a shuttle’s capacity. Since a bus driver is missing, passengers need to resolve conflicts or uncertainties on their own, unless additional systems provide such support. In this paper, we present the results from a laboratory study, in which we investigated passenger needs in relation to booking and reserving spots (seats, standing spots, and strollers) in an automated shuttle. We found that such functionalities have a low-to-medium impact on an overall scale but could constitute exclusion criteria for more vulnerable parts of the population, such as older adults, families with small children, or physically impaired individuals.

[1]  Philip T. Kortum,et al.  Determining what individual SUS scores mean: adding an adjective rating scale , 2009 .

[2]  William Payre,et al.  What impressions do users have after a ride in an automated shuttle? An interview study , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[3]  Peter Fröhlich,et al.  User Interfaces for Public Transport Vehicles: Future Opportunities and Challenges , 2018, AutomotiveUI.

[4]  James T. Miller,et al.  An Empirical Evaluation of the System Usability Scale , 2008, Int. J. Hum. Comput. Interact..

[5]  H. Hecht,et al.  User acceptance of automated public transport , 2020 .

[6]  Keith Redmill,et al.  Smooth: improved short-distance mobility for a smarter city , 2017, SCOPE@CPSWeek.

[7]  J. D. Winter,et al.  Acceptance of Driverless Vehicles: Results from a Large Cross-National Questionnaire Study , 2018 .

[8]  Alexander G. Mirnig,et al.  Suppose your bus broke down and nobody came , 2020, Personal and Ubiquitous Computing.

[9]  Denis Lalanne,et al.  Pedestrians and Visual Signs of Intent , 2019, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

[10]  Manfred Tscheligi,et al.  Where Does It Go?: A Study on Visual On-Screen Designs for Exit Management in an Automated Shuttle Bus , 2019, AutomotiveUI.

[11]  Verena Distler,et al.  Acceptability and Acceptance of Autonomous Mobility on Demand: The Impact of an Immersive Experience , 2018, CHI.

[12]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[13]  Philipp Wintersberger,et al.  Man vs. Machine: Comparing a Fully Automated Bus Shuttle with a Manually Driven Group Taxi in a Field Study , 2018, AutomotiveUI.

[14]  Ching-Fu Chen Factors affecting the decision to use autonomous shuttle services: Evidence from a scooter-dominant urban context , 2019, Transportation Research Part F: Traffic Psychology and Behaviour.

[15]  Natasha Merat,et al.  User acceptance of automated shuttles in Berlin-Schöneberg: A questionnaire study , 2018, Transportation Research Part F: Traffic Psychology and Behaviour.