ScooterLab is a National Science Foundation (NSF)
funded community research infrastructure
initiative, currently under development at the University of Texas at San Antonio (UTSA).
This publicly-available micromobility testbed and crowd-sensing infrastructure will provide
researchers with highly customizable access to a fully operational fleet of dockless e-scooters,
retrofitted with state-of-the-art sensors, and a community of riders, including data
sensed/collected from (and during) their rides. Data collected from the various experiments
on this testbed is expected to support and enable research in a variety of areas including,
but not limited to, Machine Learning & AI, High Performance Computing, Security and Privacy,
Urban Planning and Policy and Civil and Transportation Engineering. As part of the planning
activity related to the development of this testbed, we are organizing a workshop/summit
involving community researchers in order to get feedback on the critical requirements of the
primary stakeholders of this testbed, and to identify the main roadblocks and challenges related
to the development, deployment and usage of such a community research infrastructure.
Theme #1 - Engineering, development, and deployment.
The ScooterLab testbed’s foundation will be based upon a fleet of e-scooters.
Discussion under this theme will cover topics such as challenges in engineering,
development, and deployment of these e-scooters. For example, challenges in enforcing
area of operation, sensing hardware, and software integration.
Theme #2 - Customizable data collection and research enabled.
The research community can utilize ScooterLab in two ways: (i) researchers may
request specific deployment settings in order to collect data that can help test
their research hypotheses, (ii) researchers may use already published data
(from prior deployments) to test their research hypotheses. One of the goals of this
theme is to preconceive some of the research directions that the community is looking
forward to. Discussion under this theme will cover variable testbed settings such as
custom sensing hardware, scheduling, area of operation, ride pricing, and more.
Discussion will also cover IRB requirements pertaining to guest researchers’ deployment settings.
Theme #3 - Research data publication best practices.
Data collected from ScooterLab testbed will be rich of sensory and actuation data.
Under this theme, the research community will be engaged in discussing the best
practices for data publication. One of the most important discussion points will
be on how to preserve riders’ privacy (such as identity and location privacy) without
affecting the research utility of the data.
Theme #4 - Data analysis and visualization.
In addition to data publication, ScooterLab will also support fundamental data
analysis and visualization tools. Discussion under this theme will be to ideate
the most useful set of analysis and visualization tools that ScooterLab should
offer to the research community. For accessibility, these analysis and visualization
tools will most likely be delivered over a web interface.