q c UTSA School of Data Science researchers roll out new high tech e scooters

By combining the data taken from the scooters' onboard sensors with data collected from the users via surveys and their own smart devices, researchers in the ScooterLab can analyze where and when the scooters are ridden, who is riding them and how scooter usage varies based on different population segments. The ScooterLab testbed could even offer the potential to help researchers better understand traffic and road conditions and explore how scooters fit into the larger urban mobility infrastructure by analyzing how far riders walk before and after their scooter trips and whether they utilize public transit, ride sharing or private vehicles.

"The possibilities for this infrastructure are endless," Jadliwala said. "We aim to provide data which can be used for solving rider and pedestrian safety challenges, urban routing and infrastructure planning challenges, engineering and machine learning."

Since the initial brainstorming session in 2020, the team has overcome numerous challenges to make their scooters work. In many cases, it has been necessary to design many hardware and software elements in-house. These include the software that stores the raw data, the research portal that allows external researchers to access the data and the 3D-printed, weather-resistant enclosure that protects the delicate innards of the ScooterLab WBSC/sensor box.

"Rolling out the first scooters is the result of a lot of hard work and dedication from the entire ScooterLab team," said Raveen Wijewickrama, ScooterLab's vehicle and sensing development lead. "We're thrilled to have reached this milestone, especially after overcoming numerous challenges along the way."

Now the team faces new sets of challenges, including distributing the scooters to students at UTSA's Main and Downtown Campuses, finding room to store and maintain the scooters and hiring student workers to check those scooters in and out. However, Wijewickrama believes the benefits to science and the San Antonio community more than make up for hard work.

"Advancing science while working on this is a huge motivation," he said. "Another exciting aspect is providing a novel testbed and a dataset for the community, something that will contribute to research and practical solutions in the future."

Such solutions are both immediate and far-reaching. Students will now have free access to the ScooterLab e-scooters, enabling them to scoot around Main and Downtown Campuses quickly and easily. Down the road, the team hopes that the data these scooter trips provide will lead to improvements in city planning and transportation development, advancing the fields of data science and machine learning as a whole.

"It's incredibly rewarding to see the infrastructure we've built serve a dual purpose, benefiting the community while contributing to scientific progress," Wijewickrama said. "This is just the start of something much bigger, and we're excited for what's ahead."

What's ahead, specifically, is expanding the ScooterLab. The team intends to scale up the deployment of its e-scooters to accommodate more users over a larger area. It also plans to increase its community-engagement efforts by encouraging user feedback and strengthening research to ensure that the ScooterLab testbed meets the needs of the research community. Finally, the ScooterLab team hopes to invite researchers from various fields to use the testbed for their own projects, enhancing interdisciplinary collaboration to advance the field of data science even further.

This sense of community within the field is an essential element of the ScooterLab, says Jadliwala, who extends his thanks to the many champions of the project within UTSA, the School of Data Science, the National Science Foundation and beyond.