1. ScooterLab: Let’s think about our future
Dr. Greg Griffin, AICP
https://scooterlab.utsa.edu/
Think Science, 12Sept2023

2. Murtuza Jadliwala
(overall lead)
Sushil Prasad
Raveen Wijewickrama
Buddhi Ashan Mallika
Kankanamalage
Greg Griffin
Nico Molina
Anindya Maiti
Khoi Trinh
Acknowledgements
Investigators & Students
Research Collaborators

3. Origin—Street Noise & Bicycling Safety Correlated in
Washington, D.C., but not in Austin
Griffin, G. P., Hankey, S., Buehler, R., Dai, B., Le, H. T., & Simek, C.
(2019). Exploring Street Noise and Bicycle Safety: Initial Evidence from
Austin, TX and the Washington, DC Capital Area (No. 19-03944).

4. Origin—Crowdsensing Pedestrian Safety and E-scooters
Maiti, A., Vinayaga-Sureshkanth, N., Jadliwala, M.,
Wijewickrama, R., & Griffin, G. (2022, March). Impact of
e-scooters on pedestrian safety: A field study using
pedestrian crowd-sensing. In PerCom Workshops (pp.
799-805). IEEE.

5. Origin—Shared Micromobility Can Reduce Vehicle Traffic,
but not only e-scooters
Choi, K., Park, H. J., & Griffin, G. P. (2023).
Can shared micromobility replace auto travel?
Evidence from the US urbanized areas
between 2012 and 2019. International Journal
of Sustainable Transportation, 1-9.

6. What Now?
Do e-scooter rental term
lengths change travel
patterns?
Can machine
learning support
urban policy making?
What type of street-level features
may increase e-scooter crash risks?

7. How is ScooterLab different?
The ScooterLab testbed is envisioned as an instrument for the entire research
community—not just local teams.
Downtown + suburban contexts
No private company data agreements
Community data privacy and sharing platform

8. ScooterLab Operation
8

9. The ScooterLab Architecture
The ScooterLab testbed will
comprise of:
• Vehicles
• Fleet Controller
• Research Activities Management
Portal (RAMP)

10. Demo
10

11. Raw Data
• Accelerometer
11

12. Raw Data
• Gyroscope
12

13. Raw Data
• Orientation (via Accelerometer)
13
*No scooters or riders wereharmed in obtaining this data.

14. Raw Data
• Temperature
14

15. Raw Data
• GPS – Speed
15

16. Raw Data
• GPS – Route
16

17. Raw Data
• Camera
17

20. ScooterLab is building a new urban sensing
platform for improving cities.
Multi-disciplinary challenges require collaboration and sharing.
C O N T R I B U T I O N

21. Data science cannot solve all urban challenges
Urban planning addresses wicked problems with inclusiveness,
policy, design, and financing.
H O W E V E R

22. ScooterLab: Let’s think about our future
Dr. Greg Griffin, AICP
https://scooterlab.utsa.edu/
Think Science, 12Sept2023