Abstract
E-Scooters are a popular new service that provide last mile transportation, but there are reports of safety concerns for riders and impingement on other users of rights of way. Little formal research has been conducted on E-Scooter safety or the optimal approach to deployment to decrease nuisance issues. To address this, VTTI and Spin deployed a fleet of E-Scooters on the Virginia Tech campus through an exclusive, controlled research program. Through on-scooter data acquisition systems, fixed infrastructure cameras, anecdotal injury reports, and surveys, data was collected to assess safety impact as well as to understand beneficial and problematic user behaviors and patterns for subsequent countermeasure development and deployment recommendations. The resulting naturalistic dataset includes over 9,000 miles of riding data. Overall, the E-Scooter deployment on the Virginia Tech campus was safer than other reported deployments. The operational constraints that were put in place were largely effective, and with the additional results from this study, some additional constraints and expanded outreach programs may make future deployments even safer. The campus community largely considered the deployment of E-Scooters a clean alternative transportation option and viewed the service favorably.
Project Highlights
- The data collection and analysis methods pioneered in this study resulted in the collection and annotation of a first-of-its-kind comprehensive e-scooter dataset using a unique onboard DAS with multiple kinematic sensors.
- Overall, the e-scooter deployment on the VT campus was well received, with 60% of survey respondents viewing the deployment as favorable to moderately favorable, and over 200,000 total e-scooter trips taken across all three phases of the deployment.
- Results from this study indicate that infrastructure-related factors, behavior of e-scooter riders and other actors, and environmental factors all contributed to the safety critical event risk for e-scooter riders in Virginia Tech’s pedestrian-dense campus environment.
Final Report
EWD & T2 Products
Doctoral Dissertation: Novotny, A. J. (2022). Improving E-Scooter Safety: Deployment Policy Recommendations, Design Optimization, and Training Development (Virginia Tech).
Student Impact Statement(pdf): Eight students (One PhD student, one Master’s Student and six Undergraduate students) received funding and/or worked under this project (Adam Novotny, Jingbin Xu, Victor Zimbardi, Kai Ji, Yumeng Li, Daniel Burdisso, Matthew Gyimesi, Tucker Dannon all Virginia Tech students). This file contains a statement by Adam Novotny as to the impact this project had on education and workforce development.
An overview of the program was provided during Career Day at Auburn Elementary School in Riner, Virginia, to an audience of about 100 second graders.
VTTI developed a new data acquisition system including a hardware and software package called the microDAS. The data collection system was disclosed to Virginia Tech’s Link License Launch group as an IP Disclosure.
Presentations/Publications
White, E. & Viray, R. (2022). Intelligent Transportation in the DMV. Tech on Tap Presentation.
White, E. (2022). Virginia Tech E-Scooter Program Overview. Presentation to Virginia Tech’s Personal Transportation Devices Workgroup.
White, E., Mollenhauer, M., Robinson, S., et al. (2023). What factors contribute to E-Scooter crashes: a first look using a naturalistic riding approach. Journal of Safety Research, 85. https://doi.org/10.1016/j.jsr.2023.02.002
Buehler, R., Broaddus, A., White, E., Sweeney, T., & Evans, C. (2022). An Exploration of the Decline in E-Scooter Ridership after the Introduction of Mandatory E-Scooter Parking Corrals on Virginia Tech’s Campus in Blacksburg, VA. Sustainability 2023, 15(1), 226; https://doi.org/10.3390/su15010226.
Buehler, R., Broaddus, A., Sweeney, T., Zhang, W., White, E.,& Mollenhauer, M. (2021). Changes in Travel Behavior, Attitudes, and Preferences among E-Scooter Riders and Non-Riders: Results from Pre and Post E-Scooter System Launch Surveys at Virginia Tech. Transportation Research Record Journal of the Transportation Research Board. http://dx.doi.org/10.1177/03611981211002213
Final Dataset
The final datasets for this project are located in the Safe-D Collection on the VTTI Dataverse; DOI: 10.15787/VTT1/0PNR4U.
Research Investigators (PI*)
Mike Mollenhauer (VTTI/VT)*
Elizabeth White (VTTI/VT)
Sarah Robinson (VTTI/VT)
Will Vaughan (VTTI/VT)
Adam Novotny (Student-VTTI/VT)
Project Information
Start Date: 2019-06-03
End Date: 2023-01-31
Status: Complete
Grant Number: 69A3551747115
Total Funding: $467,126
Source Organization: Safe-D National UTC
Project Number: VTTI-00-023
Safe-D Theme Areas
Transportation as a Service
Big Data Analytics
Safe-D Application Areas
Vulnerable Users
Performance Measures
Planning for Safety
Operations and Design
More Information
Sponsor Organization
Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States
Performing Organization
Virginia Polytechnic Institute and State University
Virginia Tech Transportation Institute
3500 Transportation Research Plaza
Blacksburg, Virginia 24061
USA