All ETDs from UAB

Advisory Committee Chair

Virginia P Sisiopiku

Advisory Committee Members

Akhlaque Haque

Andrew Sullivan

Document Type


Date of Award


Degree Name by School

Master of Civil Engineering (MCE) School of Engineering


The topic of shared micromobility has gained significant attention in the field of transportation engineering, exhibiting a significant rise in prominence in recent times. Micromobility’s inherent attributes of user-friendliness, ubiquitous accessibility, convenience, and cost-effectiveness have drawn considerable attention from individuals. In addition, the eco-friendly attributes of diverse shared micromobility modes encourage individuals to adopt them for short commutes. VEO emerged in Birmingham, Alabama in 2021 as a new participant in the dynamic landscape of shared micromobility, offering shared e-scooters and e-bikes. Similar to other medium-sized cities, the VEO pilot program in Birmingham captured the attention and participation of local travelers., however, its impact on local traffic operations is not understood. Moreover, questions remain about the types of trips attracted by shared micromobility modes, usage patterns, and temporal trends. To bridge these knowledge gaps, this study examined shared micromobility usage and associated travel patterns in Birmingham, Alabama using field data obtained from VEO trip records in 2021-2022. After the VEO e-scooter and e-bike data were processed to remove incomplete and inaccurate records, ArcGIS maps were used to showcase trip origins and destinations. To gain further understanding of mircomobility travel patterns, iv zip code and block group densities were calculated. The analysis of the data showed that only 23% of Birmingham micromobility users chose shared e-bikes, while the rest used shared e-scooters, indicating a strong user preference for shared e-scooters over shared e-bikes. Additionally, the research findings indicated that the highest utilization rates of shared e-scooters and e-bikes were observed during nighttime periods and weekends. It was also noticed that the usage of shared micromobility modes was the highest in the fall and spring seasons. These findings suggest that travelers’ mode choice related to the use of micromobility modes is influenced by weather and environmental factors. To better understand the determinants of micromobility mode choice, two negative binomial regression models were constructed with the aim of forecasting forthcoming rates of shared e-scooter and e-bike trips respectively. The models incorporated a range of independent variables, including trip distance, duration, time, day, month, and season. Through the examination of these variables, the models sought to offer insights into the determinants that impact shared micromobility trip rates in Birmingham. The models showed that coefficient values of summer and spring seasons as well as time periods from 3 PM to 6 PM and 6 PM to 9 PM affect both shared e-scooter and e-bike use the most out of all the variables of the model. This implies that such factors play a crucial role in determining the demand and use of shared micro-mobility options in the study area. Additionally, the high R square values of these models (0.81 for the e-scooter and 0.86 for the e-bike model) suggest that the models provide a good fit to the observed data and offer reliable insights into the factors influencing the adoption and utilization of these modes of transportation. v Overall, the present study offers valuable contributions to the understanding of the role of shared e-scooters and e-bikes in Birmingham's transportation landscape. Specifically, the study sheds light on the trip characteristics, usage patterns, and temporal trends associated with these modes of transportation, providing valuable insights into their past usage and future prospects.

Available for download on Monday, September 01, 2025

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