All ETDs from UAB

Advisor(s)

Virginia P Sisiopiku

Committee Member(s)

Da Yan
Leon Jololian
Michael Anderson
Muhammad M Sherif

School

School of Engineering

Document Type

Dissertation

Department (new version)

Civil Engineering

Date of Award

9-9-2024

Abstract

The growing prevalence of micromobility has significantly impacted urban mo-‎bility, offering a sustainable and convenient alternative for short trips in urban settings. ‎As cities grapple with increasing congestion, pollution, and the demand for efficient ‎mobility solutions, micromobility options like e-scooters and e-bikes have emerged as ‎popular modes of transportation, particularly in densely populated areas. While earlier ‎research has contributed to understanding micromobility and its impact on urban set-‎tings, significant knowledge gaps still exist. Therefore, a comprehensive study is neces-‎sary to explore the multifaceted dimensions of e-scooter adoption, usage patterns of mi-‎cromobility, and their implications for urban transportation systems and traffic opera-‎tions to bridge the knowledge gaps related to this emerging mode.‎ First, this study employed a meta-analysis of survey data combined with ma-‎chine learning (ML) and SHapley Additive exPlanations (SHAP) analysis to investigate ‎and compare e-scooter user and non-user attitudes towards shared e-scooter use in ‎Washington, D.C., Miami, FL, and Los Angeles, CA. Factor analysis and the Kruskal-‎Wallis test complemented the survey analysis. The study then utilized Birmingham, AL, ‎as a case study, and employed space-time pattern mining techniques and Kernel Density ‎methods to analyze spatiotemporal demand variations and correlations between micro-‎mobility ridership, demographic characteristics, and land use patterns using clustering ‎approaches and a multilevel negative binomial model. Finally, the study employed the ‎Multi-Agent Transport Simulation (MATSim) platform to evaluate the impact of differ-‎ent shared e-scooter fleet sizes on transportation mode selection in the presence of a va-‎riety of transportation modes, including private automobiles, transit, walking, and ‎shared e-scooters. The integration of shared e-scooter trips into the comprehensive ‎MATSim traffic simulation model of the Birmingham region allowed to assess patterns ‎of e-scooter trips and their impact on local traffic operations.‎ Key findings from this comprehensive study revealed that e-scooter users were ‎predominantly aged 25 to 39, male, with higher income and education levels, and most ‎possessed a driver's license. Employment status, car ownership, and attitudes towards ‎car and technology usage significantly influenced e-scooter adoption. Additionally, this ‎study identified peak usage of e-scooters in Birmingham, AL, on weekends, during af-‎ternoon and evening hours, and in warmer months, with high-density trip origins in are-‎as such as Railroad Park and the University of Alabama at Birmingham (UAB) campus. ‎Analysis of demographic characteristics in Birmingham showed positive associations ‎between micromobility ridership and younger populations, presence of park areas, ‎commercial and residential land uses, and walkability, while increased distance from ‎the city center reduced ridership. The study also found significant seasonal trends and ‎clustering of e-scooter trips near leisure hubs, with minimal impacts on traffic opera-‎tions despite some modal shifts.‎ These studies performed and documented in this dissertation collectively con-‎tributed to a deeper understanding of shared e-scooter usage dynamics, offering strate-‎gic insights for enhancing urban mobility through effective micromobility integration. ‎The findings are expected to inform researchers, practitioners, providers, and decision ‎makers involved in urban transportation planning, policy development, and resource ‎allocation, and assist them toward promoting sustainable and efficient urban mobility ‎solutions.‎

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