Date of Graduation

8-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Engineering (PhD)

Degree Level

Graduate

Department

Civil Engineering

Advisor/Mentor

Mitra, Suman K.

Committee Member

Braham, Andrew F.

Second Committee Member

Hernandez, Sarah V.

Third Committee Member

Nakarmi, Ukash

Keywords

Bike share; E-scooter; Equity; Shared micromobility; Transportation

Abstract

The rise of shared e-scooters has sparked a paradigm shift in urban transportation, offering a flexible mode of micromobility for short-distance travel. Since their US debut in September 2017, these electric scooters have gained popularity, surpassing traditional bikesharing services in many cities. This dissertation presents four studies that delve into various aspects of e-scooter adoption, from user behavior and pandemic effects to gender disparities and equitable access, providing comprehensive insights for urban mobility planning. The first study aims to determine (i) who uses shared e-scooters and why they use them, and (ii) what effects e-scooters have on the usage of other modes of transportation. The study analyzed the survey data from the 2018 Portland E-scooter Pilot Program. To accomplish the former part of the objective, the study identifies three user classes: Recreational Enthusiasts, Commute Riders, and Intermittent Joyriders, each exhibiting unique travel behaviors and motivations. Ordered logit models reveal insights into these groups' preferences and their impact on broader transportation modes, highlighting opportunities for targeted urban planning strategies Yet, the trajectory of e-scooters was abruptly disrupted by the unprecedented COVID-19 pandemic, causing global mobility constraints, social distancing measures, travel restrictions, and remote work protocols. These challenges cascaded across transportation sectors, impacting shared micromobility services like e-scooters, leading to operational suspensions and closures. In response, the second study examines the spatio-temporal effects of the COVID-19 pandemic on shared e-scooter usage by leveraging two years (2019 and 2020) of daily shared micromobility data from Austin, Texas. Employing a series of random effects spatial-autoregressive model with a spatially autocorrelated error (SAC), the second study examines the differences and similarities in determinants of e-scooter usage during regular and pandemic periods and identifies factors contributing to the changes in e-scooter use during the Pandemic. Spatial-autoregressive models reveal spatial dependencies and pandemic-induced changes, such as increased trip distances and altered usage patterns across different urban zones. These findings underscore the nuanced effects of spatial factors and policy responses on micromobility during crises. The third study addresses gender disparities in micromobility post-pandemic, leveraging the 2022 National Household Travel Survey data. A multi-group generalized structural equation modeling approach identifies demographic and environmental determinants of usage, highlighting generational differences and the influence of education and employment status. The study underscores the need for inclusive policies to support diverse commuting needs, particularly for women in smaller urban and rural areas. Furthermore, the pandemic-induced disruptions prompted the study to embrace a broader social consideration – ensuring equitable access to shared micromobility systems, particularly for low-income and disadvantaged populations. Recognizing the barriers faced by certain user groups, the fourth study expands the scope to equity in access across 508 shared micromobility systems in the US. Utilizing a K-prototype clustering algorithm, the study assesses financial, technical, and cultural barriers. Clustering analysis identifies distinct system types and barriers, emphasizing disparities faced by low-income and disadvantaged populations. This analysis offers a roadmap for policymakers and operators to enhance accessibility and foster equitable urban mobility solutions.

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