Subject Area
Civil Engineering
Abstract
Rapid transportation advancements over the last several years have resulted in new personal mobility modes, such as shared micromobility (e.g., e-scooters, bikes, and e-bikes). These short-term rental vehicles expand transportation mobility by offering affordable, convenient, and efficient options that are easy to access. The rapid expansion of dockless micromobility systems presents major opportunities and challenges for cities, leading some to ban these services within their jurisdiction. To enhance the effectiveness of dockless shared micromobility services, address challenges created by these services, and achieve better implementation performance, cities need efficacious strategies to tackle major challenges. This dissertation contributes to the body of knowledge by improving shared micromobility system implementation and management, promoting safety and enhancing user behavior through route guidance, and exploring behavioral intentions toward autonomous micromobility systems.
First, this dissertation presents two techniques for analyzing areas of high parking demand and roadway segments with high micromobility vehicle demand. The proposed processes support efforts to assign free-floating parking, reduce vehicle clutter across cities, and assist transportation planners in identifying locations for road infrastructure improvement and ordinance enforcement. An unsupervised learning approach and analysis of vendor launching sites data is also used to appropriately locate dockless vehicle parking zones. Moreover, a comparison of three methods for identifying high-demand corridors is conducted. Two shortest path models are generated to predict trip paths for trip data without trajectories, considering rider route preferences and infrastructure types. Finally, a Simplified Matching Heuristic (SMH) that uses trip data with trajectories is developed to match trip trajectory data to the network street links, and applied in a case study in Dallas, TX.
Second, this dissertation develops the micromobility guidance tool (MGT) that guides a shared micromobility user going from a defined origin to a defined destination to a route that meets multiple criteria, including safety, comfort, and compliance. This tool emphasizes two network features, the type of infrastructure and the condition of infrastructure. Moreover, the tool locates shared micromobility parking that is closest to a user’s destination and sends alerts to avoid prohibited infrastructure types. For each trip, the proposed tool uses a shortest path routing algorithm to assign its route, and the Euclidean distance to assign closest parking. A generalized cost function was developed to estimate the time needed to cross a link while considering micromobility accessibility, user routing preferences, and ordinance restrictions. The effectiveness of MGT was tested through a case study of tens of thousands of dockless shared e-scooter trips within the City of Dallas, TX.
Third, this dissertation explores the potential use of shared autonomous micromobility systems (SAMS) as an effective solution to improper parking, clutter issues, and other challenges facing cities. Research on SAMS is still in its early development phases, and no study to date has investigated elements influencing their acceptance and adoption. This research proposes the shared autonomous micromobility systems acceptance model (SAMS-AM), an extended version of the Unified Theory of Acceptance and Use of Technology (UTAUT2), to examine the behavioral intention to utilize SAMS. The model examines psychological constructs, socio-demographic variables, transport-related variables, and city-related variables and their effects on the behavioral intention to use SAMS. An online survey was launched in four major US cities, and structural equation modeling used to analyze and test SAMS-AM. This dissertation provides, for the first time, a comprehensive investigation of user attitudes and variables determining SAMS adoption. Moreover, this dissertation offers micromobility service providers valuable guidance on how to successfully develop, advertise, and promote SAMS. Finally, this dissertation lays the groundwork for successfully integrating SAMS into urban transportation environments while ensuring alignment with user preferences and needs.
Degree Date
Spring 2024
Document Type
Dissertation
Degree Name
Ph.D.
Department
Civil and Environmental Engineering
Advisor
Janille Smith-Colin
Number of Pages
204
Format
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Recommended Citation
Zakhem, Myriam, "Toward Improved Shared Micromobility Implementation: A Data-Driven Approach to Overcome Challenges and Explore Next-Generation Acceptance" (2024). Civil and Environmental Engineering Theses and Dissertations. 34.
https://scholar.smu.edu/engineering_civil_etds/34
