Keywords

Cloud Migration; TSM&O; Decision-Support Framework; Cloud Suitability Assessment; Fuzzy Logic; Intelligent Transportation Systems

Abstract

As the Florida Department of Transportation (FDOT) advances its cloud first strategy, Transportation Systems Management and Operations (TSM&O) programs are taking a proactive role in evaluating which applications are appropriate for cloud or hybrid deployments. Although cloud platforms offer scalability, reliability, and cost efficiencies, migration decisions are complex and must account for mission criticality, latency, security, and compliance. However, transportation agencies often lack a structured approach to evaluate these characteristics across diverse applications. This study presents a modular cloud migration evaluation framework designed specifically for TSM&O applications. The framework uses an eight-module questionnaire that examines business alignment, technology compatibility, and security considerations, among other readiness factors. Module scores are normalized and aggregated using a fuzzy logic-based recommendation engine to generate an overall cloud suitability percentage. The framework is implemented through a user-friendly web-based application with role-based access levels that automates scoring and generates final suitability recommendations. To evaluate the framework’s practical performance, three transportation applications were selected, and one application received end-user validation with FDOT staff and Aimsun representatives. End users provided estimates of expected cloud suitability scores prior to completing the framework assessment, enabling a direct comparison between their estimates and the framework-generated results. While several modules demonstrated strong alignment with expert expectations, some modules presented discrepancies. These differences highlight opportunities to refine question design, granularity of response options, and module weightings. Because the scoring algorithm is modular and adjustable, refinements can easily be implemented to reduce variance between generated and expected output. The results of this study demonstrate that the framework provides transportation agencies with a structured and measurable approach to cloud migration decision-making while remaining flexible enough to be refined without structural redesign. To the best of my knowledge, this is the first framework designed specifically to evaluate cloud suitability of TSM&O applications in transportation agencies.

Thesis Completion Year

2026

Thesis Completion Semester

Spring

Thesis Chair

Agarwal, Shaurya

College

College of Engineering and Computer Science

Department

Civil, Environmental, and Construction Engineering

Thesis Discipline

Computer Science

Language

English

Access Status

Campus Access

Length of Campus Access

1 year

Campus Location

Orlando (Main) Campus

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Restricted to the UCF community until 5-15-2027; it will then be open access.

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Rights Statement

In Copyright