Akademik Veri Yönetim Sistemi
APPLIED SCIENCES, cilt.14, sa.13, ss.1-22, 2024 (SCI-Expanded)
Abstract: This research introduces the Urban Traffic Mobility Optimization Model (UTMOM),
a data-driven methodology for analyzing two distinctive urban traffic datasets through the integration of data mining and mathematical modeling. Designed to decode the complexities of urban
mobility patterns, UTMOM meticulously evaluates daily traffic dynamics with a focus on reducing
discrepancies and underscoring variations in traffic intensity, particularly during peak times. Our
findings unveil pivotal insights into the differences across datasets, providing a substantial contribution to the realms of traffic management and urban planning. UTMOM delves into the intricacies of
traffic flow variations, emphasizing the critical importance of comprehending fluctuations in traffic
volume across diverse times and locations. By incorporating detailed graphical representations and
statistical validations, including ANOVA analysis, our study delivers a comprehensive evaluation
of UTMOM’s precision in reflecting real-world traffic scenarios. These insights affirm the value
of data-informed strategies in optimizing traffic flow and alleviating congestion. Positioned as
a valuable asset for traffic engineers, data scientists, and urban planners, UTMOM advocates for
advanced modeling techniques to improve urban mobility. Beyond enriching academic discourse on
traffic analysis, UTMOM offers actionable intelligence for enhancing the efficiency and sustainability
of urban transportation systems. Through this in-depth investigation, our aim is to catalyze the
development of innovative solutions to traffic challenges, steering towards smoother and more
sustainable urban environments.