Sustainable Traffic Flow Optimization in Urban Infrastructure: Mitigating Congestion Through Dynamic Signal Control Systems

Pat Hill; Avery Martin; Ashley Gonzalez; Pat Anderson

Authors

Pat Hill PhD
Avery Martin Associate Professor
Ashley Gonzalez Professor
Pat Anderson Dr. Sc

Keywords:

Dynamic Signal Control Systems, Urban Traffic Management, Traffic Flow Optimization, Real-Time Data Analytics, Sustainable Transportation, Congestion Mitigation, Traffic Simulation, Urban Infrastructure

Abstract

The global challenge of urban traffic congestion remains a pressing issue, exacerbating travel times and increasing vehicle emissions. This study introduces a novel methodology for optimizing traffic flow using dynamic signal control systems (DSCS) informed by real-time traffic data analytics. Employing a mixed-methods approach, we conducted empirical simulations in a controlled urban environment, utilizing MATLAB R2022b for algorithm development and Python 3.9 for data analysis. Our findings indicate a significant reduction in average vehicle delay by 27% and a 15% decrease in traffic volume during peak hours when DSCS is employed compared to conventional fixed signal timings. The results validate the effectiveness of integrating adaptive control mechanisms in urban traffic management systems, underscoring the need for cities to invest in and implement such technologies for enhanced mobility. This research provides actionable insights for policymakers and urban planners in addressing the multi-faceted issues associated with urban transportation systems.

Author Biographies

Pat Hill, PhD

PhD
University of California, Berkeley
Berkeley, CA 94720

Avery Martin, Associate Professor

Associate Professor
Technische Universität München
Arcisstraße 21, 80333 München, Germany

Ashley Gonzalez, Professor

Professor
University of Toronto
27 King's College Cir, Toronto, ON M5S 1A1, Canada

Pat Anderson, Dr. Sc

Dr. Sc
University of Sydney
Camperdown NSW 2006, Australia

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