Data-driven transportation research for safer, more reliable, more accessible, and sustainable mobility.
Our research spans multiple interconnected areas of transportation engineering, combining civil infrastructure expertise with modern analytics and sociotechnical intelligence.
We apply machine learning models for prediction, classification, and optimization in transportation planning and infrastructure management.
We develop and apply advanced forecasting models — including trip generation, distribution, and assignment — to support infrastructure planning and investment policy analysis.
We assess environmental impacts using life-cycle analysis to inform sustainable transportation policies and infrastructure decisions.
We develop ITS solutions using sensors, connected vehicles, and real-time analytics to improve traffic operations.
We analyze pavement performance, deterioration mechanisms, maintenance strategies, and sustainable materials to support infrastructure and sustainable road infrastructure.
We study how individuals make travel decisions, examining mobility patterns, mode preferences, and behavioral responses to policy interventions through survey-based and data-driven methods.
Our work evaluates accessibility and travel reliability to support equitable and dependable transportation systems.
We investigate crash patterns, risk factors, and safety interventions using statistical modeling and predictive analytics.
Our research explores EV adoption, charging infrastructure, and energy impacts for sustainable mobility transitions.
An overview of TSU’s academic research activities and professional consultancy engagements in transportation engineering, planning, and sustainable mobility.
A practical toolbox for transportation research.
TSU is always looking for strong, self-motivated, and hardworking research students and collaborators. If you are interested in joining or collaborating with us, please submit your CV and a short personal description with your research interest to tsu-cee@sust.edu.
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