Transportation Planning Prediction Based on Graph Theory: A Case Study of Baltimore

This paper leverages network modeling and optimization to address traffic challenges in Baltimore. A transportation network model, using dynamic network flow, assesses the Francis Scott Key Bridge collapse, minimizing travel costs and balancing stakeholder burdens. Results show disrupted traffic, longer commutes, and negative impacts on residents and businesses, mitigated by reconstruction and traffic controls. An optimization model for Bus Rapid Transit (BRT) dedicated lanes along Potee St. to Patapsco Ave. reduces commuting time by 20% and boosts bus coverage by 25%-35%. A proposed light rail extension cuts commuting time by 30%-50% and private car use by 15%-20%, benefiting businesses and tourism. Simulations and data analysis validate these solutions, offering insights for Baltimore and beyond.