Revitalizing Baltimore's Transportation Network: A Multi-Layered Modeling Approach for Stakeholder-Centric Optimization

The traffic network in Baltimore, Maryland, is plagued by aging road infrastructure, low levels of alternative transport modes, and the collapse of the Francis Scott Key Bridge, cutting off major traffic arteries and exacerbating commuting challenges. In resolving these issues, Ant Colony Optimization (ACO) founded on biological principles has been introduced in this research as a computational paradigm for traffic optimization in cities. In addition, this paper constructs a road network model, formulates traffic flow optimization as a shortest path problem, and employs ACO in dynamically routing traffic on the basis of pheromone updates. Simulations have been performed to examine high-load road sections. The proposed ACO model successfully identified 176 high-load edges and optimized routes of vehicles, reducing average path lengths by 31% with collapse. A traffic flow optimization model founded on an ant colony algorithm is an efficient and flexible traffic planning mechanism for cities. In future research, responsiveness can be improved with real-time information integration.