An iterative vehicle re-routing algorithm based on incremental traffic flow adjustment for congestion mitigation

Traffic congestion is a critical issue due to its significant economic, environmental and social impact. In this context, route guidance systems that incorporate ITS technologies play a key role in efficiently redistributing traffic and alleviating congestion. This study proposes an innovative re-routing strategy based on the integration of variable message signs (VMSs) to optimize traffic flows. At the core of the approach is a mathematical model that minimizes congestion by considering path flows as decision variables. To solve this formulation, we developed an iterative algorithm that returns diversion rates at VMS locations. The algorithm combines targeted re-routing with the user equilibrium (UE) framework, ensuring that individual route choices are coherently integrated into a system-wide optimization process. A real-world case study on the Salerno road network (Italy) demonstrates the practical applicability and effectiveness of the methodology. Results show that the proposed strategy improves traffic efficiency and works as a valuable decision support tool for managing planned interventions and assessing multiple operational scenarios. • An innovative VMS-based re-routing approach for traffic flow optimization. • A mathematical model for congestion reduction based on path-flow variables. • An iterative algorithm combining re-routing at VMS nodes with User Equilibrium. • A real-world case study demonstrating improved network performance.