A Distributed Gradient Approach for System Optimal Dynamic Traffic Assignment

This study presents a distributed gradient-based approach to solve system optimal dynamic traffic assignment (SODTA) formulated based on the cell transmission model. The algorithm distributes SODTA into local sub-problems, who find values for their decision variables within an intersection. Each sub-problem communicates with its immediate neighbors reach consensus of common variables. A receives proposed from all adjacent sub-problems and incorporates them own offered by weighted averaging enforcing gradient step minimize objective function. Then, updated are projected onto feasible region sub-problems. finds high quality solutions in tested scenarios finite number iterations. is case network under different demand levels at most 5% optimality gap.