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This paper analyzes how the presence of service stations on highways affectstraffic congestion. We focus on the problem of optimally designing a servicestation to achieve beneficial effects in terms of total traffic congestion andpeak traffic reduction. Microsimulators cannot be used for this task due totheir computational inefficiency. We propose a genetic algorithm based on therecently proposed CTMs, that efficiently describes the dynamics of a servicestation. Then, we leverage the algorithm to train a neural network capable ofsolving the same problem, avoiding implementing the CTMs. Finally, we examinetwo case studies to validate the capabilities and performance of ouralgorithms. In these simulations, we use real data extracted from Dutchhighways.

Optimal service station design for traffic mitigation via genetic algorithm and neural network