A dynamic saturation rate extension to the multi-commodity store-and-forward model is reformulated as an efficient MILP that outperforms prior multi-commodity approaches in mixed CAV-HDV traffic simulations.
Parallel computational optimization in operations re- search: A new integrative framework, literature review and research directions
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Efficient MILP-based Urban Network Traffic Control in Mixed Autonomy with Dynamic Saturation Rates
A dynamic saturation rate extension to the multi-commodity store-and-forward model is reformulated as an efficient MILP that outperforms prior multi-commodity approaches in mixed CAV-HDV traffic simulations.