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This study develops the headway control framework in a fully automated roadnetwork, as we believe headway of Automated Vehicles (AVs) is anotherinfluencing factor to traffic dynamics in addition to conventional vehiclebehaviors (e.g. route and departure time choices). Specifically, we aim tosearch for the optimal time headway between AVs on each link that achieves thenetwork-wide system optimal dynamic traffic assignment (SO-DTA). To this end,the headway-dependent fundamental diagram (HFD) and headway-dependent doublequeue model (HDQ) are developed to model the effect of dynamic headway onroads, and a dynamic network model is built. It is rigorously proved that theminimum headway could always achieve SO-DTA, yet the optimal headway isnon-unique. Motivated by these two findings, this study defines a novel conceptof maximin headway, which is the largest headway that still achieves SO-DTA inthe network. Mathematical properties regarding maximin headway are analyzed andan efficient solution algorithm is developed. Numerical experiments on both asmall and large network verify the effectiveness of the maximin headway controlframework as well as the properties of maximin headway. This study sheds lighton deriving the desired solution among the non-unique solutions in SO-DTA andprovides implications regarding the safety margin of AVs under SO-DTA.

Maximin Headway Control of Automated Vehicles for System Optimal Dynamic Traffic Assignment in General Networks