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We consider a class of optimal control problems for measure-valued nonlineartransport equations describing traffic flow problems on networks. The objectiveisto minimise/maximise macroscopic quantities, such as traffic volume oraverage speed,controlling few agents, for example smart traffic lights andautomated cars. The measuretheoretic approach allows to study in a same settinglocal and nonlocal drivers interactionsand to consider the control variables asadditional measures interacting with the driversdistribution. We also propose agradient descent adjoint-based optimization method, ob-tained by derivingfirst-order optimality conditions for the control problem, and we providesomenumerical experiments in the case of smart traffic lights for a 2-1 junction.

A measure theoretic approach to traffic flow optimization on networks