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Unmanned air vehicles have recently attracted attention of many researchers because of their potential civil applications. A systematic integration of unmanned air vehicles in non-segregated airspace is required that allows safe operation of unmanned air vehicles along with other manned aircrafts. One of the critical issues is conflict detection and resolution. This article proposes to solve unmanned air vehicles’ conflict detection and resolution problem in metropolis airspace. First, the structure of metropolis airspace in the coming future is studied, and the airspace conflict problem between different unmanned air vehicles is analyzed by velocity obstacle theory. Second, a conflict detection and resolution framework in metropolis is proposed, and factors that have influences on conflict-free solutions are discussed. Third, the multi-unmanned air vehicle conflict resolution problem is formalized as a nonlinear optimization problem with the aim of minimizing overall conflict resolution consumption. The safe separation constraint is further discussed to improve the computation efficiency. When the speeds of conflict-involved unmanned air vehicles are equal, the nonlinear safe separation constraint is transformed into linear constraints. The problem is solved by mixed integer convex programming. When unmanned air vehicles are with unequal speeds, we propose to solve the nonlinear optimization problem by stochastic parallel gradient descent–based method. Our approaches are demonstrated in computational examples

Cooperative conflict detection and resolution of civil unmanned aerial vehicles in metropolis