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While intelligent transportation systems come in many shapes and sizes, arguably the most transformational realization will be the autonomous vehicle. As such vehicles become commercially available in the coming years, first on dedicated roads and specific conditions, and later on all public roads at all times, a phase transition will occur. Once sufficiently many autonomous vehicles are deployed, the opportunity for explicit coordination appears. This paper treats this challenging network control problem, which lies at the intersection of control theory, signal processing, and wireless communication. We provide an overview of the state of the art, while at the same time highlighting key research directions for the coming decades.

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Abstract-We study the problem of optimally controlling autonomous vehicles to safely cross an intersection. The problem is approached by solving an optimal control subproblem for all permutations of crossing sequences. For a chosen crossing sequence, we show that the subproblem of optimal longitudinal vehicle control, subject to collision avoidance constraints, can be formulated as a convex program. The proposed method transforms the problem from the original time domain to a space domain, and introduces a change of optimization variables by replacing vehicles' speed with its inverse. A case study is provided showing the effectiveness of the proposed method.