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Dynamic Resource Allocation for Efficient Sharing of Services from Heterogeneous Autonomous Vehicles

Abstract

A novel dynamic resource allocation model is introduced for efficient sharing of services provided by ad hoc assemblies of heterogeneous autonomous vehicles. A key contribution is the provision of capability to dynamically select sensors and platforms within constraints imposed by time dependencies, refueling, and transportation services. The problem is modeled as a connected network of nodes and formulated as an integer linear program. Solution fitness is prioritized over computation time. Simulation results of an illustrative scenario are used to demonstrate the ability of the model to plan for sensor selection, refueling, collaboration, and cooperation between heterogeneous resources. Prioritization of operational cost leads to missions that use cheaper resources but take longer to complete. Prioritization of completion time leads to shorter missions at the expense of increased overall resource cost. Missions can be successfully replanned through dynamic reallocation of new requests during a mission. Monte Carlo studies on systems of increasing complexity show that good solutions can be obtained using low time resolutions, with small time windows at a relatively low computational cost. In comparison with other approaches, the developed integer linear program model provides best solutions at the expense of longer computation time

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