Real-Time Planning for Multiple Autonomous Vehicles in Dynamic Uncertain Environments

This paper introduces a market-based cooperative planning system for a team of autonomous vehicles operating in a dynamic environment. The system combines the flexibility of evolution-computation techniques with the distributed nature of market strategy to compute task and paths plans. Optimization is based on a team utility function which accounts for uncertainty in knowledge of the environment. Multiple vehicles will cooperate on the same task if doing so increases the predicted team utility value. The team utility function and the associated stochastic model that predicts future system states are described. The minimum required information exchange among the vehicles is identified. Simulation results, using the Boeing Company developed Open Experimental Platform, demonstrate the effectiveness of the planning.