Scheduling and Motion Coordination of Autonomous Vehicles

This study focuses on developing an approach to solve the complex problem of task allocation and motion coordination simultaneously for a large fleet of autonomous vehicles in highly constrained operational environments. A Simultaneous Task Allocation and Motion Coordination approach is developed to solve the problem in a concurrent manner. Furthermore, a novel algorithm: Simultaneous Path and Motion Planning is proposed for collision free motion coordination based on Dijkstra and A * algorithms. The appropriateness of heuristic and evolutionary algorithms to solve the problem is investigated. A distributed computational architecture is also developed to improve the efficiency of implementation of the approach. The proposed approach is tested with static and dynamic environments, and validated by using data from an automated container terminal with fleet of autonomous straddle carriers.