Reasearch On Situation Awareness For Unmanned Surface Vehicles

Situation awareness is a soar part in an adjustable autonomy system for Unmanned Surface Vehicles (USV). USV performs special tasks in a complex environment, with these constraints, completely out of people's supervision and control to achieve full independence is unrealistic. We can make system have an adjustable autonomy and provide human intervention timely and appropriatly, improve the reliability and credibility of system. System has an adjustable autonomy has been an inevitable trend. As USV may encounteres unexpected events when it is performing the tasks in the complex marine environment. Therefore assessing the current situations timely and accuratly plays a curcial role for improving the system's adjustable autonomy. This paper studies the method of situation awareness for unmanned surface platform in adjustable autonomy system. The main work accomplished concretely follows:The thesis first briefly introduces the research situation of awareness situation of USV, it studies the functions for situaiton awareness. A three-level functional processing model, which is consist of event detection, threat assessment and impact prediction, is set up and each level is analyzed in detail. Based on analyzing the types of events, the fuzzy logic method for event detection is discussed. Threat assessment is an important part in the situaiton awareness, the bayesian network method for threat assessment is proposed. In the context of the obstacle avoidance task, monitor of the various tasks, assess the current situations, detecte the impact between mission and capacities of USV.Finally, In the context of the obstacle avoidance task, focuses on the discussion and verification for situation awareness, an USV situation awareness is built by simulation, it verifies the feasibility and effectiveness of above approaches.