Our goal for this project is to create an enabling technology for ATM+3 operations that significantly improves traffic and intent awareness for human participants without workload increases during NextGen+3 traffic load. This technology will demonstrate how IAS could enhance the safety and efficiency of civil aviation and increase acceptance of autonomy in civil aviation.

Our technical approach is to use a system which adaptively takes in datalink communication and path planning/intent/state data from all aircraft within reception and parses the information to extract concisely and succinctly only that relevant to the pilot. This IAS transforms precise messaging for human awareness, via appropriate multi-modal cueing senses, including the use of 3D audio and audio tagging. The IAS is adaptive learning from user input and contextual data via machine learning algorithms.