ADS-B and AOP Performance within a Multi-Aircraft Simulation for Distributed Air-Ground Traffic Management

Demand for use of the National Airspace System (NAS) is projected to triple in the next decade while its actual capacity will only increase by 30%. The Distributed Air Ground – Traffic Management concept (DAG-TM) is designed to improve system capacity and increase flexibility and efficiency for NAS users while maintaining or improving Federal Aviation Administration (FAA) mandated safety standards. To accomplish these goals, a collaborative decision making process has been developed that gives decision making authority to the most appropriate user: the flight crew, the air traffic service provider, or the airline dispatch. This process requires the sharing of information about flight intent, traffic, hazardous weather, and airspace restrictions. Automatic Dependence Surveillance Broadcast (ADS-B) is more accurate than radar and allows more data transfer over a larger coverage area than the Traffic Alert and Collision Avoidance System (TCAS). ADS-B is modeled in the DAG-TM concept as the primary data link between NAS users to facilitate their decision making process. Tools have been designed to aid flight crews and controllers using the information that ADS-B provides. In a joint research effort with NASA Ames, NASA Langley’s expertise is focused on flight deck operations. This includes both evaluation of human factors and the development of tools like the Autonomous Operations Planner (AOP) for the DAG-TM concept. A Joint Human-in-the-Loop Simulation involving teams at Langley and Ames, as well as subjects from various airlines and air traffic control facilities, provided extensive data. Two of our research interests focus on the performance of the ADS-B data link and AOP’s ability to assist the flight crew in successfully meeting separation assurance and traffic flow management requirements. Though ADS-B transmissions occur at constant rates, the number of messages encountered by any given receiver is dependent upon the number of aircraft in the vicinity and the range to the targeted aircraft. Previous studies have set broadcast rates to provide adequate information transfer, but the Joint Simulation provided a unique opportunity to model reception probability degradation with increasing traffic levels. We confirmed that as the traffic level increased, the reception probability decreased. Similar confirmation was found for an increasing probability of message collisions as traffic converged upon a metering fix. Several aspects of the AOP’s performance under analysis are the ability to effectively warn flight crews of conflicts and to provide reasonable and efficient solutions. Both human factors and performance metrics will be evaluated for the AOP. Conflict resolution time, seriousness of conflict level, and adherence to time and flight path constraints can help quantify AOP performance. Initial feedback from simulation participants indicates that the AOP exceeded expectations and can be improved for future implementation. Initials results indicate a high degree of precision for subject pilots using the AOP to meet required time of arrival (RTA) restrictions at traffic metering fixes as well as altitude and speed constraints. Causes for outlier cases were analyzed and In-Conformance trends compared between traffic levels do not show significant change, supporting the scalability characteristic of the DAG-TM concept. This interim analysis from the Joint Simulation will provide the basis for conclusions in the final feasibility report for the Enroute Operations Concept Element (CE-5) of the DAG-TM concept. In addition, the analysis is supporting several NASA technical reports and presentations.