UC Berkeley

The Airspace Flow Program (AFP) is a traffic management initiative that aims to mitigate delays arising from en route capacity constraints, by holding flights on the ground and metering their flow through constrained regions. It has been successful in controlling traffic with reasonable delays, but the procedures must be improved upon to handle future projected demands. This dissertation explores a future AFP concept that incorporates structured user preference inputs in a centrally-managed assignment of ground delays as well as reroutes. However, the commercial aviation industry is very competitive, and airlines are reticent to share detailed operational information without clear benefits in return. This idea must be taken into consideration when designing flight resource assignment strategies, as we address a very fundamental question in transportation service provision: how does a central authority allocate resources efficiently when they are uncertain about what users want?

A modeling framework was developed to evaluate and compare allocation strategies, under differing assumptions regarding the information that traffic managers may (or may not) have about airline flight costs. We introduce several resource allocation strategies that feature different allocation rules and route preference inputs requested of flight operators. We assess the total user-cost impact of each allocation strategy through a simple generalized cost function that represents the cost of delay for each flight caught in the AFP. This flight cost function consists of two parts: the first is a simple representation of operator flight cost characteristics that the traffic managers have adopted, while the second consists of a flight's routing preferences that are not captured by the first, and therefore are privately known to each flight's operator but not to traffic managers unless the information is offered. In one allocation strategy, users are asked to provide their private information in exchange for the employment of a resource allocation rule that rewards flights for early submission. In another, users are not asked to provide their proprietary information but are not offered the same "guarantee" regarding resource allocations, i.e. flights have less idea about what resources they will receive in the allocation. We identify some basic properties about the relationships of the assignment schemes' total flight cost efficiency results, under changing assumptions about the quality of the central decision maker's knowledge about the flight operators' route preferences. Numerical examples illustrate situations where sacrificing a system-optimal allocation rule for a sequential one (First Submitted, First Assigned, or FSFA), in order to obtain and utilize flight operators' private information about route preferences, will result in more user cost efficient resource allocations. The examples also illustrate situations where the opposite is true, i.e. it is more efficient to use a system-optimal allocation without private route preference information. Also it is found that the existing Ration-by-Schedule algorithm performs poorly in the context of our modeling framework.

The above results do not consider the effects of gaming behavior. As a result, we also study the gaming and truth-telling behavior of flight operators in response to the competition for limited en route resources. It is demonstrated that operators are incentivized to provide untruthfully high inputs in schemes where a system-optimal allocation rule is used. Using a gaming analysis, it is also demonstrated that the operators' equilibrium submission strategies in the FSFA scheme can vary significantly depending on the conditions of the AFP and their private information. However, it is also shown that flights are highly incentivized to submit at the very beginning of the FSFA planning period, which is favorable for air traffic flow management (ATFM) planning and coordination.