This grant provides funding for the conceptualization and development of a scientific platform for the design of airport security systems. In the first part, we consider the selection of passengers into groups in a purely random manner (without knowledge of their individual attributes). We first consider a static model in which the temporal aspect of passenger arrivals is ignored. We then take this basic model and enhance it by incorporating the temporal effects of arriving passengers. Two cases are analyzed. We investigate a queuing model, which considers each check station as an independent M/M/c queue operating in steady state and models passenger arrivals using a time-homogeneous Poisson stream. We also investigate a simulation model that captures the non-steady state behavior of the system and allows for a general representation of the passenger arrival process. The second part of our work will investigate: (i) the potential improvement in the efficiency of the security system by using passenger attributes in assigning groups; and (ii) the analysis of the case where several check stations can work in unison to detect a threat item.
If successful, the results of this research will be useful to several federal agencies, including the TSA, FAA and the Department of Homeland Security division of the federal government. The proposed work will lead to a better understanding as to how security procedures should be changed in response to changes in the overall threat probability. Finally, it would provide a quantitative framework to understand (i) the potential efficiency improvements that are likely to arise due to the use of individual attributes in passenger assignments to groups, and (ii) consideration of joint response of equipment to the presence of a potential threat item.
