Improving airport checkpoint efficiency
Dynamic workforce management at network screening facilities
For the nation’s airports, increases in travelers often means long waits for passengers at security checkpoints, as large volumes of travelers and baggage must be screened before takeoff. Nationally, the number of air travelers and bags that must be screened every day is immense. In 2017, the TSA reported screening more than 2 million passengers and approximately 1.4 million bags every day with an average passenger wait time of under 20 minutes.
However, the combination of current airport space constraints, projected increases in air travelers, and rising number of security threats will put more pressure on TSA staff and resources. The development of new workforce management tools will be critical for the TSA in their efforts to continue to improve operational efficiency under these challenging conditions.
The research team has been working directly with TSA personnel at Phoenix Sky Harbor and Las Vegas’ McCarran airports on a related CAOE project Dynamic Resource Allocation for Predicted Demands at a Network of Screening Facilities over the last 3 years. This project is an extension of those activities.
For this project, the team is developing analytical solutions, evaluating work schedules, and routing decisions using airport data and simulation models of the interconnected security screening checkpoints (SSCPs). This includes separate models to test staffing performance and operating procedures for checked baggage screening areas.
The simulation and optimization models will leverage previously developed tools like the passenger arrival estimator (PAE) and the dynamic queue analyzer (DQA). These models will be validated using non-sensitive (SSI) airport information provided by project partners at Sky Harbor, collected through observational procedures, and obtained from publicly available sources.
The goal of this project is to assist TSA planners response to changing workplace demands. This includes supporting the agency’s efforts to improve the performance of airport screening operations with new, data-driven tools and training. With access to new information on screening procedure efficiencies, staff work scheduling and routing options; these tools will empower TSA officials to fine-tune current processes, staffing and resource allocation to maximize efficiency, increase safety and improve the passenger experience.
Research Leadership Team
Principal Investigator: Jorge Sefair, ASU
Co-PI: Ron Askin, Arizona State University
Co-PI: Jose Espiritu, University of Texas at El Paso
Co-PI: Kelvin Cheu, University of Texas at El Paso
Co-PI: Ted Pavlic, Arizona State University