Port-of-Entry Simulation Model for Potential Wait Time Reduction and Air Quality Improvement: A Case Study at the Gateway International Bridge in Brownsville, Texas, USA

The mathematical study known as queueing theory has recently become a major point of interest for many government agencies and private companies increasing efficiency. One such application is vehicle at an international port-of-entry (POE). When queueing, fumes from idling vehicles negatively affect the overall health well-being community, especially U.S. Customs Border Protection (CBP) agents that work POEs. As such, there need to analyze optimize border crossing queuing operations minimize wait times number in queue and, thus, reduce emissions. For this research, U.S.–Mexico POE located Gateway International Bridge Brownsville, Texas, used case study. Due data privacy concerns, hourly arriving had be extracted manually each day using live time tracker online. extraction was performed month March 2022. Using these times, simulation software, SIMIO, develop interactive model calibrate service rates. output SIMIO then artificial neural network (ANN) predict particulate matter content with R2 0.402. From ANN, predictive equation been developed, which may by CBP make operational decisions improve efficiency POE. Thus, lowering average emissions queue.