Aircraft noise continues to be a major environmental issue impacting airports and their surrounding communities. Beyond being an annoyance, aircraft noise has also been found to have potentially adverse health effects on humans and animals. Thus, international, national, and local regulations have been adopted to quantify, limit, and mitigate aircraft noise. Software developed by the Federal Aviation Administration to estimate the impacts of airport noise relies on operations information that may be difficult to obtain for aircraft operating under visual flight rules at nontowered airports. Hence, leveraging the use of ADS-B as a low-cost source of operations data may improve noise estimation methods at such airports. To validate this approach, ADS-B data was compared to GPS records from aircraft avionics. With an average error of 57.72 feet laterally, 112.36 feet vertically, and 126.32 feet combined, resulting noise estimation errors as a result of ADS-B position errors are expected to be less than seven decibels. It was also found that ADS-B data can be significantly improved by incorporating atmospheric data to improve altitude information, leading to a reduction in estimation errors. The results of this study highlight the potential applicability of ADS-B usage in noise estimation and other applications.

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Excessive airport security wait times during peak operational periods have been well-documented in crowdsourced data and well-publicized among the news media. While serving a paramount purpose, airport security checkpoints are capacity constrained and frequently stressed, leading to passenger dissatisfaction and system limitations. To alleviate air travelers’ wasted wait time during the security screening process, an innovative queue management technique is explored. Passengers currently flow to Transportation Security Administration (TSA) screening lanes at terminal checkpoints via a First-Come, First-Serve (FCFS) discipline. However, repeated variations in passenger characteristics and screening times may cause this service discipline to suffer small inefficiencies that aggregately distort resource utilization and throughput speed. This paper proposes an Advance Lane Assignment System (ALAS) in which passengers are directed to specific screening lanes upon arrival to a terminal checkpoint using real-time, autonomous, feedback control. Leveraging existing Bluetooth© technology to assess lane flow rates, control logic can convey lane assignments to passengers at identification authentication gates. System feasibility was analyzed through discrete, dynamic, and probabilistic simulations of a multilane, multiphase queue model with varying traffic intensities and control logic. Basic, discrete-time Proportional-Integral-Derivative (PID) control was found to offer a 12% reduction in average passenger waiting times over the baseline FCFS discipline.