REACT: A Rapid Environmental Impact on Airport Community Tradeoff Environment

Abstract

Community noise exposure is the one of the key challenges to the potential growth of the aviation industry. Various forecasts have shown that the industry is expected to grow in the future years, and with this comes a predicted increase in noise levels around airports without a significant influx of noise reduction technologies across the fleet. In order to plan for these future scenarios, airports, airlines, the FAA, and local governments must analyze various noise mitigation strategies, operational restrictions, and changes to airport states, whilst still increasing capacity. Thus, it has become important for these entities to be able to rapidly tradeoff different noise mitigation strategies to effectively manage community noise exposure in current and future airport scenarios. However, noise modeling can be a cumbersome task due to the potential for high computational times and its case dependency. Each entity, airport, and community have their own concerns, conditions, and population structure. Current noise modeling software can take multiple hours to set up an airport case study and run a single operational state. REACT, a tradeoff environment developed in this paper, aims to provide the key stakeholders with airport-specific information, an accessible visual user interface, and most importantly, rapid computations. REACT connects the various mitigation strategies and techniques most important to each of the key stakeholders, and allows these authorities to investigate solutions that are most important to them in current and future airport states.

Air Transportation Direct Share Analysis and Forecast

“…Multiple linear regression (MLR) is the linear regression model with multiple features. Denote y i as the ith response and x ij as the jth feature for y i , and the MLR model can be formulated as equation (9), in which residual sum square (RSS) is the measurement of fitting accuracy and β j are coefficients. MLR can be easily fitted and interpreted, and one typical approach to estimate the coefficients is the least squares algorithm.…”

“…e Federal Aviation Administration (FAA) Terminal Area Forecast (TAF) is the official FAA forecast for enplanements, airport operations, terminal radar approach control (TRACON) facilities operations, and based aircraft [7]. ere is a wide range of applications of the FAA TAF, such as the air traffic controller workforce planning, airport long-term investment analysis [8], and airport environmental study [9]. O&D direct share forecasting is an essential component in the FAA TAF, which helps FAA making decisions on airport planning and investment.…”