# Data-Driven Runway and Taxiway Exits Prediction of Landing Aircraft: A Case Study at Hartsfield-Jackson Atlanta International Airport Source: [Data-Driven Runway and Taxiway Exits Prediction of Landing Aircraft: A Case Study at Hartsfield-Jackson Atlanta International Airport]() Collection index: [llms.txt]() Data updated: 2026-06-11T05:00:14.404Z Authors: Alex Porcayo, Yutian Pang, Maria Thomas, John-Paul Clarke Published: 2026-06-09T15:55:55.000Z ## Abstract Airport surface operations increasingly constrain performance at high-throughput hubs. This study examines arrival taxi-in decisions at Hartsfield-Jackson Atlanta International Airport (KATL) and proposes a two-stage, data-driven decision aid that mirrors controller workflow. Stage I predicts the runway exit selected by an arriving aircraft. Stage II predicts whether, given that exit, the aircraft will cross the active departure runway at a designated point or use the end-around taxiway. Models are trained using ASDE-X surface trajectories, aircraft characteristics, ramp destinations, short-horizon traffic rates, and weather across multiple look-back windows. We benchmark nine classifiers, including Random Forest, XGBoost, LightGBM, and CatBoost, and evaluate accuracy, macro-F1, precision-recall behavior, confusion matrices, Brier score, and Expected Calibration Error. Across east and west flows, XGBoost and LightGBM outperform Random Forest. Stage I achieves 0.86-0.89 accuracy with macro-F1 scores of 0.40-0.50, while Stage II achieves 0.70-0.74 accuracy with macro-F1 scores of 0.28-0.55. Feature-importance analysis shows that approach speed is the main driver of exit choice. Departure rate, crossing rate, ramp destination, and, for west flow, the selected exit are the strongest predictors of crossing versus end-around routing. Minority classes remain harder to predict because of feature-space overlap, as shown by t-SNE and UMAP analyses. The proposed framework supports controller situational awareness through calibrated, explainable predictions while preserving human responsibility for final routing decisions. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Runway Exit Prediction on KATL (West Flow)](): runway exit prediction; KATL (West Flow); Precision: not recorded. - [Runway Exit Prediction on KATL (East Flow)](): runway exit prediction; KATL (East Flow); Precision: not recorded. - [Taxiway Crossing Prediction on Taxi Cross West Flow Stage II](): Taxiway Crossing Prediction; Taxi Cross West Flow Stage II; Precision: not recorded. - [Taxiway Crossing Prediction on Taxi Cross East Flow Stage II](): Taxiway Crossing Prediction; Taxi Cross East Flow Stage II; Precision: not recorded. ## Original sources and implementation [Original paper]() [PDF]()