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Improving Ground-Based Trajectory Prediction through Communication of Aircraft Intent

The hypothesis that communication of aircraft intent will greatly improve trajectory accuracies as measured by commonly used trajectory prediction metrics is tested by using an anonymous sample flight with an optimized profile descent. The sample flight illustrates two common sources of trajectory prediction uncertainty: Top-Of-Descent uncertainty and an Unknown Lateral Change. The researchers selected two separate trajectory predictors to emulate ground-based trajectory prediction and a trajectory engine for generation of trajectories following aircraft intent communication via the Aircraft Intent Description Language (AIDL). Tests without AIDL produced a root mean square (RMS) of lateral or cross-track error as high as 18 nautical miles, a RMS of vertical error as high as 11,000 feet, and a RMS of time error as high as 70 seconds. With communication via AIDL, these were reduced to 0.3 nautical miles, 170 feet, and 6 seconds.