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Toward Safe Integration of UAM in Terminal Airspace: UAM Route Feasibility Assessment using Probabilistic Aircraft Trajectory Prediction

Jungwoo Cho, Seongjin Choi

TL;DR

The paper tackles safe integration of UAM into ATC-managed terminal airspace by developing a probabilistic trajectory prediction framework using conditional Normalizing Flows to model the conditional distribution $P(Y_t|X_t)$ of conventional aircraft around an ego-UAM. It integrates this with a speed-adjustment control to minimize loss-of-separation events, demonstrated in Seoul airspace with lanes and altitudes. The results reveal lane- and altitude-dependent interaction patterns, showing that adaptive speed control can enhance safety margins while inducing some delays, with Lane 1 at 1,500 ft identified as particularly favorable. The study demonstrates the potential of predictive modeling for UAM-aircraft coexistence and outlines limitations, including limited data, simplified UAM maneuvers, and a single-airport scope, pointing to future work on broader datasets and multi-airport scalability.

Abstract

Integrating Urban Air Mobility (UAM) into airspace managed by Air Traffic Control (ATC) poses significant challenges, particularly in congested terminal environments. This study proposes a framework to assess the feasibility of UAM route integration using probabilistic aircraft trajectory prediction. By leveraging conditional Normalizing Flows, the framework predicts short-term trajectory distributions of conventional aircraft, enabling UAM vehicles to dynamically adjust speeds and maintain safe separations. The methodology was applied to airspace over Seoul metropolitan area, encompassing interactions between UAM and conventional traffic at multiple altitudes and lanes. The results reveal that different physical locations of lanes and routes experience varying interaction patterns and encounter dynamics. For instance, Lane 1 at lower altitudes (1,500 ft and 2,000 ft) exhibited minimal interactions with conventional aircraft, resulting in the largest separations and the most stable delay proportions. In contrast, Lane 4 near the airport experienced more frequent and complex interactions due to its proximity to departing traffic. The limited trajectory data for departing aircraft in this region occasionally led to tighter separations and increased operational challenges. This study underscores the potential of predictive modeling in facilitating UAM integration while highlighting critical trade-offs between safety and efficiency. The findings contribute to refining airspace management strategies and offer insights for scaling UAM operations in complex urban environments.

Toward Safe Integration of UAM in Terminal Airspace: UAM Route Feasibility Assessment using Probabilistic Aircraft Trajectory Prediction

TL;DR

The paper tackles safe integration of UAM into ATC-managed terminal airspace by developing a probabilistic trajectory prediction framework using conditional Normalizing Flows to model the conditional distribution of conventional aircraft around an ego-UAM. It integrates this with a speed-adjustment control to minimize loss-of-separation events, demonstrated in Seoul airspace with lanes and altitudes. The results reveal lane- and altitude-dependent interaction patterns, showing that adaptive speed control can enhance safety margins while inducing some delays, with Lane 1 at 1,500 ft identified as particularly favorable. The study demonstrates the potential of predictive modeling for UAM-aircraft coexistence and outlines limitations, including limited data, simplified UAM maneuvers, and a single-airport scope, pointing to future work on broader datasets and multi-airport scalability.

Abstract

Integrating Urban Air Mobility (UAM) into airspace managed by Air Traffic Control (ATC) poses significant challenges, particularly in congested terminal environments. This study proposes a framework to assess the feasibility of UAM route integration using probabilistic aircraft trajectory prediction. By leveraging conditional Normalizing Flows, the framework predicts short-term trajectory distributions of conventional aircraft, enabling UAM vehicles to dynamically adjust speeds and maintain safe separations. The methodology was applied to airspace over Seoul metropolitan area, encompassing interactions between UAM and conventional traffic at multiple altitudes and lanes. The results reveal that different physical locations of lanes and routes experience varying interaction patterns and encounter dynamics. For instance, Lane 1 at lower altitudes (1,500 ft and 2,000 ft) exhibited minimal interactions with conventional aircraft, resulting in the largest separations and the most stable delay proportions. In contrast, Lane 4 near the airport experienced more frequent and complex interactions due to its proximity to departing traffic. The limited trajectory data for departing aircraft in this region occasionally led to tighter separations and increased operational challenges. This study underscores the potential of predictive modeling in facilitating UAM integration while highlighting critical trade-offs between safety and efficiency. The findings contribute to refining airspace management strategies and offer insights for scaling UAM operations in complex urban environments.

Paper Structure

This paper contains 25 sections, 13 equations, 7 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Literature Review
  3. UAM Airspace Management
  4. Trajectory Prediction
  5. Methodology
  6. Scenario description
  7. Scenarios and assumptions
  8. Separation standard between UAM and conventional aircraft
  9. Study Area Description
  10. Efficiency and safety measures
  11. Probabilistic Aircraft Trajectory Prediction via Conditional Normalizing Flows
  12. Problem Formulation
  13. Density Estimation via Normalizing Flows
  14. Model Structure
  15. Performance Evaluation for Probabilistic Aircraft Trajectory Prediction
  16. ...and 10 more sections

Figures (7)

  • Figure 1: Block diagram of the proposed framework
  • Figure 2: Illustration of the Seoul Metropolitan airspace showing UAM routes (lanes) under evaluation (white) and historic trajectories of conventional aircraft (yellow to red)
  • Figure 3: Distribution of minimum horizontal separation for baseline and speed-adjusted scenarios
  • Figure 4: Minimum horizontal separation for each lane and altitude combination
  • Figure 5: Proportion of flight delay for each lane and altitude combination
  • ...and 2 more figures