Risk-Aware Limited Rerouting and Demand Allocation in Structured UAM Airspace

Abstract

Urban Air Mobility (UAM) operations in structured airspace face a key challenge in managing congestion. This paper proposes a departure control framework with limited rerouting that identifies high-risk paths using a conflict-based risk metric and shifts part of their demand to lower-risk existing paths through short detours. The approach is evaluated in the LAAT-Flow simulation environment under three demand allocation strategies, namely full, fixed, and dynamic allocation. The results show that all strategies reduce overall network risk. Dynamic allocation provides the most stable improvement as more paths are rerouted, while full allocation initially achieves strong risk reduction but may create new bottlenecks when demand is concentrated on alternative paths. These safety improvements come at the cost of increased energy consumption due to longer alternative paths. The findings demonstrate that limited rerouting with adaptive allocation offers a practical approach for improving safety in corridor-based UAM operations.