A framework for collaborative UAM traffic flow optimization with mission preferences: Incorporating customized strategy synergy into strategic conflict management

Abstract

Urban Air Mobility (UAM) is emerging as a transformative solution to urban transportation, yet the safe and efficient implementation requires advanced UAM traffic management approaches. Although existing studies prioritize the generation of conflict-free 4-D trajectories, critical mission-specific preferences remain insufficiently integrated, influencing stakeholders’ acceptance and operational feasibility. This paper addresses this gap by proposing a collaborative UAM Traffic Flow Management (UTFM) framework that models explicit interaction constraints, combining mission preferences with strategy synergy. The framework centers on the UTFM model featuring a hierarchical conflict management architecture. In the strategic phase, the deterministic separation threshold is applied to resolve 4-D conflicts proactively, while the pre-tactical phase employs probabilistic constraints to manage flight uncertainties during disruption recovery. To solve the UTFM problem, a novel two-stage optimization algorithm is developed. The first stage encodes the conflict-based solution space via recurrent path searching and linear mapping techniques, while the second stage optimizes the 4-D flight plans by determining strategy-specific decision variables. Additionally, the Transit Search Optimization (TSO) algorithm is introduced and enhanced through constraint transcription and normal cloud model. Comprehensive experiments demonstrate that the framework can generate robust and efficient flight plans under complex constraints with diverse mission preferences. The framework could support high-throughput UAM operations with customized requirements, offering a prototype for the advanced UAM traffic management system.