Multi-objective 4D Trajectory Optimization for Online Strategic and Tactical Air Traffic Management

Gardi, Alessandro; Sabatini, Roberto; Marino, Matthew; Kistan, Trevor

doi:10.1007/978-3-319-34181-1_17

Cited by 4 publications

(1 citation statement)

References 39 publications

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“…Following this concept, experts and scholars introduced the time dimension to flight trajectory planning and proposed a series of 4D flight trajectory planning methods that could effectively improve the utilization efficiency of airspace [17] and avoid the waste of airspace. Gardi et al [18] proposed a functional development method of 4D trajectory planning, negotiation, and verification (4-PNV) based on a multi-target 4DT optimized algorithm. They also constructed a model applicable to aircraft dynamics, engine thrust, fuel consumption, and pollutant emissions, which was realized and evaluated in the multi-target 4DT optimized algorithm.…”

Section: Strategic Trajectory Planning Methodsmentioning

confidence: 99%

An ETA-Based Tactical Conflict Resolution Method for Air Logistics Transportation

Zheng

et al. 2023

Drones

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Air logistics transportation has become one of the most promising markets for the civil drone industry. However, the large flow, high density, and complex environmental characteristics of urban scenes make tactical conflict resolution very challenging. Existing conflict resolution methods are limited by insufficient collision avoidance success rates when considering non-cooperative targets and fail to take the temporal constraints of the pre-defined 4D trajectory into consideration. In this paper, a novel reinforcement learning-based tactical conflict resolution method for air logistics transportation is designed by reconstructing the state space following the risk sectors concept and through the use of a novel Estimated Time of Arrival (ETA)-based temporal reward setting. Our contributions allow a drone to integrate the temporal constraints of the 4D trajectory pre-defined in the strategic phase. As a consequence, the drone can successfully avoid non-cooperative targets while greatly reducing the occurrence of secondary conflicts, as demonstrated by the numerical simulation results.

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Section: Strategic Trajectory Planning Methodsmentioning

confidence: 99%

An ETA-Based Tactical Conflict Resolution Method for Air Logistics Transportation

Zheng

et al. 2023

Drones

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Multi-objective multi-agent decision making: a utility-based analysis and survey

Rădulescu

Mannion

Roijers

et al. 2019

Auton Agent Multi-Agent Syst

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The majority of multi-agent system (MAS) implementations aim to optimise agents' policies with respect to a single objective, despite the fact that many real-world problem domains are inherently multi-objective in nature. Multiobjective multi-agent systems (MOMAS) explicitly consider the possible trade-offs between conflicting objective functions. We argue that, in MOMAS, such compromises should be analysed on the basis of the utility that these compromises have for the users of a system. As is standard in multi-objective optimisation, we model the user utility using utility functions that map value or return vectors to scalar values. This approach naturally leads to two different optimisation criteria: expected scalarised returns (ESR) and scalarised expected returns (SER). We develop a new taxonomy which classifies multi-objective multi-agent decision making settings, on the basis of the reward structures, and which and how utility functions are applied. This allows us to offer a structured view of the field, to clearly delineate the current state-of-the-art in multi-objective multi-agent decision making approaches and to identify promising directions for future research. Starting from the execu-

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PMDRL: Pareto-front-based multi-objective deep reinforcement learning

Yang

Huang

Shi

et al. 2022

J Ambient Intell Human Comput

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Multi-objective 4D Trajectory Optimization for Online Strategic and Tactical Air Traffic Management

Cited by 4 publications

References 39 publications

An ETA-Based Tactical Conflict Resolution Method for Air Logistics Transportation

An ETA-Based Tactical Conflict Resolution Method for Air Logistics Transportation

Multi-objective multi-agent decision making: a utility-based analysis and survey

PMDRL: Pareto-front-based multi-objective deep reinforcement learning

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