Air traffic control is becoming a more and more complex task due to the increasing number of aircraft. Current air traffic control methods are not suitable for managing this increased traffic. Autonomous air traffic control is deemed a promising alternative. In this paper an air traffic control model is presented that guides an arbitrary number of aircraft across a three-dimensional, unstructured airspace while avoiding conflicts and collisions. This is done utilizing the power of graph based deep learning approaches. These approaches offer significant advantages over current approaches to this task, such as invariance to the input ordering of aircraft and the ability to easily cope with a varying number of aircraft. Results acquired using these approaches show that the air traffic control model performs well on realistic traffic densities; it is capable of managing the airspace by avoiding 100% of potential collisions and preventing 89.8% of potential conflicts.
Air traffic control is a real-time safety-critical decision making process in highly dynamic and stochastic environments. In today's aviation practice, a human air traffic controller monitors and directs many aircraft flying through its designated airspace sector. With the fast growing air traffic complexity in traditional (commercial airliners) and low-altitude (drones and eVTOL aircraft) airspace, an autonomous air traffic control system is needed to accommodate high density air traffic and ensure safe separation between aircraft. We propose a deep multi-agent reinforcement learning framewor…
Dense and complex air traffic scenarios require higher levels of automation than those exhibited by tactical conflict detection and resolution (CD\&R) tools that air traffic controllers (ATCO) use today. However, the air traffic control (ATC) domain, being safety critical, requires AI systems to which operators are comfortable to relinquishing control, guaranteeing operational integrity and automation adoption. Two major factors towards this goal are quality of solutions, and transparency in decision making. This paper proposes using a graph convolutional reinforcement learning method operatin…
Real-Time Communication-Aware Ride-Sharing Route Planning for Urban Air Mobility: A Multi-Source Hybrid Attention Reinforcement Learning Approach
School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen（科学与工程学院，香港中文大学（深圳））；Xidian University State Key Laboratory of Integrated Services Network（西安电子科技大学集成服务网络国家重点实验室）；Department of Computer Science and Engineering, Kyung Hee University（庆北大学计算机科学与工程系）
George Washington University（乔治华盛顿大学）；Iowa State University（爱荷华州立大学）
The separation assurance task will be extremely challenging for air traffic controllers in a complex and high density airspace environment. Deep reinforcement learning (DRL) was used to develop an autonomous separation assurance framework in our previous work where the learned model advised speed maneuvers. In order to improve the safety of this model in unseen environments with uncertainties, in this work we propose a safety module for DRL in autonomous separation assurance applications. The proposed module directly addresses both model uncertainty and state uncertainty to improve safety. Our…
T-Router: Learning Thalamic Routing for Reasoning with Parameter-Efficient Reinforcement Learning
College of Artificial Intelligence, Tsinghua University（清华大学人工智能学院）；State Key Laboratory of General Artificial Intelligence, School of Intelligence Science and Technology, Peking University（北京大学智能科学与技术学院通用人工智能国家重点实验室）；Beijing Institute for General Artificial Intelligence（北京通用人工智能研究院）
In a connected transportation system, adaptive traffic signal controllers (ATSC) utilize real-time vehicle trajectory data received from vehicles through wireless connectivity (i.e., connected vehicles) to regulate green time. However, this wirelessly connected ATSC increases cyber-attack surfaces and increases their vulnerability to various cyber-attack modes, which can be leveraged to induce significant congestion in a roadway network. An attacker may receive financial benefits to create such a congestion for a specific roadway. One such mode is a 'sybil' attack in which an attacker creates …
Réseau de Transport d’Électricité（法国输电网络公司）；INSERM（法国国家健康与医学研究院）；CentraleSupélec（巴黎中央理工-高等电力学院）；INRIA（法国国家信息与自动化研究所）；Universié Paris-Saclay（巴黎萨克雷大学）
For power grid operations, a large body of research focuses on using generation redispatching, load shedding or demand side management flexibilities. However, a less costly and potentially more flexible option would be grid topology reconfiguration, as already partially exploited by Coreso (European RSC) and RTE (French TSO) operations. Beyond previous work on branch switching, bus reconfigurations are a broader class of action and could provide some substantial benefits to route electricity and optimize the grid capacity to keep it within safety margins. Because of its non-linear and combinat…
Using constraint-based local search, we effectively model and efficiently solve the problem of balancing the traffic demands on portions of the European airspace while ensuring that their capacity constraints are satisfied. The traffic demand of a portion of airspace is the hourly number of flights planned to enter it, and its capacity is the upper bound on this number under which air-traffic controllers can work. Currently, the only form of demand-capacity balancing we allow is ground holding, that is the changing of the take-off times of not yet airborne flights. Experiments with projected E…
Autonomous University of Barcelona（巴塞罗那自治大学）；CRIDA A.I.E
Present air traffic complexity metrics are defined considering the interests of different management layers of ATM. These layers have different objectives which in practice compete to maximize their own goals, which leads to fragmented decision making. This fragmentation together with competing KPAs requires transparent and neutral air traffic information to pave the way for an explainable set of actions. In this paper, we introduce the concept of single aircraft complexity, to determine the contribution of each aircraft to the overall complexity of air traffic. Furthermore, we describe a meth…
Thales Air Systems（泰雷兹空中系统公司）；TAO；Thales Research & Technology（泰雷兹研究与技术公司）；INRIA Saclay（法国国家信息与自动化研究所萨克雷中心）
With the objective of handling the airspace sector congestion subject to continuously growing air traffic, we suggest to create a collaborative working plan during the strategic phase of air traffic control. The plan obtained via a new decision support tool presented in this article consists in a schedule for controllers, which specifies time of overflight on the different waypoints of the flight plans. In order to do it, we believe that the decision-support tool shall model directly the uncertainty at a trajectory level in order to propagate the uncertainty to the sector level. Then, the prob…
Nommon Solutions and Technologies（Nommon解决方案与技术公司）
Air Traffic Flow and Capacity Management (ATFCM) is one of the constituent parts of Air Traffic Management (ATM). The goal of ATFCM is to make airport and airspace capacity meet traffic demand and, when capacity opportunities are exhausted, optimise traffic flows to meet the available capacity. One of the key enablers of ATFCM is the accurate estimation of future traffic demand. The available information (schedules, flight plans, etc.) and its associated level of uncertainty differ across the different ATFCM planning phases, leading to qualitative differences between the types of forecasting t…
Centre for Modeling and Simulation（建模与仿真中心）；University of Pune（浦那大学）
The issues in air traffic control have so far been addressed with the intent to improve resource utilization and achieve an optimized solution with respect to fuel comsumption of aircrafts, efficient usage of the available airspace with minimal congestion related losses under various dynamic constraints. So the focus has almost always been more on smarter management of traffic to increase profits while human safety, though achieved in the process, we believe, has remained less seriously attended. This has become all the more important given that we have overburdened and overstressed air traffi…
Thales Air Systems（泰雷兹空中系统公司）；Thales Research & Technology（泰雷兹研究与技术公司）；INRIA Saclay Ile-de-France（法国国家信息与自动化研究所萨克雷-法兰西岛分部）；Université Paris Sud（巴黎第十一大学）
We investigate a method to deal with congestion of sectors and delays in the tactical phase of air traffic flow and capacity management. It relies on temporal objectives given for every point of the flight plans and shared among the controllers in order to create a collaborative environment. This would enhance the transition from the network view of the flow management to the local view of air traffic control. Uncertainty is modeled at the trajectory level with temporal information on the boundary points of the crossed sectors and then, we infer the probabilistic occupancy count. Therefore, we…
Numbers Beat Words: A Rigorous On-Premise Benchmark for Coupled MIMO Controller Tuning
Jinling Institute of Technology（金陵科技学院）；College of Water Resources and Civil Engineering, China Agricultural University（中国农业大学水利与土木工程学院）；Zhejiang University（浙江大学）
PACE: Perceived-Latency-Aware Cascading Service Routing and Filler Control for QoE-Efficient Retrieval-Augmented Dialogue Serving
Chongqing University（重庆大学）；National University of Defense Technology（国防科技大学）；Chongqing University of Posts and Telecommunications（重庆邮电大学）；University of Toronto Mississauga（多伦多大学密西沙加分校）；Chongqing Huayuan Zhixin Technology Co., Ltd.（重庆华远智信科技有限公司）；Inspur Yunzhou Industrial Internet Co., Ltd.（浪潮云洲工业互联网有限公司）；Guoqi Zhimo (Chongqing) Technology Co., Ltd.（国器智模（重庆）科技有限公司）
