Studies On Complex Dynamics&Congestion Mitigation Methods Of Air Traffic Flow In Terminal Airspace

The continuous growth of air transportation intensifies the conflict between demand and supply in airspace network,especially for the mega-airports and their surrounding terminal airspace,which have become the hotspots for severe traffic congestions and flight delays,and the critical bottlenecks in National Airspace System.To mitigate the airspace congestion,reduce the air traffic controllers' workload,and to improve the utilization of resource and system-wide robustness,it would be essential to carry out systematic studies on the fundamental theories and control methods of air traffic congestion in terminal airspace to support and facilitate the transformation and upgrade of air traffic system worldwide.In the centralized,sector-based air traffic operations at tactical phase,air traffic flow can be defined as a dynamic,open,complex system,which mainly consists of air traffic controllers,aircraft(pilots),and airspace,and is affected by numerous surrounding factors,like Communication/Navigation/Surveillance System,Air Traffic Management System,and weather etc..So,as a type of generalized transportation flow,air traffic flow congestion has its unique nature,i.e.the excessive demands of aircraft for both limited airspace and controllers' physical and mental resources,which can be observed by the retentions of aircraft,and decrease of control performance.Based on the generalized feature of air traffic flow,this paper studies the dynamic and complex characteristics of air traffic flow and congestion mitigation strategies,starting with a comprehensive review on the research progress and further required improvements related to terminal airspace congestion domain.The main content of this paper is stated as follows:(1)The typical and basic traffic behavior in terminal airspace is empirically studied.Characteristics of air traffic flow,like the randomness of starting points of arrival trajectories,the periodicity of air traffic volume,the fluidity of air traffic flow at macroscopic level,and the conditionality between arrivals and departures are quantitatively proved using historic data.Further,the mental model,named constant speed during conflict detection,the “psychological critical value” and uncertainty in conflict resolution,and adaptive communication duration are also discussed through “Human-In-The-Loop”(HITL)experiment.As a preliminary study,this part provides the basic knowledge for further explorations.(2)The complex dynamics of air traffic flow in terminal airspace is empirically explored.By applying a set of analytical metrics including network variables,complex network attributes,controllers' cognitive complexity,and chaotic metrics on a multi-layered network,which describes the coupled operational relations among airspace,flight trajectories,potential conflicts and controllers' commands,the dynamics of air traffic flow in Guangzhou terminal airspace is empirically revealed.At network level,Fundamental Diagrams(FDs)and Macroscopic Fundamental Diagrams(MFDs)are established to capture the phase transitions and the “demandsupply” dynamics of air traffic flow in terminal airspace.At sector level,by analyzing the degree distribution and motifs of ICCN,meta-cognition strategies,pre-activated,inhibition and stress during the transitions of phases,are shown to be the underlying mechanisms of ATCOs-flow coevolution.Finally,at system level,Chaos is found in both air traffic flow dynamics and ATCOs' activities by analyzing potential traffic conflict and communication activities.Moreover,we show that chaos emerges at unstable phases,i.e.semi-stable and congested phases.The empirical dynamics provides essential basis for understanding complex traffic phenomenon,and further microscopic and macroscopic modeling of air traffic flow.(3)The macroscopic modelling and evolution analysis of air traffic flow are studied.Based on empirical FDs,heterogeneous FDs for flows along different route segments using piecewise approximation are established.A density-speed based Modified Cell Transmission Model(MCTM)is developed with the help of a Queuing Inspector(QI)to simulate the spatio-temporal evolution of flow and congestion in terminal airspace network for the enhancement of the adaption to nonuniform cell length and unique speed profile in terminal airspace.By adopting the macroscopic simulator,air traffic congestion are divided into formulation,accumulation and dissipation(or hysteresis)phases.Then,Critical Steady State(CSS),Critical Unsteady State(CUS)and its acceptable duration are discussed in depth as crucial theoretical parameters for arrival air traffic flow management.In the end of this part,the sensitivity of congestion evolution to operational parameters are revealed,like the spatial distribution of air traffic flow,and the operational priority between arrivals and departures.The modelling and macroscopic characteristics of flow congestion provide basis for air traffic flow optimization,and also a simulation tool for validation strategies.(4)The microscopic modelling and behavior analysis of air traffic flow are studied.Based on the empirical studies on air traffic dynamics,a “human-centered” control framework of air traffic in terminal airspace is proposed,followed by a set of behavioral models including air traffic flow dynamic system,event observer,meta-cognition simulator,decision-making workload measurement,and flight operation modules.By combining above models,an agent-based simulator named “ACTSim”,is developed to present the co-evolution and interactions between air traffic flow and controllers,and further to discuss how the controllers' behavior,like look-ahead time of conflict resolution,priority of task implementation,and expected separation in sectors,impact the flow congestions and control performance.The revealed mechanism and microscopic simulator provide theoretical evidence and validation tool for designing tactical strategies for congestion mitigation.(5)An integrated tactical solution is developed to mitigate congestion in terminal airspace.Inspired by the dynamic and complex characteristics of air traffic flow discussed above,an integrated tactical solution is proposed to ease the congestion at both flow and controllers level.It consists of three control modules: “quantity control” for coupled coordination between arrival rate and off-block rate every 15 min,“sequence control” for collaborative regulation of outflow rate and transit sequence among sectors according to “quantity control” every 5min,and “trajectory control” for horizontal adjustment of trajectory in sectors to avoid conflict and to satisfy the assigned Controlled Time of Arrival by “sequence control” in real time.The solution is validated to be effective on congestion mitigation through air-ground CTM-based simulator,ACTSim,and HITL experiment.This paper follows the philosophy that “practice is guided by the theory”.With adoption of a set of crossover methods,like complex network,mathematical modelling,machine learning,control theory and “human-machine” system,the laws of congestion and “controller-flow” co-evolution mechanisms are revealed to support the development of integrated tactical solutions in dynamic environment for congestion mitigation purposes.The results of this study are essential for refining the air traffic flow theory,improving the congestion management capabilities,and providing new perspectives and solutions for air traffic system development towards advanced automation and intelligence.