Bilevel Programming Model for Joint Scheduling of Arrival and Departure Flights Based on Traffic Scenario

In order to meet the needs of collaborative decision making,considering the different demands of air traffic control units,airlines,airports and passengers in various traffic scenarios,the joint scheduling problem of arrival and departure flights is studied systematically.According to the matching degree of capacity and flow,it is determined that the traffic state of arrival/departure operation in a certain period is peak or off-peak.The demands of all parties in each traffic state are analyzed,and the mathematical models of arrival/departure flight scheduling in each traffic state are established.Aiming at the four kinds of joint operation traffic scenarios of arrival and departure,the corresponding bi-level programming models for joint scheduling of arrival and departure flights are established,respectively,and the elitism genetic algorithm is designed to solve the models.The results show that:Compared with the first-come-firstserved method,in the scenarios of arrival peak&departure off-peak and arrival peak&departure peak,the departure flight equilibrium satisfaction is improved,and the runway occupation time of departure flight flow is reduced by 38.8%.In the scenarios of arrival off-peak&departure off-peak and departure peak&arrival off-peak,the arrival flight equilibrium delay time is significantly reduced,the departure flight equilibrium satisfaction is improved by 77.6%,and the runway occupation time of departure flight flow is reduced by 46.6%.Compared with other four kinds of strategies,the optimal scheduling method can better balance fairness and efficiency,so the scheduling results are more reasonable.

Migration departure strategies of shorebirds at a final pre-breeding stopover site

Background: Departure decisions and behaviors of migratory birds at stopover sites are expected to maximize fit?ness by trade?offs among avoiding predators, optimizing refueling(energy) capacity, and matching other life?history events. We predict that species with different body sizes and migratory destinations will exhibit different behaviors when departing from the same stopover site. We also predict that with strong time constraint at the final pre?breed?ing stopover site, departure decisions may be less sensitive to exogenous factors, such as wind condition, compared to other stopover or nonbreeding sites.Methods: We recorded migratory departures of four shorebird species, i.e. Eurasian Curlew(Numenius arquata), Bar?tailed Godwit(Limosa lapponica), Great Knot(Calidris tenuirostris), and Grey Plover(Pluvialis squatarola), at Yaluji?ang Estuary Wetlands in China, a final pre?breeding stopover site in the northern Yellow Sea, from 2011 to 2014. We compared flock sizes, departure time and departure directions between species, and investigated the effects of tide and weather conditions(rain and ground wind speed and direction) on the departure decision of shorebirds.Results: We found that larger species departed in smaller flocks and were more variable in daily departure time. Departure trajectory of all four species appeared to be influenced by coastal topography. With the east–west coast?line and intertidal mudflat on the south, birds exhibited westward or eastward deflection from the shortest migra?tory routes. Bar?tailed Godwit was the only species that deviated to the southeast and did not climb over the land. Birds avoided departure during precipitation, while their departure was not related to ground wind benefit or tidal condition.Conclusions: Body size among species, which influences their vulnerability to predators, might be important in shaping shorebird departure strategies. Diverse departure directions could be the result of different wind use tac?tics in climbing stage. Narrow optimal time window of breeding might lead to reduced flexibility in departure date at a final pre?breeding site. Both endogenous and exogenous are important in shaping departure behaviors and decisions.

Optimization Method for Departure Flight Scheduling Problem Based on Genetic Algorithm

Except for the bad weather or other uncontrollable reasons,a reasonable queue of departure and arrival flights is one of the important methods to reduce the delay on busy airports.Here focusing on the Pareto optimization of departure flights,the take-off sequencing is taken as a single machine scheduling problem with two objective functions,i.e.,the minimum of total weighted delayed number of departure flights and the latest delay time of delayed flight.And the integer programming model is established and solved by multi-objective genetic algorithm.The simulation results show that the method can obtain the better goal,and provide a variety of options for controllers considering the scene situation,thus improving the flexibility and effectivity of flight plan.

A NEW AND DIRECT METHOD OF ANALYSIS THE DEPARTURE PROCESSES OF SINGLE SERVER QUEUEING SYSTEMS

In this paper, using the stochastic decomposition and renewal theory we provide the direct method for analysis the departure process of single sever M/G/1 queueing system, and further discuss the departure process of GI/G/1 queueing system. The method provided in this paper is new and concise, which make us see dearly the structure of the departure process of a single server queueing system.

Three-Dimensional Planning of Arrival and Departure Route Network Based on Improved Ant-Colony Algorithm

In order to improve safety,economy efficiency and design automation degree of air route in terminal airspace,Three-dimensional(3D)planning of routes network is investigated.A waypoint probability search method is proposed to optimize individual flight path.Through updating horizontal pheromones by negative feedback factors,an antcolony algorithm of path searching in 3Dterminal airspace is implemented.The principle of optimization sequence of arrival and departure routes is analyzed.Each route is optimized successively,and the overall optimization of the whole route network is finally achieved.A case study shows that it takes about 63 sto optimize 8arrival and departure routes,and the operation efficiency can be significantly improved with desirable safety and economy.

A Combined Arrival and Departure Scheduling for Multi-airport System

A combined arrival and departure scheduling problem is investigated for multi-airport system to alleviate the problem of airspace congestion and flight delay.Firstly,the combined scheduling problem for multi-airport system is defined through in-depth analysis of the characteristics of arrival and departure operations.Then,several constraints are taken into account,such as wake vortex separation,transfer separation,release separation,and separation in different runway operational modes.Furthermore,the scheduling model is constructed and simulated annealing algorithm is proposed by minimizing the total delay.Finally,Shanghai multi-airport system is chosen to conduct the simulation and validation.And the simulation results indicate that the proposed method is able to effectively improve the efficiency of arrival and departure operations for multi-airport system.

Real-time lane departure warning system based on principal component analysis of grayscale distribution and risk evaluation model

A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.

Study on the Bubble Growth and Departure with A Lattice Boltzmann Method

For the growth and departure of bubbles from an orifice, a free energy lattice Boltzmann model is adopted to deal with this complex multiphase flow phenomenon. A virtual layer is set at the boundary of the flow domain to deal with the no-slip boundary condition. Effects of the viscosity, surface tension, gas inertial force and buoyancy on the characteristics of bubbles when they grow and departure from an orifice in quiescent liquid are studied. The releasing period and departure diameter of the bubble are influenced by the residual gas at the orifice, and the interaction between bubbles is taken into consideration. The relations between the releasing period or departure diameter and the gravity acceleration show fair agreements with previous numerical and theoretical results. And the influence of the gas outflow velocity on bubble formation is discussed as well. For the bubbles growing in cross-flow field, effects of the cross-flow speed and the gas outflow velocity on the bubble formation are discussed, which is related to the application in ship resistance reduction. And optimal choice of the ship speed and gas outflow velocity is studied. Cases in this paper also prove that this high density ratio LBM model has its flexibility and effectiveness on multiphase flow simulations.

Urban rail departure capacity analysis based on a cellular automaton model

As an important traffic mode, urban rail transit is constantly developing toward improvement in service capacity and quality. When an urban rail transit system is evaluated in terms of its service capacity, the train departure capacity is an important index that can objectively reflect the service level of an urban rail transit facility. In light of the existing cellular automaton models, this paper proposes a suitable cellular automaton model to analyze the train departure capacity of urban rail transit under different variable factors and conditions. The established model can demonstrate the train operating processes by implementing the proposed sound rules, including the rules of train departure at the origin and intermediate stations, and the velocity and position updating rules. The properties of train traffic are analyzed via numerical experiments. The numerical results show that the departure capacity is negatively affected by the train departure control manner. In addition, （i） the real-time signal control can offer a higher train service frequency; （ii） the departure capacity gradually rises with the decrease in the line design speed to a limited extent; （iii） the departure capacity decreases with extension in the train length; （iv） the number of departed trains decreases as the train stop time increases; （v） the departure capacity is not affected by the section length. However, the longer the length, the worse the service quality of the urban rail transit line. The experiments show that the proposed cellular automaton model can be used to analyze the train service capacity of an urban rail transit system by performing quantitative analysis under various considered factors, conditions, and management modes.

Springtime migratory restlessness and departure orientation of Great Knots(Calidris tenuirostris)in the south compared to the north Yellow Sea

Background: The motivation of birds to proceed with migration is associated with both endogenous and exogenous factors. According to their migratory situation and to the characteristics of stopover sites, birds might exhibit migratory motivation differently among sites. Although migratory motivation of migrating birds has been well studied in many species, the investigation of the same species in different migratory situations and at different stopover sites is still limited. We predicted that birds at different stopover sites could differ in migratory disposition, including expression of migratory restlessness and responses to environmental cues.Methods: Here we compared migration motivation and orientation of Great Knots(Calidris tenuirostris) at two stopo ver sites, Chongming Dongtan in the south Yellow Sea, which is a temporary rest site, and Yalujiang Estuary Wetland in the north Yellow Sea, which is a critical refuelling site, during northward migration. Modified Emlen funnels, with thermal paper inside to record scratches of the birds, were used to detect activity(intensity and direction) of birds. Environmental conditions, including wind direction and speed, cloud cover, tide condition, times of the day(before and after sunset) were recorded during experiments. Generalized linear models were used to detect the effects of endogenous and exogenous factors on the migratory motivation of the birds.Results: In the south Yellow Sea, the migratory activity intensity of Great Knots was positively related to wind assistance. In the north Yellow Sea, where birds exhibited higher intensity of migratory activity than in the south, the intensity increased and the motivation to initiate migration grew stronger as the season advanced. The Great Knots exhibited wind-related orientation behaviour in the funnels at both sites.Conclusions: The results suggest that the intensity of migratory motivation differed between the two sites. Departure decisions of Great Knots appear to be affected mainly by external factors at the temporary rest site in the south Yellow Sea but possibly by endogenous factors at the final pre-breeding refuelling site in the north Yellow Sea.

Dynamic Tabu Search Algorithm for Solving Departure Scheduling Problem

The aircraft departure scheduling problem is described comprehensively. A mathematical model is built for solving this problem. Then, a local search algorithm is proposed; based on it, the dynamic tabu search technique is applied, and the related implement techniques are presented. A simulation including condition and results is performed to solve a representative problem. It is concluded that （ 1 ） departure aircrafts of each queue keep the same order comparatively all the lime, and the distribution of the departure time is well-proportioned, which accords with the ＂first-come first-serve＂ principle; （2） the total time costs are minimized, which would economize money and reduce danger; （ 3 ） the optimization result is not exclusive, which means that several approaches can be chosen at will; （4） the solution obtained is the global optimal one, which guarantees the validity of the proposed method.

Fault Geometry and Departure of Precursors From the Epicenter

Different tectonic elements may play different roles and their deformation styles and types of anomalies are also different in the process of deformation.Such differences may be the cause of the phenomena of the departure from the region with obvious anomalies from the coming epicenter,which are called "departure of precursors from epicenter." From some new experimental and numerical modeling results,five types of deformation elements are identified according to their roles in the process of deformation in a region.They are the brake(or locked),slip,yield,sensitive,and valve elements.Spatial distribution of different elements,especially sensitive and slip elements,are discussed by taking the bend fault,extension,compression,and complex en-echelon faults as examples.These elements with different roles may overlap each other in some cases or be separated in other cases.It is obvious that for different fault geometry,the spatial layout of these elements is different and thus the position and style of

Individual departure time decision considering departure scheduling utility

The scheduling utility plays a fundamental role in addressing the commuting travel behaviours. A new scheduling utility,termed as DMRD-SU, was suggested based on some recent research findings in behavioural economics. DMRD-SU admitted the existence of positive arrival-caused utility. In addition, besides the travel-time-caused utility and arrival-caused utility, DMRD-SU firstly took the departure utility into account. The necessity of the departure utility in trip scheduling was analyzed comprehensively,and the corresponding individual trip scheduling model was presented. Based on a simple network, an analytical example was executed to characterize DMRD-SU. It can be found from the analytical example that: 1) DMRD-SU can predict the accumulation departure behaviors at NDT, which explains the formation of daily serious short-peak-hours in reality, while MRD-SU cannot; 2)Compared with MRD-SU, DMRD-SU predicts that people tend to depart later and its gross utility also decreases faster. Therefore,the departure utility should be considered to describe the traveler's scheduling behaviors better.

Departure Trajectory Design Based on Pareto Ant Colony Algorithm

Due to the ever-increasing air traffic flow,the influence of aircraft noise around the airport has become significant.As most airlines are trying to decrease operation cost,stringent requirements for more simple and efficient departure trajectory are on a rise.Therefore,a departure trajectory design was established for performancebased navigation technology,and a multi-objective optimization model was developed,with constraints of safety and noise influence,as well as optimization targets of efficiency and simplicity.An improved ant colony algorithm was then proposed to solve the optimization problem.Finally,an experiment was conducted using the Lanzhou terminal airspace operation data,and the results showed that the designed departure trajectory was feasible and efficient in decreasing the aircraft noise influence.

Impact of Departure Time Uncertainty on Runway Scheduling

The flight departure process is affected by various uncertain factors,such as flight delays,scheduling delays and taxi time etc. A reliable and robust departure sequence is very important to the safe and efficient operation for airports. An optimal scheduling model for multi-runway departure considering the arrival aircraft crossing departure runway is developed. A genetic algorithm encoding flight numbers is designed to find a near-optimal solution. After that,further establish a multi-objective dynamic scheduling model and design a hybrid algorithm to solve it,and compare and analyze the results of the two models. A quantitative analysis of departure time based on the kernel density estimation is performed,and Monte Carlo simulations are carried out to explore the impact of flight departure time’s uncertainty on departure scheduling. The results based on historical data from Guangzhou Baiyun Airport are presented,showing the advantage of the proposed model and algorithm.

Sectorization Model of Terminal Airspace with Arrival and Departure Separation

Terminal airspace(TMA)is the airspace centering several military and civil aviation airports with complex route structure,limited airspace resources,traffic flow,difficult management and considerable airspace complexity.A scientific and rational sectorization of TMA can optimize airspace resources,and sufficiently utilize the control of human resources to ensure the safety of TMA.The functional sectorization model was established based on the route structure of arriving and departing aircraft as well as controlling requirements.Based on principles of sectorization and topological relations within a network,the arrival and departure sectorization model was established,using tree based ant colony algorithm(ACO)searching.Shanghai TMA was taken as an example to be sectorizaed,and the result showed that this model was superior to traditional ones when arrival and departure routes were separated at dense airport terminal airspace.

The Construction of an Ontology-Based Knowledge Management Model for Departure Procedures

With increased global economic development, the air traffic volume (including passengers and parcels) increases every year. Thus, the business-related load on air traffic controllers becomes heavier, which influences their need for frequent learning and training opportunities. Therefore, the only solution is to enhance the performance of the training for the air traffic controllers (ATCs) and to build uniform training procedures and standardized training content, which constitute a shared framework with ontology knowledge. Taking departure operation control processes as an example, the research analyzes an aviation organization framework, with information communication procedures and relevant knowledge assets from the viewpoint of departure processes, to explore a knowledge management model of aviation control. This research studies how explicit knowledge is transformed by CommonKADS methodology using the CommonKADS sheet, and the Unified Modeling Language (UML) graph presentation and ontology model are discussed in this research. This analysis procedure can be applied to the systematic analysis and establishment of similar business-based information systems, allowing this research result to be further shared in different industries

Electric Vehicle Charging Scheduling Strategy for Supporting Load Flattening Under Uncertain Electric Vehicle Departures

The scheduled electric vehicle(EV)charging flexibility has great potential in supporting the operation of power systems,yet achieving such benefits is challenged by the uncertain and user-dependent nature of EV charging behavior.Existing research primarily focuses on modeling the uncertain EV arrival and battery status yet rarely discusses the uncertainty in EV departure.In this paper,we investigate the EV charging scheduling strategy to support load flattening at the distribution level of the utility grid under uncertain EV departures.A holistic methodology is proposed to formulate the unexpected trip uncertainty and mitigate its negative impacts.To ensure computational efficiency when large EV fleets are involved,a distributed solution framework is developed based on the alternating direction method of multipliers(ADMM)algorithm.The numerical results reveal that unexpected trips can severely damage user convenience in terms of EV energy content.It is further confirmed that by applying the proposed methodology,the resultant critical and sub-critical user convenience losses due to scheduled charging are reduced significantly by 83.5%and 70.5%,respectively,whereas the load flattening performance is merely sacrificed by 17%.

毫米波通信的低复杂度时变信道估计算法

当毫米波通信系统工作于时变信道场景中时,为解决通信用户快速位移导致的方位角计算误差和信道估计算法精度下降等问题,通常要消耗大量计算资源。因此,基于用户在快时变信道场景下的信号传输特征,首先在确定毫米波传输信号方位时采用对角加载方法,根据高斯白噪声先验信息得到对角加载方法的参数;然后采用对角带矩阵分解方法对所得到的信道干扰矩阵模型进行处理,从而降低信道估计与均衡算法的复杂度。仿真结果表明,所提算法能够使工作在时变信道条件下的通信系统以低于常规算法的运算复杂度处理系统中的干扰,且不降低传输性能。