Аналіз затримок повітряних кораблів на етапі прибуття до аеропорту

Delays in arrival phase of flight depend on the manner in which airspace is organized, the application oftechnology and runway availability. Service process at the stage of arrival at airport is modeled. Service rate at airportthat has influence on waiting time for landing is analyzed.Смоделирован процесс обслуживания воздушных судов на этапе прибытия в аэропорт. Проанализирована скорость обслуживания воздушных судов в аэропорту, влияющая на время ожидания посадки. Рассмотрены причины задержки обслуживания воздушных судов на этапе прибытия в аэропорт: неэффективная организация воздушного пространства, применение устаревших технологий, доступность взлетно-посадочной полосы. Показано, что чем больше частота запросов на обслуживание к пропускной способности, тем более чувствительна ожидаемая задержка на изменения в системе.Змодельовано процес обслуговування повітряних кораблів на етапі прибуття до аеропорту. Проаналізовано швидкість обслуговування повітряних кораблів в аеропорту, яка впливає на час очікування посадки. Розглянуто причини затримки обслуговування повітряних кораблів на етапі прибуття до аеропорту: неефективна організація повітряного простору, застосування застарілих технологій, доступність злітно-посадкової смуги. Показано, що чим більша частота запитів на обслуговування до пропускної здатності, тим більш чутлива очікувана затримка на зміни в системі

Applications of stochastic modeling in air traffic management:Methods, challenges and opportunities for solving air traffic problems under uncertainty

In this paper we provide a wide-ranging review of the literature on stochastic modeling applications within aviation, with a particular focus on problems involving demand and capacity management and the mitigation of air traffic congestion. From an operations research perspective, the main techniques of interest include analytical queueing theory, stochastic optimal control, robust optimization and stochastic integer programming. Applications of these techniques include the prediction of operational delays at airports, pre-tactical control of aircraft departure times, dynamic control and allocation of scarce airport resources and various others. We provide a critical review of recent developments in the literature and identify promising research opportunities for stochastic modelers within air traffic management

Uncertainty management at the airport transit view

Air traffic networks, where airports are the nodes that interconnect the entire system, have a time-varying and stochastic nature. An incident in the airport environment may easily propagate through the network and generate system-level effects. This paper analyses the aircraft flow through the Airport Transit View framework, focusing on the airspace/airside integrated operations. In this analysis, we use a dynamic spatial boundary associated with the Extended Terminal Manoeuvring Area concept. Aircraft operations are characterised by different temporal milestones, which arise from the combination of a Business Process Model for the aircraft flow and the Airport Collaborative Decision-Making methodology. Relationships between factors influencing aircraft processes are evaluated to create a probabilistic graphical model, using a Bayesian network approach. This model manages uncertainty and increases predictability, hence improving the system's robustness. The methodology is validated through a case study at the Adolfo Suárez Madrid-Barajas Airport, through the collection of nearly 34,000 turnaround operations. We present several lessons learned regarding delay propagation, time saturation, uncertainty precursors and system recovery. The contribution of the paper is two-fold: it presents a novel methodological approach for tackling uncertainty when linking inbound and outbound flights and it also provides insight on the interdependencies among factors driving performance

Intersystem soft handover for converged DVB-H and UMTS networks

Digital video broadcasting for handhelds (DVB-H) is the standard for broadcasting Internet Protocol (IP) data services to mobile portable devices. To provide interactive services for DVB-H, the Universal Mobile Telecommunications System (UMTS) can be used as a terrestrial interaction channel for the unidirectional DVB-H network. The converged DVB-H and UMTS network can be used to address the congestion problems due to the limited multimedia channel accesses of the UMTS network. In the converged network, intersystem soft handover between DVB-H and UMTS is needed for an optimum radio resource allocation, which reduces network operation cost while providing the required quality of service. This paper deals with the intersystem soft handover between DVB-H and UMTS in such a converged network. The converged network structure is presented. A novel soft handover scheme is proposed and evaluated. After considering the network operation cost, the performance tradeoff between the network quality of service and the network operation cost for the intersystem soft handover in the converged network is modeled using a stochastic tree and analyzed using a numerical simulation. The results show that the proposed algorithm is feasible and has the potential to be used for implementation in the real environment

Observation and Analysis of Departure Operations at Boston Logan International Airport

The Departure Planner (DP) is a concept for a decision-aiding tool that is aimed at improving the departure operations performance at major congested airports. In order to support the development of the DP tool, the flow constraints and their causalities in the departure process - primarily responsible for generating inefficiencies and delays- need to be identified. This thesis is an effort to identify such flow constraints and gain a deep understanding of the underlying dynamics of the departure process based on field observations and data analysis at Boston Logan International Airport. It was observed that the departure process is a complex interactive queuing system, where aircraft queues form as a manifestation of the flow constraints. While departure delays were observed in all airport components (runways, taxiways, ramps and gates), it was concluded that the flow constraints manifest mainly at the runway system, which exhibits the largest delays and queues. Major delays and inefficiencies were also observed due to downstream flow constraints, which propagate back and block the departure flow from the airport. It was also observed that the airport system is a highly controlled system as the air traffic controllers manage the flow constraints. The air traffic controllers were, therefore, identified as another flow constraint due to their workload and their main strategies in managing the flow constraints were observed. Based on the observations, a core departure process was identified consisting of two main elements: a queuing element generated by the flow constraints and a control element representing the air traffic controller actions. This core process was abstracted using a controlled queuing framework, where the air traffic controller actions are represented by blocking the flow of aircraft in order to maintain safe operation of the airport resources according to the ATC rules and procedures and regulate the outbound flow to constrained downstream resources. The controlled queuing framework was used to analyze the departure process highlighting the queuing dynamics and the control behavior for different flow constraint examples. In conclusion, a number of implications for the Departure Planner and other improved methods for departure operations are inferred from the observations and analysis.This work was supported by the National Aeronautics and Space Administration Ames Research Center under grant NAG 2-1128

Queuing analysis and optimization of public vehicle transport stations: A case of South West Ethiopia region vehicle stations

Modern urban environments present a dynamically growing field where, notwithstanding shared goals, several mutually conflicting interests frequently collide. However, it has a big impact on the city's socioeconomic standing, waiting lines and queues are common occurrences. This results in extremely long lines for vehicles and people on incongruous routes, service coagulation, customer murmuring, unhappiness, complaints, and looking for other options, sometimes illegally. The root cause is corruption, which leads to traffic jams, stops and packs vehicles beyond their safe carrying capacity, and violates passengers' human rights and freedoms. This study focused on optimizing the time passengers had to wait in public vehicle stations. This applied research employed both data-gathering sources and mixed approaches. Then, 166 samples of key informants of transport stations were taken using the Slovin sampling formula. The time vehicles, including the drivers and auxiliary drivers ‘Weyala', had to wait was also studied. To maximize the service level at vehicle stations, a queuing model was subsequently devised ‘Menaharya’. Time, cost, and quality encompass performance, scope, and suitability for the intended purposes. The study also focused on determining the minimal response time required for passengers and vehicles queuing to reach their ultimate destinations within the transportation stations in Tepi, Mizan, and Bonga. A new bus station system was modeled and simulated by Arena simulation software in the chosen study area. 84% improvement on cost reduced by 56.25%, time 4 hours to 1.5 hours, quality, safety and designed load performance calculations employed. Stakeholders are asked to implement the model and monitor the results obtained

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv