Wind Effect Analysis on Air Traffic Congestion in Terminal Area via Cellular Automata

Enayatollahi, Fatemeh; Atashgah, M. A. Amiri

doi:10.3846/aviation.2018.6252

Cited by 5 publications

(3 citation statements)

References 27 publications

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“…Wang et al [57] and Lim et al [58] adopted a two-dimensional CA model for en-route airspace by combining optimization techniques, to search for flight paths that avoid prohibited airspace, restricted airspace, and dangerous airspace. Enayatollahi et al [59] [60] constructed a two-dimensional CA model considering a standard terminal arrival route (STAR) to investigate the impact of weather on delays and to optimize the flight path following performancebased navigation (PBN). Most studies have not focused on constructing a CA model in the global airspace, such as Japan and Europe, but in terminal airspace or specific enroute airspace.…”

Section: A Cellular Automatonmentioning

confidence: 99%

Multi-Objective Takeoff Time Optimization Using Cellular Automaton-Based Simulator

et al. 2021

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Although schedule design has further potential to reduce airline operation costs and flight delay, the effectiveness of the globally optimal schedule design integrating air traffic flow has not been discussed thus far. This paper presents a global multi-objective takeoff time optimization to design efficient flight schedules that lead to minimal congestion and provide sufficient resilience against traffic problems. NSGA-II is adopted as the multi-objective optimization technique in this study. The objective functions include minimization of the total arrival delay and total fuel consumption because these are key performance indicators of air traffic management (ATM). The design variable used in this study is the takeoff time offset of each flight landing at the Tokyo International Airport. 607 design variables were used in this study. The range of the design variables was ±300 s to investigate the effect of a minor variation in the takeoff time. A cellular automaton-based model was utilized to simulate the interaction of the flights with each other. The results of the simulations demonstrated that the obtained optimal solutions could drastically reduce the total arrival delay and total fuel consumption by 1500 min and 80 tons, respectively. The spacing adjustments of one of the optimum flight schedules, in comparison to the original flight schedule, were reduced by 80% in the en-route and terminal airspaces. Additional analyses suggest that it is preferable to have longer takeoff time intervals for flights originating from the same point during congestion hours than those during non-congestion hours. This indicates that the optimization of ground movements in airports improves the efficiency of air traffic operations. INDEX TERMSAir traffic control, air traffic management, cellular automaton, flight scheduling, ground holding program, NSGA-II, schedule design

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Section: A Cellular Automatonmentioning

confidence: 99%

Multi-Objective Takeoff Time Optimization Using Cellular Automaton-Based Simulator

et al. 2021

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“…By the advent of a new generation of technologies in robotics, a new idea called "Cooperative Robotics" (CR) has recently emerged to achieve complex missions (Enayatollahi & Atashgah, 2018;Kemsaram et al, 2017). This concept was rapidly embraced and developed in the field of AR as well.…”

Section: Introductionmentioning

confidence: 99%

Analytical Expression for Uncertainty Propagation of Aerial Cooperative Navigation

2021

Self Cite

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In this paper, the propagation of uncertainty in a cooperative navigation algorithm (CNA) for a group of flying robots (FRs) is investigated. Each FR is equipped with an inertial measurement unit (IMU) and range-bearing sensors to measure the relative distance and bearing angles between the agents. In this regard, an extended Kalman filter (EKF) is implemented to estimate the position and rotation angles of all the agents. For further studies, a relaxed analytical performance index through a closed-form solution is derived. Moreover, the effects of the sensors noise covariance and the number of FRs on the growth rate of the position error covariance is investigated. Analytically, it is shown that the covariance of position error in the vehicles equipped with the IMU is proportional to the cube of time. However, the growth rate of the navigation error is, considerably more rapid compared to a mobile robot group. Furthermore, the covariance of position error is independent of the path and noise resulting from the relative position measurements. Further, it merely depends on both the size of the group and noise characteristics of the accelerometers. Lastly, the analytical results are validated through comprehensive Guidance, Navigation, and Control (GNC) in-the-loop simulations.

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“…The demand is driven by scheduled flight plans and operational deviations on the day of operations [4]. These deviations could result from several sources [5], [6], such as system immanent uncertainties (e.g., reactionary delay [7], [8]), disturbance from external factors (e.g., weather condi-tions at airports [9] or effects of changing wind conditions during flight [10], [11]), disruptions of flights (e.g., cancellations [12], use of alternate airports [13]), or airspace operations (e.g., reduced sector capacity by activated temporary restricted areas [14]).…”

Section: Introductionmentioning

confidence: 99%

Implementation of a Long-Range Air Traffic Flow Management for the Asia-Pacific Region

Schultz¹,

Lubig

Asadi

et al. 2021

IEEE Access

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We provide a concept of operations and a corresponding implementation of a long-range air traffic flow management in the Asia-Pacific region. This management will provide an appropriate demandcapacity balancing considering both aircraft sequencing by local arrival management procedures and flow optimization to prevent over-demand in the approach area around the airport. Thus, coordination of longrange international flights demands collaboration between different flight information regions and local regulations. As Singapore Changi Airport is a central element of the Asia-Pacific flow management high share of long-haul air traffic, we use this airport to demonstrate our approach. To derive the operational conditions and actual traffic patterns at the airport, ADS-B messages and flight plan information are processed. The data are cleaned, analyzed, and filtered to provide information about arrival flows within given distances to the airport. We provide an efficacy analysis of the long-range air traffic flow management using two approaches. First, we applied a mixed-integer optimization of time shifts of normal distributed flight times. Here, the regulation of long-range flights by time shifts (e.g., achieved by speed advisories) shows a significant relief from periods of over-demand at the airport approach sector. Second, we implement a reference and a test case scenario in an agent-based simulation environment including the local arrival management procedures. Here, the number of holdings and the associated holding time could be reduced by at least 26%.

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Wind Effect Analysis on Air Traffic Congestion in Terminal Area via Cellular Automata

Cited by 5 publications

References 27 publications

Multi-Objective Takeoff Time Optimization Using Cellular Automaton-Based Simulator

Multi-Objective Takeoff Time Optimization Using Cellular Automaton-Based Simulator

Analytical Expression for Uncertainty Propagation of Aerial Cooperative Navigation

Implementation of a Long-Range Air Traffic Flow Management for the Asia-Pacific Region

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