Download or read book Optimal Sequencing and Scheduling Algorithm for Traffic Flows Based on Extracted Control Actions Near the Airport written by Sharmistha Chakrabarti and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation seeks to design an optimization algorithm, based on naturalistic flight data, with emphasis on safety to perform a benefits' analysis when sequencing and scheduling aircraft at the runway. The viability of creating a decision-support tool to aid air traffic controllers in sequencing and optimizing airport operations is evaluated through the benefits' analysis. Air traffic control is a complex and critical system that ensures the safe and efficient movement of aircraft within the airspace. This is particularly true in the immediate vicinity of an airport. Unlike in en-route or terminal area airspace where aircraft usually traverse well established routes and procedures, near the airport after completing a standard arrival procedure, the routes to the final approach are only partially defined. With safety being the foremost priority, the local tower controllers monitor and maintain separation between aircraft to prevent collisions and ensure the overall safety of the airspace. This involves constant surveillance, coordination, and decision-making to manage the dynamic movement of aircraft, changing weather conditions, and potential hazards. All the while, the controllers make decisions regarding tromboning or vectoring based on various factors, including traffic volume, airspace restrictions, weather conditions, operational efficiency, and safety considerations to ensure a safe traffic sequencing of aircraft at the runway. A novel framework is presented for modeling, characterizing, and clustering aircraft trajectories by extracting traffic control decisions of air traffic controllers. A hidden Markov model was developed and applied to transform trajectories from a sequence of temporal spatial position reports to a series of control actions. The edit distance is utilized for quantifying the dissimilarity of two variable-length trajectory strings, followed by the application of k-medoids algorithm to cluster the arrival flows. Next, a repeatable process for detecting and labeling outlier trajectories within a cluster is introduced. Through application on a set of historical trajectories at Ronald Reagan Washington National Airport (DCA), it is demonstrated that the proposed clustering framework overcomes the deficiency of the classical approach and successfully captures the arrival flows of trajectories, that undergo similar control actions. Leveraging on the set of arrival flows, statistical and machine learning models of air traffic controllers are created and evaluated when ordering aircraft to land at the runway. The potential inefficiencies are identified at DCA when sequencing aircraft. As such, there is a potential performance gap, and it appears that there is room for additional sequence optimization. With the goal of overcoming the potential inefficiencies at DCA, a mixed-integer zero-one formulation is designed for a single runway that takes into consideration safety constraints by means of separation constraints between aircraft imposed at each metering point from the entry to the airspace until landing. With the objective of maximizing runway throughput and minimizing the traversed distance, the model sequences and schedules arrivals and departures and generates safe and conflict-free arrival trajectories to actualize that scheduling. The output of the optimization shows that the model successfully recovers approximately 52% of the performance gap between the actual distance traversed and idealized (cluster centroids) distance traversed by all arrival aircraft. Moreover, each arrival aircraft, on average, traverses 2.12 nautical miles shorter than its historical trajectory and thus saving approximately 10 US gallons of jet fuel. By showcasing the potential benefits of the optimization, this dissertation takes a step towards achieving the long-term vision of developing a decision-support tool to assist air traffic controllers in optimally sequencing and scheduling aircraft. To fully leverage the potential benefits of optimization, further development and refinement of the algorithm are necessary to align it with real-world operational demands. As future work, the research would be expanded to integrate uncertainties like weather conditions, wind directions, etc. into the optimization.

Download or read book Efficient Algorithms for Optimal Arrival Scheduling and Air Traffic Flow Management written by Aditya Saraf and published by . This book was released on 2007 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research presented in this dissertation is motivated by the need for new, efficient algorithms for the solution of two important problems currently faced by the air-traffic control community: (i) optimal scheduling of aircraft arrivals at congested airports, and (ii) optimal National Airspace System (NAS) wide traffic flow management. In the first part of this dissertation, we present an optimal airport arrival scheduling algorithm, which works within a hierarchical scheduling structure. This structure consists of schedulers at multiple points along the arrival-route. Schedulers are linked through acceptance-rate constraints, which are passed up from downstream metering-points. The innovation in this scheduling algorithm is that these constraints are computed by using an Eulerian model-based optimization scheme. This rate computation removes inefficiencies introduced in the schedule through ad hoc acceptance-rate computations. The scheduling process at every metering-point uses its optimal acceptance-rate as a constraint and computes optimal arrival sequences by using a combinatorial search-algorithm. We test this algorithm in a dynamic air-traffic environment, which can be customized to emulate different arrival scenarios. In the second part of this dissertation, we introduce a novel two-level control system for optimal traffic-flow management. The outer-level control module of this two-level control system generates an Eulerian-model of the NAS by aggregating aircraft into interconnected controlvolumes. Using this Eulerian model of the airspace, control strategies like Model Predictive Control are applied to find the optimal inflow and outflow commands for each control-volume so that efficient flows are achieved in the NAS. Each control-volume has its separate innerlevel control-module. The inner-level control-module takes in the optimal inflow and outflow commands generated by the outer control-module as reference inputs and uses hybrid aircraft models to search for optimal trajectories to be flown by each aircraft so that the flows commanded by the outer control-module are achieved. The two-level control system is tested in a dynamic simulation. Furthermore, as a component of the Eulerian part of this two-level system, we present a method for deriving an aggregate airspace-model in real-time, without depending on online integration of aircraft trajectories. This method uses a baseline Eulerian airspace-model, which is derived offline using historical track-data. In real-time, parameters of this model are adapted depending on the differences between the baseline-model and the real-world. This book-keeping based model-derivation indirectly retains some trajectory information. Hence, it serves as an excellent trade-off between Eulerian and trajectory-based modeling approaches. Most importantly, as a vital improvement over previous approaches, we take into consideration the control-dependent nature of the Eulerian-model while computing optimal flow-control decisions. As a proof of concept, we derive a baseline model for the Fort-Worth center and adapt it to predict sector-counts for another set of air traffic data. We also demonstrate the use of this model in a simulation-based optimization scheme for regulating the arrival flow at the Dallas Fort-Worth airport. An application to optimal re-routing strategy computation is also presented.

Download or read book Analysis of Sequencing and Scheduling Methods for Arrival Traffic written by National Aeronautics and Space Administration (NASA) and published by Createspace Independent Publishing Platform. This book was released on 2018-07-06 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: The air traffic control subsystem that performs scheduling is discussed. The function of the scheduling algorithms is to plan automatically the most efficient landing order and to assign optimally spaced landing times to all arrivals. Several important scheduling algorithms are described and the statistical performance of the scheduling algorithms is examined. Scheduling brings order to an arrival sequence for aircraft. First-come-first-served scheduling (FCFS) establishes a fair order, based on estimated times of arrival, and determines proper separations. Because of the randomness of the traffic, gaps will remain in the scheduled sequence of aircraft. These gaps are filled, or partially filled, by time-advancing the leading aircraft after a gap while still preserving the FCFS order. Tightly scheduled groups of aircraft remain with a mix of heavy and large aircraft. Separation requirements differ for different types of aircraft trailing each other. Advantage is taken of this fact through mild reordering of the traffic, thus shortening the groups and reducing average delays. Actual delays for different samples with the same statistical parameters vary widely, especially for heavy traffic. Neuman, Frank and Erzberger, Heinz Ames Research Center...

Download or read book Analysis of Sequencing and Scheduling Methods for Arrival Traffic written by and published by . This book was released on 1990 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Bi level Optimization Algorithm for Dynamic Reversible Lane Control Based on Short term Ttraffic Flow Prediction written by Chenxi Liu and published by . This book was released on 2020 with total page 85 pages. Available in PDF, EPUB and Kindle. Book excerpt: Traffic congestion is a more and more serious problem all over the world. Reversible lanes have been used throughout the world to mitigate the effects of congestion and optimize roadway performance for more than 80 years. They have been applied on a variety of roadway types using different control methods to address an assortment of needs. However, the limited traditional control methods can not meet the increasing various demands. To address the needs of the freeway scenario, the study introduces a bi-level method based on short-term traffic flow prediction for the dynamic reversible lane control algorithm. The work improves the traditional traffic management method, reversible lane control, from static control to dynamic real-time traffic management. Taking advantage of the development of neural network technology, the input of the algorithm covers not only historical data and real-time data but also the predicted data. Advanced Bi-directional Long Short-term Memory (Abi-LSTM) model is employed for the short-term traffic flow prediction. For the control algorithm, the study introduces the bi-level optimization method to maximize the total traffic flow in both directions which determine the lane deployment. Also, the study considers the user costs in the lower level optimization formula. Finally, the study builds up a simulation to test the effect of the dynamic reversible lane control algorithm.

Download or read book Simulation based Integrated Control Algorithm for Controlling Shockwave Propagation on Freeways and Queue Spillback at On ramps written by Karteek Kumar Allam and published by . This book was released on 2015 with total page 95 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heavy traffic flow entering the freeway mainline can cause or worsen congestion on the freeway mainline due to interrupted on-ramp traffic. In order to address this problem, Freeway ramp metering systems are usually deployed to improve the traffic flow on urban freeways. These systems are attended to improve the flow on the freeway by regulating the on-ramp rate entering the freeway. However, amongst all the possible factors contributing to traffic congestion on freeways and arterials connected via ramps, lack of coordination in the operation of various system components is a major source of inefficiency at freeway and ramp conjunctions. Various ramp metering algorithms have been developed in an attempt to solve the unsystematic problem in coordinating the control of freeway, and arterials. Nevertheless, most of the algorithms control actions were selected based on either pre-defined plans or detected traffic condition. Implementation of the algorithms on the field is also a concern because of its excessive data requirements of these algorithms. Furthermore, existence of a range of flow rates in synchronized flow traffic can cause breakdown due to internal perturbations. Many algorithms failed to address the issue of worsening freeway congestion due to upstream traffic at the on-ramp. This research will formulate an integrated ramp metering control algorithm, using real time traffic measurements. Multiple priority objectives are explicitly set up to delay the congestion due to internal perturbations, maintain the throughput of freeway, and to prevent on-ramp vehicles from overflowing into arterials. This algorithm is also formulated to minimize the delays and control the shockwave propagation from the merge location of the on-ramp and the freeway. In order to measure the effectiveness, the proposed algorithm is compared with a traffic responsive algorithm, such as ALINEA (Asservissement LINeaire d'Entree Autoroutiere), and proposed recommendations accordingly. Considering the importance of gap acceptance and internal perturbations in the current research, calibration of the simulation model was conducted. For this purpose, video data was collected capturing the traffic at the merge location of the freeway and on-ramp, from which the accepted gaps and headways of the vehicles merging into the freeway have been extracted. This was given as an input to the VISSIM simulation model for calibration. The simulation test results indicate that the proposed integrated ramp metering algorithm is more effective than the ALINEA and Fixed Time ramp metering algorithms in terms of reducing the system delays and travel time on the freeway, and minimizing the freeway breakdown. Additionally, the proposed algorithm works efficiently at the ramp traffic flow of no more than 580 veh/hr. In other words, the ALINEA likely outperforms the proposed algorithm as the ramp traffic exceeds 580 veh/hr. The contribution of the research will be reflective of the following aspects: 1) developing a method with a supportive algorithm for minimizing the shockwave propagation by dampening shockwave formation of mainline freeway traffic; 2) developing a method with a supportive algorithm to reduce mainline freeway shockwaves by dispatching vehicles from the on-ramp at a flow rate that can best fit in the observed gaps to be available from the freeway traffic; 3) identifying the minimum accepted gaps at the merge location from video observation to develop appropriate gap acceptance parameters; and 4) developing an integrated computing system to provide a fundamental platform for further functionality expansion in the future for study of a multiple-ramp situation at a freeway system.

Download or read book Intelligence Artificielle Dans la Gestion Du Trafic A rien written by North Atlantic Treaty Organization. Advisory Group for Aerospace Research and Development. Guidance and Control Panel. Symposium and published by . This book was released on 1993 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book A Novel Framework for Real time Traffic Flow Parameter Estimation from Aerial Videos written by Ruimin Ke and published by . This book was released on 2016 with total page 78 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unmanned aerial vehicles (UAVs) are gaining popularity in traffic monitoring due to their low cost, high flexibility, and wide view range. Traffic flow parameters such as speed, density, and volume extracted from UAV-based traffic video are critical for traffic state estimation and traffic control, and has recently received more and more attention from researchers. However, different from stationary surveillance videos, the camera platforms move with UAVs and the motion in aerial videos makes it very challenging to process for data extraction. To address this problem, a novel framework composed of two complementary approaches for real-time traffic flow parameter estimation from aerial videos is proposed. The first approach is a motion-based approach, which identifies traffic streams and video background based on their motions using Kanade-Lucas-Tomasi (KLT) tracker and k-means clustering algorithm, and then extracts traffic flow parameters (speed, density, and volume) using connected graph and traffic flow theory. The second approach is a detection-based approach, which requires a vehicle detector training process. In this approach, vehicles from a top-view perspective are detected by the vehicle detector first and then the vehicle motion is estimated using KLT tracker as well as the background motion. Specifically, the vehicle detector is a combined cascaded classifier composed of Haar-like features and neural networks, making use of the fast processing speed of cascaded Haar classifier and the high detection rate of neural network. These two complementary approaches have their own advantages and together form the proposed framework for aerial video-based traffic flow parameter estimation. The system was tested on multiple aerial videos taken by UAVs operated in various scenarios including uncongested traffic condition, uncongested traffic condition, daytime, nighttime, UAV moving and UAV hovering. The experimental results show that the system is able to extract traffic flow speed, density and volume, and also achieves high performance in both traffic speed and vehicle count estimation in various challenging scenarios. The proposed system achieves a fast processing speed that enables real-time traffic information estimation.

Download or read book Optimizing Traffic Flow Based on Vehicle Count written by Jayaprabhu Ramamoorthy and published by . This book was released on 2017 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: One method to build an intelligent traffic control system is based on the estimation of traffic density using real-time video and image processing techniques. The idea is to control the traffic by determining the density on each side of the road and controlling the signal based on the density information. This project introduces an algorithm to determine the number of vehicles on each lane. The vehicle density can be compared with other directions in order to control the traffic signal and minimize the stop and wait time at intersections.

Download or read book Dissertation Abstracts International written by and published by . This book was released on 2001 with total page 832 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Optimization of Routing Sequencing and Scheduling in Airport Ground Movement Operations written by Gillian Louise Clare and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lists citations with abstracts for aerospace related reports obtained from world wide sources and announces documents that have recently been entered into the NASA Scientific and Technical Information Database.

Download or read book Multi agent Look ahead Traffic adaptive Control written by Ronald Theodoor Katwijk and published by . This book was released on 2008 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Computer Control Abstracts written by and published by . This book was released on 1996 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Linear and Nonlinear Optimization written by Igor Griva and published by SIAM. This book was released on 2009-03-26 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: Flexible graduate textbook that introduces the applications, theory, and algorithms of linear and nonlinear optimization in a clear succinct style, supported by numerous examples and exercises. It introduces important realistic applications and explains how optimization can address them.

Download or read book Automated Scheduling and Planning written by A. Sima Uyar and published by Springer. This book was released on 2013-07-12 with total page 311 pages. Available in PDF, EPUB and Kindle. Book excerpt: Solving scheduling problems has long presented a challenge for computer scientists and operations researchers. The field continues to expand as researchers and practitioners examine ever more challenging problems and develop automated methods capable of solving them. This book provides 11 case studies in automated scheduling, submitted by leading researchers from across the world. Each case study examines a challenging real-world problem by analysing the problem in detail before investigating how the problem may be solved using state of the art techniques.The areas covered include aircraft scheduling, microprocessor instruction scheduling, sports fixture scheduling, exam scheduling, personnel scheduling and production scheduling. Problem solving methodologies covered include exact as well as (meta)heuristic approaches, such as local search techniques, linear programming, genetic algorithms and ant colony optimisation.The field of automated scheduling has the potential to impact many aspects of our lives and work; this book highlights contributions to the field by world class researchers.

Download or read book Operations Research and Decision Aid Methodologies in Traffic and Transportation Management written by Martine Labbe and published by Springer Science & Business Media. This book was released on 1998-10-20 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a collection of state-of-the-art surveys on topics at the interface between transportation modeling and operations research given by leading international experts. Based on contributions to a NATO workshop, the surveys are up-to-date and rigorous presentations or applications of quantitative methods in the area. The subjects covered include dynamic traffic simulation techniques and dynamic routing in congested networks, operation and control of traffic management tools, optimized transportation data collection, and vehicle routing problems.