The Experts below are selected from a list of 228 Experts worldwide ranked by ideXlab platform

Magnus Egerstedt - One of the best experts on this subject based on the ideXlab platform.

  • CDC - Distributed scheduling for air traffic throughput maximization during the terminal Phase of Flight
    49th IEEE Conference on Decision and Control (CDC), 2010
    Co-Authors: Rahul Chipalkatty, Philip Twu, Amir Rahmani, Magnus Egerstedt
    Abstract:

    © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 49th IEEE Conference on Decision and Control, December 15-17, 2010, Hilton Atlanta Hotel, Atlanta, GA, USA.DOI: 10.1109/CDC.2010.5717934FAA’s NextGen program aims at increasing the capacity of the national airspace, while ensuring the safety of aircraft. This paper provides a distributed merging and spacing algorithm that maximizes the throughput at the terminal Phase of Flight using the information provided through the ADS-B framework. Using dual decomposition, aircraft negotiate with each other and reach an agreement on optimal merging times, with respect to an associated cost, that ensures proper inter-aircraft spacing. We provide a feasibility analysis that gives sufficient conditions to guarantee that proper spacing is achievable and derive maximum throughput controllers based on the air traffic characteristics of the merging Flight path

  • Air traffic maximization for the terminal Phase of Flight under FAA's NextGen framework
    29th Digital Avionics Systems Conference, 2010
    Co-Authors: Philip Twu, Rahul Chipalkatty, Amir Rahmani, Magnus Egerstedt, Ryan Young
    Abstract:

    © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 29th IEEE/AIAA Digital Avionics Systems Conference (DASC), 3-7 October 2010, Salt Lake City, Utah.DOI: 10.1109/DASC.2010.5655490The NextGen program is the FAA's response to the ever increasing air traffic, that provides tools to increase the capacity of national airspace, while ensuring the safety of aircraft. In support of this vision, this paper provides a decentralized algorithm based on dual decomposition for safe merging and spacing of aircraft at the terminal Phase of the Flight. Aircraft negotiate optimal merging times that ensure safety, while penalizing deviations from the nominal path. We provide feasibility conditions for the safe merging of all incoming legs of Flight and put the viability of the proposed algorithm to the test through simulations

Rahul Chipalkatty - One of the best experts on this subject based on the ideXlab platform.

  • CDC - Distributed scheduling for air traffic throughput maximization during the terminal Phase of Flight
    49th IEEE Conference on Decision and Control (CDC), 2010
    Co-Authors: Rahul Chipalkatty, Philip Twu, Amir Rahmani, Magnus Egerstedt
    Abstract:

    © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 49th IEEE Conference on Decision and Control, December 15-17, 2010, Hilton Atlanta Hotel, Atlanta, GA, USA.DOI: 10.1109/CDC.2010.5717934FAA’s NextGen program aims at increasing the capacity of the national airspace, while ensuring the safety of aircraft. This paper provides a distributed merging and spacing algorithm that maximizes the throughput at the terminal Phase of Flight using the information provided through the ADS-B framework. Using dual decomposition, aircraft negotiate with each other and reach an agreement on optimal merging times, with respect to an associated cost, that ensures proper inter-aircraft spacing. We provide a feasibility analysis that gives sufficient conditions to guarantee that proper spacing is achievable and derive maximum throughput controllers based on the air traffic characteristics of the merging Flight path

  • Air traffic maximization for the terminal Phase of Flight under FAA's NextGen framework
    29th Digital Avionics Systems Conference, 2010
    Co-Authors: Philip Twu, Rahul Chipalkatty, Amir Rahmani, Magnus Egerstedt, Ryan Young
    Abstract:

    © 2010 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.Presented at the 29th IEEE/AIAA Digital Avionics Systems Conference (DASC), 3-7 October 2010, Salt Lake City, Utah.DOI: 10.1109/DASC.2010.5655490The NextGen program is the FAA's response to the ever increasing air traffic, that provides tools to increase the capacity of national airspace, while ensuring the safety of aircraft. In support of this vision, this paper provides a decentralized algorithm based on dual decomposition for safe merging and spacing of aircraft at the terminal Phase of the Flight. Aircraft negotiate optimal merging times that ensure safety, while penalizing deviations from the nominal path. We provide feasibility conditions for the safe merging of all incoming legs of Flight and put the viability of the proposed algorithm to the test through simulations

Shaojun Feng - One of the best experts on this subject based on the ideXlab platform.

  • Carrier Phase-based integrity monitoring for high-accuracy positioning
    GPS Solutions, 2009
    Co-Authors: Shaojun Feng, Washington Ochieng, Terry Moore, Chris Hill, Chris Hide
    Abstract:

    Pseudorange-based integrity monitoring, for example receiver autonomous integrity monitoring (RAIM), has been investigated for many years and is used in various applications such as non-precision approach Phase of Flight. However, for high-accuracy applications, carrier Phase-based RAIM (CRAIM), an extension of pseudorange-based RAIM (PRAIM) must be used. Existing CRAIM algorithms are a direct extension of PRAIM in which the carrier Phase ambiguities are estimated together with the estimation of the position solution. The main issues with the existing algorithms are reliability and robustness, which are dominated by the correctness of the ambiguity resolution, ambiguity validation and error sources such as multipath, cycle slips and noise correlation. This paper proposes a new carrier Phase-based integrity monitoring algorithm for high-accuracy positioning, using a Kalman filter. The ambiguities are estimated together with other states in the Kalman filter. The double differenced pseudorange, widelane and carrier Phase observations are used as measurements in the Kalman filter. This configuration makes the positioning solution both robust and reliable. The integrity monitoring is based on a number of test statistics and error propagation for the determination of the protection levels. The measurement noise and covariance matrices in the Kalman filter are used to account for the correlation due to differencing of measurements and in the construction of the test statistics. The coefficient used to project the test statistic to the position domain is derived and the synthesis of correlated noise errors is used to determine the protection level. Results from four cases based on limited real data injected with simulated cycle slips show that residual cycle slips have a negative impact on positioning accuracy and that the integrity monitoring algorithm proposed can be effective in detecting and isolating such occurrences if their effects violate the integrity requirements. The CRAIM algorithm proposed is suitable for use within Kalman filter-based integrated navigation systems.

  • A measurement domain receiver autonomous integrity monitoring algorithm
    GPS Solutions, 2006
    Co-Authors: Shaojun Feng, David Walsh, Washington Yotto Ochieng, R. Ioannides
    Abstract:

    One of the key approaches to monitor the integrity of Global Satellite Navigation Systems (GNSS) is receiver autonomous integrity monitoring (RAIM). Existing RAIM algorithms utilise two tests in the position domain (for RAIM availability) and measurement domain (for failure detection). This paper proposes an alternative RAIM algorithm, which is based entirely in the measurement domain. This algorithm can be used for sensitivity analyses to support performance specification and system design. It can also be used during actual Flight operations where the trigger is the Phase of Flight and its required navigation performance (RNP) parameters. This is made possible by computationally effcient calculation of the chi-squared parameters. The algorithm reverts to the current approach if the Phase of Flight is unknown. Simulation result for non-precision approach (NPA) have been used to demonstrate the effectiveness of the proposed algorithm.

Tomas Gronstedt - One of the best experts on this subject based on the ideXlab platform.

Gregory Belenky - One of the best experts on this subject based on the ideXlab platform.

  • 0244 Examining Pilot Safety Performance Indicators at Critical Phases of Flight Across Multiple Flight Legs During Commercial Airline Trips
    Sleep, 2020
    Co-Authors: Amanda Lamp, R N Soriano Smith, Ian Rasmussen, C Keller, E Basiarz, Gregory Belenky
    Abstract:

    Abstract Introduction Prior simulation and operational studies have started to address whether the number of consecutive Flight segments negatively affects cognitive performance, fatigue, and sleepiness, without reaching a clear consensus. This study expands this literature by determining whether there are significant changes in cognitive performance, fatigue, and sleepiness at critical Phases of Flight across multiple Flight segments, while accounting for the number of segments, Flight direction, trip day, and time-of-day. Methods Fifty commercial airline pilots were studied. Each pilot flew two separate short-haul trips, each ranging from 1–4 days and 1–10 Flight segments. Cognitive performance, fatigue, and sleepiness were assessed at top-of-climb (TOC) and top-of-descent (TOD) of each Flight segment and each trip day. Cognitive performance, fatigue, and sleepiness were assessed using Psychomotor Vigilance Task (PVT) speed, Samn-Perelli (SP) ratings, and Karolinska Sleepiness Scale (KSS) ratings, respectively. Data were analyzed using Wilcoxon t-tests and verified using ANOVAs. Results Mean PVT speed (Cohen’s d =0.57), SP ratings (Cohen’s d = 0.73), and KSS ratings (Cohen’s d = 0.63) were significantly worse at TOD than TOC (p < 0.001); and, significantly varied across Flight segments (p<0.001). Cognitive performance, fatigue, and sleepiness were consistently and significantly degraded around the fifth Flight segment, improved around the sixth to eighth Flights segments, and were subsequently degraded around the eighth to tenth Flight segments. Conclusion The results indicate that cognitive performance, fatigue, and sleepiness vary across Flight segments, trip day, and Phase of Flight. Results suggest that these safety performance indices degrade after five segments, and further degrade after eight Flight segments. The results presented could be used to inform future airline scheduling and regulation. Support This work has been supported by United Airlines.