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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>Effect of Measurement Errors on Master Plane Representations of Target Position in an Air Traffic Control System</title>
      <link>https://trid.trb.org/View/2704020</link>
      <description><![CDATA[This report deals with formulations of the effects of errors in the measurement of slant range, azimuth, and altitude on master plane representations of target position in an air traffic control system supported by a multitude of surveillance radars. It is concerned with the case in which such representations are based on the method of stereographic projection. Special consideration is afforded the statistical characterization of fluctuations induced in the master plane by random measurement errors, and to confidence regions for target location that might be useful in the automatic tracking of aircraft. Emphasis is placed on noise levels commonly associated with Mode S and the Air Traffic Control Radar Beacon System (ATCRBS) under constraints consistent with the structure of coverage regions of domestic Air Route Traffic Control Centers (ARTCC's).]]></description>
      <pubDate>Mon, 08 Jun 2026 15:26:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2704020</guid>
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    <item>
      <title>Active Beacon Collision Avoidance Logic Evaluation: Volume IV, Interface (ATARS/BCAS/CIR) Phase</title>
      <link>https://trid.trb.org/View/2703677</link>
      <description><![CDATA[An evaluation of the Active Beacon Collision Avoidance System (BCAS), Automated Traffic Advisory and Resolution Service (ATARS), and the Conflict Indicator Register (CIR) interface logic was conducted at the Federal Aviation Administration Technical Center. The evaluation was performed using dynamic simulation. The test bed for the evaluation was the Fast-Time Encounter Generator (FTEG). The FTEG was modified to simulate a single ATARS/Discrete Address Beacon System (DABS) site environment. Current Active BCAS development plans are to replace the CIR with the resolution advisory register (RAR). Since the RAR must provide basically the same air-to-air BCAS coordination capability as the CIR logic, the deficiencies that were corrected in the CIR logic are relevant to the RAR logic. In all cases tested, the ATARS/BCAS interface logic permitted BCAS to resolve pop-up threats which were initially not detected by ATARS. Encounter conditions which resulted in BCAS alarms when ATARS did not alarm because of large horizontal miss distances were identified. Suppression of BCAS PWI (proximity warning  indicator) messages by ATARS in cases where BCAS had resolution responsibility was also detected.]]></description>
      <pubDate>Mon, 08 Jun 2026 15:26:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703677</guid>
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    <item>
      <title>En Route DABS/ATC Build II Testing</title>
      <link>https://trid.trb.org/View/2703680</link>
      <description><![CDATA[The primary purpose of these tests is to determine the performance of the aircraft control state (ACS) function in an en route environment. This function has been incorporated in the en route Discrete Address Beacon System/Air Traffic Control (DABS/ATC) Build II software system. It allows the en route DABS/ATC Build II system to perform primary/secondary assignments to DABS sensors for controlled aircraft within the sensor surveillance environment. Secondary objectives of this test activity are to evaluate the performance of the Build II startover function and to verify that the performance test results obtained during Build I testing can be achieved using the Build II software.]]></description>
      <pubDate>Mon, 08 Jun 2026 15:26:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703680</guid>
    </item>
    <item>
      <title>Project Plan for Electronic Tabular Display Subsystem (ETABS) Test and Evaluation</title>
      <link>https://trid.trb.org/View/2703679</link>
      <description><![CDATA[The Federal Aviation Administration (FAA) Technical Center will provide technical support to the Systems Research and Development Service (SRDS) Program Manager for Electronic Tabular Display Subsystem (ETABS) procurement, installation, and integration; conduct engineering acceptance tests; and prepare an operational evaluation of a prototype en route information processing system that will provide flight data handling functions for control sectors in Air Route Traffic Control Centers (ARTCC).]]></description>
      <pubDate>Mon, 08 Jun 2026 15:26:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703679</guid>
    </item>
    <item>
      <title>Test and Evaluation of the Discrete Address Beacon System (DABS) / Moving Target Detector (MTD) / Radar Data Acquisition Subsystem (RDAS)</title>
      <link>https://trid.trb.org/View/2703681</link>
      <description><![CDATA[The primary objectives of testing the Moving Target Detector (MTD) and the Radar Data Acquisition Subsystem (RDAS) as an integral part of the Discrete Address Beacon System (DABS) are to characterize their combined performance in: a. Providing radar/beacon correlation of DABS and Air Traffic Control Radar Beacon System (ATCRBS) targets with radar targets provided as an input to DABS from either the RDAS or MTD; b. Providing improved radar surveillance on aircraft not equipped with a beacon transponder for display and tracking purposes; and c. Providing weather information to an air traffic control (ATC) facility.]]></description>
      <pubDate>Mon, 08 Jun 2026 15:26:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703681</guid>
    </item>
    <item>
      <title>Design and Implementation of Efficient Algorithms for Automatic Determination of Corrected Slant Range</title>
      <link>https://trid.trb.org/View/2703882</link>
      <description><![CDATA[This report introduces a systematic approach to the design of algorithms for evaluating the corrected slant range in a radar surveillance system. Applications include air traffic control (ATC) operations requiring real-time continuous computation for a multitude of targets without overtaxing available computational resources. From the point of view of accuracy, utilization of memory, and computational speed, the design technique is capable of providing an algorithm that is superior to the corrected slant range technique presently employed in the National Airspace System (NAS).]]></description>
      <pubDate>Sun, 07 Jun 2026 17:29:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2703882</guid>
    </item>
    <item>
      <title>Summary of Transponder Data for Atlanta, Georgia, Area</title>
      <link>https://trid.trb.org/View/2701093</link>
      <description><![CDATA[The Federal Aviation Administration (FAA) Technical Center was requested by the FAA Southern Region in October 1979 to provide specialized support with the transponder performance analyzer (TPA) in their efforts to identify and localize Air Traffic Control Radar Beacon System (ATCRBS) coverage problems in the Atlanta, Georgia, Terminal. This support was to provide additional information and backup for other efforts in progress by the Southern Region. System performance tests, standard flight tests, and various other tests had been performed by technical and operational personnel. As a result of these tests, specific problems, localities, and aircraft types involved, beacon transponders became suspect as one source of difficulty. The requested TPA support was provided in November 1979 and data included herein provides the subject information in the transponder area of concern.]]></description>
      <pubDate>Sun, 31 May 2026 16:45:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701093</guid>
    </item>
    <item>
      <title>Analytical Investigation of Time Correction in Alpha-Beta Tracking Filters with Application to En Route Tracking</title>
      <link>https://trid.trb.org/View/2701095</link>
      <description><![CDATA[In the analysis of the α-β tracking filter, it is normally assumed that the tracking filter and data source operate in synchronism at a constant data rate. An analytical solution is obtained for the case in which the tracking filter and data source operate asynchronously, thus violating the standard assumptions. To compensate for the asynchronous operation of the filter, the technique of time correction is used to adjust the measured data point via the estimated velocity which approximates the synchronous operation of the filter and data source. The tracking filter performance in the steady-state case where time correction is used is better than that obtained from a fixed-parameter tracking filter in which the actual random time intervals between measurements are used as the temporal basis of filter operation. To ensure no degradation in system performance for purposes of air traffic control, a system timing accuracy on the order of 0.05 second is required to preserve the position measurement accuracy rather than the presently used technique which yields a timing accuracy on the order of 0.8 second. If the specified level of timing accuracy is not achieved, then it's postulated that significant errors will be introduced in the predicted position for maneuvering targets. System timing errors are presently the limiting factor in providing accurate position measurements for en route purposes and will partially nullify the data accuracy which will be available in the future.]]></description>
      <pubDate>Sun, 31 May 2026 16:45:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701095</guid>
    </item>
    <item>
      <title>Crosstalk Levels of Speech Plus Data in Remote Communications Air-Ground (RCAG)</title>
      <link>https://trid.trb.org/View/2701092</link>
      <description><![CDATA[The Federal Aviation Administration (FAA) is proposing the addition of a digital data channel to the existing telephone lines which connect air route traffic control centers (ARTCC's) with remote communications air-ground (RCAG) sites to economically transfer Remote Monitoring System (RMS) parameters and control data between the ARTCC's and the sites. FAA Specification FAA-E-2699a establishes the maximum allowable interference level to pilot/controller communications which would be allowed to result from the addition of the data channel. The tests described in this document were designed to verify that the requirements in FAA-E-2699a are sufficient to prevent disturbance to normal air traffic control (ATC) operations. The tests were performed by simulating an existing communications channel using data modems and samples of present-day Voice Frequency Control System (VFCS) equipment. Crosstalk levels of speech and data were measured under actual operating conditions. The test results indicated that the addition of an RMS data channel to existing FAA telephone lines is technically feasible and that the requirement in FAA-E-2699a concerning the data crosstalk in the audio portion of the communication channel is not adequate to prevent disturbance to normal ATC operations. The requirements concerning data crosstalk in the control portion and VFCS crosstalk in the data portion of the channel are sufficient.]]></description>
      <pubDate>Sun, 31 May 2026 16:45:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701092</guid>
    </item>
    <item>
      <title>Conference Control System Computer-Human Interface Prototype Description and Design
Rationale</title>
      <link>https://trid.trb.org/View/2698478</link>
      <description><![CDATA[The Federal Aviation Administration (FAA) Air Traffic Control System Command Center (ATCSCC) is responsible for the strategic aspects of the National Airspace System (NAS). The ATCSCC modifies traffic flow and rates when congestion, weather, equipment outages, runway closures, or other operational conditions affect the NAS. Controllers at the ATCSCC accomplish these tasks by communicating with NAS stakeholders like local FAA facilities, airlines, and other national civil aviation authorities. In 2004, the FAA deployed the Conference Control System (CCS) as part of infrastructure modernization to meet increased capacity demands. The CCS provides many new functions and a computer-human interface (CHI) based on touch-entry display (TED) technology. The NAS Human Factors Group conducted a user-centered design project to explore the CCS CHI requirements. In collaboration with the CCS User Team, we developed mouse- and TED-based CHI prototypes to demonstrate the potential CCS functionality. This report discusses the approach we took in designing the CCS prototype and the rationale for each of the important CHI elements. Many of the concepts developed in the prototype were implemented into the operational CCS. The report also discusses the role of iterative prototyping in increasing designers’ and users’ understanding of the tasks, requirements, and CHI development process. Future programs can use the design rationale to guide the creation of CHIs for new telecommunication systems. We believe that the design approach adopted in this project allowed for a better elicitation of the user requirements and helped educate the user team regarding human factors and usability issues.]]></description>
      <pubDate>Sat, 30 May 2026 18:30:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2698478</guid>
    </item>
    <item>
      <title>Software System - Probability of Detection for ARTS III</title>
      <link>https://trid.trb.org/View/2701090</link>
      <description><![CDATA[This document describes a software technique for analyzing probability of target detection in an operational Automated Radar Terminal System (ARTS). The program provides probability of detection for various hit count distributions for the standard ARTS III data extractor. The program is run on a Digital Equipment Corporation (DEC) computer model PDP-11/20; however, sufficient information is included so that it can be adapted to other computer systems.]]></description>
      <pubDate>Sat, 30 May 2026 18:30:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701090</guid>
    </item>
    <item>
      <title>Detection of Military Aircraft in an Air Traffic Control Radar Beacon System (ATCRBS) Environment</title>
      <link>https://trid.trb.org/View/2701089</link>
      <description><![CDATA[An initial survey and analysis of military Air Traffic Control Radar Beacon System (ATCRBS) transponder problems was conducted as a result of transponder performance analyzer (TPA) measurement difficulties encountered at Dobbins Air Force Base, Georgia, and from field problem reports from the Atlanta Terminal, New York and Washington Centers, and other areas. The information assembled and presented in this report demonstrates potential ATCRBS problems with high performance military aircraft in fringe areas of coverage and particularly with the Automated Radar Terminal Systems (ARTS's). Aircraft antenna patterns and switching are of primary concern.]]></description>
      <pubDate>Sat, 30 May 2026 18:30:15 GMT</pubDate>
      <guid>https://trid.trb.org/View/2701089</guid>
    </item>
    <item>
      <title>A Non-Autoregressive Multi-Horizon Flight Trajectory Prediction Framework With Gray Code Representation</title>
      <link>https://trid.trb.org/View/2658931</link>
      <description><![CDATA[Flight Trajectory Prediction (FTP) is an essential task in Air Traffic Control (ATC), which can assist air traffic controllers in managing airspace more safely and efficiently. Existing methods generally perform multi-horizon FTP tasks in an autoregressive manner, thereby suffering from error accumulation and low-efficiency problems. In this paper, a novel framework, called FlightBERT++, is proposed to i) forecast multi-horizon flight trajectories directly in a non-autoregressive way, and ii) improve the limitation of the binary encoding (BE) representation in the FlightBERT framework. Specifically, the proposed framework is implemented by a generalized encoder-decoder architecture, in which the encoder learns the temporal-spatial patterns from historical observations and the decoder predicts the flight status for the future horizons. Compared to conventional architecture, an innovative horizon-aware context generator is dedicatedly designed to consider the prior horizon information, which further enables non-autoregressive multi-horizon prediction. Additionally, the Gray code representation and the differential prediction paradigm are designed to cope with the high-bit misclassifications of the BE representation, which significantly reduces the outliers in the predictions. Moreover, a differential prompted decoder is proposed to enhance the capability of the differential predictions by leveraging the stationarity of the differential sequence. Extensive experiments are conducted to validate the proposed framework on a real-world flight trajectory dataset. The experimental results demonstrated that the proposed framework outperformed the competitive baselines in both FTP performance and computational efficiency. The code is publicly available at: https://github.com/gdy-scu/FlightBERT_PP_V2]]></description>
      <pubDate>Thu, 28 May 2026 17:09:36 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658931</guid>
    </item>
    <item>
      <title>Beyond the Gaze: Peripheral Vision-Aware Visual Detection Failures Recognition Through LLM-Based Fixation Coordinate-Sensitive Analysis</title>
      <link>https://trid.trb.org/View/2658909</link>
      <description><![CDATA[Visual detection failures are a critical challenge in air traffic control (ATC), where undetected alerts can compromise operational safety and decision-making. Previous studies have primarily assessed detection failures through target fixation patterns, yet this method struggles to identify the more complex “look-but-fail-to-see” and “see-without-looking” scenarios. This underscores the necessity of exploring peripheral vision mechanisms, where dynamic tracking trajectories could better capture the scope of visual attention. Therefore, this study proposes a classification framework for visual detection by integrating peripheral vision tracking and human attentional states, including detection failures such as peripheral vision neglect and look-but-fail-to-see errors. A hierarchical detection failure recognition framework specific to the ATC settings is further developed and validated through an ATC simulation experiment. The framework first employs an Adaptive Symbolic Alert Detection method to identify and annotate ATC-specific alert regions with spatiotemporal uncertainty (achieving 95.24% precision), followed by LLM-based evaluation of operators’ visual attention to these regions to intelligently assign classification labels. Additionally, we introduce a fixation coordinate-sensitive multi-domain feature set that captures spatiotemporal and frequency-domain characteristics across detection types, achieving 93.13% four-class classification accuracy, outperforming traditional feature sets (83.69%) and both single- and dual-domain features (ranging from 76.82% to 90.11% accuracy). These findings demonstrate that our framework effectively captures a broader and structured range of visual detection failures, providing critical insights to improve the reliability of alert detection in ATC and the design of an intelligent human-centered ATC support system.]]></description>
      <pubDate>Thu, 28 May 2026 17:09:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658909</guid>
    </item>
    <item>
      <title>Dynamic Arrival Prioritization With Target Time Management and Deep Reinforcement Learning</title>
      <link>https://trid.trb.org/View/2658908</link>
      <description><![CDATA[The European Air Traffic Management system is among the most complex systems in the world. Due to the dense nature of the European network, consequences of disruptions are often catastrophic. In particular, disruptions altering the expected flying time tend to pose great challenges to the arrival management of busy hubs. In response, EUROCONTROL released the Target Time Management (TTM) system, allowing airlines to issue Target Times of Arrival (TTA) even before depart. The TTM system helps hubs airports coordinate arrivals and departures. From the point of view of airlines, the advantage resides in being able to prioritize early arrivals of critical flights. Nevertheless, real-time prioritization is not trivial. Many studies have focused on this problem but with results limited to slot swapping in a tactical context. This is less effective compared to airlines having the ability to select a new slot at the pre-tactical level. This work covers this gap, allowing airlines to select the desired TTA even before departure. We use Deep Reinforcement Learning to create a dynamic arrival allocation model capable of prioritizing flights in terms of passenger connecting time, curfew performance, rotation delay, and fairness to other airlines. Additionally, the model is capable of adapting and react to the uncertainty in responses from the TTM. In the real-world, large anticipations in TTAs are often rejected. The model is tested with real data from SWISS International Airline. Results show an improvement of 5.9 minutes for critical passenger connection and 4.8 minutes for rotation delay versus a deterministic approach.]]></description>
      <pubDate>Thu, 28 May 2026 17:09:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2658908</guid>
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