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    <title>Research in Progress (RIP)</title>
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    <atom:link href="https://rip.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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>
    <image>
      <title>Research in Progress (RIP)</title>
      <url>https://rip.trb.org/Images/PageHeader-wTitle-RIP.jpg</url>
      <link>https://rip.trb.org/</link>
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    <item>
      <title>Assessing the Risk of Runway Incursions at Non-Towered Airports



</title>
      <link>https://rip.trb.org/View/2588328</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Tue, 12 Aug 2025 10:28:26 GMT</pubDate>
      <guid>https://rip.trb.org/View/2588328</guid>
    </item>
    <item>
      <title>Establishment of a Baseline for Guidance on Future Operations of Drone-in-a-Box in a Multi-Aircraft Environment
</title>
      <link>https://rip.trb.org/View/2512407</link>
      <description><![CDATA[Drone-in-a-box solutions have seen a surge in adoption over the last couple of years. With increased communication resilience due to 5G technology and updated approvals, these systems have been used in construction sites, for remote monitoring such as pipeline inspections, and by public safety organizations. Many of these applications rely on either being operated in remote locations or with sworn officers acting as Visual Observers (VOs). While Detect and Avoid systems are sufficient to ensure safety in single-unmanned aircraft system (UAS) remote operations, multiple UAS systems demand that automation, human factors, and community needs are all considered in a strategic response to the inherent risks of remote operations. Multiple-drone control offers a complexity where automation, human factors, and the community must come together to form this strategy. The upcoming Part 108, the Federal Aviation Administration's (FAA's) new Beyond Visual Line of Sight (BVLOS) rule, opens up endless possibilities. 

The use of swarming technologies is not new and has been researched by the Department of Defense, DARPA, and universities (including the University of Cincinnati) and showcases in the increasingly popular drone shows. Controlling multiple UAS can be as simple as preplanning missions with direct control of each UAS as in drone shows, and as complex as heterogenous solutions involving different UAS types and controllers. This more complex form of swarming control, also known as collaborative decentralized control, is essential for next gen UAS operations. 

These decentralized control methods allow for UAS to be meshed together to operate as a single system but are robust enough to have independent control with each UAS monitoring its own health to reduce the workload of the remote operator. 
This team of student researchers at the University of Cincinnati plans to establish guidelines for how such a system needs to be integrated and evaluated. The researchers will not only look at the technologies available but will give guidance on the appropriate steps to integrate these systems into real-world applications such as the Brent Spence companion bridge project as well as future needs. ]]></description>
      <pubDate>Wed, 19 Feb 2025 11:22:35 GMT</pubDate>
      <guid>https://rip.trb.org/View/2512407</guid>
    </item>
    <item>
      <title>Analysis and Deployment of an Unmanned Traffic Management System in Michigan – Phase 1 Feasibility Analysis</title>
      <link>https://rip.trb.org/View/2008009</link>
      <description><![CDATA[The Michigan Department of Transportation (MDOT) Office of Aeronautics (AERO), with support from the Michigan Economic Development Corporation (MEDC), and the Michigan Office of Future Mobility and Electrification (OFME) is committed to the
advancement, integration, and deployment of technologies needed to prepare for the future of mobility in Michigan.
AERO is collaborating with the OFME to identify opportunities to establish foundational aerial mobility infrastructure to support a range of commercial, civic and future urban air mobility use cases and working towards the commitment to creating a multimodal
operating system for the Mobility Innovation district at Michigan Central Station and Ford Motor Company. The proposed scope of work for this project includes a complex and comprehensible feasibility assessment AND A recommendation of three (3) areas
for advanced aerial mobility deployments in the state.
In conjunction with existing autonomous ground-based vehicle deployment near the proposed connected corridor between Detroit and Ann Arbor MDOT Aeronautics seeks analysis and recommendations for deployment of infrastructure needed to ensure safe
operation and regulatory approval of limited unmanned aircraft-based deliveries as part of a pilot study. This initial analysis and recommended deployment would provide the basis for establishing a statewide unmanned aircraft traffic management system.]]></description>
      <pubDate>Thu, 22 Dec 2022 14:49:05 GMT</pubDate>
      <guid>https://rip.trb.org/View/2008009</guid>
    </item>
    <item>
      <title>Human Factors Guidance for the Design, Implementation and Evaluation of AI/ML in the Human-Automation ATC Systems</title>
      <link>https://rip.trb.org/View/2072011</link>
      <description><![CDATA[The goal of this work is to produce a highly accessible guidance document that would raise awareness of the human factors issues critical to the design and implementation of Artificial Intelligence (AI) and Machine Learning (ML) technologies for integration in FAA automation to support air traffic control (ATC) operations, and provide practical guidance on system design, implementation, integration and evaluation that will enable the FAA Air Traffic Organization to avoid pitfalls and adhere to best practices for the integration of AI/ML technologies into ATC automation. This guidance document is intended to be very practical and applied in nature, with a specific focus on ATC, providing guidance for system designers and implementation teams in the PMO. 

Two-Phase Approach: (Phase 1) Identify Potential Future Applications of AI/ML Technologies and Their Integration with Other Automation to Support ATC Operations.
(Phase 2) Development of a Human Factors Guidance Document for the Design, Implementation, Integration and Evaluation of AI/ML Technologies and Their Integration with Other Automation to Support ATC Operations.

This guidance document will be designed to: (1) Raise awareness of the human factors issues critical to the design, implementation, integration and evaluation of AI/ML technologies and their integration with other automation to support ATC operations. (2) Provide practical guidance on the design, implementation, integration and evaluation of such technologies that will enable the FAA Air Traffic Organization to avoid pitfalls and adhere to best practices for the design, implementation, integration and evaluation of AI/ML technologies in support of ATC operations.

This document will consider both design and evaluation methods as well as specific guidance regarding roles and responsibilities, functionality and interface design features necessary to ensure effective human-automation interaction with such technologies.]]></description>
      <pubDate>Wed, 30 Nov 2022 08:06:21 GMT</pubDate>
      <guid>https://rip.trb.org/View/2072011</guid>
    </item>
    <item>
      <title>Application of Artificial Intelligence in the Optimization of Mobility in Dynamic Airspace Configurations During Emergency Situations</title>
      <link>https://rip.trb.org/View/1884827</link>
      <description><![CDATA[Air traffic control (ATC) system is extremely complex so it is impossible to address every component under emergency operation. In this project, the research team narrows the research scope down to airspace configuration. Current national airspace configuration follows a static layout which cannot adapt to the dynamic air traffic conditions or incoming emergency events. Therefore, the team proposes to boost the current ATC system by developing a novel machine learning (ML)-based dynamic airspace configuration (DAC) framework. Different from the traditional statistical and graphical based DAC approaches, the proposed ML-based framework aims to discover the difference of DAC on areas with different air traffic pattern, so that a mapping between ATC control and the air traffic evaluation metrics can be found. The proposed framework will provide: a DAC model that is able to self-adjust the airspace configuration based on the air traffic demands of different time periods of the day or emergency events, thus providing increased airspace capacity, safety and efficiency of ATC operations under unexpected situations with rapid demand changes.]]></description>
      <pubDate>Mon, 11 Oct 2021 23:24:45 GMT</pubDate>
      <guid>https://rip.trb.org/View/1884827</guid>
    </item>
    <item>
      <title>Investigate Age Impacts on Controlled Flight into Terrain (CFIT) Crashes in General Aviation</title>
      <link>https://rip.trb.org/View/1881804</link>
      <description><![CDATA[Controlled Flight into Terrain (CFIT) crash is defined as an unintentional collision with terrain (the ground, a mountain, a body of water, or an obstacle) while an aircraft is under positive control. It is one of three high-risk accident occurrence categories identified by the International Civil Aviation Organization. Although advanced technologies have dramatically reduced the number of General Aviation CFIT crashes over the past 20 years, CFIT crashes continue to occur and at least half of them are fatal. Therefore, it is quite momentous to identify the contributing factors and recommend countermeasures to prevent or mitigate CFIT crashes. This research will utilize the General Aviation CFIT crash data collected from National Transportation Safety Board (NTSB) and pilots’ information from Federal Aviation Administration (FAA), to perform statistical analysis to reveal the impacts of pilots’ age and other pilot related contributing factors on the occurrence of CFIT crashes in General Aviation. Based on the analysis, technology-based and policy-level countermeasures will be proposed to reduce the CFIT crashes. The research findings will help policymakers to better understand the underline reasons for General Aviation CFIT crashes and update their current practices and regulations.
The research is developed based on the CAMMSE theme of addressing the FAST Act research priority area of “Improving Mobility of People and Goods” for multimodal transportation. As discussed earlier, General Aviation plays an important role in moving people and goods, such as business travel or overnight delivery. Improving the safety of General Aviation is the foundation of improving the mobility of people and goods transported by General Aviation. The research is relevant to the CAMMSE research thrust “Innovations to improve multi-modal connections, system integration and security”. Specific project objectives include:
(1)	Review current practices and regulations on the safety operations in General Aviation,
(2)	Identify pilot related factors contributing to CFIT crashes in General Aviation,
(3)	Investigate the impacts of pilots’ age on the occurrence of CFIT crashes in General Aviation, and
(4)	Recommend technology-based and policy-level countermeasures to mitigate General Aviation CFIT crashes.
]]></description>
      <pubDate>Mon, 04 Oct 2021 13:27:28 GMT</pubDate>
      <guid>https://rip.trb.org/View/1881804</guid>
    </item>
    <item>
      <title>Counting Airport Operations Using Aircraft Transponder Signals and/or Aircraft Automatic Dependent Surveillance-Broadcast (ADS-B) Data</title>
      <link>https://rip.trb.org/View/1867582</link>
      <description><![CDATA[New proprietary and/or non-proprietary systems have been developed in an effort to more reliably and accurately count aircraft operations at airports without a staffed air traffic control tower. These systems include methods which utilize equipment that identifies aircraft transponder and/or ADS-B equipment signals. This research project will effectively update the 2018 FDOT Operations Counting at Non-Towered Airports Assessment report by exploring the feasibility, accuracy, and reliability of new technologies. These may include receiving equipment combined with specialized computer programming that would record aircraft operations. For example, a specific aircraft's location/altitude profile (as recorded using its transponder/ADS-B signals) in relation to a known airport's location, could be used to indicate a type of operation at that airport (e.g. landing, takeoff, etc.). Although several systems have been summarized in past research, new technologies continue to emerge and this project will identify and evaluate systems for counting aircraft operations using currently available technologies.]]></description>
      <pubDate>Fri, 23 Jul 2021 12:07:32 GMT</pubDate>
      <guid>https://rip.trb.org/View/1867582</guid>
    </item>
    <item>
      <title>Remote and Virtual Air Traffic Control Tower (RVT): Safety Issues and Human Factors </title>
      <link>https://rip.trb.org/View/1853634</link>
      <description><![CDATA[A number of innovative concepts and emerging technologies are being considered for use within the national air traffic control system to improve safety and efficiency. One of the latest concepts garnering significant attention is commonly referred to as a remote and virtual air traffic control tower (RVT). Specifically, RVT provides traditional air traffic service from a location other than the traditional air traffic control tower at the airport.
The focus of the proposed research is to investigate human factor related questions that may significantly affect the performance of air traffic controllers while operating remote towers. The anticipated benefits of this research include: (1) identification of key human performance factors critical to the successful implementation of RVT the U.S.; (2) assessment of advanced communication and information technologies that may facilitate further implementation of RVT; and (3) acceleration of wider adoption of RVT concepts and technologies while addressing the most vital safety and efficiency related issues.]]></description>
      <pubDate>Mon, 24 May 2021 11:42:55 GMT</pubDate>
      <guid>https://rip.trb.org/View/1853634</guid>
    </item>
    <item>
      <title>Effective Integration of Human Factors Engineering into System Development Acquisition Programs</title>
      <link>https://rip.trb.org/View/1761880</link>
      <description><![CDATA[This is a research effort that will support improved understanding and application of human factors by Federal Aviation Administration (FAA) acquisition program personnel in order to improve compliance with FAA Order 9550.8 and AMS policy and guidance. This research focus is on the identification of potential areas for improvement and on the documentation of best practices regarding the effective integration of human factors engineering into the acquisition process. The potential for technology transfer is high, in that the study recommendations will apply generally to organizations with safety critical functions, including private sector companies supporting aviation. As one input, this work will consider the adequacy of the FAA Human Factors Acquisition Job Aid, which was designed as a reference to help ensure the successful integration of human factors over the lifecycle of the FAA acquisition process. However, it also will look more broadly at how other organizations with missions to support safety-critical operations achieve this goal of effectively integrating human factors engineering into the acquisition process. It will also incorporate recent advances in relevant human factors engineering methods and the research will illustrate how they can be integrated into training materials for the personnel responsible for different stages of the acquisition process.]]></description>
      <pubDate>Mon, 04 Jan 2021 15:12:30 GMT</pubDate>
      <guid>https://rip.trb.org/View/1761880</guid>
    </item>
    <item>
      <title>Economic Impact Report for Advanced Autonomous Aircraft Technologies in Ohio</title>
      <link>https://rip.trb.org/View/1742620</link>
      <description><![CDATA[It is the intent of this research  to complete a - Urban and Regional Air Mobility (URAM), which is an accessible air transport system for passengers and cargo in all environments and Unmanned Aircraft Traffic Management (UTM), Civilian Low-altitude (400' and below) Airspace and Unmanned Aircraft System Operations economic impact report for managed air corridors for the state of Ohio connecting Ohio's major urban centers, emphasizing an air corridor connecting Cincinnati, Columbus, and Cleveland. This report will be used as a guide for Ohio's future investments and research in autonomous aircraft technologies

The FlyOhio Initiative is focused on enabling the lower altitude airspace concentrating on the advancement of autonomous aircraft technologies in Ohio. The Ohio Department of Transportation (ODOT) realizes the economic and efficiency benefits for the management of the lower altitude airspace as a vehicle to enable additional modes of transportation and commerce. Ohio is committed to the tax payers to maintain and progress its investments to stay at the forefront of technology and to meet all the goals set forth by the Ohio Department of Transportation.       ]]></description>
      <pubDate>Thu, 01 Oct 2020 17:13:47 GMT</pubDate>
      <guid>https://rip.trb.org/View/1742620</guid>
    </item>
    <item>
      <title>Guidebook for Virtual Airport Ramp Control Operations Facilities</title>
      <link>https://rip.trb.org/View/1689223</link>
      <description><![CDATA[While there are several airports around the world employing virtual operations to manage ramp activity, there has been little research or testing on the use of virtual operations including remote locations of ramp towers. While the FAA has oversight of airspace and movement areas, ramp control in the non-movement area is the responsibility of the airport operator, an airline, or a third party. Efforts are underway to manage local air traffic operations from virtual facilities, which permit the control facility to be located anywhere with secure electronic communication capability.  
ACRP Research Report 167: Guidebook for Developing Ramp Control Facilities has provided key airport considerations when developing ramp control facilities; however, additional research to determine how to implement a virtual ramp control operation is needed. 
The objective of this research was to develop a guidebook, to include a roadmap, that provides U.S. airport operators and their stakeholders* at a variety of types* and sizes of airports, the ability to implement virtual ramp control operations. The guidebook includes these considerations: 
(1) Safety of aircraft and ground operations;   
(2) Maintain and improve operational efficiencies; 
(3) Contingencies for potential network or system outages; 
(4) Integration of surface management processes and practices (e.g., Collaborative Decision Making (CDM)); 
(5) Weather events (i.e., deicing, snow removal and low visibility operations, etc.); 
(6) Effective coordination techniques with all airport operational stakeholders (i.e., other ramp towers, air traffic control (ATC), airport operations center (AOC) , and Letters of Agreement or Memoranda of Understanding); 
(7) Staffing levels and training competencies (i.e., human factors); 
(8) Management of gate and remain overnight (RON) positions; 
(9) Coordination of airline services (e.g., baggage, cargo, maintenance, and customer service); 
(10)  Budgetary implications with a calculation of return on investment (ROI)  for overall feasibility; and 
(11) Advantages and disadvantages for the development of virtual ramp control operations.   
The roadmap, which is a series of steps, decision points, and actions that need to be taken to implement a virtual facility, should include, but is not limited to, these components:
(1)  Video systems capability; 
(2)  Data connectivity; 
(3)  Usage for gate management data systems; 
(4)  Surface and area aircraft surveillance capabilities; 
(5)  Requirements for communication systems (i.e., air-to-ground / ground-to-ground); and 
(6) Consideration of resilience and IROPS for continuity of service. 

 
 ]]></description>
      <pubDate>Tue, 25 Feb 2020 10:33:31 GMT</pubDate>
      <guid>https://rip.trb.org/View/1689223</guid>
    </item>
    <item>
      <title>Advanced 4D Special Use Airspace Research</title>
      <link>https://rip.trb.org/View/1537221</link>
      <description><![CDATA[This research project will attempt to better understand the dynamic response process to accidents / incidents in commercial space transportation (CST) operations, and how such dynamic capabilities of the National Aerospace Solutions (NAS) (including air traffic control and the aircraft themselves) might be utilized to safely continue to separate air and space vehicles while minimizing the nominal operations impact on the commercial air traffic. This research will (1) incorporate a variety of models for true wind variability and wind measurement uncertainty (for selected sites) into the modeling strategy, (2) develop distributions of accident/incident debris size and their time-accurate locations so that a model of debris tracking accuracy can be generated that can then be used for assessment of the safety of the proposed dynamic evasion procedures, (3) supply dynamic 4D compact envelopes for varying levels of wind/debris tracking capabilities (e.g. with and without real-time debris tracking or wind measurements) and safety buffer sizes, (4) With input from Federal Aviation Administration (FAA) Air Traffic Control (ATC) Subject Matter Experts (SMEs), develop notional operational procedures for implementing Compact 4D Envelopes in nominal scenarios, and (5) support the evaluation of the impact of these advanced procedures on air traffic flow using NAS's FACET tool.  The work in this proposal is classified as long-term research: our work is at the point of trying to understand the major parameters and methodologies that might lead to a far more efficient use of the airspace than what we have today. For this reason, the level of modeling applied is appropriate to the early stage of this research: while the major parameters are all accounted for, there are a number of specific assumptions that will need to be revised and refined as the research transitions to a later phase, when a potential implementation may be considered.]]></description>
      <pubDate>Wed, 22 Aug 2018 13:03:36 GMT</pubDate>
      <guid>https://rip.trb.org/View/1537221</guid>
    </item>
    <item>
      <title>Mitigate Threats through Space Environment Modeling/Prediction-CU</title>
      <link>https://rip.trb.org/View/1537168</link>
      <description><![CDATA[An integrated air and space traffic management system requires seamless and real-time access to density predictions for on-orbit collision avoidance and atmospheric reentry; future knowledge of deleterious particles including energetics, meteoroids, and debris; and near-surface weather prediction.]]></description>
      <pubDate>Wed, 22 Aug 2018 13:02:12 GMT</pubDate>
      <guid>https://rip.trb.org/View/1537168</guid>
    </item>
    <item>
      <title>Mitigate Threats through Space Environment Modeling/Prediction-SU</title>
      <link>https://rip.trb.org/View/1537167</link>
      <description><![CDATA[An integrated air and space traffic management system requires seamless and real-time access to density predictions for on-orbit collision avoidance and atmospheric reentry; future knowledge of deleterious particles including energetics, meteoroids, and debris; and near-surface weather prediction.]]></description>
      <pubDate>Wed, 22 Aug 2018 13:02:11 GMT</pubDate>
      <guid>https://rip.trb.org/View/1537167</guid>
    </item>
    <item>
      <title>Characterization and Application of Air Traffic Controllers Visual Search Patterns and Control Strategies for Efficient and Effective Training</title>
      <link>https://rip.trb.org/View/1532626</link>
      <description><![CDATA[No abstract provided.]]></description>
      <pubDate>Thu, 16 Aug 2018 10:45:22 GMT</pubDate>
      <guid>https://rip.trb.org/View/1532626</guid>
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