In 2021, MIT Lincoln Laboratory is celebrating its 70th year of operation as a Federally Funded Research and Development Center and its 50th year of support to the Federal Aviation Administration. The Laboratory has developed and transitioned a range of technologies to industry to improve aviation safety and efficiency in areas including aircraft surveillance, collision avoidance, weather sensing and forecasting, traffic management, and logistics optimization. Recent thrusts have been focusing on safely increasing autonomy, developing innovative AI/machine learning capabilities, and enabling growth in unmanned aircraft operations.
In this webinar, we will engage with several researchers from Lincoln Laboratory who will provide an outline of recent advances in air traffic control technology and some of the key challenges and opportunities for the future.
This event is for ILP members, invited guests, and the MIT community. You can confirm your company's ILP membership here: https://ilp.mit.edu/search/members.
Visit Lincoln Lab Air Traffic Control: https://www.ll.mit.edu/r-d/air-traffic-control
Download ATC brochure: https://www.ll.mit.edu/doc/air-traffic-control-research-and-innovation
Jennifer Falciglia is the Program Manager for the Technology Ventures Office at MIT Lincoln Laboratory. She earned her BS in Applied Physics and minor in Mathematics from Stockton University, MEng in Engineering Physics (Optics) from Stevens Institute of Technology, an MBA from Boston University’s Executive MBA program, and a graduate certificate in the Foundations of Business from UMass Lowell.
Jennifer began her career at the Eastman Kodak Company’s Commercial and Government Systems (C&GS) organization, where she worked as an Optical Engineer developing a vision system for Kodak’s One Time Use Cameras and optical optimization techniques for laser printers. After L3-Harris (FKA ITT Industries) acquired C&GS, Jennifer supported the interferometric metrology and fabrication of large mirrors to be integrated into space-based and ground-based telescopes. She then supported GPS constellation sustainment as a Project Engineer and Integrated Product Team Lead. Jennifer joined MIT LL in 2011 as a Project Manager for several large, million-dollar procurements of major subassemblies in support of complex space and air federated projects. Jennifer moved to the Technology Ventures Office in 2019, where she helps support MIT LL technology transfer to and from small business and government stakeholders.
Jim Kuchar is Assistant Head of the Homeland Protection and Air Traffic Control Division at MIT Lincoln Laboratory. He received SB, SM, and PhD degrees in Aeronautics and Astronautics from MIT focused on flight deck alerting system displays, algorithms, and risk analysis methods. Jim served on the MIT faculty from 1995-2003, after which he joined Lincoln Laboratory leading the development of collision avoidance system technologies for manned and unmanned aircraft. In 2009 he transitioned into leading and managing Lincoln’s portfolio of weather / air traffic management programs encompassing radar systems, weather forecast algorithms, decision support technologies, and processing architectures for NextGen capabilities. He moved into his current role overseeing the Laboratory’s Air Traffic Control mission area in 2019. Jim serves on the National Airspace System Operations panel of the FAA Research, Engineering, and Development Advisory Committee (REDAC) and is an Associate Editor for the Journal of Air Transportation.
MIT Lincoln Laboratory has been supporting technology research and development for the nation’s air traffic control system for 50 years. Example contributions include aircraft surveillance systems, collision avoidance and safety assessment technology, unmanned aircraft integration, weather radar enhancements, and decision support systems to improve air traffic flow efficiency and safety. This presentation will provide a brief overview of recent accomplishments and an outline of current technology development programs.
Matt Edwards is an Assistant Group Leader at MIT Lincoln Laboratory in the Air Traffic Control mission area. His research interests include control and estimation, optimization, and the modeling and assessment of complex aerospace systems. At Lincoln Laboratory, his technical work spans the assessment and technology development of collision avoidance systems for manned and unmanned aircraft. He coordinates a diverse portfolio of programs at Lincoln Laboratory spanning air traffic surveillance and decision support for the FAA, NASA, and DoD.
The U.S. National Airspace System (NAS) depends on a robust, redundant surveillance system to ensure safe aircraft separation in the air and on the ground. However, the existing NAS surveillance network prioritizes coverage in areas and at airports with a large number of operations, so there is a surveillance gap at and around smaller airports where aircraft operations converge in a small area, potentially creating a safety hazard. Safety can be enhanced with a surveillance capability at these smaller airports, but existing airport surveillance systems are expensive to procure and maintain. Lincoln Laboratory has been working with the FAA to design and test a smaller, simpler, lower cost radar surveillance system based on phased array radar technology and modern signal processing, called the Small Airport Surveillance Sensor (SASS). This seminar will provide an overview of the SASS system concept, enabling technology, and recent test results.
Wes Olson is the leader of the Surveillance Systems Group at MIT Lincoln Laboratory overseeing approximately 50 staff members developing integrated sensing and decision support systems that enable safe and efficient air and surface transportation. Since joining MIT Lincoln Laboratory in 2007 Wes has led the Lincoln airborne collision avoidance research area supporting both the existing TCAS system as well as development of the next generation capability - ACAS X. He participates in national standards development activities in both RTCA and ASTM and is technical advisor to the US panel member on the ICAO surveillance panel. His area of expertise and experience include airborne collision avoidance systems for manned and unmanned aircraft as well as aviation human factors research. He received a B.S. degree in Human Factors Engineering from the United States Air Force Academy in 1985, and his M.S. degree (1987) and Ph.D. (1999) in Engineering Psychology from the University of Illinois at Urbana-Champaign. Prior to joining Lincoln Laboratory Wes served in the US Air Force for 22 years where he flew transport and training aircraft including the C-21, C-5 and TG-7. Positions held included associate professor on the faculty of the United States Air Force Academy as well as deputy director for operations at the Air Force Flight Standards Agency.
Integration of Unmanned Aircraft Systems (UAS) into the U.S. National Airspace System (NAS) requires the development, assessment and deployment of a number of technologies to ensure that these new vehicles do not degrade the current high levels of safety and efficiency. Successful airspace integration requires development of technology to enable UAS to detect and avoid conflicts with other aircraft. Lincoln Laboratory has a long history developing and assessing performance of collision avoidance capability for manned aircraft and has extended these activities to detect and avoid technologies for both the FAA and DoD. In 2008, Lincoln developed a new approach to the detect and avoid problem based on Markov Decision Processes and dynamic programming techniques that explicitly consider uncertainties in the current location and future trajectories of nearby aircraft. This approach allows for the selection of avoidance maneuvers that jointly optimize safety and operational suitability. This seminar will provide an overview of this approach and describe development and deployment of the DoD’s Ground Based Sense and Avoid (GBSAA) capability as well as the FAA-funded ACAS X program for UAS and Urban Air Mobility (UAM) vehicles.
Tom Reynolds is Leader of the Air Traffic Control Systems Group at MIT Lincoln Laboratory, which develops advanced technologies to address national needs in weather and transportation (especially aviation) applications. He has expertise in air transportation systems engineering, with particular interests in air traffic control system modernization and mitigating environmental impacts of aviation. He has been on the research staff at MIT and the University of Cambridge in the UK, and worked for British Airways Engineering at London Heathrow Airport and the UK Defence Evaluation and Research Agency. He has a Ph.D. in Aerospace Systems from MIT, was a UK Fulbright Scholar, is an AIAA Associate Fellow and Chair of the AIAA Aircraft Operations Technical Committee.
Air Traffic Control (ATC) is responsible for maintaining the safety and efficiency of the air transportation system. This can be especially challenging during adverse weather conditions such as heavy precipitation, reduced visibility or high winds, all of which can significantly reduce the available capacity of different parts of the aviation system. Accurately predicting these impacts in advance can allow them to be mitigated as effectively as possible. This talk will present an overview of advanced ATC decision support technologies developed at MIT Lincoln Laboratory to address these needs. A particular focus will be on the key role of industry and other stakeholders in the development and implementation of these capabilities.
Mark Veillette is a senior technical staff member in the Air Traffic Control Systems Group at MIT Lincoln Laboratory. He has been an active contributor to research efforts supported by the FAA and DoD aimed at improving weather modelling using artificial intelligence (AI). Mark is the lead developer for a number AI-based weather systems in use by the FAA and DoD, including the FAA’s Offshore Precipitation Capability (OPC) and the US Air Force’s Global Synthetic Weather Radar (GSWR) capability. Before joining the Laboratory in 2011, Mark received a B.S. in Mathematics from Bucknell University in 2005, and later his Ph.D. in Mathematics from Boston University in 2010 with a focus in probability theory, stochastic processes and machine learning.
Chelsea Curran is a technical staff member in the Air Traffic Control Systems Group at MIT Lincoln Laboratory. She received BSE degrees in Mechanical Engineering and Biomedical Engineering from Duke University, and SM and PhD degrees in Aeronautics and Astronautics from MIT. Since joining MIT Lincoln Laboratory, Chelsea has been working with the US Transportation Command (USTRANSCOM) to apply data analytics and optimization methods to improve the planning process for airlift and aerial refueling operations. She is currently leading the USTRANSCOM research program at MIT Lincoln Laboratory, and oversees a portfolio of projects aimed at helping the Command enhance its readiness for integrating artificial intelligence and machine learning capabilities.
The U. S. Air Mobility Command (AMC) provides global air transportation to the U.S. Department of Defense and other government organizations. Among its mission areas is the support of air refueling operations using tanker aircraft such as the KC-135. However, due to the aging fleet and delays in the introduction of new tanker aircraft, tanker availability is a key challenge for AMC in preserving mission readiness. MIT Lincoln Laboratory is working with AMC to explore the use of artificial intelligence and machine learning capabilities for a variety of applications related to aircraft safety and operational efficiency. Specifically, we are working to develop a predictive maintenance capability for KC-135 aircraft which relies on the fusion of flight data with maintenance records. This talk describes the algorithms that underpin this capability and how users can leverage it to improve overall aircraft readiness levels.