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Research
Air Traffic Management Master Plan - NARAE (National ATM Renovation & Enhancement)
2012 marks the 40th anniversary for the Republic of Korea(ROK)’s first trans-pacific flight. Over the past decades, ROK has seen a tremendous growth in air navigation sector fueled by robust economic growth, along with a demonstrated operational capability to handle increasing demand.
ROK has been actively investing in modernizing of air navigation system, including CNS/ATM, aviation technology, and so on. In 2011, ROK initiated on a transition to the future ATM system and is establishing future ATM plan called NARAE, National ATM Renovation And Enhancement, which means the ‘wing’ in Korean.
ROK subsequently commissioned the working group in November 2011 as a group of researchers from academia and civil aviation organizations to prepare the draft of NARAE for the future ATM system. True lab developed the ROK’s ATM master plan as below.
Implementation Plan
Period: 2011.12~2012.06
Funding: MOLIT
Team: Ohhoun Kwon, Kyowon Song, Donghoun Lee, Eunhye Kim
R&D Partnership: Korea Civil Aviation Development Association (KADA)
Autonomous Logistics
Development of Autonomous Mobile Agent System in Complex Warehouse
Unlike vehicles with men aboard, autonomous vehicles require algorithms for path planning, static obstacle avoidance, dynamic obstacle avoidance, and many more. Especially, algorithms need to be considered for co-working with human workers to easily adapt the system in existing warehouses with lower setup cost.
Therefore TRUE lab is developing an optimized algorithm for each robot to find the shortest path from origin to destination for each mission while potential conflicts and deadlocks are prevented.
The goal of this project is to develop an algorithm which enables a large quantity of mobile robots (up to 300) operate in simulation. By having a testbed in a real warehouse and mobile robots specially produced for this project, in 2015-2016 the algorithm will be tested.
Development
Breadth First Search algorithm can be modified to be adopted in three-dimensional space with discrete time windows. Similar to Amazon's Kiva system, the algorithm generates paths for multi mobile robots, and check if any cell is overlapped by more than one robots. If there is a conflict, it finds another path which is the second shortest. This is repeated until all conflicts are resolved maintaining the shortest path as much as possible.
Simulation Example
Period: 2014.06~2017.05
Funding: KAIA
Team: Yuna Noh, Seyun Kim
R&D Partnership: Urban Robotics Lab (URL, KAIST), Korea Electronics Technology Institute (KETI), Nsquare, CJ Korea Express
Probabilistic Air Traffic Flow Management (ATFM) in the next generation air transportation system
This research seeks to develop and evaluate both deterministic and stochastic Air Traffic Flow Management (ATFM) optimization models, with the purpose to be utilized in the current and future air transportation systems.
South Korea, one of leading states of the International Civil Aviation Organization (ICAO), is facing the challenge to modernize its air transportation system as mandated by the organization by 2020.
This research first addresses shortcomings of the current ATFM system by developing a mathematical model to achieve integrated system management. We also study Probabilistic Air Traffic Management (PATM), which has attracted great interests in the ATM community, and propose a stochastic route optimization model when certain challenges inhibits full utilization of the airspace. Software implementation of developed models to simulate and evaluate effectiveness of the proposed models.
Result Result
Expected Contribution
Conduct a leading research in the PATM area, which is one of the main focus of ATM research communities worldwide, and set out the opportunity to become a leading country in the future ATM
Provide systematic solution to address airspace congestion
Redefine the aviation as one of the green transportation mode through the optimal ATFM, which will result in the reduction of carbon footprint of the aviation and increase of the fuel efficiency
Period: 2011.05~2014.04
Funding: National Research Foundation of Korea (NRF)
Team: Ohhoun Kwon, Kyowon Song, Donghoun Lee
Aviation System Safety Management and Reliability Centered Maintenance Program Development
The goal of this research is to develop SMS tools for service providers and policymakers to achieve proactive safety management in accordance with ICAO guideline.
TRUE is participating on a project of development of risk model and related techniques to assess risks in the aviation organizations both in quantitative and qualitative way: direction of collecting safety data for risk analysis and risk assessment, methodology of risk assessment using safety database, and developing state safety indicators.
CATS, ESD Model
ICAO- Risk Matrix Model
FAA - Risk Matrix Model
KAIST-Risk Model
1. Worst/Most Credible Risk Matrix method
Identify both of the most frequent risk level and the worst risk level by hazard
The risk levels are visually shown on risk matrix.
2. Cromatography method
Represent probability distribution of severity by hazard into stacked bar chart.
Provide insights into overall risk level by hazard, but does not provide immediate risk assessment
3. Risk Scoring
Likelihood value from existing risk matrix’s likelihood value
Severity value from weighted sum of the number of occurrence by severity level
Useful in quantitative comparison of risks among hazards
Period: 2011.12 ~ 2015.06
Team: Ohhoun Kwon, Yuna Noh, Jiseon Lee, Donghoun Lee, Eunhye Kim, Eunseok Kim
Funding: KAIA
Patents:
Aviation safety risk assessment method based on hazard matrix and apparatus for the same. Korea Domestic Patent Application. App. No. 10-2014-0105376 (2014.08.13)
Software: Aviation Risk Identification and Assessment (ARIA)
R&D Partnership:
Impacts of volcanic eruption on aviation system
The ash cloud from the Eyjafjallajokull volcano in Iceland caused a significant impact on aviation industry on April 14, 2010. Airports across Europe were closed, and at least 17,000 flights a day were cancelled for over a week. Overall 100,000 flights were cancelled and 10 million passengers were unable to board their flights during this week. After Iceland case, there have been many studies trying to address aviation industry impact of Volcanic Ash. However, most of the volcanic eruption scenario studies have limitations.
In TRUE lab, we analyze the damage of the airports and number of the cancelled flights depend on the hypothetical case of Mt. Baegdu eruption model to derive a predicted flights path and diffusion distance of volcanic ash. This research analyzes the effect of volcanic ash to air traffic and airport by quantification value by assessing volcanic ash concentration and its altitude.
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