Publications
Visibility estimation through image analytics
June 20, 2023
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-453
Summary
MIT Lincoln Laboratory (MIT LL) has developed an algorithm, known as the Visibility Estimation through Image Analytics Algorithm (VEIA), that ingests camera imagery collected by the FAA Weather Cameras Program Office (WeatherCams) and estimates the meteorological visibility in statute miles. The algorithm uses the presence of edges in the imagery and the strength of those edges to provide an estimation of the meteorological visibility within the scene. The algorithm also combines the estimates from multiple camera images into one estimate for a site or location using information about the agreement between camera estimates and the position of the Sun relative to each camera's view. The final output for a site is a prevailing visibility estimate in statute miles that can be easily compared to existing automated surface observation systems (ASOS) and/or human-observed visibility. This report includes thorough discussion of the VEIA background, development methodology, and transition process to the WeatherCams office operational platform (Sections 2–4). A detailed software description with flow diagrams is also provided in Section 5. Section 6 provides a brief overview of future research and development related to the VEIA algorithm.
Summary
MIT Lincoln Laboratory (MIT LL) has developed an algorithm, known as the Visibility Estimation through Image Analytics Algorithm (VEIA), that ingests camera imagery collected by the FAA Weather Cameras Program Office (WeatherCams) and estimates the meteorological visibility in statute miles. The algorithm uses the presence of edges in the imagery...
READ MORE
Airspace flow rate forecast algorithms, validation, and implementation
December 15, 2015
Project Report
Published in:
MIT Lincoln Laboratory Report ATC-428
Topic:
R&D area:
R&D group:
Summary
This report summarizes work performed by MIT Lincoln Laboratory during the period 1 February 2015 - 30 November 2015 focused on developing and improving algorithms to estimate the impact of convective weather on air traffic flows. The core motivation for the work is the need to improve strategic traffic flow management decision-making in the National Airspace System. The algorithms developed as part of this work translate multiple weather forecast products into a discrete airspace impact metric called permeability.
Summary
This report summarizes work performed by MIT Lincoln Laboratory during the period 1 February 2015 - 30 November 2015 focused on developing and improving algorithms to estimate the impact of convective weather on air traffic flows. The core motivation for the work is the need to improve strategic traffic flow...
READ MORE
Forecast confidence measures for deterministic storm-scale aviation forecasts
February 5, 2014
Conference Paper
Published in:
4th Aviation, Range, and Aerospace Meteorology Special Symp., 2-6 February 2014.
Topic:
R&D area:
R&D group:
Summary
Deterministic storm-scale weather forecasts, such as those generated from the FAA's 0-8 hour CoSPA system, are highly valuable to aviation traffic managers. They provide forecasted characteristics of storm structure, strength, orientation, and coverage that are very helpful for strategic planning purposes in the National Airspace System (NAS). However, these deterministic weather forecasts contain inherent uncertainty that varies with the general weather scenario at the forecast issue time, the predicted storm type, and the forecast time horizon. This uncertainty can cause large changes in the forecast from update to update, thereby eroding user confidence and ultimately reducing the forecast's effectiveness in the decision-making process. Deterministic forecasts generally lack objective measures of this uncertainty, making it very difficult for users of the forecast to know how much confidence to have in the forecast during their decision-making process. This presentation will describe a methodology to provide measures of confidence for deterministic storm-scale forecasts. The method inputs several characteristics of the current and historical weather forecasts, such as spatial scale, intensity, weather type, orientation, permeability, and run-to-run variability of the forecasts, into a statistical model to provide a measure of confidence in a forecasted quantity. In this work, the forecasted quantity is aircraft blockage associated with key high-impact Flow Constrained Areas (FCAs) in the NAS. The results from the method, which will also be presented, provide the user with a measure of forecast confidence in several blockage categories (none, low, medium, and high) associated with the FCAs. This measure of forecast confidence is geared toward helping en-route strategic planners in the NAS make better use of deterministic storm-scale weather forecasts for air traffic management.
Summary
Deterministic storm-scale weather forecasts, such as those generated from the FAA's 0-8 hour CoSPA system, are highly valuable to aviation traffic managers. They provide forecasted characteristics of storm structure, strength, orientation, and coverage that are very helpful for strategic planning purposes in the National Airspace System (NAS). However, these deterministic...
READ MORE
Air traffic decision analysis during convective weather events in arrival airspace
September 17, 2012
Conference Paper
Published in:
12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conf. and 14th AIAA/ISSM, 17-19 September 2012.
Topic:
R&D area:
R&D group:
Summary
Decision making during convective weather events in the terminal area is shared among pilots and air traffic management, where uninformed decisions can result in wide-spread cascading delays with high-level impacts. Future traffic management systems capable of predicting terminal impacts will mitigate these unnecessary delays; however in order to realize this vision, it is important to understand the decision mechanisms behind convective weather avoidance. This paper utilizes an arrival adaptation of the Convective Weather Avoidance Model (CWAM) to investigate the catalysts for arrival traffic management decision making. The analysis is broken down by category of terminal airspace structure in addition to the type of decision. The results show that pilot behavior in convective weather is heavily dependent on the terminal airspace structure. In addition, pilot and air traffic management decisions in convective weather can be discriminated with large-scale weather features.
Summary
Decision making during convective weather events in the terminal area is shared among pilots and air traffic management, where uninformed decisions can result in wide-spread cascading delays with high-level impacts. Future traffic management systems capable of predicting terminal impacts will mitigate these unnecessary delays; however in order to realize this...
READ MORE
Evaluation of the Convective Weather Avoidance Model for arrival traffic
September 17, 2012
Conference Paper
Published in:
12th AIAA Aviation Technology, Integration, and Operations (ATIO) Conf. and 14th AIAA/ISSM, 17-19 September 2012.
Topic:
R&D area:
R&D group:
Summary
The effective management of traffic flows during convective weather events in congested air space requires decision support tools that can translate weather information into anticipated air traffic operational impact. In recent years, MIT Lincoln Laboratory has been maturing the Convective Weather Avoidance Model (CWAM) to correlate pilot behavior in the enroute airspace with observable weather parameters from convective weather forecast systems. This paper evaluates the adaptation of the CWAM to terminal airspace with a focus on arrival decision making. The model is trained on data from five days of terminal convective weather impacts. The performance of the model is evaluated on an independent dataset consisting of six days of convective weather over a variety of terminal areas. Model performance in different terminal areas is discussed and the sensitivity of prediction accuracy to weather forecast horizon is presented.
Summary
The effective management of traffic flows during convective weather events in congested air space requires decision support tools that can translate weather information into anticipated air traffic operational impact. In recent years, MIT Lincoln Laboratory has been maturing the Convective Weather Avoidance Model (CWAM) to correlate pilot behavior in the...
READ MORE
Modeling convective weather avoidance of arrivals in the terminal airspace
January 25, 2011
Conference Paper
Published in:
2nd Aviation, Range, and Aerospace Meteorology Special Symp. on Weather-Air Traffic Management Integration, 22-27 January 2011.
Topic:
R&D area:
R&D group:
Summary
For several years the NASA sponsored Convective Weather Avoidance Model (CWAM) has been under development at Lincoln Lab to correlate pilot behavior with observable weather parameters available from convective weather systems. To date, the current CWAM has focused primarily on the enroute airspace used by aircraft at cruise altitude. At these altitudes there is a strong correlation between the observable echo tops from the Corridor Integrated Weather System (CIWS) and the probability that a pilot will deviate around weather. The CWAM has lead to the development of a Weather Avoidance Field (WAF) that combines the echo tops and vertically integrated liquid (VIL) into a probabilistic forecast of the likelihood of pilot deviation. In recent years the WAF has become widely acceptance as a reliable indicator of the impact of convective weather on air traffic operations. This paper will explore the adaptation of the CWAM into the terminal airspace with a focus on the weather impact on arrival decision making. A database of convective weather impacts on several major terminals from 2009 has been collected and identification of the impact on arriving aircraft has begun. Past studies of terminal weather impact have identified aircraft that penetrated severe weather or made clear deviations around convective cells within the terminal. This study will expand the definition of an impact to identify pilot decision making occurring outside of the terminal with regard to the expected weather impact upon arrival in the terminal. Examples include rerouting to an alternate corner post, holding in enroute airspace, or diverting to an alternate airport when weather is expected along the planned terminal trajectory. These types of terminal weather avoidance decisions can often be made many miles outside of the terminal. The enroute CWAM uses spatial filters applied to the echo tops and VIL to obtain the best correlation between the weather and pilot behavior. This paper will evaluate the current CWAM filters and identify alternate spatial filters or additional weather products that may best correlate pilot decision making in the terminal. Ultimately the goal of this work is provide ATC managers and automated decision supports tools with a weather avoidance field for effective management of convective weather in terminal airspace.
Summary
For several years the NASA sponsored Convective Weather Avoidance Model (CWAM) has been under development at Lincoln Lab to correlate pilot behavior with observable weather parameters available from convective weather systems. To date, the current CWAM has focused primarily on the enroute airspace used by aircraft at cruise altitude. At...
READ MORE
Assessment and interpretation of en route Weather Avoidance Fields from the Convective Weather Avoidance Model
September 13, 2010
Conference Paper
Published in:
ATIO 2010: 10th AIAA Aviation Technology Integration and Operations Conf., 13-15 September 2010.
Topic:
R&D area:
R&D group:
Summary
This paper presents the results of a study to quantify the performance of Weather Avoidance Fields in predicting the operational impact of convective weather on en route airspace. The Convective Weather Avoidance Model identifies regions of convective weather that pilots are likely to avoid based upon an examination of the planned and actual flight trajectories in regions of weather impact. From this model and a forecast of convective weather from the Corridor Integrated Weather System a probabilistic Weather Avoidance Field can be provided to automated decision support systems of the future impact of weather on the air traffic control system. This paper will present three alternative spatial filters for the Convective Weather Avoidance Model, quantify their performance, address deficiencies in performance, and suggest potential improvements by looking at the ATC environment and common situational awareness between the cockpit and air traffic control.
Summary
This paper presents the results of a study to quantify the performance of Weather Avoidance Fields in predicting the operational impact of convective weather on en route airspace. The Convective Weather Avoidance Model identifies regions of convective weather that pilots are likely to avoid based upon an examination of the...
READ MORE
Evaluation of enroute Convective Weather Avoidance Models based on planned and observed flight
January 18, 2010
Conference Paper
Published in:
14th Conf. on Aviation, Range, and Aerospace Meteorology, ARAM, 16-21 January 2010.
Topic:
R&D area:
R&D group:
Summary
The effective management of convective weather in congested air space requires decision support tools that can translate weather information available to air traffic managers into anticipated impact on air traffic operations. The Convective Weather Avoidance Model (CWAM) has been under development at Lincoln Lab under sponsorship of NASA to develop a correlation between pilot behavior and observable weather parameters. To date, the observable weather parameters have been the Corridor Integrated Weather System (CIWS) high resolution Vertically Integrated Liquid (VIL) precipitation map and the CIWS Echo Top product. The CWAM was dependent upon a crude model to define pilot deviations based upon finding weather encounters and then comparing the distance between the planned and actual flight trajectories. Due to a large number of false deviations from this crude model, a significant amount of hand editing was required to use the database. This paper will focus on two areas of work to improve the performance of the enroute convective weather avoidance models. First, an improved automated algorithm to detect weather-related deviations that significantly reduces the percentage of false deviation detections will be presented. This new model includes additional information on each deviation, including the location the decision was made to deviate. The additional information extracted from this algorithm can be used to evaluate the conditions at the decision time which may impact the severity of weather pilots are willing to penetrate. The new deviation detection algorithm has also reduced the amount of hand editing required by removing short cuts taken to reduce the flight time, deviations that occur well past the decision time, and non-weather related reroutes. The second focus of this paper will be the comparison of three different convective weather avoidance models that have been proposed, based upon the analysis of an expanded database of flight deviations. Six weather impact days from 2007 and 2008 have been added to the existing case set from 2006, tripling the number of flight trajectories that can be used in validating the models. In addition to validating the existing CWAM, we will look at additional parameters that may improve the performance of the CWAM.
Summary
The effective management of convective weather in congested air space requires decision support tools that can translate weather information available to air traffic managers into anticipated impact on air traffic operations. The Convective Weather Avoidance Model (CWAM) has been under development at Lincoln Lab under sponsorship of NASA to develop...
READ MORE
Measuring the uncertainty of weather forecasts specific to air traffic management operations
August 4, 2008
Conference Paper
Published in:
89th ARAM Special Symp., 4 August 2008.
Topic:
R&D area:
R&D group:
Summary
In this paper, we develop a novel way to measure the accuracy of weather forecasts based upon the impact on air traffic flows. This method uses new techniques developed as part of the CWAM that consider the complicated interaction between pilots, air traffic controllers and weather. This technique, known as the blockage model (Martin et al., 2006), differentiates between minor deviations performed by pilots around convective weather and their larger deviations due to fully blocked air routes that require air traffic control interaction. This blockage model is being used by the automated Route Availability Planning Tool (RAPT) to predict route blockage for NYC departures. RAPT integrates the Corridor Integrated Weather Systems (CIWS) deterministic 0-2 hour forecasts of precipitation and echo tops into route specific forecasts of impact on air traffic in the congested east coast corridor. Applying the blockage model to the entire CIWS weather domain as a metric for scoring the performance of the forecast algorithms is shown to be an excellent approach for measuring the adequacy of the forecast in predicting the impact of the convective weather on air traffic operations.
Summary
In this paper, we develop a novel way to measure the accuracy of weather forecasts based upon the impact on air traffic flows. This method uses new techniques developed as part of the CWAM that consider the complicated interaction between pilots, air traffic controllers and weather. This technique, known as...
READ MORE
An automated visibility detection algorithm utilizing camera imagery
January 14, 2007
Conference Paper
Published in:
87Th AMS Annual Meeting, 14-18 January 2007.
Summary
The Federal Highway Administration (FHWA) has had a focused program to improve the integration of weather decision support systems into surface transportation operations since 1999. Clarus (Latin for clear) is the FHWA's most recent surface transportation weather initiative. The Clarus concept is to develop and demonstrate an integrated surface transportation weather observing, forecasting and data management system (Pisano, 2006a). As part of this effort, the FHWA is also promoting research into methods for applying new and existing sensor or probe data. These efforts include utilizing new in-vehicle sensor data that will be part of the vehicle infrastructure initiative (VII) (Pisano, 2006b), and finding innovative ways to use existing camera imagery. MIT Lincoln Laboratory (MIT/LL) was tasked to evaluate the usefulness of camera imagery for sensing ambient and road weather conditions and the feasibility for creating a portable visibility estimation algorithm. This paper gives a general background on the current utilization of camera imagery, including past and ongoing research of automated weather/condition algorithms. This is followed by a description of the MIT/LL camera test site, the analyses performed and the resultant prototype visibility estimation algorithm. In addition, the paper details application of the prototype algorithm to existing state DOT cameras in Utah. The final section discusses the future possibilities of camera-based weather and road condition algorithms.
Summary
The Federal Highway Administration (FHWA) has had a focused program to improve the integration of weather decision support systems into surface transportation operations since 1999. Clarus (Latin for clear) is the FHWA's most recent surface transportation weather initiative. The Clarus concept is to develop and demonstrate an integrated surface transportation...
READ MORE