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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Analysis and prediction of intersection traffic violations using automated enforcement system data

We report that the automated enforcement system (AES) is an effective way of supplementing traditional traffic enforcement, and the traffic violation data from AES can also be effectively used for safety research. In this study, traffic violation data were used to analyze the influencing factors associated with traffic violations and to predict the probability of violations at intersections. The potential factors influencing violations include 24 independent factors related to time, space, traffic and weather. Results from a logistic model showed that the midday period, weekends, residential districts, collector roads, congested traffic conditions, high traffic flow, lower wind speed and low temperature would increase the probability of traffic violations. The probability of violations was predicted by the random forest algorithm, which was proven to be the best traffic violation prediction model among logistic regression, Gaussian naive Bayes, and support vector machine. Moreover, the proximity weighted synthetic oversampling technique (ProWSyn) method was applied to reduce the impact of the imbalance ratio (IR) and improve the model’s prediction performance. The receiver operating characteristics (ROC) curves and Precision-Recall (PR) curves illustrated that the random forest algorithm using oversampling data had the best classifier prediction performance than undersampling data. The area under curve (AUC) and out-of-bag (OOB) error with IR = 1 reached 0.914 and 0.0787, which showed the better performance of the random forest algorithm using ProWSyn in dealing with imbalanced traffic violation data.

42 ENGINEERING↗
NASA NTRSDate not supplied

Minimum-Violation Traffic Management for Urban Air Mobility

Urban air mobility (UAM) refers to air transportation services in and over an urban area and has the potential to revolutionize mobility solutions. However, due to the projected scale of operations, current air traffic management (ATM) techniques are not viable. Increasingly autonomous systems are a pathway to accelerate the realization of UAM operations but must be fielded safely and efficiently. The heavily regulated, safety critical nature of aviation may lead to multiple, competing safety constraints that can be traded off based on the operational context. In this paper, we design a framework which allows for the scalable planning of a UAM ATM system. We formalize safety oriented constraints derived from FAA regulations by encoding them as temporal logic formulae. We then propose a method for UAM ATM that is both scalable and minimally violates the temporal logic constraints. Numerical results show that the runtime for our proposed algorithm is suitable for very large problems and is backed by theoretical guarantees of correctness with respect to given temporal logic constraints.

Urban Air Mobility↗
NASA NTRS2007

Detection and enforcement of failure-to-yield in an emergency vehicle preemption system

An intersection controlled by an intersection controller receives trigger signals from on-coming emergency vehicles responding to an emergency call. The intersection controller initiates surveillance of the intersection via cameras installed at the intersection in response to a received trigger signal. The surveillance may begin immediately upon receipt of the trigger signal from an emergency vehicle, or may wait until the intersection controller determines that the signaling emergency vehicle is in the field of view of the cameras at the intersection. Portions of the captured images are tagged by the intersection controller based on tag signals transmitted by the vehicle or based on detected traffic patterns that indicate a potential traffic violation. The captured images are downloaded to a processing facility that analyzes the images and automatically issues citations for captured traffic violations.

Bachelder, Aaron↗
NASA NTRS2017

Assessment of Air Traffic Controller Acceptability of Aircrew Route Change Requests

NASA developed the traffic aware strategic aircrew requests concept for a cockpit automation that identifies route improvements and advises the aircrew to request the change from the air traffic controller. In order to increase the chance of air traffic control approval, the automation ensures that the route is clear of known traffic, weather, and airspace restrictions. Hence the technology is anticipated to provide benefits in areas such as flight efficiency, flight schedule compliance, passenger comfort, and pilot and controller workload. In support of a field trial of a prototype of the technology, observations were conducted at the Atlanta and Jacksonville air traffic control centers to identify the main factors that affect the acceptability of aircrew requests by air traffic controllers. Observers shadowed air traffic controllers as the test flight pilot made pre-scripted requests to invoke acceptability issues and then they interviewed voluntarily fifty controllers with experience ranging from one to thirty-five years. The most common reason for rejecting requests is conflicting with traffic followed by violating air traffic procedures, increasing sector workload, and conflicting with major arrival and departure flows and flow restrictions. Quantitative parameters such as the distance that a route should maintain from sector boundaries and special use airspace were identified and recommended for inclusion in the automation.

Flight Optimization; Field Trial↗
NASA NTRS2017

Assessment of Air Traffic Controller Acceptability of Aircrew Route Change Requests

NASA developed the traffic aware strategic aircrew requests concept for a cockpit automation that identifies route improvements and advises the aircrew to request the change from the air traffic controller. In order to increase the chance of air traffic control approval, the automation ensures that the route is clear of known traffic, weather, and airspace restrictions. Hence the technology is anticipated to provide benefits in areas such as flight efficiency, flight schedule compliance, passenger comfort, and pilot and controller workload. In support of a field trial of a prototype of the technology, observations were conducted at the Atlanta and Jacksonville air traffic control centers to identify the main factors that affect the acceptability of aircrew requests by air traffic controllers. Observers shadowed air traffic controllers as the test flight pilot made pre-scripted requests to invoke acceptability issues and then they interviewed voluntarily fifty controllers with experience ranging from one to thirty-five years. The most common reason for rejecting requests is conflicting with traffic followed by violating air traffic procedures, increasing sector workload, and conflicting with major arrival and departure flows and flow restrictions. Quantitative parameters such as the distance that a route should maintain from sector boundaries and special use airspace were identified and recommended for inclusion in the automation.

Flight Optimization; Field Trial↗
NASA NTRS2016

TASAR Flight Trial 2: Assessment of Air Traffic Controller Acceptability of TASAR Requests

In support of the Flight Trial (FT-2) of NASA's prototype of the Traffic Aware Strategic Aircrew Requests (TASAR) concept, observations were conducted at the air traffic facilities to identify and assess the main factors that affect the acceptability of pilot requests by air traffic controllers. Two observers shadowed air traffic controllers at the Atlanta (ZTL) and Jacksonville (ZJX) air traffic control centers as the test flight pilot made pre-scripted requests to invoke acceptability issues and then they interviewed the observed and other controllers voluntarily. Fifty controllers were interviewed with experience ranging from one to thirty-five years. All interviewed controllers were enthusiastic about the technology and accounting for sector boundaries in pilot requests, particularly if pilots can be made aware of high workload situations. All interviewed controllers accept more than fifty percent of pilot requests; forty percent of them reject less than ten percent of requests. The most common reason for rejecting requests is conflicting with traffic followed by violating letters of agreement (LOAs) and negatively impacting neighboring sector workload, major arrival and departure flows and flow restrictions. Thirty-six requests were made during the test, eight of which were rejected due to: the aircraft already handed off to another sector, violating LOA, opposing traffic, intruding into an active special use airspace (SUA), intruding into another center, weather, and unfamiliarity with the requested waypoint. Nine requests were accepted with delay mostly because the controller needed to locate unfamiliar waypoints or to coordinate with other controllers.

Idris, Husni↗
NASA NTRS1993

Design of an air traffic computer simulation system to support investigation of civil tiltrotor aircraft operations

The TATSS Project's goal was to develop a design for computer software that would support the attainment of the following objectives for the air traffic simulation model: (1) Full freedom of movement for each aircraft object in the simulation model. Each aircraft object may follow any designated flight plan or flight path necessary as required by the experiment under consideration. (2) Object position precision up to +/- 3 meters vertically and +/- 15 meters horizontally. (3) Aircraft maneuvering in three space with the object position precision identified above. (4) Air traffic control operations and procedures. (5) Radar, communication, navaid, and landing aid performance. (6) Weather. (7) Ground obstructions and terrain. (8) Detection and recording of separation violations. (9) Measures of performance including deviations from flight plans, air space violations, air traffic control messages per aircraft, and traditional temporal based measures.

Rogers, Ralph V.↗
NASA NTRS2008

Trajectory Planning by Preserving Flexibility: Metrics and Analysis

In order to support traffic management functions, such as mitigating traffic complexity, ground and airborne systems may benefit from preserving or optimizing trajectory flexibility. To help support this hypothesis trajectory flexibility metrics have been defined in previous work to represent the trajectory robustness and adaptability to the risk of violating safety and traffic management constraints. In this paper these metrics are instantiated in the case of planning a trajectory with the heading degree of freedom. A metric estimation method is presented based on simplifying assumptions, namely discrete time and heading maneuvers. A case is analyzed to demonstrate the estimation method and its use in trajectory planning in a situation involving meeting a time constraint and avoiding loss of separation with nearby traffic. The case involves comparing path-stretch trajectories, in terms of adaptability and robustness along each, deduced from a map of estimated flexibility metrics over the solution space. The case demonstrated anecdotally that preserving flexibility may result in enhancing certain factors that contribute to traffic complexity, namely reducing proximity and confrontation.

Idris, Husni R.↗
NASA NTRSDate not supplied

Achieving Equilibrium for Dense, Integrated, Vehicle Navigation

Drone usage has proliferated in recent years with many applications that have market-changing potential. Applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. In this paper, the term drone is used to mean both Unmanned Aerial Vehicle and small Unmanned Aircraft System vehicles. Flight infrastructure can currently only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay atone airport sends ripple effects through the system, causing more delays and missed connections. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the NAS is expected to skyrocket to millions, potentially congesting the airspace resulting in possible separation violations. In air traffic control, separation is the concept of keeping an “ownship” aircraft outside a minimum distance from “intruder” aircraft to reduce the risk of the aircraft colliding, as well as preventing accidents due to secondary factors, such as wake turbulence. Maintaining proper separation is a safety critical property for drones in the airspace. This paper addresses separation in time and in distance for high volume corridors (en-route) and lanes(on ground). The requirements and necessary conditions for maintaining proper separation and reaching maximum throughput for a given corridor/lane are addressed assuming unidirectional corridors/lanes where an aircraft arrives from one side and departs from the opposite side. Simulation results are presented that show the presented solution guarantees a set of drones to reach the equilibrium state by adjusting their speed based on their distance to the aircraft in front of them. The equilibrium state is defined as a state when a set of n aircraft moving at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as a state when the aircraft cannot move at their maximum allowed speed. Unlike existing centralized and pre-planned approaches, the proposed solution is fully distributed and enables autonomous aircraft to decide to adjust their speed and distance with respect to the preceding aircraft, dynamically. Simulation results are presented that assess the feasibility of the approach using a large number of drones and evaluate the scalability of the proposed solution.

Mahyar R. Malekpour↗
NASA NTRSDate not supplied

Applying Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗
NASA NTRSDate not supplied

Machine Learning Tools for Runway Configuration Decision Support

Determining optimal runway configurations at airports, a responsibility assigned to air traffic controllers, is a challenging task. The decision-making process is intricate and involves consideration of many factors such as prevailing wind condition, convective weather, visibility, cloud ceilings, departure and arrival demand, traffic flow, equipment status, and other airport constraints. In a previous work, we developed a Runway Configuration Assistance tool using an offline reinforcement learning method called conservative Q-learning. In this paper, we evaluate and validate our Runway Configuration Assistance tool as a decision support for air traffic controllers. We validated our tool using three airports with differing levels of complexity: Charlotte Douglas International Airport, Denver International Airport, and Dallas Fort Worth International Airport. We quantified the performance of the Runway Configuration Assistance tool based on (1) agreement with historical air traffic controller decisions and (2) violation of decisions that would be obvious to subject-matter experts. Our tool showed promising results in both performance metrics for the three airports, despite the complexities in the runway configuration decision-making process. We also discuss challenges in using machine learning in general to aid air traffic management and identify deployment considerations for the Runway Configuration Assistance tool.

Runway Configuration Management↗
DOE OSTI2022

Experimental testing of a control barrier function on an automated vehicle in live multi-lane traffic

This paper experimentally tests an implementation of a control barrier function (CBF) designed to guarantee a minimum time-gap in car following on an automated vehicle (AV) in live traffic, with a majority occurring on freeways. The CBF supervises a nominal unsafe PID controller on the AV’s velocity. The experimental testing spans two months of driving, of which 1.9 hours of data is collected in which the CBF and nominal controller are active. We find that violations of the guaranteed minimum time-gap are observed, as measured by the vehicle’s on-board radar unit. There are two distinct causes of the violations. First, in multi-lane traffic, Cut-ins from other vehicles represent external disturbances that can immediately violate the minimum guaranteed time gap provided by the CBF. When cut-ins occur, the CBF does eventually return the vehicle to a safe time gap. Second, even when cut-ins do not occur, system model inaccuracies (e.g., sensor error and delay, actuator error and delay) can lead to violations of the minimum time-gap. These violations are small relative to the violations that would have occurred using only the unsafe nominal control law.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2011

Evaluation of High Density Air Traffic Operations with Automation for Separation Assurance, Weather Avoidance and Schedule Conformance

In this paper we discuss the development and evaluation of our prototype technologies and procedures for far-term air traffic control operations with automation for separation assurance, weather avoidance and schedule conformance. Controller-in-the-loop simulations in the Airspace Operations Laboratory at the NASA Ames Research Center in 2010 have shown very promising results. We found the operations to provide high airspace throughput, excellent efficiency and schedule conformance. The simulation also highlighted areas for improvements: Short-term conflict situations sometimes resulted in separation violations, particularly for transitioning aircraft in complex traffic flows. The combination of heavy metering and growing weather resulted in an increased number of aircraft penetrating convective weather cells. To address these shortcomings technologies and procedures have been improved and the operations are being re-evaluated with the same scenarios. In this paper we will first describe the concept and technologies for automating separation assurance, weather avoidance, and schedule conformance. Second, the results from the 2010 simulation will be reviewed. We report human-systems integration aspects, safety and efficiency results as well as airspace throughput, workload, and operational acceptability. Next, improvements will be discussed that were made to address identified shortcomings. We conclude that, with further refinements, air traffic control operations with ground-based automated separation assurance can routinely provide currently unachievable levels of traffic throughput in the en route airspace.

Prevot, Thomas↗
NASA NTRS2004

The Processing of Airspace Concept Evaluations Using FASTE-CNS as a Pre- or Post-Simulation CNS Analysis Tool

As NASA speculates on and explores the future of aviation, the technological and physical aspects of our environment increasing become hurdles that must be overcome for success. Research into methods for overcoming some of these selected hurdles have been purposed by several NASA research partners as concepts. The task of establishing a common evaluation environment was placed on NASA's Virtual Airspace Simulation Technologies (VAST) project (sub-project of VAMS), and they responded with the development of the Airspace Concept Evaluation System (ACES). As one examines the ACES environment from a communication, navigation or surveillance (CNS) perspective, the simulation parameters are built with assumed perfection in the transactions associated with CNS. To truly evaluate these concepts in a realistic sense, the contributions/effects of CNS must be part of the ACES. NASA Glenn Research Center (GRC) has supported the Virtual Airspace Modeling and Simulation (VAMS) project through the continued development of CNS models and analysis capabilities which supports the ACES environment. NASA GRC initiated the development a communications traffic loading analysis tool, called the Future Aeronautical Sub-network Traffic Emulator for Communications, Navigation and Surveillance (FASTE-CNS), as part of this support. This tool allows for forecasting of communications load with the understanding that, there is no single, common source for loading models used to evaluate the existing and planned communications channels; and that, consensus and accuracy in the traffic load models is a very important input to the decisions being made on the acceptability of communication techniques used to fulfill the aeronautical requirements. Leveraging off the existing capabilities of the FASTE-CNS tool, GRC has called for FASTE-CNS to have the functionality to pre- and post-process the simulation runs of ACES to report on instances when traffic density, frequency congestion or aircraft spacing/distance violations have occurred. The integration of these functions require that the CNS models used to characterize these avionic system be of higher fidelity and better consistency then is present in FASTE-CNS system. This presentation will explore the capabilities of FASTE-CNS with renewed emphasis on the enhancements being added to perform these processing functions; the fidelity and reliability of CNS models necessary to make the enhancements work; and the benchmarking of FASTE-CNS results to improve confidence for the results of the new processing capabilities.

Mainger, Steve↗
NASA NTRS1997

Identification of Error Patterns in Terminal-Area ATC Communications

Advancing air traffic management technologies have enabled a greater number of aircraft to use the same airspace more effectively. As aircraft separations are reduced and final approaches are more finely timed, there is less room for error. The present study examined 122 terminal-area, loss-of-separation and procedure violation incidents reported to the Aviation Safety Reporting System (ASRS) by air traffic controllers. Narrative description codes were used for the incidents for type of violation, contributing factors, recovery strategies, and consequences. Usually multiple errors occurred prior to the violation. Error sequences were analyzed and common patterns of errors were identified. In half of the incidents, errors were noticed in time to correct mistakes. Of these, almost 43% committed additional errors during the recovery attempt. This analysis shows that redundancies in the present air traffic control system may not be sufficient to support large increases in traffic density. Error prevention and design considerations for air traffic management systems are discussed.

Quinn, Cheryl↗
NASA NTRS2005

Joint NASA Ames/Langley Experimental Evaluation of Integrated Air/Ground Operations for En Route Free Maneuvering

In order to meet the anticipated future demand for air travel, the National Aeronautics and Space Administration (NASA) is investigating a new concept of operations known as Distributed Air-Ground Traffic Management (DAG-TM). Under the En Route Free Maneuvering component of DAG-TM, appropriately equipped autonomous aircraft self separate from other autonomous aircraft and from managed aircraft that continue to fly under today s Instrument Flight Rules (IFR). Controllers provide separation services between IFR aircraft and assign traffic flow management constraints to all aircraft. To address concept feasibility issues pertaining to integrated air/ground operations at various traffic levels, NASA Ames and Langley Research Centers conducted a joint human-in-the-loop experiment. Professional airline pilots and air traffic controllers flew a total of 16 scenarios under four conditions: mixed autonomous/managed operations at three traffic levels and a baseline all-managed condition at the lowest traffic level. These scenarios included en route flights and descents to a terminal area meter fix in airspace modeled after the Dallas Ft. Worth area. Pilots of autonomous aircraft met controller assigned meter fix constraints with high success. Separation violations by subject pilots did not appear to vary with traffic level and were mainly attributable to software errors and procedural lapses. Controller workload was lower for mixed flight conditions, even at higher traffic levels. Pilot workload was deemed acceptable under all conditions. Controllers raised several safety concerns, most of which pertained to the occurrence of near-term conflicts between autonomous and managed aircraft. These issues are being addressed through better compatibility between air and ground systems and refinements to air and ground procedures.

Barhydt, Richard↗
NASA NTRS1999

Satellite ATM Networks: Architectures and Guidelines Developed

An important element of satellite-supported asynchronous transfer mode (ATM) networking will involve support for the routing and rerouting of active connections. Work published under the auspices of the Telecommunications Industry Association (http://www.tiaonline.org), describes basic architectures and routing protocol issues for satellite ATM (SATATM) networks. The architectures and issues identified will serve as a basis for further development of technical specifications for these SATATM networks. Three ATM network architectures for bent pipe satellites and three ATM network architectures for satellites with onboard ATM switches were developed. The architectures differ from one another in terms of required level of mobility, supported data rates, supported terrestrial interfaces, and onboard processing and switching requirements. The documentation addresses low-, middle-, and geosynchronous-Earth-orbit satellite configurations. The satellite environment may require real-time routing to support the mobility of end devices and nodes of the ATM network itself. This requires the network to be able to reroute active circuits in real time. In addition to supporting mobility, rerouting can also be used to (1) optimize network routing, (2) respond to changing quality-of-service requirements, and (3) provide a fault tolerance mechanism. Traffic management and control functions are necessary in ATM to ensure that the quality-of-service requirements associated with each connection are not violated and also to provide flow and congestion control functions. Functions related to traffic management were identified and described. Most of these traffic management functions will be supported by on-ground ATM switches, but in a hybrid terrestrial-satellite ATM network, some of the traffic management functions may have to be supported by the onboard satellite ATM switch. Future work is planned to examine the tradeoffs of placing traffic management functions onboard a satellite as opposed to implementing those functions at the Earth station components.

vonDeak, Thomas C.↗