Results for “traffic violation” — Page 3

NASA NTRS2022

A Framework for Dynamic Architecture and Functional Allocations for Increasing Airspace Autonomy

To enable scalability of air travel for use cases such as cargo delivery, it is anticipated that future air traffic operations will involve unmanned aircraft operated by remote pilots. Of particular interest are schemes where a small number of pilots operate a large number of vehicles, mitigating high cost and pilot shortage issues. Such architectures require increased levels of automation and supervisory control modes. They also require ensuring safe operations when the command and control link to the vehicle is degraded or lost completely, rendering the vehicle autonomous. To evaluate these variable and dynamic architectures, this paper will present a framework for decomposing the functions necessary to ensure safe, orderly, and expeditious air travel, assessing the agents in the system, and classifying the levels of autonomy. Then, an example allocation to agents of roles for the function of separation assurance is presented, highlighting the dependency of the allocation on three main factors; time criticality of a potential separation violation, the ratio of pilots to vehicles, and the loss of the command and control link.

air traffic management↗

NASA NTRS2012

Comparison of Predictive Modeling Methods of Aircraft Landing Speed

Expected increases in air traffic demand have stimulated the development of air traffic control tools intended to assist the air traffic controller in accurately and precisely spacing aircraft landing at congested airports. Such tools will require an accurate landing-speed prediction to increase throughput while decreasing necessary controller interventions for avoiding separation violations. There are many practical challenges to developing an accurate landing-speed model that has acceptable prediction errors. This paper discusses the development of a near-term implementation, using readily available information, to estimate/model final approach speed from the top of the descent phase of flight to the landing runway. As a first approach, all variables found to contribute directly to the landing-speed prediction model are used to build a multi-regression technique of the response surface equation (RSE). Data obtained from operations of a major airlines for a passenger transport aircraft type to the Dallas/Fort Worth International Airport are used to predict the landing speed. The approach was promising because it decreased the standard deviation of the landing-speed error prediction by at least 18% from the standard deviation of the baseline error, depending on the gust condition at the airport. However, when the number of variables is reduced to the most likely obtainable at other major airports, the RSE model shows little improvement over the existing methods. Consequently, a neural network that relies on a nonlinear regression technique is utilized as an alternative modeling approach. For the reduced number of variables cases, the standard deviation of the neural network models errors represent over 5% reduction compared to the RSE model errors, and at least 10% reduction over the baseline predicted landing-speed error standard deviation. Overall, the constructed models predict the landing-speed more accurately and precisely than the current state-of-the-art.

Diallo, Ousmane H.↗

NASA NTRS2012

Design and Evaluation of Nextgen Aircraft Separation Assurance Concepts

To support the development and evaluation of future function allocation concepts for separation assurance systems for the Next Generation Air Transportation System, this paper presents the design and human-in-the-loop evaluation of three feasible function allocation concepts that allocate primary aircraft separation assurance responsibilities and workload to: 1) pilots; 2) air traffic controllers (ATC); and 3) automation. The design of these concepts also included rules of the road, separation assurance burdens for aircraft of different equipage levels, and utilization of advanced weather displays paired with advanced conflict detection and resolution automation. Results of the human-in-the-loop simulation show that: a) all the concepts are robust with respect to weather perturbation; b) concept 1 (pilots) had highest throughput, closest to assigned spacing, and fewest violations of speed and altitude restrictions; c) the energy of the aircraft during the descent phase was better managed in concepts 1 and 2 (pilots and ATC) than in concept 3 (automation), in which the situation awareness of pilots and controllers was lowest, and workload of pilots was highest. The paper also discusses further development of these concepts and their augmentation and integration with future air traffic management tools and systems that are being considered for NextGen.

Johnson, Walter↗

NASA NTRS2014

Human-Automation Cooperation for Separation Assurance in Future NextGen Environments

A 2012 Human-In-The-Loop air traffic control simulation investigated a gradual paradigm-shift in the allocation of functions between operators and automation. Air traffic controllers staffed five adjacent high-altitude en route sectors, and during the course of a two-week experiment, worked traffic under different function-allocation approaches aligned with four increasingly mature NextGen operational environments. These NextGen time-frames ranged from near current-day operations to nearly fully-automated control, in which the ground systems automation was responsible for detecting conflicts, issuing strategic and tactical resolutions, and alerting the controller to exceptional circumstances. Results indicate that overall performance was best in the most automated NextGen environment. Safe operations were achieved in this environment for twice todays peak airspace capacity, while being rated by the controllers as highly acceptable. However, results show that sector operations were not always safe; separation violations did in fact occur. This paper will describe in detail the simulation conducted, as well discuss important results and their implications.

air traffic control↗

NASA NTRS2013

Coarse-Grain Bandwidth Estimation Scheme for Large-Scale Network

A large-scale network that supports a large number of users can have an aggregate data rate of hundreds of Mbps at any time. High-fidelity simulation of a large-scale network might be too complicated and memory-intensive for typical commercial-off-the-shelf (COTS) tools. Unlike a large commercial wide-area-network (WAN) that shares diverse network resources among diverse users and has a complex topology that requires routing mechanism and flow control, the ground communication links of a space network operate under the assumption of a guaranteed dedicated bandwidth allocation between specific sparse endpoints in a star-like topology. This work solved the network design problem of estimating the bandwidths of a ground network architecture option that offer different service classes to meet the latency requirements of different user data types. In this work, a top-down analysis and simulation approach was created to size the bandwidths of a store-and-forward network for a given network topology, a mission traffic scenario, and a set of data types with different latency requirements. These techniques were used to estimate the WAN bandwidths of the ground links for different architecture options of the proposed Integrated Space Communication and Navigation (SCaN) Network. A new analytical approach, called the "leveling scheme," was developed to model the store-and-forward mechanism of the network data flow. The term "leveling" refers to the spreading of data across a longer time horizon without violating the corresponding latency requirement of the data type. Two versions of the leveling scheme were developed: 1. A straightforward version that simply spreads the data of each data type across the time horizon and doesn't take into account the interactions among data types within a pass, or between data types across overlapping passes at a network node, and is inherently sub-optimal. 2. Two-state Markov leveling scheme that takes into account the second order behavior of the store-and-forward mechanism, and the interactions among data types within a pass. The novelty of this approach lies in the modeling of the store-and-forward mechanism of each network node. The term store-and-forward refers to the data traffic regulation technique in which data is sent to an intermediate network node where they are temporarily stored and sent at a later time to the destination node or to another intermediate node. Store-and-forward can be applied to both space-based networks that have intermittent connectivity, and ground-based networks with deterministic connectivity. For groundbased networks, the store-and-forward mechanism is used to regulate the network data flow and link resource utilization such that the user data types can be delivered to their destination nodes without violating their respective latency requirements.

Cheung, Kar-Ming↗

NASA NTRS2015

Evaluating Performance of UAS Detect-And-Avoid System Using a Fast-Time Simulation Tool

Most unmanned aircraft systems will be required to be equipped with a Detect-and-Avoid (DAA) system. The surveillance performance of the DAA system to detect and track intruder aircraft will depend on the encounter geometries that unmanned aircraft are expected to have with other aircraft in the airspace. The performance of DAA alerting and avoidance system is also dependent on the timeliness of alerting for UAS pilots to give a sufficient time to determine and command a resolution maneuver to avoid well clear separation violations. This presentation introduces general background of UAS DAA systems and concept of well clear separation standard to satisfy see and avoid regulations. The presentation shows the several UAS mission profiles and analysis of the encounter geometries that were simulated using historical VFR traffic data and some proposed UAS missions. This presentation introduces several potential metrics for evaluating the performance of a DAA system and shows the results that measured through fast-time simulation with traffic scenarios that include NAS-wide VFR manned aircraft and IFR UAS flights. At the end, some research areas will be briefly discussed.

UAS↗

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. 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 often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its 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.

Distributed↗

NASA NTRSDate not supplied

A Strategic Approach for Dense, Integrated, Vehicle Navigation

Drone usage has been on the rise in recent years with applications that include parcel delivery, wildlife protection, precision farming, law enforcement, and industrial inspection, just to name a few. Once regulations and safety policies are put in place to allow for the widespread use of unmanned drones, the number of aircraft in the National Airspace System (NAS) is expected to skyrocket to millions, potentially congesting the airspace which increases the likelihood of separation violations and possibly incidents. Currently, flight infrastructure can only support a few thousand aircraft flying over the United States National Airspace System (NAS) at any given time. A delay at one airport can send ripple effects throughout the system, causing more delays and missed connections. 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 often a safety critical property for fixed-wing drones in the airspace. This paper addresses drone separation in time and distance for high volume corridors (en route) and lanes (on ground), merging as well as crossing intersections of multiple corridors/lanes. In this paper, the term drone is applied to both Unmanned Aerial Vehicle (UAV) and small Unmanned Aircraft System (UAS) vehicles operating autonomously. There exists a gamut of approaches to the merging and crossing problems. At one end of the extreme are the conservative yet low cost and verifiable solutions of today that deal with two drones at a time. At the other end are complex Machine Learning-based solutions with high computing requirements for fully autonomous drones of the future that are expected to handle all contentions. This paper presents a feasible and verifiable strategic approach to these problems that is based on distributed cooperation between the drones and the infrastructure. Three phases of the strategic approach (Prepare, Adjust, Commit) are presented. Simulation results are presented that show the proposed approach is stable and resilient to induced perturbations and guarantees a set of fixed-wing drones to merge and cross intersections by adjusting their speed based on their distance to the aircraft in front of them while remaining in the equilibrium state. The equilibrium state is defined as the state when a set of n aircraft move at a relatively constant speed and uniform spacing from each other in a congested system. A congested system is defined as the state when at least one aircraft cannot move at its 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.

Distributed↗

NASA NTRS2013

NextGen Operations in a Simulated NY Area Airspace

A human-in-the-loop simulation conducted in the Airspace Operations Laboratory (AOL) at NASA Ames Research Center explored the feasibility of a Next Generation Air Transportation System (NextGen) solution to address airspace and airport capacity limitations in and around the New York metropolitan area. A week-long study explored the feasibility of a new Optimal Profile Descent (OPD) arrival into the airspace as well as a novel application of a Terminal Area Precision Scheduling and Spacing (TAPSS) enhancement to the Traffic Management Advisor (TMA) arrival scheduling tool to coordinate high volume arrival traffic to intersecting runways. In the simulation, four en route sector controllers and four terminal radar approach control (TRACON) controllers managed traffic inbound to Newark International Airport's primary runway, 22L, and its intersecting overflow runway, 11. TAPSS was used to generate independent arrival schedules for each runway and a traffic management coordinator participant adjusted the arrival schedule for each runway 11 aircraft to follow one of the 22L aircraft. TAPSS also provided controller-managed spacing tools (slot markers with speed advisories and timelines) to assist the TRACON controllers in managing the arrivals that were descending on OPDs. Results showed that the tools significantly decreased the occurrence of runway violations (potential go-arounds) when compared with a Baseline condition with no tools. Further, the combined use of the tools with the new OPD produced a peak arrival rate of over 65 aircraft per hour using instrument flight rules (IFR), exceeding the current maximum arrival rate at Newark Liberty International Airport (EWR) of 52 per hour under visual flight rules (VFR). Although the participants rated the workload as relatively low and acceptable both with and without the tools, they rated the tools as reducing their workload further. Safety and coordination were rated by most participants as acceptable in both conditions, although the TRACON Runway Coordinator (TRC) rated neither as acceptable in the Baseline condition. Regarding the role of the TRC, the two TRACON controllers handling the 11 arrivals indicated that the TRC was very much needed in the Baseline condition without tools, but not needed in the condition with tools. This indicates that the tools were providing much of the sequencing and spacing information that the TRC had supplied in the Baseline condition.

NextGen↗

NASA NTRS2014

A Family of Well-Clear Boundary Models for the Integration of UAS in the NAS

The FAA-sponsored Sense and Avoid Workshop for Unmanned Aircraft Systems (UAS) defines the concept of sense and avoid for remote pilots as "the capability of a UAS to remain well clear from and avoid collisions with other airborne traffic." Hence, a rigorous definition of well clear is fundamental to any separation assurance concept for the integration of UAS into civil airspace. This paper presents a family of well-clear boundary models based on the TCAS II Resolution Advisory logic. For these models, algorithms that predict well-clear violations along aircraft current trajectories are provided. These algorithms are analogous to conflict detection algorithms but instead of predicting loss of separation, they predict whether well-clear violations will occur during a given lookahead time interval. Analytical techniques are used to study the properties and relationships satisfied by the models.

Munoz, Cesar A.↗

NASA NTRS1998

Steps Towards the Integration of Conflict Resolution with Metering and Scheduling

NASA Ames Research Center is developing decision support tool technology for air traffic controllers to improve the efficiency and capacity of National Airspace System. The goal is to provide technology, tools and procedures that result in the highest possible level of user preferred trajectories whenever possible with safe and efficient traffic management when necessary. The work is being conducted under the NASA Advanced Air Transportation Technology Program in cooperation with the FAA through the Inter-Agency Integrated Product Team. The objective is to develop technology and procedures that lead towards a seamless integration of conflict resolution with metering and scheduling for arrival aircraft and en route aircraft that are under metering restrictions. A requirement is that the integration incorporate user preferred trajectories. The ultimate goal is the implementation and validation of the Descent Advisor (DA) concept which provides clearance advisories to a sector controller that simultaneously meet metering constraints, are conflict free, incorporate a user preferred (e.g., minimum fuel) descent profile, and generally require no further corrective clearance as the aircraft transitions from en route cruise into the TRACON. The DA concept may also be applied to en route aircraft under metering constraints, e.g., miles-in-trail. To achieve the DA concept a stepwise development and field evaluation is anticipated. This paper addresses the initial steps towards implementation of the DA. The Traffic Management Advisor (TMA) computes arrival time sequence and required delay information for display to the sector controller during periods when arrivals must be metered due to landing rate restrictions at the airport. The Initial Conflict Probe (ICP) compares trajectory predictions for all aircraft and alerts the controller when any two aircraft are predicted to violate separation standards (5 mi. and 2000 ft. in en route airspace). ICP also includes a trial planning function allowing the controller to develop and check a separate "what if" trajectory for conflict resolution. TMA and ICP currently operate independent of one another and have separate controller displays. The TMA meter list is on the radar controller's plan view display. The ICP is still under development, but the current concept calls for a list of predicted conflicts at the data controller position. The research described herein address two steps towards the implementation of DA. The first is to develop a concept for integrated display of conflict and metering information on a controller's display. The objective is to provide the controller with situational awareness of one problem while he develops a solution to the other. The next step is to expand the concept for display of automated clearance advisories for one problem (e.g., metering) which take into account the other problems (e.g., conflicts). Information to be communicated between TMA and ICP to facilitate' manual or automated advisories is being identified as the concept matures. In order to study the ICP/TMA integration concept the CTAS conflict probe capability has been adapted to Ft. Worth Center. The system is being validated in the laboratory with all-track data and for non -interference with TMA, TMA is already running as a daily use prototype at Ft. Worth Center. A laboratory prototype system has been developed under the CTAS baseline which combines conflict and metering information on a common user interface. Elements of the user interface are shown in Figure 1. In this simple illustration the user sees the simultaneous effect of a trial plan on meter fix delay and conflict status. Delay information is shown in the aircraft flight data block, the meter list, and the TMA timeline. Experience during Descent Advisor development and observations at Ft. Worth Center high and low attitude arrival sectors during metering suggests that manual trial planning will be unworkable during rush periods due to high controller workload.

McNally, B. David↗

NASA NTRS1987

An advisory system for predicting and resolving airspace violations based on four-dimensional guidance techniques

New heuristics are integrated with four-dimensional guidance techniques developed by NASA in order to automate the prediction and resolution of airspace violations, and three rules are derived to reduce the amount of computation time for conflict detection. Controller experience has been used to establish techniques for resolving potential conflicts including speed control, altitude maneuvers, and horizontal flight maneuvers. Current aircraft states, flight plans, and extrapolation of aircraft trajectories are used to synthesize four-dimensional trajectories, and the state of the air traffic and the interaction between aircraft are projected into the future using the four-dimensional algorithms. The situation is immediately updated to incorporate any new information. Potential conflicts among multiple aircraft are resolved by fast sequential resolution of potential conflicts between aircraft pairs, one at a time.

Lee, Homer Q.↗

NASA NTRS2018

Unmanned Aerial Systems (UAS) Integration into the National Airspace System (NAS)

NASA's Unmanned Aerial Systems (UAS) integration into the National Air Space (NAS) project has been working closely with the FAA and RTCA Special Committee 228 to identify and break down barriers to UAS integration. A focus of this work is on detect and avoid (DAA) technologies. A pilot has responsibility to see and avoid other aircraft and to remain "well clear," using their best judgment (Federal Aviation Regulations (FAR) Sec. 91.113). For UAS to perform this function, the see function is replaced by sensors to detect the other aircraft. Secondly, the pilot judgment of well clear has to be replaced by a mathematical expression. For Phase 1 of this effort, a well clear violation was defined if all three of these conditions are true: a) the horizontal clearance is less than 4000 ft., and b) the vertical clearance is less than 450 ft., and c) the time to loss of well clear is less than 35 seconds. This definition was developed with a great deal of community input and testing to ensure interoperability with Air Traffic Control (ATC) and pilots of manned aircraft. Appropriate guidance, alerting and displays were developed to allow UAS, with the appropriate sensors, to effectively maintain well clear. This work contributed to FAA Technical Standard Orders: TSO-C211, Detect and Avoid and TSO-C212, ATAR for Traffic Surveillance. Phase 2 of this work extends the operational environment to include the terminal area and lesser capable aircraft that might not have the payload capability to carry the RADAR defined in Phase 1. This session reports on work from Phase 1 and initial work in Phase 2.

UAS↗

NASA NTRS2018

Detect and Avoid: Efforts from NASA's UAS Integration into the NAS Project

NASA's Unmanned Aerial Systems (UAS) integration into the National Air Space (NAS) project has been working closely with the FAA and RTCA Special Committee 228 to identify and break down barriers to UAS integration. A focus of this work is on detect and avoid (DAA) technologies. A pilot has responsibility to see and avoid other aircraft and to remain "well clear," using their best judgment (Federal Aviation Regulations (FAR) Sec. 91.113). For UAS to perform this function, the see function is replaced by sensors to detect the other aircraft. Secondly, the pilot judgment of well clear has to be replaced by a mathematical expression. For Phase 1 of this effort, a well clear violation was defined if all three of these conditions are true: a) the horizontal clearance is less than 4000 ft., and b) the vertical clearance is less than 450 ft., and c) the time to loss of well clear is less than 35 seconds. This definition was developed with a great deal of community input and testing to ensure interoperability with Air Traffic Control (ATC) and pilots of manned aircraft. Appropriate guidance, alerting and displays were developed to allow UAS, with the appropriate sensors, to effectively maintain well clear. This work contributed to FAA Technical Standard Orders: TSO-C211, Detect and Avoid and TSO-C212, ATAR for Traffic Surveillance. Phase 2 of this work extends the operational environment to include the terminal area and lesser capable aircraft that might not have the payload capability to carry the RADAR defined in Phase 1. This session reports on work from Phase 1 and initial work in Phase 2.

Detect and Avoid (DAA)↗

NASA NTRS2014

Investigating Detect-and-Avoid Surveillance Performance for Unmanned Aircraft Systems

Most unmanned aircraft systems will be required to be equipped with a Detect-and-Avoid (DAA) system with a surveillance component. The surveillance performance requirements of the DAA system to detect and track intruder aircraft will depend on the encounter geometries that unmanned aircraft are expected to have with other aircraft in the airspace. This presentation shows the analysis of the encounter geometries that were simulated using historical low-altitude traffic data and some proposed UAS missions. This analysis suggests how the overall safety and performance of a surveillance system may relate to surveillance parameters such as surveillance range, horizontal and vertical fields or regard. This study proposed and investigated potential safety and performance metrics for evaluating the performance of a surveillance system, such as the ratio of undetected and late-detected separation violations, and the time to violation at first detection for given sets of surveillance parameters.

UAS↗

NASA NTRS2014

Investigating Surveillance Performance for UAS Detect-and-Avoid Systems

Most unmanned aircraft systems will be required to be equipped with a detect-and-avoid system that is capable of maintaining appropriate separation from other aircraft. One of the critical components of detect-and-avoid systems is a surveillance system that identifies potential threat aircraft in real time and tracks these aircraft so that their future trajectories may be used to predict conflicts. The performance of the detect-and-avoid system generally depends on technical parameters of the surveillance system, such as the surveillance range. The quantitative requirements for detect-and-avoid systems will be determined to meet safety metrics for the operation of unmanned aircraft systems in the National Airspace System. This study employs a sensor model comprised of the surveillance range, and horizontal and vertical fields of regard that mainly characterize the overall performance of a surveillance system. In this study, potential metrics for evaluating the performance of a surveillance system were investigated through fast-time simulation with a traffic scenario that included both proposed unmanned aircraft flights and historical visual flight rule aircraft tracks. Using the simulation results, an overall analysis of encounter geometry highlights the encounter characteristics that relate surveillance parameters to safety metrics and detect-and-avoid system performance. Then, given several candidate surveillance volumes, performance and safety metrics are derived; these metrics include the ratio of undetected and late-detected violations and the time to violation at first detection. These example metrics demonstrate the utility of the database of encounters created in this work, a database which will be useful in the derivation of required detect-and-avoid surveillance system requirements.

Lee, Seung Man↗

NASA NTRS2011

Estimating Controller Intervention Probabilities for Optimized Profile Descent Arrivals

Simulations of arrival traffic at Dallas/Fort-Worth and Denver airports were conducted to evaluate incorporating scheduling and separation constraints into advisories that define continuous descent approaches. The goal was to reduce the number of controller interventions required to ensure flights maintain minimum separation distances of 5 nmi horizontally and 1000 ft vertically. It was shown that simply incorporating arrival meter fix crossing-time constraints into the advisory generation could eliminate over half of the all predicted separation violations and more than 80% of the predicted violations between two arrival flights. Predicted separation violations between arrivals and non-arrivals were 32% of all predicted separation violations at Denver and 41% at Dallas/Fort-Worth. A probabilistic analysis of meter fix crossing-time errors is included which shows that some controller interventions will still be required even when the predicted crossing-times of the advisories are set to add a 1 or 2 nmi buffer above the minimum in-trail separation of 5 nmi. The 2 nmi buffer was shown to increase average flight delays by up to 30 sec when compared to the 1 nmi buffer, but it only resulted in a maximum decrease in average arrival throughput of one flight per hour.

continous descent arrivals↗

NASA NTRS1971

On optimal scheduling and air traffic control in the near terminal area

A scheme is proposed for automated air traffic control of landing aircraft in the vicinity of the airport. Each aircraft is put under the control of an airport-based computer as soon as it enters the near-terminal area (NTA). Scheduling is done immediately thereafter. The aircraft is given a flight plan which, if followed precisely, will lead it to the runway at a prespecified time. The geometry of the airspace in the NTA is chosen so that delays are executed far from the outer marker, and violations of minimum altitude and lateral separations are avoided. Finally, a solution to the velocity mix problem is proposed.

Sarris, A. H.↗