Terminal area guidance incorporating heavy weather

Krozel, Jimmy; Weidner, Tara; Hunter, George

doi:10.2514/6.1997-3541

Cited by 22 publications

(7 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The problem can be formalized as a weighted regions problem in which routes obey Snell's law of refraction [5,8,9,11] as a local optimality criterion. Algorithms can exploit the fact that optimal routes bend at boundaries between regions of varying weather severity in analogy with light rays that refract as they pass through regions of varying refractive index [5][6][7][8][9][10][11]. Another approach [3] searches for paths having at most k turns (waypoints), while avoiding hazardous weather, thereby bounding the workload of the pilot and controller required to track the solution.…”

Section: Related Literaturementioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

“…Several approaches apply an optimal path algorithm based on grid search methods [3][4][5][6][7]. The problem can be formalized as a weighted regions problem in which routes obey Snell's law of refraction [5,8,9,11] as a local optimality criterion. Algorithms can exploit the fact that optimal routes bend at boundaries between regions of varying weather severity in analogy with light rays that refract as they pass through regions of varying refractive index [5][6][7][8][9][10][11].…”

Section: Related Literaturementioning

confidence: 99%

See 2 more Smart Citations

Automated Route Generation for Avoiding Deterministic Weather in Transition Airspace

Krozel¹,

Penny²,

Prete³

et al. 2007

Journal of Guidance, Control, and Dynamics

Self Cite

View full text Add to dashboard Cite

We investigate the problem of synthesizing weather avoidance routes in the transition airspace, from the 200 n mile range to the metering fixes of an airport, given a deterministic weather forecast. The investigation of the problem is motivated by the desire to maximize airspace capacity while ensuring safe separation between aircraft and between aircraft and hazardous weather. Three solution methods are compared with current day operations. Emphasis is placed on a comparison of the arrival traffic weather avoidance routing method and metrics associated with such routes. Historical weather avoidance paths (baseline) are compared with three alternatives: variations of the standard arrival routes, a geometric optimization solution synthesizing multiple nonintersecting routes, and two free-flight approaches in which aircraft fly weather avoidance routes using a greedy prioritization method. Results indicate that increases in capacity over today's system are achievable, while maintaining safety. However, such increases are limited by the method, the required supporting infrastructure, and weather severity and location.

show abstract

Section: Related Literaturementioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

Section: Related Literaturementioning

confidence: 99%

See 1 more Smart Citation

Automated Route Generation for Avoiding Deterministic Weather in Transition Airspace

Krozel¹,

Penny²,

Prete³

et al. 2007

Journal of Guidance, Control, and Dynamics

Self Cite

View full text Add to dashboard Cite

show abstract

“…For example, several automation tools are being developed for detecting and resolving air traffic conflicts and managing the arrival flow at airports (Davis et al, 1994;Slattery & Green, 1994;Paielli & Erzberger, 1997). These tools currently do not include hazardous weather information in their automated decisions, though some study of incorporating weather has begun in this area (e.g., Krozel et al, 1997). When weather is not considered by the automation, the human operator must mentally integrate the information to determine whether a given automated suggestion is appropriate.…”

Section: Introductionmentioning

confidence: 99%

Integrating objective and subjective hazard risk in decision-aiding system design

Kuchar

Walton

Matsumoto

2002

Reliability Engineering & System Safety

View full text Add to dashboard Cite

A generalized model is presented to incorporate objective (hard) and subjective (soft) hazard information in automated decision-aiding systems. The model may be used with more than one hazard, of more than one type, in a given problem. Uncertainties in state measurements, dynamics, hazard extent, and hazard severity are included, as is consideration of the fact that different operators may have different concepts of what is an acceptable or unacceptable risk. By examining the tradeoffs created by these uncertainties, appropriate decision thresholds can be selected. Using an aviation case study, information gained from observation of aircraft behavior in the presence of weather was used to develop a model of weather as a soft hazard. This information could then be used in a decision aid to provide feedback on route acceptability. IntroductionReal-time decision aiding and alerting systems are often used to assist human operators in controlling processes efficiently and in preventing undesirable incidents from occurring (such as a collision in a vehicle control application, or exceeding temperature limits in process control). There are a number of types of real-time decision aids, ranging from process status displays, to planning tools, to safety-and time-critical warning systems. However, all decision aids can be broadly classified as either active or passive. Active systems generate discrete decisions or commands that are communicated to the operator with the intent of modifying the process' future state trajectory (e.g., a traffic conflict resolution command). Passive systems provide process and environment state information to the operator (e.g., depicting precipitation levels on a weather radar display) without explicit decisions being made by the automation. Thus, an active system acts as an automated decision maker (which may agree or disagree with the human operator's decisions), while a passive system acts as an automated decision supporter.

show abstract

“…24,25 They further developed an algorithm to estimate capacity over longer time frames when weather is treated probabilistically, using computational geometry and ensemble weather forecasts to assist in defining routes with a high probability of availability. [26][27][28] Rhoda et al investigated translation of convective weather forecasts to terminal area impacts.…”

Section: Weather Impact Mitigationmentioning

confidence: 99%