Matches in SemOpenAlex for { <https://semopenalex.org/work/W3153669328> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W3153669328 abstract "Aircraft in the National Aviation System (NAS) often rely on wind information from the National Oceanic and Atmospheric Administration (NOAA) to calculate favorable paths. However, wind conditions are dynamic and the NOAA information becomes quickly outdated because it is based upon sparse sampling both in space and time. This leads to inefficient, slower, paths used in practice. A goal of the Federal Aviation Administration’s (FAA) NextGen program is to use dynamic information to reduce inefficiencies. One such way to obtain high quality dynamic information and reduce inefficiency is to use en-route aircraft as ‘sensors’. This raises a natural question, “if a fraction of the aircraft can be used for sampling, how should aircraft be routed to provide most useful information for other aircraft to minimize system costs?” To answer this question, we begin with a stylized model of the aircraft routing problem, and capture the uniquely spatial and temporal correlations in wind dynamics. This allows us to model spatial and temporal correlation between the travel time along different paths, and formulate the travel time as a Brownian surface. Under this uncertainty structure, we answer two questions: (i) if an offline schedule of paths to be sampled is desired, what is the optimal sampling schedule? and (ii) if the paths to be sampled are to be chosen in real time according to flight schedules, what is a near-optimal sampling policy? We provide answers to these questions with provable guarantees. We also generate a comprehensive testbed from real-world flight data and computationally evaluate the performance of our sampling policies. Our testbed consists of seventeen origin-destination airport pairs, with five short haul, seven medium haul and five long-haul pairs. Our results show that collecting the right information and utilizing it to plan future aircraft routes could reduce a flight's travel time and associated fuel burn by 5$%$ on average. Our modeling framework and results are also applicable to smaller, intra-city aircraft and unmanned aircraft such as UAVs and drones." @default.
- W3153669328 created "2021-04-26" @default.
- W3153669328 creator A5002047466 @default.
- W3153669328 creator A5029619641 @default.
- W3153669328 creator A5029879856 @default.
- W3153669328 date "2021-02-19" @default.
- W3153669328 modified "2023-09-23" @default.
- W3153669328 title "Sensing in Airspace for Sequential O-D Aircraft Routing" @default.
- W3153669328 hasPublicationYear "2021" @default.
- W3153669328 type Work @default.
- W3153669328 sameAs 3153669328 @default.
- W3153669328 citedByCount "0" @default.
- W3153669328 crossrefType "posted-content" @default.
- W3153669328 hasAuthorship W3153669328A5002047466 @default.
- W3153669328 hasAuthorship W3153669328A5029619641 @default.
- W3153669328 hasAuthorship W3153669328A5029879856 @default.
- W3153669328 hasConcept C111919701 @default.
- W3153669328 hasConcept C127413603 @default.
- W3153669328 hasConcept C139719470 @default.
- W3153669328 hasConcept C140779682 @default.
- W3153669328 hasConcept C146978453 @default.
- W3153669328 hasConcept C162324750 @default.
- W3153669328 hasConcept C2776381931 @default.
- W3153669328 hasConcept C2780722376 @default.
- W3153669328 hasConcept C38935604 @default.
- W3153669328 hasConcept C41008148 @default.
- W3153669328 hasConcept C42475967 @default.
- W3153669328 hasConcept C68387754 @default.
- W3153669328 hasConcept C74448152 @default.
- W3153669328 hasConcept C76155785 @default.
- W3153669328 hasConcept C79403827 @default.
- W3153669328 hasConcept C94915269 @default.
- W3153669328 hasConceptScore W3153669328C111919701 @default.
- W3153669328 hasConceptScore W3153669328C127413603 @default.
- W3153669328 hasConceptScore W3153669328C139719470 @default.
- W3153669328 hasConceptScore W3153669328C140779682 @default.
- W3153669328 hasConceptScore W3153669328C146978453 @default.
- W3153669328 hasConceptScore W3153669328C162324750 @default.
- W3153669328 hasConceptScore W3153669328C2776381931 @default.
- W3153669328 hasConceptScore W3153669328C2780722376 @default.
- W3153669328 hasConceptScore W3153669328C38935604 @default.
- W3153669328 hasConceptScore W3153669328C41008148 @default.
- W3153669328 hasConceptScore W3153669328C42475967 @default.
- W3153669328 hasConceptScore W3153669328C68387754 @default.
- W3153669328 hasConceptScore W3153669328C74448152 @default.
- W3153669328 hasConceptScore W3153669328C76155785 @default.
- W3153669328 hasConceptScore W3153669328C79403827 @default.
- W3153669328 hasConceptScore W3153669328C94915269 @default.
- W3153669328 hasLocation W31536693281 @default.
- W3153669328 hasOpenAccess W3153669328 @default.
- W3153669328 hasPrimaryLocation W31536693281 @default.
- W3153669328 hasRelatedWork W1503799034 @default.
- W3153669328 hasRelatedWork W1511514297 @default.
- W3153669328 hasRelatedWork W2034006608 @default.
- W3153669328 hasRelatedWork W2081727944 @default.
- W3153669328 hasRelatedWork W2133337234 @default.
- W3153669328 hasRelatedWork W2156957867 @default.
- W3153669328 hasRelatedWork W2278511009 @default.
- W3153669328 hasRelatedWork W2321268219 @default.
- W3153669328 hasRelatedWork W2326242448 @default.
- W3153669328 hasRelatedWork W2573562663 @default.
- W3153669328 hasRelatedWork W2600491613 @default.
- W3153669328 hasRelatedWork W2810132056 @default.
- W3153669328 hasRelatedWork W2884389291 @default.
- W3153669328 hasRelatedWork W2904055643 @default.
- W3153669328 hasRelatedWork W2945506617 @default.
- W3153669328 hasRelatedWork W2987174194 @default.
- W3153669328 hasRelatedWork W3034871379 @default.
- W3153669328 hasRelatedWork W3080270281 @default.
- W3153669328 hasRelatedWork W3099787123 @default.
- W3153669328 hasRelatedWork W3192658584 @default.
- W3153669328 isParatext "false" @default.
- W3153669328 isRetracted "false" @default.
- W3153669328 magId "3153669328" @default.
- W3153669328 workType "article" @default.