Ontology type: schema:Chapter
2017-05-18
AUTHORSAkinori Murata , Hiroyuki Sato , Keiki Takadama
ABSTRACTThis paper focuses on how cognitive loads of air traffic controllers can be reduced when optimizing both aircraft route and landing order in the airport landing problem (ALP), and proposes its method which can adaptively change the optimized aircraft landing order according to the aircraft routes partially fixed by air traffic controllers as human intervention. Though the intensive simulation on Haneda Airport in ALP, the following implications have been revealed: (1) our proposed optimization method succeeded to mostly maintain the same level of the results without fixing some of aircraft routes (i.e., the mostly same total distance of all aircrafts from the start position to the destination airport) even if air traffic controllers fixed some of aircraft routes; and (2) this result indicates that our proposed method has a great potential of reducing the cognitive loads of air traffic controllers by reducing the number of aircrafts that should be watched with fixing some of aircraft routes. More... »
PAGES422-433
Human Interface and the Management of Information: Supporting Learning, Decision-Making and Collaboration
ISBN
978-3-319-58523-9
978-3-319-58524-6
http://scigraph.springernature.com/pub.10.1007/978-3-319-58524-6_33
DOIhttp://dx.doi.org/10.1007/978-3-319-58524-6_33
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1086690447
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/17",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Psychology and Cognitive Sciences",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1701",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"name": "Psychology",
"type": "DefinedTerm"
}
],
"author": [
{
"affiliation": {
"alternateName": "The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan",
"id": "http://www.grid.ac/institutes/grid.266298.1",
"name": [
"The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan"
],
"type": "Organization"
},
"familyName": "Murata",
"givenName": "Akinori",
"id": "sg:person.011113507637.62",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011113507637.62"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan",
"id": "http://www.grid.ac/institutes/grid.266298.1",
"name": [
"The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan"
],
"type": "Organization"
},
"familyName": "Sato",
"givenName": "Hiroyuki",
"id": "sg:person.07750750604.05",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07750750604.05"
],
"type": "Person"
},
{
"affiliation": {
"alternateName": "The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan",
"id": "http://www.grid.ac/institutes/grid.266298.1",
"name": [
"The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan"
],
"type": "Organization"
},
"familyName": "Takadama",
"givenName": "Keiki",
"id": "sg:person.012774267611.99",
"sameAs": [
"https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012774267611.99"
],
"type": "Person"
}
],
"datePublished": "2017-05-18",
"datePublishedReg": "2017-05-18",
"description": "This paper focuses on how cognitive loads of air traffic controllers can be reduced when optimizing both aircraft route and landing order in the airport landing problem (ALP), and proposes its method which can adaptively change the optimized aircraft landing order according to the aircraft routes partially fixed by air traffic controllers as human intervention. Though the intensive simulation on Haneda Airport in ALP, the following implications have been revealed: (1) our proposed optimization method succeeded to mostly maintain the same level of the results without fixing some of aircraft routes (i.e., the mostly same total distance of all aircrafts from the start position to the destination airport) even if air traffic controllers fixed some of aircraft routes; and (2) this result indicates that our proposed method has a great potential of reducing the cognitive loads of air traffic controllers by reducing the number of aircrafts that should be watched with fixing some of aircraft routes.",
"editor": [
{
"familyName": "Yamamoto",
"givenName": "Sakae",
"type": "Person"
}
],
"genre": "chapter",
"id": "sg:pub.10.1007/978-3-319-58524-6_33",
"inLanguage": "en",
"isAccessibleForFree": false,
"isPartOf": {
"isbn": [
"978-3-319-58523-9",
"978-3-319-58524-6"
],
"name": "Human Interface and the Management of Information: Supporting Learning, Decision-Making and Collaboration",
"type": "Book"
},
"keywords": [
"air traffic controllers",
"cognitive load",
"traffic controllers",
"landing order",
"aircraft routes",
"intervention",
"number of aircraft",
"human intervention",
"implications",
"Haneda Airport",
"same level",
"results",
"problem",
"order",
"levels",
"controller",
"landing problem",
"optimization method",
"potential",
"load",
"great potential",
"intensive simulations",
"paper",
"method",
"number",
"aircraft",
"simulations",
"route",
"airports"
],
"name": "Towards Adaptive Aircraft Landing Order with Aircraft Routes Partially Fixed by Air Traffic Controllers as Human Intervention",
"pagination": "422-433",
"productId": [
{
"name": "dimensions_id",
"type": "PropertyValue",
"value": [
"pub.1086690447"
]
},
{
"name": "doi",
"type": "PropertyValue",
"value": [
"10.1007/978-3-319-58524-6_33"
]
}
],
"publisher": {
"name": "Springer Nature",
"type": "Organisation"
},
"sameAs": [
"https://doi.org/10.1007/978-3-319-58524-6_33",
"https://app.dimensions.ai/details/publication/pub.1086690447"
],
"sdDataset": "chapters",
"sdDatePublished": "2022-05-10T10:40",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "s3://com-springernature-scigraph/baseset/20220509/entities/gbq_results/chapter/chapter_185.jsonl",
"type": "Chapter",
"url": "https://doi.org/10.1007/978-3-319-58524-6_33"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-58524-6_33'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-58524-6_33'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-58524-6_33'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/978-3-319-58524-6_33'
This table displays all metadata directly associated to this object as RDF triples.
103 TRIPLES
23 PREDICATES
54 URIs
47 LITERALS
7 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:pub.10.1007/978-3-319-58524-6_33 | schema:about | anzsrc-for:17 |
2 | ″ | ″ | anzsrc-for:1701 |
3 | ″ | schema:author | N991642a3c2084cd5a33f526460c3eddf |
4 | ″ | schema:datePublished | 2017-05-18 |
5 | ″ | schema:datePublishedReg | 2017-05-18 |
6 | ″ | schema:description | This paper focuses on how cognitive loads of air traffic controllers can be reduced when optimizing both aircraft route and landing order in the airport landing problem (ALP), and proposes its method which can adaptively change the optimized aircraft landing order according to the aircraft routes partially fixed by air traffic controllers as human intervention. Though the intensive simulation on Haneda Airport in ALP, the following implications have been revealed: (1) our proposed optimization method succeeded to mostly maintain the same level of the results without fixing some of aircraft routes (i.e., the mostly same total distance of all aircrafts from the start position to the destination airport) even if air traffic controllers fixed some of aircraft routes; and (2) this result indicates that our proposed method has a great potential of reducing the cognitive loads of air traffic controllers by reducing the number of aircrafts that should be watched with fixing some of aircraft routes. |
7 | ″ | schema:editor | N2d001846b454466b92f123f7cbd31d4f |
8 | ″ | schema:genre | chapter |
9 | ″ | schema:inLanguage | en |
10 | ″ | schema:isAccessibleForFree | false |
11 | ″ | schema:isPartOf | N23409695c81445dfa070aaa4daf0adf3 |
12 | ″ | schema:keywords | Haneda Airport |
13 | ″ | ″ | air traffic controllers |
14 | ″ | ″ | aircraft |
15 | ″ | ″ | aircraft routes |
16 | ″ | ″ | airports |
17 | ″ | ″ | cognitive load |
18 | ″ | ″ | controller |
19 | ″ | ″ | great potential |
20 | ″ | ″ | human intervention |
21 | ″ | ″ | implications |
22 | ″ | ″ | intensive simulations |
23 | ″ | ″ | intervention |
24 | ″ | ″ | landing order |
25 | ″ | ″ | landing problem |
26 | ″ | ″ | levels |
27 | ″ | ″ | load |
28 | ″ | ″ | method |
29 | ″ | ″ | number |
30 | ″ | ″ | number of aircraft |
31 | ″ | ″ | optimization method |
32 | ″ | ″ | order |
33 | ″ | ″ | paper |
34 | ″ | ″ | potential |
35 | ″ | ″ | problem |
36 | ″ | ″ | results |
37 | ″ | ″ | route |
38 | ″ | ″ | same level |
39 | ″ | ″ | simulations |
40 | ″ | ″ | traffic controllers |
41 | ″ | schema:name | Towards Adaptive Aircraft Landing Order with Aircraft Routes Partially Fixed by Air Traffic Controllers as Human Intervention |
42 | ″ | schema:pagination | 422-433 |
43 | ″ | schema:productId | N217c1aa9432b4fa0a56f8572226df160 |
44 | ″ | ″ | Na2160d32cee647838390973c6d3d3a2d |
45 | ″ | schema:publisher | Ne0eef4dac9724599961bcd34dd8f51a4 |
46 | ″ | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1086690447 |
47 | ″ | ″ | https://doi.org/10.1007/978-3-319-58524-6_33 |
48 | ″ | schema:sdDatePublished | 2022-05-10T10:40 |
49 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
50 | ″ | schema:sdPublisher | N3d25bfc9c9d5463b8c481db667fd207f |
51 | ″ | schema:url | https://doi.org/10.1007/978-3-319-58524-6_33 |
52 | ″ | sgo:license | sg:explorer/license/ |
53 | ″ | sgo:sdDataset | chapters |
54 | ″ | rdf:type | schema:Chapter |
55 | N04650f51ac734a278e258f66c5e74743 | rdf:first | sg:person.012774267611.99 |
56 | ″ | rdf:rest | rdf:nil |
57 | N04cfb4583b194affb5ea6cf118ff6593 | rdf:first | sg:person.07750750604.05 |
58 | ″ | rdf:rest | N04650f51ac734a278e258f66c5e74743 |
59 | N217c1aa9432b4fa0a56f8572226df160 | schema:name | dimensions_id |
60 | ″ | schema:value | pub.1086690447 |
61 | ″ | rdf:type | schema:PropertyValue |
62 | N23409695c81445dfa070aaa4daf0adf3 | schema:isbn | 978-3-319-58523-9 |
63 | ″ | ″ | 978-3-319-58524-6 |
64 | ″ | schema:name | Human Interface and the Management of Information: Supporting Learning, Decision-Making and Collaboration |
65 | ″ | rdf:type | schema:Book |
66 | N2d001846b454466b92f123f7cbd31d4f | rdf:first | N64c342cf9ce24611893f3b1ab1f5684f |
67 | ″ | rdf:rest | rdf:nil |
68 | N3d25bfc9c9d5463b8c481db667fd207f | schema:name | Springer Nature - SN SciGraph project |
69 | ″ | rdf:type | schema:Organization |
70 | N64c342cf9ce24611893f3b1ab1f5684f | schema:familyName | Yamamoto |
71 | ″ | schema:givenName | Sakae |
72 | ″ | rdf:type | schema:Person |
73 | N991642a3c2084cd5a33f526460c3eddf | rdf:first | sg:person.011113507637.62 |
74 | ″ | rdf:rest | N04cfb4583b194affb5ea6cf118ff6593 |
75 | Na2160d32cee647838390973c6d3d3a2d | schema:name | doi |
76 | ″ | schema:value | 10.1007/978-3-319-58524-6_33 |
77 | ″ | rdf:type | schema:PropertyValue |
78 | Ne0eef4dac9724599961bcd34dd8f51a4 | schema:name | Springer Nature |
79 | ″ | rdf:type | schema:Organisation |
80 | anzsrc-for:17 | schema:inDefinedTermSet | anzsrc-for: |
81 | ″ | schema:name | Psychology and Cognitive Sciences |
82 | ″ | rdf:type | schema:DefinedTerm |
83 | anzsrc-for:1701 | schema:inDefinedTermSet | anzsrc-for: |
84 | ″ | schema:name | Psychology |
85 | ″ | rdf:type | schema:DefinedTerm |
86 | sg:person.011113507637.62 | schema:affiliation | grid-institutes:grid.266298.1 |
87 | ″ | schema:familyName | Murata |
88 | ″ | schema:givenName | Akinori |
89 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011113507637.62 |
90 | ″ | rdf:type | schema:Person |
91 | sg:person.012774267611.99 | schema:affiliation | grid-institutes:grid.266298.1 |
92 | ″ | schema:familyName | Takadama |
93 | ″ | schema:givenName | Keiki |
94 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.012774267611.99 |
95 | ″ | rdf:type | schema:Person |
96 | sg:person.07750750604.05 | schema:affiliation | grid-institutes:grid.266298.1 |
97 | ″ | schema:familyName | Sato |
98 | ″ | schema:givenName | Hiroyuki |
99 | ″ | schema:sameAs | https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07750750604.05 |
100 | ″ | rdf:type | schema:Person |
101 | grid-institutes:grid.266298.1 | schema:alternateName | The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan |
102 | ″ | schema:name | The University of Electro-Communications, Building W-6, 1-5-1 Chofugaoka, 181-8585, Chofu, Tokyo, Japan |
103 | ″ | rdf:type | schema:Organization |