Sensor and data fusion for intelligent transportation systems:
"Sensor and Data Fusion for Intelligent Transportation Systems introduces readers to the roles of the data fusion processes defined by the Joint Directors of Laboratories (JDL) data fusion model, data fusion algorithms, and noteworthy applications of data fusion to ITS. Additionally, the monogr...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Bellingham, Washington, USA
SPIE Press
[2019]
|
| Schlagworte: | |
| Online-Zugang: | DE-1050 DE-91 DE-706 URL des Erstveröffentlichers |
| Zusammenfassung: | "Sensor and Data Fusion for Intelligent Transportation Systems introduces readers to the roles of the data fusion processes defined by the Joint Directors of Laboratories (JDL) data fusion model, data fusion algorithms, and noteworthy applications of data fusion to ITS. Additionally, the monograph offers detailed descriptions of three of the widely applied data fusion techniques and their relevance to ITS (namely, Bayesian inference, Dempster-Shafer evidential reasoning, and Kalman filtering), and indicates directions for future research in the area of data fusion. The focus is on data fusion algorithms rather than on sensor and data fusion architectures, although the book does summarize factors that influence the selection of a fusion architecture and several architecture frameworks"-- |
| Beschreibung: | 1 Online-Ressource |
| ISBN: | 9781510627659 9781523133949 |
| DOI: | 10.1117/3.2525400 |
Internformat
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| 505 | 8 | |a Sensor and data fusion in traffic management -- Bayesian inference for traffic management -- Dempster-Shafer evidential reasoning for traffic management -- Kalman filtering for traffic management -- State of the practice and research gaps | |
| 520 | |a "Sensor and Data Fusion for Intelligent Transportation Systems introduces readers to the roles of the data fusion processes defined by the Joint Directors of Laboratories (JDL) data fusion model, data fusion algorithms, and noteworthy applications of data fusion to ITS. Additionally, the monograph offers detailed descriptions of three of the widely applied data fusion techniques and their relevance to ITS (namely, Bayesian inference, Dempster-Shafer evidential reasoning, and Kalman filtering), and indicates directions for future research in the area of data fusion. The focus is on data fusion algorithms rather than on sensor and data fusion architectures, although the book does summarize factors that influence the selection of a fusion architecture and several architecture frameworks"-- | ||
| 650 | 4 | |a Intelligent transportation systems | |
| 650 | 4 | |a Multisensor data fusion | |
| 650 | 4 | |a Motor vehicles / Automatic control | |
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| 650 | 4 | |a Algorithms | |
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| 650 | 7 | |a Intelligent transportation systems |2 fast | |
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Datensatz im Suchindex
| _version_ | 1823305667499261952 |
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| adam_text | |
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| author | Klein, Lawrence A. |
| author_GND | (DE-588)173133002 |
| author_facet | Klein, Lawrence A. |
| author_role | aut |
| author_sort | Klein, Lawrence A. |
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| building | Verbundindex |
| bvnumber | BV046037622 |
| classification_rvk | ZO 4650 |
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| contents | Sensor and data fusion in traffic management -- Bayesian inference for traffic management -- Dempster-Shafer evidential reasoning for traffic management -- Kalman filtering for traffic management -- State of the practice and research gaps |
| ctrlnum | (ZDB-30-PQE)6380049 (OCoLC)1108322409 (DE-599)BVBBV046037622 |
| discipline | Verkehr / Transport |
| doi_str_mv | 10.1117/3.2525400 |
| format | Electronic eBook |
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| id | DE-604.BV046037622 |
| illustrated | Not Illustrated |
| indexdate | 2025-02-06T11:03:06Z |
| institution | BVB |
| isbn | 9781510627659 9781523133949 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031419371 |
| oclc_num | 1108322409 |
| open_access_boolean | |
| owner | DE-1050 DE-91G DE-BY-TUM DE-706 |
| owner_facet | DE-1050 DE-91G DE-BY-TUM DE-706 |
| physical | 1 Online-Ressource |
| psigel | ZDB-50-SPI ZDB-10-ESC ZDB-30-PQE ZDB-10-ESC TUM_Lizenz ZDB-30-PQE UBY01_Einzelkauf25 |
| publishDate | 2019 |
| publishDateSearch | 2019 |
| publishDateSort | 2019 |
| publisher | SPIE Press |
| record_format | marc |
| spelling | Klein, Lawrence A. Verfasser (DE-588)173133002 aut Sensor and data fusion for intelligent transportation systems Lawrence A. Klein Bellingham, Washington, USA SPIE Press [2019] 1 Online-Ressource txt rdacontent c rdamedia cr rdacarrier Sensor and data fusion in traffic management -- Bayesian inference for traffic management -- Dempster-Shafer evidential reasoning for traffic management -- Kalman filtering for traffic management -- State of the practice and research gaps "Sensor and Data Fusion for Intelligent Transportation Systems introduces readers to the roles of the data fusion processes defined by the Joint Directors of Laboratories (JDL) data fusion model, data fusion algorithms, and noteworthy applications of data fusion to ITS. Additionally, the monograph offers detailed descriptions of three of the widely applied data fusion techniques and their relevance to ITS (namely, Bayesian inference, Dempster-Shafer evidential reasoning, and Kalman filtering), and indicates directions for future research in the area of data fusion. The focus is on data fusion algorithms rather than on sensor and data fusion architectures, although the book does summarize factors that influence the selection of a fusion architecture and several architecture frameworks"-- Intelligent transportation systems Multisensor data fusion Motor vehicles / Automatic control Traffic congestion Algorithms Algorithms fast Intelligent transportation systems fast Motor vehicles / Automatic control fast Multisensor data fusion fast Traffic congestion fast Datenfusion (DE-588)4582612-2 gnd rswk-swf Verkehrsleitsystem (DE-588)4187817-6 gnd rswk-swf Verkehrsleitsystem (DE-588)4187817-6 s Datenfusion (DE-588)4582612-2 s 1\p DE-604 Erscheint auch als Online-Ausgabe, ePub 978-1-5106-2766-6 Erscheint auch als Online-Ausgabe, Kindle 978-1-5106-2767-3 Erscheint auch als Druck-Ausgabe 978-1-5106-2764-2 https://doi.org/10.1117/3.2525400 Verlag URL des Erstveröffentlichers Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Klein, Lawrence A. Sensor and data fusion for intelligent transportation systems Sensor and data fusion in traffic management -- Bayesian inference for traffic management -- Dempster-Shafer evidential reasoning for traffic management -- Kalman filtering for traffic management -- State of the practice and research gaps Intelligent transportation systems Multisensor data fusion Motor vehicles / Automatic control Traffic congestion Algorithms Algorithms fast Intelligent transportation systems fast Motor vehicles / Automatic control fast Multisensor data fusion fast Traffic congestion fast Datenfusion (DE-588)4582612-2 gnd Verkehrsleitsystem (DE-588)4187817-6 gnd |
| subject_GND | (DE-588)4582612-2 (DE-588)4187817-6 |
| title | Sensor and data fusion for intelligent transportation systems |
| title_auth | Sensor and data fusion for intelligent transportation systems |
| title_exact_search | Sensor and data fusion for intelligent transportation systems |
| title_full | Sensor and data fusion for intelligent transportation systems Lawrence A. Klein |
| title_fullStr | Sensor and data fusion for intelligent transportation systems Lawrence A. Klein |
| title_full_unstemmed | Sensor and data fusion for intelligent transportation systems Lawrence A. Klein |
| title_short | Sensor and data fusion for intelligent transportation systems |
| title_sort | sensor and data fusion for intelligent transportation systems |
| topic | Intelligent transportation systems Multisensor data fusion Motor vehicles / Automatic control Traffic congestion Algorithms Algorithms fast Intelligent transportation systems fast Motor vehicles / Automatic control fast Multisensor data fusion fast Traffic congestion fast Datenfusion (DE-588)4582612-2 gnd Verkehrsleitsystem (DE-588)4187817-6 gnd |
| topic_facet | Intelligent transportation systems Multisensor data fusion Motor vehicles / Automatic control Traffic congestion Algorithms Datenfusion Verkehrsleitsystem |
| url | https://doi.org/10.1117/3.2525400 |
| work_keys_str_mv | AT kleinlawrencea sensoranddatafusionforintelligenttransportationsystems |