A Data Model for Determining Weather's Impact on Travel Time

Ove Andersen; Kristian Torp

doi:10.1007/978-3-319-44406-2_37

A Data Model for Determining Weather's Impact on Travel Time

Bidragets oversatte titel: En datamodel for bestemmelse af vejrets påvirkning af rejsetider

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

5 Citationer (Scopus)

Abstract

Accurate estimating travel times in road networks is a complex task because travel times depends on factors such as the weather. In this paper, we present a generic model for integrating weather data with GPS data to improve the accuracy of the estimated travel times. First, we present a data model for storing and map-matching GPS data, and integrating this data with detailed weather data. The model is generic in the sense that it can be used anywhere GPS data and weather data is available. Next, we analyze the correlation between travel time and the weather classes dry, fog, rain, and snow along with winds impact on travel time. Using a data set of 1.6 billion GPS records collected from 10,560 vehicles, over a 5 year period from all of Denmark, we show that snow can increase the travel time up to 27% and strong headwind can increase the travel time with up to 19% (compared to dry calm weather). This clearly shows that accurate travel time estimation requires knowledge about the weather.

Bidragets oversatte titel	En datamodel for bestemmelse af vejrets påvirkning af rejsetider
Originalsprog	Engelsk
Titel	Database and Expert Systems Applications : 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II
Redaktører	Sven Hartman, Hui Ma
Antal sider	8
Vol/bind	9828
Forlag	Springer Publishing Company
Publikationsdato	2016
Sider	437-444
ISBN (Trykt)	978-3-319-44405-5
ISBN (Elektronisk)	0302-9743
DOI	https://doi.org/10.1007/978-3-319-44406-2_37
Status	Udgivet - 2016
Begivenhed	27th International Conference on Database and Expert Systems Applications - DEXA 2016 - GECAD (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development) at ISEP (Instituto Superior de Engenharia do Porto), Porto, Portugal Varighed: 5 sep. 2016 → 8 sep. 2016 http://www.dexa.org/previous/dexa2016/index.html

Konference

Konference	27th International Conference on Database and Expert Systems Applications - DEXA 2016
Lokation	GECAD (Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development) at ISEP (Instituto Superior de Engenharia do Porto)
Land/Område	Portugal
By	Porto
Periode	05/09/2016 → 08/09/2016
Internetadresse	http://www.dexa.org/previous/dexa2016/index.html

Navn	Lecture Notes in Computer Science
Vol/bind	9829
ISSN	0302-9743

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Citationsformater

Andersen, Ove ; Torp, Kristian. / A Data Model for Determining Weather's Impact on Travel Time. Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II. red. / Sven Hartman ; Hui Ma. Bind 9828 Springer Publishing Company, 2016. s. 437-444 (Lecture Notes in Computer Science, Bind 9829).

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title = "A Data Model for Determining Weather's Impact on Travel Time",

abstract = "Accurate estimating travel times in road networks is a complex task because travel times depends on factors such as the weather. In this paper, we present a generic model for integrating weather data with GPS data to improve the accuracy of the estimated travel times. First, we present a data model for storing and map-matching GPS data, and integrating this data with detailed weather data. The model is generic in the sense that it can be used anywhere GPS data and weather data is available. Next, we analyze the correlation between travel time and the weather classes dry, fog, rain, and snow along with winds impact on travel time. Using a data set of 1.6 billion GPS records collected from 10,560 vehicles, over a 5 year period from all of Denmark, we show that snow can increase the travel time up to 27% and strong headwind can increase the travel time with up to 19% (compared to dry calm weather). This clearly shows that accurate travel time estimation requires knowledge about the weather.",

author = "Ove Andersen and Kristian Torp",

year = "2016",

doi = "10.1007/978-3-319-44406-2_37",

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booktitle = "Database and Expert Systems Applications",

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Andersen, O & Torp, K 2016, A Data Model for Determining Weather's Impact on Travel Time. i S Hartman & H Ma (red), Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II. bind 9828, Springer Publishing Company, Lecture Notes in Computer Science, bind 9829, s. 437-444, 27th International Conference on Database and Expert Systems Applications - DEXA 2016, Porto, Portugal, 05/09/2016. https://doi.org/10.1007/978-3-319-44406-2_37

A Data Model for Determining Weather's Impact on Travel Time. / Andersen, Ove; Torp, Kristian.
Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II. red. / Sven Hartman; Hui Ma. Bind 9828 Springer Publishing Company, 2016. s. 437-444 (Lecture Notes in Computer Science, Bind 9829).

Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review

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Andersen O, Torp K. A Data Model for Determining Weather's Impact on Travel Time. I Hartman S, Ma H, red., Database and Expert Systems Applications: 27th International Conference, DEXA 2016, Porto, Portugal, September 5-8, 2016, Proceedings, Part II. Bind 9828. Springer Publishing Company. 2016. s. 437-444. (Lecture Notes in Computer Science, Bind 9829). doi: 10.1007/978-3-319-44406-2_37