Short-term prediction of freeway travel times by fusing input-output vehicle counts and GPS tracking data
Visualitza/Obre
10.1080/19427867.2020.1864134
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/340292
Tipus de documentArticle
Data publicació2021-03
EditorInforma UK (Taylor & Francis)
Condicions d'accésAccés obert
Tots els drets reservats. Aquesta obra està protegida pels drets de propietat intel·lectual i
industrial corresponents. Sense perjudici de les exempcions legals existents, queda prohibida la seva
reproducció, distribució, comunicació pública o transformació sense l'autorització del titular dels drets
Abstract
Short-term travel time prediction on freeways is the most valuable information for drivers when selecting their routes and departure times. Furthermore, this information is also essential at traffic management centers in order to monitor the network performance and anticipate the activation of traffic management strategies. The importance of reliable short-term travel time predictions will even increase with the advent of autonomous vehicles, when vehicle routing will strongly rely on this information. In this context, it is important to develop a real-time method to accurately predict travel times. The present paper uses vehicle accumulation, obtained from input-output diagrams constructed from loop detector data, to predict travel times on freeway sections. Loop detector count drift, which typically invalidates vehicle accumulation measurements, is corrected by means of a data fusion algorithm using GPS measurements. The goodness of the methodology has been proven under different boundary conditions using simulated data.
Descripció
This is an Accepted Manuscript of an article published by Taylor & Francis Group in Transportation Letters on December 2020, available online at: http://www.tandfonline.com/10.1080/19427867.2020.1864134
CitacióMartinez, M.; Soriguera, F. Short-term prediction of freeway travel times by fusing input-output vehicle counts and GPS tracking data. "Transportation letters: the international journal of transportation research", Març 2021, vol. 13, núm. 3, p. 193-200.
ISSN1942-7867
Versió de l'editorhttps://www.tandfonline.com/doi/abs/10.1080/19427867.2020.1864134
Fitxers | Descripció | Mida | Format | Visualitza |
---|---|---|---|---|
MARGA_TRL_FS.pdf | 427,1Kb | Visualitza/Obre |