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Short-term prediction of freeway travel times by fusing input-output vehicle counts and GPS tracking data

Author
Martinez, M.; Soriguera, F.
Type of activity
Journal article
Journal
Transportation letters: the international journal of transportation research
Date of publication
2021-03
Volume
13
Number
3
First page
193
Last page
200
DOI
10.1080/19427867.2020.1864134
Project funding
Platooning of connected autonomous vehicles on freeways: microscopic modeling & management strategies
Repository
http://hdl.handle.net/2117/340292 Open in new window
URL
https://www.tandfonline.com/doi/abs/10.1080/19427867.2020.1864134 Open in new window
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 infor...
Citation
Martinez, 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.
Keywords
Freeway travel time, GPS data, count drift., data fusion, input-output diagrams, travel- time prediction
Group of research
BIT - Barcelona Innovative Transportation

Participants