Resumen
Due to the increase in vehicle transit and congestion in road networks, providing information about the state of the traffic to commuters has become a critical issue for Advanced Traveller Information Systems. These systems should assist users in making pre-trip and en-route decisions and, for this purpose, delivering travel time information is very useful because it is very intuitive and easily understood by all travellers. The aim of this paper is to present a global view of the literature on the modelling of travel time, introducing essential concepts and giving a thorough classification of the existing techniques. Most of the attention will focus on travel time estimation and travel time prediction, which are two of the most relevant challenges in travel time modelling. The definition and goals of these two modelling tasks along with the methodologies used to carry them out will be further explored and categorised.
| Idioma original | Inglés |
|---|---|
| Páginas (desde-hasta) | 119-157 |
| Número de páginas | 39 |
| Publicación | Transportmetrica A: Transport Science |
| Volumen | 11 |
| N.º | 2 |
| DOI | |
| Estado | Publicada - 7 feb 2015 |
Palabras clave
- travel time estimation
- intelligent transportation systems
- travel time prediction
- Advanced Traveller Information Systems
Project and Funding Information
- Funding Info
- Basque Government, Saiotek IT-609-13._x000D_ Spanish Ministry of Science and Innovation TIN2010-14931. _x000D_ COMBIOMED network in computational biomedicine (Carlos III Health Institute). _x000D_ Diputacion Foral de Gipuzkoa, 2011-CIEN-000060-01. _x000D_ CRC-Biomarkers project (Diputacion Foral de Bizkaia), 6-12-TK-2011-014._x000D_ Fundacion Inaki Goenaga._x000D_ University of the Basque Country UPV/EHU.
ODS de las Naciones Unidas
Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible
