A review of travel time estimation and forecasting for Advanced Traveller Information Systems

被引：190

作者：

Mori, Usue ^{[1
]}

Mendiburu, Alexander ^{[2
]}

Alvarez, Maite ^{[3
]}

Lozano, Jose A. ^{[1
]}

机构：

[1] Univ Basque Country UPV EHU, Dept Comp Sci & Artificial Intelligence, Intelligent Syst Grp, Donostia San Sebastian 20018, Spain

[2] Univ Basque Country UPV EHU, Dept Comp Architecture & Technol, Intelligent Syst Grp, Donostia San Sebastian 20018, Spain

[3] Tecnalia Res & Innovat, ICT Div, Zamudio 48170, Spain

来源：

TRANSPORTMETRICA A-TRANSPORT SCIENCE | 2015年 / 11卷 / 02期

关键词：

travel time estimation; intelligent transportation systems; travel time prediction; Advanced Traveller Information Systems; VEHICLE IDENTIFICATION DATA; DATA FUSION ALGORITHM; DATA AGGREGATION; NEURAL-NETWORKS; FREEWAY; PREDICTION; LINK; MODEL; REIDENTIFICATION; SIMULATION;

D O I：

10.1080/23249935.2014.932469

中图分类号：

U [交通运输];

学科分类号：

08 ; 0823 ;

摘要：

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.

引用

页码：119 / 157

页数：39

共 125 条

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