Overview
- A comprehensive and accurate overview of freeway travel time estimation methods
- Proposes original solutions to estimate travel time
- Analyzes, criticizes and enhances common direct measurement methods and propose a new data fusion method which jointly use direct and indirect measurements
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Tracts on Transportation and Traffic (STTT, volume 11)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (7 chapters)
-
Front Matter
Keywords
About this book
This monograph presents a simple, innovative approach for the measurement and short-term prediction of highway travel times based on the fusion of inductive loop detector and toll ticket data. The methodology is generic and not technologically captive, allowing it to be easily generalized for other equivalent types of data. The book shows how Bayesian analysis can be used to obtain fused estimates that are more reliable than the original inputs, overcoming some of the drawbacks of travel-time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) from the available data, without recurrent and costly requirements for additional data. The application of the algorithms to empirical testing in the AP-7 toll highway in Barcelona proves that it is possible to develop an accurate real-time, travel-time information system on closed-toll highways with the existing surveillance equipment, suggesting that highway operators might provide their customers with such an added value with little additional investment in technology.
Authors and Affiliations
Bibliographic Information
Book Title: Highway Travel Time Estimation With Data Fusion
Authors: Francesc Soriguera Martí
Series Title: Springer Tracts on Transportation and Traffic
DOI: https://doi.org/10.1007/978-3-662-48858-4
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2016
Hardcover ISBN: 978-3-662-48856-0Published: 08 December 2015
Softcover ISBN: 978-3-662-56959-7Published: 27 March 2019
eBook ISBN: 978-3-662-48858-4Published: 30 November 2015
Series ISSN: 2194-8119
Series E-ISSN: 2194-8127
Edition Number: 1
Number of Pages: XVIII, 212
Number of Illustrations: 61 b/w illustrations, 8 illustrations in colour
Topics: Transportation Technology and Traffic Engineering, Computational Intelligence, Artificial Intelligence, Urban Economics