Imperial College London
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Dr Rajesh Krishnan

Faculty of Engineering, Department of Civil and Environmental Engineering

Honorary Research Fellow
 
 
 
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Contact

 

+44 (0)20 7594 6111rajesh.k Website

 
 
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Location

 

618Skempton BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Zhu:2018:10.1049/iet-its.2017.0116,
author = {Zhu, L and Guo, F and Polak, J and Krishnamoorthy, R},
doi = {10.1049/iet-its.2017.0116},
journal = {IET Intelligent Transport Systems},
pages = {651--663},
title = {Urban link travel time estimation using traffic states based data fusion},
url = {http://dx.doi.org/10.1049/iet-its.2017.0116},
volume = {12},
year = {2018}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Estimated travel time is a key input for many intelligent transport systems (ITS) applications and traffic management functions. There are numerous studies that show that fusing data from different sources such as global positioning system (GPS), Bluetooth, mobile phone network (MPN), and inductive loop detector (ILD) can result in more accurate travel time estimation. However, to date, there has been little research investigating the contribution of individual data sources to the quality of the final estimate or how this varies according to source-specific data quality under different traffic states. Here, three different data sources, namely bus-based GPS (bGPS) data, ILD data, and MPN data, of varying quality are combined using three different data fusion techniques of varying complexity. In order to quantify the accuracy of travel time estimation, travel time calculated using automatic number plate recognition (ANPR) data are used as the `ground truth'. The final results indicate that fusing multiple data together does not necessarily enhance the accuracy of travel time estimation. The results also show that even in dense urban areas, bGPS data, when combined with ILD data, can provide reasonable travel time estimates of general traffic stream under different traffic states.
AU  - Zhu,L
AU  - Guo,F
AU  - Polak,J
AU  - Krishnamoorthy,R
DO  - 10.1049/iet-its.2017.0116
EP  - 663
PY  - 2018///
SN  - 1751-956X
SP  - 651
TI  - Urban link travel time estimation using traffic states based data fusion
T2  - IET Intelligent Transport Systems
UR  - http://dx.doi.org/10.1049/iet-its.2017.0116
UR  - http://hdl.handle.net/10044/1/56545
VL  - 12
ER  -
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