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Title: A multiple regression approach for traffic flow estimation
Authors: Pun, LL 
Zhao, PX
Liu, XT 
Keywords: Traffic flow estimation
Topological and geometrical Properties
Correlation analysis
Multiple linear regression
Random forest
Issue Date: 2019
Publisher: Institute of Electrical and Electronics Engineers
Source: IEEE access, 2019, v. 7, p. 35998-36009 How to cite?
Journal: IEEE access 
Abstract: Traffic flow information is of great importance for transport planning and related research. The conventional methods of automated data collection, such as annual average daily traffic (AADT) data, are often restricted by limited installation, while the state-of-the-art sensing technologies (e.g., GPS) only reflect some types of traffic flow (e.g., taxi and bus). Complete coverage of traffic flow is still lacking, thus demanding a rigorous estimation model. Most studies dedicated to estimating the traffic flow of the entire road network rely on single to only a few properties of the road network and the results may not be promising. This paper presents an idea of integrating five topological measures and road length to estimate traffic flow based on a multiple regression approach. An empirical study in Hong Kong has been conducted with three types of traffic datasets, namely floating car, public transport route, and AADT. Six measures, namely degree, betweenness, closeness, page rank, clustering coefficient, and road length, are used for traffic flow estimation. It is found that each measure correlates differently for the three types of traffic data. Multiple regression approach is then conducted, including multiple linear regression and random forest. The results show that a combination of various topological and geometrical measures has proved to have a better performance in estimating traffic flow than that of a single measure. This paper is especially helpful for transport planners to estimate traffic flow based on correlation available but limited flow data with road network characteristics.
ISSN: 2169-3536
DOI: 10.1109/ACCESS.2019.2904645
Rights: © 2019 IEEE. Translations and content mining are permitted for academic research only.Personal use is also permitted, but republication/redistribution requires IEEE permission.See for more information
The following publication L. Pun, P. Zhao and X. Liu, "A Multiple Regression Approach for Traffic Flow Estimation," in IEEE Access, vol. 7, pp. 35998-36009, 2019 is available at
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