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Mathematical Problems in Engineering
Volume 2013 (2013), Article ID 247184, 13 pages
http://dx.doi.org/10.1155/2013/247184
Research Article

An Adaptive Model for Calculating the Correlation Degree of Multiple Adjacent Signalized Intersections

1College of Transportation, Jilin University, Changchun 130022, China
2School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150091, China

Received 5 July 2013; Revised 24 August 2013; Accepted 4 October 2013

Academic Editor: Wuhong Wang

Copyright © 2013 Linhong Wang and Yiming Bie. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

As an important component of the urban adaptive traffic control system, subarea partition algorithm divides the road network into some small subareas and then determines the optimal signal control mode for each signalized intersection. Correlation model is the core of subarea partition algorithm because it can quantify the correlation degree of adjacent signalized intersections and decides whether these intersections can be grouped into one subarea. In most cases, there are more than two intersections in one subarea. However, current researches only focus on the correlation model for two adjacent intersections. The objective of this study is to develop a model which can calculate the correlation degree of multiple intersections adaptively. The cycle lengths, link lengths, number of intersections, and path flow between upstream and downstream coordinated phases were selected as the contributing factors of the correlation model. Their jointly impacts on the performance of the coordinated control mode relative to the isolated control mode were further studied using numerical experiments. The paper then proposed a correlation index (CI) as an alternative to relative performance. The relationship between CI and the four contributing factors was established in order to predict the correlation, which determined whether adjacent intersections could be partitioned into one subarea. A value of 0 was set as the threshold of CI. If CI was larger than 0, multiple intersections could be partitioned into one subarea; otherwise, they should be separated. Finally, case studies were conducted in a real-life signalized network to evaluate the performance of the model. The results show that the CI simulates the relative performance well and could be a reliable index for subarea partition.