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Frontiers of Computer Science

, Volume 11, Issue 1, pp 27–37 | Cite as

An identification model of urban critical links with macroscopic fundamental diagram theory

  • Wanli Dong
  • Yunpeng Wang
  • Haiyang Yu
Research Article

Abstract

How to identify the critical links of the urban road network for actual traffic management and intelligent transportation control is an urgent problem, especially in the congestion environment. Most previous methods focus on traffic static characteristics for traffic planning and design. However, actual traffic management and intelligent control need to identify relevant sections by dynamic traffic information for solving the problems of variable transportation system. Therefore, a city-wide traffic model that consists of three relational algorithms, is proposed to identify significant links of the road network by using macroscopic fundamental diagram (MFD) as traffic dynamic characteristics. Firstly, weightedtraffic flow and density extraction algorithm is provided with simulation modeling and regression analysis methods, based on MFD theory. Secondly, critical links identification algorithm is designed on the first algorithm, under specified principles. Finally, threshold algorithm is developed by cluster analysis. In addition, the algorithms are analyzed and applied in the simulation experiment of the road network of the central district in Hefei city, China. The results show that the model has good maneuverability and improves the shortcomings of the threshold judged by human. It provides an approach to identify critical links for actual traffic management and intelligent control, and also gives a new method for evaluating the planning and design effect of the urban road network.

Keywords

urban road network critical links intelligent transportation system macroscopic fundamental diagram 

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Notes

Acknowledgements

This research was supported by the National Natural Science Foundation of China (Grant No. 51308021). The authors would like to thank Wanbao Gao and Qiang Shu (Hefei Gelv Information Technology Co., Ltd) for assisting with their investigation and simulation data extraction effort in the Central District, Hefei city, China.

Supplementary material

11704_2016_6080_MOESM1_ESM.ppt (522 kb)
Supplementary material, approximately 522 KB.

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Copyright information

© Higher Education Press and Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.School of Transportation Science and EngineeringBeihang UniversityBeijingChina
  2. 2.Anhui Sun Create Electronics Co., Ltd.HefeiChina

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