Data Source Importance Evaluation for Highway Networks: A Complex Network-Based Approach

Huangqin HUANG; Jianhua GUO; Xiangyu SHI; Leixiao SHEN

doi:10.7307/ptt.v36i4.537

Authors

Huangqin HUANG Southeast University, Intelligent Transportation System Research Centre
Jianhua GUO Southeast University, Intelligent Transportation System Research Centre; Ministry of Transport, Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory)
Xiangyu SHI Southeast University, Intelligent Transportation System Research Centre; BYD Company Limited
Leixiao SHEN Xuzhou Highway Management Agency

DOI:

https://doi.org/10.7307/ptt.v36i4.537

Keywords:

highway network operations, data source, complex network, centrality, entropy weight method

Abstract

Data collection technologies or data sources are critical for highway network management. However, due to the limitations on available management resources, determining the importance of these data sources is necessary to allocate these resources reasonably. This study proposes a complex network based method for evaluating the importance of multiple data sources in highway networks. This method includes mainly three steps. First, the business-data source relation will be identified and formulated for the highway network. Second, a business data source complex network is built from the previously identified business-data relationship. Third, an entropy weight method is used to compute and rank the importance of data source nodes by combining three indexes of degree centrality (DC), closeness centrality (CC) and structural holes (SC) computed based on the complex network. The proposed method is applied and illustrated using the highway network of Xuzhou City, Jiangsu Province, China. The results show that among the data sources, the most important data source is the continuous traffic survey station, followed by an automatic gantry-based station and vehicle detectors-based system. Discussions on the limitations, applications and future studies are provided for the proposed approach.

Author Biographies

Huangqin HUANG, Southeast University, Intelligent Transportation System Research Centre

Huangqin Huang is a student at the Intelligent Transportation System Research Center, Southeast University, Nanjing, China. She mainly studies the field of traffic information control.

Jianhua GUO, Southeast University, Intelligent Transportation System Research Centre; Ministry of Transport, Key Laboratory of Transport Industry of Comprehensive Transportation Theory (Nanjing Modern Multimodal Transportation Laboratory)

Jianhua Guo is currently a Professor in transportation engineering at the Intelligent Transportation System Research Center, Southeast University, Nanjing, China.

Xiangyu SHI, Southeast University, Intelligent Transportation System Research Centre; BYD Company Limited

Xiangyu Shi is a research and development officer at BYD Company Limited, Shenzhen, China. He was a student at the Intelligent Transportation System Research Center, Southeast University, Nanjing, China. His main research areas during his school years were traffic signal control and traffic flow prediction.

Leixiao SHEN, Xuzhou Highway Management Agency

Leixiao Shen is a senior engineer at Xuzhou Highway Management Agency, Jiangsu, China.

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