Original scientific paper

https://doi.org/10.17559/TV-20151002055617

Adaptability evaluation of electronic vehicle identification in urban traffic: a case study of Beijing

Hui Hu ; School of Automobile, Chang’an University, Middle Section of South 2nd Ring Road, Xi’an, 710064, Shaanxi Province, P. R. China
Baowen Li ; School of Traffic and Transportation, Beijing Jiaotong University, No. 3 Shangyuancun, Haidian District, Beijing, 100044, P. R. China
Xiang Chen ; School of Automobile, Chang’an University, Middle Section of South 2nd Ring Road, Xi’an, 710064, Shaanxi Province, P. R. China
Ying Yan ; School of Automobile, Chang’an University, Middle Section of South 2nd Ring Road, Xi’an, 710064, Shaanxi Province, P. R. China
Bin Ran ; Department of Civil & Environmental Engineering, University of Wisconsin-Madison, 1212 Engineering Hall, 1415 Engineering Drive, Madison, WI 53706, USA

Abstract

Electronic vehicle identification (EVI) technology is often introduced to implement congestion-based toll. This paper presented an ex ante evaluation method for EVI adaptability and discussed the feasibility of this technology in congestion charge on the basis of assessment. First, system dynamics was introduced to qualitatively analyze the effect of EVI on urban traffic systems with feedback chains. An EVI adaptability evaluation model was then developed based on principal component analysis (PCA) and data envelopment analysis (DEA). Given numerous output variables, a PCA model was built to reduce variable dimensionalities. Subsequently, two scenarios of EVI application under a congestion-based toll in Beijing were presented and calculated according to field data. Scenario 1 covered 5 % of the total vehicles, as well as the toll zone within the 2nd Ring Road. Meanwhile, scenario 2 covered 5 % more vehicles and included Zhongguancun West District based on scenario 1. According to evaluation result, the adaptability classifications of scenarios 1 and 2 were identified as basic adaptive & adaptive respectively, and that scenario 2 was more adaptive and feasible than scenario 1. In addition, the adaptability trends of the two scenarios between 2003 and 2012 were analyzed and proved to be consistent with the practical situation. The findings had significant implications for policy makers who determined the priority domains of internet of things technology applications by assessing the adaptability of these technologies before deployment.

Keywords

adaptability; congestion charge; data envelopment analysis (DEA); electronic vehicle identification (EVI); evaluation

Hrčak ID:

153169

URI

https://hrcak.srce.hr/153169

Publication date:

19.2.2016.

Article data in other languages: croatian

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