[1] Wang Xiaofei, Li Xinwei, Fu Xinsha, et al. Construction of crash prediction model of freeway basic segmentbased on interactive influence of explanatory variables [J]. Journal of Southeast University (English Edition), 2015, 31 (2): 276-281. [doi:10.3969/j.issn.1003-7985.2015.02.021]

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Construction of crash prediction model of freeway basic segmentbased on interactive influence of explanatory variables()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

31

Issue:

2015 2

Page:

276-281

Research Field:

Traffic and Transportation Engineering

Publishing date:

2015-06-20

Info

Title:

Construction of crash prediction model of freeway basic segmentbased on interactive influence of explanatory variables

Author(s):

Wang Xiaofei¹;  Li Xinwei¹;  2;  Fu Xinsha¹;  Zhao Lixuan³;  Liu Xiaofeng⁴

¹School of Civil Engineering and Transportation, South China University of Technology, Guangzhou 510641, China
²Guangzhou Expressway Co., Ltd, Guangzhou 510288, China
³Guangdong Police College, Guangzhou 510230, China
⁴Guangdong Traffic Group Co., Ltd, Guangzhou 510623, China

Keywords:

crash;  freeway;  safety performance function(SPF);  interactive influence of explanatory variables;  generalized negative binomial(GNB)

PACS:

U412.3

DOI:

10.3969/j.issn.1003-7985.2015.02.021

Abstract:

In order to improve the prediction precision of the safety performance function(SPF)of freeway basic segments, design and crash data of 640 segments are collected from different institutions. Three negative binomial(NB)regression models and three generalized negative binomial(GNB)regression models are built to prove that the interactive influence of explanatory variables plays an important role in fitting goodness. The effective use of the GNB model in analyzing the interactive influence of explanatory variables and predicting freeway basic segments is demonstrated. Among six models, the two models(one is the NB model and the other is the GNB model.)which consider the interactive influence of the annual average daily traffic(AADT)and length are more reasonable for predicting results. Furthermore, a comprehensive study is carried out to prove that when considering the interactive influence, the NB and GNB models have almost the same fitting performance in estimating the crashes, among which the GNB model is slightly better for prediction performance.

References:

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Memo

Memo:

Biography: Wang Xiaofei(1980—), female, doctor, lecturer, xiaofeiw@scut.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.51408229, 51278202), the Program of the Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University(No.K201204), the Science and Technology Program of Guangdong Communication Department(No.2013-02-068).
Citation: Wang Xiaofei, Li Xinwei, Fu Xinsha, et al. Construction of crash prediction model of freeway basic segment based on interactive influence of explanatory variables[J].Journal of Southeast University(English Edition), 2015, 31(2):276-281.[doi:10.3969/j.issn.1003-7985.2015.02.021]

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