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| 基于广义估计方程的时间相关性事故频次建模 | |
| 作者姓名： | Wen-qing WU ;Wei WANG ;Zhi-bin LI ;Pan LIU ;Yong WANG |
| 作者单位： | [1]Jiangsu Key Laboratory of Urban Intelligent Transportation Systems, Southeast University, Nanjing 210096, China; [2]Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing 210096, China; [3]School of Transportatton Southeast University, Naniing 210096, China; [4]School of Management, Chongqing Jiaotong University, Chongqing 400074, China |
| 基金项目： | Project supported by the National Key Basic Research Program （973） of China （No. 2012CB725400）, the National High-Tech R＆D Pro-gram （863） of China （No. 2012AA112304）, and the National Natural Science Foundation of China （No. 51338003） |
| 摘 要： | 研究目的：创新要点：研究方法：重要结论：采用广义估计方程模型对存在时间相关件的事故频次数据进行建模，并与传统广义线性模型的估计效果进行对比。
通过广义估计方程来考虑事故频次建模中数据的时间相关性，从而提高参数估计准确度以及模型预测精度。基于4年高速公路交通事故频次数据，建立考虑时间相关性的广义估计方程以及传统的广义线性模型，并采用统计指标对模型效果进行对比。1．事故频次数据样本最对预测精度影响很大；2．广义估引方程能够有效考虑事故频次数据中存住的时间相关性；3．广义估计方程的参数估计比传统广义线性模型史准确，且精度更高。 |
| 关 键 词： | 广义估计方程 事故频次 时间相关 广义线型模型 |
Application of generalized estimating equations for crash frequency modeling with temporal correlation |
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| Wen-qing WU,;Wei WANG,;Zhi-bin LI,;Pan LIU,;Yong WANG.Application of generalized estimating equations for crash frequency modeling with temporal correlation[J].Journal of Zhejiang University Science,2014,15(7):529-539. | |
| Authors: | Wen-qing Wu Wei Wang Zhi-bin Li Pan Liu Yong Wang |
| Institution: | 1. Jiangsu Key Laboratory of Urban Intelligent Transportation Systems, Southeast University, Nanjing, 210096, China 2. Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Nanjing, 210096, China 3. School of Transportation, Southeast University, Nanjing, 210096, China 4. School of Management, Chongqing Jiaotong University, Chongqing, 400074, China |
| Abstract: | Traditional crash frequency modeling uses crash frequency data averaged across multiple years. When data size is small, crash data in each year are used in the modeling to extend the size of the samples. The extension of sample size could create a temporal correlation among crash frequencies of the different years, which could affect the modeling accuracy. The primary objective of this study is to evaluate the application of the generalized estimating equation (GEE) procedures to account for the temporal correlation in the longitudinal crash frequency data. Four-year crash data at exit ramps on a freeway in China were collected for modeling. Based on the same data, traditional generalized linear models (GLMs) were estimated for model comparison. Results showed that traditional GLM underestimated the standard errors of coefficients for explanatory variables. The GEE procedure with an exchangeable correlation structure successively captured the temporal correlation among the crash frequencies of the different years. The GLM with GEE outperformed the traditional GLM in providing a good fit for the crash frequency data. Results of this study can help researchers better understand how various factors affect the crash frequencies at freeway divergent areas and propose effective countermeasures. |
| Keywords: | Crash frequency Generalized estimating equation （GEE） Temporal correlation Freeway Safety |
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