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Modeling arterial travel time distribution by accounting for link correlations: a copula-based approach
| 题名： | Modeling arterial travel time distribution by accounting for link correlations: a copula-based approach |
| 正文语种： | 英文 |
| 作者： | Peng Chen; Weiliang Zeng; Min Chen; Guizhen Yu; Yunpeng Wang |
| 作者单位： | Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control, School of Transportation Science and Engineering, Beihang University, Beijing, China; Beijing Advanced Innovation Center for Big Data and Brain Computing, Beihang University, Beijing, China; School of Automation, Guangdong University of Technology, Guangdong, China |
| 关键词： | Copula; link correlations; signal coordination; travel time distribution; urban arterial |
| 摘要： | The estimation of urban arterial travel time distribution (TTD) is critical to help implement Intelligent Transportation Systems (ITS) and provide travelers with timely and reliable route guidance. The state-of-practice procedure for arterial TTD estimation commonly assumes that the path travel time follows a certain distribution without considering link correlations. However, this approach appears inappropriate since travel times on successive links are essentially dependent along signalized arterials. In this study, a copula-based approach is proposed to model arterial TTD by accounting for spatial link correlations. First, TTDs on consecutive links along one arterial in Hangzhou, China are investigated. Link TTDs are estimated through the nonparametric kernel smoothing method. Link correlations are analyzed in both unfavorable and favorable coordination cases. Then, Gaussian copula models are introduced to model the dependent structure between link TTDs. The parameters of Gaussian copula are obtained by Maximum-Likelihood Estimation (MLE). Next, path TTDs covering consecutive links are estimated based on the estimated copula models. The results demonstrate the advantage of the proposed copula-based approach, compared with the convolution without capturing link correlations and the empirical distribution fitting methods in both unfavorable and favorable coordination cases. |
| 出版年： | 2019 |
| 期刊名称： | Journal of Intelligent Transportation Systems Technology Planning and Operations |
| 卷： | 23 |
| 期： | 1 |
| 页码： | 28-40 |
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