Estimation of urban arterial travel time distribution considering link correlations

This study proposes a pair-copula construction approach to estimate the probability distribution of urban arterial travel times from link travel time distributions (TTDs). First, link correlations are investigated and empirical evidence reveals that adjacent link travel times present multiple relationships. Then, such relationships are captured by a copula mixture model in each pair-copula associated with two connected links. Finally, the arterial TTD is derived as the product of the pair-copulas and link TTDs. The proposed approach is validated with Radio Frequency Identification Data collected from an urban arterial including four links in Nanjing, China. The results indicate that the approach can dynamically capture the positively correlated, negatively correlated, and uncorrelated relationships between link travel times. The considered competing approaches are also used to benchmark the proposed approach, and comparison results confirm the effectiveness and accuracy of the approach, especially when multistate distributions, complex correlations and limited data sample are encountered.