Precise modeling and analysis of statistical patterns of vessel traffic in inland restricted waters using appropriate distributions are crucial for further studies on inland navigation safety and efficiency enhancement. This study aims to identify probabilistic models of spatial and temporal pattern for vessel traffic traversing inland bridge waters. Considering features of the special navigational condition and vessel traffic flow, several single and mixed models are proposed and tested. The proposed models are applied to two bridges using information extracted from AIS data of vessel traversing the Wuhan section of Yangtze River in three selected months of 2016. Results of the study show that:
single models are not acceptable for both spatial and temporal pattern modeling for vessel traffic traversing inland bridge waters, and among all selected single models, Burr distribution model show good adaptability and consistency;
the corresponding mixed models have much better overall goodness of fit than single models;
Logistic- GQM and Burr-GQM present the best fittings for spatial pattern;
Gamma-GQM and Burr-GQM show the best fittings for temporal pattern.
Vessel traffic's spatial and temporal patterns normally include two categories, namely spatial distribution and temporal distribution, with the spatial one characterized by transverse distribution of vessel tracks and the temporal one generally represented by vessel inter-arrival time (IAT) distribution. The study on spatial and temporal patterns of vessel traffic traversing inland bridge waters can be regarded as an exploration of vessel traffic flow theory. The research findings are the basis of ship- bridge collision probability estimation, helping to obtain a better and more accurate result (Pedersen, 2002). Besides, they are also important inputs for simulation related research works of vessel traffic flow. Thus, precise modeling and analysis of the statistical patterns of vessel traffic using appropriate distributions are crucial for further studies in the field of inland navigation safety and efficiency enhancement.
