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Considering the unobserved spatial heterogeneity, this study aims to build a Bayesian spatial multinomial logistic (BSMNL) model by utilizing the geographic information from historical maritime accidents. The proposed BSMNL model can be applied to investigate the determinants of human errors involved in maritime accidents. Compared to the traditional multinomial logistic (MNL) model, the proposed BSMNL model produces a more accurate estimate of the effects of environmental and accident factors on the occurrence likelihood of human errors in maritime accidents. Results show that accidents involving cargo and container ships; tankers carrying liquefied natural gas (LNG), liquefied petroleum gas (LPG), or oil; and fishing vessels are more likely to be associated with human errors. Further, one important finding is that the involvement of fishing vessels significantly increases the occurrence probability of both negligence errors and judgment or operational errors. In addition, the occurrence likelihood of human errors is generally higher in springtime, conditions of poor visibility, the absence of strong winds or waves, and the moored or docked status. [ABSTRACT FROM AUTHOR]

Considering the differences in traffic delays and accident costs at different stages of the shipping cycle, this study develops a system dynamics model to determine the impacts of the shipping cycle on traffic delays and accident costs at port collector-distributor roads. Taking the collector-distributor roads of Yangshan Deepwater Port in Shanghai as a case study, parameter estimation and a model validity test are conducted. The changes in traffic delays and accident costs before and during maintenance activities at different stages of the shipping cycle are analyzed by increasing the growth rates of gross domestic product (GDP), and secondary and tertiary industries in GDP. The model results show that, as the economic growth rate increases, the growth magnitudes of traffic delays and accident costs during a peak period are significantly larger than those during a trough period. The results of this study provide policies and suggestions for improving traffic efficiency and safety on port collector-distributor roads. It is suggested to increase the maintenance frequency and maintenance funds during a peak period. Additionally, it is necessary to develop an intelligent road maintenance system for port collector-distributor roads that takes the shipping cycle into account in order to enhance the road safety level. [ABSTRACT FROM AUTHOR]