To study the geographical distribution characteristics of maritime traffic risks, statistical representations of potential accident scenarios and macro collision risk models were established, and the waters with higher maritime traffic risks were generated. To better evaluate the risk of ship collision candidates during routing waterways, an improved adaptive bandwidth kernel density estimation (KDE) is proposed. This proposed algorithm is used for evaluating risk reduction of the ship routing system, which schedules and adjusts maritime traffic in congested harbor waterways. Larger bandwidth can make the hot spot region more obvious on a global scale. Moreover, the bandwidth is positively correlated with the dispersion of points. Concerning the data with sparse point distribution, a larger bandwidth should be used whereas, for data with dense points of interest, a smaller bandwidth should be considered. The results show that the KDE, with optimized bandwidth, can fit the ship encountering distribution and obtain the frequent spots for ship encountering. The comparison between KDE results before and after the ship routing system shows that the hot spots of ship collision candidates are reduced after the ship routing waterway is established.

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