Use of AIS data for performance evaluation of ship traffic with speed control

Abstract Speed control in inland water systems needs to achieve effective balance between ship operational efficiency and transport safety. However, speed limit regulations are largely formulated through expert judgment rather than objective evidence-based evaluation, which sometimes leads to inefficiency due to subjective bias. In this study, a new method is proposed to evaluate the performance of shipping traffic under current speed limits by using the automatic identification system (AIS) big data of 4923 ships in the Shanghai section of the Yangtze River in China. The key elements of this method include data acquisition, error elimination, combination of ship AIS and waterway geocoded data to model traffic flow characteristics, and estimation of the correlation between ship speed and congestion level. Shipping traffic performance in different segments is analyzed. Results reveal that the overall compliance to the speed limit is high, and only a few over-speeding cases are noted in certain segments. Furthermore, we use a normal distribution to model the correlation between ship speed and traffic volume. The findings indicate that the current speed limit in the Shanghai section of Yangtze River is rational. This work provides useful insights into testing the rationality of speed limits in other waterways or shipping channels.