Exploring effects of ship traffic characteristics and environmental conditions on ship collision frequency

Weng, Jinxian; Liao, Shiguan; Wu, Bing; Yang, Dong

doi:10.1080/03088839.2020.1721584

Cited by 32 publications

(16 citation statements)

References 36 publications

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“…The validation method is in line with previous study results (Zhang et al, 2015). The high-density distribution of NACEs is similar to previous studies in the region (Weng et al, 2020) study, as shown in Figure 10(b). Therefore, the identified NACEs are reliable and useful for analysis.…”

Section: Naces Validationsupporting

confidence: 91%

“…The ship flow analysis is a powerful tool for studying the channel efficiency, ship characteristics and ship accident types in small areas. In the Yangtze Estuary, some cross-section analysis has been used for research (Chai et al., 2020; Weng et al., 2020), and the ship characteristics of its research waters have been further defined. To further understand the relationship between NACEs and tidal changes, we conducted the cross-sectional analysis of Wusong, Nancao waterway and Zhoushan.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters

et al. 2022

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Applying non-accident critical events (NACEs) as an alternative measuring method to assess ship collision risk has become popular in recent years. NACEs has shown temporal features in different waters. This study uses the quaternion ship domain method to identify NACEs around the Yangtze Estuary and adjacent coastal waters from the Automatic Identification System (AIS) data in October 2019. The results indicate that NACEs show different temporal features in estuaries and coastal waters. The relationship between tides, channel types and ships is discussed. In addition, we established a statistical method for the occurrence time of NACEs and the state of tides according to the half-tide level and the nearest time. The outcomes of this study provide a direction for exploring the relationship between NACEs and environmental conditions, which is also instructive for the study of the causes of ship accidents.

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Section: Naces Validationsupporting

confidence: 91%

Section: Discussionmentioning

confidence: 99%

Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters

et al. 2022

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“…Since dynamic information is automatically updated based on sensor data, it is susceptible to faults and errors, similar to those described in section 3.1.1. In addition, problems may occur even in the process of collecting and transmitting data between AIS stations, as noted by Weng et al (2020). The AIS signal can also be influenced by external factors, such as weather conditions and Earth's magnetic field, due to their interference with the very high frequency (VHF) equipment.…”

Section: Ais Datamentioning

confidence: 99%

“…Moreover, the receiving station has a short time slot during which the data must be received, and due to heavy traffic in the region, it fails to receive the data from all the ships in that time. In some cases, small ships deliver inaccurate information due to incorrectly calibrated transmitters, as shown by Weng et al (2020). In a case study, Harati-Mokhtari et al (2007) observed that 2% of the MMSI (Maritime Mobile Service Identity) information was incorrect and 30% of the ships were not properly marked with the correct navigation status.…”

Section: Ais Datamentioning

confidence: 99%

Data Processing Framework for Ship Performance Analysis

Gupta,

Kim,

Steen

et al. 2022

Preprint

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The hydrodynamic performance of a sea-going ship can be analysed using the data obtained from the ship. Such data can be gathered from different sources, like onboard recorded in-service data, AIS data, and noon reports. Each of these sources is known to have their inherent problems. The current work gives a brief introduction to these data sources as well as the common problems associated with them, along with some examples. In order to resolve most of these problems, a streamlined semi-automatic data processing framework for fast data processing is developed and presented here. The data processing framework can be used to process the data obtained from any of the above three mentioned sources. The framework incorporates processing steps like interpolating weather hindcast (metocean) data to ship's location in time, deriving additional features, validating data, estimating resistance components, data cleaning, and outlier detection. A brief description of each of the processing steps is provided with examples from existing datasets. The processed data can be further used to analyse the hydrodynamic performance of a ship.

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“…In China's Yangtze River and its estuary, more than 100,000 ships pass through the estuary area each year. The rapid growth of ship density, overtaking, and encounters of surface ships may lead to higher ship accident rates [5]. In addition, serious ship collision accidents may lead to disastrous consequences [6].…”

Section: Introductionmentioning

confidence: 99%

Research on Multi-Ship Target Detection and Tracking Method Based on Camera in Complex Scenes

Hong

Cui

Chen

et al. 2022

JMSE

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Aiming at the problem that multi-ship target detection and tracking based on cameras is difficult to meet the accuracy and speed requirements at the same time in some complex scenes, an improved YOLOv4 algorithm is proposed, which simplified the network of the feature extraction layer to obtain more shallow feature information and avoid the disappearance of small ship target features, and uses the residual network to replace the continuous convolution operation to solve the problems of network degradation and gradient disappearance. In addition, a nonlinear target tracking model based on the UKF method is constructed to solve the problem of low real-time performance and low precision in multi-ship target tracking. Multi-ship target detection and tracking experiments were carried out in many scenes with large differences in ship sizes, strong background interference, tilted images, backlight, insufficient illumination, and rain. Experimental results show that the average precision of the detection algorithm of this paper is 0.945, and the processing speed is about 34.5 frame per second, where the real-time performance is much better than other algorithms while maintaining high precision. Furthermore, the multiple object tracking accuracy (MOTA) and the multiple object tracking precision (MOTP) of this paper algorithm are 76.4 and 80.6, respectively, which are both better than other algorithms. The method proposed in this paper can realize the ship target detection and tracking well, with less missing detection and false detection, and also has good accuracy and real-time performance. The experimental results provide a valuable theoretical reference for the further practical application of the method.

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Exploring effects of ship traffic characteristics and environmental conditions on ship collision frequency

Cited by 32 publications

References 36 publications

Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters

Temporal features of non-accident critical events impact from tides around the Yangtze Estuary and adjacent coastal waters

Data Processing Framework for Ship Performance Analysis

Research on Multi-Ship Target Detection and Tracking Method Based on Camera in Complex Scenes

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