Improving maritime traffic surveillance in inland waterways using the robust fusion of AIS and visual data

Qu, Jingxiang; Liu, Ryan Wen; Guo, Yu; Lu, Yuxu; Su, Jianlong; Li, Peizheng

doi:10.1016/j.oceaneng.2023.114198

Cited by 22 publications

(6 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(3) The proposed model 4 ⃝ in this paper has demonstrated significant improvements in P, R, and mAP compared to the baseline model, with increases of 1.5%, 4.3%, and 2.3%, respectively. Although there is a slight decrease in FPS, achieving a detection speed of 110 FPS is still sufficient to meet the real-time perception requirements for marine applications, considering that the transmission speed of the shipboard camera is only 25 frames per second.…”

Section: Methodsmentioning

confidence: 91%

“…In the field of ship perception, many scholars have devoted themselves to exploring how to use computer vision and image processing technology to enhance maritime environment perception abilities, and some scholars have used target detection technology to achieve the automatic perception of maritime targets visually [3]. Qu et al [4] proposed an anti-occlusion vessel tracking method to predict the vessel positions, so as to obtain a synchronized AIS and visual data for data fusion. It can overcome the vessel occlusion problem and improve the safety and efficiency of ship traffic.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research and Application of Panoramic Visual Perception-Assisted Navigation Technology for Ships

Wang,

Cai,

et al. 2024

JMSE

View full text Add to dashboard Cite

In response to challenges such as narrow visibility for ship navigators, limited field of view from a single camera, and complex maritime environments, this study proposes panoramic visual perception-assisted navigation technology. The approach includes introducing a region-of-interest search method based on SSIM and an elliptical weighted fusion method, culminating in the development of the ship panoramic visual stitching algorithm SSIM-EW. Additionally, the YOLOv8s model is improved by increasing the size of the detection head, introducing GhostNet, and replacing the regression loss function with the WIoU loss function, and a perception model yolov8-SGW for sea target detection is proposed. The experimental results demonstrate that the SSIM-EW algorithm achieves the highest PSNR indicator of 25.736, which can effectively reduce the stitching traces and significantly improve the stitching quality of panoramic images. Compared to the baseline model, the YOLOv8-SGW model shows improvements in the P, R, and mAP50 of 1.5%, 4.3%, and 2.3%, respectively, its mAP50 is significantly higher than that of other target detection models, and the detection ability of small targets at sea has been significantly improved. Implementing these algorithms in tugboat operations at ports enhances the fields of view of navigators, allowing for the identification of targets missed by AISs and radar systems, thus ensuring operational safety and advancing the level of vessel intelligence.

show abstract

Section: Methodsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Research and Application of Panoramic Visual Perception-Assisted Navigation Technology for Ships

Wang,

Cai,

et al. 2024

JMSE

View full text Add to dashboard Cite

show abstract

“…The use of data from the LIDAR device allows medium-range data from the radar device to be supplemented with data about the ship's surroundings in its immediate vicinity. The combination of traditional systems used in the marine environment, such as radar or AIS, with sensors operating in the immediate environment [15], such as artificial vision systems and LIDAR systems, allows sufficient understanding to be obtained of the ship's surroundings in the immediate and medium ranges thanks to the fusion of data, in various combinations, such as radar with LIDAR [16], AIS and a visual feed [17], or radar, LIDAR, and a camera feed [18].…”

Section: Autonomous Ship Navigationmentioning

confidence: 99%

Modeling of an Autonomous Electric Propulsion Barge for Future Inland Waterway Transport

Łebkowski,

Koznowski

2023

Energies

View full text Add to dashboard Cite

International trade is continuously rising, leading to an increase in the flow of goods passing through transportation hubs, including air and sea. In addition, the aging fleet of inland vessels necessitates renewal through the construction of new vessels, presenting opportunities for the adoption of modern transport technologies. Autonomous barges can transport bulk and containerized cargo between the central port of a specific region and smaller satellite ports, enabling the dispersal of goods over a wider area. Equipping autonomous barges with advanced sensors, such as LIDAR, computer vision systems that operate in visible light and thermal infrared, and incorporating advanced path finding and cooperation algorithms may enable them to operate autonomously, subject only to remote supervision. The purpose of this study is to explore the potential of autonomous electric propulsion barges in inland waterway transport. Given the increasing demand for efficient and sustainable transport solutions as a result of various new policies, which have set new ambitious goals in clean transportation, this study aims to develop a proposition of an electric propulsion hybrid drive inland waterway barge, and compare it to a conventional diesel-powered barge. The methodology involves the creation of a simulation model of an inland waterway class IV electric barge, equipped with advanced sensors and autonomous control systems. The barge’s navigation is managed through a multi-agent system, with evolutionary algorithms determining a safe passage route. This research also utilizes a proprietary networked ship traffic simulator, based on real inland vessel recorded routes, to conduct the autonomous navigation study. The energy consumption of the barge on a route resulting from the ship traffic simulation is then examined using the mathematical model using the OpenModelica package. As a result of the study, the proposed hybrid propulsion system achieved a 16% reduction in fuel consumption and CO2 emissions, while cutting engine operation time by more than 71%. The findings could provide valuable insights into the feasibility and efficiency of autonomous electric propulsion barges, potentially helping future developments in inland waterway transport.

show abstract

“…Nowadays, with the recovery of the world's shipping economy, the volume of crossborder trade has continued to rise [1]. The number of inland waterway vessels has also increased with the demand for water transportation [2]. Due to the complex environment and navigation conditions, inland waterway vessels are prone to traffic accidents in restricted waters [3].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Method for Ship Heading Control Using Motion Model Prediction and Fractional Order Proportion Integration Differentiation Controller

Shi,

Chen,

Chen

2023

JMSE

View full text Add to dashboard Cite

Due to the influence of the natural environment, it is very challenging to control the movement of ships to navigate safely and avoid potential risks induced by external environmental factors, especially for the development of autonomous ships in inland or restricted waterways. In this research, we propose an integrated approach for ship heading control that improves the timeliness and robustness of navigation. Recursive least squares and backward propagation neural networks are utilized to identify the ship motion model parameters under the influence of external factors and predict their development in real time. A particle swarm optimization-integrated Fractional Order Proportion Integration Differentiation (FOPID) controller is then designed based on the dynamically identified motion model to achieve accurate heading control for ships navigating in restricted waterways. A case study was conducted based on the Korea Venture Large Crude Carrier 2 (KVLCC2) model to verify the effectiveness, and a comparison between the conventional FOPID controller and the improved FOPID controller was also conducted. The results indicate that the proposed identification–prediction–optimization FOPID controller has faster speed on stabilization and has higher robustness against external influences, which could provide added value for the development of a motion controller for the autonomous ship for inland and restricted waterway navigation.

show abstract

Improving maritime traffic surveillance in inland waterways using the robust fusion of AIS and visual data

Cited by 22 publications

References 44 publications

Research and Application of Panoramic Visual Perception-Assisted Navigation Technology for Ships

Research and Application of Panoramic Visual Perception-Assisted Navigation Technology for Ships

Modeling of an Autonomous Electric Propulsion Barge for Future Inland Waterway Transport

An Integrated Method for Ship Heading Control Using Motion Model Prediction and Fractional Order Proportion Integration Differentiation Controller

Contact Info

Product

Resources

About