A spatial–temporal forensic analysis for inland–water ship collisions using AIS data

Wang, Yan; Zhang, Jinfen; Chen, Xianqiao; Chu, Xiumin; Yan, Xinping

doi:10.1016/j.ssci.2013.02.006

Cited by 78 publications

(36 citation statements)

References 36 publications

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“…The majority of studies conducted using AIS information have focussed on specific areas such as: ship surveillance, tracking, and security [2,[4][5][6][7][8][9][10][11]; prevention of maritime disasters including collision risks [6,[12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]; shipping noise levels [28][29][30][31][32][33][34][35]; or vessel emissions [36][37][38][39][40][41][42]. Only one known study see [43] has looked at AIS as a tool for marine planning in order to better visualise spatial and temporal variation in shipping activity but the authors did not use all the available vessel types, did not take into account any temporal variation in shipping activity, and concentrated their results on interpolated vessel tracks.…”

Section: Introductionmentioning

confidence: 99%

Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning

Shelmerdine¹

2015

Marine Policy

105

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Section: Introductionmentioning

confidence: 99%

Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning

Shelmerdine¹

2015

Marine Policy

105

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“…With regard to the transportation problem, it is usually time and space consuming [26] to calculate the solution using a deterministic algorithm. An algorithm that calculates all of the permutations is possible for traffic efficiency when many ships arrive in succession.…”

Section: Ship Self-organizing Cooperation Modelmentioning

confidence: 99%

“…In that case, the faster ship should enter first to increase overall efficiency, as shown in Eq. (26 …”

Section: Ship Self-organizing Cooperation Algorithmmentioning

confidence: 99%

Untitled

2018

brod

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SummaryAn effective ship scheduling strategy is critical for the efficiency of waterway transportation, especially in restricted one-way waterways. By treating ship traffic as a distributed system, a novel Ship Self-Organizing Cooperation algorithm (SSOCA) is proposed to evaluate the effects of self-organizing cooperation between ships. An assumption is made that overtaking is not allowed under the given safety requirement. Observing that traffic efficiency is influenced by speed differences, two types of delay times, wait time and navigation time as increased by speed reductions, are applied to evaluate traffic efficiency. The mathematical model of delay time is inferred in different entry sequences subsequently. Taking advantage of the delay model, each ship makes a decision regarding its own sequence to find the local optimum iteratively. An Arena-based ship traffic model is constructed. The simulation results indicate that average delay time for ships is decreased in comparison with the First Come First Served (FCFS) model. That advantage exists for different combinations of traffic flow parameters. Moreover, a balance between efficiency and computation is also achieved by distributing the computational burden to each ship.

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“…Old systems often contain AIS (automatic identification system), GPS (global positioning system), VTS (vessel traffic service), and GIS (geographic information system), while newer systems usually incorporate CCTV system for its practicability and inexpensiveness [3][4][5]. CCTV system enables marine bureau to achieve long-term robust ship tracking from a pure visual perspective.…”

Section: Introductionmentioning

confidence: 99%

Real-Time Inland CCTV Ship Tracking

Xiao

2018

Mathematical Problems in Engineering

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The predator algorithm is a representative pioneering work that achieves state-of-the-art performance on several popular visual tracking benchmarks and with great success when commercially applied to real-time face tracking in long-term unconstrained videos. However, there are two major drawbacks of predator algorithm when applied to inland CCTV (closed-circuit television) ship tracking. First, the LK short-term tracker within predator algorithm easily tends to drift if the target ship suffers partial or even full occlusion, mainly because the corner-points-like features employed by LK tracker are very sensitive to occlusion appearance change. Second, the cascaded detector within the predator algorithm searches for candidate objects in a predefined scale set, usually including 3-5 elements, which hampers the tracker to adapt to the potential diverse scale variations of the target ship. In this paper, we design a random projection based short-term tracker which can dramatically ease the tracking drift when the ship is under occlusion. Furthermore, a forward-backward feedback mechanism is proposed to estimate the scale variation between two consecutive frames. We prove that these two strategies gain significant improvements over the predator algorithm and also show that the proposed method outperforms several other state-of-the-art trackers.

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A spatial–temporal forensic analysis for inland–water ship collisions using AIS data

Cited by 78 publications

References 36 publications

Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning

Teasing out the detail: How our understanding of marine AIS data can better inform industries, developments, and planning

Untitled

Real-Time Inland CCTV Ship Tracking

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