Analysis of Tugboat Activities using AIS Data for the Tianjin Port

2020 ◽  
Vol 2674 (5) ◽  
pp. 498-509
Author(s):  
Shukai Chen ◽  
Feng Wang ◽  
Xiaoyang Wei ◽  
Zhijia Tan ◽  
Hua Wang
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Service Time ◽  
Automatic Identification ◽  
Identification System ◽  
Crucial Importance ◽  
Two Stage ◽  
Temporal And Spatial ◽  
Shed Light

The tugboat is the vessel that helps to maneuver large ships for berthing and un-berthing operations. To achieve efficient tugboat operations, investigating the features of tugboat activities is of crucial importance. This study aims to use automatic identification system (AIS) data to identify the maneuver services and analyze the characteristics of tugboat activities. A two-stage algorithm is developed to extract the time, locations, and involved tugboats for berthing and un-berthing operations from AIS data. The AIS data from Tianjin port, China, are used in the case study to demonstrate the effectiveness of the proposed method and analyze the pattern of tugboat activities. First, some important features of tugboat jobs are presented, such as the daily number of jobs and the spatial distribution of jobs. Then, a temporal and spatial analysis is conducted to investigate tugboat assignment, service time, tugboat utilization, and locations of berthing and un-berthing operations. The obtained results and implications could shed light on the deployment of tugboat berths, tugboat scheduling, and evaluation of tugboat fleet operation.

scholarly journals Modeling of Vessel Traffic Flow for Waterway Design–Port of Świnoujście Case Study

2021 ◽  
Vol 11 (17) ◽  
pp. 8126
Author(s):  
Agnieszka Nowy ◽  
Kinga Łazuga ◽  
Lucjan Gucma ◽  
Andrej Androjna ◽  
Marko Perkovič ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Traffic Flow ◽  
Probabilistic Models ◽  
Historical Data ◽  
Automatic Identification ◽  
Identification System ◽  
Practical Applications ◽  
Ship Traffic ◽  
Navigation Patterns

The paper presents an analysis of ship traffic using the port of Świnoujście and the problems associated with modelling vessel traffic flows. Navigation patterns were studied using the Automatic Identification System (AIS); an analysis of vessel traffic was performed with statistical methods using historical data; and the paper presents probabilistic models of the spatial distribution of vessel traffic and its parameters. The factors that influence the spatial distribution were considered to be the types of vessels, dimensions, and distances to hazards. The results show a correlation between the standard deviation of the traffic flow, the vessel sizes, and the distance to the hazard. These can be used in practice to determine the safety of navigation and the design of non-existing waterways and to create a general model of vessel traffic flow. The creation of the practical applications is intended to improve navigation efficiency, safety, and risk analysis in any particular area.

Automatic identification system data-driven model for analysis of ship domain near bridge-waters

2021 ◽  
pp. 1-22
Author(s):  
Lei Jinyu ◽  
Liu Lei ◽  
Chu Xiumin ◽  
He Wei ◽  
Liu Xinglong ◽  
...  
Keyword(s):  
Least Squares Method ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Automatic Identification System ◽  
Domain Models ◽  
System Data ◽  
Quantification Model ◽  
Highly Correlated

Abstract The ship safety domain plays a significant role in collision risk assessment. However, few studies take the practical considerations of implementing this method in the vicinity of bridge-waters into account. Therefore, historical automatic identification system data is utilised to construct and analyse ship domains considering ship–ship and ship–bridge collisions. A method for determining the closest boundary is proposed, and the boundary of the ship domain is fitted by the least squares method. The ship domains near bridge-waters are constructed as ellipse models, the characteristics of which are discussed. Novel fuzzy quaternion ship domain models are established respectively for inland ships and bridge piers, which would assist in the construction of a risk quantification model and the calculation of a grid ship collision index. A case study is carried out on the multi-bridge waterway of the Yangtze River in Wuhan, China. The results show that the size of the ship domain is highly correlated with the ship's speed and length, and analysis of collision risk can reflect the real situation near bridge-waters, which is helpful to demonstrate the application of the ship domain in quantifying the collision risk and to characterise the collision risk distribution near bridge-waters.

Research on Ship Classification Based on Trajectory Features

2017 ◽  
Vol 71 (1) ◽  
pp. 100-116 ◽  
Author(s):  
Kai Sheng ◽  
Zhong Liu ◽  
Dechao Zhou ◽  
Ailin He ◽  
Chengxu Feng
Keyword(s):  
Pattern Mining ◽  
Extraction Methods ◽  
Behaviour Pattern ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Trajectory Features ◽  
Ship Classification ◽  
Historical Trajectory

It is important for maritime authorities to effectively classify and identify unknown types of ships in historical trajectory data. This paper uses a logistic regression model to construct a ship classifier by utilising the features extracted from ship trajectories. First of all, three basic movement patterns are proposed according to ship sailing characteristics, with related sub-trajectory partitioning algorithms. Subsequently, three categories of trajectory features with their extraction methods are presented. Finally, a case study on building a model for classifying fishing boats and cargo ships based on real Automatic Identification System (AIS) data is given. Experimental results indicate that the proposed classification method can meet the needs of recognising uncertain types of targets in historical trajectory data, laying a foundation for further research on camouflaged ship identification, behaviour pattern mining, outlier behaviour detection and other applications.

Change and continuity in Hurstville’s Chinese restaurants

2021 ◽  
Author(s):  
Samantha Zhan Xu ◽  
Wei Wang
Keyword(s):  
Linguistic Landscape ◽  
Data Set ◽  
Landscape Studies ◽  
Chinese Restaurant ◽  
Temporal And Spatial ◽  
Restaurant Owners ◽  
Depth Interviews ◽  
Shed Light ◽  
Sydney Australia

Abstract This paper investigates the Linguistic Landscape of Chinese restaurants in Hurstville, a Chinese-concentrated suburb in Sydney, Australia. It draws on Blommaert and Maly’s (2016) Ethnographic Linguistic Landscape Analysis (ELLA) and Scollon and Scollon’s geosemiotics (2003). Our data set consists of photographs, Google Street View archives, and ethnographic fieldwork, in particular in-depth interviews with restaurant owners. This paper adopts a diachronic perspective to compare the restaurant scape between 2009 and 2019 and presents an ELLA case study of a long-standing Chinese restaurant. It aims to unveil the temporal and spatial relationships between signs, agents, and place, that demonstrate how a social and historical perspective in Linguistic Landscape studies of diasporic communities can shed light on the changes in the broader social context.

scholarly journals Automatic Identification of Environment Haptic Properties

1999 ◽  
Vol 8 (4) ◽  
pp. 394-411 ◽  
Author(s):  
Pierre E. Dupont ◽  
Capt. Timothy M. Schulteis ◽  
Paul A. Millman ◽  
Robert D. Howe
Keyword(s):  
Haptic Feedback ◽  
Sensory Information ◽  
Automatic Identification ◽  
Identification System ◽  
General Description ◽  
Research Issues ◽  
Property Identification ◽  
Remote Environment ◽  
Force Data

Many applications can be imagined for a system that processes sensory information collected during telemanipulation tasks in order to automatically identify properties of the remote environment. These applications include generating model-based simulations for training operators in critical procedures and improving real-time performance in unstructured environments or when time delays are large. This paper explores the research issues involved in developing such an identification system, focusing on properties that can be identified from remote manipulator motion and force data. As a case study, a simple block-stacking task, performed with a teleoperated two-fingered planar hand, is considered. An algorithm is presented that automatically segments the data collected during the task, given only a general description of the temporal sequence of task events. Using the segmented data, the algorithm then successfully estimates the weight, width, height, and coefficient of friction of the two blocks handled during the task. This data is used to calibrate a virtual model incorporating visual and haptic feedback. This case study highlights the broader research issues that must be addressed in automatic property identification.

scholarly journals Temporal-spatial Analysis of Contributors’ Mapping Behavior for Building Data in OpenStreetMap

2019 ◽  
Vol 2 ◽  
pp. 1-10
Author(s):  
Jin Xu ◽  
Qi Zhou
Keyword(s):  
Spatial Distribution ◽  
Spatial Analysis ◽  
Spatial Patterns ◽  
Volunteered Geographic Information ◽  
Geographic Information ◽  
Developing Regions ◽  
Temporal And Spatial Patterns ◽  
Temporal And Spatial ◽  
One Year ◽  
Beijing China

<p><strong>Abstract.</strong> Volunteered Geographic Information (VGI) crowdsourced from volunteering posts, is closely related to contributors’ mapping behavior. As the most noticeable VGI source, OpenStreetMap (OSM) is one of the most studied objectives in VGI and data contributors. In this paper, temporal-spatial analysis is applied in seeking the temporal and spatial patterns of the number of buildings and contributors in Beijing, China. Temporal changes of the number of updated buildings, and the population of total, new and quitted contributors, were interpreted, as well as the spatial distribution of updated buildings, participated contributors, and frequency of updates. The result suggests that the number of updated buildings, participated contributors, new and quitted contributors are growing. Buildings are mostly updated by a small number of contributors, the majority of which did not participated in mapping in the previous year. Most contributors update buildings for one year without succeeding till the next. Contributors are interested in updating a large amount of buildings frequently around landmarks, commercial districts, universities, and transit hubs. They update buildings at an expanding range and an increasing density, but their attentions do not necessarily bring large quantity of building updates. In general, OSM buildings in developing regions with less complete database are updated under similar patterns as developed regions where data are much more complete.</p>

scholarly journals Ship-to-ship dialogues and agreements for collision risk reduction

2021 ◽  
pp. 1-18
Author(s):  
Reyes Poo Argüelles ◽  
Jesús A. García Maza ◽  
Felipe Mateos Martín ◽  
Marlene Bartolomé
Keyword(s):  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Contributing Factors ◽  
Special Situation ◽  
Safety Communication ◽  
Good Communication ◽  
Critical Situation ◽  
International Regulations

Abstract Non-compliance with or misinterpretation of the International Regulations for Preventing Collisions at Sea (COLREGs) when assessing vessel encounters, and the lack of good communication between the vessels involved in a critical situation, are primary contributing factors in collisions. Vessels engaged in an encounter should be aware that they are part of the same scenario and situation, which can become critical. Sharing and contrasting their information about the encounter would help those responsible to take manoeuvring decisions in a consistent way. There are situations whose evaluation by the respective officers in charge of the navigational watch may diverge and lead to disagreements on the actions to be taken. If there is no proper inter-ship communication, a collision may result. This paper presents a proposal for safety communication implemented in a programmable system using common equipment (automatic identification system), and applies it to a case study of one such special situation, showing how it could help to reduce the risk of collision.

scholarly journals An Anomaly Detection Method for AIS Trajectory Based on Kinematic Interpolation

2021 ◽  
Vol 9 (6) ◽  
pp. 609
Author(s):  
Shaoqing Guo ◽  
Junmin Mou ◽  
Linying Chen ◽  
Pengfei Chen
Keyword(s):  
Anomaly Detection ◽  
Detection Method ◽  
Industrial Applications ◽  
Automatic Identification ◽  
Identification System ◽  
Maritime Transport ◽  
Rule Based ◽  
Enormous Amount ◽  
Kinematic Information

With the enormous amount of information provided by the ship Automatic Identification System (AIS), AIS is now playing a significant role in maritime transport system-related research and development. Many kinds of research and industrial applications are based on the ship trajectory extracted from raw AIS data. However, due to the issues of equipment, the transmission environment, and human factors, the raw AIS data inevitably contain abnormal messages, which have hindered the utilization of such information in practice. Thus, in this paper, an anomaly detection method that focuses on AIS trajectory is proposed, making comprehensive use of the kinematic information of the ship in the AIS data. The method employs three steps to obtain non-error AIS trajectories: (1) data preprocessing, (2) kinematic estimation, and (3) error clustering. It should be noted that steps (2) and (3) are involved in an iterative process to determine all of the abnormal data. A case study is then conducted to test the proposed method on real-world AIS data, followed by a comparison between the proposed method and the rule-based anomaly detection method. As the processed trajectories show fewer abnormal features, the results indicate that the method improves performance and can accurately detect as much abnormal data as possible.

Sign in / Sign up

Export Citation Format

Share Document