scholarly journals Risk Assessment Methodology for Vessel Traffic in Ports by Defining the Nautical Port Risk Index

2019 ◽  
Vol 8 (1) ◽  
pp. 10 ◽  
Author(s):  
Xavier Bellsolà Olba ◽  
Winnie Daamen ◽  
Tiedo Vellinga ◽  
Serge P. Hoogendoorn
Keyword(s):  
Risk Assessment ◽  
Traffic Management ◽  
Risk Index ◽  
Analytic Network Process ◽  
Assessment Method ◽  
Maritime Transportation ◽  
Automatic Identification ◽  
Identification System ◽  
Assessment Methodology ◽  
Network Process

Ports represent a key element in the maritime transportation chain. Larger vessels and higher traffic volumes in ports might result in higher risks at the navigational level. Thus, the dire need for a comprehensive and efficient risk assessment method for ports is felt. Many methodologies have been proposed so far, but their application to aggregated vessel traffic risks for the overall assessment of ports is not developed yet. Hence, the development of an approach for the appraisal of the vessel traffic risks is still a challenging issue. This research aims to develop an assessment methodology to appraise the potential risk of accident occurrence in port areas at an aggregated level by creating a ‘Nautical Port Risk Index’ (NPRI). After identifying the main nautical risks in ports, the Analytic Network Process (ANP) is used to derive the risk perception (RP) weights for each criterion from data collected through surveys to expert navigators. The consequences related to each nautical risk are identified in consultation with risk experts. By combining the RP values and the consequence of each criterion for a time period, the NPRI is calculated. The risks in the Port of Rotterdam are presented in a case study, and the method has been validated by checking the results with experts in assessing nautical port risks from the Port of Rotterdam Authority. This method can be used to assess any new port design, the performance of different vessel traffic management measures, changes in the fleet composition, or existent ports using the Automatic Identification System (AIS) data.

Methodological Aspects of the Health Risk Assessment in Application to Safety of Nanomaterial

2017 ◽  
Vol 13 ◽  
pp. 219-224 ◽  
Author(s):  
Anna A. Antsiferova ◽  
Vyacheslav A. Demin ◽  
Vladimir F. Demin
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Risk Index ◽  
Assessment Method ◽  
Assessment Tools ◽  
Specific Method ◽  
Assessment Methodology ◽  
Computer Data ◽  
Safety Standards ◽  
Methodological Aspects

Results of the health risk (HR) assessment are needed to support decisions on safety of nanotechnologies and practical use of nanomaterials/nanoparticles (NMs/NPs), including establishment of health safety standards (HSSs). To meet these needs HR assessment’ tools are developed using the great experience in the development and application of such tools for other sources of harm (ionizing radiation, chemicals, etc.), accumulated during the last decades. The tools include methodology, computer data bases and calculation codes.Three-level’ scheme of development and application of HR assessment methodology is roposed: general, specific and simplified methods. The general method serves as a basis for development of specific methods, applicable to the concrete harm sources, for development and justification of simplified methods. In this approach the specific method consists of two parts: 1) the general HR assessment method, 2) exposure – response dependences for the harm source considered in the form of age-cause-specific death or diseases coefficients. Such structure of HR assessment methodology in its full development makes specific methods being more transparent and comparable as well as safety decisions based on HR assessment for different harm sources.The proposal is made concerning the special risk index for the risk standardization and comparison. The unified approach is developed to the establishment of the HSSs and other levels of decision-making on people safety with the use of HR risk assessment in different spheres of human activity including nanotechnology and use of NPs/NMs.

scholarly journals Ship AIS Trajectory Clustering: An HDBSCAN-Based Approach

2021 ◽  
Vol 9 (6) ◽  
pp. 566
Author(s):  
Lianhui Wang ◽  
Pengfei Chen ◽  
Linying Chen ◽  
Junmin Mou
Keyword(s):  
Traffic Management ◽  
Performance Metrics ◽  
Spatial Clustering ◽  
Maritime Transportation ◽  
Automatic Identification ◽  
Identification System ◽  
Clustering Methods ◽  
Trajectory Clustering ◽  
Clustering Method ◽  
Shape Characteristics

The Automatic Identification System (AIS) of ships provides massive data for maritime transportation management and related researches. Trajectory clustering has been widely used in recent years as a fundamental method of maritime traffic analysis to provide insightful knowledge for traffic management and operation optimization, etc. This paper proposes a ship AIS trajectory clustering method based on Hausdorff distance and Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), which can adaptively cluster ship trajectories with their shape characteristics and has good clustering scalability. On this basis, a re-clustering method is proposed and comprehensive clustering performance metrics are introduced to optimize the clustering results. The AIS data of the estuary waters of the Yangtze River in China has been utilized to conduct a case study and compare the results with three popular clustering methods. Experimental results prove that this method has good clustering results on ship trajectories in complex waters.

scholarly journals Risk Assessment in PPP Projects by Applying Different MCDM Methods and Comparative Results Analysis

2018 ◽  
Vol 8 (4) ◽  
pp. 80 ◽  
Author(s):  
Alireza Valipour ◽  
Hadi Sarvari ◽  
Jolanta Tamošaitiene
Keyword(s):  
Risk Assessment ◽  
Decision Making ◽  
Construction Projects ◽  
Analytic Network Process ◽  
Assessment Method ◽  
Analytic Hierarchy ◽  
Risk Assessment Method ◽  
Network Process ◽  
Comparative Results ◽  
Simple Additive Weighting

Recently, risk assessment has become one of the most challenging issues in the areas of construction and public-private partnerships (PPPs). To address risk assessment issues, various decision-making techniques have been proposed, each with its own specific disadvantages and advantages. This paper investigates step-wise weight assessment ratio analysis (SWARA), complex proportional assessment (COPRAS), fuzzy analytic network process (FANP), fuzzy analytic hierarchy process (FAHP), fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS), simple additive weighting (SAW) and evaluation based on distance from average solution (EDAS) in order to define how various multi-attribute decision-making (MADM) methods compare when used for risk assessment in PPP projects. For this study, 5 risk assessment criteria and 10 types of risk used in Iranian highway PPP projects were selected. Four suitability and applicability tests were used to measure agreement between the rankings derived from the MADM methods. Final results show that all techniques had approximately the same rankings of risk assessment, with the SWARA, COPRAS, and EDAS methods performing slightly better. The findings of this study will help the parties in PPP and construction projects to select the best risk assessment method.

scholarly journals Improving Near Miss Detection in Maritime Traffic in the Northern Baltic Sea from AIS Data

2021 ◽  
Vol 9 (2) ◽  
pp. 180
Author(s):  
Lei Du ◽  
Osiris A. Valdez Banda ◽  
Floris Goerlandt ◽  
Pentti Kujala ◽  
Weibin Zhang
Keyword(s):  
Baltic Sea ◽  
Perceived Risk ◽  
Maritime Transportation ◽  
Near Miss ◽  
Automatic Identification ◽  
Identification System ◽  
Collision Risk ◽  
Ship Collision ◽  
The Impact ◽  
Ship Behavior

Ship collision is the most common type of accident in the Northern Baltic Sea, posing a risk to the safety of maritime transportation. Near miss detection from automatic identification system (AIS) data provides insight into maritime transportation safety. Collision risk always triggers a ship to maneuver for safe passing. Some frenetic rudder actions occur at the last moment before ship collision. However, the relationship between ship behavior and collision risk is not fully clarified. Therefore, this work proposes a novel method to improve near miss detection by analyzing ship behavior characteristic during the encounter process. The impact from the ship attributes (including ship size, type, and maneuverability), perceived risk of a navigator, traffic complexity, and traffic rule are considered to obtain insights into the ship behavior. The risk severity of the detected near miss is further quantified into four levels. This proposed method is then applied to traffic data from the Northern Baltic Sea. The promising results of near miss detection and the model validity test suggest that this work contributes to the development of preventive measures in maritime management to enhance to navigational safety, such as setting a precautionary area in the hotspot areas. Several advantages and limitations of the presented method for near miss detection are discussed.

scholarly journals Trajectory Similarity Analysis with the Weight of Direction and k-Neighborhood for AIS Data

2021 ◽  
Vol 10 (11) ◽  
pp. 757
Author(s):  
Pin Nie ◽  
Zhenjie Chen ◽  
Nan Xia ◽  
Qiuhao Huang ◽  
Feixue Li
Keyword(s):  
Traffic Management ◽  
Similarity Analysis ◽  
Automatic Identification ◽  
Identification System ◽  
Trajectory Data ◽  
Motion Direction ◽  
Maritime Traffic ◽  
A Cell ◽  
Robustness To Noise ◽  
Trajectory Similarity

Automatic Identification System (AIS) data have been widely used in many fields, such as collision detection, navigation, and maritime traffic management. Similarity analysis is an important process for most AIS trajectory analysis topics. However, most traditional AIS trajectory similarity analysis methods calculate the distance between trajectory points, which requires complex and time-consuming calculations, often leading to substantial errors when processing AIS trajectory data characterized by substantial differences in length or uneven trajectory points. Therefore, we propose a cell-based similarity analysis method that combines the weight of the direction and k-neighborhood (WDN-SIM). This method quantifies the similarity between trajectories based on the degree of proximity and differences in motion direction. In terms of its effectiveness and efficiency, WDN-SIM outperformed seven traditional methods for trajectory similarity analysis. Particularly, WDN-SIM has a high robustness to noise and can distinguish the similarities between trajectories under complex situations, such as when there are opposing directions of motion, large differences in length, and uneven point distributions.

Using AIS Data for Navigational Risk Assessment in Restricted Waters

2013 ◽  
pp. 245-254
Author(s):  
Adi Maimun ◽  
Istaz F. Nursyirman ◽  
Ang Yit Sian ◽  
Rahimuddin Samad ◽  
Sulaiman Oladokun
Keyword(s):  
Risk Assessment ◽  
Traffic Flow ◽  
Assessment Method ◽  
Collision Probability ◽  
Traffic Density ◽  
Automatic Identification ◽  
High Concentration ◽  
Marine Traffic ◽  
Cross Traffic ◽  
Strait Of Malacca

The Strait of Malacca is one of the most important shipping lanes in the world. It averages 150 ship passes a day and more than 50,000 ships annually. With a high concentration of vessels in a narrow path, multiple risk situations arise. Analyzing traffic density is made harder by cross traffic and an unknown traffic density at the Strait. In 2009, Universiti Teknologi Malaysia (UTM), through a collaboration with Kobe University, successfully installed an Automatic Identification System (AIS) receiver. Through the AIS receiver, data of ship movements in the Strait of Malacca and Singapore could be recorded. A program was established by UTM to retrieve the data for the purpose of marine traffic collision risk analysis. In this research, a risk assessment method using AIS data is proposed for restricted waters such as for the Strait of Malacca and Singapore. The Risk Assessment Methodology requires the estimation of collision probabilities. The collision probability of the proposed method considers the Traffic Density, directions of traffic flow (with respect to a subject vessel), and probability of navigational failure. An area in the Strait of Singapore between the latitudes of 1°13’N and 1°07’N and Longitudes of 103°4’E and 103°56’E was selected to illustrate the method. By analysing the AIS data of traffic flow, the probabilities of collision for the area were determined. The effect of vessel parameters of length and speed on the risks of collision are also shown.

scholarly journals Risk Assessment of Boot Hydropower Projects in Nepal Using Fuzzy Logic Approach

2018 ◽  
Vol 3 ◽  
pp. 115
Author(s):  
Pramesh Tripathi ◽  
Santosh Kumar Shrestha
Keyword(s):  
Risk Assessment ◽  
Evaluation System ◽  
Risk Index ◽  
Assessment Method ◽  
Risk Level ◽  
Hydropower Project ◽  
Hydroelectric Project ◽  
Extreme Risk ◽  
Fuzzy Logic Approach ◽  
College Of Engineering

<p>Many Hydropower Projects in Nepal are carried out with insufficient risk assessment because of which time over run or variations are predominant. Many projects are stuck in preconstruction phase and others in construction phase. In this study all possible risks associated with the BOOT Hydropower Project in Nepal were identified and evaluated. Fuzzy rating tool has been used to quantify the risk associated with the BOOT Hydropower Projects in Nepal. It provides a flexible and easily understood way to analyze the project risks.  The relative importance (impact) of risk factors was determined from the survey results. A set of questionnaire was prepared for the survey. The survey was conducted with the experts that have experience in BOOT hydropower projects. From the survey, among the type of risks, Grid Connection / Power Evacuation, Political risk and Geological risk were found to be predominant risk respectively in BOOT hydropower projects in Nepal. The risk assessment method enabled a Risk Index (R) value to be calculated, establishing a 4-grade evaluation system: low risk having R values between 1.17 and 1.69; medium risk, between 1.69 and 2.08; high risk, between 2.08 and 2.47; extreme risk, between 2.47 and 2.78. Applicability of the methodology was tested on a real case hydropower project namely Middle Modi Hydroelectric Project (15.1 MW) which is in construction phase on Modi River in Western Region in Nepal and Madhya Bhotekosi Jalavidyut Company Ltd. (102 MW) which is also in construction phase on Bhotekoshi River in Central Region in Nepal.  The risk analysis method will give investors a more rational basis on which to make decisions and it can prevent cost and schedule overruns. An overall risk index can be used as early indicators of project problems or potential difficulties. Evaluators can keep track to evaluate the current risk level with the progress of investments.</p><p><strong>Journal of Advanced College of Engineering and Management</strong>, Vol. 3, 2017, Page: 115-125</p><p> </p>

AIS Database Powered by GIS Technology for Maritime Safety and Security

2008 ◽  
Vol 61 (4) ◽  
pp. 655-665 ◽  
Author(s):  
Ziqiang Ou ◽  
Jianjun Zhu
Keyword(s):  
Traffic Management ◽  
Surveillance Program ◽  
Automatic Identification ◽  
Identification System ◽  
Gis Technology ◽  
Aerial Surveillance ◽  
Maritime Traffic ◽  
Land Control ◽  
Maritime Domain Awareness ◽  
Fundamental Requirement

The Automatic Identification System (AIS) is an efficient tool to exchange positioning data among participating naval units and land control centres. It was developed primarily as an advanced tool for assistance to sailors during navigation and for the safety of the life at sea. Maritime security has become a major concern for all coastal nations, especially after September 11, 2001. The fundamental requirement is maritime domain awareness via identification, tracking and monitoring of vessels within their waters and this is exactly what an AIS could bring. This paper will be focused on how the AIS-derived information could be used for coastal security, maritime traffic management, vessel tracking and monitoring with the help of GIS technology. The AIS data used in this paper was collected by the Canadian national aerial surveillance program.

Sign in / Sign up

Export Citation Format

Share Document