Early Adoption Technology Performance Impact: AIS on the St. Lawrence Seaway

2005 ◽  
Vol 58 (1) ◽  
pp. 17-30
Author(s):  
Martha Grabowski ◽  
Hemil Dhami
Keyword(s):  
Traffic Management ◽  
System Analysis ◽  
Automatic Identification ◽  
Identification System ◽  
Performance Impact ◽  
Critical System ◽  
Early Adoption ◽  
State Evaluation ◽  
Traffic Management System ◽  
The Impact

An Automatic Identification System (AIS) was implemented in the St. Lawrence Seaway during 2003. This paper reports the results of a trial conducted pre- and post-AIS implementation to examine the impact of AIS adoption in a safety-critical system. Analysis of the impact on three types of operators, ship's masters, mates and shore-based traffic management system operators showed that overall AIS significantly improved voyage plan monitoring, contributed to improved monitoring vigilance and offered significant aid to decision making. Recommendations include follow-on studies to include a steady state evaluation of the technology impact once the system is mature and a broadening of the pool of subjects to include a less experienced, more international and less well educated group of operators.

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.

Performance Bounds for VDES R-mode

2019 ◽  
Vol 73 (1) ◽  
pp. 92-114 ◽  
Author(s):  
Jan Šafář ◽  
Alan Grant ◽  
Paul Williams ◽  
Nick Ward
Keyword(s):  
Data Exchange ◽  
Estimation Error ◽  
Additive White Gaussian Noise ◽  
Automatic Identification ◽  
Identification System ◽  
Performance Bounds ◽  
Radio Communication ◽  
Very High Frequency ◽  
Radio Communication System ◽  
The Impact

The Very High Frequency (VHF) Data Exchange System (VDES) is a new radio communication system being developed by the international maritime community, with the principal objectives to safeguard existing Automatic Identification System (AIS) core functions and enhance maritime communication applications, based on robust, efficient and secure data transmission with wider bandwidth than the AIS. VDES is also being considered as a potential component of the R-mode concept, where the same signals used for communication are also used for ranging, thus mitigating the impact of disruptions to satellite positioning services. This paper establishes statistical performance bounds on the ranging precision of VDES R-mode, assuming an additive white Gaussian noise propagation channel. Modified Cramér-Rao bounds on the pseudorange estimation error are provided for all waveforms currently proposed for use in terrestrial VDES communications. These are then used to estimate the maximum usable ranges for AIS/VDES R-mode stations. The results show that, under the assumed channel conditions, all of the new VDES waveforms provide better ranging performance than the AIS waveform, with the best performance being achieved using the 100 kHz bandwidth terrestrial VDE waveforms.

scholarly journals Probabilistic Strategic Conflict-Management for 4D Trajectories in Free-Route Airspace

Entropy ◽  
2020 ◽  
Vol 22 (2) ◽  
pp. 159
Author(s):  
Javier Alberto Pérez-Castán ◽  
Álvaro Rodríguez-Sanz ◽  
Luis Pérez Sanz ◽  
Rosa M. Arnaldo Valdés ◽  
V. Fernando Gómez Comendador ◽  
...  
Keyword(s):  
Conflict Management ◽  
Traffic Management ◽  
Time Windows ◽  
Speed Control ◽  
Air Traffic ◽  
Traffic Management System ◽  
Operational Concept ◽  
The Impact ◽  
Strategic Conflict ◽  
Temporary Blocking

The expected growth of air traffic in the following decades demands the implementation of new operational concepts to avoid current limitations of the air traffic management system. This paper focuses on the strategic conflict management for four-dimensional trajectories (4DT) in free-route airspace. 4DT has been proposed as the future operational concept to manage air traffic. Thus, aircraft must fulfil temporary restrictions at specific waypoints in the airspace based on time windows. Based on the temporary restrictions, a strategic conflict management method is proposed to calculate the conflict probability of an aircraft pair (that intersects in the air) and to calculate temporary-blocking windows that quantify the time span at which an aircraft cannot depart because one conflict could occur. This methodology was applied in a case-study for an aircraft pair, including the uncertainty associated with 4DT. Moreover, a sensitivity analysis was performed to characterise the impact of wind conditions and speed control on the temporary-blocking windows. The results concluded that it is feasible to propose 4DT strategic de-confliction based on temporary-blocking windows. Although, uncertainty variables such as wind and speed control impact on the conflict probability and the size of the temporary-blocking windows.

Design and Implementation of Long Range Active RFID Technology

2013 ◽  
Vol 779-780 ◽  
pp. 1715-1718 ◽  
Author(s):  
Yea Jou Shiau ◽  
Yu Bin Chiu
Keyword(s):  
Long Range ◽  
Radio Frequency Identification ◽  
Traffic Management ◽  
High Speed ◽  
Service Industry ◽  
Automatic Identification ◽  
Rfid Technology ◽  
Frequency Identification ◽  
Traffic Management System ◽  
Is Design

The technology of Radio Frequency Identification, namely RFID, has been widely used in service industry for identification. The RFID system is design for inexpensive and reliable purpose in automatic identification. However, very few researchers focused on remote control module in a long range and high speed environment. This study proposed a long range active tag technology and illustrated how to implement it in traffic management system for solving the problem of traffic crowding.

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.

scholarly journals Design and Development of an AIoT Architecture for Introducing a Vessel ETA Cognitive Service in a Legacy Port Management Solution

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8133
Author(s):  
Clara I. Valero ◽  
Enrique Ivancos Pla ◽  
Rafael Vaño ◽  
Eduardo Garro ◽  
Fernando Boronat ◽  
...  
Keyword(s):  
Traffic Management ◽  
Automatic Identification ◽  
Identification System ◽  
Time Of Arrival ◽  
Legacy System ◽  
Cognitive Component ◽  
Cognitive Services ◽  
Oceanographic Data ◽  
Reducing Costs ◽  
Easy Integration

Current Internet of Things (IoT) stacks are frequently focused on handling an increasing volume of data that require a sophisticated interpretation through analytics to improve decision making and thus generate business value. In this paper, a cognitive IoT architecture based on FIWARE IoT principles is presented. The architecture incorporates a new cognitive component that enables the incorporation of intelligent services to the FIWARE framework, allowing to modernize IoT infrastructures with Artificial Intelligence (AI) technologies. This allows to extend the effective life of the legacy system, using existing assets and reducing costs. Using the architecture, a cognitive service capable of predicting with high accuracy the vessel port arrival is developed and integrated in a legacy sea traffic management solution. The cognitive service uses automatic identification system (AIS) and maritime oceanographic data to predict time of arrival of ships. The validation has been carried out using the port of Valencia. The results indicate that the incorporation of AI into the legacy system allows to predict the arrival time with higher accuracy, thus improving the efficiency of port operations. Moreover, the architecture is generic, allowing an easy integration of the cognitive services in other domains.

scholarly journals A Novel Performance Framework and Methodology to Analyze the Impact of 4D Trajectory Based Operations in the Future Air Traffic Management System

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Sergio Ruiz ◽  
Javier Lopez Leones ◽  
Andrea Ranieri
Keyword(s):  
Traffic Management ◽  
Air Traffic Management ◽  
Air Traffic ◽  
Performance Framework ◽  
Performance Requirements ◽  
The Future ◽  
Traffic Management System ◽  
And Performance ◽  
The Impact

The introduction of new Air Traffic Management (ATM) concepts such as Trajectory Based Operations (TBO) may produce a significant impact in all performance areas, that is, safety, capacity, flight efficiency, and others. The performance framework in use today has been tailored to the operational needs of the current ATM system and must evolve to fulfill the new needs and challenges brought by the TBO content. This paper presents a novel performance assessment framework and methodology adapted to the TBO concept. This framework can assess the key performance areas (KPAs) of safety, capacity, and flight efficiency; equity and fairness are also considered in this research, in line with recent ATM trends. A case study is presented to show the applicability of the framework and to illustrate how some of the complex interdependencies among KPAs can be captured with the proposed approach. This case study explores the TBO concept of “strategic 4D trajectory deconfliction,” where the early separation tasks of 4D trajectories at multisector level are assessed. The framework presented in this paper could potentially support the target-setting and performance requirements identification that should be fulfilled in the future ATM system to ensure determined levels of performance.

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.

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