The Experts below are selected from a list of 13947 Experts worldwide ranked by ideXlab platform
Jinfen Zhang - One of the best experts on this subject based on the ideXlab platform.
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Multi-Ship Collision Avoidance Decision-Making Based on Collision Risk Index
Journal of Marine Science and Engineering, 2020Co-Authors: Anmin Zhang, Wuliu Tian, Jinfen Zhang, Zebei HouAbstract:Most maritime accidents are caused by human errors or failures. Providing early warning and decision support to the officer on watch (OOW) is one of the primary issues to reduce such errors and failures. In this paper, a quantitative real-time multi-ship Collision Risk analysis and Collision avoidance decision-making model is proposed. Firstly, a multi-ship real-time Collision Risk analysis system was established under the overall requirements of the International Code for Collision Avoidance at Sea (COLREGs) and good seamanship, based on five Collision Risk influencing factors. Then, the fuzzy logic method is used to calculate the Collision Risk and analyze these elements in real time. Finally, decisions on changing course or changing speed are made to avoid Collision. The results of Collision avoidance decisions made at different Collision Risk thresholds are compared in a series of simulations. The results reflect that the multi-ship Collision avoidance decision problem can be well-resolved using the proposed multi-ship Collision Risk evaluation method. In particular, the model can also make correct decisions when the Collision Risk thresholds of ships in the same scenario are different. The model can provide a good Collision Risk warning and decision support for the OOW in real-time mode.
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Quantitative assessment of Collision Risk influence factors in the Tianjin port
Safety Science, 2018Co-Authors: Jinfen Zhang, C. Guedes Soares, Ângelo P. Teixeira, Xinping YanAbstract:Abstract Collision between ships is one of the dominant types of accident in the approaches to Tianjin port, which accounts for 65% of all types of accidents. This paper presents a quantitative maritime Risk assessment methodology by using Bayesian rules and least squares estimation method to identify the dominant factors that contribute to Collision accidents. The approach relates accident data with traffic data by pairwise comparisons between the Collision Risks under different navigation conditions and different types of ships. The results indicate that small ships with lengths smaller than 100 m have a Collision Risk much higher than larger ships. The results also indicate that safety improvement of working ships and oil tankers is one of the most effective ways to reduce the overall Collision Risk. The Collision probability of the ships without a pilot is about 9 times higher than those with a pilot. The analysis also shows that further steps should be undertaken to reduce Risk during strong wind conditions to at least the same level of the normal conditions. The results obtained are useful for managers to support their decisions to control Collision Risk.
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Use of Encounter Model for Collision Risk Assessment of Yangtze River
ICTIS 2011, 2011Co-Authors: Di Zhang, Xinping Yan, Pin-fu Yang, Jinfen ZhangAbstract:As China's largest and the world's busiest inland river, the sustainable development and navigational safety of Yangtze River are widely concerned by various parties. However, with the national development of the Middle and Western parts of China, the throughput as well as the passing ships of Yangtze River has been increasing rapidly during the past few decades. Collisions, groundings, overturns, oil-spills, fires, and other accidents have occurred repeatedly and caused serious consequences. In view of this, this paper examines Collision Risk assessment on the Yangtze River. The research presented a Collision Risk assessment approach which is based on a novel ship encounter model. This model considers the historical and the current traffic conditions as well as the environmental features, which could be used for evaluation and prediction of Collision Risk. Finally, the Collision Risk of the main route of Yangtze River was evaluated as an example.
Zhao-ning Zhang - One of the best experts on this subject based on the ideXlab platform.
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Comprehensive Study on Assessment Model of Free Flight Collision Risk
DEStech Transactions on Environment Energy and Earth Science, 2017Co-Authors: Zhao-ning ZhangAbstract:The free flight concept and the research status at home and abroad were summarized. Then the Collision Risk model of the Reich model, the double ice hockey model, the event tree model, the stochastic analysis model, have analyzed, and then the application scope, merits and drawbacks of each model were analyzed. Furthermore the Collision Risk assessment model of free flight based on CNS performance was studied. This provides a theoretical basis for the further research of free flight in the future.
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GRMSE - Research on Collision Risk Model in Free Flight Based on Position Error
Geo-Informatics in Resource Management and Sustainable Ecosystem, 2016Co-Authors: Zhao-ning Zhang, Ruijun ShiAbstract:The problem of Collision Risk in free flight with a certain safe distance is studied. In free flight, the Collision Risk is closely related to the aircraft position error. With the stochastic characteristics, we set the position error to satisfy a three-dimensional Gaussian distribution, and established the position error model of the aircraft in the horizontal and the vertical direction. Determine the location and the time when the two aircrafts are closest by the nominal route, and calculate the probability that the aircraft appears at any point near the theoretical position by the position error model. Because every Collision occurs after conflict, we calculated the conflict probability first, and then modeled the Collision Risk given safe distance in free flight. Moreover, the algorithm is presented to use this Collision Risk model to obtain the minimum safe distance with a safety target level. The results of case study show the feasibility of this model.
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The Research of Flight Collision Risk Based on Random Factors
Applied Mechanics and Materials, 2014Co-Authors: Zhao-ning Zhang, Ai Ping JiaAbstract:Using the method of stochastic differential equations to analysis two aircrafts and to establish the aircraft flight Collision Risk model. First the relative position and speed of the aircraft on the joint distribution density should be confirmed, and convert it into a Gaussian density to simplify the calculation of nonlinear filtering theory, and then use the method of stochastic differential equation to establish flight Collision Risk model, and also includes the introduction of how the CNS performance of random factors, human factors and avoidance system performance affect the flight Collision. After verifying the Collision Risk in the example, the results show that the model is feasible.
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Modeling of Collision Risk on parallel routes based on spherical protected area
2010 Chinese Control and Decision Conference, 2010Co-Authors: Zhao-ning Zhang, Jin-wei Shen, Ji-min LiuAbstract:This paper presents an analysis of Collision Risk on parallel routes, which computes the Collision Risk through establishing a model under the condition of a given target level of safety. Firstly, the three-dimensional coordination system of the aircraft is converted to two-dimensional coordination system, and then the Collision Risk assessment model is established by using multi-dimensional random variable covariance matrix on the basis of spherical protected area instead of cuboid protected area in the Reich model. Secondly, arithmetic of separation assessment is established to compute the Collision Risk under different flight separation. Finally, an example is analyzed, compared the results 1.026 ×10−12, 3.242×10−16 and 6.473×10−25 with the target level of safety 1.5×10−8 to indicate that the separation of the route is feasible.
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Lateral Collision Risk model based on CNS position error
Journal of Traffic and Transportation Engineering, 2009Co-Authors: Zhao-ning Zhang, Jin-wei Shen, Ji-min LiuAbstract:In order to confirm the safe separation of routes and evaluate the Collision Risk effectively, the lateral Collision Risk based on CNS(communication, navigation and surveillance) position error was studied. The multi-dimensional random variable covariance matrix was applied to gain the distribution function of the lateral position error under CNS environment, then the lateral Collision Risk model under CNS position error was established, and an example was calculated. Analysis result shows that the lateral Collision Risk of studied route is 4.8 10-13, which is in the safety target level of 5.0 10-9, so the route under existing CNS environment is safe. 2 figs, 12 refs.
Zhongyi Zheng - One of the best experts on this subject based on the ideXlab platform.
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A molecular dynamics approach for modeling the geographical distribution of ship Collision Risk
Ocean Engineering, 2020Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract Collision is one of the major accidents that put the safety of navigation at Risk all the time. The effective monitoring on the geographical distribution of Collision Risk is conducive to reducing the chance of Collision accidents. In this paper, a novel model intended for identifying the geographical distribution of Collision Risk in water area was proposed on the basis of radial distribution function in molecular dynamics. In this model, ship traffic and ships were converted into a molecular system. After being obtained using an analytical method, Collision Risk was generalized as distance to model the Collision Risk by radial distribution function. Finally, a space interpolation technique was applied to visualize the geographical distribution of Collision Risk. To validate the proposed model, the AIS data contained in Bohai Strait was used to conduct experiment. According to the experimental results, the map as obtained by the proposed model is capable to identify the geographical distribution of Collision Risk, and is advantageous over the traditional method in the instantaneity and accuracy of identification. Moreover, the proposed model can assist surveillance operators in the monitoring of Collision Risk and the improvement of work efficiency, thus enhancing the navigational safety in the water area.
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A novel model for identifying the vessel Collision Risk of anchorage
Applied Ocean Research, 2020Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract The Collision Risk in the port area, especially in the anchorage area, increases gradually along with the progressive development of port traffic. This paper proposes a novel anchorage Collision Risk model in the identification of the Collision Risk of anchorage. First, the regional Collision Risk model was improved in order to fit the characteristics of vessels in anchorage. Second, a novel anchorage Collision Risk indicator was proposed based on ship domains to evaluate the Collision Risk of anchorage from a global perspective. Finally, the two indicators were synthesized to obtain a more accurate anchorage Collision Risk index. The AIS data of vessels in the anchorages off the coast of Shandong peninsula in the Northern Yellow Sea of China were used for the case studies. The results indicate that the proposed anchorage model may effectively represent the Collision Risk of anchorage. The proposed model may serve as reference for the safety analysis of port traffic and assist maritime surveillance operators in the Collision Risk monitoring of port traffic to enhance traffic safety.
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A cooperative game approach for assessing the Collision Risk in multi-vessel encountering
Ocean Engineering, 2019Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract Collision Risk quantification is important for reducing Collision accidents and improving navigational safety. However, most of the related studies attached more importance to the Collision Risk between two vessels, but failed to obtain the global Collision Risk in multi-vessel encountering. This paper proposed a model which was able to assess the Collision Risk not only between any two vessels but also among multiple vessels in encountering based on a cooperative game. For assessing the global Collision Risk, a new Collision Risk indicator was proposed based on Collision avoidance manoeuvre and ship domain to represent the Collision Risk of each vessel in multi-vessel encountering first. Shapley value method was utilized to estimate the contribution of each vessel to the global Collision Risk. Global Collision Risk could be assessed based on the Collision Risk and contribution of each vessel. For validating the effectiveness of the proposed model, several experiments of different multi-vessel encountering cases were carried out. The results suggested that the model could represent the Collision Risk of multi-vessel effectively. The model can help surveillance operators have a better understanding of the global Collision Risk and lower their cognitive pressures faced with challenges from relative high traffic density or complexity.
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A novel framework for regional Collision Risk identification based on AIS data
Applied Ocean Research, 2019Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract Identification of regional Collision Risk in water area is of significance for the safety of navigation. However, traditional Risk identification models are subject to the limitations in accuracy, short-term identification and traffic characteristics. Herein, a framework was put forward to identify regional Collision Risk instantaneously based on AIS data. The vessels were clustered by using the spatial clustering method. Afterwards, the framework was divided into two steps. Firstly, Collision Risk of each cluster was obtained by Collision Risk and contribution of the vessels within the cluster. An analytical method was adopted to identify Collision Risk of each vessel from the perspective of vessel pairs. Contribution of each vessel was determined by using improved Shapley value method in game theory. Secondly, regional Collision Risk was obtained by Collision Risk and contribution of each cluster. Case studies were carried out based on the AIS data of Northern Yellow Sea in China to validate the validity of the proposed framework. The results show that the proposed framework can effectively identify Collision Risk in water area, presenting the potential for Collision Risk monitoring and Collision Risk analysis of water area.
Sameer Alam - One of the best experts on this subject based on the ideXlab platform.
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Airspace Capacity Overload Identification Using Collision Risk Patterns
2020 International Conference on Artificial Intelligence and Data Analytics for Air Transportation (AIDA-AT), 2020Co-Authors: Qing Cai, Sameer Alam, Vu DuongAbstract:The ever increasing demand for air travel may induce en-route airspace capacity overload which endangers flight safety and elicit air traffic congestion. Knowledge of airspace capacity overload is important for air traffic flow management and flight planning to mitigate air traffic congestion without compromising airspace safety level. Since the primary task of air traffic controllers is to manage traffic flow within the constraints imposed by safety requirements, i.e., to warrant the Collision Risk at a low level, in this paper, we use the aircraft mid-air Collision Risk for a given airspace as the indicator of airspace capacity overload. With given air traffic data and airspace configurations, the Collision Risk distributions inside an airspace is determined through Collision Risk modelling. Based on the density and intensity of Collision Risk, the Collision Risk distributions are converted into heatmaps and Collision Risk patterns are further recognized from the heatmaps using image processing technique. Three major states of airspace workload can be identified from theses patterns: normal state, transition state and overload state. For new traffic data during a given time period, by matching its Collision Risk distribution to the closest Collision Risk pattern, we are able to identify whether the airspace is overloaded or not. The experimental study in an en-route sector of the Singapore airspace has manifested the ability of the proposed method in Collision Risk pattern recognition and capacity overload identification.
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WSC - An Airspace Collision Risk Simulator for Safety Assessment
2019 Winter Simulation Conference (WSC), 2019Co-Authors: Jiangjun Tang, Hussein A. Abbass, Sameer AlamAbstract:Modelling the spatio-temporal dynamics and evolution of Collision Risk in an airspace is critical for multiple purposes. First, the model could be used to diagnose the critical points where the level of Risk has escalated due to particular airspace configurations and/or events. Second, the model could reveal information on the rate of Risk-escalation in an airspace, which could be used as a Risk indicator in its own right. The aim of this paper is to present an Airspace Collision Risk Simulator for safety assessment. This is achieved by developing a fast-time simulator with a suitable fidelity for spatial-temporal analysis of Collision Risk using clustering methods. This simulator integrates the airspace model, flight aerodynamic model and traffic flow model to facilitate the Collision Risk computations and visualization. The proposed simulator is a first attempt to provide actionable information on the evolution of airspace Collision Risk for airspace safety assessment, offering practical benefits to the operational air traffic control environment.
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Airspace Collision Risk Hot-Spot Identification using Clustering Models
IEEE Transactions on Intelligent Transportation Systems, 2018Co-Authors: Minh-ha Nguyen, Sameer AlamAbstract:A key safety indicator for airspace is its Collision Risk estimate, which is compared against a target level of safety to provide a quantitative basis for judging the safety of operations in airspace. However, this quantitative basis fails to provide any insight regarding the magnitude, location, and timing of the Risk of Collision, distributed within a given airspace. In this paper, we propose a methodology for the identification of Collision Risk hot spots in a given airspace. The proposed methodology consists of processing air traffic data and developing traffic routes based on entry and exit points within the airspace. These routes and other flight information are then used to project air-traffic crossings and cluster potential Collisions. The proposed method then estimates the Collision Risk for each identified cluster, culminating in Risk assessment for the entire airspace. The model extends and adopts the state-of-the art clustering models, systemically identifies airspace Collision Risk hot spots, and further analyses hot spots by analyzing cluster features (number of points and contribution to overall Risk) with flight levels and time of day. Experiments were conducted using one-month traffic data (25 440 flights) from Bahrain en-route airspace. By visualizing crossing points and clustering them in a 2-D geographic information system model we are able to identify Collision Risk hot spots, which contribute significantly to overall Collision Risk.
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A Complex Network Approach to Analyze the Effect of Intermediate Waypoints on Collision Risk Assessment
Air traffic control quarterly, 2014Co-Authors: Murad Hossain, Sameer Alam, Fergus Symon, Henk A.p. BlomAbstract:This paper investigates how estimated Collision Risk in upper airspace varies with changes in underlying airspace network complexity. Direct Route model (which assumes great circle route between entry and exit waypoints) and Intermediate Waypoint model (which uses airwaywaypoint routes between entry and exit waypoints) were used. One month of traffic data (more than 200,000 flights) from 12 countries in the Middle East was analyzed for Collision Risk estimates, and the airspace network was characterized for several complex network indicators. Results show that intermediate waypoint leads to a significant increase in Collision Risk estimates. Results also show the correlation between estimated Collision Risk and specific network complexity measures. From an operational perspective this means that in airspaces with a highly structured airspace, Collision Risk may be underestimated when using the widely accepted direct route model.
Zihao Liu - One of the best experts on this subject based on the ideXlab platform.
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A molecular dynamics approach for modeling the geographical distribution of ship Collision Risk
Ocean Engineering, 2020Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract Collision is one of the major accidents that put the safety of navigation at Risk all the time. The effective monitoring on the geographical distribution of Collision Risk is conducive to reducing the chance of Collision accidents. In this paper, a novel model intended for identifying the geographical distribution of Collision Risk in water area was proposed on the basis of radial distribution function in molecular dynamics. In this model, ship traffic and ships were converted into a molecular system. After being obtained using an analytical method, Collision Risk was generalized as distance to model the Collision Risk by radial distribution function. Finally, a space interpolation technique was applied to visualize the geographical distribution of Collision Risk. To validate the proposed model, the AIS data contained in Bohai Strait was used to conduct experiment. According to the experimental results, the map as obtained by the proposed model is capable to identify the geographical distribution of Collision Risk, and is advantageous over the traditional method in the instantaneity and accuracy of identification. Moreover, the proposed model can assist surveillance operators in the monitoring of Collision Risk and the improvement of work efficiency, thus enhancing the navigational safety in the water area.
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A novel model for identifying the vessel Collision Risk of anchorage
Applied Ocean Research, 2020Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract The Collision Risk in the port area, especially in the anchorage area, increases gradually along with the progressive development of port traffic. This paper proposes a novel anchorage Collision Risk model in the identification of the Collision Risk of anchorage. First, the regional Collision Risk model was improved in order to fit the characteristics of vessels in anchorage. Second, a novel anchorage Collision Risk indicator was proposed based on ship domains to evaluate the Collision Risk of anchorage from a global perspective. Finally, the two indicators were synthesized to obtain a more accurate anchorage Collision Risk index. The AIS data of vessels in the anchorages off the coast of Shandong peninsula in the Northern Yellow Sea of China were used for the case studies. The results indicate that the proposed anchorage model may effectively represent the Collision Risk of anchorage. The proposed model may serve as reference for the safety analysis of port traffic and assist maritime surveillance operators in the Collision Risk monitoring of port traffic to enhance traffic safety.
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A Novel Framework of Real-Time Regional Collision Risk Prediction Based on the RNN Approach
Journal of Marine Science and Engineering, 2020Co-Authors: Dapei Liu, Zihao Liu, Xin Wang, Yao Cai, Zhengjiang LiuAbstract:Regional Collision Risk identification and prediction is important for traffic surveillance in maritime transportation. This study proposes a framework of real-time prediction for regional Collision Risk by combining Density-Based Spatial Clustering of Applications with Noise (DBSCAN) technique, Shapley value method and Recurrent Neural Network (RNN). Firstly, the DBSCAN technique is applied to cluster vessels in specific sea area. Then the regional Collision Risk is quantified by calculating the contribution of each vessel and each cluster with Shapley value method. Afterwards, the optimized RNN method is employed to predict the regional Collision Risk of specific seas in short time. As a result, the framework is able to determine and forecast the regional Collision Risk precisely. At last, a case study is carried out with actual Automatic Identification System (AIS) data, the results show that the proposed framework is an effective tool for regional Collision Risk identification and prediction.
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A cooperative game approach for assessing the Collision Risk in multi-vessel encountering
Ocean Engineering, 2019Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract Collision Risk quantification is important for reducing Collision accidents and improving navigational safety. However, most of the related studies attached more importance to the Collision Risk between two vessels, but failed to obtain the global Collision Risk in multi-vessel encountering. This paper proposed a model which was able to assess the Collision Risk not only between any two vessels but also among multiple vessels in encountering based on a cooperative game. For assessing the global Collision Risk, a new Collision Risk indicator was proposed based on Collision avoidance manoeuvre and ship domain to represent the Collision Risk of each vessel in multi-vessel encountering first. Shapley value method was utilized to estimate the contribution of each vessel to the global Collision Risk. Global Collision Risk could be assessed based on the Collision Risk and contribution of each vessel. For validating the effectiveness of the proposed model, several experiments of different multi-vessel encountering cases were carried out. The results suggested that the model could represent the Collision Risk of multi-vessel effectively. The model can help surveillance operators have a better understanding of the global Collision Risk and lower their cognitive pressures faced with challenges from relative high traffic density or complexity.
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A novel framework for regional Collision Risk identification based on AIS data
Applied Ocean Research, 2019Co-Authors: Zihao Liu, Zhongyi ZhengAbstract:Abstract Identification of regional Collision Risk in water area is of significance for the safety of navigation. However, traditional Risk identification models are subject to the limitations in accuracy, short-term identification and traffic characteristics. Herein, a framework was put forward to identify regional Collision Risk instantaneously based on AIS data. The vessels were clustered by using the spatial clustering method. Afterwards, the framework was divided into two steps. Firstly, Collision Risk of each cluster was obtained by Collision Risk and contribution of the vessels within the cluster. An analytical method was adopted to identify Collision Risk of each vessel from the perspective of vessel pairs. Contribution of each vessel was determined by using improved Shapley value method in game theory. Secondly, regional Collision Risk was obtained by Collision Risk and contribution of each cluster. Case studies were carried out based on the AIS data of Northern Yellow Sea in China to validate the validity of the proposed framework. The results show that the proposed framework can effectively identify Collision Risk in water area, presenting the potential for Collision Risk monitoring and Collision Risk analysis of water area.