Showing papers on "Collision avoidance system published in 2016"

Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

Abstract: This paper describes a concept for a collision avoidance system for ships, which is based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, compliance with the Convention on the International Regulations for Preventing Collisions at Sea and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.

Advanced Driver Assistance System for Road Environments to Improve Safety and Efficiency

Abstract: The advances in Information Technologies have led to more complex road safety applications. These systems provide multiple possibilities for improving road transport. The integrated system that this paper presents deals with two aspects that have been identified as key topics: safety and efficiency. To this end, the development and implementation of an integrated advanced driver assistance system (ADAS) for rural and intercity environments is proposed. The system focuses mainly on single-carriageways roads, given the complexity of these environments compared to motorways and the high number of severe and fatal accidents on them. The proposed system is based on advanced perception techniques, vehicle automation and communications between vehicles (V2V) and with the infrastructure (V2I). Sensor fusion architecture based on computer vision and laser scanner technologies are developed. It allows real time detection and classification of obstacles, and the identification of potential risks. The driver receives this information and some warnings generated by the system. In case, he does not react in a proper way, the vehicle could perform autonomous actions (both on speed control or steering maneuvers) to improve safety and/or efficiency. Furthermore, a multimodal V2V and V2I communication system, based on GeoNetworking, facilitates the flow of information between vehicles and assists in the detection and information broadcasting processes. All this, combined with vehicle positioning, detailed digital maps and advanced map-matching algorithms, establish the decision algorithms of different ADAS systems. The applications developed include: adaptive cruise control with consumption optimization, overtaking assistance system in single-carriageways roads that takes into account appropriate speed evolution and identifies most suitable road stretches for the maneuver; assistance system in intersections with speed control during approximation maneuvers, and collision avoidance system with the possibility of evasive maneuvers. To this end, mathematical vehicle dynamics models have been used to ensure the stability, and propulsion system models are used to establish efficient patterns, Artificial Intelligence and simulation are used for experimentation and evaluation of algorithms to be implemented in the control unit. Finally, the system is designed to warn the driver if a risk is detected and, if necessary, to take control of the vehicle. The system has been implemented on a passenger car and has been tested in specific scenarios on a test track with satisfactory results. Language: en

Radar-based collision avoidance for unmanned surface vehicles

Abstract: Unmanned surface vehicles (USVs) have become a focus of research because of their extensive applications. To ensure safety and reliability and to perform complex tasks autonomously, USVs are required to possess accurate perception of the environment and effective collision avoidance capabilities. To achieve these, investigation into realtime marine radar target detection and autonomous collision avoidance technologies is required, aiming at solving the problems of noise jamming, uneven brightness, target loss, and blind areas in marine radar images. These technologies should also satisfy the requirements of real-time and reliability related to high navigation speeds of USVs. Therefore, this study developed an embedded collision avoidance system based on the marine radar, investigated a highly real-time target detection method which contains adaptive smoothing algorithm and robust segmentation algorithm, developed a stable and reliable dynamic local environment model to ensure the safety of USV navigation, and constructed a collision avoidance algorithm based on velocity obstacle (V-obstacle) which adjusts the USV’s heading and speed in real-time. Sea trials results in multi-obstacle avoidance firstly demonstrate the effectiveness and efficiency of the proposed avoidance system, and then verify its great adaptability and relative stability when a USV sailing in a real and complex marine environment. The obtained results will improve the intelligent level of USV and guarantee the safety of USV independent sailing.

A collision avoidance system at intersections using Robust Model Predictive Control

Abstract: Collisions at intersections account for about 40% of all car accidents and for about 20% of all traffic fatalities in the United States. The main cause is human error in recognition and decision making. Active safety systems have thus a great potential for increasing vehicle safety at intersections. They may issue warnings to the driver or assume control of the vehicle in critical situations. Most approaches in current research rely on the assumption that all vehicles at the intersection are controllable, and/or they can be coordinated by a central intersection manager. This paper considers the case of a single controllable ego vehicle surrounded by several uncontrollable target vehicles, without communication. Only a map with the current position and velocity of the target vehicles are assumed to be known, but no pre-defined crossing order is given. A Robust Model Predictive Control strategy is designed for finding safe gaps in the crossing traffic, and for planning optimal trajectories to maximize the ego vehicle's efficiency and driver comfort. It is shown that its performance can be enhanced by Affine Disturbance Feedback. The algorithm is tested in several simulation scenarios and implemented on a test vehicle for experimental validation.

Simulation research on emergency path planning of an active collision avoidance system combined with longitudinal control for an autonomous vehicle

Abstract: Autonomous vehicle technology is greatly valued nowadays, and an active collision avoidance system is one of the key parts for autonomous driving. This study presents a comprehensive architecture of an active collision avoidance system for an autonomous vehicle, which is integrated with a decision-making module, a path-planning module, a lateral-path-following module and a fuzzy adaptive following module (longitudinal motion) to deal with potential hazards on a straight road or a curved road. In order to make the planned path for overtaking manoeuvres safer, an improved harmonic velocity potential approach for path planning is presented, which innovatively enhances the effect of an obstacle potential on a road by adding a scale term, so that it can generate a smooth path for a vehicle-overtaking manoeuvre. All the potentials which are used for vehicle lane keeping or lane changing are well designed. The lateral-path-following module is based on the constrained linear model predictive control approach, whi...

Vehicle collision warning and active control method based on vehicle communication

Abstract: The invention relates to a vehicle collision warning and active control method based on vehicle communication. The method is realized through an early warning control device which is arranged on a vehicle. A front vehicle collision warning and active control method, a rear vehicle tailgate warning and active control method and an adjacent vehicle lane changing warning and active control method are comprised. According to the invention, a vehicle communication collaborative way is used to exchange the environmental perception and state data of two vehicles; safety distance and brake device can be adjusted by integrating the conditions of the vehicle and an adjacent vehicle; warning delay of the vehicle and the adjacent vehicle is reduced; and the vehicle and the adjacent vehicle can collaborate to make a proper active vehicle control decision and operation. The problems that the information of the adjacent vehicle is unavailable; safety distance and brake device cannot be adjusted; and vehicle collaborative collision warning and collaborative active safety operation cannot be carried out for the state of the adjacent vehicle in the prior art relying on a collision avoidance system of the vehicle are solved. The reliability and the accuracy of vehicle collision and active control are effectively improved.

Towards a generic and modular geofencing strategy for civilian UAVs

Abstract: This paper introduces the reasoning and concepts behind a generic and modular approach to obstacle avoidance based on geofencing. The issue of UAV safety is tackled from a practical point of view and a collision avoidance system based on practical usage and safety considerations is presented. Before doing so, the need for a reference model of geographic geometry is discussed, looking at global positioning in different reference systems and how to switch between the associated coordinates systems. The concept of fence is defined and the practical aspects of these fences definitions and mapping are detailed. A collision avoidance strategy is proposed that works in the case of autonomous flight as well as in the case of piloted flight. To our knowledge, this second scenario has not been extensively covered and we feel it deserves some attention since most of the civilian UAVs flying today are piloted manually by an operator. This avoidance is based on constrained optimization to find an input for the controller which prevents collision while staying as true as possible to the original command from the human operator. This strategy allows for smooth collision avoidance since it gently and continuously restricts the flight possibilities of the UAV while giving as much control freedom as possible to the operator. We also discuss how this work can be extended by taking the actual vehicle dynamic into consideration in order to make it work for a larger variety of controllers. The concept behind the “closest point” approach used above is detailed, and its limitations and possible extensions are discussed. Finally, we present the simulation framework used to test this geofencing strategy and discuss the simulation results as a proof of concept for our future implementation on real-world vehicles.

Trust-Based Analysis of an Air Force Collision Avoidance System

Abstract: This case study analyzes the factors that influence trust and acceptance among users (in this case, test pilots) of the Air Force’s Automatic Ground Collision Avoidance System. Our analyses revealed that test pilots’ trust depended on a number of factors, including the development of a nuisance-free algorithm, designing fly-up evasive maneuvers consistent with a pilot’s preferred behavior, and using training to assess, demonstrate, and verify the system’s reliability. These factors are consistent with the literature on trust in automation and could lead to best practices for automation design, testing, and acceptance.

RedEye: Preventing Collisions Caused by Red-Light Running Scooters With Smartphones

Abstract: In this paper, we present a scooter collision avoidance system that can identify red-light runners (RLRs) at intersections. When the RLR behavior is detected, the system would advise the RLR to slow down immediately and warn nearby vehicles on the intersecting road in real time. In particular, we do not consider infrastructure-based solutions such as those utilizing a radar or a camera. This is because, in addition to high implementation costs, collisions can be only avoided at intersections where such infrastructure configurations are deployed. Instead, we advance an on-scooter solution using smartphones carried by scooter riders. Smartphones provide a useful platform that has a high penetration rate, more than sufficient computational power, inertial sensors to reflect the driving behavior, and the communication capability to transmit or receive information from other vehicles. In our system, we utilize a support vector machine and design an RLR classifier for learning and predicting RLR behaviors. The evaluation results show that our system is able to achieve over 70% recognition rates when distinguishing between RLR and non-RLR cases, as compared with approximately 80% recognition rates of the infrastructure-based (and higher cost) solution using a laser range finder (LADAR).

Collision detection and avoidance

Abstract: A collision avoidance system for an unmanned aerial vehicle (UAV) receives physical space data for a flight area and creates a virtual world model to represent the flight area by mapping the physical space data with a physics engine. The automatic collision avoidance system creates a virtual UAV model to represent the UAV in the virtual world model. The automatic collision avoidance system receives flight data for the UAV and determines a current position of the virtual UAV model within the virtual world model. The automatic collision avoidance system determines a predicted trajectory of the virtual UAV model within the virtual world model, and determines whether the predicted trajectory will result in a collision of the virtual UAV model with the virtual world model. The automatic collision avoidance system performs evasive actions by the UAV, in response to determining that the predicted trajectory will result in a collision.

Field Testing of a Cyclist Collision Avoidance System for Heavy Goods Vehicles

Abstract: This paper focuses on preventing collisions between cyclists and heavy goods vehicles (HGVs). A collision avoidance system, which is designed to avoid side-to-side collisions between HGVs and cyclists, is proposed. The cyclist's motion relative to the HGV is measured with an array of ultrasonic sensors. The detected distances from ultrasonic sensors are processed in real time to construct a smooth trajectory for the cyclist. The controller assumes constant acceleration and constant yaw rate for both the HGV and the cyclist and extrapolates the relative motion forward in time. The HGV's brakes are engaged if a collision is predicted. A prototype system was built and fitted onto a test truck. The proposed collision avoidance system was tested in real time and proved to be effective within certain speed ranges.

Integrated digital active phased array antenna and wingtip collision avoidance system

Abstract: A radar system to detect and track objects in three dimensions. The radar system including antennae, transmit, receive and processing electronics is all in a small, lightweight, low-cost, highly integrated package. The radar system uses a wide azimuth, narrow elevation radar pattern to detect objects and a Wi-Fi radio to communicate to one or more receiving and display units. One application may include mounting the radar system in an existing radome on an aircraft to detect and avoid objects during ground operations. Objects may include other moving aircraft, ground vehicles, buildings or other structures that may be in the area. The system may transmit information to both pilot and ground crew.

Vehicle collision avoidance system and track planning method thereof

Abstract: The invention discloses a vehicle collision avoidance system and a track planning method thereof. The system comprises a forward looking radar, a camera, a vehicle speed sensor, a yaw angular velocity sensor, a sideslip angle sensor, a signal processing module, an electronic control unit (ECU), a throttle controller, a steering controller and a braking controller. When a vehicle is driven, signals which are transmitted by all sensors through the signal processing module are collected in real time by the electronic control unit, the road condition and the vehicle condition of the vehicle at the moment are judged in real time, if hazardous conditions possibly occur, a continuous collision avoidance executable track is generated by the ECU according to a track planning program preset in the ECU, and the related signals are output to the throttle controller, the steering controller and the braking controller for corresponding operations, so that the hazardous conditions are avoided. According to the vehicle collision avoidance system, a driver can be assisted to operate the vehicle in case of an emergency, so that the active driving safety performance can be increased.

Design and Hardware-In-Loop Implementation of Collision Avoidance Algorithms for Heavy Commercial Road Vehicles

Abstract: An important aspect from the perspective of operational safety of heavy road vehicles is the detection and avoidance of collisions, particularly at high speeds. The development of a collision avoidance system is the overall focus of the research presented in this paper. The collision avoidance algorithm was developed using a sliding mode controller (SMC) and compared to one developed using linear full state feedback in terms of performance and controller effort. Important dynamic characteristics such as load transfer during braking, tyre-road interaction, dynamic brake force distribution and pneumatic brake system response were considered. The effect of aerodynamic drag on the controller performance was also studied. The developed control algorithms have been implemented on a Hardware-in-Loop experimental set-up equipped with the vehicle dynamic simulation software, IPG/TruckMaker®. The evaluation has been performed for realistic traffic scenarios with different loading and road conditions. The Ha...

Multi-vehicle coordination collision avoidance system and method based on vehicle-vehicle communication

Abstract: The invention discloses a multi-vehicle coordination collision avoidance system and method based on vehicle-vehicle communication, and belongs to the field of vehicle active safety. The system comprises an information collection module, a communication module, an information processing module, and a voice prompt module. The method provided by the invention comprises the steps: collecting the movement data of a target vehicle and a front vehicle in real time through the information collection module, comparing the safety distance of the target vehicle with the distance from the target vehicle to the front vehicle, and judging the danger state of the two vehicles; and starting to judge whether the target vehicle and the front vehicle meet a coordination collision avoidance condition of two vehicles or not when a danger signal is received. When the target vehicle and the front vehicle meet the coordination collision avoidance condition, the time of coordination collision avoidance of the two vehicles and the expected speed are calculated, and are transmitted to other coordination collision avoidance vehicles, thereby achieving a purpose that the vehicles at the same lane achieve the expected speed in a collision time range and move at a constant speed, and achieving the coordination collision avoidance.

Intelligent Forecasting Using Dead Reckoning With Dynamic Errors

Abstract: A method for integrating, processing, and analyzing sensing data from vehicle-mounted sensors for intelligent forecasting and decision-making is introduced. This dead reckoning with dynamic errors (DRWDEs) is for a large-scale integration of distributed resources and sensing data intervehicle collision avoidance system. This sensor fusion algorithm is introduced to predict the future trajectory of a vehicle. Current systems that predict a vehicle’s future trajectory, necessary in a network of collision avoidance systems, tend to have a lot of errors when the vehicles are moving in a nonstraight path. Our system has been designed with the objective of improving the estimations during curves. To evaluate this system, our research uses a Garmin 16HVS GPS sensor, an AutoEnginuity OBDII ScanTool, and a Crossbow three-axis accelerometer. Using Kalman filters (KFs), a dynamic noise covariance matrix merged together with an interacting multiple models (IMMs) system, our DRWDE produces the future position estimation of where the vehicle will be 3 s later in time. The ability to handle the change in noise, depending on unavailable sensor measurements, permits a flexibility to use any type of sensor and still have the system run at the fastest frequency available. Compared with a more common KF implementation that runs at the rate of its slowest sensor (1 Hz in our setup), our experimental results showed that our DRWDE (running at 10 Hz) yielded more accurate predictions (25%–50% improvement) during abrupt changes in the heading of the vehicle.

On the Validation of a UAV Collision Avoidance System Developed by Model-Based Optimization: Challenges and a Tentative Partial Solution

Abstract: The development of the new generation of airborne collision avoidance system ACAS X adopts a model-based optimization approach, where the collision avoidance logic is automatically generated based on a probabilistic model and a set of preferences. It has the potential for safety benefits and shortening the development cycle, but it poses new challenges for safety assurance. In this paper, we introduce the new development process and explain its key ideas using a simple collision avoidance example. Based on this explanation, we analyze the challenges it poses to safety assurance, with a particular focus on system validation. We then propose a Genetic-Algorithm-based approach that can efficiently search for undesired situations to help the development and validation of the system. We introduce an open-source tool we have developed to support this approach and demonstrate it on searching for challenging situations for ACAS XU.

A 3D dynamic Voronoi diagram-based path-planning system for UUVs

Abstract: This paper proposes a rapid path-planning and replanning system for Unmanned Underwater Vehicles (UUVs) that navigate in environments where subsea structures and other vehicles may be present. The proposed method is based on the Voronoi diagram, which is used to generate an initial set of connected waypoints (a roadmap) in the three-dimensional (3D) space, ensuring a certain clearance to avoid collisions with obstacles or grounding (e.g. collision with the ground). A 3D continuous path, composed by straight segments and circumference arcs, connects the aforementioned waypoints. If the vehicle encounters any moving or static obstacle and a collision risk is detected, the path is replanned online. In this context, an evaluation of the risk must be performed, and a list of traffic rules inspired by the International Regulations for Preventing Collisions at Sea (COLREGs, which are adopted for surface vessels), and by the Traffic and Collision Avoidance System (TCAS, which is adopted for aerial vehicles), is proposed for underwater vehicles. Those rules define the replanning procedure, so that an effective and safe collision avoidance maneuver can be performed whenever necessary. Simulations are performed on an subsea factory scenario, and results are presented to show the effectiveness of the proposed method.

Signal lamp-free intersection automobile emergency collision avoidance system

Abstract: The invention provides a signal lamp-free intersection automobile emergency collision avoidance system. The signal lamp-free intersection automobile emergency collision avoidance system comprises an environment perception module, a positioning navigation module, a central processing unit, a remote pre-warning module and a close-range brake module, wherein the central processing unit is connected with each of the environment perception module, the positioning navigation module, the remote pre-warning module and the near-range brake module; the environment perception module comprises a wireless communication system and a radar system, which are connected; the positioning navigation module comprises a vehicle running information acquisition system and a GPS positioning system, which are connected; the central processing unit comprises a driving intention judging system, a vehicle data reception/transmission system and a planning and decision making system, which are connected. According to the signal lamp-free intersection automobile emergency collision avoidance system, emergency brake can be carried out on vehicles under dangerous conditions, so as to avoid the vehicle collision accidents.

Optimized and Trusted Collision Avoidance for Unmanned Aerial Vehicles using Approximate Dynamic Programming (Technical Report)

Abstract: Safely integrating unmanned aerial vehicles into civil airspace is contingent upon development of a trustworthy collision avoidance system. This paper proposes an approach whereby a parameterized resolution logic that is considered trusted for a given range of its parameters is adaptively tuned online. Specifically, to address the potential conservatism of the resolution logic with static parameters, we present a dynamic programming approach for adapting the parameters dynamically based on the encounter state. We compute the adaptation policy offline using a simulation-based approximate dynamic programming method that accommodates the high dimensionality of the problem. Numerical experiments show that this approach improves safety and operational performance compared to the baseline resolution logic, while retaining trustworthiness.

Evaluation of Forward Collision Avoidance system using driver's hazard perception

Abstract: Evaluating the performance of Forward Collision Avoidance Technologies (FCATs) is essential in the early stage of the system testing. Drivers are the key interaction parts between the FCATs and vehicles, which play an important role in the performance evaluation. This paper proposes a practical method to evaluate the performance of FCATs by using a novel driver hazard perception measure, namely driver's risk response time. This measure describes the driver's awareness of potential collision risk, which is defined based on the Time-to-collision (TTC) and driver's brake response in a near-crash scenario. A two-month naturalistic driving experiment has been conducted using a vehicle equipped with one FCAT, i.e., Collision Mitigation Brake System (CMBS). An interval-based cumulative frequency data pretreatment method is used to extract near-crashes. Then, the hazard perception measure is computed in near-crashes with CMBS on and off, which can show the effectiveness of CMBS. The results demonstrate that CMBS is highly-positive in improving driver's hazard perception, especially in speed range between 45 km/h and 60 km/h. This fact is consistent with the expected effect of CMBS, which shows the proposed measure for hazard perception is capable of describing drivers' awareness of collision risk. In addition, this measure is applicable to assess the performance of FCATs during the function designing stage.

Collision Avoidance System using State Dependent Riccati Equation Technique: An Experimental Robustness Evaluation

Abstract: The capacity of a vehicle to avoid collisions is predominantly defined by the friction potential of the tyres. A robustness analysis of a Collision Avoidance System is executed by simulation and experiments for extreme changes in tyre friction. The collision avoidance controller which utilizes steering angle is based on the State Dependent Riccati Equation technique. This technique can consider nonlinearities and is fault tolerant by design. The controller has been extended with an estimation concept to obtain information of the road friction prior to execution of the steering action. The friction estimation concept is experimentally evaluated and the results show a reproducible reduction of the friction after entering a low friction road section. With a simulation study the control performance for varying conditions is elaborated, whereas experimental results are provided for extreme conditions of combined slip. The results demonstrate that the controller is capable to achieve collision avoidance for the variety of driving conditions with sufficient stability.

Optimized and trusted collision avoidance for unmanned aerial vehicles using approximate dynamic programming

Abstract: Safely integrating unmanned aerial vehicles into civil airspace is contingent upon development of a trustworthy collision avoidance system. This paper proposes an approach whereby a parameterized resolution logic that is considered trusted for a given range of its parameters is adaptively tuned online. Specifically, to address the potential conservatism of the resolution logic with static parameters, we present a dynamic programming approach for adapting the parameters dynamically based on the encounter state. We compute the adaptation policy offline using a simulation-based approximate dynamic programming method that accommodates the high dimensionality of the problem. Numerical experiments show that this approach improves safety and operational performance compared to the baseline resolution logic, while retaining trustworthiness.

Collision Avoidance with Task Constraints and Kinematic Limitations for Dual Arm Robots

Abstract: Human-robot interaction (HRI) is a key element for diffusion of robotised production. Clear advantages in flexibility and productivity are possible, when the two operators are free to interact, as they are endowed with complementary skills. To achieve such a goal, safety systems capable of coping with task and robot constraints have to be designed. In this paper, a collision avoidance strategy, tackling consistency with task constraints and robot kinematic limitations, is proposed. Robot joint velocities are selected with a QP optimisation problem, minimising the difference from evasive velocities, while respecting task constraints. Integration with an industrial controller is discussed as well, while the strategy is experimentally validated on a dual arm industrial robot prototype, working in close interaction with a human.

Autonomous braking failure management in pedestrian protection

Abstract: A collision avoidance system and method for a vehicle. The system includes a video camera and a distance sensor. The system includes a driver control, a vehicle control system, and a controller. The controller is communicatively coupled to the video camera, the distance sensor, the driver control, and the vehicle control system. The controller receives a first signal from the video camera indicative of the presence of the pedestrian and receives a second signal from the distance sensor indicative of the presence of the pedestrian. The controller determines a course deviation from a current path of travel of the vehicle and activates a timer. The controller resets the timer when the driver control receives an input from the driver that is above a threshold. When the driver input is below the threshold and the timer expires, the controller applies the course deviation using the vehicle control system.

A novel collision avoidance system for bicycles

Abstract: Crash statistics show that over 80% of motorist-bicycle crashes occur within 50 feet of traffic intersections. This paper focuses on the development of a collision avoidance system for bicycles for prediction and prevention of rear and side crashes at intersections. Cost, size and weight constraints highly limit the sensors and electronics that can be used on a bicycle and necessitate the development of new vehicle detection and tracking systems. Custom sonar and laser sensors and associated position estimation algorithms for tracking are developed. A custom sonar sensor with one sonar transmitter and two receivers is developed to estimate both the distance and angular orientation of vehicles on the sides of the bicycle. A custom single-target laser sensor on a rotating platform is developed to track longer distance vehicles. A model predictive control formulation is used to determine the real-time orientation of the rotating laser platform. Preliminary experimental data is presented to evaluate the performance of the side sonar system from a prototype instrumented bicycle. Simulation results are presented on the model predictive control for the rear vehicle tracking.

Fuzzy collision avoidance system for ships

Abstract: The paper discusses the problem of maritime traffic control. A model of the relative motion of two vessels is considered. An algorithm for the generation of alarms of various types in accordance with the verbal ship---ship danger level is considered. Navigation situations are separated into levels based on the ship's maneuvering intensity and time to collision. A fuzzy decision-making system about the motion's danger level that combines Mamdani and Sugeno fuzzy inference systems is proposed. The results of the numerical experiment that demonstrates the system's operation under standard conditions and the results of the system's field tests based on real ship traffic data in the waters adjacent to the port of Vladivostok are given.