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WO2025088161A1 - Système basé sur une analyse de risque pour protection d'infrastructure - Google Patents

Système basé sur une analyse de risque pour protection d'infrastructure Download PDF

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Publication number
WO2025088161A1
WO2025088161A1 PCT/EP2024/080297 EP2024080297W WO2025088161A1 WO 2025088161 A1 WO2025088161 A1 WO 2025088161A1 EP 2024080297 W EP2024080297 W EP 2024080297W WO 2025088161 A1 WO2025088161 A1 WO 2025088161A1
Authority
WO
WIPO (PCT)
Prior art keywords
risk
risk factor
collision
path
infrastructure
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/EP2024/080297
Other languages
English (en)
Inventor
Dawid GRADOLEWSKI
Adam Jaworski
Damian DZIAK
Damian KANIECKY
Wlodek KUSLESZA
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Bioseco SA
Original Assignee
Bioseco SA
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from GB2316489.0A external-priority patent/GB2634951A/en
Application filed by Bioseco SA filed Critical Bioseco SA
Publication of WO2025088161A1 publication Critical patent/WO2025088161A1/fr
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft
    • G08G5/50—Navigation or guidance aids
    • G08G5/58—Navigation or guidance aids for emergency situations, e.g. hijacking or bird strikes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G01S13/72—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
    • G01S13/723—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar by using numerical data
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/91—Radar or analogous systems specially adapted for specific applications for traffic control
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/933—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of aircraft or spacecraft
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/66—Tracking systems using electromagnetic waves other than radio waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/88—Lidar systems specially adapted for specific applications
    • G01S17/93—Lidar systems specially adapted for specific applications for anti-collision purposes
    • G01S17/933—Lidar systems specially adapted for specific applications for anti-collision purposes of aircraft or spacecraft
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft
    • G08G5/70—Arrangements for monitoring traffic-related situations or conditions
    • G08G5/72—Arrangements for monitoring traffic-related situations or conditions for monitoring traffic
    • G08G5/723—Arrangements for monitoring traffic-related situations or conditions for monitoring traffic from the aircraft
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G5/00—Traffic control systems for aircraft
    • G08G5/80—Anti-collision systems

Definitions

  • the invention relates to a system and method for mitigating the risk of collisions of a flying object with a protected infrastructure.
  • Examples of such infrastructure are wind farms and airports, which are exposed to a risk of collision with flying objects such as avifauna and drones.
  • Mono- and stereo-vision, radars and/or lidar sensors can be used to detect flying objects and hazard situations. Detection systems based on such sensors are often used in higher risk areas such as the airspace of wind farms and airports. Once a flying object is detected in a risk area, the relevant avoidance measures are activated.
  • a method for assessing the collision risk probability of an object and a protected infrastructure comprises:
  • the prediction uncertainty includes the predicted path.
  • the invention provides a method of assessing the risk which takes into account both the location of the protected infrastructure and also a predicted path. It provides a method of quantifying the risk of a collision.
  • the method may be used in particular with stereovision systems.
  • the position risk level can be visualised as a cone from the current position of the object to the plane covering the potential collision risk area.
  • the path risk level can be visualised as a cone from the current position of the object to plane of the potential collision risk area, the central axis of the cone is the predicted path, and the angle of the cone indicates the uncertainty.
  • the overall risk level can be illustrated as the overlap of these cones.
  • the position risk factor may be estimated based on a solid angle defined by the current position of the object and the protected infrastructure collision area.
  • the position risk factor may be based on the minimum distance for collision avoidance TT.
  • Q is the solid angle defined on the relation of the protected infrastructure collision area and the current position of the flying object and Qmax is the maximum possible solid angle defined for the worst case position related to the protected infrastructure collision area.
  • the position risk factor is related to an object coefficient based on the type of detected flying object in a given environment.
  • the path risk factor may be based on a solid angle defining the future path space based on trajectory prediction and prediction uncertainty.
  • the path risk factor may be given by: where H co ii is a binary coefficient based on whether the solid angle predicted path space intersects with the surface of the protected infrastructure; Qcrmax is a maximum solid angle for the worst case of confidence level of the estimate of tracking risk space and v
  • j con can be determined from: where AP n and P n P n+1 are vectors defined by the three points A, P n , P n +1.
  • a risk assessment system comprising a processor configured to carry out the steps as described above.
  • the system may further comprise an object detection system configured to detect objects and transmit data about the detected object to the risk assessment system.
  • a localisation and identification system is configured to identify and localised position of an object detected by the object detection system and transmit data about the object’s identity and localisation to the risk assessment system.
  • a tracking system configured to anticipate the position of the detected object from successive positions and transmit data about the predicted path of the detected object to the risk assessment system.
  • a decision making system is configured to make a decision based on the determined overall risk; and activating a collision avoidance system.
  • system further comprises one or more environmental sensors configured to detect environmental factors and configured to transmit data about the environmental factors to the risk assessment system.
  • Figure 1 depicts a block diagram of the system according to the invention
  • Figure 2 illustrates a top view of the collision situation with a view of cross section of the cons illustrating risk areas due to the object’s position and the tracking;
  • Figure 3 depicts top view of the collision situation illustrating a risk area due to the object’s position including all related quantities
  • Figure 4 depicts a front view of the collision situation illustrating the position of the flying object relative to the collision area of a fixed object, including all related quantities
  • Figure 5 depicts the detected path of a flying object and a cross-section of the cone depicting the predicted path.
  • Figure 1 depicts a block diagram of a proposed system in which an object detection unit detects objects using, for example, one or more of thermal images, infrared, vision, and/or stereo vision sensors. These are used to detect a moving object in the monitoring area.
  • the localisation and identification unit identifies the type of flying object and also its position in 3D space.
  • An object tracking unit depicts the object’s trajectory and also applies an algorithm to predict the future movement of the flying object.
  • Information from the detection unit, localisation and identification unit and object tracking unit is provided to a risk assessment unit.
  • An environmental sensors unit comprises such devices as anemometers, wind direction indicator, visibility and humidity sensor, rain sensor, temperature and/or pressure sensor.
  • the unit provides information about environmental conditions which can impact detection process and or objects path characteristics.
  • Data from the environmental sensors is transmitted into the risk assessment system.
  • the risk assessment system continually assesses the collision risk level, and the operation of the risk assessment system is described in more detail below.
  • the decision-making system interacts with the risk assessment system and the collision avoidance system to control the apparatus to avoid collisions.
  • P O bj The object risk probability associated with a moving object colliding with an infrastructure, P O bj is a product of two factors: P pos , the position risk factor dependent on the current positions and Ptrack the path risk factor associated with the anticipated path of the flying object. IPobj- IPpos X Ptrack
  • the risk area/space associated with the position can be visualised as a solid angle with an apex at the current position of the flying object and covering a possible collision area of the protected infrastructure.
  • the risk area/space associated with the tracking can be visualised as a solid angle/cone, the central axis of which is the predicted path and the angle of the cone is defined by the prediction uncertainty.
  • a shortest distance for collision avoidance PT is depicted. Based on a maximum known speed of the detected flying object, Vmax together with the longest stopping time for the turbine, T s to P , a shortest distance needed to activate collision avoidance system can be calculated:
  • Tstop may comprise both the reaction time and the latency time of the system. Based on the detected type of object, or species of bird, the known maximum speed for that particular species can be used.
  • the risk space associated with the position of the flying object is defined as the solid angle Q from a flying object position P n covering the space of possible collision of radius R.
  • the radius R is the radius over which the flying objects could have direct contact with the protected infrastructure.
  • r is the shortest distance between an object position P n (x n , y n , z n ) and the closest point of the fixed object A (x a , y a , 0) and this is depicted in Figure 4.
  • the position risk factor Pp 0S (Q, r, t) can be estimated using: where:
  • - Q is a solid angle (in steradian) corresponding to a potential collision space defined by segments connecting the object’s position point P n (x n , y n , z n ) with the closest point of the protected infrastructure A(x a , y a , 0) and the furthest point of the fixed object B(Xb, yb, 0);
  • - Qmax is a solid angle (in steradian) corresponding to the maximum possible collision space when the detected object's trajectory is perpendicular to the centre of collision surface at a distance TT.
  • - S is the surface area of a base of the cone defined by angle Q and the distance r between the flying object’s position P n (x n , y n , z n ) and its closest point on the fixed object A(x a , y a , 0);
  • - r is the distance between the flying object and the closest point of the protected infrastructure
  • the tracking risk factor Ptrack is based on previously detected positions Pn-i, Pn-2, Pn-3.... This is depicted in Figure 5.
  • the future flight trajectory may be predicted using a tracking algorithm such as a Kalman filter, Multiple Hypothesis Tracking or other methods.
  • the predicted flight trajectory forms the axis of a cone and the uncertainty defines a cone around the axis and these are depicted in Figure 5.
  • the tracking risk factor can then be calculated as: where:
  • - Hcoii is a binary coefficient (0 or 1 ) based on whether the tracking path intersects with the protected infrastructure
  • - ijicon is a collision angle between the predicted collision direction and a plane of protected infrastructure
  • Qcrmax is the maximum solid angle for the worst case accuracy tracking for a particular site/process. This represents the prediction worst case uncertainty for the highest confidence level.
  • Qcrmax is estimated from the statistical properties of the prediction process.
  • N points in 3D space may be a multiple . It could be a 3o or 4o confidence level.
  • H O bj a heuristic object coefficient which is determined for a particular situation.
  • the value of H O bj is specific to the particular type of flying object and the particular site i.e. a different species of bird may have a different Hobj and the same species of bird at a different site may have a different Hobj. Hobj is therefore customised for different sites and may be amended over time based on gathered data.
  • the factors P pos and Ptrack would be:
  • the object collision risk probability Pobject related the object position and its trajectory has been discussed above.
  • environmental conditions such as wind speed and direction can impact birds’ behaviour.
  • the system performance may be affected due to visibility, humidity, rain, temperature, air pressure and other factors.
  • There is also a risk factor associated with environmental factors such as the wind speed and direction.
  • the overall strike risk probability Pstrike could be described as:
  • P strike aPobjecC*"[3Penvironment
  • the coefficients a and [3 define the impacts of the object and the environment components on overall collision risk probability and are site specific. These coefficients can be determined heuristically and may be adjusted over time using, for example, a self-learning algorithm.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • General Physics & Mathematics (AREA)
  • Electromagnetism (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Aviation & Aerospace Engineering (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

Selon l'invention, il existe un procédé d'évaluation de la probabilité de risque de frappe d'un objet volant et d'une infrastructure protégée, le procédé comprenant la détection d'une position de l'objet volant à des instants successifs, la prédiction d'un trajet sur la base de la position sur la pluralité de positions détectées, la détermination d'un facteur de risque de position sur la base de la position actuelle liée à l'infrastructure protégée et la détermination d'un risque de frappe global sur la base d'une combinaison de deux facteurs du facteur de risque de trajet et du facteur de risque de position.
PCT/EP2024/080297 2023-10-26 2024-10-25 Système basé sur une analyse de risque pour protection d'infrastructure Pending WO2025088161A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
PL44651123 2023-10-26
PLP.446511 2023-10-26
GB2316489.0 2023-10-27
GB2316489.0A GB2634951A (en) 2023-10-26 2023-10-27 A risk analysis based system for infrastructure protection

Publications (1)

Publication Number Publication Date
WO2025088161A1 true WO2025088161A1 (fr) 2025-05-01

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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009102001A1 (fr) * 2008-02-15 2009-08-20 The Tokyo Electric Power Company, Incorporated Système de recherche d'oiseau, procédé de recherche d'oiseau et programme d'ordinateur
US8742977B1 (en) * 2012-03-02 2014-06-03 Gregory Hubert Piesinger Wind turbine bird strike prevention system method and apparatus
US9583012B1 (en) * 2013-08-16 2017-02-28 The Boeing Company System and method for detection and avoidance
JP6316638B2 (ja) * 2014-04-04 2018-04-25 アジア航測株式会社 監視装置、監視方法および監視プログラム
US20190325254A1 (en) * 2014-08-21 2019-10-24 Identiflight International, Llc Avian Detection Systems and Methods
JP7231113B2 (ja) * 2020-03-25 2023-03-01 日本電気株式会社 可視化制御装置、可視化システム、可視化制御方法およびコンピュータプログラム
ES1303416U (es) * 2020-06-29 2023-09-29 3D Observer Project S L Sistema para detectar avifauna en parques eolicos

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2009102001A1 (fr) * 2008-02-15 2009-08-20 The Tokyo Electric Power Company, Incorporated Système de recherche d'oiseau, procédé de recherche d'oiseau et programme d'ordinateur
US8742977B1 (en) * 2012-03-02 2014-06-03 Gregory Hubert Piesinger Wind turbine bird strike prevention system method and apparatus
US9583012B1 (en) * 2013-08-16 2017-02-28 The Boeing Company System and method for detection and avoidance
JP6316638B2 (ja) * 2014-04-04 2018-04-25 アジア航測株式会社 監視装置、監視方法および監視プログラム
US20190325254A1 (en) * 2014-08-21 2019-10-24 Identiflight International, Llc Avian Detection Systems and Methods
JP7231113B2 (ja) * 2020-03-25 2023-03-01 日本電気株式会社 可視化制御装置、可視化システム、可視化制御方法およびコンピュータプログラム
ES1303416U (es) * 2020-06-29 2023-09-29 3D Observer Project S L Sistema para detectar avifauna en parques eolicos

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