[go: up one dir, main page]

WO2024115473A1 - Procédé, dispositif de commande et programme informatique de détermination basée sur la position d'une région d'intérêt et support de stockage lisible par ordinateur - Google Patents

Procédé, dispositif de commande et programme informatique de détermination basée sur la position d'une région d'intérêt et support de stockage lisible par ordinateur Download PDF

Info

Publication number
WO2024115473A1
WO2024115473A1 PCT/EP2023/083340 EP2023083340W WO2024115473A1 WO 2024115473 A1 WO2024115473 A1 WO 2024115473A1 EP 2023083340 W EP2023083340 W EP 2023083340W WO 2024115473 A1 WO2024115473 A1 WO 2024115473A1
Authority
WO
WIPO (PCT)
Prior art keywords
motor vehicle
interest
lane
determined
friedrichshafen
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.)
Ceased
Application number
PCT/EP2023/083340
Other languages
German (de)
English (en)
Inventor
Johannesneue STILLER
Ahmed ZIKRY
Simon DEFATSCH
Flavio DE MELO
Kyle Retan
Athanasios TASOGLOU
Bob BÖGGEMANN
John SPRUIT
Joris DOMHOF
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.)
ZF Friedrichshafen AG
Original Assignee
ZF Friedrichshafen AG
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
Application filed by ZF Friedrichshafen AG filed Critical ZF Friedrichshafen AG
Publication of WO2024115473A1 publication Critical patent/WO2024115473A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

Links

Classifications

    • 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
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F1/00—Metallic powder; Treatment of metallic powder, e.g. to facilitate working or to improve properties
    • B22F1/17—Metallic particles coated with metal
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F7/00—Manufacture of composite layers, workpieces, or articles, comprising metallic powder, by sintering the powder, with or without compacting wherein at least one part is obtained by sintering or compression
    • B22F7/06—Manufacture of composite layers, workpieces, or articles, comprising metallic powder, by sintering the powder, with or without compacting wherein at least one part is obtained by sintering or compression of composite workpieces or articles from parts, e.g. to form tipped tools
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F7/00—Manufacture of composite layers, workpieces, or articles, comprising metallic powder, by sintering the powder, with or without compacting wherein at least one part is obtained by sintering or compression
    • B22F7/06—Manufacture of composite layers, workpieces, or articles, comprising metallic powder, by sintering the powder, with or without compacting wherein at least one part is obtained by sintering or compression of composite workpieces or articles from parts, e.g. to form tipped tools
    • B22F7/08—Manufacture of composite layers, workpieces, or articles, comprising metallic powder, by sintering the powder, with or without compacting wherein at least one part is obtained by sintering or compression of composite workpieces or articles from parts, e.g. to form tipped tools with one or more parts not made from powder
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23B—TURNING; BORING
    • B23B51/00—Tools for drilling machines
    • B23B51/04—Drills for trepanning
    • B23B51/0417—Drills for trepanning including chamfer or spot bore cutter
    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23C—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; SURFACE TREATMENT OF METALLIC MATERIAL BY DIFFUSION INTO THE SURFACE, BY CHEMICAL CONVERSION OR SUBSTITUTION; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL
    • C23C24/00—Coating starting from inorganic powder
    • C23C24/08—Coating starting from inorganic powder by application of heat or pressure and heat
    • C23C24/10—Coating starting from inorganic powder by application of heat or pressure and heat with intermediate formation of a liquid phase in the layer
    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23C—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; SURFACE TREATMENT OF METALLIC MATERIAL BY DIFFUSION INTO THE SURFACE, BY CHEMICAL CONVERSION OR SUBSTITUTION; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL
    • C23C28/00—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D
    • C23C28/02—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D only coatings only including layers of metallic material
    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23C—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; SURFACE TREATMENT OF METALLIC MATERIAL BY DIFFUSION INTO THE SURFACE, BY CHEMICAL CONVERSION OR SUBSTITUTION; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL
    • C23C28/00—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D
    • C23C28/02—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D only coatings only including layers of metallic material
    • C23C28/021—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D only coatings only including layers of metallic material including at least one metal alloy layer
    • C—CHEMISTRY; METALLURGY
    • C23—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; CHEMICAL SURFACE TREATMENT; DIFFUSION TREATMENT OF METALLIC MATERIAL; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL; INHIBITING CORROSION OF METALLIC MATERIAL OR INCRUSTATION IN GENERAL
    • C23C—COATING METALLIC MATERIAL; COATING MATERIAL WITH METALLIC MATERIAL; SURFACE TREATMENT OF METALLIC MATERIAL BY DIFFUSION INTO THE SURFACE, BY CHEMICAL CONVERSION OR SUBSTITUTION; COATING BY VACUUM EVAPORATION, BY SPUTTERING, BY ION IMPLANTATION OR BY CHEMICAL VAPOUR DEPOSITION, IN GENERAL
    • C23C28/00—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D
    • C23C28/02—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D only coatings only including layers of metallic material
    • C23C28/023—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D only coatings only including layers of metallic material only coatings of metal elements only
    • C23C28/025—Coating for obtaining at least two superposed coatings either by methods not provided for in a single one of groups C23C2/00 - C23C26/00 or by combinations of methods provided for in subclasses C23C and C25C or C25D only coatings only including layers of metallic material only coatings of metal elements only with at least one zinc-based layer
    • 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
    • G01S17/931—Lidar systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • 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
    • G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B22—CASTING; POWDER METALLURGY
    • B22F—WORKING METALLIC POWDER; MANUFACTURE OF ARTICLES FROM METALLIC POWDER; MAKING METALLIC POWDER; APPARATUS OR DEVICES SPECIALLY ADAPTED FOR METALLIC POWDER
    • B22F5/00—Manufacture of workpieces or articles from metallic powder characterised by the special shape of the product
    • B22F2005/001—Cutting tools, earth boring or grinding tool other than table ware
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B23—MACHINE TOOLS; METAL-WORKING NOT OTHERWISE PROVIDED FOR
    • B23B—TURNING; BORING
    • B23B2226/00—Materials of tools or workpieces not comprising a metal
    • B23B2226/57—Plasterboard, i.e. sheetrock
    • 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
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/932—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles using own vehicle data, e.g. ground speed, steering wheel direction
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/16—Anti-collision systems
    • G08G1/167—Driving aids for lane monitoring, lane changing, e.g. blind spot detection

Definitions

  • the invention relates to a method, a control unit and a computer program for position-based determination of an area of interest located in a lane of a roadway in the direction of travel in front of a motor vehicle, as well as a computer-readable storage medium on which the computer program is stored.
  • An automatic emergency braking system (Advanced Emergency Braking System (AEBS)) is used to avoid or mitigate collisions in an autonomous motor vehicle.
  • the autonomous motor vehicle can, for example, be a transport vehicle, for example a passenger transport vehicle.
  • the motor vehicle can be a means of mass transportation.
  • the motor vehicle can, for example, be referred to as a “Group Rapid Transport (GRT)” vehicle.
  • GRT Group Rapid Transport
  • the motor vehicle can, for example, be configured so that, with a few exceptions, it essentially drives on the roadway, whereby the roadway can be reserved for the motor vehicle and other similar motor vehicles, for example other GRTs.
  • the roadway can be referred to as a "segregated lane”.
  • the motor vehicle can accordingly be configured so that it does not drive on any other lanes apart from the lanes reserved for these types of motor vehicles.
  • the exceptions can include, for example, bus stops, parking spaces or charging stations.
  • An AEBS method on which the AEBS system is based can be roughly divided into five or six steps:
  • a first step one or more objects in the direction of travel in front of the motor vehicle are detected by means of at least one sensor arranged in the motor vehicle.
  • the sensor can be, for example, a radar sensor or a lidar sensor.
  • the object or objects can be detected by means of two or more sensors, in particular by means of one or more radar sensors and/or by means of one or more lidar sensors.
  • During detection in particular Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 the objects that are in the field of view of the corresponding sensor are detected.
  • corresponding sensor data is generated, in particular radar data or lidar data.
  • the data can each be representative of the positions and/or speeds of the corresponding objects, whereby the positions and/or speeds can be identified by Cartesian coordinates.
  • the radar data and the lidar data are merged to form the sensor data.
  • an area of interest also known as a region of interest (ROI)
  • ROI region of interest
  • the area of interest is determined so that it lies on the road in the direction of travel in front of the motor vehicle. Furthermore, the area of interest can be determined in such a way that it is highly likely that an object that is not in the area of interest does not pose a danger to the motor vehicle.
  • the sensor data is used to check whether one or more of the detected objects are in the area of interest or not. If one or more of the detected objects are not in the area of interest, these objects can be excluded when the AEBS process is continued.
  • it is checked whether the objects that are not excluded in the third step and are therefore in the area of interest pose a danger to the motor vehicle. If one or more of the detected objects in the area of interest do not pose a danger to the motor vehicle, these objects can be excluded when the AEBS process is continued.
  • braking in other words deceleration, for example an emergency brake, of the motor vehicle is initiated in such a way that a collision of the motor vehicle with the object is avoided or at least reduced if the object poses a threat to the motor vehicle.
  • braking in other words deceleration, for example an emergency brake, of the motor vehicle is initiated in such a way that a collision of the motor vehicle with the object is avoided or at least reduced if the object poses a threat to the motor vehicle.
  • the area of interest is determined accurately. It is therefore an object of the invention to provide a method, a control device and a computer program for position-based determination of an area of interest that is located on a lane of a road in the direction of travel in front of a motor vehicle, which contribute to the area of interest being determined particularly accurately and/or suitably.
  • One aspect of the invention relates to a method for position-based determination of an area of interest that is located on a lane of a road in the direction of travel in front of a motor vehicle.
  • the method comprises: receiving position data that are representative of a current vehicle position of the motor vehicle; determining reference point positions of reference points along the lane, the reference points being representative of a course of the lane in the direction of travel in front of the motor vehicle, depending on the position data using a lane lookup table in which the reference point positions are assigned to the reference points; and determining the area of interest depending on the reference points and depending on a width of the motor vehicle.
  • One aspect of the invention relates to a control device for position-based determination of the area of interest that is located on the lane in the direction of travel in front of the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Motor vehicle, the control unit comprising: a memory unit for storing the position data, the lane lookup table and the width of the motor vehicle; and a processor that is configured to process the method explained above and below.
  • the control unit can be arranged in the motor vehicle, for example.
  • the control unit can be communicatively coupled to an external unit for retrieving and/or receiving the sensor data, the position data, the speed data and/or other data, for example via the Internet with a server on which the corresponding data is stored.
  • One aspect of the invention relates to a computer program for position-based determination of the area of interest that is located in the lane in the direction of travel in front of the motor vehicle, the computer program having instructions that cause the method explained above and below to be processed when they are executed by the control unit.
  • One aspect of the invention relates to a computer-readable medium on which the computer program is stored. In most driving situations, in particular when the motor vehicle is moving along the road at medium or high speed and neither a stop nor a turn is initiated, the position-based determination of the region of interest provides particularly accurate results, in particular compared to a speed-based determination of the region of interest.
  • the region of interest in these driving situations can be adapted more precisely to the road, in particular the corresponding lane, by the position-based determination than by the speed-based determination. Therefore, the method can be configured such that the position-based determination of the region of interest is the standard for determining the region of interest.
  • the region of interest can also be referred to as a "region of interest" (ROI).
  • ROI region of interest
  • the region of interest can be the region of the road that the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Motor vehicle is likely to be driven over in the near future. In this case, the area of interest is in the same lane of the road as the motor vehicle.
  • the area of interest can also be in another lane of the road, for example in a lane that borders the lane on which the motor vehicle is traveling. This can help to detect objects at an early stage that could pose a danger to the motor vehicle in the near future, for example if the object is in the other lane and is approaching the lane on which the motor vehicle is traveling.
  • the fact that the area of interest is determined on a position-based basis means that the area of interest is essentially determined depending on the position data. In particular, this can mean that other data can also be taken into account in the position-based determination of the area of interest, such as a lane of the road on which the motor vehicle is currently traveling, a shape of the motor vehicle and/or a width of the area of interest to be determined.
  • the fact that the area of interest is determined based on position can also mean that the area of interest is determined at least partially depending on the speed data, with the speed data only serving as a supplement in the position-based determination of the area of interest, for example to restrict the area of interest determined based on the position data, for example with regard to its length.
  • the method can be configured so that the position-based determination of the area of interest is the standard for determining the area of interest.
  • the position data that are representative of the vehicle position of the motor vehicle can be generated by a position sensor, transmitted to the control unit and received by the control unit.
  • the position sensor can be a GPS receiver, for example.
  • the position data can be representative of an orientation of the motor vehicle, in other words the motor vehicle orientation.
  • the orientation of the motor vehicle can be used, for example, to determine which lane of the road the motor vehicle is currently traveling in, as explained in more detail below. If necessary Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 the orientation can be generated, for example, by means of an orientation sensor, a magnetic sensor, for example a compass, GPS, and/or by means of an inertial measurement unit (IMU), transmitted to the control unit and received by the control unit.
  • the reference point positions of the reference points can be specified, for example, by GPS coordinates in the lane lookup table.
  • the reference point positions and optionally the reference points can be provided with indices in the lane lookup table and ordered accordingly.
  • the lane lookup table can have an index for each reference point and a reference point position of the reference point assigned to the index, for example within a row of the lane lookup table.
  • An order of the indices can correspond to an order of the reference points on the lane in the real world.
  • the lane lookup table can have lane orientations that are assigned to the corresponding reference points and that are representative of how the lane is oriented at the respective reference point. If necessary, the lane orientation can be specified, for example, as an absolute lane angle, for example in relation to one or more cardinal directions.
  • the lane lookup table can have lane lengths that are assigned to the corresponding reference points and that are representative of how long the lane is starting from a starting point of the corresponding lane at the respective reference point.
  • the motor vehicle can, for example, have a separate lane lookup table for each lane on which the motor vehicle moves, so that the motor vehicle can determine the area of interest on each lane based on position.
  • the corresponding lane lookup tables can be stored in the motor vehicle, for example in the memory unit of the control unit of the motor vehicle, or made available to the motor vehicle via a communication connection, for example via the Internet.
  • the lane lookup tables can be created in advance depending on the real lanes by measuring the corresponding lanes and extracting the relevant measurement results and storing them in the corresponding lane lookup tables.
  • the lane lookup tables can also contain information about one or more curves, for example corresponding curvature data, for example in the form of the lane orientations assigned to the corresponding reference points.
  • the width of the motor vehicle is normally fixed depending on and/or corresponds to an actual width of the motor vehicle. The width can be stored in the storage unit, for example.
  • the autonomous motor vehicle can be a transport vehicle, for example a passenger transport vehicle.
  • the motor vehicle can be a means of mass transportation.
  • the motor vehicle can be referred to, for example, as a “group rapid transport vehicle”.
  • the motor vehicle can, for example, be configured so that it essentially drives on the roadway with a few exceptions, whereby the roadway can be reserved for the motor vehicle and other similar motor vehicles, for example other GRTs.
  • the roadway can be referred to as a "segregated lane”.
  • the motor vehicle can accordingly be configured so that it does not drive on any other lanes apart from the lanes reserved for these types of motor vehicles.
  • the exceptions can include, for example, bus stops, parking spaces or charging stations.
  • the control signal can be representative of the braking of the motor vehicle.
  • a driving line on the lane is determined depending on the specified reference points.
  • the reference point positions of the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Reference points can be specified in the lane lookup table, for example, so that the driving line runs in the middle of the corresponding lane.
  • the driving line can, for example, run parallel to a center line of the roadway and/or parallel to one or both side edges of the roadway.
  • the driving line is determined by connecting the reference points.
  • the reference points can be selected so that they have a distance of, for example, 1 cm to 20 cm, for example 5 cm to 15 cm, for example 10 cm, along the driving line.
  • the region of interest is determined depending on the reference points and depending on the width of the motor vehicle by defining a first outer boundary of the region of interest on one side of the driving line and a second outer boundary of the region of interest on the other side of the driving line, wherein the outer boundaries each have a predetermined distance from the driving line that corresponds to at least half the width of the motor vehicle, and wherein the outer boundaries each run parallel to the driving line.
  • the outer boundaries are determined by determining a first outer point for the first outer boundary and a second outer point for the second outer boundary for each of the reference points, the outer points are determined such that they each have the predetermined distance from the corresponding reference point and that they each lie on a straight line that runs through the corresponding reference point and that is perpendicular to a tangent to the driving line at the corresponding reference point, and then the first outer points are connected to one another to form the first outer boundary and the second outer points are connected to one another to form the second outer boundary.
  • the predetermined distance is set to correspond to the width of the motor vehicle plus an additional tolerance range.
  • the width of the region of interest can be specified so that it is slightly larger than the width of the motor vehicle.
  • the additional tolerance range can contribute to the safety of the motor vehicle.
  • the additional tolerance range can be, for example, between 1 cm and 20 cm, for example between 5 cm and 15 cm, for example approximately 15 cm.
  • the position data are representative of a front position of a front of the motor vehicle; and the region of interest is determined such that it extends from the front in the direction of travel.
  • the method comprises: receiving speed data that is representative of a current speed of the motor vehicle; and determining the length of the region of interest depending on the current speed.
  • the speed data can be generated by a speed sensor arranged in the motor vehicle, transmitted to the control unit and received by the control unit.
  • the speed data can be retrieved from the storage unit of the motor vehicle, for example from the storage unit of the control unit of the motor vehicle, and received by the processor of the control unit.
  • the length can be determined, for example, depending on the speed and a collision time duration.
  • the collision time duration can be determined, for example, by means of a method for avoiding or reducing a collision of an autonomous motor vehicle with an object, as explained in more detail below.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Alternatively, the length can be determined depending on the speed using a length lookup table in which suitable lengths of the area of interest are assigned to different speeds.
  • the length can, for example, extend from the front of the motor vehicle to a longitudinal end of the area of interest.
  • the number of reference points required to determine the area of interest can then be determined. The greater the length, the more reference points are required to determine the area of interest.
  • the roadway has the lane and at least one other lane.
  • the roadway has a separate lane for each direction of travel.
  • the roadway has two lanes, one extending in one direction and the other extending in the opposite direction.
  • the region of interest can be determined to be located in the lane in which the motor vehicle is traveling.
  • the lane in which the motor vehicle is traveling can be referred to as the first lane and the other lane can be referred to as the second lane.
  • the region of interest is thus determined to be located in the first lane.
  • the roadway has the lane and at least one other lane; and the region of interest is determined to be located in one of the lanes that is next to the lane in which the motor vehicle is traveling. In this case, the region of interest is thus determined to be located in the second lane.
  • One object of the invention is achieved by a method for determining whether an object is located in an area of interest in the direction of travel in front of a motor vehicle, comprising: receiving sensor data that are representative of an object that is located in the direction of travel in front of the motor vehicle; position-based determination of the region of interest as explained above; determining two Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 or more triangles that together cover the area of interest using external points by means of which the outer boundaries of the area of interest are determined; and sequentially checking whether the object is located in one or more of the triangles until all triangles have been checked.
  • the area of interest can be divided into triangles that together cover the area of interest, in particular exactly cover it, i.e.
  • the sensor data can be generated by at least one sensor.
  • the sensor can be a radar or a lidar sensor, for example.
  • the sensor data can alternatively be generated by two or more sensors, wherein the sensors can have at least one radar and at least one lidar sensor, for example.
  • the sensor data can be transmitted from the sensor(s) to the control unit that carries out the method and received by the control unit.
  • the outer boundaries have the first outer boundary and the second outer boundary; the triangles have first triangles and second triangles; the first triangles are each determined by means of two first outer points on the first outer boundary and a second outer point on the second outer boundary; the second triangles are each determined using two second outer points on the second outer boundary and a first outer point on the first outer boundary; and the first and second Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 External points are chosen to determine the triangles so that the triangles do not overlap one another and completely, in particular exactly, cover the area of interest. This helps to ensure that the triangles do not protrude beyond the area of interest and that the entire area of interest is exactly and completely covered by the triangles.
  • the computer-readable medium can be a hard disk, a USB storage device, a RAM, a ROM, an EPROM or a FLASH memory.
  • the computer-readable medium can also be a data communication network, such as the Internet, which enables the download of a program code.
  • Fig.1 shows an embodiment of an autonomous motor vehicle.
  • Fig.2 shows a flow chart of an embodiment of a general method for avoiding or reducing a collision of the autonomous motor vehicle with an object.
  • Fig.3 shows a flow chart of an embodiment of a special method for avoiding or reducing a collision of the autonomous motor vehicle with the object.
  • Fig.4 shows a display on which an example driving situation is shown.
  • Fig.5 shows a flow chart of an embodiment of a special method for avoiding or reducing a collision of the autonomous motor vehicle with the object.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30
  • Fig.6 shows a top view of an exemplary driving situation, of the motor vehicle and of an area of interest in front of the motor vehicle.
  • Fig.7 shows a flow chart of an embodiment of a method for position-based determination of an area of interest.
  • Fig.8 shows a flow chart of an embodiment of a method for determining whether the object in the area of interest is in front of the motor vehicle in the direction of travel.
  • Fig.9 shows a vehicle model of the motor vehicle for speed-based determination of the area of interest.
  • Fig.10 shows a schematic diagram to explain the speed-based determination of the area of interest.
  • Fig.11 shows a flow chart of an embodiment of a method for speed-based determination of the area of interest.
  • Fig.12 shows an example of two driving lines for the motor vehicle.
  • Fig.13 shows a flow chart of an embodiment of a method for determining a probability with which the motor vehicle is in a lane of a roadway.
  • Fig.14 shows a diagram in which several exemplary courses of time periods that pass until the motor vehicle collides with the object are shown as a function of a speed of the motor vehicle.
  • Fig.15 shows a flow chart of an embodiment of a special method for avoiding or reducing the collision of the autonomous motor vehicle with the object.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30
  • Fig.16 shows a diagram in which several exemplary lengths of the area of interest are shown as a function of the speed of the motor vehicle.
  • Fig.17 shows a flow chart of an embodiment of a special method for avoiding or reducing the collision of the autonomous motor vehicle with the object.
  • the reference symbols used in the figures and their meaning are listed in summary form in the list of reference symbols.
  • General Fig.1 shows an embodiment of an autonomous motor vehicle 20.
  • the motor vehicle 20 has a passenger cabin 21 for accommodating one or more passengers (not shown), a door 22 for entering or exiting the passenger cabin 21, wheels 23 for moving the motor vehicle 20, a braking device 24 for braking, in other words decelerating, the motor vehicle 21, and a control unit 25 for operating the motor vehicle 22.
  • the motor vehicle 20 can be configured such that both the wheels 23 on a front axle of the motor vehicle 20 and the wheels 23 on a rear axle of the motor vehicle 20 are steerable, in particular pivotable relative to the corresponding axle.
  • the autonomous motor vehicle 20 can be, for example, a transport vehicle, for example a passenger transport vehicle.
  • the motor vehicle 20 can be a means of mass transportation.
  • the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 The motor vehicle 20 can be referred to, for example, as a “Group Rapid Transport vehicle” (“GRT” for short).
  • the motor vehicle 20 can, for example, be configured so that it essentially drives on a predetermined lane 32 (see Figure 4), with a few exceptions in which special driving maneuvers are necessary or at least carried out.
  • the lane 32 can be reserved for the motor vehicle 20 and other similar motor vehicles 20, for example other GRTs.
  • the lane 32 can be referred to as a “segregated lane”.
  • the motor vehicle 20 can accordingly be configured so that it does not drive on any lanes other than the lanes 32 reserved for this type of motor vehicle.
  • the exceptions can include, for example, bus stops, parking spaces or charging stations.
  • the motor vehicle 20 may perform the sideways movement at or near these exceptions.
  • the roadway 32 may, for example, have a first lane 34 (see Figure 4) and a second lane 36 adjacent to the first lane 34.
  • the first lane 34 may be intended for a first direction of travel of the motor vehicle 20
  • the second lane 36 may be intended for a second direction of travel of the motor vehicle 20.
  • each of the lanes 34, 36 may be used by the motor vehicle 20 in both directions.
  • the motor vehicle 20 may be a first motor vehicle 20 that can move in both directions on the first lane 34, and a second motor vehicle 20 can move in both directions on the second lane 36.
  • the control unit 25 can, for example, have or form a vehicle control of the motor vehicle 20.
  • the control unit 25 has a memory unit 26 for storing data and a processor 27 for processing the data.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 The control unit 25 can be communicatively coupled to an external unit (not shown) for retrieving and/or receiving sensor data, position data, speed data and/or other data, for example via the Internet to a server on which the corresponding data is stored.
  • the control unit 22 can be configured to help avoid or reduce a collision of the motor vehicle 20 traveling on the roadway 32 with an object 50 (see Figure 4).
  • the storage unit 26 serves to store sensor data, in particular radar data and/or lidar data, position data, speed data and/or one or more time threshold values
  • the processor 27 is configured in this context to execute a method for avoiding or reducing the collision of the motor vehicle 20 traveling on the roadway 32 with the object 50.
  • the time threshold values can be stored in the storage unit 26 in the form of a time threshold lookup table in which predetermined speeds of the motor vehicle 20 are assigned to corresponding time threshold values.
  • the control unit 22 can be configured to generate a control signal for braking the motor vehicle 20, wherein the control signal is representative of the braking of the motor vehicle 20.
  • control signal can be configured such that the braking device 24 initiates the braking of the motor vehicle 20 in response to receiving the control signal.
  • the braking device 24 can be a hardware that communicates with the control unit 22 and with mechanical and/or hydraulic brakes (not shown) of the motor vehicle 20.
  • the braking device 24 can be implemented as software and processed by the control unit 22.
  • the control unit 22 can be configured to determine a region of interest 60 (see Figure 6) that is located on a lane, for example the first lane 34, in the direction of travel in front of the motor vehicle 20, based on position.
  • the storage unit 26 is used to store sensor data, positions Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 tion data and / or speed data, and the processor 27 is configured in this context to process a method for position-based determination of the area of interest 60.
  • the control unit 22 can be configured to determine the area of interest 60 based on speed.
  • the storage unit 26 serves to store sensor data, position data and / or speed data
  • the processor 27 is configured in this context to process a method for speed-based determination of the area of interest 60.
  • the control unit 22 can be configured to determine a probability with which the motor vehicle 20 is located in one of the lanes 34, 36 of the roadway 32.
  • the storage unit 26 serves to store position data and at least one lane lookup table which is assigned to the corresponding lane 34, 36 and in which reference points 94, 96 (see Figure 14) are assigned corresponding reference point positions, wherein the reference points 94, 96 are representative of a course of the corresponding lane 34, 36 in the direction of travel in front of the motor vehicle 20, and the processor 27 is configured in this context to execute a method for determining the probability.
  • Figure 2 shows a flow chart of an embodiment of a general method for avoiding or reducing a collision of the autonomous motor vehicle 20 with the object 50 (see Figure 4).
  • sensor data can be received.
  • the sensor data are representative of the object 50 that is located in front of the motor vehicle 20 in the direction of travel.
  • the sensor data can be generated by at least one sensor (not shown).
  • the sensor can be, for example, a radar or a lidar sensor.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 The sensor data can alternatively be generated by two or more sensors, wherein the sensors can, for example, have at least one radar and at least one lidar sensor.
  • the sensor data can comprise radar data or lidar data, or the radar data and the lidar data can be merged to form the sensor data.
  • the sensor data can be transmitted from the sensor(s) to the control unit 25 of the motor vehicle 20 that carries out the method and received by the control unit 25.
  • the sensor data can be in the form of a list that contains all objects 50 in front of the motor vehicle 20 that are detected by the sensor(s).
  • the radar data can be in the form of a radar list in which the objects 50 detected by radar are stored as radar objects.
  • the lidar data can be in the form of a lidar list in which the objects 50 detected by means of lidars are stored as lidar objects.
  • the sensor data can be fused, in particular if the radar data and the sensor data are received in step S2. If necessary, the fused sensor data can be in the form of a fusion list, which can have fusion objects, radar-only objects and/or lidar-only objects, as explained in more detail below.
  • the region of interest 60 which is located on the roadway 32 in the direction of travel in front of the motor vehicle 20, can be determined. The region of interest 60 can be determined, for example, depending on position data that are representative of a current vehicle position of the motor vehicle 20 and/or depending on speed data that are representative of a current speed of the motor vehicle 20. The region of interest 60 can also be referred to as a "region of interest" (ROI).
  • ROI region of interest
  • the region of interest 60 can be the area of the roadway 32 that the motor vehicle 20 is expected to drive over in the near future. In this case, the region of interest 60 is located in the same lane 34, 36 of the roadway 32 as the motor vehicle 20. However, the region of interest 60 can also be located on Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 another lane 34, 36 of the roadway 32, for example in a lane 34, 36 that is adjacent to the lane 34, 36 on which the motor vehicle 20 is traveling.
  • the position data can be generated by a position sensor (not shown), transmitted to the control unit 25 and received by the control unit 25.
  • the position sensor can be arranged in the motor vehicle 20.
  • the position sensor can be a GPS receiver, for example.
  • the position data can also be representative of an orientation of the motor vehicle 20, in other words a vehicle orientation.
  • the position data can include orientation data that is representative of the vehicle orientation of the motor vehicle 20.
  • the orientation data can be generated, for example, by means of an orientation sensor, a magnetic sensor, for example a compass, GPS, and/or by means of an inertial measurement unit (IMU), transmitted to the control unit and received by the control unit.
  • the vehicle orientation can be specified, for example, as a yaw angle, for example as an absolute yaw angle.
  • the absolute yaw angle can be specified, for example, with reference to one or more of the cardinal directions or in a proprietary reference system of the control unit.
  • the speed data can be generated by a speed sensor (not shown) arranged in the motor vehicle 20, transmitted to the control unit 25 and received by the control unit 25.
  • the speed data can be retrieved from the storage unit 26 of the motor vehicle 20 and received by the control unit 25.
  • step S8 it can be checked whether the object 50 or one, two or more other objects 50 are in the area of interest. Area 60, depending on the sensor data and the determined area of interest 60.
  • step S8 can be carried out for all objects 50 that are coded in the sensor data, the radar data and/or the lidar data.
  • Object positions of the objects 50 can be determined from the sensor data, for example in Cartesian coordinates, for example in a first coordinate system.
  • the area of interest 60 can be specified in Cartesian coordinates, for example also in the first coordinate system.
  • step S8 it can be easily checked using the corresponding Cartesian coordinates whether one, two or more of the objects 50 are in the area of interest 60 or not. If the condition of step S8 is met, processing can be continued in an optional step S10. If the condition of step S8 is not met, processing can be continued again in step S2.
  • step S10 it can be determined whether one or more of the objects 50 located in the area of interest 60 pose a danger to the motor vehicle 20.
  • one or more of the objects 50 can be so small and/or light that they do not pose a danger to the motor vehicle 20.
  • one of the objects 50 can be, for example, a bird sitting on the roadway 32.
  • one or more of the objects 50 can cross the roadway 32 so quickly that there is no danger of a collision.
  • one of the objects 50 can be, for example, a bird flying over the roadway 32. If the condition of step S10 is met, processing can continue in a step S12.
  • step S10 processing can be continued again in step S8, for example with another of the objects 50.
  • step S12 the control signal for the braking device 24 of the motor vehicle 20 can be generated. If the optional step S10 is not processed, the control signal is generated when one or more of the objects 50 are in the area of interest 60. If the optional step S10 is processed, the control signal is only generated when one or more of the objects 50 in the area of interest 60 represent a danger to the motor vehicle 20.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30.
  • Braking, in other words deceleration, of the motor vehicle can be a "normal" braking process, an emergency brake or a rapid braking of the motor vehicle.
  • the emergency brake can be configured in such a way that little or no consideration is given to driving comfort and the focus is only on braking the motor vehicle 20 as quickly as possible.
  • the rapid braking can be configured in such a way that driving comfort is taken into account and the focus is on braking the motor vehicle 20 as quickly as possible.
  • the braking distance of the motor vehicle 20 is normally shorter with the emergency brake than with the rapid braking, and shorter with the rapid braking than with normal braking.
  • the amount of negative acceleration during braking can, for example, be in a range from 1 m/s2 to 10 m/s2, for example from 2 m/s2 to 5 m/s2, for example approximately 3 m/s2.
  • the negative acceleration can be significantly higher during the emergency brake than during the normal braking process.
  • the amount of negative acceleration can be greater during the rapid brake than during the normal braking process and smaller than during the emergency brake.
  • the motor vehicle can brake until it comes to a standstill.
  • Switching logic Fig. 3 shows a flow chart of an embodiment of a special method for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50.
  • the special method explained with reference to Figure 3 can largely correspond to the general method explained with reference to Figure 2.
  • the special method explained with reference to Figure 3 can have steps that largely correspond to or are even identical to steps of the general method explained with reference to Figure 2. Therefore, only the steps of the special method according to Figure 3 in which the special method according to Figure 3 deviates from the general method according to Figure 2 are explained below.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 A step S20 of the special method for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50 can correspond to the step S2 of the general method for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50.
  • processing of the sensor data corresponding to the step S4 can be carried out, in particular if the sensor data comprises the radar data and the lidar data.
  • the position data can be received, for example as explained in more detail above with reference to step S6.
  • the speed data can be received, for example as explained in more detail above with reference to step S6.
  • it can be checked whether a predetermined exclusion criterion is met that speaks against determining the area of interest 60 in a position-based manner, depending on the position data and/or the speed data. In most driving situations, in particular when the motor vehicle 20 is moving at medium or high speed on the roadway 32 and neither a stop nor a turn is initiated, the position-based determination of the area of interest 60 can provide more accurate results than the speed-based determination of the area of interest 60.
  • the area of interest 60 in these driving situations can be adapted more precisely to the roadway 32, in particular the corresponding lane 34, 36, by the position-based determination than with the speed-based determination.
  • the speed-based determination of the region of interest 60 can provide more accurate results. Therefore, the position-based determination of the region of interest 60 can be specified as standard and only switched to the speed-based determination if one or one, two or more other exclusion criteria that characterize the special driving maneuvers are met.
  • a first of the exclusion criteria can be met, for example, if the motor vehicle 20 is currently in an area in which the area of interest 60 is to be determined exclusively on the basis of speed. There can be areas on and/or on the roadway 32 for which it is known that the motor vehicle 20 has to carry out special driving maneuvers in these areas, for example sideways movement or a tight curve, for which the position-based determination of the area of interest 60 is unsuitable.
  • the probability that the speed-based determination of the area of interest 60 will provide a more accurate result than the position-based determination of the area of interest 60 may be relatively high, particularly compared to a situation in which the motor vehicle is not currently in the area in which the area of interest 60 is to be determined exclusively based on speed.
  • the area in which the area of interest 60 is to be determined exclusively based on speed may have a parking lot, a bus stop or a charging station for the motor vehicle 20, or an intersection at which the roadway 32 crosses another roadway 32.
  • the other roadway 32 may also be reserved for the motor vehicle 20 or the other similar motor vehicles 20, for example other GRTs.
  • the other lane 32 can also be a separate lane 32, in particular a "segregated lane".
  • the method can be configured so that the area of interest 60 is only determined based on position if the first exclusion criterion is not met and if no other exclusion criterion speaks against the position-based determination.
  • the first exclusion criterion can be met, for example, if the motor vehicle 20 is currently at a stop or is approaching the stop.
  • the probability that the speed-based determination of the area of interest 60 will provide a more accurate result than the position-based determination of the area of interest 60 can be relatively high, in particular compared to Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 a situation in which the motor vehicle 20 is not currently at a stop and/or is not approaching the stop.
  • the stop can be located next to the roadway 32.
  • the stop can be used to allow one or more passengers to get into and/or get out of the motor vehicle 20.
  • the position data can be representative of the fact that the motor vehicle is at the stop or is approaching it. In this context, the position data can be generated independently of the GPS receiver of the motor vehicle 20.
  • the position data can be generated by a sensor that is arranged at the stop or near the stop and that is configured to detect the motor vehicle 20 approaching or standing at the stop.
  • initiating and/or performing the sideways movement can be representative of the fact that the motor vehicle is in the area of the stop or is approaching it.
  • a second exclusion criterion can be met, for example, if the motor vehicle 20 has initiated or is already carrying out the sideways movement.
  • the vehicle orientation which can be used for the position-based determination of the area of interest, for example to check which lane the motor vehicle is in, can deviate from a direction of movement of the motor vehicle, so that the position-based determination of the area of interest 60 can be unsuitable in the case of sideways movement of the motor vehicle 20.
  • the method can be configured such that the area of interest 60 is only determined position-based if the second exclusion criterion is not met and if no other exclusion criterion speaks against the position-based determination.
  • a probability can be determined with which the motor vehicle 20 is moving in a lane 34 of the roadway 32.
  • This probability can be determined, for example, using the method explained below for determining the probability that the autonomous motor vehicle 20 is in the lane 34, 36 of the roadway 32.
  • a third of the exclusion criteria can be met if this probability is less than Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 is a predetermined probability threshold.
  • the predetermined probability threshold can, for example, be in a range from 80% to 100%, for example from 80% to 90%, for example approximately 80%.
  • the probability threshold can, for example, be empirically determined by a manufacturer of the motor vehicle 20 and specified by storing the probability threshold on the memory unit 26 of the control unit 25.
  • the probability that the speed-based determination of the region of interest 60 will provide a more accurate result than the position-based determination of the region of interest 60 can be relatively high, in particular compared to a situation in which the probability is equal to or greater than the predefined probability threshold.
  • the method can be configured such that the region of interest 60 is only determined position-based if the third exclusion criterion is not met and if no other exclusion criterion speaks against the position-based determination.
  • a current speed of the motor vehicle 20 can be determined depending on the speed data.
  • a fourth exclusion criterion can be met if the determined speed is less than a predefined speed threshold.
  • the specified speed threshold value can, for example, be in a range from 0.5 m/s to 10 m/s, for example from 1 m/s to 5 m/s, for example 2 m/s.
  • the speed threshold value can, for example, be determined empirically by the manufacturer of the motor vehicle 20 and specified by storing the speed threshold value in the memory unit 26 of the control unit 25. If the speed is lower than the speed threshold value, there may be an increased probability that the motor vehicle 20 will leave its current lane 34, 36 or the roadway 32 in the near future.
  • the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Probability that the speed-based determination of the region of interest 60 will produce a more accurate result than the position-based determination of the region of interest 60 may be relatively high, especially compared to a situation in which the speed is equal to or greater than the specified speed threshold.
  • the method can be configured so that the region of interest 60 is only determined position-based if the fourth exclusion criterion is not met and if no other exclusion criterion speaks against the position-based determination.
  • the exclusion criteria are referred to as "first", "second", “third” and "fourth” exclusion criteria. However, this numbering does not represent any restriction and serves solely to distinguish one selection criterion from the other.
  • this numbering does not represent an order or a priority of the exclusion criteria. If several of the exclusion criteria are checked, these can be checked in any combination, priority and/or order. Furthermore, one, two or three of the selection criteria with a higher number can be checked without a selection criterion with a lower number being checked. For example, only the second and fourth selection criteria can be checked, whereas a check of the first and third selection criteria is omitted. This example can be transferred to any other combination of checking the selection criteria. If the condition of step S26 is not met, processing can continue in a step S28. If the condition of step S26 is met, processing can continue in a step S30.
  • step S28 the region of interest 60 is determined in a position-based manner depending on the position data, for example by means of a method for position-based determination of the region of interest 60, which is located on the lane 34, 36 in the direction of travel in front of the motor vehicle 20, as explained in more detail below.
  • the fact that the region of interest 60 is determined in a position-based manner means that the region of interest 60 is essentially determined in a position-based manner depending on the position data.
  • the fact that the area of interest 60 is determined on a position-based basis can also mean that the area of interest 60 is determined at least partially depending on the speed data, wherein the speed data only serve as a supplement in the position-based determination of the area of interest 60, for example to restrict the area of interest 60 determined depending on the position data, for example its Length l ROI (see Figure 10).
  • the method can be configured such that the position-based determination of the region of interest 60 is the standard for determining the region of interest 60.
  • the region of interest 60 is determined in a speed-based manner depending on the speed data, for example by means of a method for speed-based determination of the region of interest 60 that is located on the lane 34, 36 in the direction of travel in front of the motor vehicle 20, as explained in more detail below.
  • the fact that the region of interest is determined in a speed-based manner means that the region of interest is essentially determined in a speed-based manner depending on the speed data. This can mean in particular that other data can also be taken into account in the speed-based determination of the region of interest 60, such as a yaw rate ⁇ ego of the motor vehicle 20, a shape of the motor vehicle 20 and/or a width of the region of interest 60 to be determined.
  • Steps S32, S34 and S36 can be processed corresponding to steps S8, S10 and S12 respectively.
  • Fusion of the radar and lidar data Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30
  • Fig.4 shows a display 30 on which an exemplary driving situation is shown.
  • Figure 4 and in particular the display 30 show the roadway 32 with the first lane 34 and the second lane 36, which are separated from each other by a center line 35.
  • a right side edge of the roadway 32 in Figure 4 can be referred to as the first side edge 37 and a left side edge of the roadway 32 in Figure 4 can be referred to as the second side edge 39.
  • the objects 50 have radar objects 38 that are encoded in the radar data, contour points 40 that are encoded in the lidar data, and fusion objects 42.
  • One, two or more of the contour points 40 that are close to each other are representative of a lidar object.
  • the display 30 shows several lidar objects, which can also be encoded in the lidar data.
  • Radar objects 38 on or in which none of the contour points 40 lies can also be referred to as radar-only objects.
  • Lidar objects for which no radar object 38 exists can also be referred to as lidar-only objects.
  • One of the fusion objects 42 is generated for each of the contour points 40 that lies on or in one of the radar objects 38.
  • the radar objects 38 and the lidar objects in particular the corresponding radar data and the corresponding lidar data, are fused, as explained in more detail with reference to Figure 5. If several of the contour points 40 that correspond to one of the lidar objects are located on or in one of the radar objects 38, it may be that based on one of the corresponding contour points 40 together with the corresponding radar object, only one of the fusion objects 42 is generated, whereby any of these contour points 40 can be used for the fusion with the corresponding radar object 38.
  • Figure 4 and the display 30 show several speed vectors 44 that are representative of the directions of movement and speeds of the radar-only objects and which are drawn with a dash-dot line in Figure 4, several speed vectors 46 that are representative of the directions of movement and speeds of the lidar-only objects and which are drawn with a dotted line in Figure 4.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 line
  • several speed vectors 48 that are representative of the directions of movement and speeds of the fusion objects 42 and that are marked with a solid line in Figure 4.
  • Fig.5 shows a flow chart of an embodiment of a special method for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50.
  • radar data can be received that are representative of one or more of the radar objects 38 that are in front of the motor vehicle 20 in the direction of travel.
  • the radar data can be generated by the radar sensor, transmitted to the control unit 25 and received by the control unit 25.
  • the radar sensor can be arranged in the motor vehicle 20, for example.
  • the radar data can be generated by two or more radar sensors, which can each be arranged in the motor vehicle 20, for example.
  • the radar sensor(s) can be part of a radar system.
  • the radar data can be in the form of a digital radar object list in which the radar objects 38 are listed. For example, each radar object in the radar object list can be assigned a unique identification number (ID), a size and/or a position of the corresponding radar object.
  • ID unique identification number
  • directions of movement of the objects 50 can be determined.
  • orientations of the corresponding objects 50 can be determined and the radar data can be supplemented so that the radar data are representative of the orientations of the corresponding objects 50.
  • the orientations can be assigned to the corresponding radar objects in the radar object list. If necessary, when the radar data and the lidar data are later merged, the supplemented radar data can be merged with the lidar data.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Normally, the radar data are only representative of a position and size of the object 50.
  • the directions of movement of the objects 50 can be determined using radar data that are recorded at different points in time, in particular successive points in time. If the objects 50 are other road users, for example other vehicles, the orientations of the objects 50 can correspond to their directions of movement. The orientations can therefore be determined depending on the directions of movement, for example by selecting the orientations parallel to the corresponding directions of movement or identical to the corresponding directions of movement. The fact that one of the objects 50 is another road user can be recognized, for example, by the fact that the corresponding object 50 is on the roadway 32.
  • radar systems which each have one or more radar sensors and a corresponding evaluation logic, wherein the evaluation logic has an object recognition which is able to recognize whether one or more of the radar objects 38 are other road users or not and/or which road user(s) the object(s) 50 are.
  • the radar data can be representative of classes to which the radar objects 38 belong.
  • the classes of objects 50 can be assigned sizes of the radar objects 38.
  • the classes can include, for example, "truck”, “transporter”, “car”, “motorcycle”, “bicycle” and/or "pedestrian”, wherein the (standard) sizes assigned to these classes become smaller in the list from the class "truck” to the class "pedestrian".
  • the radar data can be adapted so that the radar data is representative of the radar objects 38 with the corresponding sizes of the radar objects 38. For example, the sizes can be assigned to the corresponding radar objects in the radar object list. If necessary, when merging the radar data with the lidar data, the adjusted radar data can be merged with the lidar data.
  • a radar system that has a suitable radar sensor and that provides the aforementioned functions is currently sold by the company "Conti", for example the model ARS 404-21 or the model ARS 408-12, which are sold as Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 standardized ARS interfaces can be used and are described in the corresponding technical documentation from Conti, in particular in "Technical Documentation, ARS 404-21 (Entry), ARS 408-21 (Premium)", Version 1.91, May 18, 2018. This and documentation of other suitable radar systems can be obtained, for example, from https://conti-engineering.com/components/ars-408/.
  • the lidar data can be received which are representative of one or more of the lidar objects which are located in front of the motor vehicle 20 in the direction of travel.
  • the lidar data can be in the form of a digital lidar object list which has the lidar objects.
  • the lidar data can be generated by a lidar sensor, transmitted to the control unit 25 and received by the control unit 25.
  • the lidar sensor can be arranged in the motor vehicle 20, for example.
  • the lidar data can be generated by two or more lidar sensors, which can each be arranged in the motor vehicle 20, for example.
  • the lidar data can include contour data representative of contour points 40, with each of the lidar objects being represented by one or more of the contour points 40.
  • each contour point can be assigned a unique identification number (ID), a lidar object, a speed of the corresponding lidar object and a position of the corresponding lidar object.
  • ID unique identification number
  • a lidar system having a suitable lidar sensor is currently sold by the company “ibeo automotive”, for example from the “LUX” series, in particular the “Ibeo LUX 4L”, and is described in the corresponding technical documentation from ibeo, in particular in “Interface Specification for ibeo LUX, ibeo LUX systems and ibeo Evaluation Suite”, version 1.48.2, July 28, 2017, available at www.ibeo-as.com.
  • This and documentation of other suitable lidar systems can be obtained, for example, from https://www.ibeo-as.com/en/products/sensors/IbeoLUX.
  • This lidar system provides Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 as outputs a position of a detected object, a speed of the detected object, a speed of the motor vehicle and a class of the motor vehicle.
  • the radar data, possibly the supplemented radar data, and the lidar data can be merged to form the sensor data, the sensor data being representative of one or more of the sensor objects that correspond to the radar objects 38 and/or the lidar objects.
  • the fact that the radar data and the lidar data are merged to form the sensor data means that the radar data and the lidar data are combined, for example to be mutually verified and/or mutually supplemented.
  • the sensor data can be in the form of the fusion list that has the sensor objects.
  • a corresponding fusion object 42 can be generated for the contour point 40 and all other contour points 40 of the same lidar object and encoded in the sensor data. If none of the contour points 40 of one of the lidar objects overlaps with one of the radar objects 38, a lidar-only object can be generated for the corresponding lidar object and encoded in the sensor data. For each of the radar objects 38 for which no overlapping contour point 40 is found, a radar-only object can be generated and encoded in the sensor data.
  • the sensor objects can be classified into radar-only objects whose corresponding radar objects 38 do not correspond to any of the lidar objects, into lidar-only objects whose corresponding lidar objects do not correspond to any of the radar objects 38 and/or into fusion objects 42 whose radar objects 38 each correspond to at least one of the lidar objects.
  • the sensor objects can be divided into radar-only objects 38, lidar-only objects and fusion objects 42, where no corresponding lidar objects were found for radar-only objects 38, no corresponding radar objects were found for lidar-only objects, and fusion objects 42.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 a corresponding radar object 38 and at least one corresponding lidar object were found for each of the fusion objects 42.
  • the sensor data can be in the form of the digital fusion list, which has the sensor objects, in particular the fusion objects 42, the radar-only objects 38 and/or the lidar-only objects.
  • the radar data can have radar time information that is assigned to the radar objects 38 and that is representative of a first point in time at which the radar objects 38 were detected.
  • the lidar data can have lidar time information that is assigned to the lidar objects and that is representative of a second point in time at which the lidar data was detected. When fusing the radar data and the lidar data, the most recent radar data and the most recent lidar data can then be fused to form the sensor data.
  • a detection of the objects 50 based exclusively on the radar data has the advantages over a detection of the objects 50 based exclusively on lidar data that clearly identified objects 50 are consistently recognized as such over time, that the probability that the detected objects 50 are real is relatively high and that a speed of the radar sensor and thus of the motor vehicle 20 can be determined using the radar data.
  • the detection based on the radar data also has a disadvantage compared to the detection based on lidar data, namely that a position determination and/or a size determination of the detected objects 50 is relatively poor.
  • the detection of objects 50 based on the lidar data has the advantage over the detection of objects 50 based on the radar data that contour point positions of the contour points 40 along the contours of the objects 50 can be determined very precisely.
  • the detection based on the lidar data also has a disadvantage over the detection based on radar data, namely that objects 50 that were actually clearly identified can be recognized over time as new objects 50, so that no conclusion can be drawn about the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 speed of the lidar sensor and thus of the motor vehicle 20 and that object positions, object dimensions and object orientations of detected objects 50 are recognized relatively poorly.
  • the fusion objects 42 can be assigned a predetermined first probability with which the fusion objects 42 actually exist, for example in the fusion list.
  • the radar-only objects can be assigned a predetermined second probability with which the radar-only objects actually exist, for example in the fusion list.
  • the lidar-only objects can be assigned a predetermined third probability with which the lidar-only objects actually exist, where the first probability is greater than the second probability and greater than the third probability. If necessary, the determination explained below as to whether one or more of the sensor objects are located in the area of interest 60 and/or the determination as to whether one or more of the sensor objects located in the area of interest 60 poses a danger to the motor vehicle 20 can then be carried out depending on the corresponding probabilities.
  • the probability that the corresponding object 50 actually exists and is actually located in front of the motor vehicle 20 in the direction of travel is greater than if the object 50 is detected exclusively by radar or exclusively by lidar.
  • This circumstance can be taken into account by assigning the probabilities and in particular by assigning the greatest probability to the fusion objects 42.
  • a corresponding crossing fusion object 42 can then be encoded in the sensor data if the corresponding fusion object 42 meets the fusion crossing criterion.
  • the fusion objects 42 can be stored in the fusion list.
  • the fusion objects 42 can initially be marked in the fusion list as not crossing the roadway 32. If the corresponding crossing fusion object 42 is found for one of the fusion objects 42, the crossing fusion object 42 can be stored in the fusion list in addition to the corresponding fusion object 42.
  • the crossing fusion object 42 can be encoded in the sensor data in addition to the corresponding fusion object 42 if the corresponding fusion object 42 meets one, two or more of the fusion crossing criteria.
  • the fusion crossing criteria(s) to be checked can, for example, come from a group comprising: the corresponding lidar object is relevant; the corresponding lidar object has an age that is greater than a predetermined age threshold, for example greater than 100 ms, for example greater than 500 ms, for example greater than 1000 ms; a lateral speed of the corresponding lidar object is greater than a predefined lidar lateral speed threshold, for example greater than 1 m/s, for example greater than 1.5 m/s, for example greater than 1.75 m/s; all contour points 40 belonging to the corresponding lidar object do not overlap with any moving radar object 38; a probability of existence of the corresponding radar object 38 is greater than a predefined radar object existence threshold, for example greater than 80%, for example greater than 85%, for example greater than 90%; a lateral speed of the corresponding radar object 38 is greater than a predefined radar lateral speed threshold, for example greater than 1 m/s, for example greater than 1.5 m/s, for example greater than 1.75
  • the age of the lidar object refers to how many lidar data that were recorded consecutively immediately before the current lidar data already contain the corresponding lidar object. In other words, the age of the lidar object refers to how many lidar object lists that were created consecutively immediately before the current lidar object list already contain the corresponding lidar object. The more of the lidar data or lidar object lists the corresponding lidar object is contained in, the older the corresponding lidar object is.
  • the probability of existence of the radar object can be determined, for example, depending on the age of the radar object.
  • the age of the radar object can, for example, be determined corresponding to the age of the lidar object.
  • the lidar-only objects it can be checked whether the corresponding lidar-only object meets at least one lidar crossing criterion that is representative of the fact that the corresponding lidar-only object crosses the roadway 32 in front of the motor vehicle 20. If necessary, in addition to the lidar-only object, a corresponding crossing lidar-only object can be encoded in the sensor data if the corresponding lidar-only object meets the lidar crossing criterion. As explained above, the lidar-only objects can be stored in the fusion list. The lidar-only objects can be marked in the fusion list as not crossing the roadway 32.
  • the lidar crossing fusion object 42 can be stored in the fusion list in addition to the corresponding lidar-only object.
  • it can be checked whether the corresponding lidar-only object meets two or more lidar crossing criteria, each of which is representative of the fact that the corresponding lidar-only object crosses the roadway 32 in front of the motor vehicle 20.
  • the crossing lidar-only object can be stored in addition to the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 corresponding lidar-only object can be encoded in the sensor data if the corresponding lidar-only object meets one, two or more of the lidar crossing criteria.
  • the lidar crossing criteria(s) to be checked can, for example, come from a group comprising: an age of the lidar-only object is greater than a predetermined lidar age threshold, for example greater than 100 ms, for example greater than 500 ms, for example greater than 1000 ms; a distance of the lidar-only object to the motor vehicle 20 is greater than a predetermined lidar distance threshold, measured from a center Z (see Figure 9) of the motor vehicle 20, for example greater than 1 m, for example greater than 5 m, for example approximately 6 m; a length of the lidar-only object is less than a predefined length threshold (it is unlikely that there is no corresponding radar object 38 for a very long lidar object), for example less than 3 m, for example less than 2 m, for example less than 1.5 m; a width of the lidar-only object is less than a predefined width threshold (it is unlikely that there is no corresponding radar object 38 for a very wide lidar object), for example less than 3 m, for example
  • the age of one of the lidar-only objects can be determined using historical lidar data, checking whether the corresponding lidar object is already encoded in previously acquired lidar data, in particular in previous lidar data that was acquired consecutively and directly before the current lidar data.
  • the age can be Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 be assumed to be the longer the more previous lidar data the corresponding lidar object is encoded in.
  • the age of one of the lidar-only objects can be assumed to be the longer the more previous lidar object lists the corresponding lidar object is included in.
  • it can be checked whether the corresponding object 50 meets one or more relevance criteria.
  • the corresponding fusion object 42, radar-only object or lidar-only object can be marked as relevant in the fusion list if the corresponding fusion object 42, radar-only object or lidar-only object meets one or more of the relevance criteria.
  • the corresponding fusion object 42, radar-only object or lidar-only object can be marked as not relevant if the corresponding fusion object 42, radar-only object or lidar-only object does not meet any of the relevance criteria.
  • the relevance criteria(s) to be checked can, for example, come from a group, the group having a first subgroup that relates to the radar-only objects 38 and a second subgroup that relates to lidar-only objects and fusion objects 42.
  • the first subgroup can have: a probability of existence of the corresponding radar object 38 is greater than a predetermined probability of existence threshold; the corresponding radar object 38 is included in the current radar object list; an amount of a cross-sectional area (Radar Cross Section (RCS)) of the corresponding radar object 38 is greater than a predetermined cross-sectional threshold value, for example greater than 1 dBm2, for example greater than 3 dBm2, for example greater than 5 dBm2; information about a reliability of one or more measured values describing dynamic properties, for example the speed; the corresponding radar object 38 does not belong to a class that includes large objects, such as trucks or vans; the corresponding radar object 38 is stationary (it is very unlikely that there is no corresponding lidar object for a stationary radar object 38).
  • RCS Radar Cross Section
  • the second subgroup may have: a number of contour points 40 belonging to the corresponding lidar-only object is greater than a predetermined number threshold, for example greater than 2, for example greater than 3; a density of contour points 40 belonging to the corresponding lidar-only object is greater than a predetermined density threshold (if the distance of the corresponding lidar-only object to the motor vehicle 20 is smaller than a predetermined distance threshold, for example smaller than 2 m, for example smaller than 1 m, for example approximately 0.35 m; there is more than one contour point 40 to the corresponding lidar-only object.
  • a predetermined number threshold for example greater than 2, for example greater than 3
  • a density of contour points 40 belonging to the corresponding lidar-only object is greater than a predetermined density threshold (if the distance of the corresponding lidar-only object to the motor vehicle 20 is smaller than a predetermined distance threshold, for example smaller than 2 m, for example smaller than 1 m, for example approximately 0.35 m; there is more than one contour point 40 to the corresponding lidar-
  • the age of one of the lidar-only objects can be determined using historical lidar data, checking whether the corresponding lidar object is already encoded in previously acquired lidar data, in particular in earlier lidar data that were acquired consecutively and directly before the current lidar data.
  • the age can be specified as being the longer the more earlier lidar data the corresponding lidar object is encoded in. In other words, the age of one of the lidar-only objects can be assumed to be the greater the more earlier lidar object lists the corresponding lidar object is contained in.
  • the position data that are representative of the current vehicle position of the motor vehicle 20 can be received. The position data can be received corresponding to the step S22 explained above.
  • step S48 the speed data that are representative of a current speed of the motor vehicle 20 can be received.
  • the speed data can be received corresponding to the step S24 explained above.
  • step S50 the region of interest 60 that is located on the roadway 32 in the direction of travel in front of the motor vehicle 20 can be determined depending on the position data and/or the speed data, for example position-based or speed-based, as explained in more detail below.
  • the step Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 S50 can be processed corresponding to step S6 explained above.
  • step S50 can be processed corresponding to steps S26, S28 and S30 explained above.
  • a step S52 depending on the sensor data, it can be checked for each of the sensor objects in the fusion list whether the corresponding sensor object is located in the area of interest 60 or not.
  • Step S52 can be processed corresponding to step S8 or S32 explained above.
  • step S54 it can be determined whether one or more of the sensor objects located in the area of interest 60 pose a danger to the motor vehicle 20.
  • Step S54 can be processed corresponding to step S10 or S34 explained above.
  • the first probability is assigned to the fusion objects 42 in the foregoing, the second probability to the radar-only objects and/or the third probability to the lidar-only objects, then optionally only the fusion objects, only the radar-only objects or only the lidar-only objects whose assigned probability is greater than a predetermined probability threshold can be taken into account in steps S52 and/or S54. If it is checked in the foregoing whether the fusion objects 42, the radar-only objects and/or the lidar-only objects are relevant, for example based on the relevance criteria, then optionally only the fusion objects, only the radar-only objects or only the lidar-only objects that were assessed as relevant can be taken into account in steps S52 and/or S54.
  • a step S56 the control signal for the braking device 24 of the motor vehicle 20 can be generated, for example corresponding to the steps S12 or S36 explained above.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Position-based determination of the ROI Fig.6 shows a top view of an exemplary driving situation, of the motor vehicle 20 and of the area of interest 60 in front of the motor vehicle 20.
  • the motor vehicle 20 has a width B.
  • the motor vehicle 20 moves on the roadway 32, in particular on the first lane 34, in Figure 6 in the direction of travel upwards.
  • the area of interest 60 is delimited on its lateral outer sides by a first outer boundary 56 and a second outer boundary 58.
  • the first outer boundary 56 is defined by interconnected first outer points 52 and the second outer boundary 58 is defined by interconnected second outer points 54.
  • the length l ROI (in the longitudinal direction, perpendicular to the lateral direction) of the region of interest 60 can be fixed or determined depending on the speed of the motor vehicle 20, for example by means of the method explained below for avoiding or reducing the collision of the autonomous motor vehicle 20, which is traveling on the roadway 32, with the object 50.
  • Figure 7 shows a flow chart of an embodiment of a method for position-based determination of the region of interest 60.
  • the position data can be received which are representative of the current vehicle position and optionally of an orientation of the motor vehicle 20, in other words a vehicle orientation of the motor vehicle 20.
  • the step S60 can be processed corresponding to the step S22 or S46.
  • the position data can be representative of a front position of a front 62 (see Figure 9) of the motor vehicle 20.
  • the area of interest 60 can subsequently be determined such that it extends from the front 62 in the current direction of travel of the motor vehicle 20.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 The position of the motor vehicle 20 can be specified in a two-dimensional coordinate system in the form of an X and a Y coordinate and the vehicle orientation can be specified as an angle, for example as a yaw angle and/or direction of travel of the motor vehicle 20.
  • the coordinate system can, for example, refer to the motor vehicle 20, have the center Z or a center of the front 62 of the motor vehicle 20 as the origin, and/or be referred to as a motor vehicle coordinate system.
  • a proprietary coordinate system or a real-world coordinate system can be used as the coordinate system.
  • the position data can thus be available, for example, as: where x V (t) the X-position of the motor vehicle 20 at time t, y V (t) the Y-position of the motor vehicle 20 at time t and ⁇ V (t) is the yaw angle or the direction of travel of the motor vehicle 20 at the time t.
  • the speed data can be received, for example corresponding to the step S24 or S48 explained above.
  • the current speed of the motor vehicle 20 can be determined depending on the speed data and subsequently the length l ROI (see Figure 9) of the area of interest 60 depending on the speed of the motor vehicle 20.
  • the length l ROI can be determined, for example, depending on the speed and a collision time duration.
  • the collision time duration can be determined, for example, using a method for determining the collision time duration, as explained in more detail below.
  • the length l ROI depending on the speed using a length look-up table in which different speeds have suitable lengths l ROI of the area of interest 60.
  • the length l ROI can, for example, extend from the front 62 of the motor vehicle 20 to a longitudinal end of the region of interest 60.
  • reference point positions of reference points 94, 96 (see Figure 14) along the lane, for example the first lane 34, can be determined.
  • the reference points 94, 96 can be representative of a course of the lane 34, 36 in the direction of travel in front of the motor vehicle 20.
  • the reference points 94, 95 can be positioned along a center of the corresponding lane 34, 36.
  • the reference point positions can be determined depending on the position data using a lane lookup table in which the reference point positions are assigned to the reference points 94, 96.
  • the reference point positions can each be specified in a two-dimensional coordinate system in the form of an X and a Y coordinate, and an orientation of the corresponding lane 34, 36, in other words a lane orientation, can be specified as an angle.
  • the coordinate system can be, for example, a proprietary coordinate system or a real-world coordinate system, wherein the position of the motor vehicle 20 and the reference point positions are either specified in the same coordinate system or are transferred to the same coordinate system.
  • the reference point positions can be, for example, present as: where xL is the X-coordinate of the corresponding reference point of lane L, yL is the Y-coordinate of the corresponding reference point of lane L, ⁇ L the lane orientation of lane L at the corresponding reference point and l L the length of the lane L up to the corresponding reference point.
  • the lane L can be, for example, the first or the second lane 34, 36, in which context the index L of the lane 34, 36 can be, for example, equal to 1 for the first lane 34 or 2 for the second lane 36.
  • the motor vehicle 20 can, for example, have a separate lane lookup table for each lane 34, 36 on which the motor vehicle 20 moves, so that the motor vehicle 20 can determine the area of interest 60 on a position-based basis in each lane 34, 36.
  • the corresponding lane lookup tables Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 lanes can be stored in the motor vehicle 20, for example in the storage unit 26 of the control unit 25, or made available to the motor vehicle 20 via a communication connection, for example via the Internet.
  • the lane lookup tables can be created in advance depending on the real lanes 34, 36, for example by measuring the corresponding lanes 34, 36 and extracting the relevant measurement results and storing them in the corresponding lane lookup tables.
  • the lane lookup tables can also contain information about one or more curves, for example corresponding curvature data.
  • the reference point positions of the reference points 94, 96 can be specified, for example, by GPS coordinates in the lane lookup table.
  • the reference point positions and optionally the reference points 94, 96 can be provided with indices in the lane lookup table and ordered accordingly.
  • the lane lookup table can have an index for each reference point and a reference point position of the reference point assigned to the index, for example within a row of the lane lookup table.
  • An order of the indices can correspond to an order of the reference points 94, 96 on the lane 34, 36 in the real world, with the length l L of the lane up to the corresponding reference point increases from reference point to reference point.
  • the length lL of the lane up to the corresponding reference point can then also be specified as the number of reference points, taking into account the distance between the reference points.
  • the length l ROI of the area of interest can be specified as a number of reference points.
  • the lane 34, 36 for which the area of interest 60 is to be determined can be a part of the roadway 32, which has the two or more lanes 34, 36.
  • the area of interest 60 can then be determined such that it is located in the lane 34, 36 on which the motor vehicle 20 is currently traveling, for example in the first lane 34.
  • the area of interest 60 can be determined such that it is located in the lane 34, 36 that is next to the Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 lane 34, 36 on which the motor vehicle 20 is currently driving, for example on the second lane 36.
  • the area of interest 60 can be determined depending on the reference points 94, 96 and depending on the width B of the motor vehicle 20.
  • a driving line 90, 92 can be determined on the lane 34, 36, wherein the driving line 90, 92 can be determined by connecting the reference points 94, 96.
  • the reference point positions of the reference points 94, 96 can be specified in the lane lookup table, for example, such that the driving line 90, 92 runs in the middle of the corresponding lane 34, 36.
  • the driving line 90, 92 can, for example, run parallel to the center line 35 of the roadway 32 and/or parallel to one of the two side edges 37, 39 of the roadway 32.
  • the reference points 94, 96 can be selected such that they are spaced apart along the driving line 90, 92 by, for example, 1 cm to 20 cm, for example, 5 cm to 15 cm, for example 10 cm.
  • the width B of the motor vehicle 20 is normally fixed depending on an actual width B of the motor vehicle 20.
  • the width B can, for example, be stored in the memory unit 26.
  • the outer points 52, 54 can be determined in such a way that they each Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 have the specified distance from the corresponding reference point 94, 96 and that they each lie on a straight line that runs through the corresponding reference point 94, 96 and that is perpendicular to a tangent to the driving line 90, 92 at the corresponding reference point 94, 96.
  • the first outer points 52 can then be connected to one another to form the first outer boundary 56, and the second outer points 54 can be connected to one another to form the second outer boundary 58.
  • the specified distance can each correspond to at least half the width B of the motor vehicle 20.
  • the specified distance can, for example, be specified such that it corresponds to the width B of the motor vehicle 20 plus an additional tolerance range, whereby the tolerance range can be in a range, for example, from 1 cm to 50 cm, for example 5 cm to 25 cm, for example approximately 10 cm, i.e. approximately 5 cm on each side of the motor vehicle 20.
  • the width of the area of interest 60 can be specified such that it is slightly larger than the width B of the motor vehicle 20.
  • the additional tolerance range can contribute to the safety of the motor vehicle 20. If the area of interest 60 is determined based on position, as explained with reference to Figures 6 and 7, it can be particularly advantageous to check using the method explained below with reference to Figure 8 whether one or more of the objects 50 are located in the area of interest 60.
  • Fig.8 shows a flow chart of an embodiment of a method for determining whether the object 50 is located in the region of interest 60 in the direction of travel in front of the motor vehicle 20, which is particularly advantageous if the region of interest 60 is determined based on position.
  • the sensor data can be received, for example corresponding to one of the steps S2 or S20 explained above.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30
  • the region of interest 60 can be determined based on position, as explained above.
  • two or more triangles can be determined that together cover the region of interest 60.
  • the triangles can be determined, for example, based on the outer points 52, 54.
  • the region of interest 60 can be divided into triangles that together form the region of interest 60, and the check as to whether or not the object 50 is in the region of interest 60 can be carried out separately for each of these triangles.
  • the triangles can have first triangles and second triangles, one of the triangles of the region of interest 60, in particular one of the second triangles, being shown in Figure 6.
  • the first triangles can each be determined using two first outer points 52 on the first outer boundary 56 and a second outer point 54 on the second outer boundary 58.
  • the first outer points 52 can be indexed using the running variable i, which is a natural number
  • the second outer points 54 can be indexed using the running variable j, which is a natural number.
  • the first triangles can thus be determined, for example, using the j-th second outer point 54 and using the i-th and (i+1)-th first outer points 56.
  • the second triangles can each be determined using two of the second outer points 54 on the second outer boundary 58 and one of the first outer points 52 on the first outer boundary 56.
  • the second triangles can thus be determined, for example, using the i-th first outer point 52 and using the j-th and (j+1)-th second outer points 54, as shown in Figure 6 on one of the triangles.
  • How many triangles are determined based on the outer points 52, 54 to cover the area of interest 60 can be determined based on the length l ROI of the area of interest.
  • the first and second outer points 52, 54 for determining the triangles can be selected such that the triangles do not overlap each other and completely cover the area of interest 60.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 In a step S70, it can be checked sequentially, i.e. for each of the determined triangles one after the other, whether one or more of the objects 50 are located in one or more of the triangles until all triangles have been checked.
  • the front and rear axles of the motor vehicle 20, in particular the corresponding wheels 23, can steer independently of one another.
  • only a longitudinal speed v needs to be taken into account. long and an angular velocity or yaw rate ⁇ ego of the motor vehicle 20 to determine the region of interest 60 is not useful, since this does not take into account the sideways movement of the motor vehicle 20 during the particular driving maneuvers.
  • An elegant approach to also take into account the sideways movement arises from the way in which Forces parameterizes the vehicle movement, for example in "A generic vehicle controller", by A. J. de Graaf, Technical Report (unnumbered), Frog Navigation Systems B.V., September 2003.
  • a position and attitude of the virtual bicycle in the vehicle coordinate system with the longitudinal axis V and with the center Z of the motor vehicle 20 is determined by the following variables: - a side angle ⁇ c , which describes the angle between the virtual bicycle and the longitudinal axis V; - a steering angle ⁇ s, which describes the steering angle of the virtual bicycle with front wheel steering; - a length l F , which represents a distance between the front and rear wheels of the virtual bicycle, where the length l F is chosen to be equal to the distance between the centre Z and the front axle of the motor vehicle 20.
  • the angles ⁇ c and ⁇ s are such that an instantaneous center of rotation (ICR) of the virtual bicycle corresponds to that of the motor vehicle 20, whereby a simple representation of the movement of the motor vehicle 20 can be achieved, which provides a basis for determining the region of interest 60.
  • ICR instantaneous center of rotation
  • a derivative of the side angle ⁇ c assumed to be equal to zero. This assumption implies that the angular velocity of the motor vehicle 20, also referred to as the yaw rate ⁇ ego, is identical to the yaw rate ⁇ of the virtual bicycle.
  • the control unit 25 has the longitudinal speed v long and the lateral velocity v lat of the center Z and the yaw rate ⁇ ego
  • the side angle ⁇ c is then given by At a low speed v ego of the motor vehicle 20, the calculation of the side angle ⁇ c may be inaccurate due to measurement noise in practice or numerical inaccuracies in a corresponding simulation. This problem can be mitigated by setting the side angle ⁇ c to zero as the speed decreases.
  • the side angle ⁇ c can be determined as follows: To adjust the steering angle ⁇ s To obtain the speed v s a center S of the front wheel of the virtual bicycle.
  • v s is the velocity vector of this center S in the real number space
  • ⁇ is the angular velocity vector
  • r vs a vector of length l F of the frame in the longitudinal direction of the virtual bicycle. If one assumes a coordinate system that consists of the longitudinal and lateral axes of the vehicle coordinate system and a Z-axis perpendicular to the vehicle plane, v s expressed by its three components, i.e.
  • the speed v can be determined using the component v s in the longitudinal direction of the virtual bicycle as follows
  • the yaw rate ⁇ can be calculated based on the component v s be determined which is caused by a rotation of the virtual bicycle and are specified as For this and the following calculations, it is assumed that the motor vehicle 20 is travelling in a forward direction, namely in the first direction of travel. Travelling in a reverse direction requires a small adjustment of the calculations, as explained below.
  • the region of interest 60 is determined by the expected route of the motor vehicle 20, represented by the virtual bicycle.
  • the region of interest 60 covers an area that is "curved" along an arc, with a width that increases with increasing distance from the motor vehicle 20, and the determined, finite length l ROI .
  • Fig.10 shows a schematic diagram for explaining the speed-based determination of the region of interest 60, in particular an example of the region of interest 60, together with a number of relevant variables.
  • Fig.10 also shows two relevant coordinate systems: firstly, a coordinate system P of the virtual bicycle, the origin of which is in the center of the rear axle of the virtual bicycle and is aligned with the longitudinal axis of the bicycle, and secondly, a rotated coordinate system S of the virtual bicycle, which is aligned tangentially to a center line of the region of interest 60 and the origin of which is in the center of a handlebar of the virtual bicycle.
  • the region of interest 60 only applies to objects 50 located in front of the motor vehicle 20, i.e. H.
  • the target distance d t can be specified as where R e is a radius of a circle with the origin in the rotation center ICR through the center of the front wheel of the virtual bicycle and ⁇ t > 0 is the angle between a line from the rotation center ICR through the front wheel center and a line from the rotation center ICR pointing to the object 50.
  • the coordinates of the target position in the coordinate system S are equal to where ( ⁇ ⁇ ⁇ , ⁇ ⁇ ⁇ ) is the position of object 50 in the coordinate system P, and is the angle between the line from the rotation center ICR through the center of the rear wheel of the virtual bicycle and the line from the rotation center ICR through the center of the front wheel of the virtual bicycle, and R( ⁇ ) is a rotation matrix according to This results in with so that a suitable formulation for the coordinates of the object 50 is obtained.
  • a remaining unknown variable, which is used for the calculation of d t required, the radius R ICR with the rotation center ICR which can be determined as follows Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 where v is the longitudinal speed of the virtual bicycle.
  • R ICR,max for the target radius R t be introduced, for example, to 10 6 m, which is almost equivalent to driving straight ahead. Since a simple limitation of R ICR would still mean that the R ICR would have to be calculated first, the upper limit can be introduced in another way, as explained below.
  • both the speed v and the yaw rate ⁇ become very small when braking to a standstill or at low speeds. Consequently, the control unit 25 can calculate R ICR very sensitive to steering operations and to measurement noise at speed react. It can be prevented that R ICR remains undetermined at standstill by a minimum speed v ROI,min > 0 is introduced, which follows which solves the first problem.
  • the second problem i.e. the sensitivity of the measurements to noise at very low speeds, can be mitigated to some extent by using R ICR at low speeds on R ICR,max Furthermore, a speed-dependent lower limit R ICR,lb (v) for R ICR be introduced.
  • R ICR,min The minimum radius can be chosen to be equal to a minimum turning radius of the motor vehicle 20, whereby R ICR,lb (v) can be specified by
  • R ICR,lb (v) the boundaries of the region of interest 60 may be too narrow at low speeds due to the sensitivity of the R calculation. ICR can still be relatively inaccurate during steering movements.
  • the measured yaw rate ⁇ m be filtered with a low-pass filter, for example according to the following first-order discrete time filter: where ⁇ m,r a "raw" measured yaw rate, t s a sampling time of the control unit 25 and ⁇ ⁇ are a time constant, and k ⁇ Z denotes the discrete time.
  • the same type of filter can also be applied to the longitudinal velocity v long applied.
  • the boundaries of the region of interest 60 can be described by mathematically describing its outer boundaries 56, 58. This can be used, for example, to visualize the region of interest 60.
  • the first outer boundary 56 which in the figures is the right outer boundary of the region of interest 60, can be defined by the parameterized coordinates ( ⁇ ⁇ ⁇ , ⁇ ⁇ ⁇ ) and the second outer boundary 58, which in the figures is the left outer boundary of the region of interest 60, can be defined by the parameterized coordinates ( ⁇ ⁇ ⁇ , ⁇ ⁇ ⁇ ), each in the coordinate system P of the virtual bicycle.
  • the outer boundaries 56, 58 can be specified by Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 where d ⁇ [0, l ROI (v)] is the arc distance along the centerline of the region of interest 60 measured from the front wheel of the virtual bicycle, and where the angle ⁇ is between a line from the center of rotation ICR through a point on the left or right outer boundary 56, 58 and a line from the center of rotation through the center of the rear wheel of the virtual bicycle. That is, the angle ⁇ can be given by Fig.11 shows a diagram of a flow chart of an embodiment of a method for speed-based determination of the area of interest.
  • the area of interest 60 is located on the roadway 32 in the direction of travel in front of the motor vehicle 20 and is expected to be driven over by the motor vehicle 20 in the near future.
  • the speed data can be received which are relevant for a current speed v ego of the motor vehicle 20, for example corresponding to step S24.
  • yaw data can be received which are representative of the yaw rate ⁇ ego of the motor vehicle 20.
  • the yaw rate ⁇ ego of the motor vehicle 20 can be generated, for example, by means of a yaw rate sensor, a magnetic sensor, for example a compass, GPS, and/or by means of an inertial measurement unit (IMU), transmitted to the control unit 25 and received by the control unit 25.
  • IMU inertial measurement unit
  • the side angle ⁇ c can be determined depending on the speed data, for example using the formulas explained above, wherein the side angle ⁇ c the angle between a frame of a given virtual bicycle and the longitudinal axis V of the motor vehicle 20.
  • the virtual bicycle can be specified so that the rear axle Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 of the virtual bicycle passes through the geometric center Z of the motor vehicle 20 and that the length l F of the frame of the virtual bicycle corresponds to a distance of the center Z to the front axle of the motor vehicle 20.
  • the current speed v ego of the motor vehicle 20 can be expressed in the form of a lateral speed v lat and a longitudinal velocity v long of the center Z in the velocity data.
  • the side angle ⁇ c can then be determined depending on the lateral velocity vlat and the longitudinal velocity vlong of the center Z.
  • the side angle ⁇ c by means of an inverse function of the angular function tangent depending on the lateral velocity v lat and the longitudinal velocity v long determined as explained above.
  • the region of interest 60 can be determined depending on the azimuth angle ⁇ c and the yaw rate ⁇ or ⁇ ego determined, for example using the formulas explained above. It is then easy to check whether one of the objects 50 is located in the speed-based region of interest 60.
  • the object 50 can be classified as being located in the region of interest 60 if the following conditions are met: where l ROI (v) the optionally speed-dependent length, in particular the arc length, of the region of interest is 60 and ⁇ ROI (d t ) is the optional distance-dependent arc width at the position of the object 50.
  • the length l ROI (v) can be determined, for example, on the basis of the stopping distance of the motor vehicle 20 at maximum deceleration. If the distance between the motor vehicle 20 and the object 50 is small, ⁇ ROI (d t ) can be determined, for example, by a width of the corresponding lane 34, 36 or by the width B of the motor vehicle 20.
  • the area of interest Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Area 60 can be approximately assumed to be left/right symmetrical with respect to an expected path of the motor vehicle 20. If the motor vehicle 20 is traveling in reverse, the formulas explained above can be used unchanged to determine the area of interest 60 and/or to check whether one of the objects 50 is located in the area of interest 60, with only the sign of the measured yaw rate ⁇ m must be changed.
  • Lane detector Fig.12 shows an example of two of the previously explained driving lines 90, 92 for the motor vehicle 92.
  • the first driving line 90 is marked by the first reference points 94 and the second driving line 92 is marked by the second reference points 96.
  • the first driving line 90 is representative of the first lane 34.
  • the second driving line 92 is representative of the second lane 36.
  • the motor vehicle 20 can move according to a speed vector 98 in the direction of travel, for example along the first driving line 90.
  • Fig.13 shows a flow chart of an embodiment of a method for determining the probability with which the motor vehicle 20 is in one of the lanes 34, 36, for example in the first lane 34.
  • the position data that are representative of the current vehicle position of the motor vehicle 20 can be received, for example corresponding to the steps S22, S46 or S60 explained above.
  • the position data can be in the form of X and Y coordinates. If the position data are representative of the vehicle orientation of the motor vehicle 20, the position data can include the current vehicle orientation, in particular in the form of the yaw angle.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30
  • a reference point position of one of the reference points 94, 96 along the lane 34, 36 can be determined. The reference point position can be determined depending on the position data using a first lane lookup table that is assigned to the corresponding lane 34, 36 and in which the corresponding reference point positions are assigned to the reference points 94, 96.
  • the reference points 94, 96 can be representative of a course of the corresponding lane 34, 36 in the direction of travel in front of the motor vehicle 20.
  • the reference point position and the corresponding reference point 94,96 can be determined such that the reference point position is closest to the current vehicle position of the motor vehicle 20, compared to the reference point positions of the other reference points 94,96 in the first lane lookup table.
  • the first reference points 94 can be determined together with their reference point positions, for example in the form of X and Y coordinates, with the lane orientations at the corresponding first reference points 94 and optionally with the lengths l L the first lane 34 at the corresponding first reference points 94 in the first lane lookup table.
  • the second reference points 96 can be stored together with their reference point positions, for example in the form of X and Y coordinates, with the lane orientations at the corresponding second reference points 96 and optionally with the lengths l L the second lane 36 at the corresponding second reference points 96 is stored in a second lane lookup table. If the lane orientation of the corresponding lane 34, 36 at the corresponding reference points 94, 96 is assigned to the reference points 94, 96 in the lane lookup tables, then in step S82, in addition to the reference point position, the lane orientation at the determined reference point position that is assigned to the corresponding reference point 94, 96 and that is closest to the current motor vehicle position can be determined using the first lane lookup table.
  • the first and possibly further lane lookup tables can be created in advance depending on the real lanes 34, 36, for example by measuring the corresponding lanes 34, 36 and extracting the relevant measurement results and storing them in the corresponding lane lookup tables.
  • the lane lookup tables can also contain information about one or more curves, for example corresponding curvature data, whereby the curvature data can be stored in the form of the lane orientations in the corresponding lane lookup table.
  • a distance of the determined reference point position to the current vehicle position can be determined.
  • the reference point position and the current vehicle position can be in Cartesian coordinates of the same coordinate system and the distance can be determined using simple known mathematical methods. For example, the distance can be determined and/or specified as a Euclidean distance. If the position data are representative of the vehicle orientation of the motor vehicle 20 and in step S82 the lane orientation at the determined reference point position is determined using the first lane lookup table in addition to the reference point position, then in step S84 a deviation of the current vehicle orientation from the determined lane orientation can be determined in addition to the distance.
  • the distance and the deviation can be specified according to a Gaussian distribution as where x V (t) and x L (t) are the vectors introduced above at time t, which indicate the vehicle position and orientation, and the reference point position and lane orientation, respectively.
  • x V (t) and x L (t) are the vectors introduced above at time t, which indicate the vehicle position and orientation, and the reference point position and lane orientation, respectively.
  • the probability can be determined using a predefined distance lookup table in which different distances are assigned corresponding probabilities.
  • the distance lookup table can be determined in advance empirically or by means of simulation and stored, for example, on the storage unit 26.
  • the probability that the motor vehicle 20 is in the corresponding lane 34, 36 can be used, for example, to determine the region of interest 60 based on position, as explained above. If the deviation of the vehicle orientation from the lane orientation is determined in step S84, the probability can be determined using the specified distance lookup table, whereby in this context different distances and/or different deviations are assigned corresponding probabilities in the distance lookup table.
  • the distance and the deviation can be taken into account together in the form of where ⁇ ⁇ is a confidence value that can be interpreted and used as the probability that the motor vehicle 20 is in the lane 34, 36.
  • the determined probability that the motor vehicle 20 is in the lane 34, 36 can be compared with a predetermined lane threshold value. If the determined probability is smaller Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 than the specified lane threshold, the motor vehicle 20 can be classified as not being in the corresponding lane 34, 36. If the probability is equal to or greater than the specified lane threshold, the motor vehicle 20 can be classified as being in the corresponding lane 34, 36.
  • the specified lane threshold can be specified, for example, greater than 80%, for example greater than 85%, for example greater than 90%, and can be a maximum of 100%.
  • the motor vehicle 20 can be configured to drive on the corresponding lane 34, 36 either in a first direction of travel or in a second direction of travel opposite to the first direction of travel, wherein the first lane lookup table can be representative of the course of the first lane 34 in the first direction of travel and a second lane lookup table can be representative of the course of the first lane 34 in the second direction of travel.
  • the current direction of travel of the motor vehicle 20 can be determined, for example, based on the position data, in particular the current vehicle orientation, in particular the current yaw angle.
  • the first or the second lane lookup table can then be selected to determine the reference point position that is closest to the current vehicle position of the motor vehicle 20.
  • the reference point position that is closest to the current vehicle position of the motor vehicle 20 can be determined using the first lane lookup table if the current direction of travel corresponds to the first direction of travel
  • the reference point position can be determined using the second lane lookup table if the current direction of travel corresponds to the second direction of travel, wherein in the second lane lookup table the reference point positions are assigned to the first reference points 94 that are representative of the course of the first lane 34 in the second direction of travel.
  • the method described above for determining the probability with which the motor vehicle 20 is in the lane 34, 36 of the roadway 32 can be checked.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 whether the motor vehicle 20 is in the second lane 36.
  • the reference point position that is closest to the current vehicle position of the motor vehicle 20 can be determined using a third lane lookup table, wherein in the third lane lookup table the reference point positions are assigned to the second reference points 96 that are representative of a course of the second lane 36 in the second direction of travel.
  • a fourth lane lookup table can be stored in which the reference point positions are assigned to the second reference points 96 that are representative of the course of the second lane 36 in the first direction of travel.
  • the reference point position closest to the current vehicle position of the motor vehicle 20 can be searched not only in the first lane lookup table, but also in the second, third and/or fourth lane lookup table.
  • the reference point position closest to the current vehicle position of the motor vehicle 20 can be searched in the fourth lane lookup table if the motor vehicle 20 is traveling in the first direction of travel and the distance of the current vehicle position to the closest reference point position from the first lane lookup table is greater than the predetermined lane threshold.
  • the motor vehicle 20 is classified as being in the second lane 36.
  • the distance of the current vehicle position to the closest reference point position from the first lane lookup table is already smaller than the specified lane threshold value, consultation of the fourth lane lookup table can be dispensed with and the motor vehicle 20 can be classified as being in the first lane 34.
  • the first reference point 94 closest to the current vehicle position from the first lane lookup table and the second reference point 96 closest to the current vehicle position from the fourth lane lookup table can be searched for and the corresponding distances to the current vehicle position can be determined.
  • the motor vehicle 20 can be classified as being in the first lane 34. If the distance between the current vehicle position and the determined first reference point 94 is greater than the distance between the current vehicle position and the determined second reference point 96, the motor vehicle 20 can be classified as being in the second lane 36. However, if both distances are greater than the specified lane threshold value, the motor vehicle 20 can be classified as being in neither the first nor the second lane 34, 36.
  • the check as to which lane 34, 36 the motor vehicle 20 is currently located is determined using the previously explained confidence value ⁇ and thus both the distance between the position of the motor vehicle 20 and the closest reference point 94, 96 and the deviation between the current vehicle orientation and the lane orientation in the closest reference point 94, 96 are taken into account in the check, then, for example, the confidence value ⁇ ⁇ for all lanes 34, 36 and directions of travel, in particular using the first to fourth lane lookup tables.
  • the motor vehicle 20 can then be classified as being in the lane 34, 36 for which the confidence value ⁇ is the highest.
  • the motor vehicle 20 can be classified as not being in any of the lanes 34, 36 if the highest confidence value ⁇ is smaller than the predetermined lane threshold value.
  • the lane threshold value can be determined, for example, by first determining how far the motor vehicle 20 can deviate from the lane 34, 36 in terms of its position and orientation in order to just be classified as being in the corresponding lane 34, 36.
  • corresponding threshold values can be determined empirically and/or by simulation in advance and stored in the control unit 25.
  • a maximum distance between the X coordinate and the Y coordinate of the position Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 tion of the motor vehicle 20 from the X-coordinate or the Y-coordinate of the reference point position of the corresponding reference point 94, 96 can be specified with 0.2 m each, and a maximum deviation of the current vehicle orientation from the lane orientation at the corresponding reference point 94, 96 can be specified with 0.108 rad.
  • TTC and length ROI Fig.14 shows a diagram in which several example curves of speed-dependent time threshold values are shown as a function of the speed of the motor vehicle 20, with the time threshold values being given in the form of Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 where i is representative of a driving situation and can, for example, assume the values A for a first driving situation, B for a second driving situation and C for a third driving situation and where is the period of time that elapses until a collision with one of the objects 50 occurs.
  • a fourth driving situation can, for example, refer to the fact that the object 50 is a pedestrian who is crossing the roadway 32, whereby this fourth driving situation is assumed in this description to be the same as the first driving situation A, since the corresponding simulations resulted in the same values for both driving situations.
  • a time threshold lookup table can be generated using the diagram shown in Figure 14, in particular using the corresponding data.
  • Friedrichshafen 2022-11-30 of the time threshold lookup table can be assigned to the different speeds ego the respective first time threshold value if this first time threshold value at the corresponding speed v ego greater than the corresponding second and third time threshold values; the different speeds v ego the respective second time threshold can be assigned in the time threshold lookup table if this second time threshold is greater than the corresponding first and the corresponding third time threshold; and the different speeds v ego the respective third time threshold can be assigned in the time threshold lookup table if this third time threshold is greater than the corresponding first and the corresponding second time threshold.
  • the different speeds v ego The largest of the corresponding time threshold values is assigned to each of them.
  • the total time threshold value at a given speed v ego of the motor vehicle 20, the largest of the time threshold values at the specified speed vego can thus be selected, for example according to Fig.15 shows a flow chart of an embodiment of a special method for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50 that is traveling on the roadway 32.
  • the sensor data can be received that are representative of the fact that the object 50 is located in front of the motor vehicle 20 in the direction of travel.
  • the step S80 can be processed, for example, corresponding to the steps S2, S20 or S67.
  • the speed data can be received that are representative of the current speed vego of the motor vehicle 20.
  • the current speed vego can, for example, be determined using the radar data or retrieved from the storage unit 26.
  • Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 the time period TTC that elapses until the motor vehicle 20 collides with the object 50 can be determined, depending on the sensor data and the speed data.
  • the time period TTC can be defined as ⁇ t c (t) in the form where a distance d(t) from the motor vehicle to the object 50 can be specified with where q tgt (t) the position of the object 50 at time t and q ego (t) describes the position of the motor vehicle 20 at time t.
  • q ego (t) the position vector explained above ⁇ ⁇ ( ⁇ ) without the vehicle orientation, in particular without the yaw angle of the motor vehicle 20.
  • the position q ego (t) of the object 50 can be determined from the sensor data and the position data.
  • the position q ego (t) of the object 50 may correspond to a probable impact point on the object 50.
  • the position q ego (t) of the motor vehicle 20 may, for example, refer to a position of the center of the front bumper of the motor vehicle 20.
  • the parameter d s may refer to a specified safety distance that should be maintained from the object 50 when the motor vehicle 20 has come to a standstill after braking.
  • step S86 the speed-dependent time threshold value ⁇ ⁇ ⁇ ⁇ , ⁇ from- depending on the speed data, in particular depending on the speed v ego of the motor vehicle 20.
  • the speed-dependent Time threshold ⁇ ⁇ ⁇ ⁇ , ⁇ can be determined, for example, using the time threshold lookup table.
  • a step S87 it can be checked whether the determined time period TTC is less than the determined time threshold value. If the condition of step S87 is met, processing can be continued again in step S80. If the condition of step S87 is not met, processing can be continued in a step S88.
  • the control signal for the braking device 24 of the motor vehicle 20 can be generated.
  • the time period TTC that elapses until the motor vehicle 20 collides with the corresponding object 50 can be determined for each of the objects 50, depending on the sensor data and the speed data.
  • the control signal for the braking device 24 can then be generated if one of the determined time periods TTC is less than the determined time threshold value.
  • Fig.16 shows a diagram in which several exemplary lengths l ROI of the area of interest 60 as a function of the speed vego of the motor vehicle 20.
  • the diagram according to Figure 16 and in particular the courses of the lengths l ROI can be determined, for example, by means of simulations corresponding to the individual driving situation or empirically in advance, for example by the manufacturer of the control unit 25 and/or the motor vehicle 20.
  • the lengths l ROI of the area of interest 60 to one of the driving situations i can be determined, for example, according to Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 where ⁇ ⁇ ⁇ corresponds to a trigger distance in the corresponding driving situation, i again indicates the driving situation A, B, C, and the additional term "0.8vego" is provided, which prevents the braking of the motor vehicle 20 due to one of the objects 50 from being triggered at the exact moment in which the corresponding object 50 enters the area of interest 60, which could cause a small delay in the initiation of the braking process.
  • This additional term in particular its amount, can be determined empirically or by means of simulation, for example, and then specified. This results in the various speeds v ego three different lengths each l ROI of the area of interest, especially first lengths l ROI,1 for the first driving situation A, second lengths l ROI,2 for the second driving situation B and third lengths l ROI,3 for the driving situation C.
  • a length look-up table can be generated.
  • the different speeds v ego the respective first length l ROI,1 be assigned if this first length l ROI,1 at the corresponding speed v ego greater than the corresponding second and third length l ROI,2 , l ROI,3 is; the different speeds v ego the respective second length l ROI,2 be assigned if this second length l ROI,2 at the corresponding speed v ego greater than the corresponding first and third length l ROI,1 , l ROI,3 and the different speeds v ego the respective third length l ROI,3 be assigned if this third length l ROI,3 at the corresponding speed v ego greater than the corresponding first and second length l ROI,1 , l ROI,2
  • the different speeds v ego Length reference table the largest of the corresponding lengths Length l ROI,i To determine the area of interest 60, in particular to determine its length l ROI can thus achieve the greatest length l ROI,i in driving situations i at speed v ego
  • a step S90 can be processed corresponding to the step S80.
  • the position data representative of the current vehicle position of the motor vehicle 20 can be received, for example corresponding to the step S22.
  • the speed data can be received, for example corresponding to the step S24.
  • the time period TTC can be determined, for example corresponding to the step S84.
  • the time threshold value can be determined, for example corresponding to the step S86.
  • the length lROI of the region of interest 60 which is located on the roadway 32 in the direction of travel in front of the motor vehicle 20, can be determined depending on the time period TTC and the speed data, for example using the length lookup table.
  • the length l ROI of the area of interest 60 can be determined by determining, depending on the speed v ego of the motor vehicle 20 and the determined time threshold value, a trigger distance is determined, wherein the trigger distance is the distance between the object 50 and the motor vehicle 20 that the object 50 has to the motor vehicle 20 when the time period TTC falls below the corresponding time threshold value.
  • the length l ROI be selected so that it is greater than the trigger distance.
  • a step S97 it can be checked whether the object 50 is located in the area of interest 60, depending on the sensor data, for example corresponding to step S66 and/or corresponding to the method explained with reference to Figure 8.
  • the control signal for the braking device 24 can be generated, for example corresponding to one of the steps S12, S36 or S56.
  • the general method explained above for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50, the special methods explained above for avoiding or reducing the collision of the autonomous motor vehicle 20 with the object 50 and/or the other methods explained above can be combined with one another as desired.
  • the general method can serve as a basic framework and the special methods can optionally serve as building blocks of the basic framework, for example depending on the specific application.
  • the region of interest 60 should be determined on a position-based or speed-based basis, for example as in the method explained with reference to Figure 3.
  • the sensor data can be fused, as in the method explained with reference to Figure 5.
  • the region of interest 60 can be determined on a position-based basis, for example as in the method explained with reference to Figure 8.
  • the region of interest 60 can be determined based on speed, for example as in the method explained with reference to Internal ZF Friedrichshafen AG File 213055 Friedrichshafen 2022-11-30 Figure 11.
  • it can be checked whether the motor vehicle 20 is currently in lane 34, 36, for example as in the method explained with reference to Figure 13.
  • the time period TTC can be determined, for example as in the method explained with reference to Figure 15.
  • the length l ROI of the region of interest 60 can be determined, for example as in the method explained with reference to Figure 17.

Landscapes

  • Chemical & Material Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Materials Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Metallurgy (AREA)
  • Organic Chemistry (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Composite Materials (AREA)
  • Manufacturing & Machinery (AREA)
  • Electromagnetism (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Traffic Control Systems (AREA)

Abstract

L'invention concerne un procédé de détermination basée sur la position d'une zone d'intérêt (60) située dans une voie (34, 36) devant un véhicule automobile (20) dans le sens de déplacement. Le procédé consiste à : recevoir des données de position représentant une position actuelle du véhicule à moteur (20) ; déterminer des positions de point de référence de points de référence (94, 96) le long de la voie (34), les points de référence (94, 96) représentant un trajet de la voie (34, 36) devant le véhicule à moteur (20) dans la direction de déplacement, en fonction des données de position sur la base d'une table de consultation de voie dans laquelle les positions de point de référence sont attribuées aux points de référence (94, 96) ; et déterminer la région d'intérêt (60) en fonction des points de référence (94, 96) et en fonction d'une largeur (B) du véhicule à moteur (20).
PCT/EP2023/083340 2022-11-30 2023-11-28 Procédé, dispositif de commande et programme informatique de détermination basée sur la position d'une région d'intérêt et support de stockage lisible par ordinateur Ceased WO2024115473A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102022212875.3A DE102022212875A1 (de) 2022-11-30 2022-11-30 Verfahren, Steuergerät und Computerprogramm zum positionsbasierten Ermitteln eines interessierenden Bereichs, und computerlesbares Speichermedium
DE102022212875.3 2022-11-30

Publications (1)

Publication Number Publication Date
WO2024115473A1 true WO2024115473A1 (fr) 2024-06-06

Family

ID=91079204

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/EP2023/083340 Ceased WO2024115473A1 (fr) 2022-11-30 2023-11-28 Procédé, dispositif de commande et programme informatique de détermination basée sur la position d'une région d'intérêt et support de stockage lisible par ordinateur

Country Status (2)

Country Link
DE (1) DE102022212875A1 (fr)
WO (1) WO2024115473A1 (fr)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102023201699A1 (de) 2023-02-24 2024-08-29 Zf Friedrichshafen Ag Verfahren zum Ermitteln eines Überlappungswerts, Verfahren zum Überprüfen eines interessierenden Bereichs, Verfahren zum Überprüfen eines vorgegebenen Verlaufs einer Fahrspur, Verfahren zum Überprüfen einer Objektdetektionswahrscheinlichkeit und Steuergerät

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102018129079A1 (de) * 2017-11-22 2019-05-23 GM Global Technology Operations LLC Fahrbahnkorridor
US20210188286A1 (en) * 2019-12-20 2021-06-24 Baidu Usa Llc A spline curve and spiral curve based reference line smoothing method
EP3882815A1 (fr) * 2020-03-20 2021-09-22 Aptiv Technologies Limited Procédé de génération d'un réseau dynamique

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102011003614A1 (de) * 2011-02-03 2012-08-09 Robert Bosch Gmbh Verfahren zur Festlegung eines Suchkorridors in einem Überwachungssystem in einem Fahrzeug
DE102018001581A1 (de) * 2018-02-28 2018-08-02 Daimler Ag Verfahren zur Prädiktion des Fahrverhaltens anderer Verkehrsteilnehmer
DE102019204260A1 (de) * 2019-03-27 2020-10-01 Zf Friedrichshafen Ag Steuern eines Kraftfahrzeugs
DE102020213588A1 (de) * 2020-10-29 2022-05-05 Robert Bosch Gesellschaft mit beschränkter Haftung Verfahren und Vorrichtung zum Betreiben eines automatisierten Fahrzeugs

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102018129079A1 (de) * 2017-11-22 2019-05-23 GM Global Technology Operations LLC Fahrbahnkorridor
US20210188286A1 (en) * 2019-12-20 2021-06-24 Baidu Usa Llc A spline curve and spiral curve based reference line smoothing method
EP3882815A1 (fr) * 2020-03-20 2021-09-22 Aptiv Technologies Limited Procédé de génération d'un réseau dynamique

Non-Patent Citations (4)

* Cited by examiner, † Cited by third party
Title
A. J. DE GRAAF: "Technical Report (unnumbered", September 2003, FROG NAVIGATION SYSTEMS B.V., article "A generic vehicle controller"
A. J. DE GRAAF: "Technical Report", July 2012, 2GETTHERE B.V., article "Steering pole"
INTERFACE SPECIFICATION FOR IBEO LUX, IBEO LUX SYSTEMS AND IBEO EVALUATION SUITE, 28 July 2017 (2017-07-28)
TECHNICAL DOCUMENTATION, ARS 404-21 (ENTRY), ARS 408-21 (PREMIUM, 18 May 2018 (2018-05-18)

Also Published As

Publication number Publication date
DE102022212875A1 (de) 2024-06-06

Similar Documents

Publication Publication Date Title
EP3160813B1 (fr) Procédé de création d'un modèle d'environnement d'un véhicule
EP2676857B1 (fr) Procédé et dispositif de génération d'un paramètre de commande pour un système d'assistance de distance d'un véhicule à base d'images
DE112020005236T5 (de) Fahrzeugsteuergerät und fahrzeugsteuersystem
DE102018203615A1 (de) Einrichtung und Verfahren zum Steuern des Platooning von Fahrzeugen
DE102019103352A1 (de) Trajektorienverfolgung für die fahrzeugseitensteuerung unter verwendung eines neuronalen netzwerks
WO2020089311A1 (fr) Système de commande et procédé de commande de planification, sur la base d'échantillonnages, de trajectoires possible pour des véhicules automobiles
DE102018113926A1 (de) Autonome Fahrzeugantriebssysteme und Verfahren für kritische Zustände
DE102017100633B4 (de) Präventions-sicherheitsvorrichtung für die kursänderung eines kleinfahrzeugs
DE102023132342A1 (de) Fahrzeug zur kollisionsvermeidung und verfahren zum betrieb desselben
DE102018219665B4 (de) Steuereinheit zum Betreiben eines autonomen Fahrzeugs
DE102015114464A9 (de) Einheitlicher Bewegungsplaner für ein autonom fahrendes Fahrzeug beim Ausweichen vor einem bewegten Hindernis
WO2014161691A1 (fr) Procédé et dispositif de guidage d'un véhicule dans l'environnement d'un objet
DE102021127028A1 (de) Systeme und verfahren für anpassbare heckkollisionswarnmeldungen
DE112021006846T5 (de) Systeme und Verfahren zur szenarioabhängigen Trajektorienbewertung
WO2020002100A1 (fr) Procédé de fonctionnement d'un véhicule au moins partiellement automatisé
DE102015015302A1 (de) Verfahren zum teil- oder vollautonomen Betrieb eines Fahrzeugs und Fahrerassistenzvorrichtung
DE112022001981T5 (de) Pönalisierung des Gegenlenkens bei Fahrzeugkurvenfahrten
DE112022001133T5 (de) Systeme und Verfahren zur Fahrzeugbewegungsplanung
DE102012007127A1 (de) Verfahren zum Bestimmen einer Bewegungsbahn für ein Fahrzeug
DE102023133786A1 (de) Steuerungsvorrichtung eines autonomen fahrzeugs und verfahren dazu
EP4185506A1 (fr) Procédé permettant de déterminer une trajectoire pour commander un véhicule
WO2024115473A1 (fr) Procédé, dispositif de commande et programme informatique de détermination basée sur la position d'une région d'intérêt et support de stockage lisible par ordinateur
DE102023203305A1 (de) Fahrzeug und Durchführung eines risikominimalen Manövers und Verfahren zum Betreiben des Fahrzeugs
WO2024115472A1 (fr) Procédé, dispositif de commande et programme informatique pour empêcher ou réduire une collision d'un véhicule autonome avec un objet et support de stockage lisible par ordinateur
DE102022212888A1 (de) Verfahren, Steuergerät und Computerprogramm zum Vermeiden oder Vermindern einer Kollision eines autonomen Kraftfahrzeugs mit einem Objekt, und computerlesbares Speichermedium

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 23814179

Country of ref document: EP

Kind code of ref document: A1

122 Ep: pct application non-entry in european phase

Ref document number: 23814179

Country of ref document: EP

Kind code of ref document: A1