WO2021260283A1 - Method and device for controlling the movement of a vehicle - Google Patents

Method and device for controlling the movement of a vehicle Download PDF

Info

Publication number
WO2021260283A1
WO2021260283A1 PCT/FR2021/050798 FR2021050798W WO2021260283A1 WO 2021260283 A1 WO2021260283 A1 WO 2021260283A1 FR 2021050798 W FR2021050798 W FR 2021050798W WO 2021260283 A1 WO2021260283 A1 WO 2021260283A1
Authority
WO
WIPO (PCT)
Prior art keywords
dimensional
vehicle
dimensional point
cloud
current
Prior art date
Application number
PCT/FR2021/050798
Other languages
French (fr)
Inventor
Guillaume POINT
Audrey RIZZO
Original Assignee
Psa Automobiles Sa
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Psa Automobiles Sa filed Critical Psa Automobiles Sa
Priority to EP21732960.6A priority Critical patent/EP4168828A1/en
Publication of WO2021260283A1 publication Critical patent/WO2021260283A1/en

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
    • 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
    • G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
    • 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
    • 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
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
    • G01S7/4808—Evaluating distance, position or velocity data

Definitions

  • the invention relates to a method and device for controlling the movement of a vehicle, in particular of the automobile type, from a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle.
  • ADAS driver assistance systems
  • ADAS Advanced Driver-Assistance System
  • French Advanced Driver Assistance System
  • the most advanced driving assistance systems control the movement of the vehicle which becomes a so-called autonomous vehicle, that is to say a vehicle capable of driving in the road environment without the intervention of the driver.
  • An autonomous vehicle of level higher than 2 must be able to estimate the free space all around the vehicle.
  • this type of vehicle is generally equipped with various sensors such as video cameras, LIDAR (in English “Laser Detection And Ranging”) or other which are distributed all around the vehicle, in particular on the windshield, the windshields. front and rear shocks or on the roof.
  • the data from these sensors can be used, for example by an ADAS system, to estimate the free space located near the vehicle and thus anticipate the driving of the vehicle to avoid any collision with an object in this environment. This is the case, in particular, when the vehicle is traveling on a lane and is approaching another vehicle. An estimate of the free space located between these two vehicles then makes it possible to anticipate possible braking. This is also the case when the vehicle must park in a parking space. An estimate of the free space between the vehicle and any object, wall, ceiling or other parked vehicle helps prevent a collision. This is also the case when the vehicle is traveling in an urban area where the estimation of the free space located in front, behind or on its sides can prove useful to anticipate any collision with possible cyclists, vehicles, street furniture. or other object.
  • An object of the present invention is to improve the existing methods making it possible to control the movement of a vehicle by estimating the free space accessible to it. vehicle from a cloud of three-dimensional data from on-board sensors in this vehicle.
  • the invention relates to a method for controlling the movement of a vehicle, comprising a step of acquiring a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle; a step of transforming the three-dimensional data cloud into a two-dimensional point cloud expressed in a polar coordinate frame associated with a plane, to each three-dimensional data item corresponds a two-dimensional point defined by a radial distance between a pole of the polar coordinate frame and the two-dimensional point, and an azimuth angle defined between the plane and a segment connecting the pole and the two-dimensional point; an iterative step of modifying the two-dimensional point cloud by deleting a current two-dimensional point when two neighboring two-dimensional points current two-dimensional point are not sufficiently distant from each other to avoid a collision between the vehicle and an object near this vehicle; and a step of controlling the movement of said vehicle as a function of a convex envelope formed by the two-dimensional point cloud thus modified and defining a free space accessible to the vehicle
  • the method transforms the three-dimensional data cloud into a two-dimensional point cloud and determines a polygonal convex envelope from a modified two-dimensional point cloud.
  • This convex envelope provides an estimate of the free space accessible to the vehicle.
  • a system for controlling the movement of the vehicle implementing the method can then control the movement of the vehicle as a function of this convex envelope.
  • the method uses simple geometric principles of low complexity compared to those of a method based on a neural network for example. It therefore requires little computing resources.
  • the convex envelopes obtained are representative of what is expected in terms of a convex envelope that closely matches a two-dimensional point cloud while respecting steric non-collision constraints.
  • the method does not make use of artificial intelligence techniques, therefore does not suffer from the problems associated with this type of technique such as, in particular, validation and security problems.
  • the method is independent of the technology or of the sensor model used, as long as the latter provides a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle.
  • the method is robust and capable of respecting the constraints of real hard time. This is one of the crucial elements for the development of autonomous driving systems above level 2 which must also operate in all conditions (night, precipitation, etc.).
  • an iteration of the iterative step comprises a sub-step of obtaining at least one current two-dimensional point of the two-dimensional point cloud having a high radial distance; and for each current two-dimensional point, a sub-step of calculating a first minimum distance between a segment connecting a current two-dimensional point and the pole of the reference frame of polar coordinates, and another two-dimensional point of the two-dimensional point cloud determined so as to that the difference between the azimuth angle of said other two-dimensional point and the azimuth angle of the current two-dimensional point is minimal and positive; a sub-step of calculating a second minimum distance between said segment and another two-dimensional point of the two-dimensional point cloud determined so that the difference between the azimuth angle of said other two-dimensional point and the angle of azimuth of the current two-dimensional point is minimum and negative; and a sub-step of removing a current two-dimensional point from the two-dimensional point cloud when the sum of the first and second distances is
  • an iteration of the iterative step comprises a substep for obtaining at least one pair formed of a first and a second successive two-dimensional points having distances minimum radials among a set of two-dimensional points sorted according to their azimuth angle; and for each current pair of two-dimensional points thus formed: a sub-step of deleting all the two-dimensional points from the two-dimensional point cloud whose azimuth angles are between the azimuth angles of the first and second two-dimensional points of a current torque when the absolute value of the difference between the azimuth angles of the first and second two-dimensional points of said current torque is less than a threshold value defined to avoid a collision between the vehicle and an object near this vehicle; said two-dimensional points of the two-dimensional point cloud are preserved when the absolute value of said difference is greater than the threshold value.
  • the method further comprises an (optional) step of deleting the three-dimensional data corresponding to echoes from the ground. This step removes three-dimensional data which correspond to ground echoes and which are therefore irrelevant for estimating the free space around the vehicle.
  • the method further comprises a step of filtering the cloud of two-dimensional points making it possible to keep only a single two-dimensional point per azimuth angle.
  • At least one sensor is a transmitter / receiver of electromagnetic waves, preferably in the infrared range, of the LIDAR type or a radio wave transmitter / receiver such as a radar.
  • the invention relates to a device for moving a vehicle, comprising at least one emitter / receiver of electromagnetic waves and / or radio waves and a memory associated with at least one processor configured for setting up. implementation of the steps of the above method.
  • the invention relates to a vehicle comprising the above device.
  • the invention relates to a computer program product comprising instructions adapted for performing the above method steps when the computer program is executed by at least one processor.
  • FIG. 1 schematically illustrates a vehicle 1 carrying several sensors 10, 11, 12, 13 and 14 according to a particular and non-limiting embodiment of the present invention
  • FIG. 2 schematically illustrates a three-dimensional mark associated with a vehicle according to a particular embodiment of the present invention
  • FIG. 3 illustrates a flowchart of the various steps of a method for controlling the movement of a vehicle of FIG. 1, according to a particular and non-limiting example of the present invention
  • FIG. 4 illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to a particular and non-limiting exemplary embodiment of the present invention
  • FIG. 5 schematically illustrates the various sub-steps of step 350 of FIG. 4, according to another particular and non-limiting example of embodiment of the present invention
  • FIG. 6 illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to another particular and non-limiting exemplary embodiment of the present invention
  • FIG. 7 schematically illustrates the various sub-steps of step 350 of FIG. 6, according to another particular and non-limiting exemplary embodiment of the present invention.
  • FIG. 8 schematically illustrates a device configured to control the movement of a vehicle of Figure 1, according to a particular non-limiting embodiment of the present invention.
  • FIG. 1 schematically illustrates a vehicle 1, for example a motor vehicle or more generally a land motor vehicle, carrying several sensors 10, 11, 12, 13 and 14 according to a particular and non-limiting example of the present invention.
  • the sensors 10 and 11 are positioned on the front and rear bumpers of the vehicle 1, the sensors 12 and 13 on the sides and the sensor 14 on the roof.
  • This example of the positioning of the sensors as well as the number of sensors are given only as an indication and in no way limit the scope of the invention. Indeed, several other sensors can be positioned in various other places of the vehicle such as on the windshield, windows, doors, etc.
  • the sensors 10 to 14 on board the vehicle 1 are sensors suitable for emitting and receiving waves and determining the distance from surrounding objects by analysis of the emitted waves which are reflected on objects located at proximity to the vehicle and in the field of action of these sensors.
  • These sensors 10 to 14 are periodically active. The period between two emissions may depend on the movement of the vehicle. It may for example depend on the speed of the vehicle. The faster the vehicle, the shorter the period can be.
  • the activity of sensors can still be continuous when, in particular, the vehicle is looking for a parking space and / or is maneuvering to park in a parking space.
  • the activation of these sensors can also be individualized. For example, if the vehicle is backing up, the sensors on the front of the vehicle are not activated.
  • a sensor once activated, makes it possible to detect objects in the environment of the vehicle and to measure the distance between the sensor and the detected objects. These objects can be, for example, other vehicles, pedestrians, cyclists, street furniture, reflective strips delimiting a parking space, etc.
  • the active sensor emits waves that reflect off these objects.
  • the active sensor collects these reflected waves and identifies the position and the distance of the objects located near the vehicle 1 as a function of these emitted and reflected waves.
  • a multi-dimensional data cloud is then formed. Each of these multidimensional data corresponds to at least one emitted wave which has been reflected by an object.
  • the free space accessible to a vehicle is defined as a set of data expressed in a multidimensional space. These data can theoretically take all the possible values in this space of the kinematic parameters of the vehicle, taking into account the constraints of non-collision with objects present around it.
  • the multi-dimensional space is a subspace of M 6 corresponding to the three parameters of position (x, y, z) and orientation ⁇ a, b, g) of the vehicle in the space.
  • the vehicle will be assumed to be spherical with a sufficient radius to ensure compliance with the non-collision constraints.
  • the dimensions relative to the orientation are degenerated, and the data space is reduced to a three-dimensional space (x, y, z) as illustrated in figure 2.
  • the dimensionality of this three-dimensional space (x, y, z) can be reduced by assuming that a vehicle is moving on a locally flat surface, and that the extension of the instantaneous scene of which the vehicle is the center is much less depending on the 'z axis than along the x and y axes.
  • the dimensionality of the three-dimensional space can therefore be reduced to a two-dimensional space (x, y).
  • the three-dimensional data obtained from the sensors on board the vehicle will therefore be represented by two-dimensional data expressed in a coordinate system (0, x, y).
  • the invention then consists in determining a convex envelope in this two-dimensional space representing the free space accessible to the vehicle 1.
  • This convex envelope complies with the constraints of non-collision between this vehicle and any surrounding objects. Due to the discrete nature of the information available, in the form of a three-dimensional data cloud, this convex envelope is a polygon whose vertices are two-dimensional points originating from the three-dimensional data cloud.
  • FIG. 3 illustrates a flowchart of the various steps of a method for estimating free space accessible to a vehicle of FIG. 1, according to a particular and non-limiting example of the present invention.
  • Each three-dimensional data represents the coordinates of a point in three-dimensional space.
  • the three-dimensional data cloud can be represented by a matrix P of dimension 3xN formed of three vectors X, YZ of dimension N representing the coordinates xi, yi, zi of the three-dimensional data Pw [Math 1] with respectively ⁇ and of f Z represents the transpose of the vector X, respectively Y and Z.
  • At least one sensor is a transmitter / receiver of electromagnetic waves, for example of the LIDAR type, and / or a transmitter / receiver of radio waves.
  • a LIDAR sensor makes it possible to detect objects in the environment of the vehicle and to measure the distance between the sensor and the objects detected by the emission of light rays (electromagnetic waves) emitted by lasers radiating preferably in the non-visible range ( infrared for example).
  • the method comprises a step 320 (optional) of deleting the three-dimensional data corresponding to echoes from the ground.
  • the segmentation algorithm of B. Douillard et al. (On the Segmentation of 3D LIDAR Point Clouds", 2011 IEEE International Conference on Robotics and Automation (http://dx.doi.Org/10.1109/ICRA.2011.5979818)) can be used to isolate three-dimensional data that correspond to ground echoes of other three-dimensional data and remove those isolated three-dimensional data.
  • We can also use the algorithm of I. Bogoslavskiy & C. Stachniss (“Efficient Online Segmentation for Sparse 3D Laser Scans", Photogrammetrie - Fernerkundung - Geoinformation 85, 41 (2016) (http://dx.doi.org/10.1007 / s41064-016-0003-y), or that of Y.
  • the three-dimensional data cloud Pi is transformed into a cloud of two-dimensional points Mi expressed in a reference frame of polar coordinates (r, ⁇ p) associated with a plane P with r a polar coordinate called the radial distance defined between a pole O of the polar coordinate system and a two-dimensional point belonging to the plane P and f another polar coordinate called the azimuth angle defined between the plane P and a segment connecting the pole O and the two-dimensional point of the plane P as shown in the figure 5.
  • each three-dimensional datum Pi corresponds a two-dimensional point Mi of the plane P.
  • the case may arise where several two-dimensional points share the same azimuth angle. This may be due to a mode of operation of a sensor which can record several echoes for a single emitted wave, for example when the laser beam meets a window, then a solid obstacle further away. This can also be due to the sampling steps of the sensors to determine an azimuth angle.
  • the transform of the three-dimensional data cloud Pi represented by points Mi expressed in the coordinate system (0, x, y), into a cloud P s of two-dimensional points Mi expressed in a coordinate system with polar coordinates (t, f) is given by:
  • P s is a 2xN-dimensional matrix formed by two vectors R and F of dimension N and the function arctan2 is the four-quadrant arc tangent giving the value of an angle in the interval [0,2p [.
  • P s can therefore be described as a function of a single scalar variable r ( ⁇ p).
  • the method comprises a step 340 (optional) which filters the three-dimensional data cloud Pi by keeping only a single two-dimensional point Mi per azimuth angle value.
  • step 340 when several two-dimensional points share a same azimuth angle value and different radial distance values, only the two-dimensional point having the smallest radial distance is kept in the two-dimensional point cloud.
  • step 340 when several two-dimensional points share the same azimuth angle value and different radial distance values, a two-dimensional point is created with said azimuth angle value and an equal radial distance to a value obtained from the values of the radial distances of these two-dimensional points such as the average or the median of these radial distances.
  • the cloud Ps of two-dimensional points is modified by deleting a current two-dimensional point when two two-dimensional points neighboring the current two-dimensional point are not sufficiently distant from each other to avoid a collision between the vehicle and an object near that vehicle.
  • the two-dimensional point cloud Ps thus modified forms a convex envelope of the free space accessible to the vehicle.
  • a step 360 the movement of the vehicle is controlled by a control system which implements the previous steps to obtain this cloud P s of two-dimensional points.
  • This two-dimensional point cloud forms a convex envelope of the free space accessible to the vehicle and this control system can then indicate what are the possible movements of the vehicle as a function of this convex envelope.
  • FIG. 4 illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to a particular and non-limiting exemplary embodiment of the present invention.
  • a sub-step 351 at least one current two-dimensional point Mi.max of the cloud P s of two-dimensional points having a high radial distance is obtained.
  • a given number of current two-dimensional points Mi.max having the highest radial distances are obtained from the cloud P s of two-dimensional points.
  • any two-dimensional point of the cloud Ps of two-dimensional points whose radial distance is greater than a given threshold value is a current two-dimensional point Mi.
  • a current two-dimensional point Mi.max is obtained from a subset of the two-dimensional points of the cloud Ps of two-dimensional points.
  • a current two-dimensional point Mi.max is then a two-dimensional point of this subset which has the maximum radial distance (the highest among the radial distances of the other two-dimensional points of this subset).
  • a subset of the two-dimensional point cloud Ps can be obtained, for example, by grouping the two-dimensional points according to their azimuth angles sorted in ascending order, for example. It is in fact possible to partition a circle into different angular sectors and create a subset of two-dimensional points per angular sector.
  • a two-dimensional point having its azimuth angle which belongs to a given angular sector then belongs to the subset associated with this angular sector. It is also possible to envisage forming subsets of a given number of successive two-dimensional points, that is to say of two-dimensional points whose azimuth angles follow one another in a list of the azimuth angles of the two-dimensional points sorted according to an order, for example ascending. A first two-dimensional point is added to a first subset. Then the two-dimensional point whose azimuth angle is the next in the list is also added to this first subset, and so on until the two-dimensional point subset has reached a given number of points two-dimensional. Another sub-subset is then formed until the two-dimensional points of the two-dimensional point cloud Ps are exhausted.
  • Sub-steps 352, 353 and 354 are executed for each current two-dimensional point Mi.max
  • a first minimum distance D1 is calculated between a segment connecting the current two-dimensional point Mi.max and the pole O of the coordinate system with polar coordinates, and another two-dimensional point Mi + i of the cloud P s of two-dimensional points or, according to a variant, of a subset of the cloud Ps.
  • This two-dimensional point Mi + i is determined so that the difference between its azimuth angle ⁇ p i + 1 and l ' azimuth angle (p t of the current two-dimensional point Mi.max is minimal and positive when one considers that the azimuth angles increase in the anti-clockwise direction.
  • a second minimum distance D2 is calculated between a segment connecting the current two-dimensional point Mi.max and the pole O of the reference frame of polar coordinates, and another two-dimensional point MM of the cloud Ps of two-dimensional points or, according to a variant, of a subset of the cloud Ps.
  • This two-dimensional point MM is determined so that the difference between its azimuth angle and the azimuth angle (p t of the current two-dimensional point Mi is minimal and negative when one considers that the azimuth angles increase in the anti-clockwise direction.
  • the distances D1 and D2 ensure that the two-dimensional points Mi + i and Mi-i are the “left” and “right” neighboring two-dimensional points of the closest current two-dimensional point Mi.max.
  • the current two-dimensional point Mi.max is then deleted from the cloud P s of two-dimensional points when the sum of the first and second distances D1 and D2 is less than a threshold value T.
  • the current two-dimensional point Mi.max is kept when the sum of the first and second distances is greater than the threshold value.
  • the method determines whether a new iteration of step 350 is necessary by checking whether a condition is satisfied or not. If a new iteration of step 350 is required, substeps 351 to 354 are executed again. According to one example, the method stops when no two-dimensional point Mi, max is deleted in the previous step.
  • the process stops when a number of two-dimensional points have been deleted.
  • FIG. 6 illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to another particular and non-limiting exemplary embodiment of the present invention.
  • At least one pair formed of a first and a second successive two-dimensional points is formed.
  • the two-dimensional points of the point cloud P s are sorted according to an order, for example increasing, of their azimuth angles.
  • Two two-dimensional points are then said to be successive when the difference in azimuth angles is minimal.
  • a first and a second two-dimensional point form a couple when they are successive and when they have the smallest (minimum) radial distances among the radial distances of a set of two-dimensional points.
  • each pair of two-dimensional points Mj and Mk is obtained from the cloud P s of two-dimensional points.
  • the two-dimensional points Mj and Mk are then successive two-dimensional points of the cloud Ps which have a radial distance less than a threshold value.
  • each pair of two-dimensional points Mj and Mk is obtained from a subset of the two-dimensional points of the cloud Ps.
  • the two-dimensional points Mj and Mk are then successive two-dimensional points of this subset of the cloud P s which have minimum radial distances (the smallest among the radial distances of the other two-dimensional points of this subset of the cloud P s ).
  • a subset of the Ps cloud can be obtained, for example, by grouping the two-dimensional points according to their azimuth angles. It is in fact possible to partition a circle into different angular sectors and create a subset of two-dimensional points per angular sector. A two-dimensional point having its azimuth angle which belongs to a given angular sector then belongs to the subset associated with this angular sector. It is also possible to envisage forming sub- sets of a given number of successive two-dimensional points. A first two-dimensional point is added to a first subset. Then the two-dimensional point having a positive and minimum azimuth angle difference with the first two-dimensional point is also added to this first subset. And so on until the subset of two-dimensional points has reached a given number of two-dimensional points. Another sub-subset is then formed until the two-dimensional points of the cloud Ps are exhausted.
  • a sub-step 356 illustrated in FIG. 7 for each pair of two-dimensional points Mj and Mk consult the two-dimensional points M P with j ⁇ p ⁇ k, corresponding to the two-dimensional points whose azimuth angles lie between the angles azimuth of the two-dimensional points Mj and Mk are then deleted when the absolute value of the difference between the azimuth angles of the two-dimensional points Mj and Mk is less than a threshold value T. Said two-dimensional points are kept when the absolute value of said difference is greater than the threshold value T.
  • step 350 determines whether a new iteration of step 350 is necessary by checking whether a condition is true or not. If a new iteration of step 350 is required, substeps 355 through 357 are executed again.
  • the process stops when a given number of two-dimensional points have been deleted.
  • the method stops when no two-dimensional point has been deleted in a previous iteration.
  • the threshold value T is defined to avoid any collision between the vehicle and an object near this vehicle. Indeed, only the two-dimensional points distant by a value greater than the threshold value T are used to form the convex envelope of the free space.
  • the cloud P s is formed from three-dimensional data coming from sensors located on the front of the vehicle, the convex envelope formed by the corresponding two-dimensional points will indicate that the vehicle can pass between these two-dimensional points without risk of collision. It is the same for any convex envelope formed by a cloud of three-dimensional data. modified according to the invention. The vehicle can thus move without risk of collision between the three-dimensional data of the convex envelope.
  • the threshold value T varies according to the dimensions of the vehicle.
  • the threshold value T is at least equal to the width of the vehicle.
  • the threshold value is at least equal to the length of the vehicle.
  • the threshold value T is greater than the dimensions of the vehicle to increase the free space and thus facilitate maneuvering of the vehicle inside the convex envelope representing this free space without risk of collision
  • FIG. 8 schematically illustrates a device 400 configured to control the movement of a vehicle based on the estimate of the free space accessible to this vehicle, according to a particular and non-limiting embodiment of the present invention.
  • the device 400 corresponds for example to a device on board the vehicle, such as for example a computer or a set of computers.
  • the device 400 is for example configured for the implementation of the steps of the method described with reference to FIGS. 3, 4 and / or 6.
  • Examples of such a device 400 include, without being limited thereto, on-board electronic equipment such as 'an on-board computer of a vehicle, an electronic computer such as an ECU (“Electronic Control Unit”), a smart phone (from the English “smartphone”), a tablet, a laptop computer.
  • ECU Electronic Control Unit
  • smart phone from the English “smartphone”
  • a tablet a laptop computer.
  • the elements of the device 400 individually or in combination, can be integrated in a single integrated circuit, in several integrated circuits, and / or in discrete components.
  • the device 400 can be produced in the form of electronic circuits or software (or computer) modules or else a combination of electronic circuits and software modules.
  • the device 400 is coupled in communication with other devices or similar systems, for example by means of a communication bus or through dedicated input / output ports.
  • the device 400 comprises one (or more) processor (s) 410 configured to execute instructions for carrying out the steps of the method and / or for executing the instructions of the software (s) embedded in the device 410.
  • the processor 410 can include integrated memory, an input / output interface, and various circuits known to those skilled in the art.
  • the device 410 further comprises at least one memory 420 corresponding for example to a volatile and / or non-volatile memory and / or comprises a memory storage device which may comprise volatile and / or non-volatile memory, such as EEPROM, ROM , PROM, RAM, DRAM, SRAM, flash, magnetic or optical disk.
  • EEPROM electrically erasable programmable read-only memory
  • ROM read-only memory
  • PROM electrically erasable programmable read-only memory
  • RAM random access memory
  • DRAM dynamic random access memory
  • SRAM static random access memory
  • flash magnetic or optical disk
  • the computer code of the on-board software (s) comprising the instructions to be loaded and executed by the processor is for example stored in the memory 420.
  • the device 400 comprises a block 430 of interface elements for communicating with external devices, for example a remote server or the “cloud”, devices such as a communication reader. near field or a radio receiver.
  • Block 430 of interface elements is also configured to receive a three-dimensional data cloud from on-board sensors such as sensors 10-14.
  • Block 430 of interface elements is also configured to emit a two-dimensional point cloud. and / or a convex envelope formed from this two-dimensional point cloud resulting from the method described with reference to FIGS. 3, 4 and / or 6.
  • the interface elements of block 430 include one or more of the following interfaces:
  • radiofrequency interface for example of the Bluetooth® or Wi-Fi® type, LTE (from English “Long-Term Evolution” or in French “Long-term Evolution”), LTE-Advanced (or in French LTE-advanced );
  • USB interface from English “Universal Serial Bus” or “Bus Universel en Série” in French);
  • the device 400 comprises a communication interface 440 which makes it possible to establish communication with other devices via a communication channel 450.
  • the communication interface 440 corresponds for example to a transmitter configured for transmitting and receiving information and / or data via the communication channel 450 such as three-dimensional data clouds, two-dimensional point clouds and / or convex envelopes formed from these two-dimensional point clouds.
  • the communication interface 440 corresponds for example to a wired network of the CAN type (standing for “Controller Area Network” or in French “Network of controllers”), CAN FD (standing for “Controller Area Network Flexible Data”). Rate ”or in French
  • Flexible data rate controller network FlexRay (according to ISO 17458) or Ethernet (according to ISO / IEC 802.3).
  • the device 400 can supply output signals to one or more external devices, such as a display screen, one or more speakers and / or other peripherals respectively via interfaces. output not shown.
  • one or more external devices such as a display screen, one or more speakers and / or other peripherals respectively via interfaces. output not shown.
  • the vehicle 1 of Figure 1 carries a device of Figure 7.
  • the invention is not limited to the embodiments described above but extends to a method of controlling the use of a vehicle, and to the device configured for implementing the method.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • General Physics & Mathematics (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Electromagnetism (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)

Abstract

The invention relates to a method and device for controlling the movement of a vehicle. The method acquires a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle; transforms the cloud of three-dimensional data into a cloud of two-dimensional points expressed in a polar coordinate system, modifies this two-dimensional point cloud by deleting a current two-dimensional point whenever two two-dimensional points adjacent to the current two-dimensional point are not sufficiently far away from each other to avoid a collision between the vehicle and an object close to this vehicle, and controls the movement of the vehicle as a function of a convex envelope formed by the two-dimensional point cloud modified in this way and defining a free space accessible to the vehicle.

Description

DESCRIPTION DESCRIPTION
Titre : Procédé et dispositif de contrôle du déplacement d’un véhicule La présente invention revendique la priorité de la demande française 2006537 déposée le 23.06.2020 dont le contenu (texte, dessins et revendications) est ici incorporé par référence. Title: Method and device for controlling the movement of a vehicle The present invention claims the priority of French application 2006537 filed on 06.23.2020, the content of which (text, drawings and claims) is incorporated here by reference.
Domaine technique Technical area
L’invention concerne un procédé et dispositif de contrôle du déplacement d’un véhicule, notamment de type automobile, à partir d’un nuage de données tridimensionnelles obtenues par réflexion d’ondes émises par des capteurs embarqués sur le véhicule. The invention relates to a method and device for controlling the movement of a vehicle, in particular of the automobile type, from a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle.
Arrière-plan technologique Technological background
Il est connu des systèmes d’aide à la conduite, dit ADAS (de l’anglais « Advanced Driver-Assistance System » ou en français « Système d’aide à la conduite avancé »), pour guider ou contrôler le déplacement d’un véhicule dans son environnement pour atteindre sa destination. Les systèmes d’aide à la conduite les plus aboutis assurent le contrôle du déplacement du véhicule qui devient un véhicule dit autonome, c’est-à-dire un véhicule apte à rouler dans l’environnement routier sans intervention du conducteur. Un véhicule autonome de niveau supérieur à 2 doit être en mesure de pouvoir estimer l’espace libre tout autour du véhicule. Pour cela, ce type de véhicule est généralement équipé de divers capteurs tels que des caméras vidéo, LIDAR (en anglais « Laser Détection And Ranging ») ou autre qui sont répartis tout autour du véhicule, notamment sur le pare-brise, les pare-chocs avant et arrière ou encore sur le toit. Lorsque le véhicule se déplace dans un environnement, les données issues de ces capteurs peuvent être utilisés, par exemple par un système ADAS, pour estimer l’espace libre situé à proximité du véhicule et ainsi anticiper la conduite du véhicule pour éviter toute collision avec un objet de cet environnement. C’est le cas, notamment, lorsque le véhicule roule sur une voie et qu’il se rapproche d’un autre véhicule. Une estimation de l’espace libre situé entre ces deux véhicules permet alors d’anticiper un éventuel freinage. C’est aussi le cas lorsque le véhicule doit stationner sur une place de parking. Une estimation de l’espace libre entre le véhicule et tout objet, mur, plafond ou autre véhicule stationné permet d’éviter toute collision. C’est également le cas lorsque le véhicule circule dans une zone urbaine où l’estimation de l’espace libre situé devant, derrière ou sur ses côtés peut s’avérer utile pour anticiper toute collision avec d’éventuels cyclistes, véhicules, mobilier urbain ou autre objet. There are known driver assistance systems, known as ADAS (from the English "Advanced Driver-Assistance System" or in French "Advanced Driver Assistance System"), to guide or control the movement of a vehicle. vehicle in its environment to reach its destination. The most advanced driving assistance systems control the movement of the vehicle which becomes a so-called autonomous vehicle, that is to say a vehicle capable of driving in the road environment without the intervention of the driver. An autonomous vehicle of level higher than 2 must be able to estimate the free space all around the vehicle. For this, this type of vehicle is generally equipped with various sensors such as video cameras, LIDAR (in English "Laser Detection And Ranging") or other which are distributed all around the vehicle, in particular on the windshield, the windshields. front and rear shocks or on the roof. When the vehicle is moving in an environment, the data from these sensors can be used, for example by an ADAS system, to estimate the free space located near the vehicle and thus anticipate the driving of the vehicle to avoid any collision with an object in this environment. This is the case, in particular, when the vehicle is traveling on a lane and is approaching another vehicle. An estimate of the free space located between these two vehicles then makes it possible to anticipate possible braking. This is also the case when the vehicle must park in a parking space. An estimate of the free space between the vehicle and any object, wall, ceiling or other parked vehicle helps prevent a collision. This is also the case when the vehicle is traveling in an urban area where the estimation of the free space located in front, behind or on its sides can prove useful to anticipate any collision with possible cyclists, vehicles, street furniture. or other object.
Il est connu d’estimer l’espace libre situé à proximité d’un véhicule par des systèmes de contrôle du déplacement d’un véhicule, de type ADAS, basés sur des données issues de capteurs vidéo, le plus souvent placés sur le haut du pare-brise. Ces systèmes de contrôle fournissent des estimations d’espace libre satisfaisantes dans des conditions optimales. Par contre, l’estimation de l’espace libre ainsi que la résolution en distance se dégradent fortement lorsque ces conditions sont moins favorables notamment en cas de pluie intense, de brouillard, de faible luminosité (nuit), ou encore en cas d’éblouissement des capteurs vidéo. Ces défauts sont propres aux capteurs fonctionnant dans le spectre visible. Il est également connu d’utiliser des réseaux neuronaux pour estimer un espace libre à partir de données tridimensionnelles obtenus à partir de capteurs. Toutefois, ces solutions ont une complexité élevée et sont consommatrices en ressources. D’autres approches déterminent une intersection entre un volume de forme donnée et un nuage de données tridimensionnelles obtenues à partir de capteurs. Mais les résultats ne sont pas suffisamment probants pour pouvoir être utilisés. It is known to estimate the free space located near a vehicle by systems for controlling the movement of a vehicle, of the ADAS type, based on data from video sensors, most often placed on the top of the vehicle. windshield. These control systems provide satisfactory free space estimates under optimal conditions. On the other hand, the estimate of the free space as well as the distance resolution deteriorate sharply when these conditions are less favorable, in particular in the event of intense rain, fog, low light (night), or even in the event of dazzling. video sensors. These defects are specific to sensors operating in the visible spectrum. It is also known to use neural networks to estimate free space from three-dimensional data obtained from sensors. However, these solutions have high complexity and consume resources. Other approaches determine an intersection between a volume of a given shape and a cloud of three-dimensional data obtained from sensors. But the results are not sufficiently convincing to be able to be used.
Résumé de l’invention Summary of the invention
Un objet de la présente invention est d’améliorer les procédés existants permettant de contrôler le déplacement d’un véhicule par estimation de l’espace libre accessible à ce véhicule à partir d’un nuage de données tridimensionnelles issues de capteurs embarqués dans ce véhicule. An object of the present invention is to improve the existing methods making it possible to control the movement of a vehicle by estimating the free space accessible to it. vehicle from a cloud of three-dimensional data from on-board sensors in this vehicle.
Selon un premier aspect, l’invention concerne un procédé de contrôle du déplacement d’un véhicule, comprenant une étape d’acquisition d’un nuage de données tridimensionnelles obtenues par réflexion d’ondes émises par des capteurs embarqués sur le véhicule ; une étape de transformation du nuage de données tridimensionnelles en un nuage de points bidimensionnels exprimés dans un repère de coordonnées polaires associé à un plan, à chaque donnée tridimensionnelle correspond un point bidimensionnel défini par une distance radiale entre un pôle du repère de coordonnées polaires et le point bidimensionnel, et un angle d’azimut défini entre le plan et un segment reliant le pôle et le point bidimensionnel ; une étape itérative de modification du nuage de points bidimensionnels par suppression d’un point bidimensionnel courant dès lors que deux points bidimensionnels voisins point bidimensionnel courant ne sont pas suffisamment distants l’un de l’autre pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule ; et une étape de contrôle du déplacement dudit véhicule en fonction d’une enveloppe convexe formée par le nuage de points bidimensionnels ainsi modifié et définissant un espace libre accessible au véhicule.According to a first aspect, the invention relates to a method for controlling the movement of a vehicle, comprising a step of acquiring a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle; a step of transforming the three-dimensional data cloud into a two-dimensional point cloud expressed in a polar coordinate frame associated with a plane, to each three-dimensional data item corresponds a two-dimensional point defined by a radial distance between a pole of the polar coordinate frame and the two-dimensional point, and an azimuth angle defined between the plane and a segment connecting the pole and the two-dimensional point; an iterative step of modifying the two-dimensional point cloud by deleting a current two-dimensional point when two neighboring two-dimensional points current two-dimensional point are not sufficiently distant from each other to avoid a collision between the vehicle and an object near this vehicle; and a step of controlling the movement of said vehicle as a function of a convex envelope formed by the two-dimensional point cloud thus modified and defining a free space accessible to the vehicle.
Le procédé transforme le nuage de données tridimensionnelles en un nuage de points bidimensionnels et détermine une enveloppe convexe polygonale à partir d’un nuage modifié de points bidimensionnels. Cette enveloppe convexe procure une estimation de l’espace libre accessible au véhicule. Un système de contrôle du déplacement du véhicule implémentant le procédé, peut alors contrôler le déplacement du véhicule en fonction de cette enveloppe convexe. En modifiant le nuage de points bidimensionnels en un nuage de points bidimensionnels suffisamment distants l’une de l’autre pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule, des espaces libres sont ainsi respectés entre ces points bidimensionnels pour assurer la non- collision entre le véhicule et un objet à proximité de ce véhicule. Le procédé procure alors une information sémantique au nuage de données tridimensionnelles en définissant une enveloppe convexe à partir de ces points bidimensionnels. The method transforms the three-dimensional data cloud into a two-dimensional point cloud and determines a polygonal convex envelope from a modified two-dimensional point cloud. This convex envelope provides an estimate of the free space accessible to the vehicle. A system for controlling the movement of the vehicle implementing the method can then control the movement of the vehicle as a function of this convex envelope. By modifying the two-dimensional point cloud into a two-dimensional point cloud sufficiently distant from each other to avoid a collision between the vehicle and an object near this vehicle, free spaces are thus respected between these two-dimensional points to ensure the non-collision between the vehicle and an object near this vehicle. The method then provides semantic information to the three-dimensional data cloud by defining a convex envelope from these two-dimensional points.
Le procédé utilise des principes géométriques simples et de faible complexité comparés à ceux d’un procédé basé sur un réseau neuronal par exemple. Il requiert donc peu de ressources de calcul. Les enveloppes convexes obtenues sont représentatives de ce qui est attendu en termes d’enveloppe convexe épousant au plus près un nuage de points bidimensionnels tout en respectant des contraintes stériques de non-collision. De plus, le procédé ne faisant pas appel aux techniques d’intelligence artificielle, ne souffre donc pas des problèmes associés à ce type de techniques tels que, notamment des problèmes de validation et de sécurité. Le procédé est indépendant de la technologie ou du modèle de capteur employé, tant que celui-ci fournit un nuage de données tridimensionnelles obtenues par réflexion d’ondes émises par des capteurs embarqués sur le véhicule. Par ailleurs, le procédé est robuste et capable de respecter les contraintes de temps réel dur. Il s’agit d’un des éléments cruciaux pour la mise au point de systèmes de conduite autonome de niveau supérieur à 2 qui doit par ailleurs fonctionner en toute condition (nuit, précipitations, etc.). The method uses simple geometric principles of low complexity compared to those of a method based on a neural network for example. It therefore requires little computing resources. The convex envelopes obtained are representative of what is expected in terms of a convex envelope that closely matches a two-dimensional point cloud while respecting steric non-collision constraints. In addition, the method does not make use of artificial intelligence techniques, therefore does not suffer from the problems associated with this type of technique such as, in particular, validation and security problems. The method is independent of the technology or of the sensor model used, as long as the latter provides a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle. Furthermore, the method is robust and capable of respecting the constraints of real hard time. This is one of the crucial elements for the development of autonomous driving systems above level 2 which must also operate in all conditions (night, precipitation, etc.).
Selon un exemple particulier et non limitatif de l’invention, une itération de l’étape itérative comporte une sous-étape d’obtention d’au moins un point bidimensionnel courant du nuage de points bidimensionnels ayant une distance radiale élevée ; et pour chaque point bidimensionnel courant, une sous-étape de calcul d’une première distance minimale entre un segment reliant un point bidimensionnel courant et le pôle du repère de coordonnées polaires, et un autre point bidimensionnel du nuage de points bidimensionnels déterminé de manière à ce que la différence entre l’angle d’azimut dudit autre point bidimensionnel et l’angle d’azimut du point bidimensionnel courant est minimale et positive ; une sous-étape de calcul d’une seconde distance minimale entre ledit segment et un autre point bidimensionnel du nuage de points bidimensionnels déterminé de manière à ce que la différence entre l’angle d’azimut dudit autre point bidimensionnel et l’angle d’azimut du point bidimensionnel courant est minimale et négative ; et une sous-étape de suppression d’un point bidimensionnel courant du nuage de points bidimensionnels lorsque la somme des première et seconde distances est inférieure à une valeur seuil définie pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule ; un point bidimensionnel courant étant conservé lorsque la somme des première et seconde distances est supérieure à la valeur seuil. Selon un autre exemple particulier et non limitatif de l’invention, une itération de l’étape itérative comporte une sous-étape d’obtention d’au moins un couple formé d’un premier et d’un second points bidimensionnels successifs ayant des distances radiales minimales parmi un ensemble de points bidimensionnels triés selon leur angle d’azimut ; et pour chaque couple courant de points bidimensionnels ainsi formé : une sous-étape de suppression de tous les points bidimensionnels du nuage de points bidimensionnels dont les angles d’azimut sont compris entre les angles d’azimut des premier et second points bidimensionnels d’un couple courant lorsque la valeur absolue de la différence entre les angles d’azimut du premier et du second points bidimensionnels dudit couple courant est inférieure à une valeur seuil définie pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule ; lesdits points bidimensionnels du nuage de points bidimensionnels sont conservés lorsque la valeur absolue de ladite différence est supérieure à la valeur seuil. According to a particular and non-limiting example of the invention, an iteration of the iterative step comprises a sub-step of obtaining at least one current two-dimensional point of the two-dimensional point cloud having a high radial distance; and for each current two-dimensional point, a sub-step of calculating a first minimum distance between a segment connecting a current two-dimensional point and the pole of the reference frame of polar coordinates, and another two-dimensional point of the two-dimensional point cloud determined so as to that the difference between the azimuth angle of said other two-dimensional point and the azimuth angle of the current two-dimensional point is minimal and positive; a sub-step of calculating a second minimum distance between said segment and another two-dimensional point of the two-dimensional point cloud determined so that the difference between the azimuth angle of said other two-dimensional point and the angle of azimuth of the current two-dimensional point is minimum and negative; and a sub-step of removing a current two-dimensional point from the two-dimensional point cloud when the sum of the first and second distances is less than a threshold value defined to avoid a collision between the vehicle and an object near this vehicle; a current two-dimensional point being kept when the sum of the first and second distances is greater than the threshold value. According to another particular and non-limiting example of the invention, an iteration of the iterative step comprises a substep for obtaining at least one pair formed of a first and a second successive two-dimensional points having distances minimum radials among a set of two-dimensional points sorted according to their azimuth angle; and for each current pair of two-dimensional points thus formed: a sub-step of deleting all the two-dimensional points from the two-dimensional point cloud whose azimuth angles are between the azimuth angles of the first and second two-dimensional points of a current torque when the absolute value of the difference between the azimuth angles of the first and second two-dimensional points of said current torque is less than a threshold value defined to avoid a collision between the vehicle and an object near this vehicle; said two-dimensional points of the two-dimensional point cloud are preserved when the absolute value of said difference is greater than the threshold value.
Ces deux exemples particuliers tiennent compte d’une valeur de seuil qui est définie selon des caractéristiques dimensionnelles du véhicule de manière à ce que le véhicule puisse accéder à l’espace situé entre deux données tridimensionnelles du nuage. These two specific examples take into account a threshold value that is defined according to dimensional characteristics of the vehicle so that the vehicle can access the space between two three-dimensional data in the cloud.
Selon une variante du procédé, le procédé comporte en outre une étape (optionnelle) de suppression des données tridimensionnelles correspondant à des échos du sol. Cette étape permet de supprimer les données tridimensionnelles qui correspondent à des échos du sol et qui ne sont donc pas pertinentes pour l’estimation de l’espace libre autour du véhicule. According to a variant of the method, the method further comprises an (optional) step of deleting the three-dimensional data corresponding to echoes from the ground. This step removes three-dimensional data which correspond to ground echoes and which are therefore irrelevant for estimating the free space around the vehicle.
Selon une variante du procédé, le procédé comporte en outre une étape de filtrage du nuage de points bidimensionnels permettant de ne conserver qu’un seul point bidimensionnel par angle d’azimut. According to a variant of the method, the method further comprises a step of filtering the cloud of two-dimensional points making it possible to keep only a single two-dimensional point per azimuth angle.
Selon une variante du procédé, au moins un capteur est un émetteur/récepteur d’ondes électromagnétiques, de préférence dans le domaine infrarouge, de type LIDAR ou un émetteur/récepteur d’onde radio tel qu’un radar. According to a variant of the method, at least one sensor is a transmitter / receiver of electromagnetic waves, preferably in the infrared range, of the LIDAR type or a radio wave transmitter / receiver such as a radar.
L’emploi de capteurs de type LIDAR ou radar permet une bonne discrimination en distance et sont beaucoup moins sensibles aux conditions difficiles (brouillard, pluie, nuit, éblouissement, etc.), étant donné la robustesse de ces deux technologies de capteurs. Selon un deuxième aspect, l’invention concerne un dispositif du déplacement d’un véhicule, comprenant au moins un émetteur/récepteur d’ondes électromagnétiques et/ou d’ondes radio et une mémoire associée à au moins un processeur configuré pour la mise en oeuvre des étapes du procédé ci-dessus. The use of LIDAR or radar type sensors allows good distance discrimination and are much less sensitive to difficult conditions (fog, rain, night, glare, etc.), given the robustness of these two sensor technologies. According to a second aspect, the invention relates to a device for moving a vehicle, comprising at least one emitter / receiver of electromagnetic waves and / or radio waves and a memory associated with at least one processor configured for setting up. implementation of the steps of the above method.
Selon un troisième aspect, l’invention concerne un véhicule comprenant un dispositif ci- dessus. According to a third aspect, the invention relates to a vehicle comprising the above device.
Selon un quatrième aspect, l’invention concerne un produit programme d’ordinateur comportant des instructions adaptées pour l’exécution des étapes du procédé ci-dessus lorsque le programme d’ordinateur est exécuté par au moins un processeur. According to a fourth aspect, the invention relates to a computer program product comprising instructions adapted for performing the above method steps when the computer program is executed by at least one processor.
Brève description des figures Brief description of the figures
D’autres caractéristiques et avantages de l’invention ressortiront de la description des modes de réalisation non limitatifs de l’invention ci-après, en référence aux figures 1 à 8 annexées, sur lesquelles : Other characteristics and advantages of the invention will emerge from the description of the non-limiting embodiments of the invention below, with reference to the attached Figures 1 to 8, in which:
[Fig. 1] illustre de façon schématique un véhicule 1 embarquant plusieurs capteurs 10, 11 , 12, 13 et 14 selon un exemple de réalisation particulier et non limitatif de la présente invention ; [Fig. 1] schematically illustrates a vehicle 1 carrying several sensors 10, 11, 12, 13 and 14 according to a particular and non-limiting embodiment of the present invention;
[Fig. 2] illustre schématiquement un repère tridimensionnel associé à un véhicule selon un exemple de réalisation particulier de la présente invention ; [Fig. 2] schematically illustrates a three-dimensional mark associated with a vehicle according to a particular embodiment of the present invention;
[Fig. 3] illustre un organigramme des différentes étapes d’un procédé de contrôle du déplacement d’un véhicule de la figure 1 , selon un exemple de réalisation particulier et non limitatif de la présente invention ; [Fig. 3] illustrates a flowchart of the various steps of a method for controlling the movement of a vehicle of FIG. 1, according to a particular and non-limiting example of the present invention;
[Fig. 4] illustre un organigramme des différentes sous-étapes de l’étape 350 de la figure 1 , selon un exemple de réalisation particulier et non limitatif de la présente invention ; [Fig. 4] illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to a particular and non-limiting exemplary embodiment of the present invention;
[Fig. 5] illustre de façon schématique les différentes sous-étapes de l’étape 350 de la figure 4, selon un autre exemple de réalisation particulier et non limitatif de la présente invention ; [Fig. 6] illustre un organigramme des différentes sous-étapes de l’étape 350 de la figure 1 , selon un autre exemple de réalisation particulier et non limitatif de la présente invention ; [Fig. 5] schematically illustrates the various sub-steps of step 350 of FIG. 4, according to another particular and non-limiting example of embodiment of the present invention; [Fig. 6] illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to another particular and non-limiting exemplary embodiment of the present invention;
[Fig. 7] illustre de façon schématique les différentes sous-étapes de l’étape 350 de la figure 6, selon un autre exemple de réalisation particulier et non limitatif de la présente invention ; [Fig. 7] schematically illustrates the various sub-steps of step 350 of FIG. 6, according to another particular and non-limiting exemplary embodiment of the present invention;
[Fig. 8] illustre schématiquement un dispositif configuré pour contrôler le déplacement d’un véhicule de la figure 1 , selon un exemple de réalisation particulier non limitatif de la présente invention. [Fig. 8] schematically illustrates a device configured to control the movement of a vehicle of Figure 1, according to a particular non-limiting embodiment of the present invention.
Description des modes de réalisation Description of the embodiments
Un procédé et dispositif vont maintenant être décrits dans ce qui va suivre en référence conjointement aux figures 1 à 8. Des mêmes éléments sont identifiés avec des mêmes signes de référence tout au long de la description qui va suivre. A method and device will now be described in what follows with reference in conjunction with Figures 1 to 8. The same elements are identified with the same reference signs throughout the description which follows.
[Fig. 1] illustre de façon schématique un véhicule 1 , par exemple automobile ou plus généralement un véhicule à moteur terrestre, embarquant plusieurs capteurs 10, 11 , 12, 13 et 14 selon un exemple de réalisation particulier et non limitatif de la présente invention. Selon cet exemple les capteurs 10 et 11 sont positionnés sur les pare-chocs avant et arrière du véhicule 1 , les capteurs 12 et 13 sur les côtés et le capteur 14 sur le toit. Cet exemple de positionnement des capteurs ainsi que le nombre de capteurs ne sont donnés qu’à titre indicatif et ne limite en rien la portée de l’invention. En effet, plusieurs autres capteurs peuvent être positionnées à divers autres endroits du véhicule tel que sur le pare-brise, les vitres, portes, etc. [Fig. 1] schematically illustrates a vehicle 1, for example a motor vehicle or more generally a land motor vehicle, carrying several sensors 10, 11, 12, 13 and 14 according to a particular and non-limiting example of the present invention. According to this example, the sensors 10 and 11 are positioned on the front and rear bumpers of the vehicle 1, the sensors 12 and 13 on the sides and the sensor 14 on the roof. This example of the positioning of the sensors as well as the number of sensors are given only as an indication and in no way limit the scope of the invention. Indeed, several other sensors can be positioned in various other places of the vehicle such as on the windshield, windows, doors, etc.
Selon un mode de réalisation de l’invention, les capteurs 10 à 14 embarqués dans le véhicule 1 sont des capteurs adaptés pour émettre et recevoir des ondes et déterminer la distance des objets environnants par analyse des ondes émises qui sont réfléchies sur des objets situé à proximité du véhicule et dans le champ d’action de ces capteurs. Ces capteurs 10 à 14 sont actifs périodiquement. La période entre deux émissions peut dépendre du déplacement du véhicule. Elle peut par exemple dépendre de la vitesse du véhicule. Plus le véhicule va vite et plus la période peut être courte. L’activité des capteurs peut encore être en continu lorsque, notamment, le véhicule recherche une place de parking et/ou est en train de manœuvrer pour se garer dans une place de parking. L’activation de ces capteurs peut également être individualisée. Par exemple, si le véhicule est en train de reculer, les capteurs situés sur l’avant du véhicule ne sont pas activés. Un capteur, une fois activé, permet de détecter des objets dans l’environnement du véhicule et de mesurer la distance entre le capteur et les objets détectés. Ces objets peuvent être, par exemple, d’autres véhicules, des piétons, des cyclistes, du mobilier urbain, des bandes réfléchissantes délimitant une place de parking, etc. Pour détecter des objets environnants, le capteur actif émet des ondes qui se réfléchissent sur ces objets. Le capteur actif collecte alors ces ondes réfléchies et identifie la position et la distance des objets situés à proximité du véhicule 1 en fonction de ces ondes émises et réfléchies. Un nuage de données multi-dimensionnelles est alors formé. Chacune de ces données multidimensionnelles correspond à au moins une onde émise qui a été réfléchie par un objet. According to one embodiment of the invention, the sensors 10 to 14 on board the vehicle 1 are sensors suitable for emitting and receiving waves and determining the distance from surrounding objects by analysis of the emitted waves which are reflected on objects located at proximity to the vehicle and in the field of action of these sensors. These sensors 10 to 14 are periodically active. The period between two emissions may depend on the movement of the vehicle. It may for example depend on the speed of the vehicle. The faster the vehicle, the shorter the period can be. The activity of sensors can still be continuous when, in particular, the vehicle is looking for a parking space and / or is maneuvering to park in a parking space. The activation of these sensors can also be individualized. For example, if the vehicle is backing up, the sensors on the front of the vehicle are not activated. A sensor, once activated, makes it possible to detect objects in the environment of the vehicle and to measure the distance between the sensor and the detected objects. These objects can be, for example, other vehicles, pedestrians, cyclists, street furniture, reflective strips delimiting a parking space, etc. To detect surrounding objects, the active sensor emits waves that reflect off these objects. The active sensor then collects these reflected waves and identifies the position and the distance of the objects located near the vehicle 1 as a function of these emitted and reflected waves. A multi-dimensional data cloud is then formed. Each of these multidimensional data corresponds to at least one emitted wave which has been reflected by an object.
De manière générale l’espace libre accessible à un véhicule se définit comme un ensemble des données exprimées dans un espace multi-dimensionnel. Ces données peuvent prendre théoriquement toutes les valeurs possibles dans cet espace des paramètres cinématiques du véhicule, compte tenu des contraintes de non-collision avec des objets présents autour de lui. Pour un véhicule se déplaçant dans un espace tridimensionnel, l’espace multi-dimensionnel est un sous-espace de M6 correspondant aux trois paramètres de position ( x,y,z ) et d’orientation {a,b,g) du véhicule dans l’espace. Selon l’invention, le véhicule sera supposé sphérique avec un rayon suffisant pour assurer le respect des contraintes de non-collision. Dans ce cas, les dimensions relative à l’orientation sont dégénérées, et l’espace des données est réduit à un espace tridimensionnel (x,y,z) tel que illustré sur la figure 2. D’autre part, la dimensionnalité de cet espace tridimensionnel (x,y,z) peut être réduite en faisant l’hypothèse qu’un véhicule se déplace sur une surface localement plane, et que l’extension de la scène instantanée dont le véhicule est le centre est beaucoup moins importante selon l’axe z que selon les axes x et y. La dimensionnalité de l’espace tridimensionnel peut donc être ramené à un espace bidimensionnel (x,y). Les données tridimensionnelles obtenues à partir des capteurs embarqués dans le véhicule seront donc représentées par des données bidimensionnelles exprimées dans un repère (0,x,y). L’invention consiste alors à déterminer une enveloppe convexe dans cet espace bidimensionnel représentant l’espace libre accessible au véhicule 1. Cette enveloppe convexe respecte des contraintes de non-collision entre ce véhicule et d’éventuels objets environnants. Du fait de la nature discrète des informations disponibles, sous forme de nuage de données tridimensionnelles, cette enveloppe convexe est un polygone dont les sommets sont des points bidimensionnels issus du nuage de données tridimensionnels. In general, the free space accessible to a vehicle is defined as a set of data expressed in a multidimensional space. These data can theoretically take all the possible values in this space of the kinematic parameters of the vehicle, taking into account the constraints of non-collision with objects present around it. For a vehicle moving in a three-dimensional space, the multi-dimensional space is a subspace of M 6 corresponding to the three parameters of position (x, y, z) and orientation {a, b, g) of the vehicle in the space. According to the invention, the vehicle will be assumed to be spherical with a sufficient radius to ensure compliance with the non-collision constraints. In this case, the dimensions relative to the orientation are degenerated, and the data space is reduced to a three-dimensional space (x, y, z) as illustrated in figure 2. On the other hand, the dimensionality of this three-dimensional space (x, y, z) can be reduced by assuming that a vehicle is moving on a locally flat surface, and that the extension of the instantaneous scene of which the vehicle is the center is much less depending on the 'z axis than along the x and y axes. The dimensionality of the three-dimensional space can therefore be reduced to a two-dimensional space (x, y). The three-dimensional data obtained from the sensors on board the vehicle will therefore be represented by two-dimensional data expressed in a coordinate system (0, x, y). The invention then consists in determining a convex envelope in this two-dimensional space representing the free space accessible to the vehicle 1. This convex envelope complies with the constraints of non-collision between this vehicle and any surrounding objects. Due to the discrete nature of the information available, in the form of a three-dimensional data cloud, this convex envelope is a polygon whose vertices are two-dimensional points originating from the three-dimensional data cloud.
[Fig. 3] illustre un organigramme des différentes étapes d’un procédé d’estimation d’espace libre accessible à un véhicule de la figure 1 , selon un exemple de réalisation particulier et non limitatif de la présente invention. [Fig. 3] illustrates a flowchart of the various steps of a method for estimating free space accessible to a vehicle of FIG. 1, according to a particular and non-limiting example of the present invention.
Dans une première étape 310, au moins un capteur 10 à 14 du véhicule 1 est actif et un nuage de données tridimensionnelles Pi (i=1 à N) est acquise par réflexion d’ondes émises par ces capteurs actifs. Chacune donnée tridimensionnelle représente les coordonnées d’un point dans l’espace tridimensionnel. In a first step 310, at least one sensor 10 to 14 of the vehicle 1 is active and a three-dimensional data cloud Pi (i = 1 to N) is acquired by reflection of waves emitted by these active sensors. Each three-dimensional data represents the coordinates of a point in three-dimensional space.
Mathématiquement, le nuage de données tridimensionnelles peut se représenter par une matrice P de dimension 3xN formée de trois vecteurs X, Y Z de dimension N représentant les coordonnées xi,yi,zi des données tridimensionnelles Pw [Math 1]
Figure imgf000011_0001
avec respectivement Ύ et de fZ représente la transposée du vecteur X, respectivement Y et Z. Mathematically, the three-dimensional data cloud can be represented by a matrix P of dimension 3xN formed of three vectors X, YZ of dimension N representing the coordinates xi, yi, zi of the three-dimensional data Pw [Math 1]
Figure imgf000011_0001
with respectively Ύ and of f Z represents the transpose of the vector X, respectively Y and Z.
Selon un mode de réalisation de l’étape 310, au moins un capteur est un émetteur/récepteur d’ondes électromagnétiques par exemple de type LIDAR et/ou un émetteur/récepteur d’ondes radio. According to an embodiment of step 310, at least one sensor is a transmitter / receiver of electromagnetic waves, for example of the LIDAR type, and / or a transmitter / receiver of radio waves.
Un capteur LIDAR permet de détecter des objets dans l’environnement du véhicule et de mesurer la distance entre le capteur et les objets détectés par l’émission de rayons lumineux (ondes électromagnétiques) émis par des lasers rayonnant de préférence dans le domaine non visible (infrarouge par exemple). Selon un mode de réalisation, le procédé comporte une étape 320 (optionnelle) de suppression des données tridimensionnelles correspondant à des échos du sol. A LIDAR sensor makes it possible to detect objects in the environment of the vehicle and to measure the distance between the sensor and the objects detected by the emission of light rays (electromagnetic waves) emitted by lasers radiating preferably in the non-visible range ( infrared for example). According to one embodiment, the method comprises a step 320 (optional) of deleting the three-dimensional data corresponding to echoes from the ground.
Selon un exemple, l’algorithme de segmentation de B. Douillard et al. ("On the Segmentation of 3D LIDAR Point Clouds", 2011 IEEE International Conférence on Robotics and Automation (http://dx.doi.Org/10.1109/ICRA.2011.5979818)) peut être utilisé pour isoler les données tridimensionnelles qui correspondent à des échos du sol des autres données tridimensionnelles et supprimer ces données tridimensionnelles isolées. On peut encore utiliser l’algorithme de I. Bogoslavskiy & C. Stachniss ("Efficient Online Segmentation for Sparse 3D Laser Scans", Photogrammetrie - Fernerkundung - Geoinformation 85, 41 (2016) (http://dx.doi.org/10.1007/s41064-016-0003-y), ou encore celui de Y. Zhou et al. ("A Fast and Accurate Segmentation Method for Ordered LiDAR Point Cloud of Large-Scale Scenes", IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 11, 1981 (2014) (http://dx.doi.org/10.1109/LGRS.2014.2316009). According to one example, the segmentation algorithm of B. Douillard et al. ("On the Segmentation of 3D LIDAR Point Clouds", 2011 IEEE International Conference on Robotics and Automation (http://dx.doi.Org/10.1109/ICRA.2011.5979818)) can be used to isolate three-dimensional data that correspond to ground echoes of other three-dimensional data and remove those isolated three-dimensional data. We can also use the algorithm of I. Bogoslavskiy & C. Stachniss ("Efficient Online Segmentation for Sparse 3D Laser Scans", Photogrammetrie - Fernerkundung - Geoinformation 85, 41 (2016) (http://dx.doi.org/10.1007 / s41064-016-0003-y), or that of Y. Zhou et al. ("A Fast and Accurate Segmentation Method for Ordered LiDAR Point Cloud of Large-Scale Scenes", IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 11, 1981 ( 2014) (http://dx.doi.org/10.1109/LGRS.2014.2316009).
Dans une étape 330, le nuage de données tridimensionnelles Pi est transformé en un nuage de points bidimensionnels Mi exprimés dans un repère de coordonnées polaires (r,<p) associé à un plan P avec r une coordonnée polaire appelée distance radiale définie entre un pôle O du repère de coordonnées polaires et un point bidimensionnel appartenant au plan P et f une autre coordonnée polaire appelée angle d’azimut défini entre le plan P et un segment reliant le pôle O et le point bidimensionnel du plan P tel que illustré sur la figure 5. In a step 330, the three-dimensional data cloud Pi is transformed into a cloud of two-dimensional points Mi expressed in a reference frame of polar coordinates (r, <p) associated with a plane P with r a polar coordinate called the radial distance defined between a pole O of the polar coordinate system and a two-dimensional point belonging to the plane P and f another polar coordinate called the azimuth angle defined between the plane P and a segment connecting the pole O and the two-dimensional point of the plane P as shown in the figure 5.
A chaque donnée tridimensionnelle Pi correspond un point bidimensionnel Mi du plan P. Cependant, il peut se produire le cas où plusieurs points bidimensionnels partagent le même angle d’azimut. Ceci peut être dû à un mode de fonctionnement d’un capteur qui peut enregistrer plusieurs échos pour une seule onde émise, par exemple quand le faisceau laser rencontre une vitre, puis un obstacle solide plus loin. Ceci peut aussi être dû au pas d’échantillonnage des capteurs pour déterminer un angle d’azimut. Mathématiquement, la transformée du nuage de données tridimensionnelles Pi, représentées par des points Mi exprimés dans le repère (0,x,y), en un nuage Ps de points bidimensionnels Mi exprimés dans un repère de coordonnées polaire ( t, f ) est donné par: To each three-dimensional datum Pi corresponds a two-dimensional point Mi of the plane P. However, the case may arise where several two-dimensional points share the same azimuth angle. This may be due to a mode of operation of a sensor which can record several echoes for a single emitted wave, for example when the laser beam meets a window, then a solid obstacle further away. This can also be due to the sampling steps of the sensors to determine an azimuth angle. Mathematically, the transform of the three-dimensional data cloud Pi, represented by points Mi expressed in the coordinate system (0, x, y), into a cloud P s of two-dimensional points Mi expressed in a coordinate system with polar coordinates (t, f) is given by:
[Math 2] où Ps est une matrice de dimension 2xN formée de deux vecteurs R et F de dimension N et la fonction arctan2 est l’arc tangente à quatre quadrants donnant la valeur d’un angle dans l’intervalle [0,2p[. Le vecteur R = t[r1, ... ,rN ] correspond aux distances radiales des points bidimensionnels Mi du plan P, et le vecteur F = t[<p1, ... , fN ] correspond à leurs angles azimut. Dans cette représentation, Ps peut donc être décrit comme une fonction d’une seule variable scalaire r(<p). [Math 2] where P s is a 2xN-dimensional matrix formed by two vectors R and F of dimension N and the function arctan2 is the four-quadrant arc tangent giving the value of an angle in the interval [0,2p [. The vector R = t [r 1 , ..., r N ] corresponds to the radial distances of the two-dimensional points Mi of the plane P, and the vector F = t [<p 1 , ..., f N ] corresponds to their angles azimuth. In this representation, P s can therefore be described as a function of a single scalar variable r (<p).
Selon un mode de réalisation, le procédé comporte une étape 340 (optionnelle) qui filtre le nuage de données tridimensionnelles Pi en ne conservant qu’un seul point bidimensionnel Mi par valeur d’angle d’azimut. According to one embodiment, the method comprises a step 340 (optional) which filters the three-dimensional data cloud Pi by keeping only a single two-dimensional point Mi per azimuth angle value.
Selon une variante de l’étape 340, lorsque plusieurs points bidimensionnels partagent une même valeur d’angle d’azimut et différentes valeurs de distance radiale, seul le point bidimensionnel ayant la distance radiale la plus faible est conservé dans le nuage de point bidimensionnels. According to a variant of step 340, when several two-dimensional points share a same azimuth angle value and different radial distance values, only the two-dimensional point having the smallest radial distance is kept in the two-dimensional point cloud.
Selon une autre variante de l’étape 340, lorsque plusieurs points bidimensionnels partagent une même valeur d’angle d’azimut et différentes valeurs de distance radiale, un point bidimensionnel est créé avec ladite valeur d’angle d’azimut et une distance radiale égale à une valeur obtenue à partir des valeurs des distances radiales de ces points bidimensionnels telle que la moyenne ou la médiane de ces distances radiales. Dans une étape itérative 350, le nuage Ps de points bidimensionnels est modifié par suppression d’un point bidimensionnel courant dès lors que deux points bidimensionnels voisins du point bidimensionnel courant ne sont pas suffisamment distants l’un de l’autre pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule. Le nuage Ps de points bidimensionnels ainsi modifié forme une enveloppe convexe de l’espace libre accessible au véhicule. According to another variant of step 340, when several two-dimensional points share the same azimuth angle value and different radial distance values, a two-dimensional point is created with said azimuth angle value and an equal radial distance to a value obtained from the values of the radial distances of these two-dimensional points such as the average or the median of these radial distances. In an iterative step 350, the cloud Ps of two-dimensional points is modified by deleting a current two-dimensional point when two two-dimensional points neighboring the current two-dimensional point are not sufficiently distant from each other to avoid a collision between the vehicle and an object near that vehicle. The two-dimensional point cloud Ps thus modified forms a convex envelope of the free space accessible to the vehicle.
Dans une étape 360, le déplacement du véhicule est contrôlé par un système de contrôle qui implémente les étapes précédentes pour obtenir ce nuage Ps de points bidimensionnels. Ce nuage de points bidimensionnels forme une enveloppe convexe de l’espace libre accessible au véhicule et ce système de contrôle peut alors indiquer quels sont les déplacements possibles du véhicule en fonction de cette enveloppe convexe. In a step 360, the movement of the vehicle is controlled by a control system which implements the previous steps to obtain this cloud P s of two-dimensional points. This two-dimensional point cloud forms a convex envelope of the free space accessible to the vehicle and this control system can then indicate what are the possible movements of the vehicle as a function of this convex envelope.
[Fig. 4] illustre un organigramme des différentes sous-étapes de l’étape 350 de la figure 1 , selon un exemple de réalisation particulier et non limitatif de la présente invention.[Fig. 4] illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to a particular and non-limiting exemplary embodiment of the present invention.
Dans une sous-étape 351 , au moins un point bidimensionnel courant Mi.max du nuage Ps de points bidimensionnels ayant une distance radiale élevée est obtenu. In a sub-step 351, at least one current two-dimensional point Mi.max of the cloud P s of two-dimensional points having a high radial distance is obtained.
Selon une variante de la sous-étape 351 , un nombre donné de points bidimensionnels courant Mi.max ayant des distances radiales les plus élevées sont obtenus parmi le nuage Ps de points bidimensionnels. According to a variant of the sub-step 351, a given number of current two-dimensional points Mi.max having the highest radial distances are obtained from the cloud P s of two-dimensional points.
Selon une autre variante, tout point bidimensionnel du nuage Psde points bidimensionnels dont la distance radiale est supérieure à une valeur de seuil donnée est un point bidimensionnel courant Mi. According to another variant, any two-dimensional point of the cloud Ps of two-dimensional points whose radial distance is greater than a given threshold value is a current two-dimensional point Mi.
Selon une autre variante de la sous-étape 351 , un point bidimensionnel courant Mi.max est obtenu à partir d’un sous-ensemble des points bidimensionnels du nuage Psde points bidimensionnels. Un point bidimensionnel courant Mi.max est alors un point bidimensionnel de ce sous-ensemble qui a la distance radiale maximale (la plus élevée parmi les distances radiales des autres points bidimensionnels de ce sous-ensemble). Un sous-ensemble du nuage Ps de points bidimensionnels peut être obtenu, par exemple, en regroupant les points bidimensionnels selon leurs angles d’azimut triés par ordre croissant par exemple. On peut en effet partitionner un cercle en différents secteurs angulaires et créer un sous-ensemble de points bidimensionnels par secteur angulaire. Un point bidimensionnel ayant son angle d’azimut qui appartient à un secteur angulaire donné appartient alors au sous-ensemble associé à ce secteur angulaire. On peut également envisager de former des sous-ensembles d’un nombre donné de points bidimensionnels successifs c’est-à-dire de points bidimensionnels dont les angles d’azimut se suivent dans une liste des angles d’azimut des points bidimensionnels triés selon un ordre, par exemple croissant. Un premier point bidimensionnel est ajouté à un premier sous-ensemble. Puis le point bidimensionnel dont l’angle d’azimut est le suivant dans la liste est aussi ajouté à ce premier sous-ensemble, et ainsi de suite jusqu’à ce que le sous-ensemble de points bidimensionnels ait atteint un nombre donné de points bidimensionnels. Un autre sous-sous-ensemble est alors formé jusqu’à épuisement des points bidimensionnels du nuage Ps de points bidimensionnels. According to another variant of the sub-step 351, a current two-dimensional point Mi.max is obtained from a subset of the two-dimensional points of the cloud Ps of two-dimensional points. A current two-dimensional point Mi.max is then a two-dimensional point of this subset which has the maximum radial distance (the highest among the radial distances of the other two-dimensional points of this subset). A subset of the two-dimensional point cloud Ps can be obtained, for example, by grouping the two-dimensional points according to their azimuth angles sorted in ascending order, for example. It is in fact possible to partition a circle into different angular sectors and create a subset of two-dimensional points per angular sector. A two-dimensional point having its azimuth angle which belongs to a given angular sector then belongs to the subset associated with this angular sector. It is also possible to envisage forming subsets of a given number of successive two-dimensional points, that is to say of two-dimensional points whose azimuth angles follow one another in a list of the azimuth angles of the two-dimensional points sorted according to an order, for example ascending. A first two-dimensional point is added to a first subset. Then the two-dimensional point whose azimuth angle is the next in the list is also added to this first subset, and so on until the two-dimensional point subset has reached a given number of points two-dimensional. Another sub-subset is then formed until the two-dimensional points of the two-dimensional point cloud Ps are exhausted.
Des sous-étapes 352, 353 et 354 sont exécutées pour chaque point bidimensionnel courant Mi.max Sub-steps 352, 353 and 354 are executed for each current two-dimensional point Mi.max
Dans une sous-étape 352 illustrée à la figure 5, une première distance minimale D1 est calculée entre un segment reliant le point bidimensionnel courant Mi.max et le pôle O du repère de coordonnées polaires, et un autre point bidimensionnel Mi+i du nuage Ps de points bidimensionnels ou, selon une variante, d’un sous-ensemble du nuage Ps. Ce point bidimensionnel Mi+i est déterminé de manière à ce que la différence entre son angle d’azimut <pi+1 et l’angle d’azimut (pt du point bidimensionnel courant Mi.max soit minimale et positive lorsque l’on considère que les angles d’azimut croissent selon le sens anti-horaire. In a sub-step 352 illustrated in FIG. 5, a first minimum distance D1 is calculated between a segment connecting the current two-dimensional point Mi.max and the pole O of the coordinate system with polar coordinates, and another two-dimensional point Mi + i of the cloud P s of two-dimensional points or, according to a variant, of a subset of the cloud Ps. This two-dimensional point Mi + i is determined so that the difference between its azimuth angle <p i + 1 and l ' azimuth angle (p t of the current two-dimensional point Mi.max is minimal and positive when one considers that the azimuth angles increase in the anti-clockwise direction.
Dans une sous-étape 353 illustrée à la figure 5, une seconde distance minimale D2 est calculée entre un segment reliant le point bidimensionnel courant Mi.max et le pôle O du repère de coordonnées polaires, et un autre point bidimensionnel MM du nuage Ps de points bidimensionnels ou, selon une variante, d’un sous-ensemble du nuage Ps. Ce point bidimensionnel MM est déterminé de manière à ce que la différence entre son angle d’azimut
Figure imgf000015_0001
et l’angle d’azimut (pt du point bidimensionnel courant Mi soit minimale et négative lorsque l’on considère que les angles d’azimut croissent selon le sens anti-horaire. Les distances D1 et D2 assurent que les points bidimensionnels Mi+i et Mi-i sont les points bidimensionnels voisins « gauche » et « droit » du point bidimensionnel courant Mi.max les plus proches. In a sub-step 353 illustrated in FIG. 5, a second minimum distance D2 is calculated between a segment connecting the current two-dimensional point Mi.max and the pole O of the reference frame of polar coordinates, and another two-dimensional point MM of the cloud Ps of two-dimensional points or, according to a variant, of a subset of the cloud Ps. This two-dimensional point MM is determined so that the difference between its azimuth angle
Figure imgf000015_0001
and the azimuth angle (p t of the current two-dimensional point Mi is minimal and negative when one considers that the azimuth angles increase in the anti-clockwise direction. The distances D1 and D2 ensure that the two-dimensional points Mi + i and Mi-i are the “left” and “right” neighboring two-dimensional points of the closest current two-dimensional point Mi.max.
Dans une sous-étape 354, le point bidimensionnel courante Mi.max est alors supprimé du nuage Ps de points bidimensionnels lorsque la somme des première et seconde distances D1 et D2 est inférieure à une valeur seuil T. Le point bidimensionnel courant Mi.max est conservé lorsque la somme des première et seconde distances est supérieure à la valeur seuil. In a sub-step 354, the current two-dimensional point Mi.max is then deleted from the cloud P s of two-dimensional points when the sum of the first and second distances D1 and D2 is less than a threshold value T. The current two-dimensional point Mi.max is kept when the sum of the first and second distances is greater than the threshold value.
Une fois que tous les points bidimensionnels courants Mi.max ont été considérés, le procédé détermine alors si une nouvelle itération de l’étape 350 est nécessaire en vérifiant si une condition est vérifiée ou pas. Si une nouvelle itération de l’étape 350 est requise, les sous-étapes 351 à 354 sont à nouveau exécutées. Selon un exemple, le procédé s’arrête lorsqu’aucun point bidimensionnel Mi, max n’est supprimé à l’étape précédente. Once all the current two-dimensional points Mi.max have been considered, the method then determines whether a new iteration of step 350 is necessary by checking whether a condition is satisfied or not. If a new iteration of step 350 is required, substeps 351 to 354 are executed again. According to one example, the method stops when no two-dimensional point Mi, max is deleted in the previous step.
Selon un exemple, le procédé s’arrête lorsqu’un nombre de points bidimensionnels a été supprimé. According to one example, the process stops when a number of two-dimensional points have been deleted.
[Fig. 6] illustre un organigramme des différentes sous-étapes de l’étape 350 de la figure 1 , selon un autre exemple de réalisation particulier et non limitatif de la présente invention. [Fig. 6] illustrates a flowchart of the various sub-steps of step 350 of FIG. 1, according to another particular and non-limiting exemplary embodiment of the present invention.
Dans la sous-étape 355 illustrée à la figure 7, au moins un couple formé d’un premier et d’un second points bidimensionnels successifs est formé. Pour cela, les points bidimensionnels du nuage de points Ps sont triés selon un ordre, par exemple croissant, de leurs angles d’azimut. Deux points bidimensionnels sont alors dits successifs lorsque la différence d’angles d’azimut est minimale. Un premier et un second point bidimensionnels forment un couple lorsqu’ils sont successifs et qu’ils ont des distances radiales les plus faibles (minimales) parmi les distances radiales d’un ensemble de points bidimensionnels. In the sub-step 355 illustrated in FIG. 7, at least one pair formed of a first and a second successive two-dimensional points is formed. For this, the two-dimensional points of the point cloud P s are sorted according to an order, for example increasing, of their azimuth angles. Two two-dimensional points are then said to be successive when the difference in azimuth angles is minimal. A first and a second two-dimensional point form a couple when they are successive and when they have the smallest (minimum) radial distances among the radial distances of a set of two-dimensional points.
Selon une variante de la sous-étape 355, chaque couple de points bidimensionnels Mj et Mk est obtenu à partir du nuage Ps de points bidimensionnels. Les points bidimensionnels Mj et Mk sont alors des points bidimensionnels successifs du nuage Ps qui ont une distance radiale inférieure à une valeur de seuil. According to a variant of sub-step 355, each pair of two-dimensional points Mj and Mk is obtained from the cloud P s of two-dimensional points. The two-dimensional points Mj and Mk are then successive two-dimensional points of the cloud Ps which have a radial distance less than a threshold value.
Selon une autre variante de la sous-étape 355, chaque couple de points bidimensionnels Mj et Mk est obtenu à partir d’un sous-ensemble des points bidimensionnels du nuage Ps. Les points bidimensionnels Mj et Mk sont alors des points bidimensionnels successifs de ce sous-ensemble du nuage Ps qui ont des distances radiales minimales (les plus faibles parmi les distances radiales des autres points bidimensionnels de ce sous-ensemble du nuage Ps). According to another variant of the sub-step 355, each pair of two-dimensional points Mj and Mk is obtained from a subset of the two-dimensional points of the cloud Ps. The two-dimensional points Mj and Mk are then successive two-dimensional points of this subset of the cloud P s which have minimum radial distances (the smallest among the radial distances of the other two-dimensional points of this subset of the cloud P s ).
Un sous-ensemble du nuage Ps peut être obtenu, par exemple, en regroupant les points bidimensionnels selon leurs angles d’azimut. On peut en effet partitionner un cercle en différents secteurs angulaires et créer un sous-ensemble de points bidimensionnels par secteur angulaire. Un point bidimensionnel ayant son angle d’azimut qui appartient à un secteur angulaire donné appartient alors au sous-ensemble associé à ce secteur angulaire. On peut également envisager de former des sous- ensembles d’un nombre de points bidimensionnels successifs donné. Un premier point bidimensionnel est ajouté à un premier sous-ensemble. Puis le point bidimensionnel ayant une différence d’angle d’azimut positive et minimale avec le premier point bidimensionnel est aussi ajouté à ce premier sous-ensemble. Et ainsi de suite jusqu’à ce que le sous-ensemble de points bidimensionnels ait atteint un nombre donné de points bidimensionnels. Un autre sous-sous-ensemble est alors formé jusqu’à épuisement des points bidimensionnels du nuage Ps. A subset of the Ps cloud can be obtained, for example, by grouping the two-dimensional points according to their azimuth angles. It is in fact possible to partition a circle into different angular sectors and create a subset of two-dimensional points per angular sector. A two-dimensional point having its azimuth angle which belongs to a given angular sector then belongs to the subset associated with this angular sector. It is also possible to envisage forming sub- sets of a given number of successive two-dimensional points. A first two-dimensional point is added to a first subset. Then the two-dimensional point having a positive and minimum azimuth angle difference with the first two-dimensional point is also added to this first subset. And so on until the subset of two-dimensional points has reached a given number of two-dimensional points. Another sub-subset is then formed until the two-dimensional points of the cloud Ps are exhausted.
Dans une sous-étape 356 illustrée à la figure 7, pour chaque couple de points bidimensionnels Mj et Mk„ tous les points bidimensionnels MP avec j < p < k , correspondants aux points bidimensionnels dont les angles d’azimut sont compris entre les angles d’azimut des points bidimensionnels Mj et Mk sont alors supprimés lorsque la valeur absolue de la différence entre les angles d’azimut des points bidimensionnels Mj et Mk est inférieure à une valeur seuil T. Lesdits points bidimensionnels sont conservés lorsque la valeur absolue de ladite différence est supérieure à la valeur seuil T. In a sub-step 356 illustrated in FIG. 7, for each pair of two-dimensional points Mj and Mk „all the two-dimensional points M P with j <p <k, corresponding to the two-dimensional points whose azimuth angles lie between the angles azimuth of the two-dimensional points Mj and Mk are then deleted when the absolute value of the difference between the azimuth angles of the two-dimensional points Mj and Mk is less than a threshold value T. Said two-dimensional points are kept when the absolute value of said difference is greater than the threshold value T.
Une fois que tous les couples courants de points bidimensionnels ont été considérés, le procédé détermine alors si une nouvelle itération de l’étape 350 est nécessaire en vérifiant si une condition est vérifiée ou pas. Si une nouvelle itération de l’étape 350 est requise, les sous-étapes 355 à 357 sont à nouveau exécutées. Once all the current pairs of two-dimensional points have been considered, the method then determines whether a new iteration of step 350 is necessary by checking whether a condition is true or not. If a new iteration of step 350 is required, substeps 355 through 357 are executed again.
Selon un exemple, le procédé s’arrête lorsqu’un nombre donné de points bidimensionnels a été supprimé. According to one example, the process stops when a given number of two-dimensional points have been deleted.
Selon un autre exemple, le procédé s’arrête lorsque aucun point bidimensionnel n’a été supprimé à une itération précédente. According to another example, the method stops when no two-dimensional point has been deleted in a previous iteration.
La valeur de seuil T est définie pour éviter toute collision entre le véhicule et un objet à proximité de ce véhicule. En effet, seuls les points bidimensionnels distants d’une valeur supérieure à la valeur de seuil T sont utilisés pour former l’enveloppe convexe de l’espace libre. Ainsi, admettons que le nuage Ps soit formé de données tridimensionnelles issues de capteurs situés sur l’avant du véhicule, l’enveloppe convexe formée par les points bidimensionnels correspondant indiquera que le véhicule peut passer entre ces points bidimensionnels sans risque de collision. Il en est de même pour toute enveloppe convexe formée d’un nuage de données tridimensionnelles modifié selon l’invention. Le véhicule peut ainsi se déplacer sans risque de collision entre les données tridimensionnelles de l’enveloppe convexe. The threshold value T is defined to avoid any collision between the vehicle and an object near this vehicle. Indeed, only the two-dimensional points distant by a value greater than the threshold value T are used to form the convex envelope of the free space. Thus, let us assume that the cloud P s is formed from three-dimensional data coming from sensors located on the front of the vehicle, the convex envelope formed by the corresponding two-dimensional points will indicate that the vehicle can pass between these two-dimensional points without risk of collision. It is the same for any convex envelope formed by a cloud of three-dimensional data. modified according to the invention. The vehicle can thus move without risk of collision between the three-dimensional data of the convex envelope.
Selon une variante, la valeur de seuil T varie selon les dimensions du véhicule. Ainsi, par exemple, pour une enveloppe formée à partir de points bidimensionnels correspondant à des données tridimensionnelles issues de capteur situés sur l’avant ou l’arrière du véhicule, la valeur de seuil T est au moins égale à la largeur du véhicule. Pour ceux situés sur les côtés, la valeur de seuil est au moins égale à la longueur du véhicule. According to one variant, the threshold value T varies according to the dimensions of the vehicle. Thus, for example, for an envelope formed from two-dimensional points corresponding to three-dimensional data from sensors located on the front or rear of the vehicle, the threshold value T is at least equal to the width of the vehicle. For those located on the sides, the threshold value is at least equal to the length of the vehicle.
Selon une variante, la valeur de seuil T est supérieure aux dimensions du véhicule pour augmenter l’espace libre et ainsi faciliter les manoeuvres du véhicule à l’intérieur de l’enveloppe convexe représentant cet espace libre sans risque de collision According to a variant, the threshold value T is greater than the dimensions of the vehicle to increase the free space and thus facilitate maneuvering of the vehicle inside the convex envelope representing this free space without risk of collision
[Fig. 8] illustre schématiquement un dispositif 400 configuré pour contrôler le déplacement d’un véhicule basé sur l’estimation de l’espace libre accessible à ce véhicule, selon un exemple de réalisation particulier et non limitatif de la présente invention. Le dispositif 400 correspond par exemple à un dispositif embarqué dans le véhicule, tel que par exemple un calculateur ou un ensemble de calculateurs. [Fig. 8] schematically illustrates a device 400 configured to control the movement of a vehicle based on the estimate of the free space accessible to this vehicle, according to a particular and non-limiting embodiment of the present invention. The device 400 corresponds for example to a device on board the vehicle, such as for example a computer or a set of computers.
Le dispositif 400 est par exemple configuré pour la mise en oeuvre des étapes du procédé décrit en regard des figures 3, 4 et/ou 6. Des exemples d’un tel dispositif 400 comprennent, sans y être limités, un équipement électronique embarqué tel qu’un ordinateur de bord d’un véhicule, un calculateur électronique tel qu’une UCE (« Unité de Commande Electronique »), un téléphone intelligent (de l’anglais « smartphone »), une tablette, un ordinateur portable. Les éléments du dispositif 400, individuellement ou en combinaison, peuvent être intégrés dans un unique circuit intégré, dans plusieurs circuits intégrés, et/ou dans des composants discrets. Le dispositif 400 peut être réalisé sous la forme de circuits électroniques ou de modules logiciels (ou informatiques) ou encore d’une combinaison de circuits électroniques et de modules logiciels. Selon différents modes de réalisation particuliers, le dispositif 400 est couplé en communication avec d’autres dispositifs ou systèmes similaires, par exemple par l’intermédiaire d’un bus de communication ou au travers de ports d’entrée / sortie dédiés. Le dispositif 400 comprend un (ou plusieurs) processeur(s) 410 configurés pour exécuter des instructions pour la réalisation des étapes du procédé et/ou pour l’exécution des instructions du ou des logiciels embarqués dans le dispositif 410. Le processeur 410 peut inclure de la mémoire intégrée, une interface d’entrée/sortie, et différents circuits connus de l’homme du métier. Le dispositif 410 comprend en outre au moins une mémoire 420 correspondant par exemple à une mémoire volatile et/ou non volatile et/ou comprend un dispositif de stockage mémoire qui peut comprendre de la mémoire volatile et/ou non volatile, telle que EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, disque magnétique ou optique. The device 400 is for example configured for the implementation of the steps of the method described with reference to FIGS. 3, 4 and / or 6. Examples of such a device 400 include, without being limited thereto, on-board electronic equipment such as 'an on-board computer of a vehicle, an electronic computer such as an ECU (“Electronic Control Unit”), a smart phone (from the English “smartphone”), a tablet, a laptop computer. The elements of the device 400, individually or in combination, can be integrated in a single integrated circuit, in several integrated circuits, and / or in discrete components. The device 400 can be produced in the form of electronic circuits or software (or computer) modules or else a combination of electronic circuits and software modules. According to different particular embodiments, the device 400 is coupled in communication with other devices or similar systems, for example by means of a communication bus or through dedicated input / output ports. The device 400 comprises one (or more) processor (s) 410 configured to execute instructions for carrying out the steps of the method and / or for executing the instructions of the software (s) embedded in the device 410. The processor 410 can include integrated memory, an input / output interface, and various circuits known to those skilled in the art. The device 410 further comprises at least one memory 420 corresponding for example to a volatile and / or non-volatile memory and / or comprises a memory storage device which may comprise volatile and / or non-volatile memory, such as EEPROM, ROM , PROM, RAM, DRAM, SRAM, flash, magnetic or optical disk.
Le code informatique du ou des logiciels embarqués comprenant les instructions à charger et exécuter par le processeur est par exemple stocké sur la mémoire 420.The computer code of the on-board software (s) comprising the instructions to be loaded and executed by the processor is for example stored in the memory 420.
Selon un mode de réalisation particulier et non limitatif, le dispositif 400 comprend un bloc 430 d’éléments d’interface pour communiquer avec des dispositifs externes, par exemple un serveur distant ou le « cloud », des dispositifs tels qu’un lecteur de communication en champ proche ou un récepteur radio. Le bloc 430 d’éléments d’interface est également configuré pour recevoir un nuage de données tridimensionnelles issues de capteurs embarqués tels que les capteurs 10 à 14. Le bloc 430 d’éléments d’interface est également configuré pour émettre un nuage de points bidimensionnel et/ou d’une enveloppe convexe formée à partir de ce nuage de points bidimensionnels issu du procédé décrit en regard des figures 3, 4 et/ou 6. Les éléments d’interface du bloc 430 comprennent une ou plusieurs des interfaces suivantes : According to a particular and non-limiting embodiment, the device 400 comprises a block 430 of interface elements for communicating with external devices, for example a remote server or the “cloud”, devices such as a communication reader. near field or a radio receiver. Block 430 of interface elements is also configured to receive a three-dimensional data cloud from on-board sensors such as sensors 10-14. Block 430 of interface elements is also configured to emit a two-dimensional point cloud. and / or a convex envelope formed from this two-dimensional point cloud resulting from the method described with reference to FIGS. 3, 4 and / or 6. The interface elements of block 430 include one or more of the following interfaces:
- interface radiofréquence RF, par exemple de type Bluetooth® ou Wi-Fi®, LTE (de l’anglais « Long-Term Evolution » ou en français « Evolution à long terme »), LTE- Advanced (ou en français LTE-avancé) ; - RF radiofrequency interface, for example of the Bluetooth® or Wi-Fi® type, LTE (from English "Long-Term Evolution" or in French "Long-term Evolution"), LTE-Advanced (or in French LTE-advanced );
- interface USB (de l’anglais « Universal Serial Bus » ou « Bus Universel en Série » en français) ; - USB interface (from English "Universal Serial Bus" or "Bus Universel en Série" in French);
- interface HDMI (de l’anglais « High Définition Multimedia Interface », ou « Interface Multimedia Haute Définition » en français) ; - HDMI interface (from English "High Definition Multimedia Interface", or "High Definition Multimedia Interface" in French);
- interface LIN (de l’anglais « Local Interconnect Network », ou en français « Réseau interconnecté local »). Selon un autre mode de réalisation particulier, le dispositif 400 comprend une interface de communication 440 qui permet d’établir une communication avec d’autres dispositifs via un canal de communication 450. L’interface de communication 440 correspond par exemple à un transmetteur configuré pour transmettre et recevoir des informations et/ou des données via le canal de communication 450 tels que des nuages de données tridimensionnelles, des nuages de points bidimensionnels et/ou des enveloppes convexes formées à partir de ces nuages de points bidimensionnels. L’interface de communication 440 correspond par exemple à un réseau filaire de type CAN (de l’anglais « Controller Area Network » ou en français « Réseau de contrôleurs »), CAN FD (de l’anglais « Controller Area Network Flexible Data-Rate » ou en français - LIN interface (standing for “Local Interconnect Network”). According to another particular embodiment, the device 400 comprises a communication interface 440 which makes it possible to establish communication with other devices via a communication channel 450. The communication interface 440 corresponds for example to a transmitter configured for transmitting and receiving information and / or data via the communication channel 450 such as three-dimensional data clouds, two-dimensional point clouds and / or convex envelopes formed from these two-dimensional point clouds. The communication interface 440 corresponds for example to a wired network of the CAN type (standing for “Controller Area Network” or in French “Network of controllers”), CAN FD (standing for “Controller Area Network Flexible Data”). Rate ”or in French
« Réseau de contrôleurs à débit de données flexible »), FlexRay (selon la norme ISO 17458) ou Ethernet (selon la norme ISO/IEC 802.3). “Flexible data rate controller network”), FlexRay (according to ISO 17458) or Ethernet (according to ISO / IEC 802.3).
Selon un mode de réalisation particulier supplémentaire, le dispositif 400 peut fournir des signaux de sortie à un ou plusieurs dispositifs externes, tels qu’un écran d’affichage, un ou des haut-parleurs et/ou d’autres périphériques via respectivement des interfaces de sortie non représentées. According to a further particular embodiment, the device 400 can supply output signals to one or more external devices, such as a display screen, one or more speakers and / or other peripherals respectively via interfaces. output not shown.
Selon un mode de réalisation, le véhicule 1 de la figure 1 embarque un dispositif de la figure 7. According to one embodiment, the vehicle 1 of Figure 1 carries a device of Figure 7.
Bien entendu, l’invention ne se limite pas aux modes de réalisation décrits ci-avant mais s’étend à un procédé de contrôle d’utilisation d’un véhicule, et au dispositif configuré pour la mise en oeuvre du procédé. Of course, the invention is not limited to the embodiments described above but extends to a method of controlling the use of a vehicle, and to the device configured for implementing the method.

Claims

REVENDICATIONS
1. Procédé de contrôle de déplacement d’un véhicule, comprenant : une étape (310) d’acquisition d’un nuage de données tridimensionnelles obtenues par réflexion d’ondes émises par des capteurs embarqués sur le véhicule; une étape (330) de transformation du nuage de données tridimensionnelles en un nuage de points bidimensionnels exprimés dans un repère de coordonnées polaires associé à un plan, à chaque donnée tridimensionnelle correspond un point bidimensionnel défini par une distance radiale entre un pôle du repère de coordonnées polaires et le point bidimensionnel, et un angle d’azimut défini entre le plan et un segment reliant le pôle et le point bidimensionnel ; une étape (350) itérative de modification du nuage de points bidimensionnels par suppression d’un point bidimensionnel courant dès lors que deux points bidimensionnels voisins du point bidimensionnel courant ne sont pas suffisamment distants l’un de l’autre pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule ; et une étape (360) de contrôle du déplacement dudit véhicule en fonction d’une enveloppe convexe formée par le nuage de points bidimensionnels ainsi modifié et définissant un espace libre accessible au véhicule. 1. A method of controlling the movement of a vehicle, comprising: a step (310) of acquiring a cloud of three-dimensional data obtained by reflection of waves emitted by sensors on board the vehicle; a step (330) of transforming the three-dimensional data cloud into a two-dimensional point cloud expressed in a polar coordinate frame associated with a plane, to each three-dimensional data item corresponds a two-dimensional point defined by a radial distance between a pole of the coordinate frame polar and the two-dimensional point, and an azimuth angle defined between the plane and a segment connecting the pole and the two-dimensional point; an iterative step (350) for modifying the two-dimensional point cloud by deleting a current two-dimensional point when two two-dimensional points neighboring the current two-dimensional point are not sufficiently distant from each other to avoid a collision between the vehicle and an object near this vehicle; and a step (360) of controlling the movement of said vehicle as a function of a convex envelope formed by the two-dimensional point cloud thus modified and defining a free space accessible to the vehicle.
2. Procédé selon la revendication 1 , pour lequel une itération de l’étape itérative (350) comporte une sous-étape d’obtention (351) d’au moins un point bidimensionnel courant du nuage de points bidimensionnels ayant une distance radiale élevée ; et pour chaque point bidimensionnel courant, une sous-étape (352) de calcul d’une première distance minimale entre un segment reliant un point bidimensionnel courant et le pôle du repère de coordonnées polaires, et un autre point bidimensionnel du nuage de points bidimensionnels déterminé de manière à ce que la différence entre l’angle d’azimut dudit autre point bidimensionnel et l’angle d’azimut du point bidimensionnel courant est minimale et positive ; une sous-étape (353) de calcul d’une seconde distance minimale entre ledit segment et un autre point bidimensionnel du nuage de points bidimensionnels déterminé de manière à ce que la différence entre l’angle d’azimut dudit autre point bidimensionnel et l’angle d’azimut du point bidimensionnel courant est minimale et négative ; et une sous-étape (354) de suppression d’un point bidimensionnel courant du nuage de points bidimensionnels lorsque la somme des première et seconde distances est inférieure à une valeur seuil définie pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule ; un point bidimensionnel courant étant conservé lorsque la somme des première et seconde distances est supérieure à la valeur seuil. 2. Method according to claim 1, for which an iteration of the iterative step (350) comprises a sub-step of obtaining (351) at least one current two-dimensional point of the two-dimensional point cloud having a high radial distance; and for each current two-dimensional point, a sub-step (352) of calculating a first minimum distance between a segment connecting a current two-dimensional point and the pole of the polar coordinate frame, and another two-dimensional point of the determined two-dimensional point cloud so that the difference between the azimuth angle of said other two-dimensional point and the azimuth angle of the current two-dimensional point is minimal and positive; a substep (353) of calculating a second minimum distance between said segment and another two-dimensional point of the two-dimensional point cloud determined so that the difference between the azimuth angle of said other two-dimensional point and the azimuth angle of the current two-dimensional point is minimal and negative; and a sub-step (354) of deleting a current two-dimensional point from the two-dimensional point cloud when the sum of the first and second distances is less than a threshold value defined to avoid a collision between the vehicle and an object near this. vehicle; a current two-dimensional point being kept when the sum of the first and second distances is greater than the threshold value.
3. Procédé selon la revendication 1 , pour lequel une itération de l’étape itérative (350) comporte une sous-étape (355) d’obtention d’au moins un couple formé d’un premier et d’un second points bidimensionnels successifs ayant des distances radiales minimales parmi un ensemble de points bidimensionnels triés selon leur angle d’azimut ; et pour chaque couple courant de points bidimensionnels ainsi formé : une sous-étape (356) de suppression de tous les points bidimensionnels du nuage de points bidimensionnels dont les angles d’azimut sont compris entre les angles d’azimut des premier et second points bidimensionnels d’un couple courant lorsque la valeur absolue de la différence entre les angles d’azimut du premier et du second points bidimensionnels dudit couple courant est inférieure à une valeur seuil définie pour éviter une collision entre le véhicule et un objet à proximité de ce véhicule ; lesdits points bidimensionnels du nuage de points bidimensionnels sont conservés lorsque la valeur absolue de ladite différence est supérieure à la valeur seuil. 3. Method according to claim 1, for which an iteration of the iterative step (350) comprises a sub-step (355) of obtaining at least one pair formed of a first and a second successive two-dimensional points. having minimum radial distances among a set of two-dimensional points sorted by their azimuth angle; and for each current pair of two-dimensional points thus formed: a sub-step (356) of deleting all the two-dimensional points from the two-dimensional point cloud whose azimuth angles are between the azimuth angles of the first and second two-dimensional points of a current torque when the absolute value of the difference between the azimuth angles of the first and second two-dimensional points of said current torque is less than a threshold value defined to avoid a collision between the vehicle and an object near this vehicle ; said two-dimensional points of the two-dimensional point cloud are preserved when the absolute value of said difference is greater than the threshold value.
4. Procédé selon l’une des revendications 1 à 3, qui comporte en outre une étape de suppression (320) des données tridimensionnelles correspondant à des échos du sol. 4. Method according to one of claims 1 to 3, which further comprises a step of removing (320) three-dimensional data corresponding to ground echoes.
5. Procédé selon l’une des revendications 1 à 4, qui comporte en outre une étape (340) de filtrage du nuage de points bidimensionnels permettant de ne conserver qu’un seul point bidimensionnel par angle d’azimut. 5. Method according to one of claims 1 to 4, which further comprises a step (340) of filtering the two-dimensional point cloud making it possible to keep only a single two-dimensional point per azimuth angle.
6. Procédé selon l’une des revendications 1 à 5, pour lequel au moins un capteur est un émetteur/récepteur d’ondes électromagnétiques et/ou d’ondes radio. 6. Method according to one of claims 1 to 5, for which at least one sensor is a transmitter / receiver of electromagnetic waves and / or radio waves.
7. Dispositif de contrôle du déplacement d’un véhicule, comprenant au moins un émetteur/récepteur d’ondes électromagnétiques et/ou d’ondes radio et une mémoire associée à au moins un processeur configuré pour la mise en oeuvre des étapes du procédé selon l’une quelconque des revendications 1 à 6. 7. Device for controlling the movement of a vehicle, comprising at least one transmitter / receiver of electromagnetic waves and / or radio waves and a memory associated with at least one processor configured for implementing the steps of the method according to any one of claims 1 to 6.
8. Véhicule comprenant un dispositif selon la revendication 7. 8. Vehicle comprising a device according to claim 7.
9. Produit programme d’ordinateur comportant des instructions adaptées pour l’exécution des étapes du procédé selon l’une des revendications 1 à 6, lorsque le programme d’ordinateur est exécuté par au moins un processeur. 9. Computer program product comprising instructions adapted for the execution of the process steps according to one of claims 1 to 6, when the computer program is executed by at least one processor.
PCT/FR2021/050798 2020-06-23 2021-05-10 Method and device for controlling the movement of a vehicle WO2021260283A1 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
EP21732960.6A EP4168828A1 (en) 2020-06-23 2021-05-10 Method and device for controlling the movement of a vehicle

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR2006537A FR3111713B1 (en) 2020-06-23 2020-06-23 Method and device for controlling the movement of a vehicle
FRFR2006537 2020-06-23

Publications (1)

Publication Number Publication Date
WO2021260283A1 true WO2021260283A1 (en) 2021-12-30

Family

ID=73642973

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/FR2021/050798 WO2021260283A1 (en) 2020-06-23 2021-05-10 Method and device for controlling the movement of a vehicle

Country Status (3)

Country Link
EP (1) EP4168828A1 (en)
FR (1) FR3111713B1 (en)
WO (1) WO2021260283A1 (en)

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2006537A1 (en) 1968-04-19 1969-12-26 Celanese Corp Preparation of bis-hydroxyalkyl esters of benzene
US20190324148A1 (en) * 2018-04-19 2019-10-24 Faraday&Future Inc. System and method for ground and free-space detection

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
FR2006537A1 (en) 1968-04-19 1969-12-26 Celanese Corp Preparation of bis-hydroxyalkyl esters of benzene
US20190324148A1 (en) * 2018-04-19 2019-10-24 Faraday&Future Inc. System and method for ground and free-space detection

Non-Patent Citations (5)

* Cited by examiner, † Cited by third party
Title
B. DOUILLARD ET AL.: "On the Segmentation of 3D LIDAR Point Clouds", 2011 IEEE INTERNATIONAL CONFÉRENCE ON ROBOTICS AND AUTOMATION, 2011, Retrieved from the Internet <URL:http://dx.doi.org/10.1109/ICRA.2011.5979818>
I. BOGOSLAVSKIYC. STACHNISS: "Efficient Online Segmentation for Sparse 3D Laser Scans", PHOTOGRAMMETRIE - FERNERKUNDUNG - GEOINFORMATION, vol. 85, 2016, pages 41, Retrieved from the Internet <URL:http://dx.doi.org/10.1007/s41064-016-0003-y>
MUHAMMAD SUALEH ET AL: "Dynamic Multi-LiDAR Based Multiple Object Detection and Tracking", SENSORS, vol. 19, no. 6, 26 March 2019 (2019-03-26), pages 1474, XP055679812, DOI: 10.3390/s19061474 *
NEUMANN LEO ET AL: "Free Space Detection: A Corner Stone of Automated Driving", 2015 IEEE 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS, IEEE, 15 September 2015 (2015-09-15), pages 1280 - 1285, XP032804169, DOI: 10.1109/ITSC.2015.210 *
Y. ZHOU ET AL.: "A Fast and Accurate Segmentation Method for Ordered LiDAR Point Cloud of Large-Scale Scenes", IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, vol. 11, 2014, pages 1981, XP011549257, Retrieved from the Internet <URL:http://dx.doi.org/10.1109/LGRS.2014.2316009> DOI: 10.1109/LGRS.2014.2316009

Also Published As

Publication number Publication date
FR3111713A1 (en) 2021-12-24
FR3111713B1 (en) 2022-07-08
EP4168828A1 (en) 2023-04-26

Similar Documents

Publication Publication Date Title
CA3063011A1 (en) System and method for detecting and tracking objects
JP2023510162A (en) Sensor degradation detection and improvement
WO2019121056A1 (en) Method for recognising objects in a three dimensional scene
FR3096637A1 (en) Method and device for determining a path for an autonomous vehicle
EP4176286A1 (en) System and method for detecting an obstacle in an area surrounding a motor vehicle
WO2021260283A1 (en) Method and device for controlling the movement of a vehicle
WO2022152986A1 (en) Method and device for monitoring the trajectory of a vehicle traveling on a traffic lane
FR3106108A1 (en) Method and device for determining the trajectory of a road
FR3118669A1 (en) Method and device for determining a trajectory of an autonomous vehicle
EP4090565B1 (en) Method and device for controlling a vehicle
WO2024115827A1 (en) Method and device for controlling a driving assistance system in an environment containing an intersection
WO2023144470A1 (en) Method and device for controlling the trajectory of an autonomous vehicle travelling in an environment comprising at least one moving object
FR3118746A1 (en) Method and device for aiding the driving of a vehicle traveling on a road comprising several traffic lanes
FR3123862A1 (en) Method and device for controlling an autonomous vehicle
FR3128678A1 (en) Method and device for trajectory control of an autonomous vehicle
WO2023099828A1 (en) Method and device for controlling an adaptive cruise control system of a vehicle
FR3130228A1 (en) Method and device for controlling an automatic lane change system
WO2022157433A1 (en) Method and device for controlling a first vehicle following a second vehicle over a portion of road comprising a turn
FR3123619A1 (en) A method of regulating the speed of a vehicle traveling on a roadway from a target vehicle.
FR3123981A1 (en) Method and device for trajectory control of an autonomous vehicle
WO2023078936A1 (en) Processing of lidar sensor data
WO2023111412A1 (en) Method and device for controlling the acceleration of a vehicle
EP4351944A1 (en) Method and device for controlling the speed of a vehicle based on a target vehicle
WO2023037060A1 (en) Method and device for controlling the speed of an autonomous vehicle
WO2023105131A1 (en) Method and device for controlling an adaptive cruise control system of a vehicle

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: 21732960

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

ENP Entry into the national phase

Ref document number: 2021732960

Country of ref document: EP

Effective date: 20230123