Method and device for checking the reliability of information on the location of a vehicle obtained from a GNSS system

Abstract

The present invention relates to a method and a device for checking the reliability of information on the location of a vehicle (11) obtained from a satellite geolocation system. To this end, first data on the location of the vehicle (11) are determined from signals received from satellites (111 to 114) and second data on the location of the vehicle (11) are determined from data received from sensors onboard the vehicle (11). A first level of vehicle location accuracy is determined by comparing the first data and the second data. The first level of accuracy is compared with a second level of location accuracy obtained from a satellite visibility map. The reliability of the second level of accuracy is determined on the basis of a result of comparing the first level of accuracy with the second level of accuracy.

Description

DESCRIPTION Title: Method and device for verifying the reliability of vehicle location information obtained from a GNSS system technical field

[0001] The present invention claims priority from French application 2410436 filed on September 30, 2024, the content of which (text, drawings and claims) is incorporated herein by reference.

[0002] The present invention relates to methods and devices for verifying the reliability of vehicle location information obtained from a satellite geolocation system, known as a GNSS system. More broadly, the present invention relates to a method and device for monitoring the location of an automated vehicle traveling in a road environment, particularly, but not exclusively, for an electric motor vehicle. Technological background

[0003] With the development of automated vehicles (from the English "Automated Vehicle"), also called autonomous vehicles, needs have emerged in terms of route planning and tracking, particularly depending on the environment around the automated vehicle.

[0004] Controlling the trajectory of an automated vehicle, through one or more driver assistance systems, known as ADAS (Advanced Driver-Assistance System) systems, embedded in the automated vehicle, requires a good knowledge of the environment around the automated vehicle as well as an exact knowledge of the position of the automated vehicle.

[0005] The location of an automated vehicle is obtained, as with any vehicle, by using a receiver of a geolocation system based on a satellite positioning system designated by the acronym GNSS (Global Navigation Satellite System). global satellite"), for example a GPS system (from the English "Global Positioning System" or in French "Système de emplacement global"), Galileo or Glonass.

[0006] In certain environments, such as urban areas with buildings, mountainous regions, or densely wooded areas, the reception of satellite signals can be disrupted. Signal occlusion and reflection can lead to multiple paths for the transmitted signals, resulting in inaccuracies in the GNSS receiver's position assessment. A lack of precise location for an automated vehicle within a hazardous area of ​​its environment creates risks related to controlling the vehicle's movement to safely reach or traverse that hazardous area without leaving the designated lanes or colliding with obstacles. Summary of the present invention

[0007] One object of the present invention is to solve at least one of the problems of the technological background described above.

[0008] Another object of the present invention is to improve the safety of a vehicle, for example an automated vehicle, travelling in a road environment.

[0009] According to a first aspect, the present invention relates to a method for verifying the reliability of vehicle location information obtained from a satellite geolocation system, the method being implemented by at least one processor and comprising the following steps: a) determination of first representative vehicle location data along a path traveled by the vehicle from signals received from a set of satellites of the geolocation system; b) determination of second representative vehicle location data along the path from data received from at least one sensor on board the vehicle; c) determination of a first level of accuracy of vehicle location along the path by comparison of the first and second data; d) comparison of the first level of accuracy to a second level of accuracy of vehicle location along the path obtained from a satellite visibility map associated with the path, the satellite visibility map including representative visibility data of the set of satellites from the path; e) determination of a first representative reliability information of the second level of accuracy based on a result of the comparison of the first level of accuracy to the second level of accuracy.

[0010] Using two different sources to obtain the vehicle's location—namely, a GNSS system and one or more sensors onboard the vehicle—allows us to verify whether the location obtained from one source, the GNSS system, corresponds to the location obtained from the other source. Comparing these two locations provides information on the level of accuracy of the positioning, which can then be compared with similar information obtained from a satellite visibility map. The result of this comparison allows us to verify whether the expected level of positioning accuracy from the satellite visibility map is reliable.Determining reliability helps to know whether a vehicle, especially an automated vehicle, will be able to use the level of location accuracy information that can be obtained from the GNSS system associated with the satellite visibility map, which makes it possible to anticipate potential location problems and thus improve the safety of the vehicle and other road users.

[0011] Ensuring that the level of accuracy of the location is sufficient reduces, for example, the risk of deviating from the intended trajectory, which reduces the risk of an accident and increases the safety of an automated vehicle, its possible passengers and other road users.

[0012] According to one variant, when the result indicates a difference between the first level of accuracy and the second level of accuracy less than a threshold, the first piece of information is representative of a verified reliability of the second level of accuracy and said first piece of information is recorded and associated with said path.

[0013] According to another variant, when the result indicates a difference between the first level of precision and the second level of precision greater than the threshold, the process further includes a step of verifying an association of a second piece of information with the path, the second piece of information being representative of a difference between the first level of precision and the second level of precision greater than the threshold, the second piece of information being prior to the first piece of information, the first piece of information being further determined according to a result of the verification.

[0014] According to another variant, when the result of the verification indicates the presence of an association of the second piece of information with the path, the first piece of information is representative of the difference between the first level of accuracy and the second level of accuracy and the first piece of information is recorded and associated with the path, the process further comprising a step of determining a set of causes resulting in the difference between the first level of accuracy and the second level of accuracy by analyzing an area including the path taking the first piece of information as a reference for the analysis.

[0015] According to an additional variant, when the result of the verification indicates an absence of association of the second piece of information with the path, the process includes a reiteration of steps a) to e) to confirm the first piece of information.

[0016] According to yet another variant, the first piece of information is transmitted to a remote device via a wireless connection.

[0017] According to another variant, at least one sensor belongs to a set of sensors comprising: - an inertial sensor; - a radar; - a lidar; and - a camera.

[0018] According to a second aspect, the present invention relates to a device for verifying the reliability of vehicle location information obtained from a satellite geolocation system, the device comprising a memory associated with a processor configured for implementing the steps of the process according to the first aspect of the present invention.

[0019] According to a third aspect, the present invention relates to a vehicle, for example of an automated type, comprising a device as described above according to the second aspect of the present invention.

[0020] According to a fourth aspect, the present invention relates to a system comprising the vehicle as described above according to the third aspect of the present invention and a remote device connected wirelessly to the vehicle.

[0021] According to a fifth aspect, the present invention relates to a computer program which includes instructions adapted for carrying out the steps of the process according to the first aspect of the present invention, in particular when the computer program is executed by at least one processor.

[0022] Such a computer program can use any programming language, and be in the form of source code, object code, or an intermediate form between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0023] According to a sixth aspect, the present invention relates to a computer-readable recording medium on which is recorded a computer program comprising instructions for carrying out the steps of the process according to the first aspect of the present invention.

[0024] On the one hand, the recording medium can be any entity or device capable of storing the program. For example, the medium can include a storage means, such as a ROM, a CD-ROM or a microelectronic circuit-type ROM, or a magnetic recording means or a hard drive.

[0025] On the other hand, this recording medium can also be a transmissible medium such as an electrical or optical signal, such a signal being able to be transmitted via an electrical or optical cable, by conventional or radio frequency, by self-directing laser beam, or by other means. The computer program according to the present invention can, in particular, be downloaded from a network such as the Internet.

[0026] Alternatively, the recording medium may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to execute or to be used in the execution of the process in question. Brief description of the figures

[0027] Other features and advantages of the present invention will become apparent from the description of the specific and non-limiting embodiments of the present invention below, with reference to the attached Figures 1 to 4, in which:

[0028] [Fig. 1] schematically illustrates an environment including a vehicle, according to a particular embodiment of the present invention;

[0029] [Fig. 2] illustrates a flowchart of the different operations of a reliability verification process for the location information of a vehicle in Figure 1 obtained from a satellite geolocation system, according to a particular and non-limiting embodiment of the present invention.

[0030] [Fig. 3] illustrates a device configured for the reliability verification of location information of a vehicle of figure 1 obtained from a satellite geolocation system, according to a particular and non-limiting embodiment of the present invention.

[0031] [Fig. 4] illustrates a flowchart of the different steps of a process for verifying the reliability of location information of a vehicle from figure 1 obtained from a satellite geolocation system, according to a particular and non-limiting embodiment of the present invention. Description of examples of achievements

[0032] A method and device for verifying the reliability of vehicle location information obtained from a satellite geolocation system will now be described in what follows with joint reference to Figures 1 to 4. The same elements are identified with the same reference signs throughout the description that follows.

[0033] The terms "first," "second" (or "firsts," "seconds"), etc., are used in this document by arbitrary convention to identify and distinguish different elements (such as operations, means, etc.) implemented in the embodiments described below. Such elements may be distinct or correspond to a single element, depending on the embodiment.

[0034] According to a particular and non-limiting embodiment of the present invention, the reliability verification of vehicle location information obtained from a satellite geolocation system is implemented in the vehicle, for example, by one or more processors of one or more vehicle computers. This vehicle corresponds, for example, to an automated vehicle, that is, a vehicle configured to operate in a road environment with a level of autonomy exceeding a certain threshold, for example, without a driver or without intervention from a driver.

[0035] To this end, initial representative location data for the vehicle along a path traveled by the vehicle are determined from signals received from a set of satellites in the geolocation system, known as a GNSS system, via a GNSS receiver installed in the vehicle. Secondary representative location data for the vehicle along the path are determined from data received from at least one sensor installed in the vehicle, for example, sensors from the vehicle's inertial measurement unit (IMU), one or more of the vehicle's cameras, or the vehicle's radar and / or lidar. The first and second data sets are compared to determine an initial level of accuracy for the vehicle's location along the path.This first level of accuracy is compared to a second level of accuracy for vehicle location along the path obtained, determined, or deduced from a satellite visibility map of the GNSS system's satellite array, specifically from the path. Comparing the first level of accuracy to the second level of accuracy provides initial information representative of the reliability of the second level of accuracy, and consequently, representative of the reliability of the satellite visibility map associated with the path.

[0036] Figure 1 schematically illustrates a road environment 1 comprising a vehicle 10 and a vehicle 11, according to a particular and non-limiting embodiment of the present invention.

[0037] Road environment 1 corresponds to any environment in which the automated vehicle 10 is likely to travel. Road environment 1 corresponds, for example, to an urban environment or a mixed environment. including an urban part and an extra-urban part, a non-city environment, etc.

[0038] According to a particular embodiment, the road environment 1 includes one or more areas in each of which the reception of satellite signals emitted by a set of satellites of a satellite geolocation system may be disrupted, inducing a risk in determining the location of the autonomous vehicle 10 when the latter follows a determined route or path in the road environment 1.Disruption of satellite signal reception is, for example, due to the presence of one or more buildings possessing a set of determined characteristics, for example one or more buildings with a height greater than a threshold (for example 5 or 10 m) and / or a width greater than a threshold (for example 10, 20 or 50 m) and / or including materials that disrupt the reception of satellite signals, such a building being likely to obstruct the reception of satellite signals and / or to generate multiple paths for receiving satellite signals.

[0039] An automated vehicle is defined as a vehicle equipped with a sophisticated driver assistance system that ensures vehicle control and is capable of operating in its road environment without driver intervention or under the control of a person not involved in driving the automated vehicle, except in emergencies, for example. A vehicle capable of such autonomous driving must have a level of autonomous driving capability exceeding a certain threshold out of a total number of levels. For example, the automated vehicle must have an autonomy level of 4 or higher out of the 5 levels defined in the classification published by the federal agency responsible for road safety in the USA, or out of the 6 levels defined in the classification published by the international organization of motor vehicle manufacturers, which includes 6 levels.According to one embodiment, the automated vehicle 10 has a level of autonomy greater than or equal to 3 out of the 5 or 6 levels provided for in the two classifications mentioned above.

[0040] The automated vehicle 10 corresponds for example to a vehicle with a combustion engine, an electric vehicle or a hybrid vehicle (combining a combustion engine and an electric motor).

[0041] In one embodiment, the automated vehicle 10 corresponds to an autonomous shuttle, for example, with an electric motor. Such an autonomous shuttle is configured to follow a predetermined route with stops along the way to pick up one or more passengers. The route may be modified over time (for example, occasionally or seasonally), for example, according to user needs, to avoid temporary construction zones, etc. In another embodiment, the autonomous shuttle is shared by several users in an on-demand service model, for example, whereby the autonomous shuttle picks up each passenger at a predetermined location via a mobile application or website managed by the autonomous shuttle operator and drops them off at their desired destination.

[0042] According to another example of implementation, the automated vehicle 10 corresponds to a vehicle configured to transport and deliver parcels to one or more recipients, the route to be taken varying according to the delivery addresses of the parcels.

[0043] The automated vehicle 10 also corresponds, for example, to a so-called connected vehicle, that is to say an automated vehicle configured to communicate (transmit and receive) data according to a wireless communication mode, for example via a wireless network infrastructure or according to a direct communication mode.

[0044] To this end, the automated vehicle 10 includes a communication system or interface comprising, for example, one or more communication antennas connected to a telematic control unit (TCU), which is itself connected to one or more computers of the automated vehicle 10's embedded system. The antenna(s), the TCU, and the computer(s) form, for example, a multiplexed architecture for providing various services necessary for the proper functioning of the automated vehicle 10. The computer(s) and the TCU communicate and exchange data with each other via one or more computer buses, for example, a CAN (Controller Area Network) or CAN FD (Controller Area Network Flexible Data-Rate) data bus. flexible data rate controllers”), FlexRay (according to ISO 17458) or Ethernet (according to ISO / IEC 802-3).

[0045] The network infrastructure includes, for example, communication devices 101 corresponding, for example, to an antenna of a cellular network of type LTE 4G or 5G or to a UBR (“Roadside Unit”).

[0046] Each communication device 101 is advantageously connected to one or more remote servers 110 or to the cloud 100 via a wired and / or wireless connection. The communication device 101 is thus configured to act as a relay between the cloud 100 and its servers 110 on the one hand, and the automated vehicle 10 on the other.

[0047] The automated vehicle 10 communicates, for example, using a so-called V2X communication system, for example based on the 3GPP LTE-V or IEEE 802.11p standards of ITS G5. In such a V2X communication system, each vehicle carries a node (or wireless communication system / interface) to enable vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I) and / or vehicle-to-pedestrian (V2P) communication, with pedestrians being equipped with mobile devices (for example, a smartphone) configured to communicate with the vehicles.

[0048] The automated vehicle 10 also includes a receiver for a GNSS-type geolocation system configured to determine data representative of its geographic position at any given time based on signals received from a set of GNSS satellites 111 to 114. The data representing the geographic position takes, for example, the form of coordinates (latitude and longitude). The geographic position obtained from the GNSS system is said to be absolute in that the coordinates are expressed in the same reference frame for each vehicle, namely the world reference frame.

[0049] A process for verifying the reliability of vehicle location information obtained from a GNSS system is implemented by one or more computers of a vehicle 11 different from the automated vehicle 10, i.e. by one or more processors of this or these computers.

[0050] An example of implementation is described opposite Figure 2 below.

[0051] Vehicle 11 corresponds to an automated or non-automated vehicle, that is, a vehicle whose driving is controlled by a set of ADAS systems in an automated manner or by a driver in a manual manner.

[0052] Vehicle 11 carries initial means for determining its position / location from signals received from the GNSS system's satellites 111 to 114. These initial means correspond to a GNSS system receiver identical or similar to the one carried in the automated vehicle 10.

[0053] Vehicle 11 also carries secondary means of determining its position / location from data received from one or more sensors on board vehicle 11. This sensor or these sensors correspond to one or more of the following sensors, in any possible combination: - one or more inertial sensors from an inertial measurement unit of vehicle 11: the data received from such sensors allows vehicle 11 to determine its position independently of the GNSS system; the received data feeds, for example, the GNSS fusion module adapted to the use of inertial data by modifying the weighting of the different parameters of the particle filter (for example, an extended Kalman filter) necessary for determining the position of vehicle 11; and / or - one or more millimeter-wave radars arranged on the vehicle 11, for example at the front, at the rear, on each front / rear corner of the vehicle; each radar is adapted to emit electromagnetic waves and to receive the echoes of these waves reflected by one or more objects, for the purpose of detecting obstacles and their distances from the vehicle 11; and / or - one or more LIDAR(s) (from the English "Light Detection And Ranging", or (Light Detection and Ranging), a LIDAR sensor corresponding to an optoelectronic system composed of a laser emitter, a receiver including a light collector (to collect the portion of the light emitted by the emitter and reflected by any object located in the path of the light rays emitted by the emitter) and a photodetector that transforms the collected light into an electrical signal; a LIDAR sensor thus makes it possible to detect the presence of objects located in the emitted light beam and to measure the distance between the sensor and each detected object; and / or - one or more cameras (associated or not with a depth sensor) for the acquisition of one or more images of the environment around the vehicle 11 located in the field of vision of the camera(s).

[0054] Data received from sensors such as one or more cameras allows the identification of elements of the road environment 1 in which the vehicle 11 is traveling, through the implementation of one or more image processing methods. The identification of specific elements (buildings, intersections, monuments, etc.) whose location is known (for example, contained in mapping data to which the vehicle 11 has access, such data being stored, for example, in the vehicle 11's memory or received from a server via a wireless connection) allows the vehicle 11 to determine its location relative to these specific elements, based on information such as the distance to them. The distance to these specific elements is obtained, for example, via an image processing method or via data received from LiDAR or radar.

[0055] Vehicle 11 further includes one or more wireless communication systems or interfaces identical or similar to those of automated vehicle 10, vehicle 11 corresponding to a connected vehicle.

[0056] Figure 2 schematically illustrates a process for verifying the reliability of location information of a vehicle (such as vehicle 11 or automated vehicle 10) obtained from a satellite geolocation system, according to particular and non-limiting examples of embodiments of the present invention.

[0057] In a first operation 20 of the process, the vehicle 11 begins a driving phase in a determined area of ​​the road environment 1, for example on a specific road or section of road associated with a route.

[0058] The driving phase is triggered, for example, following the receipt of a request, which request is generated and transmitted by the automated vehicle 10 or by a remote device from the "cloud" 100, via a wireless connection.

[0059] Such a driving phase is triggered, for example, to verify that the information contained in a satellite visibility map associated with the road environment 1 is correct, and more specifically that associated with a route or part of a route followed by an automated vehicle such as the automated vehicle 10.

[0060] The driving phase is triggered, for example: - during a new route that the automated vehicle 10 will have to follow, to verify the validity of the data on the satellite visibility map associated with this new route; and / or - when a route followed by the automated vehicle 10 is modified, the driving will, for example, only concern the portion of the road corresponding to the modified or added portion of the route in order to more specifically verify the satellite visibility map associated with this portion of the road; and / or - in the event of a problem encountered by the automated vehicle 10 on the path or a portion of the path associated with the route followed by the automated vehicle 10; and / or - periodically, for example every week, every month or every 2, 3 or 6 months.

[0061] A satellite visibility map associated with a given territory, for example road environment 1, includes data representative of the visibility of each satellite in the 111 to 114 satellite set of the GNSS system used by the automated vehicle 11 and the vehicle 10 to determine its current position based on the satellite signals received.

[0062] Representative visibility data for the 111-114 satellite set includes representative visibility information for each satellite in the 111-114 GNSS system, from a set of points in the road environment 1 (or more precisely from a road or part of a road followed by the automated vehicle along a determined route).

[0063] The satellite visibility map is for example generated by the remote device 110 based on representative data of orbital parameters of each satellite in the set of satellites 111 to 114 and representative data of a digital surface model associated with the road environment 1, the representative visibility data of the set of satellites 111 to 114 being thus obtained from the representative data of orbital parameters of each satellite and the representative data of a digital surface model associated with the road environment 1.

[0064] A satellite visibility map, for example, is associated with a specific time point. Indeed, as the location of satellites varies in space over time according to the orbit followed by each of these satellites, the satellite visibility map also varies over time, the visibility of each satellite from a point or a surface element of the road environment 1 varying according to the location of the satellite in its orbit.

[0065] The representative visibility data for the satellite array 111 to 114 thus obtained represent, for example, the visibility of each satellite in the GNSS system from a set of points in the road environment 1 for different time intervals within a given time range. According to one variant, the first data received correspond to representative data of the orbital parameters of each satellite and representative data of a digital surface model associated with the road environment 1. The computer(s) of the automated vehicle 10 or vehicle 11 and / or the processor(s) of the remote device 110 perform the calculations to predict visibility in a given area or on specific sections of road at different time intervals, according to the needs of the automated vehicle 10 or vehicle 11, for example.

[0066] The satellite visibility map is generated using any method known to a person skilled in the art, for example as described in the document entitled "Study for the creation of GNSS satellite visibility maps", by Guillaume Bizouard, published in the journal XYZ, No. 111 to 2 ème quarter 2007.

[0067] The method described involves extrapolating the orbital / Keplerian parameters of the satellites to the desired forecast date or time, given that these calculations relating to celestial mechanics are known. Various changes of reference frames are applied to the results of the calculations to obtain topocentric coordinates (azimuth and elevation). For each satellite, its topocentric coordinates are thus obtained at the desired observation point on Earth, for example, for each point in a set of points in the road environment.

[0068] The set of points includes, for example, reference points defining the road segments of the road environment 1 (including the path(s) followed by the automated vehicle 10 and the vehicle 11), the paths forming the road segments being discretized to obtain the set of points.

[0069] To refine the satellite visibility of a point in the road environment 1, whose defined area is 1000, it is necessary to take into account the surrounding obstacles (buildings and vegetation, for example). To this end, the method described plans to use geodata describing the space associated with the road environment 1, whose defined area is 1000. This geodata is obtained, for example, from a LiDAR point cloud (for example, obtained from LiDAR(s) on board an aircraft that flew over the road environment 1, whose defined area is 1000, for the acquisition of the point cloud). This geodata corresponds, for example, to data from a digital surface model, known as a DSM, also called a digital terrain model.

[0070] The satellite visibility map thus obtained makes it possible to know at any point in the road environment 1, the visibility of each satellite in the constellation, for example to determine if a satellite is visible in direct line of sight at a given time.

[0071] The representative visibility data of the set of satellites 111 to 114 thus correspond to data enabling the determination of which satellites 111 to 114 are visible from a point or a surface element of the road environment 1, at a given time.

[0072] According to one variant, the representative visibility data for the set of satellites 111 to 114 correspond to data indicating the number of satellites visible from each point in the road environment point set 1, for example 1, 2, 3, 4, 5 or more satellites at a given time.

[0073] The quality or level of accuracy of the automated vehicle 10's localization depends on the number of satellites visible from that location. To obtain a localization with a level of accuracy exceeding a certain threshold, a signal emitted from four satellites within direct line of sight is required. While three satellites are sufficient to obtain a position using trilateration, a fourth satellite is necessary to precisely determine the offset of the receiver onboard the automated vehicle 10 relative to the clocks of satellites 111 to 114. For example, a clock offset of 10 nanoseconds induces a position error of 3 meters. The greater the number of satellites visible from a given position, the more precise the position determination will be.

[0074] The representative visibility data from the 111 to 114 satellite array also represent a level of location accuracy that a vehicle can achieve by determining its position / location from the received satellite signals. This level of vehicle location accuracy is referred to hereafter as the second level of vehicle location accuracy. The second level of positional accuracy that can be determined on the road environment at a given moment corresponds to an indicator (called the second indicator) taking, for example, a value from a defined set of values, such as a set of 3, 5, or 10 values. The higher the value of the indicator, the greater the accuracy obtained. According to one variant, the second level of position accuracy corresponds to an indicator with a value in centimeters, corresponding to the accuracy in centimeters that can be obtained.

[0075] The process operations are described with regard to driving on a road or a section of a road. The invention is not limited to such an example but extends to verifying the reliability of satellite vehicle location information in any area, route, or road environment.

[0076] In a second operation 21 of the process, the reliability of the second level of accuracy obtainable from the satellite visibility map is verified. This verification corresponds to a consistency check between the ground truth as determined by the vehicle 11 traversing the path being verified and the data from the satellite visibility map.

[0077] To this end, vehicle 11, i.e., the vehicle 11 control unit responsible for the process, determines initial representative location data for vehicle 11 along its path from signals received from the set of satellites 111 to 114 of the satellite geolocation system (GNSS system). Vehicle 11 thus determines its position or location at one or more points along the path (the number of points depending, for example, on the length of the path) from the satellite signals received from the set satellite, this or these locations being determined by the receiver on board the vehicle 11.

[0078] Location is determined for example every 10, 30 or 50 cm and / or every 100, 200 or 500 ms along the path followed by vehicle 11.

[0079] This initial data is stored in a memory of the vehicle 11, for example temporarily in a buffer of the computer in charge of the process.

[0080] The vehicle 11 further determines second representative position or location data of the vehicle 11 along the path from data received from one or more sensors on board the vehicle 11.

[0081] This sensor or these sensors belong to a set of sensors including: - an inertial sensor; - a radar; - a lidar; and - a camera.

[0082] This second data is stored in a memory of the vehicle 11, for example temporarily in a buffer of the computer in charge of the process.

[0083] The first and second data points are determined for the same point(s) on the path, for example in parallel, so that the position of vehicle 11 determined via the GNSS system can be compared with the position of vehicle 11 determined by the on-board sensor(s), i.e. without using the signals received from the GNSS system satellite(s).

[0084] A first level of accuracy in locating vehicle 11 along the path is determined by comparing the first and second data, for example for each point for which the first and second data have been determined.

[0085] The comparison between the first and second data points reveals a discrepancy between the location obtained from the GNSS system and the location obtained from the data received from the onboard sensor(s). This comparison provides an initial indicator of the consistency between the obtained location and the data received. of the GNSS system and the location obtained from the data received from the onboard sensor(s) and on the reliability of the location obtained from the GNSS system.

[0086] The first level of precision corresponds, for example, to the deviation, expressed in centimeters. In another example, the first level of precision corresponds to an indicator (called the first indicator) taking, for example, a value from a defined set of values, for example, from a set comprising 3, 5, or 10 values, the precision obtained being, for example, all the higher the larger the value of the indicator.

[0087] In a third operation 22 of the process, the first level of accuracy (or first indicator) is compared to the second level of accuracy (or second indicator).

[0088] To be compared, the first indicator and the second indicator are representative of the same quantity, for example a distance in centimeters or the value in the defined set of values.

[0089] A first representative piece of information regarding the reliability of the second level of accuracy is determined based on the result of comparing the first level of accuracy to the second level of accuracy.

[0090] When the comparison indicates that the difference between the first level of accuracy and the second level of accuracy is less than or equal to a threshold (e.g. equal to 0 when these levels of accuracy are represented by a value from the defined set of values ​​or equal to 10, 20 or 30 cm when these levels of accuracy are expressed in centimeters), the process continues with a fourth operation 23.

[0091] Otherwise, when the comparison indicates that the difference between the first level of accuracy and the second level of accuracy is greater than the threshold, the process continues with a fifth operation 24.

[0092] In the fourth operation 23 of the process, the first piece of information indicates that the second level of accuracy is reliable, the second level of accuracy being consistent with the first level of accuracy. The first piece of information is therefore representative of the verified reliability of the second level of accuracy, and such first information is stored in memory and associated with the path (or the point on the path considered).

[0093] This initial information is associated, for example, with each point for which first and second data points have been verified, or with each segment of an elementary path (that is, with each segment of a path of a determined distance, for example, equal to 10, 20, or 50 cm). This initial information is, for example, recorded in a memory of the vehicle 11.

[0094] When the entire route has been traveled by vehicle 11, it transmits all the first determined information to the remote device via the wireless connection so that the latter can record it in memory and associate this reliability information with the visibility map data to indicate to other vehicles receiving the satellite visibility map whether the information understood is reliable (or not, as described opposite operations 24 to 27).

[0095] In the fifth operation 24 of the process, it is checked whether a difference between the first level of precision and the second level of precision has already been determined and detected. Thus, the presence or absence of an association of a second piece of information representing a difference between the first level of precision and the second level of precision greater than the threshold, and prior to the first piece of information (i.e., reported and detected before the first piece of information) is verified.

[0096] It is thus checked whether such a second piece of information is associated with the path, for example stored in the memory of vehicle 11 with the data from the satellite visibility map for example.

[0097] According to one variant, the verification is implemented by the remote device 110. According to this variant, the result of the comparison between the first level of accuracy and the second level of accuracy is transmitted by the vehicle 11 to the remote device 110 via the wireless connection linking them.

[0098] According to the result 25 of the verification, the process continues with a sixth operation 26 or with a seventh operation 27.

[0099] The process continues with the sixth operation 26 when no second information has been previously associated with the path, that is, when no difference between the first level of precision and the second level of precision has been previously reported or detected.

[0100] The process continues with the seventh operation 27 when at least one second piece of information has been previously associated with the path, that is, when at least one difference between the first level of precision and the second level of precision has been previously identified or detected.

[0101] In the sixth operation 26 of the process, another test run on the path in question is required to confirm the difference between the first level of accuracy and the second level of accuracy. This second test run is carried out, for example, with the same vehicle 11 or with another vehicle equipped in the same way as vehicle 11. The operations described previously, in particular the second operation 21 and the third operation 22, are repeated.

[0102] In the seventh operation 27 of the process, the first piece of information confirmed via the presence of the second piece of information is recorded and associated with the path, for example in the satellite visibility map stored at the remote device 110.

[0103] For example, a query is generated to request an analysis of the environment around the path and determine the reasons for the observed difference (e.g., the presence of an unlisted building, a weather event disrupting satellite signal reception, etc.). The set of causes leading to the difference between the first and second levels of accuracy is determined by analyzing an area encompassing the path, using the first piece of information as the reference for the analysis.Such a determination is obtained for example from data received from sensor(s) on board vehicle 11, for example a camera (via the implementation of one or more image processing methods on the received image data) and / or a lidar, considering the first information as reference information regarding the difference between the first level of accuracy observed or detected on the ground by vehicle 11 and the first level of accuracy obtained from the satellite visibility map.

[0104] According to one variant, the determination of the reasons for the difference is implemented later by one or more persons mandated to analyze the causes of the difference on the ground, based on the first information and considering the first information as reference or ground truth.

[0105] The process ends with the eighth operation, 28.

[0106] Figure 3 schematically illustrates a device 3 configured to verify the reliability of location information obtained from a satellite geolocation system for an automated vehicle such as the automated vehicle 10, according to various specific and non-limiting embodiments of the present invention. The device 3 corresponds, for example, to a device embedded in a vehicle such as the vehicle 11, corresponding, for example, to a computer.

[0107] According to a particular embodiment, device 3 corresponds to a remote device such as remote device 110.

[0108] Device 3 is, for example, configured to carry out at least some of the operations described opposite Figures 1 and 2 and / or the steps of the process described opposite Figure 4. Examples of such a device 3 include, but are not limited to, embedded electronic equipment such as a vehicle's on-board computer, an electronic control unit such as an ECU (Electronic Control Unit), a TCU, a controller, a computer, a server, or a mobile communication device (for example, embedded in an automated vehicle 10 and connected by wired or wireless communication to that automated vehicle 10). The elements of device 3, individually or in combination, may be integrated into a single integrated circuit, into several integrated circuits, and / or into discrete components.Device 3 can be implemented in the form of electronic circuits or software (or computer) modules or a combination of electronic circuits and software modules.

[0109] Device 3 includes one or more processors 30 configured to execute instructions for carrying out the steps of the process and / or for executing instructions from the software embedded in Device 3. The processor 30 may include integrated memory, an input / output interface, and various circuits known to those skilled in the art. Device 3 further includes at least one memory 31, for example, volatile and / or non-volatile memory, and / or includes a memory storage device that may include volatile and / or non-volatile memory, such as EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic disk, or optical disk.

[0110] The computer code of the embedded software(s) including the instructions to be loaded and executed by the processor is for example stored on memory 31.

[0111] According to various specific and non-limiting embodiment examples, device 3 is coupled in communication with other similar devices or systems and / or with communication devices, for example a TCU (Telematic Control Unit), for example via a communication bus or through dedicated input / output ports.

[0112] According to a specific and non-limiting embodiment, device 3 includes a block 32 of interface elements for communicating with external devices. The interface elements of block 32 include one or more of the following interfaces: - radio frequency RF interface, for example of the Wi-Fi® type (according to IEEE 802.11), for example in the 2.4 or 5 GHz frequency bands, or of the Bluetooth® type (according to IEEE 802.15.1), in the 2.4 GHz frequency band, or of the Sigfox® type using UBN (Ultra Narrow Band) radio technology, or LoRa in the 868 MHz frequency band, LTE (Long-Term Evolution), LTE-Advanced, 5G; - USB interface (from the English "Universal Serial Bus" or "Universal Serial Bus" in French); - HDMI interface (from the English "High Definition Multimedia Interface", or "High Definition Multimedia Interface" in French); - LIN interface (from the English "Local Interconnect Network", or in French "Réseau interconnecté local").

[0113] According to another specific and non-limiting embodiment, the device 3 includes a communication interface 33 that enables communication with other devices (such as other computers in the embedded system) via a communication channel 330. The communication interface 33 corresponds, for example, to a transmitter configured to transmit and receive information and / or data via the communication channel 330. The communication interface 33 corresponds, for example, to a CAN-type wired network (of (from the English "Controller Area Network" or in French "Réseau de contrôlers"), CAN FD (from the English "Controller Area Network Flexible Data-Rate" or in French "Réseau de contrôlers à débit de données flexible"), FlexRay (standardized by the ISO 17458 standard) or Ethernet (standardized by the ISO / IEC 802-3 standard).

[0114] According to a particular and non-limiting embodiment, the device 3 can provide output signals to one or more external devices, such as a display screen 340, touch or not, one or more speakers 350 and / or other peripherals 360 (projection system) via output interfaces 34, 35 and 36 respectively. According to a variant, one or more of the external devices is integrated into the device 3.

[0115] Figure 4 illustrates a flowchart of the different steps in a method for verifying the reliability of vehicle location information obtained from a satellite geolocation system, according to a particular, non-limiting embodiment of the present invention. The method is implemented, for example, by a computer, such as device 3 in Figure 3.

[0116] In a first step 41, initial representative data on the location of the vehicle along a path traveled by the vehicle are determined from signals received from a set of satellites of the geolocation system.

[0117] In a second step 42, second representative data for the location of the vehicle along the path are determined from data received from at least one sensor on board the vehicle.

[0118] In a third step 43, a first level of accuracy of vehicle location along the path is determined by comparing the first data and the second data.

[0119] In a fourth step 44, the first level of accuracy is compared to a second level of accuracy of vehicle location along the path obtained from a satellite visibility map associated with the path, the satellite visibility map comprising representative visibility data of the set of satellites from the path.

[0120] In a fifth step 45, a first representative reliability information of the second level of accuracy is determined based on a result of the comparison of the first level of accuracy to the second level of accuracy.

[0121] According to one variant, the variants and examples of the operations described in relation to Figure 1 and / or Figure 2 apply to the steps of the process in Figure 4.

[0122] Of course, the present invention is not limited to the embodiments described above but extends to a method for determining the reliability of information contained in a satellite visibility map, which would include secondary steps without departing from the scope of the present invention. The same would apply to a device configured for implementing such a method.

Claims

DEMANDS 1. A method for verifying the reliability of vehicle location information (11) obtained from a satellite geolocation system, said method being implemented by at least one processor and comprising the following steps: a) determining (41) first representative location data of said vehicle (11) along a path traveled by said vehicle from signals received from a set of satellites (111 to 114) of said satellite geolocation system; b) determining (42) second representative location data of said vehicle (11) along said path from data received from at least one sensor on board said vehicle (11); c) determining (43) a first level of location accuracy of said vehicle (11) along said path by comparison of the first data and the second data; (d) comparison (44) of the first level of accuracy to a second level of accuracy of location of said vehicle along said path obtained from a satellite visibility map associated with said path, said satellite visibility map comprising data representative of the visibility of said set of satellites (111 to 114) from said path; (e) determination (45) of a first representative reliability information of the second level of accuracy based on a result of the comparison of the first level of accuracy to the second level of accuracy.

2. A method according to claim 1, wherein, when said result indicates a difference between the first level of accuracy and the second level of accuracy less than a threshold, said first information is representative of the reliability of the second level of accuracy and said first information is recorded and associated with said path.

3. A method according to claim 2, wherein, when said result indicates a difference between the first level of accuracy and the second level of accuracy above said threshold, said method further comprises a step of verifying a association of a second piece of information to said path, said second piece of information being representative of a difference between the first level of precision and the second level of precision higher than said threshold, said second piece of information being prior to said first piece of information, said first piece of information being further determined according to a result of said verification.

4. A method according to claim 3, wherein, when the result of said verification indicates the presence of an association of said second information with said path, said first information is representative of said difference between the first level of accuracy and the second level of accuracy and said first information is recorded and associated with said path, said method further comprising a step of determining a set of causes resulting in the difference between the first level of accuracy and the second level of accuracy by analyzing an area including said path, taking said first information as a reference for said analysis.

5. A method according to claim 3, wherein, when the result of said verification indicates an absence of association of said second information with said path, said method comprises a repetition of steps a) to e) to confirm said first information.

6. A method according to any one of claims 1 to 5, wherein said first information is transmitted to a remote device (110) via a wireless connection.

7. A method according to any one of claims 1 to 6, wherein said at least one sensor belongs to a set of sensors comprising: - an inertial sensor; - a radar; - a lidar; and - a camera.

8. Computer program comprising instructions for carrying out the method according to any one of claims 1 to 7, when such instructions are executed by at least one processor.

9. Device (3) for verifying the reliability of vehicle location information obtained from a satellite geolocation system, said device comprising a memory (31) associated with at least one processor (30) configured for carrying out the steps of the method according to any one of claims 1 to 7.

10. Vehicle (11) comprising the device (3) according to claim 9.

Images