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

Abstract

The present invention relates to a method and device for verifying the reliability of vehicle location information (11) obtained from a satellite geolocation system. To this end, first vehicle location data (11) from signals received from satellites (111 to 114) and second vehicle location data (11) from data received from sensors onboard the vehicle (11) are determined. A first level of vehicle location accuracy is determined by comparing the first and second data. This first level of accuracy is compared to a second level of location accuracy obtained from a satellite visibility map. 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. (See Figure 1 for abbreviations.)

Description

Title of the invention: Method and device for verifying the reliability of vehicle location information obtained from a GNSS system. Technical field

[0001] 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

[0002] With the development of automated vehicles (from the English "Automated Vehicle"), also called autonomous vehicles, needs in terms of route planning and tracking, particularly depending on the environment around the automated vehicle, have emerged.

[0003] Controlling the trajectory of an automated vehicle, by means of one or more driver assistance systems, called ADAS system(s) (from the English "Advanced Driver-Assistance System" or in French "Système d'aide à la conduite avancé"), 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.

[0004] The location of an automated vehicle is obtained as for any vehicle by the use of a receiver of a geolocation system based on a satellite positioning system designated by the acronym GNSS (from the English "Global Navigation Satellite System" or in French "Système de navigation globale par satellite"), for example a GPS system from the English "Global Positioning System" or in French "Système de emplacement global"), Galileo or Glonass.

[0005] In certain environments, such as urban areas with buildings, mountainous areas, or densely wooded areas, the reception of signals emitted by satellites can be disrupted, with signal occlusion and reflection resulting in multiple paths for the emitted signals. This leads to inaccuracies in the GNSS receiver's position assessment. A lack of precise location of the automated vehicle in a hazardous area of ​​the environment in which the automated vehicle is operating creates risks regarding the control of the vehicle's movement. automated to reach or cross this hazardous area safely, without leaving the traffic lanes or hitting any obstacles. Summary of the present invention

[0006] One object of the present invention is to solve at least one of the problems of the technological background described above.

[0007] Another object of the present invention is to improve the safety of a vehicle, for example an automated vehicle, travelling in a road environment.

[0008] 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 initial 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 data and the 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 precision based on a result of the comparison of the first level of precision to the second level of precision.

[0009] Using two different sources to obtain the vehicle's location, namely a GNSS system and one or more sensors onboard the vehicle, makes it possible 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 location, which can be compared with similar information obtained from a satellite visibility map. The result of the comparison makes it possible to verify whether the level of location accuracy expected from the satellite visibility map is reliable or not. Determining the reliability makes it possible to know whether a vehicle, in particular an automated vehicle, will be able to use the information on the level of location accuracy that can be obtained from the GNSS system associated with the satellite visibility map. which allows us to anticipate potential location problems and thus improve the safety of the vehicle and other road users.

[0010] 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.

[0011] 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.

[0012] 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 method 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.

[0013] 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 precision and the second level of precision and the first piece of information is recorded and associated with the path, the method further comprising a step of determining a set of causes leading to the difference between the first level of precision and the second level of precision by analyzing an area including the path taking the first piece of information as a reference for the analysis.

[0014] According to a further 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.

[0015] According to yet another variant, the first piece of information is transmitted to a remote device via a wireless connection.

[0016] 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.

[0017] According to a second aspect, the present invention relates to a device for verifying the reliability of vehicle location information obtained of a satellite geolocation system, the device comprising a memory associated with a processor configured for the implementation of the steps of the process according to the first aspect of the present invention.

[0018] 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.

[0019] 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.

[0020] 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.

[0021] Such a computer program may use any programming language, and be in the form of source code, object code, or an intermediate code between source code and object code, such as in a partially compiled form, or in any other desirable form.

[0022] 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.

[0023] 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 disk drive.

[0024] 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 an Internet-type network.

[0025] 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

[0026] Other features and advantages of the present invention will become apparent from the description of the particular and non-limiting embodiments of the present invention below, with reference to the attached Figures 1 to 4, in which:

[0027] [Fig.1] schematically illustrates an environment including a vehicle, according to a particular embodiment of the present invention;

[0028] [Fig.2] illustrates a flowchart of the different operations of a process of Verification of the reliability of vehicle location information from [Fig. 1] obtained from a satellite geolocation system, according to a particular and non-limiting embodiment of the present invention

[0029] [Fig.3] illustrates a device configured for the reliability verification of a location information of a vehicle of [Fig.1] obtained from a satellite geolocation system, according to a particular and non-limiting embodiment of the present invention.

[0030] [Fig.4] illustrates a flowchart of the different stages of a verification process reliability of a vehicle location information of the [Fig.1] obtained from a satellite geolocation system, according to a particular and non-limiting embodiment of the present invention. Description of examples of achievements

[0031] 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 following description.

[0032] The terms "first," "second" (or "firsts," "seconds"), etc., are used in this document by arbitrary convention to allow for the identification and distinction of 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.

[0033] 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 to say, 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.

[0034] To this end, initial representative location data for the vehicle along a path traveled by the vehicle are determined from received signals The vehicle's location is determined from a set of satellites belonging to the GNSS geolocation system, via a receiver of such a system installed in the vehicle. Secondary data points representing the vehicle's location along the route are determined from data received from at least one sensor onboard the vehicle, such as sensors from the vehicle's inertial measurement unit (IMU), one or more vehicle cameras, or the vehicle's radar and / or lidar. The first and second data points are compared to determine a first level of accuracy for the vehicle's location along the route. This first level of accuracy is then compared to a second level of accuracy for the vehicle's location along the route, obtained, determined, or deduced from a satellite visibility map of the GNSS system's satellites, particularly from the route itself.Comparing the first level of accuracy to the second level of accuracy allows us to determine initial information representative of the reliability of the second level of accuracy, and therefore representative of the reliability level of the satellite visibility map associated with the path.

[0035] Fig. 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.

[0036] The road environment 1 corresponds to any environment in which the automated vehicle 10 is likely to travel. The road environment 1 corresponds, for example, to an urban environment, a mixed environment comprising an urban part and an extra-urban part, a non-city environment, etc.

[0037] 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 route or path determined 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 specific characteristics, for example, one or more buildings with a height exceeding a threshold (e.g., 5 or 10 m) and / or a width exceeding a threshold (e.g., 10, 20 or 50 m) and / or containing materials that disrupt satellite signal reception; such a building is likely to obstruct satellite signal reception and / or generate multiple satellite signal reception paths.

[0038] An automated vehicle corresponds to a vehicle equipped with a sophisticated driver assistance system ensuring control of the vehicle, which is capable of driving in its road environment without intervention from a driver or under the control of a No one intervenes in the operation of the automated vehicle, except in an emergency, for example. A vehicle enabling such autonomous driving must have a level of autonomous driving higher than a certain level out of a total number of levels. For example, the automated vehicle has 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 an autonomy level of 3 or higher out of the 5 or 6 levels defined in the two classifications mentioned above.

[0039] The automated vehicle 10 corresponds for example to a vehicle with a thermal engine, an electric vehicle or a hybrid vehicle (combining a thermal engine and an electric motor).

[0040] According to 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. According to another embodiment, the autonomous shuttle is shared by several users in an on-demand service mode, for example, that is, the autonomous shuttle picks up each passenger at a predetermined location via a mobile application or a website managed by the autonomous shuttle operator and drops them off at the destination desired by each passenger.

[0041] According to another embodiment, 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.

[0042] The automated vehicle 10 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.

[0043] 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, referred to as a TCU (Telematic Control Unit), 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 implementing different useful services for the proper functioning of the automated vehicle 10. The computer(s) and the TCU unit communicate and exchange data with each other via one or more computer buses, for example a CAN data bus (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 (according to the ISO 17458 standard) or Ethernet (according to the ISO / IEC 802-3 standard).

[0044] 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”).

[0045] Each communication device 101 is advantageously connected to one or more remote servers 110 or to the "cloud" 100 (or in French "nuage") 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.

[0046] The automated vehicle 10 communicates, for example, using a so-called V2X communication system, for example based on the 3GPP LTE-V or IEEE 802.1 lp 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.

[0047] The automated vehicle 10 further 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 satellites 111 to 114 of the GNSS system. The data representing the geographic position take, 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 frame of reference for each vehicle, namely the world frame of reference.

[0048] A reliability verification process for 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.

[0049] An example of implementation is described opposite [Fig.2] below.

[0050] Vehicle 11 corresponds to an automated or non-automated vehicle, that is to say a vehicle whose driving is controlled by an AD AS system in an automated manner or by a driver in a manual manner.

[0051] The vehicle 11 carries initial means for determining its position / location from signals received from the set of satellites 111 to 114 of the GNSS system. These initial means correspond to a GNSS system receiver identical or similar to that carried in the automated vehicle 10.

[0052] The vehicle 11 also carries second means for determining its position / location from data received from one or more sensors on board the vehicle 11. This sensor or these sensors correspond to one or more of the following sensors, according to all possible combinations: - one or more inertial sensors from an inertial navigation system 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 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, in order to detect obstacles and their distances from vehicle 11; and / or - one or more LIDAR(s) (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).

[0053] Data received from sensors such as one or more cameras makes it possible to identify elements of the road environment 1 in which the vehicle 11 is traveling, by implementing one or more image processing methods. The identification of particular elements (buildings, intersections, monuments, etc.) of which Knowing the location (for example, contained in mapping data to which the vehicle has access, such data being stored in the vehicle's memory or received from a server via a wireless connection) allows the vehicle to determine its location relative to these particular elements, based on information such as the distance to them. The distance to these particular elements is obtained, for example, via an image processing method or via data received from LiDAR or radar.

[0054] The vehicle 11 further comprises one or more wireless communication systems or interfaces identical or similar to those of the automated vehicle 10, the vehicle 11 corresponding to a connected vehicle.

[0055] Figure 2 schematically illustrates a reliability verification process for a 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 embodiments of the present invention.

[0056] 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.

[0057] 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.

[0058] 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.

[0059] 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 - when a problem is 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.

[0060] A satellite visibility map associated with a given territory, for example the road environment 1, includes data representative of the visibility of each satellite in the set of satellites 111 to 114 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.

[0061] The representative visibility data of the satellite set 111 to 114 includes representative visibility information of each satellite of the satellite set 111 to 114 of the GNSS system, from a set of points in the road environment 1 (or more precisely of a path or part of a path followed by the automated vehicle following a determined route).

[0062] The satellite visibility map is for example generated by the remote device 110 as a function of 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.

[0063] A satellite visibility map is, for example, associated with a specific time instant. Indeed, since 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.

[0064] The representative visibility data for the set of satellites 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 instants belonging to a given time range. According to one embodiment, 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 road segments at different time instants, according to the needs of the automated vehicle 10 or vehicle 11, for example.

[0065] The satellite visibility map is generated according to any method known to a person skilled in the art, for example as described in the document entitled "Study for the production of GNSS satellite visibility maps", by Guillaume Bizouard, published in the XYZ magazine, No. 111 in the 2nd quarter of 2007.

[0066] The described method involves extrapolating the orbital / Keplerian parameters of the satellites to the desired forecast date or time, these calculations relating to celestial mechanics being 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 location on Earth, for example, for each point in a set of points in the road environment 1.

[0067] The point set includes, for example, reference points defining the road sections of the road environment 1 (including the path(s) followed by the automated vehicle 10 and the vehicle 11), the paths forming the road sections being discretized to obtain the point set.

[0068] 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 provides for the use of geodata describing the space associated with the road environment 1, whose defined area is 1000, this geodata being 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 corresponding, for example, to data from a digital surface model, known as a DSM, also called a digital terrain model.

[0069] 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.

[0070] 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.

[0071] According to one variant, the representative visibility data of the set of satellites 111 to 114 correspond to data indicating the number of satellites visible from each point of the set of points of the road environment 1, for example 1, 2, 3, 4, 5 or more satellites at a given time.

[0072] The quality or level of accuracy of the automated vehicle's localization 10 depends on the number of satellites visible from that location. To obtain a localization with a level of accuracy exceeding a certain threshold, it is necessary to obtain a signal emitted from four satellites within direct line of sight. Indeed, while three satellites are sufficient to obtain a position using the trilateration technique, a fourth satellite is necessary to precisely determine the offset of the onboard receiver. in 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.

[0073] The representative visibility data for the 111 to 114 satellite array are thus also representative of a level of location accuracy that a vehicle can obtain by determining its position / location from the received satellite signals. This level of vehicle location accuracy is hereafter referred to as the second level of vehicle location accuracy. The second level of position accuracy that can be determined in the road environment at a given time corresponds to an indicator (called the second indicator) taking, for example, a value from a defined set of values, for example, from a set comprising 3, 5, or 10 values, the accuracy obtained being, for example, higher the larger the value of the indicator.According to one variant, the second level of positional accuracy corresponds to an indicator with a value in centimeters, representing the achievable accuracy in centimeters.

[0074] The operations of the process 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.

[0075] In a second operation 21 of the process, the reliability of the second level of accuracy that can be obtained from the satellite visibility map is verified. Such a verification corresponds to a consistency check between the ground truth as determined by the vehicle 11 traveling along the path being verified and the data from the satellite visibility map.

[0076] To this end, the vehicle 11, i.e., the vehicle 11 control unit responsible for the process, determines initial representative location data for the vehicle 11 along the path traveled by the vehicle 11 from signals received from the satellite array 111 to 114 of the satellite geolocation system (GNSS system). The 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 satellite array, this location or these locations being determined by the receiver onboard the vehicle 11.

[0077] The location is determined for example every 10, 30 or 50 cm and / or every 100, 200 or 500 ms along the path followed by the vehicle 11.

[0078] 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.

[0079] 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.

[0080] This sensor or these sensors belong to a set of sensors comprising: - an inertial sensor; - a radar; - a lidar; and - a camera.

[0081] These second data are stored in a memory of the vehicle 11, for example temporarily in a buffer of the computer in charge of the process.

[0082] The first and second data are determined for the same point or points of 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).

[0083] A first level of accuracy in locating the vehicle 11 along the path is determined by comparing the first data and the second data, for example for each point for which the first and second data have been determined.

[0084] The result of comparing the first and second data points provides 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 location obtained from the GNSS system and the location obtained from the data received from the onboard sensor(s), and of the reliability of the location obtained from the GNSS system.

[0085] The first level of precision corresponds, for example, to the deviation, expressed in centimeters. According to 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.

[0086] 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).

[0087] For comparison, 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.

[0088] A first representative reliability information of the second level of precision is determined based on the result of the comparison of the first level of precision to the second level of precision.

[0089] 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 (for example 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.

[0090] Otherwise, when the comparison indicates that the difference between the first level of precision and the second level of precision is greater than the threshold, the process continues with a fifth operation 24.

[0091] 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 a verified reliability of the second level of accuracy, and such first information is stored in memory and associated with the path (or the point of the path considered).

[0092] This first piece of information is, for example, associated with each point for which first and second data have been verified, or with each segment of an elementary path (i.e., with each segment of a path of a determined distance, for example equal to 10, 20, or 50 cm). This first piece of information is, for example, recorded in a memory of the vehicle 11.

[0093] When the entire path has been traveled by the vehicle 11, the latter 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 that the information understood is reliable (or not, as described opposite operations 24 to 27).

[0094] 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 representative of 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.

[0095] 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.

[0096] 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.

[0097] According to the result 25 of the verification, the process continues with a sixth operation 26 or with a seventh operation 27.

[0098] The process continues with the sixth operation 26 when no second information has been previously associated with the path, that is to say when no difference between the first level of precision and the second level of precision has been previously raised or detected.

[0099] 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 to say when at least one difference between the first level of precision and the second level of precision has been previously retrieved or detected.

[0100] In the sixth operation 26 of the process, another run along the path in question is required to confirm the difference between the first level of accuracy and the second level of accuracy. This second run is, for example, carried out 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.

[0101] 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.

[0102] A request is generated, for example, to request an analysis of the environment around the path and determine the reasons for the observed difference (e.g., presence of an unlisted building, weather event disrupting the reception of satellite signals, etc.). The determination of a set of causes leading to the difference between the first level of accuracy and the second level of accuracy is obtained by analyzing an area including the path, taking the first piece of information as the reference for the analysis. Such a determination is obtained, for example, from data received from sensor(s) onboard the 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 piece of information as the reference information for 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.

[0103] According to one variant, the determination of the reasons for the difference is implemented subsequently 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.

[0104] The process ends with the eighth operation 28.

[0105] 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.

[0106] According to a particular embodiment, device 3 corresponds to a remote device such as remote device 110.

[0107] 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 [Fig. 4]. Examples of such a device 3 include, but are not limited to, embedded electronic equipment such as a vehicle 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, software (or computer) modules, or a combination of electronic circuits and software modules.

[0108] The device 3 comprises one (or more) processor(s) 30 configured to execute instructions for carrying out the steps of the process and / or for executing instructions from the software embedded in the device 3. The processor 30 may include integrated memory, an input / output interface, and various circuits known to those skilled in the art. The device 3 further comprises 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.

[0109] 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.

[0110] According to various particular and non-limiting embodiments, the 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.

[0111] According to a particular and non-limiting embodiment, the device 3 comprises a block 32 of interface elements for communicating with external devices. The interface elements of the block 32 comprise 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").

[0112] According to another particular and non-limiting embodiment, the device 3 includes a communication interface 33 which 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 wired network of the CAN (Controller Area Network), CAN FD (Controller Area Network Flexible Data-Rate), FlexRay (standardized by ISO 17458) or Ethernet (standardized by ISO / IEC 802-3) type.

[0113] 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. In one variant, one or more of the external devices is integrated into device 3.

[0114] 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 and non-limiting embodiment of the present invention. The method is, for example, implemented by a computer, for example by device 3 in Figure 3.

[0115] In a first step 41, initial representative vehicle location data along a path traveled by the vehicle are determined from signals received from a set of satellites of the geolocation system.

[0116] In a second step 42, second representative vehicle location data along the path are determined from data received from at least one sensor on board the vehicle.

[0117] In a third step 43, a first level of accuracy of vehicle location along the path is determined by comparison of the first data and the second data.

[0118] 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.

[0119] In a fifth step 45, a first representative reliability information of the second level of accuracy is determined based on a result of comparing the first level of accuracy with the second level of accuracy.

[0120] According to one variant, the variants and examples of the operations described in relation to [Fig.1] and / or [Fig.2] apply to the steps of the process in [Fig.4].

[0121] Of course, the present invention is not limited to the embodiments described above but extends to a method for determining the reliability of the 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 location information for a vehicle (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 for 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 for 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 for said vehicle (11) along said path by comparing the first and 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 an association of a second piece of information with said path, said second piece of information being representative of a difference between the first level of precision and the second level of precision above said threshold, said second information being prior to said first information, said first 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 leading to 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.

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