DEVICE AND METHOD FOR LOCATING A VEHICLE

Abstract

The invention relates to a location device suitable for installation in a vehicle, the location device comprising a sensor (11) and an electronic processing unit programmed to: - match data (DT1) representative of a road environment of the vehicle, obtained by means of said sensor, with data (D1) relating to the positioning of at least one remarkable element located in this road environment, pre-recorded in a storage unit (13) of the electronic processing unit, - determine a reliability level (NF1) of this remarkable element as a function of the result of said matching, and to - determine a position (POSV) of the vehicle using the result of said matching only if the reliability level (NF1) of the corresponding remarkable element is greater than a given reliability threshold (SF1). The invention also relates to an associated location method.

Description

- figures 3A and 3B each schematically represent an image, respectively of a first type of remarkable element and of a second type of remarkable element likely to be located in the road environment of the vehicle, - figure 4 schematically represents a localization method implemented in the localization device of figure 1, and - Figure 5 schematically represents a previous position of the vehicle of Figure 1, as well as a plurality of potential positions that the vehicle could occupy. Figure 1 schematically represents a vehicle 1, here a motor vehicle such as a car, a truck, or even a bus, located on a traffic lane 3. The vehicle 1 can be a vehicle whose movements are manually controlled by a driver, or an autonomous vehicle. The vehicle 1 comprises a location device 10 which comprises a sensor 11, making it possible to capture data relating to a road environment 2 of the vehicle 1, in particular data relating to the positions of elements of this environment relative to the vehicle 1. The sensor 11 can be produced by means, in particular: - an image sensor, such as a front, rear or side camera, - a radar, - an ultrasonic detector, - or a lidar (according to the Anglo-Saxon acronym for “Light Detection and Ranging”), such as a laser rangefinder (or laser scanner). The road environment 2 of the vehicle designates all objects, terrain, roads, reliefs, plants, and constructions located near the vehicle 1, as well as those possibly distant from the vehicle 1 but visible or at least detectable from it, such as for example a particularly tall distant building. The sensor 11 is more precisely adapted to capture data representative of a portion of the vehicle's road environment located within a detection field of the sensor. In the embodiment described below, the sensor 11 is produced by means of an image sensor, in this case a video camera. The detection field of the sensor 11 corresponds in this case to the field of vision CH of the image sensor. The image sensor 11 is adapted here to be arranged in the vehicle 1 so that its field of vision CH includes a part of the road environment 2 located in front of the vehicle 1. Optionally, the localization device may comprise one or more additional sensors as described above. Thus, the localization device may for example comprise the aforementioned image sensor 11 as well as a lidar. The location device 10 also comprises an electronic processing unit 12 comprising in particular a processor performing logical operations, for example a microprocessor, and a storage unit 13, produced for example by means of a hard disk or a rewritable non-volatile memory. The electronic processing unit 12 is connected to the sensor 11, and is adapted to receive the data captured by this sensor 11, or at least data representative of these. Map data, representative of a network of traffic lanes on which the vehicle 1 travels, are stored in the storage unit 13. This cartographic data includes in particular data relating to the positioning of remarkable elements, detectable by means of said sensor, located on this network of traffic lanes or near this network of traffic lanes. The expression “remarkable element” designates an element that can be identified and located effectively by means of the data captured by the sensor 11, such as for example a road sign element such as a traffic sign, a traffic light, in particular a traffic light, or a road marking line. Such a remarkable element can also correspond to a barrier or a parapet bordering a traffic lane, to a building facade, to an element of street furniture, or to a relief having a specific shape. Here, said cartographic data further comprises, for each of said remarkable elements, an indication of a category of elements remarkable to which this remarkable element belongs. Such a category corresponds, for example, to remarkable elements of the type "traffic light", or of the type "speed limit sign", or of the type "right turn sign". The storage unit further includes, for at least one of these categories of remarkable elements, here for each of them, descriptive data, representative of common characteristics specific to the remarkable elements belonging to this category. These descriptive data are representative of characteristics specific to this category, and common to the different remarkable elements that are part of it. They may be representative of a shape or texture common to these elements, or include a typical image of an element belonging to this category. Figures 3A and 3B show two such images: one, IM1, representative of a remarkable element of the “traffic light” type (Figure 3A), and the other, IM2, representative of a remarkable element of the “speed limit indication sign” type. Such descriptive data may also include data representative of the positioning, relative to each other, of characteristic points, such as angular points, or points exhibiting high brightness or contrast, of a remarkable element typical of this category. Figure 2 schematically represents, for an example of road configuration, an IMG image of the road environment 2 of the vehicle 1 captured by the image sensor. Several notable features located in this road environment are visible in this IMG image, in particular a traffic light ER1, a road sign ER2, a road marking line ER3, and a building facade ER4. According to a particularly remarkable characteristic of the location device 10, the processing unit 12 is programmed to execute the following steps of the location method shown schematically in FIG. 4: E1) for at least one of said remarkable elements ER1, ..., ERi, ..., ERN located in the road environment 2 of vehicle 1: - matching (operations MC1, MCi, MCN of figure 4) the data relating to the positioning of this remarkable element ER1, ERi, ERN, provided by the storage unit 13, with data representative of the road environment 2 of the vehicle 1 obtained by means of said sensor 11, and - determine a reliability level NF1, ..., NFi, ..., NFN of this remarkable element ER1, ERi, ..., ERN, based on the result of said matching, and for E2) determining a POSV position of the vehicle 1 using the result of said matching only if said reliability level NF1, ..., NFi, ..., NFN is greater than a given reliability threshold SF1, SFi, ..., SFN. By means of this arrangement, the POSV position of the vehicle 1 is determined based on the one or those remarkable elements which actually make it possible to carry out such a matching in a reliable and precise manner. So, one of the remarkable elements: - for which the data stored in the storage unit of the location device is not reliable, for example because that item has been moved, or - for which the captured data does not allow reliable matching, for example because this element is partially hidden, is not taken into account in determining the vehicle's position. The accuracy and reliability with which the vehicle's POSV position is determined are then advantageously improved. It will be noted that the data relating to the positioning of the aforementioned remarkable elements ER1, ..., ERi, ..., ERN are present in the storage unit 13 before the execution of steps E1) and E2), for example because they were recorded there before the locating device 10 was put into service. Here, the processing unit 12 is programmed more precisely to, in step E1), carry out said matching, and determine the associated reliability level NF1, ..., NFi, ..., NFN, for each of the remarkable elements ER1ERi, ..., ERN located in the road environment 2 of vehicle 1. The number of remarkable elements ER1, ..., ERi, ..., ERN which are located in the road environment 2 of the vehicle 1 and which are included in the detection field of the sensor, is noted N. These remarkable elements are referenced here by the index i, between 1 and N. The localization method, the main steps of which are shown in Figure 4, comprises the steps E1) and E2) mentioned above. This method is implemented in the localization device 10 described above. Steps E1) and E2) are now described in more detail. Step E1) In the embodiment of the localization method described here, step E1) comprises a processing step E10) of data captured DCAPT by the sensor 11, prior to the matching E11) itself, as is shown schematically in FIG. 4. The E10) processing step of the captured DCAPT data includes: - a detection of the remarkable elements present in the detection field of the sensor 11, comprising an identification of the category to which each of the remarkable elements detected belongs, and - a determination, for each remarkable element ER1, ..., ERi, ..., ERN detected, of processed data DT1, ..., DTi, ..., DTN concisely representing this remarkable element. It is recalled that the detection field of the sensor corresponds here to the field of vision CH of the image sensor 11, and that the captured data DCAPT are representative of an image of the road environment 2 of the vehicle captured by the latter. The remarkable elements mentioned above are detected by analyzing this image, using a shape recognition algorithm, for example. The processed data DT1, ..., DTi, ..., DTN representing one of these remarkable elements may include in particular: - a position of the remarkable element, in the captured image, - a position of the remarkable element relative to the vehicle, deduced from the captured image, - positions of characteristic points of this remarkable element (angular point, very bright and / or contrasted point, point presenting particular properties with respect to a change in image scale), - a part of the captured image (i.e. a sub-image), in which this remarkable element is visible. When the location device comprises several sensors (for example several cameras), it may be provided, during the processing step E10), to - process the data captured by each of these sensors, then - determine the said processed data DT1, ..., DTi, ..., DTN by merging the results obtained during the processing of the data coming respectively from the different sensors. The data provided by the storage unit 13 of the location device 10 here includes, for each remarkable element ER1, ..., ERi, ..., ERN located in the road environment 2 of the vehicle 1, reference data D1, ..., Di, ..., DN relating to this remarkable element. The reference data D1, ..., Di, ..., DN relating to one of these remarkable elements include: - data relating to the positioning of this remarkable element, and, here, - the descriptive data (which have been described previously), corresponding to the category to which this remarkable element belongs (for example a characteristic image of a traffic light, if the remarkable element is a traffic light). During the following step E11), for each remarkable element ER1, ..., ERi, ..., ERN located in the road environment 2 of the vehicle 1, the reference data D1, ..., Di, ..., DN relating to this element are matched MC1, ..., MCi, ..., MCN, individually, with the processed data DT1, ..., DTi, ..., DTN corresponding to this element. As previously indicated, during the matching step E11), a reliability level NF1, ..., NFi, ..., NFN is determined for each of the remarkable elements. This level of reliability is determined here by testing to what extent the reference data D1, ..., Di, ..., DN relating to this remarkable element allow the captured data to be accounted for. This test can be performed using a known statistical test method of comparison or goodness-of-fit between the captured data and the reference data. The reliability level is determined more precisely, here, by testing to what extent the data relating to the positioning of this remarkable element (included in the said reference data D1, ..., DI, ..., DN) allow, taking into account a previous POSP position of vehicle 1 (figure 5) and a vehicle movement model, to account for the captured DCAPT data. The method therefore comprises determining a plurality of potential positions POS1, ..., POSj, ... POSM, which the vehicle 1 could occupy (figure 5). These potential positions POS1, ..., POSj, ... POSM are distributed around an average potential position <posj>which is determined based on the previous position POSP of vehicle 1 and the velocity vector of vehicle 1. The average potential position <posj>of the vehicle is determined in accordance with the vehicle's movement model, for example by integrating over time, from an instant corresponding to the previous position POSP, to a later instant corresponding to this average position <posj>, the vehicle's speed vector. The vehicle's movement model may correspond, for example, to a kinematic movement model in which the vehicle is simplified to a two-wheeled vehicle, generally called the "bicycle model", or to a kinematic movement model taking into account the geometry of the vehicle's front axle, such as the kinematic model known as the "Ackermann model". The number of potential positions POS1, ..., POSj, ... POSM thus determined is noted M. These potential positions are referenced here by the index j, between 1 and M. For each of the remarkable elements ER1, ..., ERi, ..., ERN, the associated matching operation MC1, ..., MCi, ..., MCN is then carried out by means of the following steps, executed for each of said potential positions POS1, ..., POSj, ... POSM: (a) determination, based on said potential position and data relating to the positioning of the remarkable element stored in the storage unit 13, of expected data, representative of a position that said remarkable element would occupy in relation to the vehicle if the vehicle were positioned at this potential position POS1, ..., POSj, ... POSM, b) comparing said expected data with said DCAPT captured data, and c) determination, for said remarkable element ER1, ..., ERi, ... ERN, of a likelihood level NVij associated with this potential position POS1, ..., POSj, ... POSM of the vehicle, based on the result of said comparison. The likelihood level bearing the reference NVij is that associated with the potential position POSj, and is determined by comparing, for the remarkable element ERi, the captured data with the data pre-recorded in the storage unit 13. The expected data determined during step a) may, as here, include expected perceptual data, of the same type as the processed data DT1, ..., DTi, ... DTN relating to this remarkable element. These expected perceptual data correspond to an estimate of the processed data that would be obtained if the vehicle were positioned at this potential position POS1, ..., POSj, ... POSM. During step b), the expected data determined in step a) are more particularly compared, here, with the processed data DT1, ..., DTi,... ,DTN relating to the remarkable element considered. When the processed data DT1, ..., DTi,... ,DTN include the positions of characteristic points of the remarkable element, this comparison is for example carried out by: - calculating, for each characteristic point, a difference between the position of this point as indicated by the processed data, and the expected position of this point, as indicated by the expected data mentioned above, then in - summing the differences thus determined to obtain an overall difference between predictions and observation, for this remarkable element. The comparison made in step b) can also be made, more simply, by calculating a difference between: - on the one hand, the position that the remarkable element considered would occupy, relative to the vehicle, if the vehicle was positioned at one of the potential positions, determined on the basis of the data relating to the positioning of this remarkable element stored in the storage unit 13 of the device, and, - on the other hand, a position of this remarkable element in relation to the vehicle, deduced from the captured data. Here, in step c), the likelihood level NVij, associated respectively with each of the potential positions of the vehicle, is determined so as to be all the greater as the aforementioned overall deviation is small. In other words, the likelihood level is all the greater as the expected data, determined for this potential position, are close to the processed data from the captured data. As an example, the likelihood level NVij may for example be inversely proportional to the overall deviation between data, mentioned above. In the embodiment of the localization method described here, the reliability level NFi associated with the remarkable element ERi is determined as a function of the likelihood levels NVi1, ..., NVij, ..., NViM, associated respectively with the potential positions POS1, ..., POSi ..., POSM of the vehicle, and which were determined during the matching MCi based on this remarkable element ERi. This reliability level NFi is determined more precisely, here, by summing the likelihood levels determined for this remarkable element ERj, for all the potential positions POS1, ..., POSi ..., POSM of the vehicle, in accordance with the following formula F1: NFi = SjZÎ1 NVij (Fl). Alternatively, this reliability level NFi could for example be equal to the likelihood level NFij, which, among the likelihood levels determined for this remarkable element ERi, is the largest. Step E2) In step E2), the processing unit 12 tests here, for each of the remarkable elements ER1, ..., ERi, ..., ERN having been the subject of a matching, whether the reliability level NF1, ..., NFi, ..., NFN of this remarkable element is greater than the reliability threshold SF1, ..., SFi, ..., SFN. When the reliability level NF1, NFi, NFN of this remarkable element is higher than the corresponding reliability threshold SF1, SFi, SFN, this remarkable element is considered reliable. Otherwise, it is considered unreliable. Among the N remarkable elements that have been matched, a number N' (less than or equal to N) of reliable remarkable elements, ERF1, ... ERFi', ... ERFN' are thus selected. These reliable remarkable elements are referenced here by the index i', between 1 and N'. Here, the value of the reliability threshold to be used is determined directly by the category to which the remarkable element which is the subject of this reliability test belongs. Thus, if the remarkable element is a first traffic light in the vehicle's road environment, or a second traffic light in this environment, the reliability threshold value used for this element will be that associated with the category of remarkable elements "traffic light". The value of the reliability threshold to be used for a given category of remarkable elements can for example be determined during preliminary tests before putting the location device 10 into service, by comparing the reliability levels obtained in road situations for which it is proven that a remarkable element of this category is reliable, and those obtained in other configurations for which the remarkable elements of this category are clearly unreliable. The value of the reliability threshold to be used for a given category of remarkable elements can also be determined according to values ​​usually recommended for a statistical test of adequacy (such as the reliability test carried out here), for example those recommended for the so-called "chi-square" test of adequacy (also called "chi-square", or x2)- In alternative embodiments (not shown), instead of testing the reliability of said remarkable elements by considering them individually, in isolation from each other (as described above), their reliability could be tested by instead considering all of the remarkable elements of the same category, located in the road environment of the vehicle. For example, in this case, we can provide for each of the categories, of which at least one remarkable element is located in the road environment of the vehicle, to determine whether this category is reliable or not reliable, based on the reliability levels of the remarkable elements belonging to this category. The processing unit may, for example, be programmed to determine that such a category is reliable provided that the reliability level of each of its elements is greater than the reliability threshold associated with this category. Alternatively, the processing unit could also be programmed to determine that such a category is reliable, provided that an average of the reliability levels of its notable elements is greater than the reliability threshold associated with that category. In the embodiment mentioned above, for which the reliability levels are determined directly category by category, and not element by element, a category is considered reliable if its reliability level is higher than the corresponding reliability threshold. Under these alternative embodiments, a remarkable element is ultimately considered reliable when it belongs to a reliable category of remarkable elements. Whatever the embodiment considered, the POSV position of the vehicle 1 is then determined, based on the results of the matching carried out for the reliable remarkable elements ERF1, ... ERFi', ... ERFN'. To do this, the processing unit 12 first determines here, for each potential position POSj, an overall level of likelihood NGVj, as a function of the levels of likelihood NVi'j associated with this potential position POSj, and which were obtained for each of the reliable remarkable elements ERFi'. The overall likelihood level NGVj of the potential position POSj is for example determined in accordance with the formula F2 below, that is to say by summing, for all the reliable remarkable elements, the likelihood levels NVi'j associated with this potential position POSj: NGVj = ZSi'NVi'j (F2) . The processing unit 12 then determines the position POSV of the vehicle 1 as a function of the potential positions POS1, ..., POSj, ...., POSM of the latter and of the corresponding overall likelihood levels NGV1, ..., NGVj, ... NGVM. The POSV position of the vehicle 1 is determined more particularly by calculating a weighted average of said potential positions POS1, POSj, POSM, each assigned a weighting coefficient which is determined according to the overall level of likelihood NGV1, NGVj, ... NGVM of this potential position. The weighting coefficients associated respectively with each of the potential positions of the vehicle may in particular each be equal to the overall level of likelihood of this potential position. In this case, the position of the vehicle is determined in accordance with the following formula F3: POSV = POSj x NGVj] / [Xff NGVj] (F3). Alternatively, instead of being determined by a weighted average calculation, the vehicle's POSV position could, for example, be determined as being equal to that of said potential positions POS1, ..., POSj, ..., POSM which (among these potential positions) has the greatest overall level of likelihood. Optionally, a final reliability level, associated with the POSV position of the vehicle 1 thus determined, is calculated in step E2), based on the reliability levels of the remarkable elements present in the road environment 2 of the vehicle 1. The final NFPOS reliability level is for example equal to the sum of the reliability levels of the reliable remarkable elements: NFPOS = SËi'NFi' (F4) . According to another optional characteristic, step E2) may comprise the calculation of a determination uncertainty, linked to the precision with which the POSV position of the vehicle 1 is obtained. This determination uncertainty may for example be equal to the standard deviation of all the potential positions of the vehicle, each assigned a weighting coefficient equal for example to the overall level of likelihood of this potential position. According to a particularly remarkable optional characteristic, the localization method can, as here, comprise a determination of an orientation of the vehicle 1 relative to its road environment 2, in addition to the determination of its POSV position described above. The data captured by DCAPT sensor 11 is indeed sensitive to the orientation of vehicle 1. Here, for example, the position of a remarkable element in the image captured by the image sensor clearly depends on the orientation of vehicle 1 relative to its road environment 2. This dependence of the captured DCAPT data with the orientation of vehicle 1 allows a determination of this orientation. For this, it is possible, for example, to determine, in step E1), not only the potential positions of the vehicle 1, but also the potential orientations OR 1, ...ORk, ..., ORP of the latter. Similar to what was described above, a likelihood level NVijk is then calculated for each pair formed by one of the POSj positions and one of the potential ORk orientations, when matching based on the remarkable element ERi. The reliability level of the remarkable element ERi can then be determined based on these likelihood levels, for example by summing these likelihood levels for all potential positions and orientations of the vehicle. The optional features of step E2) relating to the determination of the POSV position of the vehicle, which have been described above, can then also be applied to the determination of its orientation. In other embodiments, the reliability levels of the remarkable elements located in the road environment 2 of the vehicle 1 could be determined differently from what has been described above. For example, in an alternative embodiment, it can be provided that the matching of the captured DCAPT data, with the reference data provided by the storage unit 13, is carried out by calculating the values ​​of the correlation function of the captured image, with an image representative of the remarkable element concerned, provided by the storage unit 13. The reliability level of this remarkable element can then be equal, for example, to the maximum value of this correlation function, while the offset between images, for which this correlation function is maximum, provides information on the position of the vehicle.< / posj> < / posj> < / posj>

Claims

CLAIMS 1. A location device (10) adapted to be installed in a vehicle (1), the location device comprising: -a sensor(11), and - an electronic processing unit (12) comprising a storage unit (13) in which data relating to the positioning of remarkable elements located on, or near a network of traffic lanes are stored, the processing unit (12) being programmed to: El) for at least one of said remarkable elements (ERI, ERI, ERN) located in a road environment (2) of the vehicle (1): - matching (MCI, .... MCi, .... MON) the data relating to the positioning of this remarkable element (ER1, ERi, ERN), provided by the storage unit (13), with data representative of the road environment (2) of the vehicle (1) obtained by means of said sensor (11), and - determine a reliability level (NF1, NFÎ, .... NFN) of this remarkable element (ERI, ERi, ERN), based on the result of said matching, and for E2) determining a position (POSV) of the vehicle (1) using the result of said matching only if said reliability level (NF1,...» NFi,NFN) is greater than a given reliability threshold (SF1, .... SFi, .... SFN), the storage unit (13) containing: - for each of the said remarkable elements (ER1, ERi.....ERN), an indication of a category of remarkable elements to which this remarkable element belongs, and " for at least one of the categories of remarkable elements, descriptive data, representative of common characteristics specific to the remarkable elements belonging to this category the processing unit (12) being programmed to, in step E1), carry out said matching as a function, in addition, of the descriptive data associated with the category to which the said remarkable element matched belongs characterized in that the processing unit (12) is further programmed for, the matching of step E1) having been carried out for several of said remarkable elements located in the road environment of the vehicle: - determine that the category to which at least one of the said remarkable elements matched belongs is reliable, based at least on the level of reliability of this remarkable element, and for - determine the position of the vehicle using, for each of said matches, the corresponding result, only if the associated remarkable element belongs to one of the reliable categories of remarkable elements, 2. Location device (10) according to claim 1. wherein the processing unit (12) is programmed to determine the reliability level (NF1, NFi, .... NFN) of the matched remarkable element (ER1, ERi, .... ERN) by testing to what extent the data relating to the positioning of this remarkable element, stored in the storage unit (13) of the location device, make it possible to account for the data representative of the road environment (2) of the vehicle (1), obtained by means of said sensor (11).

3. Location device (10) according to claim 2, in which the processing unit (12) is programmed to test to what extent the data, relating to the positioning of the remarkable element (ER1, ERi, ...» ERN) provided in correspondence, make it possible to account for said data representative of the road environment (2) of the vehicle (1), taking into account a previous position (POSP) of the vehicle (1) and a movement model of the vehicle (1).

4. A locating device (10) according to claim 3, wherein the processing unit (12) is programmed to: - determine a plurality of potential positions (POS1, ,,,, POSj, POSM) that the vehicle could occupy (1), distributed around an average potential position ( <posj>). this average potential position ( <posj>) being determined as a function of the previous position (POSP) of the vehicle (1) and a vehicle movement speed (1 ), and for - carrying out the matching of said data representative of the road environment (2) of the vehicle (1), with the data relating to the positioning of said remarkable element (ER1, ERi, .... ERN), on the basis of said potential positions that the vehicle (1) could occupy.

5. Location device (10) according to claim 4, wherein the processing unit (12) is programmed to carry out said matching, by means of the following steps, executed for each of said potential positions (POS1, POSj, .... POSM): - determine, as a function of this potential position (POSj) and the data relating to the positioning of the matched remarkable element (ERi), ​​stored in the storage unit (13), an expected data item representative of a position that said remarkable element (ERi) would occupy relative to the vehicle (1) if the vehicle (1) were positioned at this potential position (POSj), ~ compare said expected data with said data representative of the road environment (2) of the vehicle (1), and - determine, for said remarkable element (ERi), ​​a level of likelihood (NV^) associated with this potential position (POSj) of the vehicle (1), based on the result of said comparison.

6. Focusing device (10) according to claim 5, wherein the processing unit (12) is programmed to determine the reliability level (NFi) of said remarkable element (ERI, .... ERi, ERN) matched as a function of the likelihood levels (NV^, NVip .... NVim) associated respectively with the potential positions (POS1, POSj, POSM) of the vehicle, and which have been determined for this remarkable element (ERi).

7. Location device (10) according to one of claims 5 and 6, in which the processing unit (12) is programmed to, in step E2), determining the position (POSV) of the vehicle (1) as a function of said potential positions (POS1, POSj, POSM), and, for each of said potential positions, using the corresponding likelihood level (NVn, ■■■, NV?, .... NVnm) only if the reliability level of the remarkable element, for which the likelihood level of this potential position was determined, is greater than said reliability threshold, 8. Location device (10) according to claim 7, in which the processing unit (12) is programmed for, the matching of step E1) having been carried out for several of said remarkable elements located in the road environment of the vehicle: - determine, for each of said potential positions (POS1, ..... POSj, .... POSM), a global level of likelihood (NGVj) equal to the sum of all the levels of likelihood (NVti, NVq, .... NVmi) associated with this potential position (POSj), and which were obtained respectively for each of the remarkable elements (ERF1, .... ERFi', .... ERFN') whose level of reliability is higher than the corresponding reliability threshold, and for - determine the position (POSV) of the vehicle (1) as a function of the global likelihood levels (NGVj) respectively associated with each of said potential positions (POS1,POSj, POSM).

9. Location device (10) according to claim 8, wherein the processing unit (12) is programmed to determine that the position (POSV) of the vehicle (1) is equal to that of said potential positions (POS1, POSj, POSM) which, among said potential positions, has the greatest overall level of likelihood (NGV1tNGVj,..., NGV«).

10. Location device (10) according to claim 8. wherein the processing unit (12) is programmed to determine that the position (POSV) of the vehicle (1) is equal to a weighted average of said potential positions (POS1, .... POSj, ..., POSM) each assigned a weighting coefficient which is determined as a function of the overall level of likelihood (NGVj) of this potential position (POSj).

11. Location device (10) according to one of claims 1 to 10, in which the processing unit (12) is further programmed to, in step E2), determine an orientation of the vehicle (1) as a function of said matching.< / posj> < / posj>

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