Analytical system for analysing a manual vehicle-parking manoeuvre

Abstract

The present invention relates to an analytical system (2) embedded in a vehicle (1), comprising: - a plurality of sensors (4), - a control module (5) configured to determine a reference path and an actual path of the vehicle (1) and / or a positional deviation of the vehicle (1) with respect to a surrounding obstacle and / or to a road marking demarcating a parking space, characterized in that the control module (5) is configured to compute an overall score (S) of a manual parking manoeuvre of the vehicle (1) depending on the determined paths of the vehicle (1) and / or on the determined positional deviation of the vehicle (1) with respect to the surrounding obstacle and / or the road marking, the analytical system (2) comprising a communication module (6) configured to transmit an assessment of said manoeuvre, the assessment being based on the overall score computed by the control module (5).

Description

Description Title of the invention: Analytical system for a manual parking maneuver of a vehicle

[0001] The present invention relates to the field of vehicles which can be equipped with a parking assistance device, and more particularly concerns an analytical system on board such vehicles.

[0002] It is known that some recent vehicles include a parking assistance device that parks the vehicle in place of the driver. To this end, such a vehicle is equipped with a plurality of sensors for analyzing the environment in order to determine a parking space located near the vehicle and within which it is suitable for parking. Once the parking space has been determined, an artificial intelligence, and / or an algorithm, integrated into the vehicle is able to take control of the vehicle, in particular the pedals, the steering wheel and the gear lever, in order to park the vehicle within the parking space in place of the driver.

[0003] The parking assistance system allows the driver to avoid having to perform the parking maneuver themselves, which can be tricky. In addition, algorithms ensure that the final position of the vehicle once parked is optimal in terms of distance from certain surrounding obstacles, such as a curb or other vehicles parked nearby.

[0004] However, it has been determined that this parking assistance device is very rarely used by people who own a vehicle equipped with such a device. Some of these people do not use the parking assistance device simply because they are unaware that such a device is integrated into their vehicle. Other people are aware of this device in their vehicle but prefer to park themselves. Furthermore, this device is not yet optimal, particularly in terms of its relatively slow execution speed which can annoy vehicle users and traffic. The parking assistance device is therefore generally underused.

[0005] The present invention makes it possible to encourage the use of such a device by proposing an analytical system on board a vehicle comprising: - a plurality of sensors, each of the sensors being configured to measure in real time a distance relative to said vehicle, - a control module configured to determine, from the distances measured by the sensors, a reference trajectory and an actual trajectory of the vehicle and / or at least one deviation in positioning of the vehicle relative to at least one surrounding obstacle and / or relative to at least one marking on the ground delimiting a parking space,

[0006] characterized in that the control module is configured to calculate an overall score of a manual parking maneuver of the vehicle based on the determined trajectories of the vehicle and / or the determined positioning deviation of the vehicle relative to the surrounding obstacle and / or the ground markings delimiting the space, the analytical system comprising a communication module configured to transmit a report of said manual parking maneuver, the report being based on the overall score calculated by the control module.

[0007] Thanks to the invention, when the driver of the vehicle performs a parking maneuver manually, that is to say without using a parking assistance device integrated into his vehicle, the analytical system ensures an analysis of his parking maneuver and can generate a report that can be transmitted to the driver, the report being able, if the parking maneuver is imperfect, to encourage him to use the parking assistance device rather than park manually. If the parking assistance device is not integrated into the vehicle, but the latter is equipped so that such a parking assistance device can be integrated, the report can also encourage the driver to carry out an update in order to download and install the parking assistance device on his vehicle.

[0008] The sensors are advantageously arranged so as to be oriented towards the outside of the vehicle. In addition, the sensors are preferably arranged all around the vehicle in order to be able to fully detect surrounding obstacles wherever they are. The sensors thus provide a complete overview of the external environment, thus subsequently participating in the determination of trajectories and / or positioning deviations. The real-time analysis also allows the sensors to continue to carry out their measurements, even while the vehicle is in the process of parking.

[0009] It will be understood that these sensors are also essential for implementing the possible parking assistance device, the vehicle needing to have a set of information concerning the external environment before carrying out an automatic parking maneuver.

[0010] Once the coordinates of the free parking space have been acquired and a first series of measurements taken by the sensors during a situation where the vehicle is close to a free parking space, the control module will process these measurements. From the initial position of the vehicle, the control module determines the reference trajectory, which corresponds to an optimal trajectory that the vehicle must take during its parking maneuver to park properly in the parking space. This reference trajectory may differ depending on the situation, for example depending on the initial position of the vehicle, or depending on the parking maneuver to be carried out, such as a niche, a battle arrangement or a herringbone arrangement.

[0011] The actual trajectory of the vehicle is determined in real time when the vehicle is in the process of parking, from the initial position of the vehicle to a final position of the vehicle, corresponding to a position where the driver considers that his parking maneuver is complete and that the vehicle is parked.

[0012] When the vehicle is in its final position, the determination of positioning deviations makes it possible to check whether the vehicle is correctly positioned within the parking space. The positioning deviations may, for example, relate to a measurement of a distance between the vehicle and a curb, for example a sidewalk running alongside the parking space. One or more positioning deviations may also be determined between the vehicle and / or vehicles parked in adjacent parking spaces. The positioning deviations may also, alternatively or additionally, be determined relative to road markings delimiting the target parking space.

[0013] Based on the various data previously described and received, the overall score for the parking maneuver performed by the driver is calculated. A high overall score corresponds to a correctly executed parking maneuver, while a low overall score corresponds to an imprecisely executed parking maneuver. It should be understood, however, that this rating scale is arbitrary and that a low overall score could correspond to a correctly executed parking maneuver, since the rating scale that will be described below is arranged accordingly.

[0014] The communication module allows information relating to the quality of the driver's parking maneuver to be communicated to the latter, based on the overall score previously calculated.

[0015] According to a characteristic of the invention, the control module is configured to determine a trajectory deviation between the actual trajectory of the vehicle and the reference trajectory. The trajectory deviation is determined in real time, preferably after the reference trajectory has been determined and throughout the actual trajectory of the vehicle, i.e. during the manual parking maneuver. The trajectory deviation makes it possible in particular to determine whether the movement of the vehicle is close to or far from the reference trajectory. An actual trajectory of the vehicle is optimal if it is similar or substantially similar to the reference trajectory, which corresponds to a zero or small trajectory deviation.

[0016] According to a characteristic of the invention, the control module is configured to assign a trajectory score by comparing the trajectory deviation with at least one trajectory threshold. Advantageously, the trajectory deviation is compared to several trajectory thresholds in order to refine the trajectory score as much as possible. The trajectory deviation is determined globally in order to take into account the entire actual trajectory of the vehicle. The trajectory deviation can be determined globally by averaging the position deviations at a given time between the position that the vehicle should have at that time and the position of the vehicle actually observed.

[0017] The lower the trajectory deviation, meaning that the actual trajectory is close to the reference trajectory, the higher the trajectory score. Conversely, the higher the trajectory deviation, meaning that the actual trajectory is far from the reference trajectory, the lower the trajectory score.

[0018] If the trajectory score is calculated, it is taken into account for the calculation of the overall score of the manual parking maneuver.

[0019] According to a feature of the invention, the control module is configured to assign a positioning score by comparing the positioning deviation of the vehicle with a threshold positioning deviation. The positioning deviation makes it possible to analyze the final position of the parked vehicle, how it is positioned in relation to surrounding obstacles and whether this positioning is correct following the manual parking maneuver.

[0020] Several types of threshold positioning deviations can be considered depending on the environment outside the vehicle. A positioning score can be high if the positioning deviation associated with it is as small as possible, or conversely if it is of a reasonable magnitude without being too small.

[0021] If at least one positioning score is calculated, this is taken into account for the calculation of the overall score of the manual parking maneuver.

[0022] According to a characteristic of the invention, the positioning deviation of the vehicle is measured between a longitudinal end of the vehicle and a surrounding obstacle and / or one of the ground markings delimiting the space, and / or between a lateral end of the vehicle and a surrounding obstacle and / or one of the ground markings delimiting the space, the positioning score being a function of all the positioning deviations measured, each being compared to a specific threshold positioning deviation. It often happens that a parking space is at least partially delimited along two dimensions. It is therefore preferable to determine a positioning deviation with the longitudinal end or the lateral end of the vehicle. Advantageously, the positioning deviation is determined with respect to three ends among the two longitudinal ends and the two lateral ends of the vehicle.Each of the measured positioning deviations is thus taken into account for the positioning score attributed to the manual parking maneuver.

[0023] According to a characteristic of the invention, the control module is configured to count a number of iterations carried out to carry out the manual parking maneuver, each iteration corresponding to a change in the direction of movement of the vehicle. This is an additional criterion and an additional score which results from it allowing the overall score of the manual parking maneuver to be established. By change of direction of the vehicle, we mean a change from the forward movement of the vehicle to the reverse movement of the vehicle or vice versa. Thus, an additional iteration is counted for each of these passages, these being carried out in order to adjust the trajectory and / or position of the vehicle during the manual parking maneuver.

[0024] According to a feature of the invention, the control module is configured to assign an iteration score by comparing the number of iterations to a reference iteration threshold. The reference iteration threshold is previously determined by the control module and corresponds to the number of iterations estimated to be necessary to perform the parking maneuver. The comparison carried out by the control module makes it possible to determine whether the driver of the vehicle performs more iterations than the reference iteration threshold, and if so, how many additional iterations the driver performs. The iteration score is therefore based on these criteria.

[0025] If the iteration score is calculated, it is taken into account for the calculation of the overall score of the manual parking maneuver.

[0026] According to a feature of the invention, the control module is configured to determine a level of difficulty of the manual parking maneuver, the control module being configured to adjust the overall score according to the determined level of difficulty. Such a level of difficulty may for example be relative to the dimensions of the parking space and to a comparison of these dimensions with the dimensions of the vehicle. The smaller the space of the parking space, the higher the level of difficulty of the parking maneuver is considered. Conversely, if the space of the parking space is large enough for the vehicle to easily fit into it, then the level of difficulty of the parking maneuver is considered low.

[0027] Depending on the determined difficulty level, adjustments such as adding or subtracting points from the various scores mentioned above thus affect the overall score of the manual parking maneuver.

[0028] The invention also covers a method for analyzing a manual parking maneuver of a vehicle, implemented by an analytical system as previously described, comprising:

[0029] - a step of analyzing a trajectory of the vehicle during the manual parking maneuver, and / or

[0030] - a step of measuring at least one positioning deviation, said positioning deviation being determined from the distances measured between the vehicle and at least one surrounding obstacle and / or at least one of the ground markings delimiting the space at the end of the manual parking maneuver,

[0031] - a step of calculating an overall score for the manual parking maneuver from data obtained during the analysis step and / or the measurement step,

[0032] - a step of communicating a report on the manual parking maneuver, the report being a function of a result of the step of calculating the overall score.

[0033] As previously described, the analysis method begins with a determination of the trajectories during the manual parking maneuver of the vehicle and / or by a determination of at least one positioning deviation relative to the vehicle and to at least one surrounding obstacle, and / or a ground marking, once the manual parking maneuver of the vehicle has been completed.

[0034] From this data, the control module will calculate the overall score of the manual parking maneuver, possibly from the trajectory or positioning scores if these have been calculated previously.

[0035] If it is necessary to transmit the report to the driver, the communication module can transmit the report, for example, by visual display on an on-board computer in the vehicle.

[0036] According to a characteristic of the invention, the analysis method comprises a step of counting at least one iteration of maneuver of the vehicle during the manual parking maneuver, the step of calculating the overall score being implemented from data obtained during the analysis step and / or the measurement step and / or the counting step. Just as for the determination of the trajectory and / or the positioning deviation, the analysis method can count the iterations, as described previously.

[0037] According to a characteristic of the invention, the analysis method comprises an estimation step establishing a level of difficulty of the manual parking maneuver of the vehicle, the calculation of the overall score being adjusted according to the level of difficulty determined during the estimation step. It is thanks to this step that the level of difficulty allows the addition or removal of points from the overall score.

[0038] According to a characteristic of the invention, the overall score of the manual parking maneuver of the vehicle is compared to a theoretical overall score, the communication step being implemented when a difference between the overall score and the theoretical score is greater than a given threshold. The theoretical score can be considered as being the minimum score to be reached for the analytical system to consider that the manual parking maneuver has been correctly executed. If the calculated overall score is too far from this theoretical overall score, then the communication module The communication can transmit the report to the driver.

[0039] According to a feature of the invention, the assessment includes a recommendation to use a parking assistance device if the overall score of the manual parking maneuver of the vehicle is lower than the theoretical overall score. As mentioned previously, the assessment may advise the driver, in a non-exhaustive manner, to use or install the parking assistance device if his manual parking maneuver is considered imperfect by the analytical system.

[0040] In another example, the analytical system can be configured so that the report contains driving advice addressed to the driver to help him improve his next manual parking maneuvers.

[0041] In another example, if the overall score of the vehicle's manual parking maneuver is significantly higher than the theoretical overall score, the analytical system can reward the driver with the award of a fictitious title or a virtual fictitious badge of good driver in the area of ​​parking maneuvers.

[0042] The stage of communicating the report may consist, in addition to or as an alternative to sending and presenting the report to the driver, and if the sending conditions are met, sending it to a remote server, for example for the purpose of feeding a database linked to the manufacturer's profile.

[0043] Other characteristics and advantages of the invention will become apparent from the following description on the one hand, and from several examples of embodiment given for informational and non-limiting purposes with reference to the attached schematic drawings on the other hand, in which:

[0044] [Fig.l] is a representation of a vehicle equipped with an analytical system according to the invention, said vehicle being at the start of a manual parking maneuver,

[0045] [Fig.2] is a representation of the vehicle during a manual parking maneuver,

[0046] [Fig.3] is a representation of the vehicle after the manual parking maneuver,

[0047] [Fig.4] is a flowchart of a method for analyzing a manual parking maneuver implemented by the analytical system,

[0048] [Fig.5] is a table detailing an example of an overall score calculation of the manual parking maneuver.

[0049] [Fig. 1] represents a vehicle 1 equipped with an analytical system 2 according to the invention. The vehicle 1 is driven by a driver preparing to carry out a manual parking maneuver, despite the fact that his vehicle 1 is equipped with a parking assistance device. The latter is not used by the driver, for example because the driver does not wish to use it or because he is unaware that his vehicle 1 is equipped with it.

[0050] The vehicle 1 is about to be parked in a parking space 3. The parking space 3 is delimited by one or more obstacles 100 and / or by one or more markings on the ground. According to the example of [Fig.l], the parking space 3 is delimited by a first adjacent parking space 101 occupied by a first third-party vehicle 102, by a second adjacent parking space 103 occupied by a second third-party vehicle 104, and by an edge 105 which may for example be a sidewalk and delimiting the parking space 3. Such a configuration can take place in various environments, for example in a parking lot or in a street.

[0051] In [Fig.l], the manual parking maneuver about to be executed is a parallel parking maneuver, but it can also be any other manual parking maneuver, for example a bay or herringbone parking maneuver.

[0052] The analytical system 2 comprises a plurality of sensors 4, a control module 5 and a communication module 6. The sensors 4 are advantageously oriented towards the exterior of the vehicle 1 and are advantageously arranged along the entire length of the vehicle 1 so as to be able to capture the entire environment outside the vehicle 1.

[0053] The sensors 4 are configured to measure a distance in real time between the vehicle 1 and at least one of the surrounding obstacles 100 and / or at least one of the ground markings delimiting the target space). In this respect, the sensors 4 may for example be sonars, cameras and / or radars.

[0054] The control module 5 is capable of receiving and processing the distances measured by the sensors 4 in order to establish several parameters linked to the manual parking maneuver which will follow. The control module 5 can for example be integrated within an electronic assembly of the vehicle 1.

[0055] The communication module 6 is connected to the control module 5 and can transmit messages to the driver, for example via a display screen located on the dashboard of the vehicle 1. The communication module 6 associated with the analytical system according to the invention may only be active once the parking maneuver has been carried out. The communication module may, as an alternative or in addition to what has just been mentioned, be configured to generate messages to a remote server, in particular for the purposes of informing the automobile manufacturer or the equipment manufacturer designing the analytical system.

[0056] In [Fig.l], the vehicle 1 is in position to start the manual parking maneuver. In a manner that may be prior to this maneuver, the analytical system 2, particularly the sensors 4 and the control module 5, can perform multiple tasks.

[0057] One of these tasks is to estimate a level of difficulty of the manual parking maneuver. To do this, using the sensors 4, the control module 5 determines the dimensions X, Y of the parking space 3 and compares these dimensions with the size of the vehicle 1. The level of difficulty can, for example, be determined based on a difference between the length X of the parking space 3 and the length of the vehicle 1.

[0058] According to the following example, the level of difficulty of the maneuver will be considered high if the difference between the length X of parking space 3 and the length of vehicle 1 is less than 90 cm. The level of difficulty will be considered medium if this difference is between 90 cm and 110 cm. Finally, the level of difficulty will be considered low if this difference is greater than 110 cm.

[0059] The control module 5, using the sensors 4, can also analyze the external environment of the vehicle 1, in particular the obstacles 100, in order to define a reference trajectory 7 represented in dot-and-dash lines in [Fig.1]. The reference trajectory 7 corresponds to the trajectory that the vehicle 1 must follow in order to carry out an optimal parking maneuver allowing it to stop in an ideal final position. It is thus understood that the manual parking maneuver that will follow will be partly analyzed according to the trajectory of the vehicle 1.

[0060] [Fig.l] also represents a plurality of iterations 8 at the level of the reference trajectory 7. The iterations 8 correspond to the number of changes in direction of movement of the vehicle 1, that is to say a change from forward gear to reverse gear, or from reverse gear to forward gear.

[0061] In [Fig.l], it is possible to see, along the reference trajectory 7, that two iterations 8 are represented, namely a first virtual iteration 8a corresponding to a curved reverse gear according to the reference trajectory 7, and a second virtual iteration 8b corresponding to a forward gear within the parking space 3 in order to readjust the position of the vehicle 1. The total number of virtual iterations corresponds to a reference threshold of iterations.

[0062] Just as for the reference trajectory 7, the iterations 8 represented in [Fig.l] represented in number of two correspond to a reference number of iterations 8 defining the optimal number of iterations to carry out the parking maneuver.

[0063] [Fig. 2] shows vehicle 1 in the process of a manual parking maneuver, i.e., with the driver of vehicle 1 performing said parking maneuver. As illustrated in [Fig. 2], the driver has already initiated a curve in order to park in parking space 3 by parallel parking. In order to improve the clarity of [Fig. 2], the set of sensors 4 shown in [Fig. 1] is not illustrated in [Fig.2] but the sensors 4 are still present in a configuration as illustrated in [Fig.1].

[0064] During the manual parking maneuver, the vehicle 1 follows an actual trajectory 9, here represented in solid lines. The actual trajectory 9 is followed in real time as the vehicle 1 moves, thanks to the sensors 4 measuring the distances between the vehicle 1 and the obstacles 100 and / or the ground markings and to the control module 5 which processes these measurements.

[0065] In addition, the analytical system 2 can perform a real-time comparison between the reference trajectory 7 and the actual trajectory 9 of the vehicle 1, and thus calculate a trajectory deviation 10 which can change over the course of the manual parking maneuver. The trajectory deviation is determined for a given instant, for example a determined time after the start of the maneuver, taking into account the spatial coordinates of the location where the vehicle should be, in particular the center of its rear axle if the driver had taken the reference trajectory 7 and the spatial coordinates of the location where the vehicle is at this given instant.

[0066] Such a trajectory deviation 10 may increase or decrease during the manual parking maneuver performed by the driver, depending on whether the actual trajectory 9 respectively moves away from or towards the reference trajectory 7. In [Fig.2], the trajectory deviation 10 is not negligible, leading to the belief that the manual parking maneuver performed by the driver is not optimal.

[0067] In addition, the iterations 8 of the vehicle 1 parking according to the actual trajectory 9 are also illustrated. According to the actual trajectory 9, the driver of the vehicle 1 performs a first actual iteration 8c in reverse, a second actual iteration 8d in forward gear, a third actual iteration 8e in reverse gear and a fourth actual iteration 8f in forward gear. Compared to the reference trajectory 7, the driver of the vehicle 1 therefore performs, during his manual parking maneuver, two additional iterations 8, at the rate of four iterations 8 instead of two.

[0068] [Fig. 3] represents the vehicle 1 within the parking space 3 once the driver considers his manual parking maneuver to be completed. The analytical system 2, particularly the sensors, not shown here, and the control module 5, can measure at least one positioning difference 11 between the obstacles 100, and / or the ground markings, and the vehicle 1 once the manual parking maneuver thereof is completed.

[0069] As shown in [Fig. 3], the positioning deviations 11 can be measured between a lateral end 12 of the vehicle 1 and at least one of the obstacles 100 and / or at least one of the ground markings, and / or between a longitudinal end 13 of the vehicle 1 and at least one of the obstacles 100 and / or at least one of the markings on the ground.

[0070] In [Fig.3], a first positioning deviation 11a and a second positioning deviation 11b are measured between the edge 105 and the lateral end 12 of the vehicle 1 closest to said edge 105. The first positioning deviation 11a and the second positioning deviation 11b are measured at two different points of the lateral end 12 of the vehicle 1 and make it possible to define whether the vehicle has been stopped at a suitable distance from the curb, and these two positioning deviations are compared with each other in order to check the parallelism of the vehicle 1 along the edge 105 once parked within the parking space 3.

[0071] In addition, a third positioning deviation 11e is measured between a front longitudinal end 13a of the vehicle 1 and the rear of the first third-party vehicle 102, and / or a ground marking near the front longitudinal end of the vehicle, and a fourth positioning deviation 11d is measured between a rear longitudinal end 13b of the vehicle 1 and the front of the second third-party vehicle 104 and / or a ground marking near the front longitudinal end of the vehicle. These positioning deviations make it possible to determine whether the vehicle is too close to a third-party vehicle and / or one of the ground markings. Furthermore, the third positioning deviation 13c and the fourth positioning deviation 11d are here compared with each other in order to check whether the vehicle 1 is equidistant from the two third-party vehicles 102, 104 and / or from the nearby ground markings delimiting the target space.The measurement of all these positioning differences 11 makes it possible in particular to ensure that the vehicle 1 is correctly parked within the parking space 3.

[0072] [Fig. 4] is a flowchart schematizing the progress of an analysis method 50 of the manual parking maneuver performed by the driver of the vehicle. The analysis method 50 is implemented by the analytical system and comprises one or more data determination steps, said data being determined during or after the manual parking maneuver of the vehicle, as illustrated in FIGS. 1 to 3. At the end of the analysis method 50, the analytical system assigns an overall score S relating to the execution of the manual parking maneuver.

[0073] The analysis method 50 begins with an initiation step 51. This initiation step 51 makes it possible to start the analysis method 50. The initiation step 51 can be triggered manually by the driver of the vehicle or automatically in the event of detection of a parking maneuver.

[0074] The analysis method 50 can then continue with an estimation step 52 which establishes the level of difficulty D of the manual parking maneuver, for example as a function of the dimensions of the parking space concerned, as illustrated in [Fig.1]. This estimation step 52 is optional but makes it possible to refine the overall score attributed to the manual parking maneuver.

[0075] The analysis method 50 also comprises a step 53 of analyzing the actual trajectory 9 of the vehicle during the manual parking maneuver and / or a step 54 of measuring the deviation(s) in positioning of the vehicle relative to the surrounding obstacles at the end of the manual parking maneuver. The analysis step 53 and / or the measurement step 54 takes place after the initiation step 51. The analysis step 53 and / or the measurement step 54 may also take place simultaneously and / or after the estimation step 52 if the latter has been implemented.

[0076] The analysis step 53 consists of comparing the actual trajectory 9 of the vehicle with the reference trajectory 7 in order to determine the trajectory deviation 10 in real time, as illustrated in [Fig. 2]. The analysis step 53 thus takes place during the manual parking maneuver performed by the driver of the vehicle. Since the analysis step 53 is performed in real time, an overall trajectory deviation E(T) can be measured, for example by calculating an average of the different trajectory deviations 10 measured over time, and for example by calculating a quadratic error relating to the trajectory deviation. The overall trajectory deviation E(T) is subsequently compared to at least one trajectory threshold E(Ts) in order to assign a trajectory score S(T) to the manual parking maneuver. The trajectory score S(T) can extend between two values ​​previously defined according to a means for calculating the overall score S of the manual parking maneuver.

[0077] If the estimation step 52 has been implemented, the trajectory score S(T) can be adjusted according to the difficulty level D established during said estimation step 52. Such an adjustment can for example consist of an addition of point if the estimated difficulty level D was considered high, or a removal of point if the estimated difficulty level D was considered low.

[0078] The measuring step 54 consists of measuring the positioning deviation(s) 11 of the vehicle relative to at least one of the surrounding obstacles and / or at least one of the ground markings delimiting the space, once the manual parking maneuver is completed, that is to say at the moment when the vehicle is parked in its final position. This measurement of positioning deviation(s) 11 is carried out by the sensors equipped on the vehicle, as illustrated in [Fig.3].

[0079] Once at least one of the positioning deviations 11 is measured, it is compared to a threshold positioning deviation E(Pref) and a positioning score S(P) is assigned to the manual parking maneuver. The positioning score S(P) can also be at least partially assigned based on a comparison between two positioning deviation measurements 11.

[0080] Just as for the trajectory score S(T), the positioning score S(P) can be adjusted according to the difficulty level D of the parking maneuver manual established during estimation step 52 if it has been implemented.

[0081] The analysis method 50 may also be capable of implementing a counting step 55, for example simultaneously with the implementation of the trajectory step 53. The counting step 55 ensures a reading of the number of real iterations Ir carried out by the driver of the vehicle during the manual parking maneuver, and compares this number of real iterations Ir with the number of virtual iterations Iv established, as illustrated in [Fig. 2]. An iteration score S(I) is thus established as a function of a difference between the number of real iterations Ir carried out and the number of virtual iterations Iv determined.

[0082] Just as for the trajectory score S(T) and the positioning score S(P), the iteration score S(I) can be adjusted according to the difficulty level D of the manual parking maneuver established during the estimation step 52 if it has been implemented.

[0083] Once one or more of the steps described above have been implemented, the analysis method 50 continues with a calculation step 56 of the overall score S of the manual parking maneuver performed. The overall score S may for example be equal to the sum of several previously established scores S(X) among the trajectory score S(T), the positioning score S(P) or the iteration score S(I). The calculation step 56 may also be accompanied by an adjustment step 57 executed only if the estimation step 52 has been implemented. This adjustment step 57 makes it possible to adjust the overall score S into an adjusted overall score S' according to the different adjustments of the previously cited scores and according to the level of difficulty D estimated during the estimation step 52. The overall score S or the adjusted overall score S' is then calculated and compared to a theoretical overall score Sref.

[0084] Depending on the comparison between the overall score S or the adjusted overall score S' of the manual parking maneuver and the theoretical overall score Sref, the analysis method 50 can continue with a communication step 58 which transmits a report of the manual parking maneuver to the driver, for example visually via a display screen of the dashboard of the vehicle. The report can contain different information depending on the overall score S or the adjusted overall score S' and its difference with the theoretical overall score Sref. If the overall score S or the adjusted overall score S' is low compared to the theoretical overall score Sref, the report provided during the communication step 58 can for example be a recommendation to use the parking assistance device in order to facilitate the parking maneuvers of the vehicle thereafter.

[0085] [Fig.5] is an example of a table listing a calculation of the overall score S or the adjusted overall score S'. For this example, we will assume that the intermediate scores mentioned previously, namely the trajectory score S(T), the po- positioning S(P) and the iteration score S(I), were all calculated.

[0086] Furthermore, since the estimation step has also been carried out, the table also lists several examples of adjustment based on the estimated difficulty level D. Three difficulty levels have been established: a first difficulty level DI corresponds to a high difficulty level, a second difficulty level D2 corresponds to a medium difficulty level, and a third difficulty level D3 corresponds to a low difficulty level. It is thus understood that it is the adjusted overall score S' that is calculated. Depending on the estimated difficulty level D, the adjustment of each score can consist of a gain or a loss of points, each score remaining, however, in the illustrated example, between 0 and 5.

[0087] Each of the intermediate scores is awarded relative to a total of 5 points. The positioning score S(P) is divided into a first positioning score S(P1) and a second positioning score S(P2), each having a total of 5 points. The adjusted overall score S' is therefore calculated relative to a total of 20 points.

[0088] For the trajectory score S(T), a squared error EQ is calculated from the overall trajectory deviation previously determined. The squared error EQ is then compared to the trajectory thresholds, corresponding to values ​​in centimeters. Thus, if the squared error is less than 20cm, the trajectory score S(T) is 5 points. If the squared error is less than 30cm, the trajectory score S(T) is 4 points. If the squared error is less than 40cm, the trajectory score S(T) is 2 points. If the squared error is greater than or equal to 40cm, the trajectory score S(T) is 1 point.

[0089] The trajectory score S(T) is increased by 1 point if the first difficulty level DI has been estimated, remains the same if the second difficulty level D2 has been estimated or is reduced by 1 point if the third difficulty level D3 has been estimated.

[0090] The first positioning score S (PI) is relative to the measurements of the first positioning deviation 11a and the second positioning deviation 11b illustrated in [Fig.3], i.e. between the lateral end of the vehicle and the edge.

[0091] This first positioning score allows the distance of the vehicle from the edge to be taken into account in general. If the sum of the first positioning deviation 1 la and the second positioning deviation 11b is less than 20cm then the first positioning score S(P1) is 5 points. If the sum of the first positioning deviation 1 la and the second positioning deviation 11b is less than 30cm then the first positioning score S(P1) is 4 points. If the sum of the first positioning deviation 1 la and the second positioning deviation 11b is greater than or equal to 30cm then the first positioning score S(P1) is 3 points.

[0092] Additionally, the parallelism of the vehicle along the edge is also taken into account. Thus, if the difference between the absolute value of the first positioning deviation 1 la and the absolute value of the second positioning deviation 11b is greater than or equal to 30cm, then the first positioning score S(P1) is 2 points, and if the difference between the absolute value of the first positioning deviation 1 la and the absolute value of the second positioning deviation 11b is greater than or equal to 40cm, then the first positioning score S(P1) is 1 point.

[0093] The first positioning score S (PI) is increased by 2 points if the first difficulty level DI has been estimated, remains the same if the second difficulty level D2 has been estimated or is reduced by 2 points if the third difficulty level D3 has been estimated.

[0094] The second positioning score S(P2) relates to the measurements of the third positioning gap 1 le and the fourth positioning gap 1 Id illustrated in [Fig.3], i.e. between each longitudinal end of the vehicle and the third-party vehicles and / or the ground markings delimiting the space. The second positioning score S(P2) here makes it possible to assess whether the vehicle is parked uniformly between the two third-party vehicles and / or between the ground markings delimiting the space.

[0095] If the absolute value of the difference between the third positioning deviation 1 le and the fourth positioning deviation 1 ld is less than 20cm, then the second positioning score S(P2) is 5 points. If the absolute value of the difference between the third positioning deviation 1 le and the fourth positioning deviation 1 ld is less than 30cm, then the second positioning score S(P2) is 4 points. If the absolute value of the difference between the third positioning deviation 1 le and the fourth positioning deviation 1 ld is less than 40cm, then the second positioning score S(P2) is 2 points. If the absolute value of the difference between the third positioning deviation 1 le and the fourth positioning deviation 1 ld is greater than or equal to 40cm, then the second positioning score S(P2) is 1 point.

[0096] The second positioning score S(P2) is increased by 2 points if the first difficulty level DI has been estimated, is increased by 1 point if the second difficulty level D2 has been estimated or remains identical if the third difficulty level D3 has been estimated.

[0097] The iteration score S(I) is calculated as a function of the number of real iterations Ir compared to the number of virtual iterations Iv which represents the reference threshold of iterations, as described in [Fig.2],

[0098] If the difference between the number of real iterations Ir and the number of virtual iterations Iv is less than or equal to 0, then the iteration score S(I) is 5 points. If the difference between the number of real iterations Ir and the number of virtual iterations Iv is equal to 1, then the iteration score S(I) is 4 points. If the difference between the number of real iterations Ir and the number of virtual iterations Iv is equal to 2, then the iteration score S(I) is 3 points. If the difference between the number of real iterations Ir and the number of virtual iterations Iv is equal to 3, then the iteration score S(I) is 2 points. If the difference between the number of real iterations Ir and the number of virtual iterations Iv is strictly greater than 3, then the iteration score S(I) is 1 point.

[0099] The iteration score S(I) is increased by 1 point if the first difficulty level DI has been estimated, remains the same if the second difficulty level D2 has been estimated or is reduced by 1 point if the third difficulty level D3 has been estimated.

[0100] The adjusted overall score S' out of 20 points corresponds to the sum of the scores described previously and adjusted according to the difficulty level D. As mentioned, the adjusted overall score is compared to the theoretical overall score Sref out of 20 points which is a score corresponding to a correctly executed parking maneuver.

[0101] If the absolute value of the difference between the adjusted overall score S' and the theoretical overall score Sref is greater than or equal to 3, then a report B is transmitted to the driver of the vehicle via the communication step mentioned above.

[0102] If the adjusted overall score S' is lower than the theoretical overall score Sref, then a first assessment B 1 is transmitted to the driver. This first assessment B 1 includes the recommendation to use the parking assistance device. The first assessment B1 may also include a recommendation to download a paid update to activate the possibility of using the parking assistance device if the vehicle is originally compatible but not equipped. The first assessment B 1 may also include driving advice to improve future manual parking maneuvers. For example, if one of the intermediate scores is particularly low compared to the others, the advice may specifically focus on a parameter specific to said intermediate score in order to subsequently improve this score.

[0103] If the adjusted overall score S' is higher than the theoretical overall score Sref, then a second assessment B2 is sent to the driver. The second assessment B2 can, for example, be a congratulatory message or a fictitious certification of good driver, relating to parking maneuvers.

[0104] The figures in the table in [Fig.5] are only examples and can be completely modified, whether it be the conditions linked to each of the scores, or the different thresholds for assigning said scores.

[0105] Of course, the invention is not limited to the examples which have just been described and numerous adjustments can be made to these examples without departing from the scope of the invention.

[0106] The invention, as just described, achieves the aim it set itself, and makes it possible to propose an analytical system evaluating a manual parking maneuver and encouraging the use of a parking assistance device in the event of an imperfect manual parking maneuver. Variants not described here could be implemented without departing from the context of the invention, provided that, in accordance with the invention, they comprise an analytical system in accordance with the invention.

Claims

Claims

1. Analytical system (2) on board a vehicle (1) comprising: - a plurality of sensors (4), each of the sensors (4) being configured to measure in real time a distance relative to said vehicle (1), - a control module (5) configured to determine, from the distances measured by the sensors (4), a reference trajectory (7) and an actual trajectory (9) of the vehicle (1) and / or at least one positioning deviation (11) of the vehicle (1) relative to at least one surrounding obstacle (100) and / or relative to at least one ground marking delimiting a parking space, characterized in that the control module (5) is configured to calculate an overall score (S) of a manual parking maneuver of the vehicle (1) as a function of the determined trajectories of the vehicle (1) and / or the determined positioning deviation (11) of the vehicle (1) relative to the surrounding obstacle (100) and / or the ground markings delimiting the space, the analytical system (2) comprising a communication module (6) configured to transmit a report (B) of said manual parking maneuver, the report (B) being based on the overall score (S) calculated by the control module (5).

2. Analytical system (2) according to claim 1, wherein the control module (5) is configured to determine a trajectory deviation (10) between the actual trajectory (9) of the vehicle (1) and the reference trajectory (7).

3. Analytical system (2) according to the preceding claim, in which the control module (5) is configured to assign a trajectory score (S(T)) by comparing the trajectory deviation (10) with at least one trajectory threshold (E(Ts)).

4. Analytical system (2) according to any one of the preceding claims, wherein the control module (5) is configured to assign a positioning score (S(P)) by comparing the positioning deviation (11) of the vehicle (1) with a threshold positioning deviation (E(Pref)).

5. Analytical system (2) according to the preceding claim, during of which the positioning deviation (11) of the vehicle (1) is measured between a longitudinal end (13) of the vehicle (1) and a surrounding obstacle (100) and / or one of the ground markings delimiting the space, and / or between a lateral end (12) of the vehicle (1) and a surrounding obstacle (100) and / or one of the ground markings delimiting the space, the positioning score (S(P)) being a function of all the positioning deviations (11) measured, each being compared to a specific threshold positioning deviation (E(Pref)).

6. Analytical system (2) according to any one of the preceding claims, in which the control module (5) is configured to count a number of iterations (8) carried out to carry out the manual parking maneuver, each iteration (8) corresponding to a change in direction of movement of the vehicle (1).

7. Analytical system (2) according to the preceding claim, in which the control module (5) is configured to assign an iteration score (S(I)) by comparing the number of iterations (8) to a reference threshold of iterations (8).

8. Analytical system (2) according to any one of the preceding claims, wherein the control module (5) is configured to determine a difficulty level (D) of the manual parking maneuver, the control module (5) being configured to adjust the overall score (S) according to the determined difficulty level (D).

9. Method for analyzing (50) a manual parking maneuver of a vehicle (1), implemented by an analytical system (2) according to any one of the preceding claims, comprising: a step of analyzing (53) a trajectory of the vehicle (1) during the manual parking maneuver, and / or a step of measuring (54) at least one positioning deviation (11), said positioning deviation (11) being determined from the distances measured between the vehicle (1) and at least one surrounding obstacle (100) and / or at least one of the ground markings delimiting the space at the end of the manual parking maneuver, a step of calculating (56) an overall score (S) of the manual parking maneuver from data obtained during the analysis step (53) and / or the measurement step (54), a step of communicating (58) a report (B) of the manual parking maneuver, the result (B) being a function of a result of the calculation step (56) of the overall score (S).

10. Analysis method (50) according to the preceding claim, comprising a step of counting (55) at least one iteration (8) of maneuvering of the vehicle (1) during the manual parking maneuver, the step of calculating (56) the overall score (S) being implemented from data obtained during the analysis step (53) and / or the measurement step (54) and / or the counting step (55).

11. Analysis method (50) according to claim 9 or 10, comprising an estimation step (52) establishing a level of difficulty (D) of the manual parking maneuver of the vehicle (1), the calculation of the overall score (S) being adjusted according to the level of difficulty (D) determined during the estimation step (52).

12. Analysis method (50) according to any one of claims 9 to 11, during which the overall score (S) of the manual parking maneuver of the vehicle (1) is compared to a theoretical overall score (Sref), the communication step (58) being implemented when a difference between the overall score (S) and the theoretical overall score (Sref) is greater than a given threshold.

13. Analysis method (50) according to the preceding claim, during which the assessment (B) comprises a recommendation to use a parking assistance device if the overall score (S) of the manual parking maneuver of the vehicle (1) is lower than the theoretical overall score (Sref).

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