Vehicle seat positioning optimization system

Abstract

Vehicle seat positioning optimization system The invention relates to a system (12) for optimizing the positioning of a vehicle seat (10), comprising: - a module (14) for obtaining and saving a morphological parameter of a passenger on the seat; - a seat positioning adjustment module (16) comprising at least one sensor within the vehicle and controlling said positioning; - a module for determining the positioning adjustment to be applied according to said morphological parameter;The system is configured to: - determine at least one adjustment change optimizing passenger comfort to be applied during vehicle operation, - automatically modify the seat positioning to achieve said adjustment change, or - signal to the passenger the adjustment change to be applied, via an interaction module (20), and guide them to manually achieve the adjustment change, via a predetermined audible or visual signal. Figure for the abbreviation: Figure 1;

Description

Title of the invention: System for optimizing the positioning of a vehicle seat

[0001] The present invention relates to a system for optimizing the positioning of a vehicle seat, comprising:

[0002] - a module for obtaining and saving at least one morphological parameter representative of a typical passenger seated in the seat;

[0003] - a seat positioning adjustment module, the adjustment module including at least one sensor, located within the vehicle, and configured to control the positioning of the seat;

[0004] - a determination module configured to determine the position adjustment seat operation to be applied at least according to said at least one morphological parameter representative of the current passenger.

[0005] The invention also relates to a vehicle comprising such an optimization system.

[0006] The invention also relates to a method for optimizing the positioning of a vehicle seat.

[0007] The present invention also relates to a computer program comprising software instructions which, when executed by a computer, implement such a method for optimizing the positioning of a vehicle seat.

[0008] A vehicle seat must provide satisfactory comfort for accommodating passengers in the vehicle.

[0009] To do this, it is known to use at least one representative morphological parameter of a typical passenger seated in the seat to implement a first automatic adjustment of the positioning of said seat.

[0010] However, such an initial adjustment, achieved automatically according to current state-of-the-art technology, does not always meet the individual comfort needs of the passenger, particularly when the passenger experiences specific local pain. In the presence of such pain, the passenger can currently only attempt to adjust the seat position themselves by trial and error, which is not optimal and does not always provide the desired pain relief. Furthermore, from a safety perspective, such trial and error, when performed by a passenger who is also the driver, most often requires the vehicle to be stopped so as not to disturb their concentration while driving.

[0011] One of the aims of the invention is to overcome these drawbacks by proposing a system for optimizing the positioning of a vehicle seat that is simple and quick to implement. works for the passenger, in order to effectively optimize their comfort and relieve or even avoid local bodily pain.

[0012] To this end, the invention relates to a system for optimizing the positioning of a vehicle seat, comprising:

[0013] - a module for obtaining and saving at least one morphological parameter representative of a typical passenger seated in the seat;

[0014] - a seat positioning adjustment module, the adjustment module including at least one sensor, located within the vehicle, and configured to control the positioning of the seat;

[0015] - a determination module configured to determine the position adjustment seat operation to be applied at least according to said at least one representative morphological parameter of the current passenger;

[0016] the optimization system being configured for:

[0017] - determine, using the optimization system determination module, at less a change in seat positioning adjustment, optimizing the comfort of the current passenger, and to be applied while the vehicle is in operation,

[0018] - automatically modify the seat positioning via the adjustment module to achieve the adjustment change to be applied, or

[0019] - signal to the current passenger the change in the positioning adjustment of the seat to be applied, via a system interaction module with the current passenger, and guide the passenger to manually change the seat positioning to achieve the adjustment change, via a predetermined audible or visual signal representative of achieving the adjustment change.

[0020] Thus, the seat positioning optimization system according to the invention makes it easier and faster for passengers to access an optimal seat position that maximizes their comfort, for example by minimizing localized pain in identified body areas. Indeed, according to the present invention, the change in positioning adjustment that optimizes passenger comfort is achieved either automatically, via the adjustment module, or manually but in a guided manner, which avoids any trial and error and, where applicable, avoids having to stop the vehicle to achieve the seat positioning adjustment necessary to relieve passenger discomfort while driving.

[0021] According to other optional features of the invention, taken individually or in any technically feasible combination:

[0022] - the change in positioning adjustment is determined from the initial adjustment of the seat positioning before starting the vehicle, and / or from a positioning adjustment initially selected by the current passenger, via the interaction module, before starting the vehicle;

[0023] - the determination module is configured to determine the change adjustment of the seat positioning also depending on the uninterrupted duration of driving the vehicle by the current passenger;

[0024] - the determination module is configured to determine the change seat positioning adjustment to be applied, by machine learning, from at least one input element belonging to the group comprising at least,

[0025] - said at least one morphological parameter representative of the current passenger;

[0026] - the vehicle model;

[0027] - at least one piece of information representative of the vehicle occupancy rate;

[0028] - machine learning uses a database built beforehand starting from at least one building element belonging to the group comprising at least:

[0029] - a plurality of mannequin body types,

[0030] - a plurality of predetermined positioning adjustment rules,

[0031] - a plurality of vehicle occupancy rates,

[0032] - a plurality of vehicle types,

[0033] - a plurality of distinct body areas.

[0034] - the interaction module is configured to display a plurality of cor zones distinct areas to be relieved via the change in seat positioning adjustment, each body area being selectable by the current passenger, and the determination module is configured to determine the change in seat positioning adjustment to be applied also according to at least one body area to be relieved previously selected by the current passenger;

[0035] - the determination module is further configured to:

[0036] - to associate a local comfort score to each doublet formed from a body zone selectable and a seat positioning, and associate an overall comfort score with each seat positioning,

[0037] - select the positioning associated with the maximum overall comfort score, and for each selectable body area, the positioning associated with a maximum local comfort score,

[0038] and the interaction module is designed to display selectable information representative of each of the positions selected by the determination module.

[0039] According to another aspect, the invention also relates to a vehicle comprising a system for optimizing the positioning of a seat as described above.

[0040] The present invention also relates to a method for optimizing the positioning of a vehicle seat, the method being suitable for implementation by the seat positioning optimization system described above, the module the determination method being configured to determine an optimal seat positioning adjustment to be applied based on at least one representative morphological parameter of the average passenger, the method comprising at least:

[0041] - a machine learning step using a database built at prerequisite, starting from at least one building element belonging to the group comprising at least:

[0042] - a plurality of mannequin body types,

[0043] - a plurality of predetermined positioning adjustment rules,

[0044] - a plurality of vehicle occupancy rates,

[0045] - a plurality of vehicle types,

[0046] - a plurality of distinct body areas,

[0047] the first phase of machine learning providing a predictive model associating:

[0048] - an overall comfort score for each first distinct set formed at least:

[0049] - of a mannequin-like morphology of said plurality,

[0050] - of a type of vehicle of said plurality,

[0051] - of a seat positioning,

[0052] and / or

[0053] - a local comfort score for each second distinct set formed:

[0054] - of a mannequin-like morphology of said plurality,

[0055] - of a type of vehicle of said plurality,

[0056] - of a seat positioning,

[0057] - of a bodily area of ​​said plurality,

[0058] - a step of optimizing the positioning of a seat in a given vehicle, configured to provide a passenger, during operation of said vehicle, based on at least one representative morphological parameter of said passenger, for each body area, with the positioning associated with the maximum local comfort score and / or the positioning associated with the maximum overall comfort score,

[0059] the optimization step being suitable to be repeated during uninterrupted operation of said vehicle in question, and / or in case of change of passenger and / or occupancy rate of said vehicle, and / or in case of stop / restart of said vehicle.

[0060] The invention also relates to a computer program comprising software instructions which, when executed by a computer, implement such a method of optimizing the positioning of a seat.

[0061] These features and advantages of the invention will become clearer upon reading the following description, given solely by way of non-limiting example, and made with reference to the accompanying drawings, in which:

[0062] - [Fig. 1] [Fig. 1] is a schematic representation of an optimization system of the positioning of a vehicle seat according to an embodiment of the invention;

[0063] - [Fig.2] [Fig.2] is a flowchart of an example of an optimization process of the vehicle seat positioning implemented by the vehicle seat positioning optimization system of [Fig.1];

[0064] - [Fig.3] [Fig.3] is a schematic representation of the positions of the same mannequin optimizing overall comfort or the comfort of specific body areas;

[0065] - [Fig.4] [Fig.4] is a histogram representation of a score of overall comfort and local comfort scores respectively associated with distinct body areas, for each positioning maximizing one of these scores.

[0066] A transport vehicle 10, referred to simply as vehicle 10 in what follows, is shown in [Fig.1].

[0067] The vehicle 10 is, for example, a motor vehicle, or alternatively, an aircraft, or any other type of vehicle transporting passengers, such as a car, a bus, a train, an airplane, or a truck.

[0068] The vehicle 10 is suitable for moving in an environment.

[0069] It should be noted that, in the present description, the expression "specific to" means interchangeably "suitable for", "adapted to" or "configured for".

[0070] The vehicle includes within its passenger compartment at least one seat, not shown in [Fig. 1], and a system 12 for optimizing the positioning of said at least one vehicle seat 10, comprising:

[0071] - a module for obtaining 14 and saving at least one parameter mor phological representative of a typical passenger seated in the seat;

[0072] - a seat positioning adjustment module 16, the adjustment module including at least one sensor, located within the vehicle, and configured to control the positioning of the seat;

[0073] - a determination module 18 configured to determine the position adjustment seat operation to be applied at least according to said at least one morphological parameter representative of the current passenger.

[0074] According to the present invention, the optimization system 12 is specifically configured to:

[0075] - determine, using the determination module 18 of the optimization system 12, at least one change in seat positioning adjustment, optimizing the comfort of the current passenger, and to be applied while the vehicle is in operation 10,

[0076] - automatically modify, via adjustment module 16, the positioning of the seat to achieve the adjustment change to be applied, or

[0077] - signal to the current passenger the change in the positioning adjustment of the seat to be applied, via an interaction module 20 of system 12 with the passenger current, and guide the passenger to manually change the seat positioning to achieve the adjustment change, via a predetermined audible or visual signal representative of achieving the adjustment change.

[0078] According to the present invention, such a seat corresponds to the seat of a driver passenger or to the seat of an accompanying passenger.

[0079] In particular, module 14 for obtaining and saving at least one morphological parameter is, according to a first variant, coupled to the interaction module 20 and capable of querying the passenger by request(s), via said interaction module 20, on his measurements.

[0080] According to a second variant, the module 14 for obtaining and saving at least one morphological parameter is connected to a set of sensors, including for example at least one height sensor(s) located within the passenger compartment of the vehicle 10, and the module 14 for obtaining and saving is suitable for implementing a processing of the data provided by the set of sensors, in particular image processing(s) to determine at least one morphological parameter of the current passenger such as his height, his weight, his torso height, his arm length, his leg length, the distance between his elbow and his wrist, the distance between his shoulder and his elbow, the distance between his knee and his ankle etc.

[0081] The seat positioning adjustment module 16 includes, according to a first variant, one or more means for manually adjusting the seat positioning, to modify the positioning of the seat relative to the longitudinal axis of the vehicle, modify the seat height, the angle between the backrest and the seat cushion, etc.

[0082] In addition or as an alternative, the seat positioning adjustment module 16 includes one or more motorized seat positioning adjustment means, controllable, in particular according to the present invention, by the determination module 18 to automatically modify the seat positioning to achieve the adjustment change to be applied to increase the individual comfort of the passenger.

[0083] The adjustment module 16 includes at least one sensor, located within the vehicle, and configured to control the positioning of the seat at all times.

[0084] The determination module 18 allows, in particular during the first seating of the current passenger considered, to determine the initial positioning adjustment of the seat to be applied at least according to said at least one representative morphological parameter of the current passenger, then, according to the present invention, to determine a change in positioning adjustment, individually optimizing the comfort of the current passenger.

[0085] In particular, the determination module 18 is configured to determine the change in positioning adjustment to be applied to optimize the comfort of the passenger, from the initial seat positioning adjustment before vehicle start, and / or from a positioning adjustment initially selected by the current passenger, via interaction module 20, before vehicle start.

[0086] As an optional addition, the determination module 18 is configured to determine the positioning adjustment change to be applied to optimize passenger comfort, based on the uninterrupted duration of vehicle operation by the current passenger. This consideration notably takes into account the fatigue associated with maintaining the same posture for said uninterrupted duration.

[0087] As an optional complement, the determination module 18 is further configured to determine the seat positioning adjustment change to be applied, by machine learning, from at least one input element belonging to the group comprising at least,

[0088] - said at least one morphological parameter representative of the current passenger;

[0089] - the vehicle model;

[0090] - at least one piece of information representative of the vehicle occupancy rate.

[0091] Taking into account the vehicle occupancy rate allows the determination module 18 to determine a positioning change adapted both to the desired comfort of the passenger occupying the seat in question and also adapted to the overall comfort of all the occupants of the vehicle, for example to optimize both the comfort of the driver passenger and the passenger sitting behind the driver passenger.

[0092] Furthermore, as an optional additional complement to this variant, the machine learning uses a database constructed beforehand from at least one building block belonging to the group comprising at least:

[0093] - a plurality of mannequin body types,

[0094] - a plurality of predetermined positioning adjustment rules,

[0095] - a plurality of vehicle occupancy rates,

[0096] - a plurality of vehicle types,

[0097] - a plurality of distinct body areas.

[0098] In particular, the predetermined positioning adjustment rules correspond to industry-specific rules derived in particular from expert know-how associated with the optimization of seat positioning within vehicles 10, optimizing the comfort of its occupants.

[0099] According to a particular aspect, the database is designed to be updated as passenger needs change, also to improve the machine learning implemented in order to best prevent passenger ailments associated with their posture within said vehicle 10.

[0100] According to a particular embodiment of the present invention, the interaction module 20 is configured to display a plurality of distinct body zones, i.e. N distinct body zones, with N an integer, to be relieved via the change in seat positioning adjustment to be determined by the determination module 18, each body zone being selectable by the current passenger via the interaction module 20. According to this same particular embodiment, the determination module 18 is then further configured to determine the change in seat positioning adjustment to be applied also according to at least one body zone to be relieved previously selected by the current passenger.

[0101] For example, the distinct and selectable body areas to be relieved are the head, in particular neck pain or eye strain, the torso (i.e. the bust), in particular the back, lumbar pain or sciatica, the arms which tend to get tired from continuously holding the steering wheel, the legs, etc.

[0102] According to a particular aspect of this particular embodiment, the determination module 18 is further configured to:

[0103] - to associate a local comfort score to each doublet formed from a body area selectable and a seat positioning, and associate an overall comfort score with each seat positioning,

[0104] - select the positioning associated with the maximum overall comfort score, and for each selectable body area, the positioning associated with a maximum local comfort score,

[0105] the interaction module 20 being then suitable for displaying selectable information representative of each of the positions selected by the determination module, as illustrated later in relation to [Fig.2].

[0106] According to a particular aspect, such an audible or visual signal is broadcast by the interaction module 20 via one or more loudspeakers, not shown, located within the passenger compartment of the vehicle 10, and via a light indicator such as a light-emitting diode (LED) dedicated to seat positioning adjustment located near a means of manually adjusting the positioning of said seat and / or located on the dashboard of said vehicle.

[0107] In particular, the achievement of the adjustment change is specifically signaled to the passenger via a change in the color of the light signal, going from red (representing the fact that the positioning change to be applied has not been achieved) to green when it has been achieved.

[0108] Furthermore, the interaction module 20 is designed to display, via a dashboard screen, or to broadcast orally, via one or more speakers, instructions to guidance to guide and assist the passenger in achieving the positioning change to apply in order to optimize their comfort.

[0109] In the example of [Fig.1], the system 12 for optimizing the positioning of a vehicle seat 10 includes an information processing unit 22 formed for example of a memory 24 associated with a processor 26.

[0110] In the example of [Fig. 1], the retrieval module 14 and the determination module 18 are each implemented as software, or a software component, executable by the processor 26. The memory 24 is then capable of storing retrieval software configured to obtain, notably by generating and transmitting request(s) via the interaction module 20, at least one morphological parameter representative of the current passenger seated. The memory 24 is also capable of storing determination software configured for a change in seat positioning adjustment, optimizing the comfort of the current passenger, and for application during vehicle operation. The processor 26 of the information processing unit 22 is then capable of executing the retrieval software and the determination software.

[0111] In an alternative not shown, the acquisition module 14 and the determination module 18 are each implemented as a programmable logic component, such as an FPGA (Field Programmable Gate Array) or as a dedicated integrated circuit, such as an ASIC (Application Specified Integrated Circuit).

[0112] When a system 12 for optimizing the positioning of a vehicle seat 10, according to the present invention, is implemented in the form of one or more software programs, i.e., in the form of a computer program, it is also capable of being stored on a computer-readable medium (not shown). The computer-readable medium is, for example, a medium capable of storing electronic instructions and being connected to a bus of a computer system. By way of example, the readable medium is an optical disc, a magneto-optical disc, a ROM, a RAM, any type of non-volatile memory (e.g., EPROM, EEPROM, FLASH, NVRAM), a magnetic card, or an optical card. A computer program comprising software instructions is then stored on the readable medium.

[0113] The operation of the system 12 for optimizing the positioning of a vehicle seat 10 will now be explained with the help of [Fig.2], representing a flowchart of an example of a process 30 for optimizing the positioning of a vehicle seat implemented by the system 12 for optimizing the positioning of a vehicle seat previously described in relation to [Fig.1].

[0114] During an initial step 32, the vehicle seat positioning optimization system 12, via its determination module 18, implements a step

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[0135] machine learning A using a database built beforehand from at least one building block belonging to the group comprising at least: - a plurality of Ei body types for models, - a plurality E2 of predetermined positioning adjustment rules, - a plurality, not represented, of vehicle occupancy rates, - a plurality, not represented, of vehicle types, - a plurality, not represented, of distinct body areas, the first phase of machine learning A providing a predictive model M associating: - an overall comfort score for each first distinct set formed at least: - of a model-like physique of said plurality, - of a type of vehicle of said plurality, - of a seat positioning, and / or - a local comfort score for each second distinct set formed: - of a model-like physique of said plurality, - of a type of vehicle of said plurality, - of a seat positioning, - of a bodily area of ​​said plurality, In other words, thanks to machine learning, the vehicle seat positioning optimization system 12 learns for each set of input parameter(s) the seat positioning that maximizes in terms of score the comfort of a local body area, or globally the whole body. For example, to determine the local comfort score associated with the passenger's torso as a function of seat positioning, the determination module 18 determines, for each positioning, and each dummy morphology of said plurality, the angle Al between the torso and the vertical relative to the vehicle floor and the angle A2 between the thigh and the torso of the dummy morphology considered. The local comfort score associated with the STorse torso is then obtained in the following form: f(Al)*w. k(A2)*w. ç _ 7 v 7 Al + v 7 An Torso~ WL HL A i + A2 with / , respectively k, a function comparing the value, particularly in degrees, of Al, respectively A2, to predetermined minimum and maximum bounds, configurable and input to the system 12 for optimizing the positioning of a seat according to the present invention, and h'a! and H a2 of predetermined weightings configurable and input to the system 12 for optimizing the positioning of a seat according to the present invention, such as for example W. = 1 Al and H' = 2.

[0136] For example, for angle A2 between the thigh and the torso, A2min=90, A2max=120, and if A2=105 (i.e., the value in the middle of the interval [90; 120]), then k(A2=105) = 1, considering that g applies a probability density function of a normal distribution (i.e., a Gaussian distribution). In other words, it is the position of the value within this range of values ​​at the predetermined minimum and maximum bounds that influences the score. The same principle is applied to angle A1 between the torso and the vertical relative to the vehicle floor.

[0137] The overall comfort score SG corresponds in particular to a weighted average of the local comfort scores obtained. For example, if we consider seven distinct body areas whose local comfort score was obtained similarly to the local comfort score associated with the torso STo as described above, such as: the shins, associated with the local comfort score STib, the feet, associated with the local comfort score SP, the thighs associated with the local comfort score Sc, the thigh support associated with the local comfort score SA-c, the head associated with the local comfort score STe, the torso associated with the local comfort score STo, the arms associated with the local comfort score SB, the overall comfort score SG is obtained according to the following formula:

[0138] ç = + (STih^vTU>) + (SP*wP) + (SC*H'C) + (^,c^,c) + (STe*wTe) + (SB*wB) H- + Wp + 4- 4- + IVp

[0139] with wTo^ wtu^ wp, wc, wa-c> wTc” vv b predetermined, configurable and input weights of the system 12 for optimizing the positioning of a seat according to the present invention.

[0140] Once the model M is obtained at the end of the machine learning step 32, the method 30 comprises, according to the present invention, a step 34 during which the determination module 18 optimizes the positioning of the seat to provide a current passenger, during operation of said vehicle considered, according to at least one representative morphological parameter of said current passenger, for each body area, the positioning associated with the maximum local comfort score and / or the positioning associated with the maximum global comfort score, the optimization step 34 being capable of being repeated during uninterrupted operation of said vehicle considered, and / or in the event of a change of passenger and / or occupancy rate of said vehicle, and / or in the event of a stop / restart of said vehicle.

[0141] In other words, during this step 34, the determination module 18 determines the change in positioning adjustment to be applied to meet the comfort needs of the current passenger.

[0142] Then, during a step 36, the interaction module 20 of the vehicle seat positioning optimization system 12 displays a plurality of zones distinct bodily pressures to be relieved via the change in seat positioning adjustment, each body zone being selectable by the current passenger, for example by touch pressure or by means of a slider.

[0143] As shown in [Fig.2], five zones Zb Z2, Z3, Z4 and G of the screen are displayed for selection by the current passenger user. Zone Z1 corresponds in particular to the proposed seat positioning optimizing (i.e. maximizing) head comfort, zone Z2 to the proposed seat positioning optimizing torso comfort, zone Z3 to the proposed seat positioning optimizing leg comfort, zone Z4 to the proposed seat positioning optimizing arm comfort, and zone G to the proposed seat positioning optimizing overall passenger comfort.

[0144] During a step 38, the seat positioning optimization system 12 detects the area of ​​the screen of the interaction module 20 selected by the passenger, selects the seat positioning adjustment change associated with this passenger selection and automatically modifies, via the adjustment module 16, the seat positioning to achieve the adjustment change to be applied, or signals to the current passenger this seat positioning adjustment change to be applied, via the interaction module 20 with the current passenger, and guides him to manually modify the seat positioning to achieve the desired adjustment change, via a predetermined audible or visual signal representative of the achievement of the adjustment change.

[0145] In other words, according to the example in [Fig.2], the system 12 for optimizing the positioning of a seat is capable of simultaneously offering five distinct changes in seat positioning adjustment according to the desired local or global comfort.

[0146] Fig. 3 is a schematic representation of the positions of the same mannequin optimizing overall comfort or the comfort of specific body areas, with the height H in mm relative to the floor of the vehicle 10 on the ordinate, and the distance P in mm relative to the front end of the passenger compartment, with abscissa 0 mm, along the longitudinal axis of the vehicle 10 on the abscissa.

[0147] In [Fig. 3], a zone 42 defined by two lines 42A and 42B specific to each type of vehicle 10 is also shown. This zone 42 defines an additional constraint optionally taken into account in determining the change in seat positioning adjustment S associated with a maximum local comfort score or a maximum global comfort score, which must also ensure that each passenger 46, represented here by a male dummy with a height of 1.83 m (1830 mm), has his eye 48 within zone 42.

[0148] Optionally, determining the change according to the present invention The seat positioning adjustment S also takes into account the location of the steering wheel 50 specific to each type of vehicle 10, as well as the distance of the passenger represented here by a mannequin to the trim 52 of the passenger compartment dashboard.

[0149] As illustrated by [Fig.3], depending on the body area whose comfort one seeks to optimize, distinct passenger postures are to be favoured.

[0150] In particular, on [Fig.3] are respectively represented the postures which allow to optimize the comfort of the zone Zi corresponding to the head, the zone Z2 corresponding to the torso, the zone Z3 corresponding to the legs, the zone Z4 corresponding to the arms, the zone G optimizing the overall comfort of the passenger.

[0151] Thus, since each passenger has specific needs during the journey, according to the present invention, as illustrated in [Fig. 3], different postural positions adapted to the particular needs of the passenger are offered. If the passenger has problems in a specific part of the body, the system according to the present invention is designed to offer a position that maximizes the comfort score related to that specific part of the body.

[0152] It should be noted that according to the present invention, each proposed change in the positioning adjustment of the seat S is based on the particular morphology of the passenger obtained by the aforementioned obtaining module 14, this morphology being an input to the optimization system according to the present invention, as well as the type of vehicle, and the occupancy rate.

[0153] The [Fig.4] is a representation in the form of a set of 56 histograms of an overall comfort score and local comfort scores respectively associated with distinct body areas, for each positioning maximizing one of these scores, the value of each score being here between 0 and 1.

[0154] According to a particular aspect of the present invention, the present invention, the determination module 18 is configured to determine, at each iteration, N+l scores, comprising N local scores associated with each body area whose comfort optimization is sought, and an overall score, each iteration being instantiated at the request of the passenger, and / or periodically according to a predetermined period from the start of the vehicle 10, for example every hour.

[0155] On [Fig.4], histogram 58 corresponds to the five scores obtained for a first seat positioning which maximizes the overall score of zone G optimizing the overall passenger comfort, these five scores including the overall score of zone G and four local scores of: zone Zi corresponding to the head, zone Z2 corresponding to the torso, zone Z3 corresponding to the legs, zone Z4 corresponding to the arms.

[0156] Histogram 60 corresponds to the five scores obtained for a second seat positioning which this time maximizes the local score of the body zone Zi corresponding to the head relative to the four other scores including the overall score of zone G optimizes overall passenger comfort and the three local scores of zone Z2 correspond to the torso, zone Z3 to the legs, zone Z4 to the arms.

[0157] Histogram 62 corresponds to the five scores obtained for a third seat positioning which this time maximizes the local score of the body zone Z2 corresponding to the torso in relation to the four other scores including the global score of the zone G optimizing the overall comfort of the passenger and the three local scores of the zone Zi corresponding to the head, the zone Z3 corresponding to the legs, the zone Z4 corresponding to the arms.

[0158] Histogram 64 corresponds to the five scores obtained for a fourth seat positioning which this time maximizes the local score of the body zone Z3 corresponding to the legs compared to the four other scores including the global score of zone G optimizing the overall comfort of the passenger and the three local scores of zone Zi corresponding to the head, zone Z2 corresponding to the torso, zone Z4 corresponding to the arms.

[0159] Histogram 66 corresponds to the five scores obtained for a fifth seat positioning which this time maximizes the local score of the body zone Z4 corresponding to the arms in relation to the four other scores including the global score of the zone G optimizing the overall comfort of the passenger and the three local scores of the zone Zi corresponding to the head, the zone Z2 corresponding to the torso, the zone Z3 corresponding to the legs.

[0160] A person skilled in the art will understand that the invention is not limited to the embodiments described, nor to the particular examples of the description, the embodiments and variants mentioned above being capable of being combined with each other to generate new embodiments of the invention.

[0161] The present invention thus makes it possible to improve the seating comfort of each passenger in a personalized way, because it is adapted to meet each individual comfort need, localized or global and / or to relieve specific body areas in a personalized way.

[0162] In other words, the present invention allows for relaxation that can be focused locally on specific body parts, such as the arms, back, vision, torso, legs, etc.

[0163] Furthermore, by means of the machine learning implemented, the present invention is suitable for avoiding (i.e. preventing), for a passenger user having problems with a specific part of the body and likely to experience chronic pain during long-distance journeys, the pain before it occurs, and avoiding the associated muscle tension.

[0164] Thus, the present invention makes it possible to avoid the health risks associated with the fact to remain seated in the same position for a prolonged period of time.

Claims

Demands

1. A system (12) for optimizing the positioning of a vehicle seat (10), comprising: - a module (14) for obtaining and saving at least one representative morphological parameter of a typical passenger seated in the seat; - a seat positioning adjustment module (16), the adjustment module comprising at least one sensor, located within the vehicle, and configured to control the seat positioning; - a determination module (18) configured to determine the seat positioning adjustment to be applied at least according to said at least one representative morphological parameter of the current passenger; characterized in that the optimization system is configured to: - determine, using the optimization system's determination module, at least one change in seat positioning adjustment, optimizing the comfort of the current passenger, and to be applied during vehicle operation, - automatically modify, via the adjustment module, the seat positioning to achieve the required adjustment change, the system further comprising an interaction module configured to display a plurality of distinct body areas to be relieved via the seat positioning adjustment change, each body area being selectable by the current passenger, and wherein the determination module is configured to determine the seat positioning adjustment change to be applied also based on at least one body area to be relieved previously selected by the current passenger, or - signal to the current passenger the change in seat positioning adjustment to be applied, via said interaction module (20) of the system with the current passenger, and guide the passenger to manually change the seat positioning to achieve the change in adjustment, via a predetermined audible or visual signal representative of achieving the change in adjustment.

2. A system according to claim 1, wherein the change in positioning adjustment is determined from the initial positioning adjustment of the seat before the vehicle starts, and / or from a positioning adjustment initially selected by the passenger currently, via the interaction module, before the vehicle starts.

3. System according to claim 1 or 2, wherein the determination module is configured to determine the change in seat positioning adjustment also as a function of the uninterrupted duration of vehicle driving by the current passenger.

4. A system according to any one of the preceding claims, wherein the determination module is configured to determine the change in seat positioning adjustment to be applied, by machine learning, from at least one input element belonging to the group comprising at least: - said at least one morphological parameter representative of the current passenger; - the vehicle model; - at least one piece of information representative of the vehicle occupancy rate.

5. System according to claim 4, wherein the machine learning uses a database constructed beforehand from at least one building element belonging to the group comprising at least: - a plurality of mannequin morphologies, - a plurality of predetermined positioning adjustment rules, - a plurality of vehicle occupancy rates, - a plurality of vehicle types, - a plurality of distinct body areas.

6. A system according to any one of the preceding claims, wherein the determination module is further configured to: - associate a local comfort score with each doublet formed by a selectable body zone and a seat positioning, and associate an overall comfort score with each seat positioning, - select the positioning associated with the maximum overall comfort score, and for each selectable body zone, the positioning associated with a maximum local comfort score, and wherein the interaction module is suitable for displaying selectable information representative of each of the positionings selected by the determination module.

7. Vehicle (10) comprising a system (12) for optimizing the positioning of a seat according to any one of the preceding claims.

8. previous. Method (30) for optimizing the positioning of a vehicle seat, the method being adapted to be implemented by the seat positioning optimization system according to any one of the preceding claims 1 to 6, the determination module being configured to determine an optimal seat positioning adjustment to be applied based on at least one representative morphological parameter of the average passenger, the method comprising at least: - a machine learning step using a database previously constructed from at least one building block belonging to the group comprising at least: - a plurality of model body types, - a plurality of predetermined positioning adjustment rules, - a plurality of vehicle occupancy rates, - a plurality of vehicle types, - a plurality of distinct body areas, the first phase of machine learning providing a predictive model associating: - an overall comfort score for each first distinct set formed at least: - a mannequin-like morphology of said plurality, - a type of vehicle of said plurality, - a seat positioning, and / or - a local comfort score for each second distinct set formed by: - ​​a mannequin morphology of said plurality, - of a type of vehicle of said plurality, - of a seat positioning, - of a bodily area of ​​said plurality, - a step for optimizing the positioning of a seat in a given vehicle, configured to provide a typical passenger, during the operation of said vehicle, with the positioning associated with the maximum local comfort score and / or the positioning associated with the maximum overall comfort score, based on at least one representative morphological parameter of said passenger, for each body area, the optimization step being capable of being repeated during operation.

9. uninterrupted operation of said vehicle in question, and / or in the event of a change of passenger and / or occupancy rate of said vehicle, and / or in the event of a stop / restart of said vehicle. Computer program comprising software instructions which, when executed by a computer, implement, at least in part, a method for optimizing the positioning of a seat according to claim 8.

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