FR3122009A1 - Method, device and system for predicting a maintenance operation for a vehicle - Google Patents

Abstract

A vehicle maintenance prediction method and device are disclosed. To this end, first data representative of the use of the vehicle (10) are received from a remote database (101). Second data representative of a user's schedule of the vehicle (10) and third data representative of a current state of the vehicle (10) are also received. A set of information representative of a current context for the vehicle is determined from the second and third data. At least one piece of information representative of a maintenance prediction of one or more components of the vehicle is rendered, for example displayed, according to a result of an analysis of the set of information in relation to the first data. Figure for abstract: Figure 1

Description

Method, device and system for predicting a maintenance operation for a vehicle

The invention relates to methods, devices and data communication systems for vehicles, in particular automobiles, for example autonomous. The invention also relates to a method and a device for recommending a vehicle, for example for recommending a point of interest or a route to arrive at a point of interest.

Technology background

Contemporary vehicles are made up of a large number of components or organs, each of these components requiring maintenance, the frequency of which depends in particular on the component.

When the driver of a vehicle is confronted with a defect or breakdown of one or more components of his vehicle, the latter must then contact a specialized center to determine whether the breakdown or defect observed requires a maintenance operation. corrective action to correct the fault or defect after the latter has appeared. Such corrective maintenance is most often accompanied by an intervention or repair in a garage, for example. Such corrective maintenance is synonymous with the costs generated by the corrective maintenance and the inconvenience caused by the immobilization of the vehicle for a period sometimes going up to several days, which is particularly inconvenient when the driver of the vehicle has planned a long journey, for example to go on vacation.

It therefore appears necessary to find solutions to limit the risk of breakdown or immobilization of the vehicle.

An object of the present invention is to solve at least one of the drawbacks of the prior art.

An object of the present invention is to improve the prevention of breakdowns or defects in the component(s) of a vehicle.

According to a first aspect, the invention relates to a method for predicting maintenance for a vehicle, the method being implemented by at least one processor, the method comprising the following steps:

- reception of first data representative of use of the vehicle from a remote database, second data representative of a timetable of a user of the vehicle and third data representative of a current state of the vehicle;

- determination of information representative of a current context for the vehicle from the second data and the third data;

- analysis of information in relation to the first data;

- rendering of at least one item of information representative of a maintenance prediction of at least one component of the vehicle according to a result of the analysis.

According to a variant, the rendering comprises a display of at least one recommendation via a man-machine interface implemented in the vehicle.

According to another variant, the first data belong to a first set of data comprising:

- data representative of a type of trip associated with each trip traveled with the vehicle;

- data representative of journey time associated with each journey traveled with the vehicle;

- data representative of a date associated with each journey made with the vehicle;

- data representative of a distance traveled for each trip traveled with the vehicle;

- data representative of a type of road taken for each trip taken with the vehicle.

According to an additional variant, the second data belong to a second set of data comprising:

- data representing a date associated with each event recorded in the timetable;

- data representative of a duration associated with each event recorded in the timetable;

- data representative of a reason associated with each event recorded in the timetable;

- data representative of a destination associated with each event recorded in the timetable.

According to yet another variant, the third data belong to a third set of data comprising:

- data representative of a total distance traveled by the vehicle;

- data representative of a type of maintenance carried out on at least one component of the vehicle;

- data representative of a time instant of performance of maintenance on at least one component of the vehicle;

- data representative of the current condition or wear of at least one component of the vehicle.

According to an additional variant, the analysis is implemented by a neural network.

According to a second aspect, the invention relates to a maintenance prediction device for a vehicle, the device comprising a memory associated with a processor configured for the implementation of the steps of the method according to the first aspect of the invention.

According to a third aspect, the invention relates to a vehicle, for example of the automotive type, comprising a device as described above according to the second aspect of the invention.

According to a fourth aspect, the invention relates to a system comprising the vehicle as described above according to the third aspect of the invention and a remote device comprising a database, the remote device being connected in communication with the vehicle according to a wireless connection.

According to a fifth aspect, the invention relates to a computer program which comprises instructions adapted for the execution of the steps of the method according to the first aspect of the invention, this in particular when the computer program is executed by at least one processor.

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

According to a sixth aspect, the invention relates to a computer-readable recording medium on which is recorded a computer program comprising instructions for the execution of the steps of the method according to the first aspect of the invention.

On the one hand, the recording medium can be any entity or device capable of storing the program. For example, the medium may comprise a storage means, such as a ROM memory, a CD-ROM or a ROM memory of the microelectronic circuit type, or even a magnetic recording means or a hard disk.

On the other hand, this recording medium can also be a transmissible medium such as an electrical or optical signal, such a signal being able to be conveyed via an electrical or optical cable, by conventional or hertzian radio or by self-directed laser beam or by other ways. The computer program according to the invention can in particular be downloaded from an Internet-type network.

Alternatively, the recording medium may be an integrated circuit in which the computer program is incorporated, the integrated circuit being adapted to execute or to be used in the execution of the method in question.

Brief description of figures

Other characteristics and advantages of the invention will emerge from the description of the non-limiting embodiments of the invention below, with reference to the appended figures 1 to 3, in which:

schematically illustrates a communication environment of a vehicle, according to a particular embodiment of the present invention;

schematically illustrates a maintenance prediction device for the vehicle of the , according to a particular embodiment of the present invention;

illustrates a flowchart of the different steps of a maintenance prediction method for the vehicle of the , according to a particular embodiment of the present invention.

A method, a device and a maintenance prediction system for a vehicle will now be described in the following with reference to FIGS. 1 to 3. The same elements are identified with the same reference signs throughout the description which go follow.

schematically illustrates a communication environment for a vehicle 10, according to a particular and non-limiting embodiment of the present invention.

There illustrates a communication environment 1 for a vehicle 10.

The vehicle 10 corresponds for example to a vehicle with a combustion engine, with electric motor(s) or else a hybrid vehicle with a combustion engine and one or more electric motors. The vehicle 10 thus corresponds for example to a land vehicle, for example an automobile, a truck, a bus, a motorcycle. Finally, the vehicle 10 corresponds to an autonomous vehicle or not, that is to say a vehicle circulating according to a determined level of autonomy or under the total supervision of the driver.

The vehicle 10 also advantageously embeds a communication system configured to communicate with one or more remote devices 101, 11 via an infrastructure of a wireless communication network. The remote device 101 advantageously corresponds to a device configured to process data, for example data stored in the memory of the remote device 101 and/or data received from the vehicle 10. The remote device 101 corresponds for example to a "cloud" server 100, the remote device 101 hosting for example in memory a database comprising a set of data representative of the preferences of a user of the vehicle 10, for example the owner or the driver of the vehicle 10.

The remote device 11 corresponds for example to a mobile communication device 11 such as a smart phone (“smartphone”) or a tablet. One or more mobile applications are advantageously installed on the mobile communication device 11, this or these mobile applications collecting for example data on the user and transmitting this data or part of it to the remote device 101 and/or of the vehicle 10.

The communication system of the vehicle 10 comprises for example one or more communication antennas connected to a telematics control unit, called TCU (from the English “Telematic Control Unit”), itself connected to one or more computers of the on-board system of the vehicle 10, for example an IVI computer (from the English “In-Vehicle Infotainment” or in French “Infodivertissement on-board”), which IVI computer controls the infotainment system of the vehicle 10 and the data to be rendered in the vehicle 10 (for example by display on a display screen embedded in the vehicle 10). The antenna(s), the TCU unit and the computer(s) form, for example, a multiplexed architecture for performing various services useful for the proper operation of the vehicle and for assisting the driver and/or the passengers of the vehicle in controlling the vehicle 10, for example by displaying regulatory speed information on a display device on board the vehicle 10. The computer(s) and the unit TCU communicate and exchange data with each other via one or more computer buses , for example a communication bus of the CAN data bus type (from the English “Controller Area Network” or in French “Réseau de Contrôleurs”), CAN FD (from the English “Controller Area Network Flexible Data-Rate” or in French “Flexible Data Rate Controller Network”), FlexRay (according to ISO 17458 standard) or Ethernet (according to ISO/IEC 802-3 standard).

The mobile communication infrastructure allowing wireless data communication between the vehicle 10 and the remote data processing device 101 and/or the mobile communication device 11 comprises, for example, several communication equipment items 110 of the relay antenna type (network cellular) or roadside unit, called UBR. In a mode of communication using such a network architecture, the data is for example transmitted by the vehicle 10 to the remote device 101 and/or to the mobile communication device 11 via a relay antenna 110 (the antenna 110 being for example connected to the " cloud” 100 via a wired connection).

The wireless communication system allowing the exchange of data between the vehicle 10 and the remote device 101 corresponds for example to:

- a V2I vehicle-to-infrastructure communication system, for example based on the 3GPP LTE-V or IEEE 802.11p standards of ITS G5; Or

a communication system of the cellular network type, for example a network of the LTE type (from the English “Long-Term Evolution” or in French “Long-term Evolution”), LTE-Advanced (or in French LTE-advanced) 4G or 5G LTE; Or

- A WiFi type communication system according to IEEE 802.11, for example according to IEEE 802.11n or IEEE 802.11ac.

According to a variant embodiment, the mobile communication device 11 and the vehicle exchange data according to a direct wireless connection, that is to say without going through the network infrastructure. The wireless connection is for example of the Bluetooth® or Wifi Direct® type.

According to a variant embodiment, the vehicle 10 also carries a satellite geolocation system configured to determine the current position of the vehicle 10, the vehicle 10 carrying for this purpose a receiver of a GPS type system (from the English " Global Positioning System” or in French “Global Positioning System”) or Galileo for example in communication with a computer of the on-board system of the vehicle 10.

The database 101 hosts or stores a first set of first data associated with the user, for example data corresponding to or describing a profile of use of the vehicle by this user, for example a profile of driving of the vehicle by this user . This first set of first data comprises for example all or part of the following data, according to all possible combinations:

- data representative of the routes followed by the vehicle 10 and/or of the journeys made by the vehicle 10;

- data representative of the destinations entered into the navigation system of the vehicle 10 or of the mobile communication device 11;

- Time information associated with the journeys made, for example the date of the journey and/or the duration of the journey;

- kinematic data (for example the speed) associated with the journeys made;

- data representative of places and break times;

- data representative of a type of journey associated with each journey traveled with the vehicle, the type of journey comprising for example the types 'professional journey', 'personal journey', 'family journey', 'holiday journey', etc ;

- data representative of a distance traveled for each trip traveled with the vehicle 10;

- data representative of a type of road taken for each route traveled with the vehicle 10, the type of road comprising for example the types “motorway”, “fast lane”, “national road”, “city”, etc. ;

- any data describing the behavior of the user when using the vehicle 10.

These first data are for example received from the vehicle 10 as the vehicle 10 and/or the mobile communication device 11 are used (for example the data on the journeys when the mobile communication device 11 comprises an application used as a navigation system by the user).

The communication environment 1 further comprises one or more entities or infrastructures in charge of the maintenance of vehicles 12, for example a dealership or generally a car garage, transmitting information or data via the Internet network, for example via the “cloud” 100. At least part of this information is received by the remote device 101, by the mobile communication device 11 and/or by the vehicle 10. The information or data transmitted by the entity 12 includes for example:

- data relating to maintenance operations of the vehicle 10, for example the result of a check or a diagnosis of the vehicle 10, the change of certain parts or certain components (for example the tires, the battery, the brakes) ;

- data relating to the dates on which the maintenance operations were carried out;

- data relating to the condition of the vehicle during these maintenance operations, such as the mileage of the vehicle during the maintenance operation;

- the location of the entity that carried out the maintenance operation.

According to a variant embodiment, the database also hosts or stores data representative of the preferences of the user, these data being for example collected from the mobile communication device 11 (corresponding for example to Internet searches), from applications social networks, applications for playing audio and/or video media, etc.

The first set of data and the data or information relating to the maintenance operations are for example analyzed and processed by applying one or more automatic learning methods to them, also called machine learning methods. , for example by relying on a neural network.

Such methods make it possible in particular to classify the data received and to determine the profile of use of the vehicle by this user. Such methods also make it possible to cross-reference the first data with the vehicle maintenance data to establish a relationship between the maintenance operations and the use made of the vehicle 10.

A maintenance prediction process for the vehicle 10 is advantageously implemented by the vehicle 10 (that is to say by one or more devices on board the vehicle 10, for example one or more computers) and/or by a system comprising the vehicle 10 and one or more remote devices such as the device 101 and/or the mobile communication device 11 connected in communications to the vehicle 10 via one or more wireless connections.

In a first operation, the vehicle 10 receives the first data representative of the use made of the vehicle 10 by the user. This first data is advantageously received from the remote device 101, for example after transmission of a request by the vehicle 10 to the remote device 101. According to a variant embodiment, the first data is received automatically, without a request, for example at intervals regular or each time the vehicle 10 is started, for example.

A set of second data representative of the timetable are also received by the vehicle 10. This second data is for example received from the mobile communication device 11, such second data being for example stored in the memory of the mobile communication device 11 and/or on a “cloud” server 100. Such second data is for example entered by the user via the man-machine interface associated with a mobile application of the diary type.

The second data includes for example all or part of the following data forming a second set of data, according to all possible combinations:

- data representing a date associated with each event recorded in the timetable; an event advantageously corresponds to an entry in the diary, a type or a reason (for example 'meeting', 'holidays', 'appointment with a doctor', etc.) being associated with each event;

- data representative of a duration associated with each event recorded in the timetable;

- data representative of a reason associated with each event recorded in the timetable;

- data representative of a destination associated with each event recorded in the timetable.

A set of third data representative of the current state of the vehicle 10 are also received by the vehicle 10, for example by one or more computers of the on-board system of the vehicle 10. These third data are for example received from one or more sensors and /or on-board systems in the vehicle.

The third data includes for example all or part of the following data forming a third set of data, according to all possible combinations:

- data representative of a total distance traveled by the vehicle, corresponding for example to the current mileage of the vehicle 10; and or

- data representative of a type of maintenance carried out on at least one component of the vehicle, such data being for example stored in the memory of a computer or received from a remote device of the "cloud" 100; the type of maintenance makes it possible to identify the operation carried out and/or the parts or components concerned (for example oil change, change of tyres, brake pads, battery, etc.); and or

- data representative of a time instant of performance of maintenance on at least one component of the vehicle, such data being for example stored in the memory of a computer or received from a remote device of the "cloud" 100;

- data representative of the current state or the wear of one or more organs or one or more parts of the vehicle (for example the brakes, the tires, the battery, the oil level), these data being for example received from ad hoc sensors.

In a second operation, the vehicle 10 determines one or more items of information representative of the current context of the vehicle 10 from the second and third data received or obtained in the first operation.

The information describing the context of the current path includes for example:

- one or more information relating to a journey to be made determined from the second data of the timetable. For example, if the timetable contains an event of the 'holiday' or 'appointment' type, it is determined that a distance will soon be covered by the vehicle 10, for example from location information associated with the event 'holidays' or 'appointment'; and or

- one or more pieces of information describing the state of the vehicle 10 at the time of carrying out a route determined from the second time use information, the state of the vehicle 10 being determined from the third data.

According to a variant embodiment, the information describing the current context also includes one or more of the following information:

- information representative of the position of the vehicle, for example obtained from the geolocation or navigation system on board the vehicle 10, or from a geolocation or navigation system installed in the mobile communication device 11;

- information representative of a route or route followed by the vehicle, for example obtained from the geolocation or navigation system on board the vehicle 10, or from a geolocation or navigation system installed in the mobile communication device 11;

- time information, for example obtained from a vehicle clock.

In a third operation, the vehicle 10 analyzes the current context information of the vehicle obtained in the second operation in relation to the first data received in the first operation. The analysis is for example implemented by a neural network implemented by one or more computers of the on-board system of the vehicle 10.

The analysis includes for example a crossing between the context information and the first data relating to the use of the vehicle 10.

Such a crossing thus makes it possible to determine whether a maintenance operation is to be planned according to the current context of the vehicle, knowing the habits of use of the vehicle.

For example, if a holiday type event is detected, the current date is in winter and the first usage data indicate that the user usually goes to the mountains in winter, the vehicle 10 predicts for example that a snow chain type is to be expected or that a change of tires to fit snow or winter tires is to be expected, which causes the process to go to the fourth operation.

According to another example, if an event of the long trip type is detected from the second data, and that the difference between the current mileage of the vehicle (detected from the third data) and the mileage of the vehicle 10 at which the last control or the last oil change is close to a value corresponding to the frequency at which the user usually carries out a control or an oil change of the vehicle 10, then the vehicle 10 predicts that a control or an oil change is to be carried out before the associated date to the event, which causes the process to go to the fourth operation.

If no prediction is made following the analysis, the process ends with the third operation.

In a fourth operation, depending on the result of the analysis implemented in the third operation, one or more recommendations are generated or rendered, intended for the user to warn the user that one or more maintenance operations have been one or more components or components of the vehicle 10 are suggested or recommended.

The rendering of such a recommendation is advantageously generated by the IVI computer in charge of the vehicle's infotainment system.

The rendering corresponds for example to the rendering of a voice message by one or more loudspeakers of the vehicle 10 and/or by the loudspeaker of the mobile communication device 11 when the latter is on board the vehicle 10 and connected to the latter. .

According to another example, the rendering corresponds to a display of graphic content on a screen on board the vehicle and/or on the screen of the mobile communication device 11 when the latter is on board the vehicle 10 and connected to the latter. . According to this example, a text explaining the maintenance operation to be carried out or the recommendation determined from the analysis is displayed on a screen via a man-machine interface (known as HMI), for example the HMI managed by the IVI computer. According to a variant, a graphic icon illustrating the maintenance operation to be carried out is displayed, instead of the text or in addition to the text. According to a variant embodiment, one or more additional pieces of information (also called metadata) are also displayed in addition to the icon and/or the text, these additional pieces of information comprising, for example, a deadline for carrying out the operation, a proposal for a nearby car garage that can perform the operation, etc.

Such a process thus makes it possible to plan or predict maintenance operations according to the real situation of the user and of the vehicle, taking into account a use profile generated as the vehicle 10 is used by the user. user (for example during a so-called learning period). This makes it possible to avoid a breakdown or a problem on the vehicle 10, knowing the use that will be made of the vehicle 10 in the future from the second data on the use of time of the user of the vehicle 10.

schematically illustrates a device 2 configured to predict one or more maintenance operations for the vehicle 10, according to a particular and non-limiting embodiment of the present invention. The device 2 corresponds for example to a device on board the vehicle 10, for example a computer. According to another example, the device 2 corresponds to a calculation or data processing device, for example the remote device 101 and/or the mobile communication device 11.

The device 2 is for example configured for the implementation of the operations described with regard to the and/or the steps of the process described with regard to the . Examples of such a device 2 include, but are not limited to, on-board electronic equipment such as a vehicle's on-board computer, an electronic computer such as an ECU ("Electronic Control Unit"), a telematics control unit, known as a TCU (Telematic Control Unit), a smartphone, a tablet, a laptop computer, a server, or a combination of several of the devices listed above. The elements of device 2, individually or in combination, can be integrated in a single integrated circuit, in several integrated circuits, and/or in discrete components. The device 2 can be made in the form of electronic circuits or software (or computer) modules or else a combination of electronic circuits and software modules.

The device 2 comprises one (or more) processor(s) 20 configured to execute instructions for carrying out the steps of the method and/or for executing the instructions of the software or software embedded in the device 2. The processor 20 can include integrated memory, an input/output interface, and various circuits known to those skilled in the art. The device 2 further comprises at least one memory 21 corresponding for example to a volatile and/or non-volatile memory and/or comprises a memory storage device which can comprise volatile and/or non-volatile memory, such as EEPROM, ROM, PROM, RAM, DRAM, SRAM, flash, magnetic or optical disk.

The computer code of the on-board software or software comprising the instructions to be loaded and executed by the processor is for example stored on the memory 21.

According to various particular embodiments, the device 2 is coupled in communication with other similar devices or systems and/or with communication devices, for example a TCU (from the English “Telematic Control Unit” or in French “Unité Telematics Control"), for example via a communication bus or through dedicated input/output ports.

According to a particular and non-limiting embodiment, the device 2 comprises a block 22 of interface elements for communicating with external devices, for example a remote server or the “cloud”, a TCU unit. Block 22 interface elements include one or more of the following interfaces:

- RF radio frequency interface, for example of the Bluetooth® or Wi-Fi® type, LTE (from English "Long-Term Evolution" or in French "Evolution à long terme"), LTE-Advanced (or in French LTE-advanced );

- USB interface (from the English "Universal Serial Bus" or "Universal Serial Bus" in French);

- HDMI interface (from the English “High Definition Multimedia Interface”, or “Interface Multimedia Haute Definition” in French);

- LIN interface (from English “Local Interconnect Network”, or in French “Réseau interconnecté local”).

Data are for example loaded to the device 2 via the interface of block 22 using a Wi-Fi® network such as according to IEEE 802.11, an ITS G5 network based on IEEE 802.11p or a mobile network such as a 4G network (or LTE Advanced according to 3GPP release 10 – version 10) or 5G, in particular an LTE-V2X network.

According to another particular embodiment, the device 2 comprises a communication interface 23 which makes it possible to establish communication with other devices (such as other computers of the on-board system or other servers) via a communication channel 230. The communication interface 23 corresponds for example to a transmitter configured to transmit and receive information and/or data via the communication channel 230. The communication interface 23 corresponds for example to a CAN-type wired network ( from the English "Controller Area Network" or in French "Réseau de Contrôleurs"), CAN FD (from the English "Controller Area Network Flexible Data-Rate" or in French "Réseau de Contrôleurs à Flow de Data Flexible"), FlexRay (standardized by ISO 17458) or Ethernet (standardized by ISO/IEC 802-3).

According to an additional particular embodiment, the device 2 can provide output signals to one or more external devices, such as a display screen, one or more loudspeakers and/or other peripherals (projection system ) via respectively suitable output interfaces. According to a variant, one or the other of the external devices is integrated into the device 2. The display screen corresponds for example to a screen, touchscreen or not.

illustrates a flowchart of the different steps of a vehicle maintenance prediction method, according to a particular and non-limiting embodiment of the present invention. The method is for example implemented by a device on board the vehicle 10 or by the device 2 of the .

In a first step 31, the vehicle (or one or more computers of the vehicle) receives first data representative of the use of the vehicle from a remote database, second data representative of a schedule of a user of the vehicle and third data representative of a current state of the vehicle.

In a second step 32, the vehicle (or one or more vehicle computers) determines information representative of a current context for the vehicle from the second data and the third data received in the first step 31.

In a third step 33, the vehicle (or one or more vehicle computers) analyzes the information determined in the second step 32 in relation to the first data received in the first step 31

In a fourth step 34, the vehicle (or one or more computers of the vehicle) renders at least one item of information representative of a maintenance prediction of at least one component of the vehicle.

According to a variant embodiment, the variants and examples of the operations described in relation to the apply to the process steps of the .

Of course, the invention is not limited to the embodiments described above but extends to a method for recommending one or more maintenance operations to be carried out which would include secondary steps without thereby departing from the scope of the present invention. The same would apply to a device configured for the implementation of such a method.

The invention also relates to a vehicle, for example an automobile or more generally an autonomous land motor vehicle, comprising the device 2 of the .

The invention also relates to a system comprising the device 2 of the (or a set of devices 2) on board a vehicle and a remote data processing device, for example the remote device 101, the device(s) 2 being connected in wireless communication with the remote data processing device .

Claims (10)

Maintenance prediction method for vehicle (10), said method being implemented by at least one processor, said method comprising the following steps:
- reception (31) of first data representative of use of said vehicle (10) from a remote database (101), second data representative of a time use of a user of said vehicle (10) and third data representative of a current state of said vehicle (10);
- determination (32) of information representative of a current context for said vehicle (10) from said second data and said third data;
- analysis (33) of said information in relation to said first data;
- rendering (34) of at least one item of information representative of a maintenance prediction of at least one component of said vehicle (10) as a function of a result of said analysis. A method according to claim 1, wherein said rendering comprises displaying at least one recommendation via a man-machine interface implemented in said vehicle (10). Method according to claim 1 or 2, wherein said first data belongs to a first set of data comprising:
- data representative of a type of journey associated with each journey traveled with said vehicle (10);
- data representative of journey time (10) associated with each journey traveled with said vehicle (10);
- data representative of a date associated with each journey traveled with said vehicle (10);
- data representative of a distance traveled for each trip traveled with said vehicle (10);
- data representative of a type of road taken for each journey traveled with said vehicle (10). Method according to one of Claims 1 to 3, for which the said second data belong to a second set of data comprising:
- data representative of a date associated with each event recorded in said timetable;
- data representative of a duration associated with each event recorded in said timetable;
- data representative of a pattern associated with each event recorded in said timetable;
- data representative of a destination associated with each event recorded in said timetable. Method according to one of Claims 1 to 4, for which the said third data belong to a third set of data comprising:
- data representative of a total distance traveled by said vehicle (10);
- data representative of a type of maintenance carried out on at least one member of said vehicle (10);
- data representative of a time instant of performance of maintenance on at least one member of said vehicle (10);
- data representative of the current state or wear of said at least one component of said vehicle (10). Method according to one of Claims 1 to 5, for which the said analysis is implemented by a neural network. Computer program comprising instructions for implementing the method according to any one of the preceding claims, when these instructions are executed by a processor. Maintenance prediction device (2) for a vehicle, said device (2) comprising a memory (21) associated with at least one processor (20) configured for the implementation of the steps of the method according to any one of Claims 1 to 6. Vehicle (10) comprising the device (2) according to claim 8. A system comprising the vehicle according to claim 9 and a remote device (101) comprising a database, the remote device being linked in communication with said vehicle via a wireless connection.