Determining the similarity of use of motor vehicles

Abstract

The invention relates to a method for determining a similarity value in use between a first motor vehicle (10) and a second motor vehicle (20). The invention also relates to a computer system (100) implementing such a method. Figure for the abstract: 1

Description

Title of the invention: Determination of the similarity of use of motor vehicles Technical field of the invention

[0001] The present invention relates to the field of computer tools designed to facilitate after-sales monitoring of motor vehicles. The invention relates in particular to a method for determining, by a computer system, a usage similarity value between a first motor vehicle and a second motor vehicle. The invention further relates to a computer system that implements such a method. The invention is applicable to motor vehicles, in particular motorized land vehicles such as cars. Prior art

[0002] It is known that car manufacturers are constantly seeking to improve vehicle quality, particularly to minimize the risk that potential breakdowns could compromise the safety of their users. To this end, computer tools for after-sales vehicle monitoring are generally available, notably for recording dealership visits caused by vehicle breakdowns. However, these tools remain relatively basic insofar as they generally do not allow for the precise determination of vehicle usage, in particular for conducting a comparative analysis of the operating conditions of several vehicles.However, vehicle operating conditions directly influence wear and tear, and the ability to determine these conditions as precisely as possible is therefore crucial for diagnosing the causes of breakdowns in order to consider corrective measures to prevent them, such as modifying production techniques or reinforcing certain vehicle components. In this context, current after-sales vehicle monitoring systems, which remain inadequate for accurately determining vehicle usage, still lack relevance and, consequently, effectiveness in maximizing vehicle quality. Summary of the invention

[0003] The invention aims to solve this problem. In particular, its objective is to provide a solution for precisely determining the use made of a motor vehicle, notably by enabling a comparative analysis of the use made of a group of vehicles. By these means, the invention aims to provide computerized tools for post-tracking selling more relevant motor vehicles, and thus contributing to enabling a demonstrable improvement in vehicle quality.

[0004] In order to achieve these goals, the invention relates, according to a first aspect, to a method for determining, by a computer system, data characterizing a similarity value in use of a first motor vehicle and a second motor vehicle, the method comprising the steps of: i. obtain data characterizing a first set of journeys made by the first vehicle and data characterizing a second set of journeys made by the second vehicle; ii. determine, based on the data obtained during step i), data characterizing a first causal graph for the first vehicle and data characterizing a second causal graph for the second vehicle; iii. determine data characterizing a comparison of the first causal graph and the second causal graph; and iv. determine said data characterizing a similarity value of use of a first motor vehicle and a second motor vehicle based on the data determined during step iii).

[0005] According to one variant, step ii) can be carried out using the direct LiNGAM algorithm.

[0006] According to another variant, step iii) may include a step of determining data characterizing a first set of all causal paths included in the first causal graph and a second set of all causal paths included in the second causal graph.

[0007] According to yet another variant, step iii) may include a step consisting of determining data characterizing a number of operations necessary to go from the first set of all causal paths included in the first causal graph to the second set of all causal paths included in the second causal graph.

[0008] According to yet another variant, each of said operations may consist of adding or removing a node or an edge.

[0009] According to yet another variant, said data characterizing a first set of journeys made by the first vehicle and said data characterizing a second set of journeys made by the second vehicle may contain data characterizing at least one speed value, at least one engine speed value, at least one pressure value exerted on an accelerator pedal and at least one gear ratio engaged.

[0010] According to a second aspect, the invention relates to a system for determining a similarity value of use of a first motor vehicle and a second motor vehicle, said system being a computer system and comprising a first device for acquiring data relating to journeys on board the first vehicle, a second device for acquiring data relating to journeys on board the second vehicle and a remote server of the first and second vehicles which is configured to implement a method as described above. Brief description of the figures

[0011] Other features and advantages of the invention will become apparent from an examination of the detailed description below, and the accompanying figures, in which:

[0012] [Fig-1] is a diagram illustrating the context of the invention; and

[0013] [Fig.2] is a flowchart illustrating the steps of a process according to the invention;

[0014] [Fig.3] illustrates the implementation of at least one step of the process according to the invention;

[0015] [Fig.4] illustrates the implementation of at least one step of the process according to the invention; And

[0016] [Fig.5] illustrates the implementation of at least one step of the process according to the invention. Detailed description of the invention

[0017] Fig. 1 schematically illustrates the context of the invention. The diagram shows a system 100 for determining a similarity value of use between a first motor vehicle 10 and a second motor vehicle 20. The system 100 according to the invention comprises a first device for acquiring trip data 200 on board the first vehicle 10, for example a computer, a second device for acquiring trip data 200' on board the second vehicle 20 and a server 300 remote from the first vehicle 10 and the second vehicle 20. In a conventional manner, the first and second vehicles 10, 20 communicate with the server 300 by means of conventional wireless communication networks and protocols (e.g. 3 / 4 / 5G; ITS-G5; C-V2X) and radio frequency signal communication equipment (not shown) which is on board each of the vehicles 10, 20.

[0018] According to the invention, all the elements of the system 100 according to the invention described above contribute to enabling the implementation of a method for determining a similarity value of use of a first motor vehicle and a second motor vehicle, as described below in relation to figures 2-5.

[0019] Figure [Fig.2] illustrates by means of a flowchart the steps of the process according to the invention.

[0020] According to a first step 401 of the method according to the invention, the server 300 obtains data characterizing a first set of journeys made by the first vehicle 10 and data characterizing a second set of journeys made by the second vehicle 20.

[0021] Preferably, this data is generated by the data acquisition devices 200, 200' installed on board each vehicle during journeys and is transmitted to the server 300 periodically or immediately following a journey. For example, this data includes a vehicle identification number and, for each journey, at least one speed reached during the journey, at least one engine speed reached during the journey, at least one pressure applied to the vehicle's accelerator pedal during the journey, and at least one gear engaged during the journey. Figure 3 shows a table illustrating this data obtained by the server 300 during this first step of the method according to the invention. Each row corresponds to a journey and each column to a type of data obtained.The first column identifies the vehicle in question by its vehicle identification number (VIN), the second column contains a speed value, the third column an ​​engine speed value, the fourth column a pressure value applied to the accelerator pedal, and the fifth column an ​​engaged gear. Thus, at the end of this first step of the process according to the invention, the server 300 advantageously holds data that exhaustively define the operating conditions of each of the vehicles 10, 20 during the journeys undertaken.

[0022] Next, according to a second step 402 of the method according to the invention, the server 300 determines, based on the data obtained during the previous step, data characterizing a first causal graph for the first vehicle 10 and data characterizing a second causal graph for the second vehicle 20. To do this, the server 300 preferentially uses the LiNGAM direct algorithm. Thanks to such an algorithm, the server 300 can thus directly determine, based on the data obtained during the previous step, a causal graph for each of the vehicles. Such a graph, which is thus determined for each vehicle during this second step of the method according to the invention, therefore establishes the causal links between the observed parameters.

[0023] Figure 4 shows two examples of causal graphs that can be determined by the server 300 during this second step of the process according to the invention: a first causal graph for the first vehicle 10 on the left of the figure (VIN1) and a second causal graph for the second vehicle 20 on the right of the figure (VIN2). Thus, if we refer to the causal graph on the left, we understand that a A causal link exists, in particular, between speed and the selected gear. The causal graph on the right also shows that, given the use of the second vehicle 20, a causal link exists between engine speed and the selected gear, whereas this causal link is not present in the causal graph on the left. In other words, the use of the first vehicle 10, as established by the values ​​recorded in the table in [Fig. 3], does not allow us to establish a causal link between engine speed and the gear. Conversely, the use of the second vehicle 20 does allow us to establish such a causal link.On this basis, it can be deduced that the driver of the first vehicle 10 changes gears solely based on speed, while the driver of the second vehicle 20 also takes engine speed into account when changing gears.

[0024] Then, according to a third step 403 of the method according to the invention, the server 300 determines data characterizing a comparison of the first causal graph and the second causal graph that were determined during the previous step of the method. To do this, the server 300 first determines all the causal paths that are included in the first causal graph and all the causal paths that are included in the second causal graph. The implementation of this step is schematically illustrated by the table shown in [Fig.5], in which each row lists a causal path from the first causal graph in the left column and, similarly, from the second causal graph in the right column.

[0025] Server 300 then proceeds by determining a number of operations necessary to go from the first set of all causal paths included in the first causal graph to the second set of all causal paths included in the second causal graph. According to the invention, such an operation consists of adding or removing a node or an edge.

[0026] Thus, according to the illustrated example, the first set of causal paths, in other words the first causal graph, differs from the second set of causal paths, in other words the second causal graph, only by the causal path that links the engine speed (i.e., node 1) to the engaged gear ratio (i.e., node 3). Indeed, this causal path is present only in the second causal graph (listed in the second row of the right-hand column). The 300 server therefore determines in this case that three operations are necessary to go from the first causal graph to the second causal graph. Indeed, it is necessary in this case to construct the causal path between node 1 and node 3 in the first causal graph, and, consequently, to add node 1, add node 3, and add an edge between node 1 and node 3.Conversely, moving from the second set of causal paths included in the second causal graph to the set of causal paths included in the first graph. causal requires removing the edge between node 1 and node 3, removing node 1 and removing node 3, and therefore also performing three operations.

[0027] Finally, according to a fourth step 404 of the process according to the invention, the server 300 determines said data characterizing a similarity value of use of a first motor vehicle and a second motor vehicle according to the data determined during the previous step.

[0028] According to the illustrated example, the comparison between the first causal graph and the second causal graph performed in the previous step of the process establishes that the number of operations required to move from the first causal graph to the second causal graph is three. Thus, the server 300 determines in this case that the usage similarity value of the first vehicle 10 and the second vehicle 20 is three. As can be understood, the fewer operations required to move from one graph to the other, the more similar the uses. When no operations are required, meaning that the causal graphs considered are identical, the usage similarity is total.

[0029] Thus, thanks to the method and system according to the invention described above, a solution is provided for precisely determining the use made of a motor vehicle, in particular by enabling a comparative analysis of the use made of a group of vehicles. In this way, the invention allows for the provision of more relevant computer tools for after-sales monitoring of motor vehicles, and can thus contribute to improving vehicle quality.

Claims

Demands

1. A method for determining, by a computer system (100), data characterizing a usage similarity value of a first motor vehicle (10) and a second motor vehicle (20), characterized in that the method comprises the steps of: i. obtaining data characterizing a first set of journeys made by the first vehicle and data characterizing a second set of journeys made by the second vehicle; ii. determining, based on the data obtained during step i), data characterizing a first causal graph for the first vehicle and data characterizing a second causal graph for the second vehicle; iii. determining data characterizing a comparison of the first causal graph and the second causal graph; and iv.determine the said data characterizing a similarity value of use of a first motor vehicle and a second motor vehicle based on the data determined during step iii).

2. A method according to claim 1, characterized in that step ii) is carried out using the direct algorithm of LiNGAM.

3. A method according to any one of the preceding claims, characterized in that step iii) comprises a step of determining data characterizing a first set of all causal paths included in the first causal graph and a second set of all causal paths included in the second causal graph.

4. A method according to claim 3, characterized in that step iii) comprises a step of determining data characterizing a number of operations necessary to go from the first set of all causal paths included in the first causal graph to the second set of all causal paths included in the second causal graph.

5. A method according to claim 4, characterized in that each of said operations consists of adding or removing a node or an edge.

6. A method according to any one of the preceding claims, characterized in that said data characterizing a first set of journeys made by the first vehicle and said data characterizing a second set of journeys made by the second vehicle contain data characterizing at least one speed value, at least one engine speed value, at least one pressure value exerted on an accelerator pedal and at least one gear ratio engaged.

7. System (100) for determining a similarity value of use of a first motor vehicle (10) and a second motor vehicle (20), characterized in that said system is a computer system which includes a first trip data acquisition device (200) on board the first vehicle, a second trip data acquisition device (200') on board the second vehicle and a server (300) remote from the first and second vehicles which is configured to implement a method according to one of the preceding claims.