Vehicle setting adjusting method, device, program, medium, system and vehicle

Abstract

The present disclosure relates to a method for adjusting vehicle settings for a user (12). The method comprises receiving first data (D1) comprising a characterization of the user (12) and receiving second data (D2) indicative of a position of a key element (14) of the vehicle (10). Furthermore, the method comprises identifying a characterization of the user (12) in the first data (D1) by mapping the second data (D2) onto the first data (D1), and triggering an adjustment of the vehicle setting based on the characterization of the user (12). Furthermore, a data processing device (28), a computer program (36) and a computer readable storage medium (34) are disclosed. Furthermore, a vehicle setting adjustment system (16) is described. The invention further relates to a vehicle (10).

Description

Technical Field

[0001] The present invention relates to a method of adjusting vehicle settings for a user.

[0002] Furthermore, the invention relates to a data processing device, a computer program and a computer-readable storage medium.

[0003] The invention also relates to a vehicle settings adjustment system and a vehicle. Background Art

[0004] It is well known to adjust vehicle settings according to the user. In this case, the position and / or configuration of the vehicle seat can be adjusted according to the user. This means that the position and / or configuration of the seat can be selected as a function of the user's overall height and / or as a function of the measurements of the user's body parts. The adjustment can be done manually. In other words, the vehicle setting can be the position and / or configuration of the seat. Another example of a vehicle setting that can be adjusted for the user is the orientation of the rearview mirror. Summary of the invention

[0005] The object of the present invention is to further improve the user's experience when using a vehicle, for example in terms of comfort.

[0006] This problem is at least partly solved or alleviated by the subject matter of the independent claims of the present invention, wherein further examples are incorporated in the dependent claims.

[0007] According to a first aspect, a method for adjusting vehicle settings for a user is provided. The method comprises:

[0008] - receiving first data comprising a representation of a user,

[0009] - receiving second data indicative of a position of a vehicle key element relative to the vehicle,

[0010] — identifying a representation of the user in the first data by mapping the second data onto the first data,

[0011] —Triggering adjustments to vehicle settings based on user characterization.

[0012] The second data can be used to quickly and reliably identify the representation of the user in the first data. In addition, mapping the second data to the first data is computationally efficient. Therefore, the adjustment of the vehicle settings can be triggered in a manner suitable for the user. This improves the comfort of the user. When performing the present method, it can be assumed that the user carries a key element of the vehicle. In this case, any way to lock and / or unlock the vehicle is considered to be a key element. The key element can be, for example, a standard key card or a smart phone with a digital key or any other electronic device configured to lock and / or unlock the vehicle. Therefore, the second data can be used to identify the representation of the user in the first data. In this case, mapping the second data to the first data means identifying a part of the first data corresponding to the second data. In other words, the first data and the second data are combined. In an example where the first data is optical image data, mapping the second data to the first data can be imagined as marking a point or part corresponding to the position of the key element in the optical image data. Therefore, the representation of the user in the first data can be identified with high reliability. The representation of the user is a representation of at least one feature of the user's body, such as the full body height of the user's body or the measurement of each part of the body. Therefore, the vehicle settings can be reliably adjusted based on this. This improves the comfort of the user.

[0013] Note that the method of the invention can be performed when the user is outside the vehicle. Thus, the characterization of the user can be a characterization of the user in relation to a user outside the vehicle. In this case, the user is, for example, approaching the vehicle. Thus, the user can also be described as a future user. This has the advantage that when the user enters the vehicle, the adjustment of the vehicle settings may have already started or may even have been terminated. In other words, when the user enters the vehicle, the vehicle settings have already been adjusted according to the user.

[0014] If used in a fleet vehicle (e.g., a fleet car) or a rental vehicle (e.g., a rental car), the method according to the present invention is particularly useful. Such vehicles are often used by a variety of different users, so that the execution of the method according to the present disclosure significantly increases the comfort of the users.

[0015] In one example, the second data include sensor data related to at least two detection positions on the vehicle. According to another example, the second data include sensor data related to at least three detection positions on the vehicle. Note that the second data is an indication of the position of the key element. In one example, the sensor data related to each of at least two or at least three positions describes the detection signal strength and / or detection direction connecting the position and the key element. Therefore, if the second data include sensor data related to at least two or at least three detection positions on the vehicle, accuracy and reliability are enhanced.

[0016] It should be noted that the sensor data associated with the at least two detection positions may be two-dimensional sensor data or three-dimensional sensor data for each of the at least two detection positions. Even if two-dimensional sensor data associated with each of the at least two detection positions is provided, the position of the key element may be indicated in three-dimensional space.

[0017] According to one example, mapping the second data onto the first data includes applying triangulation and / or triangulation techniques to sensor data associated with at least two detection locations on the vehicle. Using triangulation techniques and / or triangulation techniques provides an accurate indication of the location of the key element. Note that applying triangulation techniques also requires that the sensor data include directional information. In summary, the second data can be accurately mapped onto the first data.

[0018] In one example, the second data includes radar sensor data, lidar sensor data and / or image sensor data. Additionally or alternatively, the first data includes image data. The radar sensor data may be ultra-wideband sensor data. Optionally, the image sensor data may be referred to as visual sensor data. The visual sensor data may be stereoscopic vision sensor data. In this case, the characterization of the user may involve a point cloud of radar sensor data, lidar sensor data and / or image sensor data. In the case where the visual sensor data is stereoscopic vision sensor data, the characterization of the user may technically be represented by two point clouds. However, these point clouds may be fused. Such data may be provided by sensors that are frequently used in vehicles, in particular vehicles that provide full or partial autonomous driving functionality. Based on this, the method according to the present disclosure may be performed in a reliable manner.

[0019] In one example, identifying the representation of the user in the first data includes estimating at least one detection angle associated with the representation of the user based on the received second data and the relative position between the first sensor associated with the first data and the second sensor associated with the second data. In this case, the estimated detection angle is associated with the first sensor providing the first data. In one example, the detection angle is a viewing angle, such as a vertical viewing angle and / or a horizontal viewing angle. Therefore, the representation of the user in the first data can be identified with high accuracy.

[0020] According to an example, identifying the representation of the user in the first data includes applying an object detection technique to the first data. This is a reliable way to identify the representation of the user in the first data.

[0021] According to one example, identifying the representation of the user in the first data includes preprocessing the first data. This means that before the representation of the first user is actually recognized, the first data undergoes a processing step. The processing step may include a quality enhancement step. Additionally or alternatively, the processing step may include a coordinate transformation. In one example, the first data is image data and the preprocessing includes correcting the image data. This means that distortions are eliminated. The purpose of the preprocessing is to facilitate the recognition of the representation of the user. This includes improving the recognition quality and accuracy of the representation of the user. Based on this, the recognition of the representation of the user is improved.

[0022] In one example, the method further includes estimating a physical characteristic of the user based on the identified representation of the user, and triggering an adjustment of the vehicle settings based on the estimated physical characteristic. Thus, the vehicle settings can be precisely adjusted according to the user's needs.

[0023] In one example, the physical characteristics include one or more of the user's overall height, the user's upper body height, the user's overall leg length, the user's thigh length, the user's calf length, or the user's weight. In this case, the overall leg length is measured from the user's foot to the user's hip. The thigh length is the distance from the user's knee to the user's hip. The calf length is measured from the user's foot to the user's knee. All of these physical characteristics can be addressed by the vehicle settings (e.g., seat settings). If the vehicle settings are adjusted to all or some of these physical characteristics, the user's comfort will be improved.

[0024] In one example, the vehicle is set up for one or more of an airbag setting, a seatbelt setting, a seat setting, or a rearview mirror setting. The airbag setting may relate to the inflation volume, inflation time, expansion force, and / or explosion force. The seatbelt setting may relate to the height of the connection point on the B-pillar. The seat setting may relate to the position and / or configuration of the seat. The rearview mirror setting may relate to the orientation of the rearview mirror. These settings may affect the comfort of the vehicle user. Therefore, by adjusting these settings for the user, the user's comfort is improved.

[0025] The method may be at least partially computer-implemented and may be implemented by software or hardware or by both software and hardware. In addition, the method may be performed by computer program instructions running on a device providing data processing functionality. The data processing device may be a suitable computing device, such as an electronic control module, etc. It may also be a distributed computer system. The data processing device or computer may include one or more of a processor, a memory, a data interface, etc., respectively.

[0026] According to a second aspect, a data processing device is provided, comprising means for implementing the method according to the invention. Thus, using such a data processing device, vehicle settings can be reliably adjusted for the vehicle user. This increases the comfort of the user.

[0027] According to a third aspect, a computer program is provided comprising instructions which, when executed by a computer, cause the computer to perform the method of the invention. Thus, using such a computer program, vehicle settings can be reliably adjusted for a vehicle user. This increases the comfort of the user.

[0028] According to a fourth aspect, there is provided a computer readable storage medium comprising instructions which, when executed by a computer, cause the computer to perform the method of the present disclosure. Thus, using such a computer readable storage medium, vehicle settings can be reliably adjusted for a vehicle user. This improves the user's comfort.

[0029] According to a fifth aspect, a vehicle setting adjustment system is provided. The vehicle setting adjustment system comprises: at least one first sensor configured to provide first data including a representation of a user; at least one second sensor configured to provide second data indicating the position of a key element of a vehicle; a driver unit configured to adjust vehicle settings; and a data processing device according to the present disclosure, wherein the data processing device is communicatively connected to the at least one first sensor, the at least one second sensor and the driver unit. As previously mentioned, it is assumed that the user carries a key element of the vehicle. Likewise, any method capable of locking and / or unlocking a vehicle is considered a key element. The key element may be, for example, a standard key chain or a smartphone with a digital key or any other electronic device configured to unlock a vehicle. Thus, using the second sensor, a reliable indication of the position of the key element may be provided. Using the first sensor, first data including a representation of the user is provided in a reliable manner. Thus, the combination of the first sensor, the second sensor and the data processing device is capable of accurately identifying the representation of the user. The representation of the user is a representation of at least one feature of the user's body, such as the full body height or partial size of the user's body. Thus, the vehicle settings may be reliably adjusted using the data processing device and the driver unit. This improves the comfort of the user.

[0030] In one example, the first sensor includes an image sensor, and / or the second sensor includes one or more of a radar sensor, a lidar sensor, or an image sensor. The radar sensor may be an ultra-wideband sensor. The image sensor may also be referred to as a vision sensor. The vision sensor may be a stereo vision sensor. Such sensors are accurate and reliable. Based on the data provided by the sensors, the vehicle settings may be adjusted reliably and appropriately.

[0031] In one example, the first sensor is formed by an optical camera. The second sensor may also be formed by an optical camera.

[0032] According to a sixth aspect, a vehicle is provided, comprising a data processing device according to the invention or a vehicle settings adjustment system according to the invention. In such a vehicle, the vehicle settings can be adjusted reliably for the user. This increases the comfort of the user.

[0033] It should be noted that the above examples can be combined with each other, regardless of the aspects involved.

[0034] These and other aspects of the disclosure will be apparent from and elucidated with reference to the examples described hereinafter. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Examples of the present invention will be described below with reference to the following drawings.

[0036] Figure 1 A vehicle according to the present disclosure is shown, comprising a vehicle settings adjustment system according to the present disclosure, a data processing device according to the present disclosure, a computer program according to the present disclosure and a computer-readable storage medium according to the present disclosure, wherein the method for adjusting vehicle settings for a user according to the present disclosure can be performed by the vehicle,

[0037] Figure 2 showing first data including a characterization of a vehicle user,

[0038] Figure 3 shows the Figure 2 The first data, and

[0039] Figure 4 Determining characteristics of a user based on a characterization of a vehicle user is shown. DETAILED DESCRIPTION

[0040] The drawings are schematic representations only and serve merely to illustrate examples of the invention. Identical or equivalent elements are in principle provided with the same reference numerals.

[0041] Figure 1 A vehicle 10 is shown.

[0042] also, Figure 1 A user 12 is shown carrying a key element 14 . The user 12 is approaching the vehicle 10 .

[0043] The vehicle 10 includes a vehicle settings adjustment system 16 .

[0044] In the present example, the vehicle setting adjustment system 16 comprises two first sensors 18a, 18b, which comprise image sensors formed as optical cameras. The two first sensors 18a, 18b are respectively arranged in the housing of the outside side mirrors.

[0045] The first sensors 18 a , 18 b are each configured to provide first data D1 comprising a representation of the user 12 .

[0046] The vehicle settings adjustment system 16 also includes a second sensor.

[0047] exist Figure 1 In the example of FIG. 5 , a total of six second sensors 20 a , 20 b , 20 c , 20 d , 20 e , and 20 f are provided.

[0048] The second sensors 20a, 20b, 20c, 20d, 20e, 20f are designed as radar sensors, more precisely as ultra-wideband sensors.

[0049] The second sensor 20 a , 20 b , 20 c , 20 d , 20 e , 20 f is configured to provide second data D2 indicating the position of the key element 14 of the vehicle 10 .

[0050] It should be noted that in other examples, the second sensors 20a, 20b, 20c, 20d, 20e, 20f may be alternatively formed as a lidar sensor or an image sensor. The following will be explained in conjunction with a radar sensor. However, the explanation is also applicable to other types of sensors.

[0051] The vehicle settings adjustment system 16 further comprises a driver unit 22 configured for adjusting vehicle settings.

[0052] In the illustrated example, the drive unit 22 includes a driver seat positioning drive 24. The driver seat positioning drive 24 is configured to adjust the position of a driver seat 26 along the longitudinal direction of the vehicle 10.

[0053] It should be noted that the driver unit 22 including the driver seat positioning driver 24 is for illustration only. In other examples, the driver unit 22 may alternatively or additionally include an airbag setting driver, a seat belt setting driver, a rearview mirror setting driver, or a different kind of seat setting driver, such as a backrest driver configured to adjust the backrest inclination of the driver seat 26.

[0054] Furthermore, the vehicle settings regulating system 16 comprises a data processing device 28 .

[0055] The data processing device 28 is communicatively connected to each first sensor 18 a , 18 b , each second sensor 20 a , 20 b , 20 c , 20 d , 20 e , 20 f and the driver unit 22 .

[0056] The data processing device 28 includes a data processing unit 30 and a data storage unit 32 .

[0057] The data storage unit 32 includes a computer-readable storage medium 34 .

[0058] On the computer-readable storage medium 34 and thus on the data storage unit 32 , a computer program 36 is provided.

[0059] The computer program 36 and the computer readable storage medium 34 include instructions which, when executed by the data processing unit 30 or more generally a computer, cause the data processing unit 30 or computer to perform a method of adjusting vehicle settings for a user.

[0060] The data processing unit 30 and the data storage unit 32 thus form a device 38 for implementing the method for adjusting vehicle settings to a user.

[0061] A first step S1 of the method of adjusting vehicle settings according to a user comprises receiving first data D1 containing a representation of the user 12. The first data D1 are received at a data processing device 28.

[0062] Since in this example, the user 12 is only located within the field of view of the first sensor 18a, the first data D1 is provided by the first sensor 18a. It should be understood that in other cases, the first sensor 18b may be used to provide the first data D1.

[0063] As mentioned above, the first data D1 is image sensor data.

[0064] The first sensor data provided by the first sensor 18a is exemplified as follows: Figure 2 Note that the representation of the user 12 is also indicated by reference numeral 12, although strictly speaking the user and the representation of the user are different.

[0065] In a second step S2 of the method for adjusting vehicle settings for a user, second data D2 are received.

[0066] In this example, the second data D2 is provided by the second sensors 20 a , 20 b , 20 c located on the driver's side of the vehicle 10 .

[0067] Since the second sensors 20 a , 20 b , 20 c are located at different positions on the vehicle 10 , the second data D2 includes sensor data associated with three detection positions on the vehicle 10 .

[0068] More specifically, the second data D2 is composed of sensor data D2a provided by the second sensor 20a, sensor data D2b provided by the second sensor 20b, and sensor data D2c provided by the second sensor 20c.

[0069] As mentioned above, the second data D2 indicates the position of the key element 14 .

[0070] In this example, the sensor data D2a indicates the distance da between the key element 14 and the second sensor 20a. The sensor data D2b indicates the distance db between the key element 14 and the second sensor 20b. The sensor data D2c indicates the distance dc between the key element 14 and the second sensor 20c. Figure 1 In FIG. 1 , the sensor data are shown by three circles, with a second sensor 20 a , 20 b , 20 c at their center, respectively, and with radii corresponding to da, db, dc, respectively.

[0071] The distance between the key element 14 and each second sensor 20a, 20b, 20c may be indicated by the signal strength received by each second sensor 20a, 20b, 20c and / or the time of flight detected by each second sensor 20a, 20b, 20c.

[0072] Since in the present example, the second sensors 20a, 20b, 20c, 20d, 20e, 20f are radar sensors, the second data D2 includes radar sensor data.

[0073] The third step S3 comprises identifying a representation of the user 12 in the first data D1 by mapping the second data D2 onto the first data D1.

[0074] The third step S3 comprises several sub-steps.

[0075] In the first sub-step S31, the first data D1 is preprocessed. In this example, the preprocessing includes correction of the first data D1. Therefore, the first data D1 is Figure 2 The state shown is converted to Figure 3 Status shown.

[0076] In a second sub-step S32, an object detection technique is applied to the first data D1, more precisely, to the pre-processed first data D1. In this example, the object detection technique is configured to detect people in the first data D1.

[0077] To illustrate the result of the second sub-step S32, Figure 3 , the detected people are highlighted by thick lines along their corresponding contours.

[0078] In the third sub-step S33, the trilateration technique is applied to the second data D2, i.e., the sensor data D2a, D2b, and D2c associated with three locations on the vehicle 10. In short, the position of the key element 14 is determined based on the detected distances da, db, dc between the key element 14 and each of the second sensors 20a, 20b, 20c. Because the position of each of the second sensors 20a, 20b, 20c on the vehicle 10 is known, the position of the key element 14 relative to the vehicle 10 can be determined in three dimensions.

[0079] Thereafter, in a fourth sub-step S34, a distance d between the position of the key element 14 and the first sensor 18a may be calculated. This is because the position of the first sensor 18a on the vehicle 10 is known. Furthermore, also based on the known position of the first sensor 18a on the vehicle 10, a detection angle α defining the direction in which the key element 14 is positioned relative to the first sensor 18a may be determined. More precisely, the vertical detection angle α may be calculated. v and horizontal detection angle α h (See Figure 1 and 3 ).

[0080] Then, in the fifth sub-step S35, the vertical detection angle α may be used. v and horizontal detection angle α h The position of the key element 14 is marked in the first data D1. Figure 3 shown.

[0081] Based on this, in a sixth sub-step S36 , the representation of the user 12 may be identified by selecting the detected person that is closest to the position of the key element 14 or overlaps with the position of the key element 14 .

[0082] exist Figure 3 In the example of FIG. 1 , the leftmost person is identified as a representation of the user 12 in the first data D1 .

[0083] Therefore, in the seventh sub-step S37, the received second data D2 and the determined vertical detection angle α may be used to determine the vertical detection angle α. v and horizontal detection angle α h At least one detected angle is estimated in relation to a representation of the user 12 , the received first data D1 comprising the determined representation of the user 12 and the known position of the first sensor 18 a .

[0084] This is Figure 4 , where only the detection angles associated with the vertical direction are shown, denoted by β1 and β2. It should be understood that the detection angles associated with the horizontal direction can be determined in the same way.

[0085] Thereafter, in a fourth step S4 , physical characteristics of the user are estimated based on the identified characterization of the user 12 .

[0086] Reference again Figure 4 , the full body height H of the user 12 can be determined using trigonometric operations based on the detected angles β1, β2 and the distance d.

[0087] Based on this, in a fifth step S5 , an adjustment of vehicle settings is triggered depending on the estimated physical characteristics of the user 12 , ie depending on the estimated full body height of the user 12 .

[0088] In this example, a lookup table is provided on the data storage unit 32 of the data processing device 28. The lookup table includes a list of full body heights ranging from 1.5 meters to 2.1 meters. In addition, the lookup table includes the appropriate position of the driver's seat 26 associated with each full body height in the list.

[0089] It should be noted that the method of adjusting vehicle settings for a user has been explained in conjunction with the physical characteristic of the user's full body height. This is purely illustrative. In other examples, the physical characteristic may additionally or alternatively relate to any one or more of the user's upper body height, the user's entire leg length, the user's thigh length, the user's calf length, or the user's weight. Note that for this purpose, the object detection technology needs to be configured to detect the upper body, legs, thighs, or calves, respectively. In order to estimate weight, the width of the user's representation may be determined.

[0090] As used herein, the phrase "at least one" when referring to a list of one or more entities should be understood as at least one entity selected from any one or more entities in the list of entities, but does not necessarily include at least one of each entity specifically listed in the list of entities, nor does it exclude any combination of entities in the list of entities. This definition also allows that in addition to the entities specifically identified in the list of entities referred to by the phrase "at least one", other entities may optionally exist, whether or not they are related to the specifically identified entities. Thus, as a non-limiting example, "at least one of A and B" (or equivalently, "at least one of A or B", or equivalently "at least one of A and / or B") may refer to at least one (optionally including more than one) A in one example, without B (and optionally including entities other than B); at least one, optionally including more than one B, without A (and optionally including entities other than A); in yet another example, at least one, optionally including more than one A, and at least one, optionally including more than one B (and optionally including other entities). In other words, the phrases "at least one", "one or more", and "and / or" are open-ended expressions that are both conjunctive and disjunctive in operation. For example, each of the expressions "at least one of A, B, and C", "at least one of A, B or C", "one or more of A, B and C", "one or more of A, B or C", and "A, B and / or C" may represent A alone, B alone, C alone, A and B together, A and C together, B and C together, A, B and C together, and optionally any one of the foregoing in combination with at least one other entity.

[0091] By studying the drawings, the disclosure and the appended claims, a person skilled in the art may understand and implement other variations of the disclosed examples when implementing the claimed disclosure. In the claims, the word "comprising" does not exclude other elements or steps, and the indefinite article "a" or "an" does not exclude a plurality. A single processor or other unit may implement the functions of several items or steps listed in the claims. The fact that certain measures are cited in mutually different dependent claims does not indicate that a combination of these measures cannot be used to advantage. The computer program may be stored / distributed on a suitable medium, such as an optical storage medium or solid-state medium provided with or as part of other hardware, but may also be distributed in other forms, such as via the Internet or other wired or wireless telecommunications systems. Any reference signs in the claims should not be interpreted as limiting the scope of the claims.

[0092] Reference Mark List

[0093] 10 Vehicles

[0094] 12 users

[0095] 14 Key element

[0096] 16 Vehicle settings adjustment system

[0097] 18a First sensor

[0098] 18b First sensor

[0099] 20a Second sensor

[0100] 20b Second sensor

[0101] 20c Second sensor

[0102] 20d Second sensor

[0103] 20e Second sensor

[0104] 20f Second sensor

[0105] 22 Driver Unit

[0106] 24 Driver seat positioning actuator

[0107] 26 Driver's seat

[0108] 28 Data processing equipment

[0109] 30 Data processing unit

[0110] 32 Data storage unit

[0111] 34 Computer readable storage medium

[0112] 36 Computer Programs

[0113] 38 Apparatus for performing a method of adjusting vehicle settings to a user

[0114] d Distance between key element and first sensor

[0115] da The distance between the key element and the second sensor 20a

[0116] db The distance between the key element and the second sensor 20b

[0117] dc The distance between the key element and the second sensor 20c

[0118] D1 First Data

[0119] D2 Second data

[0120] D2a sensor data

[0121] D2b sensor data

[0122] D2c sensor data

[0123] HHeight

[0124] S1 First step

[0125] S2 Step 2

[0126] S3 Step 3

[0127] S31 First sub-step

[0128] S32 Second sub-step

[0129] S33 The third sub-step

[0130] S34 Fourth sub-step

[0131] S35 Fifth sub-step

[0132] S36 Sixth sub-step

[0133] S37 Seventh sub-step

[0134] S4 Step 4

[0135] S5 Step 5

[0136] α Detection angle

[0137] α v Vertical detection angle in relation to the key element

[0138] α h Horizontal detection angle in relation to the key element

[0139] β1 Detection angle related to the user

[0140] β2 Detection angle related to the user

Claims

1. A method for adjusting vehicle settings for a user (12), the method comprising: - receiving first data (D1) (S1) comprising a representation of said user (12), - receiving second data (D2) (S2) indicating the position of a key element (14) of the vehicle (10) relative to the vehicle (10), - identifying (S3) the representation of the user (12) in the first data (D1) by mapping the second data (D2) onto the first data (D1), - triggering an adjustment (S5) of the vehicle settings based on the characterization of the user (12).

2. The method according to claim 1, wherein the second data (D2) comprises sensor data (D2a, D2b, D2c) associated with at least two detection locations on the vehicle (10).

3. The method according to claim 2, wherein mapping the second data (D2) onto the first data (D1) comprises applying trilateration and / or triangulation techniques to the sensor data (D2a, D2b, D2c) associated with at least two detection locations on the vehicle (10).

4. The method according to claim 1, wherein the second data (D2) comprises radar sensor data, lidar sensor data and / or image sensor data, and / or The first data (D1) includes image data.

5. The method according to claim 1, wherein identifying the representation of the user (12) in the first data (D1) includes estimating at least one detection angle (β1, β2) associated with the representation of the user (12) based on the received second data (D2) and the relative position between a first sensor (18a, 18b) associated with the first data (D1) and a second sensor (20a, 20b, 20c, 20d, 20e, 20f) associated with the second data (D2).

6. The method of claim 1, wherein identifying the representation of the user (12) in the first data (D1) comprises applying an object detection technique to the first data (D1).

7. The method according to claim 1, further comprising estimating a physical characteristic of the user (12) based on the identified representation of the user (12), and triggering an adjustment (S4) of the vehicle setting based on the estimated physical characteristic.

8. The method according to claim 7, wherein the physical characteristics include one or more of the following: the overall height (H) of the user (12), - the upper body height of the user (12), - the entire leg length of the user (12), - the length of the thigh of the user (12), - the calf length of the user (12), or - The weight of the user (12).

9. A method according to any one of the preceding claims, wherein the vehicle setting is one or more of an airbag setting, a seat belt setting, a seat setting or a rear view mirror setting.

10. A data processing device (28) comprising means (38) for performing the method of any of the preceding claims.

11. A computer program (36) comprising instructions, wherein when a computer executes the computer program (36), the instructions cause the computer to perform the method of any one of claims 1 to 9.

12. A computer readable storage medium (34) comprising instructions, wherein when executed by a computer, the instructions cause the computer to perform the method of any one of claims 1 to 9.

13. A vehicle setting adjustment system (16), comprising at least one first sensor (18a, 18b) configured to provide first data (D1) comprising a representation of the user (12), at least one second sensor (20a, 20b, 20c, 20d, 20e, 20f) configured to provide second data (D2) indicating a position of a key element (14) of the vehicle (10), - a driver unit (22) configured to adjust settings of the vehicle, A data processing device (28) according to claim 10, wherein the data processing device (28) is communicatively connected to the at least one first sensor (18a, 18b), the at least one second sensor (20a, 20b, 20c, 20d, 20e, 20f) and the driver unit (22).

14. A vehicle setting adjustment system (16) according to claim 13, wherein the first sensor (18a, 18b) includes an image sensor and / or wherein the second sensor (20a, 20b, 20c, 20d, 20e, 20f) includes one or more of a radar sensor, a lidar sensor or an image sensor.

15. A vehicle (10) comprising a data processing device (28) according to claim 10 or a vehicle settings adjustment system (16) according to claim 13 or 14.

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