METHOD FOR PROVIDING AGGREGATED DATA AND VEHICLE

Description

[0001] The invention relates to a method for providing aggregated data after a collision event of an open vehicle and to an open vehicle for carrying out such a method.

[0002] Collisions occur frequently in road traffic. Such collisions typically occur between two or more vehicles, which are usually also damaged in the collision. While drivers of enclosed four-wheeled motor vehicles are typically relatively well protected by the surrounding vehicle, drivers of open and / or two-wheeled motor vehicles are typically at a higher risk of personal injury.

[0003] DE 10 2016 103 638 A1 shows a method for determining the condition of a vehicle user who has been involved in an accident, in which, after detecting a critical situation of the user and / or the vehicle, the distance between the user and the vehicle is determined and a condition of the user is determined depending on the distance between the user and the vehicle and then a message is sent out, wherein the type and / or content of the message is generated depending on the condition of the user.

[0004] Accordingly, it may be advantageous to advantageously provide data relating to such a driver and / or a collision event involving such a driver.

[0005] This is achieved according to the invention by a method and an open vehicle according to the respective main claims. Advantageous embodiments can be found, for example, in the respective subclaims. The content of the claims is incorporated into the content of the description by express reference.

[0006] The invention relates to a method for providing aggregated data following a collision event of an open vehicle, the method comprising the following steps: Determining a position of the vehicle, determining one or more of driver position after the collision, collision intensity and driver health status, forming aggregated data based on the determined position and the determined driver position after the collision, collision intensity and / or driver health status, and sending the aggregated data to a receiver.

[0007] The collision intensity is classified into one of four classes.

[0008] The collision intensity is classified into a first class if an accelerometer indicates a low-speed collision and an acoustic sensor indicates a number of collisions below a collision threshold. The collision intensity is classified into a second class if an accelerometer indicates a low-speed collision and an acoustic sensor indicates a number of collisions at least as great as the collision threshold. The collision intensity is classified into a third class if an accelerometer indicates a high-speed collision and an acoustic sensor indicates a number of collisions below the collision threshold.The collision intensity is classified into a fourth class when an acceleration sensor indicates a high-speed collision and an acoustic sensor indicates a number of collisions at least as large as the collision threshold.

[0009] Using such a process, data can be aggregated and forwarded to a suitable recipient, which can help provide rapid assistance in the event of a collision involving an open-top vehicle. This can, for example, accelerate rescue efforts.

[0010] The aggregated data can be provided and sent, for example, in one message or in multiple messages.

[0011] The open vehicle can in particular be a two-wheeled motor vehicle such as a scooter or a motorcycle. The attachment of a sidecar or the hitching of a trailer is included in the term two-wheeled motor vehicle. In principle, the method described here can also be applied to other vehicles which, for example, have three or four wheels and in which the driver sits on an open, largely unenclosed seat and in which similar conditions can arise as with two-wheeled vehicles. For example, these can be trikes or quads. In principle, an open vehicle can be understood in particular as a vehicle in which the driver is largely not enclosed on the sides and / or in which the driver can be thrown from a seat in the event of a collision and is then away from the vehicle.

[0012] The position of the vehicle is typically the position in which the vehicle itself is located after the collision. This can be determined, for example, using a satellite navigation device.

[0013] In particular, the driver position can be independent of and distinct from the position of the vehicle. Open or two-wheeled vehicles are typically far less capable than four-wheeled or enclosed vehicles of maintaining a driver in position after a collision event, so the driver is often located away from the vehicle after the collision event. In particular, the driver position can be determined relative to the vehicle. The collision intensity typically characterizes the severity of a collision event. The driver health status refers to the driver who was driving the vehicle prior to the collision event and characterizes health-related information.It should be understood that in the event that two or more persons were on the vehicle prior to the collision, the measures described here for one driver and his or her medical condition can also be carried out for multiple persons.

[0014] According to the implementation described herein, the aggregated data essentially describes the position of the vehicle. This is generally useful for determining the vehicle's location and thus usually also for knowing where a collision occurred. This facilitates the initiation of rescue measures.

[0015] The classification described above allows for a meaningful classification of collision intensity, which provides information on both the speed and the number of collisions and thus provides indications of the rescue measures to be initiated.

[0016] For the driver position after the collision, collision intensity, and driver health status data, one of these data, two of these data, or all three of these data can be used. It is advantageous to use all three.

[0017] The transmission may, for example, be carried out via a mobile network, another radio network, or another suitable data transmission method. In particular, the transmission may be automated and / or electronic.

[0018] According to a preferred embodiment, the driver's position after the collision, the collision intensity, and the driver's health status are determined, and the aggregated data is generated based on these. This allows for particularly comprehensive information about the collision event and is particularly advantageous in initiating rescue measures.

[0019] The driver position can be determined especially after the collision using a radio module in the vehicle and a radio module worn by the driver, and / or using a pressure sensor that senses whether the driver is positioned on a seat.

[0020] The aforementioned pressure sensor can, in particular, make a yes / no decision as to whether the driver is still sitting in the seat intended for them. The aforementioned radio modules can, in particular, determine the distance between the driver and the vehicle. In collisions involving open vehicles, drivers can generally be ejected from their seats and therefore be located away from the vehicle after the collision. Using suitable radio modules, the distance between the driver and the vehicle can be determined or at least classified.

[0021] The collision intensity can be determined in particular using at least one acceleration sensor, and / or using at least one sound sensor.

[0022] For example, an acceleration sensor can determine the deceleration during a collision event, with a high deceleration indicating a particularly severe intensity. A sound sensor, for example, can determine whether noise is generated during a collision event, which can also determine how many collisions occurred and / or how many vehicles were involved in the collision.

[0023] The rider's health status can be determined, in particular, using a pulse rate sensor. This can be worn, for example, in the rider's helmet or on the rider's wrist. This allows the rider's current heart rate to be determined. Normal heart rate typically indicates a relatively good state of health, whereas a lack of pulse, for example, may indicate the need for immediate resuscitation.

[0024] Specifically, the driver position after the collision can be classified into one of three classes, indicating the distance between the driver and the vehicle after the collision. This allows for a classified analysis, which can provide a faster overview of a collision event. This also applies to other data, described below, that can be classified.

[0025] The driver position after the collision can be classified into a first class if a pressure sensor indicates that the driver is sitting on the vehicle. The driver position after the collision can be classified into a second class if a pressure sensor indicates that the driver is not sitting on the vehicle, and radio modules indicate that the distance between the vehicle and the driver is below a distance threshold. These can be, for example, the radio modules described above. The driver position after the collision can be classified into a third class if a pressure sensor indicates that the driver is not sitting on the vehicle, and radio modules indicate that the distance between the vehicle and the driver is at least as great as the distance threshold.

[0026] The classification into one of three possible classes described above can indicate where the driver is likely to be located and ultimately also provide an indication of the severity of the collision, since in a serious collision, it can be assumed that the driver is lying far away from the vehicle. The first class can, in particular, indicate that the driver is still sitting on the vehicle, and thus only minor damage and / or only minor impairment of the driver's health can be expected.

[0027] In particular, the acceleration sensor can indicate a low-speed collision if the maximum acceleration during a collision event is below an acceleration threshold. In particular, the acceleration sensor can indicate a high-speed collision if the maximum acceleration during a collision event is at least as great as the acceleration threshold. This allows for simple classification of the acceleration or speed.

[0028] In particular, the sound sensor can indicate a collision every time the sound intensity exceeds a threshold. This makes it easy to determine how many collisions occur. Typically, the sound intensity initially rises above the threshold during a collision and immediately falls below it again. If a subsequent collision occurs, the threshold is exceeded again. This allows for separate determination of collisions.

[0029] Specifically, the driver's health status can be classified into one of three categories. This classification can be based, for example, on the driver's heart rate, with suitable heart rate thresholds being defined for each of the three categories. This allows for easy inference about the driver's immediate health status.

[0030] It should be understood that it is generally possible to use more or fewer classes than specified. However, the specified numbers have proven advantageous.

[0031] Preferably, one or more patterns are defined, each pattern defining a combination of classes. The aggregated data can be forwarded to a specific recipient assigned to the pattern if all parameters are classified in a class, which in combination are defined by the pattern. This allows such patterns to be defined in order to appropriately determine to whom certain collisions are reported. For example, patterns can be defined such that they only record collisions for which the aforementioned parameters are classified in such a way that there is a particularly high probability of requiring very rapid rescue measures. Emergency control centers, for example, can then be informed immediately about such collision events.

[0032] According to one possible embodiment, the aggregated data with respect to driver position after the collision, collision intensity, and driver health status can be formed only from indications of classes into which the driver position after the collision, collision intensity, and driver health status have been classified. In other words, it is not the actual recorded data that is aggregated, but rather indications of the classes into which this data has been aggregated. This can be done, in particular, as described above.

[0033] The position can be determined, in particular, using a satellite navigation system in the vehicle. Such satellite navigation systems are present in numerous vehicles and can be used here to determine the position and thus provide emergency services with an indication of where the collision occurred.

[0034] The invention further relates to an open vehicle having an acceleration sensor and a sound sensor, wherein the open vehicle is configured to carry out a method according to any one of claims 1-13, wherein the data of the acceleration sensor and the sound sensor are used to classify the collision intensity.

[0035] A total of 36 possible combinations of classifications are conceivable for the described classifications. This facilitates communication with potential recipients such as emergency control centers, police stations, insurance agencies, repair shops, and emergency numbers, which, as already mentioned, can be specifically informed and / or receive a quick overview of the accident.

[0036] Further features and advantages will become apparent to those skilled in the art from the exemplary embodiment described below with reference to the accompanying drawings. These show: Fig. 1: a vehicle and a driver, Fig. 2: a basic approach to data processing, Fig. 3: a classification approach, and Fig. 4: a pattern formation approach.

[0037] Fig. 1shows a purely schematic view of an open vehicle 1 and a driver 2. In the state shown, the driver 2 is located away from the vehicle 1, since a state after a collision is shown in which the driver 2 was thrown from the vehicle 1. In typical situations of this type, the driver 2 is lying on the ground away from the vehicle 1. The vehicle 1 has a satellite navigation system 10 which can determine the position of the vehicle 1. The vehicle 1 has a radio module 20 which can communicate with a further radio module 25, the latter being shown schematically next to the driver 2. This can be located in a helmet, for example. The two radio modules 20, 25 can exchange radio signals with each other and thereby determine the distance between the vehicle 1 and the driver 2. The radio module 20 thus provides information about the distance, which can be evaluated as described below.The vehicle 1 has a pressure sensor 30, which can determine whether the driver 2 is sitting on the vehicle 1. The vehicle 1 has an acceleration sensor 40, which can measure the acceleration or deceleration of the vehicle 1. A pulse rate sensor 50 is shown on the driver 2, which can be embodied, for example, in a watch or other device worn on the body. This measures the pulse rate of the driver 2 and reports it back to the vehicle 1 via a radio connection. The vehicle 1 also has a sound sensor 60, which records sound from the environment. The aforementioned elements 10, 20, 25, 30, 40, 50, 60 are sensors of the vehicle 1 and the driver 2.

[0038] The vehicle 1 further comprises a processing unit 4 which evaluates the data obtained and forwards it if necessary and whose functionality is described below.

[0039] Fig. 2shows the processing unit 4 in greater detail. The processing unit 4 has a data acquisition module 5, to which data of the already described with reference to Fig. 1 described sensors 10, 20, 30, 40, 50, 60. These data are forwarded to an evaluation module 6, where the information described below with reference to Fig. 3 and Fig. 4The processing steps described are carried out. Data obtained therefrom are forwarded to a communications module 8, which can forward the data to one or more recipients E. In the present case, for example, the first recipient E1 is an emergency control center, the second recipient E2 is a police station, the third recipient E3 is an insurance agency, the fourth recipient E4 is a workshop, and the fifth recipient E5 is an emergency number. An emergency number can, in particular, be the number of a close contact person who is to be informed in the event of serious physical injury to driver 2.

[0040] In Fig. 3 On the left, next to the sensors 10, 20, 30, 40, 50, 60, the data obtained from them are shown, namely position (Pos), driver position (FP), collision intensity (ZI) and driver health status (FGZ).

[0041] The position Pos is forwarded directly to a decision module 7, which decides on a possible forwarding of data, for example as described below with reference to Fig. 4 described.

[0042] The data from the pressure sensor 30 and the radio module 20, and possibly also from the additional radio module 25, are used to classify the driver position FP. A parameter p indicates whether the pressure sensor 30 detects that the driver 2 is sitting on the vehicle 1 (1) or not (0). A parameter RF indicates whether the radio module 20 indicates a short distance (1) or a long distance (0). Accordingly, three classes are possible, which are divided into Fig. 3are entered, namely "Driver still seated" (first class), "Driver thrown a short distance" (second class), and "Driver thrown a long distance" (third class). The option in the upper right field, which would correspond to a seated driver who was thrown a long distance, is impossible in practice.

[0043] Data from the acceleration sensor 40 and the sound sensor 60 are used to classify the collision intensity. The sound sensor 60 determines whenever a measured sound intensity (SS) exceeds an intensity threshold ts. This is considered a collision event. In the matrix provided in this regard, the left-hand column distinguishes how often the sound intensity (SS) is greater than the intensity threshold ts, with a comparison being made with a collision threshold n. Furthermore, the acceleration sensor 30 is evaluated for an acceleration g, which is typically a deceleration, and this is evaluated, as shown, to determine whether it is less than or greater than an acceleration threshold tg.Accordingly, the collision intensity can be classified into one of four classes, namely "slow, few collisions" (first class), "slow, many collisions" (second class), "fast, few collisions" (third class), and "fast, many collisions" (fourth class).

[0044] Data from the pulse rate sensor 50 is used to classify the driver's health status (FGZ) into one of three classes. If the driver has a normal pulse rate, the "PR normal" class is used. If an abnormal pulse is present, indicating a potentially critical condition, the "PR abnormal" class is used. If no pulse is detected, the "PR = 0" class is used, indicating a potential risk of death. This allows rescue personnel to quickly assess the driver's health status, so that rescue measures can be prepared immediately. As described in Fig. 3As can be seen, these three classes are marked with three symbols, which are also shown below in Fig. 4 are used, namely "$" for "PR normal" (first class), "%" for "PR abnormal" (second class) and "!" for "PR = 0" (third class).

[0045] The decision module 7 decides how the classified information should be forwarded. Accordingly, information is passed to the communication module 8, which forwards the respective information to one or more of the recipients E. An example of this is described below with reference to Fig. 4 be given.

[0046] Fig. 4shows a table with entries, where each entry corresponds to a possible combination of classifications of the three data. The rows correspond to three classes A (first class), B (second class), C (third class) of the driver position FP after the collision. The columns labeled ZI1, ZI2, ZI3, ZI4 correspond to the four classes of collision intensity ZI. Each of these classes is further subdivided with respect to the classification of the driver health status FGZ, where the classifications related to Fig. 3 explained symbols are used.

[0047] Patterns can be defined from a total of 36 fields, with each pattern selecting a number of the displayed fields. If the combination of classifications corresponds to a field contained in a pattern, it can be specified that the correspondingly aggregated data be forwarded to one or more predetermined recipients E1, ..., E5. Thus, for example, data from a severe collision event, indicated, for example, by a collision intensity in the third or fourth class, can be forwarded to all specified recipients, whereas data from events in which the driver 2 is still sitting on the vehicle 1 and the pulse is normal, for example, are only forwarded to an insurance agency.

[0048] Overall, the procedure described here enables particularly practical and practically useful information to be provided to suitable recipients about collisions involving open vehicles, which enables a quick and appropriate response, in particular also the provision of rapid assistance.

[0049] The steps mentioned in the method according to the invention can be carried out in the specified order. However, they can also be carried out in a different order, as long as this is technically reasonable. The method according to the invention can be carried out in one of its embodiments, for example, with a specific combination of steps, in such a way that no further steps are carried out. However, in principle, further steps can also be carried out, even those not mentioned.

[0050] It should be noted that features may be described in combination in the claims and in the description, for example to facilitate understanding.

[0051] References in subclaims may indicate preferred combinations of the respective features, but do not exclude other combinations of features. List of reference symbols:

[0052] 1Vehicle 2Driver 4Processing unit 5Data acquisition module 6Evaluation module 7Decision module 8Communication module 10Satellite navigation system 20Radio module 25Further radio module 30Pressure sensor 40Acceleration sensor 50Pulse rate sensor 60Sound sensor EEceiver PosPosition FPDriver position after collision ZICollision intensity FGZDriver health status RFParameter for distance pParameter for pressure gAcceleration tgAcceleration threshold SSSound intensity tsSound threshold nCollision threshold

Claims

1. Method for supplying aggregated data after an impact event of an open vehicle (1), wherein the method comprises the following steps: - determining a position (Pos) of the vehicle (1), - determining one or more driver positions (FP) after the impact, impact intensity (ZI) and driver health condition (FGZ), - forming aggregated data based on the determined position (Pos) and the determined driver position (FP) after the impact, impact intensity (ZI) and / or driver health condition (FGZ), and - transmitting the aggregated data to a receiver (E), characterized in that - the impact intensity (ZI) is classified into one of four classes, - wherein the impact intensity (ZI) is classified into a first class when an acceleration sensor (40) indicates an impact at a low speed and an acoustic sensor (60) indicates a number of impacts below a collision threshold value (n), - wherein the impact intensity (ZI) is classified into a second class when an acceleration sensor (40) indicates an impact at a low speed and an acoustic sensor (60) indicates a number of impacts at least as great as the collision threshold value (n), - wherein the impact intensity (ZI) is classified into a third class when an acceleration sensor (40) indicates an impact at a high speed and an acoustic sensor (60) indicates a number of impacts below the collision threshold value (n), and / or - wherein the impact intensity (ZI) is classified into a fourth class when an acceleration sensor (40) indicates an impact at a high speed and an acoustic sensor (60) indicates a number of impacts at least as great as the collision threshold value (n).

2. Method according to Claim 1, - wherein the driver position (FP) after the impact, impact intensity (ZI) and driver health condition (FGZ) are determined and the aggregated data are formed based thereon.

3. Method according to one of the preceding claims, - wherein the driver position (FP) after the impact is determined - using a radio module (20) in the vehicle (1) and a radio module (25) which is worn by the driver (2), and / or - using a pressure sensor (30) which senses whether the driver (2) is positioned on a seat.

4. Method according to one of the preceding claims, - wherein the impact intensity (ZI) is determined - using at least one acceleration sensor (40), and / or - using at least one acoustic sensor (60).

5. Method according to one of the preceding claims, - wherein the driver health condition (FGZ) is determined using a pulse rate sensor (50).

6. Method according to one of the preceding claims, - wherein the driver position (FP) after the impact is classified into one of three classes which indicate a distance between the driver (2) and the vehicle (1) after the impact event.

7. Method according to Claim 6, - wherein the driver position (FP) after the impact is classified into a first class when a pressure sensor (30) indicates that the driver (2) is sitting on the vehicle (1), - wherein the driver position (FP) after the impact is classified into a second class when a pressure sensor (30) indicates that the driver (2) is not sitting on the vehicle (1) and radio modules (20, 25) indicate that a distance between the vehicle (1) and the driver (2) is below a distance threshold value, and / or - wherein the driver position (FP) after the impact is classified into a third class when a pressure sensor (30) indicates that the driver (2) is not sitting on the vehicle (1) and radio modules (20, 25) indicate that a distance between the vehicle (1) and the driver (2) is at least as great as the distance threshold value.

8. Method according to one of the preceding claims, - wherein the acceleration sensor (40) indicates an impact at a low speed when a maximum acceleration (g) during an impact event is below an acceleration threshold value (tg), and - wherein the acceleration sensor (40) indicates an impact at a high speed when a maximum acceleration (g) during an impact event is at least as great as the acceleration threshold value (tg).

9. Method according to one of the preceding claims, - wherein the acoustic sensor (60) indicates an impact each time the acoustic intensity (SS) exceeds an acoustic threshold value (ts).

10. Method according to one of the preceding claims, wherein the driver health condition (FGZ) is classified into one of three classes.

11. Method according to one of Claims 6 to 10, - wherein one or more patterns is defined, wherein each pattern defines a combination of classes, and - wherein the aggregated data are forwarded to a particular receiver (E) which is assigned to the pattern when all parameters which in combination are defined by the pattern are classified into one class.

12. Method according to one of Claims 6 to 11, - wherein the aggregated data in relation to driver position (FP) after the impact, impact intensity (ZI) and driver health condition (FGZ) are formed only from indications of classes into which the driver position (FP) after the impact, the impact intensity (ZI) and the driver health condition (FGZ) have been classified.

13. Method according to one of the preceding claims, - wherein the position (Pos) is determined using a satellite navigation system (10) in the vehicle (1).

14. Open vehicle (1), having an acceleration sensor (40) and an acoustic sensor (60), wherein the open vehicle (1) is configured to carry out a method according to one of the preceding claims, wherein the data of the acceleration sensor (40) and the acoustic sensor (60) are used to classify the impact intensity.