Method and device for actuating at least one personal protection device of a vehicle

Abstract

Method (600) for activating at least one personal protection device (115) of a vehicle (100), the method (600) comprising the following steps: - reading (610) at least one occupant signal (125, 215) representing a muscle tension state of at least one muscle of a body part (135) of a vehicle occupant (140) and / or an attention status of the vehicle occupant (140); and - controlling the personal protection means (115) using the occupant signal (125, 215) in order to actuate the personal protection means (115), characterized in that in the controlling step (620) a reaction pattern (Rx1) is determined from a plurality of reaction patterns of the vehicle occupant (140) using the at least one occupant signal (125, 215) and / or a travel parameter (200), wherein the controlling of the personal protection means (115) takes place on the basis of the determined reaction pattern (Rx1).

Description

State of the art

[0001] The invention is based on a device or a method according to the class of the independent claims. The present invention also relates to a computer program.

[0002] In recent decades, a very high level of safety has been achieved in vehicle traffic. In particular, passive safety measures and the further development of restraint systems, as well as more rigid car bodies, have continuously reduced the number of fatalities and serious injuries in accidents over the past 20 years. With the introduction of active safety measures, such as the Electronic Stability Program (ESP) or combined active and passive safety solutions such as Rollover Sensing (RoSe), Early Pole Crash Detection (EPCD), or Secondary Collision Mitigation (SCM), considerable progress has been made, particularly in reducing the severity of injuries in serious accidents.Due to the increased introduction of integrated safety systems as a result of the increased use of predictive sensors and automatic braking systems, the introduction of semi-autonomous driving and especially braking functions is currently taking place and an additional reduction in the risk of accidents and the consequences of accidents is to be expected.

[0003] A suitable estimation and prediction of occupant movement is advantageous for the correct adjustment of restraint systems in crash scenarios preceded by some type of driving maneuver or driving situation, such as a pre-crash maneuver. From the publication DE 10 2008 002 243 A1, an estimation method for determining occupant acceleration according to a determination rule from model parameters and vehicle deceleration is known. A determination without the aid of occupant sensors is proposed. The object of the present invention is to improve occupant protection in vehicle collisions with a preceding pre-crash phase and associated occupant movement. The focus of the invention is to provide a suitable prediction model of occupant movement based on a state of muscle tension and alertness.Using this prediction model, it is possible to provide precise information about the time and location of the occupant moving forward and thus also to gradually adapt the restraint system to the occupant movement.

[0004] DE 10 2011 106 247 A1 discloses a method for controlling a belt tensioner, in which a driving maneuver and / or the driver's attention level are inferred from the temporal progression of a state variable and / or an environmental variable of the vehicle. The belt tensioner is then activated depending on the detected driving maneuver and / or the driver's attention level.

[0005] From DE 10 2010 010 475 A1, a method for controlling a belt retractor is known in order to detect the muscle tone of the vehicle occupant by means of a sensor on or in the seat in order to be able to draw conclusions about his or her state of fatigue.

[0006] DE 10 2015 014 791 A1 discloses a method for determining the posture of a passenger using a plurality of sensors distributed over a large area of ​​a vehicle seat. A similar method is known from DE 10 2004 046 514 A1.

[0007] It is known from DE 10 2004 021 174 A1 that a safety-critical driving situation can be derived from the evaluation of body reactions. Disclosure of the invention

[0008] Against this background, the approach presented here presents a method, a device using this method, and finally a corresponding computer program according to the main claims. The measures listed in the dependent claims allow advantageous further developments and improvements of the device specified in the independent claim.

[0009] The approach presented here provides a method for actuating at least one personal protection device of a vehicle, the method comprising the following steps: - Reading in at least one occupant signal representing a muscle tension state of at least one muscle of a body part of a vehicle occupant and / or an attention status of the vehicle occupant; and - Controlling the personal protection device using the occupant signal to actuate the personal protection device.

[0010] A occupant protection device can be understood, for example, as an airbag, a seat adjustment unit, a belt tensioner or a similar device that reduces the risk of injury to a person in or on the vehicle in the event of an accident. An occupant signal can be understood as a signal that represents a state of muscle tension, muscle contraction, muscle relaxation, muscle activity or the like of at least one muscle of a body part of the or a vehicle occupant. Alternatively or additionally, the occupant signal can depict the alertness status of the vehicle occupant, for example whether the vehicle occupant is tired, sleepy or awake. A body part of the vehicle occupant can be understood to mean, in particular, the head and neck, an upper body or the arms or legs of the vehicle occupant.

[0011] The approach presented here is based on the finding that a personal protection device can be deployed effectively if the vehicle occupant can be more closely characterized in terms of their muscle relaxation and / or alertness status. For example, the head of a vehicle occupant who shows no or only minimal muscle activity in the neck or head area can be thrown significantly further forward in an accident than if there is high muscle tension in the neck or head area. The situation is similar with the alertness of the vehicle occupant; however, it should be noted that if the vehicle occupant is awake or alert, the movement amplitude of this vehicle occupant's head in an impact is not as great as if the vehicle occupant is tired or drowsy.This is due, for example, to the fact that an alert vehicle occupant can closely monitor traffic developments and, accordingly (usually already unconsciously), make compensatory movements of corresponding body parts, thus significantly reducing the uncontrolled forward movement of certain body parts, such as the head. The approach proposed here offers the advantage of being able to actuate the occupant protection devices more precisely than conventional approaches by using additional parameters to control them. This reduces the risk of injury to the vehicle occupant in the event of an accident and, on the other hand, avoids potentially unnecessary activation of occupant protection devices, especially irreversible occupant protection devices.

[0012] A favorable embodiment of the approach proposed here is one in which, in the reading step, the occupant signal is read in from a belt retractor and / or from an image sensor and / or an evaluation unit for evaluating data from an image sensor and / or a seat positioning device and / or a seat-integrated occupant weight sensor and / or a mobile device, such as a handheld smartphone. Such an embodiment offers the advantage that units already installed as standard in vehicles can usually be reused to implement additional functions, so that only very low additional costs arise for such additional functions.

[0013] According to another embodiment of the approach proposed here, several temporally consecutive occupant signals can be read in during the reading step, and the occupant signals can be processed, whereby a forward movement of at least one body part of the vehicle occupant is determined. Such an embodiment offers the advantage of being able to determine the muscle tension state of a body part of the vehicle occupant and / or the alertness status of the vehicle occupant significantly more precisely by processing the temporally consecutive occupant signals than would be possible by evaluating a snapshot.

[0014] Furthermore, an embodiment of the approach proposed here is conceivable in which at least one driving parameter is read in, wherein the movement of the at least one body part is determined during processing using the at least one driving parameter. A driving parameter can be understood, for example, as a physical quantity such as a lateral or longitudinal acceleration, a yaw rate, a speed, a pitch angle, and / or quantities derived or calculated therefrom, in particular one that changes as the vehicle moves.Such an embodiment of the approach proposed here offers the advantage that the attention status and / or the muscle tension state can be detected or assigned much more precisely by taking driving parameters into account, since the effect of external forces or quantities on at least one body part can provide a very precise statement about the muscle tension state on or in the corresponding body part or about the attention of the vehicle occupant.

[0015] Furthermore, according to one embodiment of the approach proposed here, in the actuating step, a reaction pattern can be determined from a plurality of reaction patterns of the vehicle occupant using the at least one occupant signal and / or a driving parameter, wherein the actuation of the personal protection device is carried out on the basis of the determined reaction pattern. A reaction pattern can also be referred to synonymously here as a reaction type or reaction pattern type. A reaction pattern can be understood as one of several types of how a movement of a vehicle occupant can be characterized during critical driving maneuvers such as emergency braking or an impact. For example, the vehicle occupant can adopt a "sloppy" (i.e. flexible or pliable) reaction pattern in which, for example, during a braking maneuver, the vehicle occupant has a high forward displacement of the head and / or upper body.It is also conceivable that the vehicle occupant adopts a "stiff" reaction pattern, in which they show high muscle tension and in which they show the slightest forward displacement of the head and / or upper body during a braking maneuver, for example. In another "normal" reaction pattern, which the vehicle occupant can adopt, for example, the muscle tension can lie in a normal range between the "sloppy" and "stiff" reaction patterns. The attention status of the vehicle occupant can also be divided or grouped into one of the various reaction patterns, whereby, for example, an awake vehicle occupant is more likely to recognize a critical driving situation and to tense muscles on or for the relevant body part accordingly, so that an awake vehicle occupant can also be assumed to be awake.Conversely, a tired vehicle occupant will also exhibit strong muscle tension in or for the affected body part, so that the tired and / or sleepy vehicle occupant would be more likely to be classified as having the "sloppy" reaction pattern. Such an embodiment of the approach presented here offers the advantage of being able to perform, for example, a predetermined parameterization of the personal protection device for activation by selecting one of several reaction patterns. This allows the numerical or circuit-related implementation effort to be kept very low, while offering a high degree of flexibility, for example, if international adaptations need to be made.

[0016] A particularly advantageous embodiment of the approach proposed here is one in which, in the control step, a reaction pattern is selected from a plurality of reaction patterns dependent on the vehicle occupant and / or from a plurality of predetermined reaction patterns. For example, the various available reaction patterns can depend on the age, weight, gender, height, and / or nationality / origin, etc., of the vehicle occupant, allowing a selection from a highly person-specific set of reaction patterns. This can also be made dependent on the alertness level, particularly of a passenger. Such an embodiment enables very precise parameterization of the relevant personal protection device.Predetermined reaction patterns can be understood as a reaction pattern that is read, for example, from a memory and applies to a large number of vehicle occupants. Such an embodiment advantageously enables the integration of specific movement patterns into predetermined accident scenarios, so that, based on knowledge of general hazard relationships for vehicle occupants in specific traffic situations, a classification of the various reaction patterns is possible.

[0017] Another advantageous embodiment of the approach proposed here is one in which the reaction pattern of the vehicle occupant is repeatedly determined during the activation step while the vehicle is traveling. Such an embodiment of the approach proposed here offers the possibility, particularly during longer vehicle journeys, of conducting a timely assessment of the vehicle occupant's muscle tension and / or alertness level, and of being able to activate the personal protection device accordingly based on current and timely information or parameters.

[0018] Furthermore, in a particular embodiment of the approach proposed here, the activation of the personal protection device can be carried out in the activation step using multiple reaction patterns for the vehicle occupant, in particular with the reaction pattern that is closer in time to the activation time of the personal protection device receiving greater weight. For example, different parameter sets assigned to the individually detected reaction patterns of the vehicle occupant can be linked to one another and used as the basis for the activation of the personal protection device.It is particularly advantageous to weight the respective recognized reaction patterns depending on the time of detection for the respective reaction pattern in question, in particular whereby the reaction pattern recognized closest in time to the activation time of the personal protection device is given a higher weighting than a reaction pattern recognized further back in time.

[0019] This method can be implemented, for example, in software or hardware or in a mixture of software and hardware, for example in a control unit or in a sensor system.

[0020] The approach presented here further provides a device designed to perform, control, or implement the steps of a variant of a method presented here in corresponding devices. This embodiment of the invention in the form of a device also allows the problem underlying the invention to be solved quickly and efficiently.

[0021] For this purpose, the device can have at least one computing unit for processing signals or data, at least one memory unit for storing signals or data, at least one interface to a sensor or an actuator for reading sensor signals from the sensor or for outputting data or control signals to the actuator, and / or at least one communication interface for reading or outputting data embedded in a communication protocol. The computing unit can be, for example, a signal processor, a microcontroller, or the like, wherein the memory unit can be a flash memory, an EEPROM, or a magnetic storage unit.The communication interface can be designed to read in or output data wirelessly and / or wired, wherein a communication interface that can read in or output wired data can read this data, for example, electrically or optically from a corresponding data transmission line or output it to a corresponding data transmission line.

[0022] In this case, a device can be understood as an electrical device that processes sensor signals and outputs control and / or data signals depending on them. The device can have an interface, which can be implemented in hardware and / or software. In a hardware implementation, the interfaces can, for example, be part of a so-called system ASIC, which contains a wide variety of functions of the device. However, it is also possible for the interfaces to be separate integrated circuits or to consist at least partially of discrete components. In a software implementation, the interfaces can be software modules that are present, for example, on a microcontroller alongside other software modules.

[0023] Also advantageous is a computer program product or computer program with program code that can be stored on a machine-readable carrier or storage medium such as a semiconductor memory, a hard disk memory or an optical memory and is used to carry out, implement and / or control the steps of the method according to one of the embodiments described above, in particular when the program product or program is executed on a computer or a device.

[0024] Examples of the approach presented here are shown in the drawings and explained in more detail in the following description. It shows: Fig. 1 a vehicle in which a device for actuating at least one personal protection means according to an embodiment of the approach proposed here; Fig. 2 a possible flowchart for a variant of the approach presented here; Fig. 3 two diagrams showing values ​​from an evaluation of several test drives from a test project; Fig. 4 a representation of the head forward displacement versus the braking deceleration and assignment of three exemplary muscle activity types; Fig. 5 thus a diagram explaining the types of muscle activity depending on different personal parameters of a vehicle occupant; and Fig. 6 a flowchart of a method according to an embodiment.

[0025] In the following description of advantageous embodiments of the present invention, the same or similar reference numerals are used for the elements shown in the various figures and having a similar effect, whereby a repeated description of these elements is omitted.

[0026] Fig. 1 shows a vehicle 100 in which a device 110 for actuating or activating at least one passenger protection device 115 is provided according to an exemplary embodiment of the approach proposed here. The passenger protection device 115 can be configured, for example, as a belt tensioner or an airbag. The device 110 has an interface 120 for reading in at least one occupant signal 125, which is output, for example, by an image sensor such as an interior camera 130 for detecting the passenger compartment of the vehicle 100 and which directly or indirectly represents a muscle tension state of at least one muscle of a body part, such as the head 135, or a muscle tension state of a vehicle occupant 140.It is also conceivable that the occupant signal 125 is provided by the belt tensioner as a passenger protection device 115, wherein the occupant signal 125 represents a force level, tension, or tightness of the vehicle seat belt 127 and / or a roll-out status of the vehicle seat belt 127, thereby providing an indication of the forward displacement of a vehicle occupant. Alternatively or additionally, the occupant signal 125 can represent the attention status of the vehicle occupant 140. An attention status can be understood, for example, as the degree of attention with which the vehicle occupant 140 observes the traffic situation.Depending on the occupant signal 125 or a signal derived from the occupant signal 125, such as a reaction type or pattern of the vehicle occupant 140 that is independent of the occupant signal 125, the personal protection means 115 is now controlled in a control unit 145 belonging to the device 110 using the occupant signal 125 in order to activate or actuate the personal protection means 115.

[0027] An important aspect of the approach presented here is the estimation of the tension state and alertness status of an occupant 140, for example, based on a dynamic evaluation of the occupant's forward displacement and occupant kinematics. This is estimated under normal driving conditions and is thus subject to the parameters of normal driving dynamics with maximum lateral and longitudinal accelerations of up to 1g. A special aspect of the estimation can be seen in the assignment of a reaction pattern type, for example, from "tense" to "relaxed," based on continuous measurements and a statistical methodology. As a result, for example, an adapted control of both reversible and irreversible protection systems is triggered in the event of a collision or another safety-critical driving condition of the vehicle. Various interior sensors can be used as measurement sensors.It is conceivable to use sensors integrated in the belt, e.g. a rotation sensor installed on the spindle in the belt machine or force measuring sensors located in an electrical belt.

[0028] Using such a sensor, for example, the current belt extension can be measured. In a special way, various values ​​can be sampled and measured in a chronological sequence. The belt extension measured there is representative of the upper body movement of the occupant 140. If the belt extension measured at the belt spindle is then related, for example, to driving dynamics values, the relationship between the vehicle and the occupant movement can be advantageously represented. Vehicle variables considered as driving dynamics values ​​include, for example, longitudinal and lateral acceleration, rotational acceleration, yaw rates, pitch angles, speeds, etc., and variables derived and calculated from them.

[0029] This relationship can very well characterize the muscle tension state of a vehicle occupant. For example, a rough distinction can be made between three different (basic) types of reactions of a vehicle occupant to different driving maneuvers: - “sloppy”: Flexible, pliable, shows the highest forward displacement, for example during a braking maneuver; - “stiff”: stiff, tense, showing, for example, the slightest forward displacement during a braking maneuver of the vehicle 100; and - "normal": lies between "sloppy" and "stiff".

[0030] These reaction types, for example, are largely dependent on the individual and age and are rooted in the occupant's personal characteristics / lifestyle, etc. Additionally, there are temporarily variable characteristics, e.g., falling asleep in the passenger seat or becoming tense in a dangerous situation. In the first case, a "stiff" type can also fall into the "sloppy" mode, just as in the second case, a "sloppy" type can also switch to the "stiff" type. Naturally, the attention factor plays a correspondingly large role here.

[0031] An alternative occupant sensing method utilizes the interior camera 130 in the vehicle 100. Using such a camera 130, for example, the forward displacement of the occupant 140 can be tracked and measured over time. Depending on the resolution and sampling rate, a similarly high level of accuracy can be achieved as with a belt-integrated system. A special form of the interior camera 130 is a driver observation camera. Normally, the focus here is on the occupant's face and eyes. However, relevant information on the occupant's kinematics can also be derived from this. In addition, eye detection or the detection of parameters relating to eye opening, including the temporal change or the speed of eye movement, enables attention classification, which in turn is used as algorithm parameters for reaction pattern grouping.

[0032] The following comments can be made as advantages of the approach presented here: - Increased occupant safety → reduction of occupant load and thus the severity of injuries, especially in cases where a collision can no longer be prevented and there is a dedicated pre-crash phase with occupant movement. - Enabler and motivator for adaptive restraint systems, e.g. adaptive airbag, electromotive retractor, adaptive belt force limiter, etc. - Dual or additional use of installed sensors, such as an interior camera (which is installed for other purposes). - Use for the control of comfort systems, e.g. dynamic driving seats; occupant type-optimized control. - UX factor: Feedback to the occupant regarding type grouping and attention levels is possible. - Additional benefit for the control of electric motor retractors for actively retracting a forward-facing occupant (not by braking), as the required force can be better estimated. (→ More comfortable adjustment possible). - With increasing automation, occupant restraint strategies can be adapted to the vehicle interior.

[0033] Fig. Figure 2 shows a possible flow chart for a variant of the approach presented here. It describes the determination of a reaction pattern for a specific dynamic maneuver x1, e.g., partial braking during a journey.

[0034] According to the Fig. 2, for the dedicated driving dynamics maneuver x1, a driving parameter 200, for example in the form of an acceleration value a x , a y , a z or a speed value v x , vy , v z determined (each related to one of the three spatial directions x, y or z) and this driving parameter 200 is transferred to a threshold value decider 205. In the threshold value decider 205, it is checked whether the driving parameter 200 is above a threshold value THD. If this is the case (branch J), the driving parameter 200 is transferred to a comparator 210, whereby if the driving parameter 200 is not greater than the threshold value THD, no further action takes place (branch N).

[0035] Furthermore, the occupant signal 215 is detected by an occupant sensor system OCC, which comprises, for example, a sensor of a belt retractor or the camera 125, which is then also fed to the comparator 210.

[0036] In the comparator 210, using predefined relationships, it is now determined which reaction (pattern) type best fits the currently observed vehicle occupant. For this purpose, for example, a first relationship 220 is used in which an occupant movement I is represented over time t. For example, in the case of high muscle tension and / or a high level of attention, a "stiff" reaction type (type A) in the relationship diagram 220 may fit the vehicle occupant 140 well, in which only a slight occupant movement I is recorded over time t during the selected driving dynamics maneuver x1. If the muscle tension and / or attention of the vehicle occupant 140 is somewhat lower, a higher occupant movement I over time t will be recorded during the dedicated driving dynamics maneuver (type B, or referred to as a "normal" reaction pattern or reaction type).With even lower muscle tension and / or attention of the vehicle occupant 140, an even greater occupant movement I of the vehicle occupant 140 will be recorded over time t than for type B, which can then be seen as reaction pattern type C in the representation from the correlation diagram 220. Finally, for the reaction pattern type "sloppy" (type D in the correlation diagram 220), in which the lowest muscle tension and / or attention of the vehicle occupant 140 is recorded, a greatest occupant movement I of the vehicle occupant 140 will be recorded over time t during the dedicated driving dynamics maneuver or even a normal driving state.

[0037] Furthermore, the comparator 210 also considers a relationship 225 between the vehicle movement F over time t, from which, for example, the physical relationships during a cornering of the vehicle 100 or a braking of the vehicle 100 at a traffic light on the vehicle occupant 140 during the specific driving dynamics maneuver can be identified, which act on the vehicle occupant 140 independently of the muscular tension and / or attention of the vehicle occupant 140. In this way, the vehicle movements can be used to compensate for occupant movements that are independent of the muscular tension and / or attention of the vehicle occupant 140.

[0038] Finally, a relationship 230 can also be taken into account in the comparator 210, from which the occupant movement I is mapped to the vehicle movement F as a function of the currently present reaction type or reaction pattern (type) of the vehicle occupant 140 (for example, according to the representation in the relationship diagram 220). In this way, the respective vehicle occupant 140 can be individually adjusted or targeted as to how he or she will move in which state of attention or with which muscle tension in the respective specific driving dynamics maneuver.

[0039] From this data, using the occupant signal 215 and the driving parameter 200, the reaction type in maneuver x1 is determined in a unit 235 and output via an interface 240. This reaction pattern Rx1 can subsequently be used in a unit 245 to control the personal protection device. Furthermore, even after the reaction pattern Rx1 has been output, the comparison step in comparator 210 can now be performed with the current occupant signal 215 and driving parameter 200 read in again. In this way, continuous monitoring of the vehicle occupant 140 can take place, so that the personal protection device 115 can be actuated based on parameters detected in real time.

[0040] In summary, it can be stated that the result from the comparison of the driving dynamics variables (“VEH”) with the occupant dynamics variables (“OCC”) is, for example, reaction type Rx1. It should be noted that the determination is a time-dependent process, i.e., to determine dynamic values, all values ​​corresponding to t* are determined. The occupant values ​​are only evaluated when a relevant driving dynamics maneuver, e.g., a braking maneuver starting in the 0.1-0.2 g range, occurs. At the beginning of a journey, a standard reaction type S is assumed, which corresponds to today's restraint strategy. During the course of the evaluation, a reclassification into a corresponding reaction type A, B, C, etc. takes place. Another example is the beginning of a lane change, in which lateral movements are brought together with the y-accelerations of the vehicle 100.As soon as a defined threshold THD is reached for the driving dynamics values, the comparison is carried out as shown in . Fig. 2, shown on the right.

[0041] Fig. Figure 2 shows an exemplary sequence of an embodiment for determining a reaction pattern for a specific driving dynamic maneuver x1, e.g., partial braking. As a result, a reaction type Rx1 is then recognized, output, and used to control a personal protection device. The exemplary reaction types A to D (in Fig. 2, top right) can be assigned depending on the vehicle's deceleration. Alternatively, stored curves can also be dependent on age, gender, mass, or even nationality.

[0042] Fig. Figure 3 shows two diagrams in which values ​​from an evaluation of 30 test drives with test subjects are presented. In the upper part of the diagram, the braking acceleration a during a braking maneuver is plotted over time t, whereas in the lower part of the diagram, a head displacement s is plotted over time t during a braking maneuver with assignment of a reaction type. In the upper part of the diagram, a high braking acceleration a is represented by a line with diamonds, a medium acceleration a by a line with triangles, and a low acceleration a by a line with squares. In the lower part of the diagram, the head displacement s (in mm) for a "sloppy" reaction type is represented by a line with diamonds, the head displacement s (in mm) for a "stiff" reaction type by a line with squares, and the head displacement (in mm) for a "normal" reaction type by a line with triangles. The algorithmic implementation of the graphs, i.e., the determination of the current reaction type of the vehicle occupant, can be carried out using characteristic maps stored in the control unit.

[0043] Examples of diagrams from the Fig. Three test drives were evaluated. The basis for the test drives were passengers who were only wearing a lap belt. From a corresponding video analysis, the kinematics for the individual test subjects could be evaluated. Fig. 3 On the left side, the different braking maneuvers from the family are shown, i.e., "high" corresponds to the outer envelope, "low" to the inner envelope, and "AVG" to the average value. The braking maneuver is a 1 g braking maneuver. The corresponding forward displacements of the occupant's head are shown in the same figure on the right. Depending on the type of activity, a different forward displacement is achieved. In this case, an increased head forward displacement can be observed due to the missing chest belt. However, the results shown here are also valid for fully belted occupants and for other measured values, such as chest forward displacement.

[0044] If the head forward displacement is divided by the corresponding time-synchronous braking acceleration, the values ​​for the first period of the braking maneuver are Fig. 4 shows three different reaction types: “sloppy” (line with diamonds), “medium” (line with squares) and “stiff” (lines with triangles).

[0045] It becomes clear that, similar to the schematic sketch in Fig. As indicated in Figure 2, right, a clear separation of the different patterns or reaction types can be seen. This makes it possible to assign different reaction types usable for a safety function based on the dynamic evaluation of occupant data such as forward displacement and the corresponding relationship to vehicle acceleration.

[0046] Fig. Figure 4 shows a representation of the head displacement s versus the braking deceleration a and assignment of three exemplary muscle activity types "sloppy", "medium" and "stiff". The different muscle activity types as in Fig. 4 are of course not only a function of forward displacement, but can depend on various factors, such as mass, age, gender, nationality / origin, etc., as described in the Fig. 5 is shown in more detail.

[0047] Fig. Figure 5 shows a diagram explaining the types of muscle activity depending on different personal parameters of a vehicle occupant. Fig. 5, the x-axis represents time and the y-axis represents an occupant-specific parameter for characterizing muscle activity (for example, head / thorax forward displacement versus vehicle acceleration). In such a diagram, the individual curves can be stored as data in a memory as a look-up table. For example, muscle activity type A, B, C, or D can be described as a function of, for example, mass. The look-up table thus serves as a representation of the functional relationships and is in Fig. 5 is one-dimensional. Other person-specific parameters, such as age, gender, or nationality, can also serve as input values. A combination of these parameters is also conceivable, allowing more complex functional relationships to be mapped. If no parameters are available, a reference value is set.

[0048] During a journey, a finite number of short driving maneuvers x1 ... x n hazards that can be evaluated and each assigns a reaction pattern Rx1 ... Rx nallow. Since the reaction pattern can change over the course of a journey due to a different level of attention of the occupant, e.g. sleep, a weighted method for assessing and assigning a time- and situation-adapted reaction pattern R# (# = number of the appropriate reaction pattern / reaction type) is necessary. The weighting method should give greater weight to evaluated driving maneuvers and corresponding assigned reaction patterns that are closer in time to the activation of the protection and / or comfort systems than to those that occurred at an earlier point in time during the journey. Possible approaches include (time-)weighted averaging, but also fuzzy methods or other deep learning approaches. For example, weighted averaging can be carried out using a ring buffer (first-in-first-out strategy).The weighting factors, which can be accessed in a memory, serve as the basis for the weighted averaging, and the classified reaction type serves as the input value. The calculation is then performed according to the following formula: Result=P1⋅A+P2⋅B+P3⋅C+P4⋅D∑A+B+C+D where P i the parameters and A, B, C, and D the respective proportions of the classifications of the Rx i from the ring buffer at the time i represent.

[0049] The main reason for the approach of time-weighted averaging, which is based on the trigger point, is that the evaluations of an active, fit state of a passenger who changes to a drowsy state during the journey should be given less weight, since otherwise an underestimation of the forward movement of the occupant (who would then have fallen asleep at the time of triggering) would occur and, associated with this, a less than optimal triggering of the adaptive restraint systems adapted to the determined forward displacement of the occupant would occur.

[0050] The focus of the evaluation, for example, based on seat belt extension, is the observation of the front passenger. For the driver, additional variables can be used as input variables (e.g., occupant signal 125), which can reflect, among other things, the intensity with which the steering wheel is held.

[0051] Fig.6 shows a flowchart of an embodiment of the approach presented here as a method 600 for activating at least one passenger protection device of a vehicle. The method comprises a step 610 of reading in at least one occupant signal representing a muscle tension state of at least one muscle of a body part of a vehicle occupant and / or an alertness status of the vehicle occupant. The method 600 also comprises a step 620 of controlling the passenger protection device using the occupant signal to actuate the passenger protection device.

[0052] If an embodiment comprises an “and / or” link between a first feature and a second feature, this is to be read as meaning that the embodiment according to one embodiment has both the first feature and the second feature and according to another embodiment has either only the first feature or only the second feature.

Claims

[1] Method (600) for activating at least one personal protection device (115) of a vehicle (100), the method (600) comprising the following steps: - reading (610) at least one occupant signal (125, 215) representing a muscle tension state of at least one muscle of a body part (135) of a vehicle occupant (140) and / or an attention status of the vehicle occupant (140); and - controlling the personal protection means (115) using the occupant signal (125, 215) to actuate the personal protection means (115), characterized by in that in the actuating step (620) a reaction pattern (Rx1) is determined from a plurality of reaction patterns of the vehicle occupant (140) using the at least one occupant signal (125, 215) and / or a travel parameter (200), wherein the actuation of the personal protection means (115) takes place on the basis of the determined reaction pattern (Rx1). [2] Method (600) according to claim 1, characterized by in that in the reading step (610) the occupant signal (125, 215) is read in by a belt retractor (115) and / or by an image sensor (130) and / or an evaluation unit for evaluating data from an image sensor (130) and / or seat positioning device and / or seat-integrated occupant weight sensing and / or a mobile device. [3] Method (600) according to one of the preceding claims, characterized by in that in the step of reading in (610) a plurality of temporally successive occupant signals (125, 215) are read in and the occupant signals (125, 215) are processed, wherein a movement of at least the body part (135) of the vehicle occupant (140) is determined, estimated, estimated or predicted. [4] Method (600) according to claim 3, characterized byin that in the step of reading (610) at least one driving parameter (200) is further read in, wherein during processing the determination of the movement of the at least one body part (135) takes place using the at least one driving parameter (200). [5] Method (600) according to claim 1, characterized by in that in the step of controlling (620) a reaction pattern (Rx1) is selected from a plurality of reaction patterns (A, B, C, D) dependent on the vehicle occupant (140) and / or from a plurality of predetermined reaction patterns (A, B, C, D). [6] Method (600) according to one of the preceding claims, characterized by that in the step of controlling (620) during a journey of the vehicle (100) the reaction pattern (Rx1) of the vehicle occupant (140) is repeatedly determined. [7] Method (600) according to claim 6, characterized byin that in the actuating step (620) the actuation of the personal protection means (115) takes place using a plurality of reaction patterns (Rx1, A, B, C, D) for the vehicle occupant (140), in particular wherein the reaction pattern (Rx1, A, B, C, D) which is closer in time to an actuation time of the personal protection means (115) is given a higher weight. [8] Device arranged to carry out steps of the method (600) according to one of the preceding claims in corresponding units (120, 145). [9] Computer program adapted to carry out the method (600) according to any one of claims 1 to 7. [10] A machine-readable storage medium on which the computer program according to claim 9 is stored.

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