Procedure and control unit for personal protection in a vehicle

Abstract

Procedure (200) for personal protection of a vehicle (100), wherein the procedure (200) comprises the following steps: Determining (210) a likely impact position (175) of an object (160; 660; 860) arranged in the vicinity of the vehicle (100) on the vehicle (100) using an environment sensor signal (154) from at least one environment sensor (120) arranged in the vehicle (100) to detect the vicinity of the vehicle (100); and Generating (220) a control signal (156) to control at least one safety device (140) of the vehicle (100) using the determined expected impact position (175) and a collision position (170; 870) calculated using a collision sensor signal (152) caused by a collision with the object (160; 660; 860) from at least one collision sensor (110) of the vehicle (100), characterized by a step (230) of fusing the determined expected impact position (175) and the collision position (170; 870) to determine a fused impact position located between the expected impact position (175) and the collision position (170; 870), wherein in the step (220) of generating the control signal (156) is generated using the fused impact position, wherein in step (230) of merging a mean or median or weighted sum is formed from the determined expected impact position (175) and the collision position (170; 870).

Description

State of the art

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

[0002] Various types of sensors can be used in vehicles to detect collisions with objects and / or people. If a collision is detected, on-board safety devices can be activated.

[0003] DE 103 23 483 A1 describes a device for determining a relative speed between a vehicle and an impact object.

[0004] DE 10 2005 006 763 A1 also discloses a method in which the relative speed of a first object is detected before it impacts a moving second object, such as a vehicle. In addition, the force acting upon impact is recorded.

[0005] From the document DE 10 2006 047 629 A1 a method is known for calculating the point of impact of the body of a pedestrian on the hood of a vehicle, which enables a targeted activation of the protective means of the motor vehicle.

[0006] From the document DE 10 2012 202 835 A1 a method for checking the plausibility of a collision parameter using an impact sensor signal is known. Disclosure of the invention

[0007] Against this background, the approach presented here presents a method, a control unit that uses this method, and finally a corresponding computer program according to the main claims. The measures listed in the dependent claims enable advantageous further developments and improvements of the device specified in the independent claim.

[0008] According to embodiments of the present invention, in particular, a calculation of the expected impact position of an object, for example, a pedestrian, can be carried out using environmental sensors installed in a vehicle and this expected impact position can be used within a pedestrian protection algorithm. In this case, for example, sensor data from environmental sensors and collision sensors can be combined in a suitable manner.

[0009] Advantageously, according to embodiments of the present invention, such use of a predicted object impact position from a forward-looking environment sensor in a vehicle, for example within a pedestrian protection algorithm, can improve a triggering decision regarding personal protection devices. Thus, the reliability and accuracy of the protection of vehicle occupants and, additionally or alternatively, pedestrians can be inexpensively increased.

[0010] A method for personal protection for a vehicle is presented, comprising the following steps: Determining a probable impact position of an object arranged in an environment of the vehicle on the vehicle using an environment sensor signal from at least one environment sensor arranged in the vehicle for detecting the environment of the vehicle; and Generating a control signal for controlling at least one safety device of the vehicle using the determined expected impact position and a collision position calculated using a collision sensor signal from at least one collision sensor of the vehicle caused by a collision with the object.

[0011] This method can be implemented, for example, in software or hardware or in a hybrid form of software and hardware, for example in a control unit. The vehicle can be a motor vehicle, in particular a road-bound motor vehicle, for example a passenger car, a truck, or another commercial vehicle. The object can be a person or an object in the vicinity of the vehicle. The safety device can be designed to protect a person in the vicinity of the vehicle and additionally or alternatively an occupant of the vehicle from the consequences of a collision. In the generating step, the control signal can also be generated using an anticipated time of impact of the object on the vehicle, determined using the environment sensor signal.The determination step can be repeated or carried out for several objects, whereby in the generation step several objects can be taken into account for the control signal.

[0012] According to one embodiment, the method can comprise a step of fusing the determined expected impact position and the collision position to determine a fused impact position located between the expected impact position and the collision position. In this case, in the generating step, the control signal can be generated using the fused impact position. In particular, the fused impact position can correspond to the expected impact position, the collision position, or an intermediate position between them. In this case, fusing can be understood as assigning and / or combining data into a common data set. Such an embodiment offers the advantage that the accuracy and reliability of detecting an actual position of contact with the object can be increased.

[0013] In the fusion step, a mean, a median, or a weighted sum can be calculated from the determined expected impact position and the collision position. This embodiment offers the advantage that data fusion can be performed quickly and easily.

[0014] The method can also include a step of comparing a deviation between the determined expected impact position and the collision position with at least one deviation threshold. In this case, in the generation step, the control signal can be generated depending on the result of the comparison. In particular, if the deviation falls below or meets the deviation threshold, the control signal can be generated using the expected impact position and the collision position. Such an embodiment offers the advantage that a plausibility check of sensor signals can be achieved, thus ensuring reliable detection of the actual contact position between the object and the vehicle.

[0015] In the execution step, a further comparison can be performed between a probable time of impact of the object on the vehicle, determined using the environment sensor signal, and a collision time calculated using the collision sensor signal. In the generation step, the control signal can be generated depending on the result of the further comparison. In particular, the control signal can be generated using the probable impact position and the collision position, up to a predefinable maximum time difference between the probable time of impact and the calculated time of collision. Such an embodiment offers the advantage that a temporal plausibility check of the sensor signals can also be performed in order to increase the accuracy of collision detection.

[0016] In a further embodiment, the temporal plausibility check and / or the spatial plausibility check are interdependent. In one variant, the deviation threshold for comparing the determined and predicted impact position is adjusted depending on the difference between the expected impact time and the calculated collision time. If the time difference is small, the deviation threshold is raised, whereby the control signal can be generated even if the difference between the determined and predicted impact position is larger. In a second variant, the maximum time difference between the expected impact time and the collision time is adjusted depending on the difference between the predicted and determined impact positions.If there is a small spatial deviation between the predicted and determined impact position, the maximum time difference between the expected impact time and the collision time is increased, allowing the control signal to be generated even with a larger time difference. This embodiment can be advantageously used to determine a general system inaccuracy and / or measurement inaccuracy and adapt the generation of the control signal accordingly. This allows for even better verification of fluctuations between different measured objects and object types, and the tolerated total deviation can be further reduced with comparable results.

[0017] The interdependence of prediction and measurement inaccuracies can also be visualized geometrically by using an xy coordinate system and plotting, for example, the deviation in the impact position on the x-axis and the deviation in the impact time on the y-axis. The area in which the predicted object is related to the measured impact is, for example, a circle created by a fixed radius (if the deviations in the impact position and time were considered separately, a rectangle would result). In addition to a circular dependency (e.g., Euclidean distance of deviations = circular shape), other dependencies are also possible (e.g., Manhattan distance = diamond shape, for faster calculation).

[0018] Furthermore, in the generating step, the control signal can be generated using position data that represents a position of the at least one safety device relative to a detection range of the at least one environmental sensor. In this case, in the generating step, the control signal can also be generated using further position data that represents a position of the object relative to the vehicle. Such an embodiment offers the advantage that a further limitation of the collision area can be achieved in order to be able to specifically control at least one affected safety device or an affected part of a safety device.

[0019] Furthermore, in the generation step, the control signal can be generated using object data that represents a type of object determined using the environmental sensor signal. The object data can, in particular, indicate whether the object is a person or an object. The object data can also be provided by the at least one environmental sensor. Such an embodiment offers the advantage that the control of the at least one safety device can be carried out more reliably and in a more situation-appropriate and accurate manner, so that a setting of the at least one safety device that is suitable for the collision object can be reliably made.

[0020] Furthermore, the control signal generated in the generating step can be configured to set a trigger threshold for triggering the at least one safety device depending on the environmental sensor signal and additionally or alternatively depending on the collision sensor signal. In particular, the control signal can include command information that can cause the trigger threshold to be set to robust, for example, if the object is an object, or to sensitive, for example, if the object is a person. Such an embodiment offers the advantage that personal protection can be implemented safely depending on the situation.

[0021] The control signal generated in the generating step can be configured to set the triggering threshold for a time period within which an expected time of impact of the object on the vehicle, determined using the environmental sensor signal, lies. Outside of the time period, the triggering threshold can be set to a standard or preset value. Such an embodiment offers the advantage that, for example, in a collision involving multiple objects, a suitable triggering threshold can be set for each object at the respective collision time in order to improve personal protection.

[0022] The approach presented here further provides a control unit configured 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 control unit also allows the problem underlying the invention to be solved quickly and efficiently.

[0023] For this purpose, the control unit 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 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 EPROM, 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.

[0024] In this context, a control unit can be understood as an electrical device that processes sensor signals and outputs control and / or data signals depending on them. The control unit can have an interface that 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 control unit. 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.

[0025] In an advantageous embodiment, the control unit controls a protective device of the vehicle for personal protection. For this purpose, the control unit can, for example, access at least one read sensor signal. Control is achieved via actuators, such as pyrotechnic ignition devices, mechanical actuators, or the like.

[0026] 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.

[0027] Embodiments of the invention are illustrated in the drawings and explained in more detail in the following description. It shows: Fig. 1 a schematic representation of a vehicle with a system for personal protection according to an embodiment; Fig. 2 a flowchart of a method for personal protection according to an embodiment; Fig. 3 a schematic representation of the vehicle with the personal protection system from Fig. 1; Fig. 4 a schematic representation of the vehicle with the personal protection system from Fig. 1 or Fig. 3; Fig. 5 a schematic representation of the vehicle with the personal protection system from Fig. 1, Fig. 3 or Fig. 4; Fig. 6 a schematic representation of the vehicle with the personal protection system from Fig. 1, Fig. 3, Fig. 4 or Fig. 5 with several objects in the vicinity of the vehicle; Fig. 7 a schematic representation of the vehicle with the personal protection system from Fig. 1, Fig. 3, Fig. 4, Fig. 5 or Fig. 6 when driving straight ahead; Fig. 8 a schematic representation of the vehicle with the personal protection system from Fig. 1, Fig. 3, Fig. 4, Fig. 5, Fig. 6 or Fig. 7 when cornering; Fig. 9 shows a diagram of a collision sensor signal and a threshold value for the personal protection system from Fig. 1, Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7 or Fig. 8; and Fig. 10 a diagram of a collision sensor signal and an adjusted threshold value for the personal protection system from Fig. 1, Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7 or Fig. 8.

[0028] 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.

[0029] Fig. Figure 1 shows a schematic representation of a vehicle 100 with a personal protection system according to one exemplary embodiment. The vehicle 100 is a motor vehicle, in particular a road-bound motor vehicle, for example, a passenger car. The vehicle 100 has the personal protection system.

[0030] The personal protection system has, according to the Fig. 1, the exemplary embodiment shown has, by way of example, only a collision sensor 110 for detecting a collision, an environment sensor 120 for detecting the environment of the vehicle 100, a control unit 130 and a safety device 140 for personal protection.

[0031] For example only, the collision sensor 110 is embodied as a pressure hose sensor, while the surroundings sensor 120 is embodied as a vehicle camera. The surroundings sensor 120 has a detection area 125 in the surroundings of the vehicle 100. The safety device 140 is, for example, a front-end structure with adjustable rigidity, for example, a deployable hood and / or an external airbag.

[0032] The control unit 130 is connected to the collision sensor 110, the environment sensor 120, and the safety device 140 in a signal-transmitting manner. The control unit 130 is configured to read in a collision sensor signal 152 from an interface to the collision sensor 110, read in an environment sensor signal 154 from an interface to the environment sensor 120, and output or provide a control signal 156 for controlling the safety device 140 to an interface to the safety device 140.

[0033] In other words, the control unit 130 is designed to provide the control signal 156 using the collision sensor signal 152 and the environment sensor signal 154.

[0034] Furthermore, Fig. 1 shows an object 160 in the surroundings of the vehicle 100. The object 160 is merely an example of a person. The object 160 is partially located within the detection range 125 of the environment sensor 120 of the vehicle 100.

[0035] The control unit 130 has a determination device 132 and a generation device 134. The determination device 132 is designed to determine a probable impact position 175 of the object 160 arranged in the environment of the vehicle 100 on the vehicle 100 using the environment sensor signal 154. The generation device 134 is designed to generate the control signal 156 using the determined probable impact position 175 and a collision position 170. The collision position 170 is calculated using the collision sensor signal 152 caused by a collision with the object 160.

[0036] Fig. 2 shows a flowchart of a method 200 for personal protection according to an embodiment. The method 200 for personal protection is used in conjunction with the vehicle of Fig. 1 or a similar vehicle. Furthermore, the method 200 for personal protection for a vehicle using the personal protection system or the control unit from Fig. 1 or a similar system or control device.

[0037] The method 200 for personal protection comprises a step 210 of determining a probable impact position of an object located in the vehicle's surroundings on the vehicle using an environment sensor signal from at least one environment sensor located in the vehicle for detecting the surroundings of the vehicle. Furthermore, the method 200 for personal protection comprises a step 220 of generating a control signal for controlling at least one safety device of the vehicle. The generating step 220 is carried out using the determined probable impact position and a collision position calculated using a collision sensor signal from at least one collision sensor of the vehicle caused by a collision with the object.

[0038] According to one embodiment, in step 220 of generating, the control signal is generated using position data that represents a position of the at least one safety device relative to a detection range of the at least one environmental sensor. Additionally or alternatively, in step 220 of generating, the control signal is generated using object data that represents an object type determined using the environmental sensor signal.

[0039] According to one embodiment, the control signal generated in step 220 of generating is configured to set a triggering threshold for triggering the at least one safety device depending on the environment sensor signal and / or the collision sensor signal. Optionally, the control signal generated in step 220 of generating is configured, in particular, to set the triggering threshold for a period of time within which an expected time of impact of the object on the vehicle, determined using the environment sensor signal, lies.

[0040] Optionally, the method 200 for personal protection also includes a step 230 of merging the determined probable impact position and the collision position to determine a fused impact position located between the probable impact position and the collision position. The merging step 230 can be executed between the determining step 210 and the generating step 220. In this case, in the generating step 220, the control signal is generated using the fused impact position. The merging step 230 can be executed between the determining step 210 and the generating step 220. According to one embodiment, in the merging step 230, a mean value or a median value is formed from the determined probable impact position and the collision position.

[0041] According to a further exemplary embodiment, the method 200 for personal protection additionally or alternatively comprises a step 240 of performing a comparison of a deviation between the determined probable impact position and the collision position with at least one deviation threshold value. In step 220 of generating, the control signal is generated depending on a result of the comparison performed in step 240 of performing. The step 240 of performing the comparison can be executed between the step 210 of determining and the step 220 of generating. Optionally, in step 240 of performing, a further comparison is performed between a probable time of impact of the object on the vehicle determined using the environment sensor signal and a collision time calculated using the collision sensor signal.In step 220 of generating, the control signal is generated depending on a result of the further comparison.

[0042] Fig. 3 shows a schematic representation of the vehicle 100 with the personal protection system from Fig. 1. Here, the vehicle 100 and the personal protection system in Fig. 3, for reasons of representation, only the collision sensor 110 and the detection range 125 of the environment sensor are shown as examples. Furthermore, the object 160 in the form of a person and the expected impact position 175 are shown. The object 160 is partially located within the detection range 125. A directional arrow illustrates a relative movement between the object 160 and the vehicle 100, more precisely, the expected impact position 175.

[0043] Fig. 4 shows a schematic representation of the vehicle 100 with the personal protection system from Fig. 1 or Fig. 3. Here, the vehicle 100 and the personal protection system in Fig. 4, for reasons of representation, only the collision sensor 110 and the detection range 125 of the environment sensor are shown as examples. Furthermore, the object 160 in the form of a person, the calculated collision position 170, and the expected impact position 175 are shown. The object 160 is partially located within the detection range 125. A directional arrow illustrates a relative movement between the object 160 and the vehicle 100, more precisely the calculated collision position 170. Furthermore, Fig. 4 shows a deviation 480 between the calculated collision position 170 and the determined expected impact position 175.

[0044] In other words, show Fig. 3 and Fig. 4 a plausibility check of the calculated collision position 170 or of an impact position calculated by means of an acceleration sensor (PCS - Pedestrian Contact Sensor) or pressure tube sensor (PTS - Pressure Tube Sensor) with the aid of the determined probable impact position 175 or of a probable environmental sensor impact position.

[0045] An advantage here is the plausibility of the impact position or collision position 170 of the object 160 or pedestrian actually calculated using PTS / PCS. Fig. 3 shows the vehicle 100, which is equipped with the environment sensor, for example a camera, and can detect a pedestrian and calculate a probable impact position 175 of the pedestrian on the vehicle 100. In addition, the vehicle 100 is equipped with the collision sensor 110, for example in the form of a PTS. Thus, in Fig. 3 shows a calculation of an expected pedestrian impact point or an expected impact position 175 on the vehicle 100 by the environmental sensors of the vehicle 100.

[0046] In Fig. Figure 4 shows how the object 160 or the pedestrian impacts the vehicle 100. Based on the collision sensor signals or PTS signals, the actual pedestrian impact position or collision position 170 is calculated, which can still be verified for plausibility. In other words, Fig. 4 the calculation of a deviation 480 between the expected impact position 175 or the expected pedestrian impact point and the calculated collision position 170 or the pedestrian impact point calculated using the PTS signals with subsequent plausibility check of the calculated collision position 170 or the PTS pedestrian impact point.

[0047] The deviation 480 (Δimpact) between the expected impact position 175 (impact estimated ) or the expected pedestrian impact point and the calculated collision position 170 (impact calculated ) or the pedestrian impact point determined by the PTS signals according to Δimpact = |impact estimated - impact calculated| calculated. If the deviation 480 between the two positions is below a deviation threshold, i.e. Δimpact ≤ threshold, the calculated collision position 170 or the impact point calculated by the PTS is plausible and, for example, trigger thresholds of a pedestrian algorithm are changed in the robust or sensitive direction according to the impact position calculated (using PTS). However, if the deviation 480 between the expected and the calculated impact position is above the deviation threshold, then no or only a slight threshold adjustment is made in the algorithm based on the PTS-based collision position 170, as this may, for example, be inaccurate. For a PCS-based pedestrian protection system, the plausibility of the impact position is checked using the expected impact position in a similar way to the procedure shown.

[0048] In a further embodiment, not only the magnitude of the adjustment can be adjusted to the deviation of the deviation 480 and / or the temporal deviation, but additionally or alternatively the direction of the adjustment: In the case of a large deviation, the trigger thresholds can be changed, in particular, in the robust direction. A large difference between the predicted and measured value indicates that a misinterpretation of the situation may be present, whereby changing it in the robust direction can reduce the probability of false triggering.

[0049] However, in order to perform such a plausibility check of the collision position 170, it is advantageous, in addition to the above calculation, to freeze the expected impact position 175 provided by the environment sensor, together with an expected time to impact (TTI = Time to Impact), within the pedestrian protection algorithm before the pedestrian leaves the detection zone 125 or field of view of the environment sensor or enters a blind zone of the environment sensor. This ensures that the expected impact position 175 is available for the plausibility calculation when the pedestrian impacts the vehicle 100. Frozen data can also be understood as data from a past measurement cycle, which, without further measured values ​​from the measured object, can be used to predict, for example, the relative movement of the object. It is also conceivable that the data is not frozen, but a virtual, no longer visible object is simulated and an impact is predicted.

[0050] In the Fig. 3 and Fig. Figure 4 shows an example of how a plausibility calculation of the calculated collision position 170 or pedestrian impact position can be performed using the expected impact position 175 of the environmental sensors. Furthermore, the procedure also covers a plausibility calculation of an impact position for a non-pedestrian object.

[0051] Fig. Figure 5 shows a schematic representation of the vehicle 100 with the personal protection system of Fig. 1, Fig. 3 or Fig. 4. The representation in Fig. 5 of the illustration Fig. 4 except that instead of the deviation, a fusion 580 of the calculated collision position 170 and the determined expected impact position 175 is illustrated.

[0052] In other words, Fig. 5 shows the fusion 580 of the calculated collision position 170 or PTS / PCS impact position with the determined expected impact position 175 or environment sensor impact position. By fusion 580 of the expected impact position of the object / pedestrian 160 (coming from the environment sensor) and the impact position of the object / pedestrian 160 calculated using PTS / PCS, the impact position detection of the PTS / PCS can be improved. Fig. Figure 5 illustrates how the pedestrian impacts the vehicle 100. The collision position 170, or the actual pedestrian impact position, is calculated based on the collision sensor signals or PTS signals. A fused impact point is determined by fusion 580.

[0053] To improve the calculated collision position 170, the fusion 580 of the determined expected impact position 175 or the expected pedestrian impact point and the calculated collision position 170 can be performed to form a fused impact point. This fusion 580 of the two impact points can be performed, among other things, by calculating the mean and median values ​​or a weighted sum. Optionally, the fusion 580 of the two impact points can also be performed, among other things, only if the calculated collision position 170 is also plausible, see, for example, Fig. 4. The merged impact position lies somewhere between the expected impact position 175 and the calculated collision position 170, but not outside them.

[0054] Fig. Figure 6 shows a schematic representation of the vehicle 100 with the personal protection system of Fig. 1, Fig. 3, Fig. 4 or Fig. 5 with several objects 160 and 660 in an environment of the vehicle 100. Here, the vehicle 100 and the system for personal protection in Fig. 6, for reasons of representation, only the collision sensor 110 and the detection range 125 of the environment sensor are shown by way of example. Furthermore, a first object 160 in the form of a person or a pedestrian and a second object 660 in the form of a non-pedestrian object in the environment of the vehicle 100 are shown, as well as the calculated collision position 170 of the object 160 and the expected impact position 175 of the object 660. The first object 160 is arranged outside the detection range 125. The second object 660 is arranged partially within the detection range 125. Directional arrows illustrate a relative movement between the first object 160 and the vehicle 100, more precisely the calculated collision position 170, and between the second object 660 and the vehicle 100, more precisely the determined expected impact position 175.

[0055] In other words, Fig. 6 the possibility of object plausibility check using the calculated collision position 170 or PTS / PCS impact position and the determined expected impact position 175 or expected environmental sensor impact position. Such object plausibility check of the object / pedestrian 160 or 660 is possible, for example, using the expected impact position 175 or impact position and the expected time to impact or collision (TTI). This is particularly useful when multiple objects / pedestrians 160 or 660 are detected / hit by the vehicle 100. Here, based on the expected impact position 175 or impact position (from the environmental sensor system) and the collision position 170 calculated using PTS / PCS in conjunction with the TTI, it is possible to determine whether the struck object 660 or the struck pedestrian 160 also matches the object detected by the environmental sensor.

[0056] In Fig. 6, for example, a pedestrian, as the first object 160, strikes the right outer side of a bumper of vehicle 100 (detected via PTS / PCS). This pedestrian was not detected by the environment sensor due to the limited field of view or detection range 125 of the environment sensor. Instead, the environment sensor detects a non-pedestrian object or the second object 660 in its detection range 125 and then calculates an expected impact position 175 of the non-pedestrian object or the second object 660, for example, on the left side of the bumper.

[0057] In this case, a comparison is made between the calculated collision position 170 of the first object 160 and the expected impact position 175 of the second object 660 detected by the environment sensor. A deviation between the positions 170 and 175 in this example lies outside the range of values ​​determined, for example, with reference to Fig. 4 and, for example, above an additional second threshold. In this way, it can be determined that the second object 660 detected by the environment sensor is not a pedestrian, which impacts the right side of the bumper as the first object 160, because objects 160 and 660 do not match due to their impact positions. In this case, for example, the algorithm's thresholds are not adjusted sensitively or robustly; instead, the algorithm's default behavior is used. The same applies analogously to the reverse case, in which a non-pedestrian object is not detected by the environment sensor, while a pedestrian is detected and the non-pedestrian object impacts the vehicle 100 (here on the right) first.In this context, the TTI is also important to determine whether the object detected by the environment sensor not only coincides with the impact position but also with the hit object in terms of time.

[0058] Fig. Figure 7 shows a schematic representation of the vehicle 100 with the personal protection system of Fig. 1, Fig. 3, Fig. 4, Fig. 5 or Fig. 6 when driving straight ahead. 100 of the vehicle and the personal protection system are Fig. 7, for reasons of representation, only the collision sensor 110 and the detection range 125 of the environment sensor are shown as examples. Furthermore, the object 160 in the form of a person or a pedestrian and the calculated collision position 170 are shown. The object 160 is located outside the detection range 125. Directional arrows illustrate a relative movement between the object 160 and the vehicle 100, more precisely the calculated collision position 170. Furthermore, Fig. 7 illustrates a stay 780 of the object 160 in the detection area 125 during the relative movement. Fig. 7 shows a first area 712 with standard behavior or without coverage by the detection area 125 and a second area 714 with variable behavior or with coverage by the detection area 125.

[0059] Fig. Figure 8 shows a schematic representation of the vehicle 100 with the personal protection system of Fig. 1, Fig. 3, Fig. 4, Fig. 5, Fig. 6 or Fig. 7 when cornering. In Fig. 8, only the collision sensor 110 and the detection zone 125 of the environment sensor are shown for illustrative purposes of the vehicle 100 and the passenger protection system. Furthermore, a first object 160 in the form of a first person 160 or a first pedestrian 160, as well as a second object 860 in the form of a second person 860 or a second pedestrian 860 in the environment of the vehicle 100, as well as a first calculated collision position 170 and a second calculated collision position 870 are shown. The first object 160 is partially located within the detection zone 125. The second object 860 is located outside the detection zone 125. Directional arrows illustrate a relative movement between the first object 160 and the vehicle 100, more precisely the first calculated collision position 170, as well as between the second object 860 and the vehicle 100, more precisely the second calculated collision position 870.Also in . Fig. 7, the first area 712 with standard behavior or without coverage by the detection area 125 and the second area 714 with variable behavior or with coverage by the detection area 125 are shown.

[0060] With reference to Fig. 7 and Fig. 8 below explains the possibility of identifying an impact area on the bumper that can be covered by the environment sensors and incorporating this information into the pedestrian algorithm. One advantage is that, using the expected impact position of the object / pedestrian 160 and 860, an area on the bumper or a part of a safety device can be identified in which algorithm thresholds can be adjusted.

[0061] Out of Fig. Figure 7 shows that pedestrian 160 only briefly entered the detection zone 125 of the environment sensor. This may mean that pedestrian detection is performed using the PTS. In this case, the algorithm thresholds are not set to be robust or sensitive; instead, a standard behavior applies.

[0062] Which area 714 of the bumper is currently covered by the environment sensor and which area 712 cannot be covered is also determined by the environment sensor, e.g., also based on driving dynamics, and sent, for example, to an airbag control unit. It is then determined whether the calculated collision position 170 or 870 lies in the first area 712 or the second area 714 of the bumper. Only if the calculated collision position 170 or 870 lies in the second area 714 covered by the environment sensor, is a robust or sensitive setting of algorithm thresholds based on the detected object 160 or 860 performed. For the first area 712, a robust or sensitive setting of the algorithm thresholds is omitted.

[0063] In Fig. Figure 8 shows another example of the area-differentiated treatment of threshold adjustments. This is a curve. In this example, the first pedestrian 160 is not detected by the environment sensor, while the second pedestrian 860 is detected by the environment sensor. The environment sensor detects the curve, e.g., also via additional vehicle dynamics sensors, of the vehicle 100 and reports, for example, to the airbag control unit that the right area of ​​the bumper with the first area 712 is not detected by the environment sensor, while the left area of ​​the bumper with the second area 714 is detected by the environment sensor. If Fig. 8, if the first pedestrian 160 impacts the first area 712 of the bumper, no anticipatory sensitive adjustment of the algorithm thresholds takes place, provided that the first collision position 170 determined using PTS / PCS is also located in the first area 712. If, however, the second pedestrian 860 impacts the second area 714 of the vehicle bumper, the algorithm thresholds are sensitively adjusted, provided that the second collision position 870 determined using PTS / PCS is also plausible, compare with Fig. 4, and in the second area 714. In addition, a robust adjustment of the algorithm thresholds can be made if a detected object 160 or 860 is a non-pedestrian object and this object hits the second area 714. In this context, a fusion of expected and actual positions, compare with Fig. 5, as well as an object plausibility check, compare with Fig. 6, take place.

[0064] Fig. Figure 9 shows a diagram of a collision sensor signal and a threshold value for the personal protection system from Fig. 1, Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7 or Fig. 8. In the diagram, time t is plotted along the abscissa axis, while a pressure P is plotted along the ordinate axis. The pressure P corresponds to the sum of the pressure signals from a vehicle's collision sensor, which is designed as a pressure hose sensor. The sum of the pressure signals is derived from the sensor signals pL and pR from, for example, two sensor elements of the collision sensor.

[0065] Furthermore, a threshold value 910 is shown in the diagram, which represents, for example, a triggering threshold for triggering a safety device of the vehicle. Pressure values ​​below threshold value 910 indicate a collision between the vehicle and, for example, a small animal, while pressure values ​​above threshold value 910 represent a collision with a pedestrian. A first graph 920 shows a pressure curve representing a collision between the vehicle and a pedestrian. The first graph 920 extends into the area above threshold value 910. Thus, the pressure curve during the collision with the pedestrian exceeds threshold value 910. A second graph 930 shows a pressure curve representing a collision between the vehicle and a small animal. The second graph 930 extends below threshold value 910.

[0066] The Fig. The diagram shown in Figure 9 illustrates a threshold comparison within a decision logic of a control unit of the personal protection system using the example of a filtered pressure signal sum.

[0067] Fig. Figure 10 shows a diagram of a collision sensor signal and an adjusted threshold value for the personal protection system from Fig. 1, Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. 7 or Fig. 8. In the diagram, time t is plotted along the abscissa axis, while a pressure P is plotted along the ordinate axis. The pressure P corresponds to the sum of the pressure signals from a vehicle's collision sensor, which is designed as a pressure hose sensor. The sum of the pressure signals is derived from the sensor signals pL and pR from, for example, two sensor elements of the collision sensor.

[0068] Furthermore, a threshold value 910 is shown in the diagram, which represents, for example, a trigger threshold for triggering a safety device of the vehicle. Pressure values ​​below threshold value 910 indicate a collision between the vehicle and, for example, a small animal, while pressure values ​​above threshold value 910 represent a collision with a pedestrian. A graph 920 shows a pressure curve representing a collision between the vehicle and a pedestrian. Graph 920 extends into the area above threshold value 910. Thus, the pressure curve exceeds threshold value 910 during the collision with the pedestrian.

[0069] The threshold value 910 is changed, in particular lowered, within a time window 1015. The time window 1015 represents a time window of a threshold adjustment. In other words, Fig. 10 shows a threshold adjustment of filtered pressure signals in the event of a pedestrian impact. The adjustment of the threshold value 910 is performed via a speed-dependent time window 1015, which is dependent on the estimated time to collision (TTC).

[0070] With reference to the Fig. 9 and Fig. 10, the possibility of a robust or sensitive threshold adjustment of algorithm thresholds using the calculated collision position or environmental sensor impact position is explained in more detail. This is done using the expected impact position of the object / pedestrian and in conjunction with plausibility check and fusion or the Fig. 4 to 8 the threshold value 910 is adjusted in the robust or sensitive direction, for example in the pedestrian protection algorithm.

[0071] In Fig. Figure 9 shows an example of the signal curve for the filtered signal sum (left and right sensors) in a pressure-hose-based pedestrian protection system over time. The signal 920 occurring during a pedestrian impact has a higher amplitude than, for example, the signal 930 occurring during an impact with a small animal (non-pedestrian object). Within the algorithm, the signal 920 or 930 is typically compared with a fixed speed-dependent threshold value 910 (Thd(v)). The threshold value divides the signal amplitudes into the pedestrian and non-pedestrian ranges.

[0072] The threshold comparison is performed in a similar manner for the other features within the algorithm. Thresholds tailored to the respective features are used. In practice, it may happen that the feature-specific thresholds are set relatively low, for example, due to the bumper geometry or other influencing factors that lead to different signal amplitudes in pedestrian impacts along the bumper. According to exemplary embodiments, it is possible, for example, to prevent non-pedestrian objects from generating an excessively high signal amplitude and thus exceeding the set thresholds, and to prevent the thresholds from being set unnecessarily high.

[0073] According to embodiments, it is particularly provided to use camera, radar or similar pedestrian detection systems to support a triggering decision of safety devices in order to set the threshold values ​​more sensitively or more robustly at runtime before the impact and thus always recognize a pedestrian as such and avoid false triggering.

[0074] For example, if an object is a pedestrian and the conditions for plausibility and / or fusion are from at least one of the Fig. 4 to 8 are met, and the pedestrian fits the impacted object in terms of the expected time to impact (TTI), the threshold value 910 is set more sensitively within the decision logic ( Fig. 10). Using the TTI, the time window 1015 can be determined in which the object is expected to hit the vehicle's bumper. Within this time window 1015, a threshold adjustment is made within the decision logic, either robustly or sensitively, depending on the object and the conditions from the Fig. 4 to 8 are met.

[0075] With reference to the Fig. 1 to 10, exemplary embodiments are explained again below in summary and in other words. According to exemplary embodiments, the use of a predicted impact position 175 or object impact location from a forward-looking environment sensor 120 in a vehicle 100 is provided within a pedestrian protection algorithm to improve the triggering decision.

[0076] To detect pedestrian collisions, sensors installed in the vehicle bumper, for example in the form of collision sensor 110, are used. Systems based on two or more acceleration sensors (PCS - Pedestrian Contact Sensor) are widely used. Pressure tube sensors (PTS - Pressure Tube Sensor) are also available. With both acceleration and pressure tube sensors, the impact of an object 160, 660, 860 in the relevant area of ​​the bumper leads to a signal increase within the detecting sensors. The amplitude of the detected signals depends, among other things, on the mass and speed of the impacting object 160, 660, 860.

[0077] The signals emitted by the sensors are further processed within algorithms with the aim of classifying the impact object or object 160, 660, 860 as a pedestrian or non-pedestrian. If the algorithm detects that object 160, 660, 860 is a pedestrian, active restraint devices are activated, depending on the vehicle speed, to cushion the pedestrian's impact on the front of the vehicle. If, however, no pedestrian is detected, the active restraint devices are not triggered. To perform the necessary classification of the impact object within the algorithm, the processed signals, such as raw signals, window integrals, integrals, derivatives, etc., are compared with threshold values.If one or more relevant signals exceed their thresholds, the impact object is most likely a pedestrian, and the active restraint systems are triggered. See, for example, the . Fig. 9 and Fig. 10.

[0078] According to exemplary embodiments, it can be achieved that the sensor technology installed in the vehicle 100 is not sufficient to classify an object as a pedestrian with sufficient precision. In this case, environmental sensors 120 already installed in the vehicle 100, e.g., radar, camera, ultrasound, etc., are used to classify objects 160, 660, 860 located in front of a vehicle 100, e.g., as pedestrians or non-pedestrian objects. Furthermore, the environmental sensors 120 provide an estimated time (TTI = Time to Impact) until the detected object 160, 660, 860 or the pedestrian is expected to impact the vehicle 100. Using these variables, algorithm thresholds can be set sensitively or robustly, depending on whether a pedestrian (sensitively) or a non-pedestrian object (more robustly) was detected by the environmental sensors 120. This happens in a defined time window 1015 and is, for example, the same for the entire width of the bumper.The estimated or anticipated impact position 175 of an object 160, 660, 860 can be provided by the environment sensors 120 of the vehicle 100 and thus used, for example, in the pedestrian protection algorithm.

[0079] In a first step, for example, the expected impact position 175 of a detected object 160, 660, 860 or a pedestrian on the vehicle 100 is calculated within the environmental sensors 120 installed in the vehicle 100, e.g., radar, camera, ultrasound, etc. Subsequently, the expected impact position 175 of the object 160, 660, 860 or pedestrian on the bumper of the vehicle 100 is sent, for example, via CAN / FlexRay, to an airbag control unit or the control unit 130 of the personal protection system and received there. The data on the expected impact position 175 is received together with the TTI and other variables matching the object / pedestrian 160, 660, 860 detected by the environmental sensors 120. Within the airbag control unit or control unit 130, the received data is preprocessed following receipt of the data.

[0080] Thereafter, the expected impact position 175 of the object / pedestrian 160, 660, 860 is used together with the TTI and other variables, particularly within the pedestrian protection algorithm, for example, for at least one of the following purposes. In order to perform a plausibility check 480 of the collision position 170, 870 of the object / pedestrian 160, 660, 860 actually calculated by the PTS / PCS installed in the vehicle 100, as described, for example, in Fig. 4. In order to perform a fusion 580 of the expected impact position 175 of the object / pedestrian 160, 660, 860 and the collision position 170, 870 of the object / pedestrian 160, 660, 860 calculated by the PTS / PCS, as shown, for example, in Fig. 5. In order to carry out an object plausibility check using the expected impact position 175 of the object / pedestrian 160, 660, 860 together with the TTI, as is the case, for example, in Fig. 6. In order to identify an area 714 on the bumper using the expected impact position 175 of the object / pedestrian 160, 660, 860, in which algorithm thresholds are adjusted, as described, for example, in the Fig. 7 and Fig. 8. In order to adapt threshold values ​​in the pedestrian protection algorithm, such as the threshold value 910, in the robust or sensitive direction using the expected impact position 175 of the object / pedestrian 160, 660, 860, as is shown for example in the Fig. 9 and Fig. 10 is shown.

[0081] According to exemplary embodiments, a calculation of an expected impact position 175 of the object / pedestrian 160, 660, 860 is carried out with the aid of environmental sensors 120 installed in the vehicle 100, and this expected impact position 175 is used, for example, within a pedestrian protection algorithm to improve a triggering decision. This results in, among other things, the following advantages.

[0082] One advantage lies in the plausibility check of the collision position 170, 870 of the object / pedestrian 160, 660, 860 actually calculated by the PTS / PCS. This primarily makes it possible to determine whether there are any inadmissible deviations 480 between the collision position 170, 870 actually calculated by the PTS / PCS and the expected impact position 175. In such a case, for example, threshold values ​​in the algorithm, such as threshold 910, can only be adjusted slightly or not at all based on the calculated collision position 170, 870, since the collision position 170, 870 calculated by the PTS / PCS is likely too inaccurate. Furthermore, it is possible, for example, to switch the trigger thresholds robustly if the deviation is large, since an error could be present.

[0083] By merging 580 the expected impact position 175 of the object / pedestrian 160, 660, 860 based on the environment sensor data 154 and the collision position 170 of the object / pedestrian 160, 660, 860 calculated by the PTS / PCS, errors in the impact position detection of the PTS / PCS can be partially compensated. For example, if the distance between two PCS in a vehicle 100 is very high because only a few PCS are installed along the bumper, the collision position 170, 870 of an object / pedestrian 160, 660, 860 calculated by the PCS can only be calculated inaccurately. With the help of the expected impact position 175 of the object / pedestrian 160, 660, 860 from the environment sensor 120, this inaccurate collision position 170, 870 can be improved by the fusion 580 with the expected impact position 175 of the object / pedestrian 160, 660, 860.This allows the corresponding algorithm thresholds to be adjusted more precisely depending on the resulting impact position, which can, for example, minimize false activations or non-activations of active restraint devices.

[0084] A further advantage lies in the plausibility check of the object / pedestrian 160, 660, 860 based on the expected impact position 175 and the TTI. This is particularly important when multiple objects / pedestrians 160, 660, 860 are detected / hit by the vehicle 100. Based on the expected impact position 175 and the collision position 170, 870 calculated by the PTS / PCS in conjunction with the time to impact or TTI, it is possible to determine whether the struck object 160, 660, 860 or the struck pedestrian also matches the object 160, 660, 860 detected by the environment sensor 120. This is done with the help of the expected impact position 175 from the environment sensor system. This is especially important if thresholds within the algorithm are to be set more robustly or sensitively.For example, if an object 160, 660, 860 hits the right outer side of the bumper (detected via PTS / PCS) and the expected impact position 175 of the object 160, 660, 860 determined by the environment sensor 120 is, for example, on the left side of the bumper, then the object 160, 660, 860 detected by the environment sensor 120 is not the same object 160, 660, 860 that hits the right side of the bumper, i.e., the objects 160, 660, 860 do not match. In this case, the algorithm's threshold values ​​are not adjusted, and the algorithm's default behavior is used. In this context, the TTI is also important to additionally determine whether the two objects / pedestrians 160, 660, 860 also coincide in time with the object / pedestrian 160, 660, 860 that was hit.

[0085] A further advantage is that, using the expected impact position 175 of the object / pedestrian 160, 660, 860 and, for example, also based on driving dynamics, defined areas 714 on the bumper can be identified, within which algorithm thresholds can be adjusted. Only if the object 160, 660, 860 actually impacts in these areas 714 (plausibility check based on collision position 170, 870) are the algorithm thresholds adjusted to be more robust or sensitive.

[0086] Finally, using the expected impact position 175 of the object / pedestrian 160, 660, 860, thresholds in the pedestrian protection algorithm, such as threshold 910, are adjusted in the robust or sensitive direction.

[0087] Thus, a calculation of an expected impact position 175 of an object / pedestrian 160, 660, 860 can be realized with the aid of environmental sensors 120 installed in the vehicle 100 and the use of this expected impact position 175 within a pedestrian protection algorithm to improve the triggering decision.

[0088] 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 (200) for personal protection for a vehicle (100), the method (200) comprising the following steps: Determining (210) a probable impact position (175) of an object (160; 660; 860) arranged in an environment of the vehicle (100) on the vehicle (100) using an environment sensor signal (154) from at least one environment sensor (120) arranged in the vehicle (100) for detecting the environment of the vehicle (100); and Generating (220) a control signal (156) for controlling at least one safety device (140) of the vehicle (100) using the determined expected impact position (175) and a collision position (170; 870) calculated using a collision sensor signal (152) caused by a collision with the object (160; 660; 860) from at least one collision sensor (110) of the vehicle (100), characterized bya step (230) of fusing the determined expected impact position (175) and the collision position (170; 870) to determine a fused impact position located between the expected impact position (175) and the collision position (170; 870), wherein in the step (220) of generating, the control signal (156) is generated using the fused impact position, wherein in the merging step (230) a mean value or a median value or a weighted sum is formed from the determined expected impact position (175) and the collision position (170; 870). [2] Method (200) according to claim 1, characterized bya step (240) of performing a comparison of a deviation (480) between the determined probable impact position (175) and the collision position (170; 870) with at least one deviation threshold value, wherein in the step (220) of generating the control signal (156) is generated depending on a result of the comparison. [3] Method (200) according to one of the preceding claims, characterized by that in step (240) of carrying out a further comparison is carried out between a probable time of impact of the object (160; 660; 860) on the vehicle (100) determined using the environment sensor signal (154) and a collision time calculated using the collision sensor signal (152), wherein in step (220) of generating the control signal (156) is generated depending on a result of the further comparison. [4] Method (200) according to one of the preceding claims 2 or 3, characterized bythat in step (240) of carrying out a deviation threshold value used for the comparison of the determined and predicted impact position is changed as a function of a difference between the expected impact time and the calculated collision time. [5] Method (200) according to one of the preceding claims, characterized by in that in the generating step (220), the control signal (156) is generated using position data that represents a position of the at least one safety device (140) relative to a detection range (125) of the at least one environmental sensor (120). [6] Method (200) according to one of the preceding claims, characterized by in that in the generating step (220), the control signal (156) is generated using object data which represent a type of object (160; 660; 860) determined using the environment sensor signal (154). [7] Method according to one of the preceding claims, characterized by that the control signal (156) generated in step (220) of generating is designed to set a triggering threshold value (910) for triggering the at least one safety device (140) depending on the environment sensor signal (154) and / or the collision sensor signal (152). [8] Method (200) according to claim 7, characterized by in that the control signal (156) generated in the generating step (220) is designed to set the triggering threshold value (910) for a time period (1015) within which an expected time of impact of the object (160; 660; 860) on the vehicle (100) lies, ascertained using the environment sensor signal (154). [9] Control device (130) which is designed to carry out the steps of the method (200) according to one of the preceding claims in corresponding devices (132, 134). [10] Computer program adapted to carry out the method (200) according to any one of claims 1 to 8. [11] A machine-readable storage medium on which the computer program according to claim 10 is stored.

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