Abstract:
An occupant protection system for a motor vehicle includes at least one crash sensor for measuring a motion variable. The occupant protection system includes an occupant protection device, controlled by an ignition signal, and a control device for determining the ignition signal subject to an average time value of the motion variable measured by the crash sensor during at least one first time interval.

Description:
FIELD OF THE INVENTION 
   The present invention relates to an occupant protection system for a motor vehicle. Such an occupant protection system may include an airbag and/or a belt tensioner. 
   BACKGROUND INFORMATION 
   Airbag systems are described, for example, in the article “Hardware and Mechanics of Real Airbag Control Systems” published on the Internet page www.informatik.uni-dortmund.de/airbag/seminarphase/hardware_vortrag.pdf. 
   U.S. Pat. No. 5,583,771, U.S. Pat. No. 5,684,701 and U.S. Pat. No. 6,532,508 describe the triggering of an airbag by a neural network as a function of an output signal of an acceleration sensor. 
   German Published Patent Application No. 198 54 380 describes a method for detecting the severity of a vehicle collision, where the output signals of a plurality of acceleration sensors are supplied to a neural network. In the method, the start of the evaluation of the acceleration-sensor output signals is determined by a trigger signal, which is output by an acceleration sensor when it output signal exceeds a predefined threshold value. This acceleration sensor causes the other acceleration sensors to supply the specific output signal at one and the same time. It is also provided that the output signals of the acceleration sensors be integrated one or two times. 
   German Published Patent Application No. 100 35 505 describes a method, in which the future time characteristic of the output signal of an acceleration sensor is predicted with the aid of a neural network on the basis of the acceleration-sensor signals at least one defined time. 
   German Published Patent Application No. 100 40 111 describes a method for producing a triggering decision for restraining devices in a vehicle, where the difference of measured acceleration values is calculated and the magnitude of the difference is subsequently integrated. The integral is compared to at least one threshold value. If the integral does not exceed this threshold value by a predefined time, then the position of a triggering threshold for the measured acceleration or for a speed change derived from it is modified in such a manner, that the triggering sensitivity becomes lower. 
   Described in German Published Patent Application No. 101 03 661 is a method for sensing lateral impact in a motor vehicle; acceleration sensors, from whose output signals the difference is calculated, being situated on the left and right sides of the vehicle. The differential acceleration signal is integrated or summed up. For the purpose of side-impact sensing, the differential speed signal is compared to a threshold value, which is calculated as a function of the differential acceleration signal. 
   SUMMARY 
   Example embodiments of the present invention may provide occupant protection systems for a motor vehicle, e.g., an occupant protection system including an airbag and/or a belt tensioner. In so doing, it may be provided for the triggering of such an occupant protection system for a motor vehicle to be particularly precise. 
   An occupant protection system for a motor vehicle may include at least one crash sensor for measuring a motion variable of the motor vehicle, the occupant protection system including an occupant protection device controllable via an ignition signal, and a control unit for ascertaining or generating the ignition signal as a function of a time average, over at least a first time interval, of the motion variable measured by the crash sensor, and, e.g., as a function of a time average of the motion variable measured by the crash sensor, over a second time interval different from the first time interval. 
   An occupant protection device within the present context may include, e.g., an airbag and/or a belt tensioner. 
   An average value within present context may be an arithmetic mean or a weighted average. In the case of such a weighted average, e.g., more recent values of the motion variable in the relevant time interval may be more heavily weighted than older values of the motion variable in the relevant time interval. An average value within the present context may also be a value proportional to an average value. The average value may be a value proportional to the arithmetic mean. In this context, the average value may be a value proportional to the integral of the motion variable in the relevant time interval or the sum of sampled values of the motion variable in the relevant time interval. 
   A motion variable of the motor vehicle within the present context may be an acceleration, a speed, or a displacement, or a variable derived from one of these variables. In this context, the motion variable may be an acceleration. 
   A crash sensor within the present context may be an acceleration sensor for measuring an acceleration in one or more directions. A crash sensor within the present context may also be a radar device, an infrared set-up, or a camera. In this case, a motion variable of the motor vehicle may be a distance of the motor vehicle from an obstacle, the first or second derivative of this distance, or another similar variable. A crash sensor within the present context may also be a sensor for measuring a deformation of the motor vehicle. Such a sensor may be a fiber-optic sensor or a sensor described in German Published Patent Application No. 100 16 142. In this case, a motion variable of the motor vehicle may be a deformation of the motor vehicle, the first or second derivative of this deformation, or another similar variable. 
   An ignition signal within the present context may be a binary signal, which indicates if an occupant protection device, such as an airbag and/or a belt tensioner, should be triggered. Such an ignition signal within the present context may be a “FIRE/NO-FIRE” signal described in German Published Patent Application No. 100 35 505. An ignition signal within the present context may also be a more complex signal, which indicates the degree (e.g., stage 1 or stage 2) to which an airbag should be fired. In addition, such an ignition signal within the present context may be a crash-severity parameter or an occupant acceleration or loading described in German Published Patent Application No. 100 35 505. An ignition signal within the present context may be, or include, an information item indicating the location and/or the direction of a collision. 
   A second time interval different from a first time interval may differ from the first time interval in its length and/or its position. 
   The ignition signal may be ascertainable by the control unit as a function of time averages of the motion variable measured by the crash sensor in two to twenty, e.g., in two to ten, different time intervals. The ignition signal may be ascertainable by the control unit as a function of time averages of the motion variable measured by the crash sensor in two to five different time intervals. Different time intervals within the present context may differ from each other in the length and/or in the position. 
   The time intervals may be between 1 ms and 200 ms long, e.g., between 4 ms and 32 ms long, and, e.g., between 8 ms and 24 ms long. The time intervals may be the same length, or they may vary in length. 
   At least two, e.g., adjacent, time intervals may be staggered by between 1 ms and 50 ms, e.g., by between 2 ms and 16 ms. All adjacent time intervals may each be offset from each other by between 1 ms and 50 ms, e.g., by between 2 ms and 16 ms. 
   The occupant protection system may include at least one additional crash sensor for measuring a motion variable of the motor vehicle, the ignition signal also being ascertainable by the control unit as a function of at least one time average of the motion variable measured by the additional crash sensor over a time interval. The additional crash sensor may be positioned more than 0.5 m away from the crash sensor mentioned at the outset. 
   In a motor vehicle, e.g., a motor vehicle including an occupant protection system that has one or more of the above-mentioned features, the motor vehicle the motor vehicle may include at least one crash sensor for measuring a motion vehicle of the motor vehicle and an occupant protection device controllable via an ignition signal, the motor vehicle including a control unit for ascertaining or generating the ignition signal as a function of a time average of the motion variable measured by the crash sensor over at least one first time interval, and, e.g., as a function of a second time interval of the motion variable measured by the crash sensor over a second time interval different from the first time interval. 
   In a method for operating an occupant protection system for a motor vehicle, e.g., by a method for operating an occupant protection system, having one or more of the above-mentioned features, the occupant protection system includes an occupant protection device controllable via an ignition signal, and the ignition signal being ascertained as a function of a time average of a measured motion variable over at least one first time interval, and, e.g., as a function of a time average of the measured motion variable over a second time interval different from the first time interval. 
   A motor vehicle within the present context may include, e.g., a land vehicle that may be used individually in road traffic. For example, motor vehicles in the present context are not restricted to land vehicles having an internal combustion engine. 
   Further features and details of exemplary embodiments of the present invention are described in more detail below with reference to the appended Figures. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
       FIG. 1  is a plan view of a motor vehicle. 
       FIG. 2  illustrates an exemplary embodiment of an occupant protection system. 
       FIG. 3  illustrates an exemplary embodiment of a control module. 
       FIG. 4  illustrates an exemplary embodiment of a triggering module. 
       FIG. 5  illustrates an exemplary embodiment of an output signal of a crash sensor. 
       FIG. 6  illustrates the integral of the output signal illustrated in  FIG. 5 , in one time interval. 
       FIG. 7  illustrates an exemplary embodiment of a neural network. 
       FIG. 8  illustrates an exemplary embodiment of a decision tree. 
       FIG. 9  illustrates an exemplary embodiment of a triggering module. 
       FIG. 10  illustrates an exemplary embodiment of a triggering module. 
       FIG. 11  illustrates an exemplary embodiment of a triggering module. 
   

   DETAILED DESCRIPTION 
     FIG. 1  is a plan view of a motor vehicle  1  having an occupant protection system, which is illustrated in  FIG. 2  in the form of a block diagram. The occupant protection system includes at least an airbag  15 , see, e.g.,  FIG. 2 , and/or a belt tensioner  16 , see, e.g.,  FIG. 2 . The occupant protection system additionally includes a control unit  2  for triggering airbag  15  and/or belt tensioner  16 , as well as a crash sensor S 2  integrated into the right front end of motor vehicle  1  and a crash sensor S 3  integrated into the left front end of motor vehicle  1 . Crash sensors S 2  and S 3  are connected to control unit  2  by leads  5  and  6 . 
   Crash sensors S 2  and S 3 , as well as an additional crash sensor S 1  integrated into control unit  2 , as illustrated in  FIG. 2 , may take the form of acceleration sensors. Suitable acceleration sensors are described, for example, in chapter 3.2, ‘Acceleration Sensor,’ of the article “Hardware and Mechanics of Real Airbag Control Systems” published on the Internet page www.informatik.uni-dortmund.de/airbag/seminarphase/hardware_vortrag.pdf. Examples of suitable acceleration sensors include Bosch SMB060, Bosch PAS3 or Bosch UPF1. A suitable acceleration sensor may include, for example, a Bessel low-pass filter having a cutoff frequency of, e.g., 400 Hz. Crash sensors S 1 , S 2 , and S 3  supply acceleration values aS 1 , aS 2 , and aS 3 , respectively, as output signals. 
   The occupant protection system additionally includes a belt sensor  11  for detecting if a seat belt is being used, and for outputting a corresponding belt information item MBELT. The occupant protection system further includes a seat-occupancy sensor  12  for detecting if, or how, a seat is occupied, and for outputting a corresponding seat-occupancy information item MSEAT. An example of a suitable seat-occupancy sensor is a pressure sensor integrated into the seat. Also suitable is an infrared scanning system described in chapter 3.3, “Interior Sensing,” of the article “Hardware and Mechanics of Real Airbag Control Systems” published on the Internet page www.informatik.uni-dortmund.de/airbag/seminarphase/hardware_vortrag.pdf. Infrared scanning and fuzzy logic not only allow seat occupancy to be detected, but also allow a determination as to whether the seat occupant is an object, such as a purse, or a person. To this end, a line of, e.g., eight or more light-emitting diodes above the seat emit infrared light, and a CCD matrix of 64 pixels records the scene illuminated in this manner. These charged coupled devices, abbreviated CCD, are made up of photodiodes and amplifier elements in matrix configurations. In this context, incident light releases charge carriers in each instance. A signal generated in this manner is amplified, processed, and stored. This procedure is repeated at different angles, and the seat is scanned in this manner. Image-processing algorithms and fuzzy-logic algorithms detect contours of objects and persons from these signals. 
   It may also be provided that the occupant-protection system include a control element  14  for activating or deactivating airbag  15 . A corresponding switching signal is designated by reference character ONOFF. 
   Control unit  2  includes a control module  10  for calculating and outputting an ignition signal AIR fur airbag  15  and/or an ignition signal BELT for belt tensioner  16  as a function of acceleration values aS 1 , aS 2 , and aS 3 , belt information item MBELT, seat-occupancy information item MSEAT, and switching signal ONOFF. 
     FIG. 3  illustrates an exemplary embodiment of control module  10 . Control module  10  includes a triggering module  20  for calculating and outputting an ignition recommendation CRASH as a function of acceleration values aS 1 , aS 2 , and aS 3 . Control module  10  additionally includes a firing table  21  for calculating and outputting ignition signal AIR for airbag  15  and/or ignition signal BELT for belt tensioner  16  as a function of ignition recommendation CRASH, belt information item MBELT, seat-occupancy information item MSEAT, and switching signal ONOFF. Thus, it may be provided that ignition signal AIR only be equal to ignition recommendation CRASH, when a corresponding seat is occupied by a person of a specific size, and that ignition signal AIR otherwise be equal to 0. 
   Both ignition recommendation CRASH and ignition signals AIR and BELT may be ignition signals. Both ignition recommendation CRASH and ignition signals AIR and BELT may be a binary signal, e.g., in accordance with the “FIRE/NO-FIRE” signal described in German Published Patent Application No. 100 35 505, which indicates whether an occupant protection device, such as an airbag and/or a belt tensioner, should be triggered. Both ignition recommendation CRASH and ignition signals AIR and BELT may also be a more complex signal. Both ignition recommendation CRASH and ignition signal AIR may be, for example, a more complex signal which indicates the degree (e.g., stage 1 or stage 2) to which airbag  15  should be fired. Both ignition recommendation CRASH and ignition signal AIR may additionally include, for example, a crash-severity parameter described in German Published Patent Application No. 100 35 505 or an occupant acceleration or occupant loading. It may be provided that both ignition recommendation CRASH and ignition signals AIR and BELT may indicate the location and/or the direction of a collision. 
     FIG. 4  illustrates an exemplary embodiment of triggering module  20 . Triggering module  20  includes an analog-to-digital converter  25  (analog-to-digital converter) for sampling acceleration value aS 1  and outputting a sampled acceleration value aS 1 , an analog-to-digital converter  26  for sampling acceleration value aS 2  and outputting a sampled acceleration value aS 2 , and an analog-to-digital converter  27  for sampling acceleration value aS 3  and outputting a sampled acceleration value aS 3 . 
   The sampling frequency of the Δt of analog-to-digital converters  25 ,  26 , and  27  may be, for example, 4 kHz. Triggering module  20  additionally includes (digital) integrators  31 ,  32 ,  33 ,  34 ,  35 , and  36 . 
   Using integrator  31 , a pseudospeed value v 0 S 1  at time t 0  is ascertained according to 
               v   ⁢           ⁢   0   ⁢           ⁢   S   ⁢           ⁢   1     =       ∫       t   0     -     τ   0         t   0       ⁢     as   ⁢           ⁢     1   ·     ⅆ   t             ,         
where τ0 is the length of a time interval [t 0 −τ 0 , t 0 ] or 40 (cf.,  FIG. 5 ). Time t 0  designates the current time, i.e., the current value of time t.
 
   Using integrator  32 , a pseudospeed value v 1 S 1  at a time t 0 −τ 1  is ascertained according to 
   
     
       
         
           
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   Using integrator  33 , a pseudospeed value v 2 S 1  at a time t 0 −τ 2  is ascertained according to 
   
     
       
         
           
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   Using integrator  34 , a pseudospeed value v 3 S 1  at a time t 0 −τ 3  is ascertained according to 
   
     
       
         
           
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   Using integrator  35 , a pseudospeed value v 0 S 2  at time t 0  is ascertained according to 
   
     
       
         
           
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     FIG. 5  and  FIG. 6  illustrate the effect of integrators  31 ,  32 ,  33 ,  34 ,  35 , and  36 . In this context,  FIG. 5  illustrates an example of the curve of (sampled) acceleration value as 1  versus time t in the event of a frontal collision of motor vehicle  1  with an obstacle.  FIG. 6  illustrates an example of a curve of pseudospeed value v 0 S 1  for τ 0 =24 ms. 
   In the exemplary embodiment illustrated in  FIG. 6 , τ 1  is 17 ms, τ 2  is 34 ms, and τ 3  is 51 ms. τ 1  may be 8 ms, τ 2  may be 16 ms, and τ 3  may be 24 ms. 
   Pseudospeed values v 0 S 1 , v 1 S 1 , v 2 S 1 , v 3 S 1 , v 0 S 2 , and v 0 S 3  are examples of time averages within the present context. 
   Triggering module  20  further includes a trigger generator  30  for generating trigger recommendation CRASH. Trigger generator  30  may take the form of a neural network, as illustrated in  FIG. 7  in an exemplary embodiment. 
   The neural network illustrated in  FIG. 7  includes six input nodes  50 ,  51 ,  52 ,  53 ,  54 ,  55 , six covered nodes  60 ,  61 ,  62 ,  63 ,  64 ,  65 , and an output node  70 , each input node  50 ,  51 ,  52 ,  53 ,  54 ,  55  being connected to each covered node  60 ,  61 ,  62 ,  63 ,  64 ,  65 , and each covered node  60 ,  61 ,  62 ,  63 ,  64 ,  65  being connected to output node  70 . In  FIG. 7 , however, not all of the connections between input nodes  50 ,  51 ,  52 ,  53 ,  54 ,  55  and covered nodes  60 ,  61 ,  62 ,  63 ,  64 ,  65  are illustrated for reasons of clarity. 
   Pseudospeed value v 0 S 1  is the input variable input into input node  50 , pseudospeed value v 1 S 1  is the input variable input into input node  51 , 
   pseudospeed value v 2 S 1  is the input variable input into input node  52 , 
   pseudospeed value v 3 S 1  is the input variable input into input node  53 , 
   pseudospeed value v 0 S 2  is the input variable input into input node  54 , and 
   pseudospeed value v 0 S 3  is the input variable input into input node  55 . 
   The output variable from output node  70  is ignition recommendation CRASH. 
   Details regarding neural networks may be found in U.S. Pat. No. 5,583,771, U.S. Pat. No. 5,684,701, and the documents “Techniques And Application Of Neural Networks”, Taylor, M. and Lisboa, Ellis Horwood, West Sussex, England, 1993, “Naturally Intelligent Systems”, Caudill, M. and Butler, G., MIT Press, Cambridge, 1990, and “Digital Neural Networks”, Kung, S. Y., PTR Prentice Hall, Englewood Cliffs, N.J., 1993, cited in U.S. Pat. No. 5,684,701. 
   
     
       
             
             
           
         
             
                 
               TABLE 1 
             
             
                 
                 
             
           
           
             
                 
               /* Evaluation function */ 
             
             
                 
               int evaluate_Action(double *x) 
             
             
                 
               { 
             
             
                 
                int CRASH; 
             
             
                 
                if (v0S3 &lt; δ v0S3  ) { 
             
             
                 
                 if (v0S2 &lt; δ v0S2  ) { 
             
             
                 
                  if (v2S1 &lt; δ v2S1  ) { 
             
             
                 
                   if (v0S1 &lt; δ v0S1  ) { 
             
             
                 
                    CRASH = 0; 
             
             
                 
                   } else { 
             
             
                 
                    if (v0S3 &lt; δ v0S3,2  ) { 
             
             
                 
                     CRASH = 0; 
             
             
                 
                    } else { 
             
             
                 
                     if (v0S1 &lt; δ v0S1,2  ) { 
             
             
                 
                      if (v1S1 &lt; δ v1S1  ) { 
             
             
                 
                       CRASH = 1; 
             
             
                 
                      } else { 
             
             
                 
                       CRASH = 0; 
             
             
                 
                      } 
             
             
                 
                     } else { 
             
             
                 
                      CRASH = 1; 
             
             
                 
                     } 
             
             
                 
                    } 
             
             
                 
                   } 
             
             
                 
                  } else { 
             
             
                 
                   if (v0S2 &lt; δ v0S2,2  ) { 
             
             
                 
                    CRASH = 0; 
             
             
                 
                   } else { 
             
             
                 
                    if (v0S3 &lt; δ v0S3,3  ) { 
             
             
                 
                     CRASH = 0; 
             
             
                 
                    } else ( 
             
             
                 
                     CRASH = 1; 
             
             
                 
                    } 
             
             
                 
                   } 
             
             
                 
                  } 
             
             
                 
                 } else { 
             
             
                 
                  CRASH = 1; 
             
             
                 
                 } 
             
             
                 
                } else { 
             
             
                 
                 CRASH = 1; 
             
             
                 
                } 
             
             
                 
                return (CRASH); 
             
             
                 
               } 
             
             
                 
                 
             
           
        
       
     
   
   As an alternative, trigger generator  30  may take the form of a sequence of comparisons to limiting values. Table 1 illustrates such a sequence of comparisons to limiting values, the code illustrated in Table 1 having been automatically generated by a learning process. For the code illustrated in Table 1, τ 1  is 4 ms, τ 2  is 8 ms, and τ 0  is 24 ms. 
     FIG. 8  illustrates the code of Table 1 represented as a decision tree  80 . In this context, reference numeral  81  denotes the inquiry as to whether v 0 S 3  is less than a limiting value δ v0S3 . 
   Reference numeral  82  denotes the inquiry as to whether v 0 S 2  is less than a limiting value δ v0S2 . 
   Reference numeral  83  denotes the inquiry as to whether v 2 S 1  is less than a limiting value δ v2S1 . 
   Reference numeral  84  denotes the inquiry as to whether v 0 S 1  is less than a limiting value δ v0S1 . 
   Reference numeral  85  denotes the inquiry as to whether v 0 S 3  is less than a limiting value δ v0S3,2 . 
   Reference numeral  86  denotes the inquiry as to whether v 0 S 1  is less than a limiting value δ v0S1,2 . 
   Reference numeral  87  denotes the inquiry as to whether v 1 S 1  is less than a limiting value δ v1S1 . 
   Reference numeral  88  denotes the inquiry as to whether v 0 S 2  is less than a limiting value δ v0S2,2 . 
   Reference numeral  89  denotes the inquiry as to whether v 0 S 3  is less than a limiting value δ v0S3,3 . 
   As illustrated in  FIG. 8  and Table 1, trigger generator  30  disregards pseudospeed value v 3 S 1 . This is taken into account in the learning process, but is disregarded by the learning algorithm for generating the code according to Table 1. 
     FIG. 9  illustrates an exemplary embodiment of a triggering module  120  that is an alternative to triggering module  20 . In this context, integrators  32 ,  33 , and  34  are replaced by lag elements  132 ,  133 , and  134 , which are positioned such that pseudospeed value v 1 S 1  results as pseudospeed value v 0 S 1  delayed by time τ 1 , pseudospeed value v 2 S 1  results as pseudospeed value v 0 S 1  delayed by time τ 2 , and pseudospeed value v 3 S 1  results as pseudospeed value v 0 S 1  delayed by time τ 3 . 
   One example of a possible (simple) implementation of integrator  31  (and appropriately adapted for integrators  32 ,  33 , and  34 ) is 
               vS   ⁢           ⁢   1   ⁢     (   i   )       =       c   ·   Δ     ⁢           ⁢   t   ⁢       ∑     j   =     i   -       τ   0       Δ   ⁢           ⁢   t           i     ⁢     as   ⁢           ⁢   1   ⁢     (   j   )             ,         
where i is a running index for specifying current time t 0  and is a constant. In this case, pseudospeed values v 0 S 1 , v 1 S 1 , v 2 S 1 , and v 3 S 1  are yielded, for example, in accordance with the following relationships:
 
   
     
       
         
           
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             ⁢ 
             
                 
             
             ⁢ 
             S 
             ⁢ 
             
                 
             
             ⁢ 
             1 
           
           = 
           
             v 
             ⁢ 
             
                 
             
             ⁢ 
             S 
             ⁢ 
             
                 
             
             ⁢ 
             1 
             ⁢ 
             
               ( 
               
                 i 
                 - 
                 
                   
                     τ 
                     3 
                   
                   
                     Δ 
                     ⁢ 
                     
                         
                     
                     ⁢ 
                     t 
                   
                 
               
               ) 
             
           
         
       
     
   
     FIG. 10  illustrates an exemplary embodiment of a triggering module  220  that is an alternative to triggering module  20 . In this context, integrators  32 ,  33 , and  34  are replaced by integrators  232 ,  233 , and  234 . In this context, pseudospeed value v 1 S 1  is ascertained via integrator  232  according to 
   
     
       
         
           
             v 
             ⁢ 
             
                 
             
             ⁢ 
             1 
             ⁢ 
             
                 
             
             ⁢ 
             S 
             ⁢ 
             
                 
             
             ⁢ 
             1 
           
           = 
           
             
               ∫ 
               
                 
                   t 
                   0 
                 
                 - 
                 
                   τ 
                   1 
                 
               
               
                 t 
                 0 
               
             
             ⁢ 
             
               as 
               ⁢ 
               
                   
               
               ⁢ 
               
                 1 
                 · 
                 
                   
                     ⅆ 
                     t 
                   
                   . 
                 
               
             
           
         
       
     
   
   Using integrator  233 , a pseudospeed value v 2 S 1  at time t 0  is ascertained according to 
   
     
       
         
           
             v 
             ⁢ 
             
                 
             
             ⁢ 
             2 
             ⁢ 
             
                 
             
             ⁢ 
             S 
             ⁢ 
             
                 
             
             ⁢ 
             1 
           
           = 
           
             
               ∫ 
               
                 
                   t 
                   0 
                 
                 - 
                 
                   τ 
                   ⁢ 
                   
                       
                   
                   ⁢ 
                   2 
                 
               
               
                 t 
                 0 
               
             
             ⁢ 
             
               as 
               ⁢ 
               
                   
               
               ⁢ 
               
                 1 
                 · 
                 
                   
                     ⅆ 
                     t 
                   
                   . 
                 
               
             
           
         
       
     
   
   Using integrator  234 , a pseudospeed value v 3 S 1  at a time t 0  is ascertained according to 
   
     
       
         
           
             v 
             ⁢ 
             
                 
             
             ⁢ 
             3 
             ⁢ 
             S 
             ⁢ 
             
                 
             
             ⁢ 
             1 
           
           = 
           
             
               ∫ 
               
                 
                   t 
                   0 
                 
                 - 
                 τ3 
               
               
                 t 
                 0 
               
             
             ⁢ 
             
               as 
               ⁢ 
               
                   
               
               ⁢ 
               
                 1 
                 · 
                 
                     
                 
                 ⁢ 
                 
                   
                     ⅆ 
                     t 
                   
                   . 
                 
               
             
           
         
       
     
   
   In triggering module  20  illustrated in  FIG. 4  and triggering module  120  illustrated in  FIG. 9 , the time intervals differ in their position. However, in triggering module  220  illustrated  FIG. 10 , the time intervals differ in their length. It may also be provided that time intervals differ in their length and in their position. A corresponding exemplary embodiment is illustrated in  FIG. 11 .  FIG. 11  illustrates an exemplary embodiment of a triggering module  320  that is an alternative to triggering module  220 . In this context, integrator  234  is replaced by an integrator  334 , with the aid of which a pseudospeed value v 3 S 1  at a time t 0 −τ 4  is ascertained according to 
   
     
       
         
           
             v 
             ⁢ 
             
                 
             
             ⁢ 
             3 
             ⁢ 
             S 
             ⁢ 
             
                 
             
             ⁢ 
             1 
           
           = 
           
             
               ∫ 
               
                 
                   t 
                   0 
                 
                 - 
                 
                   τ 
                   3 
                 
                 - 
                 
                   τ 
                   4 
                 
               
               
                 
                   t 
                   0 
                 
                 - 
                 
                   τ 
                   4 
                 
               
             
             ⁢ 
             
               as 
               ⁢ 
               
                   
               
               ⁢ 
               
                 1 
                 · 
                 
                     
                 
                 ⁢ 
                 
                   
                     ⅆ 
                     t 
                   
                   . 
                 
               
             
           
         
       
     
   
   For example, in connection with neural networks, automatically generated decision trees, or comparable, learning, evaluation procedures, particularly robust control of airbags and belt tensioners may be provided. 
   Although explained in the exemplary embodiments in view of airbags and belt tensioners for a frontal collision, the foregoing should not be considered to be restricted. Example embodiments of the present invention are also applicable to side airbags and other occupant protection systems. In one implementation for side airbags, crash sensors S 2  and S 3  may be arranged, for example, in the B-pillar. It may be provided that at least one pseudospeed value over at least one additional time interval be calculated for crash sensor S 2  and/or crash sensor S 3 , as well. 
   A control unit within the present context may also be a distributed system. A control unit within the present context does not have to be accommodated in a single housing. A control unit within the present context may also be an individual chip or a printed circuit board. 
   To the extent that decision trees are mentioned in connection with the generation of ignition recommendation CRASH, these may also be replaced by regression trees, association tables, rule sets, supervector machines, or other machine-learning procedures, etc. 
   Instead of motion variables or their average values, differences of motion variables, average values of these differences, and/or differences of average values may also be used. Thus, e.g., a subtractor may be provided in front of integrators  31 ,  32 ,  33 ,  34 ,  35 ,  36 ,  232 ,  233 ,  234 , and  334  illustrated in  FIG. 4 ,  FIG. 9 ,  FIG. 10 , and/or  FIG. 11 , so that instead of sampled acceleration values as 1 , as 2 , as 3 , differential values Δas 1 , Δas 2 , Δas 3  are input variables of integrators  31 ,  32 ,  33 ,  34 ,  35 ,  36 ,  232 ,  233 ,  234 , and  334 , Δas 1  being equal to difference as 1 −as 2 , Δas 2  being equal to difference as 1 −as 3 , and Δas 3  being equal to difference as 2 −as 3 . In addition, it may be provided that differential value Δas 1  be processed in the same manner as sampled acceleration value as 1  illustrated in  FIG. 4 ,  FIG. 9 ,  FIG. 10 , and/or  FIG. 11 , that differential value Δas 2  be processed in the same manner as sampled acceleration value as 1  illustrated in  FIG. 4 ,  FIG. 9 ,  FIG. 10 , and/or  FIG. 11 , and/or that differential value Δas 3  be processed in the same manner as sampled acceleration value as 2  illustrated in  FIG. 4 ,  FIG. 9 ,  FIG. 10 , and/or  FIG. 11 . In this case, the number of integrators and the number of input variables are to be appropriately adapted to trigger generator  30 . 
   Differences may also be time differences. Thus, it may be provided that differential values Δas 1 , Δas 2 , Δas 3  be used in place of sampled acceleration values as 1 , as 2 , as 3  as input variables of integrators  31 ,  32 ,  33 ,  34 ,  35 ,  36 ,  232 ,  233 ,  234 , and  334 , Δas 1 ( t ) being equal to difference as 1 ( t )−as 1 ( t −τ), Δas 2  being equal to difference as 2 ( t )−as 2 ( t −τ) or difference as 2 ( t )−as 3 ( t −τ), and Δas 3  being equal to difference as 3 ( t )−as 3 ( t −τ) or difference as 3 ( t )−as 2 ( t −τ). 
   In accordance with above-mentioned variants with regard to the calculation of a difference, motion variables within the present context may also be differences of motion variables, when they are used as input variables. 
   One may proceed with pseudospeed values v 0 S 1 , v 1 S 1 , v 2 S 1 , v 3 S 1 , v 0 S 2 , v 0 S 3  in an analogous manner. Accordingly, average values of motion variables within the present context may also be differences of average values of motion variables or average values of differences of motion variables, when they are used as input variables. 
   
     
       
             
           
             
             
             
           
         
             
                 
             
             
               LIST OF REFERENCE NUMERALS 
             
             
                 
             
           
           
             
                 
             
           
        
         
             
                 
               1 
               motor vehicle 
             
             
                 
               2 
               control device 
             
             
                 
               5, 6 
               leads 
             
             
                 
               10 
               control module 
             
             
                 
               11 
               belt sensor 
             
             
                 
               12 
               seat-occupancy sensor 
             
             
                 
               14 
               control element 
             
             
                 
               15 
               airbag 
             
             
                 
               16 
               belt tensioner 
             
             
                 
               20, 120, 220, 320 
               triggering module 
             
             
                 
               21 
               firing table 
             
             
                 
               25, 26, 27 
               analog-to-digital converter 
             
             
                 
               30 
               trigger generator 
             
             
                 
               31, 32, 33, 34, 
               integrator 
             
             
                 
               35, 36, 232, 233, 
             
             
                 
               234, 334 
             
             
                 
               40 
               time interval 
             
             
                 
               50, 51, 52, 53, 
               input node 
             
             
                 
               54, 55 
             
             
                 
               60, 61, 62, 63 
               covered node 
             
             
                 
               64, 65 
             
             
                 
               70 
               output node 
             
             
                 
               80 
               decision tree 
             
             
                 
               81, 82, 83, 84, 
               inquiry 
             
             
                 
               85, 86, 87, 88, 89 
             
             
                 
               132, 133, 134 
               lag element 
             
             
                 
               AIR, BELT 
               ignition signal 
             
             
                 
               aS1, aS2, aS3, 
               acceleration value 
             
             
                 
               as1, as2, as3 
             
             
                 
               CRASH 
               ignition recommendation 
             
             
                 
               ONOFF 
               switching signal 
             
             
                 
               MBELT 
               belt information 
             
             
                 
               MSEAT 
               seat-occupancy information 
             
             
                 
               S1, S2, S3 
               crash sensor 
             
             
                 
               t 
               time 
             
             
                 
               t0 
               current time 
             
             
                 
               v0S1, v1S1, v2S1, 
               pseudospeed value 
             
             
                 
               v3S1, v0S2, v0S3 
             
             
                 
               τ 0 , τ 1 , τ 2 , τ 3   
               length of a time interval