Patent Abstract:
A method for calibrating an internal sensor in a vehicle with an external sensor which is designed to detect external positional data dependent on a position of the vehicle. The method includes: detecting the external positional data using the external sensor; sending the external positional data to the vehicle and filtering the internal positional data based on the external positional data and dependent on the position of the vehicle and by an internal sensor.

Full Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    This application is the U.S. National Phase Application of PCT International Application No. PCT/EP2015/071889 filed Sep. 23, 2015, which claims priority to German Patent Application No. 10 2014 219 382.6, filed Sep. 25, 2014, the contents of such applications being incorporated by reference herein. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The invention relates to a method for calibrating a vehicle, a control device for carrying out the method, the vehicle with the control device and a system for implementing the method. 
       BACKGROUND OF THE INVENTION 
       [0003]    From DE 102012016867 A1, which is incorporated by reference, a parking assistance system for parking a vehicle is known. It comprises a stationary verification and monitoring device able to wirelessly connect with a vehicle, configured to monitor an automatic parking maneuver. 
       SUMMARY OF THE INVENTION 
       [0004]    An aspect of the invention aims to improve the use of the parking assistance system. 
         [0005]    According to an aspect of the invention, a method for calibrating an internal sensor in a vehicle with an external sensor, which is designed to detect external positional data dependent on a position of the vehicle, comprises:
       detecting the external positional data using the external sensor;   sending the external positional data to the vehicle; and   filtering internal positional data detected by the internal sensor and dependent on the position of the vehicle based on the external positional data.       
 
         [0009]    The indicated method is based on the idea that using stationary verification and monitoring devices, like those known from the parking assistance systems mentioned above, via the wireless connection with the vehicle the positional data of the vehicle can be redundantly detected. On the basis of this redundant detection, the internally detected positional data and thus the internal sensor can be synchronized, for, by way of example, fault finding, calibrating the internal sensor or, by way of example, in the course of a sensor fusion, generally refining the positional data of the vehicle. In this way, the use of the external positional data can be extended. 
         [0010]    In a further development of the method indicated, the external sensor is arranged in a parking facility, particularly a multi-storey parking lot, for tracking the vehicle and can thus be used in a stationary verification and monitoring device of a parking assistance system, like the abovementioned parking assistance system. Here the external sensor is then used as part of a guidance system for the vehicle in the multi-storey parking lot, to guide the vehicle to a parking space in the multi-storey parking lot. 
         [0011]    Alternatively, the external sensor can also be used in a parking facility for the temporary storage of finished vehicles at the end of a production line. In the course of this temporary storage, by using the method indicated and in a particularly advantageous manner, when a newly produced vehicle is parked in a parking space of the parking facility the internal sensor is calibrated in-situ upon switching off, or a calibration already performed at the end of the line can be automatically checked. 
         [0012]    In another further development of the indicated method, the internal positional data are checked with the filtering based on the external positional data. In this way, errors in the detection of the position of the vehicle and the description by the internal positional data can be discovered which, by way of example, are caused by aging effects and/or by the effects of changes in the installation position. Changes in the installation position can, by way of example, occur as a result of a change in the sensor geometry during accidents or similar involving the vehicle and are generally not considered in the subsequent operation of the vehicle. Specifically, in highly accurate ADAS driver assistance systems, such as, for example, an automatic parking assistant, even minor errors must be avoided, however, since these can limit the performance of ADAS functions in vehicles very considerably. 
         [0013]    In a particular further development, the method indicated comprises the step of calibrating a sensor detecting the internal positional data in the vehicle based on the checking. In this way the abovementioned errors can be automatically corrected. In this way, more robust operation of ADAS functions in vehicles can be ensured much more reliably. 
         [0014]    In yet another further development of the method indicated, the external positional data are designed to describe an absolute position of the vehicle. Here the positional data describing the absolute position can be provided on a receiver of a Global Navigation Satellite System, or GNSS, signal. This can, by way of example, take place upon leaving the abovementioned multi-storey parking lot, in which no GNSS signal is usually receivable. Through the absolute position of the vehicle provided, here the GNSS receiver can, upon leaving the multi-storey parking lot, when a GNSS signal is received again, locate the vehicle more quickly and supply values for the absolute position of the vehicle. 
         [0015]    According to a further aspect of the invention, a control device is designed to carry out one of the methods indicated. 
         [0016]    In a further development of the control device indicated, the device indicated comprises a memory and a processor. Here the method indicated is stored in the form of a computer program in the memory, and the processor is provided for carrying out the method, when the computer program is loaded from the memory into the processor. 
         [0017]    According to a further aspect of the invention, a computer program comprises program code means for carrying out all steps of one of the methods indicated, when the computer program is executed on a computer or one of the devices indicated. 
         [0018]    According to a further aspect of the invention a computer program product contains a program code, stored on a machine-readable data carrier and which, when executed on a data processing device, carries out one of the processes indicated. 
         [0019]    According to another aspect of the invention, a vehicle comprises an indicated control device. 
         [0020]    According to a further aspect of the invention, the object is achieved by means of a system for carrying out a method according to one of the abovementioned embodiments. The system comprises means for detecting a vehicle. These means are permanently installed. The means are further supplied with information sent to the vehicle. The system further comprises an arithmetic and logical unit to determine and provide the information to be sent. The system furthermore comprises a control device to be fitted in a vehicle. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0021]    The characteristics, features and advantages of this invention described above, and the way in which these are achieved, will become clearer and more understandable through the following description of the embodiments, explained in more detail by reference to the drawings, in which: 
           [0022]      FIG. 1  is a schematic diagram of a vehicle in a multi-storey parking lot; 
           [0023]      FIG. 2  is a schematic diagram of the vehicle from  FIG. 1 , 
           [0024]      FIG. 3  is a schematic diagram of a vehicle ad-hoc network, in which the vehicle of  FIGS. 1 and 2  is able to participate; and 
           [0025]      FIG. 4  is a schematic diagram of a fusion sensor in the vehicle of  FIGS. 1 and 2 . 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
       [0026]    Identical technical elements are given the same reference numerals in the figures, and described only once. 
         [0027]    Reference is made to  FIG. 1 , in which a vehicle  2  in a multi-storey parking lot  4  is shown in a schematic diagram. 
         [0028]    As can be seen in  FIG. 1 , a number of other vehicles  6  can park in the multi-storey parking lot  4 . To park the vehicle  2  in the multi-storey parking lot  4 , a route  16  to a parking space  10  between the already parked vehicles  6  must be found. The vehicle  2  must then be moved along this route  16  to the parking space  10  and parked in the parking space  10 . 
         [0029]    In the present embodiment, in the multi-storey parking lot  4  there is a parking assistant with a plurality of external position sensors  12  distributed through the multi-storey parking lot  4 . The external position sensors  12  externally detect the position of vehicle  2  and describe this in positional data, which are therefore referred to in the following as external positional data  14 . The positional sensors  12  also report the external positional data  14  and thus the position of the vehicle  2  to a higher-order evaluation device (not shown). The evaluation device knows all free parking spaces  10  in the multi-storey parking lot  4  and based on the position of the vehicle  2  described with the external positional data  14  and the location of the parking space  10  calculates the route  16  to this and indicates this as a reference variable to the vehicle  2 . 
         [0030]    Each position sensor  12  in the multi-storey parking lot  4  has a radio antenna  18 , with which the parking assistant can send the route  16  as a reference variable and/or the external positional data  14  of the vehicle  2  as actual data in a radio signal  20  to the vehicle  2 . 
         [0031]    Based on the specified route  16  as reference variable and the external positional data  14  as actual data, the vehicle  2  can then, in a Highly Automated Driving (HAD) function, perform a suitable control action on the vehicle  2 , guide the vehicle  2  along the route  16  and park it in the parking space  10 . This means that the entire parking maneuver can be driverless. 
         [0032]    As already stated, the external positional data  14  represent external sensor information from the perspective of the vehicle  2 . This must be distinguished from internal sensor information from the perspective of the vehicle  2 , detected by sensors present inside the vehicle  2 . A few examples of this are given below using  FIG. 2 . 
         [0033]    The vehicle  2  comprises a chassis  20  and four wheels  22 . Each wheel  22  can be rotated individually by means of an electric motor  24  secured permanently to the chassis  20 , to move the vehicle  2  in a movement direction  26  along the route  16  in the multi-storey parking lot  4   
         [0034]    Here a loss of traction of the wheels  22  of the vehicle  2  and an associated deviation by the vehicle  2  from a trajectory specified by a steering signal  28  yet to be described, through understeering or oversteering, can be avoided by vehicle dynamics control  30 . The vehicle dynamics control  30 , like the abovementioned HAD function, is one of the driver assistance functions of what is known as ADAC. 
         [0035]    In the present embodiment, the vehicle  4  has speed sensors  32  on the wheels  22  for the vehicle dynamics control  30 , each detecting a speed  34  of the wheels  22 . The speeds  34  are an example of the abovementioned internal sensor information and are therefore internal sensor data from the perspective of the vehicle  2 . The vehicle  2  also comprises a vehicle dynamics sensor  35  outputting vehicle dynamics data  33 , which similarly represent internal sensor information and are therefore internal sensor data from the perspective of the vehicle  2 . 
         [0036]    Based on the detected speeds  34  and the vehicle dynamics data  33 , a controller  36  can determine in a manner known to a person skilled in the art, if the vehicle  2  slides in the lane or even deviates from the abovementioned trajectory, and respond accordingly with an in itself known controller output signal  38 . The controller output signal  38  can then be used by a controlling element  40 , to drive actuators, by means of actuating signals  42 , such as the electric motors  24 , which respond to slipping and deviation from the specified trajectory in a known manner, by way of example through torque-vectoring. Further details and alternative design possibilities of the vehicle dynamics control  30  can be inferred from DE 10 2011080789 A1, which is incorporated by reference. 
         [0037]    The HAD function is implemented in a suitable arithmetic and logical device with reference numeral  44 , referred to in the following as the HAD function  44 . The HAD function  44  can obtain the route  16  to the parking space  10  as a reference variable and the external positional data  14  as actual data, from a radio receiver  46  yet to be described which receives the corresponding radio signal  20  via a vehicle antenna  47 . Essentially, on this basis the HAD function  44  performs a setpoint/actual value comparison and by means of the steering signal  28  and a drive signal  37  intervenes in the vehicle  2 , to move the vehicle  2  along the route  16  to the parking space. While by means of the drive signal  37  via the actuator  40  the electric motors  24  for driving the vehicle  2  are being operated, the vehicle  2  is steered with the steering signal  28  via a steering system  50 . For the sake of brevity, an additional braking device that is necessary for braking the vehicle  2 , and which is similarly actuated by the HAD function  44 , is not dealt with in more detail hereinafter. 
         [0038]    To be able to respond to any obstacles such as pedestrians or similar on the route  16 , the vehicle  2  has a front camera  52  facing in the direction of movement  26  of the vehicle  2 , which captures an image  54  at an angle  56  in front of the vehicle  2  and a radar sensor  58 , which determines by radar rays  60  a distance  62  to a possible obstacle in front of the vehicle. In the image  54  the HAD function can, together with the distance  62 , identify any obstacles in front of the vehicle  2  and with the steering signal  28  and the abovementioned braking device avoid these as necessary. Both the image  54  and the distance  62  represent internal sensor information and thus internal sensor data from the perspective of the vehicle  2 . Further details on the HAD function  44  can be inferred, by way of example, from DE 102012112442 A1, which is incorporated by reference. 
         [0039]    Finally, a GNSS receiver  64  may be present in the vehicle  2  for receiving a corresponding GNSS signal via a GNSS antenna  68  from a Global Navigation Satellite System (GNSS). From this GNSS signal  66 , the GNSS receiver  64  determines a global position  70  of the vehicle  2 . This global position  70  also represents internal sensor information and thus internal sensor data from the perspective of the vehicle  2 . In the multi-storey parking lot  4 , however, receipt of a GNSS signal  66  is not possible, and as a result the global position  70  cannot be determined either. This is shown in  FIG. 2  by a broken line. 
         [0040]    Now that the difference between internal sensor data and external sensor data has been explained, the transmission of the external sensor data, thus the external positional data  14  from the multi-storey parking lot  4  to the vehicle  2  in the radio signal  20 , will be briefly addressed. 
         [0041]    The radio signal  20  can essentially be transmitted via any network structure. In the following, by way of example, what is referred to as a vehicle ad-hoc network is used as an example, for which certain country-specific communication protocols, by way of example in the context of ETSI TC ITS at ETSI in Europe, and in the context of IEEE 1609 at IEEE and at SAE in the United 
         [0042]    States of America, have been proposed. 
         [0043]    Such a vehicle ad-hoc network is also known as a Car2X network and will be explained below in more detail using  FIG. 3 , in which it is represented in the form of a cloud supporting the radio signal  20  and is given reference numeral  72 . 
         [0044]    Each position sensor  12  in the multi-storey parking lot  4  comprises a transmitter with two network layers for sending the radio signal  20 . A routing layer  74  generates from the data sent, e.g. the external position  14  or the route  16 , data packets  76  with a predetermined structure and modulates these in a physical layer  78  on the radio signal  20 . Here the structure of the data packets  76  is determined in the abovementioned specification, wherein to generate the data packets  76  further information, such as, for example, time stamps, may be necessary. 
         [0045]    To be able to apply the HAD function  44  in the multi-storey parking lot  4 , the positional data  14  detected by the external position sensors  12  of the multi-storey parking lot  4  must describe the external position of the vehicle  2  with high precision. Accordingly, the external positional data  14  are of correspondingly high quality in terms of the tolerance of the external position of the vehicle  2 . 
         [0046]    In the present embodiment, this high-quality external position  14  is intended to be used to check and/or calibrate internal sensors in the vehicle  2 . It is pointed out here that the high-quality external position  14  could also be used at a parking facility at the end of a vehicle manufacturer&#39;s production line, to check and/or calibrate internal sensors in the vehicle  2 . The multi-storey parking lot  4  is therefore merely one of many possible applications. This will be explained in the following using the vehicle dynamics sensor  35 . The following method can essentially be applied to any internal sensor in the vehicle  2 , however. 
         [0047]    For this application, a fusion sensor  80  shown in  FIG. 4  is used. The basic concept behind the fusion sensor  80  is to compare the external positional data  14  from the radio receiver  46 , the internal sensor information, such as the vehicle dynamics data  33  from the vehicle dynamics sensor  35 , and the wheel speeds  34  from the wheel speed sensors  32 , and to determine a signal-to-noise ratio in at least one of the sensor signals. Based on the signal-to-noise ratio the internal sensors of the vehicle  2  can then be checked and, if necessary, calibrated. 
         [0048]    The fusion sensor  80  can also output refined positional data  82  of the vehicle  2  from the received sensor information in the multi-storey parking lot  4 . These refined positional data  82  can describe the position of the vehicle  2  in the multi-storey parking lot  2  and its vehicle dynamics in the multi-storey parking lot  2 . To determine the refined positional data  82  external positional data  14  from the radio receiver  46  are compared with the vehicle dynamics data  33  from the vehicle dynamics sensor  14  in a filter  84 , whereby the signal-to-noise ratio in the external positional data  14  is determined from the radio signal  46  or the vehicle dynamics data  33  from the vehicle dynamics sensor  35 . For this the filter  84  can have any design, but a Kalman filter is most effective in achieving this object with a comparatively low demand on computing power. In the following, therefore, the filter  84  will preferably be a Kalman filter  84 . 
         [0049]    The refined positional data  82  of the vehicle  2  enter the Kalman filter  84  together with comparative positional data  86  of the vehicle  2 . The refined positional data  82  are generated in the design in question in, by way of example, a strapdown algorithm  88  known from DE 102006029148 A1, which is incorporated by reference from the vehicle dynamics data  33 . In contrast, the comparative positional data  86  are obtained from a model  90  of the vehicle  2 , which in the first instance is supplied with the external position data  14  from the radio receiver  46 . From the external positional data  14 , in the model  90 , the comparative positional data  86  are then determined, containing the same information as the refined positional data  82 . The refined positional data  82  and the comparative positional data  86  differ merely by their values. 
         [0050]    Based on the refined positional data  82  and the comparative positional data  86 , the Kalman filter  84  calculates an error budget  92  for the refined positional data  82  and an error budget  94  for the comparative positional data  86 . In the following, an error budget is understood to be a total error in a signal, made up of various individual errors in the detection and transmission of the signal. The error budget of a signal can include the deviation from the expected value of the signal and the variance of the signal. 
         [0051]    The error budget  94  of the refined positional data  82  and the error budget  96  of the comparative positional data  86  can then be correspondingly used in the strapdown algorithm  88  and in the model  90  for correcting the refined positional data  82  or the comparative positional data  86 . This means that the refined positional data  82  and the comparative positional data  86  are corrected iteratively by their errors. 
         [0052]    As soon as the vehicle  2  leaves the multi-storey parking lot  4 , the external positional data  14  can be replaced by the global position  70  from the GNSS receiver  64 , whereby the refined positional data  82  can be immediately updated. 
         [0053]    In the context of the present embodiment, the error budget  94  of the refined positional data  82  can be used for setting the vehicle dynamics sensor  35 . This is shown in  FIG. 4  by a dotted line. Through the calibration of the vehicle dynamics sensor based on the error budget  94 , the high quality of the external positional data  14  is used to improve the quality of an internal sensor, in this case the vehicle dynamics sensor  35 , and thus of the corresponding sensor signal, in this case the vehicle dynamics data  33 , in the vehicle  2 . 
         [0054]    The wheel speed sensors  32 , of which, for the sake of brevity, only one is shown in  FIG. 4 , could also be calibrated in the same way.

Technology Classification (CPC): 6