Abstract:
Method for determining a dynamic variable representative for a lateral movement of a located object in a driver assistance system for motor vehicles, which has two angle-resolving distance sensors situated laterally offset to one another for locating the object, using which a radial component of the relative velocity of the object along the particular line of sight is also measurable, wherein the dynamic variable is calculated on the basis of the radial components of the relative velocity measured by the two distance sensors.

Description:
FIELD OF THE INVENTION 
     The present invention relates to a method for determining a dynamic variable representative for a lateral movement of a located object in a driver assistance system for motor vehicles, which has two angle-resolving distance sensors situated laterally offset to one another for locating the object, using which a radial component of the relative velocity of the object along the particular line of sight is also measurable. 
     BACKGROUND INFORMATION 
     Examples of driver assistance systems in which the present invention is used are, for example, so-called ACC systems (adaptive cruise control), which allow an automatic regulation of the distance to a preceding vehicle (the object), as well as predictive safety systems (PSS), which are used for automatically recognizing an imminent collision, so that measures for avoiding the collision or for mitigating the collision consequences may be initiated. 
     Precise knowledge of the lateral movements of the object is significant, for example, in the cases in which a merging vehicle, from which an increased danger of collision originates, is to be recognized as early as possible or, vice versa, the earliest possible recognition of vehicles turning off or leaving the host vehicle&#39;s lane is necessary, so that the host vehicle is not decelerated unnecessarily strongly and/or may accelerate again earlier. 
     The transverse component of the velocity (in the direction transverse to the roadway) and the yaw rate of the object may be cited in particular as examples of dynamic variables which are representative for the lateral movement of an object. The yaw rate is significant because it allows an early estimation of the future movement direction and thus the lateral velocity of the object. 
     Typical driver assistance systems normally have an angle-resolving, long-range radar sensor (LRR) for locating preceding vehicles and other objects, using which the distance and the relative velocity or, more precisely, the radial component of the relative velocity may be measured relatively precisely. The angle resolution capability of the radar sensor additionally allows at least a coarse estimation of the azimuth angle, so that together with the distance information, the position of the object in a two-dimensional coordinate system may be determined. Because of the limited angle resolution capability, the precision when determining the lateral position (y position) of the object is significantly worse, however, than the precision when determining the distance. 
     A direct measurement of the transverse component of the velocity of the object is not possible. This variable may therefore only be determined indirectly, by tracking the lateral positions of the object over a certain period of time and differentiating with respect to time. The unavoidable inaccuracies in the measurement of the lateral position of the object are reinforced still further upon the calculation of the derivatives with respect to time, so that the results are subject to significant measurement noise, which may not be entirely suppressed even by filtering the data. The calculation of the derivative with respect to time and the filtering operations additionally have the result that the data for the lateral velocity of the object are only available comparatively late. 
     A driver assistance system is described in German Patent No. DE 199 49 409, in which two short-range radar sensors (SRR) are used for locating objects ahead of the vehicle, which only measure distances and relative velocities, but not azimuth angle. Because the two sensors are situated laterally offset to one another, however, the lateral position of the object may be determined at least approximately by triangulation on the basis of the distance data. The lateral velocity may also only be determined here by differentiation with respect to time. 
     German Patent No. DE 10 2004 028 822 describes a driver assistance system having a “scanning” distance sensor, such as a radar or lidar sensor, using which the rear of a preceding vehicle may be scanned, so that distance data are obtained for multiple points on the rear of the object, the particular associated azimuth angles being known. Under the assumption that the reflection points from which the distance data are obtained lie approximately on a straight line which is oriented perpendicular to the longitudinal axis and thus to the motion direction of the object, the orientation of the object and, on the basis of this, the lateral velocity of the object are determined from the distance data. The precision is also decisively a function of the angle resolution capability of the sensor in this method. 
     SUMMARY OF THE INVENTION 
     An object of the present invention is to provide a method for driver assistance systems, which allows rapid and precise determination of at least one dynamic variable which is representative for the lateral movement of a located object. 
     This object is achieved in a method according to the present invention in that the dynamic variable is calculated on the basis of the radial components of the relative velocity measured by the two distance sensors. 
     The method according to the present invention assumes that two distance sensors are provided, which are situated at a specific lateral distance from one another on the host vehicle, and each of which is capable of measuring the radial component of the relative velocity of the object, “radial component” meaning the velocity component along the line of sight from the affected sensor to the object in each case. As will be explained in greater detail in the description of the exemplary embodiments, the radial components thus measured are influenced due to various effects by dynamic variables, which are representative of the lateral movement of the object, in particular by the lateral velocity and the yaw rate of the object, and these influences have the result in particular that the two sensors measure different values for the radial component of the relative velocity. The lateral movement of the object may be inferred on the basis of these differences. 
     An important advantage of this method is that the measurement of the lateral movement is decisively based on the analysis of relative velocities which may be measured very precisely with the aid of radar sensors. In addition, these variables may be converted directly into a lateral velocity and/or yaw rate of the object, without having to be differentiated once again with respect to time. The desired dynamic variable is therefore immediately available, and the obtained data already have a relatively high quality even without time-consuming filtering. 
     In one specific embodiment, the located object is viewed as a punctiform object, and the lateral velocity of the object is calculated directly on the basis of the measured radial components and azimuth angle. The inaccuracies in the determination of the azimuth angle are incorporated into the result, but the measured azimuth angle does not have to be derived with respect to time once again during the calculation of the lateral velocity, and the occurrence of measurement noise is therefore avoided, which would otherwise be caused by the derivation with respect to time of statistically fluctuating measured variables. 
     According to another specific embodiment, the located object is viewed as an extended object and it is assumed that the two distance sensors receive signals from two different reflection points on the object. In this case, the yaw rate of the object may also result in differences in the measured radial components. 
     Under the assumption that the lines of sight from the sensors to the associated reflection points on the object run approximately parallel and therefore the differences in the measured radial components of the velocity may hardly be caused by the lateral velocity of the object, the yaw rate of the object may then be determined on the basis of the difference of the measured radial components and the distance of the reflection points. 
     This is particularly advantageous for early recognition of vehicles turning off, because a preceding vehicle which constantly remains in its own lane will have a yaw rate close to zero, while in the starting phase of a turning operation, as soon as the driver of this vehicle turns the steering wheel, the yaw rate increases abruptly. A change in the lateral velocity also occurs only as a result of this yaw rate change. The present invention therefore has the advantage that it allows turning or lane-changing operations of preceding vehicles to be recognized already as they begin. 
     By integrating the yaw rate over time, the current orientation of the object may also be determined, from which the lateral velocity may in turn be calculated. 
     On the other hand, if the two reflection points on an extended object lie relatively close to one another, the influence of the yaw rate may be neglected and the differences in the measured radial component of the relative velocity may be converted directly into a lateral velocity, as for a punctiform object. 
     The method described above for analyzing the data for an extended object is based on various assumptions which will normally only be approximately fulfilled in practice. However, it is possible to perform the analysis methods based on various idealizing assumptions in parallel and then to calculate weighted mean values from the values thus obtained for the desired dynamic variables, the weighting being a function of how realistic the relevant idealizing assumptions are in the particular situation. 
     According to still a further specific embodiment of the method according to the present invention, a relationship between the differences in the measured radial components of the relative velocity and a probability parameter, which indicates the probability of a turning operation and/or lane change, is set up directly on the basis of geometric models and/or empirical data. This probability parameter is also a dynamic variable representative of the lateral movement of the object in the meaning of the present invention. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  shows a sketch of a vehicle equipped with a driver assistance system when locating an approximately punctiform object. 
         FIG. 2  shows a vector diagram for  FIG. 1 . 
         FIG. 3  shows a sketch of the vehicle from  FIG. 1  when locating an extended object. 
         FIG. 4  shows a characteristic curve to determine a probability parameter according to a specific embodiment of the method according to the present invention. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  schematically shows the front part of a motor vehicle  10 , which is equipped with a driver assistance system  12 , such as an ACC system. This driver assistance system includes two angle-resolving distance sensors  14 L and  14 R, which are installed in proximity to the left and right lateral delimitations of vehicle  10  in the front part, so that they jointly monitor the area in front of vehicle  10 . For example, distance sensors  14 L and  14 R are long-range radar sensors (LRR). 
     In the example shown, an approximately punctiform object  16 , such as the rear end of a preceding motorcycle, is located by both distance sensors  14 L and  14 R. It may be assumed as a somewhat idealized case that both sensors receive radar echoes from a single reflection point  18  on the rear of object  16 . Accordingly, left distance sensor  14 L measures the value for the distance between reflection point  18  and this distance sensor and a value for radial component v rL  of the relative velocity of object  16 , i.e., the relative velocity component in the direction parallel to line of sight  20 L, which connects radar sensor  14 L to reflection point  18 . In addition, distance sensor  14 L also measures azimuth angle α between the forward direction of vehicle  10  and line of sight  20 L on the basis of its angle-resolving capability. 
     Correspondingly, right distance sensor  14 R measures the distance between this sensor and reflection point  18 , radial component v rR  of the relative velocity of object  16  along line of sight  20 R, and azimuth angle β between this line of sight and the forward direction. 
     The forward direction of vehicle  10  defines a coordinate system having axis x running in the travel direction of this vehicle and axis y running perpendicular thereto. A vector diagram is drawn for object  16 , which indicates absolute velocity V abs  of this object and its relative velocity v in relation to vehicle  10 . The difference between absolute and relative velocities is intrinsic velocity V of vehicle  10 . 
     A method will now be described, using which it is possible to obtain a relatively precise value for the vector of relative velocity v of object  16  on the basis of the data of distance sensors  14 L and  14 R, in particular also a relatively precise value for the relative lateral velocity of object  16 , i.e., for y component v y  of vector v. 
     Relative velocity v is decomposed into its components v x  and v y  in  FIG. 2 . In addition, line of sight  20 R from right distance sensor  14 R in  FIG. 1 , i.e., the line of sight which forms angle β with the forward direction, and radial component v rR  of the relative velocity along this line of sight are shown. 
     A right triangle A, B, C may be seen in  FIG. 2 , whose hypotenuse is x component v x  of the relative velocity. This triangle contains angle β, and its adjacent side is a part of the vector which represents radial component v rR . 
     Furthermore, a right triangle B, D, E may be seen, having lateral velocity v y  as the hypotenuse. This triangle also contains angle β, and its opposite side (section D-E) corresponds to the missing part of radial component v rR . It follows therefrom:
 
 v   rR   =v   y *sin β+ v   x *cos β  (1)
 
     The corresponding equation is obtained for line of sight  20 L:
 
 v   rL   =v   y *sin α+ v   x *cos α  (2)
 
     Overall, the matrix equation is thus obtained: 
     
       
         
           
             
               
                 
                   
                     
                       
                         v 
                         rL 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         sin 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         αcos 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         α 
                       
                     
                     
                       
                         v 
                         x 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         v 
                         x 
                       
                     
                   
                   
                     
                       
                           
                       
                     
                     
                       = 
                     
                     
                       
                           
                       
                     
                     
                       * 
                     
                     
                       = 
                     
                     
                       
                         M 
                         * 
                       
                     
                   
                   
                     
                       
                         v 
                         rR 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         sin 
                         ⁢ 
                         
                             
                         
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                         βcosβ 
                       
                     
                     
                       
                         v 
                         y 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         v 
                         x 
                       
                     
                   
                 
               
               
                 
                   ( 
                   3 
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     To obtain the desired variables v y  and v x , matrix M only still has to be inverted in a known way: 
     
       
         
           
             
               
                 
                   
                     
                       
                         v 
                         x 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         cos 
                         ⁢ 
                         
                             
                         
                         ⁢ 
                         β 
                       
                     
                     
                       
                         
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                           cos 
                         
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                         α 
                       
                     
                     
                       
                         v 
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                         = 
                         
                           
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                         v 
                         y 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         
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                         βcos 
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                         α 
                       
                     
                     
                       
                           
                       
                     
                     
                       
                         v 
                         rR 
                       
                     
                   
                 
               
               
                 
                   ( 
                   4 
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     In this way, vectorial relative velocity v of object  16  and thus in particular also its lateral velocity v y′  are obtained from measured azimuth angles α and β and measured radial components v rL  and v rR , and this is performed directly, without passing by a derivative with respect to time of the y location coordinate (lateral position) of reflection point  18 . 
     These calculations are executed in an electronic computer which is part of driver assistance system  12 . 
       FIG. 3  shows a sketch similar to  FIG. 1 , in which an extended object  22 , such as the rear of a preceding passenger automobile, is located by the two distance sensors  14 L,  14 R instead of an approximately punctiform object. Left distance sensor  14 L receives a radar echo from a reflection point  24  in this case, while right distance sensor  14 R receives an echo from another reflection point  26 . The location of reflection points  24 ,  26  is determined by the condition that at these points the perpendicular incidence of the rear of object  22  coincides with line of sight  20 L or  20 R, respectively. Reflection points  24  and  26  lie on a straight line  28 , which corresponds to the rear of object  22 , and the distance between reflection points  24 ,  26  is only slightly less than the width of object  22  and also differs only slightly from the distance between both distance sensors  14 L,  14 R of vehicle  10 . 
     For this reason, in this case both lines of sight  20 L and  20 R run nearly parallel to one another. If object  22  does not execute a yaw movement, measured radial components v rL  and v rR  are therefore nearly equal, and they correspond to the absolute value of the relative velocity of object  22 . However, it is assumed in the example shown that object  22  (for example, because of a steering wheel turn) executes a yaw movement having angular velocity ω, with the result that radial component v rL  measured by the left distance sensor is greater and radial component v rR  measured by the right distance sensor is correspondingly smaller. 
     In this case, information about the lateral movement of object  22  may be obtained in the following way. 
     Because the distances to particular reflection points  24  and  26  may be measured relatively precisely using distance sensors  14 L and  14 R and, somewhat less precisely, corresponding azimuth angles α and β may also be measured, the location of reflection points  24 ,  26  in the x-y coordinate system may be determined. The location of straight line  28  is thus also determined, and if one assumes that extended object  22  is a traveling vehicle, the travel direction of this vehicle will be the direction perpendicular to straight line  28 . The direction of the vector which specifies absolute velocity v abs  of object  22  is thus known, but not the absolute value of this vector. 
     In the example shown, radial components v rL  and v rR  are approximately equal with opposite signs, which means that their mean value, which specifies the radial component of the relative velocity of object  22  as a whole, is approximately zero. In this case, the absolute value of v abs  must be equal to the component of intrinsic velocity V of vehicle  10  which is parallel to vector v abs . This component may be determined by calculation from the known absolute value of intrinsic velocity V and the known location of straight line  28 . Vector v abs  is then known. By subtraction of intrinsic velocity V, vectorial relative velocity v and thus also its components v y  and v x  are obtained. 
     If the mean value of radial components v rL  and v rR  is not zero, this means that object  22  is moving in relation to vehicle  10  along nearly parallel lines of sight  20 L and  20 R, and the mean value of radial components v rL  and v rR  may be represented as a vector which describes this relative movement. This vector may also, like intrinsic velocity V, be decomposed into a component parallel to v abs  and a component perpendicular thereto, and the absolute value of v abs  is the sum of the parallel components of the relative velocity and intrinsic velocity V. 
     This method will be more precise the further apart reflection points  24  and  26  lie and the less azimuth angles α and β differ. On one hand, as a function of the contour of the rear of object  22 , if reflection points  24 ,  26  lie relatively close to one another, the determination of the location of straight line  28  is less reliable, but on the other hand the influence of yaw rate ω is then so small that it may be neglected. In addition, azimuth angles α and β will then differ significantly from one another, so that more precise results are obtained when velocity components v y  and v x  are calculated according to equation (4). 
     It is also possible to apply both modes of calculation in parallel and to weight the results differently depending on the distance of the reflection points. 
     The direct analysis of difference v rL −v rR  of the radial components provides further useful information. If this is divided by the known distance between reflection points  24  and  26 , yaw rate ω of object  22  is obtained directly. 
     On the one hand, this allows a check of the results of the previously described calculations for velocity components v y  and v x . Specifically, if the vector of absolute velocity v abs  of object  22  is reconstructed therefrom and from intrinsic velocity V and tracked over multiple measuring cycles, the directions assumed by vector v abs  must correspond to the time integral of yaw rate ω. Deviations because of measurement inaccuracies are possible, however, because the measured variables are incorporated differently in the calculation of ω on the one hand and the calculation of the direction of v abs  on the other hand. The existence or nonexistence of such deviations therefore provides information about the precision of the measurements. 
     In a typical traffic situation, a preceding vehicle (object  22 ) is tracked over a longer period of time by the driver assistance system of vehicle  10 . On a straight section, yaw rate ω will be nearly zero. However, if object  22  turns off into a side street or changes to an adjoining lane, this is always initiated by a steering operation which immediately results in a non-vanishing yaw rate ω. This increase of the yaw rate may be detected using the method described above without delay. Only in the further course of the turning or lane-changing operation will a measurable direction change of absolute velocity v abs  result, and the corresponding measurements may be used to verify the detected turning or lane-changing operation. 
     The direct measurement and analysis of yaw rate ω thus allows especially early recognition of turning and lane-changing operations. This is true not only for lane-changing operations in which the preceding vehicle changes from the host lane to an adjacent lane, but rather also for merging operations, in which the preceding vehicle changes from an adjacent lane to the host vehicle&#39;s lane. 
     The methods described above with reference to  FIGS. 1 and 2  on the one hand and  FIG. 3  on the other hand share the feature that difference v rL −v rR  of the radial components becomes greater if object  16  or  22  turns to the right during a starting turning or lane-changing operation, and becomes smaller if the object turns to the left. It is therefore possible through mathematical analysis of typical traffic situations and/or by experiments to directly produce a relationship between difference v rL −v rR  of the radial components and the turning or lane-changing probability of the object. 
     An example of such a relationship is shown in  FIG. 4 . A probability parameter P is plotted against difference v rL   † −v rR  therein. The turning probability varies between 0 and +1 and is given by the absolute value of P. The sign of P indicates the direction: for a turning operation (or lane-changing operation) to the right, P is positive, and for a turning operation (or lane-changing operation) to the left, P is negative. 
     If such a relationship for turning probability P is stored in driver assistance system  12 , a turning operation may be recognized early, namely as soon as difference v rL −v rR  exceeds a specific threshold value. If necessary, turning probability P shown in  FIG. 4  may also be combined with other probability parameters, which are based on other criteria, or the threshold value for the recognition of a turning operation may be varied on the basis of other criteria, such as the existence of a turning possibility, which is recognized on the basis of the digital street maps of a navigation system.