DE102015009308B4 - Method for operating a driver assistance system and motor vehicle - Google Patents

Abstract

Method for operating a driver assistance system of a motor vehicle (1), which has at least one radar sensor (2) that records radar data describing the area surrounding the motor vehicle (1), wherein for at least one road user detected in the radar data, at least one property of all wheel rims ( 18, 25, 29) the rim information describing the road user is determined from the radar data, the rim information for assigning a vehicle type class to the road user is evaluated by means of a classifier and the assigned vehicle type class is taken into account by at least one function of the driver assistance system, characterized in that a radar sensor ( 2) is used with a radar transceiver (13) realized by a semiconductor chip (10), in particular a CMOS chip, the rim information being the reflection strength of a rim (18, 25, 29), in particular of all rims (18, 25, 29), include end is determined, the classifier having different sub-criteria related to properties contained in the rim information, the results of which are combined to determine the vehicle type class, wherein a sub-criterion related to the reflection strength of the rims (18, 25, 29) uses at least three disjoint parameter ranges, wherein reflection strengths of a two-wheeler class, in particular a bicycle class, lying in a first parameter range comprising the lowest reflection strengths, reflection strengths of a passenger car class lying in a second parameter range comprising medium reflection strengths and reflection strengths of a truck class lying in a third parameter range comprising the greatest reflection strengths are assigned.

Description

The invention relates to a method for operating a driver assistance system of a motor vehicle, which has at least one radar sensor that records radar data describing the surroundings of the motor vehicle, wherein for at least one road user detected in the radar data, at least one property of all wheel rims of the road user that is detectable in the radar data is taken from the Radar data is determined, the rim information for assigning a vehicle type class to the road user is evaluated by means of a classifier and the assigned vehicle type class is taken into account by at least one function of the driver assistance system. In addition, the invention relates to a motor vehicle.

Driver assistance systems for motor vehicles have already been proposed in a large number of configurations in the prior art. For at least one function, driver assistance systems use input data that describes the circumstances in and/or around one's own motor vehicle and can, for example, evaluate these against action criteria, if these are met, the driver assistance system carries out an action, for example a driving intervention, an information output, in particular a warning to the driver , and/or the adjustment of operating parameters of another vehicle system. The input data are often (possibly pre-evaluated) sensor data from various sensors of the motor vehicle, and in the case of driver assistance systems related to the area surrounding the motor vehicle, therefore also from environmental sensors. A sensor that is frequently used as part of driver assistance systems is a radar sensor that supplies radar data about the surroundings of the motor vehicle.

The use of radar sensors in motor vehicles is already widely known in the prior art. Nowadays, radar sensors are mostly used as environment sensors for a medium and large distance range in order to be able to determine the distance, angle and relative speed of other road users or larger objects. Radar data of this type can be included in environment models or also be made available directly to vehicle systems. In the known prior art, longitudinal guidance systems, such as ACC, or also safety systems, for example, benefit from radar data.

Radar sensors of conventional design usually have a larger expansion and are rather clumsy, since the antennas and the electronic components required directly on the antenna, i.e. the radar front end, are integrated in one housing. The electronic components mainly form the radar transceiver, which contains a frequency controller (usually including a phase-locked loop - PLL), mixers, a low-noise amplifier (LNA) and the like, but often control modules and digital signal processing components are also implemented close to the antenna, for example around already processed ones To be able to give sensor data, for example object lists, to a connected bus, for example a CAN bus.

The realization of semiconductor-based radar components proved difficult for a long time, since expensive special semiconductors, in particular GaAs, were required. Smaller radar sensors were proposed, the entire radar front end of which is implemented on a single chip using SiGe technology, before solutions using CMOS technology became known. Such solutions are the result of the extension of CMOS technology to high-frequency applications, which is also often referred to as RF-CMOS. Such a CMOS radar chip is extremely small and does not use expensive special semiconductors, so it offers significant advantages over other semiconductor technologies, especially in terms of production. An example implementation of a 77 GHz radar transceiver as a CMOS chip is described in the article by Jri Lee et al., "A Fully Integrated 77-GHz FMCW Radar Transceiver in 65-nm CMOS Technology", IEEE Journal of Solid State Circuits 45 (2010), pp. 2746-2755.

After it was also proposed to implement the chip and the antenna in a common package, an extremely inexpensive small radar sensor is possible, which can meet installation space requirements much better and also has a very low signal-to-noise ratio due to the short signal paths high frequencies and larger, variable frequency bandwidths. Such small radar sensors can therefore also be used for short-range applications, for example in the range from 30 cm to 10 m.

It has also already been proposed to provide such a CMOS transceiver chip and/or a package with a CMOS transceiver chip and antenna on a common printed circuit board with a digital signal processing processor (DSP processor) or to also integrate the functions of the signal processing processor into the CMOS Integrate transceiver chip. A similar integration is possible for control functions.

Especially with safety systems as a typical example of driver assistance systems, the detection of dynamic and static targets in the environment of one's own motor vehicle plays an important role term role. Depending on the detected objects in the area surrounding the motor vehicle and their properties, the traffic situation can then be evaluated, which in turn, as already indicated, can lead to measures, for example a warning for the driver. It was suggested that a situation analysis (SITA) of the current traffic situation should be carried out as a preliminary step to the evaluation of action criteria in order to avoid false and/or incorrect warnings in more complex traffic situations. With the SITA, a large number of data describing the current traffic situation, in particular also radar data, can be used in order to provide a good basis for the actual algorithm evaluating warning criteria.

Especially when considering possible collision scenarios, but also with other functions, not only is the position of other road users in relation to one's own vehicle relatively important information when evaluating a traffic situation, but also the classification of the other road user, for example as a car, truck or two-wheeler. For example, a predicted accident severity and/or the collision probability are often determined as a function of classification information that describes the type of road user. While radar data from the radar sensor is often used for the actual detection and localization of the other road user, image data from optical surroundings sensors, for example cameras, are usually used to classify the type of road user. In this case, however, there is not only the problem of the need for suitable surveillance of the surroundings by the cameras, but these also have other disadvantages. For example, optical environment sensors are very sensitive to dirt and environmental influences, such as different weather conditions. As a result, it may not be possible to classify other road users with sufficient reliability.

DE 10 2012 021 461 A1 relates to a method and a device for the classification of vehicles, wherein at least one wheel of a vehicle is detected by means of at least one radar sensor. The idea is to first use the radar sensor to generate a superpositioned overall signal from several scatter centers of the wheel, which is formed from a characteristic course of radar radiation reflected from the scatter centers during the rotation of the wheel, so that a signature is created from which a wheel variable can be derived can, which in turn can be used to determine a vehicle category. To determine information about the size of the wheel, the time profile of the radar data during a rotation of the wheel should be taken into account, so that a band-spread reflected target echo (blade flashing) is produced.

DE 10 2008 037 233 A1 relates to a vehicle classifier with a device for detecting a rolling wheel, in which a radar speed measurement of individual sections of the circumference is carried out. It is assumed that the peripheral section of the wheel, which is opposite the point of contact with the base, is faster than the moving system in relation to the moving system, embodied by the hub of the wheel, so that a characteristic measurement signal arises that is only from one on a base rolling wheel can originate.

The invention is therefore based on the object of specifying a possibility for improved surveillance of the surroundings using radar data.

To solve this problem, the features of claim 1 are provided according to the invention in a method of the type mentioned. In this case, it is provided that the rim information comprehensively determines the reflection strength of a rim, in particular of all rims.

The invention is based on the combination of two findings. On the one hand, it is now possible, particularly within the framework of the modern radar technologies already discussed at the outset, to use radar sensors in motor vehicles which, despite their space-saving size, can reproduce the location of a reflection with high resolution. For example, the use of radar sensors is conceivable within the scope of the present invention, which offer a spatial resolution of less than 5 cm, in particular less than 3.5 cm. This makes it possible to resolve smaller structures in the radar data and to detect them accordingly. After radar data has so far mainly represented the presence of objects, be they static or dynamic objects, it is now possible to resolve properties, in particular substructures, of these objects and to use them appropriately.

It has been shown that a substructure of other road users, in particular other motor vehicles and bicycles, which can be detected and used particularly well, is provided by the wheel rims. Studies have shown that the rims represent the main scattering centers of the reflections on the side surface of a road user, in particular a target vehicle, so that the rim information will therefore mainly relate to all rims on one side of the other road user. Due to the availability of modern radar sensors in motor vehicles, it is possible relatively accurately resolve the location of these major scattering centers. This allows, through separate interpretation of the rim reflection of target vehicles, not only to better resolve the relative position of the other road user, but also to determine the vehicle type class of the road user, with road users preferably having a passenger car class and/or a truck class and/or at least one two-wheeler class as vehicle type classes for rims be used. A two-wheeler class can be broken down even further, since bicycles and motorcycles, for example, differ further. In general, the vehicle type class determined in this way can expediently be used by other road users to improve a situation analysis of the current traffic situation by a driver assistance system.

By taking into account the vehicle type classes of other road users, the method described here allows a better interpretation of the current traffic situation, with the use of optical sensors that are more dependent on the environmental conditions preferably being able to be completely avoided. Critical traffic situations, in particular with regard to imminent side collisions, can be better assessed, so that a timely and adequate measure, in particular a warning to the driver, can be taken. Of course, another consideration of the vehicle type class of the road user is also conceivable. Overall, the improved possible situation analysis of a current traffic situation allows functions of the driver assistance systems to be executed more reliably, which in particular also makes it possible to reduce the rate of false alarms and false alarms.

As already mentioned, it has been found that the rims are the main reflective targets on the side surface of other motor vehicles, ie road users. Consequently, the rims in the radar data can expediently be detected as the main reflection centers in an area containing radar data of the road user, which relates in particular to a side view. It is already known how individual reflection events, which are contained in the radar data, can be assigned to a specific object, here a road user, in particular as part of a pre-evaluation. After a high-resolution radar sensor is used, an area covered by reflections is created in which the main reflection centers (main scattering centers) can be easily localized by appropriate analysis algorithms. Customary processing algorithms for segmenting road users in radar data are already known; In particular, algorithms from image processing can also be transferred to the radar data to detect the wheel rims, after these are available in a specific spatial resolution as a kind of “image” of the road user. Main reflection centers can also be determined by looking at intensity curves or the like.

In a specific embodiment of the invention, it can be provided that the rim information also contains at least one position of at least one rim, in particular all rims, and/or the distance of at least one pair, in particular all adjacent pairs, of rims and/or an extent of at least one rim, in particular all rims and/or a number of detected rims is comprehensively determined. A large number of different properties can therefore be derived from the radar data, which differ from vehicle type class to vehicle type class and thus provide the basis for a reliable classification. In order to realize this in concrete terms, the invention provides that the classifier has sub-criteria related to different properties contained in the rim information, the results of which are combined to determine the vehicle type class. It has been shown that often not a single property is sufficient to allow a sufficiently reliable vehicle type classification. For example, the spacing between adjacent rims on a set of wheels on a truck may be similar to that on the two wheels on a bicycle, but there are significant differences in reflectance/expansion. A suitable logic can evaluate the results of the sub-criteria and draw corresponding conclusions about the actual vehicle type classes, it being noted that it is also conceivable to use sub-criteria for mutual plausibility checks.

It can be provided that a sub-criterion related to the dimensions of the rims uses at least three disjoint parameter ranges, wherein in a first parameter range comprising the smallest extents, extents of a two-wheeler class, in particular a bicycle class, in a second, medium extents parameter range, extents of a passenger car class and in a third parameter range encompassing the largest extents, extents of a truck class are assigned. In the case of two-wheelers, especially bicycles, due to the spokes, reflections usually only occur in a clearly recognizable quantity from a small, inner area, so that a small extent can be assumed. Trucks often have extremely large wheel rims, which is also reflected in the radar data.

According to the invention, a sub-criterion is provided with regard to the reflection strength of the rims, which also uses at least three disjoint parameter ranges, with reflection strengths of a two-wheeler class lying in a first parameter range comprising the lowest reflection strengths, in particular a bicycle class, and reflection strengths of a passenger car class lying in a second parameter range comprising medium reflection strengths and in a third parameter range encompassing the greatest reflection strengths, reflection strengths are assigned to a truck class. Here, too, use is made of the fact that the large wheel rims of a truck reflect the radar beams very strongly.

A further concrete embodiment of a sub-criterion provides that a sub-criterion evaluating the number of rims assigns a rim number that exceeds a threshold value, in particular four, to a truck class. Trucks often have a larger number of wheels and therefore also a larger number of wheel rims that can be seen from the side. This can also be used for differentiation.

It should be pointed out once again that these are only examples of sub-criteria. Of course, a large number of other sub-criteria are also conceivable within the scope of the present invention, for example those that consider the distance from adjacent rims. This shows how useful the combination of several sub-criteria can be, since the rim scattering centers on a two-wheeler, for example, are close together like on a truck, but they do not reflect as strongly as on a passenger car or truck, so that the reflection strength can be decisive; alternatively or additionally also the expansion.

It has proven particularly expedient if at least one property is determined from an intensity profile and/or histogram determined along a line running through the center of a detected rim. Intensity curves can be evaluated using customary, known methods for curve analysis in order to determine characteristic values that directly correspond to properties that can be contained in the rim information. In an intensity curve, the rim usually appears as a peak, the height of which is a measure of the reflection strength and the width of which reflects the extent of the rim. The distance between adjacent peaks corresponds to the distance between adjacent rims.

As already mentioned, the invention takes advantage of the emergence of new, high-resolution, modern radar technologies. The present invention provides that a radar sensor with a radar transceiver implemented by a semiconductor chip, in particular a CMOS chip, is used. It is particularly advantageous in this context if, in addition to the radar transceiver, a digital signal processing component (DSP) and/or a control unit of the radar sensor are also implemented by the semiconductor chip and/or an antenna arrangement of the radar sensor is implemented with the semiconductor chip as a package. In this way, extremely compact radar sensors can be created that can easily be accommodated in the motor vehicle and, because of the short signal paths, also allow an excellent signal-to-noise ratio. With such radar sensors on a semiconductor basis, in particular on a CMOS basis, operation at high frequencies and with a high frequency bandwidth can also be implemented.

Particularly in the case of a radar sensor implemented within the technology, but also in general, it is extremely expedient in this context if the radar sensor operates in a frequency range from 77 to 81 GHz and/or with a frequency bandwidth greater than 1 GHz, in particular 4 GHz. is operated.

A high-resolution radar system with a bandwidth of 4 GHz can achieve a very high distance resolution, for example of approximately 3.4 cm, relative to conventional automotive radar sensors used to date. The resolution also correlates with the distance measurement accuracy, which means that with higher resolution, the accuracy is also very high. In this way, for example, the dimensions of the rims, but also the rim information in general, can be measured very precisely.

An expedient development of the invention provides that several, in particular eight, radar sensors are used, which completely cover the surroundings of the motor vehicle in a 360° angular range. For example, it is possible to use an array of eight radar sensors, three of which can be installed in the front and three in the rear bumper. Two further, laterally aligned radar sensors can be provided, for example, in the doors of the motor vehicle, in particular by having a radar-permeable, paintable window in front of the door panel is seen. Since the several radar sensors are expediently wide-angle radar sensors, for example with an opening angle of up to 170°, for example 160°, in azimuth and of up to 120°, for example 90°, in elevation, the entire environment is thus reliably covered around the motor vehicle. The laterally aligned radar sensors are particularly relevant when considering road users driving parallel at the same height. However, it is of course also conceivable to use the method for other road users, for example crossing road users, for whom the front or rear radar sensors are then more relevant.

In an expedient embodiment, a safety system can be used as the driver assistance system, the vehicle type class being taken into account when determining a collision value describing a possible collision with the respective road user. For example, the determined vehicle type class of another road user can be used if an accident severity and/or a collision probability is to be estimated.

It should also be noted at this point that the method according to the invention does not necessarily have to be carried out by a control unit assigned (exclusively) to the driver assistance system, but rather, in particular in the case of several functions of different driver assistance systems that use the vehicle type class, a central control unit can be provided, which then prefers the sensor data , also comprising the radar data, evaluates various environmental sensors of the motor vehicle in order to already provide suitable input data for the various functions, for example in the form of an environment model, as has already been proposed in principle in the prior art. If the environment model is object-oriented, the vehicle type classes of other road users can be directly assigned there, for example. If the control unit that pre-evaluates the sensor data in this way also carries out the functions, one can also speak of a “central driver assistance system” which implements a large number of functions of individual sub-driver assistance systems.

In addition to the method, the invention also relates to a motor vehicle having at least one driver assistance system and a control unit designed to carry out the method according to the invention. All statements relating to the method according to the invention can be transferred analogously to the motor vehicle according to the invention, with which the advantages already mentioned can also be obtained.

• 1 eine Prinzipskizze eines erfindungsgemäßen Kraftfahrzeugs,
• 2 einen in dem Kraftfahrzeug eingesetzter Radarsensor,
• 3 Felgen-Reflektionszentren bei einem Teil eines Lastkraftwagens,
• 4 einen 3 zugehörigen Intensitätsverlauf,
• 5 Felgen-Reflektionszentren bei einem Personenkraftwagen,
• 6 einen 5 zugehörigen Intensitätsverlauf,
• 7 Felgen-Reflektionszentren bei einem Zweirad, und
• 8 einen 7 zugehörigen Intensitätsverlauf.

Further advantages and details of the present invention result from the exemplary embodiments described below and from the drawing. show:

• 1 a schematic diagram of a motor vehicle according to the invention,
• 2 a radar sensor used in the motor vehicle,
• 3 rim reflection centers on part of a truck,
• 4 a 3 associated intensity profile,
• 5 Rim reflection centers on a passenger car,
• 6 a 5 associated intensity profile,
• 7 Rim reflection centers on a two-wheeler, and
• 8th a 7 associated intensity profile.

1 1 shows a schematic diagram of a motor vehicle 1 according to the invention. In the present case, it has eight radar sensors 2, which are designed as wide-angle radar sensors and, as can be seen from the indicated detection areas 3, allow 360° detection of the surroundings of motor vehicle 1. The radar sensors 2 based on CMOS technology are extremely small, for example less than 3 cm by 3 cm, so that they can be installed in the front or rear bumper 4, 5 of the motor vehicle 1 and installation in side doors 6 is also possible is when, for example, a radar-transparent window is provided in the sheet metal.

The radar data from the radar sensors 2 are evaluated in a control unit 7, which is assigned to a driver assistance system, here a safety system, and is also designed to carry out the method according to the invention.

2 shows the structure of the radar sensors 2 in more detail in the form of a schematic diagram. A radar sensor 2 has a housing 8 in which a printed circuit board 9 is held, on which a semiconductor chip 10, here a CMOS chip, is arranged. The semiconductor chip 10 is realized together with an antenna arrangement 11 of the radar sensor 2 as a package 12, the antenna arrangement 11 being configured such that angles to a reflecting point can be detected in two mutually perpendicular planes.

In addition to the radar transceiver 13 , the semiconductor chip 10 also implements a digital signal processing component 14 (DSP) and a control unit 15 of the radar sensor 2 .

The radar sensors 2 are operated in a frequency range of 77 to 81 GHz with a frequency bandwidth of 4 GHz in order to be able to supply radar data describing the surroundings of the motor vehicle 1 with high resolution.

This radar data is now evaluated in control unit 7 in order to be able to determine the vehicle type class, in particular truck, car or two-wheeler, of other road users. For this purpose, a search is made in the area assigned to the respective road user, in which reflections of the road user were received, for the main scattering centers, particularly in the lower area, which correspond to the wheel rims of the target vehicle as a road user. Various types of algorithms can be used here, which evaluate intensity profiles, for example, or are also based on image processing algorithms. Since the radar sensors 2 have a high spatial resolution, in particular in the range of 3.5 cm, the positions of the rims and also their dimensions can be determined quite precisely. In addition, the reflection strength of the rims is determined. Other useful properties, such as the distance between adjacent rims and the total number of rims on the side of the road user under consideration, can also be determined.

the 3 and 4 show as a first specific example the rear part of a truck 16, which has three axles with wheels 17 that are visible in the side view shown. The rims 18 of the wheels 17 represent the main centers of reflection, which is to be indicated by the individual reflection events in the radar data indicated by stars. For clarity, reflection events from other parts of the truck 16 are not shown.

4 shows an intensity curve along a horizontal line through the centers of the respective rims 18, in which the peaks 19, which are generated by the respective rims 18, stand out clearly. From the intensity curve of the 4 properties of the rims 18 that are important for further evaluation can be determined as part of the rim information to be determined. For example, the height 20 of the peak 19 is a measure of the reflection strength, the width 21 of a peak 19 is a measure of the extent of the corresponding rim 18 and the distance 22 between two peaks corresponds to the distance between two adjacent rims 18. It can be seen that the reflect Rims 18 of the truck 16 are extremely strong and quite extensive. In addition, adjacent rims 18 follow one another extremely closely in the rear area. Another specific property as rim information here is the (total) number of rims 18 on the side that can be detected by the radar sensors 2 .

5 1 shows a passenger car 23 as a further example of another road user, which as usual has two wheels 24 and therefore two rims 25 on each side. Here, too, the rims 25 represent the main reflection centers, which can be seen in the associated intensity profile according to FIG 6 clearly shows. However, as can be seen from the peaks 26, the rims reflect weaker (smaller peak height) and the rims 25 are less extended (smaller peak width). Furthermore, the distance between the adjacent rims 25 is significantly greater. The number of rims 25 is evidently less than the number of rims 18 of the truck 16.

7 shows an example of a two-wheeler 27 as a further road user, a bicycle with two wheels 28 and correspondingly associated rims 29. Due to the low reflection of the spokes, the main reflection centers of the rims 29 are mainly the central parts, which nevertheless reflect relatively weakly in comparison. see also the in 8th associated intensity profile. The peaks 30 are extremely weak here.

In the method according to the invention, the rim information can be evaluated by a classifier which, in the present case, combines a number of partial criteria which in turn relate to specific properties contained in the rim information. From the finding that the large rims 18 of the truck 16 reflect the radar beams very strongly, while the rims 25 of the passenger car 23 reflect moderately strongly and the rims 29 of the two-wheeler 27 only have a weak reflection, there is a partial criterion that checks whether the reflection strength, specifically expressed for example as the value of the height 20 of the peaks 19, 26 and 30, is within certain intervals (parameter ranges) which are assigned to the different vehicle type classes. Corresponding investigations can be formulated with regard to the extent, for example expressed over the width 21 of the peaks 19, 26, 30. From the number of rims 18, 25, 29 it can be concluded that a truck 16 is probably involved if there are more than two rims 18, 25, 29 per side. A sub-criterion can also evaluate the distances between the rims 18, 25, 29, for example, by the Distances between the peaks 19, 26, 30 can be reproduced in the intensity curves.

After several sub-criteria are combined for mutual plausibility and better decision-making, a reliable result is finally available. For example, both the two-wheeler 27 and the truck 16 have rims 18, 29 close together, but the number of rims 18, 29, the reflection strength and the extent represent clear distinguishing features.

As a result, the classifier therefore supplies a vehicle type class, in particular “passenger car”, “truck” or “two-wheeler”, which the driver assistance system designed as a safety system can use for improved determination of collision parameters.

Claims (11)

Method for operating a driver assistance system of a motor vehicle (1), which has at least one radar sensor (2) that records radar data describing the area surrounding the motor vehicle (1), wherein for at least one road user detected in the radar data, at least one property of all wheel rims ( 18, 25, 29) the rim information describing the road user is determined from the radar data, the rim information for assigning a vehicle type class to the road user is evaluated by means of a classifier and the assigned vehicle type class is taken into account by at least one function of the driver assistance system, characterized in that a radar sensor ( 2) is used with a radar transceiver (13) realized by a semiconductor chip (10), in particular a CMOS chip, the rim information being the reflection strength of a rim (18, 25, 29), in particular of all rims (18, 25, 29), incl send is determined, the classifier having different sub-criteria related to properties contained in the rim information, the results of which are combined to determine the vehicle type class, wherein a sub-criterion related to the reflection strength of the rims (18, 25, 29) uses at least three disjoint parameter ranges, wherein reflection strengths of a two-wheeler class, in particular a bicycle class, lying in a first parameter range comprising the lowest reflection strengths, reflection strengths of a passenger car class lying in a second parameter range comprising medium reflection strengths and reflection strengths of a truck class lying in a third parameter range comprising the greatest reflection strengths are assigned. procedure after claim 1 , characterized in that the passenger car class and/or the truck class and/or the two-wheeler class are used as vehicle type classes for road users having rims (18, 25, 29). procedure after claim 1 or 2 , characterized in that the rim information includes at least one position of at least one rim (18, 25, 29), in particular all rims (18, 25, 29), and/or the distance between at least one pair, in particular all pairs, of rims (18, 25, 29) and/or an extent of at least one rim (18, 25, 29), in particular all rims (18, 25, 29), and/or a number of detected rims (18, 25, 29) is comprehensively determined. procedure after claim 3 , characterized in that a sub-criterion related to the dimensions of the rims (18, 25, 29) uses at least three disjunctive parameter ranges, wherein in a first parameter range comprising the smallest dimensions, the dimensions of the two-wheeler class, in particular a bicycle class, lie in a second, middle Extensions of the passenger car class that encompass the parameter range and extensions of the truck class that are in a third parameter range that encompasses the largest extents are assigned. Procedure according to one of claims 3 or 4 , characterized in that a sub-criterion evaluating the number of rims (18, 25, 29) assigns a rim number exceeding a threshold value, in particular four, to a truck class. Method according to one of the preceding claims, characterized in that at least one property is determined from an intensity profile and/or histogram determined along a line running through the center of a detected rim (18, 25, 29). Method according to one of the preceding claims, characterized in that in addition to the radar transceiver (13), a digital signal processing component (14) and/or a control unit (15) of the radar sensor (2) are also implemented by the semiconductor chip (10) and/or an antenna arrangement (11) of the radar sensor (2) is realized with the semiconductor chip (10) as a package (12). Method according to one of the preceding claims, characterized in that the radar sensor (2) in a frequency range of 77 up to 81 GHz and/or with a frequency bandwidth greater than 1 GHz, in particular 4 GHz. Method according to one of the preceding claims, characterized in that several, in particular eight, radar sensors (2) are used which completely cover the surroundings of the motor vehicle (1) in a 360° angular range. Method according to one of the preceding claims, characterized in that a safety system is used as the driver assistance system, the vehicle type class being taken into account when determining a collision value describing a possible collision with the respective road user. Motor vehicle (1) having at least one radar sensor (2), at least one driver assistance system and a control unit (7) designed to carry out the method according to one of the preceding claims, in particular assigned to and/or central to the driver assistance system.

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