WO2018134139A1

WO2018134139A1 - Establishing a measure for a local traffic density by a driver assistance system of a motor vehicle

Info

Publication number: WO2018134139A1
Application number: PCT/EP2018/050801
Authority: WO
Inventors: Kevin Nguyen
Original assignee: Valeo Schalter Und Sensoren Gmbh
Priority date: 2017-01-18
Filing date: 2018-01-15
Publication date: 2018-07-26
Also published as: DE102017100871A1

Abstract

The invention relates to a driver assistance system (2) for a motor vehicle (1), comprising a sensor device (3) for capturing an environment of the motor vehicle (1), as well as the calculation unit (5) for establishing a measure for a traffic density, wherein the sensor device (3) is configured to capture an available road surface (6) of a road (7), on which a motor vehicle (1) is driving; and the calculation unit (5) is configured to calculate a surface size value A of the captured available road surface (6) and to establish a measure p for a local traffic density in dependency on the surface size value A calculated for the available road surface (6), in order to establish a traffic density on a road (7) fast and reliably.

Description

Establishing a measure for a local traffic density by a driver assistance system of a motor vehicle

The invention relates to a driver assistance system for a motor vehicle, comprising a sensor device for capturing an environment of the motor vehicle and comprising a calculation unit for establishing a measure for a traffic density. The invention also relates to a corresponding method for establishing a measure of a traffic density by a driver assistance system of a motor vehicle.

For establishing or determining a traffic density in road traffic various approaches are used. Commonly a plurality of traffic participants for establishing a traffic density transmit information about their respective position and possibly also the speed of their movement to a global, i.e. cross-vehicle system. This may for instance be effected via an application on a mobile telephone with positioning functionality. Thereby the system has access to information of a plurality of vehicles which for instance are present in a predetermined road section. By means of this information a number of vehicles in the selected road section, a vehicle density, can be estimated. For instance then on the basis of an average speed a traffic density can be estimated by the system. Also thereby for instance vehicles, which move at a speed below average, for instance at a speed which is less than half of a speed limit applying in the road section, are detected and used for establishing the traffic density. Generally the vehicles on the basis of the captured information can be subdivided into various groups or clusters and these can be used in different ways for an estimation of the traffic density. Such methods are based on real time data, however, due to the required cross-vehicle evaluation are affected by a delay.

In this context for instance from the US 20140358413 an on-board device for a motor vehicle for traffic density estimation is disclosed. In this context individual vehicles are assigned each to a corresponding lane and for calculation of a traffic density within the individual lanes a respective distance of the vehicle from the own motor vehicle is established. In this connection, however, further vehicles covered by other vehicles may lead to a distortion of the calculation of the traffic density.

The invention is based on the task of establishing a traffic density on a road fast and reliably and in particular to describe it with an informative measure. This task is solved by the subject matters of the independent patent claims. Advantageous embodiments derive from the dependent patent claims, the description, and the figures.

The invention relates to a driver assistance system for a motor vehicle, comprising a sensor device for capturing (in the sense of scanning or detecting) an environment of the motor vehicle and comprising a calculation unit for establishing (in the sense of determining or evaluating or calculating) a measure for a traffic density. In this connection the sensor device is configured for capturing an available and thereby free road surface of a road on which the motor vehicle is driving. An available surface of a road in this connection can relate to a surface of a road or to a lane of a road that is intended for use by the motor vehicle in a standard operation of the motor vehicle according to the respective ruling traffic regulations. In particular for instance a road surface, which is not intended to be driven on, cannot be understood as available road surface, for instance an emergency lane. The available road surface thus can be determined by at least one lane, in particular number and width of the lane or lanes, of the road, on which the motor vehicle is driving. In particular, the available road surface can be given or predetermined by the lanes, which are envisaged to be driven on by vehicles in the driving direction of the motor vehicle. Thus, for instance, in the case of a road with one lane in each direction, the part of the road surface can be captured as available road surface by the sensor device, e.g. a camera, as available road surface, which is in the field of vision of the camera and is to be assigned to the lane on which the own motor vehicle is present or moving. In this connection, it is the part of the available road surface, which is not covered and/or occupied by a different object, for instance a different vehicle, that is captured by the camera. The available road surface of the road thus can correspond to a surface or area available for maneuvering the motor vehicle or the other vehicles on the road.

The captured available road surface in this connection is given by the overall road surface, which can be scanned or monitored by the sensor device, which corresponds to a theoretically reachable maximum capture area of the sensor device on the road, less a partial road surface, which at the time of capture cannot be scanned or monitored by the sensor device and thus is not capable of being captured. Thus, the overall road surface which can be monitored is the available road surface, which in the absence of other vehicles or other movable objects, such as for instance branches of trees or construction site signs on the road, can be captured or monitored by the sensor device. The partial road surface, which cannot be scanned and thus is not captured or monitored, is the part of the overall road surface, which during capture (i.e. at a respective capture time) is concealed or occupied by one or several captured objects (relative to the sensor device). The uncaptured partial road surface, thus at the time of capture is either occupied by the object or the objects or concealed by the object or the objects from the perspective of the sensor device. The area of the partial road surface not occupied by an object in this connection can be referred to as shadow area. The area of the partial road surface occupied by an object can be referred to as object area. In particular the object area then together with the shadow area forms the uncaptured partial road surface. The uncaptured partial road surface then in turn together with the captured available road surface forms in particular the overall road surface.

The captured available road surface consequently can be taken in particular as the area of the road around the motor vehicle, which can be captured (i.e. scanned) by the sensor device, and from which the area of the road is deducted, which the sensor device cannot detect or monitor, for instance because it is occupied by a different vehicle or covered by it.

The calculation unit in this connection is configured to calculate a surface size value A of the available road surface captured by the sensor device and to establish (in the sense of determine or evaluate or calculate) a measure p for a local traffic density in the

environment of the motor vehicle in dependency on the surface size value A calculated for the available road surface. The calculation unit thus is configured to quantify the captured available road surface on the basis of the surface size value A and to estimate a local traffic density by the measure p on the basis of the quantified available road surface.

This, to start with, has the advantage that in contrast to many cross-vehicle systems not a global but a local traffic density is estimated. The traffic density thus is already estimated by the motor vehicle without additional information of other motor vehicles or for instance a data processing unit, which is not part of the vehicle. Moreover, a quantitative evaluation of the local traffic density is realized in a way that is simple in terms of measurement technology with a small number of variables. Thus, without considerable delay a measure for the local traffic density can be established or determined and, for instance, be provided to a further device of the driver assistance system. The traffic density quantified by the measure p can then be taken into consideration by the driver assistance system for further functionalities. In this connection through the quantification of the captured available road surface also one or more further vehicles already that are concealed by another vehicle, i.e. one or more further vehicles in the shadow area of the respective other vehicle, are implicitly considered or taken account for in the measure p, since the area of the road surface occupied by the further vehicle is not captured as available road surface. As a consequence the result is not corrupted or distorted by the presence or absence of the covered other vehicle and the traffic density is better quantified by the measure p than is the case with hitherto known methods. The measure p thus is a particularly informative measure for the traffic density, which represents the traffic-relevant properties of a traffic flow particularly well.

In this connection in a particularly advantageous embodiment it is envisaged that the captured available road surface is located in a longitudinal axis or longitudinal direction of the vehicle in front of and behind and lateral to the motor vehicle, i.e. around the motor vehicle. The captured available road surface consequently can be located around the motor vehicle. In an intended arrangement of the sensor device on the motor vehicle, the sensor device is thus configured for capturing the available road surface in front of and behind and lateral to the motor vehicle. As part of this document, the indication„in a longitudinal axis of the vehicle in front of" corresponds to„on a vehicle front",„in a longitudinal axis of the vehicle behind" to„on a rear part of the vehicle" and„in a longitudinal axis of the vehicle lateral to" to„on a vehicle side".

This has the advantage that the local traffic density, which is not only determined by the vehicles in front of the motor vehicle, but by the traffic as a whole around the motor vehicle, can be estimated particularly precisely.

In a further advantageous embodiment it is envisaged that the sensor device has a camera and/or a lidar and/or a laser scanner and/or a radar.

This has the advantage that a particularly large area of available road surface can be captured, since the ranges of the named sensor devices for instance in comparison to an ultrasonic sensor device are particularly large. Thereby the captured available road surface is also quantified more precisely and accordingly the local traffic density better described by the measure p. The latter is the case in particular if the captured available road surface in the establishing of the measure p is put in relation to the overall road surface that can be captured or scanned by the sensor device, as it is described further below.

In a further advantageous embodiment it is envisaged that the calculation unit is configured for calculating the surface size value A in dependency on a respective available width of the road driven on in a transverse direction or transverse axis of the motor vehicle. In this connection the available width can be determined by the number and width of lanes of the road driven on available for driving in the driving direction of the motor vehicle. For instance the available width thus can be determined by a lane recognition device and/or a navigation system and/or a camera, for instance also in connection with data deposited for a lane width. In this connection also country-specific settings with regard to the lane width according to the regulations envisaged for the lane can be taken into account.

This has the advantage that only the actually available width of the road, and thus only the road surface, which can actually be driven on, is considered. Adjacent surfaces of the road that do not belong to the available road surface are thus not or only erroneously also captured as available road surfaces. Consequently, these surfaces are not added to an actually available road surface, which is to be captured for the establishing or determining of the traffic density. Thereby the surface size value A can be calculated particularly precisely, which raises the quality of the estimation for the local traffic density. Thus a range of the sensor device, which, for instance, in the case of intended arrangement of the sensor device on the motor vehicle exceeds the respective available width of the road for the calculation of the surface size value A can be compensated for with great precision.

In a further advantageous embodiment it is envisaged that the calculation unit is configured for establishing or determining the measure p for the local traffic density also in dependency on a predetermined or predeterminable minimum value A_min for the surface size value A of the available road surface and/or in dependency on a predetermined or predeterminable maximum value A_max for the surface size value A of the available road surface. In particular the calculation unit can be configured in such a way that the measure p for the local traffic density is determined using the relation p a [cos ( π *

+ 1]. The predetermined maximum value A_max for the surface size value A of

the available road surface can then in particular represent the physical expansion of the overall road surface that can be monitored by the sensor device, as it is for instance described further below. The predetermined minimum value A_min for the surface size value A of the available road surface can then in particular represent the physical expansion of a road surface captured in a predetermined reference traffic situation, as it is for instance described further below.

This has the advantage that the captured available road surface is put in relation to a respective minimum or maximum value so that the measure p gains in informative value. In particular thus also the measure p can be standardized, for instance to values between 0 and 1 , so that a local traffic density is described by the measure p in a particularly intuitively plausible way. Moreover, thus the measures p established for a respective local traffic density by various driver assistance systems for various motor vehicles with different sensor devices are rendered comparable. So, for instance for a central storing and evaluating of the measures p of different motor vehicles, as it will be described further below, can be realized particularly easily.

In this connection in a further advantageous embodiment it can be envisaged that the maximum value A_max is predetermined in dependency on a maximum sensor range of the sensor device in a longitudinal axis or longitudinal direction of the vehicle in front of the motor vehicle and/or in dependency on a maximum sensor range of the sensor device in the longitudinal direction of the vehicle behind the motor vehicle. In particular the corresponding maximum sensor range in front of and/or behind the motor vehicle of the sensor device can be deposited or stored in the calculation unit for a sensor device that is arranged on the motor vehicle as intended. For instance the maximum value A_max can be predetermined in dependency on a value of 200 metres as maximum sensor range of the sensor device in the longitudinal direction of the motor vehicle in front of the motor vehicle and in dependency on a value of 50 metres as the maximum sensor range of the sensor device in the longitudinal vehicle direction behind the motor vehicle. In particular, the maximum value A_max can also be envisaged in dependency on the available width for a multi-lane road, preferably with three, four, or five, or six lanes, in particular preferably a road with three lanes. In this connection for instance for each lane a width of 3.5 metres can be assumed. In particular, the maximum value A_max can preferably also be

predetermined in dependency on a length of the motor vehicle in the longitudinal direction of the vehicle, which can for instance amount to 5 metres. Thus, in the case of a three- lane road for the maximum value A_max thus it ensues A_max = (200 metres + 50 metres + 5 metres) x (3.5 metres x 3) = 2,677.5 square metres for the present example. Preferably, the maximum value A_max can be predetermined in dependency on the available width of the road, on which the motor vehicle is driving during capturing.

This has the advantage that respective individual properties of the motor vehicle or the sensor device are adjusted. Moreover, thus a uniform measure p for the various sensor devices and thus different motor vehicles can be realized.

In a further advantageous embodiment in this connection it is envisaged that the minimum value A_min is predetermined in dependency on an assumed minimum distance for two further vehicles arranged in front of and behind the motor vehicle on a single-lane road, i.e. in dependency on a predetermined reference traffic situation. In particular the minimum value A_min can also be predetermined in dependency on an assumed length of the motor vehicle. For instance for the width of the single-lane road a value of 3.5 metres can be deposited or given, and for the length of the motor vehicle, in which the driver assistance system is to be integrated, 5 metres. The minimum distance between the motor vehicles in this connection can for instance be assumed to be 3 meters. For the assumption of vehicles present in the middle of the single-lane road as well as for instance a camera centrally arranged in the center of the own motor vehicle as sensor device thus for the exemplary value a minimum value of A_min = 41 square metres is rendered for motor vehicles of 2 metres width.

This has the advantage that, similar to the latter embodiment, the surface size value A can be put in relation to a realistic situation, a reference traffic situation, for instance a traffic jam, by the minimum value A_min. In the very connection with the latter embodiment a very large dynamic of a factor of e.g. over 60 is rendered between the smallest possible surface size value A and the largest surface size value A. The traffic density thus can be estimated very precisely for a plurality of situations.

In the case of the surface size value A being smaller than the minimum value A_min or greater than the maximum value A_max, the surface size value A can be set to the minimum value A_min or the maximum value A_max, respectively. This renders the mathematical handling easier. Since the cases named here are rare exceptions, the result is hereby not or not considerably corrupted or distorted.

In a further advantageous embodiment it is envisaged that the calculation unit is configured to establish the measure p for the local traffic density also in dependency on a speed v of the motor vehicle. Thus a speed of the motor vehicle itself, an "Eigen-Speed", can be taken into account for the evaluation of the local traffic density on the basis of the measure p.

This has the advantage that the traffic-relevant properties of the traffic are particularly well represented by the measure p. Thus for the very purpose of a jam detection or a routing or route guidance not only the number of vehicles in a road section is relevant, but also the speed possible or realized in the road section. Thus, a particularly informative measure for the local traffic density is provided. In this connection in a further advantageous embodiment it can be envisaged that the calculation device is configured to establish the measure for the local traffic density also in dependency on a predetermined maximum value v_max for the speed v of the motor vehicle. The maximum value v_max in this connection can be fixed or preset, for instance it can be set to a value of 130 km/h or more. In this connection it may be envisaged that the calculation unit is configured to establish the measure p in dependency on the maximum value v_max instead of in dependence on the speed v, if the speed v is larger than the predetermined maximum value v_max. This can for instance be realized, if in the calculation of the measure p by means of a formula the speed v in the formula is replaced by the maximum value v_max for the speed. In particular can the calculation unit be configured to establish the measure for the local traffic density using the relation p a [cos (π *—— ) +

This has the advantage that in this way a scope for a formula used for establishing the measure p, which for instance contains the relation just mentioned, can be adapted to a respective prevailing traffic condition. Also the measure p can be adjusted by the selection of the maximum value v_max to the common speeds. For instance the maximum value v_max can be predetermined in dependency on a road class of the respective road driven on and thus for instance set to 130 km/h for motorways and for country roads to 100 km/h. This has the advantage that the measure p for the traffic density can also be adapted to a traffic flow to be expected for the corresponding road or to a corresponding speed of traffic.

In a particularly advantageous combination of the described embodiments the calculation unit is configured to establish the measure p using the relation p a [cos π *

ll * [cos (π *—— ) + ll , in particular with p = - * [cos (π * ^Ama_^{x A} ) + l| * [

V ^vmax' J 2 L V A_max A_mi_nJ J L

+ 1 . This relation has turned out to be particularly advantageous for a measure of the local traffic density.

In a further advantageous embodiment it is envisaged that the driver assistance system has a transmission device, which is configured to transmit the established measure p for the local traffic density to a data processing unit, which is not part of the vehicle. In particular the corresponding data processing unit in this connection is configured to establish or derive a measure for a global traffic density from a multitude of transmitted measures p for a respective local traffic density. The global traffic density in this connection can be the global traffic density for the road section on which the motor vehicle is driving. This has the advantage that the measure for the global traffic density can be derived in a particularly simple, fast and reliable way from the local traffic densities, e.g. by the algebraic average.

Correspondingly, the present invention also relates to a system for establishing a measure for the global traffic density with a data processing unit not part of the vehicle and one or several driver assistance systems or one or several motor vehicles with a respective driver assistance system according to one of the described embodiments. The data processing unit in this connection can also be part of a different vehicle. In this connection the data processing unit advantageously is configured to transmit a corresponding measure for the global traffic density back to the driver assistance system or systems.

This has the advantage that the measure for the global traffic density is particularly precise, since in the transmitted measures p also vehicles are considered, which are not equipped with such a driver assistance system and thus are not part of the system for establishing the measure for the global traffic density.

The invention also relates to a motor vehicle comprising a driver assistance system according to one of the described embodiments.

The invention also relates to a method for establishing a measure of a traffic density by a driver assistance system of a motor vehicle, with a number of method steps. One method step in this connection is a capturing of an available road surface of a road, on which the motor vehicle is driving, by a sensor device of the driver assistance system. A further method step is a calculating of a surface size value A of the captured available road surface by a calculation unit of the driver assistance system. A subsequent method step is an establishing of a measure p for a local traffic density in dependency on the surface size value A calculated for the available road surface through the calculation unit.

Advantages and advantageous embodiments of the method here correspond to advantages and advantageous embodiments of the driver assistance system or the system for establishing a traffic density.

Further features of the invention are apparent from the claims, the figures and the description of figures. The features and feature combinations mentioned above in the description as well as the features and feature combinations mentioned below in the description of figures and/or shown in the figures alone are usable not only in the respectively specified combination, but also in other combinations without departing from the scope of the invention. Thus, implementations are also to be considered as encompassed and disclosed by the invention, which are not explicitly shown in the figures and explained, but arise from and can be generated by separated feature combinations from the explained implementations. Implementations and feature combinations are also to be considered as disclosed, which thus do not have all of the features of an originally formulated independent claim. Moreover, implementations and feature combinations are to be considered as disclosed, in particular by the implementations set out above, which extend beyond or deviate from the feature combinations set out in the relations of the claims.

Embodiments of the invention are explained in more detail in the following by reference to schematic drawings. These show in:

Fig. 1 a motor vehicle with an exemplary embodiment of a driver assistance system in an exemplary traffic situation from a bird's eye perspective;

Fig. 2 an exemplary reference traffic situation, on the basis of which an exemplary presetting of a minimum value A_min for the surface size value A is explained; and

Fig. 3 a further exemplary reference traffic situation, on the basis of which an

exemplary presetting of a maximum value A_max for the surface size A is explained.

In the various figures same elements or elements having the same functions in this connection are equipped with the same reference signs.

In Fig. 1 a motor vehicle 1 with an exemplary embodiment of a driver assistance system 2 in an exemplary traffic situation is represented from a bird's eye perspective. The driver assistance system 2 in the instant case comprises a sensor device 3 with a first camera 4a, which is arranged on a front of the motor vehicle 1 here as well as a second camera 4b, which is arranged on a rear part of the motor vehicle 1 here. In the shown example the two cameras 4a, 4b each are configured as 270 degree cameras so that by the sensor device 3 an environment of the motor vehicle 1 in the present case can be completely captured, i.e. across a range of 360 degree. The driver assistance system 2 also has a calculation unit 5, which is configured to calculate a measure p for a traffic density. In the present case, three objects 9a to 9c are shown, which represent further vehicles here and which accordingly conceal shadow areas 10a to 10c of the road 7 from the sensor device 3 or cover these shadow areas 10a to 10c relative to the sensor device 3.

The sensor device 3 is configured to capture an available, i.e. free road surface 6 of a road 7, on which the motor vehicle 1 is driving. The available road surface 6 in the present case is the surface of the road 7, on which it can be driven, in the area of a capture range 8 of the sensor device 3, which is not occupied by the objects 9a to 9c that are captured by the sensor device 3 and which is not hidden by the detected objects 9a to 9c from the perspective of the sensor device 3 and thus concealed from the sensor device 3. The capture range 8 in this connection in the present case is limited in its lateral expansion in the y-direction, the transverse direction of the motor vehicle in this case, so that an erroneous capturing of surfaces that can be driven on, for instance capturing a service and emergency lane as surface that can be driven on, next to the driving lanes of the road 7 as available road surface 6 is excluded here.

The captured available road surface 6, however, can thus be the capture range 8 of the sensor device 3 less the respective object area of the captured objects 9a to 9c as well as the respective shadow areas 10a to 10c. If there is no object present in the capture range 8, the captured available road surface 6 is equal to the capture range 8 and the available overall road surface. The captured available road surface 6 thus corresponds to that part of the lane of the road 7 present in the capture range 8, which is capable of being captured or scanned by the sensor device 3, and thus "can be seen by the sensor device 3".

The calculation unit 5 of the driver assistance system 2 in the shown example is configured to calculate a surface size value A of the captured available road surface 6, i.e. for instance a size of the captured available road surface 6 in square metres, and to establish a measure p for a local traffic density in dependency on the surface size value A calculated for the available road surface 6. This approach is based on the insight that the captured available road surface 6 grows smaller the more objects 9a to 9c are travelling in the capture range 8 on the road 7. Thus, the captured available road surface 6 is a parameter for a local traffic density, which in dependency on this parameter can be calculated simply and without having to refer to a central data infrastructure. The local traffic density thus is established by means of the measure p as function of an available road surface 6, i.e. the surface of the road 7, which is available for driving maneuvers. The captured available road surface 6 in this example is put in relation to the capture range 8 in order to standardize the measure p. The standardization thus is effected by means of the measure p for the local traffic density through the calculation unit 5 in dependency on a predetermined maximum value A_max for the surface size value A of the available road surface 6, which corresponds to a maximum available road surface 6. The maximum available road surface is the available road surface 6 in the absence of any objects 9a to 9c on the road 7. The maximum value A_max thus represents the surface of the shown capture range 8. Correspondingly, in this case the available road surface 6 is identical to the shown capture range 8. The capture range 8 in the present case on the one hand is given by the available width B of the road 7 as well as by the length Lx of the own motor vehicle 1 , as well as the maximum sensor range L1 of the sensor device 3 in the positive x-direction, i.e. in the longitudinal direction of the motor vehicle 1 , and the maximum sensor range L2 of the sensor device 3 in the negative x-direction, i.e. the maximum sensor range of the sensor device behind the motor vehicle 1 . The limited capture range 8 in this connection is consciously restricted in the lateral direction to the lanes of the road 7, which can be driven on in standard operation of the motor vehicle, since an additional enlargement, for instance by a side lane or further environment of the road 7, would change the respective ratio between the captured available road surface 6 and the capture range 8 and thus the ratio of the predetermined maximum value A_max and the surface size value A. Thus the measure p would be corrupted.

In the present case the calculation unit 5 is also configured to establish the measure p for the local traffic density not only in dependency on the maximum value A_max, but also in dependency on a minimum value A_min and in dependency on a speed v of the motor vehicle. The minimum value A_min in this connection is the minimum value that the surface size value A can have for an assumed exemplary reference traffic situation shown in Fig. 2. Accordingly, in the shown example the calculation unit 5 is configured to calculated the measure p by means of the equation p = - * [cos (π * ^A^^~A j + 1] * i_Cos (π *—— ) +

2 L V A_max A_mi_n _l L V ^vmax' lj. In this connection the maximum value v_max for the speed v corresponds to a fixed predetermined value, for instance 130 km/h as nominal speed or maximum speed for a motorway. However, it can be predetermined to be different for country roads and motorways, in particular in dependency on a road class of the road 7 driven on. If the speed v of the motor vehicle 1 is larger than the maximum value v_max, it is presently set to a maximum value v_max for the calculation of the measure p in the above equation.

Accordingly, in the present case also a surface size value A, which is larger than the maximum value A_max, is set to a maximum value A_max and a surface size value A, which is smaller than the minimum value A_min, to a minimum value A_min.

Thus, a local traffic density is quantified in dependency on the relation of the captured available road surface and the available overall road surface that can be scanned or monitored and in dependency on the respective speed v of the motor vehicle 1 , in a simple and reliable way.

In Fig. 2 now an exemplary reference traffic situation is represented, on the basis of which an exemplary calculation of the minimum value A_min is explained. For the predetermining of the minimum value A_min a fictitious reference traffic situation is assumed, in which the motor vehicle 1 is driving on an as small as possible road with an available width B, which in the present case is determined by a single lane and is given for instance by 3.5 meters. The motor vehicle 1 in this connection is in the middle of the road 7, wherein in the x- direction in front of and behind the motor vehicle 1 at a respective distance d, which is assumed to have a predetermined value, for instance 3 metres, an object 9a, 9b, here respectively configured as other vehicle, is arranged. The motor vehicle 1 and the respective objects 9a, 9b in this connection are assumed with a width b and a length I, which in the present case are predetermined with 2 metres for the width b and 5 metres for the length I. In such a scenario the surface of the captured available road surface 6 and thus the minimum value A_min for the motor vehicle 1 present in the middle of the road 7 or the single lane and objects 9a, 9b are determined to be 41 .875 square metres. In this connection a sensor device 3 (Fig. 1 ) with cameras 4a, 4b (Fig. 1 ) arranged on the front side and the rear side of the motor vehicle 1 is assumed here.

In Fig. 3 the available road surface 6 is shown for the case that there is not a single object in the capture range 8. In this case the available road surface 6 corresponds to the shown capture range 8 of the sensor device 3, which in the present case is limited laterally in the y-direction to the width of the road B of the road 7. Accordingly, the size of the captured available road surface 6 is given by the available width B, the length Lx of the motor vehicle 1 as well as the maximum front side sensor range L1 and the maximum rear sensor range L2 of the motor vehicle 1 . If the motor vehicle 1 is for instance 5 metres long and can capture objects 9a to 9c (Fig. 1 ) in a front side distance of up to 200 metres and objects 9a to 9c (Fig. 1 ) behind the motor vehicle 1 in a rear side distance of up to 50 metres, in the present case of a three-lane road shown with a lane width of 3.5 metres the size of the capture range and thus the maximum value A_max for the surface size value A is given to be 2.677,5 square metres. The large difference between the minimum value A_min and the maximum value A_max for the surface size value A is indicative of the large dynamic, which can be covered by the measure p. Thus, by the described interconnection a plurality of different situations can be summarized and represented in a simple and informative way by the measure p.

Claims

1 . Driver assistance system (2) for a motor vehicle (1 ), comprising a sensor device (3) for capturing the environment of the motor vehicle (1 ), and comprising a calculation unit (5) for establishing a measure for a traffic density,

characterized in that

- the sensor device (3) is configured for capturing an available road surface (6) of a road (7), on which the motor vehicle (1 ) is driving; and

- the calculation unit (5) is configured for calculating a surface size value A of the captured available road surface (6) and for establishing a measure p for a local traffic density in dependency on the calculated surface size value A calculated for the available road surface (6).

2. Driver assistance system (2) according to claim 1 ,

characterized in that

the captured available road surface (6) is located in front of and behind and lateral to the motor vehicle (1 ).

3. Driver assistance system (2) according to any one of the preceding claims,

characterized in that

the sensor device (3) has a camera (4a, 4b) and/or a lidar and/or a laser scanner and/or a radar.

4. Driver assistance system (2) according to any one of the preceding claims,

characterized in that

the calculation unit (5) is configured for calculating the surface size value A in dependency on a respective available width (B) of the road (7) in a transverse direction of the motor vehicle (1 ).

5. Driver assistance system (2) according to any one of the preceding claims,

characterized in that the calculation unit (5) is configured for establishing the measure p for the local traffic density also in dependency on a predetermined minimum value A_min for the surface size value A of the available road surface (6) and/or a preset maximum value A_max for the surface size value A of the available road surface (6), in particular using the relation p a [cos (π * j ₊ i]

^ Amax A_mi_n

6. Driver assistance system (2) according to claim 5,

characterized in that

the maximum value A_max is preset in dependency on a maximum sensor range (L1 ) of the sensor device (3) in a longitudinal direction of the motor vehicle (1 ) in front of the motor vehicle (1 ) and/or a maximum sensor range (L2) of the sensor device (3) in the longitudinal direction of the motor vehicle behind the motor vehicle (1 ).

7. Driver assistance system (2) according to claim 5 or 6,

characterized in that

the minimum value A_min is preset in dependency on an assumed minimum distance (d) for two further vehicles (9a, 9b) each arranged in front of and behind the motor vehicle (1 ) on a single-lane road (7).

8. Driver assistance system (2) according to any one of the preceding claims,

characterized in that

the calculation unit (5) is configured for establishing the measure p for the local traffic density also in dependency on a speed v of the motor vehicle (1 ).

9. Driver assistance system (2) according to claim 8,

characterized in that

the calculation unit (5) is configured for establishing the measure p for the local traffic density also in dependency on a preset maximum value v_max for the speed v of the motor vehicle (1 ), in particular using the relation p a [cos (π *—— ) + 1] .

10. Driver assistance system (2) according to any one of the preceding claims,

characterized in that

the driver assistance system (2) has a transmission device, which is configured for transmitting the established measure p for the local traffic density to a data processing device which does not form part of the vehicle.

1 1 . Motor vehicle (1 ) comprising a driver assistance system (2) according to any one of the preceding claims.

12. Method for establishing a measure of a traffic density by a driver assistance system (2) of a motor vehicle, comprising the method steps:

- capturing an available road surface (6) of a road (7), on which a motor vehicle (1 ) is driving, by a sensor device (3) of the driver assistance system (2);

- calculating a surface size value A of the captured available road surface (6) by a calculation unit (5) of the driver assistance system (2);

- establishing a measure p for a local traffic density in dependency on the calculated surface size value A calculated for the available road surface (6) by the calculation unit (5).