Method and auxiliary system for the relatency evaluation of an

Abstract

The invention relates to a method and an auxiliary system (10) for the correlation evaluation of environmental objects (5, 6). The invention also relates to a correspondingly arranged motor vehicle (4). In the method, individual relative movements of the objects (5, 6) relative to the motor vehicle (4) are determined on the basis of the environmental data. Based on this, a respective distance (15, 16, 18, 19) required to achieve a steady state behind the respective object (5, 6) is determined as a function of a driving parameter of each detected object (5, 6) specified for the motor vehicle (4). For the detected objects (5, 6), a respective correlation check is carried out on the basis thereof, the respective object (5, 6) being classified to be correlated or not correlated for guiding the motor vehicle (4).

Description

Technical Field

[0001] The invention relates to a method and an assistance system for evaluating the relevance of objects in a corresponding environment of a correspondingly arranged motor vehicle. The invention also relates to such a motor vehicle. Background Art

[0002] In today's motor vehicles, there are numerous assistance functions and systems for supporting the driver in the guidance of the vehicle or for at least partially automated guidance of the motor vehicle. These functions and systems typically rely on environmental recognition, i.e., on the most accurate possible identification of objects in the respective environment. This applies, for example, to longitudinal control functions such as adaptive cruise control (ACC). However, in this case, not only must the objects be identified, but ideally it must also be determined whether the identified objects are at all relevant for the guidance of the motor vehicle or the adjustment of the corresponding assistance functions or vehicle components.

[0003] In addition, nowadays, the quality and working mode of corresponding auxiliary functions and systems and the requirements for driving comfort or passenger comfort are getting higher and higher. Accordingly, for example, objects should be identified as early as possible and classified as relevant if necessary, so as to avoid sudden manipulation, wherein, but at the same time, quality or reliability improvement should be carried out with respect to avoiding wrong identification or wrong classification and corresponding wrong or unnecessary reaction. A scheme to realize this can be to expand the correlation area in principle, in which objects are classified as relevant. However, this may bring disadvantages, such as performance, i.e., accuracy and reliability are limited, especially in urban areas, on curved local roads and usually in relatively complex traffic situations, and the scalability for new functions, especially automation level 2 and higher levels is limited. Therefore, the false positive rate increases in larger spacings and the false negative rate increases in nearby areas often hinder the corresponding expansion of application areas or use areas, i.e., so-called ODD (operation design domain). Therefore, improvement is still needed.

[0004] As a solution, DE 10 2009 006 747 A1 describes an environment evaluation system for evaluating an object in a vehicle environment in terms of its relevance as a target object for an alarm control or regulation system for a vehicle. In a first step, each detected object is evaluated for its transverse relevance and separately from it for its longitudinal relevance for the own vehicle. In a second step, for each detected object, a total relevance is calculated based on its transverse relevance and its longitudinal relevance. In a third step, the detected object with the greatest total relevance is selected as the only target object for the own vehicle. In this way, it can also be ensured that the target object is selected predictably and clearly from a plurality of detected objects.

[0005] In order to implement an auxiliary function or system, the driving passage of the corresponding motor vehicle is often observed, which is also called a driving corridor. For this purpose, DE 10 2013 015 028 A1 discloses a method for operating a vehicle, wherein a driving passage is predicted and a vehicle environment is detected, in which the vehicle moves forward with a high probability. Here, the driving passage is predicted so that the driving passage gradually becomes smaller along the driving direction as the spatial and / or temporal distance from the instantaneous vehicle position increases. Then, based on the position that the object instantaneously occupies or is expected to occupy in the near future relative to the driving passage, the relevance of the detected object in the vehicle environment in front is determined. Then, based on the determined relevance of the object to the vehicle, it is decided whether it should be allowed to automatically take measures to avoid collisions or measures to mitigate the consequences of collisions.

[0006] DE 10 2013 200 409 A1 also relates to monitoring the environment of a vehicle. The method therein includes reading a distance image of the environment, wherein the distance image includes a plurality of distance values. These distance values ​​represent the results of a plurality of distance measurements of the vehicle environment detected by the sensor, which are performed using a sensor for stereoscopic image detection. In addition, the method includes identifying obstacles located in the environment using the distance values ​​contained in the selected cutout of the distance image. In addition, the number and quality of relevant distance values ​​are determined, which represent the distance values ​​contained in the cutout, and which can be assigned to the obstacle. Finally, the value of the presence measure of the presence of the obstacle is determined based on the number and quality of the relevant distance values. Summary of the invention

[0007] The object of the present invention is to achieve an improved recognition of objects relevant to the guidance of the vehicle.

[0008] This object is achieved according to the invention by the subject matter of the independent claims. Possible embodiments and developments of the invention are disclosed in the dependent claims, the description and the drawings.

[0009] The method according to the invention can be used for the relevance evaluation of objects in the environment of a motor vehicle. In the method steps of the method according to the invention, environmental data are detected, which describe or characterize objects located in the corresponding environment of the motor vehicle. The environmental data can be received or recorded in particular by means of an environmental sensor device of the corresponding motor vehicle. Similarly, the environmental data can come from other traffic participants and / or infrastructure of traffic monitoring, etc., and then be detected or have been detected, for example, via Car2X, WLAN or mobile wireless data connection, etc. In the sense of the invention, the detection of these environmental data means or includes receiving or calling these environmental data via a corresponding interface or from a data storage device, or also means or includes recording these environmental data by means of a corresponding environmental sensor device.

[0010] In the sense of the present invention, an object may in particular be or include other road users, for example other vehicles which may also be referred to as stranger vehicles.

[0011] The environment in which these objects are located or in which these objects are detected or recognized or have been recognized can be, in particular, an area located ahead of the motor vehicle in its direction of travel.

[0012] In a further method step of the method according to the invention, the respective relative movements of the object relative to the motor vehicle, determined with respect to the motor vehicle, in particular the relative speed or also the relative acceleration, are determined. For this purpose, corresponding data or instructions can be extracted or calculated from the environmental data, for example, depending on the type of environmental data. The relative movement of the object can thus be determined here in an object-specific manner. Here, it is also possible to determine the respective current positions of the object, for example relative to the motor vehicle or in a preset, in particular fixed to the world coordinate system. Likewise, for example, the position and the own movement of the motor vehicle, i.e., in particular the speed and the direction of movement or also the acceleration, can be determined or called up, for example, with respect to a preset coordinate system, for example, via the onboard power supply or by corresponding controllers or sensors of the motor vehicle.

[0013] In another method step of the method according to the invention, based on this consideration, i.e. according to the driving parameters preset for the motor vehicle, a corresponding, i.e. object-specific distance is determined for each detected object, i.e. calculated, which distance will be required to achieve a stable state of the motor vehicle behind the corresponding object. Therefore, when the corresponding object is assumed to be the front object, or the motor vehicle is traveling behind the object or is positioned behind the object, this distance may be required. The distance determined here can be in particular a spatial distance, i.e. a road section. Similarly, the distance can be a time distance, i.e. a time or a duration. These two possibilities can be considered to be effectively equivalent here, because the road section and the corresponding time are fixedly related to each other by the speed of the motor vehicle and the driving parameters or the preset safety standards, and can thus be converted to each other. That is, for example, the time required to reach a stable state can be first determined, and then the time is converted into a corresponding spatial distance, which can then be used for one or more other data processing steps when necessary. The distance determined here can be, for example, a minimum distance, i.e., at least the minimum required road section is estimated in order to achieve a stable state under the consideration of the preset driving parameters or the preset safety standards. Likewise, the determined distance may be, for example, a minimum time, i.e., a time or duration that is at least expected to be required at least in order to reach a stable state, taking into account predefined driving parameters or predefined safety standards. In this case, for example, it is possible to proceed from a constant own motion of the respective object, or to simulate an expected or possible motion of the respective object, for example, using a corresponding predefined motion model, etc.

[0014] Likewise, other distances, spacings and / or ranges mentioned here may be understood as spatial variables or corresponding temporal variables.

[0015] The preset parameters may be, for example, intervals, average values, expected values ​​and / or limit values ​​of one or more parameters that influence or limit the movement of the motor vehicle. The preset parameters may indicate or take into account which movement or movement change of the motor vehicle is technically possible, safe, comfortable or expected. The preset parameters may, for example, specify the maximum jerk, maximum acceleration, maximum deceleration, maximum yaw rate, rated speed or target speed, safe distance or expected distance from the corresponding object and / or the like. The rated speed or target speed may be, for example, the locally permitted maximum speed or minimum speed in the corresponding situation, the expected speed set by the driver of the motor vehicle for the speed control device of the motor vehicle, the speed determined or measured by the system for longitudinally guiding the motor vehicle, etc.

[0016] A stable state can be achieved, for example, when the distance between the motor vehicle and the respective object does not decrease further (i.e. remains constant) or increases, the motor vehicle has the same speed as the respective object or a lower speed than the respective object, in particular at a given safety distance or minimum distance or a predefined desired distance to the respective object, and absolutely no active control or regulation intervention in the longitudinal guidance of the motor vehicle is necessary to avoid a collision between the motor vehicle and the respective object, etc. In other words, a stable state in the present sense can be provided when the motor vehicle can reliably maintain its subsequently described state of motion.

[0017] The at least one object-specific distance can be calculated as a spatial distance s, for example, as a sum of a predetermined distance offset as a first summand, a product of a predetermined time constant and the corresponding setpoint speed or target speed as a second summand, and a distance required for a braking maneuver to be performed to reach a stable state as a third summand. This can be expressed, for example, by the following relationship:

[0018] s=a+b·MIN(v ego , v target )+c·v rei 2 ,

[0019] Among them, a, b, c are preset parameters, v ego is the speed of the vehicle, v target is the velocity of the corresponding object, MIN is its minimum value, and v rei is the relative speed between the vehicle and the corresponding object, where MIN(v ego , v target) can represent the rated speed or the target speed. Here, the middle term mainly corresponds to the above-mentioned time, which is required to reach the stable state behind the corresponding object. The first term can be understood as a distance offset. The last term corresponds to the distance required for braking to reach a stable state. Therefore, different distances can be calculated according to the preset parameterization, that is, the preset values ​​of parameters a, b, and c. This distance can, for example, include or take into account the movement of the motor vehicle in the corresponding time or can also include or take into account the preset minimum distance or safety distance or the expected distance from the corresponding object set by the motor vehicle driver. For example, this distance can take into account or include the road section expected to be passed by the motor vehicle in the corresponding time. However, the speed at which the corresponding object may move and the additional space subsequently generated for the operation of the motor vehicle can also be considered. The at least one distance can be calculated under one or more preset assumptions or boundary conditions, which are determined by the method according to the present invention or the auxiliary system based thereon. Therefore, for example, it can be stipulated that the method according to the present invention is applied as described only when the corresponding object does not actively move toward the motor vehicle, the motor vehicle is not in a completely manual operating mode, or the like. It can also be considered, for example, that the motor vehicle does not actively accelerate to the corresponding object. Likewise, for example, the corresponding object-specific time can be first determined or—for example with correspondingly different parameterizations—a plurality of object-specific times can be determined. This can then be converted into the described spatial distance or the described spatial distances.

[0020] In a further method step of the method according to the invention, a relevance check is performed for each detected object based on the respective at least one object-specific distance, wherein the respective object is classified as relevant or irrelevant for the guidance of the motor vehicle. For example, an object can be classified as relevant if the current distance of the object from the motor vehicle is at most as great as the distance or the distance determined for the object. Otherwise, that is, if the object is further away from the motor vehicle than the distance or the distance determined for the object, the object can be classified as irrelevant. The distance can thus be used as a threshold value for the relevance of the respective object or as a basis for determining or specifying such a threshold value.

[0021] The invention also makes it possible to determine or track the objects that are actually relevant in a particularly simple, low-cost and reliable manner even in the case of a plurality of detected objects. In this case, by individual observation in comparison with previous approaches, objects that are particularly far from the vehicle can already be classified as relevant or irrelevant, without taking into account the problems described at the beginning of the extended relevance range. In addition, the relevance description of each object can be better adapted to an extended ODD or new functions or applications in comparison with conventional approaches due to the adjustability over time. The invention makes it possible to meet not only the increased quality requirements but also the comfort requirements, as explained in more detail elsewhere.

[0022] In a possible design of the present invention, the preset maximum possible or maximum permissible jerk of the motor vehicle is also taken into account when determining the corresponding distance. In the sense of the present invention, jerk is a derivative or change of acceleration. It is thus also possible to consider how quickly the current acceleration of the motor vehicle can be reduced. The maximum permissible jerk can be, for example, a preset maximum value or the maximum possible jerk technically or in compliance with preset safety standards, taking into account or according to current operating conditions and / or environmental conditions. The maximum possible or permissible jerk can also be set by the driver of the motor vehicle. By taking into account the jerk proposed here, the corresponding distance can be determined particularly accurately or in detail. This ultimately enables a particularly precise and reliable correlation classification.

[0023] In another possible design of the present invention, the relevance for all detected objects is determined. The driving channel or driving corridor in which the motor vehicle is expected to move is also predicted or estimated. Then, only those objects among the detected objects that are classified as relevant and located in the driving channel are output or marked as relevant, that is, if necessary, objects to be considered for at least one preset driving assistance function of the motor vehicle. Here, objects outside the driving channel can be classified as irrelevant to the driving assistance function, that is, not to be considered. This can be effective, for example, at least for objects outside the driving channel that are predicted not to move into the path of travel. Objects located in the driving channel can be classified as relevant to the driving assistance function, that is, classified as being considered (at least potentially) by the driving assistance function. Such a driving assistance function can be, for example, an adaptive cruise controller (ACC) or the like. The design proposed here by the present invention can, for example, reduce the computational cost for the driving assistance function for selecting the target object or regulating object of the driving assistance function. Thus, the method according to the present invention can also reliably and robustly and particularly low-latency support or implementation of the effective application of the corresponding assistance function with the help of an embedded system, that is, corresponding limited hardware resources.

[0024] In another possible embodiment of the present invention, the determination of the at least one distance includes determining a first distance and a larger second distance for the detected object. The first distance is obtained here as the minimum distance for reliably guiding the motor vehicle, that is, as the minimum distance required for reaching a stable state without collision. The first distance can be determined, for example, using the above formula using a preset first parameterization. In contrast, the second distance is obtained in a more comfortable vehicle guidance, which can also be referred to as a maximum distance or comfort distance. In other words, in order to determine the second distance, for example, it can be assumed or based on a smaller jerk, a smaller acceleration or deceleration, a smaller force, a smaller yaw rate and / or the like. The second distance can be determined, for example, using the above formula using a preset second parameterization. In the embodiment of the present invention proposed here, the first distance, the second distance or the distance between them is used for the correlation check. In other words, the first distance and the second distance thus define the boundaries of a closed interval, that is, the interval includes these boundaries, wherein the distance that is ultimately used for correlation classification or correlation check, that is, for example, as a corresponding threshold value, is part of the interval. Which distance is actually used as the threshold value for relevance can be preset or dynamically determined, for example, depending on the situation, the use case or the individual requirements or target settings for the corresponding application of the present invention. By means of the design of the present invention proposed here, on the one hand, it can be ensured that objects at a distance from the motor vehicle less than the first distance (for which there is a risk of collision) are always classified as relevant. On the other hand, the second distance can limit the number and spacing of objects that may be classified as relevant. The corresponding data processing consumption can also be limited thereby. This is based on the recognition that objects that are farther from the motor vehicle than the second distance can typically remain out of consideration for the guidance of the vehicle without causing a loss of comfort or safety.

[0025] In a possible improvement of the present invention, a driving corridor or driving gallery in which a motor vehicle is expected to move is predicted or estimated. The quality of this estimate is then further determined, that is, for example, accuracy, safety or confidence. Based on this, a third distance is also determined, which is smaller when the estimated quality of the driving corridor is low and larger when the estimated quality of the driving corridor is high. When this third distance based on quality is smaller than the first distance, the object is classified as relevant only when the distance between the object and the motor vehicle corresponds to the first distance at most. In other words, even if the quality of the estimated driving corridor is very low or poor, which may cause the third distance to be lower than the first distance, the first distance is also observed as the minimum distance for the correlation check. Therefore, objects that are close to each other can be reliably classified as relevant, which can help improve safety. When this third distance based on quality is greater than the second distance, the object is classified as relevant only when the distance between the object and the motor vehicle corresponds to the second distance at most. In other words, here, if the estimation of the driving corridor is particularly accurate and reliable or safe and therefore, if necessary, it is also possible to know which objects are located in the driving corridor of the motor vehicle with a correspondingly large confidence at a distance exceeding the second distance, then the correlation area is also limited to the second distance. As a result, the corresponding data processing effort for tracking a correspondingly large number of objects can be limited or reduced, for example, wherein neither a significant loss of comfort nor a significant loss of safety need be tolerated due to the correspondingly larger distance from the motor vehicle and objects that are further away than the second distance and are therefore not classified as relevant.

[0026] When this third distance based on quality is between the first distance and the second distance, the object is classified as relevant only when the distance between the object and the motor vehicle corresponds at most to the third distance. In other words, the third distance based on quality thus defines the correlation area. This means that if the third distance is located in an interval formed or defined or limited by the first distance and the second distance, the third distance in the correlation check is used as a threshold. If the third distance based on quality is outside this interval, its nearest interval boundary, i.e. the first distance or the second distance, is used as a threshold in the correlation check. Through the design of the present invention proposed here, not only can the particularly high quality and performance requirements for auxiliary functions and systems for auxiliary or at least partially automated guidance of motor vehicles be met, but also the particularly high comfort requirements can be met.

[0027] The estimation of the driving corridor can correspond to an estimation of the course of the lane ahead in the direction of travel of the motor vehicle or take into account this course of the lane. In this case, the third distance can be introduced as an additional distance, which is based on the quality of the estimation of the driving corridor and thus on the quality of the available inputs that characterize or estimate the course of the lane. Such inputs can be or include, for example, measurement data or sensor data of an especially multimodal surroundings sensor system of the motor vehicle, trajectory or movement data or control data of an unfamiliar vehicle, map data and / or the like.

[0028] The quality of the estimation of the driving corridor can take into account the uncertainty of these inputs, so that a greater uncertainty leads to a lower quality. In the sense of the present invention, the quality can be understood as the quality of the prediction of the driving corridor, that is, the area in which the motor vehicle is traveling. If the driving corridor is estimated only based on the current steering angle of the motor vehicle, the quality can be particularly low and lead to a correspondingly small third distance. However, in this case, by using the first distance as a threshold for the correlation check, it can still be ensured that the detected objects that are relatively close but may be farther away from the motor vehicle than the third distance are classified as relevant, so that these objects can be taken into account in the corresponding control or regulation, for example. In order to determine the quality of the driving corridor estimation, for example, the recognizability of the lane boundary, the resolution or detail level of the map, the positioning accuracy of the trajectory of other traffic participants and / or the like can be used or taken into account more. It can also be considered, for example, that the uncertainty of the corresponding measurement increases or typically increases with the increase of the distance from the motor vehicle, the error may play a more significant role in a larger distance, that is, a larger error effect may be generated in a larger distance, and / or the like. Similarly, for example, inconsistent indications of different inputs or low statistically related covariances may lead to poor quality or mean poor quality. The third distance can be determined object-specifically or locally or globally, that is, equally applicable to all objects. The latter can be realized with particularly low data processing expenditure, while the first several possibilities can realize particularly robust correlation checks, for example when different sections of the driving corridor are estimated with different quality or accuracy.

[0029] In a possible improvement of the present invention, the quality of the estimation of the driving corridor is determined based on the distance. A distance below a preset quality threshold is then used as the third distance. In other words, the quality of the estimation of the driving corridor can decrease with increasing distance from the motor vehicle, i.e. with a correspondingly larger prediction range. The quality threshold can be preset in particular for the quality of the estimation of the driving corridor and / or the standard deviation of the input used for this, i.e. the data or measurement. Similarly, the quality threshold can be preset, for example, for the convolution of the estimation of the driving corridor with the uncertainty of the object detection. Through the design of the present invention proposed here, a particularly robust and reliable determination of the relevant object can be achieved or can be achieved, especially when the third distance is between the first distance and the second distance.

[0030] In another possible embodiment of the present invention, when a stable state of the motor vehicle has been achieved, that is, given, with respect to the detected object, a correlation region extending from the motor vehicle in the direction of the object is limited to a preset standard distance or a current distance from the corresponding object, in which the object is classified as relevant. Such a standard distance can be fixedly or dynamically preset, for example, according to the current speed of the motor vehicle, the characteristics of the local lane surface, etc. It can be ensured by the preset standard distance that objects representing a risk of collision or, for example, objects that may require emergency braking intervention, etc. are always classified as relevant. Similarly, the preset standard distance can be a desired distance preset by the driver of the motor vehicle. When the object is at least a preset minimum distance from the motor vehicle and moves in the same driving direction as the motor vehicle at the same speed as the motor vehicle or moves away from the motor vehicle, a stable state may already exist for example with respect to the object when the object is detected. In this state and in this position, for example, when the object enters the lane in which the motor vehicle is traveling in this state and in this position, or in a similar situation, the object can be detected for the first time. By means of the embodiment of the present invention proposed here, the correlation region can be determined particularly simply and inexpensively in this case, which can achieve a correspondingly simple and inexpensive correlation check.

[0031] In another possible design of the present invention, the object classified as relevant is only classified as no longer relevant from the selection or rejection distance, which is greater than the distance at which the object is classified as relevant. The rejection distance can be determined individually for each object. Therefore, the rejection distance can depend on the relative movement and / or relative position of each object relative to the motor vehicle, for example. Similarly, the rejection distance can be greater than the distance at which the corresponding object is classified as relevant by a preset value or percentage. Similarly, in order to determine the corresponding rejection distance, another parameterization of the above formula for the distance can be preset. Thus, that is, the rejection distance can always be greater than the maximum correlation distance at which the corresponding object is classified as relevant, that is, greater than the corresponding correlation area, so when the object is located in the area of ​​the maximum correlation distance, that is, at the end of the correlation area away from the motor vehicle, the inconsistent, frequently and rapidly changing classification of the object can be avoided. The characteristic proposed here can be understood as a hysteresis, wherein the object at the maximum distance from the motor vehicle (the maximum distance will still lead to the classification as relevant) needs to be farther away from the motor vehicle before being classified as no longer relevant, that is, at least until the rejection distance. If the motor vehicle then approaches again until it falls below the rejection distance, it is not immediately classified as relevant again, but only when it reaches or falls below the maximum relevance distance, i.e., enters the relevance area. This allows for robust and consistent control or regulation of functions or systems based on objects classified as relevant.

[0032] Another aspect of the present invention is an assistance system for a motor vehicle. The assistance system according to the present invention has an interface for detecting environmental data implemented in hardware and / or software, the environmental data describing the position and relative movement of an object, and the assistance system has a processing device, such as a microchip, a microprocessor or a microcontroller, etc. and a computer-readable data memory coupled to the processing device. The assistance system according to the present invention is configured to implement the method according to the present invention, in particular automatically. For this purpose, a corresponding operation or computer program can be stored in the data memory, which encodes or implements the method steps, measures or processes described in conjunction with the method according to the present invention or corresponding control instructions. The operation or computer program can then be implemented or can be implemented with the help of a processing device in order to implement the corresponding method or realize its implementation. The assistance system according to the present invention can be designed, for example, as a controller for a motor vehicle, etc.

[0033] Another aspect of the invention is a motor vehicle having an environment sensor system for detecting objects in the corresponding environment of the motor vehicle, i.e. for recording corresponding environment data, and an assistance system according to the invention. The motor vehicle can also have at least one further assistance component which performs or fulfills its function based on the objects classified as relevant by the assistance system according to the invention. The motor vehicle according to the invention can in particular be a motor vehicle as described in conjunction with the assistance system according to the invention or in conjunction with the method according to the invention or corresponding thereto.

[0034] Further features of the invention can be derived from the claims, the drawings and the description of the drawings. The features and feature combinations mentioned above in the description of the drawings and the features and feature combinations shown separately in the following description of the drawings and / or in the drawings can be used not only in the respectively given combination but also in other combinations or alone without departing from the scope of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In the single figure, the drawing shows a schematic overview for explaining a method for determining surrounding objects relevant for vehicle control. DETAILED DESCRIPTION

[0036] Various assistance functions and systems of the vehicle can use or take into account as a database or input which objects present in the respective vehicle environment are actually relevant for vehicle guidance, for example due to their position and relative movement. Figure 1 The schematic overview of a traffic scene on a road 1 is shown. The road 1 comprises a lane 2 and an adjacent lane 3, which can both be provided for the same direction of travel. A motor vehicle 4 is moving on the lane 2, at a distance behind a vehicle in front 5. In the same direction of travel as the motor vehicle 4 and the vehicle in front 5, a further vehicle is moving on the adjacent lane 3, which is referred to here as a secondary vehicle 6.

[0037] The motor vehicle 4 has an environment sensor device 7 for detecting corresponding objects in the environment, in particular in front of the vehicle in the driving direction. By means of the environment sensor device 7, in particular, the vehicle in front 5 and the secondary vehicle 6 can be detected as such objects. Based on the corresponding environmental data recorded by the environment sensor device 7, the control device 8 of the motor vehicle 4 can act, for example, for longitudinal adjustment of the motor vehicle 4. For this purpose, the control device 8 can, for example, send corresponding control or adjustment signals to the vehicle devices 9 of the motor vehicle 4, such as drive devices, etc. In order for the control device 8 to be able to react effectively, safely and comfortably for the passengers of the motor vehicle 4, they should only take into account objects that are actually relevant for the guidance of the motor vehicle 4. In order to realize the corresponding classification of the detected objects, in this case, for example, the vehicle in front 5 and the secondary vehicle 6, as relevant or irrelevant, the motor vehicle 4 has a corresponding assistance system 10. It is schematically shown here that the assistance system 10 includes an interface 11, through which the environmental data can be detected from the environment sensor device 7, as well as a processor 12 and a data memory 13 for processing environmental data.

[0038] During the operation of the motor vehicle 4 , its expected driving path 14 is continuously estimated. Here, a determination of the quality of the respective estimate of the driving path 14 is also performed. This can also be performed, for example, by the assistance system 10 or another component of the motor vehicle 4 .

[0039] The relevance of the detected objects should not be based solely on the current movement state of the motor vehicle 4 itself. Instead, the relevance should be determined for each object individually and as a function of its relative movement state with respect to the motor vehicle 4. This makes it possible to determine the time distance and / or spatial distance required by the motor vehicle 4 or the control device 8 in order to achieve a stable, i.e., steady state of the motor vehicle 4 or to achieve this state in the control behind the respective object. In this case, for example, the required spatial distance can be determined directly, or the respective required time can be determined first and based on this, a distance determination can then be performed for the corresponding spatial distance.

[0040] For this purpose, a corresponding distance calculation rule and a plurality of parameterizations for the distance calculation rule can be predefined. In particular, at least two different parameterizations or at least two different parameterized versions of a predefined distance calculation rule can be used in order to first calculate two different distances for each detected object.

[0041] A simple variant of this distance calculation rule can be expressed, for example, as s=a+b·MIN(v ego , v target )+c·v rei 2 Here, the evaluation result MIN(v ego , v target) can be the smaller of the speed of the motor vehicle 4 on the one hand and the speed of the respective object under observation on the other hand or the nominal speed or the target speed of the motor vehicle 4 in the stable, ie steady state, behind the respective object. The quadratic speed term c·v rei 2 Indicates the hypothetical distance of the necessary braking of the motor vehicle 4 required to achieve a stable and steady state. Here, this term can be zero when the speed of the motor vehicle 4 is already less than the speed of the object under observation.

[0042] For example, a first minimum distance 15 is calculated for the vehicle 5 ahead by means of a first parameterization. This first minimum distance 15 defines a minimum relevance range, which extends from the motor vehicle 4 in its driving direction and is minimally required by the motor vehicle 4 in order to achieve a stable, i.e., steady state behind the corresponding object, here behind the vehicle 5 ahead. The second preset parameterization is used to calculate a first comfort distance 16 for the vehicle 5 ahead. This first comfort distance 16 defines a relevance range, which extends from the motor vehicle 4 in its driving direction, which allows a more comfortable control behavior and an earlier relevance classification of the control device 8. Thus, for example, the driver of the motor vehicle 4 can be given confidence in the capabilities and functions of the assistance systems of the motor vehicle 4, i.e., in particular in the capabilities and functions of the control device 8 or also the assistance system 10. Therefore, for the vehicle 5 ahead, the first minimum distance 15 is calculated here as the first minimum distance and the first comfort distance 16 is calculated as the second distance.

[0043] Furthermore, a mass distance 17 based on the estimated mass of the driving corridor 14 is determined as a third distance. It is then determined for the vehicle ahead 5 whether this mass distance 17 is less than the first minimum distance 15 or greater than the first comfort distance 16 or between them, i.e., in the interval defined by the first minimum distance 15 and the first comfort distance 16. In the example shown here, for the vehicle ahead 5, the mass distance 17 between the first minimum distance 15 determined for the vehicle ahead 5 and the first comfort distance 16 determined for the vehicle ahead 5 is located on the side of the vehicle ahead 5 facing away from the motor vehicle 4. In other words, the distance of the vehicle ahead 5 from the motor vehicle 4 is therefore less than the first comfort distance 16 and also less than the mass distance 17, but greater than the first minimum distance 15.

[0044] It is provided that the quality distance 17 determines the relevance region when it is between the corresponding minimum distance and the corresponding comfort distance. Since this is the case for the vehicle 5 ahead, the quality distance 17 is used as a limit distance or threshold for the relevance check or relevance classification of the vehicle 5 ahead. Since the distance of the vehicle 5 ahead from the motor vehicle 4 is less than the quality distance 17, i.e. the vehicle 5 ahead is located in the relevance region extending from the motor vehicle 4 to the quality distance 17, the vehicle 5 ahead is classified as guidance-relevant for the motor vehicle 4. This can be done independently of the driving corridor 14 or, for example, in order to take into account the relevance as much as possible for a specific downstream driving assistance function, at least when or only when the motor vehicle is located in the driving corridor 14 (as in this case). Therefore, the vehicle 5 ahead can then be taken into account, for example, by the control device 8.

[0045] If (unlike what is shown here for the vehicle ahead 5 ) the quality distance 17 is outside the interval defined by the first minimum distance 15 and the first comfort distance 16 , the interval boundary closest to the quality distance 17 is used instead to define the corresponding object-specific relevance area, i.e. as a threshold for the relevance check of the corresponding object, here the vehicle ahead 5 .

[0046] A corresponding distance calculation and relevance check are also performed for the secondary vehicle 6, similar to what has been described for the vehicle in front 5. Therefore, the second minimum distance 18 and the second comfort distance 19 are calculated for the secondary vehicle 6 using the parameterization described and taking into account the relative movement of the secondary vehicle 6 relative to the motor vehicle 4. Here, it is also determined whether the quality distance 17 is located inside or outside the boundary, that is, inside or outside the interval defined by the second minimum distance 18 and the second comfort distance 16. In the example shown here, the quality distance 17 is greater than the second comfort distance 19 for the secondary vehicle 6. In this case, the quality distance 17 is not used to define the relevance range for the secondary vehicle 6, but the relevance range is limited to the nearest interval boundary, in this case to the second comfort distance 19. Since the distance of the secondary vehicle 6 from the motor vehicle 4 is greater than the second comfort distance 19, the motor vehicle 4 is classified as irrelevant for the guidance of the motor vehicle 4. Therefore, the control device 8 can perform its function, for example, without taking into account the secondary vehicle 6. The situation shown here by way of example may occur, for example, when the motor vehicle 4 moves at a greater speed than the motor vehicle 4 and the vehicle in front 5.

[0047] The functionality of the assistance system 10 described here can be used to perform a distance-related relevance evaluation of an object as a basis or foundation for different driver assistance systems or assistance functions of the motor vehicle 4. For further explanation, two extreme cases are described. The first extreme case is a stationary object, which the motor vehicle 4 approaches at a certain speed. In order to achieve a stable, i.e., steady state in the regulation or vehicle guidance, the overall speed of the motor vehicle 4 must be reduced until the motor vehicle 4 stops behind the stationary object. This maneuver, for example, may take relatively more time than a less drastic speed adaptation and therefore means a correspondingly large or wide relevance region for objects that are stationary or move much slower than the motor vehicle 4. The other extreme case is an object that moves in the same driving direction as the motor vehicle 4 at a speed greater than or equal to that of the motor vehicle 4. In this case, a stable steady state has been achieved in the regulation of the motor vehicle 4 without further measures, whereby the relevance region can be set or limited to a preset or expected distance or the current distance to the corresponding object or the desired distance set by the driver of the motor vehicle 4, etc.

[0048] Objects that have been detected and classified as relevant once, for example, the vehicle in front 5, can move away from the motor vehicle 4 in the following process, for example, when these objects accelerate. For this case, a further distance can be determined in each case, and when this distance is exceeded, the corresponding object is classified as no longer relevant, that is, discarded. This further distance is shown here as a first rejection distance 20 for the vehicle in front 5 by way of example. Here, the first rejection distance 20 is always greater than the first comfort distance 16. This can be ensured, for example, by presetting a corresponding further parameterization for the distance calculation rule and using it to determine the first rejection distance 20.

[0049] It should be noted here that Figure 1 The sizes and distances in the figures, ie in particular the positions and distances of different distances, are not true to scale and are shown purely by way of example and diagrammatically.

[0050] In summary, the described example shows how longitudinal target selection can be implemented, in particular based on the input data quality, in particular in multimodal embedded systems, for determining the driving lane assignment, ie, the longitudinal relevance evaluation.

[0051] Reference numerals list

[0052] 1 Road

[0053] 2 lanes

[0054] 3 Adjacent lanes

[0055] 4 Motor Vehicles

[0056] 5 Vehicle ahead

[0057] 6 vehicles

[0058] 7 Environmental sensing device

[0059] 8. Adjustment Devices

[0060] 9 Vehicle components

[0061] 10. Assistance System

[0062] 11 Interface

[0063] 12 Processor

[0064] 13 Data storage

[0065] 14 Driving channel

[0066] 15 First minimum distance

[0067] 16 First comfort distance

[0068] 17 Mass distance

[0069] 18 Second minimum distance

[0070] 19 Second comfort distance

[0071] 20 First rejection distance.

Claims

1. A method for evaluating the relevance of objects (5, 6) in the environment of a motor vehicle (4), wherein: detecting environmental data which describe objects (5, 6) located in the respective environment of the motor vehicle (4), determining the respective relative movements of the objects (5, 6) relative to the motor vehicle (4), Based on this, at least one object-specific distance (15, 16, 18, 19) is determined for each detected object (5, 6) according to driving parameters preset for the motor vehicle (4), which distance is required to achieve a stable state of the motor vehicle (4) behind the respective object (5, 6), and A relevance check is performed for each of the detected objects (5, 6) based on at least one distance (15, 16, 18, 19) specific to the respective object, wherein the respective object (5, 6) is classified as relevant or irrelevant for the guidance of the motor vehicle (4).

2. The method according to claim 1, characterized in that When determining the respective distances (15, 16, 18, 19), the maximum permissible jerk of the motor vehicle (4) is also taken into account.

3. The method according to any one of the preceding claims, characterized in that The relevance of all detected objects (5, 6) is determined, a driving corridor (14) in which the motor vehicle (4) is expected to move is estimated, and only those of the detected objects (5, 6) which are classified as relevant and are located in the driving corridor (14) are output as objects (5) relevant for a driver assistance function of the motor vehicle (4).

4. The method according to any one of the preceding claims, characterized in that Determining the at least one distance (15, 16, 18, 19) comprises: determining a first distance (15, 18) and a larger second distance (16, 19) for the detected object (5, 6), the first distance being obtained as a minimum distance for safely guiding the motor vehicle (4), the second distance being obtained when the vehicle is guided more comfortably than the safe guidance, and the first distance (15, 18), the second distance (16, 19) or a distance (17) between the first distance and the second distance being used for the correlation check.

5. The method according to claim 4, characterized in that estimating a driving path (14) in which the motor vehicle (4) is expected to move, determining the quality of the estimate and, on this basis, also determining a third distance (17), which is smaller when the quality is lower and larger when the quality is higher, and If the third distance (17) is smaller than the first distance (15, 18), the object (5, 6) is classified as relevant only if the distance between the object (5, 6) and the motor vehicle (4) corresponds at most to the first distance (15, 18), If the third distance (17) is greater than the second distance (16, 19), the object (5, 6) is classified as relevant only if the distance between the object (5, 6) and the motor vehicle (4) corresponds at most to the second distance (16, 19), and If the third distance (17) is between the first distance (15, 18) and the second distance (16, 19), the object (5, 6) is classified as relevant only if the distance between the object (5, 6) and the motor vehicle (4) corresponds at most to the third distance (17).

6. The method according to claim 5, characterized in that The quality is determined as a function of the distance and the third distance (17) is used as the distance at which a quality threshold value which is predefined, in particular for a standard deviation or for a convolution of an estimate of the driving path (14) with an uncertainty of the object detection, is undershot.

7. The method according to any one of the preceding claims, characterized in that When a stable state of the motor vehicle (4) is determined with respect to a detected object (5, 6), a relevance region extending from the motor vehicle (4) in the direction of the object (5, 6) is limited to a preset standard distance or a current distance to the respective object (5, 6) within which the object (5, 6) is classified as relevant.

8. The method according to any one of the preceding claims, characterized in that Objects (5, 6) classified as relevant are classified as no longer relevant only from a rejection distance (20) which is greater than the distance (16, 17, 19) at which these objects were classified as relevant.

9. An assistance system (10) for a motor vehicle (4), having an interface (11) for detecting environmental data, the environmental data describing the position and relative movement of objects (5, 6), the assistance system having a processor device (12) and a computer-readable data memory (13) coupled to the processor device, wherein the assistance system (10) is configured to implement a method according to any of the preceding claims.

10. A motor vehicle (4) having an environment sensor system (7) for detecting objects (5, 6) in the respective environment of the motor vehicle (4) and an assistance system (10) according to claim 9 coupled to the environment sensor system.

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