Evaluation device for evaluating trajectory hypotheses of a vehicle

Abstract

An evaluation device (105) for evaluating a predefined trajectory hypothesis (A) of a vehicle (100), wherein the evaluation device (105) comprises a calculation unit (115), a detection unit (120) and a dispatching unit (125). The calculation unit (115) is configured to calculate at least one necessary driving parameter (φ) for the vehicle (100) to follow the predefined trajectory hypothesis (A). A The detection unit (120) is configured to detect the current driving parameter (φ) of the vehicle (100). ego The dispatching unit (125) is configured to use the current driving parameter ( ego ) and the necessary driving parameters ( A ) assigns a probability value (P(A)) for the vehicle (100) to follow a predefined trajectory hypothesis (A).

Description

Technical Field

[0001] The invention relates to an evaluation device for evaluating a trajectory hypothesis of a vehicle, a vehicle having such an evaluation device, and a method for controlling the evaluation device of a vehicle. Background Art

[0002] For driver assistance systems, the driver partially or primarily defines the future state of the autonomous vehicle. To make decisions, these systems consider one or more hypotheses about the vehicle's predicted state within a certain prediction period.

[0003] US Pat. No. 9,610,945 B2 discloses a system for identifying an intersection between a host vehicle and a target vehicle. Data related to the target vehicle is collected. A map of the surrounding environment is developed. A probability of driver intent is determined based at least in part on the map. A threat estimate is determined based at least in part on the probability of driver intent. At least one of a plurality of safety systems is activated based at least in part on the threat estimate. Summary of the Invention

[0004] Against this background, it is an object of the present invention to provide an improved evaluation device for evaluating a trajectory hypothesis of a vehicle, an improved vehicle having such an evaluation device, and an improved method for controlling an evaluation device of a vehicle.

[0005] This object is achieved by an evaluation device for evaluating a trajectory hypothesis of a vehicle, by a vehicle having such an evaluation device, and by a method according to the invention for controlling an evaluation device of a vehicle.

[0006] Advantageously, a probability value for the vehicle following a predefined trajectory hypothesis can be evaluated, wherein according to an embodiment, this probability value can subsequently be used by a driver assistance system of the vehicle, for example to predict a possible collision of the vehicle with an object or another vehicle.

[0007] An evaluation device for evaluating a predefined trajectory hypothesis for a vehicle includes a calculation unit, a detection unit, and an assignment unit. The calculation unit is configured to calculate at least one necessary driving parameter for the vehicle to follow the predefined trajectory hypothesis. The detection unit is configured to detect a current driving parameter of the vehicle. The assignment unit is configured to assign a probability value for the vehicle to follow the predefined trajectory hypothesis using the current driving parameter and the necessary driving parameter.

[0008] The vehicle may be a utility vehicle or a commercial vehicle, such as a truck or bus. The evaluation device may be configured to receive at least a predefined trajectory hypothesis or a plurality of different predefined trajectory hypotheses from a determination unit. The determination unit may be configured to determine at least one predefined trajectory hypothesis for the vehicle using, for example, at least sensor information, driver monitoring information, and / or observed environmental information of the vehicle. The predefined trajectory hypothesis may be a possible trajectory for the vehicle to follow from a set of multiple possible trajectories. The required driving parameter may be a subsequent driving parameter that must be activated in order for the vehicle to follow the predefined trajectory hypothesis. The required driving parameter may be an actuation value or control value of a vehicle setting unit of the vehicle. The current driving parameter may be an actuation value or control value of the same vehicle setting unit of the vehicle, such that the current driving parameter and the required driving parameter are comparable driving parameters. The assignment unit may be configured to assign a probability value for the vehicle following the predefined trajectory hypothesis using a comparison result between the current driving parameter and the required driving parameter.

[0009] According to one embodiment, the calculation unit may be configured to calculate at least a second required driving parameter for the vehicle to follow a second predefined trajectory hypothesis, and the assignment unit may be configured to assign a second probability value for the vehicle to follow the second predefined trajectory hypothesis using the current driving parameter and the second required driving parameter. Such an embodiment provides the advantage of calculating the second probability value for the second predefined trajectory hypothesis. According to one embodiment, the probability value and the second probability value may be compared to determine which of the two predefined trajectory hypotheses may be selected as the one with the higher probability value to be followed.

[0010] According to one embodiment, the dispatching unit is configured to assign a higher probability value for the vehicle to follow the predefined trajectory hypothesis than the probability value for the vehicle to follow the second predefined trajectory hypothesis if the current driving parameters are more similar to the required driving parameters than to the second required driving parameters, and / or the dispatching unit is configured to assign a second higher probability value for the vehicle to follow the second predefined trajectory hypothesis than the probability value for the vehicle to follow the predefined trajectory hypothesis if the current driving parameters are more similar to the second required driving parameters than to the required driving parameters. According to one embodiment, the higher probability value for the vehicle to follow the predefined trajectory hypothesis may be assigned if the difference between the current driving parameters and the required driving parameters is less than the difference between the current driving parameters and the second required driving parameters. According to one embodiment, the higher second probability value for the vehicle to follow the second predefined trajectory hypothesis may be assigned if the difference between the current driving parameters and the second required driving parameters is less than the difference between the current driving parameters and the required driving parameters.

[0011] According to one embodiment, the calculation unit may be configured to calculate the necessary driving parameters as a steering wheel angle and / or a necessary acceleration for the vehicle to follow a predefined trajectory hypothesis, and / or the detection unit may be configured to detect the current driving parameters as an actuated steering wheel angle and / or an actuated acceleration of the vehicle. Such driving parameters can be easily compared.

[0012] According to one embodiment, the evaluation device may include a determination unit configured to determine at least one predefined trajectory hypothesis for the vehicle using at least vehicle sensor information, driver monitoring information, and / or observed environmental information. According to one embodiment, the vehicle sensor information may represent the vehicle's yaw rate and / or the vehicle's speed. For example, the boundary of the current lane may serve as a source for predicting the predefined trajectory hypothesis. Advantageously, the predefined trajectory hypothesis for the vehicle may be determined by considering actual driving information.

[0013] According to one embodiment, the assessment device may include a collision calculation unit, wherein the collision calculation unit is configured to calculate a collision probability value for a collision between the vehicle and an object or another vehicle using a probability value. According to one embodiment, the collision calculation unit may be configured to calculate a collision probability value for a collision between the vehicle and an object or another vehicle on a predefined trajectory using a probability value. Such a collision probability value may be used to avoid a possible collision. The collision calculation unit may improve vehicle safety.

[0014] According to one embodiment, the collision calculation unit may be configured to use the collision likelihood value to calculate a collision avoidance strategy for adjusting a predefined trajectory hypothesis. By adjusting the predefined trajectory hypothesis, collisions may be advantageously avoided.

[0015] According to one embodiment, the evaluation device may further include a selection unit, wherein the selection unit is configured to select a predefined trajectory hypothesis as the predicted trajectory to be followed by the vehicle if the probability value reaches or exceeds a defined probability value or includes a highest probability value among a plurality of assigned probability values for a plurality of different predefined trajectory hypotheses. Advantageously, the predefined trajectory hypothesis may be selected as the predicted trajectory, for example, as the one that can be selected by the driver of the vehicle to be most likely to be followed.

[0016] According to one embodiment, the selection unit may be configured to provide a control signal to a control unit of the vehicle, wherein the control signal is configured to control the vehicle so as to follow the predicted trajectory. Such a control signal may be used to automatically control the vehicle.

[0017] According to an embodiment, the evaluation device may comprise a control unit, wherein the control unit is configured to control the vehicle using the control signal to follow the predicted trajectory.

[0018] According to one embodiment, the dispatching unit can be configured to be able to dispatch the probability value based on the deviation between the necessary driving parameter and the current driving parameter and / or at least one previous driving parameter of the vehicle actuated before the current driving parameter and / or at least one previous necessary driving parameter of the vehicle calculated at the necessary driving parameter.

[0019] A vehicle comprises an embodiment of the aforementioned evaluation device. The vehicle may be a multi-purpose vehicle or a commercial vehicle, such as a truck, a bus, or the like.

[0020] A method for controlling the above-mentioned evaluation device, comprising:

[0021] calculating at least one necessary driving parameter for the vehicle to follow a predefined trajectory hypothesis;

[0022] Detecting the vehicle's current driving parameters; and

[0023] A probability value for the vehicle following a predefined trajectory hypothesis is assigned using the current driving parameters and the necessary driving parameters.

[0024] The method or steps of the method can be performed using the aforementioned evaluation device.

[0025] Also advantageous is a computer program product with a program code, which can be stored on a machine-readable medium, such as a semiconductor memory, a hard disk or an optical memory, for executing the method of one of the aforementioned exemplary embodiments when the program product is executed on a computer or device. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In the following description, embodiments of the solution shown here will be explained in more detail with reference to the accompanying drawings, in which:

[0027] Figure 1 A schematic diagram showing a vehicle comprising an evaluation device for evaluating a predefined trajectory hypothesis according to an embodiment of the present invention; and

[0028] Figure 2 A flow chart of a method for controlling an evaluation device according to an embodiment of the present invention is shown.

[0029] In the following description of advantageous embodiments of the present invention, identical or similar reference numerals will be used for similarly acting elements shown in the various figures, wherein a repeated description of these elements will be omitted. DETAILED DESCRIPTION

[0030] Figure 1A schematic diagram of a vehicle 100 is shown, which includes an evaluation device 105 according to an embodiment of the present invention for evaluating a predefined trajectory hypothesis A. The vehicle 100 is a utility vehicle or a commercial vehicle and / or is configured as an autonomous vehicle 100 or a semi-autonomous vehicle 100. According to this embodiment, the vehicle 100 includes at least one vehicle sensor 110.

[0031] The evaluation device 105 for evaluating a predefined trajectory hypothesis A comprises a calculation unit 115, a detection unit 120 and a dispatching unit 125. The calculation unit 115 is configured to calculate at least one necessary driving parameter φ for the vehicle 100 to follow the predefined trajectory hypothesis A. A The detection unit 120 is configured to detect the current driving parameter Φ of the vehicle 100 ego The dispatch unit 125 is configured to use the current driving parameter Φ ego and necessary driving parameters Ф A A probability value P(A) for the vehicle 100 to follow the predefined trajectory hypothesis A is assigned.

[0032] According to this embodiment, evaluation device 105 is configured to receive at least a predefined trajectory hypothesis A or a plurality of different predefined trajectory hypotheses A, B from determination unit 130. Determination unit 130 is configured to determine at least one predefined trajectory hypothesis A for vehicle 100 using, for example, at least sensor information 135 of vehicle 100, driver monitoring information, and / or observed environmental information from vehicle sensors 110. According to an embodiment, sensor information 135 represents a yaw rate of vehicle 100 and / or a vehicle speed of vehicle 100. For example, the boundary of the current lane is used as a source for predicting predefined trajectory hypothesis A and / or a second predefined trajectory hypothesis B. According to this embodiment, determination unit 130 is part of evaluation device 105.

[0033] The predefined trajectory hypothesis A is a possible trajectory to be followed by the vehicle 100 among a set of possible multiple trajectories. Necessary driving parameters Φ A is the subsequent driving parameter that must be activated in order to control the vehicle 100 to follow the predefined trajectory hypothesis A. Necessary driving parameter Φ A represents, for example, an actuation value or a control value of a vehicle setting unit of the vehicle 100. Current driving parameter Φ ego Indicates the actual actuation value or control value. Current driving parameter Φ ego represents the actuation value or control value of the same vehicle setting unit of the vehicle 100, and thus the current driving parameter Φ ego and necessary driving parameters Ф A is a comparable driving parameter. According to one embodiment, the dispatching unit 125 is configured to use the current driving parameter Φ ego and necessary driving parameters Ф AThe comparison result therebetween assigns a probability value P(A) for the vehicle 100 to follow the predefined trajectory hypothesis A.

[0034] According to this embodiment, the calculation unit 115 is configured to calculate at least a second necessary driving parameter Φ for the vehicle 100 to follow the second predefined trajectory hypothesis B B ; The dispatch unit 125 is configured to use the current driving parameters Ф ego and the second necessary driving parameter Ф B A second probability value P(B) for the vehicle 100 following the second predefined trajectory hypothesis B is assigned.

[0035] According to this embodiment, the dispatching unit 125 is configured to: ego and necessary driving parameters Ф A The similarity is greater than the current driving parameter Ф ego The second necessary driving parameter Ф B , the vehicle 100 is assigned a higher probability value P(A) than the probability value for the vehicle 100 to follow the second predefined trajectory hypothesis B to follow the predefined trajectory hypothesis A, and / or the dispatching unit 125 is configured to if the current driving parameter Φ ego The second necessary driving parameter Ф B The similarity is greater than the current driving parameter Ф ego and necessary driving parameters Ф A , then assign a second probability value P(B) for the vehicle 100 to follow the second predefined trajectory hypothesis B that is higher than the probability value for the vehicle 100 to follow the predefined trajectory hypothesis A. According to one embodiment, if the current driving parameter Φ ego and necessary driving parameters Ф A The difference between them is less than the current driving parameter Ф ego and the second necessary driving parameter Ф B If the difference between the current driving parameters Φ and the current driving parameters Φ is greater than the difference between the current driving parameters Φ and the current driving parameters Φ, a higher probability value P(A) may be assigned for the vehicle 100 to follow the predefined trajectory hypothesis A. ego and the second necessary driving parameter Ф B The difference between them is less than the current driving parameter Ф ego and necessary driving parameters Ф A If the difference between , then the vehicle 100 may be assigned a higher second probability value P(B) of following the second predefined trajectory hypothesis B.

[0036] According to this embodiment, the calculation unit 115 is configured to calculate the necessary driving parameter Φ A As the necessary steering wheel angle and / or necessary acceleration for the vehicle 100 to follow the predefined trajectory hypothesis A and / or the detection unit 120 is configured to detect the current driving parameter Φ egoAs an actuated steering wheel angle and / or an actuated acceleration of the vehicle 100 .

[0037] According to this embodiment, the evaluation device 100 further includes a collision calculation unit 140, wherein the collision calculation unit 140 is configured to calculate a collision probability value CP(A) of the vehicle 100 colliding with an object or another vehicle using a probability value P(A). According to one embodiment, the collision calculation unit 140 is configured to calculate the collision probability value CP(A) of the vehicle 100 colliding with an object or another vehicle on a predefined trajectory hypothesis A using the probability value P(A). According to this embodiment, the collision calculation unit 140 is configured to calculate a second collision probability value of the vehicle 100 colliding with the object or another vehicle using a probability value P(B). According to one embodiment, the collision calculation unit 140 is configured to calculate a second collision probability value of the vehicle 100 colliding with an object or another vehicle on a second predefined trajectory hypothesis B using the probability value P(B).

[0038] According to this embodiment, the collision calculation unit 140 is configured to use the collision probability value CP(A) to calculate a collision avoidance strategy for adjusting the predefined trajectory hypothesis A. According to one embodiment, the collision calculation unit 140 is further configured to use the second collision probability value to calculate a second collision avoidance strategy for adjusting the second predefined trajectory hypothesis B.

[0039] According to one embodiment, the evaluation device 100 further includes a selection unit, wherein the selection unit is configured to select the predefined trajectory hypothesis A as the predicted trajectory to be followed by the vehicle 100 if the probability value P(A) reaches or exceeds a defined probability value or includes the highest probability value among a plurality of assigned probability values for the plurality of different predefined trajectory hypotheses A, B. According to one embodiment, the selection unit is configured to select the second predefined trajectory hypothesis B as the predicted trajectory to be followed by the vehicle 100 if the second probability value P(B) reaches or exceeds a defined probability value or includes the highest probability value among a plurality of assigned probability values for the plurality of different predefined trajectory hypotheses A, B. According to one embodiment, the selection unit is configured to provide a control signal to a control unit of the vehicle 100, wherein the control signal is configured to control the vehicle 100 to follow the predicted trajectory. According to one embodiment, the evaluation device 100 includes a control unit configured to control the vehicle 100 to follow the predicted trajectory using the control signal.

[0040] According to one embodiment, the dispatching unit 125 is configured to be able to A and the current driving parameter Φ ego Deviations and / or current driving parameters Φ of the vehicle 100 ego At least one previous driving parameter of a previous actuation and / or the necessary driving parameter Φ of the vehicle 100 AThe probability value P(A) is assigned based on at least one previously calculated necessary driving parameter. An example of assigning the probability value P(A) and the second probability value P(B) is shown above:

[0041] P(A)=f(|Ф ego -Ф A |)

[0042] P(B)=f(|Ф ego -Ф B |)

[0043] In other words, Figure 1 The architecture of an evaluation device 105 is shown, which enables the use of control values to estimate the probabilities of trajectory hypotheses A, B, which can also be referred to as “autonomous motion trajectories” or “autonomous vehicle trajectories”.

[0044] According to one embodiment, evaluation device 105 is integrated or implemented into a driver assistance system of vehicle 100, such as ACC (Adaptive Cruise Control), AEBS (Advanced Emergency Braking System), or PAEBS. For such driver assistance systems, the driver of vehicle 100 partially or primarily defines the future state of autonomous vehicle 100. To make a decision, these systems consider one or more trajectory hypotheses A, B of the predicted vehicle state within a certain prediction period.

[0045] According to one embodiment, hypotheses A and B (autonomous vehicle trajectories) for future vehicle states within a prediction period are estimated using various sources, such as sensor information 135 within autonomous vehicle 100, driver monitoring information, and / or observed environmental information. For example, the current lane boundary, if available, is a source for predicting the future vehicle trajectory. Another source is the current state of vehicle dynamics, such as yaw rate and vehicle speed. To make a decision based on the autonomous vehicle trajectory for each of hypotheses A and B, the dispatch unit 125 assigns / estimates a certain probability of occurrence. According to one embodiment, based on the probabilities of the trajectory hypotheses A and B, for example, the highest probability is selected or the probability of each hypothesis A and B is directly considered when making a decision.

[0046] In the context of autonomous driving, control algorithms are used to calculate the necessary actuation values, such as steering wheel angle, acceleration requirements, etc., based on the predicted trajectory.

[0047] Here, a basic idea is to use the actuation values of the autonomous vehicle controller to estimate the probability of whether the driver will follow a certain trajectory hypothesis A, B. To estimate the probability of occurrence, this function is applied to different autonomous vehicle trajectories A, B. For each of the trajectories A, B, ..., an actuation value is calculated, and the control algorithm of the autonomous vehicle 100 will select the actuation value to follow a specific trajectory. According to one embodiment, the estimated actuation value is then compared with the actual actuation value.

[0048] According to one embodiment, the occurrence probability of each autonomous vehicle trajectory A, B is calculated based on the deviation of the estimated actuation value from the actual actuation value and the corresponding value at the previous time step.

[0049] According to one embodiment, the occurrence probabilities are then used to estimate the collision probability for a particular autonomous vehicle trajectory A, B, which can then be used, for example, in a collision avoidance strategy.

[0050] Figure 2 1 is a flow chart showing a method 200 for controlling an evaluation device according to an embodiment of the present invention. Figure 1 The described evaluation device or a similar evaluation device is performed.

[0051] The control method 200 includes a step 210 of calculating at least one necessary driving parameter for the vehicle to follow a predefined trajectory hypothesis. The control method 200 also includes a step 220 of detecting a current driving parameter of the vehicle. Furthermore, the control method 200 includes a step 230 of assigning a probability value for the vehicle to follow the predefined trajectory hypothesis using the current driving parameter and the necessary driving parameter.

[0052] Reference Signs List

[0053] Ф A Necessary driving parameters

[0054] Ф B The second necessary driving parameter

[0055] Ф ego Current driving parameters

[0056] A Predefined trajectory assumption

[0057] B. Predefined trajectory assumptions

[0058] CP(A) collision probability value

[0059] P(A) probability value

[0060] P(B) second probability value

[0061] 100 vehicles

[0062] 105 Evaluation Equipment

[0063] 110 Vehicle Sensors

[0064] 115 computing units

[0065] 120 detection units

[0066] 125 dispatch units

[0067] 130 Determine Unit

[0068] 135 Sensor Information

[0069] 140 Collision Calculation Unit

[0070] 200 Method for controlling an evaluation device of a vehicle

[0071] 210 Calculation steps

[0072] 220 Detection Steps

[0073] 230 dispatch steps

Claims

1. An evaluation device (105) for evaluating a predefined trajectory hypothesis (A) of a vehicle (100) having a driver assistance system, the evaluation device (105) being integrated or implemented in the driver assistance system of the vehicle (100); wherein The evaluation device (105) comprises: A calculation unit (115), wherein the calculation unit (115) is configured to be able to calculate at least one necessary driving parameter (φ) for the vehicle (100) to follow a predefined trajectory hypothesis (A) A ); A detection unit (120), wherein the detection unit (120) is configured to detect a current driving parameter (φ) of the vehicle (100) ego );as well as A dispatching unit (125), wherein the dispatching unit (125) is configured to use the current driving parameter ( ego ) and the necessary driving parameters (Ф A ) assigning a probability value (P(A)) for the vehicle (100) to follow a predefined trajectory hypothesis (A); and a selection unit, wherein the selection unit is configured to select a predefined trajectory hypothesis (A) as a predicted trajectory to be followed by the vehicle (100) if the probability value (P(A)) reaches or exceeds a defined probability value or includes a highest probability value among a plurality of assigned probability values (P(A), P(B)) for a plurality of different predefined trajectory hypotheses (A, B); The driving assistance system controls the vehicle and the vehicle setting unit using at least one necessary driving parameter, the necessary driving parameter being an actuation value or a control value of the vehicle setting unit of the vehicle.

2. The evaluation device (105) according to claim 1, wherein The calculation unit (115) is configured to be able to calculate at least a second necessary driving parameter (φ) for the vehicle (100) to follow a predefined second predefined trajectory hypothesis (B). B ); the dispatching unit (125) is configured to be able to use the current driving parameter ( ego ) and the second necessary driving parameter ( B ) assigns a second probability value (P(B)) for the vehicle (100) to follow a second predefined trajectory hypothesis (B).

3. The evaluation device (105) according to claim 2, wherein The dispatching unit (125) is configured to: if the current driving parameter ( ego ) and the necessary driving parameters (Ф A ) is greater than the current driving parameter ( ego ) and the second necessary driving parameter ( B ), the vehicle (100) is assigned a higher probability value (P(A)) for following the predefined trajectory hypothesis (A) than the probability value for the vehicle to follow the second predefined trajectory hypothesis (B); and / or the dispatching unit (125) is configured to: if the current driving parameter ( ego ) and the second necessary driving parameter ( B ) is greater than the current driving parameter ( ego ) and the necessary driving parameters (Ф A ), then assigning a second probability value (P(B)) for the vehicle (100) to follow the second predefined trajectory hypothesis (B) that is higher than the probability value for the vehicle to follow the predefined trajectory hypothesis (A).

4. The evaluation device (105) according to any one of the preceding claims, wherein The calculation unit (115) is configured to calculate the necessary driving parameters ( A ) as a necessary steering wheel angle and / or necessary acceleration for the vehicle (100) to follow the predefined trajectory hypothesis (A) and / or the detection unit (120) is configured to be able to detect the current driving parameter ( ego ) as the actuated steering wheel angle and / or actuated acceleration of the vehicle (100).

5. The evaluation device (105) according to any one of claims 1 to 3, comprising a determination unit (130), wherein the determination unit (130) is configured to be able to determine at least one predefined trajectory hypothesis (A) for the vehicle (100) using at least sensor information (135) of the vehicle (100), driver monitoring information and / or observed environment information.

6. The evaluation device (105) according to any one of claims 1 to 3, comprising a collision calculation unit (140), wherein: The collision calculation unit (140) is configured to be capable of calculating a collision probability value (CP(A)) of the vehicle (100) colliding with an object or another vehicle using a probability value (P(A)).

7. The evaluation device (105) according to claim 6, wherein The collision calculation unit (140) is configured to use the collision probability value (CP(A)) to calculate a collision avoidance strategy for adjusting a predefined trajectory hypothesis (A).

8. The evaluation device (105) according to any one of claims 1 to 3, wherein The dispatching unit (125) is configured to be able to A ) and the current driving parameter (Ф ego ) and / or the vehicle (100) in the current driving parameter ( ego ) before actuating at least one previous driving parameter and / or the vehicle (100) within said necessary driving parameter ( A ) is used to assign a probability value (P(A)) based on at least one previously necessary driving parameter calculated previously.

9. A vehicle (100), wherein: The vehicle (100) comprises an evaluation device (105) according to one of the preceding claims.

10. A method (200) of controlling an evaluation device (105) according to any one of claims 1 to 8, wherein: The method (200) comprises: Calculating (210) at least one necessary driving parameter (φ) for the vehicle (100) to follow a predefined trajectory hypothesis (A) A ); Detect (220) the current driving parameter (φ) of the vehicle (100) ego );as well as Using the current driving parameters ( ego ) and the necessary driving parameters (Ф A ) assigns (230) a probability value (P(A)) for the vehicle (100) to follow a predefined trajectory hypothesis (A), selecting, by a selection unit, a predefined trajectory hypothesis (A) as a predicted trajectory to be followed by the vehicle (100) if the probability value (P(A)) reaches or exceeds a defined probability value or includes a highest probability value among a plurality of assigned probability values (P(A), P(B)) for a plurality of different predefined trajectory hypotheses (A, B); The driving assistance system controls the vehicle and the vehicle setting unit using at least one necessary driving parameter, the necessary driving parameter being an actuation value or a control value of the vehicle setting unit of the vehicle.

11. A computer program configured to implement, control or execute the steps (210, 220, 230) of the method (200) according to claim 10, when the method (200) is executed on a respectively configured device (105).

12. A machine-readable data carrier comprising a computer program according to claim 11.

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