Driver assistance system for controlling the speed of a vehicle from at least two front vehicle

Abstract

The present disclosure relates to a driver assistance system for controlling the speed of a vehicle according to at least two further vehicles in front of the vehicle. The driver assistance system includes: a control system; and a sensor system for detecting a respective further speed of a respective further vehicle wherein the control system is configured to perform a weighting of the further speeds relative to each other and to determine a target speed of the vehicle as a function of the respective further speed and as a function of the weighting of the further speeds, and controlling a speed of the vehicle according to the target speed.

Description

Technical Field

[0001] The present disclosure relates generally to the field of autonomous and semi-autonomous control of vehicles, and in particular to driver assistance systems for controlling vehicle speed. Background Art

[0002] It is known to control the speed of a vehicle according to the speed of another vehicle traveling directly in front of the vehicle. Conventional adaptive cruise control (ACC) systems can be designed to calculate a target speed of the vehicle according to the speed of the other vehicle and control the speed of the vehicle according to the target speed so that the vehicle follows the other vehicle. Utility Model Content

[0003] Various embodiments provide a driver assistance system for controlling the speed of a vehicle. Advantageous embodiments are also described. The embodiments of the present disclosure can be freely combined with each other as long as they are not mutually exclusive.

[0004] In one aspect, the present disclosure relates to a driver assistance system for controlling the speed of a vehicle based on at least two other vehicles ahead of the vehicle. The driver assistance system includes a control system and a sensor system for detecting respective additional speeds of the respective additional vehicles. The control system is configured to weight the additional speeds relative to one another and determine a target speed for the vehicle based on the respective additional speeds and the weightings of the additional speeds. Furthermore, the control system is configured to control the speed of the vehicle based on the target speed.

[0005] The driver assistance system can allow the target speed to be calculated so that the corresponding influence of the corresponding other speed on the target speed can be different compared to the corresponding one of the other other speeds because the control system is configured to perform weighting of the corresponding other speeds. The more the control system weights the corresponding other speed, the stronger or greater the corresponding influence of the corresponding other speed on the calculation of the target speed. In one example, the control system can be configured to calculate the corresponding product of the corresponding other speed and the corresponding weighting factor in order to perform the weighting of the corresponding other speed. According to this example, the control system can be configured to calculate the target speed based on the sum of the corresponding products. In one example, the target speed can be equal to the sum of the corresponding products.

[0006] Generally, taking into account the additional speeds of at least two other vehicles ahead of the vehicle to control the vehicle's speed can allow the vehicle's speed to be controlled in a manner that reduces the vehicle's fuel consumption. This is due to the fact that, in most cases, the weighted sum of the two additional speeds may vary less over time than the corresponding individual additional speeds. Since the target speed is calculated based on the corresponding additional speeds, the temporal variation of the target speed can be reduced in most cases. Since the target speed serves as a setpoint for the vehicle's speed when the control unit controls the vehicle's speed, this can reduce the temporal variation of the vehicle's acceleration, thereby reducing the vehicle's fuel consumption and improving driving comfort.

[0007] Typically, weighting can be performed so that the additional speed of another vehicle closer to the vehicle is weighted more than the additional speed of the other vehicle, and vice versa. In the first case, the control system can control the vehicle's speed with an emphasis on maintaining a predetermined ideal or effective distance from the other vehicle next to the vehicle (hereinafter also referred to as the nearest leading vehicle). However, fuel consumption can still be reduced compared to speed control that only considers the additional speed of the nearest leading vehicle. In another case, the control system can control the vehicle's speed with a greater focus on reducing the vehicle's fuel consumption. In this case, according to one example, the distance between the vehicle and the nearest leading vehicle may sometimes be less than the predetermined ideal or effective distance.

[0008] Generally, the weighting of the respective additional speeds can allow the calculation of the target speed to be adapted to the vehicle's usage. In one example, the weighting can depend on the type of vehicle. For example, when the vehicle is a police car, the additional speed of the nearest leading vehicle can have a greater influence on the calculation of the target speed than the additional speed of another additional vehicle. When the vehicle is a truck, the additional speed of the nearest leading vehicle can have a smaller influence on the calculation of the target speed than the additional speed of another additional vehicle. Thus, when the vehicle is a police car, the driver assistance system can better track the nearest leading vehicle, and when the vehicle is a truck, the driver assistance system can calculate the target speed so that the vehicle's fuel consumption can be reduced to a greater extent.

[0009] According to one embodiment, the control system can be configured to adapt the weighting to the traffic conditions involving the vehicle and at least two other vehicles. This can enable the driver assistance system to implement a control strategy for controlling speed based on the traffic conditions. For example, when the speed of the nearest leading vehicle changes periodically over time at a higher rate than the speed of another other vehicle, the weighting can be adapted so that the additional speed of the other other vehicle has a greater impact on the target speed than the additional speed of the nearest leading vehicle. In this case, the additional speed of the nearest leading vehicle can be weighted more than the additional speed of the other other vehicle. In one example, the control system can be configured to detect the traffic conditions, such as based on sensor data generated by a sensor system.

[0010] Adapting the weighting to the traffic conditions can allow for even further reductions in vehicle fuel consumption, compared to an embodiment in which the weightings of the other speeds relative to one another are fixed over time and do not adapt to the traffic conditions. Furthermore, adapting the weighting to the traffic conditions and using the weightings to calculate the target speed for controlling the speed can require less computational effort and, therefore, can allow for real-time speed control taking into account the other vehicles, compared to an approach in which the states of the other vehicles are predicted to determine the optimal control input for controlling the speed by solving a numerical optimization problem.

[0011] According to another embodiment, the traffic situation can be specified by the corresponding driving mode of the corresponding other vehicle. According to this embodiment, the control system can be configured to adapt the weighting of the other speed according to the corresponding driving mode. In one example, the corresponding driving mode can be described by the corresponding level of fluctuation of the corresponding other speed over time. The control system can be configured to adapt the weighting of the other speed so that the more constant the corresponding other speed is over time, the stronger or greater the amount by which the corresponding other speed is weighted. The control system can be configured to detect the corresponding driving mode, in particular through sensor data. Adjusting the weighting of the other speed according to the corresponding driving mode can allow the speed of the vehicle to be controlled so that the speed of the vehicle can follow the other speed of whichever of the two other vehicles is driven more fuel-efficiently. Therefore, compared to conventional ACC systems, the speed of the vehicle does not necessarily have to follow the other speed of the nearest leading vehicle. As a result, the fuel consumption of the vehicle can be further reduced.

[0012] In another aspect, the present disclosure relates to a computer program product comprising instructions, wherein execution of the instructions by one or more processors initiates the one or more processors to perform a method for controlling the speed of a vehicle based on at least two other vehicles ahead of the vehicle. In a first step, respective additional speeds of the respective additional vehicles may be detected by a sensor system. In a second step, the additional speeds may be weighted relative to one another by a control system. In a third step, a target speed for the vehicle may be determined based on the respective additional speeds and based on the weighting of the additional speeds relative to one another by the control system. In a fourth step, the speed of the vehicle may be controlled by the control system based on the target speed.

[0013] Advantageous forms of a system and a computer program product are also described, the computer program product comprising instructions for executing the method for controlling the speed of a vehicle in dependence on at least two further vehicles in front of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The following embodiments of the present disclosure are explained in more detail, by way of example only, with reference to the accompanying drawings, in which:

[0015] Figure 1 schematically depicts a vehicle including a driver assistance system and a control system for controlling vehicle speed according to one or more embodiments shown and described herein;

[0016] Figure 2 Schematically illustrates a method of manufacturing a system according to one or more embodiments shown and described herein. Figure 1 Traffic situation of the vehicle shown in and two other vehicles in front of the vehicle;

[0017] Figure 3 schematically depicts the steps of a method for controlling vehicle speed according to one or more embodiments shown and described herein;

[0018] Figure 4 schematically depicts a data flow for controlling vehicle speed according to one or more embodiments shown and described herein;

[0019] Figure 5 Schematically illustrates a system with a database according to one or more embodiments shown and described herein. Figure 1 The control system shown; and

[0020] Figure 6 Schematically depicts a data flow for calculating weighting factors for performing a weighting operation on a target object according to one or more embodiments shown and described herein. Figure 1 The respective speeds of the two other vehicles shown in are weighted. DETAILED DESCRIPTION

[0021] Figure 1 A driver assistance system 1 is depicted for controlling the speed of a vehicle 2 (hereinafter also referred to as ego speed 101) based on another vehicle in front of the vehicle 2 (hereinafter also referred to as a lead vehicle). The lead vehicle may include at least two other vehicles. Figure 2 2. The driver assistance system 1 may comprise a control system 3 and a sensor system 4 for detecting a respective further speed of the respective leading vehicle, also referred to below as the respective further speed v i,lead , for example a first additional speed v of the first leading vehicle 21 1,lead and a second further speed v of the second leading vehicle 22 2,lead . Detect the corresponding other speed v i,lead It may involve calculating the corresponding additional velocity v i,lead In the context of this disclosure, the term "corresponding additional speed v i,lead " can be used to indicate the corresponding other speed v i,lead The sensor system 4 may include one or more lidar sensors, one or more radar sensors, and / or one or more camera devices for transmitting a set of electromagnetic waves and receiving a set of corresponding electromagnetic waves reflected at a corresponding leading vehicle. The sensor system 4 may be configured to generate sensor data 200 based on the set of reflections of the received electromagnetic waves. The sensor data 200 may be used to determine a corresponding further speed v i,lead Alternatively, a corresponding additional velocity v may be included i,lead In one example, the control system 3 may be configured to calculate a corresponding further speed v from the sensor data 200 . i,lead , wherein when the sensor data 200 does not include a corresponding additional speed v i,lead Therefore, in one example, the corresponding additional speed v i,lead It can be detected by the sensor system 4 and the control system 3 together.

[0022] The control system 3 may be an electronic control unit, a central processing unit (CPU), or the like for performing the functions described herein. Thus, the control system 3 may be configured to receive, analyze, and process sensor data, perform calculations and mathematical functions, convert data, generate data, control vehicle system components (e.g., controlling the self-speed 101 via active control of the propulsion system 5 and / or the braking system 6), etc. The control system 3 may include one or more processors 52 ( Figure 5 ) and other components, such as one or more memory modules 51 ( Figure 5) and database 50( Figure 5 ). Each of the one or more processors can be a controller, an integrated circuit, a microchip, a central processing unit, or any other computing device. One or more memory modules can be non-transitory computer-readable media, and can be configured as RAM, ROM, flash memory, a hard drive, and / or any device capable of storing computer-executable instructions so that the computer-executable instructions can be accessed by one or more processors. Computer-executable instructions can include logic or algorithms written in any programming language of any generation, such as machine language that can be executed directly by a processor, or assembly language, object-oriented programming, scripting language, microcode, etc., which can be compiled or assembled into computer-executable instructions and stored on one or more memory modules. Alternatively, computer-executable instructions can be written in a hardware description language, such as logic implemented via a field programmable gate array (FPGA) configuration or an application-specific integrated circuit (ASIC) and all its equivalents. Therefore, the systems, methods, processes, and / or computer product programs described herein can be implemented as pre-programmed hardware elements or a combination of hardware and software components in any conventional computer programming language. Additionally, provided herein is a computer program product for use with or by the control system 3 to control components of the vehicle 2 (e.g., controlling the self-speed 101 via actively controlling the propulsion system 5 and / or the braking system 6). The computer program product may include a computer-usable medium having computer-readable instructions or program code embodied thereon.

[0023] The control system 3 may be configured to perform a weighting of the additional speeds of the leading vehicles relative to each other. Furthermore, the control system 3 may be configured to weight the additional speeds v according to the respective additional speeds v i,lead And the target speed 100 of the vehicle 2 is determined according to the weighting of the other speeds. In addition, the control system 3 can be configured to control the ego speed 101 according to the target speed 100.

[0024] Figure 3 The steps of a method for controlling an ego speed 101 in dependence on at least two further vehicles 21, 22 are shown. In a first step 1001, the respective further speed v of the respective further vehicle i,lead can be detected by the sensor system 4. In a second step 1002, a weighting of the further speeds relative to each other can be performed by the control system 3. In a third step 1003, the target speed 100 of the vehicle 2 can be determined based on the respective further speed v i,lead And it is determined according to the weighting of the other speeds with respect to each other by the control system 3. In a fourth step 1004, the self speed 101 may be controlled by the control system 3 according to the target speed 100.

[0025] The control system 3 can be connected to the propulsion system 5 of the vehicle 2 and the braking system 6 of the vehicle 2. In one example, the control system 3 can be configured to control the self-speed 101 by sending a control signal 300 to the propulsion system 5 and / or the braking system 6. In addition, the control system 3 can generate the control signal 300 based on the target speed 100.

[0026] Figure 4 A flow chart showing the data flow for controlling the ego speed 101 is depicted. The sensor system 4 may send sensor data 200 to the control system 3. The control system 3 may calculate the target speed 100 based on the sensor data 200. The sensor data 200 may include a corresponding further speed v i,lead Or it can be used to calculate the corresponding additional velocity v i,lead Furthermore, the control system 3 can calculate a control signal 300 based on the target speed 100 and the ego speed 101. The ego speed 101 can be measured by a speed sensor (not shown) of the vehicle 2. If the measured ego speed 101 deviates from the target speed 100, the control system 3 can recalculate the control signal 300. This recalculation of the control signal 300 can be performed repeatedly, so that the control loop for controlling the ego speed 101 is repeatedly executed. The target speed 100 can be used as the set point for the ego speed 101 used to execute the control loop.

[0027] The control system 3 may be configured to calculate a weighted sum of the further speeds, hereinafter also referred to as "sum w ", in order to perform weighting of the additional speeds. The weighted sum can be the corresponding additional speed v i,lead and the corresponding weighting factor w i Therefore, the control system 3 can be designed to calculate the weighted sum according to the following formula:

[0028] The total number of leading vehicles considered for calculating the target speed 100 may be given by n, and i may correspond to the respective leading vehicles. In one example, the target speed 100 may be equal to a weighted sum of the other speeds. According to another example, the target speed 100 may be calculated based on the weighted sum, for example by multiplying the weighted sum by a correction factor. According to Figure 2 In the example shown, the total number of leading vehicles n may be equal to 2. However, in some applications, the total number n may also be equal to 3, or may even take values ​​as high as 5 or more.

[0029] In one example, the control system 3 may be configured to cause the corresponding additional speed v i,lead The weighting of is adapted to the traffic situation involving vehicle 2 and at least two further vehicles 21, 22. This may involve making the corresponding weighting factors w iAdapt to traffic conditions. Set the corresponding additional speed v i,lead Adapting the weighting of the speeds to the traffic situation can be achieved by adapting the weighting of the other speeds according to the driving mode of the corresponding other leading vehicle. In this case, the traffic situation can be specified by the driving mode. The control system 3 can be configured to detect the driving mode based on the sensor data 200. In one example, the driving mode can be related to the distance between the leading vehicle and vehicle 2.

[0030] In one example, the respective driving modes may involve respective additional speeds v i,lead The corresponding fluctuations over time are also referred to as corresponding speed fluctuations in the following. The control system 3 may be configured to adjust the weighting of the further speeds such that the more constant the corresponding further speed is over time, the stronger or greater the amount by which the corresponding further speed is weighted. The control system 3 may be configured to adjust the corresponding weighting factor w i , so that the corresponding weighting factor w i There is a negative correlation between the increase of and the corresponding increase of speed fluctuation. In one example, the corresponding weighting factor w i It can be increased in proportion to the reduction of the corresponding speed fluctuations.

[0031] The corresponding velocity fluctuation, also referred to as ξ in the following formula, can be calculated in different ways i,lead According to one example, the control system 3 may be configured to calculate the respective speed fluctuation as a function of the respective absolute value of the respective difference between the respective average speed and the respective further speed of the respective leading vehicle as follows:

[0032] where v i,lead,m indicates the respective average speed of the respective leading vehicle i during the time interval starting from t1 and ending at t1. During the time interval, the sensor system 4 and the control system 3 detect the respective further speed v at various moments in time. i,lead To calculate the integral, a discretization method can be applied using these values. According to another aspect, the control system 3 can be configured to calculate the corresponding speed fluctuation ξ as follows i,lead :

[0033]

[0034] According to this aspect, a greater deviation of the respective further speed from the respective mean speed can influence the respective speed fluctuation ξ more strongly or to a greater extent than in the above-described example. i,lead According to another aspect, the control system 3 may be configured to calculate the corresponding speed fluctuation as follows:

[0035]

[0036] According to this aspect, the respective speed fluctuations can be calculated similarly to the respective standard deviations of the respective further speeds. This can allow using statistical methods and / or neural networks to control the ego speed 101 in an easier or more ideal manner.

[0037] The aspect for calculating the corresponding speed fluctuation described above may be used as an example only. However, independently of the aspect for calculating the corresponding speed fluctuation, the control system 3 may be configured to calculate the corresponding speed fluctuation such that the larger the corresponding speed fluctuation, the smaller the corresponding additional speed v i,lead More frequent and / or stronger deviations from the corresponding average speed v during the time interval i,lead,m .

[0038] According to one embodiment, the respective driving pattern may involve respective fluctuations over time of the respective acceleration of the respective further vehicle, hereinafter also referred to as respective acceleration fluctuations. According to this embodiment, the control system 3 may be configured to adjust the weighting of the further speed such that the more constant the respective acceleration over time, the more strongly or more the respective further speed is weighted.

[0039] Similarly to taking into account the change of other speeds, the control system 3 can be configured to adjust the corresponding weighting factor w i , so that the corresponding weighting factor w i There is a negative correlation between the increase of and the corresponding increase of acceleration fluctuation. In one example, the corresponding weighting factor w i It can be increased in proportion to the reduction of the corresponding acceleration fluctuations.

[0040] The corresponding acceleration fluctuation, also referred to as ψ in the following, can be calculated in different ways i,lead According to one example, the control system 3 may be configured to calculate the corresponding acceleration fluctuation as follows:

[0041] where a i,lead represents the corresponding acceleration, a i,lead,m represents the respective average acceleration of the respective leading vehicle i during the time interval starting at t1 and ending at t2. During the time interval, the respective acceleration a i,lead are detected by the sensor system 4 and the control system 3 or calculated by the control system 3 using the corresponding other speeds at various times. These detected values ​​can be used to calculate the last-mentioned integral by means of a discretization method.

[0042] According to another aspect, the control system 3 may be configured to calculate the corresponding acceleration fluctuations as follows:

[0043]

[0044] According to this aspect, a greater deviation of the respective acceleration from the respective mean acceleration can have a stronger influence on the value of the respective acceleration fluctuation than in the above-described example.

[0045] According to another aspect, the control system 3 may be configured to calculate the corresponding acceleration fluctuations as follows:

[0046]

[0047] According to this aspect, the respective acceleration variations can be calculated similarly to the respective standard deviations of the respective acceleration variations. This can allow the use of statistical methods and / or neural networks to control the ego speed 101 in an easier or ideal manner.

[0048] Independently of the aspect used to calculate the respective acceleration variations, the control system 3 can be configured to calculate the respective acceleration variations such that the respective acceleration variations deviate more, more frequently, and / or more strongly from the respective average acceleration during the time interval. The respective acceleration fluctuations can indicate the respective dynamic intensity of the respective leading vehicle.

[0049] According to the example, Figure 5 As shown, the control system 3 may be configured to perform the weighting of the respective further speeds according to the database 50. The database 50 may include respective weighting factors w for performing the weighting of the respective further speeds. i The database 50 may be stored in a memory module 51 of the control system 3. One or more processors 52 of the control system 3 may load the database 50 into a cache of the one or more processors 52 for performing weighting.

[0050] In one example, the control system 3 can use the database 50 to calculate the corresponding weighting factor w according to the input file 60 i ,like Figure 6 As shown. Input file 60 may include values ​​for at least one parameter describing the traffic situation. In most cases, input file 60 may include a set of values ​​describing the traffic situation. For example, input file 60 may include a corresponding distance from the corresponding leading vehicle to vehicle 2, a corresponding additional speed, a corresponding speed change, and / or a corresponding acceleration change.

[0051] The aforementioned corresponding relationship of the database 50 can be converted into the corresponding weighting factor w iis associated with a corresponding distance, a corresponding additional speed, a corresponding speed change and / or a corresponding acceleration change. The corresponding relationship can be provided in the form of a corresponding function. In one example, the respective functions can be implemented by a neural network. In this case, the database 50 may include data specifying the neural network, such as the number of hidden layers, the number of neurons in each layer, and the values ​​of the connection weights connecting these neurons to each other. Alternatively or in addition, the corresponding relationship can be provided in the form of a two-dimensional table with rows and columns and / or a three-dimensional table and / or a higher dimensional table. In one example, the database 50 can be configured so that a variety of different sets of corresponding functions can be provided according to the ego speed 101, so as to provide different functions for the weighting factors of different values ​​of the ego speed 101.

[0052] According to one aspect of the aforementioned method, the method may further include optimizing the database 50 based on previous traffic conditions of the vehicle 2 or the second vehicle. According to this aspect, the respective previous target speeds of the vehicle 2 or the second vehicle are determined based on the previous weighting of the respective speeds of a second further vehicle (not shown in the figure) ahead of the vehicle 2 or the second vehicle under the respective traffic conditions. The respective previous target speeds and the previous weightings may provide a further database. The further database may also include performance data of the vehicle 2 or the second vehicle, such as the average fuel consumption and / or average acceleration of the vehicle 2 or the second vehicle. The further database may be used for optimizing the database 50 and, therefore, for optimizing the respective functions. The optimization of the respective functions may be performed offline, for example, by an external server located outside the vehicle 2 or onboard the vehicle 2. The optimized database 50 may be sent to the control system 3 for storing the database 50 in the memory module 51. The optimization of the database 50 may be considered as training of a neural network, wherein the respective functions of the database 50 are implemented by the neural network.

[0053] In the following, it is assumed that a control loop is executed during a time period including several time intervals, including the aforementioned time interval. For each time interval, the corresponding speed fluctuation and / or corresponding acceleration fluctuation of each corresponding leading vehicle can be calculated in a similar manner as for the aforementioned time interval. In addition, the corresponding weighting factor w that can be used to calculate the target speed 100 during the corresponding time interval can be recalculated based on the corresponding speed fluctuation and / or corresponding acceleration fluctuation of the time interval before the corresponding time interval. i In one example, the lengths of the time intervals may be equal and may be in the range of 10 to 20 seconds or longer. The lengths of the time intervals may be determined by offline optimization on an external server.

[0054] According to actual test results, it is advantageous to consider a total number of three leading vehicles n when calculating target speed 100. This is likely due to the fact that, on the one hand, the optimization of the weighting factors becomes more complex as the total number of leading vehicles involved in calculating target speed 100 increases. On the other hand, if the total number n is two, the temporal variation of target speed 100 may still be significantly higher compared to applications where the total number n is three. Therefore, fuel consumption can be reduced less with a total number n of two than with an application where the total number n is three.

[0055] In one embodiment, control system 3 may be configured to perform weighting of the respective additional speeds when the respective relative distance is greater than the calculated ideal or effective following distance between vehicle 2 and the nearest leading vehicle and less than a predetermined threshold distance. Otherwise, i.e., in other circumstances, control system 3 may not perform weighting of the respective additional speeds as described above. Furthermore, control system 3 may be programmed not to perform weighting of the respective additional speeds of the respective additional vehicles that are further than the predetermined threshold distance, i.e., to disable weighting of the respective speeds in other circumstances. The predetermined threshold distance is greater than the calculated ideal or effective following distance and, in a non-limiting example, may be in the range of 200 to 400 meters. The predetermined threshold distance may be greater than 400 meters or less than 200 meters.

[0056] Disabling weighting of the respective other speeds of the respective other vehicles when the respective relative distances of the respective other vehicles are greater than a predetermined threshold distance can have the following advantage: a portion of the leading vehicle located further than the predetermined threshold distance can be discarded for calculating target speed 100. This can allow for controlling ego speed 101 with less computational effort and furthermore allow for more robust control of ego speed 101. Furthermore, disabling weighting when the distance between the nearest other vehicle and vehicle 2 is less than the calculated ideal or effective following distance can increase the desirability or effectiveness of driver assistance system 1. In this case, disabling weighting can allow the distance between the nearest other vehicle and vehicle 2 to be adjusted so that it becomes equal to or greater than the ideal or effective following distance as quickly as possible. This can be achieved by operating vehicle 2's conventional ACC system. In one example, the conventional ACC system can calculate the ideal or effective following distance based on the respective speeds of the nearest other vehicle and ego speed 101.

[0057] In one example, a conventional ACC system can be integrated into a driver assistance system. In one example, control system 3 can set target speed 100 such that target speed 100 is calculated as described above or equal to another target speed calculated by the conventional ACC system, whichever is smaller. This can further enhance the desirability or efficiency of driver assistance system 1. Conventional ACC systems can operate in different states, such as speed control mode or distance control mode. In one example, when the conventional ACC system operates in speed control mode, weighting is turned off, and when the conventional ACC system operates in distance control mode, weighting is turned on.

[0058] In another embodiment, the control system 3 can be configured to adapt the weighting of the additional speeds to the respective type of the respective other vehicle. For example, the control system 3 can perform the weighting of the additional speeds such that the larger the respective other vehicle, the more the additional speed of the respective vehicle is weighted. This can reduce fluctuations in the ego speed 101, as larger vehicles generally travel at a more constant speed.

[0059] While particular embodiments have been shown and described herein, it will be appreciated that various other changes and modifications may be made without departing from the spirit and scope of the claimed subject matter. Furthermore, while various aspects of the claimed subject matter have been described herein, these aspects need not be used in combination. Accordingly, the appended claims are intended to cover all such changes and modifications within the scope of the claimed subject matter.

Claims

1. A driver assistance system for controlling the speed of a vehicle based on at least two other vehicles ahead of the vehicle, the driver assistance system comprising: control systems; as well as a sensor system configured to detect a respective further speed of the respective further vehicle, Wherein, the control system is configured to: performing a weighting of the further speeds relative to one another and determining a target speed for the vehicle as a function of the respective further speeds and as a function of the weightings of the further speeds, and The speed of the vehicle is controlled according to the target speed.

2. The driver assistance system according to claim 1, wherein: The control system is further configured to adapt the weighting to traffic conditions involving the vehicle and the at least two further vehicles.

3. The driver assistance system according to claim 2, wherein: The traffic situation can be specified by a respective driving mode of the respective further vehicle, and the control system is further configured to adapt the weighting of the further speeds in dependence on the respective driving mode.

4. The driver assistance system according to claim 3, wherein: The respective driving pattern relates to a respective fluctuation of the respective further speed over time, and the control system is further configured to adjust a weighting of the further speed such that the more constant the respective further speed over time, the stronger the respective further speed is weighted.

5. The driver assistance system according to claim 3, wherein: The respective driving pattern relates to a respective fluctuation in a respective acceleration of the respective further vehicle over time, and the control system is further configured to adapt the weighting of the further speed such that the more constant the respective acceleration is over time, the stronger the respective further speed is weighted.

6. The driver assistance system according to claim 1, wherein: Traffic conditions relating to respective relative distances of the respective other vehicles to the vehicle; and The control system is further configured to perform the weighting of the respective additional speeds when the respective relative distance is greater than a calculated ideal following distance between the vehicle and the one of the additional vehicles closest to the vehicle and is less than a predetermined threshold distance, wherein the predetermined threshold distance is greater than the calculated ideal following distance.

7. The driver assistance system according to claim 1, wherein: The control system is further configured to adapt the weighting of the further speeds to the respective type of the respective further vehicle.

8. The driver assistance system according to claim 2, wherein: The control system is further configured to perform the weighting according to a database, wherein the database comprises a respective relationship between a respective weighting factor for performing the weighting of the respective further speed and at least one parameter for describing the traffic situation.

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