Method for adapting a selection distance

Abstract

The invention relates to a method for adapting a selection distance (d1) of a driver assistance system (104) for a vehicle (100), which comprises at least one first sensor (106, 108) for detecting surroundings (102) of the vehicle (100) and a second sensor (212) for determining a position of the vehicle (100), wherein the driver assistance system (104) is designed to control the vehicle (100) depending on the selection distance (d1), wherein the method comprises the steps of: a) determining (S400) a value for the selection distance (d1), the selection distance (d1) corresponding at most to a detection distance (d2) of the first sensor (106, 108); b) receiving (S401) map data (220), the map data (220) comprising at least one carriageway course of a carriageway (300, 300', 300'') of the vehicle (100) in a direction of travel; and c) adapting (S402) the value of the selection distance (d1) depending on the map data (220) and the position of the vehicle (100).

Description

[0001] 2024PF00829

[0002] 1

[0003] METHOD FOR ADJUSTING A SELECTION DISTANCE

[0004] The present invention relates to a method for adjusting a selection distance. Furthermore, the present invention relates to a computer program product, a device, a driver assistance system, and a vehicle.

[0005] Driver assistance systems in modern vehicles are designed to influence the vehicle's driving behavior, for example by adjusting speed or acceleration. Conventional driver assistance systems rely on data from the vehicle's surroundings, which is collected by various sensors, such as front cameras.

[0006] This environmental data typically includes lanes, road markings, traffic signs, and other road users. A vehicle ahead serves as a reference point for adapting the driving style. The driver assistance system continuously selects this vehicle based on a predefined distance using the provided environmental data.

[0007] To minimize errors in selecting the vehicle ahead in certain driving situations, such as when cornering, the preset distance is set to a conservative value at the factory. This value is less than the theoretically maximum possible range of the driver assistance system's sensors. This compromise aims to increase reliability in selecting the vehicle ahead and to avoid incorrect decisions. This limitation of the driver assistance system means that not all driving situations can be handled by the system with the same level of safety and comfort.

[0008] US patent 2004 / 0016870 A1 discloses an imaging system for a vehicle. The imaging system comprises an image sensor and a controller. The image sensor serves to detect a 2024PF00829

[0009] 2

[0010] The system captures an image of a scene outside the vehicle. The control unit receives the captured image, which represents a representative image dataset of the external scene. The control unit can apply an edge detection algorithm to a reduced image dataset. This reduced image dataset is representative of a target zone of the captured image. The control unit can be configured to process the reduced image dataset more intensively than other image data, which is representative of areas of the captured image outside the target zone, in order to detect objects present within the target zone. The imaging system can be integrated with a side object detection system, a lane change assist system, a lane departure warning system, and / or similar systems.

[0011] Against this background, one object of the present invention is to improve the selection of a selection distance of a driver assistance system for a vehicle.

[0012] According to a first aspect, a method for adjusting the selection distance of a driver assistance system for a vehicle is proposed, comprising at least a first sensor for detecting the vehicle's surroundings and a second sensor for determining the vehicle's position. The driver assistance system is configured to control the vehicle depending on the selection distance. The method comprises the steps: a) determining a value for the selection distance, where the selection distance corresponds at most to the detection distance of the first sensor; b) receiving map data, where the map data includes at least one lane of the vehicle in one direction of travel; and c) adjusting the value of the selection distance depending on the map data and the vehicle's position.

[0013] This allows the risk of incorrectly selecting a vehicle ahead, depending on the driving situation (e.g., when cornering), to be minimized by adjusting the selection distance value, regardless of the detection distance of the first sensor. 2024PF00829

[0014] 3

[0015] The vehicle may be equipped with or include the driver assistance system. The vehicle that includes or is equipped with the driver assistance system is referred to below as the Ego vehicle.

[0016] For example, the selection distance is the maximum distance up to which a vehicle ahead of the ego vehicle or a lead vehicle can be selected. For instance, the ego vehicle's driving style is adapted to the selected lead vehicle. This adaptation can be achieved using the driver assistance system. The ego vehicle's driving style includes, for example, its current acceleration and / or speed.

[0017] The driver assistance system includes, for example, adaptive cruise control (ACC), emergency braking assist, a collision warning system, and / or lane departure warning. The driver assistance system can, in particular, adapt the driving style of the Ego vehicle by controlling it.

[0018] The driver assistance system can include sensors, such as the first sensor and the second sensor. In some examples, the first sensor and the second sensor are integrated into the ego vehicle, and information gathered by the first and second sensors is provided to the driver assistance system. For example, the first sensor can be configured as a group of multiple sensors. The sensors can be mounted on the exterior of the ego vehicle. In particular, the sensors of the first sensor are distributed across the exterior of the ego vehicle. For example, the second sensor can comprise multiple sensors that can be configured to detect the driving style of the ego vehicle.

[0019] The Ego vehicle, for example, is a vehicle that drives at least partially automatically, with the driver assistance system enabling a degree of automation, for example according to the SAE automation levels. 2024PF00829

[0020] 4

[0021] For example, the selection distance value is determined by setting a default value. This default value can be selected from a plurality of values. For instance, the default value is selected from a lookup table containing a large number of values. The lookup table can be stored on a memory module of the ego vehicle. The selection distance value specifically defines the maximum distance within which an object, such as the lead vehicle ahead, can be selected. In particular, an initial selection distance value is determined from the lookup table based on the current driving behavior of the ego vehicle, such as its speed or acceleration.

[0022] The detection distance is, in particular, the maximum distance at which the first sensor can detect the ego-vehicle's surroundings. For example, the detection distance depends on the characteristics of the first sensor. These characteristics include, for example, image resolution, field of view, dynamic range, frame rate, sensor size, light sensitivity, range, and / or frequency range. The detection distance can also be affected by the ego-vehicle's environment. For example, the detection distance is influenced by a dark environment, a bright environment, reflections or glare, obstacles in the environment, weather conditions, the reflective properties of an object, and / or the ambient temperature.

[0023] The map data can be provided, for example, using a storage module in the ego vehicle. This storage module can be part of the driver assistance system. "Receiving map data" includes, for example, loading the map data from the storage module and / or providing the map data to a server via a wireless connection.

[0024] The direction of travel of the ego vehicle is specifically the direction in which the ego vehicle is moving. 2024PF00829

[0025] 5

[0026] The roadway can be the roadway on which the ego-vehicle is located. For example, the map data includes the roadway layout of future roads for the ego-vehicle. For example, the roadway on which the ego-vehicle is located is determined using the second sensor.

[0027] "Adjusting the selection distance value" includes, for example, selecting the selection distance value from a variety of options and setting the selection distance to the selected value. In particular, the variety of options can be provided by the aforementioned lookup table. For example, when adjusting the selection distance, a value is calculated based on the road surface and / or the map data.

[0028] For example, the position of the ego-vehicle is set in relation to the map data. Specifically, the map data is received based on the ego-vehicle's position. The received map data includes, in particular, the ego-vehicle's position and its surrounding area.

[0029] According to one embodiment, an initial value is specified, which is a lower limit for determining in step a) and for adjusting in step c) the value of the selection distance.

[0030] The initial value is chosen, for example, to prevent the ego vehicle from being incorrectly selected in every situation. This incorrect selection could include vehicles in lanes other than the ego vehicle's lane, objects at the roadside, and / or objects outside the lane.

[0031] For example, the initial value is a value set before the Ego vehicle is put into operation, for instance, during a development phase. The initial value is, in particular, a minimum limit for the value of 2024PF00829.

[0032] 6

[0033] Selection distance. For example, the selection distance value in operation can take on values ​​between the initial value and the detection distance.

[0034] According to one embodiment, the roadway includes at least one straight section and / or at least one curve. This allows the selection distance to be adjusted depending on the specific roadway.

[0035] In particular, the road curvature has a start, an end, and a radius of curvature. For example, the road alignment can include information about traffic volume and / or construction sites, especially roadworks and motorway construction sites. For example, the selection distance value in step c) is adjusted depending on the radius of curvature.

[0036] According to one embodiment, the value of the selection distance in step c) is adjusted before a specific change in the road course that is outside the detection distance of the first sensor.

[0037] This adjusts the value for the selection distance before a change, for example from the straight section of road to the curved section of road, is within the detection distance.

[0038] According to one embodiment, the specific change includes a change from the straight section of roadway to the curve of the roadway and / or from the curve of the roadway to the straight section of the roadway.

[0039] For example, a boundary is defined at the specific change, with the boundary separating the straight section of the roadway from the roadway curve. In particular, the boundary is determined using map data. The boundary is preferably the beginning and / or the end of the roadway curve. 2024PF00829

[0040] 7

[0041] According to one embodiment, the value for the selection distance is adjusted to a value between the initial value and the detection distance in the case of a change to the straight section of the road, and adjusted to the initial value in the case of a change to the curvature of the road.

[0042] This helps avoid incorrect selections, especially when cornering. Similarly, on straight stretches of road, the selection distance can be set higher than the initial value. This allows the ego vehicle's driving style to be adjusted early when driving at high speeds and high relative speeds between the ego vehicle and the lead vehicle, thus increasing safety.

[0043] According to one embodiment, the vehicle is controlled by the driver assistance system depending on the environment detected by the first sensor and the adjusted value for the selection distance according to step c).

[0044] For example, the driver assistance system is designed to adapt the driving style of the ego vehicle depending on the selected distance. Specifically, the driver assistance system adapts the driving style of the ego vehicle when it is driving on a highway, particularly a multi-lane highway, country road, and / or motorway. For example, when activated, the driver assistance system controls the ego vehicle.

[0045] According to one embodiment, the first sensor comprises a camera, in particular a front camera, a lidar sensor and / or a radar sensor, and the second sensor comprises a GPS receiver and / or an inertial measuring unit.

[0046] For example, multiple sensors can simultaneously capture the environment, with one environment being generated from a multitude of environments captured by the sensors. 2024PF00829

[0047] 8

[0048] Similarly, the ego vehicle can include the GPS receiver and the inertial measurement unit and combine information from these two sensors. This allows information from the GPS receiver or the inertial measurement unit to be validated and / or supplemented using the inertial measurement unit or the GPS receiver.

[0049] According to one embodiment, the map data in step b) is provided according to the ADASIS v2 protocol and / or the ADASIS v3 protocol.

[0050] The ADASIS v2 and ADASIS v3 protocols are widely used standards. This allows map data to be provided regardless of the manufacturer.

[0051] For example, the adasisV3 protocol extends the information available in the ADASIS v2 protocol.

[0052] According to one embodiment, the map data is provided by means of a vehicle provisioning unit.

[0053] The deployment unit can, for example, include the aforementioned storage module. Furthermore, the deployment unit can include another module configured to update the map data.

[0054] According to a second aspect, a computer program product is proposed with instructions which, when executed by a control unit of the vehicle, cause the control unit to execute the procedure according to the first aspect or an embodiment of the first aspect.

[0055] A computer program product, such as a computer program tool, can be stored, for example, as a storage medium or storage unit, such as a memory card, USB stick, CD-ROM, DVD, SSD, RAM, ROM, EPROM, EEPROM, or in the form of a downloadable file.2024PF00829

[0056] 9

[0057] provided or delivered by a server in a network. This can be done, for example, in a wireless communication network by transmitting a corresponding file with the computer program product or the computer program tool.

[0058] According to a third aspect, a device for adjusting the selection distance of a driver assistance system for a vehicle is proposed. This device comprises at least a first sensor for detecting the vehicle's surroundings and a second sensor for determining the vehicle's position. The driver assistance system is configured to control the vehicle depending on the selection distance. The device includes: a determination unit for determining a value for the selection distance, wherein the selection distance corresponds at most to the detection distance of the first sensor; a receiving unit for receiving map data, wherein the map data includes at least one lane of the vehicle in one direction of travel; and an adjustment unit for adjusting the selection distance value depending on the map data and the vehicle's position.

[0059] The respective unit can be implemented in hardware and / or software. In a hardware implementation, the respective unit can, for example, be a computer or a microprocessor. In a software implementation, the respective unit can be a computer program, a function, a routine, an algorithm, a part of program code, or an executable object. Furthermore, each of the aforementioned units can also be part of a higher-level control system of the Ego vehicle, such as a central electronic control unit (ECU) and / or an engine control unit.

[0060] According to one embodiment, the device further comprises a detection unit for recognizing objects within the detection distance from the environment detected by the first sensor. 2024PF00829

[0061] 10

[0062] For example, with the help of the detection unit, objects located within the environment, such as the lead vehicle, can be detected from the environment detected with the help of the first sensor.

[0063] According to a fourth aspect, a driver assistance system is proposed with a device according to the third aspect or according to an embodiment of the third aspect.

[0064] According to a fifth aspect, a vehicle with a driver assistance system is proposed according to the fourth aspect.

[0065] The embodiments and features described for the proposed method apply accordingly to the proposed device, the proposed driver assistance system and the proposed vehicle, and vice versa.

[0066] Other possible implementations of the invention also include combinations of features or embodiments described previously or subsequently with regard to the exemplary embodiments, even if not explicitly mentioned. In such cases, the person skilled in the art will also add individual aspects as improvements or additions to the respective basic form of the invention.

[0067] Further advantageous embodiments and aspects of the invention are the subject of the dependent claims and the exemplary embodiments of the invention described below. The invention will be explained in more detail below with reference to preferred embodiments and the accompanying figures.

[0068] Fig. 1 schematically shows a top view of a vehicle;

[0069] Fig. 2 schematically shows a view of a driver assistance system and other components of a vehicle; 2024PF00829

[0070] 11

[0071] Fig. 3 shows in Fig. 3a) - Fig. 3c) several vehicles on different sections of the roadway; and

[0072] Fig. 4 shows steps of a procedure for adjusting a selection distance.

[0073] In the figures, identical or functionally equivalent elements have been given the same reference symbols, unless otherwise indicated.

[0074] Fig. 1 shows a schematic bird's-eye view of an ego-vehicle 100. The ego-vehicle 100 is, for example, a passenger car or truck located in an environment 102. The ego-vehicle 100 has a driver assistance system 104, which can be implemented, for example, by an electronic control unit (ECU). The driver assistance system 104 is designed to control the movement of the ego-vehicle 100. In addition, several environmental sensors 106, 108 are arranged on the ego-vehicle 100. These include, for example, optical sensors 106 and ultrasonic sensors 108. The optical sensors 106 include, for example, visual cameras, radar, and / or lidar. The optical sensors 106 can each capture an image of a respective area from the environment 102 of the ego-vehicle 100 and output it as a sensor signal.The ultrasonic sensors 108 are configured to detect the distance to objects in the environment 102 and output a sensor signal. The sensor signal is received and processed by the driver assistance system 104 to control the movement of the Ego vehicle 100.

[0075] For example, the Ego vehicle 100 can exhibit a level of automation according to the SAE classification system. The SAE classification system was published in 2014 by SAE International, a standards organization for motor vehicles, as J3016 "Taxonomy and Definitions for Terms Related to On-Road Motor Vehicle Automated Driving Systems." It is based on six different levels of automation and considers the degree of system intervention required and the driver's attention. [The2024PF00829]

[0076] 12

[0077] SAE automation levels range from a fully manual system (Level 0), through driver assistance systems of Levels 1 and 2, to semi-autonomous (Levels 3 and 4) and fully autonomous (Level 5) systems, where no driver is required. An autonomous vehicle (also known as a driverless car, self-driving car, and robot car) is a vehicle that can perceive its surroundings and navigate without human input, and it corresponds to SAE automation level 5.

[0078] The Driver Assistance System 104 is configured to implement automated driving functions to provide a level of automation as described above, where the level of automation can be any level from Level 1 to Level 5. For example, the Driver Assistance System 104 is configured to provide one or more of the following functions: Adaptive Cruise Control (ACC), Lane Keeping Assist (LKA), Automatic Emergency Braking (AEB), Automatic Emergency Steering (AES), Traffic Jam Assist (TJA), Highway Driving Assist (HWA), and / or Traffic Jam Pilot (TJP).

[0079] Fig. 2 schematically shows a detailed view of the driver assistance system 104 and its components. The driver assistance system 104 comprises a device 200 for adjusting a selection distance d1 (see Fig. 3), which in turn includes a recognition unit 202, a determination unit 204, a receiving unit 206, and an adaptation unit 208.

[0080] The adaptation unit 208 comprises the determination unit 204 and a first memory module 210. A table, for example, is stored on the first memory module 210. This table lists values ​​that the selection distance d1 can assume. The adaptation unit 208 can access the table on the first memory module 210 and use the table to adjust the value of the selection distance d1. Initially, the value of the selection distance d1 is determined using the determination unit 204. For example, the determination unit 204 determines the selection distance d1 based on the current speed of the ego vehicle 100. If the ego vehicle 100 is traveling at a high speed, the 2024PF00829

[0081] 13

[0082] The selection distance d1 from the determining unit 204 is also chosen to be high. At low speeds of the Ego vehicle 100, the determining unit 204 chooses a low value for the selection distance d1.

[0083] Furthermore, the driver assistance system 104 includes a second sensor 212, which is, for example, a GPS receiver and can detect the current position of the ego vehicle 100. The driver assistance system 104 also has a deployment unit 214. The deployment unit 214 comprises a second memory module 216 and a radio module 218. Map data 220 is stored on the second memory module 216. The radio module 218 is configured to update the map data 220, for example, via an internet connection to a server (not shown in Fig. 2) established using the radio module 218.

[0084] Furthermore, the driver assistance system 104 includes a controller 222. The controller 222 receives a value for the selection distance d1 from the adaptation unit 208 and outputs a control signal to a powertrain 224 of the ego vehicle 100, whereby the powertrain 224 adapts the driving behavior, for example the speed or acceleration, of the ego vehicle 100 depending on the control signal.

[0085] The functions of the previously introduced components of the driver assistance system 104 are described below with the aid of Fig. 3a) - Fig. 3c).

[0086] Figures 3a) - 3c) show sections of lanes 300, 300' and 300" respectively. A top view of the ego vehicle 100 is shown on lanes 300, 300' and 300" respectively, traveling on the two-lane lane. A lead vehicle 302 is traveling in the same lane as the ego vehicle 100, preceding it. Another vehicle 304 is located in a second lane of lanes 300, 300' and 300" respectively.

[0087] 14

[0088] The Ego vehicle 100 is equipped with the driver assistance system 104 described above. In Figures 3a) - 3c), the driving style of the Ego vehicle 100 is controlled by the driver assistance system 104.

[0089] In Fig. 3a), the ego-vehicle 100 is traveling on a straight section of road 306. For this purpose, the front camera 106 detects the surroundings 102 within a circular segment-shaped distance, shown as dotted lines in Figs. 3a) - 3c), up to a detection distance d2. The detection distance d2 is the distance, starting from the current position of the ego-vehicle 100, up to which the front camera 106 can detect the surroundings 102. The detection distance d2 depends on the characteristics of the front camera 106 and the conditions of the surroundings 102.

[0090] The environment 102 captured by the front camera 106 is transmitted as a signal to the detection unit 202 (see Fig. 2). The detection unit 202 detects objects within the detection distance d2, such as the lead vehicle 302 and the other vehicle 304. The detected objects are provided as a signal to the adaptation unit 208.

[0091] The deployment unit 214 receives the current position of the ego vehicle 100 from the second sensor 212. Depending on the current position, the deployment unit 214 provides the map data 220, which is received as a signal by the receiving unit 206. The receiving unit 206 receives the map data 220, for example, according to the ADASIS v2 protocol. According to the ADASIS v2 protocol, the receiving unit 206 receives information about a curvature of the roadway 300, for example, the beginning of the curvature, the end of the curvature, and the radius of curvature. Since the ego vehicle 100 is currently moving on the straight section of roadway 306, the receiving unit 206 also provides this information to the adaptation unit 208.

[0092] The determination unit 204 determines an initial value for the selection distance d1. The value determined by the determination unit 204 depends on the current speed of the 2024PF00829

[0093] 15

[0094] The Ego vehicle's specific value of 100 can, in the case of a high current speed, correspond to the detection distance d2. At a minimum, the first value corresponds to an initial value d3. The initial value d3 is factory preset and represents a minimum value for the selection distance d1.

[0095] When the driver assistance system 104 is in operation and the signals from the detection unit 202 and the receiver unit 206 are provided to the adaptation unit 208, the adaptation unit 208 adjusts the value for the selection distance d1. To do this, it accesses the first memory module 210 and the table stored therein. The table contains values ​​for the selection distance d1, with the values ​​lying between the initial value d3 and the value of the detection distance d2. The adaptation unit 208 selects a value from the table depending on the current position, provided by the second sensor 212, and the map data 220. In Fig. 3a), the ego vehicle 100 is on the straight section of road 306. Accordingly, the adjusted value d1, provided by the adaptation unit 208, corresponds to the detection distance d2 previously determined by the determination unit 204.

[0096] Depending on the selected selection distance d1, the device 200 selects the lead vehicle 302 and provides this information as a signal to the controller 222. The controller 222 then adjusts the driving behavior of the ego vehicle 100 to that of the lead vehicle 302.

[0097] For example, the ego vehicle 100 and the lead vehicle 302 are traveling at high speed on lane 300 (highway driving), with the speed of the ego vehicle 100 being greater than the speed of the lead vehicle 302. Because the selection distance d1 is chosen to be equal to the detection distance d2, i.e., equal to the maximum possible selection distance d1, the lead vehicle 302 can be selected early as the target object to which the driving behavior of the ego vehicle 100 should be adapted. Accordingly, when the ego vehicle 100 approaches the lead vehicle 302, the driver assistance system 104 can adjust the speed of the ego vehicle 2024PF00829

[0098] 16

[0099] 100 adjusts by sending a corresponding signal from the controller 222 to the drive train 224.

[0100] In Fig. 3b), the ego vehicle 100 is traveling on a straight section of road 306' on lane 300'. At a distance greater than the detection distance d3, the straight section of road 306' transitions into a curve 308. As previously described, the selection distance d1 is adjusted by the adaptation unit 208. In Fig. 3b), a change in lane 310 is not within the detection distance d2 and therefore cannot be detected by the front camera 106. The map data 220 received by the receiver unit 206 contains the information about the change in lane 310 and transmits this information to the adaptation unit 208. The adaptation unit 208 receives information about the change in the roadway 310 and the current position of the ego vehicle 100. The adaptation unit 208 then adjusts the value of the selection distance d1 with a value from the table of the first memory module 210.

[0101] Since the roadway 300' transitions from the straight roadway section 306' to the roadway curve 308, the value of the selection distance d1 is reduced compared to the previously described journey on the straight roadway section 306 in Fig. 3a). For example, the value for the selection distance d1 is adjusted by the adaptation unit 208 to equal the initial value d3. To do this, the value for the selection distance d1, which was determined by the determination unit 204 based on the driving behavior of the ego vehicle 100, is overwritten by the adaptation unit 208.

[0102] Since the adaptation unit 208 receives the current position of the ego vehicle 100 and the map data 220 as input, the selection distance d1 can be adjusted shortly before the road surface changes 310. To do this, the adaptation unit 208 relates the beginning of the road curvature to the current position of the ego vehicle 100. By adjusting the selection distance d1 before the road surface change 310 enters the detection distance d1 range, incorrect selections during cornering are avoided. 2024PF00829

[0103] 17

[0104] In Fig. 3c), the ego vehicle 100 is shown during such a journey on a road curve 308'. If the selection distance d1 were chosen to be equal to the recognition distance d2, as in Fig. 3a), the driver assistance system 104 would incorrectly select the other vehicle 304 in the second lane as the vehicle ahead and adjust the driving behavior of the ego vehicle 100 accordingly. After traversing the road curve 308', the adaptation unit 208 adjusts the selection distance d1 again before a further change in the road (not shown in Fig. 3a) - Fig. 3c).

[0105] By adjusting the selection distance d1, the safety and driving comfort of the driver and other vehicle occupants can be ensured depending on the driving situation during a journey on the straight road section 306, 306' as well as during driving over the road curve 308, 308'.

[0106] Fig. 4 shows steps S400 - S402 of a method for adjusting the selection distance d1. In step S400, a value for the selection distance d1 is determined using the determination unit 204, where the selection distance d1 corresponds at most to the detection distance d2 of the first sensor 106, 108.

[0107] In step S401, the receiving unit 206 receives the map data 220, wherein the map data 220 includes at least one lane profile of the lane 300, 300', 300" of the Ego vehicle 100 in one direction of travel.

[0108] In step S402, the adaptation unit 208 adjusts the value of the selection distance d1 depending on the map data 220 and the position of the ego vehicle 100.

[0109] Although the present invention has been described using exemplary embodiments, it can be modified in many ways. 2024PF00829

[0110] 18

[0111] For example, the selection distance d1 is adjusted to a value between the detection distance d2 and the initial value d3. Specifically, initial value d3 < selection distance d1 < detection distance d2. For example, the selection distance d1 is continuously adjusted as the ego vehicle 100 approaches the change in lane 310. For example, the selection distance d1 is adjusted while traversing lane curve 308' depending on the radius of the lane curve 308'. Alternatively, map data 220 can also be provided using the ADASIS v3 protocol. The ADASIS v3 protocol can be used in addition to the ADASIS v2 protocol. For example, radio module 218 can be used to update map data 220 and / or to supplement map data 220 with current traffic conditions, such as traffic volume and / or lane obstructions.Alternatively, the map data 220 can be provided via the radio module 218 instead of being stored on the memory module 216. For example, the second sensor 212 is an inertial measurement unit that measures the driving behavior of the ego vehicle 100 and provides it to the device 200 and the provisioning unit 214. For example, the second sensor 212 combines the inertial measurement unit and the GPS receiver. For example, the value for the selection distance d1 is calculated according to a formula as a function of the radius of the road curvature 308, 308'. In another embodiment, the recognition unit 202 can be included by the front camera 106. 2024PF00829.

[0112] 19

[0113] REFERENCE MARK LIST

[0114] 100 Ego vehicles

[0115] 102 surroundings

[0116] 104 Driver assistance system 106 Optical sensor

[0117] 108 Ultrasonic sensor

[0118] 200 Device

[0119] 202 Recognition unit

[0120] 204 Unit of determination

[0121] 206 Receiving unit

[0122] 208 Adjustment unit

[0123] 210 first memory module 212 second sensor

[0124] 214 Deployment unit 216 Second storage module 218 Radio module

[0125] 220 maps

[0126] 222 regulators

[0127] 224 Powertrain

[0128] 300, 300', 300" lane

[0129] 302 Command vehicle

[0130] 304 more vehicles

[0131] 306, 306' straight section of road 308, 308' curve of road

[0132] 310 Change of the roadway

[0133] d1 selection distance

[0134] d2 detection distance

[0135] d3 initial value 2024PF00829

[0136] 20

[0137] S400 - S402 Procedure steps

Claims

2024PF00829 21 PATENT CLAIMS 1. Method for adjusting a selection distance (d1) of a driver assistance system (104) for a vehicle (100), which includes at least a first sensor (106, 108) for detecting an environment (102) of the vehicle (100) and a second sensor (212) for determining a position of the vehicle (100), wherein the driver assistance system (104) is configured to control the vehicle (100) depending on the selection distance (d1), the method comprising the steps: a) Determining (S400) a value for the selection distance (d1) where the selection distance (d1) corresponds at most to a detection distance (d2) of the first sensor (106, 108); b) Receiving (S401) map material (220), wherein the map material (220) includes at least one lane profile of a lane (300, 300', 300") of the vehicle (100) in one direction of travel; and c) Adjusting (S402) the value of the selection distance (d1) depending on the map data (220) and the position of the vehicle (100).

2. Method according to claim 1, wherein an initial value (d3) is specified which is a lower limit for determining in step a) and for adjusting in step c) the value of the selection distance (d1).

3. Method according to one of claims 1 or 2, wherein the roadway comprises at least one straight roadway section (306, 306') and / or at least one roadway curve (308, 308').

4. Method according to one of claims 1 to 3, wherein the value of the selection distance (d1) in step c) is adjusted before a certain change (310) of the road course located outside the detection distance (d2) of the first sensor (106, 108).

5. Method according to claim 4, wherein the specific change (310) is a change from the straight roadway section (306, 306') to the roadway curvature (308, 308') and / or 2024PF00829 22 encompasses the road curvature (308, 308') to the straight road section (306, 306').

6. Method according to claim 5, wherein the value for the selection distance (d1) is adjusted to a value between the initial value (d3) and the detection distance (d2) in the case of a change to the straight road section (306, 306'), and is adjusted to the initial value (d3) in the case of a change to the road curvature (308, 308').

7. Method according to one of claims 1 to 6, wherein the vehicle (100) is controlled by means of the driver assistance system (104) depending on the environment (102) detected by the first sensor (106, 108) and the adapted value for the selection distance (d3) according to step c).

8. Method according to any one of claims 1 to 7, wherein the first sensor (106, 108) comprises a camera, in particular a front camera, a lidar sensor and / or a radar sensor and the second sensor (212) comprises a GPS receiver and / or an inertial measuring unit.

9. Method according to any one of claims 1 to 8, wherein the map material (220) is provided in step b) according to the ADASIS v2 protocol and / or the ADASIS v3 protocol.

10. Method according to any one of claims 1 to 9, wherein the map material (220) is provided by means of a provisioning unit (214) of the vehicle (100).

11. Computer program product with instructions which, when executed by a control unit (104) of the vehicle (100), cause the control unit (104) to perform the method according to any one of claims 1 to 10.

12. Device (200) for adjusting a selection distance (d1) of a driver assistance system (104) for a vehicle (100) which has at least one first sensor (106, 108) for the 2024PF00829 23 The device (200) comprises: a sensor for detecting the environment (102) of the vehicle (100) and a second sensor (212) for determining the position of the vehicle (100), wherein the driver assistance system (104) is configured to control the vehicle (100) depending on the selection distance (d1), and wherein the device (200) comprises: a determination unit (204) for determining a value for the selection distance (d1), wherein the selection distance (d1) corresponds at most to a detection distance (d2) of the first sensor (106, 108); a receiving unit (206) for receiving map material (220), wherein the map material (220) comprises at least one lane profile of a carriageway (300, 300', 300") of the vehicle (100) in one direction of travel; and an adjustment unit (208) for adjusting the value of the selection distance (d1) depending on the map material (220) and the position of the vehicle (100).

13. Device (200) according to claim 12, further comprising a detection unit (202) for detecting objects (302, 304) within the detection distance (d1) from the environment (102) detected by the first sensor (106, 108).

14. Driver assistance system (104) with a device (200) according to claim 12 or 13.

15. Vehicle (100) with a driver assistance system (104) according to claim 14.

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