System for creating a vehicle environment model

Abstract

The system for creating a vehicle environment model is connected or can be connected to: a navigation unit, which is equipped to provide information about the instantaneous position of the vehicle and information about the road segment in front of the vehicle in time and space, and to provide the information in a digital map format and / or in absolute position information; an interface, which is equipped to communicate with the objects to be merged in the surroundings of the vehicle, the information received by the interface including the absolute position information about the objects to be merged; and / or a sensor unit, which is equipped to detect the objects to be merged in the surroundings of the vehicle and provide relative position information about the objects to be merged relative to the vehicle. The system determines the geometry of the road segment in front of the vehicle by using the information about the road segment in front of the vehicle provided by the navigation unit, and merges the absolute and / or relative position information about the objects to be merged with the information in the digital map format provided by the navigation unit based on the road geometry determined thereby to create a vehicle surrounding environment model.

Description

Background Art

[0001] Methods and systems for creating a vehicle surroundings model for the vehicle surroundings are presented herein. Various sensors and information sources are used in vehicles to meet the complex requirements of driver assistance systems and driverless vehicles. These sensors include, for example, one or more cameras, radar sensors and lidar sensors. In addition, the vehicle can also receive information from the cloud or from communication with other objects. Communication between vehicles and objects is often also referred to as "vehicle-to-everything communication" (V2X). The term refers to the communication between a vehicle and objects that the vehicle is in contact with. Therefore, the term includes the communication of a vehicle with other vehicles, with infrastructure objects and with people (pedestrians). Infrastructure objects can include, for example, traffic lights, traffic signs, mobile and fixed road edge markings, buildings, signs and billboards. In addition, information from digital maps also plays an increasingly important role as a data source. For example, information about road topology, speed limits, traffic signs and the slope and curvature of the road can be stored in a digital map. In addition, there are so-called HD maps, which contain information about the road route and additional data with very high accuracy. In addition, information that cannot be detected by conventional vehicle sensors can be stored in the digital map. For example, the gradient and curvature of the road can be read out from a map so that the driving dynamics can be adjusted automatically.

[0002] Prior art

[0003] DE 10 2014 111 126 A1 discloses a method for creating an environment map of an area surrounding a motor vehicle. By means of sensor devices in / on the motor vehicle, objects in the surrounding area can be detected, wherein position values ​​describing the position of the objects are determined by a control device of the motor vehicle based on data from the sensors. The position values ​​thus determined are transmitted to a map of the surroundings, wherein a vector between the object and a predetermined reference point of the motor vehicle is determined, thereby forming the origin of a vehicle coordinate system. The vector determined in the vehicle coordinate system is transformed into a global coordinate system of a map of the vehicle surroundings, and a position value in the map of the vehicle surroundings is determined based on the transformed vector.

[0004] US 2017 / 371349 A1 discloses a vehicle control device including a communication unit. The communication unit detects location information on the vehicle and can communicate with an external server and another vehicle. A processor controls the communication unit to receive map information from the external server and to receive location information about the other vehicle from the other vehicle. The processor combines the detected location information about the vehicle and the received location information about the other vehicle with the received map information so as to control the vehicle based on the combined information. Summary of the invention

[0005] Target

[0006] Against this background, the present disclosure relates to the object of providing an improved system and an improved method for creating a model of a vehicle's surroundings, with which position information in different formats can be merged to create a model of the vehicle's surroundings, regardless of the density of the available information.

[0007] Proposed technical solution

[0008] A system for creating a vehicle surroundings model is proposed as a technical solution. The system for creating a vehicle surroundings model is associated with at least one navigation unit, at least one interface and / or at least one sensor unit. The at least one navigation unit is equipped to provide information about the instantaneous position of the vehicle and information about at least one road segment in front of the vehicle in space and time, wherein the navigation unit provides information in a digital map format and / or in absolute position information. The at least one interface is equipped to communicate with at least one object to be merged in the vehicle surroundings, wherein the information received by the interface includes absolute position information about at least one object to be merged. The at least one sensor unit is equipped to detect at least one object to be merged in the vehicle surroundings, wherein the at least one sensor unit is also equipped to provide relative position information about at least one object to be merged relative to the vehicle. The system is equipped to determine the road geometry of the road segment in front of the vehicle by using the information about the road segment in front of the vehicle provided by the at least one navigation unit, wherein the system is equipped to merge the absolute position information and / or relative position information about at least one object to be merged with the information provided by the at least one navigation unit in a digital map format based on the road geometry determined thereby, so as to create a model of the vehicle's surroundings.

[0009] In the present disclosure, information from a digital map (eg, information about the instantaneous position of the vehicle and information about a road section in front of the vehicle) is referred to as information in a digital map format.

[0010] It is possible to merge information from various information sources, such as digital maps in the vehicle, data from the cloud, V2X and information from sensor units (cameras, radars, etc.). By using this merged information, it is possible to create a model of the surrounding environment populated by all these sources. Driver assistance systems and systems for driverless vehicles can access this merged model of the surrounding environment. Using the proposed system, it is possible to merge information from various information sources even if the data density is relatively low (i.e. there are relatively few objects or points with known position information on the road segment in front of the vehicle). Since the proposed system can determine the geometry of the road segment in front of the vehicle, the information itself can be merged based on the road geometry determined thereby, even if the data density of this section of road in front of the vehicle is relatively low.

[0011] For example, relative position information may be provided by sensor units such as camera units, radar units, and ultrasonic sensor units. Examples of such relative position information from various units include:

[0012] - Radar unit: distance and optional angle to objects in front of the vehicle

[0013] - Camera unit: distance to traffic signs, traffic lights and pedestrians

[0014] - Ultrasonic sensor unit: distance to vehicles in parallel lanes

[0015] For example, absolute position information (eg, in world coordinates) may be transmitted by objects such as traffic lights, traffic signs, and the like.

[0016] An example of an application for merging information to create a model of the vehicle's surroundings may be a traffic light as an object to be merged. The traffic light is detected by a sensor unit, for example by a camera unit. The traffic light sends its position to the system via an interface with absolute position information, for example in world coordinates. This information may be merged to create a unified model of the surroundings, for example in the following two cases:

[0017] Traffic lights are listed in the vehicle surroundings model and the objects to be merged (ie traffic lights) detected by the sensor unit should be correctly associated with existing objects in the surroundings model.

[0018] The detected objects are not present in the model of the surroundings and should be inserted into the model of the surroundings by merging information from various information sources.

[0019] The system may be configured to transform the relative position information or absolute position information of the objects to be merged in a digital map format. Thus, a surrounding environment model based on the information in the digital map format may be created. Additionally or alternatively, the system may be configured to transform the relative position information or absolute position information about the objects to be merged and the information in the digital map format into a predefined coordinate format. Thus, it is also possible to create a surrounding environment model conforming to another coordinate format.

[0020] The system may be configured to determine the absolute position information from the relative position information about the at least one object to be merged.

[0021] If the relative position information is limited to the distance to the object to be merged, the system can be equipped to determine the absolute position information based on this distance and additional information about the road segment and / or the object to be merged. This additional information can be determined or detected by the following steps, for example:

[0022] - Determine the type of object to be merged (eg traffic sign, other road user), for example by evaluating sensor information (eg camera unit) and / or position information.

[0023] - Calculating several possible alternative points for the position of the object to be merged, wherein the possible alternative points are located on a circle around the vehicle when the distance between the vehicle and the object to be merged is known.

[0024] - Using known information of different types of objects from the object to be merged. For example, road signs are located at the edge of the road, so that the edge of the road can be used as a reference geometry for determining the road geometry. For example, for a vehicle as the object to be merged, a lane dividing line can be a suitable reference geometry for determining the road geometry.

[0025] The information in the digital map format may be information in a path / offset format. The digital map format may be, for example, a path / offset format according to the ADASIS protocol. Driver assistance systems in motor vehicles often do not have enough memory to store large digital maps. For this reason, one of the units and / or the system in the vehicle usually has a relatively large memory unit. For example, such a unit may be a navigation unit of the vehicle. Depending on the instantaneous vehicle position, the relevant details may be read out of the map from the memory unit and transmitted to one of the driver assistance systems in a predefined format. For example, such transmission may be carried out via a vehicle bus system or by means of other technologies such as shared memory. The driver assistance system that may receive such data may create a model of the surroundings based on it, the so-called electronic horizon. This vehicle surroundings model and / or this electronic horizon only contains a part of the total digital map, so this certainly reduces the demand for resources. ADASIS is a known protocol for such information transmission and display. In order to transmit information, the information is not sent as raw data, such as complete geographic coordinates, but in a special display form.

[0026] The system may be equipped to determine the offset of an object to be merged by merging information about the instantaneous position of the vehicle in a path / offset format with absolute position information or relative position information of the object to be merged. The proposed system may merge relative position information or absolute position information with information in a path / offset format. Firstly, absolute position information of at least one interface and / or relative position information of at least one sensor unit may be made available to the system. The navigation unit may provide information about the instantaneous position of the vehicle and about a road segment in front of the vehicle in a path / offset format. An offset between the instantaneous vehicle position, the path / offset format and the relative position information or absolute position information of the object to be merged may be determined based on the information provided.

[0027] The system may be equipped to determine the geometry of the road by using information provided by the at least one navigation unit to determine one or more geometric points whose absolute position information and / or whose position in a digital map format is known.

[0028] The system can be equipped to determine the offset of the object to be merged by using the (one or more) geometric points thus determined. If there are multiple geometric points (high data density), the geometric points can be directly associated with the object to be merged in the simplest case. The geometric point at the shortest distance to the object to be merged can be used. In this case, the offset of the geometric point thus determined can be used as the offset of the object to be merged. If the distance between the object to be merged and the nearest geometric point is greater than a predetermined threshold, there will be no direct association. If the distance between the geometric point and the object to be merged is greater than a predetermined threshold, a neutral geometric point closer to the object to be merged can be determined by interpolation (or extrapolation) between two or more geometric points. Depending on the geometry of the road, the density of the geometric points G and the required accuracy, linear methods, high-order polynomials or some other suitable methods can be used for interpolation and / or extrapolation. The absolute position information of the geometric points thus determined can be known in world coordinates, and the process of offset can also be known. For this reason, the offset of the object to be merged can correspond to the offset of the geometric point.

[0029] The system may be configured to determine a node by using information provided by at least one navigation unit to determine the geometry of the road, such that absolute position information about the node and / or its position in a path / offset format is known.

[0030] The system may be configured to estimate a geometry of a road segment between the object to be merged and a node closest to the object to be merged, wherein the system is further configured to estimate a distance between the object to be merged and the node based on the estimated geometry of the road segment.

[0031] The system may be configured to determine an offset between a node and an object to be merged based on the estimated distance.

[0032] The system may be equipped to estimate the route of the road segment based on at least one information item detected by one or at least one sensor unit and / or based on at least one information item or information provided by at least one interface. The following information may be included in the estimate:

[0033] - evaluate information from sensor units, such as images from camera units, e.g. regarding the course of road markings, the positions of detected objects relative to one another, etc.,

[0034] - using distance and angle information from sensor units such as radar units and / or lidar units,

[0035] - store recently driven vehicle trajectories, for example by storing GPS position(s),

[0036] - using steering angle and vehicle speed, and

[0037] - Use nodes from a digital map, from which the world coordinates are known.

[0038] The system can be equipped to determine whether the object to be merged is on the same path or in the same lane as the vehicle. In this way, there can be a correct association of the path and lane of the object to be merged. If the object to be merged is located on a different path or in a different lane, the offset must be corrected accordingly, since each path has its own offset origin. Data from a digital map in a path / offset format and data detected by at least one sensor unit can be used for this purpose.

[0039] The system may be equipped to determine information in a digital map format of objects to be incorporated by means of relative displacement vectors starting from instantaneous absolute position information about the vehicle, whose absolute position information is known.

[0040] As another alternative, a motor vehicle is proposed, comprising a system according to any of the previously proposed solutions.

[0041] For another method, a method for creating an environment model of a motor vehicle is proposed. The method comprises the following steps: providing information about the instantaneous position of the vehicle and about at least one road segment in front of the vehicle in both time and space, wherein the information is provided in a digital map format and / or as absolute position information; communicating with at least one object to be incorporated in the vehicle surroundings, wherein the received information includes absolute position information about the at least one object to be incorporated, and / or detecting at least one object to be incorporated in the vehicle surroundings, wherein relative position information relative to the vehicle is provided about the at least one object to be incorporated; determining the geometry of the road segment in front of the vehicle using the information about the road segment in front of the vehicle, the information being provided by at least one navigation unit; merging the absolute position information and / or relative position information about the at least one object with the information provided by the at least one navigation unit in a digital map format to create a vehicle surroundings model based on the geometry of the road thus determined.

[0042] The method may include the following steps: transforming relative position information or absolute position information about the objects to be merged into information in a digital map format and / or transforming relative position information or absolute position information about the objects to be merged and information in a digital map format into a predefined coordinate format.

[0043] The absolute position information may be determined based on the relative position information about the at least one object to be merged.

[0044] If the relative position information is limited to the distance to the object to be merged, the absolute position information can be determined based on this distance and additional information about the road segment and / or the object to be merged.

[0045] The information provided by the at least one navigation unit may be used to determine one or more geometric points whose absolute position information and / or whose position is known in a digital map format in order to determine the road geometry.

[0046] The information in the digital map format may be information in a path / offset format.

[0047] The offset of the object to be merged may be determined by merging information about the instantaneous position of the vehicle in a digital map format and absolute position information or relative position information about the object to be merged.

[0048] The determined geometric point(s) may be used to determine the offset of the objects to be merged.

[0049] The road geometry can be determined by using information provided by the at least one navigation unit to determine at least one node whose absolute position information or relative position information and / or whose position is known in a digital map format.

[0050] A road segment between the object to be merged and a node closest to the object to be merged may be estimated, wherein a distance between the object to be merged and the node may be estimated based on a geometry of the estimated road segment.

[0051] Based on the estimated distance, the offset between the node and the object to be merged can be determined.

[0052] The course of the road segment may be estimated based on information detected by at least one sensor or at least one sensor unit and / or based on information provided by at least one interface or the at least one interface.

[0053] It may be determined whether the object to be merged is on the same path as the vehicle or in the same lane as the vehicle.

[0054] The information in the digital map format of the objects to be incorporated, whose absolute position information is known, can be determined using the relative displacement vector starting from the instantaneous absolute position information about the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Additional details, features, advantages and effects of the methods and apparatus described herein may be gathered from the following description of presently preferred variants and the accompanying drawings, in which:

[0056] Figure 1 A schematic diagram of a system for creating a surrounding environment model for a vehicle is shown;

[0057] Figure 2 An example of a view illustrating a logical map format in a path / offset format is shown;

[0058] Figure 3 An example of a diagram illustrating a merger of information in a path / offset format with relative position information is shown;

[0059] Figure 4 An example of another diagram illustrating the merging of information in a path / offset format with relative position information;

[0060] Figure 5 An example of a diagram illustrating a process of determining absolute position information according to a distance between an object to be merged and a vehicle is shown;

[0061] Figure 6 An example of a diagram for determining an offset of an object to be merged for a case where the geometry of a road is determined by using a plurality of geometric points is shown;

[0062] Figure 7 An example of a diagram showing determination of road geometry by using nodes with known absolute position information is shown;

[0063] Figure 8 An example of a diagram illustrating the determination of offsets of objects to be merged by means of nodes is shown;

[0064] Fig. 9 An example of a diagram in which a road extends in a curve between vehicles, nodes, and objects to be merged is shown;

[0065] Fig.10 An example of an estimated road geometry and / or an estimated route of a road is shown;

[0066] Fig.11 An example of a diagram illustrating how position information is determined in a path / offset format on an example of a traffic light system with known absolute position information is shown;

[0067] Fig.12 shows an example of a diagram illustrating a problem in merging position information in path / offset format with absolute position information in the case of a curved road route;

[0068] Fig.13 and 14 Schematic diagrams each showing a different possibility for merging data to create a model of the vehicle's surroundings; and

[0069] Fig.15A diagram illustrating the advantages of a vehicle surroundings model with incorporated position information is shown. DETAILED DESCRIPTION

[0070] Figure 1 Schematically illustrated are a sensor unit 110, a system 120, a navigation unit 130, and an interface 140, which may be incorporated into a motor vehicle (not shown). The sensor unit 110, the navigation unit 130, and the interface 140 may be connected to the system 120, which in turn is connected to the navigation unit 130.

[0071] The sensor unit 110 may be, for example, a camera unit, a radar unit, a lidar unit, etc. However, the system 120 may also be connected to a plurality of sensor units 110, i.e., the system 120 may be connected to a camera unit, a radar unit, and a lidar unit. The sensor unit 110 provides the system 120 with relative position information about objects to be merged (not shown) around the vehicle. If the sensor unit 110 is a camera unit, it may be a time-of-flight (TOF) camera unit. A time-of-flight camera may detect the surroundings of the vehicle in 3D based on the distance measurement method it performs. The time-of-flight camera illuminates the surroundings of the vehicle with light pulses, and the camera unit measures the time required for the light to travel to the object and back for each pixel. The required time is then used to determine the distance to the detected object. The sensor unit 110 may be additionally equipped to detect the route of the road boundary and / or lane markings. In addition, the sensor unit 110 may be equipped to detect the width of the road.

[0072] The navigation unit 130 is equipped to provide information about the instantaneous position of the vehicle and at least one section of road in front of the vehicle in time and space based on the position information and / or map information about the vehicle. This information can be provided in a digital map format. The navigation unit 130 can be correspondingly equipped to determine the instantaneous position of the motor vehicle based on a signal, in particular a GPS signal. In addition, the navigation unit 130 can access map data in a digital map format stored in a memory in the navigation unit 130, which is provided in the form of an external data medium and / or a cloud system. The map data can also contain information about the route of the road boundary and / or the route of the lane marking and / or the width of the road. The current vehicle position can be provided to the navigation unit 130 in a digital map format. The map data can also include information about the geometry of the road and the topology of the road segment in front of the vehicle.

[0073] The interface 140 is equipped to communicate with at least one object to be incorporated in the vehicle's surroundings. The information received by the interface 140 includes absolute position information about the at least one object to be incorporated. The interface 140 may also be an interface for so-called "V2X" communication. V2X refers to vehicle-to-object communication. This expression therefore includes communication of the vehicle with other vehicles, with infrastructure objects and with people (pedestrians). Infrastructure objects may be, for example, traffic lights, traffic signs, mobile and fixed road boundaries, buildings, signs, billboards, etc.

[0074] The system 120 is equipped to determine geometric points and / or nodes using known absolute position information and / or using known position information in a path / offset format from information provided by the navigation unit 130. Using the geometric points and / or nodes thus determined, the system 120 can determine the geometry of the road segment in front of the vehicle. The system is also equipped to merge the absolute position information and / or relative position information about at least one object to be merged with the information provided by the at least one navigation unit 130 in a path / offset format based on the geometry of the road thus determined, so as to create a model of the vehicle surroundings. The map data may also include information about the route of road boundaries and / or the route of lane markings and / or the width of the road.

[0075] Figure 2 A schematic diagram illustrating the path / offset format for position information about objects (such as vehicles and traffic signs, nameplates and intersections) in a digital map according to the ADASIS protocol is shown. Roads are represented by paths and are clearly marked by path IDs. For each path, there is an offset given in meters (or cm, mm, etc.), and thus defines the position of the object and additional information, such as road curvature values ​​and gradient values ​​on the path. The current vehicle position is defined with the help of path / offset information. For example, position information from a sensor unit (such as a camera unit, a radar unit or a lidar unit in a vehicle) is usually given in relative position information. For example, a camera or radar can therefore indicate that the relevant object and / or the object to be merged (e.g., a traffic sign or other vehicle) is located at a certain distance from the vehicle. In contrast, data received via V2X technology can be used as absolute position information (e.g., WGS84 world coordinates). For example, a street lamp can send a momentary switch state to the street lamp together with the absolute position information in the WGS84 format.

[0076] For example, the following reference Figures 3 to 11Embodiments of methods for creating a surrounding environment model of a vehicle that can be performed by system 120 are described. In the embodiments described below, merging relative or absolute position information from various information sources with information in a path / offset format according to the ADASIS protocol will be explained. In the present disclosure, position information from a digital map is referred to as information in a path / offset format, or also referred to as information in a digital map format. The path / offset format is an example of a digital map format.

[0077] Figure 3 An example of a diagram showing a merger of information in a path / offset format with relative position information is shown. An ego vehicle 10 is traveling on a road 12. A path ID 8 is assigned to the road 12 in a digital map. The offset of the path 8 has a linear increase in the direction of the dashed arrow P. For example, a camera unit and / or a radar unit (not shown) on the ego vehicle 10 detects a construction site 14 and a vehicle 16 in a lane 18. The distance to the construction site 14 and the vehicle 16 can be determined based on the camera and radar information. Furthermore, it is known from the camera and radar information in which lanes 18 and 20 the objects 14 and 16 are located. For this purpose, the construction site 14 and the vehicle 16 as well as the ego vehicle 10 can be assigned to the path 8. The offset of the object is obtained from the relative distance ΔOffset to the ego vehicle and the instantaneous offset value of the ego vehicle:

[0078] Offset object =Offset ego vehicle + ΔOffset

[0079] The above explains the general process of merging the information in path / offset format with the relative position information. Figure 2 In the example shown, a prerequisite for merging is that the road must have no or almost no curvature. The merging of path / offset information with relative position information is described below without being limited to a specific alignment of a road.

[0080] Figure 4 Another example of a vehicle situation map is shown, where a merging of information in a path / offset format with relative position information is preferred. Figure 4 An ego vehicle 10 is shown on a road 12 which, in this exemplary figure, has only a single lane. Figure 2 Differently, the road 12 here is not straight but has curvature. An intersection is a special case. At an intersection, the direction of travel may differ by 90° from the previous direction of travel. Also in the special case of an intersection, the information in the path / offset format may be merged with the relative position information according to the following description.

[0081] The ego vehicle 10 has a sensor unit (not shown), such as a camera unit or a radar unit, for example, which is used to detect an object to be merged, such as a traffic sign 22 (speed limit 60 km / h). According to this example, the traffic sign represents the object to be merged 22. However, the object to be merged can also be another traffic participant, a street light, a traffic sign or a pedestrian.

[0082] The sensor unit (not shown) can provide relative position information with only one coordinate relative to the object 22 to be merged. This position information can be, for example, the distance of the object 22 relative to the ego vehicle 10 (for example, the object is 10 meters away). However, it is also possible for the sensor unit to provide more accurate position information with at least two coordinates. For example, such coordinates can be given in polar coordinates or Cartesian coordinates. The position information can then include distance and angle, for example, the object is 50 meters away and at an angle of 5° to the direction of travel.

[0083] The variables shown in the following table were used.

[0084]

[0085] For example, a digital map may provide information about the geometry of the road, typically absolute position information, such as in world coordinates. The geometry of the road includes, among other things, the geometry of the road markings and the geometry of the lane markings. The geometry of the lane markings is at a point G Figure 4 As shown in. About the geometric point G, about the corresponding path G(x o )’s world coordinate G(x w ,y w ) and the offset value are known. Figure 4 In the example, information is available at a sufficiently high density, that is, each point G(x w ,y w ) is very small, so that multiple geometric points G(x w ,y w ) is located in the immediate vicinity of the object 22 to be merged. The world coordinate E(x w ,y w ) in the position information and offset value E(x o ) is also known.

[0086] The sensor unit detects the object 22 to be incorporated and represents its relative position information relative to the ego vehicle 10 either one-dimensionally (specifying only the distance to the ego vehicle 10 ) or by more accurate position information (e.g. angle and distance relative to the ego vehicle 10 and with a displacement vector).

[0087] First, the absolute position information is determined based on the relative position information about the object 22 provided by the sensor unit. The absolute position information can be given in world coordinates. The world coordinates (O(x)) of the object 22 are determined from the relative position information about the object 22. wo ,y wo )). World coordinates are usually not given as Cartesian coordinates, but in a first approximation as spherical coordinates. The WGS84 model uses an oblate spheroid to describe the Earth's surface. For a simpler explanation of the merge, a spherical representation of the Earth is assumed. This approximation is sufficiently accurate for short distances between the vehicle and the object to be merged.

[0088] If the sensor unit provides the angle α and the distance d to the object 22 to be merged, the result is the world coordinates E(x wE ,y wE ) of the object 22 in the world coordinates (O(x wo ,y wo )):

[0089]

[0090] where d is the distance from the ego vehicle 10 to the object 22, α is the angle in the direction of the object 22 measured from the line joining the ego vehicle and the North Pole, and R is the radius of the Earth.

[0091] If the sensor unit provides a displacement vector = (a, b), then d and α must first be calculated from this vector. Next, O(x wo ,y wo ). For example, geometric relations can produce the following results:

[0092]

[0093] in α F is the heading of the ego vehicle (measured from the line joining the ego vehicle and the North Pole), and α O is the angle between the longitudinal axis of the ego vehicle 10 and the object 22. This angle is determined by the vector Export.

[0094] Figure 5 An example of a diagram illustrating a process for determining absolute position information of the object 22 to be merged based on a distance d between the ego vehicle 10 and the object 22 to be merged is shown.

[0095] A sensor unit (not shown) provides a distance d between the ego vehicle 10 and the object 22 to be merged. The object 22 to be merged is Figure 5 An example of a diagram in FIG. 2 is a traffic sign. Possible points O for indicating the absolute position information of the object 22 possible (x w , y w ) is located on a circle around the ego vehicle 10 with a radius d, i.e. the radius corresponds to the distance d. Based on the information determined from the sensor unit or a combination of information from a plurality of sensor units (e.g. a combination of information provided by a radar unit and a camera unit), it can be determined that the object 22 to be merged is a traffic sign. Since the object 22 to be merged is a traffic sign, the geometry of the road can be determined with the aid of the geometry of the road boundary as a reference geometry. The geometric point G(x w , y w ) and G(x o ) is known from the geometry of the road boundary. The absolute position information O(x) of the object 22 in the world coordinates wo , y wo ) can use all possible object points O of the object 22 to be merged possible (x w , y w ) and the road G(x w , y w ) is determined by the intersection of the geometric shapes.

[0096] If, as described above, the absolute position information O(x) about the object 22 to be merged cannot be determined directly in world coordinates due to insufficient sensor information, wo , y wo ), then various types of additional information can be used to determine the best possible alternative point for the absolute position information of the object 22 to be merged. This additional information can be determined or detected by the following steps, for example:

[0097] - For example, by evaluating the camera information and / or the position information, the type of object to be incorporated (eg traffic sign / other traffic participant) is determined.

[0098] - For O possible (x w , y w ) calculates possible multiple possible alternative points. This is referred to above according to Figure 5 An example of a diagram of FIG. 2 is described, where if the distance d to the object 22 to be merged is known, then possible alternative points O possible (x w , y w ) is located on a circle around the ego vehicle 10 (see Figure 5 ).

[0099] - Use known information about the different object types of the object to be merged. For example, this includes information such as: street signs are located at the edge of the lane, so the edge of the road is best used as reference geometry. When the object to be merged is another vehicle, the lane markings can be used as suitable reference geometry to determine the geometry of the road.

[0100] With the aid of this information, a suitable replacement point is selected from the possible replacement points.

[0101] Figure 6 An example of a diagram for determining the offset of an object 22 to be incorporated when determining the geometry of a road using a plurality of geometric points G whose absolute position information is known is shown. In this case, the geometric points G with known absolute position information are at a short distance from each other.

[0102] For example, in calculating the absolute position information O(x wo , y wo ) then we must choose a suitable geometric point G search And it must be as close as possible to O(x wo , y wo ). If they do correspond, then one would expect, for example, that wo , y wo ) is the geometric point G with the shortest distance. If there are a large number of geometric points G (high data density), then in the simplest case, the geometric points G can be directly assigned to the objects to be merged O(x wo , y wo ):

[0103] O(x wo , y wo ) = G search (x w , y w )

[0104] If the object to be merged O(x wo , y wo ) If the distance from the nearest geometric point G is greater than a predetermined threshold, then no direct correspondence can be found. In this case, a new geometric point G with a better correspondence to the object point O can be determined by interpolating (or extrapolating) between two or more geometric points. interpol (x wo , y wo ), so that we can determine:

[0105] O(x wo , y wo ) = G interpolo (x w , yw )

[0106] Depending on the course of the road geometry, the density of the geometry points G, the required accuracy and additional criteria, linear methods or higher order polynomials or some other suitable method may be used for interpolation and / or extrapolation. Due to the prerequisites described here, the world coordinate x w , y w The absolute position information and offset x in o The routes all start from the geometric point G search Therefore, the offset of the object 22 to be merged is related to G search The offset corresponds to:

[0107] G search (x o ) = O(x oo )

[0108] In this way, the offset of the object point O of the object to be merged is determined. If an interpolated or extrapolated geometric point G is used interpol As a reference, we must first interpol The basis is one or more known adjacent geometry points of the road geometry. The following assignments can then be made:

[0109] G interpol (x o ) = O(x oo )

[0110] refer to Figure 6 , the above steps can be explained as an example. Geometric point G 105 (x w105 , y w105 ) and the object to be merged 22 (O(x wo , y wo )) have a good correspondence; in order to simplify the diagram, Figure 6 It is not shown, but it is in Figure 5 In other words, the geometric point G 105 (x w105 , y w105 ) is substantially the same as the position of the object 22 to be merged (O(x wo , y wo )) corresponds to (see Figure 5 ). To this end, the geometric point G 105 (x w105 , y w105 ) of the offset G 105 (x o,105 ) can be combined with the object 22 to be merged (O(x wo , ywo )) is associated with the offset:

[0111] G 105 (x o,105 ) = O(x oo )

[0112] Figure 7 An example of a diagram is shown, in which the road geometry is determined with the aid of nodes with known absolute position information. There may be situations where the road geometry cannot be determined by means of geometric points. In these cases, there may be only a few geometric points with known absolute position information or no geometric points at all and / or the known geometric points may be too far apart from each other. In other words, the data density is so low that simple interpolation or extrapolation methods with the known geometric points do not produce sufficiently accurate results. Furthermore, it may happen that data points cannot be interpolated or extrapolated. This is the case, for example, if there are no geometric points at all for a road or a lane, but only absolute position information is available, for example in world coordinates for objects such as traffic lights and other irregularly distributed objects.

[0113] Figure 8 An example of a starting situation in a merge with low data density, i.e., with few known geometry points and / or geometry points that are too far from each other, is shown. n It can be a geometric point on the road. Nodes S1, S2 and S n The large distances between them do not allow reasonable interpolation. For example, node S3 can be a landmark, a street lamp, or a traffic sign with V2X capabilities, which can send their absolute position information.

[0114] Similarly, in the current case, if it is not known, then in the current case, it is also possible to first determine the object O(x wo , y wo )’s absolute position information. This has been described in detail above.

[0115] After determining the objects to be merged O(x wo , y wo ) can be found to represent the distance from the object O(x wo , y wo ) of the node S with the minimum distance search (x w , y w ). Figure 8 In the example, node S3 is selected for this purpose. By using node S(x w ,y w ) and the object O(x wo , y wo ) known world coordinates, calculate from the object O(xwo , y wo ) to the available nodes:

[0116]

[0117] For these equations, a spherical model of the earth with radius R is assumed as the basis. It is expected that this earth model meets the accuracy requirements of most applications. If still higher accuracy is required, then other earth models (e.g., a rotating ellipsoid) can be used. For many applications, it is sufficient if the nodes and objects in the surroundings of the ego vehicle 10 are referenced in a Cartesian coordinate system. This is especially true for nodes and objects in a near circle around the ego vehicle 10. When using a Cartesian coordinate system, d is obtained from

[0118]

[0119] Which earth model and which coordinate system to use for reference in nodes and objects will depend mainly on the accuracy requirements of the respective application and the available resources (processor speed, memory, available computation time, etc.). wo ,y wo ) and node S n The distance d between them is to select the appropriate node S n For example, we can select objects O(x wo , y wo ) is the node S at the minimum distance n , but other parameters can also be used for appropriate nodes S n Therefore, node S n There may be one (or more) confidence indicators. This indicator may indicate, for example, how confident it is that the node is actually at the stored location. For example, a node S may be reported by an official agency. n The location of a node S (e.g., a highway authority reports the location of a speed limit sign in world coordinates) or when a node S n A high confidence level is obtained when the location of has been confirmed by many different participants. If the confidence level is low, then the node can be excluded for further processing, and a node S at a larger distance d but with a higher confidence level can be selected. n One or more confidence parameters provided by the data provider may be used as confidence intervals. Furthermore, it is possible to calculate the confidence parameters before using the node itself. For example, a timestamp (e.g., node S n ), control parameters (e.g., variance of the measured node positions), the type of data source (e.g., other traffic participants or public authorities), and the node S nThe type of traffic sign (e.g., temporary or permanently erected) may be used as an input variable for calculating the confidence parameter.

[0120] Since the data density of node S is low, we can expect O(x wo , y wo ) is offset O(x o , o ) cannot be offset from the selected node S n (x o ) is derived. Therefore, in most cases, the offset of the selected node S is assigned as the object to be merged O(x wo , y wo ) is not possible, so that the following conditions are met:

[0121] S search (x o ) ≠ O(x o,o )

[0122] Figure 8 An example of a diagram for determining the offset of an object to be merged with a node S is shown, wherein according to Figure 8 In the diagram of , the road is straight. In order to improve the accuracy of the offset determination of the object, it is necessary to estimate the geometry of the road and how the offset travels along the road. If the road is at node S search and the object are straight, then the object to be merged 22 and the node S search The known distance between , the offset O(x) of the object 22 to be merged is calculated as follows o , o ):

[0123] x o,o = +

[0124] Optionally, the following fact can be considered: the object 22 to be merged and the node S search Not on the same side of the road. Figure 7 For example, node S search is located on the left side of the road, and the object to be merged 22 is located on the right side of the road. In this case, the distance along the road must be calculated based on the geometric relationship . Used to determine The required parameters can be obtained from the database (for example, road width b road stored in a digital map) or can be determined with the aid of vehicle sensors (e.g. with the aid of a vehicle camera to determine the road width b road ). Given a known road width and In this case, this produces:

[0125] =

[0126] In b road In the case of a vehicle, this may involve, in addition to the width of the road, other geometric variables such as lane widths or other distances that can be derived from sensor information detected by at least one sensor unit or from a digital map. Furthermore, a sensor unit on the vehicle (e.g. a camera unit, a radar unit) may be used to verify whether the prerequisite for a straight road is met. If the road is a small radius curve, then The determination of Figure 8 In this case, it is necessary to determine the geometry of the road and thus the offset route along the road by means of estimation based on nodes with known absolute position information and / or known information in path / offset format. Therefore, information mainly from vehicle sensors is used as input. Thus, S can be estimated, for example, using information from at least one sensor unit. search and the road geometry between the object to be merged. For example, the at least one sensor unit can be a camera unit. The course of the lane markings can be evaluated in the image captured by the camera unit. As support, for example, steering angles and vehicle trajectories that have already been traveled and recorded can be used. Thus, the remaining road course can be extrapolated from the course of the road that has already been traveled a certain distance.

[0127] Fig. 9 An example of a diagram is shown, where the road is between the ego vehicle 10, the node S search There is a curvature between the self-vehicle 10 and the object 22 to be merged. The road geometry between the self-vehicle 10 and the object 22 to be merged can be estimated by using one or more sensor units (camera unit, odometer, GPS, etc.) of the self-vehicle 10. Therefore, S search and the distance between the object 22 to be merged, so that the offset O(x o , o ) can be calculated as follows:

[0128] x o,o = +

[0129] The most precise possible determination The method is particularly important to achieve the required accuracy. The following information can be input into the estimate, for example:

[0130] - evaluate the camera image, e.g. the route relative to road markings, the position of detected objects relative to each other, etc.,

[0131] - using distance information and angle information from sensor units such as radar units and / or lidar units,

[0132] - For example, by storing GPS location data to store recently travelled vehicle trajectories,

[0133] - using steering angle and vehicle speed, and

[0134] - Use nodes from a digital map, whose world coordinates are known.

[0135] Fig.10 An example of an estimated road geometry and / or an estimated road route is shown. If the road geometry can be estimated, then the distance between the ego vehicle 10 and the object 22 to be merged (or the node S) is obtained as follows n and the object to be merged 22) is the offset difference ΔOffset:

[0136] ΔOffset =

[0137] Where a denotes the starting point of the path integration (e.g., node, vehicle), and b denotes the position of the object 22 to be incorporated. For the solution of this problem, different coordinate systems can be used (e.g., Cartesian coordinate system, polar coordinate system). The choice of coordinate system depends on the respective conditions, i.e., in particular, which input parameters are available for estimating the route of the road geometry.

[0138] like Fig.10 As shown in FIG. 1 , a camera unit (not shown) of the ego vehicle 10 detects the surroundings of the vehicle, in particular the surroundings in front of the vehicle. The geometry of the road and / or the course of the road are estimated with the aid of the information detected by the camera unit. For example, the estimate can be obtained by evaluating the lane markings in the camera image. In this arrangement, it is proposed to calculate the longitudinal coordinate x in the Cartesian vehicle coordinate system. F Given the estimated path s of road 12 g :

[0139] s g = f(x F )

[0140] In the current case, this produces:

[0141]

[0142] If the distance d and the angle α of the object 22 to be merged from the ego vehicle 10 are known (eg from information from at least one sensor unit such as a radar unit), then the following holds for b in the vehicle coordinate system:

[0143] b = d cos α

[0144] Fig.11 It is shown how position information is determined in a path / offset format in the example of a traffic light system with known absolute position information. The traffic light system 24 represents the object to be merged. This is primarily absolute position information in the case of position information sent from a V2X base station to a vehicle, for example. Thus, for example, the traffic light system sends the instantaneous switch state together with its absolute position information in WGS84 coordinates (i.e. in world coordinates) to the traffic light 24. For the merging of the absolute position information with the position information in path / offset format, the instantaneous absolute vehicle position (or some other suitable reference) is used. For example, the absolute position information about the vehicle 10 is known from a GPS receiver in the vehicle 10. Likewise, the vehicle position in path / offset format (e.g. ADASIS) is also known.

[0145] The path / offset display of the relevant object 24 (e.g., a traffic light system) can be found in different ways. In the simplest case, for example, when the distance between the vehicle and the relative object is small and when the course of the road is approximately straight, the relative displacement vector (vehicle 10 to object 24 to be merged) can be calculated from the absolute position of the vehicle and the absolute position of the object 24 to be merged. The relative displacement between the vehicle 10 and the object 24 is thus known. Figures 3 to 10 Explains how to determine position information from known absolute position information in path / offset format.

[0146] Both the position information in path / offset format and the absolute position information in world coordinates (WGS84 coordinates) are known to the ego vehicle 10. From these world coordinates of the ego vehicle 10 and the traffic light system 24, a relative displacement vector between the ego vehicle 10 and the traffic light system 24 can be calculated, the traffic light system 24 representing the object to be merged. This vector can then be used to calculate the position information of the traffic light system in path / offset format from the position information in path / offset format of the ego vehicle 10. After the position information in path / offset format has been calculated, the traffic light system can be inserted into a model of the vehicle's surroundings. For example, this vehicle surroundings model can be an electronic field of view (e.g., according to the ADASIS protocol).

[0147] Fig.12 An example of a diagram illustrating a problem in merging position information in the path / offset format with absolute position information in the case of a curved road route is shown. When the route of the road is curved, a displacement vector between the ego vehicle 10 and the object of interest or object to be merged 26 can be calculated. However, if this is then added to the offset value of the ego vehicle 10, the result is a false value for the offset (and possibly the path) of the object to be merged 26, because the offset value of the road does not follow the displacement vector (see Fig.10 ). The actual deviation route corresponds to the path integral along arrow P, which is Fig.11 The dashed line in the figure is as described above. The additional process and the merging of the absolute position information with the position information in the path / offset format then correspond to the above. To avoid repetition, reference is made to the above given Figures 3 to 10 Detailed description.

[0148] Fig.13 and 14 The merging possibilities created by the present disclosure are shown to enable the creation of a vehicle surroundings model. The above examples involve merging relative and absolute position information (relative and world coordinate formats) with position information in a logical map display (path / offset format). This is in Fig.13 . The position information detected by the sensor unit of the vehicle may be, for example, information from a camera unit and / or a radar unit. For example, the logical map display may be an electronic range according to the ADASIS protocol. Therefore, the above-described embodiments relate in particular to integrating relative or absolute position information into the digital field of view. For ADAS / AD applications, this results in the advantage that a unified and merged environment model is created regardless of the source of the position information.

[0149] In addition to this method, Fig.14 As shown in , it is also possible not to integrate the relative or absolute position information into the electronic field of view, but to merge the relative and / or absolute position information with the position information from the electronic field of view (in path / offset format) to generate an additional vehicle surroundings model with a different coordinate system. Fig.14 In the merging of relative and / or absolute position information and position information about the electronic field of view (in path / offset format) is merged into an additional environment model that uses a different coordinate system than the electronic field of view in path / offset format. This can be, for example, a Cartesian coordinate system or a polar coordinate system that also moves with the ego vehicle. The merging of position information disclosed herein and described above includes according to Fig.13 and 14 There are two possibilities. Fig.14 When used, the same steps must first be performed as in the above embodiments. After these steps, the combined position information can be transferred to another coordinate system (eg, Cartesian coordinate system and / or polar coordinate system).

[0150] According to reference Figures 1 to 12 In an embodiment of the method described for creating a surroundings model of a vehicle, relative position information or absolute position information (world coordinates, e.g. WGS84 coordinates) relative to the ego vehicle is merged with information in path / offset format. For example, due to this merging of information, the following information can be integrated into the electronic field of view and / or the surroundings model of the vehicle:

[0151] - Information about the instantaneous status of the traffic light system. By means of the information merging described here, it is possible to merge the real-time updates of the switch status of the traffic light system originating from the V2X data source with the position information of the traffic light system originating from the digital map. Only by merging this information is it possible to merge the real-time information with the static data from the digital map. Without such a merging, it is impossible to determine how the real-time information can be correlated with the objects in the electronic field of view. Using this correlation, the (self-driving) vehicle can respond appropriately to the corresponding traffic light.

[0152] - Information about the instantaneous status of variable speed displays (e.g. LED speed displays on motorways). What has been said above also applies here to real-time data from traffic light systems. For example, real-time data about speed limits received by V2X cannot be correlated with static objects from digital maps and / or electronic horizons without information merging.

[0153] - Information about the position and speed of other traffic participants (e.g. other vehicles, pedestrians, etc.). The merging of information makes it possible to integrate the positions of other traffic participants into the digital field of view. Thus, information from the digital map as well as information from the vehicle sensors are available in a shared surroundings model. This leads to a better assessment of the situation with regard to many ADAS / AD functions.

[0154] - Information about recent changes in the road route (e.g. at a construction site). For example, the route of a changed lane guide at a construction site can be sent to the vehicle via V2X. By merging the information, this information can be integrated into the digital field of view.

[0155] - Information about traffic obstacles (e.g., accidents, roadblocks). In this case, it may be helpful to integrate position information from different sources into a shared electronic view.

[0156] Fig.15 The advantages of merging information from different information sources based on the example of a traffic light system are shown. Without the integration and correlation of data from different sources (e.g., digital maps, vehicle sensors, and V2X data sources), a unified environment model cannot be obtained. It is not possible to associate the same objects from different data sources and combine their information.

[0157] By integrating these different types of information into an environment model (e.g., ADASIS), the following applications can be realized in the ADAS / AD scope, for example:

[0158] - Warns the driver of dangerous places or traffic obstacles along the path of travel. Thanks to the merging of information, it is possible to determine whether dangerous locations are on the path currently being travelled and whether these are relevant for the vehicle.

[0159] - Consideration of information about the instantaneous condition of traffic lights and information about variable speed limits in speed selection for smart cruise control (e.g. green ACC). Through the merging of information, real-time data from sources such as V2X cannot be merged and associated with other objects from digital maps (traffic lights, traffic signs) to form a shared environment model and / or field of view. Without this association, the information received from the V2X data source cannot be interpreted.

[0160] - Display information about instantaneous traffic light conditions and information about variable speed limits on the vehicle's human-machine interface (HMI). By merging the information, data from different sources can be associated and interpreted in a shared environment model.

[0161] - Selection of alternative routes due to traffic obstacles. By combining the information, it is possible to determine whether a traffic obstacle is relevant to the vehicle.

[0162] The variants of the above-mentioned methods or devices and their functional aspects and operational aspects are only used to provide a better understanding of the structure, function and characteristics. They do not limit the present disclosure to these embodiments. The accompanying drawings are partially schematically drawn, and in some cases, important characteristics and effects are clearly emphasized to illustrate functions, effective principles, technical embodiments and features. Any function, any principle, any technical embodiment and any feature disclosed in the figure or text can be freely and arbitrarily combined with any feature, other function, principle, technical embodiment and feature contained in or derived from any claim, text and / or other figure, so that all conceivable combinations can be attributed to the described method and / or device and are associated with it. This also includes the combination of all the various embodiments in the text, that is, the combination of different variants in any part of the specification, the claims and the text, the claims and the drawings. For the value range given here, it keeps all the numerical values ​​therebetween and is also disclosed.

[0163] The claims also do not limit the disclosure and therefore not all possible combinations of features presented herein. All features disclosed are also explicitly disclosed both individually and in combination with any other features.

Claims

1. A system (120) for creating a model of the surrounding environment of a vehicle (10), the system comprising: At least one navigation unit (130) is configured to provide instantaneous position information of the vehicle in time and space and road segment information about at least one road segment ahead of the vehicle (10), wherein the navigation unit (130) provides the road segment information in a digital map format, the road segment information comprising route information about a route of one of a road boundary and a lane marking of the at least one road segment, At least one sensor unit (110) configured to detect at least one object (14, 22, 24) and to provide relative position information indicating a distance between the vehicle (10) and the at least one object, The system (120) is configured to determine a geometry of at least one road segment ahead of the vehicle based on route information, the geometry of the at least one road segment comprising distributed geometry points representing one of a road boundary and a lane marking, each geometry point comprising absolute position information, The system is configured to merge the absolute position information of at least one object (14, 22, 24) with the information in a digital map format provided by the at least one navigation unit (130) to create a vehicle surrounding environment model, wherein the merging comprises: identifying a plurality of alternative points of at least one object based on the relative position information, the plurality of alternative points being located on a circle around the vehicle, the circle having a radius corresponding to a distance from the vehicle to the at least one object; identifying a corresponding replacement point among the plurality of replacement points of the at least one object based on an evaluation of the plurality of replacement points and the geometric point, wherein the corresponding replacement point includes absolute replacement point information corresponding to the absolute position information of the at least one object; and creating a vehicle surroundings model based on the geometry of the road and the absolute position information of the at least one object, wherein the vehicle surroundings model includes at least one object model representing the at least one object, and The vehicle is controlled based on the vehicle surroundings model.

2. The system (120) of claim 1, wherein the system (120) is configured to transform relative position information or absolute position information about at least one object (14, 22, 24) to be merged into information in a digital map format, and / or wherein the system is configured to transform relative position information or absolute position information about at least one object (14, 22, 24) to be merged and information in a digital map format into a predefined coordinate format.

3. The system (120) of claim 2, wherein the system (120) is configured to determine the absolute position information based on the distance and additional information about the road segment.

4. The system (120) of claim 1, wherein the system (120) is configured to determine a geometric point (G) whose absolute position information and / or whose position in a digital map format is known by using information provided by the at least one navigation unit (30) in order to determine the geometry of the road.

5. The system (120) of claim 1, wherein the system (120) is configured to determine the offset of the at least one object (14, 22, 24) to be merged by merging the instantaneous position information of the vehicle (10) in a digital map format with the absolute position information or the relative position information of the at least one object (14, 22, 24) to be merged.

6. The system (120) of claim 5, wherein the system is configured to determine an offset of at least one object (14, 22, 24) to be merged by using the corresponding geometrical point determined thereby or a plurality of geometrical points determined thereby.

7. The system (120) of claim 1, wherein the system (120) is configured to determine at least one node (S) whose absolute position information or relative position information and / or whose position in a digital map format is known by using the route information provided by the at least one navigation unit (130) in order to determine the geometry of the road.

8. The system (120) of claim 7, wherein the system (120) is configured to estimate a geometry of a road segment between at least one object (14, 22, 24) to be merged and at least one node (S) closest to the at least one object (14, 22, 24) to be merged, wherein the system (120) is further configured to estimate a distance (d) between the at least one object (14, 22, 24) to be merged and at least one node (S) based on the estimated geometry of the road segment.

9. The system (120) of claim 8, wherein the system (120) is configured to determine an offset between at least one node (S) and at least one object (14, 22, 24) to be merged based on the estimated distance (d).

10. The system (120) of claim 8, wherein the system (120) is configured to estimate a route of a road segment based on information detected by at least one sensor unit (110) and / or based on information provided by at least one interface (140).

11. The system (120) of claim 1, wherein the system (120) is configured to determine whether the at least one object (14, 22, 24) to be merged is located on the same path or in the same lane (12) as the vehicle (10).

12. The system (120) as claimed in claim 1, wherein the system (120) is configured to determine information in a digital map format of an object (14, 22, 24) to be incorporated, whose absolute position information is known, by means of a relative displacement vector starting from instantaneous absolute position information about the vehicle (10).

13. The system (120) of claim 1, wherein a driver assistance system is configured to access the vehicle surroundings model to control the vehicle.

14. The system (120) of claim 1, wherein the system is a driver assistance system.

15. A vehicle (10) comprising the system (120) according to any one of claims 1 to 14.

16. A method for creating a model of the surrounding environment of a vehicle, wherein the method comprises the following steps: providing instantaneous position information of the vehicle (10) in time and space and road segment information about at least one road segment ahead of the vehicle (10), wherein the road segment information is provided in a digital map format and includes route information about a route of one of a road boundary and a lane marking of the at least one road segment, detecting at least one object to be incorporated in the surroundings of the vehicle to provide relative position information of the at least one object (14, 22, 24) indicating a distance between the vehicle (10) and the at least one object, Determining the geometry of at least one road segment ahead of the vehicle based on route information about the road segment ahead of the vehicle (10), the geometry of the at least one road segment comprising distributed geometry points representing one of a road boundary and a lane marking, each geometry point comprising absolute position information, Combining the absolute position information of at least one object (14, 22, 24) with the information in a digital map format provided by the at least one navigation unit (130) to create a vehicle surroundings model, the merging comprising: identifying a plurality of alternative points of at least one object based on the relative position information, the plurality of alternative points being located on a circle around the vehicle, the circle having a radius corresponding to a distance from the vehicle to the at least one object; identifying a corresponding replacement point among the plurality of replacement points of the at least one object based on an evaluation of the plurality of replacement points and the geometric point, wherein the corresponding replacement point includes absolute replacement point information corresponding to the absolute position information of the at least one object; and creating a surrounding environment model based on the geometric shape of the road and the absolute position information of the at least one object, wherein the surrounding environment model includes at least one object model representing the at least one object, and The vehicle is controlled based on the vehicle surroundings model.

17. The method of claim 16, wherein the method comprises at least one of the following steps: Converting relative position information or absolute position information about at least one object (14, 22, 24) to be merged into information in a digital map format, and / or Relative position information or absolute position information about at least one object (14, 22, 24) to be merged and information in a digital map format are transformed into a predefined coordinate format.

18. The method as claimed in claim 17, wherein the absolute position information is determined based on additional information about the road segment and / or the at least one object (14, 22, 24) to be merged.

19. The method as claimed in claim 16, wherein the geometric point (G) whose absolute position information and / or whose position in digital map format is known is determined by using information provided by the at least one navigation unit (30) in order to determine the geometry of the road.

20. The method as claimed in claim 16, wherein the offset of the at least one object (14, 22, 24) to be merged is determined by merging instantaneous position information of the vehicle (10) in a digital map format with absolute position information or relative position information about the at least one object (14, 22, 24) to be merged.

21. The method as claimed in claim 20, wherein the offset of at least one object (14, 22, 24) to be merged is determined by using the geometrical point (G) thus determined.

22. The method of claim 16, wherein the node(s) whose absolute position information or relative position information and / or whose position in a digital map format is known is determined by using the information provided by the at least one navigation unit in order to determine the geometry of the road.

23. The method of claim 22, wherein a geometry of a road segment between the at least one object to be merged (14, 22, 24) and a corresponding node (S) closest to the at least one object to be merged (14, 22, 24) is estimated, so that a distance (d) between the at least one object to be merged (14, 22, 24) and the corresponding node (S) is estimated based on the estimated geometry of the road segment to provide an estimated distance.

24. The method as claimed in claim 23, wherein an offset between the corresponding node (S) and the at least one object (14, 22, 24) to be merged is determined based on the estimated distance (d).

25. The method as claimed in claim 23 or 24, wherein the course of the road segment is estimated based on information detected by at least one sensor unit (110) and / or based on at least one item of information provided by at least one interface (140).

26. The method as claimed in claim 16, wherein it is determined whether the at least one object (14, 22, 24) to be merged is located on the same path or in the same lane (12) as the vehicle (10).

27. The method as claimed in claim 16, wherein information in a digital map format of an object to be incorporated, whose absolute position information is known, is determined by means of a relative displacement vector starting from the instantaneous absolute position information about the vehicle (10).

Images