Method for operating a vehicle assistance or control system

Abstract

The present invention relates to a method for operating a vehicle assistance or control system, which has a vehicle (VHCL) and an off-board obstacle recognition sensor (RMTS) for identifying obstacles of the vehicle (VHCL), wherein the vehicle includes an on-board obstacle recognition sensor (EGOS) for identifying obstacles of the vehicle (VHCL), wherein a first grid map is generated based on the off-board obstacle recognition sensor, and a second grid map is generated based on the on-board obstacle recognition sensor or based on the vehicle, and wherein a merged grid map is generated based on the first grid map and the second grid map.

Description

Technical Field

[0001] The invention relates to a method for operating a vehicle assistance or control system. Background Art

[0002] Patent document US2016 / 0368489A1 discloses a parking assistance system, in which a communication connection is established between an external parking automation system and a vehicle, wherein the distance between an identified object and the vehicle is measured. A brake control system of the vehicle is activated based on the measured distance. US 2018 / 0012497 A1 discloses a vehicle navigation system for automatically transferring a vehicle from a starting position to a target position. It can be provided that, for example, sensors outside the vehicle communicate with sensors on the vehicle for the purpose of guiding the vehicle. US 2016 / 0368489 A1 discloses a system for driving a motor vehicle based on image data. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide an improved or alternative transportation vehicle auxiliary or control system.

[0004] The aforementioned technical problem is solved by a method for operating a vehicle assistance or control system, the vehicle assistance or control system having a vehicle and an off-board obstacle recognition sensor for identifying obstacles of the vehicle, wherein the vehicle comprises an on-board obstacle recognition sensor for identifying obstacles of the vehicle, wherein a first grid map is generated based on (or in relation to) the off-board obstacle recognition sensor, a second grid map is generated based on the on-board obstacle recognition sensor or based on the vehicle, and wherein a merged grid map is generated based on the first grid map and the second grid map. In this case, it is particularly provided that in the merged grid map, the grid has a "free" or "unoccupied" state, and the grid has a "free" or "unoccupied" state in the first and / or second grid map.

[0005] In an advantageous embodiment of the invention, in the first grid image or in the merged grid image, the status of the grids showing the means of transport as obstacles is set to “free” or “unoccupied”.

[0006] In a further advantageous embodiment of the invention, the combined grid image is generated as a function of the orientation of the non-vehicle obstacle detection sensor relative to the vehicle and / or relative to the vehicle obstacle detection sensor.

[0007] In an advantageous embodiment of the invention, the off-board obstacle recognition sensor comprises a marking. In another advantageous embodiment of the invention, the means of transport comprises at least one camera for recognizing the marking and a tracking module for determining the angle of the position of the off-board obstacle recognition sensor relative to a reference axis of the means of transport, but in particular not determining the distance between the on-board obstacle recognition sensor and the off-board obstacle recognition sensor. If the means of transport is a vehicle, the reference axis in the sense of the invention may be, for example, the longitudinal axis of the vehicle. In another advantageous embodiment of the invention, the orientation of the off-board obstacle recognition sensor relative to the means of transport and / or relative to the on-board obstacle recognition sensor is also determined based on the angle, the output signal of the off-board obstacle recognition sensor and the output signal of the on-board obstacle recognition sensor.

[0008] In a further advantageous embodiment of the invention, the orientation of the off-board obstacle detection sensor relative to the vehicle and / or relative to the on-board obstacle detection sensor is determined based on the measured values ​​of the off-board obstacle detection sensor and the measured values ​​of the on-board obstacle detection sensor.

[0009] In a further advantageous embodiment of the invention, the orientation of the non-vehicle obstacle detection sensor relative to the vehicle and / or relative to the vehicle obstacle detection sensor is determined by optimizing and / or minimizing the distance between

[0010] - between the measured values ​​of the rotation of the off-board obstacle recognition sensor and the measured values ​​of the translation of the on-board obstacle recognition sensor,

[0011] - between the measured values ​​of the rotation of the onboard obstacle recognition sensor and the measured values ​​of the translation of the off-board obstacle recognition sensor,

[0012] - between the rotational and translational measurements of the off-board obstacle recognition sensor and the measurements of the on-board obstacle recognition sensor, or

[0013] - between the rotational and translational measured values ​​of the onboard obstacle recognition sensor and the measured values ​​of the off-board obstacle recognition sensor.

[0014] In a further advantageous embodiment of the invention, the rotation does not include more than one degree of freedom and the translation does not include more than two degrees of freedom. In a further advantageous embodiment of the invention, the off-board obstacle recognition sensor includes a marking, by means of which the angle of the position of the off-board obstacle recognition sensor relative to the reference axis of the vehicle is determined, but in particular the distance between the on-board obstacle recognition sensor and the off-board obstacle recognition sensor is not determined. In a further advantageous embodiment of the invention, the translation is reduced by one degree of freedom by means of the angle.

[0015] In a further advantageous embodiment of the invention, a laser radar is used as the vehicle-mounted obstacle recognition sensor and / or the non-vehicle-mounted obstacle recognition sensor.

[0016] In a further advantageous embodiment of the invention, the measured values ​​of the non-vehicle obstacle recognition sensor are transmitted wirelessly from the non-vehicle obstacle recognition sensor to the vehicle-mounted obstacle recognition sensor.

[0017] In an advantageous embodiment of the invention, the off-board obstacle recognition sensor is arranged in the parking space or parking bay. In another embodiment of the invention, this or another off-board obstacle recognition sensor is arranged in the parking space or parking bay.

[0018] The aforementioned technical problem is also solved by a vehicle of the aforementioned vehicle assistance or control system, for example, by a vehicle having an on-board obstacle recognition sensor and a receiving device, wherein the on-board obstacle recognition sensor is used to recognize obstacles of the vehicle, and the receiving device is used to receive an output signal of an off-board obstacle recognition sensor for recognizing obstacles (of the vehicle), wherein the vehicle includes a synchronization module, which is used to determine the orientation or posture of the off-board obstacle recognition sensor relative to the vehicle and / or relative to the on-board obstacle recognition sensor.

[0019] It can be provided that a grid diagram is displayed or represented in a vehicle by means of a display. In this case, it can be provided in particular that the vehicle is displayed integrated into the grid diagram. In addition or alternatively, it can be provided that the grid diagram is used to control automatic parking or guide the vehicle.

[0020] In a further advantageous embodiment of the invention, it is provided that in the grid image, information indicating that the means of transport is an obstacle is removed.

[0021] In a further advantageous embodiment of the invention, the vehicle assistance or control system comprises an in particular wireless communication system for transmitting output signals of the off-board obstacle detection sensor to a receiving device.

[0022] In a further advantageous embodiment of the invention, the off-board obstacle detection sensor is arranged in front of the parking space or parking bay.

[0023] In a further advantageous embodiment of the invention, the one or a further off-vehicle obstacle detection sensor is arranged in the parking space or parking bay.

[0024] It can be provided that the off-board obstacle recognition sensor is not fixed in position. In this case, it can be provided that the off-board obstacle recognition sensor is part of the autonomous driving robot or is installed on such a robot.

[0025] Off-board in the sense of the present invention means in particular not being part of a vehicle or not being fixedly connected to the vehicle. On-board in the sense of the present invention is in particular the opposite of off-board. On-board in the sense of the present invention means being integrated into a vehicle or at least fixedly connected to the vehicle.

[0026] The output signals associated with the on-vehicle obstacle recognition sensors and the off-vehicle obstacle recognition sensors are synonymous with the measured values ​​of these sensors or at least contain the measured values ​​of these sensors.

[0027] A grid diagram in the sense of the present invention is in particular synonymous with an occupation grid diagram or a grid diagram (placeholder grid diagram, grid diagram). In particular, it is provided that a grid (or cell, cell) of a grid diagram or a grid diagram can have at least two different states. A state indicating that there is an obstacle in the grid or cell and a state indicating that there is no obstacle in the grid or cell. However, it can also be provided that at least three states are displayed in the grid diagram or the grid diagram, wherein the third state indicates that it is not known whether the grid or cell is occupied, i.e. it is not known whether there is an obstacle in the grid or cell.

[0028] The measured value synchronization algorithm in the sense of the present invention is in particular an ICP algorithm. The ICP or iterative closest point algorithm in the sense of the present invention is in particular an algorithm that adapts point clouds (or cloud points, bivariate point distribution) to each other. In order to apply the method, it is particularly provided that the point clouds have been or will be approximately aligned with each other in advance. When executing the algorithm, it is particularly attempted that the point clouds are as good as possible consistent with each other by means of rotation and translation. Based on a set of approximately determined initial transformation parameters for rotation and translation, for this purpose, for each point from one point cloud, the closest point (closest point) to the corresponding point from the other point cloud is determined. Then the sum S of the distances of all these point pairs is formed, in particular the square. A measure of the quality of coordination between point clouds is thus obtained. The goal is in particular to minimize the optimization amount, i.e. the above-mentioned sum S, by changing the variation parameters. There are different methods for determining appropriate transformation parameters, which are partly based on the structure of the basic point cloud. The corresponding iterative process is continued until an acceptable optimal value is found, or the iterative process is interrupted if the desired optimal value cannot be found or the desired optimal value cannot be determined. In particular, it is provided here (see above) that the orientation of the non-vehicle obstacle detection sensor relative to the vehicle and / or relative to the vehicle obstacle detection sensor is determined by optimizing and / or minimizing the distance between

[0029] - between the rotational measurements of the off-board obstacle recognition sensor and the translational measurements of the on-board obstacle recognition sensor,

[0030] - between the measured values ​​of the rotation of the onboard obstacle recognition sensor and the measured values ​​of the translation of the off-board obstacle recognition sensor,

[0031] - between the rotational and translational measurements of the off-board obstacle recognition sensor and the measurements of the on-board obstacle recognition sensor, or

[0032] - between the measured values ​​of the onboard obstacle recognition sensor in rotation and translation and the measured values ​​of the off-board obstacle recognition sensor. In particular, it is provided that the rotation does not include more than one degree of freedom and the translation does not include more than two degrees of freedom. The function on which the optimization is based is, for example, the following:

[0033]

[0034] Here, N is the number of point pairs from the two point clouds used for the optimization. These are in particular adjacent measured values. R stands for rotation and T for translation or displacement. Here, EGOSi denotes the i-th measured value of the onboard obstacle recognition sensor (possibly minus the center of gravity of the N measured values). The same also applies to RMTSi related to the non-onboard obstacle recognition sensors. However, it is particularly provided in the context of the invention that the formula is not three-dimensional, but two-dimensional. Therefore, the formula can also be expressed as follows:

[0035]

[0036] Here, xEGOSi represents the x-component of the i-th measured value of the onboard obstacle recognition sensor (minus the center of gravity of N measured values ​​if necessary), and yEGOSi represents the corresponding value in the y direction. The same applies to xRMTSi and yRMTSi related to the non-onboard obstacle recognition sensor xT. xT represents a displacement or translation in the x direction, while yT represents a displacement or translation in the y direction.

[0037] In a particularly suitable manner, the angle of the position of the non-vehicle obstacle recognition sensor relative to the reference axis of the vehicle is additionally determined by another method, in particular by a marking on the non-vehicle obstacle recognition sensor, but in particular the distance between the vehicle-mounted obstacle recognition sensor and the non-vehicle obstacle recognition sensor is not determined. In this way, the number of degrees of freedom is reduced from three to two. Although the above formula includes three degrees of freedom, namely one rotational degree of freedom and two translational degrees of freedom, the following optimized formula is obtained by taking into account the angle θ relative to the reference axis, for example the longitudinal axis of the vehicle:

[0038]

[0039] Therefore, the optimization can only be determined for two degrees of freedom, namely for the rotational degree of freedom relative to the rotation R and the translational degree of freedom xT. If the number of measured values ​​is insufficient, past measured values ​​can be added. For example, a SLAM algorithm can be used for this.

[0040] In addition to simplifying the optimization by reducing the degrees of freedom, it can also be provided that the determination of the angle is used to check the plausibility of the automated driving. Thus, for example, automated driving of the vehicle is permitted only if the following conditions are met:

[0041]

[0042] A means of transport in the sense of the present invention may be a means of transportation. A means of transport in the sense of the present invention may be a means of transport for transporting people and / or goods, or may be understood as such. A means of transport in the sense of the present invention may be a driven vehicle. A driven vehicle in the sense of the present invention means in particular that a technical drive is provided, wherein it may be provided that the main components of the drive are arranged outside the vehicle, but preferably inside the vehicle or integrated in the vehicle. A driven vehicle in the sense of the present invention is in particular a vehicle that is not primarily driven by animal and / or human power. However, a driven vehicle in the sense of the present invention may optionally include a drive by wind and / or the sun. The drive in the sense of the present invention may be an internal combustion engine and / or an electric motor. A driven vehicle in the sense of the present invention is in particular a land vehicle and / or a motor vehicle. A motor vehicle in the sense of the present invention is in particular a land vehicle that can be used alone in road traffic. A motor vehicle in the sense of the present invention is in particular not limited to a land vehicle with an internal combustion engine. A motor vehicle in the sense of the present invention may also be understood as a vehicle driven by an electric motor, for example a vehicle for 3D mobility. A means of transport in the sense of the present invention is in particular a truck, in particular a truck with a tractor and a trailer. Here, the trailer may in particular be a container. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Further advantages and details are obtained from the following description of exemplary embodiments. Here, it is shown:

[0044] Figure 1 An embodiment of a transportation assistance or control system is shown in a schematic diagram.

[0045] Figure 2 An exemplary scenario of a motor vehicle approaching a parking space is shown, wherein a Figure 1 A transportation assistance or control system for assistance,

[0046] Figure 3 Shown with Figure 2 The grid map corresponding to the scene,

[0047] Figure 4 Show according to Figure 2 , but with the aid of an off-board obstacle detection sensor, the measuring points are shown.

[0048] Figure 5An exemplary embodiment is shown based on a grid matrix of measuring points which are obtained with the aid of onboard obstacle detection sensors and off-board obstacle detection sensors,

[0049] Figure 6 Shows a truck approaching a parking space.

[0050] Figure 7 Shows the truck backing into and approaching the Figure 6 Example of a grid diagram of parking space conditions,

[0051] Figure 8 Show that the process continues according to Figure 6 In an embodiment of the case, the truck is parked in reverse according to the non-vehicle obstacle recognition sensor. Figure 6 Parking spaces,

[0052] Fig. 9 An embodiment of a further scenario with a parking space and obstacles and the use of a mobile off-board obstacle recognition sensor as a pilot or navigator for a truck with an on-board obstacle recognition sensor is shown,

[0053] Fig.10 Shows the use of Fig. 9 An embodiment of a grid diagram of an on-board obstacle recognition sensor but without the output signal of the off-board obstacle recognition sensor as an obstacle,

[0054] Fig.11 An embodiment of a grid diagram using the output of a mobile off-board obstacle recognition sensor but eliminating trucks as known obstacles is shown,

[0055] Fig.12 Show according to Fig.10 and Fig.11 The grid maps of are superimposed into a combined grid map for truck control.

[0056] Fig.13 Show that the process continues according to Fig. 9 An embodiment of a situation in which a truck approaches a parking space and a mobile off-board obstacle recognition sensor moves into the parking space,

[0057] Fig.14 An embodiment of a merged grid map is shown, wherein a truck image that does not necessarily belong to the grid map is inserted for positioning.

[0058] Fig.15 Show that the process continues according to Fig.13 An embodiment of the case in which the truck is parked in a parking space with the assistance of an off-board obstacle recognition sensor,

[0059] Fig.16 An embodiment of a grid diagram based on output signals of an onboard obstacle recognition sensor of a truck, wherein the onboard obstacle recognition sensor is arranged on a tractor of the truck and the trailer of the truck causes a shadow behind the truck, and

[0060] Fig.17 An embodiment of a grid diagram using a combination of output signals of an onboard obstacle recognition sensor and an off-board obstacle recognition sensor is shown, wherein shadows behind a trailer are compensated by using the off-board obstacle recognition sensor. DETAILED DESCRIPTION

[0061] Figure 1 A vehicle assistance or control system is shown, which comprises at least one off-board obstacle recognition sensor RMTS and a vehicle, such as a vehicle VHCL, in particular a truck. The vehicle or vehicle VHCL comprises an on-board obstacle recognition sensor for recognizing obstacles of the vehicle and a receiving device IO for receiving output signals of the off-board obstacle recognition sensor RMTS. The data exchange between the vehicle VHCL and the off-board obstacle recognition sensor RMTS can be realized via a separate wireless communication connection or via signals by means of which the obstacle recognition is realized.

[0062] The means of transport or vehicle VHCL also includes a synchronization module, which is used to determine the orientation of the non-onboard obstacle recognition sensor RMTS relative to the means of transport or vehicle VHCL or relative to the onboard obstacle recognition sensor EGOS. In the present embodiment, the synchronization module includes a module ICP, in which a measurement value synchronization algorithm, such as an ICP algorithm, is implemented. In a supplementary embodiment, "1D tracking" of the non-onboard obstacle recognition sensor RMTS can also be performed, in particular marker-based "1D tracking". For this purpose, the means of transport or vehicle VHCL can have a camera system CAM, whose output signal or multiple output signals are analyzed by the tracking module TRK as follows, so that the direction of the means of transport or vehicle VHCL relative to the non-onboard obstacle recognition sensor RMTS (angle relative to the reference axis) is determined.

[0063] The vehicle or vehicle VHCL further comprises a map generator MG2 for generating a grid map EGOM from the output signals of the onboard obstacle recognition sensor EGOS. In the grid map EGOM, the surroundings of the vehicle VHCL are represented in the form of a grid, the grid surfaces of which are, for example, Figure 3As shown in , the state "unknown" U, the state "free" F and the state "occupied" B may be included. In addition, the vehicle VHCL includes a map generator MG1, by means of which a grid map RMTM is generated from the output signal of the non-vehicle obstacle recognition sensor RMTS. The merging module MPM combines the grid map EGOM and the grid map RMTM into a (merged) integrated grid map according to the posture or orientation of the vehicle VHCL relative to the non-vehicle obstacle recognition sensor RMTS, for example Figure 5 In this case, the grid surface is not displayed as occupied but rather as free, which corresponds to an obstacle that is detected by the non-vehicle obstacle detection sensor RMTS as belonging to the means of transport or vehicle VHCL.

[0064] It can be provided that the grid map MAP is displayed by means of a display DSP of the vehicle VHCL and / or is used by the control device CTRL in order to (automatically) move the vehicle VHCL.

[0065] The working principle of the above-mentioned transportation auxiliary or control system is explained according to the following figures. Figure 4 , Figure 2 A scenario with a parking space PL is also shown. Reference numeral 1 denotes a point detected as an obstacle by means of the non-vehicle obstacle detection sensor RMTS, and reference numeral 2 denotes a point detected as an obstacle by means of the vehicle-mounted obstacle detection sensor EGOS.

[0066] Figure 3 The corresponding grid diagram EGOM is shown, which is obtained by analyzing the output signals of the vehicle-mounted obstacle recognition sensor EGOS. Here, the transportation means VHCL and the non-vehicle-mounted obstacle recognition sensor RMTS are only shown in the grid diagram for better positioning. However, in one embodiment, they can also be part of the grid diagram EGOM. Figure 4 A parking space with points identified as obstacles by the off-board obstacle recognition sensor RMTS is shown (see above). The resulting grid map MAP is Figure 5 As shown in Figure 2 , 3 , 4 The relevant scenario involves the positioning of the off-board obstacle recognition sensor RMTL in front of the parking space PL.

[0067] Figure 6 Another scenario is shown in which the transport vehicle VHCL is a trailer truck LKW, wherein the onboard obstacle detection sensors are arranged in the tractor ZM but not in the trailer AUFL. Furthermore, it is provided that the off-board obstacle detection sensors RMTS are arranged inside the parking space PL2. Figure 7The situation in which the truck LKW has already passed the parking space PL2 is shown, more precisely according to the situation in the corresponding grid map MAP. Figure 8 Continue in.

[0068] Fig. 9 , Fig.13 and Fig.15 A different scenario for another scenario or embodiment of the above-described vehicle assistance or control system is shown. Reference numeral PL3 denotes the boundary of a parking space and reference numeral OB3 denotes a further obstacle. The purpose is to park the trailer truck LKW in the parking space formed by the boundary PL3. In the scenario shown or Fig. 9 In the scenario shown, the off-board obstacle recognition sensor RMTS is not arranged in a fixed position, but is arranged on the autonomous robot vehicle. As an autonomous pilot or navigator, the off-board obstacle recognition sensor RMTS guides the trailer-truck LKW to the desired parking space and assists in parking, as shown in the following figure: For clarification, Fig.10 and Fig.11 First, the grid graphs EGOM and RMTM are shown with the corresponding objects removed as obstacles. That is, Fig.10 A grid diagram EGOM is shown, in which an off-board obstacle recognition sensor that is identified as an obstacle is not displayed as an obstacle, but rather as an unknown surface U including a projected “visual shadow”, Fig.11 The grid diagram EGOM is shown, in which the non-vehicle obstacle recognition sensor that is identified as an obstacle is not displayed as an obstacle, but as an unknown surface U including a projected “visual shadow”. Fig.10 and Fig.11 The grid diagram shown in Fig.12 The grid map MAP.

[0069] exist Fig.13 , the trailer truck LKW has moved closer to the parking space. In addition, the off-board obstacle detection sensor RMTS has entered the parking space formed by the parking space boundary PL3. Fig.14 The resulting grid map MAP is shown. In this case, the trailer truck LKW is placed symbolically in the grid map. This is mainly used for orientation, wherein the trailer truck LKW is not part of the grid map MAP, but only serves to explain the content disclosed by the present invention. However, it can also be provided that in one embodiment, the grid map MAP is supplemented by a corresponding symbolic representation of the trailer truck LKW. Fig.15 In the scenario shown, the trailer truck LKW drives past the parking space and reverses in order to park in the parking space formed by the parking space boundary PL3. Fig.16The grid diagram EGOM shown for the corresponding scenario in shows a particular problem. Here, a visible shadow with the reference symbol SIS can be seen, which is due to the fact that the on-board obstacle detection sensor EGOS is installed on the tractor ZM of the trailer-truck and not on the trailer AUFL. This means that the trailer AUFL of the trailer-truck LKW creates a visible shadow SIS behind. This can be compensated by the off-board obstacle detection sensor RMTS in the parking space, as can be seen from the corresponding grid diagram MAP, as shown in Fig.17 shown.

[0070] The parking space boundary PL3 can also represent the boundary of a loading or unloading ramp or be part of such a loading or unloading ramp. It can be provided that the off-board obstacle detection sensor or its movable base is so low that it can pass under the trailer AUFL or tractor ZUG so that it can guide the next vehicle.

[0071] It can be provided that the control device of the non-vehicle obstacle detection sensor is controlled as a function of the quality of determining the orientation of the non-vehicle obstacle detection sensor relative to the vehicle and / or relative to the vehicle-mounted obstacle detection sensor. This is used, for example, to provide feedback on whether the vehicle is following the non-vehicle obstacle detection sensor in a suitable manner and / or to ensure that the output signals of the non-vehicle obstacle detection sensor and the vehicle-mounted obstacle detection sensor are sufficient for determining the orientation.

Claims

1. A method for operating a vehicle assistance or control system having a vehicle (VHCL) and an off-board device for detecting obstacles of the vehicle (VHCL) - an obstacle recognition sensor (RMTS), wherein the vehicle comprises an onboard obstacle recognition sensor (EGOS) for recognizing obstacles of the vehicle (VHCL), the first grid map is generated based on the off-board obstacle recognition sensor, the second grid map is generated based on the onboard obstacle recognition sensor or on the vehicle, and wherein, A merged grid map is generated based on the first grid map and the second grid map, wherein the merged grid map is generated based on the orientation of the non-vehicle obstacle recognition sensor relative to the vehicle and / or relative to the vehicle-mounted obstacle recognition sensor (EGOS), wherein the orientation of the non-vehicle obstacle recognition sensor relative to the vehicle and / or relative to the vehicle-mounted obstacle recognition sensor (EGOS) is determined by optimizing and / or minimizing a distance, wherein the distance is - between the measured values ​​of the rotation of the off-board obstacle recognition sensor and the measured values ​​of the translation of the on-board obstacle recognition sensor, - between the measured values ​​of the rotation of the onboard obstacle recognition sensor and the measured values ​​of the translation of the off-board obstacle recognition sensor, - between the rotational and translational measurements of the off-board obstacle recognition sensor and the measurements of the on-board obstacle recognition sensor, or - between the rotational and translational measured values ​​of the onboard obstacle recognition sensor and the measured values ​​of the off-board obstacle recognition sensor.

2. The method according to claim 1, characterized in that In the first grid map or the merged grid map, the status of the grids showing the means of transport as obstacles is set to unoccupied.

3. The method according to claim 1, characterized in that The orientation of the off-board obstacle detection sensor relative to the vehicle and / or relative to the on-board obstacle detection sensor (EGOS) is determined based on the measured values ​​of the off-board obstacle detection sensor and the measured values ​​of the on-board obstacle detection sensor.

4. The method according to claim 1, characterized in that: The rotation does not include more than one degree of freedom and the translation does not include more than two degrees of freedom.

5. The method according to claim 1, characterized in that The non-vehicle obstacle recognition sensor comprises a marker, by means of which the angle of the non-vehicle obstacle recognition sensor position relative to a reference axis of the vehicle is determined, but the distance between the onboard obstacle recognition sensor and the non-vehicle obstacle recognition sensor is not determined.

6. The method according to claim 5, characterized in that The translation is reduced by one degree of freedom by means of the angle.

7. The method according to claim 1, characterized in that Use LiDAR as an onboard obstacle recognition sensor (EGOS) and / or a non-onboard obstacle recognition sensor (RMTS).

8. The method according to claim 1, characterized in that The measured values ​​of the non-vehicle obstacle recognition sensor (RMTS) are wirelessly transmitted from the non-vehicle obstacle recognition sensor (RMTS) to the vehicle-mounted obstacle recognition sensor (EGOS).

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