Transportation assistance or control system and its use as a pilot

Abstract

A transport assistance or control system comprising a transport means (VHCL) and a movable offboard obstacle detection sensor (RMTS) for detecting obstacles for the transport means (VHCL), wherein the transport means includes an onboard obstacle detection sensor (EGOS) for detecting obstacles for the transport means (VHCL), and wherein the transport assistance or control system comprises a synchronization module with a three-degrees-limited iterative closest point algorithm for determining the orientation of the offboard obstacle detection sensor with respect to the transport means and / or with respect to the onboard obstacle detection sensor (EGOS) as a function of an output signal of the offboard obstacle detection sensor and an output signal of the onboard obstacle detection sensor.

Description

The invention relates to a transport assistance or control system. The invention further relates to the use of the aforementioned transport assistance or control system as a pilot for a means of transport. US Patent 2016 / 0368489 A1 discloses a parking assistance system in which a communication link is established between an external parking automation system and a vehicle, measuring the distance between a detected object and the vehicle. Based on the measured distance, a brake control system of the vehicle is activated. US Patent 2018 / 0012497 A1 discloses a vehicle navigation system for automatically guiding a vehicle from a starting position to a destination position. This system may include communication between a sensor outside the vehicle and a sensor on the vehicle, for example, for vehicle guidance. US Patent 2016 / 0368489 A1 discloses a system for guiding motor vehicles based on image data. US patent 2005 / 0 240 323 A1 proposes a parking attendant robot that uses a camera to analyze both the vehicle and the parking space, thereby determining the best way for the vehicle to park efficiently. Using real-time data such as steering angle and speed, the robot provides precise parking instructions to the vehicle user. JP 2007-233771A discloses a system for guiding an autonomous vehicle to a parking space using a guidance robot. The guidance robot recognizes the shape and surroundings of the vehicle to calculate the best route to the parking space. German patent DE 10 2017 211 523 A1 discloses an intelligent navigation system for vehicles that can predict when a driver will need assistance. By connecting two vehicles, the system allows one vehicle to take control while the other steers. In DE 10 2018 214 697 A1, a device is described which uses a camera to detect road areas and converts them into a bird's-eye view, thus creating or supplementing a grid map. The object of the invention is to provide an improved or alternative transportation assistance or control system. The aforementioned task is solved by a transport assistance or control system comprising a transport means and an offboard obstacle detection sensor, which is in particular autonomously movable, for detecting obstacles for the transport means, wherein the transport means comprises an onboard obstacle detection sensor for detecting obstacles for the transport means, and wherein the transport assistance or control system comprises a synchronization module with an iterative closest point algorithm limited to three degrees of freedom for determining the orientation of the offboard obstacle detection sensor with respect to the transport means and / or with respect to the onboard obstacle detection sensor as a function of an output signal of the offboard obstacle detection sensor and an output signal of the onboard obstacle detection sensor. In an advantageous embodiment of the invention, the offboard obstacle detection sensor comprises a marker, and the means of transport comprises at least one camera for detecting the marker and a tracking module for determining the angle of the position of the offboard obstacle detection sensor with respect to a reference axis of the means of transport, but in particular not the distance between the onboard obstacle detection sensor and the offboard obstacle detection sensor. A reference axis within the meaning of this disclosure can, for example, be the longitudinal axis of a vehicle if the means of transport is a vehicle. In a further advantageous embodiment of the invention, the orientation of the offboard obstacle detection sensor with respect to the means of transport and / or with respect to the onboard obstacle detection sensor can also be determined as a function of the angle, the output signal of the offboard obstacle detection sensor, and the output signal of the onboard obstacle detection sensor. In a further advantageous embodiment of the invention, the transport means (VHCL) comprises a grid map generated by the synchronization module. In a further advantageous embodiment of the invention, the grid map includes information relating to an output signal of the onboard obstacle detection sensor, into which information relating to the output signal of the offboard obstacle detection sensor is integrated. It is particularly provided that the grid map displays the state "free" or "unoccupied" for which the output signal of the onboard obstacle detection sensor and / or the output signal of the offboard obstacle detection sensor indicates the state "free" or "unoccupied". In a further advantageous embodiment of the invention, information identifying the transport means as an obstacle is removed from the grid map. In a further advantageous embodiment of the invention, the onboard obstacle detection sensor and / or the offboard obstacle detection sensor is or comprises a lidar. In a further advantageous embodiment of the invention, the means of transport is a truck with a tractor unit and a semi-trailer. In a further advantageous embodiment of the invention, the onboard obstacle detection sensor is part of the tractor unit. In a further advantageous embodiment of the invention, the camera is part of the tractor unit. In a further advantageous embodiment of the invention, at least one rear-facing camera and / or at least one forward-facing camera is implemented in each of the left and / or right side mirrors of the tractor unit. In a further advantageous embodiment of the invention, the transport assistance or control system comprises a, in particular bidirectional, wireless communication link between the offboard obstacle detection sensor and the transport vehicle or the onboard obstacle detection sensor. The aforementioned task is further accomplished by using an offboard obstacle detection sensor of a aforementioned transport assistance or control system according to one of the preceding claims as a guide for the transport vehicle, wherein the offboard obstacle detection sensor guides the transport vehicle from a starting point to a desired location, in particular along a predetermined trajectory. It may be provided that the transport vehicle transmits its desired location to the offboard obstacle detection sensor. The desired route or a corresponding trajectory is then communicated, for example, by the offboard obstacle detection sensor or by a central control unit superior to it for controlling offboard obstacle detection sensors or a plurality of offboard obstacle detection sensors. The aforementioned task is also solved by a means of transport of a aforementioned means of transport assistance or control system, for example by a means of transport with an onboard obstacle detection sensor for detecting obstacles for the means of transport, and with a receiving device for receiving an output signal from an offboard obstacle detection sensor for detecting obstacles (for the means of transport), wherein the means of transport includes a synchronization module for determining the orientation or pose of the offboard obstacle detection sensor with respect to the means of transport and / or with respect to the onboard obstacle detection sensor. It may be provided that the grid map is displayed on a screen within the means of transport. In particular, it may be provided that the means of transport is integrated into the grid map. Alternatively or additionally, it may be provided that the grid map serves as a control system for autonomous parking or driving of the means of transport. In a further advantageous embodiment of the invention, the transport assistance or control system comprises a communication system, in particular a wireless one, for transmitting an output signal from the offboard obstacle detection sensor to the receiving device. Offboard, as used in this disclosure, specifically means not being part of the means of transport or not being permanently attached to the means of transport. Onboard, as used in this disclosure, specifically means the opposite of offboard. Onboard, as used in this disclosure, specifically means integrated into a means of transport or at least permanently attached to it. The output signal with respect to onboard obstacle detection sensors and offboard obstacle detection sensors is synonymous with measured values ​​of these sensors or at least contains measured values ​​of these sensors. A grid map within the meaning of this disclosure is, in particular, synonymous with occupancy grid map or grid map. It is specifically provided that the grids (or cells) of the grid map can assume at least two different states: one indicating that an obstacle is present in the grid or cell, and one indicating that no obstacle is present. However, it can also be provided that at least three states are displayed in the grid map, the third state indicating that it is unknown whether the grid or cell is occupied or unoccupied, i.e., whether an obstacle is present in the grid or cell. A measurement synchronization algorithm within the meaning of this disclosure is, in particular, an ICP algorithm. An ICP, or Iterative Closest Point Algorithm, within the meaning of this disclosure is, according to the invention, an algorithm that makes it possible to align point clouds. For the application of the method, it is particularly provided that the point clouds are or are pre-aligned approximately. In carrying out the algorithm, particular attempts are made to align the point clouds as closely as possible by means of rotation and translation. Starting from a set of approximately determined initial transformation parameters for rotation and translation, the nearest point (closest point) in the other point cloud is determined for each point from one point cloud. Subsequently, the sum S, in particular the squares, of the distances across all these point pairs is calculated.This yields a measure of the quality of the agreement between the point clouds. The primary goal is to minimize this optimization measure, i.e., the aforementioned sum S, by modifying the transformation parameters. Various approaches exist for determining suitable transformation parameters, some of which are based on the structure of the underlying point clouds. A corresponding iterative process is continued until an acceptable optimum is found, or it is terminated if no desired optimum can be found or determined.It is specifically provided that the orientation of the offboard obstacle detection sensor with respect to the means of transport and / or with respect to the onboard obstacle detection sensor is determined by optimizing and / or minimizing the distances between: rotated measurements of the offboard obstacle detection sensor and shifted measurements of the onboard obstacle detection sensor; rotated measurements of the onboard obstacle detection sensor and shifted measurements of the offboard obstacle detection sensor; rotated and shifted measurements of the offboard obstacle detection sensor and measurements of the onboard obstacle detection sensor; or rotated and shifted measurements of the onboard obstacle detection sensor and measurements of the offboard obstacle detection sensor. It is specifically provided that the rotation does not exceed one degree of freedom and the shift does not exceed two degrees of freedom.The underlying function for the optimization is, for example, as follows: Here, N is the number of point pairs from the two point clouds intended for optimization. These are, in particular, adjacent measured values. R represents the rotation and T represents the translation or displacement. Here, EGO denotes an i-th measured value (possibly subtracting the centroid of the N measured values) of the onboard obstacle detection sensor. The same applies to RMTS with respect to the offboard obstacle detection sensor. However, for the purposes of this disclosure, it is specifically intended that the equation is not three-dimensional but only two-dimensional. Therefore, the equation can also be represented as follows: Here, xEGOS denotes the x-component of an i-th measurement (possibly subtracting the centroid of the N measurements) from the onboard obstacle detection sensor, and yEGOS denotes the corresponding value in the y-direction. The same applies to xRMTSi and yRMTSi with respect to the offboard obstacle detection sensor. xT denotes the displacement or translation in the x-direction, and yT denotes the translation or displacement in the y-direction. It is provided in a particularly suitable manner to additionally determine, by another method, in particular by a marker on the offboard obstacle detection sensor, the angle of the position of the offboard obstacle detection sensor with respect to a reference axis of the means of transport, but not, however, the distance between the onboard obstacle detection sensor and the offboard obstacle detection sensor. In this way, the number of degrees of freedom is reduced from three to two. While the equation above includes three degrees of freedom, namely one rotational degree of freedom and two translational degrees of freedom, taking into account the angle θ with respect to a reference axis, such as the longitudinal axis of a vehicle, results in the following equation for optimization: The optimization therefore only needs to be determined for two degrees of freedom: one rotational degree of freedom with respect to the rotation R and one translational degree of freedom xT. If the number of measurements is insufficient, historical measurements can be used. For example, a SLAM algorithm can be employed for this purpose. Instead of simplifying optimization by reducing the degrees of freedom, it may also be possible to use the angle determination for plausibility checks or for querying in autonomous driving scenarios. For example, autonomous driving of the vehicle could only be permitted if the following conditions are met: A means of transport within the meaning of this disclosure can be a means of locomotion. A means of transport within the meaning of this disclosure can be a means of transport for the carriage of persons and / or goods, or be understood as such. A means of transport within the meaning of this disclosure can be a powered vehicle. A powered vehicle within the meaning of this disclosure means, in particular, that a technical drive is provided, whereby it may be provided that essential parts of the drive are arranged outside the vehicle, but preferably inside or integrated into the vehicle. A powered vehicle within the meaning of this disclosure is, in particular, a vehicle that is not primarily driven by the power of animals and / or humans. However, a powered vehicle within the meaning of this disclosure may optionally include propulsion by wind and / or sun.A propulsion system within the meaning of this disclosure can be an internal combustion engine and / or an electric motor. A powered vehicle within the meaning of this disclosure is, in particular, a land vehicle and / or a motor vehicle. A motor vehicle within the meaning of this disclosure is, in particular, a land vehicle that can be used individually in road traffic. Motor vehicles within the meaning of this disclosure are not limited to land vehicles with internal combustion engines. A motor vehicle within the meaning of this disclosure can also be understood to be a motor-driven vehicle, for example, a vehicle for 3D mobility. A means of transport within the meaning of this disclosure is, in particular, a truck, especially a truck with a tractor unit and a semi-trailer. The semi-trailer can, in particular, be a container. Further advantages and details will become apparent from the following description of exemplary embodiments. Figure 1 shows an exemplary embodiment of a vehicle assistance or control system in a schematic diagram; Figure 2 shows an exemplary scenario for a motor vehicle approaching a parking space, where a vehicle assistance or control system according to Figure 1 is provided for assistance; Figure 3 shows a grid map corresponding to the scene in Figure 2; Figure 4 shows the situation according to Figure 2, but with measurement points represented by an offboard obstacle detection sensor; Figure 5 shows an exemplary embodiment for a grid matrix based on measurement points obtained by means of an onboard obstacle detection sensor and an offboard obstacle detection sensor; Figure 6 shows a situation in which a truck approaches a parking space.Figure 7 shows an embodiment of a grid map relating to a situation in which a truck reverses into the parking space shown in Figure 6; Figure 8 shows an embodiment for a further development of the situation shown in Figure 6, wherein the truck reverses into the parking space shown in Figure 6 with the assistance of an offboard obstacle detection sensor; Figure 9 shows an embodiment for a further scenario with a parking space and an obstacle object, and using a mobile offboard obstacle detection sensor to act as a guide or pilot for a truck with an onboard obstacle detection sensor; Figure 10 shows an embodiment of a grid map using the output signal of the onboard obstacle detection sensor shown in Figure 9, but with the offboard obstacle detection sensor removed as an obstacle.Fig. 11 shows an embodiment of a grid map using the output signal of the mobile offboard obstacle detection sensor, but without the truck as a known obstacle; Fig. 12 shows a superposition of the grid maps according to Fig. 10 and Fig. 11 to form a consolidated grid map for use in controlling the truck; Fig. 13 shows an embodiment for continuing the situation according to Fig. 9, wherein the truck approaches the parking space and the mobile offboard obstacle detection sensor has been moved into the parking space; Fig. 14 shows an embodiment of a consolidated grid map, wherein an image of the truck is included for orientation purposes, which does not necessarily belong to the grid map; Fig. 15 shows an embodiment for continuing the situation according to Fig. 13, wherein the truck performs a maneuver to park in the parking space with the assistance of the offboard obstacle detection sensor.Figure 16 shows an embodiment of a grid map based on the output signal of the onboard obstacle detection sensor of the truck, wherein the onboard obstacle detection sensor is arranged on the tractor unit of the truck and a semi-trailer of the truck causes shadowing behind the truck; Figure 17 shows an embodiment of a consolidated grid map using the output signals of the onboard obstacle detection sensor and the offboard obstacle detection sensor, wherein the shadowing behind the semi-trailer is compensated by using the offboard obstacle detection sensor; and Figure 18 shows a method for controlling the movement of the offboard obstacle sensor. Fig. 1 shows a transport assistance or control system comprising at least one mobile or movable offboard obstacle detection sensor (RMTS) and a transport vehicle, such as a vehicle (VHCL), in particular a truck. The transport vehicle (VHCL) comprises an onboard obstacle detection sensor for detecting obstacles for the transport vehicle and a receiving device (IO) for receiving an output signal from the offboard obstacle detection sensor (RMTS). Data exchange between the transport vehicle (VHCL) and the offboard obstacle detection sensor (RMTS) can take place via a separate wireless communication link or via a signal by which obstacle detection is performed. The transport vehicle (VHCL) further comprises a synchronization module for determining the orientation of the offboard obstacle detection sensor (RMTS) relative to the VHCL and / or the onboard obstacle detection sensor (EGOS). In the present embodiment, the synchronization module includes an ICP module in which a measurement synchronization algorithm, such as an ICP algorithm, is implemented. In a further embodiment, 1D tracking, in particular marker-based 1D tracking of the offboard obstacle detection sensor (RMTS), can also be performed. For this purpose, the VHCL can have a camera system (CAM) whose output signal(s) are evaluated by a tracking module (TRK) to determine the direction (angle relative to a reference axis) of the VHCL relative to the offboard obstacle detection sensor (RMTS). The transport vehicle VHCL also includes a map generator MG2 for generating a grid map EGOM from the output signal of the onboard obstacle detection sensor EGOS. The EGOM grid map represents the environment of the transport vehicle VHCL as a grid, whose grid areas, as shown for example in Fig. 3, can represent the state "unknown" U, the state "clear" F, and the state "occupied" B. Furthermore, the transport vehicle VHCL includes a map generator MG1, which generates a grid map RMTM from the output signal of the offboard obstacle detection sensor RMTS. A merging module MPM combines the EGOM grid map and the RMTM grid map into a (consolidated) integrated grid map, as shown for example in Fig. 5, depending on the pose or orientation of the transport vehicle VHCL relative to the offboard obstacle detection sensor RMTS.In this process, grid areas are not displayed as occupied but as free, which correspond to obstacles identified by the offboard obstacle detection sensor RMTS as belonging to the means of transport or vehicle VHCL. It may be provided that the grid map MAP is displayed by means of a DSP display of the transport vehicle VHCL and / or is used by a CTRL controller to move the transport vehicle VHCL (autonomously). The functionality of the aforementioned transport assistance or control system is explained with reference to the following figures. Figure 2, like Figure 4, shows a scenario with a parking space PL. Reference numeral 1 indicates the points that are detected as obstacles by the offboard obstacle detection sensor RMTS, and reference numeral 2 indicates the points that are detected as obstacles by the onboard obstacle detection sensor EGOS. Fig. 3 shows the corresponding grid map EGOM, which is obtained by evaluating the output signal of the onboard obstacle detection sensor EGOS. The transport vehicle VHCL and the offboard obstacle detection sensor RMTS are shown in the grid map EGOM for orientation purposes only. However, they can also be included in the grid map EGOM in some configurations. Fig. 4 shows the parking space with the points that are detected as obstacles by the offboard obstacle detection sensor RMTS (see above). The resulting grid map MAP is shown in Fig. 5. The scenario described in Figs. 2, 3, 4, and 5 involves moving the offboard obstacle detection sensor RMTLs in front of the parking space PL. Fig. 6 shows another scenario where the transport vehicle VHCL is a semi-trailer truck (LKW), with the onboard obstacle detection sensor located in the tractor unit (ZM) but not in the semi-trailer (AUFL). Furthermore, the offboard obstacle detection sensor (RMTS) is located inside the parking space (PL2). Fig. 7 shows the situation where the truck has passed the parking space (PL2), based on a corresponding grid map (MAP). A parking maneuver by the truck (LKW) is shown, which continues in Fig. 8. Figures 9, 13, and 15 show various scenes of a further scenario or embodiment for the aforementioned transport assistance or control system. Reference numeral PL3 denotes the boundary of a parking space, and OB3 denotes another obstacle. The goal is to park the semi-trailer truck in the parking space defined by the boundary PL3. In the depicted scenario, or in the scene shown in Figure 9, the offboard obstacle detection sensor RMTS is not stationary but mounted on an autonomously driving robot vehicle. As an autonomously operating guide or pilot, the offboard obstacle detection sensor RMTS leads the semi-trailer truck to the desired parking space and assists with parking, as illustrated below with reference to the figures: For clarification, Figures 10 and 11 first show the grid maps EGOM and RMTM, respectively, already cleared of their respective partners as obstacles.Figure 10 shows the EGOM grid map, where the offboard obstacle detection sensor, identified as an obstacle, is not represented as an obstacle but as an unknown area U including the cast "visual shadow". Figure 11 shows the EGOM grid map, where the offboard obstacle detection sensor, identified as an obstacle, is not represented as an obstacle but as an unknown area U including the cast "visual shadow". Combining the grid maps shown in Figures 10 and 11 yields the MAP grid map shown in Figure 12. Figure 13 depicts a scene in which the semi-trailer truck has moved closer to the parking space. The offboard obstacle detection sensor RMTS has also moved into the parking space defined by the parking space boundary PL3. The resulting grid map MAP is shown in Figure 14. The semi-trailer truck is symbolically placed in the grid map. This serves primarily for orientation purposes; the semi-trailer truck is not part of the grid map MAP but is only used to illustrate this disclosure. However, it is also possible that in one embodiment the grid map MAP is supplemented by a corresponding symbolic representation of the semi-trailer truck. In the scene shown in Figure 15, the semi-trailer truck has driven past the parking space and is reversing to park in the space defined by the parking space boundary PL3.The particular problem is illustrated by the grid map EGOM, shown in Fig. 16 for the corresponding scene. A visual shadow, labeled SIS, is visible, resulting from the fact that the onboard obstacle detection sensor EGOS is mounted on the tractor unit ZM of the semi-trailer truck LKW and not on the trailer AUFL. This means that the trailer AUFL of the semi-trailer truck creates a rear visual shadow SIS. This shadow is compensated for by the offboard obstacle detection sensor RMTS in the parking space, as shown in the corresponding grid map MAP, depicted in Fig. 17. The parking space boundary PL3 can also be, or represent, a boundary of a loading or unloading ramp, or be part of such a loading or unloading ramp. It may be designed so that the offboard obstacle detection sensor or its mobile base is low enough to pass under the trailer (AUFL) or the tractor unit (ZU), thus guiding the next vehicle. It may be provided that the control of the offboard obstacle detection sensor is dependent on a certain level of accuracy in determining the orientation of the offboard obstacle detection sensor relative to the means of transport and / or relative to the onboard obstacle detection sensor. This serves, for example, as feedback on whether the means of transport is following the offboard obstacle detection sensor appropriately and / or to ensure that the output signals of the offboard obstacle detection sensor and the onboard obstacle detection sensor are sufficient for determining the orientation. An exemplary implementation of this procedure is shown in Fig. 18, where in step S101 the accuracy G (= 1 / S or 1 / S (R,T) or 1 / S (R, xT)) is read or determined to establish the orientation of the offboard obstacle detection sensor relative to the transport vehicle (VHCL or truck) or relative to the onboard obstacle detection sensor. If the accuracy G is less than the limit value SG, the corresponding query S102 is followed in step S103 by a correction of the offboard obstacle detection sensor's movement. This correction can, for example, involve reversing, i.e., a movement relative to the assumed direction of the transport vehicle, and / or a lateral movement relative to the intended trajectory of the planned movement of the offboard obstacle detection sensor. If, on the other hand, the quality G is not less than the limit value SG, the offboard obstacle detection sensor continues its movement in the planned manner in a step S104 following query S102.With regard to the scenario shown in Fig. 15, the offboard obstacle detection sensor would ensure sufficient coverage of the measured values ​​using the described method. Therefore, in the scenario shown in Fig. 15, the offboard obstacle detection sensor would not immediately move to the end of the parking space, but rather gradually, following the movement of the vehicle and potentially along the right edge. A similar motion correction can also be achieved by comparing the offboard obstacle sensor's view of the vehicle with the known geometry of the vehicle. Based on this comparison, the offboard obstacle sensor can adjust its trajectory, or its movement in general, to the situation or to follow the vehicle. However, it can also be provided that, by evaluating the comparison of the vehicle's geometry with the measurement points identified by the offboard obstacle sensor as the vehicle, an angle is determined—either as an alternative or in addition to the described method using the marker—which is also used to save a degree of freedom when determining the vehicle's orientation relative to the offboard obstacle sensor.

Claims

A transport assistance or control system comprising a transport means (VHCL) and a movable offboard obstacle detection sensor (RMTS) for detecting obstacles for the transport means (VHCL), wherein the transport means includes an onboard obstacle detection sensor (EGOS) for detecting obstacles for the transport means (VHCL), and wherein the transport assistance or control system comprises a synchronization module with a three-degrees-limited iterative closest point algorithm for determining the orientation of the offboard obstacle detection sensor with respect to the transport means and / or with respect to the onboard obstacle detection sensor (EGOS) as a function of an output signal of the offboard obstacle detection sensor and an output signal of the onboard obstacle detection sensor. Transport assistance or control system according to claim 1, characterized in that the offboard obstacle detection sensor comprises a marker. Transport assistance or control system according to claim 2, characterized in that the transport means (VHCL) comprises at least one camera for detecting the marker and a tracking module for determining the angle of the position of the offboard obstacle detection sensor in relation to a reference axis of the transport means. Transport assistance or control system according to claim 3, characterized in that the orientation of the offboard obstacle detection sensor with respect to the transport means and / or with respect to the onboard obstacle detection sensor can also be determined depending on the angle, the output signal of the offboard obstacle detection sensor and the output signal of the onboard obstacle detection sensor. Transport assistance or control system according to one of the preceding claims, characterized in that the transport means (VHCL) comprises a grid map generated by means of the synchronization module. Transport assistance or control system according to claim 5, characterized in that the grid map comprises information relating to an output signal of the onboard obstacle detection sensor (EGOS), into which information relating to the output signal of the offboard obstacle detection sensor is integrated. Transport assistance or control system according to claim 6, characterized in that information indicating the transport means as an obstacle is removed from the grid map. Transport assistance or control system according to one of the preceding claims, characterized in that the onboard obstacle detection sensor (EGOS) and / or the offboard obstacle detection sensor (RMTS) is or comprises a lidar. Transport assistance or control system according to one of the preceding claims, characterized in that the transport means is a truck (lorry) with a tractor unit and a semi-trailer. Use of an offboard obstacle detection sensor of a transport assistance or control system according to one of the preceding claims as a guide for the transport means, wherein the offboard obstacle detection sensor guides the transport means from a starting point to a desired location, in particular along a predetermined trajectory.

Images