Procedure for maneuvering a vehicle in a formally incorrectly resolvable situation

Abstract

The invention relates to a method (100) for maneuvering a vehicle (1) in a formally incorrectly resolvable situation, comprising the following steps: - detecting (101) the formally incorrectly resolvable situation on the basis of an analysis of sensor data, wherein the sensor data result from a detection of at least one sensor (2) of the vehicle (1), - initiating (102) a transmission of a description of the formally incorrectly resolvable situation to an external data processing device (3), - receiving (103) at least one instruction from the external data processing device (3), wherein the at least one instruction comprises a maneuvering strategy for the formally incorrectly resolvable situation, - determining (104) a trajectory for the vehicle (1) for the formally incorrectly resolvable situation on the basis of an evaluation of the at least one received instruction, - initiating (105) the maneuvering of the vehicle (1) based on the determined trajectory. Furthermore, the invention relates to a computer program, a device, and a storage medium for this purpose.

Description

[0001] The invention relates to a method for maneuvering a vehicle in a formally incorrectly resolvable situation. Furthermore, the invention relates to a computer program, a device, and a storage medium for this purpose. State of the art

[0002] Autonomous vehicles without human drivers (L4-5) occasionally encounter regulatory dead ends, e.g., incorrectly signposted construction sites from which there is no escape except by violating a rule. This leads, for example, to an interruption of function or a reversion to a "minimum risk maneuver," e.g., stopping in one lane, and can also trigger negative consequences, e.g., traffic jams.

[0003] According to various state-of-the-art approaches, the problem and behavior described above require human intervention, which is resolved, for example, by remote operation by specialist personnel. Often, dispatching a human driver to the location of the problem may also be necessary. Negative effects such as traffic jams or the blocking of emergency vehicles may lead to fundamental consequences for the manufacturers or operators, such as the revocation of their operating license. People are typically better able to assess the situation and develop strategies that lead to a sufficiently safe solution to the problem despite a formal rule violation, e.g., ignoring incorrect signage.Because these situations occur rarely and are highly individual, they are considered "long-tail" problems that typically cannot be addressed in machine learning due to the lack of sufficient training data. Due to the highly individual nature of the situation, machine-based strategies such as the general lowering of constraints or rules do not necessarily lead to the best solutions. These strategies typically lead to the targeted lowering of one condition or rule, i.e., the violation of one rule, but not the violation of the others. Disclosure of the invention

[0004] The invention relates to a method having the features of claim 1, a computer program having the features of claim 8, a device having the features of claim 9, and a computer-readable storage medium having the features of claim 10. Further features and details of the invention emerge from the respective subclaims, the description, and the drawings. Features and details described in connection with the method according to the invention naturally also apply in connection with the computer program according to the invention, the device according to the invention, and the computer-readable storage medium according to the invention, and vice versa, so that reciprocal reference is always possible with regard to the disclosure of the invention.

[0005] The subject matter of the invention is, in particular, a method for maneuvering a vehicle in a formally incorrectly resolvable situation, comprising the following steps, wherein the steps can be carried out repeatedly and / or sequentially. The formally incorrectly resolvable situation can, for example, be incorrect signage, an accident, or a construction site, and can be formally incorrectly resolvable in that it is not possible to travel without violating at least one rule, such as crossing a solid line. The vehicle can have a planning function that calculates a safe trajectory for the vehicle based on a perception and known rules. In particular, there are situations in which the set of solutions is zero, or where confidence in a solution is not sufficiently high. These situations are, in particular, the formally incorrectly resolvable situations.Maneuvering can, for example, be an automated driving along a predetermined or calculated trajectory, where the trajectory can describe a movement of the vehicle through space, which can also include an acceleration and / or braking process.

[0006] The formally incorrectly resolvable situation can also be described as a situation in which a predefined rule is broken, which is used for the at least partially automated maneuvering of the vehicle.

[0007] In a first step, the formally incorrectly resolvable situation is preferably detected based on an analysis of sensor data, wherein the sensor data results from the detection of at least one sensor of the vehicle. The at least one sensor can be, for example, a camera sensor, a radar sensor, an ultrasonic sensor, and / or a LiDAR sensor. The sensor data can accordingly include image data, radar data, ultrasonic data, and / or LiDAR data. The analysis can, for example, be a pattern or object detection in the sensor data.

[0008] In a further step, a transmission of a description of the formally incorrectly resolvable situation to an external data processing device is preferably initiated. The description can be a problem description of the formally incorrectly resolvable situation, for example describing an existing obstacle such as a vehicle involved in an accident or a construction site. The description can be generated on the basis of the detected formally incorrectly resolvable situation and / or the analysis of the sensor data. The generation of the description can be carried out, for example, by a processor of an on-board computer of the vehicle. The external data processing can be a server such as a cloud server, for example. The transmission can be wireless via a radio connection, for example. The description could include relevant observations in advance and a calculated on-board planning result orinclude a justification for the lack of a solution.

[0009] In a further step, at least one instruction is preferably received from the external data processing device, wherein the at least one instruction comprises a maneuvering strategy for the formally incorrectly resolvable situation. The at least one instruction can, for example, be at least one trajectory to be followed by the vehicle. It is also conceivable for the at least one instruction to comprise specifications and / or information regarding the type of formally incorrectly resolvable situation and how it can be avoided. For example, the at least one instruction could indicate that a vehicle involved in an accident or a construction site can be avoided.

[0010] In a further step, a trajectory for the vehicle for the formally incorrectly resolvable situation is preferably determined based on an evaluation of the at least one received instruction. Determining the trajectory could, for example, also be the adoption of a trajectory suggested within the framework of the at least one instruction. A corresponding trajectory could also be determined based on the specifications and / or information of the at least one instruction, which takes these specifications and / or information into account or implements them. Determining the trajectory can be carried out by a planning module of the vehicle, which is, for example, a software module. Furthermore, a "break-the-rule" module can be provided in the vehicle, which has the planning module and in which the meaning of rules such as traffic regulations can be modified and / or deliberately overridden.

[0011] In a further step, maneuvering of the vehicle is preferably initiated based on the determined trajectory. For example, automated driving along the determined trajectory can be authorized and executed by the vehicle.

[0012] It may be advantageous if, within the scope of the invention, the determination further comprises the following step: - Validating the at least one received instruction taking into account a current perception of the vehicle, wherein the current perception represents an environment of the vehicle which is determined on the basis of the sensor data.

[0013] In simple terms, this can be used to check whether at least one received instruction is feasible. For example, a calculation can be made to determine whether an existing obstacle can be avoided according to an example instruction, for which the sensor data can be analyzed accordingly. This additional validation can advantageously provide additional security for the vehicle.

[0014] Furthermore, it is conceivable that the at least one instruction is or was determined based on a recording of the behavior of at least one further vehicle, wherein the recording of the behavior for the formally incorrectly resolvable situation is initiated by at least one trigger. The behavior can, for example, be a driven trajectory of the at least one further vehicle. In simple terms, it can be recorded how the at least one further vehicle resolved the formally incorrectly resolvable situation. In particular, several driven trajectories can be taken into account in order to subsequently determine an optimal trajectory for the formally incorrectly resolvable situation based on an analysis of the several trajectories.The at least one trigger for the recording can, for example, be a construction site sign and / or a noticeable deviation in the driving style of a human driver of the at least one other vehicle and / or a manual triggering by the driver of the at least one other vehicle. The recording can provide the at least one instruction and / or expand it with further instructions. In particular, a planning module of the vehicle then determines the trajectory for the vehicle, deliberately disregarding the rules broken by human drivers of the at least one other vehicle, and compares this trajectory with those used by the human drivers of the at least one other vehicle (“imitation driving”). During the recording, it is particularly documented how and why a respective rule was broken.In the context of the present invention, the at least one further vehicle is also referred to in particular as a “CSSD Contributor” (CSSD-CC) vehicle.

[0015] In a further embodiment, the at least one instruction can further comprise metadata which describes at least one determined risk and / or a type of maneuvering strategy and / or traffic rules broken during the maneuvering strategy. The determined risk can be, for example, a distance to other road users and / or a time to collision, i.e. a time until a collision with a road user or an obstacle. The type of maneuvering strategy can be, for example, driving in a convoy or driving alone while waiting for oncoming traffic. A possible traffic rule broken during the maneuvering strategy is, for example, crossing a solid line. The metadata can advantageously be used to determine the trajectory for the vehicle more precisely.

[0016] It may also be possible that, in the event that there is no instruction for the situation that cannot be formally resolved correctly, the procedure further includes the following step: - Initiating control of the vehicle by a tele-operator who manually controls the vehicle remotely.

[0017] The teleoperator can, for example, be a qualified operator or automated software that remotely controls the vehicle. The teleoperator can perform the control, for example, by accessing a camera and / or at least one other sensor and corresponding actuators such as the vehicle's steering, accelerator, and brakes.

[0018] According to a further advantage, the method may further comprise the following step: - initiating a transmission of the at least one instruction to a tele-supervisor, wherein the tele-supervisor performs a validation of the at least one instruction.

[0019] The telesupervisor can, for example, be a specialist or automated software that validates the at least one instruction. Various conditions, such as maintaining a certain distance between the vehicle and other road users or obstacles, can be checked. This can advantageously provide additional security for the at least one instruction.

[0020] According to a further possibility, the method may further comprise the following step: - Issuing a notification to a driver of the vehicle, wherein the notification obtains a release from the driver for the specific trajectory, wherein the initiation of the maneuvering is carried out or blocked based on a result of the obtained release.

[0021] This can advantageously guide the vehicle driver to check the specific trajectory. For example, the driver can evaluate whether the specific trajectory is drivable, whether there are obstacles in the way, or whether driving along the specific trajectory could pose any other risks. This can advantageously provide additional protection for the vehicle.

[0022] It is possible for the method according to the invention to be used in a vehicle. The vehicle can be designed, for example, as a motor vehicle and / or passenger vehicle and / or an autonomous vehicle. The vehicle can have a vehicle device, for example, for providing an autonomous driving function and / or a driver assistance system. The vehicle device can be designed to control and / or accelerate and / or decelerate and / or steer the vehicle at least partially automatically.

[0023] The invention also relates to a computer program, in particular a computer program product, comprising instructions that, when executed by a computer, cause the computer to carry out the method according to the invention. Thus, the computer program according to the invention provides the same advantages as those described in detail with reference to a method according to the invention.

[0024] The invention also relates to a data processing device configured to carry out the method according to the invention. The device can be, for example, a computer that executes the computer program according to the invention. The computer can have at least one processor for executing the computer program. A non-volatile data memory can also be provided, in which the computer program is stored and from which the computer program can be read by the processor for execution.

[0025] The invention may also provide a computer-readable storage medium that contains the computer program according to the invention and / or includes instructions that, when executed by a computer, cause the computer to carry out the method according to the invention. The storage medium is designed, for example, as a data storage device such as a hard disk and / or a non-volatile memory and / or a memory card. The storage medium can, for example, be integrated into the computer.

[0026] Furthermore, the method according to the invention can also be implemented as a computer-implemented method.

[0027] Further advantages, features, and details of the invention will become apparent from the following description, which describes embodiments of the invention in detail with reference to the drawings. The features mentioned in the claims and in the description may be essential to the invention individually or in any combination. They show: Fig. 1 a schematic visualization of a method, a device, a storage medium and a computer program according to embodiments of the invention, Fig. 2 a schematic representation of a possible arrangement for a method according to embodiments of the invention.

[0028] In Fig. 1, a method 100, a device 10, a storage medium 15 and a computer program 20 according to embodiments of the invention are schematically shown.

[0029] Fig. 1 shows, in particular, a method 100 for maneuvering a vehicle 1 in a formally incorrectly resolvable situation. In a first step 101, the formally incorrectly resolvable situation is detected based on an analysis of sensor data, wherein the sensor data result from detection by at least one sensor 2 of the vehicle 1. For this purpose, the sensor data can, for example, be temporarily stored in a data memory and retrieved therefrom. In a second step 102, a transmission of a description of the formally incorrectly resolvable situation to an external data processing device 3 is initiated. The initiation can be carried out by a corresponding processor, for example in an on-board computer of the vehicle 1.In a third step 103, at least one instruction is received from the external data processing device 3, wherein the at least one instruction comprises a maneuvering strategy for the formally incorrectly resolvable situation. In a fourth step 104, a trajectory for the vehicle 1 for the formally incorrectly resolvable situation is determined based on an evaluation of the at least one received instruction. This determination can also be performed by the corresponding processor, for example in the on-board computer of the vehicle 1. In a fifth step 105, the maneuvering of the vehicle 1 is initiated based on the determined trajectory. This can also be performed by the corresponding processor, for example in the on-board computer of the vehicle 1.

[0030] Fig.2 shows a possible arrangement for a method according to embodiments of the invention. Here, a vehicle 1 transmits, based on an analysis of sensor data from a sensor 2, a description of a formally incorrectly resolvable situation to an external data processing device 3, which is embodied as a cloud server. This external data processing device 3 has access to various instructions that were determined based on at least one recording from another vehicle 4, wherein the recording was performed by a sensor 2a of the other vehicle 4. This at least one instruction can now be transmitted directly to the vehicle 1. Alternatively, the at least one instruction can first be transmitted to a telesupervisor 6, which first validates the at least one instruction and then forwards it to the vehicle 1.In addition, a driver 7 of the vehicle 1 can authorize a trajectory determined based on the at least one instruction. If no instruction is available for the formally incorrectly resolvable situation, the external data processing device 3 can transmit a corresponding notification to a teleoperator 5, allowing the teleoperator to subsequently remotely control the vehicle 1.

[0031] The concept of Crowd Supported Safe Driving (CSSD) according to embodiments of the present invention is based in particular on real-time observation of the behavior of human drivers in a specific situation and the adoption of this strategy. The cloud-based online approach preferably does not consider the behavior of just one driver, e.g., following the vehicle in front, but rather uses "swarm intelligence" to derive the best strategy. By referencing the specific driving situation, e.g., based on a time and / or location, the "long-tail" problem does not arise here, and instead, a sufficient amount of data from previous human drivers can be used.

[0032] According to exemplary embodiments, the invention describes a concept with which a vehicle in a formally incorrectly resolvable situation receives a strategy (e.g., trajectory) from a cloud-based "break-the-rule" system in real time and, if necessary, iteratively, with the aid of an online connection to cloud computing resources, taking into account information from other human-driven vehicles (V2X). These (intentional) rule violations are preferably documented (when, where, why, on what basis). Furthermore, these rule violations can optionally be validated by a teleoperator 6 (remote control center) before execution. In addition, the documented rule violations can be fed back into the development process to improve the underlying system or vehicle, e.g., through further training and / or manual exceptions.

[0033] One advantage of the invention according to exemplary embodiments is, for example, that a fast and "human-like" solution can be provided for traffic situations that are difficult or impossible to train for vehicles. Furthermore, "swarm intelligence" can advantageously be used in real time to generate optimal solutions for traffic situations that cannot be handled formally in accordance with the rules. Furthermore, complete documentation of pragmatic rule violations and optional time-saving validation by a remote operator can be provided. The systems, or vehicles, can also be improved by incorporating human behavior into development and design. Furthermore, the method can also achieve greater acceptance of autonomous vehicles among the public and authorities.

[0034] A basic function according to exemplary embodiments is described below from the perspective of the vehicle 1, in particular of the autonomous vehicle 1 (CSSD-AD). A vehicle 1 can have a planning function which calculates a safe trajectory for the vehicle 1 on the basis of perception and known rules. In this case, there are situations in particular in which the solution set is zero or where confidence in a solution is not sufficiently high. In this case, the planning module in the vehicle 1 (CSSD-PM) preferably signals a need for support to an external data processing device 3, such as a cloud-based off-board “CSSD Problem Solver” (CSSD-PS). For this purpose, the vehicle 1 preferably transmits relevant data, for example a problem description or “situation deadlock,” to the external data processing device 3 (CSSD-PS). The description could include relevant observations in advance and a calculated on-board planning result orinclude a justification for the lack of a solution. On the basis of information not available to vehicle 1, the CSSD-PS calculates a solution in the form of at least one instruction and transmits this to the requesting vehicle 1. The at least one instruction comprises, for example, a recommendation for a trajectory as well as information about the deliberately broken or reduced rules. The on-board CSSD-PM can then validate the received at least one instruction, taking into account the 'rule violations' and the current perception, and can also iteratively request help again in the event of short-term changes in the situation. If the on-board CSSD-PM comes to the same result as the off-board CSSD-PS, taking into account the 'rule violations', it can use the trajectory.

[0035] Below, a basic function according to exemplary embodiments is described from the perspective of a "CSSD Contributor" (CSSD-CC) vehicle 4 with a human driver. A minimum equipment of the vehicles 4 includes, in particular, a Central Control Unit (CCU), which acts as a central processing module that collects, processes, and reacts to inputs from various sensors and systems in the vehicle 4. The CCU can also coordinate and control various functions and systems of the vehicle 4, such as navigation, collision detection, vehicle control, and communication with external networks or other vehicles. Furthermore, the CSSD-CC vehicle 4 preferably includes a driver assistance system with traffic sign recognition and a perception module, which converts on-board sensor data into a description of the environment, and a CSSD Contributor Module (CSSD-CM). The CSSD-CM preferably sends relevant observations in a format to be defined (e.g.CPM) to the cloud-based "CSSD Realtime Digital Twin" (CSSD-DT), for example, and can also receive "observation orders" from this for specific locations. Relevant observations include, for example, observations at the locations commissioned by the CSSD-DT, or observations that the on-board perception module itself considers relevant. Triggers for this can be, for example, general construction site signs or noticeable deviations by the human driver, e.g., driving over solid lines for a long time as detected by Lane Keeping Assist. In combination with deviations of the route from the HD map data, detected accident situations involving other vehicles, traffic control by humans (police or construction site employees), elephants / climate control stickers / lost cargo on the road, etc., a trigger can also be triggered. In addition to automatic detection of triggers via the vehicle system, a trigger can also be set by the human driver, e.g.by pressing a button, for example, on a touchscreen or through voice input. The CSSD-CC vehicle 4 can transmit its own trajectory to the CSSD-DT. In addition, it can also record and transmit metadata, such as the risk or criticality determined during the route (e.g., distance to other road users, time to collision, etc.), the type of maneuver (e.g., convoy or solo while waiting for oncoming traffic, etc.), and any traffic rules or constraints broken during the maneuver.

[0036] A basic function is described below according to exemplary embodiments from the perspective of a "CSSD Realtime Digital Twin" (CSSD-DT). The CSSD-DT comprises in particular a map, for example an online HD map, into which information from as many sources as possible is fed in promptly. This can have a format that is as standardized as possible. The task of the CSSD-DT is, for example, to supply the CSSD-PS with relevant and as up-to-date information as possible. The CSSD-DT can therefore manage measurement campaigns for the CSSD-CC vehicles 4. Triggers for campaigns can be, for example, the following: Relevant messages from external sources in the HD map (e.g. construction site construction, accidents, etc.), e.g. (C)-ITS information; messages from individual CSSD-CCs (see CSSD-CC function) that are substantiated via a campaign; requests from the CSSD-PS for which no information is currently available.

[0037] If the CSSD-DT receives information from the measurement campaigns, it preferably stores it and can, for example, also generate a confidence value that can serve as an input for the CSSD-PS. The confidence value increases, for example, with multiple identical messages from the CSSD-CC and decreases over time. Optionally, metadata from the CSSD-CC vehicles can also be used, e.g., the risk assessment of the trajectory driven. The information in the CSSD-DT can also serve as input for updates to the online HD map for other purposes.

[0038] A basic function is described below according to exemplary embodiments from the perspective of the CSSD-PS. The CSSD-PS receives requests from the CSSD-PM in particular and can first check whether relevant data for the specific problem situation has already been stored in the CSSD-DT. If no data is stored, or if the data is not sufficiently up-to-date, it preferably rejects the request or forwards the entire process to a teleoperator 5, who can then manually remotely control the requesting vehicle 1. However, if sufficiently up-to-date information on the requested situation has already been stored in the CSSD-DT, the CSSD-PS determines in particular the behavior of the CSSD-CC vehicles 4 in connection with the "situation deadlock" described in the CSSD-PM request. In this way, the CSSD-PS can recognize which strategy human drivers have used. This can then be determined which "formal" rule violations human drivers commit to pragmatically resolve the situation, i.e.which constraints are violated or should be deprioritized. Furthermore, it can be determined which trajectories were selected. Within the CSSD-PS, a "Break-the-Rule" module (CSSD-BR) is then preferably initialized. This module has a planning module in which the meaning of rules can be modified or deliberately overridden. The planning module in the CSSD-BR calculates a trajectory, preferably by deliberately disregarding the rules broken by human drivers, and can compare this trajectory with those used by the human drivers ("imitation driving"). If these are sufficiently similar, the CSSD-PS transmits the result of the CSSD-BR to the CSSD-PM in the requesting vehicle 1. Optionally, the CSSD-BM can also have the result validated by a telesupervisor 6 before transmission, which can advantageously provide a comparatively quick and simple process compared to teleoperation.If the result of the CSSD-BR's trajectory calculation deviates too significantly from the trajectories of the human drivers, the CSSD-PS transmits the result preferentially to a teleoperator 5, who can then remotely control the requesting vehicle 1. Optionally, the trajectory can also be approved by a passenger of the requesting vehicle 1, for example, via a touchscreen or voice communication, e.g., via an LLM module that explains which trajectory is chosen, why, and what risks are associated with it.

[0039] After approval, the requesting vehicle 1 preferably follows the trajectory received from CSSD-PS and CSSD-PM or determines a new trajectory based on newly weighted constraints or rules. Optionally, the hazard warning lights can be automatically activated when following the determined trajectory.

[0040] Abbreviations used: C-IST: Connected Intelligent Transport System CSSD: Crow Supported Safe Driving CSSD-AD: Vehicle with CSSD-enabled AD driving function CSSD-BR: 'Break the Rule' module in CSSD-PS CSSD-CC: (Conventional) vehicle with CSSD support function CSSD-CM: Module for generating CSSD-relevant data in CSSD-CC CSSD-DT: CSSD Realtime Digital Twin CSSD-PM: Planning module in the CSSD-AD driving function CSSD-PS: CSSD problem solver module

[0041] The above explanation of the embodiments describes the present invention exclusively by way of examples. Of course, individual features of the embodiments can be freely combined with one another, provided they are technically feasible, without departing from the scope of the present invention.

Claims

[1] Method (100) for maneuvering a vehicle (1) in a formally incorrectly resolvable situation, comprising the following steps: - detecting (101) the formally incorrectly resolvable situation on the basis of an analysis of sensor data, wherein the sensor data result from a detection of at least one sensor (2) of the vehicle (1), - initiating (102) a transmission of a description of the formally incorrectly resolvable situation to an external data processing device (3), - receiving (103) at least one instruction from the external data processing device (3), wherein the at least one instruction comprises a maneuvering strategy for the formally incorrectly resolvable situation, - determining (104) a trajectory for the vehicle (1) for the formally incorrectly resolvable situation on the basis of an evaluation of the at least one received instruction, - initiating (105) the maneuvering of the vehicle (1) based on the determined trajectory. [2] Method (100) according to claim 1, characterized by that the determining (104) further comprises the following step: - Validating the at least one received instruction taking into account a current perception of the vehicle (1), wherein the current perception represents an environment of the vehicle (1) which is determined on the basis of the sensor data. [3] Method (100) according to one of the preceding claims, characterized by that the at least one instruction is or was determined on the basis of a recording of a behavior of at least one further vehicle (4), wherein the recording of the behavior for the formally incorrectly resolvable situation is triggered by at least one trigger. [4] Method (100) according to one of the preceding claims, characterized bythat the at least one instruction further comprises metadata describing at least one determined risk and / or a type of maneuvering strategy and / or traffic rules broken during the maneuvering strategy. [5] Method (100) according to one of the preceding claims, characterized by that in the event that there is no instruction for the formally incorrectly resolvable situation, the method (100) further comprises the following step: - Initiating control of the vehicle (1) by a tele-operator (5) who manually remotely controls the vehicle (1). [6] Method (100) according to one of the preceding claims, characterized by that the method (100) further comprises the following step: - initiating a transmission of the at least one instruction to a tele-supervisor (6), wherein the tele-supervisor (6) carries out a validation of the at least one instruction. [7] Method (100) according to one of the preceding claims, characterized by that the method (100) further comprises the following step: - issuing a notification to a driver (7) of the vehicle (1), wherein the notification obtains a release from the driver (7) for the specific trajectory, wherein the initiation (105) of the maneuvering is carried out or blocked based on a result of the obtained release. [8] Computer program (20) comprising instructions which, when the computer program (20) is executed by a computer (10), cause the computer (10) to carry out the method (100) according to one of the preceding claims. [9] Device (10) for data processing, which is arranged to carry out the method (100) according to one of claims 1 to 7. [10] A computer-readable storage medium (15) comprising instructions which, when executed by a computer (10), cause the computer (10) to carry out the steps of the method (100) according to any one of claims 1 to 7.

Images