Autonomous travel vehicle management system and method

Abstract

To provide an autonomous travel vehicle management system and a method thereof for dynamically managing a driving routine of one or a plurality of autonomous travel vehicles V included in a cooperation type system.SOLUTION: An autonomous travel vehicle management system comprises: one or a plurality of autonomous travel vehicles V communicatively connected to an external control center 300; and a route planner 302. In addition, in order to enable a dynamic expected safe area allocation mechanism, the autonomous travel vehicle management system is further configured to: continuously determine a change in an environment of the system; detect potential and existing hazards; and calculate and allocate adaptive emergency routes and associated exclusive safety areas to the autonomous travel vehicle V according to the hazard detection, and as a result, the autonomous travel vehicle management system will create an efficient and reliable system environment.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present application relates to an autonomous vehicle management system and method for dynamically managing the travel routines of one or more autonomous vehicles. [Background technology]

[0002] In recent years, the demand for human-collaborative autonomous robotic systems has increased significantly due to the ever-increasing need to provide fast and controllable work routines while simultaneously combating the shrinking workforce. In such complex ecosystems, optimizing productivity while simultaneously ensuring safety for both human workers and autonomous components coexisting within a predefined space has become paramount. As a result, modern collaborative systems typically implement numerous safety strategies within the system's management core.

[0003] Here, one general and effective strategy to further improve safety standards in collaborative systems has been found by dynamically allocating exclusive safety areas for each human worker and machine worker included in a predefined workspace, and implementing a safety stop interaction by the machine worker whenever two of these exclusive areas overlap.

[0004] As a most notable example, in Japanese Patent Publication No. 2021-135801, a similar exclusive safety area mechanism is applied to a system managing the control of an autonomous forklift that picks up one or more pallets from a start position and transports them to a predetermined location, and when the forklift arrives at a given start position, a predetermined system component is defined to allocate an exclusive safety area to the corresponding forklift based on the detected position of the forklift itself and the position and orientation of the required pallet. Furthermore, when providing an exclusive safety area to the above-mentioned forklift, a different allocation pattern is defined to further align the allocation process of the corresponding exclusive area with the requirements of the underlying management system. Summary of the Invention

[0005] Specifically, as a first embodiment of the allocation pattern, the system of the cited document is specified to allocate a fixed, exclusive safety area to each existing forklift truck that is large enough to cover all potential movement and / or emergency routes, including cases where the corresponding forklift truck is required to deviate from its originally assigned route, such as in the case of an emergency collision event. In addition, as a second embodiment, the allocation of such a safety area different from the initial movement route should be performed only after determining the need for an additional emergency route.

[0006] For this reason, although each of the above-mentioned allocation patterns can further improve safety or efficiency within existing cooperative systems to some extent, there is still a problem that none of the existing safety area allocation strategies can simultaneously sufficiently and synergistically improve both of the desired system characteristics. For example, the first embodiment of the allocation strategy cited above can cover all potential emergency routes and thus provide an improved safety structure for all individuals present in a given system, but the allocation of all potential routes also requires the allocation of a large exclusive safety area for each machine unit, even if it is not in use, thus further restricting the movement of other system entities and ultimately leading to a decrease in system efficiency. On the other hand, the restriction of a small exclusive safety area defined by the second embodiment allows more diverse movement patterns for each existing machine, but the allocation of a safety area only in the event of a determined emergency may result in a less safe environment, and at the same time, each machine is forced to wait for a waiting period until an appropriate emergency route and associated safety area are found by the system.

[0007] Therefore, in order to solve the above-mentioned problems and further improve both the efficiency and safety environment that are clearly lacking in state-of-the-art cooperative autonomous systems, an autonomous vehicle management system and method according to the claims of the present invention are proposed herewith. Furthermore, the dependent claims define preferred embodiments of the claimed invention.

[0008] For this reason, an autonomous vehicle management system according to the claimed invention may be configured to synergistically improve safety and efficiency characteristics within a collaborative environment, particularly by providing a dynamic safety area allocation strategy for one or more autonomously driven vehicles in the system, and in particular by implementing a predictive hazard detection mechanism in coordination with a dynamic and responsive vehicle path and exclusive area allocation assignment strategy.

[0009] To this end, the autonomous vehicle management system of the claimed invention may be capable of dynamically managing the driving routines of multiple autonomous vehicles contained in a predefined environment, such as a warehouse, a public or standalone street or road, or any given area that can be allocated as a location for cooperative autonomous systems. As such, the present invention is therefore not limited to a particular autonomous system or a particular vehicle type, but can potentially be implemented in any autonomous system, including closed automated supply systems such as the automated forklift environments presented in the above-cited documents, tracked or wheeled self-propelled vehicles, buses, or even outdoor structures such as those provided by railway elements.

[0010] Overall structure of autonomous vehicle management system Regarding the inclusive elements provided by the proposed invention, the proposed autonomous vehicle management system may, according to a preferred embodiment, firstly comprise at least an external control center including at least an exclusive area manager for managing the exclusive safety areas present or to be implemented in the system, and one or more autonomous vehicles are communicatively connected to the external control center and to at least a route planner for managing the different travel routes assigned to the one or more autonomous vehicles.

[0011] Here, the external control center may be preferentially arranged as a centralized or decentralized communication device that is permanently or limitedly coupled to each of one or more autonomous vehicles by a communication connection means, such as a wireless LAN connection, Bluetooth, or any other preferentially wireless connectivity, that allows the external control center to transfer data and / or instructions to one or more autonomous vehicles while simultaneously receiving information from one or more autonomous vehicles for internal processing. As a result, the external control center's exclusive area manager may also be preferentially designed as a physical or computational module of the external control center and thus be able to communicate with one or more autonomous vehicles present in the system.

[0012] Furthermore, with regard to the route planner, its respective physical and / or computational elements may equally be implemented as modules in the external control center and therefore share the same communication capabilities as those assigned to the exclusive area manager described above. In contrast, in additional equally preferred embodiments, it is also equally possible that the route planner may also be designed as a standalone device with the same communication characteristics afforded to the external control center, or that the route planner may be specifically implemented as an integrated component of each of one or more autonomous vehicles.

[0013] Additionally, with respect to the initial characteristics of each of the system elements described above, a route planner and an exclusive area manager may be preferentially defined as connected, centralized system components that can define and oversee the current travel route and associated exclusive safety area assigned to each of one or more autonomous vehicles based on one or more implemented mechanisms described below.

[0014] Calculation and allocation of initial paths and exclusive safety areas For that reason, in a first preferred embodiment, the route planner is initially configured to calculate and assign at least an initial travel path (hereinafter referred to as an "initial route") to each of one or more autonomous vehicles, the initial route including travel instructions used to define a preferred travel path and direct the given autonomous vehicle to travel within the system environment, while the exclusive area manager may be further configured to calculate and store at least an exclusive safety area assigned to each of the generated initial routes, respectively, defining areas where the given autonomous vehicle may be configured to automatically pause if an object is found to enter the respective safety area. As a result, using the above-mentioned initial definition of the initial route and the associated exclusive safety area, the corresponding autonomous vehicle management system may be able to generate an initial travel trajectory along which the given autonomous vehicle is permitted to travel, in particular so as to fulfill a current task requested by the vehicle (e.g., transporting a given element from a starting point to a destination location) while maintaining safety within the system environment using the additionally provided exclusively defined safety area.

[0015] Here, the generation and allocation of the respective initial paths and exclusive safety areas provided by the path planner and the exclusive areas may vary depending on the internal structure of the comprehensive cooperative system. In a first embodiment, a given task, such as transporting a predefined object, may preferably be assigned to one of one or more autonomous vehicles included in the system (e.g., by an external message provided by a user or the system itself), and as a result, the autonomous vehicle is required to receive route instructions to safely travel from a predetermined start location to its indicated destination. In this embodiment, each autonomous vehicle may be able to send a request to the path planner to find a sufficient path to reach it, and the path planner may be correspondingly configured to calculate a respective initial path for the corresponding autonomous vehicle based on information included in the received path calculation request (e.g., the calculation request may include a given start location, an end location, a predetermined time by which the autonomous vehicle must reach the end location, or a speed specification that the path planner may use to derive the initial path). Additionally, after calculating a sufficient route, the route planner may further preferably be configured to send the calculated initial route to an exclusive area manager and request from the exclusive area manager to calculate and allocate a corresponding exclusive safety area for the calculated initial route.

[0016] The exclusive area manager may then be configured to calculate, i.e., derive, a sufficient exclusive safety area for each preferred initial route based on the information received along with the route planner's requests and / or internal guidelines predetermined by the autonomous vehicle management system. As an example, the exclusive area manager may derive a corresponding exclusive safety area associated with a given initial route by allocating a predetermined area around the initial route with a predefined size, where the size of each area may depend on preset size parameters within the respective system. Furthermore, in addition to or instead of the above-mentioned measures, the exclusive area manager may also be configured to assign additional parameters to further define the size or shape of the corresponding exclusive area.

[0017] Here, by way of example, the exclusive area may preferably be further configured to define the exclusive safety area in a time- or location-dependent manner. By way of example, a given exclusive safety area may also be defined as a given area surrounding the current position of the autonomous vehicle assigned to the initial route, with the size of the area again being predetermined by system-specific parameters. In this way, it is particularly possible to provide the most efficient safety area determination process, particularly by allocating only the area currently surrounding each autonomous vehicle, since the remaining currently unused areas in the system environment can still be allocated / allocated to different system elements. Furthermore, in another example, the size or location of the exclusive area may be variably defined depending on the current time, location, or other parameters of the environment or the assigned autonomous vehicle, so that the exclusive safety area may likewise be specifically adapted to different requirements included in the system, as needed (e.g., if different locations in the system require different safety distances).

[0018] As a result, based on the above-described generation mechanisms performed by the route planner and each exclusive area manager, it may be possible to determine a sufficient initial route and safety area required to reach a given predetermined location by one or more autonomous vehicles included in the system.

[0019] At the same time, it is further noted that the above-described exemplary decision processes of both the route planner and the exclusive area manager define only one of multiple possible embodiments by which a corresponding initial route and associated exclusive safety area may be generated, and therefore are not to be considered limiting of the general scope of the present invention.

[0020] Therefore, as an alternative embodiment different from the above description, the generation and assignment of a given initial path should not be limited to, for example, a single autonomous vehicle existing in the corresponding system, but can similarly be used to calculate and assign a single initial path to multiple existing autonomous vehicles. This may be particularly useful in the case of repetitive delivery routes or locally confined environments where a majority of autonomous vehicles are, by definition, forced to share at least partially the same transport truck, since calculating and assigning a single initial path to multiple autonomous vehicles can efficiently save resources required to assign each of the autonomous vehicles its own seemingly identical initial path. The calculation and definition of each exclusive safety area can then also be performed in a vehicle-specific manner, for example, by defining each of the exclusive safety areas used depending on the location of the vehicle to be assigned, or conversely, by broadly determining a predefined area surrounding the initial path shared by all of the corresponding autonomous vehicles.

[0021] Additionally, the existence of initial routes and exclusive safe areas already calculated and assigned to other autonomous vehicles may also be utilized by the route planner and exclusive area manager to determine and calculate corresponding new initial routes.

[0022] Here, for example, after successfully calculating and allocating each initial route and the exclusive safety area associated with the initial route, the external control center may be further configured to store information about the calculated and allocated initial route and associated exclusive safety area in a predetermined storage area, preferably provided by an internal or external storage element connected to the external control center, such as a hard drive, a storage server, or any other entity capable of reliably storing information generated or received by the external control center. Based on this, the route planner and / or the exclusive area manager may, for example, also preferably be configured to refer to the stored information about the initial route and associated exclusive safety area that is currently already being used by multiple other autonomous vehicles present in the system for the calculation of the initial route or associated exclusive safety area, and calculate a new initial route or associated exclusive safety area based on the referenced information.

[0023] As a result, in a preferred embodiment, the route planner may also be configured, illustratively, to retrieve information from a predetermined storage area regarding the current or potential locations of existing initial routes and / or exclusive safety areas already assigned to different autonomous vehicles in the system, and calculate a corresponding initial route in a manner that avoids contact with or proximity to the other autonomous vehicles. To this end, for example, the route planner may preferably be configured to preferentially calculate only initial routes that do not overlap with stored, and thus already assigned, initial routes or exclusive safety areas of any of the other autonomous vehicles, thereby efficiently avoiding potential collisions with other elements in the system. In a similar manner, the exclusive area manager may also be configured to calculate and assign an associated exclusive safety area for a calculated initial route only if the safety area does not match an already calculated and assigned initial route or exclusive safety area associated with a different vehicle, so that the generation and assignment of the corresponding safety area can also be performed in a safety-promoting manner.

[0024] It is therefore appreciated that, in particular, by further providing a customizable and scalable path generation mechanism, a more accurate and therefore safer path management process can be enabled, thereby generating improvements over current management systems of the state of the art, already based on the above-described mechanism for adaptively calculating and assigning initial paths and associated exclusionary safety areas to pre-defined autonomous vehicles.

[0025] The behavior of one or more autonomous vehicles Furthermore, following calculation of the initial route and associated exclusive safety area assigned to at least one of the one or more autonomous vehicles present in the system, the exclusive area manager of the external control center may preferably forward the initial route and associated exclusive safety area (including travel instructions) to the assigned autonomous vehicle.

[0026] To this end, the external control center may keep track of the current initial routes and exclusive safety areas currently assigned to existing autonomous vehicles in the system by initially and additionally storing information about the initial routes and exclusive safety areas in a predetermined storage area, such as the storage area used to calculate the initial routes and exclusive safety areas or a separate storage area. At the same time, the stored information may also preferably include further specifications or instructions connected to the stored initial routes and associated exclusive safety areas, such as specifications of the assigned autonomous vehicle (e.g., registration number, current location, initial request forwarded to the vehicle, etc.), or dynamically updated parameters such as the current location of the assigned autonomous vehicle, so as to enable accurate review of the vehicle's actions if necessary.

[0027] Each one of the one or more autonomous vehicles assigned to the calculated initial route and associated exclusive safety area may then preferably receive the respective calculated initial route and exclusive safety area from the exclusive area manager, and may further be configured to travel from a predetermined start point to a destination point based on the assigned and received initial route.

[0028] As noted above, the information received by the initial path and exclusive safety area may include additional specifications for the corresponding autonomous vehicle that indicate how the autonomous vehicle is required to move. As an example, the initial path may include additional information such as a start time, a start location, and / or a speed required for the assigned autonomous vehicle to perform the movement. Furthermore, additional environmental information or conditions may equally be included in the initial path or exclusive safety area information, such as specific stopping specifications where the vehicle is required to stop (e.g., in the event of a detected object such as a detected "stop" sign or red light), so that each of one or more autonomous vehicles present in the system may receive specific instructions on how to perform its requested action.

[0029] Furthermore, with regard to the general composition of the existing autonomous vehicles included in the system, the design of each of the autonomous vehicles is not limited to a specific task or superstructure, but can generally be assigned to any autonomous vehicle layout that can navigate itself based on received instructions, in particular the initial path and exclusive safety areas described above. Therefore, an "autonomous vehicle" in the context of the present invention may preferably be understood initially as each mobile entity that is compatible with at least the mechanisms of an additional external control center included in the system and that can automatically follow the instructions described above.

[0030] Hazard Detection Mechanism Thus, using an external control center and one or more autonomous vehicle initial mechanisms to calculate and assign initial paths and associated exclusionary safety areas to each of one or more autonomous vehicles in the system, the present invention can efficiently and dynamically manage the assignment of intended travel routines even for multiple autonomous vehicles moving simultaneously within a predefined system space.

[0031] At the same time, to equally encompass the generation and specification of potential emergency routes for each of the autonomous vehicles required in the cooperative system, particularly to avoid collisions with unexpected objects, such as human workers, that coexist in the system's environment and ignore the currently assigned exclusive safety areas, the proposed autonomous vehicle management system may further comprise additional emergency routes and associate emergency safety area calculation mechanisms to further improve the safety and efficiency of the overall system.

[0032] Specifically, for this purpose, the autonomous vehicle management system may preferably employ an exclusive safe area calculation process that can enable additional predicted hazard detection mechanisms coupled with alternative routes (hereinafter also referred to as "route candidates") and additional dynamic adaptive collision avoidance strategies.

[0033] For that reason, in order to initially generate such additional anticipated hazard detection mechanisms, the external control center and / or one or more autonomous vehicles present in the system may preferably be further configured to detect changes in the environment around an initial route assigned to at least one of the one or more autonomous vehicles.

[0034] Here, "detecting changes in the environment" may refer preferentially to any potential recognition, including optical, electrical, acoustic, or any other type of recognition that can be used for discrimination, used by an external control center or at least one of one or more autonomous vehicles to recognize objects or other entities (e.g., humans or moving machines) within the system and detect changes in object position or other detectable characteristics for hazard determination.

[0035] Thus, in a first preferred embodiment, for example, it may be possible that one or more autonomous vehicles of the system may further be equipped with one or more detectors, such as on-board cameras, infrared sensors, or location scanners, that can detect objects or entities present in the system's environment and may at least track the location or other properties of the detected objects over a certain predetermined amount of time. Similarly, the external control center may also be equipped with such detectors, illustratively by positioning the detectors at predetermined locations in the system's environment and communicatively connecting them to the external control center, so that each of the elements present in the current autonomous vehicle management system may be used as a detection component utilized in the anticipated hazard detection mechanism. Furthermore, in additional embodiments, it may also be equally possible that the detection of a specific object may be, illustratively, by using GPS data of the specific object recognized by an external satellite system, with the data being forwarded to the external control center or at least one of the one or more autonomous vehicles, such that each detection mechanism implemented here is not limited to active "detection" performed by one or more entities of the corresponding system alone, but may also be based on receiving and analyzing additional information detected outside the system itself, so as to be similarly understood as a cooperative detection system.

[0036] As a result, in order to establish the above-mentioned predicted hazard detection mechanism in the present invention, the external control center and / or one or more autonomous vehicles configured to detect changes in the corresponding environment around the initial path may be specifically configured to recognize objects present around the assigned initial path by observing a predetermined area around the given initial path using at least one of the above-mentioned detection mechanisms, and to detect time-dependent behavior, i.e., preferably, spatial position changes, speed, or any other desirable properties of each of the recognized objects around the environment.

[0037] Furthermore, in order to utilize the environmental information so generated for the anticipated hazard detection mechanism, and thus enable adaptive and dynamic generation of emergency routes for each of the one or more autonomous vehicles, the respective external control center and / or one or more autonomous vehicles performing object detection may be further configured to determine, based on the detected behavior of the recognized objects, whether one or more of the recognized objects should be identified as a potential threat to the one or more autonomous vehicles assigned to the observed initial route, and in response to the determination, the external control center and / or one or more autonomous vehicles may similarly be further configured to calculate appropriate emergency routes and associated exclusionary safe areas to be used by the one or more autonomous vehicles if the respective objects become, at some point, a real, i.e., actual, hazard. Thus, compared to existing emergency area allocations currently used in state-of-the-art management systems, the emergency route and safety area generation mechanism of the present invention may be particularly configured to not only generate and allocate a certain number of emergency routes and associated exclusive safety areas simultaneously with the generation of a given initial route or, respectively, only one at a time when an actual danger has already been detected, but instead to perform a proactive, adapted calculation of an emergency route and associated exclusive safety area whenever a given object has already been identified as a potential danger (i.e., an object that is potentially dangerous to one or more of the autonomous vehicles in the future) rather than as an actual (i.e., current) danger.

[0038] As a result, specifically, since each of one or more autonomous vehicles is equipped with multiple corresponding emergency (route) strategies that are already used (when facing a threat), and at the same time, the amount of required emergency routes and associated exclusive safety areas can be significantly reduced using the adaptive nature of the correspondingly calculated emergency routes, the potential waiting time required by the corresponding autonomous vehicles to calculate functional emergency routes when facing a real danger based on the above-mentioned adaptive emergency route and associated safety area generation mechanism can be efficiently avoided.

[0039] Based on this, the corresponding hazard detection and adapted emergency route calculation and related safety area calculation strategies performed by the proposed autonomous vehicle management system may be prioritized as follows:

[0040] In a first step, the external control center and / or one or more autonomous vehicles, which detect changes in the environment around a predefined initial path, may be configured to first select information about recognized objects and then determine the danger of each object based on this information.

[0041] For this purpose, the external control center or one or more autonomous vehicles may be configured to collect object-specific information from its own storage area or request the necessary information from other entities of the autonomous vehicle management system, for example, by preferentially and continuously storing information such as the position, time, or even speed of each recognized object in an object-specific manner, and subsequently retrieving this information for hazard detection. Here, as an example, as opposed to individual storage areas, the external control center or one or more autonomous vehicles may each equally and preferably be connected to a central storage entity, such as a storage server or a communicatively connectable hard drive, in which each detected object information may be continuously and alternately stored and accessed.

[0042] Subsequently, if the respective external control center or one or more autonomous vehicles successfully retrieve information about a given detected object, a determination of the danger of the given object (also called the "danger determination process") may be preferably performed based on the above information by classifying the object into one of several danger levels defined by the system.

[0043] Here, in one preferred embodiment, the autonomous vehicle management system may, for example, define the danger of each detected object and may include at least three danger levels, which may be further subdivided by the names "actual danger," "potential danger," and "no danger," as described below. Specifically, objects classified as "actual danger" may be viewed as objects that require an immediate response from at least one of the one or more autonomous vehicles because such objects appear to collide with or otherwise harm the respective autonomous vehicles in a predictable amount of time. One example of such an object may be a person jumping in front of a moving vehicle. A "potential hazard," in contrast, may be viewed as an object that could potentially become a "real hazard" at some point, but is not yet viewed as an actual threat to one of the system's one or more autonomous vehicles. An example of this might be, for example, a human worker walking next to a moving autonomous vehicle, but still at a significant distance from the vehicle. Finally, an object classified as "non-threatening" may be any object that, at the time of detection, is not deemed to pose any potential threat to the autonomous vehicles, at least in the near future. This may occur, for example, when a given object maintains a sufficient distance from each of the vehicles such that no harm can effectively be caused by the object in the near future.

[0044] In this case, the classification of each recognized object into one of the above-mentioned danger levels may itself be carried out by comparing object information received by an external control center or one or more autonomous vehicles with one or more parameters and / or thresholds predetermined by the system, preferably defined by one or more existing autonomous vehicles.

[0045] For this reason, in a first preferred embodiment, determining the danger level of a recognized object may be performed, for example, by analyzing the distance of the recognized object to each of one or more autonomous vehicles present in the system or currently moving along the observed initial path, and comparing said distance to predefined distance thresholds that serve as upper or lower categorization limits.

[0046] Thus, within a given embodiment, the external control center or one or more autonomous vehicles may be configured to, for example, preferably extract at least the location, most preferably the current location, of each object from the corresponding object information and calculate the object's distance to each of the corresponding vehicles for a risk determination of each object. Subsequently, the external control center or one or more autonomous vehicles may further compare the calculated distance with a predetermined distance threshold and assign one of the above-mentioned risk levels to the object for each autonomous vehicle associated with the given distance.

[0047] As a result, assuming that the distance of a respective object to one of the one or more autonomous vehicles is determined to be, for example, less than a predetermined potential danger value but greater than a predetermined actual danger value, the external control center and / or one or more autonomous vehicles may be configured to, for example, define the object (for the autonomous vehicle assigned to the distance used) as a "potential danger," and a distance less than the predetermined actual danger value may lead to categorization as an "actual danger" for the particular vehicle. In contrast, a distance greater than the stated potential danger value may lead to categorization as "no danger."

[0048] As a result, based on the above-described vehicle-specific determination of risk levels performed for each object and each autonomous vehicle present in the system, the present invention can provide a mechanism that can reliably predict the risk of any object recognized by the external control center and / or one or more autonomous vehicles, and can implement effective countermeasures to avoid vehicle collisions and / or waiting times, even before the detection of an actual risk present in the system. In addition, since each identified risk level is likewise already defined based on a specific vehicle distance and therefore always assigned to a respective vehicle, each calculated risk level can likewise be seen as an efficient way to further improve the adaptability and efficiency of the system, in particular by only performing emergency route generation for specific vehicles in the case of a specific risk level, significantly reducing the number of required safety area allocations and, in general, the required calculation steps within the system.

[0049] Furthermore, apart from the distance criteria described above, other object information and / or system thresholds may also be used preferentially to create and / or influence alternative or additional risk level categorizations.

[0050] For example, in another embodiment, it may be possible that additional characteristic properties of a given object, such as the type of object (e.g., whether the object is a person or a machine), its size, or its past trajectory, may also be included in determining the respective risk level.

[0051] Additionally, in a further preferred embodiment, it may equally be possible for the external control center or one or more autonomous vehicles to be configured to determine a given risk level not only by parameters referring to the current properties of the object and the corresponding autonomous vehicle, but also by further relying on an extrapolation of already existing movement patterns of both the object or the corresponding autonomous vehicle that potentially exist in such near future, for example.

[0052] For that reason, in an additional preferred embodiment of the danger determination process described above, the external control center and / or one or more autonomous vehicles may equally be configured to determine, based on information referencing the objects and the corresponding autonomous vehicles (such as trajectories or time-dependent sequences of location information), predict the distance between the objects present and the corresponding autonomous vehicles in a predetermined amount of likely time, and then categorize the danger level of each object based on the predicted distance. In this way, potential threats (and respective effective interventions) to one or more existing autonomous vehicles in the system may be detected earlier, even if more reliable emergency detections can be generated.

[0053] Hazard detection based vehicle behavior Additionally, following identification of the respective danger levels assigned to each recognized object and associated with each corresponding autonomous vehicle, i.e., determining the potential and actual dangers that are of concern at a given recognition time, the autonomous vehicle management system may further implement a number of different countermeasures based on the determined dangers, including, in particular, the generation of emergency routes and associated safety area allocations for each of one or more autonomous vehicles associated with the given danger level, so as to effectively overcome any threats currently present in the system.

[0054] Based thereon, at least one or more of the following criteria may preferably be implemented by the autonomous vehicle management system or a corresponding element thereof, where, for the sake of better understanding, each of the criteria may be exemplarily performed in this specification on a first autonomous vehicle (hereinafter referred to as the "first autonomous vehicle"), which represents any of one or more autonomous vehicles of the system that have been assigned to an initial route (and most preferably are already traveling along the initial route) and that are associated with one or more risk level detections determined in a previous risk determination process. Thus, if the first autonomous vehicle is found to be associated with only a "no risk" level determination, i.e., no potential and / or actual risk can currently be found by the risk determination process for the first autonomous vehicle, the autonomous vehicle management system may be configured to suspend any further actions with respect to the first autonomous vehicle and thus allow the first autonomous vehicle to continue traveling along the initial route originally assigned to it. Furthermore, if the first autonomous vehicle may be assigned at least one “potential danger” determination, and therefore at least one potential danger has been detected for the first autonomous vehicle, the autonomous vehicle management system, more specifically the external control center and / or one or more autonomous vehicles, may be configured to perform a route candidate generation process that defines the generation of potential emergency routes to be used by the first autonomous vehicle if the object designated as a “potential danger” becomes an actual danger at some point. To this end, the external control center and / or one or more autonomous vehicles may be at least configured to calculate and store one or more potential emergency routes (hereinafter also referred to as “route candidates”) associated with the first autonomous vehicle, each of which can preferentially avoid the danger created by the recognized object, and further to calculate and store an exclusive safety area (hereinafter referred to as a “safety area candidate”) associated with each respective route candidate. As a result, in this way, if a previously recognized potential danger changes from a potential danger to an actual danger, potential emergency routes may already be available to the first autonomous vehicle. Additionally, if a given object is determined to be a "real danger" to the first autonomous vehicle, and thus indicates at least one "real danger" determination event in the corresponding danger determination process, the first autonomous vehicle may be configured to implement a route switching process to efficiently avoid each danger currently imminently present in the vicinity of the first autonomous vehicle. To this end, the first autonomous vehicle may preferably select one of the previously stored route candidates previously calculated and assigned to the first autonomous vehicle, set the selected route candidate as a new initial route to follow and the exclusive safety area candidate associated with the selected route candidate as a new exclusive safety area, and finally continue traveling along the new initial route to effectively continue traveling to the destination location without requiring any further steps. In contrast, if a route candidate and / or the associated safe area candidate cannot be selected by the first autonomous vehicle, the first autonomous vehicle is preferably configured to suspend its movement and cause a forced collision avoidance by the autonomous vehicle management system.

[0055] As a result, an efficient predicted danger avoidance strategy may be generated based on the above-mentioned process steps executed by the first autonomous vehicle in the event of a detected danger level. In particular, since the above-mentioned route candidate generation process is typically performed before the route switching process (specifically, since the system can always detect a potential danger earlier than an actual danger based on the above-mentioned danger detection mechanism), the above-mentioned emergency route generation and usage strategy may be able to always provide the first autonomous vehicle with a desired emergency route possibility even before the actual danger is actually detected, leading to the effect that a potential waiting time for calculating an emergency route when necessary (i.e., at the time of actual danger detection) can be effectively avoided.

[0056] At the same time, the above-described process steps enable improved efficiency and continuous allocation of required exclusive safe areas within the system. Therefore, since each of the above-described steps relies on previous detections of a corresponding risk level assigned to a given (first) autonomous vehicle and at least one object, which, as described above, is preferably performed in a continuous manner within the proposed system, the above-described process steps may also preferably be performed continuously, e.g., in a consecutive, predetermined time sequence, to effectively adapt to the occurrence of changes detected in the system's environment. Similarly, one or more of the respective steps may also preferably be processed in parallel when two or more of the above-described conditions may apply at once, e.g., when two or more objects may be determined to pose a "potential risk" or an "actual risk." In this way, the external control center and / or one or more autonomous vehicles may be configured in this case to calculate and assign one or more given path candidates and associated safety area candidates to the first autonomous vehicle associated with the first object, for example, while the first autonomous vehicle itself may perform a path switching process for the second object associated with the "actual risk" detection. Furthermore, several route candidate generation processes and / or route switching processes may also be performed simultaneously.

[0057] Route candidate generation process The following may provide further information and / or description of possible embodiments of a route candidate generation process performed by the external control center and / or one or more autonomous vehicles of the proposed system after performing hazard detection and generating different hazard levels associated with recognized objects and a given autonomous vehicle, where a given process step may be assigned to any single autonomous vehicle of one or more autonomous vehicles present in the system, still referred to as the first autonomous vehicle.

[0058] Thus, as described above, each candidate path generation process may be preferably executed by the external control center and / or one or more autonomous vehicles when there is a change in the system's environment, i.e., when a given object is recognized as a "potential danger" to a given first autonomous vehicle in light of a hazard detection process preferably preferentially implemented by the system. In that regard, each candidate path generation process may primarily aim to generate one or more emergency paths, hereinafter also referred to as "candidate paths," for the first autonomous vehicle so as to efficiently avoid threats such as a collision between the first autonomous vehicle and an object when the change in the environment may become an "actual danger" at some point, and at the same time, associated candidate safe areas may be assigned to the candidate paths so as to enable an adaptive hazard-dependent safe area allocation mechanism.

[0059] For that reason, in a first preferred embodiment of each path candidate generation process, the generation / calculation of one or more path candidates may be performed as a priority before the calculation and allocation of the associated safe area candidates.

[0060] Here, the one or more candidate paths may be calculated based on object-specific information, particularly regarding the nature of the object that has been determined to be a "real danger", system internal information including vehicle-specific characteristics, and a predetermined candidate path calculation algorithm implemented in an external control center and / or one or more autonomous vehicles and fed with the above information to determine different optional candidate paths.

[0061] Based on this, in a preferred embodiment, the calculation of one or more route candidates may, for example, include calculation of at least first and second route candidates for the first autonomous vehicle, and preferentially, the first and second route candidates may be different from an initial route of the first autonomous vehicle, and the first and second route candidates may be calculated by implementing information about the object and system internal information into first and second route candidate calculation algorithms.

[0062] For that reason, the first path candidate computation algorithm may be implemented, for example, such that each first path candidate computed for the first autonomous vehicle and output by the first path candidate computation algorithm may continuously maintain a maximum distance of the first autonomous vehicle to a potential hazard represented by an associated object. Thus, by way of example, the first path candidate computation algorithm may be used to generate the first path candidates by determining alternative paths for the first autonomous vehicle to travel, preferably away from the location of each potential hazard or, for example, away from a location where each potential hazard may become an actual hazard.

[0063] In contrast, the second path candidate may be defined inversely as the output of the second path candidate calculation algorithm, such that the first autonomous vehicle maintains a predefined distance from the potential hazard while the second path candidate may also be eventually realigned, if possible, with the initial path of the first autonomous vehicle. Here, as an example, to realize the second path candidate, the second path candidate calculation algorithm may be preferably configured to implement an evasion curve in the second path candidate to avoid a potentially hazardous collision event, and further form the second path candidate such that the second path candidate subsequently reconnects with the initial path assigned to each of the initial paths.

[0064] Thus, by providing a second route candidate, a potential emergency route may be generated that allows for minimal changes to the vehicle's initial route, thus leading to an efficiency-focused route alternative, while the first route candidate may be defined to ensure maximum safety for all entities in the system.

[0065] Furthermore, with regard to the possible information that the external control center and / or one or more autonomous vehicles may need to calculate one or more candidate routes, preferably using at least one of the candidate route calculation algorithms described above, the external control center and / or one or more autonomous vehicles may be configured to receive specific information about objects associated with potential hazards and the first autonomous vehicle for which one or more candidate routes are to be calculated, and to calculate each candidate route based on different predetermined relationships that can be extracted from the information.

[0066] As an example, in a preferred embodiment, the external control center and / or the one or more autonomous vehicles may be able to calculate at least one candidate path based on the relative position of the corresponding object with respect to the first autonomous vehicle, where the relative position may define one of the above-mentioned relationships and can be extracted by the external control center and / or the one or more autonomous vehicles by receiving position information of the corresponding object and the first autonomous vehicle for the candidate path calculation. To this end, the external control center and / or the one or more autonomous vehicles may be configured to read information about the detected object and the currently used autonomous vehicle by accessing a memory area, specifically the memory areas mentioned with respect to the initial path calculation and hazard detection, and then implement the read information in an internal relationship conversion module that can calculate the necessary relationships (based on the read information) for the respective path calculation.

[0067] Based on this, a preferred path candidate calculation process based on the relative positions of the object and the first autonomous vehicle as exemplary relationship parameters may result in different path orientation candidates, depending on, for example, which side of the first autonomous vehicle the object is currently on. As an example, if a respective object is identified as being on the left side of the first autonomous vehicle, the external control center and / or one or more autonomous vehicles may be configured to calculate / determine, based on one or more underlying path candidate calculation algorithms, an appropriate path candidate oriented to the right side of the first autonomous vehicle so as to reliably avoid any potential threats posed by the corresponding object. Conversely, the same technique may be similarly applied in the case of other relative positions of the objects, such that, for example, if an object is on the right side, a path candidate on the left side may be preferred, or if an object is in front of the first autonomous vehicle, a path candidate oriented strictly to the side or even behind the vehicle may be prioritized.

[0068] As a result, based on the fact that the corresponding route candidate calculation process may take into account the specific and predetermined relationship between each object and the first autonomous vehicle, each of the route candidates so generated can be generated in an effective, specifically adaptive, manner, thus resulting in more efficient generation of emergency routes while requiring fewer route candidates and associated exclusive safety area allocations to provide each safe travel routine for each autonomous vehicle.

[0069] Additionally, in a further preferred embodiment, the above-mentioned calculation of corresponding path candidates may be further supplemented not only using information and / or relationships of the corresponding objects and the first autonomous vehicle with respect to current characteristics of the environment, but also with such information and / or characteristics that may be predicted in the (near) future.

[0070] Thus, in a given embodiment, the external control center and / or one or more autonomous vehicles may equally be configured to calculate and determine one or more candidate paths based on predictions, i.e., predictions of object movements, to further improve the accuracy of each candidate path calculation output.

[0071] For that reason, in a preferred embodiment, the external control center and / or one or more autonomous vehicles, and in particular the above-mentioned path candidate calculation algorithm implemented therein, may likewise be configured to perform an initial prediction calculation process for the corresponding path candidate calculation, for example by performing an extrapolation mechanism on object data, and then use the prediction output for the actual calculation of the corresponding path candidate, such as the predicted location of a given corresponding object at a given, still-probable time point. In this way, not only may safety within the corresponding cooperative system be further improved, in particular since the autonomous vehicles may each be equipped with multiple different emergency routes that are considered for any potential behavior of the associated object, but also the accuracy and efficiency of the respective candidate calculation procedures may be further improved, in particular since the continuous extrapolation analysis and output may enable earlier and more accurate explanation of the object's future movements.

[0072] Calculation and allocation of relevant safe area candidates Furthermore, after successfully calculating each of the one or more candidate routes, the external control center and / or the one or more autonomous vehicles may be further configured to calculate and store a corresponding exclusive safety area, hereinafter also referred to as a "candidate safety area," for each of the calculated candidate routes, primarily to ensure the continued safe movement of the first autonomous vehicle even while it is traveling along one of the calculated candidate routes.

[0073] Here, each candidate safe area may preferably retain the same characteristics as the exclusive safe area preferentially associated with each of the initial routes assigned to one or more autonomous vehicles, so that the candidate safe area may be equally viewed as the assigned safe area of ​​the corresponding autonomous vehicle (here, the first autonomous vehicle), and under normal conditions, the movement of the corresponding autonomous vehicle should be ensured primarily by causing the one or more autonomous vehicles (including the first autonomous vehicle) to pause their movement if an object is found to be entering the assigned safe area (see further conditions below).

[0074] As a result, in a preferred embodiment, the parameters and conditions based on which the candidate safety area associated with a given candidate route in the present invention may be calculated may be preferentially the same as those already described for the exclusive safety area associated with the previous initial route. That is, when the candidate safety area may be fully calculated, the external control center and / or one or more autonomous vehicles may equally calculate and allocate the candidate safety area associated with the candidate route by allocating a given area around the candidate route having a predefined size according to the exclusive area manager process for the exclusive safety area, and may further include additional system or time-dependent parameters for safety area determination to further define the size or shape of the corresponding candidate safety area, or may even be configured to move along the first autonomous vehicle while traversing the candidate safety route to generate candidate safety areas having the same predefined size and shape.

[0075] Furthermore, after fully calculating each one or more candidate routes and associated candidate safe areas, the external control center and / or one or more autonomous vehicles may subsequently be configured to preferentially store at least one candidate route and associated candidate safe area in a predetermined storage area (e.g., again, any of the potential storage areas described with respect to the initial route calculation process) and assign each route and safety area to a corresponding first autonomous vehicle, for example, by assigning a vehicle-specific marker, such as a vehicle-specific ID, to the instructions so generated. In this manner, specifically, the first autonomous vehicle may be able to efficiently retrieve the information and instructions contained in the candidate routes and associated candidate safe areas, especially since each of the calculated routes and safety areas may already be inherently organized within an existing system.

[0076] Additionally, in further preferred embodiments, it may equally be possible for the external control center and / or one or more autonomous vehicles to be configured to preferentially store each candidate route and associated candidate exclusive safety area, and then similarly add the area of ​​each of the stored candidate exclusive safety areas to the area currently assigned to the exclusive safety area of ​​the respective first autonomous vehicle. In this manner, it may be possible to further increase the efficiency and security of one or more autonomous vehicles in the system, particularly by adding each of the safety areas associated with a potential emergency route used by the autonomous vehicle to the vehicle's exclusive safety area, even before the actual act of emergency route use, with the area into which the autonomous vehicle will travel in the event of an emergency condition already preferentially allocated, i.e., fixed, to the corresponding autonomous vehicle. At the same time, this may avoid the need to introduce additional security instructions to the autonomous vehicles when a given object is located in the existing candidate route space, particularly because the autonomous vehicles are already configured to suspend vehicle movement when the object is located within their assigned exclusive safety area.

[0077] Additionally, in further preferred embodiments, the external control center and / or the one or more autonomous vehicles may also be configured, even after successfully storing each candidate route and associated candidate safety area in the corresponding storage area, to further manage and / or update the stored candidate route and candidate safety area, thereby dynamically changing both the form of the currently used exclusive safety area and the availability of the candidate route and candidate exclusive safety area for use by the autonomous vehicles. To this end, the external control center and / or the one or more autonomous vehicles may, for example, preferably be configured to delete and / or update a given stored candidate route and associated candidate exclusive safety area, preferably when predetermined conditions are met in the system, and potentially further adapt the exclusive safety area assigned to the autonomous vehicle associated with the deleted and / or updated route and safety area according to the performed deletion and / or update process.

[0078] For that reason, in a preferred embodiment, it may be possible that the external control center and / or one or more autonomous vehicles may be configured to delete and / or update each candidate route and associated candidate safe area, for example, whenever a given predetermined change in the environment is detected (e.g., when a recognized object associated with a given danger level moves, resulting in a change in its previous danger level) and / or whenever a predefined time period (after storage) has elapsed. Additionally, in another preferred embodiment, the external control center and / or one or more autonomous vehicles may be configured to similarly adapt the exclusive safety areas currently used by the autonomous vehicles assigned to the deleted and / or updated candidate route or candidate exclusive safety area based on the respective deletions and / or updates, preferably also by deleting and / or updating areas previously added to the exclusive safety area of ​​the autonomous vehicle. Here, as an example, adapting an existing exclusive safety area may illustratively include deleting an area associated with a deleted exclusive safety area candidate that was previously added to the exclusive safety area of ​​the autonomous vehicle (e.g., where each of the stored exclusive safety area candidates may have previously been added to the vehicle's exclusive safety area after the path candidate calculation). In another example, in the case of an updated, i.e., modified, exclusive safety area candidate, the area previously added to the respective autonomous vehicle's exclusive safety area may be modified to the updated characteristics of the exclusive safety area candidate. In this manner, it may be possible to efficiently and dynamically update and align the areas assigned to each exclusive safety area present in the system, thereby maintaining a fast and reliable response to given changes in the system's environment.

[0079] Internal Route Candidate Selection Mechanism Furthermore, in another preferred embodiment of the present invention, preferably even before the above-mentioned storage step, it may equally be possible for each route candidate and associated safety area candidate to likewise undergo an additional route candidate selection mechanism, so as to further enable the possibility of filtering out invalid or even prohibited route candidates calculated by the external control center and / or one or more autonomous vehicles, thus further improving the efficiency and accuracy of the underlying candidate calculation procedure.

[0080] For that reason, in an additional preferred embodiment, the external control center and / or one or more autonomous vehicles, in which respective route candidates and associated safety area candidates for the first autonomous vehicle have been calculated, may be further configured to perform an additional selection process on the calculated route candidates and safety area candidates, and thereafter store only such route candidates and associated safety area candidates that are permitted in the selection process.

[0081] Here, each selection process itself may be preferentially performed by the external control center and / or one or more autonomous vehicles based on multiple selection parameters that further define the usefulness of a given route candidate and / or safety area candidate. For example, within each selection process, the external control center and / or one or more autonomous vehicles may preferably be configured to analyze predetermined characteristics of each route candidate and / or associated safety area candidate, and may allow subsequent storage of only those routes and safety areas whose characteristics may satisfy predefined conditions implemented in the selection process. As an example, each selection process may include analyzing the length of the route candidate, the time it takes for each first autonomous vehicle to travel along the route candidate, or the amount of safety area required for this route, and allow subsequent storage of each route candidate and associated safety area candidate only if at least one, or preferentially all, of the analyzed characteristics meet predefined thresholds.

[0082] As a result, using the additional selection process described above, calculated candidate routes and candidate safety areas that may potentially not meet a predetermined set of standards in the underlying management system may thereby be effectively filtered out, thus further improving the efficiency and accuracy of the underlying system by effectively conditioning the allocation of emergency routes and safety areas.

[0083] In addition, the selection mechanism described above may preferably also be used to further align the calculated route candidates and associated safe area candidates with the initial routes and route candidates and safe areas already present in the system.

[0084] Specifically, in a cooperative system, security issues may arise primarily when given autonomous vehicles share portions of one of the initial paths, route candidates, or associated safety areas, such as when a collision between the respective vehicles may not be completely avoidable, so the respective selection mechanisms may also preferably be used to filter out calculated route candidates and associated safety area candidates that may fall, even if only partially, on the system's already existing (i.e., used and / or stored) initial paths, route candidates, and / or associated safety areas.

[0085] For that reason, additional embodiments of the route candidate selection process described above may equally include mechanisms by which potentially uncertain route candidates and associated safe area candidates may be filtered out before storage.

[0086] To this end, in a preferred embodiment, the external control center and / or one or more autonomous vehicles may further be configured to send an additional request to store each route candidate and associated safety area candidate in the exclusive area manager of the external control center, mainly to cause the corresponding exclusive area manager to implement the above-mentioned safety inspection mechanism, and preferably to only store each route candidate and associated safety area candidate if the external control center and / or one or more autonomous vehicles receive a corresponding storage permission message from the exclusive area manager in response to acceptance by the exclusive area manager after the safety inspection.

[0087] Here, the safety inspection mechanism of the exclusive area manager may preferably be processed by the exclusive area manager in a similar manner as the exclusive area manager may define the exclusive safety area of ​​the associated initial route described above. Specifically, the exclusive safety area may also preferably be configured to store and / or retrieve information about already existing, i.e., stored, initial routes, route candidates, and associated safety area candidates and / or exclusive safety areas (preferably in a similar manner as described with respect to the exclusive safety area described above), and then, preferably based on the stored route and safety area information, only transmit a corresponding storage permission message to the external control center and / or one or more autonomous vehicles if the characteristics of each route candidate and associated safety area candidate sent to the exclusive area manager for safety inspection can satisfy multiple predetermined conditions.

[0088] For that reason, in a preferred embodiment of the above-mentioned safety inspection mechanism, the external area manager may be configured to, for example, read information of currently stored exclusive safety areas and safety area candidates present in the system, which may preferably be the current and / or time-dependent location of each safety area, compare this information with the characteristics, i.e., the calculated location, of the safety area candidates to be inspected by the exclusive area manager, and send a corresponding storage authorization message to the external control center and / or one or more autonomous vehicles only if each inspected safety area candidate does not overlap with any of the currently stored exclusive safety areas and safety area candidates.

[0089] As mentioned above, in this way, even if a given autonomous vehicle may be required to travel along one of the provided candidate safe paths, it may be efficiently avoided that a given autonomous vehicle may collide with any other autonomous vehicles in the system, and in particular, any (even potentially) dangerous convergence between two autonomous vehicles may be completely prevented, such as when pre-selecting (i.e., pre-filtering) candidate paths that share even only part of the same safe area with another already-existing initial path or candidate path.

[0090] Additionally, the mechanisms described above may also enable further improvements in the adaptability of the overall autonomous vehicle management system.

[0091] For example, the above-described path checking mechanisms may not only involve the determination and selection of stored new path candidates and associated safety area candidates for a given autonomous vehicle, but may equally be used to further adapt and improve the overall allocation and use of travel paths included in the provided system.

[0092] For that reason, in additional preferred embodiments, not only may the exclusive area manager implementing the above-mentioned security checking mechanism be configured to output (or not output) a given storage authorization message to an external control center and / or one or more autonomous vehicles after detecting the sufficiency / insufficiency of a corresponding route candidate or associated safety area candidate, but it may equally be possible that the detection may likewise be used to further adapt already existing (i.e., stored) route and safety area definitions or allocations so as to improve the efficiency of the management system overall.

[0093] Thus, in additional embodiments, the exclusive area manager may, in some examples, be configured to still send a storage authorization message to the external control center and / or one or more autonomous vehicles (contrary to the above-described embodiment) if it is detected during security screening that the requested candidate safety area may overlap only with a currently stored initial route and / or its associated exclusive safety area, and instead erase the already stored initial route and associated safety area that overlaps with the candidate safety area, while further reassigning the new initial route and associated exclusive safety area to one or more autonomous vehicles to which the erased initial route was assigned.

[0094] Here, this may in some instances lead to further improvements in the system's route allocation efficiency, in particular, such as the additional possibility of reallocating already existing travel routes and associated safety areas, and where necessary (i.e., for example, when no other potential safe routes can be found for a given autonomous vehicle), the current route allocation can be dynamically adapted individually to environmental changes or newly emerging requirements within the system.

[0095] Furthermore, instead of or in addition to the above procedure, if the exclusive area manager determines that a given route candidate or associated safe area candidate is not sufficient when performing the above security check mechanism, the route manager may also preferably calculate its own alternative route candidates, and the exclusive area manager may calculate the associated alternative safe area candidates and send the alternative route candidates and alternative safe area candidates to the corresponding external control center and / or one or more autonomous vehicles instead of sending a corresponding storage authorization message (meanwhile, the external control center and / or one or more autonomous vehicles may be further configured to automatically store the alternative route and safety area for emergency avoidance). This may efficiently avoid additional waiting time in the system.

[0096] Route candidate selection Based on the above-mentioned route candidate generation mechanism implemented in the proposed autonomous vehicle management mechanism, each of the one or more current autonomous vehicles may therefore be assigned one or more emergency routes (route candidates) and associated safety areas (respective safety area candidate) stored for the respective autonomous vehicle, and at the same time, each of the stored emergency routes and safety areas may preferably be adapted and assigned to a recognized specific potential danger before a respective change in the environment / respective object may become an actual danger to the corresponding autonomous vehicle.

[0097] As a result, within the present invention, in particular, a corresponding avoidance strategy can be easily and efficiently implemented for a corresponding autonomous vehicle that faces an actual danger from a given object at a determined time by simply selecting one of the calculated and stored candidate paths and associated safe areas, and switching the initial path and safety area currently being used by the autonomous vehicle to the selected candidate path and associated candidate safe area.

[0098] Therefore, within a preferred embodiment of the proposed autonomous vehicle management system, a given autonomous vehicle, for example the first autonomous vehicle described above, may be further configured to, when an actual danger to the autonomous vehicle is detected in the previous danger detection step, apply countermeasures against the imminent danger by selecting one of the stored candidate routes and associated candidate safe areas assigned to the corresponding autonomous vehicle and, preferentially, to the corresponding object assigned to the detected actual danger, and modifying the initial route and safety area with the selected candidate route and candidate safe area (i.e., the autonomous vehicle further moves along the selected candidate route).

[0099] Here, the identification of selectable route candidates and associated safe area candidates may be efficiently performed within the system. In particular, since each of the stored route candidates and associated safe area candidates has already been assigned to a given autonomous vehicle and a predetermined / recognized object, a corresponding (first) autonomous vehicle facing an object of the "actual danger" level may further be configured to simply identify the object assigned to the current actual danger and retrieve the stored route candidates and associated safe area candidates assigned to the identified object from a predetermined storage area in which the respective route and area information is preferentially stored.

[0100] Additionally, the selection of each candidate route and associated safety area used for hazard avoidance may preferably be based on a predetermined avoidance state defined and managed internally by the autonomous vehicle management system. For example, the autonomous vehicle management system may include at least a “security-first state” and an “efficiency-first state,” whereby the selection of corresponding candidate route and associated candidate safety area may be based on the state currently existing in the autonomous vehicle management system. As an example, if the first and second candidate route of the first embodiment of the candidate route generation process described above exist, and the autonomous vehicle management system is currently in the efficiency-first state, each (first) autonomous vehicle may be configured to select the candidate route and safety area associated with the highest likelihood of avoiding the corresponding threat (i.e., the first candidate route and safety area in the first embodiment). In the efficiency-first state, the autonomous vehicle may select the existing candidate route and safety area (i.e., the second candidate route and associated safety area in the first embodiment) that corresponds to the most efficient (e.g., fastest) means of still reaching the destination location.

[0101] Integrated car-free and car-free areas In light of the above-mentioned mechanisms and strategies implemented in the present invention, the proposed autonomous vehicle management system therefore provides a versatile approach to further improve the safety and efficiency of current cooperative systems, primarily because it enables a fast and predictive method to generate countermeasures against potential dangers present in the system.

[0102] At the same time, since the proposed path and safety area generation mechanisms are each freely applicable to any kind of cooperative system, independent of the type or task assigned to the autonomous vehicles included in the system, and in particular the adaptive nature of the initial path and candidate path generation process described above similarly allows for the inclusion of different environmental characteristics if necessary, the present invention may equally and efficiently be implemented in closed machining systems or even road-based delivery systems that typically include impassable or prohibited areas.

[0103] For that reason, in another preferred embodiment of the present invention, the autonomous vehicle management system may equally and preferably be capable of calculating and allocating the above-mentioned initial routes, route candidates, and their associated safety areas, incorporating different local characteristics, such as permissible and prohibited crossing areas, contained in the system's corresponding environment into the respective mechanisms used in the present invention.

[0104] To this end, for example, at least the external control center, the one or more autonomous vehicles, and / or one of their implemented elements may be further configured to store and access additional map data including two-dimensional information regarding travel areas in which the one or more autonomous vehicles are traveling, said two-dimensional information being at least information regarding one or more vehicle priority areas defining travel areas within the system's respective environment in which the one or more autonomous vehicles are permitted and / or estimated to travel, and one or more vehicle prohibited areas that may define travel areas in the system in which the one or more autonomous vehicles are generally prohibited from traveling, thus describing a given system environment including different local characteristics.

[0105] In an additional step, at least the route planner of the external control center may be further configured to similarly access the map data, calculate and allocate at least a given initial route by referencing the map data, and utilize only system locations defined in the map data as vehicle priority areas. Conversely, the exclusive area manager of the external control center may also perform the calculation of each exclusive safety area in the same manner, particularly by equally accessing the existing map data and utilizing only vehicle priority area locations to allocate given exclusive safety areas, so that each of the initial routes and exclusive safety area allocations created in the present invention can be efficiently allocated to a specific predetermined travel area, as needed.

[0106] Additionally, the same local constraints may equally be applied during the calculation and allocation of corresponding route candidates and associated safety area candidates performed after hazard detection, preferably by the external control center and / or one or more autonomous vehicles, by preferentially similarly limiting the allocation of said route candidates and safety areas to locations associated with vehicle-preferred areas in the respective map data. In contrast, in a different embodiment, it may equally be possible that locations corresponding to vehicle-prohibited areas may still be acceptable, at least for the calculation of the respective route candidates and safety area candidates, so as to further increase the amount of possible potential emergency routes for a given autonomous vehicle. As a result, within this embodiment, an exclusive area manager implementing a security selection mechanism for excluding certain route candidates and safety areas may still be configured, for example, to similarly send a storage authorization message to the corresponding external control center and / or one or more autonomous vehicles, even if the location of a given route candidate and / or associated safety area candidate may overlap with an existing vehicle-prohibited area present in the map data.

[0107] As a result, it is shown that the proposed autonomous vehicle management system of the claimed invention may include several benefits compared to management systems commonly used in cooperative environments.

[0108] Additionally, the above-described management system may also envision multiple autonomous vehicle management method steps not yet provided or disclosed by conventional autonomous vehicle management systems.

[0109] Here, the method may also be defined for dynamically managing driving routines of a plurality of autonomous vehicles by an autonomous vehicle management system, preferably comprising at least an external control center, one or more autonomous vehicles communicatively connected to the external control center, and a route planner, where the external control center may further comprise at least an exclusive area manager, and the route planner may be included in the external control center or one or more vehicles. Additionally, the method may at least comprise: calculating and assigning an initial route to one or more autonomous vehicles by a route planner, and calculating and storing an exclusive safe area for the initial route by an exclusive area manager; autonomously traveling, by one or more autonomous vehicles, from a predetermined start point to a destination point based on an assigned initial route; detecting, by the external control center and / or the one or more autonomous vehicles, changes in the environment around the initial route and determining at least one of potential or actual danger to the one or more autonomous vehicles traveling along the assigned initial route; When a change in the environment around the assigned initial route is determined to be a potential danger, calculating, by the external control center and / or the one or more autonomous vehicles, for a first autonomous vehicle of the one or more autonomous vehicles, at least one route candidate that is different from the assigned initial route and an exclusive safe area candidate that is associated with the at least one route candidate, and storing the at least one route candidate and the exclusive safe area candidate; selecting, by the first autonomous vehicle, one of the stored candidate routes if a change in the environment around the initial route is determined to be a real danger; setting, by the first autonomous vehicle, the selected candidate route as a new initial route and setting, by the first autonomous vehicle, the selected candidate exclusive safe area associated with the selected candidate route as a new exclusive safe area; and continuing, by the first autonomous vehicle, travel along the new initial route.

[0110] Additionally, the method also includes: adding, by the external control center and / or the one or more autonomous vehicles, the stored candidate exclusive safety areas to the area assigned to the exclusive safety area of ​​the first autonomous vehicle; sending, by the external control center and / or one or more autonomous vehicles, a request for each calculated candidate path to an exclusive area manager, and storing each candidate path and the calculated candidate exclusive safety area; storing, by the external control center and / or the one or more autonomous vehicles, at least one candidate path and candidate exclusive safety area only if the external control center and / or the one or more autonomous vehicles receive a storage authorization message from the exclusive area manager; storing, by an exclusive area manager at an external control center, information regarding each stored exclusive safety area and each stored exclusive safety area candidate; The method may include, by the external control center, at least if the requested exclusive safety area candidate does not overlap with any of the stored exclusive safety areas and stored safety area candidates, accessing the stored information and transmitting a storage authorization message to the external control center and / or one or more autonomous vehicles. [Brief explanation of the drawings]

[0111] [Figure 1a] 1 is a schematic diagram illustrating an exemplary allocation of an exclusive safe area in a cooperative system according to a first embodiment of the prior art; [Figure 1b] 1 is a schematic diagram illustrating an exemplary allocation of an exclusive safe area in a collaborative system according to the present invention; [Figure 2a] 1 is a schematic diagram showing an exemplary allocated exclusionary safety area according to the present invention upon detection of a potential danger; [Figure 2b]1 is a schematic diagram showing an exemplary allocation of exclusive safety areas according to the present invention during route candidate calculation; [Figure 2c] 1 is a schematic diagram showing an example of allocated exclusive safe areas and allocated exclusive safe area candidates according to the present invention during route candidate selection; FIG. [Figure 3] 1 is a diagram illustrating an example of the composition of elements included in an autonomous vehicle and control center according to a first embodiment of the present invention. FIG. [Figure 4] 1 is a flow chart including the general working principle of an autonomous vehicle management system according to a predefined embodiment of the present invention; [Figure 5a] FIG. 3 is a diagram illustrating an example of a workflow for risk level determination according to the first embodiment. [Figure 5b] FIG. 10 is a diagram illustrating an example of a workflow for risk level determination according to the second embodiment. [Figure 6] FIG. 1 illustrates an exemplary workflow for one of one or more autonomous vehicles of a system to travel along an initial path and dynamically allocate a safety area. [Figure 7] FIG. 2 is an exemplary diagram illustrating a workflow of candidate safe path calculation according to an embodiment of the present invention. [Figure 8a] FIG. 10 is a diagram illustrating an example of a workflow for predicting the movement of a potential hazard. [Figure 8b] FIG. 8b is an exemplary diagram illustrating the movement prediction of FIG. 8a using a human and another vehicle as exemplary hazardous objects. [Figure 9a] FIG. 2 is an exemplary diagram illustrating a workflow for calculating first and second candidate paths according to one embodiment of the candidate calculation process of the present invention. [Figure 9b] FIG. 9b is a diagram exemplarily showing route candidates generated by the workflow shown in FIG. 9a. [Figure 10a] FIG. 2 is an exemplary diagram illustrating a workflow for storing and allocating exclusive safe areas according to a first embodiment. [Figure 10b] FIG. 10 is an exemplary diagram illustrating a workflow for storing and allocating exclusive safe areas according to a second embodiment. [Figure 11a] FIG. 2 is an exemplary diagram illustrating a starting position of an autonomous vehicle to which an initial path has been assigned, in accordance with one embodiment of the present invention. [Figure 11b] FIG. 11b is an exemplary diagram of the system of FIG. 11a, showing the allocated safety area for the autonomous vehicle. [Figure 11c] FIG. 11b is an exemplary diagram of the system of FIG. 11a with the autonomous vehicle's allocated safe area in view and an object entering the exclusive safe area. [Figure 11d] FIG. 11b is an exemplary diagram of the system of FIG. 11a with the autonomous vehicle traveling along an initial path. [Figure 11e] FIG. 11C is an exemplary diagram of the system of FIG. 11D, where the autonomous vehicle's allocated safe area is visible and an object has entered the exclusive safe area. [Figure 11f] FIG. 11D is an exemplary illustration of the system of FIG. 11D, showing the autonomous vehicle's allocated safe area in view and two objects near the left and right sides of the autonomous vehicle. [Figure 11g] FIG. 11D illustrates an exemplary system of FIG. 11D with the autonomous vehicle's allocated safe area visible, the autonomous vehicle in a different location on the initial path, and two objects near the front and right side of the autonomous vehicle. [Figure 12a] 11a, showing an exemplary system of FIG. 11a in which the allocated exclusive safe area and candidate path for the autonomous vehicle are visible, the allocated exclusive safe area including the original exclusive safe area and the calculated candidate exclusive safe area, and objects assigned to the candidate path are shown to the left of the autonomous vehicle. [Figure 12b] 11a, showing an exemplary system of FIG. 11a in which the allocated exclusive safe area and candidate path for the autonomous vehicle are visible, the allocated exclusive safe area including the original exclusive safe area and the calculated candidate exclusive safe area, and objects assigned to the candidate path are shown to the right of the autonomous vehicle. [Figure 12c]FIG. 11B is an exemplary diagram illustrating the system of FIG. 11A, in which the allocated exclusive safe area and candidate path for the autonomous vehicle are visible, the allocated exclusive safe area includes the original area of ​​the exclusive safe area and the calculated candidate exclusive safe area, and the object assigned to the candidate path is shown in front of the autonomous vehicle. [Figure 13] FIG. 4 is an exemplary diagram illustrating another embodiment of the composition of elements of FIG. 3 in which the route planner is included in one or more autonomous vehicles. [Figure 14] FIG. 10 is an exemplary diagram illustrating the concept of including map data including vehicle-preferred areas and vehicle-prohibited areas for initial route calculation. DETAILED DESCRIPTION OF THE INVENTION

[0112] Preferred aspects and embodiments will now be described in more detail with reference to the accompanying drawings, in which the same or similar features in different drawings and embodiments are indicated by like reference numerals. It should be understood that the following detailed description of various preferred aspects and embodiments is not intended to limit the scope of the present invention.

[0113] 1a shows an exemplary diagram of path and safety area allocation for two autonomous vehicles V1 and V2 according to a commonly used autonomous vehicle management system. Here, autonomous vehicles V1 and V2 are illustratively assigned first and second paths IRV1 and IRV2, respectively, along which the autonomous vehicles V1 and V2 are required to travel to fulfill transportation requests assigned to the autonomous vehicles. Additionally, both autonomous vehicles V1 and V2 are assigned predetermined exclusive safety areas SAV1 and SAV2 that define areas where the autonomous vehicles are required to suspend their travel if a given object, such as a human or another vehicle, may be introduced into the area, thereby enabling collision avoidance when traveling along the assigned travel paths.

[0114] For this reason, in conventional systems such as the one shown in FIG. 1a, the allocation of exclusive safety areas is typically performed in such a way that potential emergency routes that autonomous vehicles V1 and V2 need to travel in the event of an imminent collision crisis are automatically incorporated into the assigned exclusive safety areas, thereby enabling the autonomous vehicles to travel safely, while at the same time, even if no emergency action is taken by the autonomous vehicles at all, a large system area is typically occupied by each of the exclusive safety areas sSAV1 and SAV2. As a result, at least, the area usage required by typical autonomous vehicle management systems is still determined to be inefficient.

[0115] 1b, in contrast, illustrates the allocation of typical exclusive safety areas required for exemplary autonomous vehicles V3 and V4 according to the present invention when the autonomous vehicles V3 and V4 are traveling along their respective initial routes IRV3 and IRV4 and are deemed free of additional hazards and / or objects around the autonomous vehicles V3 and V4. As can be seen, the exclusive safety areas SAV3 and SAV4 for the autonomous vehicles V3 and V4, respectively, are significantly smaller than the commonly used exclusive safety areas SAV1 and SAV2 shown in FIG. 1a, primarily because the autonomous vehicle management system of the present invention provides for implementing a dynamic exclusive safety area allocation mechanism that adds the required additional safety area only when necessary (e.g., when a given detected hazard emerging from an object causes one of the autonomous vehicles V3 and V4 of the present invention to move along the provided emergency route). In this manner, safety area allocation can be implemented significantly more efficiently, which equally leads to improved efficiency within the comprehensive cooperative system.

[0116] 2a-2c further exemplarily show an overall step-by-step illustration of the dynamic safety area allocation mechanism introduced by the present invention.

[0117] Here, in Fig. 2a, the same autonomous vehicle V3 as already shown in Fig. 1b may be used, which is currently moving along its first assigned initial route IRV3 and which has been assigned a respective exclusive safety area SAV3. Furthermore, in the illustrated situation, there is an object O depicted as a person moving next to the autonomous vehicle V3, defining a potential collision risk for the autonomous vehicle V3. As a result, in order to avoid a potential collision while at the same time efficiently preventing the autonomous vehicle V3 from pausing its current movement, the autonomous vehicle management system may be configured to dynamically calculate predicted emergency routes (so-called "route candidates", CR1 and CR2 shown in FIG. 2b) before an actual hazardous event is detected (e.g., when an object O enters the exclusive safety area SAV3 of the autonomous vehicle V3), and to allocate to the autonomous vehicle V3 additional exclusive safety area candidates (CSA1 and CSA2 in FIG. 2c) that are added to the exclusive safety area SAV3 of the autonomous vehicle V3 and associated with the calculated emergency routes CR1 and CR2, thereby providing a more efficient yet equally safety-ensuring safety area allocation mechanism.

[0118] FIG. 3 shows a further preferred embodiment of the elements included in the proposed autonomous vehicle management system of the present invention, as well as their preferred composition.

[0119] Specifically, the proposed autonomous vehicle management system may include at least one or more autonomous vehicles V capable of traversing a predefined area of ​​the system, and a control center 300, which in this embodiment includes at least a route planner 302 and an exclusive area manager 304. Furthermore, to move one or more autonomous vehicles V, each autonomous vehicle V requires movement instructions included in an initial route (exemplarily illustrated herein by element 404), which is received by the autonomous vehicles V, in the embodiment of FIG. 3 , preferably primarily by using a predefined communication connection, by first sending a route request 402 to the route planner 302 of the external control center, and then receiving an initial route 404 assigned to the respective autonomous vehicle V by the route planner 302. The initial route 404 itself may further include all necessary instructions, such as time, speed, start location, end location, and manner in which the autonomous vehicles V are instructed to move, and the autonomous vehicles V are further configured automatically to execute the instructions included in the initial route.

[0120] Additionally, with regard to dynamic adjustment of the initial route, including performing dynamic emergency (i.e., candidate) route calculation, additional exclusive safety area candidate allocation, and switching to an emergency route if necessary, the one or more autonomous vehicles may each further comprise a local route calculation feedback loop, represented by element 406 in FIG. 3 .

[0121] In this regard, the local path calculation feedback loop 406 may comprise some functions and / or mechanisms that are implemented in this embodiment of FIG. 3 by each autonomous vehicle V itself (or, respectively, by one or more modules included in the autonomous vehicle V); in other embodiments, such functions and mechanisms may be equally performed by other elements of the proposed autonomous vehicle management system, such as the external control center 300, or may be partially performed in parallel by the vehicle V and the external control center 300. For this reason, when receiving the initial path 404 from the control center 300, the local path calculation feedback loop 406 may first begin by retrieving the exclusive safety area associated with the initial path 404. To this end, the autonomous vehicle V may send an exclusive area request 408 to an exclusive area manager 304 communicatively coupled to the autonomous vehicle V, which may calculate, store, and assign the associated exclusive safety area to each autonomous vehicle V before receiving the exclusive safety area.

[0122] At the same time, to be able to permanently consider dangerous encounters while traveling along the initial path 404, the autonomous vehicle V continuously calculates, stores, and updates new emergency paths, so-called candidate safe paths, and associated candidate exclusive safe areas using a permanent feedback loop of the local path calculation feedback loop 406, depicted by elements 408, 410, 412, and 416 in FIG. 3. Specifically, the feedback loop includes at least the continuous acts of recognizing environmental changes, i.e., recognizing objects (defined by the environment recognition element 414) present around the initial path 404 of the autonomous vehicle V, and subdividing the recognized objects into different risk levels that describe the objects' currently expected danger. Furthermore, depending on the results of the detection, each feedback loop continues either to adaptively calculate additional candidate safe paths and additional associated candidate exclusive safe areas, or to select a given candidate safe path and safe area for collision avoidance.

[0123] More specifically, if the danger of a given recognized object is determined to be a potential danger (as defined by the "potential danger detection" element 412 in FIG. 3), i.e., an object that may become an actual danger in a predetermined amount of time, the autonomous vehicles V may perform an additional candidate path calculation step, represented by the "candidate safe path calculation" element 410 in FIG. 3, in which an emergency path to be used to avoid the object (if it becomes an actual danger at some point) is calculated and stored with reference to each autonomous vehicle V. In addition, additional candidate exclusive safe areas associated with the calculated candidate paths are also then generated and preferably allocated to the autonomous vehicles V (again, by requesting the calculation of the exclusive area manager 304 of the external control center 300 to calculate appropriate candidate exclusive safe areas using the exclusive area request 408), thereby enabling dynamic and adaptive generation of safe areas for each autonomous vehicle V in the system.

[0124] In contrast, if a given object is an actual danger (hereinafter also defined by the danger level of "actual danger" as defined by danger detection 416 in FIG. 3), i.e., if the object clearly defines a threat to the autonomous vehicle V, the autonomous vehicle V may perform adaptive path selection 420, whereby the autonomous vehicle V chooses from one of the previously stored and assigned path candidates and associated exclusive safe area candidates, and then performs collision avoidance by switching its dynamic path movement to the instructions contained in the selected path candidate (defined by path follower 422, i.e., the autonomous vehicle V follows the path candidate instead of the initial path).

[0125] This therefore allows for providing a continuous, adaptive and efficient route and safety area allocation strategy.

[0126] Figure 4 illustrates the above-described workflow of the embodiment of the invention according to Figure 3, this time as an exemplary step-by-step flowsheet, where the left side of the diagram may define the process performed by the external control center 300, and the right side defines the process performed by at least one of the system's one or more autonomous vehicles V. Again, the calculation of potential paths and associated potential exclusionary safe areas is here handled by the one or more autonomous vehicles V, but can likewise preferably be performed by other elements of the system in other embodiments.

[0127] Thus, to begin movement of autonomous vehicle V, in step SB01, autonomous vehicle V may first request to receive instructions from route planner 302 of external control center 300 regarding an initial route for traveling from start location A to destination location B.

[0128] In response, the route planner 302 of the external control center 300 receives the request from the autonomous vehicle V, calculates an appropriate initial route, and returns the initial route including instructions to the autonomous vehicle V in step SA01.

[0129] In step SB02, the autonomous vehicle V also requests from the exclusive area manager 304 an exclusive safe area associated with the received initial route.

[0130] In response, in step SA02, the exclusive area manager 304 receives the request and calculates the associated exclusive safety area, which is then transmitted back to the autonomous vehicle V. The autonomous vehicle V then receives the associated exclusive safety area and stores and / or allocates both the initial path and the exclusive safety area with reference to the autonomous vehicle V. During this time, the autonomous vehicle V may preferably be prohibited from moving until the initial path and exclusive safety area have been fully received, stored, and / or allocated.

[0131] The autonomous vehicle V may then travel along the assigned initial route, during which the above-described adaptive route candidate and exclusive safe area candidate calculations and hazard avoidance mechanisms may be continuously performed, including the following steps:

[0132] In step SB03, environmental recognition is performed by the autonomous vehicle V. That is, the autonomous vehicle V performs detection of current changes in the environment, for example, detection of obstacles present along the initial path.

[0133] At the same time, as shown in step SB04, the autonomous vehicle V may continuously access the instructions contained in the initial route and perform adaptations to the vehicle's current characteristics (e.g., changing the speed, direction, etc. of the vehicle V) to follow the initial route.

[0134] Further, in step SB05, based on the environmental recognition performed in step SB03, it is determined whether a potential hazard may exist in the vicinity of the autonomous vehicle V. If such a potential hazard exists, the autonomous vehicle V performs safe path candidate calculation SB06, which includes calculating, allocating, storing, and potentially allocating one or more path candidates and associated exclusive safe area candidates to avoid a potential collision caused by the potential hazard.

[0135] Furthermore, if no potential danger is found, the autonomous vehicle V assesses in step SB07 that no real or actual danger is found.

[0136] If no actual danger is found, the autonomous vehicle V continues along the initial path in step SB08, repeating the detection steps described above until it reaches a predetermined location.

[0137] In contrast, if an actual danger is determined in step SB07, the autonomous vehicle further assesses whether suitable potential safe paths have been stored and assigned to each dangerous object.

[0138] If no suitable path candidate was stored, the autonomous vehicle V finally performs full braking, thus avoiding the given collision by completely pausing its movement (step SB09).

[0139] Alternatively, if suitable route candidates have been stored, it may be further detected whether each route candidate can be continued completely or whether another threat may be present within the vicinity of a selectable stored route candidate, and if it is determined that the stored route candidates can be followed continuously (step SB11), the autonomous vehicle V may select a route candidate and follow the route candidate until the destination location is reached, or the autonomous vehicle V may select and follow each route candidate and then stop at a predetermined location.

[0140] FIG. 5a further illustrates an exemplary embodiment of the potential hazard detection mechanism shown in step SB05.

[0141] Specifically, in this embodiment, a potential hazard may be determined by determining the distance from a given recognized object O to the autonomous vehicle V, and defining the object O as a potential hazard if the distance is less than a predetermined potential hazard threshold.

[0142] Therefore, for this purpose, the autonomous vehicle V may receive, in a first step SB071a, information about each object recognized during the environment recognition SB03, which information may include at least the location of each object. For this purpose, for example, the autonomous vehicle V may access a predetermined memory area in which information about each recognized object is continuously stored within the system of the present invention.

[0143] The autonomous vehicle V may then equally calculate the distance from the autonomous vehicle V to the object O by accessing its own location information (SB072a) and then determining whether the calculated distance is less than a predetermined potential hazard threshold (SB073a). Thus, if the distance is indeed small, the autonomous vehicle V may further assign and register the object as a potential hazard (SB074a) and follow the steps of SB06 shown in FIG. 4.

[0144] Furthermore, the same method may be applied to detect actual danger in the system, particularly by using an additional actual danger threshold that is smaller than the potential danger value, and determining actual danger when the distance is recognized to be smaller than the actual danger threshold (in this case, determining potential danger would require a distance smaller than the potential danger threshold but greater than the actual danger threshold).

[0145] For that reason, the right side of Figure 5a may show a given example of the danger levels that may exist after executing the danger determination mechanism of Figure 5a, where the actual danger threshold may be indicated by line 502 and the potential danger threshold may be defined by line 503. As a result, object O3 will be considered an actual danger, object O2 will be considered a potential danger, and object O1 will be considered no danger at all.

[0146] In addition, FIG. 5b illustrates another embodiment of the danger detection step of SB07, in which instead of only the distance between the vehicle V and the object O, the position and velocity of each object are received as parameters (SB071b), and the danger level of a given object O is determined by predicting the distance from the object O to the vehicle V at a predetermined time in the future. Specifically, in this case, the autonomous vehicle V may calculate a trajectory, or in this case, the x- and y-related components of a two-dimensional trajectory of each object O, based on the received position and velocity information (SB072b), and determine whether the distance from the vehicle V to the trajectory at a given time is less than predetermined thresholds, such as the potential danger threshold and actual danger threshold described above (SB073b, SB074b), according to the detection mechanism described above. In this way, an even more accurate assessment of the danger level of the object O can be achieved.

[0147] Here, on the right side of Figure 5b, there is shown an additional illustration of the determination mechanism of Figure 5b, where a first object O4 may exhibit a first trajectory VE4 that always provides sufficient distance to the vehicle V, while a second trajectory VE5 of a second object O5 may exhibit insufficient distance at some point in time. Thus, O5 may be determined as a potential danger, and O4 may be considered no danger.

[0148] FIG. 6 further illustrates a simplified illustration of the continuous adaptation and movement mechanisms performed by autonomous vehicle V during movement as described by steps SB04 or SB08, respectively, of FIG.

[0149] Here, the autonomous vehicle V shown in this embodiment may be equipped with a dynamic movement mechanism that, in particular, requires the presence of an appropriate exclusive safety area whenever a subsequent movement is to be performed. That is, the movement mechanism shown in Figure 6 is specifically defined in such a way that the autonomous vehicle V may only move in a direction where an exclusive safety area already exists, and in addition, further exclusive safety areas may be continuously allocated and assigned to the autonomous vehicle V as needed to enable the continued safety of the vehicle.

[0150] Thus, based on the above-described embodiment, the movement mechanism SB04 / SB08 of the autonomous vehicle V may be initiated by a request to move further along the initial path assigned to the autonomous vehicle V.

[0151] For this purpose, in a first step SB081, the autonomous vehicle V may detect whether the next movement step to be performed to follow the initial path is already ensured by the assigned exclusive safety area, i.e. whether the next movement step will still be within the area defined by the currently assigned exclusive safety area.

[0152] If it is determined that the next movement step is still secure with the currently assigned exclusive safety area, the autonomous vehicle V may further check whether a new preferred exclusive safety area can be safely allocated / assigned to the autonomous vehicle V for the next movement step as well, so as to enable the next movement step thereafter (SB042).

[0153] If both of the above criteria are currently met for the autonomous vehicle V, the autonomous vehicle V may proceed to the next appropriate movement step indicated by the initial path and further retrieval of the initial path in step SB045. Additionally, an additional exclusive safety area allocation process may be performed in step SB088 by requesting and retrieving an updated exclusive safety area from the exclusive area manager 304 of the external control center 300 to provide a sufficient basis for the next movement step of the autonomous vehicle V.

[0154] In contrast, if the next movement step cannot be entered because the exclusive safety area in which the next movement step would be ensured is not currently assigned to the autonomous vehicle V (i.e., the next movement step would enter an area that is not included in the exclusive safety area currently assigned to the autonomous vehicle V), the autonomous vehicle V may check whether the exclusive safety area required to proceed further is currently allocated / assigned to another vehicle's current candidate exclusive safety area (SB083).

[0155] If this is not the case (i.e., the required area is instead being used by another vehicle that is in the exclusive safe area instead of the candidate safe area), the autonomous vehicle may instead wait for a predetermined amount of time (SB084 / SB085) and then attempt to claim the required area again.

[0156] Alternatively, if the required area is found to be part of another vehicle's potential exclusive safe area, the autonomous vehicle V may instead send a request to the route planner 302 of the external control center 300 to receive an alternative route to reach the determined destination location (SB089), and proceed through the alternative route after receiving it by equally requesting consecutive external safe area allocations from the exclusive area manager 304.

[0157] FIG. 7 further illustrates a first preferred embodiment for calculating candidate paths, such as that included in step SB06 shown in FIG.

[0158] Here, specifically, the route candidate calculation mechanism depicted in FIG. 7 is based on receiving spatial information of objects associated with corresponding potential hazards, as well as using a prediction algorithm during movement.

[0159] To this end, in a first step SB061, the autonomous vehicle may receive information, in particular spatial information such as the location, speed, and / or trajectory of the corresponding object that has already been analyzed.

[0160] The autonomous vehicle V may then predict the movement of the object and anticipate one or more future positions of the object by analyzing the retrieved information (SB062).

[0161] The autonomous vehicle V may then begin calculating appropriate path candidates by first detecting the object's location at the time of prediction. Specifically, the autonomous vehicle may first check whether the object is located in front of the vehicle V (step SB063), to the right-hand side of the vehicle V (SB065), or to the left-hand side at the time of prediction, and calculate appropriate path candidate or candidates accordingly (steps SB064, SB066, SB067).

[0162] Furthermore, after fully calculating one or more route candidates, the autonomous vehicle V may further require exclusive safety area candidates associated with each of the calculated route candidates. To this end, in this embodiment, the autonomous vehicle V requests corresponding exclusive safety area candidates from the exclusive area manager 304 of the external control center 300 by, among other things, sending a candidate area calculation request to the exclusive area manager 304 (step SB068). The exclusive area manager 304 then calculates each exclusive safety area candidate, stores them if possible, assigns them to the associated route candidate, allocates them (SA05), and finally returns them to the autonomous vehicle V. Furthermore, in a possible embodiment, the exclusive area manager 304 may equally perform an additional security selection process at this point, whereby even successfully calculated exclusive safety area candidates may subsequently be omitted, i.e., may not be returned to the autonomous vehicle V if the calculated exclusive safety area candidate does not meet predefined requirements set by the system.

[0163] The autonomous vehicle V may then examine the exclusive safe area candidates received from the exclusive safe area (SB069) and then store such route candidates for which an associated exclusive safe area candidate has been received (SB0610). That is, only such calculated route candidates are stored and thereby available for use by the autonomous vehicle V that encompass at least one associated exclusive safe area candidate in the system; as a result, the exclusive safe area candidate calculation process performed by the exclusive area manager 304 can similarly be viewed as an efficient pre-selection process for each calculated route candidate.

[0164] For that reason, it may equally be possible in different embodiments that the calculation of the associated exclusive safety area candidates is not performed by the exclusive area manager 304 itself, but may instead be performed by any of the other elements present in the autonomous vehicle management system. In these embodiments, the exclusive area manager 304 may still be configured to perform pre-selection of the calculated route candidates by, preferably, preferentially sending a storage authorization request to the exclusive area manager 304 containing information about the calculated route candidates and, if applicable, the already calculated exclusive safety area candidates assigned to the route candidates, and storing the calculated route candidates (and associated exclusive safety area candidates) only if the exclusive area manager 304 retransmits a storage authorization message to the autonomous vehicle V for each of the route candidates after performing additional selection mechanisms (e.g., security selection mechanisms).

[0165] FIG. 8a further shows a more detailed diagram of one embodiment of the object movement prediction strategy (step SB062) used in the embodiment of FIG. 7 to predict the location of potentially dangerous objects for path candidate calculation.

[0166] Here, each strategy may initially include, in a first step (SB0621), a type recognition of each object O. To this end, for example, the autonomous vehicle V may be configured to compare certain / detected characteristics of the recognized object O, such as size, shape, and / or speed, with predefined characteristics stored in a system memory and assigned to defined object types (e.g., human, car, motorcycle, bicycle, etc.), thereby identifying the respective type of the recognized object O.

[0167] Subsequently, different movement prediction strategies may be implemented by the autonomous vehicle V depending on the outcome of the above object type identification.

[0168] For example, if the autonomous vehicle V can recognize the object type of the corresponding object O as an object with wheels and a steering wheel (e.g., a car, a motorcycle, a bicycle), the autonomous vehicle V may further be configured to predict the movement of the object by utilizing a nonholonomic system model, preferentially assigned explicitly to the object type of each object (SB0622). Based on this, the autonomous vehicle may, for example, predict the vector length and direction of a trajectory potentially taken by the object based on the respective model and the received information, and subsequently calculate one or more candidate paths based on the trajectory vectors so generated.

[0169] 8a, the autonomous vehicle V further uses the prediction of the object O's sustained movement behavior to output not only a predicted movement of the object O, but also an additional vector defining the variability of the object's movement (e.g., a left or right turn in a predetermined amount of time, step SB0623, etc.). As a result, in this way, the efficiency of the corresponding path candidate can be further improved, particularly since each possible movement of the object O can be included in the subsequent calculation of the path candidate.

[0170] In contrast, in the case of step SB062, the autonomous vehicle V may be able to identify the object type of the corresponding object O as a freely movable object (e.g., a person), or may be unable to identify the object type of the corresponding object O, and the movement prediction strategy of FIG. 8a may be specified to calculate a predicted vector based on a more general approach, for example, by using a linear interpolation model (SB0624), and also to output not only one predicted vector for subsequent path candidate calculation, but also several variations, for example, vectors representing a 45-degree turn of the object in each direction from the original expected movement vector (SB0625).

[0171] Furthermore, Figure 8b also exemplarily illustrates different movement prediction strategies depicted according to Figure 8a, where the upper part of Figure 8b illustrates a case where the object type of the object OP cannot be sufficiently identified by the autonomous vehicle V (e.g., because the object is related to a person that is difficult to identify). In this case, the movement prediction method may calculate a prediction vector VEOP2 based on a linear interpolation model, and then add VEOP1 and VEOP3 to calculate suitable path candidates.

[0172] In contrast, the bottom part of Figure 8b shows the case where the object OV is sufficiently identified as a vehicle, specifically as a forklift, whereby the movement prediction strategy specifically calculates the prediction vector VEOV2 and the variations VEOV1 and VEOV3 according to the nonholonomic system model assigned to the identified object type.

[0173] FIG. 9a further illustrates an additional embodiment of the candidate path calculation mechanism performed in step SB06 of FIG.

[0174] Here, specifically, the embodiment of Fig. 9a includes a mechanism for calculating at least two different route candidates for each potential hazard detected in the previous hazard detection step SB05, and at the same time, to calculate these route candidates, the prediction information obtained from the movement prediction mechanism of Fig. 8 is used to calculate both of the route candidates.

[0175] For that reason, in a first step SB06A1, an iterative loop is initiated in which each of the following process steps is iteratively performed for each predicted motion vector previously generated by the motion prediction mechanism.

[0176] Therefore, in a second step SB06A2, each predicted movement vector is iteratively selected and then used in a next step SB06A3 to calculate a first candidate path, where the first candidate path may be calculated, for example, by using a predetermined calculation algorithm, so that the maximum distance from the autonomous vehicle V to the object O is always maintained, resulting in a safety-first candidate path.

[0177] Subsequently, after the first route candidate has been fully calculated for each predicted movement vector, the first route candidate is registered and stored (SB06A4), and calculation of the second route candidate (SB06A5) begins.

[0178] Here, in contrast to the first route candidate, the second route candidate may be calculated, for example based on a second predetermined calculation algorithm, in order to always maintain a certain distance from the autonomous vehicle V to the object O, while at the same time making it possible to connect the second route candidate to the initial route at some point in time (thus defining the second route candidate as a short route that prioritizes transportation efficiency).

[0179] Finally, after calculating the second path candidate, the latter is equally registered / stored by the autonomous vehicle V (SB06A7) and the preceding steps are repeated again for another predicted movement vector (or respectively, the calculation ends in step SB068).

[0180] Figure 9b further illustrates the characteristics of the first and second candidate paths, respectively, calculated by the candidate calculation mechanism of Figure 9a. Specifically, the upper part of Figure 9b illustrates the orientation of the first candidate path CR1 used by the autonomous vehicle V, which faces away from the predicted motion vector VEO of the object O, thus maximizing the distance to the object possible. Instead, the lower part of Figure 9b illustrates that the second candidate path CR2 remains rather close to the initial path of the vehicle V and even reconnects with it after a certain amount of time, resulting in an efficient collision avoidance process.

[0181] 10a further illustrates an exemplary workflow of one embodiment of the exclusive area selection and allocation mechanism performed by the exclusive area manager 304 and used in the present invention to calculate and select sufficient safe areas to be assigned to associated initial or candidate routes. Thus, each process step may be used to calculate both the exclusive safe area (SA04) assigned to the initial route of the autonomous vehicle V or the candidate exclusive safe area (SA05) assigned to a candidate route. At the same time, the same process may also be used in or included in the security selection process of the exclusive area manager 304 described above, which is not yet explicitly shown herein.

[0182] For that reason, in a first step SA041 of the exclusive safety area selection mechanism of FIG. 10a, the exclusive area manager 304 may receive requested exclusive safety areas and / or exclusive safety area candidates previously calculated by the exclusive area manager 304, the autonomous vehicle V, or any other element of the autonomous vehicle management system to be considered for allocation (i.e., assignment to a given initial route or route candidate).

[0183] In the next step SA042, the exclusive area manager 304 may receive information about each currently stored safety area, i.e., mainly about the location area of ​​each exclusive safety area and exclusive safety area candidate in the system that is currently allocated or used. For this purpose, the exclusive area manager 304 may be able to store the information in a format that it created, for example by storing each piece of information individually in a predetermined memory area, or at least be able to read the information from a memory area in which the respective information is already stored. As a result, the exclusive area manager gains access to each area in the system that is currently assigned or allocated to an exclusive safety area or exclusive safety area candidate, which may equally be summarized in a single exclusive safety area map.

[0184] Thereafter, to test the sufficiency of each requested safety area, the exclusive area manager 304 may perform a test to determine whether at least the requested safety area, or at least a portion of the requested safety area, is currently in use, i.e., allocated in the system (SA043). To do this, the exclusive area manager 304 may read the location of the area defined by the requested safety area from the received safety area information and compare the location of each area with the areas currently allocated to exclusive safety areas or exclusive safety area candidates in the system (SA044).

[0185] Subsequently, if the exclusive area manager 304 identifies that the location of the area defined by the requested safety area is not currently allocated / used by any of the autonomous vehicles V, the exclusive area manager 304 may allocate the requested area to the respective assigned initial route or route candidate (and therefore to each autonomous vehicle V associated with the route, step SA045) and may further return the approved and allocated safety area to the corresponding autonomous vehicle (SA047).

[0186] Additionally, the exclusive area manager 304 may also similarly store the newly allocated safe area in the corresponding storage area (SA048), and then update the information about the currently stored safe area by terminating the safe area selection.

[0187] In contrast, if the requested safety area has already been stored / used by any of the corresponding autonomous vehicles V, the exclusive area manager 304 may not allocate and store the requested safety area, but may instead send a failure message to the respective autonomous vehicle V requesting storage and / or allocation of the safety area (or conversely, not send a storage acknowledgement message) (SA046), which typically results in the calculated initial path or path candidates being omitted or updated (see again FIG. 4).

[0188] Furthermore, Figure 10b shows another embodiment of the above-described safe area selection mechanism, where the difference between the mechanisms of Figures 10a and 10b is defined by the substitution process implemented by the exclusive area manager 304 when the location area of ​​the requested safe area is identified as already in use by another exclusive safe area or exclusive safe area candidate in the system.

[0189] In this embodiment, as opposed to not allocating and storing each requested safety area, the exclusive area manager 304 may instead further identify whether the requested safety area belongs to an exclusive safety area candidate (SA046'), and then still approve the allocation and storage of the requested safety area (SA0410' and SA048) if each stored safety area currently blocking the area required by the requested safety area is assigned only to the initial path of another autonomous vehicle V (SA047') and no other objects or vehicles are currently present in the requested area (SA048'). Thus, by performing these additional steps, safety within the system may be further improved, particularly since the allocation of exclusive safety area candidates, and therefore the generation and existence of path candidates, may be prioritized within the system. Additionally, to compensate for the requested safety area allocation, the exclusive area manager 304 may further erase (SA049') the corresponding previously stored safety area and preferably reassign a new initial path and exclusive safety area to each autonomous vehicle V that was assigned the erased safety area.

[0190] To further demonstrate the mechanisms implemented in each autonomous vehicle management system, FIG. 11 a shows yet another diagram of an embodiment of a cooperative system in accordance with the present invention, where an autonomous vehicle V is shown at a given start location A and has been assigned an initial route IR that requires the autonomous vehicle V to travel to a destination location B.

[0191] Additionally, to further illustrate the preferred travel behavior of an autonomous vehicle V in accordance with the present invention and the importance of the exclusive safety area assigned to a given autonomous vehicle V, Figures 11b and 11c illustrate a situation in which the autonomous vehicle V is unable to travel along the initial route IR based on the assigned exclusive safety area SA. Specifically, in this case, an object O has been found to enter the assigned exclusive safety area SA of vehicle V, temporarily halting any movement of the autonomous vehicle V (see again the movement mechanism shown in Figure 6).

[0192] FIG. 11d further illustrates a situation in which each autonomous vehicle V is allowed to move along its initial path to some extent, so that the location of the autonomous vehicle V differs from that in FIGS. 11a-11c, and at the same time, the exclusive safety area SA assigned to the autonomous vehicle V is adapted to the movement, in particular by repeatedly allocating new location areas to the assigned exclusive safety area SA. By comparison, the same movement characteristics of the autonomous vehicle V shown in FIGS. 11b and 11c still apply to later stages of the movement, thus causing the autonomous vehicle V to pause its movement again when the object O once again enters the (newly) allocated exclusive safety area of ​​the vehicle V in FIG. 11e.

[0193] 11f and 11g, in contrast, show exemplary diagrams of the hazard detection mechanism used in the present invention. Two objects O1 and O2 shown in FIG. 11f and O3 and O4 shown in FIG. 11g do not enter the exclusive safety area SA of the autonomous vehicle V, and the autonomous vehicle V may move freely along the initial path IR. At the same time, since each of the objects O1-O4 is already in the vicinity of the autonomous vehicle V, the autonomous vehicle may initiate its hazard detection mechanism by first recognizing the presence of the objects, and preferably specific information about each object in the system. As a result, in the systems shown in FIGS. 11f and 11g, the autonomous vehicle V may, for example, recognize an object on the left-hand side of the vehicle (object O1) and an object on the right-hand side (object O2) in the system of FIG. 11f, and an object on the right-hand side of the vehicle V (object O3) and an object in front of the vehicle V (object O4) in the system of FIG. 11g.

[0194] 12a, 12b, and 12c further illustrate different situations in which an autonomous vehicle V is already using the hazard detection, path candidate, and exclusive safe area candidate calculation mechanisms implemented in the system to avoid a collision with, in particular, a moving object O that has been preferentially detected as a potential hazard (FIGS. 12a, 12b, and 12c may differ only by the position and movement of the object O, by reference).

[0195] Here, in each of the situations, each autonomous vehicle V is able to calculate multiple potential emergency routes, specifically the first and second route candidates CR1, CR2, which in this case are preferentially drawn with reference to Figures 9a and 9b, and similarly it was sufficient to allocate respective exclusive safe area candidates CSA1 and CSA2 assigned to the first and second route candidates, so that the autonomous vehicle V is provided with multiple possibilities for efficient collision avoidance, in particular by selecting one or each existing route candidate and moving along it, and at the same time reducing the number and size of the required safe area allocations to a minimum each time.

[0196] 13 further illustrates a second embodiment of the composition of the proposed autonomous vehicle management system according to the present invention, in which the elements and mechanisms included therein may be the same as those in the composition already described with reference to FIG. 3. In contrast, the only difference from the embodiment of FIG. 3 may be indicated by the location of the path planner 302′, which in this case is located in one or more autonomous vehicles V instead of in an external control center 300′. This composition may therefore enable further improvement of the efficiency of the management system, mainly because it allows for a direct connection of the path planner 302′ and the path calculation feedback loop of each autonomous vehicle V, thus resulting in a more stable and error-free signal conversion between each of the existing elements.

[0197] 14 illustrates yet another concept to be included in a proposed autonomous vehicle management system. Specifically, because a particular cooperative system may require autonomous vehicles V not to travel along certain areas (e.g., in a road-based system that includes both vehicle movement areas and human walking areas), another possible mechanism implemented in the initial path calculation and exclusive safety area calculation mechanisms described above may be to provide vehicle-prohibited and vehicle-preferential areas. Here, a given system may define, even before the initial path calculation, specific areas within the system's environment that each of one or more autonomous vehicles may access for travel (vehicle-preferential areas, e.g., see PA1, PA2, PA3, and PA4 in FIG. 14 ), and areas where travel by one or more autonomous vehicles is prohibited (vehicle-prohibited areas, e.g., see VPAl, VPA2, and VPA3 in FIG. 14 ).

[0198] In order to include these areas in the initial route calculation, and preferably also in the route candidate calculation and the calculation of the associated safety areas, the elements of the proposed autonomous vehicle management system may further be configured to receive information about the location of each predetermined preferred and prohibited area in the system and to adapt the vehicle route and safety area calculation according to these predetermined areas, by prohibiting route and safety area calculation along at least the vehicle prohibited areas (see, for example, initial route IR2, which is prohibited because it crosses a vehicle prohibited area, specifically vehicle prohibited area VPA2, while initial route IR1 is still in use). In this way, specific local characteristics of the environment can be easily included in the proposed inventive mechanism, while still maintaining the efficiency and safety of the respective management system.

[0199] It is further noted that embodiments of the present disclosure may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present disclosure may take the form of a computer program product on a computer-readable medium having computer-executable program code embodied on the medium.

[0200] It should be noted that arrows are sometimes used in the drawings to represent communications, transfers, or other operations involving two or more entities. A double-sided arrow generally indicates that an operation can occur in both directions (e.g., a command / request in one direction and a corresponding reply in the other direction, or peer-to-peer communication initiated by either entity), although in some situations the operation may not necessarily occur in both directions.

[0201] It should be noted that while single-sided arrows may generally indicate exclusively or primarily one-way activity, in certain circumstances such directional activity may actually involve activity in both directions (e.g., a message from sender to receiver and an acknowledgment from receiver back to sender, or the establishment of a connection before forwarding and the termination of the connection after forwarding). Thus, the types of arrows used in particular diagrams to represent particular activities are exemplary and should not be viewed as limiting.

[0202] Aspects / examples / embodiments are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatuses, etc. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable program code.

[0203] Any computer-executable program code may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to create a particular machine, whereby the program code executing on the computer or other programmable data processing apparatus creates means for implementing the functions / acts / output specified in the flowcharts, block diagram blocks, drawings, and / or descriptions.

[0204] These computer-executable program codes may also be stored in a computer-readable memory that can instruct a computer or other programmable data processing apparatus to function in a particular manner, whereby the program code stored in the computer-readable memory creates an article of manufacture including instructions that implement the functions / acts / output specified in the flowcharts, block diagram blocks, drawings, and / or descriptions.

[0205] The computer-executable program code may also be loaded into a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to generate a computer-implemented process, whereby the program code executing on the computer or other programmable apparatus provides steps to implement the functions / acts / output specified in the flowcharts, block diagram blocks, drawings, and / or descriptions. Alternatively, the computer-program implemented steps or acts may be combined with operator- or human-implemented steps or acts to implement an embodiment.

[0206] Communications networks generally may include public and / or private networks, may include local area, wide area, metropolitan area, storage, and / or other types of networks, and may employ communications technologies including, but not limited to, analog, digital, optical, wireless (e.g., Bluetooth), networking, and internetworking technologies.

[0207] It should also be noted that devices may use communication protocols and messages (e.g., messages that are created, sent, received, stored, and / or processed by the devices), and such messages may be carried by a communication network or medium.

[0208] Unless otherwise required by context, this disclosure should not be construed as limited to any particular communication message type, format, or protocol. Thus, communication messages may generally include, without limitation, frames, packets, datagrams, user datagrams, cells, or other types of communication messages.

[0209] Unless the context requires otherwise, it should be understood that reference to a particular communications protocol is exemplary and that alternative embodiments may employ variations of such communications protocols (e.g., modifications or extensions of protocols as may be made from time to time) or other protocols now known or developed in the future, where appropriate.

[0210] It should also be noted that logic flows may be described herein to demonstrate various aspects and should not be construed as limiting the disclosure to any particular logic flow or logic implementation. The described logic may be divided into different logic blocks (e.g., programs, modules, functions, or subroutines) without changing the overall result.

[0211] In many cases, logic elements may be added, modified, omitted, performed in a different order, or implemented using different logic constructs (e.g., logic gates, looping primitives, conditional logic, and other logic constructs) without changing the overall result.

[0212] The present disclosure may be embodied in many different forms, including, but not limited to, computer program logic used in conjunction with a processor (e.g., a microprocessor, microcontroller, digital signal processor, or general-purpose computer), programmable logic used in conjunction with a programmable logic device (e.g., a field programmable gate array (FPGA) or other PLD), discrete components, integrated circuits (e.g., an application-specific integrated circuit (ASIC)), or any other means including any combination thereof. Computer program logic implementing some or all of the described functionality is typically implemented as a series of computer program instructions that are converted into a computer-executable form, stored on a computer-readable medium, and executed by a microprocessor under the control of an operating system. Hardware-based logic implementing some or all of the described functionality may be implemented using one or more appropriately configured FPGAs.

[0213] Computer program logic implementing all or part of the functionality described herein above may be embodied in various forms, including but not limited to source code form, computer executable form, and various intermediate forms (e.g., forms produced by an assembler, compiler, linker, or locator).

[0214] Source code may include a series of computer program instructions implemented in any of a variety of programming languages ​​(e.g., object code, assembly language, or a high-level language such as Fortran, C, C++, JAVA, Python, or HTML) for use with various operating systems or operating environments. The source code may define and use various data structures and communication messages. The source code may be in a computer-executable form (e.g., via an interpreter), or the source code may be converted into a computer-executable form (e.g., via a translator, assembler, or compiler).

[0215] Computer-executable program code for carrying out operations of embodiments of the present disclosure may be written in an object-oriented, scripting, or non-scripting programming language, such as Java, Perl, Smalltalk, C++, etc. However, computer program code for carrying out operations of embodiments may also be written in conventional procedural programming languages, such as the "C" programming language or a similar programming language.

[0216] Computer program logic implementing all or part of the functionality described above in this specification may execute at different times (e.g., simultaneously) on a single processor, or may execute at the same or different times on multiple processors, and may run under a single operating system process / thread or under different operating system processes / threads.

[0217] Thus, the term "computer process" may generally refer to the execution of a series of computer program instructions, whether different computer processes are executed on the same processor or different processors, and whether different computer processes run under the same operating system process / thread or different operating system processes / threads.

[0218] A computer program may be permanently or transiently fixed in any form (e.g., source code form, computer executable form, or intermediate form) in a tangible storage medium, such as a semiconductor memory device (e.g., RAM, ROM, PROM, EEPROM, or flash programmable RAM), a magnetic memory device (e.g., a diskette or fixed disk), an optical memory device (e.g., a CD-ROM), a PC card (e.g., a PCMCIA card), or other memory device.

[0219] A computer program may be embodied in any form of signal that can be transmitted to a computer using any of a variety of communication technologies, including, but not limited to, analog, digital, optical, wireless (e.g., Bluetooth), networking, and internetworking technologies.

[0220] The computer program may be distributed in any form, such as on a removable storage medium (e.g., shrink-wrapped software) with printed or electronic documentation, preloaded onto a computer system (e.g., in system ROM or on a fixed disk), or distributed over a communications system (e.g., the Internet or World Wide Web) from a server or electronic bulletin board.

[0221] Hardware logic (including programmable logic used in conjunction with programmable logic devices) that implements all or a portion of the functionality described herein above may be designed using traditional manual methods, or may be designed, captured, simulated, or electronically documented using a variety of tools, such as computer-aided design (CAD), hardware description languages ​​(e.g., VHDL or AHDL), or PLD programming languages ​​(e.g., PALASM, ABEL, or CUPL).

[0222] Any suitable computer readable medium may be utilized, including, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or medium.

[0223] More specific examples of computer-readable media include, but are not limited to, an electrical connection having one or more wires, or other tangible storage media such as a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a compact disc read-only memory (CD-ROM), or other optical or magnetic storage elements.

[0224] The programmable logic may be permanently or transiently fixed in a tangible storage medium, such as a semiconductor memory device (e.g., RAM, ROM, PROM, EEPROM, or flash programmable RAM), a magnetic memory device (e.g., a diskette or fixed disk), an optical memory device (e.g., a CD-ROM), or other memory device.

[0225] The programmable logic may be fixed in the form of signals that can be sent to a computer using any of a variety of communication technologies, including, but not limited in any way to, analog, digital, optical, wireless (e.g., Bluetooth), networking, and internetworking technologies.

[0226] The programmable logic may be distributed on a removable storage medium (e.g., shrink-wrapped software) with printed or electronic documentation, preloaded onto a computer system (e.g., in system ROM or on a fixed disk), or distributed over a communications system (e.g., the Internet or World Wide Web) from a server or bulletin board. Of course, some aspects may be implemented as a combination of both software (e.g., a computer program product) and hardware. Still other embodiments may be implemented entirely in hardware or entirely in software.

[0227] While certain exemplary embodiments have been described and illustrated in the accompanying drawings, it should be understood that such embodiments are illustrative and that the embodiments are not limited to the specific constructions and configurations shown and described, as various other changes, combinations, omissions, modifications, and substitutions are possible in addition to those described in the preceding paragraphs.

[0228] Those skilled in the art will recognize that various adaptations, modifications, and / or combinations of the above-described embodiments can be made. It should therefore be understood that, within the scope of the appended claims, the present disclosure may be practiced other than as specifically described herein. For example, unless expressly stated otherwise, the steps of the processes described herein may be performed in a different order than described herein, and one or more steps may be combined, divided, or performed simultaneously. Furthermore, those skilled in the art will recognize, in light of the present disclosure, that different examples or aspects described herein may be combined to form other examples.

Claims

1. An autonomous vehicle management system that dynamically manages driving routines of a plurality of autonomous vehicles (V), an external control center (300; 300') comprising at least an exclusive area manager (304; 304'); one or more autonomous vehicles (V) communicatively connected to said external control center (300; 300'); a route planner (302; 302′) included in the external control center (300; 300′) or in the one or more autonomous vehicles (V), the route planner (302; 302') is configured to calculate and assign an initial route (IR) to the one or more autonomous vehicles (V); the exclusive area manager (304; 304') is configured to calculate and store an exclusive safety area (SA) for the initial route (IR); The one or more autonomous vehicles (V) are configured to autonomously travel from a predetermined start point to a destination point based on the assigned initial route (IR); The external control center (300; 300′) and / or the one or more autonomous vehicles (V) are further configured to detect changes in the environment around the initial route (IR) and determine at least one of potential or actual dangers to the one or more autonomous vehicles (V) traveling along the assigned initial route (IR); If the change in the environment around the assigned initial route is determined to be a potential danger, the external control center (300; 300′) and / or one or more autonomous vehicles (V) are further configured to perform a route candidate generation process, the route candidate generation process comprising at least: calculating, for a first autonomous vehicle of the one or more autonomous vehicles (V), at least one candidate path (CR) different from the assigned initial path (IR), and a candidate exclusive safe area (CSA) associated with the at least one candidate path; storing at least one set of the candidate routes (CR) and candidate exclusive safe areas (CSAs) associated with the candidate routes (CR); If the change in the environment around the initial route is determined to be an actual danger, the first autonomous vehicle is configured to perform a route switching process, the route switching process comprising at least: selecting one of said set of stored candidate paths (CR) and associated candidate exclusive safe areas; setting the selected candidate route (CR) as a new initial route, and setting the candidate exclusive safe area (CSA) associated with the selected candidate route as a new exclusive safe area; and continuously moving along the new initial route.

2. The route candidate generation process performed by the external control center (300; 300′) and / or the one or more autonomous vehicles (V) further comprises:

2. The autonomous vehicle management system of claim 1, further comprising allocating the stored candidate safe area (CSA) to an area assigned to the exclusive safe area (SA) of the first autonomous vehicle by adding the stored candidate exclusive safe area (CSA).

3. The route candidate generation process performed by the external control center (300; 300′) and / or the one or more autonomous vehicles (V) further comprises: Sending a request for each of the calculated candidate paths (CR) to the exclusive area manager (304; 304') to store the respective calculated candidate paths (CR) and calculated candidate exclusive safe areas (CSAs); and storing at least one of the set of candidate routes (CR) and candidate exclusive safe areas (CSA) only if a storage authorization message is received from the exclusive area manager (304; 304').

4. the exclusive area manager (304; 304′) of the external control center (300; 300′) is configured to store information about each exclusive safety area (SA) currently stored by the external control center (300; 300′) and each candidate exclusive safety area (CSA) currently stored by the external control center (300; 300′) and / or one or more autonomous vehicles (V); 4. The autonomous vehicle management system of claim 3, wherein if the requested candidate exclusive safety area (CSA) does not overlap with at least one of the stored candidate exclusive safety area (SA) and the stored candidate exclusive safety area (CSA), the exclusive area manager (304; 304′) is configured to access the stored information and transmit the storage authorization message to the first autonomous vehicle by transmitting the storage authorization message.

5. The external control center (300; 300′) and / or the one or more autonomous vehicles (V) are configured to determine at least one of the potential danger or the actual danger based on a danger determination process, the danger determination process comprising: receiving object information regarding an object (O) identified as a potential or actual hazard, the object information including at least the position or the position and velocity of said object (O); and determining whether the object (O) is a potential or actual danger to one of the one or more autonomous vehicles (V) by comparing the received object information with a predetermined threshold defined by each of the one or more autonomous vehicles (V).

6. the predetermined threshold is defined by at least a distance from the object (O) to one of the one or more autonomous vehicles (V); The object (O) is defined as a potential hazard if the distance from the object (O) to at least one of the one or more autonomous vehicles (V) is less than a predetermined potential hazard value and greater than a predetermined actual hazard value; 6. The autonomous vehicle management system of claim 5, wherein an object (O) is defined as an actual danger if the distance from the object (O) to at least one of the one or more autonomous vehicles (V) is less than a predetermined actual danger value.

7. The at least one candidate path (CR) calculated by the first autonomous vehicle is calculated to avoid the potential danger posed by an object (O) to the first autonomous vehicle; 3. The autonomous vehicle management system of claim 1 or 2, wherein the external control center (300; 300') and / or the one or more autonomous vehicles (V) are configured to calculate the at least one candidate path (CR) based on a relative position of the object (O) with respect to the first autonomous vehicle.

8. the at least one candidate path (CR) calculated by the external control center (300; 300′) and / or the one or more autonomous vehicles (V) is calculated to avoid the potential danger posed by an object (O) for the first autonomous vehicle; 3. The autonomous vehicle management system of claim 1 or 2, wherein the first autonomous vehicle is configured to calculate the at least one candidate path (CR) based on a prediction of movement of the object (O).

9. the step of calculating, by the external control center (300; 300′) and / or the one or more autonomous vehicles (V), the at least one candidate path (CR) comprises calculating at least a first candidate path (CR1) and a second candidate path (CR2); the first candidate path (CR1) is defined to maintain a maximum distance from the first autonomous vehicle to the potential hazard; 3. The autonomous vehicle management system of claim 1, wherein the second candidate route (CR2) is defined to maintain a predefined distance from the first autonomous vehicle to the potential hazard and to eventually align with the initial route.

10. the external control center (300; 300′) and / or the one or more autonomous vehicles (V) are configured to manage the stored route candidates (CR), 3. The autonomous vehicle management system according to claim 1 or 2, wherein the external control center (300; 300') and / or the one or more autonomous vehicles (V) are configured to erase and / or update stored candidate paths (CR) and associated candidate exclusive safe areas (CSAs) based at least on detected changes in the environment or after a predefined time has elapsed since storage.

11. the exclusive area manager (304; 304') of the external control center is configured to store information about each stored exclusive safety area (SA) and each stored candidate exclusive safety area (CSA); the exclusive area manager (304; 304′) is configured to send the storage permission message to the first autonomous vehicle if the requested exclusive safe area candidate (CSA) overlaps only with a stored initial route (IR); 4. The autonomous vehicle management system of claim 3, wherein the route planner (302; 302′) is configured to delete the stored initial routes (IR) that overlap with the candidate exclusive safe area (CSA) and reassign new initial routes to the one or more autonomous vehicles (V) that were assigned the deleted initial routes.

12. the route planner (302; 302') is configured to calculate an alternative route candidate, and the exclusive area manager (304; 304') is configured to calculate an alternative safety area candidate associated with the alternative route candidate, if the exclusive area manager (304; 304') has not sent a storage permission message to the first autonomous vehicle after the external control center (300; 300') and / or the one or more autonomous vehicles (V) have sent a request to the exclusive area manager (304; 304') to store the respective calculated route candidate (CR) and exclusive safety area candidate (CSA) for the calculated route candidate (CR); the exclusive area manager (304; 304′) is configured to send the alternative route candidates and the alternative safe area candidates to the first autonomous vehicle; 4. The autonomous vehicle management system of claim 3, wherein the first autonomous vehicle is configured to store the alternative candidate route and the alternative candidate safe area as a candidate route (CR) and the candidate exclusive safe area (CSA) associated with the candidate route (CR).

13. the external control center (300; 300′) and / or the one or more autonomous vehicles (V) are configured to store map data comprising two-dimensional information about a travel area in which the one or more autonomous vehicles (V) are traveling, the two-dimensional information includes at least information regarding one or more vehicle priority areas (PAs) that define the travel areas in which the one or more autonomous vehicles are preferably to travel, and one or more vehicle prohibited areas (VPAs) that define the travel areas in which the one or more autonomous vehicles are prohibited from traveling; the route planner (302; 302') is configured to access the map data and calculate and assign an initial route (IR) by utilizing only locations defined by the vehicle priority areas (PA) for route calculation; 3. The autonomous vehicle management system according to claim 1 or 2, wherein the exclusive area manager (304; 304′) of the external control center (300; 300′) is configured to access the map data and calculate and store the exclusive safety area (SA) of the corresponding initial route (IR) by utilizing only locations defined by the vehicle priority area (PA) for exclusive safety area calculation.

14. 14. The autonomous vehicle management system of claim 13, wherein the exclusive area manager (304; 304′) is configured to compare the requested exclusive candidate safe area (CSA) with the map data and, if the requested exclusive candidate safe area (CSA) overlaps with an area defined by the vehicle priority area (PA) and / or the vehicle prohibited area (VPA), to transmit the store and transmit message to the external control center (300; 300′) and / or the one or more autonomous vehicles (V).

15. 1. A method for dynamically managing driving routines of a plurality of autonomous vehicles (V) by an autonomous vehicle management system, comprising at least an external control center (300; 300′), one or more autonomous vehicles (V) communicatively connected to said external control center (300; 300′), and a route planner (302; 302′), said external control center (300; 300′) further comprising at least an exclusive area manager (304; 304′), said route planner (302; 302′) being included in said external control center (300; 300′) or said one or more vehicles (V), said method comprising at least: calculating and assigning an initial route (IR) to the one or more autonomous vehicles (V) by the route planner (302; 302'); and calculating and storing an exclusive safety area (SA) for the initial route (IR) by the exclusive area manager (302; 204'); autonomously traveling by the one or more autonomous vehicles (V) from a predetermined starting point to a destination point based on the assigned initial route (IR); detecting, by the external control center (300; 300') and / or the one or more autonomous vehicles (V), changes in the environment around the initial route (IR) and determining at least one of potential or actual dangers to the one or more autonomous vehicles (V) traveling along the assigned initial route (IR); When the change in the environment around the assigned initial route (IR) is determined to be a potential danger, the external control center (300; 300′) and / or the one or more autonomous vehicles (V) calculate, for a first autonomous vehicle of the one or more autonomous vehicles (V), at least one candidate route (CR) different from the assigned initial route (IR) and a candidate exclusive safe area (CSA) associated with the at least one candidate route (CR), and store the at least one candidate route (CR) and the candidate exclusive safe area (CSA); selecting, by the first autonomous vehicle, one of the stored candidate routes (CRs) if the change in the environment around the initial route is determined to be a real danger; setting, by the first autonomous vehicle, the selected candidate route (CR) as a new initial route, and setting the selected candidate exclusive safe area (CSA) associated with the selected candidate route (CR) as a new exclusive safe area; continuing, by the first autonomous vehicle, travel along the new initial path.

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