Method, apparatus, and computer program product for automated carriers

Abstract

The present invention relates to methods, apparatus and computer programs for vehicles that operate at least semi-autonomously, and in particular to adjusting the at least semi-autonomous operation of a vehicle based on a prediction of the driving behavior of other at least semi-autonomous vehicles. A method for a first vehicle (100) is adapted to adjust the at least semi-autonomous operation of the first vehicle based on a prediction of the driving behavior of one or more second vehicles (200), the one or more second vehicles being at least semi-autonomous vehicles. The method comprises: receiving (110) one or more wireless messages from the one or more second vehicles, the one or more wireless messages comprising information about one or more automation capabilities that the one or more second vehicles can have. The method comprises: predicting (120) the driving behavior of the one or more second vehicles based on the information about the one or more automation capabilities that the one or more second vehicles can have. The method comprises: adjusting (130) the at least semi-autonomous operation of the first vehicle based on the prediction of the driving behavior of the one or more second vehicles.

Description

Technical Field

[0001] The present invention relates to methods, apparatus and computer programs for at least semi-autonomous operating vehicles, and in particular to adjusting the at least semi-autonomous operation of a vehicle based on predictions of the driving behavior of other at least semi-autonomous operating vehicles. Background Art

[0002] The study of automated (e.g., autonomous or semi-autonomous) vehicles is an area of ​​research and development. In some scenarios, the future of mobility is linked to vehicles becoming both connected and automated. It is expected that in the near future, more and more automated vehicles (AVs) will be driving on public roads.

[0003] In general, different automation levels are distinguished, for example SAE (Society of Automotive Engineers) levels 1-5. For example, German patent application DE 10 2015 205 135 A1 discloses different automation levels that can be used for a vehicle, which level depends on the scenario in which the vehicle is located. For example, in the above-mentioned patent application, the currently available automation level can be transmitted to other vehicles. A similar concept is used in US patent application US2017 / 0158116 A1, where a vehicle provides a notification as to whether the vehicle is in manual, semi-automatic or fully automatic driving mode. US patent application US2019 / 0324451 A1 discloses a concept in which the automation level is adjusted based on the surrounding traffic. In German patent application DE 10 2018 128892A1, the automation level of a second vehicle can be adapted based on the actions of a first vehicle.

[0004] In international patent application WO 2019 / 185217 A1, information about the advanced driver assistance features supported by a vehicle is transmitted from one vehicle to another, enabling the latter vehicle to have a better understanding of the driving behavior of the former vehicle, thereby enabling the latter vehicle to make adjustments to its speed or direction to avoid a collision with the former vehicle. In US 2015 / 0149019 A1, a vehicle uses a signal transmitted by another vehicle to determine that the latter vehicle is operating at least semi-autonomously. In this case, the former vehicle takes action to autonomously operate the former vehicle.

[0005] In DE 2017 222874 A1, a vehicle receives a message from another vehicle, wherein the message indicates the autonomous driving system being used, such as its version or manufacturer, which enables the former vehicle to predict the driving behavior of the former vehicle and initiate a driving maneuver accordingly. In US 2018 / 335785 A1, a vehicle predicts the behavior of another vehicle, for example, based on whether the other vehicle is being operated autonomously, and adapts its autonomous or semi-autonomous control in response to the predicted behavior.

[0006] AVs can communicate via a network, or even directly with each other or with the infrastructure. This enables AVs to collaborate to increase safety and efficiency.

[0007] It may be desirable to provide an improved concept for automated vehicles that takes into account different driving behaviors of the vehicle.

[0008] This desire is solved by the subject matter of the independent claims. Summary of the Invention

[0009] Embodiments are based on the discovery that autonomously or semi-autonomously operating vehicles (also referred to as automated vehicles (AVs), as described above) behave differently than human-driven vehicles. For example, a vehicle may behave differently depending on its level of automation. In addition to varying levels of automation, AVs also use different software versions with varying features. Consequently, within a group of AVs, the automation level, available features, and software versions of the automated operations may differ, leading to different driving behaviors among the different AVs. This varying driving behavior can complicate AV operation or coordination, as these different AVs share the road and may coordinate with one another. To enable or improve an AV's prediction of the driving behavior of other AVs, the AV can receive wireless messages from the other AVs indicating the automation capabilities of the other AVs (which, in turn, may depend on the automation level, software version, available features, driving scenario, etc.). The AV can use this information to enable coordination, improve AV perception, and predict the behavior of other vehicles. Thus, the AV can use the automation capabilities broadcast by the other AVs to predict the driving behavior of the other AVs and ultimately adjust its own automated / at least semi-autonomous operation.

[0010] Various embodiments of the present disclosure provide a method for a first vehicle. The method is suitable for adjusting the at least semi-autonomous operation of the first vehicle based on a prediction of the driving behavior of one or more second vehicles. The first vehicle and the one or more second vehicles are vehicles that operate at least semi-autonomously (also referred to as "automated vehicles" or AVs in the context of the present disclosure). The method includes: receiving one or more wireless messages from the one or more second vehicles. The one or more wireless messages include information about one or more automation capabilities that the one or more second vehicles can have. The method includes: predicting the driving behavior of the one or more second vehicles based on the information about the one or more automation capabilities that the one or more second vehicles can have. The method includes: adjusting the at least semi-autonomous operation of the first vehicle based on the prediction of the driving behavior of the one or more second vehicles. Receiving information about the automation capabilities of the second vehicle can enable or improve the prediction of the driving behavior of the second vehicle, which in turn can lead to appropriate adjustments to the automated driving of the first vehicle.

[0011] In addition to information regarding automation capabilities, various other pieces of information may also be used to more accurately convey the likely driving behavior of the second vehicle.

[0012] For example, the one or more wireless messages may (further) include information about the manufacturer and version of one or more automation capabilities that the one or more second vehicles can have. Thus, the driving behavior of the one or more second vehicles can be predicted based on the information about the manufacturer and version of one or more automation capabilities that the one or more second vehicles can have. The behavior of the automated driving of the second vehicle may also depend on the manufacturer and / or software version of the automation capability, because different manufacturers may implement slightly different driving behaviors, which may also evolve over time.

[0013] The one or more wireless messages may (further) include information about the maximum automation level and / or the currently applied automation level of the one or more second vehicles. The driving behavior of the one or more second vehicles may be predicted based on the information about the maximum automation level and / or the currently applied automation level of the one or more second vehicles. As noted above, an automated vehicle may behave differently depending on its automation level.

[0014] In addition to autonomous operation, possible collaboration between vehicles may also affect their driving behavior. For example, the one or more wireless messages may include information about one or more collaboration capabilities that the one or more second vehicles can have and / or information about one or more collaborative driving maneuvers currently performed by the one or more second vehicles. The driving behavior of one or more second vehicles can be predicted based on the information about one or more collaboration capabilities that the one or more second vehicles can have and / or information about one or more collaborative driving maneuvers currently performed by the one or more second vehicles. By taking into account possible or actually performed collaborative driving maneuvers, the prediction of driving behavior can be improved.

[0015] Some vehicles have different performance modes, such as an “economy mode” that prioritizes energy usage, a “comfort mode” that seeks to reduce sudden movements, or a “sport mode” that aims to improve the acceleration behavior of the vehicle. These performance modes may also have an impact on the driving behavior of the second vehicle. For example, the one or more wireless messages may include information about the driving performance settings currently used by the one or more second vehicles. The driving behavior of the one or more second vehicles may be predicted based on the information about the driving performance settings currently used by the one or more second vehicles.

[0016] In some scenarios, vehicles may also broadcast their driving intentions to other vehicles, for example, to initiate a collaborative driving behavior. For example, the one or more wireless messages may include information about the driving intentions of one or more second vehicles. The driving behavior of one or more second vehicles may be predicted based on the information about the driving intentions of the one or more second vehicles. For example, knowledge of the intended driving behavior may improve the prediction of the driving behavior of the one or more second vehicles.

[0017] There are various aspects of the at least semi-autonomous operation of the first vehicle that can be adjusted based on the predicted driving behavior. For example, adjusting the at least semi-autonomous operation of the first vehicle can include adjusting the currently applied automation level of the first vehicle. For example, different automation levels may be possible depending on the predicted driving behavior of one or more second vehicles.

[0018] In some cases, overall driving safety can be improved if some or all of the related vehicles operate at the same automation level. The method may include determining a common automation level suitable for use by the first vehicle and at least a subset of the one or more second vehicles based on the predicted driving behavior of the one or more second vehicles. The method may include transmitting information about the determined common automation level to at least the subset of the one or more second vehicles.

[0019] In some embodiments, coordinating at least semi-autonomous operation of a first vehicle may include selecting at least one of the one or more second vehicles to engage in a coordinated driving maneuver. The method may include transmitting a collaboration message to the selected at least one vehicle. For example, based on the predicted driving behavior of the other vehicles, a vehicle suitable for collaboration may be identified, for example, because the predicted driving behavior can be suitably combined with the driving behavior of the first vehicle.

[0020] In various embodiments, adjusting the at least semi-autonomous operation of the first vehicle can include adjusting one of a speed of the first vehicle and a minimum distance of the first vehicle relative to one or more second vehicles. Depending on the predicted driving behavior of the one or more second vehicles, a higher or lower speed and / or a higher or lower minimum distance may be desirable, for example, to account for possible erratic driving behavior due to a possible change in the automation level of one of the one or more second vehicles.

[0021] Information is received from one or more second vehicles via the one or more wireless messages. For example, the one or more wireless messages may be collaborative awareness messages (CAMs). In other words, information used to predict the driving behavior of the one or more second vehicles may be included in the CAM. Alternatively, separate messages may be used. In other words, the one or more wireless messages may be wireless messages received in addition to the collaborative awareness messages from the one or more second vehicles.

[0022] In addition to receiving the wireless message, the first vehicle may also broadcast its own information about its automation capabilities. In other words, the method may include: transmitting a wireless message to one or more second vehicles, the wireless message including information about one or more automation capabilities that the first vehicle can have. For example, the wireless message may further include: information about the manufacturer of one or more automation capabilities that the first vehicle can have, information about the version of one or more automation capabilities that the first vehicle can have, information about the maximum automation level of the first vehicle, information about the currently applied automation level of the first vehicle, information about one or more collaborative capabilities that the first vehicle can have, information about one or more collaborative driving maneuvers currently performed by the first vehicle, information about the driving performance settings currently used by the first vehicle, and information about the driving intentions of the first vehicle. Thus, the information can be transmitted to the second vehicle and used by the second vehicle to predict the driving behavior of the first vehicle (similar to the prediction performed by the first vehicle).

[0023] Various embodiments of the present disclosure relate to a corresponding apparatus for a first vehicle, the apparatus being adapted to adjust at least semi-autonomous operation of the first vehicle based on a prediction of the driving behavior of one or more second vehicles. The one or more second vehicles are vehicles that operate at least semi-autonomously. The apparatus includes an interface for communicating with the one or more second vehicles. The apparatus includes a control module configured to perform the above-described method.

[0024] Various embodiments of the present disclosure relate to a method for a vehicle (e.g., the second vehicle described above) that operates at least semi-autonomously. The method includes transmitting a wireless message to one or more additional vehicles. The wireless message includes information about one or more automation capabilities that the vehicle can have. For example, the wireless message may further include: information about the manufacturer of the one or more automation capabilities that the vehicle can have, information about the version of the one or more automation capabilities that the vehicle can have, information about the maximum automation level of the vehicle, information about the currently applied automation level of the vehicle, information about one or more collaborative capabilities that the vehicle can have, information about one or more collaborative driving maneuvers currently performed by the vehicle, information about the driving performance settings currently used by the vehicle, and information about the driving intentions of the vehicle. For example, one or more additional vehicles may use the information to predict the driving behavior of the vehicle.

[0025] Various embodiments of the present disclosure relate to corresponding apparatus for a vehicle that operates at least semi-autonomously, including an interface for communicating with one or more other vehicles and a control module configured to execute the above method.

[0026] Various embodiments of the present disclosure relate to a computer program having a program code for performing at least one of the above methods when the computer program is executed on a computer, a processor or a programmable hardware component. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Some other features or aspects will be described, by way of example only and with reference to the accompanying drawings, the following non-limiting embodiments of use of an apparatus or method or computer program or computer program product, in which:

[0028] Figure 1a and 1b A flow chart illustrating an example of a method for a first vehicle, the method being suitable for coordinating at least semi-autonomous operation of the first vehicle;

[0029] Figure 1c A block diagram illustrating an example of an apparatus for a first vehicle, the apparatus being adapted to coordinate at least semi-autonomous operation of the first vehicle;

[0030] Figure 1d A schematic diagram illustrating interaction between a first vehicle and a second vehicle;

[0031] Figure 2a A flow chart illustrating an example of a method for at least semi-autonomous operation of a vehicle; and

[0032] Figure 2b A block diagram illustrating an example of an apparatus for at least semi-autonomous operation of a vehicle is shown. DETAILED DESCRIPTION

[0033] Various example embodiments will now be described more fully with reference to the accompanying drawings in which some example embodiments are illustrated. In the accompanying drawings, the thickness of lines, layers, or regions may be exaggerated for clarity. Optional components may be illustrated using broken lines, dashed lines, or dotted lines.

[0034] Accordingly, although the exemplary embodiments are capable of various modifications and alternative forms, embodiments thereof are shown in the drawings by way of example and will be described in detail herein. However, it should be understood that there is no intention to limit the exemplary embodiments to the particular forms disclosed, but rather that the exemplary embodiments are intended to encompass all modifications, equivalents, and alternatives falling within the scope of the present invention. The same reference numerals throughout the description of the figures refer to the same or similar elements.

[0035] As used herein, the term "or" refers to a non-exclusive "or" unless otherwise indicated (e.g., "or else," or "or alternatively"). Furthermore, as used herein, words used to describe relationships between elements should be broadly interpreted to include direct relationships or the presence of intermediate elements, unless otherwise indicated. For example, when an element is referred to as being "connected" or "coupled" to another element, the element may be directly connected or coupled to the other element or there may be intermediate elements. In contrast, when an element is referred to as being "directly connected" or "directly coupled" to another element, there are no intermediate elements. Similarly, words such as "between," "adjacent," etc. should be interpreted in a similar manner.

[0036] The terms used herein are for the purpose of describing specific embodiments only and are not intended to limit the exemplary embodiments. As used herein, the singular forms "a," "an," and "the" are also intended to include the plural forms, unless the context clearly indicates otherwise. It will be further understood that the terms "comprise," "comprising," "include," or "including" when used herein specify the presence of stated features, integers, steps, operations, elements, or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or groups thereof.

[0037] Unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which the exemplary embodiments belong. It will be further understood that terms (e.g., terms defined in commonly used dictionaries) should be interpreted as having a meaning consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless explicitly defined as such herein.

[0038] Figure 1a and 1b A flow chart illustrating an example of a method for a first vehicle 100 adapted to adjust at least semi-autonomous operation of the first vehicle (in combination with a vehicle) based on a prediction of the driving behavior of one or more second vehicles 200 is shown. Figure 1c 、 1d 2b shows carriers 100; 200). Generally speaking, the method can be performed by a first carrier, such as the device 10 of the first carrier 100. In some cases, at least a subset of the method can also be performed by one of one or more second carriers 200, such as the device 20 of the second carrier 200. On the other hand, the carrier 100 can alternatively or additionally perform the method in conjunction with Figure 2a The method shown. One or more second vehicles and also the first vehicle are vehicles that operate at least semi-autonomously. The method includes: receiving 110 one or more wireless messages from the one or more second vehicles. The one or more wireless messages include information about one or more automation capabilities that the one or more second vehicles can have. The method includes: predicting 120 a driving behavior of the one or more second vehicles based on the information about the one or more automation capabilities that the one or more second vehicles can have. The method includes: adjusting 130 the at least semi-autonomous operation of the first vehicle based on the prediction of the driving behavior of the one or more second vehicles.

[0039] Figure 1c A block diagram of an example of a corresponding apparatus 10 for a first vehicle 100 is shown, the apparatus 10 being suitable for coordinating at least semi-autonomous operation of the first vehicle. The apparatus comprises an interface 12 for communicating with one or more second vehicles. The apparatus further comprises a control module 14 coupled to the interface 12 and configured to perform a combined operation. Figure 1a and / or the method shown in 1b.

[0040] To better outline the scenario, Figure 1d . Figure 1d A schematic diagram showing the interaction between one of the second carriers 200 and the first carrier 100. The first carrier 100 includes the device 10. The second carrier 200 includes the device 20 (e.g., as combined with Figure 2bFor example, the device 20 may be similar to Figure 1c For example, the vehicle 100 and / or the vehicle 200 may be a land vehicle, a road vehicle, a sedan, a car, an off-road vehicle, a motor vehicle, a truck, or a lorry.

[0041] The following description involves Figure 1a and / or 1b method and involves Figure 1c and / or the corresponding apparatus and vehicle of 1d (and also the corresponding computer program). Features introduced in conjunction with the method may also be applied to the corresponding apparatus / vehicle and / or computer program (and vice versa).

[0042] Various embodiments of the present disclosure relate to methods, apparatus, and computer programs for a first vehicle, adapted to adjust at least semi-autonomous operation of the first vehicle based on a prediction of the driving behavior of one or more second vehicles 200. In this context, the term "at least semi-autonomous operation" indicates that at least one of the vehicle subsystems used to control / manipulate the movement of the vehicle is autonomously operated. For example, according to SAE Standard J3016, six levels of automated (or autonomous) driving are distinguished, from Level 0 to Level 5. These six levels are denoted as: Level 0 (no automation, driver operates the vehicle), Level 1 (driver assistance, driver operates the vehicle with the help of an assistance system that provides longitudinal or lateral guidance), Level 2 (partial automation, driver assistance system provides assistance with longitudinal or lateral guidance), Level 3 (conditional automation, automated driving with the expectation that the driver must resume control at some point), Level 4 (high automation, automated driving without the expectation that the driver must resume control at some point), and Level 5 (full automation in any scenario where the driver is also capable). For example, "operating at least semi-autonomously" may indicate an automation level of at least level 2 or at least level 3. In the context of this application, the terms "autonomous" and "automated" may be used interchangeably. For example, the term "operating at least semi-autonomously" may be understood as "at least partially automated."

[0043] The method adjusts the at least semi-autonomous operation of the first vehicle based on the predicted driving behavior of one or more second vehicles, which predicted driving behavior is in turn predicted based on the one or more wireless messages received from the one or more second vehicles. For example, the one or more wireless messages may be wireless messages that are periodically transmitted by and received from the one or more second vehicles. For example, the one or more wireless messages may be wireless messages received directly from the one or more second vehicles, such as so-called device-to-device (D2D) messages, and in particular vehicle-to-vehicle (V2V) messages. For example, the one or more wireless messages may be broadcast by the one or more second vehicles, such as as D2D / V2V messages. In some cases, direct communication may be assisted by a relay, such as a roadside communication relay that retransmits the one or more wireless messages. In this case, the terms D2D or V2V may still apply.

[0044] In V2V communication, one wireless message used to periodically convey information between vehicles is a so-called collaborative awareness message (CAM). For example, the one or more wireless messages may be collaborative awareness messages. The CAM includes the position, heading, vehicle type, timestamp, etc. of the vehicle transmitting the CAM. Furthermore, in the context of the present disclosure, the CAM may now include various information segments attributed to the one or more wireless messages. Alternatively (or additionally), the one or more wireless messages may be wireless messages received in addition to collaborative awareness messages from one or more second vehicles. For example, a hybrid scenario may be used in which some information segments are included in the CAM and some information is transmitted via additional wireless messages.

[0045] As previously noted, the one or more wireless messages include various information segments that can be used to predict the driving behavior of one or more second vehicles. In particular, the one or more wireless messages include information about one or more automation capabilities that one or more second vehicles can have. Likewise, the driving behavior of one or more second vehicles is predicted based on the information about the one or more automation capabilities that one or more second vehicles can have. For example, the information about the one or more automation capabilities that one or more second vehicles can have may indicate which automation capabilities can be used or are being used for at least semi-autonomous operation of the one or more vehicles. For example, the information about the one or more automation capabilities that one or more second vehicles can have may include a bit vector that indicates, for each of a set of predefined automation capabilities, whether the corresponding second vehicle is (e.g., currently or typically) capable of performing the automation capability. Alternatively, the information about the one or more automation capabilities that one or more second vehicles can have may include a list of automation capabilities that the corresponding second vehicle can have.

[0046] In some cases, information about one or more automation capabilities that one or more second vehicles can have can be derived from other information, such as the manufacturer of the second vehicle, the software version of the corresponding automation capability, and / or the automation level of the second vehicle. For example, in order to achieve a given automation level, a vehicle according to a given manufacturer may provide a set of required capabilities (and optionally also a set of optional capabilities). These sets of required (or optional) capabilities may change over time, so that, for example, a vehicle (according to the manufacturer) that is capable of semi-autonomous operation at level 3 in 2020 has different capabilities than a vehicle that is capable of semi-autonomous operation at level 3 in 2025. Therefore, the manufacturer, software version and / or automation level can be used to determine which set of required capabilities is applicable. Therefore, the one or more wireless messages may include information about the manufacturer and version of one or more automation capabilities that one or more second vehicles can have. Additionally or alternatively, the one or more wireless messages include information about the maximum automation level and / or the currently applied automation level of the one or more second vehicles. Thus, the driving behavior of one or more second vehicles can be predicted based on information about the manufacturer and version of one or more automation capabilities that the one or more second vehicles can have, and / or based on information about the maximum automation level and / or the currently applied automation level of the one or more second vehicles. For example, the information about the manufacturer and version of one or more automation capabilities that the one or more second vehicles can have, and / or the information about the maximum automation level and / or the currently applied automation level of the one or more second vehicles may include or indicate information about the one or more automation capabilities that the one or more second vehicles can have. In this scenario, the first vehicle can distinguish between automation capabilities that are "typically" available and automation capabilities that are currently in use (e.g., based on the currently used automation level).

[0047] Another factor in determining the likely driving behavior of one or more second vehicles is the “performance mode” in which the one or more second vehicles are being driven. For example, the “performance mode” or “driving performance setting” may be one of a “sport mode / sport driving performance setting”, which may include more intense acceleration; a “comfort mode / driving performance setting”, which may guide the vehicle's operation towards fewer sudden movements; an “economy mode / driving performance setting”, which may reduce the energy usage of the respective second vehicle; or a “balanced mode”. Depending on the driving performance setting, the driving behavior of the respective second vehicle may vary, and the prediction of the driving behavior may be adjusted accordingly. In other words, the one or more wireless messages may include information about the driving performance setting currently used by the one or more second vehicles. For example, the information about the driving performance setting currently used by the one or more second vehicles may indicate which driving performance setting the respective second vehicle is currently using. The driving behavior of one or more second vehicles may be predicted based on the information about the driving performance setting currently used by the one or more second vehicles.

[0048] Another factor is the actual driving intention of the corresponding second vehicle. In many cases, the driving intention of one or more second vehicles can be derived (derived by the first vehicle) based on their position, speed and heading - the position, speed and heading are included in the CAM received from the corresponding vehicle, and used to predict the driving behavior of one or more second vehicles. However, in some cases, information about driving intention can be included in the one or more wireless messages. For example, the one or more wireless messages may include information about the driving intention of one or more second vehicles. The driving behavior of one or more second vehicles can be predicted based on information about the driving intention of one or more second vehicles. For example, information about driving intention can be received as part of a collaboration request or independently of any planned collaboration of the corresponding second vehicle.

[0049] As indicated above, the behavior of one or more second vehicles may also depend on possible collaboration between the vehicles. For example, at an intersection, collaboration between vehicles may be used to perform a "platoon start", where vehicles that are queued at the intersection are started simultaneously and in a coordinated manner. This collaboration capability (and the actual collaboration being performed) or lack of collaboration capability has a major impact on the driving behavior of the respective vehicles, resulting in an adjustment of the predicted driving behavior of the one or more second vehicles. For example, the one or more wireless messages may include information about one or more collaboration capabilities that the one or more second vehicles are capable of and / or information about one or more collaborative driving maneuvers that the one or more second vehicles are currently performing. The driving behavior of one or more second vehicles may be predicted based on information about one or more collaboration capabilities that the one or more second vehicles are capable of and / or information about one or more collaborative driving maneuvers that the one or more second vehicles are currently performing.

[0050] In the above description, only the abstract term "adjusting 130 the at least semi-autonomous operation of the first vehicle based on a prediction of the driving behavior of one or more second vehicles" has been used. In practice, various aspects of the at least semi-autonomous operation of the first vehicle may be adjusted. In this context, the term "at least semi-autonomous operation of the first vehicle" may indicate that the operation of the first vehicle being adjusted relates to the operation of the first vehicle and therefore to its movement. For example, the prediction of the driving behavior of one or more second vehicles may be used to adjust how the first vehicle moves in the at least semi-autonomous operation. In some cases, the prediction of the driving behavior may be used to cease the at least semi-autonomous operation entirely, thereby giving control of the vehicle to the driver of the vehicle.

[0051] For example, adjusting the at least semi-autonomous operation of the first vehicle can include adjusting 138 one of the speed of the first vehicle and a minimum distance of the first vehicle relative to one or more second vehicles. These two parameters can be based on how predictable and / or abrupt the movement of the one or more second vehicles is predicted to be. In scenarios where the movement of the one or more second vehicles is predicted with a high degree of certainty (e.g., on a nearly empty highway), a higher speed and / or a smaller minimum distance can be selected.

[0052] As hinted above, another factor that can be adjusted is the automation level used by the first vehicle. For example, different automation levels can be selected based on how predictable and / or abrupt the movements of one or more second vehicles are predicted to be. In other words, adjusting the at least semi-autonomous operation of the first vehicle includes adjusting 132 the automation level currently applied by the first vehicle. For example, in ambiguous scenarios, a lower automation level (e.g., Level 3) can be selected, and the driver can be warned that they may be required to take control on short notice. Because this automation level can also be applied to other vehicles, the determined automation level can be shared among vehicles occupying the same (or adjacent) portion of the road. For example, the method can include determining 134 a common automation level suitable for use by the first vehicle and at least a subset of the one or more second vehicles based on the predicted driving behavior of the one or more second vehicles, and transmitting 135 information about the determined common automation level to at least the subset of the one or more second vehicles. For example, the common automation level can be determined similarly to the automation level currently applied by the first vehicle, for example based on how predictable and / or ambiguous the driving of the one or more second vehicles is.

[0053] Finally, adjusting the at least semi-autonomous operation of the first vehicle can be related to performing collaboration between the first vehicle and one or more second vehicles. For example, adjusting the at least semi-autonomous operation of the first vehicle can include: selecting 136 at least one of the one or more second vehicles to engage in order to perform a coordinated driving maneuver; and transmitting 137 a collaboration message to the selected at least one vehicle. For example, the predicted driving behavior and / or the collaboration capabilities included in the one or more wireless messages can be used to identify a vehicle among the one or more second vehicles that is suitable for collaboration with the first vehicle.

[0054] As already indicated above, the first vehicle can be both a recipient and a transmitter of the wireless message. In fact, the same type of wireless message received by the first vehicle can also be transmitted from the first vehicle to one or more second vehicles. Therefore, the method may include: transmitting (e.g., broadcasting) a wireless message 140 to one or more second vehicles, the wireless message including information about one or more automation capabilities that the first vehicle can have. For example, the wireless message transmitted by the first vehicle may include information about the manufacturer of one or more automation capabilities that the first vehicle can have, information about the version of one or more automation capabilities that the first vehicle can have, information about the maximum automation level of the first vehicle, information about the currently applied automation level of the first vehicle, information about one or more collaborative capabilities that the first vehicle can have, information about one or more collaborative driving maneuvers currently performed by the first vehicle, information about the driving performance settings currently used by the first vehicle, and information about the driving intentions of the first vehicle.

[0055] In various embodiments, interface 12 may correspond to any component for obtaining, receiving, transmitting, or providing analog or digital signals or information, such as any connector, contact, pin, register, input port, output port, conductor, channel, etc., that allows for providing or obtaining signals or information. The interface may be wireless or wired, and may be configured to communicate with other internal or external components, i.e., to transmit or receive signals or information. Interface 12 may include additional components to enable corresponding communications within a mobile communication system. Such components may include transceiver (transmitter and / or receiver) components, such as one or more low-noise amplifiers (LNAs), one or more power amplifiers (PAs), one or more duplexers, one or more diplexers, one or more filters or filter circuits, one or more converters, one or more mixers, and correspondingly adapted radio frequency components. Interface 12 may be coupled to one or more antennas, which may correspond to any transmitting and / or receiving antennas, such as horn antennas, dipole antennas, patch antennas, sector antennas, etc. The antennas may be arranged in a defined geometric arrangement, such as a uniform array, a linear array, a circular array, a triangular array, a uniform field antenna, a field array, combinations thereof, etc. In some examples, the interface 12 may be used for the purpose of transmitting or receiving information (such as information, input data, control information, further information messages, etc.), or both transmitting and receiving information.

[0056] like Figure 1c and 1dAs shown, the corresponding interface 12 is coupled to the corresponding control module 14 at the device 10. For example, the control module 14 can be implemented using one or more processing units, one or more processing devices, one or more processors, or any component for processing (such as a processor, a computer, or a programmable hardware component operable with corresponding adapted software). In other words, the described functions of the control module 14 can also be implemented using software, which is then executed on one or more programmable hardware components. Such hardware components may include general-purpose processors, digital signal processors (DSPs), microcontrollers, and the like.

[0057] In an embodiment, communication (i.e., transmission, reception, or both) may occur directly between the devices 10 / 20 or vehicles 100 / 200. Such communication may utilize a mobile communication system. Such communication may be implemented directly, for example, by means of device-to-device (D2D) communication. Such communication may be implemented using the specifications of the mobile communication system. An example of D2D is direct communication between vehicles, also referred to as vehicle-to-vehicle communication (V2V), vehicle-to-vehicle communication, and dedicated short range communication (DSRC). Technologies that enable such D2D communication include 802.11p, 3GPP systems (4G, 5G, NR, and beyond), and the like.

[0058] In an embodiment, the interface 12 can be configured to perform wireless communication in a mobile communication system. To do so, radio resources are used, such as frequency resources, time resources, code resources and / or space resources, which can be used for wireless communication with a base transceiver station and for direct communication. The base transceiver station can control the assignment of radio resources, i.e., determine which resources are used for D2D and which resources are not used for D2D. Here and in the following, the radio resources of the respective components can correspond to any conceivable radio resources on a radio carrier, and they can use the same or different granularity on the respective carriers. The radio resources can correspond to resource blocks (such as RBs in LTE / LTE-A / unlicensed LTE (LTE-U)), one or more carriers, subcarriers, one or more radio frames, radio subframes, radio slots, one or more code sequences potentially with corresponding spreading factors, one or more spatial resources (such as spatial subchannels, spatial precoding vectors), any combination thereof, and the like. For example, in direct cellular vehicle-to-everything (C-V2X) (where V2X includes at least V2V, V2-infrastructure (V2I), etc.), transmissions from 3GPP Release 14 onwards can be managed by the infrastructure (so-called Mode 3) or run in the UE.

[0059] In combination with the proposed concept, or one or more examples described above or below (e.g., Figures 2a to 2b ) to mention more details and aspects of the method, apparatus, vehicle and computer program. The method, apparatus, vehicle and computer program may include one or more additional optional features corresponding to one or more aspects of the proposed concept or one or more examples described above or below.

[0060] Figure 2a A flow chart illustrating an example of a method for at least semi-autonomous operation of a vehicle 100; 200 is shown. For example, the method may be performed by a vehicle 100; 200. The method includes transmitting 140 a wireless message to one or more additional vehicles 100; 200 (e.g., a first vehicle or one or more second vehicles). Figure 2b A block diagram of an example of a corresponding apparatus 20 for a vehicle operating at least semi-autonomously is shown. The apparatus may include an interface 22 for communicating with one or more other vehicles, and a controller configured to perform Figure 2a methods and / or Figure 1a The control module 24 is coupled to the interface 22 .

[0061] For example, the wireless message may correspond to a combination of Figures 1a to 1d One of the one or more wireless messages introduced. Thus, the wireless message includes information about one or more automation capabilities that the vehicle is capable of. The wireless message may include: information about the manufacturer of the one or more automation capabilities that the vehicle is capable of, information about the version of the one or more automation capabilities that the vehicle is capable of, information about the maximum automation level of the vehicle, information about the currently applied automation level of the vehicle, information about one or more collaborative capabilities that the vehicle is capable of, information about one or more collaborative driving maneuvers currently performed by the vehicle, information about the driving performance settings currently used by the vehicle, and information about the driving intentions of the vehicle. For example, the vehicle may be Figures 1a to 1d One of the one or more second carriers 200, or Figures 1a to 1d Therefore, the vehicle can also be configured to perform Figure 1a and / or 1b, and the apparatus 20 may be similar to Figure 1c and / or 1d. However, in some cases, Figures 1a to 1d Some features of the method and apparatus for Figures 2a to 2b The method and / or apparatus may be optional.

[0062] In various embodiments, interface 22 may correspond to any component for obtaining, receiving, transmitting, or providing analog or digital signals or information, such as any connector, contact, pin, register, input port, output port, conductor, channel, etc., that allows for providing or obtaining signals or information. The interface may be wireless or wired, and may be configured to communicate with other internal or external components, i.e., to transmit or receive signals or information. Interface 22 may include additional components to enable corresponding communications within a mobile communication system. Such components may include transceiver (transmitter and / or receiver) components, such as one or more low-noise amplifiers (LNAs), one or more power amplifiers (PAs), one or more duplexers, one or more diplexers, one or more filters or filter circuits, one or more converters, one or more mixers, and correspondingly adapted radio frequency components. Interface 22 may be coupled to one or more antennas, which may correspond to any transmitting and / or receiving antennas, such as horn antennas, dipole antennas, patch antennas, sector antennas, etc. The antennas may be arranged in defined geometric configurations, such as uniform arrays, linear arrays, circular arrays, triangular arrays, uniform field antennas, field arrays, or combinations thereof. In some examples, interface 22 may be used for the purpose of transmitting or receiving information (such as information, input data, control information, further information messages, etc.), or both.

[0063] like Figure 2b As shown, the corresponding interface 22 is coupled to the corresponding control module 24 at the device 10. For example, the control module 24 can be implemented using one or more processing units, one or more processing devices, one or more processors, or any component for processing (such as a processor, a computer, or a programmable hardware component operable with corresponding adapted software). In other words, the described functions of the control module 24 can also be implemented using software, which is then executed on one or more programmable hardware components. Such hardware components may include general-purpose processors, digital signal processors (DSPs), microcontrollers, and the like.

[0064] In an embodiment, communication (i.e., transmission, reception, or both) may occur directly between the devices 10 / 20 or vehicles 100 / 200. Such communication may utilize a mobile communication system. Such communication may be implemented directly, for example, by means of device-to-device (D2D) communication. Such communication may be implemented using the specifications of the mobile communication system. An example of D2D is direct communication between vehicles, also referred to as vehicle-to-vehicle communication (V2V), vehicle-to-vehicle communication, and dedicated short range communication (DSRC). Technologies that enable such D2D communication include 802.11p, 3GPP systems (4G, 5G, NR, and beyond), and the like.

[0065] In an embodiment, the interface 22 can be configured to perform wireless communication in a mobile communication system. To do so, radio resources are used, such as frequency resources, time resources, code resources and / or space resources, which can be used for wireless communication with a base transceiver station and for direct communication. The base transceiver station can control the assignment of radio resources, i.e., determine which resources are used for D2D and which resources are not used for D2D. Here and in the following, the radio resources of the respective components can correspond to any conceivable radio resources on a radio carrier, and they can use the same or different granularity on the respective carriers. The radio resources can correspond to resource blocks (such as RBs in LTE / LTE-A / unlicensed LTE (LTE-U)), one or more carriers, subcarriers, one or more radio frames, radio subframes, radio slots, one or more code sequences potentially with corresponding spreading factors, one or more spatial resources (such as spatial subchannels, spatial precoding vectors), any combination thereof, and the like. For example, in direct cellular vehicle-to-everything (C-V2X) (where V2X includes at least V2V, V2-infrastructure (V2I), etc.), transmissions from 3GPP Release 24 onwards can be managed by the infrastructure (so-called Mode 3) or run in the UE.

[0066] In combination with the proposed concept, or one or more examples described above or below (e.g., Figures 1a to 1d ) to mention more details and aspects of the method, apparatus, vehicle and computer program. The method, apparatus, vehicle and computer program may include one or more additional optional features corresponding to one or more aspects of the proposed concept or one or more examples described above or below.

[0067] Various embodiments of the present disclosure relate to automation level and / or collaborative broadcast messages. For example, automation level and / or collaborative broadcast messages may correspond to a combination of Figures 1a to 2b Introduced wireless message(s). As already noted above, various kinds of information may be shared by AVs (e.g., the second vehicle and / or the first vehicle) to facilitate prediction of the AV's driving behavior by other AVs (e.g., the first vehicle). For example, the AVs may share this information via direct communication via a broadcast message. For example, this information may be transmitted as a new broadcast message, or it may be included within an existing vehicle broadcast message, such as a collaborative awareness message (CAM). In some scenarios, this information may be distributed via roadside infrastructure (which may act as a relay).

[0068] Automation and collaboration broadcast messages may include one or more of the following characteristics: AV level (automation capabilities), such as SAE level and / or software version, collaboration capabilities, AV characteristics, AV status and actions (e.g., the maneuver the AV is currently performing, such as the AV is parking, turning, etc.), a timestamp, the ID and model (type, size) of the vehicle itself, and the location of the vehicle itself.

[0069] For example, an AV may determine possible automation levels and collaborations by, for example, predicting the driving behavior of other AVs, even if the AV is not using it, thereby adjusting the AV's automation level and / or collaborating with other AVs.

[0070] An AV A can share its automation-related information, such as its SAE level (for example), software version, automation features / capabilities, and / or an estimate of the possible automation level. For example, a visual notification of the possible automation level can be provided to the driver of the vehicle, for example as a warning, so the driver can take over operation of the vehicle. In some cases, different modes (sport, comfort) can be considered.

[0071] For example, AVs (or other AVs) can share their cooperation-related information, such as cooperation capabilities (platooning, maneuver coordination) or detected possible cooperation.

[0072] For example, an AVA can share its state and actions (e.g., what the vehicle is doing in a) and / or b)), i.e., the state of automation or collaboration. Other entities (e.g., a vehicle that receives one of the above information segments from the AVA) can use this information to predict the AVA's behavior, adapt their behavior based on the AVA, and / or evaluate whether collaboration is possible.

[0073] Below, some examples are given. In the first example, a platoon launch is performed at a traffic light (as a collaborative example). A first AV may be queued at the traffic light with other vehicles (e.g., AVs). (e.g., all) AVs can share their automation and collaborative broadcast messages. The first AV can verify whether the vehicle(s) in front of it can support the platoon launch (collaboration capability) to improve fuel and traffic flow efficiency.

[0074] In a second example, AV driving mode adaptation is performed (as a collaborative example). A first AV is driving on a street with other vehicles (AVs). (For example, all) AVs are sharing their automation and collaborative broadcast messages. The first AV can verify whether the surrounding vehicle (or vehicles) are driving with a different automation method and then adapt its own driving behavior to it to increase fuel and traffic flow efficiency.

[0075] In a third example, initiation of any type of collaboration is performed (as an example of collaboration). A first AV is driving on a street with other vehicles (e.g., AVs). (e.g., all) AVs are sharing their automation and collaboration broadcast messages. The first AV can verify whether (one or more) other vehicles offer any type of collaboration, and if so, it can initiate a certain type of collaboration.

[0076] For example, AVA may correspond to binding Figures 1a to 1c One of the second carriers introduced and / or the first carrier, and the "other" AV (e.g., the first AV) may correspond to a combination of Figures 1a to 1c The first vehicle introduced.

[0077] In combination with the proposed concept, or one or more examples described above or below (e.g., Figures 1a to 2b ) to mention more details and aspects of the automation level and / or collaborative broadcast message. The automation level and / or collaborative broadcast message may include one or more additional optional features corresponding to one or more aspects of the proposed concept or one or more examples described above or below.

[0078] As already mentioned, in embodiments, the corresponding methods can be implemented as computer programs or codes that can be executed on corresponding hardware. Therefore, another embodiment is a computer program having program code for carrying out at least one of the above methods when the computer program is executed on a computer, a processor, or a programmable hardware component. A further embodiment is a computer-readable storage medium storing instructions that, when executed by a computer, a processor, or a programmable hardware component, causes the computer to carry out one of the methods described herein.

[0079] Those skilled in the art will readily recognize that the step of various methods described above can be performed by a programmed computer, for example, can determine or calculate the position of a time slot. In this article, some embodiments are also intended to contain program storage devices, for example digital data storage media, and this program storage device is machine or computer readable and machine executable or computer executable instruction program is encoded, wherein the instruction is carried out some or all of the step of the method described herein. Program storage devices can be for example digital memory, magnetic storage media such as disks and tapes, hard disk drives or optically readable digital data storage media. Embodiments are also intended to contain the computer programmed to perform the described steps of the method described herein, or contain (field) programmable logic array ((F) PLA) or (field) programmable gate array ((F) PGA) programmed to perform the described steps of the method described above.

[0080] The description and the accompanying drawings only illustrate the principles of the present invention. It will be appreciated that those skilled in the art will be able to envision various arrangements that, although not explicitly described or shown herein, embody the principles of the present invention and are included in its spirit and scope. In addition, all examples recorded herein are in principle clearly intended to be used only for teaching purposes to assist the reader in understanding the principles of the present invention and the concepts contributed by (one or more) inventors to promote this area, and should be interpreted as not being limited to such specific examples and conditions. In addition, all statements recording the principles, aspects and embodiments of the present invention and their specific examples herein are intended to cover their equivalents. When functions are provided by a processor, these functions can be provided by a single dedicated processor, by a single shared processor, or by multiple separate processors (some of which can be shared). In addition, the explicit use of the term "processor" or "controller" should not be interpreted as exclusively referring to hardware that can execute software, and can implicitly include but are not limited to digital signal processor (DSP) hardware, network processor, application specific integrated circuit (ASIC), field programmable gate array (FPGA), read-only memory (ROM), random access memory (RAM) and non-volatile storage device for storing software. Conventional or customized other hardware can also be included. Their function may be carried out through the operation of program logic, through dedicated logic, through the interaction of program control and dedicated logic, or even manually, the particular technique being selectable by the implementer as more specifically understood from the context.

[0081] It will be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative circuitry embodying the principles of the invention. Similarly, it will be appreciated that any flow charts, flow diagrams, state transition diagrams, pseudo-random codes, and the like represent various processes that can be substantially represented in a computer-readable medium and thus executed by a computer or processor, regardless of whether such a computer or processor is explicitly shown.

[0082] In addition, the following claims are hereby incorporated into the Detailed Description, where each claim can stand on its own as a separate embodiment. Although each claim can stand on its own as a separate embodiment, it should be noted that although a dependent claim refers to a specific combination with one or more other claims in the claims, other embodiments may include combinations of the dependent claim with the subject matter of each other dependent claim. Such combinations are proposed herein unless it is stated that a specific combination is not intended. In addition, it is intended that features of a claim be included in any other independent claim, even if that claim is not directly dependent on that independent claim.

[0083] It is further noted that the methods disclosed in the specification or in the claims can be implemented by an apparatus having means for carrying out each of the respective steps of these methods.

[0084] Reference Symbol List

[0085] 10 Devices

[0086] 12 interfaces

[0087] 14 Control Module

[0088] 20 devices

[0089] 22 interfaces

[0090] 24 Control Module

[0091] 100 First Vehicle

[0092] 110 Receive one or more wireless messages

[0093] 120 Predicting Driving Behavior

[0094] 130 Adjusting Vehicle Operations

[0095] 132 Adjusting Automation Levels

[0096] 134 Determine the public automation level

[0097] 135 Transmits information about common automation levels

[0098] 136 Selecting a vehicle for collaboration

[0099] 137 Transmitting Collaboration Messages

[0100] 138 Adjust speed and / or minimum distance

[0101] 140 Transmitting wireless messages

[0102] 200 Second Vehicle

Claims

1. A method for a first vehicle (100), the method being adapted to adjust at least semi-autonomous operation of the first vehicle based on a prediction of driving behavior of one or more second vehicles (200), the one or more second vehicles being at least semi-autonomous operating vehicles, the method comprising: receiving (110) one or more wireless messages from one or more second vehicles, the one or more wireless messages including information about one or more automation capabilities that the one or more second vehicles are capable of; predicting (120) driving behavior of the one or more second vehicles based on information about the one or more automated capabilities that the one or more second vehicles are capable of; as well as Adjusting (130) at least semi-autonomous operation of a first vehicle based on a prediction of driving behavior of one or more second vehicles, wherein the one or more wireless messages include: information about one or more collaborative capabilities that the one or more second vehicles are capable of and information about one or more collaborative driving maneuvers currently being performed by the one or more second vehicles, wherein the driving behavior of the one or more second vehicles is predicted based on the information about one or more collaborative capabilities that the one or more second vehicles are capable of and / or information about one or more collaborative driving maneuvers currently being performed by the one or more second vehicles.

2. The method of claim 1 , wherein the one or more wireless messages comprise: Information about the manufacturer and version of one or more automation capabilities that the one or more second vehicles can have, wherein the driving behavior of the one or more second vehicles is predicted based on the information about the manufacturer and version of one or more automation capabilities that the one or more second vehicles can have.

3. The method of claim 1 or 2, wherein the one or more wireless messages comprise: Information about a maximum automation level and / or a currently applied automation level for one or more second vehicles, wherein a driving behavior of the one or more second vehicles is predicted based on the information about the maximum automation level and / or the currently applied automation level for the one or more second vehicles.

4. The method of claim 1 or 2, wherein the one or more wireless messages comprise: Information about driving performance settings currently used by one or more second vehicles, wherein driving behavior of the one or more second vehicles is predicted based on the information about driving performance settings currently used by the one or more second vehicles.

5. The method of claim 1 or 2, wherein the one or more wireless messages comprise: Information about a driving intention of the one or more second vehicles, wherein a driving behavior of the one or more second vehicles is predicted based on the information about the driving intention of the one or more second vehicles.

6. The method of claim 1 or 2, wherein adjusting the at least semi-autonomous operation of the first vehicle comprises: The currently applied automation level of the first vehicle is adjusted (132).

7. The method according to claim 1 or 2, comprising: determining (134) a common automation level suitable for use by the first vehicle and at least a subset of the one or more second vehicles based on the predicted driving behavior of the one or more second vehicles; and transmitting (135) information about the determined common automation level to at least the subset of the one or more second vehicles.

8. The method of claim 1 or 2, wherein adjusting the at least semi-autonomous operation of the first vehicle comprises: selecting (136) at least one of the one or more second vehicles to engage in order to perform a coordinated driving maneuver; and transmitting (137) a collaboration message to the selected at least one vehicle.

9. The method of claim 1 or 2, wherein adjusting the at least semi-autonomous operation of the first vehicle comprises: One of a speed of the first vehicle and a minimum distance of the first vehicle relative to one or more second vehicles is adjusted (138).

10. The method according to claim 1 or 2, wherein the one or more wireless messages are collaboration awareness messages (CAMs), or wherein the one or more wireless messages are wireless messages received in addition to collaboration awareness messages from one or more second vehicles.

11. The method according to claim 1 or 2, comprising: A wireless message (140) is transmitted to one or more second vehicles, the wireless message including information regarding one or more automation capabilities that the first vehicle is capable of. 12 . A computer program product having a program code for performing the method according to claim 1 , when the computer program is executed on a computer, a processor or a programmable hardware component.

13. An apparatus (10; 200) for at least semi-autonomous operation of a vehicle (100; 200) 20), the device comprises: an interface (12; 22) for communicating with one or more further vehicles (100; 200); and A control module (14; 24) configured to carry out the method according to one of claims 1 to 11.

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