Patent Description:
Vehicular communication is a field of research and development. To enable an autonomous or semi-autonomous driving of vehicles, vehicles are expected to use Vehicle-to-Vehicle-communication (V2V) and Vehicle-to-Network (V2N) communication, e.g. to coordinate driving maneuvers and/or to receive tele-operated driving instructions. This communication is generally wireless, i.e. vehicles may wirelessly communicate with other vehicles in their vicinity and/or with backend services via cellular mobile communication systems.

Tele-operated driving (ToD) is getting more and more interest. The main concept of ToD is an automated vehicle (AV) remotely driven by a control/command center (CC). CC and AV may be far away from each other. They are connected via a radio communication system (e.g. <NUM>th, <NUM>th Generation mobile communication systems (<NUM>, <NUM>)) and its backhaul. Therefore, a certain end-to-end (E2E) delay and data rate are to be expected. The CC controls the automated vehicle (AV) via remote control. In direct control the CC directly controls one or more actuators of the AV.

For example, 5GCroCo will trial <NUM> technologies in the cross-border corridor along France, Germany and Luxembourg. In addition, 5GCroCo also aims at defining new business models that can be built on top of this unprecedented connectivity and service provisioning capacity. Further information can be found on https://5qcroco.

Document <CIT> describes a concept using a vehicular Artificial Intelligence (Al) unit, which is configured: to receive inputs from a plurality of vehicular sensors of a vehicle; to locally process within the vehicle at least a first portion of the inputs; to wirelessly transmit via a vehicular wireless transmitter at least a second portion of the inputs to a remote tele-driving processor located externally to the vehicle; to wirelessly receive via a vehicular wireless receiver from the remote tele-driving processor, a remotely-computed processing result that is received from a remote Artificial Intelligence (Al) unit; and to implement a vehicular operating command based on the remotely-computed processing result, via an autonomous driving unit of the vehicle or via a tele-driving unit of the vehicle.

Document <CIT> discloses a method for providing a multimedia broadcast/multicast service (MBMS) to a terminal related to a vehicle by a broadcast and multicast service center (BM-SC). The method includes identifying at least one candidate service area that the terminal is predicted to pass through, and transmitting, to an MBMS-gateway (MBMS-GW) a request for configuring the radio bearer of the at least one candidate service area.

Document <CIT> describes a concept for a connected vehicle environment, in which network connection parameters such as a network congestions window and bit rate are automatically adjusted dependent on a location of a vehicle in order to optimize network performance. A geospatial database stores learned relationships in order to optimize network performance of a connected vehicle at different physical locations when configured in accordance with different network parameters. The vehicle can then adjust its network parameters dynamically dependent on its location. A vehicle may maintain multiple connections to different networks concurrently for transmitting duplicate data of a data stream with the vehicle independently adjusting parameters associated with different networks to optimize performance.

<NPL> present a risk assessment approach that allows to control the behavior of self-driving cars. This continuous real-time risk assessment considers uncertainties as well as accident severity predictions to intervene integrally. It allows predictive traffic interaction and collision avoidance, and also an intelligent crash interaction. These decisions are made on incomplete data, due to imperfect environment perception data and road users' unknown intentions. Advanced, situational and numerical dependencies are regarded. Furthermore, the benefit of multiple approximating accident severity estimations are discussed.

Document<NPL>, illuminates the 5GCroCo project, with a total budget of <NUM> million Euro and partially funded by the European Commission, which aims at validating <NUM> technologies in the Metz-Merzig-Luxembourg cross-border corridor, traversing the borders between France, Germany and Luxembourg. 5GCroCo validation will focus on three use cases: <NUM>) tele-operated driving, <NUM>) high-definition map generation and distribution for automated vehicles, and <NUM>) Anticipated Cooperative Collision Avoidance.

Document <CIT> relates generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. A method may include receiving data associated with a sensor measurement of a perceived object, determining a label associated with the perceived object based on an initial calibration, retrieving log file data associated with the label, determining a calibration parameter associated with the sensor measurement based on the retrieved log file data, and storing the calibration parameter in association with a sensor associated with the sensor measurement. Sensors may be calibrated on the fly while the autonomous vehicle is in operation using one or more other sensors and/or fused data from multiple types of sensors.

There is a demand for an improved concept for control in ToD.

Embodiments are based on the finding that ToD control performance is linked to communication link performance. For example, latency and data rate performance of a communication link between a CC/tele-operator and a tele-operated vehicle contribute significantly to a reaction time of the vehicle. In the uplink, i.e. the communication link from the vehicle to the CC, there are communication latencies involved between data acquisition at the vehicle (e.g. video and other sensing) and data presentation (e.g. video display). The tele-operator hence reacts to delayed data and issues a control command, which undergoes further communication delay when being communicated to the vehicle in the downlink (from the CC to the vehicle). To avoid safety risks, the speed limit of the vehicle should be the lower the higher the communication delays. It is one finding of embodiments that the speed limit for a remote operated vehicle should depend on the predicted quality of service (pQoS) of the communication link. It is a further finding that the speed limit should also depend on the traffic environment the remote operated vehicle is in. For example, on a Saturday afternoon in a residential area on a sunny day the speed limit should be far lower than on a weekday on a highway in the middle of the night at low traffic density.

Embodiments provide a method for determining a speed limit for a tele-operated vehicle. The method comprises obtaining information related to an environment of the tele-operated vehicle, and obtaining information related to a predictive quality of service, pQoS, of a communication link between the tele-operated vehicle and a tele-operator of the vehicle. The method further comprises determining the speed limit based on the information related to the environment of the tele-operated vehicle and the information related to the pQoS. Embodiments may consider a quality of the communication link and environmental information when determining a speed limit for a tele-operated vehicle.

The method may further comprise applying the speed limit to the vehicle while being tele-operated. Speed limits of tele-operated vehicles may be adapted to radio and traffic conditions in embodiments.

In some embodiments the communication link may comprise a wireless part and wired part and the pQoS may at least relate to the wireless part. For example, the wireless part of a communication link may be a main contributor for communication delays/latencies and at least some embodiments may focus on the main contributor.

The pQoS may comprise at least one of a latency and a data rate. The speed limit determination may consider data rate and latency on a communication link and therefore determine a reliable impact of the communication on the reaction time of the vehicle.

For example, the obtaining of the information related to the environment may comprise determining the information related to the environment based on sensor data of the tele-operated vehicle, the obtaining of the information related to the environment may comprise determining the information related to the environment based on sensor data shared among vehicles in the environment of the tele-operated vehicle, and/or the obtaining of the information related to the environment may comprise receiving the information related to the environment from a communication network. Embodiments may consider information on the environment of the vehicle, which may consume capacity of the communication link to the vehicle or other information on the same environment, which may be received from other sources, e.g. one or more other vehicles, traffic infrastructure, or other network components.

The determining of the speed limit may comprise determining a first lower speed limit for a first lower pQoS and the determining of the speed limit may comprise determining a second higher speed limit for a second higher pQoS in some embodiments. Embodiments may adapt the speed limit to the pQoS in a way that the better the pQoS the higher the speed limit.

The determining of the speed limit may comprise determining a first lower speed limit for a first environment with first higher traffic dynamics and the determining of the speed limit may comprise determining a second higher speed limit for a second environment with second lower traffic dynamics in embodiments. Embodiments may adapt the speed limit to traffic dynamics in a way that the higher the traffic dynamics the lower the speed limit.

In some embodiments the obtaining of the information related to the environment comprises receiving the information related to the environment from traffic infrastructure in the environment of the tele-operated vehicle. Information from other entities may be considered for the speed limit.

The determining of the speed limit may be further based on a probability of an occurrence of an event triggering a time-critical reaction of the tele-operated vehicle. The speed limit may hence consider traffic/environmental situation implications on a need for time-critical maneuvers of the vehicle, e.g. a probability of emergency brake maneuvers.

The probability of the occurrence of the event triggering the time-critical reaction may be related to the environment of the tele-operated vehicle. The environmental situation and properties, e.g. time of day, category of environment (highway, or residential), etc. may be considered for determining the speed limit in embodiments.

For example, the obtaining of the information related to the pQoS of the communication link between the tele-operated vehicle and the tele-operator of the vehicle may comprise receiving the information related to the pQoS from a communication system. Embodiments may exploit information provided by involved communications systems, e.g. mobile communication systems.

Embodiments further provide a computer program having a program code for performing one or more of the described methods, when the computer program is executed on a computer, processor, or programmable hardware component. A further embodiment is a computer readable storage medium storing instructions which, when executed by a computer, processor, or programmable hardware component, cause the computer to implement one of the methods described herein.

Another embodiment is an apparatus for determining a speed limit for a tele-operated vehicle. The apparatus comprises one or more interfaces configured to communicate in a communication network; and a control module configured to control the one or more interfaces, wherein the control module is further configured to perform one of the methods described herein. Further embodiments are a vehicle comprising the apparatus and a network component comprising the apparatus.

It will be further understood that the terms "comprises", "comprising", "includes" 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.

<FIG> illustrates a block diagram of an embodiment of a method <NUM> for determining a speed limit for a tele-operated vehicle. The method <NUM> comprises obtaining <NUM> information related to an environment of the tele-operated vehicle. The method <NUM> further comprises obtaining <NUM> information related to a pQoS of a communication link between the tele-operated vehicle and a tele-operator of the vehicle. The method <NUM> further comprises determining <NUM> the speed limit based on the information related to the environment of the tele-operated vehicle and the information related to the pQoS.

In embodiments the speed limit is the maximum speed that the vehicle can drive while being tele-operated. The method <NUM> may further comprise applying the speed limit to the vehicle while being tele-operated. Tele-operating the vehicle is to be understood as a remote operation of the vehicle. For example, a remote operator or tele-operator located at a CC takes over control of the vehicle by means of control commands (e.g. acceleration/deceleration commands, steering commands, etc.). Tele-operated driving (ToD) might become a key technology in order to solve issues with L4/L5 (L4: highly automatic, L5: fully automatic) driven vehicles, such as interpretation issues or deadlocks (situations, which cannot be resolved by autonomous or automatic control mechanisms only).

These issues occur when automatic driven vehicles (AV) are not able to interpret and to solve a situation due to not clear traffic conditions, e.g. an accident or a construction site. These vehicles may need external instruction from someone else to solve the situation, which can be the so-called control center (CC). A ToD vehicle will be driven remotely by CC, an operator therein, respectively.

The ToD performance is related to the communication link performance. The communication link may comprise a wireless part and wired part and the pQoS may relate at least to the wireless part in some embodiments. For example, the communication link comprises the air interface (Uu link in 3GPP (<NUM>rd Generation Partnership Project), wireless part of the communication link) between the vehicle and the base station (access node) and then the connection through the operator backbone (core network, wired part). Depending on the quality of the link, the control of the vehicle will be adapted in embodiments: the vehicle will be controlled directly (joystick-like) or indirectly (waypoints, or environmental model editions). The environment may be characterized by the type of road, e.g. highway, country road, city road, residential area road, number of lanes, traffic density, traffic dynamics, etc. Moreover, the time of day, the day of week, the weather, current traffic condition/density; and other factors may be comprised in the information related to the environment of the tele-operated vehicle.

Embodiments may provide a remote-control maximal speed definition based on pQoS and vehicle environment. Two main factors are crucial for the determination of the driving speed of the AV in a ToD session. The first is predictive quality of service (pQoS), e.g. the future data rate and even more important latency. The pQoS may comprise at least one of a latency and a data rate. In embodiments QoS or pQoS may comprise one or more elements of the group of, latency, data rate, error rate/reliability, packet error rate, packet inter-reception time, etc. Such QoS may depend on different factors, e.g. the radio access technology (RAT), pathloss, environment, interference situation, load, processing delay, etc..

Indeed, these QoS indicators negatively affect the control of the vehicle and as a consequence the speed of the AV needs to be adapted. The second influence factor is the AV environment and the required reaction time, which is needed for the remote controlling from the CC to the AV. a remotely driven AV located in a downtown area and surrounded by moving humans does not allow so much latency as a vehicle driving on an abandoned street.

<FIG> illustrates a block diagram of an embodiment of an apparatus <NUM> for determining a speed limit for a tele-operated vehicle <NUM>, an embodiment of a vehicle <NUM>, and an embodiment of a network component <NUM>. As shown in <FIG> the apparatus <NUM> for determining the speed limit for the tele-operated vehicle <NUM> comprises one or more interfaces <NUM> configured to communicate in a communication network. The apparatus <NUM> further comprises a control module <NUM>, which is configured to control the one or more interfaces <NUM>, and which is coupled to the one or more interfaces <NUM>. The control module <NUM> is further configured to perform one of the methods <NUM> described herein. As further shown in <FIG> in broken lines (as optional from the perspective of the apparatus <NUM>), an entity <NUM> comprising an embodiment of the apparatus <NUM> is another embodiment. Such entity <NUM> may be a vehicle or a network component (e.g. a server, a computer, a base station, hardware, CC, etc.).

The apparatuses <NUM> and the vehicle or network component <NUM> may communicate at least partly through a mobile communication system. The mobile communication system, may, for example, correspond to one of the Third Generation Partnership Project (3GPP)-standardized mobile communication networks, where the term mobile communication system is used synonymously to mobile communication network. The messages (input data, control information) may hence be communicated through multiple network nodes (e.g. internet, router, switches, etc.) and the mobile communication system, which generates the delay or latencies considered in embodiments. For example, the uplink direction refers to the direction from a vehicle to the command center and the downlink direction refers from the command center to the vehicle.

The mobile or wireless communication system may correspond to a mobile communication system of the 5th Generation (<NUM>, or New Radio) and may use mm-Wave technology. The mobile communication system may correspond to or comprise, for example, a Long-Term Evolution (LTE), an LTE-Advanced (LTE-A), High Speed Packet Access (HSPA), a Universal Mobile Telecommunication System (UMTS) or a UMTS Terrestrial Radio Access Network (UTRAN), an evolved-UTRAN (e-UTRAN), a Global System for Mobile communication (GSM) or Enhanced Data rates for GSM Evolution (EDGE) network, a GSM/EDGE Radio Access Network (GERAN), or mobile communication networks with different standards, for example, a Worldwide Inter-operability for Microwave Access (WIMAX) network IEEE <NUM> or Wireless Local Area Network (WLAN) IEEE <NUM>, generally an Orthogonal Frequency Division Multiple Access (OFDMA) network, a Time Division Multiple Access (TDMA) network, a Code Division Multiple Access (CDMA) network, a Wideband-CDMA (WCDMA) network, a Frequency Division Multiple Access (FDMA) network, a Spatial Division Multiple Access (SDMA) network, etc..

Service provision may be carried out by a network component, such as a base station transceiver, a relay station or a UE, e.g. coordinating service provision in a cluster or group of multiple UEs/vehicles. A base station transceiver can be operable or configured to communicate with one or more active mobile transceivers/vehicles and a base station transceiver can be located in or adjacent to a coverage area of another base station transceiver, e.g. a macro cell base station transceiver or small cell base station transceiver. Hence, embodiments may provide a mobile communication system comprising two or more mobile transceivers/vehicles <NUM> and one or more base station transceivers, wherein the base station transceivers may establish macro cells or small cells, as e.g. pico-, metro-, or femto cells. A mobile transceiver or UE may correspond to a smartphone, a cell phone, a laptop, a notebook, a personal computer, a Personal Digital Assistant (PDA), a Universal Serial Bus (USB) -stick, a car, a vehicle, a road participant, a traffic entity, traffic infrastructure etc. A mobile transceiver may also be referred to as User Equipment (UE) or mobile in line with the 3GPP terminology. A vehicle may correspond to any conceivable means for transportation, e.g. a car, a bike, a motorbike, a van, a truck, a bus, a ship, a boat, a plane, a train, a tram, etc..

A base station transceiver can be located in the fixed or stationary part of the network or system. A base station transceiver may be or correspond to a remote radio head, a transmission point, an access point, a macro cell, a small cell, a micro cell, a femto cell, a metro cell etc. A base station transceiver can be a wireless interface of a wired network, which enables transmission of radio signals to a UE or mobile transceiver. Such a radio signal may comply with radio signals as, for example, standardized by 3GPP or, generally, in line with one or more of the above listed systems. Thus, a base station transceiver may correspond to a NodeB, an eNodeB, a gNodeB, a Base Transceiver Station (BTS), an access point, a remote radio head, a relay station, a transmission point, etc., which may be further subdivided in a remote unit and a central unit.

A mobile transceiver or vehicle can be associated with a base station transceiver or cell. The term cell refers to a coverage area of radio services provided by a base station transceiver, e.g. a NodeB (NB), an eNodeB (eNB), a gNodeB, a remote radio head, a transmission point, etc. A base station transceiver may operate one or more cells on one or more frequency layers, in some embodiments a cell may correspond to a sector. For example, sectors can be achieved using sector antennas, which provide a characteristic for covering an angular section around a remote unit or base station transceiver. A base station transceiver may operate multiple sectorized antennas. In the following, a cell may represent an according base station transceiver generating the cell or, likewise, a base station transceiver may represent a cell the base station transceiver generates.

The apparatus <NUM> may be comprised in a server, a base station, a NodeB, a UE, a vehicle, a network component, a relay station, or any service coordinating network entity in embodiments. It is to be noted that the term network component may comprise multiple sub-components, such as a base station, a server, etc..

In embodiments the one or more interfaces <NUM> may correspond to any means for obtaining, receiving, transmitting or providing analog or digital signals or information, e.g. any connector, contact, pin, register, input port, output port, conductor, lane, etc. which allows providing or obtaining a signal or information. An interface may be wireless or wireline and it may be configured to communicate, i.e. transmit or receive signals, information with further internal or external components. The one or more interfaces <NUM> may comprise further components to enable according communication in the (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 circuitry, one or more converters, one or more mixers, accordingly adapted radio frequency components, etc. The one or more interfaces <NUM> may be coupled to one or more antennas, which may correspond to any transmit and/or receive antennas, such as horn antennas, dipole antennas, patch antennas, sector antennas etc. In some examples the one or more interfaces <NUM> may serve the purpose of transmitting or receiving or both, transmitting and receiving, information, such as information, input data, control information, further information messages, etc..

As shown in <FIG> the respective one or more interfaces <NUM> are coupled to the respective control module <NUM> at the apparatus <NUM>. In embodiments the control module <NUM> may be implemented using one or more processing units, one or more processing devices, any means for processing, such as a processor, a computer or a programmable hardware component being operable with accordingly adapted software. In other words, the described functions of the control module <NUM> may as well be implemented in software, which is then executed on one or more programmable hardware components. Such hardware components may comprise a general-purpose processor, a Digital Signal Processor (DSP), a micro-controller, etc..

In embodiments, communication, i.e. transmission, reception or both, may take place among mobile transceivers/vehicles <NUM> directly, e.g. forwarding input data or control information to/from a control center. Such communication may make use of a mobile communication system. Such communication may be carried out directly, e.g. by means of Device-to-Device (D2D) communication. Such communication may be carried out using the specifications of a mobile communication system. An example of D2D is direct communication between vehicles, also referred to as Vehicle-to-Vehicle communication (V2V), car-to-car, Dedicated Short Range Communication (DSRC), respectively. Technologies enabling such D2D-communication include <NUM>. 11p, 3GPP systems (<NUM>, <NUM>, NR and beyond), etc..

In embodiments, the one or more interfaces <NUM> can be configured to wirelessly communicate in the mobile communication system, e.g. in an embodiment in which the apparatus <NUM> is implemented in vehicle <NUM> and the method <NUM> is carried out at the vehicle <NUM>. In order to do so radio resources are used, e.g. frequency, time, code, and/or spatial resources, which may be used for wireless communication with a base station transceiver as well as for direct communication. The assignment of the radio resources may be controlled by a base station transceiver, i.e. the determination which resources are used for D2D and which are not. Here and in the following radio resources of the respective components may correspond to any radio resources conceivable on radio carriers and they may use the same or different granularities on the respective carriers. The radio resources may correspond to a Resource Block (RB as in LTE/LTE-A/LTE-unlicensed (LTE-U)), one or more carriers, sub-carriers, one or more radio frames, radio sub-frames, radio slots, one or more code sequences potentially with a respective spreading factor, one or more spatial resources, such as spatial sub-channels, spatial precoding vectors, any combination thereof, etc. For example, in direct Cellular Vehicle-to-Anything (C-V2X), where V2X includes at least V2V, V2-Infrastructure (V2I), etc., transmission according to 3GPP Release <NUM> onward can be managed by infrastructure (so-called mode <NUM>) or run in a UE.

In order to determine a speed limit in an embodiment for a tele-operated vehicle <NUM>, it may be critical to predict the QoS in the communication network.

<FIG> illustrates a traffic scenario in an embodiment and a block diagram of a method <NUM> in a tele-operated vehicle <NUM>. In the traffic scenario illustrated on the left of <FIG> an automatic vehicle <NUM> is in an exceptional traffic scenario. A truck <NUM> is in the way of the vehicle <NUM> and the vehicle <NUM> needs to use the lane of the oncoming traffic to pass the truck <NUM>. Since this situation cannot be resolved by means of the control mechanisms of the vehicle <NUM> itself, a communication link <NUM> to a base station <NUM> and on to a control center has been established. <FIG> further indicates a pedestrian <NUM>, which may cross the path of vehicle <NUM>. This situation makes clear that the vehicle needs to be able to stop within a certain short distance. The determining <NUM> of the speed limit is therefore further based on a probability of an occurrence of an event triggering a time-critical reaction (pedestrian in front of the vehicle) of the tele-operated vehicle <NUM>. A reaction time can be determined from the delay/latency of the communication link and the reaction time of the tele-operator. With a given maximum distance until stop of the vehicle <NUM>, the braking distance of the vehicle, and the delay/latency a speed limit can be calculated. The probability of the occurrence of the event triggering the time-critical reaction is related to the environment of the tele-operated vehicle <NUM> (e.g. the probability of a suddenly occurring pedestrian in front of the vehicle <NUM> is higher on a sunny Saturday afternoon in a residential area than it is in the middle of the night on an abandoned highway during a week day).

<FIG> also illustrates an embodiment of an apparatus <NUM> on the right, which is implemented at the vehicle <NUM> in this embodiment. The apparatus <NUM> comprises a communication unit <NUM>, which is an implementation of the above-described one or more interfaces <NUM>. The communication unit <NUM> may provide radio links to a CC, to an overlaying mobile communication system, and also to other vehicles. Therewith, sensor sharing can be used to exchange information on the environment with other vehicles or to communicate sensor data to the CC. There are multiple options on determining the environmental information in embodiments. For example, the obtaining <NUM> of the information related to the environment may comprise determining the information related to the environment based on sensor data of the tele-operated vehicle <NUM> itself (video, radar, lidar, etc.), the obtaining <NUM> of the information related to the environment may comprise determining the information related to the environment based on sensor data shared among vehicles in the environment of the tele-operated vehicle <NUM> (data from sensors of other vehicles), and/or the obtaining <NUM> of the information related to the environment may comprises receiving the information related to the environment from a communication network. For example, an environmental model may be formed by a server in the network, which provides such information to the apparatus <NUM>. Yet another option is that the obtaining <NUM> of the information related to the environment comprises receiving the information related to the environment from traffic infrastructure in the environment of the tele-operated vehicle. For example, traffic infrastructure (lights, signs, etc.) may generate information related to a traffic density, which can then be provided to the apparatus <NUM>.

As further illustrated a pQoS profile comprising at least information related to a predicted latency and data rate may also be obtained at the apparatus <NUM>. The obtaining <NUM> of the information related to the pQoS of the communication link between the tele-operated vehicle <NUM> and the tele-operator of the vehicle <NUM> may comprise receiving the information related to the pQoS from a communication system. the overlaying mobile communication system (e.g. <NUM>, LTE, ITS-G5 (Intelligent Transport System <NUM>th Generation)) may provide such information to the apparatus <NUM>. The apparatus <NUM> also comprises a control module <NUM>, e.g. a processor, which performs a prediction of the environment at the automatic vehicle <NUM>.

Embodiments may then determine the speed limit taking into account both factors pQoS and the environment. Compared to a simple but inefficient approach, which selects a fixed low speed, e.g. <NUM>/h, embodiments may allow a more adequate speed limit setting. For example, a risk assessment for surrounding objects may be carried out. A maximum speed considering the latency given by the communications system is then calculated. A maximum velocity (speed limit) may then be communicated for remote control, e.g. to a CC.

For example, if a braking distance of a vehicle corresponds to the distance travelled in <NUM> (rough approximation for exemplary purposes only), then a vehicle travelling at <NUM>/s needs <NUM> to stop. If the latency (round trip delay) in the network is <NUM>, then the vehicle travels <NUM> before an emergency brake command takes effect after an according situation has been sensed. The reaction distance of the vehicle is then <NUM>. Hence, if <NUM> is the required reaction distance in a current traffic scenario and the latency is <NUM>, then the speed limit is <NUM>/s. If in another environment the reaction distance is <NUM>, then the speed limit is <NUM>/s.

Embodiments may calculate a maximum speed of the AV <NUM> during the ToD by.

The quality of service indicator can be the data rate, and/or the latency. The method <NUM> may can run on the vehicle <NUM>, where the surrounding environment information comes from sensors and collective perception. Alternatively, the method <NUM> may run at the CC or any other network component, where the surrounding environment information comes from the sensors of the AV, infrastructure, or the communication network itself. The calculated maximal speed may then be exchanged between the AV and the CC. The determining <NUM> of the speed limit may comprise determining a first lower speed limit for a first lower pQoS and the determining <NUM> of the speed limit may comprise determining a second higher speed limit for a second higher pQoS. The determining <NUM> of the speed limit may comprise determining a first lower speed limit for a first environment with first higher traffic dynamics and the determining <NUM> of the speed limit may comprise determining a second higher speed limit for a second environment with second lower traffic dynamics.

As already mentioned, in embodiments the respective methods may be implemented as computer programs or codes, which can be executed on a respective hardware. Hence, another embodiment is 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. A further embodiment is a computer readable storage medium storing instructions which, when executed by a computer, processor, or programmable hardware component, cause the computer to implement one of the methods described herein.

The description and drawings merely illustrate the principles of the invention. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described or shown herein, embody the principles of the invention and are included within its scope. Furthermore, all examples recited herein are principally intended expressly to be only for pedagogical purposes to aid the reader in understanding the principles of the invention and the concepts contributed by the inventor(s) to furthering the art and are to be construed as being without limitation to such specifically recited examples and conditions. Moreover, all statements herein reciting principles, aspects, and embodiments of the invention, as well as specific examples thereof, are intended to encompass equivalents thereof.

Furthermore, the following claims are hereby incorporated into the detailed description, where each claim may stand on its own as a separate embodiment. While each claim may stand on its own as a separate embodiment, it is to be noted that - although a dependent claim may refer in the claims to a specific combination with one or more other claims - other embodiments may also include a combination 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. Furthermore, it is intended to include also features of a claim to any other independent claim even if this claim is not directly made dependent to the independent claim.

Claim 1:
A method (<NUM>) for determining a speed limit for a tele-operated vehicle (<NUM>), the method (<NUM>) comprising
obtaining (<NUM>) information related to an environment of the tele-operated vehicle (<NUM>);
obtaining (<NUM>) information related to a predictive quality of service, pQoS, of a communication link (<NUM>) between the tele-operated vehicle (<NUM>) and a tele-operator of the vehicle (<NUM>); and
determining (<NUM>) the speed limit based on the information related to the environment of the tele-operated vehicle (<NUM>) and the information related to the pQoS,
wherein the determining (<NUM>) of the speed limit comprises determining a first lower speed limit for a first lower pQoS and wherein the determining (<NUM>) of the speed limit comprises determining a second higher speed limit for a second higher pQoS, wherein the determining (<NUM>) of the speed limit is further based on a probability of an occurrence of an event triggering a time-critical reaction of the tele-operated vehicle (<NUM>).