Inter-vehicle communication resource scheduling method and device, equipment, vehicle and storage medium

Abstract

This invention relates to the field of vehicle communication technology, specifically to a method, apparatus, device, vehicle, and storage medium for scheduling communication resources between vehicles. The method includes: constructing a neighbor state table for the current vehicle; generating a communication graph and a conflict graph between the current vehicle and its neighboring vehicles based on the neighbor state table; determining the cluster head capability weight of the current vehicle based on the communication graph; and determining the cluster head capability weights of its neighboring vehicles; if the cluster head capability weight of the current vehicle is greater than the cluster head capability weights of all its neighboring vehicles, determining the current vehicle as the cluster head; and generating a resource scheduling table between the current vehicle and its neighboring vehicles based on the conflict graph; wherein the resource scheduling table is used to allocate communication resources to each neighboring vehicle. This invention can achieve optimality and adaptability in cluster head election to adapt to network changes caused by vehicle movement, thereby effectively improving the reliability of V2V communication.

Description

Technical Field

[0001] This invention relates to the field of vehicle communication technology, specifically to a method, apparatus, equipment, vehicle, and storage medium for scheduling communication resources between vehicles. Background Technology

[0002] With the development of vehicle-to-everything (V2X) technology, the demand for high-density communication between vehicles (V2V) and other vehicles is increasing. In V2V communication scenarios, vehicles need to frequently exchange safety information (such as location, speed, and acceleration), control commands, and broadband services (such as forward video transmission and sensor data sharing).

[0003] In existing technologies, an interference topology map is constructed based on interference information, and graph coloring theory is used to cluster all vehicle users based on the interference topology map. Vehicle users that do not interfere with each other are grouped into the same cluster, and a channel is allocated to each vehicle user.

[0004] However, in the above process, the clustering logic mainly relies on graph coloring theory for static partitioning, which leads to unreasonable cluster head election and difficulty in adapting to the high dynamic characteristics of V2V communication networks, thus resulting in a decrease in the reliability of V2V communication. Summary of the Invention

[0005] One objective of this invention is to provide a method for scheduling inter-vehicle communication resources to solve the problem of decreased reliability of V2V communication caused by static clustering using dependency graph coloring theory; a second objective is to provide an inter-vehicle communication resource scheduling device; a third objective is to provide an electronic device; a fourth objective is to provide a vehicle; a fifth objective is to provide a computer-readable storage medium; and a sixth objective is to provide a computer program product.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for scheduling communication resources between vehicles, comprising:

[0008] Construct a neighbor status table for the current vehicle; wherein, the neighbor status table includes the relative operating status between at least one neighbor vehicle of the current vehicle and the current vehicle; the neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the beacon is higher than a preset minimum communication threshold;

[0009] Based on the neighbor status table, a communication graph and a conflict graph are generated between the current vehicle and each of the neighboring vehicles; wherein, the communication graph includes the communication links between the current vehicle and each of the neighboring vehicles; and the conflict graph represents the communication conflict situation between each of the communication links.

[0010] Based on the communication graph, the cluster head capability weight of the current vehicle is determined; and the cluster head capability weight of the neighboring vehicles is determined; wherein, the cluster head capability weight characterizes the vehicle's computing power and the connectivity and stability of the communication connection;

[0011] If it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each of the neighboring vehicles, the current vehicle is determined as the cluster head; and a resource scheduling table between the current vehicle and each of the neighboring vehicles is generated according to the conflict graph; wherein, the resource scheduling table is used to allocate communication resources to each of the neighboring vehicles.

[0012] Further, determining the cluster head capability weight of the current vehicle based on the communication graph, and determining the cluster head capability weight of the neighboring vehicles, includes:

[0013] The stability weight of the current vehicle is determined based on the relative speed between the current vehicle and each of its neighboring vehicles; wherein the stability weight characterizes the communication connection stability of the vehicle.

[0014] Based on the degree information of the current vehicle, the connectivity weight of the current vehicle is determined; wherein, the degree information represents the total number of neighboring vehicles connected to the current vehicle in the communication graph; and the connectivity weight represents the vehicle's communication coverage and management capabilities.

[0015] Based on the current vehicle's computing power and energy information, the resource weight of the current vehicle is determined; wherein, the resource weight represents the vehicle's ability to schedule and execute computing resources.

[0016] The cluster head capability weight of the current vehicle is determined based on the stability weight, the connectivity weight, and the resource weight.

[0017] Furthermore, generating a resource scheduling table between the current vehicle and each of its neighboring vehicles based on the conflict graph includes:

[0018] Based on the communication graph and the conflict graph, the current vehicle and each of the neighboring vehicles are divided to obtain at least one maximum independent set; wherein the communication links between the vehicles in the maximum independent set do not interfere with each other in physical space.

[0019] Based on the constraints of the at least one maximum independent set and the communication demand information between the current vehicle and each of the neighboring vehicles, a resource scheduling table is generated between the current vehicle and each of the neighboring vehicles; wherein, the constraints include not allocating resources in the same time slot and resources in the same frequency to conflicting communication links.

[0020] Furthermore, the resource scheduling table includes a broadband resource allocation strategy, which includes the frequency and time slot ultimately allocated to each neighboring vehicle processing broadband services.

[0021] The step of generating a resource scheduling table between the current vehicle and each of the neighboring vehicles based on the constraints of the at least one maximum independent set and the communication requirement information between the current vehicle and each of the neighboring vehicles includes:

[0022] Based on the broadband service requirements in the communication demand information and the constraints of the at least one maximum independent set, an initial broadband resource allocation strategy is determined; wherein, the initial broadband resource allocation strategy includes the frequency and time slot initially allocated to each neighboring vehicle processing broadband services.

[0023] Based on the initial broadband resource allocation strategy and the feasibility risk function, the feasibility risk penalty corresponding to the initial broadband resource allocation strategy is determined; wherein, the feasibility risk penalty is the feasibility risk penalty caused to the remaining spectrum resources after the initial bandwidth block allocation strategy is executed;

[0024] Based on the aforementioned feasibility risk penalty, the initial broadband resource allocation strategy is adjusted to obtain the broadband resource allocation strategy in the resource scheduling table.

[0025] Furthermore, the resource scheduling table includes a narrowband service resource allocation strategy; the narrowband service resource allocation strategy includes the frequency hopping sequence and non-uniform frequency hopping probability distribution ultimately allocated to each neighboring vehicle processing narrowband services.

[0026] The step of generating a resource scheduling table between the current vehicle and each of the neighboring vehicles based on the constraints of the at least one maximum independent set and the communication requirement information between the current vehicle and each of the neighboring vehicles includes:

[0027] Based on the narrowband service requirements in the communication demand information and the constraints of the at least one maximum independent set, the frequency hopping sequence in the narrowband service resource allocation strategy in the resource scheduling table is determined; wherein, the frequency hopping sequence includes multiple frequency points selected from the current communication frequency band for communication;

[0028] The frequency hopping sequence is processed to obtain the net gain score for each frequency hopping point in the frequency hopping sequence; wherein, the net gain score characterizes the communication channel quality of the frequency hopping point;

[0029] The net benefit score of each frequency hopping point in the frequency hopping sequence is mapped to obtain the non-uniform frequency hopping probability distribution in the narrowband service resource allocation strategy in the resource scheduling table.

[0030] Further, the processing of the frequency hopping sequence to obtain the net gain score for each frequency hopping point in the frequency hopping sequence includes:

[0031] Collect the signal power strength of each discrete frequency point in the current communication frequency band of the vehicle;

[0032] A frequency point marking table is generated based on the signal power intensity of each discrete frequency point; wherein, the frequency point marking table includes discrete frequency points that have severe external interference and are not suitable for use;

[0033] Based on the frequency point marking table, determine the utility score for each discrete frequency point in the current communication frequency band;

[0034] The net benefit score of the frequency hopping frequency point is determined based on the utility score and overlap penalty of the discrete frequency point corresponding to the frequency hopping frequency point; wherein, the overlap penalty represents the total interference intensity caused by the external interference source and other services within the cluster when the discrete frequency points overlap.

[0035] Furthermore, constructing the neighbor status table for the current vehicle includes:

[0036] Broadcast the current vehicle's discovery beacon; and receive the discovery beacon sent by the neighboring vehicle; wherein the discovery beacon includes vehicle identity information, current acceleration, physical layer timestamp, and phase measurement reference information;

[0037] The phase difference between the current vehicle and the neighboring vehicle is determined based on the phase reference information in the discovery beacon sent by the current vehicle and the phase reference information in the discovery beacon sent by the neighboring vehicle.

[0038] The physical distance between the current vehicle and the neighboring vehicle is determined based on the phase difference between the current vehicle and the neighboring vehicle, the physical layer timestamp in the discovery beacon of the current vehicle and the physical layer timestamp in the discovery beacon sent by the neighboring vehicle.

[0039] The relative speed between the current vehicle and the neighboring vehicles is determined based on the physical distance between the current vehicle and the neighboring vehicles; wherein, the vehicle identity information, the physical distance between the current vehicle and each of the neighboring vehicles, and the relative speed constitute the relative operating state in the neighbor status table.

[0040] Furthermore, generating a communication graph and a conflict graph between the current vehicle and each of its neighboring vehicles based on the neighbor status table includes:

[0041] Based on the neighbor status table, a local perception topology is generated between the current vehicle and each of the neighboring vehicles; wherein, the local perception topology represents the topological connection relationship between each vehicle;

[0042] Based on the local perception topology, a communication graph and a conflict graph are generated between the current vehicle and each of its neighboring vehicles.

[0043] Furthermore, generating a communication graph and a conflict graph between the current vehicle and each of its neighboring vehicles based on the local perception topology includes:

[0044] Based on the local perception topology, a communication graph is generated between the current vehicle and each of the neighboring vehicles; wherein the communication graph includes a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link;

[0045] Based on the communication graph between the current vehicle and each of the neighboring vehicles, a conflict graph between the current vehicle and each of the neighboring vehicles is generated; wherein, the conflict graph includes vertices representing each of the communication links and at least one conflict edge; the conflict edge is determined based on two vertices meeting a communication conflict condition; the communication conflict condition includes that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver of the second vertex is less than a preset minimum reception threshold under communication interference from the transmitter of the first vertex of the two vertices.

[0046] Furthermore, after generating a resource scheduling table between the current vehicle and each of the neighboring vehicles based on the conflict graph, the method further includes:

[0047] If the monitored operating status between the current vehicle and each of the neighboring vehicles meets preset conditions, the cluster head neighbor vehicle with the highest cluster head capability weight among the neighboring vehicles is determined as the new cluster head; wherein, the preset conditions include any one of the following: the average relative speed between the current vehicle and each of the neighboring vehicles is greater than a preset threshold, the stability weight of the vehicle is continuously lower than a preset threshold value within a preset time period, the computing power and energy information of the current vehicle cannot meet the conditions for maintaining the operation of the interference coordination algorithm, and the number of neighboring vehicles that are not within the maximum direct communication range of the vehicle is greater than a preset number; the stability weight characterizes the communication connection stability of the vehicle;

[0048] A scheduling context is generated based on the resource scheduling table; and the scheduling context is sent to the new cluster head; wherein, the scheduling context includes the resource scheduling table and the current scene interference label table; the scheduling context is used to generate a new resource scheduling table;

[0049] The system receives the new resource scheduling table sent by the new cluster head and communicates according to the new resource scheduling table.

[0050] Furthermore, the method also includes:

[0051] If it is determined that the cluster head capability weight of the vehicle is less than the cluster head capability weight of any of the neighboring vehicles, the neighboring vehicle with the largest cluster head capability weight among all the neighboring vehicles is determined as the cluster head;

[0052] Generate an access request for the vehicle; and send the access request to the cluster head; wherein the access request is used to obtain a resource scheduling table;

[0053] The cluster head sends a resource scheduling table; and the cluster head sends a resource scheduling table for communication.

[0054] Based on the aforementioned technical means, a corresponding communication graph and conflict graph are constructed by using a neighbor state table between the current vehicle and its neighboring vehicles. According to the communication graph, the cluster head capability weight of each vehicle in the cluster structure is determined. By comparing the cluster head capability weights, if the current vehicle is determined to be the cluster head, it generates a resource scheduling table among its neighboring vehicles for allocating communication resources. Furthermore, through graph theory modeling and cluster head capability weight calculation, the optimality and adaptability of cluster head election are achieved. The cluster head is responsible for resource scheduling, and cluster members communicate according to the resource schedule to adapt to network changes caused by vehicle movement, thereby effectively improving the reliability of V2V communication.

[0055] A vehicle-to-vehicle communication resource scheduling device, comprising:

[0056] A construction module is used to construct a neighbor status table for the current vehicle; wherein, the neighbor status table includes the relative operating status between at least one neighbor vehicle of the current vehicle and the current vehicle; the neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the discovered beacon is higher than a preset minimum communication threshold;

[0057] The first generation module is used to generate a communication graph and a conflict graph between the current vehicle and each of the neighboring vehicles based on the neighbor status table; wherein, the communication graph includes communication links between the current vehicle and each of the neighboring vehicles; and the conflict graph represents the communication conflict situation between each of the communication links.

[0058] The determination module is used to determine the cluster head capability weight of the current vehicle based on the communication graph; and to determine the cluster head capability weight of the neighboring vehicles; wherein the cluster head capability weight characterizes the vehicle's computing power and the connectivity and stability of the communication connection;

[0059] The second generation module is used to determine the current vehicle as a cluster head if it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each of the neighboring vehicles; and to generate a resource scheduling table between the current vehicle and each of the neighboring vehicles according to the conflict graph; wherein the resource scheduling table is used to allocate communication resources to each of the neighboring vehicles.

[0060] Furthermore, the determining module is specifically configured to: determine the stability weight of the current vehicle based on the relative speed between the current vehicle and each of the neighboring vehicles; wherein the stability weight characterizes the communication connection stability of the vehicle; determine the connectivity weight of the current vehicle based on the degree information of the current vehicle; wherein the degree information characterizes the total number of neighboring vehicles connected to the current vehicle in the communication graph; the connectivity weight characterizes the communication coverage and management capability of the vehicle; determine the resource weight of the current vehicle based on the computing power and energy information of the current vehicle; wherein the resource weight characterizes the scheduling and execution capability of the vehicle's computing resources; and determine the cluster head capability weight of the current vehicle based on the stability weight, the connectivity weight, and the resource weight.

[0061] Furthermore, the second generation module is specifically used for: dividing the current vehicle and each of the neighboring vehicles according to the communication graph and the conflict graph to obtain at least one maximum independent set; wherein the communication links between the vehicles in the maximum independent set do not interfere with each other in physical space; generating a resource scheduling table between the current vehicle and each of the neighboring vehicles according to the constraints of the at least one maximum independent set and the communication demand information between the current vehicle and each of the neighboring vehicles; wherein the constraints include not allocating resources in the same time slot and resources in the same frequency to communication links that conflict.

[0062] Furthermore, the resource scheduling table includes a broadband resource allocation strategy, which includes the frequency and time slots ultimately allocated to each neighboring vehicle processing broadband services. The second generation module is further specifically configured to: determine an initial broadband resource allocation strategy based on the broadband service requirements in the communication demand information and the constraints of the at least one maximum independent set; wherein the initial broadband resource allocation strategy includes the frequency and time slots initially allocated to each neighboring vehicle processing broadband services; determine a feasibility risk penalty corresponding to the initial broadband resource allocation strategy based on the initial broadband resource allocation strategy and a feasibility risk function; wherein the feasibility risk penalty is the feasibility risk penalty incurred on the remaining spectrum resources after executing the initial bandwidth block allocation strategy; and adjust the initial broadband resource allocation strategy based on the feasibility risk penalty to obtain the broadband resource allocation strategy in the resource scheduling table.

[0063] Furthermore, the resource scheduling table includes a narrowband service resource allocation strategy; the narrowband service resource allocation strategy includes a frequency hopping sequence and a non-uniform frequency hopping probability distribution ultimately allocated to each neighboring vehicle processing narrowband services; the second generation module is further specifically used for: determining the frequency hopping sequence in the narrowband service resource allocation strategy in the resource scheduling table based on the narrowband service requirements in the communication requirement information and the constraints of the at least one maximum independent set; wherein the frequency hopping sequence includes multiple frequency hopping points selected from the current communication frequency band for communication; processing the frequency hopping sequence to obtain a net benefit score for each frequency hopping point in the frequency hopping sequence; wherein the net benefit score characterizes the communication channel quality of the frequency hopping point; and mapping the net benefit score of each frequency hopping point in the frequency hopping sequence to obtain the non-uniform frequency hopping probability distribution in the narrowband service resource allocation strategy in the resource scheduling table.

[0064] Furthermore, the second generation module is specifically used for: collecting the signal power intensity of each discrete frequency point in the current communication frequency band of the vehicle; generating a frequency point marking table based on the signal power intensity of each discrete frequency point; wherein the frequency point marking table includes discrete frequency points that have severe external interference and are unsuitable for use; determining the utility score of each discrete frequency point in the current communication frequency band based on the frequency point marking table; determining the net benefit score of the frequency hopping frequency point based on the utility score of the discrete frequency point corresponding to the frequency hopping frequency point and the overlap penalty; wherein the overlap penalty characterizes the total interference intensity caused by the external interference source and other services within the cluster when the discrete frequency points overlap.

[0065] Furthermore, the construction module is specifically used for: broadcasting the discovery beacon of the current vehicle; and receiving the discovery beacon sent by the neighboring vehicle; wherein the discovery beacon includes vehicle identity information, current acceleration, physical layer timestamp, and phase measurement reference information; determining the phase difference between the current vehicle and the neighboring vehicle based on the phase reference information in the discovery beacon sent by the current vehicle and the phase reference information in the discovery beacon sent by the neighboring vehicle; determining the physical distance between the current vehicle and the neighboring vehicle based on the phase difference between the current vehicle and the neighboring vehicle, the physical layer timestamp in the discovery beacon of the current vehicle, and the physical layer timestamp in the discovery beacon sent by the neighboring vehicle; and determining the relative speed between the current vehicle and the neighboring vehicle based on the physical distance between the current vehicle and the neighboring vehicle; wherein the vehicle identity information, the physical distance between the current vehicle and each of the neighboring vehicles, and the relative speed constitute the relative operating state in the neighboring state table.

[0066] Furthermore, the first generation module is specifically used to: generate a local perception topology between the current vehicle and each of the neighboring vehicles based on the neighbor status table; wherein the local perception topology represents the topological connection relationship between each vehicle; and generate a communication graph and a conflict graph between the current vehicle and each of the neighboring vehicles based on the local perception topology.

[0067] Furthermore, the first generation module is specifically configured to: generate a communication graph between the current vehicle and each of the neighboring vehicles based on the local sensing topology; wherein the communication graph includes a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link; and generate a conflict graph between the current vehicle and each of the neighboring vehicles based on the communication graph; wherein the conflict graph includes a vertex representing each of the communication links and at least one conflict edge; the conflict edge is determined based on two vertices meeting a communication conflict condition; the communication conflict condition includes that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver of the second vertex is less than a preset minimum reception threshold under communication interference from the transmitter of the first vertex of the two vertices.

[0068] Furthermore, in the second generation module, after generating a resource scheduling table between the current vehicle and each of the neighboring vehicles based on the conflict graph, the device is further configured to: if the monitoring of the operating status between the current vehicle and each of the neighboring vehicles meets preset conditions, determine the cluster head neighboring vehicle with the largest cluster head capability weight among the neighboring vehicles as the new cluster head; wherein, the preset conditions include any one of the following: the average relative speed between the current vehicle and each of the neighboring vehicles is greater than a preset threshold, the stability weight of the vehicle is continuously lower than a preset threshold value within a preset time period, the computing power and energy information of the current vehicle cannot meet the conditions for maintaining the operation of the interference coordination algorithm, and the number of vehicles among the neighboring vehicles that are not within the maximum direct communication range of the vehicle is greater than a preset number; the stability weight characterizes the communication connection stability of the vehicle; generate a scheduling context based on the resource scheduling table; and send the scheduling context to the new cluster head; wherein, the scheduling context includes the resource scheduling table and the current scene interference label table; the scheduling context is used to generate a new resource scheduling table; receive the new resource scheduling table sent by the new cluster head, and communicate according to the new resource scheduling table.

[0069] Furthermore, the device is also configured to: if it is determined that the cluster head capability weight of the vehicle is less than the cluster head capability weight of any of the neighboring vehicles, determine the neighboring vehicle with the largest cluster head capability weight among the neighboring vehicles as the cluster head; generate an access request for the vehicle; and send the access request to the cluster head; wherein the access request is used to obtain a resource scheduling table; receive the resource scheduling table sent by the cluster head; and perform communication according to the resource scheduling table sent by the cluster head.

[0070] An electronic device includes: a memory and a processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the method described above.

[0071] A vehicle includes a vehicle body and electronic equipment as described above disposed in the vehicle body.

[0072] A computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the method described above.

[0073] A computer program product comprising a computer program that, when executed by a processor, implements the above-described method.

[0074] The beneficial effects of this invention are:

[0075] (1) This invention achieves the optimality and adaptability of cluster head election by using graph theory modeling and cluster head capability weight calculation. The cluster head is responsible for resource scheduling, and the other vehicles communicate according to resource scheduling to adapt to network changes caused by vehicle movement, thereby effectively improving the reliability of V2V communication.

[0076] (2) This invention solves the problem of ambiguous interference boundaries by using high-precision short-range communication ranging technology, and provides a reliable physical topology basis for dynamic clustering and resource scheduling;

[0077] (3) The present invention further ensures the service continuity during cluster head switching through dynamic maintenance and smooth switching mechanism, so as to adapt to the dynamic requirements of high-density V2V communication scenarios. Attached Figure Description

[0078] Figure 1 An application scenario diagram of a crossroads provided by the present invention;

[0079] Figure 2 This is a flowchart illustrating a method for scheduling communication resources between vehicles according to an embodiment of the present invention.

[0080] Figure 3 This is a flowchart illustrating another method for scheduling inter-vehicle communication resources according to an embodiment of the present invention.

[0081] Figure 4 This is a schematic diagram of vehicle communication before and after intra-cluster partitioning provided in an embodiment of the present invention;

[0082] Figure 5 This is an example diagram of a communication diagram and a conflict diagram provided in an embodiment of the present invention;

[0083] Figure 6 This is a flowchart of an interference coordination algorithm provided in an embodiment of the present invention;

[0084] Figure 7 The overall flowchart of an inter-vehicle equipment interference coordination method based on high-precision short-range communication ranging and dynamic clustering is provided in an embodiment of the present invention.

[0085] Figure 8 This is a schematic diagram of the structure of a vehicle-to-vehicle communication resource scheduling device according to an embodiment of the present invention;

[0086] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0087] The embodiments of the present invention will be described below with reference to the accompanying drawings and preferred embodiments. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be understood that the preferred embodiments are only for illustrating the present invention and not for limiting the scope of protection of the present invention.

[0088] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. Therefore, the drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0089] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use, processing, transmission, provision, disclosure, and application of the relevant data all comply with relevant laws, regulations, and standards, necessary confidentiality measures have been taken, they do not violate public order and good morals, and corresponding operation portals are provided for users to choose to authorize or refuse.

[0090] Furthermore, the technical solution involved in this application, which involves big data analysis of user information (including but not limited to personal biometrics, identity data, consumption data, asset data, electronic terminal operation data, etc.) and the use of artificial intelligence technology for automated decision-making, and makes decisions that have a significant impact on user rights based on the results of automated decision-making, provides users with corresponding operation entry points for users to choose to agree to or reject the results of automated decision-making; if the user chooses to reject, the process will proceed to the expert decision-making process.

[0091] This application can be applied to, but is not limited to, the following typical vehicle-to-everything (V2X) scenarios: autonomous driving platooning on highways, large parking lots or underground garages, complex urban intersections, and congested road sections. For example, Figure 1 An application scenario diagram of a crossroads provided by the present invention, such as... Figure 1As shown, this scenario is located at a standard intersection in the core urban area during morning and evening rush hours. A large number of vehicles are queuing for traffic lights in all four directions, with intervals of approximately 1-3 meters between vehicles, forming a typical high-density node distribution. This includes stationary waiting vehicles, slowly creeping queues, and vehicles crossing the intersection. This area crossing the intersection not only has vehicle-to-vehicle (V2V) communication needs but also faces numerous external interference sources and interfering communication links, including roadside units (RSUs), Wi-Fi hotspots from pedestrians, and Wi-Fi signals from surrounding shops. All these devices compete for limited spectrum resources.

[0092] In the above scenario, an interference topology map can be constructed based on interference information. Then, graph coloring theory is used to cluster all vehicle users according to this map, with non-interfering vehicle users grouped into the same cluster, and a channel allocated to each user. However, the clustering logic relies primarily on graph coloring theory for static partitioning, leading to unreasonable cluster head election and difficulty in adapting to the highly dynamic characteristics of V2V communication networks, thus resulting in decreased V2V communication reliability.

[0093] The inter-vehicle communication resource scheduling method provided by this invention achieves optimality and adaptability in cluster head election through graph theory modeling and cluster head capability weight calculation, so as to adapt to network changes brought about by vehicle movement, thereby effectively improving the reliability of V2V communication.

[0094] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0095] Figure 2 This is a flowchart illustrating a method for scheduling communication resources between vehicles according to an embodiment of the present invention, as shown below. Figure 2 As shown, the method includes:

[0096] 201. Construct a neighbor status table for the current vehicle; wherein, the neighbor status table includes the relative operating status between the current vehicle and at least one of its neighbor vehicles; a neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the beacon is higher than a preset minimum communication threshold.

[0097] For example, the execution subject of this embodiment can be an electronic device in the current vehicle, such as a controller. The electronic device can be simply referred to as the device. During the operation of the current vehicle, the device obtains the current vehicle's operating status through sensors and positioning modules inside the vehicle, including, for example, driving speed, driving acceleration, and driving position. The device broadcasts the vehicle's operating status to the surrounding environment at a preset period and power using short-range communication technology, and receives signals from vehicles within the current vehicle's maximum direct communication range and whose signal-to-noise ratio corresponding to the beacon is higher than a preset minimum communication threshold (e.g., within the direct communication range of SparkLink Low Energy (SLE) technology). Figure 1 The operating status of vehicles within the congested intersection area shown in the box includes, for example, driving speed, driving acceleration, and driving position.

[0098] In this process, each of the current vehicle and its neighboring vehicles broadcasts discovery beacons to the surrounding environment at a preset period and power through its Device-to-Device (D2D) module. Discovery beacons are periodic, broadcast signal packets emitted during the initialization phase of the StarSignal SLE D2D link, similar to Bluetooth broadcast packets. Each discovery beacon carries the vehicle's identity information, current acceleration, physical layer timestamps for accurate ranging, and phase measurement reference information for phase measurement. Each vehicle only receives discovery beacons from neighboring vehicles within its direct range.

[0099] At this point, the scene where the vehicle and each of its neighboring vehicles are located forms a cluster structure. The device uses its own vehicle as a reference to calculate the current vehicle's operating state and the operating state of each neighboring vehicle. Specifically, it can subtract the operating state of each neighboring vehicle from the current vehicle's operating state to obtain the relative operating state (collision, moving away, or remaining relatively stationary) between the current vehicle and each neighboring vehicle. This includes the vehicle identity information of each neighboring vehicle, the physical distance between it and the current vehicle, and the relative speed, in order to obtain a neighboring state table containing the relative operating states between the vehicle and each neighboring vehicle.

[0100] Short-range communication technologies include, but are not limited to, SparkLink Low Energy (SLE) / SparkLink Basic (SLB), Ultra Wide Band (UWB), Dedicated Short Range Communications (DSRC), or Bluetooth and WiFi modules with ranging capabilities. The vehicle's maximum direct communication range and preset minimum communication threshold can be determined by the vehicle's own hardware communication performance or set by the user according to their needs; no restrictions are imposed here.

[0101] 202. Based on the neighbor status table, generate a communication graph and a conflict graph between the current vehicle and each neighbor vehicle; the communication graph includes the communication links between the current vehicle and each neighbor vehicle; the conflict graph represents the communication conflicts between each communication link.

[0102] For example, the device obtains the communication connection status between multiple neighboring vehicles through its internal communication sensing module and by combining the relative operating status (e.g., relative speed and relative distance) between each neighboring vehicle and the current vehicle in the neighbor status table. Based on the communication connection status between these multiple neighboring vehicles and the communication connection status between the current vehicle and each neighboring vehicle, the device generates a communication graph, including the communication links between the current vehicle and each neighboring vehicle, where each communication link represents the communication connection status between the corresponding two vehicles.

[0103] Furthermore, for each pair of communication links in the communication graph, based on the relative operating status (e.g., relative speed and relative distance) between each neighboring vehicle and the current vehicle in the neighbor status table, the spatial multiplexing distance (e.g., the relative distance between the transmitter in the first communication link and the receiver in the second communication link) is determined (e.g., the relative distance between the transmitter in the first communication link and the receiver in the second communication link). It is then determined whether the spatial multiplexing distance is lower than a preset distance. If the spatial multiplexing distance is determined to be lower than the preset distance, then it is determined that there is a communication conflict between the first communication link and the second communication link; otherwise, there is no communication conflict between the first communication link and the second communication link.

[0104] 203. Based on the communication graph, determine the cluster head capability weight of the current vehicle; and determine the cluster head capability weight of neighboring vehicles; wherein, the cluster head capability weight represents the vehicle's computing power and the connectivity and stability of the communication connection.

[0105] For example, the device invokes a preset graph processing algorithm, such as a pre-trained graph neural network, to process the communication graph, extracting the current vehicle's computing resources and communication connections to measure its connectivity and centrality. Based on this graph neural network, the device further processes the current vehicle's computing resources and communication connections to obtain its cluster head capability weight, representing the current vehicle's computing power, connectivity, and stability. Simultaneously, for each neighboring vehicle, the device obtains its own computing resources and communication connections, processes these to obtain its own cluster head capability weight, representing each neighboring vehicle's computing power, connectivity, and stability. Then, each neighboring vehicle and the current vehicle broadcast their own cluster head capability weights, allowing the current vehicle to determine the cluster head capability weights of each neighboring vehicle.

[0106] 204. If it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each neighboring vehicle, the current vehicle is determined as the cluster head; and a resource scheduling table between the current vehicle and each neighboring vehicle is generated according to the conflict graph; wherein, the resource scheduling table is used to allocate communication resources to each neighboring vehicle.

[0107] For example, the device compares the cluster head capability weight of the current vehicle with the cluster head capability weight of each neighboring vehicle. If it is determined that the cluster head capability weight of the current vehicle is greater than that of each neighboring vehicle, the current vehicle is determined as the cluster head among all neighboring vehicles, and each neighboring vehicle is a cluster member. At this point, the current vehicle holds the right to internal resource scheduling among the neighboring vehicles. That is, the current vehicle senses external interference information (such as the communication status of mobile communication devices like phones and computers) and communication spectrum resources through the device's spectrum sensing module. The device incorporates communication links with communication conflicts, communication spectrum resources, and external interference information in the conflict graph into a unified optimization framework to execute a preset interference coordination algorithm, thereby calculating the optimal resource allocation scheme among the neighboring vehicles to obtain a resource scheduling table. This resource scheduling table includes the optimal communication resource allocation strategy for each neighboring vehicle's communication services. Each optimal communication resource allocation strategy avoids the allocation of frequency band resources with communication conflicts based on the conflict graph and reduces the communication interference intensity of external interference information. The device sends the resource scheduling table to each neighboring vehicle through its communication module, enabling each neighboring vehicle to obtain communication resources for inter-vehicle communication according to the resource scheduling table. The preset interference coordination algorithm is set by the user according to the actual situation, and there are no restrictions here.

[0108] For example, based on the distributed election principle, the environment of the current vehicle and its neighboring vehicles is transformed into a stable star cluster structure, with each vehicle serving as a candidate node. Each vehicle periodically broadcasts its cluster head capability weight via SLE D2D (Device-to-Device) links. Candidate nodes continuously monitor the cluster head capability weights of other candidate nodes within their direct connection range. Only when the cluster head capability weight reaches its highest value within its direct connection range is it officially designated as the cluster head (G-Node).

[0109] This embodiment provides a method for scheduling inter-vehicle communication resources. By using graph theory modeling and cluster head capability weight calculation, the optimality and adaptability of cluster head election are achieved. The cluster head is responsible for resource scheduling, and cluster members communicate according to the resource scheduling to adapt to network changes brought about by vehicle movement, thereby effectively improving the reliability of V2V communication.

[0110] Figure 3 This is a flowchart illustrating another method for scheduling inter-vehicle communication resources according to an embodiment of the present invention, as shown below. Figure 3 As shown, the method includes:

[0111] 301. Construct a neighbor status table for the current vehicle; wherein, the neighbor status table includes the relative operating status between the current vehicle and at least one of its neighbor vehicles; a neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the beacon is higher than a preset minimum communication threshold.

[0112] For example, the content of this step can be found in step 202, and will not be repeated here.

[0113] In one possible implementation, step 301 includes the following steps:

[0114] The first step is to broadcast the current vehicle's discovery beacon and receive discovery beacons from neighboring vehicles. The discovery beacon includes vehicle identification information, current acceleration, physical layer timestamp, and phase measurement reference information.

[0115] The second step is to determine the phase difference between the current vehicle and the neighboring vehicle based on the phase reference information in the discovery beacon sent by the current vehicle and the phase reference information in the discovery beacon sent by the neighboring vehicle.

[0116] The third step is to determine the physical distance between the current vehicle and its neighboring vehicles based on the phase difference between the current vehicle and its neighboring vehicles, the physical layer timestamp in the current vehicle's discovery beacon, and the physical layer timestamp in the discovery beacon sent by the neighboring vehicles.

[0117] The fourth step is to determine the relative speed between the current vehicle and its neighboring vehicles based on the physical distance between the current vehicle and its neighboring vehicles. The vehicle identification information, the physical distance between the current vehicle and each neighboring vehicle, and the relative speed constitute the relative operating status in the neighbor status table.

[0118] Specifically, the current vehicle and each of its neighboring vehicles broadcast discovery beacons to the surrounding environment at a preset period and power through their SLE (Device-to-Device) modules. Discovery beacons are periodic, broadcast signal packets emitted during the initialization phase of the StarSignal SLE D2D link, similar to Bluetooth broadcast packets. Each discovery beacon carries the vehicle's identity information, current acceleration, physical layer timestamps for accurate ranging, and phase measurement reference information for phase measurement. Each vehicle only receives discovery beacons from neighboring vehicles within its direct range, thus establishing a preliminary D2D communication link. For each vehicle, using phase ranging technology supported by the SLE protocol stack, the physical distance Dij between itself (vehicle i) and the beacon-emitting vehicle j is accurately calculated. After receiving discovery beacons from each neighboring vehicle, the current vehicle compares the phase reference information generated by the internal oscillator in its own discovery beacon with the phase reference information (including signal phase) in the received discovery beacon. By measuring multiple sets of phase differences, the signal transmission delay can be calculated with high precision, and the physical distance Dij can then be deduced. The measured physical distance Dij is used as the physical weight of the topology connection between the two vehicles. The directly connectable range is defined as follows: two vehicles can successfully establish a D2D physical link based on the Star-Signal SLE protocol, and the signal-to-noise ratio of the received signal meets the minimum ranging and communication requirement threshold SNRmin (SNR). Within this range, the maximum directly connectable range is defined as Dmax. If the link quality is within Dmax and meets the requirements, the vehicle is considered a directly connectable neighbor vehicle, capable of intra-cluster communication and ranging handshake. The receiving vehicle (e.g., the current vehicle) calculates the real-time relative velocity ΔVij with its neighbor vehicle by differentiating the continuously measured physical distance Dij or by utilizing the Doppler frequency shift characteristics of the physical layer signal. The real-time relative velocity is used to measure the dynamic stability of the topology link between the two vehicles and is a crucial dynamic adaptability parameter in subsequent dynamic clustering and cluster head election. Each vehicle independently constructs a neighbor state table, which dynamically stores the vehicle identity information (such as identity identifier, physical distance Dij, and relative speed ΔVij) of all directly connectable neighbor vehicles.

[0119] By using short-range communication ranging technology (such as phase ranging technology supported by the SLE protocol stack), and based on the physical layer characteristics of radio signals (such as phase difference and time of flight), the physical distance and relative speed between vehicles can be directly obtained. This can reduce signal obstruction problems in scenarios such as tunnels and underground parking garages, as well as the misjudgment of interference information in multipath propagation, improve the accuracy of topology construction, provide a reliable physical basis for subsequent dynamic clustering and resource scheduling, and enhance the communication reliability in high-density V2V scenarios.

[0120] 302. Based on the neighbor status table, generate the local perception topology between the current vehicle and each neighbor vehicle; wherein, the local perception topology represents the topological connection relationship between each vehicle.

[0121] For example, the device obtains the communication information between the current vehicle or each neighboring vehicle and other neighboring vehicles from the neighboring state table through the communication module. The device regards the current vehicle itself as the central node i of the graph, and all the nodes j corresponding to the neighbors that satisfy the direct connection range constraint as vertices of the graph. The link connecting nodes i and j is regarded as the edge Eij of the graph, thereby obtaining the local perception topology between the current vehicle and each neighboring vehicle to represent the relative spatiotemporal state between each vehicle. The local perception topology may include the physical distance between vehicles, relative speed, and topological connection relationships.

[0122] Based on a dynamic update mechanism, node i of the current vehicle periodically updates its neighbor state table. If the signal of a neighbor node j is continuously lower than the minimum signal-to-noise ratio (SNR) threshold or exceeds the SLE direct connection range for a given period of time, then node j is removed from the local sensing topology. Furthermore, the dynamic update mechanism ensures that the topology map is adjusted in real time as the vehicle moves, improving the accuracy of topology construction and providing a reliable physical basis for subsequent dynamic clustering and resource scheduling. The minimum SNR threshold and the SLE direct connection range are preset by the user based on actual conditions and are not restricted here.

[0123] 303. Based on the local perception topology, generate a communication graph and a conflict graph between the current vehicle and each of its neighboring vehicles.

[0124] For example, based on the local perception topology of the current vehicle, the device obtains the communication status between the current vehicle or each neighboring vehicle and other neighboring vehicles in the local perception topology through the communication module. Based on graph construction technology (e.g., a trained graph neural network), it generates corresponding communication links for every two neighboring vehicles (or between vehicles) with communication connections in the local perception topology, resulting in a communication graph. This communication graph includes the communication links between the current vehicle and each pair of neighboring vehicles. For each pair of communication links in the communication graph, combining the local perception topology and the communication graph, it determines whether there is a communication conflict between each pair of communication links, thus obtaining a conflict graph between the vehicle and its neighboring vehicles.

[0125] In one example, a first spatial multiplexing distance is determined between the transmitter (vehicle sending the message) in the first communication link and the transmitter in the second communication link, and a second spatial multiplexing distance is determined between the receiver (vehicle receiving the message) in the first communication link and the receiver in the second communication link. If the first spatial multiplexing distance is greater than a corresponding preset distance and the second spatial multiplexing distance is less than a corresponding preset distance, then a communication conflict exists between the first and second communication links; otherwise, no communication conflict exists. And / or, for each pair of communication links in the communication graph, based on the neighbor state table, a first relative speed and a second relative speed are calculated between the transmitter in the first communication link and the receiver in the second communication link. If the first relative speed is negative, indicating that the transmitter in the first communication link and the receiver in the second communication link are approaching each other, and the second relative speed is positive, indicating that the transmitter in the first communication link and the receiver are moving away from each other, then a communication conflict exists between the first and second communication links.

[0126] By constructing a local sensing topology with physical distance and relative speed as edges, the connection relationship and motion state between vehicles are dynamically reflected. Based on this, a communication graph and a conflict graph are constructed, which improves the accuracy of the communication graph and the conflict graph, reduces the probability of communication conflicts caused by topology misjudgment, and further enhances the communication reliability in high-density V2V scenarios.

[0127] In one possible implementation, step 303 includes the following steps:

[0128] The first step is to generate a communication graph between the current vehicle and each of its neighboring vehicles based on the local sensing topology. The communication graph includes a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link.

[0129] The second step is to generate a conflict graph between the current vehicle and its neighboring vehicles based on the communication graph between the current vehicle and its neighboring vehicles. The conflict graph includes vertices representing each communication link and at least one conflict edge. The conflict edge is determined based on two vertices meeting the communication conflict condition. The communication conflict condition includes that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver of the second vertex is less than a preset minimum reception threshold under communication interference from the transmitter of the first vertex.

[0130] Specifically, the device constructs a graph model between the current vehicle and its neighboring vehicles in real time based on real-time data from the local sensing topology. This model identifies the node i or node j of each vehicle in the current and neighboring vehicles. A communication edge Eij exists between any two vehicle nodes i and j, forming a communication link denoted as Lij. The condition is that the physical distance Dij between vehicle nodes i and j is within the maximum direct connection range Dmax of SLE D2D, and vehicle node i successfully receives and decodes the discovery beacon from vehicle node j, with the signal-to-noise ratio of the received signal exceeding a preset minimum communication threshold. In other words, the vehicle corresponding to node i is considered a neighboring vehicle. Furthermore, a graph model is constructed using a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link, resulting in a communication graph. Based on graph construction technology, the device generates vertices corresponding to each communication link in the communication graph and determines whether any two communication links meet preset communication conflict conditions. If the preset communication conflict conditions are met, a communication conflict is determined between the two communication links, and a corresponding conflict edge is generated for those two communication links. The device constructs a graph model of each vertex representing a communication link and each conflicting edge to obtain a conflict graph. The preset communication conflict condition is that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver at the second vertex is less than a preset minimum reception threshold under communication interference from the transmitter at the first vertex.

[0131] For example, collision edges are determined based on a signal-to-interference-plus-noise ratio (SINR) threshold. For each pair of communication links La (Txi→Rxj) and Lb (Txk→Rxl), the interference I caused by the transmitter Txi of La to the receiver Rxl of Lb is considered. Txi→Rxl When the critical value is reached, a collision between the two links is determined. Specifically, when Rxl receives the signal from Lb, its SINR... Rxl SINR is below the preset minimum receive threshold due to interference from Txi. Rxl conf In this case, a conflict edge Econf is added between La and Lb. Where SINRRxl =P Rxl Txk / (I Txi→Rxl +N0) <SINR Rxl conf , where P Rxl Txk It is the target signal power of Lb, I Txi→Rxl La represents the interference power, and N0 represents the noise floor. By constructing communication and conflict graphs, mathematical topological constraints are provided for dynamic clustering and resource scheduling, thereby improving the structural level of topology construction and the reliability of resource scheduling.

[0132] For example, Figure 4 This is a schematic diagram of vehicle communication before and after intra-cluster partitioning according to an embodiment of the present invention, as shown below. Figure 4 As shown, Figure 4 Image (a) illustrates the application of the method of the present invention to a vehicle. Figure 1 Communication status before cluster partitioning in a mid-scenario Figure 4 (b) illustrates that after applying the method of this invention, vehicles are divided into two independent cluster structures, C1 and C2, based on the precise physical distance and interference relationship between the vehicle and its neighboring vehicles. A corresponding communication graph is generated within each cluster structure, and based on the communication graph, the cluster head capability weight of each vehicle within each cluster structure is determined to elect a cluster head (G-Node) as the sole resource manager. This G-Node is responsible for executing the multi-target frequency band frequency hopping optimization interference coordination algorithm, precisely allocating and scheduling resources for the cluster members (T-Nodes) within the cluster structure, thus realizing the transformation from a contention mode to a deterministic scheduling mode within the cluster. The cluster division boundary and G-Node election are determined based on the maximum direct connection range and the minimum signal-to-noise ratio threshold. Therefore, cluster C1 and cluster C2 are naturally isolated in terms of physical and channel quality, and do not meet the basic direct communication conditions. However, in practical applications, if vehicles in cluster C1 need to communicate with vehicles in cluster C2, the following two relay schemes can be provided: (1) G-Node relay transmission: Since G-Node has the optimal topology location and management capabilities, it can be used as an inter-cluster bridge. That is, the G-Node of cluster C1 can forward information to the G-Node of cluster C2 through D2D multi-hop or temporary link, and the latter will perform secondary scheduling; (2) Cellular network relay: If the geographical distance between the two clusters is too far to perform efficient D2D relay, then information communication can be carried out through V2N cellular network. In addition, this method can realize high reliability and efficient spectrum reuse of intra-cluster V2V communication without the participation of base stations, and indirectly support the needs of cross-cluster communication.

[0133] 304. Based on the communication graph, determine the cluster head capability weight of the current vehicle; and determine the cluster head capability weight of neighboring vehicles; wherein, the cluster head capability weight characterizes the vehicle's computing power and the connectivity and stability of the communication connection.

[0134] For example, the content of this step can be found in step 203, and will not be repeated here.

[0135] In one possible implementation, step 304, determining the cluster head capability weight of the current vehicle in its cluster structure based on the communication graph, includes the following steps:

[0136] The first step is to determine the stability weight of the current vehicle based on the relative speed between the current vehicle and each of its neighboring vehicles; whereby the stability weight characterizes the stability of the vehicle's communication connection.

[0137] The second step is to determine the connectivity weight of the current vehicle based on its degree information. The degree information represents the total number of neighboring vehicles connected to the current vehicle in the communication graph, while the connectivity weight represents the vehicle's communication coverage and management capabilities.

[0138] The third step is to determine the resource weight of the current vehicle based on its computing power and energy information; whereby the resource weight represents the vehicle's ability to schedule and execute computing resources.

[0139] The fourth step is to determine the cluster head capability weight of the current vehicle based on the stability weight, connectivity weight, and resource weight.

[0140] Specifically, the device acquires the relative speed between the current vehicle and each neighboring vehicle, and calculates each relative speed, for example, by averaging the relative speeds to obtain the result ΔVavg. The device then uses a preset calculation method to calculate ΔVavg, for example, Ws = 1 / (1 + ΔVavg), to obtain the stability weight Ws of the current vehicle, which characterizes the communication connection stability of the vehicle. A higher stability weight Ws indicates that the current vehicle is relatively stationary or moving in the same direction and at the same speed with its neighboring vehicles, and the topology connection is more stable. Based on the communication graph, the device acquires the total number of neighboring vehicles connected to the current vehicle in the communication graph, and uses this total number as the degree information N of the current vehicle. The device then uses a preset calculation method to calculate this degree information N, for example, Wc = θN, where θ is a first preset coefficient, to obtain the connectivity weight of the current vehicle, which characterizes the communication coverage and management capabilities of the current vehicle. A node with a higher degree value has more neighboring nodes connected, a wider management range, and is more suitable as a centralized scheduling center for communication resources. The device obtains the vehicle's computing power and energy information M (e.g., current computing power resources and remaining battery power) through the vehicle's battery management system and computing resource manager. The device uses a preset calculation method to calculate this computing power and energy information M, for example, Wr = ηM, where η is a second preset coefficient, to obtain the vehicle's resource weight Wr. This weight represents the vehicle's communication coverage and management capabilities, ensuring that subsequently elected cluster heads (G-Nodes) have sufficient computing power and energy to execute complex interference coordination algorithms, preventing communication interruptions due to insufficient cluster head resources. The device uses a preset weighted calculation method to calculate the vehicle's stability weight, connectivity weight, and resource weight, for example, Wcap = ρWs + μWc + γWr, to obtain the vehicle's cluster head capability weight Wcap. The weight coefficients ρ, μ, and γ are preset adjustment coefficients used to balance the proportion of stability and resource efficiency in the overall objective. The preset calculation method and preset coefficients involved in this step can be provided by the user based on actual conditions; no restrictions are imposed here.

[0141] By comprehensively calculating the weights of stability (negatively correlated with average relative speed), connectivity (node ​​degree in the communication graph), and resource capabilities (computing power, power consumption), the optimality of subsequent cluster head election is achieved, thereby improving the stability of the cluster structure and the efficiency of resource management.

[0142] 305. If it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each neighboring vehicle in the cluster structure in which the current vehicle is located, then the current vehicle is determined to be the cluster head in the cluster structure in which the current vehicle is located.

[0143] For example, the content of this step can be found in step 204, and will not be repeated here.

[0144] In one possible implementation, after step 304, the following steps are also included:

[0145] The first step is to determine the cluster head if the cluster head capability weight of a vehicle is less than that of any neighboring vehicle. Then, determine the neighboring vehicle with the largest cluster head capability weight among all the neighboring vehicles and make it the cluster head.

[0146] The second step is to generate a vehicle access request and send the access request to the cluster head; the access request is used to obtain the resource scheduling table.

[0147] The third step is to receive the resource scheduling table sent by the cluster head and then communicate based on the resource scheduling table sent by the cluster head.

[0148] Specifically, if the device determines that a vehicle's cluster head capability weight is less than that of any neighboring vehicle, it identifies the neighboring vehicle with the highest cluster head capability weight as the cluster head. All candidate nodes (neighboring vehicles or the current vehicle) whose own weight is lower than the G-Node immediately abandon the cluster head election and become cluster members (T-Nodes). At this point, the device sends an access request to the cluster head (G-Node) through the communication module in the current vehicle, ultimately resulting in a star-shaped D2D cluster structure with a clearly defined central node. Upon receiving the access request, the neighboring vehicle acting as the cluster head generates a resource scheduling table based on the communication needs of all vehicles sending access requests, and referring to the process of generating a resource scheduling table based on the current vehicle. The neighboring vehicle acting as the cluster head sends the generated resource scheduling table to each vehicle that sent an access request. Then, the current vehicle receives the resource scheduling table sent by the neighboring vehicle acting as the cluster head and acquires communication resources according to the communication resource allocation strategy in the resource scheduling table to perform vehicle-to-vehicle (V2V) communication.

[0149] 306. Based on the communication graph and the conflict graph, divide the current vehicle and each of its neighboring vehicles to obtain at least one maximum independent set; wherein the communication links between the vehicles in the maximum independent set do not interfere with each other in physical space.

[0150] For example, the device of the current vehicle (G-Node) introduces a communication graph and a constraint graph, and uses these graphs to establish hard physical constraints on resource allocation, i.e., to define all conflicting communication links within the cluster. The device then performs graph theory algorithms on the communication and constraint graphs to partition the vehicle and its neighbors, resulting in one or more maximally independent sets. All communication links in each maximally independent set are physically independent, thus allowing them to reuse resources simultaneously in the same time slot and frequency. Each maximally independent set defines the spatial reuse limit for resource allocation within the cluster of the vehicle and its neighbors, providing a feasible subset of resource allocations for subsequent interference coordination algorithms.

[0151] For example, Figure 5 Example diagrams of communication and collision diagrams provided in an embodiment of the present invention, such as... Figure 5 As shown, Figure 5 (a) in the diagram is a communication diagram. Figure 5 (b) in the diagram represents the conflict graph. In this case, there are a total of 6 nodes representing vehicles (V1, V2, V3, V4, V5, V6) in the communication graph, all connected to each other, meaning they are all within the maximum direct connection range of the current vehicle. Any two nodes have a communication edge (e.g., 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15) forming a communication link. These 15 communication links constitute... Figure 5 The vertices of the conflict graph in (b) are shown, where communication links L2 have conflicting edges with L6 and L8, L7 has conflicting edges with L10 and L11, and L11 has conflicting edges with L15. A maximum independent set can be defined, where all communication links in the maximum independent set are physically independent. For example, in... Figure 5 In the diagram, the communication links marked in gray form a maximum independent set, and the communication links containing the white squares form a maximum independent set.

[0152] 307. Based on the constraints of at least one maximum independent set and the communication demand information between the current vehicle and each neighboring vehicle, generate a resource scheduling table between the current vehicle and each neighboring vehicle; wherein the constraints include that resources in the same time slot and resources in the same frequency are not allocated to communication links that conflict.

[0153] For example, the device determines constraints between maximally independent sets based on at least one maximally independent set, including ensuring that resources in the same time slot and frequency are not allocated to conflicting communication links. The device collects communication demand information and external interference information between the vehicle and its neighboring vehicles through environmental perception; the communication demand information includes the communication demand information of each neighboring vehicle, including broadband service demands and / or narrowband service demands. Further, the device can use a spectrum sensing module to scan and detect the energy of the current communication frequency band to identify external interference information. The device incorporates the communication demand information, constraints, and external interference information of all neighboring vehicles (T-Nodes) into a unified optimization framework to execute an interference coordination algorithm, thereby calculating a resource scheduling table containing the optimal resource allocation scheme.

[0154] Specifically, the device takes as input the communication requirements of all neighboring vehicles (T-Nodes), the constraints between each maximum independent set, and external interference information, and executes an interference coordination algorithm. The goal of this algorithm is to maximize the comprehensive objective function J, which is the total utility minus the overlap penalty and feasibility risk. The formula for the comprehensive objective function is as follows:

[0155] ;

[0156] Where S represents the communication demand information of all neighboring vehicles (T-Nodes), and U(s) is the utility function of each communication service s in the communication demand information, which is determined by the service type, priority, and bandwidth requirements of the communication service. The total system utility is represented by J. Poverlap represents the total interference intensity caused by spectrum overlap among all communication services in the current resource allocation scheme. α is the overlap penalty weight; a higher α value indicates a greater tendency to completely avoid spectrum overlap. The maximum independent sets provided by the conflict graph are hard constraints of Poverlap; any allocation scheme that does not meet the constraints of the maximum independent sets will be excluded. Prisk is the feasibility risk function, which is used to assess whether there are still enough contiguous resource blocks of remaining spectrum to meet the needs of other services within the cluster after allocating broadband services. If the remaining spectrum is fragmented too much, the Prisk value will be high. β is the feasibility risk weight; a higher β value indicates a greater tendency to protect the continuity and integrity of spectrum resource allocation, prioritizing the basic survival rights of all communication services. By maximizing J, the G-Node can achieve optimal balanced scheduling of resources within the cluster, ensuring that V2V links do not physically conflict, i.e., ensuring the constraints of the conflict graph, prioritizing high-priority services, while avoiding the waste and excessive fragmentation of spectrum resources.

[0157] In one possible implementation, the resource scheduling table includes a broadband resource allocation strategy, which includes the frequency and time slot ultimately allocated to each neighboring vehicle processing broadband services; step 307 includes the following steps:

[0158] The first step is to determine the initial broadband resource allocation strategy based on the broadband service requirements in the communication demand information and the constraint of at least one maximum independent set; wherein, the initial broadband resource allocation strategy includes the frequency and time slot initially allocated to each neighboring vehicle that processes broadband services.

[0159] The second step is to determine the feasibility risk penalty corresponding to the initial broadband resource allocation strategy based on the initial broadband resource allocation strategy and the feasibility risk function; wherein, the feasibility risk penalty is the feasibility risk penalty caused to the remaining spectrum resources after the initial bandwidth block allocation strategy is executed.

[0160] The third step is to adjust the initial broadband resource allocation strategy based on the feasibility risk penalty, resulting in the broadband resource allocation strategy in the resource scheduling table.

[0161] Specifically, when the communication demand information includes broadband service requirements, it involves high-bandwidth demand services. In this case, the device adopts a feasibility protection strategy. First, based on the broadband service requirements in the communication demand information and the constraint of at least one maximum independent set, an initial broadband resource allocation strategy is determined. This initial strategy includes the frequency and time slot initially allocated to each neighboring vehicle processing broadband services. Then, the device calls a preset feasibility risk function and calculates it based on the initial broadband resource allocation strategy. This calculation yields the feasibility risk penalty on the remaining spectrum resources after executing the initial bandwidth block allocation strategy. This penalty is used to limit excessive fragmentation of the spectrum in communication resources caused by resource allocation behavior, ensuring that subsequent narrowband or secondary broadband services still have continuous resource space available. Based on the goal of minimizing the feasibility risk penalty, the device continuously adjusts the initial broadband resource allocation strategy. For example, it uses techniques such as sliding window scanning and prefix sum acceleration to quickly calculate the optimal continuous spectrum block (including frequency and time slot) that can maximize the broadband service utility under the premise of minimizing the feasibility risk penalty. This leads to the final broadband resource allocation strategy, including the frequency and time slot finally allocated to each neighboring vehicle that processes broadband services, such as continuously using frequency A to frequency D from time 1 to time 10.

[0162] In one possible implementation, the resource scheduling table includes a narrowband service resource allocation strategy; the narrowband service resource allocation strategy includes the frequency hopping sequence and non-uniform frequency hopping probability distribution ultimately allocated to each neighboring vehicle processing narrowband services; step 307 includes the following steps:

[0163] The first step is to determine the frequency hopping sequence in the narrowband service resource allocation strategy in the resource scheduling table based on the narrowband service requirements in the communication demand information and the constraint condition of at least one maximum independent set; wherein, the frequency hopping sequence includes multiple frequency points selected from the current communication frequency band for communication.

[0164] The second step is to process the frequency hopping sequence to obtain the net gain score for each frequency hopping point in the sequence; whereby the net gain score characterizes the communication channel quality of the frequency hopping point.

[0165] The third step is to map the net benefit score of each frequency hopping point in the frequency hopping sequence to obtain the non-uniform frequency hopping probability distribution in the narrowband service resource allocation strategy in the resource scheduling table.

[0166] Specifically, when the communication demand information includes narrowband service requirements, based on the narrowband service requirements in the communication demand information and the constraint of at least one maximum independent set, multiple frequency hopping points selected for communication and the frequencies and time slots allocated to each neighboring vehicle processing narrowband services are obtained from the current communication spectrum resources. This yields the frequency hopping sequence in the narrowband service resource allocation strategy of the resource scheduling table. This frequency hopping sequence is the order or algorithm of frequency hopping, indicating which frequency a neighboring vehicle (T-Node) should hop to to transmit and receive information at each time. The frequency and time slot of each neighboring vehicle processing narrowband services satisfy the constraint of at least one maximum independent set, meaning that the same time slot and frequency cannot be allocated to communication links connected by conflict edges in the conflict graph, avoiding intra-cluster collision interference. Afterwards, the device performs non-uniform frequency hopping probability shaping on the frequency hopping sequence and calculates the net benefit score for each frequency hopping point in the sequence; the net benefit score characterizes the communication channel quality of the frequency hopping point. Furthermore, based on the mapping relationship between each preset net benefit score and each preset probability, the device performs probability mapping on the net benefit score of each frequency hopping point in the frequency hopping sequence to obtain the non-uniform frequency hopping probability distribution in the narrowband service resource allocation strategy of the resource scheduling table. This includes the probability of being allocated to each frequency hopping point at different frequencies, guiding T-Nodes to prioritize the use of high-benefit, low-conflict frequency hopping points, statistically ensuring low latency and high reliability of narrowband services. Finally, the device (G-Node, which is the current vehicle at this point) generates a resource scheduling table containing the resource allocation of all T-Nodes based on the optimization results of the multi-target frequency band infection coordination algorithm. The table includes: allocated frequency, time slot, frequency hopping sequence, and non-uniform frequency hopping probability distribution. The G-Node distributes this scheduling table to all T-Nodes in the cluster, i.e., all neighboring vehicles, in real time through the SLE control channel. Each T-Node must strictly communicate according to the G-Node's scheduling table, thereby completely transforming the competition mode within the cluster into an ordered scheduling mode. Throughout the process, the G-Node continuously monitors the spectrum. If a change in external interference sources is detected, the multi-target frequency band infection coordination algorithm will be immediately re-run and the resource scheduling table updated. Furthermore, through the aforementioned inefficiency scoring and probability allocation mechanism, the current spectrum resources are intelligently reused. That is, communication links that do not interfere with each other in physical space can reuse resources simultaneously in the same time slot and on the same frequency, thereby maximizing the spatiotemporal utilization efficiency of limited spectrum resources while ensuring the reliability of communication links.

[0167] For example, Figure 6 Here is a flowchart of an interference coordination algorithm provided in an embodiment of the present invention, as shown below. Figure 6As shown, the device performs an environmental awareness process to scan the spectrum and mark external interference frequencies, obtaining a frequency marking table. Then, the device introduces a constraint graph and a communication graph, extracting the maximum independent set (MIS) for the current vehicle and each neighboring vehicle as a hard constraint for spatial multiplexing, thus identifying all conflicting communication links within the cluster. The current vehicle, acting as the cluster head (G-Node), takes the cluster's communication requirements and the MIS set as input and executes an interference coordination algorithm. Specifically, the G-Node prioritizes high-bandwidth-demand services, and when allocating contiguous bandwidth blocks, it must simultaneously assess the feasibility risk penalty that this allocation would impose on the remaining spectrum. Subsequently, the G-Node allocates resources for latency-sensitive narrowband services. When calculating resource allocation, it must ensure that the allocation results satisfy the MIS constraint, i.e., the same time slot and frequency cannot be allocated to links connected by edges in the conflict graph, avoiding intra-cluster collision interference. Finally, based on the optimization results of the FHO algorithm, the G-Node generates a scheduling table containing the resource allocations of all T-Nodes. The G-Node sends the scheduling table to all T-Nodes in the cluster in real time via the SLE control channel, and the T-Nodes communicate according to the G-Node's scheduling table.

[0168] In one possible implementation, the frequency hopping sequence is processed to obtain a net gain score for each frequency hopping point in the sequence, including:

[0169] Step 1: Collect the signal power intensity of each discrete frequency point in the vehicle's current communication frequency band.

[0170] Step 2: Generate a frequency point marking table based on the signal power intensity of each discrete frequency point; the frequency point marking table includes discrete frequency points that have severe external interference and are not suitable for use.

[0171] Step 3: Determine the utility score of each discrete frequency point in the current communication frequency band based on the frequency point marking table.

[0172] Step 4: Determine the net benefit score of the frequency hopping frequency point based on the utility score and overlap penalty of the discrete frequency point corresponding to the frequency hopping frequency point; where the overlap penalty represents the total interference intensity caused by the external interference source and other services within the cluster when the discrete frequency points overlap.

[0173] Specifically, the device performs environmental awareness to identify and avoid strong external interference. This involves continuously scanning and detecting the energy of the current communication frequency band using a spectrum sensing module, and collecting the signal power intensity of each discrete frequency point in the current communication band in real time. Based on the detected energy strength, the device identifies discrete frequency points with severe external interference that are unsuitable for use and converts them into a frequency point labeling table. According to the frequency point labeling table and a preset utility function, the device determines the utility score of each discrete frequency point in the current communication band. The utility score of all discrete frequency points overlapping with those in the frequency point labeling table is significantly reduced. The device determines the overlap penalty for each discrete frequency point using a preset overlap penalty function. This penalty includes the total interference intensity caused by external interference sources and other services within the cluster when overlapping at each discrete frequency point. The device then subtracts the overlap penalty from the utility score of the discrete frequency point corresponding to each frequency hop to obtain the net benefit score for each frequency hop.

[0174] The deployment of the device's spectrum sensing module can be integrated with a dedicated radio frequency acquisition front-end to achieve continuous broadband spectrum monitoring of the current communication frequency band. Given different terminal forms and application scenarios, the integration scheme, channel bandwidth, and real-time requirements of this radio frequency acquisition front-end will vary depending on the specific vehicle communication unit or V2X terminal design.

[0175] By combining feasibility risk assessment with non-uniform probabilistic shaping interference coordination algorithm, the spectrum continuity of V2V broadband services is guaranteed. External interference is intelligently avoided through probabilistic shaping, which improves spectrum utilization efficiency and system robustness while ensuring the reliability of basic security messages.

[0176] In one possible implementation, after step 307, the following steps are also included:

[0177] The first step is to determine the new cluster head if the operating status between the monitored vehicle and its neighboring vehicles meets the preset conditions. This is done by identifying the cluster head neighboring vehicle with the highest cluster head capability weight among the neighboring vehicles. The preset conditions include any one of the following: the average relative speed between the vehicle and its neighboring vehicles is greater than a preset threshold; the vehicle's stability weight is continuously lower than a preset threshold within a preset time period; the vehicle's computing power and energy information cannot meet the conditions for maintaining the operation of the interference coordination algorithm; and the number of neighboring vehicles that are not within the vehicle's maximum direct communication range is greater than a preset number. The stability weight represents the stability of the vehicle's communication connection.

[0178] The second step is to generate a scheduling context based on the resource scheduling table and send the scheduling context to the new cluster head. The scheduling context includes the resource scheduling table and the current scene interference label table. The scheduling context is used to generate a new resource scheduling table.

[0179] The third step is to receive the new resource scheduling table sent by the new cluster head and communicate according to the new resource scheduling table.

[0180] Specifically, based on a dynamic maintenance and smooth handover mechanism, the device monitors the status of the G-Node and all T-Nodes within the cluster in real time, i.e., the operational status between the vehicle and its neighboring vehicles. This operational status includes the relative speed between the current vehicle and its neighboring vehicles, and / or the computing power and energy information of the current vehicle, and / or whether each neighboring vehicle is within the vehicle's maximum direct communication range, and / or the vehicle's stability weight within a preset time period. The device invokes preset conditions and determines whether the operational status meets these conditions. These preset conditions include any of the following: the average relative speed between the current vehicle and its neighboring vehicles is greater than a preset threshold; the vehicle's stability weight remains below a preset threshold within a preset time period; the current vehicle's computing power and energy information are insufficient to maintain the operation of the interference coordination algorithm; and the number of neighboring vehicles not within the vehicle's maximum direct communication range is greater than a preset number. The stability weight characterizes the communication connection stability of the vehicle. If the device determines that the operational status between the vehicle and its neighboring vehicles meets the preset conditions, it initiates a soft handover process, designating the cluster head neighboring vehicle with the highest cluster head capability weight as the new cluster head. To ensure communication continuity across all V2V links within a cluster, a smooth transition of the scheduling context must be performed. The original cluster head, i.e., the current vehicle, packages the current resource scheduling table, frequency hopping probability distribution, and the latest environmental interference flag table into a scheduling context via the device. This scheduling context is then passed to the newly elected G-Node, i.e., the new cluster head, through the SLE control channel. Subsequently, the new G-Node, based on the new input and real-time environmental awareness, progressively runs the FHO algorithm and smoothly iteratively updates the scheduling table to obtain a new resource scheduling table, achieving seamless handover. The new cluster head sends the new resource scheduling table to the current vehicle, enabling the current vehicle to acquire communication resources and conduct inter-vehicle communication according to the new resource scheduling table.

[0181] To prevent frequent cluster head switching due to minor fluctuations in the cluster head capability weight of vehicles at the cluster boundary, a hysteresis threshold mechanism can be adopted. Switching is only officially triggered when the cluster head capability weight of the new G-Node continuously exceeds that of the current G-Node (original cluster head) within a continuous time period.

[0182] For example, Figure 7 This is an overall flowchart of a vehicle-to-vehicle interference coordination method based on high-precision short-range communication ranging and dynamic clustering, provided in an embodiment of the present invention. Figure 7As shown, in step one, each vehicle activates a high-precision short-range communication ranging module, utilizing the physical layer characteristics of radio signals (such as phase ranging, time-of-flight ranging, etc.) to measure the physical distance and relative speed between vehicles. Each vehicle independently constructs a neighbor state table, containing neighbor vehicle identifiers, distances and relative speeds with other vehicles, and dynamically constructs and updates the local sensing topology in real time based on the measurement results. In step two, the vehicles use the data from step one to construct a communication graph and a conflict graph. That is, each vehicle calculates its own G-Node election capability weight based on stability, connectivity, and resource advantages. Through distributed election, the node with the highest weight is established as the G-Node (cluster head), and other nodes are converted into T-Nodes (cluster members) to join, forming a star-shaped D2D cluster structure. Step 3: As the scheduling center, the G-Node first performs a spectrum scan to avoid strong external interference. Then, the G-Node uses the conflict graph to extract the maximum independent set as a hard constraint for spatial reuse and executes the Frequency Hopping Optimization (FHO) algorithm. This algorithm maximizes the comprehensive objective function to safeguard the feasibility of V2V broadband services and shape the non-uniform frequency hopping probability of narrowband services. Step 4: The G-Node continuously monitors the stability of the cluster topology and its own resource status. When the handover conditions are met (such as a continuous decrease in stability weight), a soft handover process is initiated. The current G-Node passes the current resource scheduling table and frequency hopping probability distribution, among other scheduling contexts, to the newly elected G-Node. The new G-Node maintains the original scheduling in the initial takeover phase and then iteratively updates it to ensure service continuity.

[0183] When the cluster structure undergoes drastic changes, the role and scheduling control of the G-Node are transferred to a new optimal candidate, namely the new G-Node, with the lowest risk of business interruption. The new G-Node maintains the original scheduling in the initial stage of takeover and then iteratively updates it to ensure business continuity.

[0184] In this embodiment, based on the above embodiments, high-precision short-range communication ranging, graph theory modeling, and multi-objective optimization interference coordination algorithms are integrated to transform the disordered V2V network into a star cluster structure with centralized scheduling by G-Nodes. By accurately identifying the interference relationship between communication links and performing resource scheduling, the spectrum utilization efficiency and service reliability can be effectively improved.

[0185] Figure 8 This is a schematic diagram of the structure of a vehicle-to-vehicle communication resource scheduling device according to an embodiment of the present invention, as shown below. Figure 8 As shown, the device includes:

[0186] The construction module 401 is used to construct the neighbor status table of the current vehicle; wherein, the neighbor status table includes the relative operating status between at least one neighbor vehicle of the current vehicle and the current vehicle; the neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the discovered beacon is higher than a preset minimum communication threshold;

[0187] The first generation module 402 is used to generate a communication graph and a conflict graph between the current vehicle and each neighboring vehicle based on the neighbor status table; wherein, the communication graph includes the communication links between the current vehicle and each neighboring vehicle; the conflict graph represents the communication conflict between each communication link;

[0188] The determination module 403 is used to determine the cluster head capability weight of the current vehicle based on the communication graph; and to determine the cluster head capability weight of neighboring vehicles; wherein, the cluster head capability weight characterizes the vehicle's computing power and the connectivity and stability of the communication connection;

[0189] The second generation module 404 is used to determine the current vehicle as the cluster head if it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each neighboring vehicle; and to generate a resource scheduling table between the current vehicle and each neighboring vehicle according to the conflict graph; wherein the resource scheduling table is used to allocate communication resources to each neighboring vehicle.

[0190] Furthermore, module 403 is specifically used for: determining the stability weight of the current vehicle based on the relative speed between the current vehicle and each neighboring vehicle; wherein the stability weight characterizes the communication connection stability of the vehicle; determining the connectivity weight of the current vehicle based on the degree information of the current vehicle; wherein the degree information characterizes the total number of each neighboring vehicle connected to the current vehicle in the communication graph; the connectivity weight characterizes the communication coverage and management capability of the vehicle; determining the resource weight of the current vehicle based on the computing power and energy information of the current vehicle; wherein the resource weight characterizes the scheduling and execution capability of the vehicle's computing resources; and determining the cluster head capability weight of the current vehicle based on the stability weight, connectivity weight, and resource weight.

[0191] Furthermore, the second generation module 404 is specifically used to: divide the current vehicle and each neighboring vehicle according to the communication graph and the conflict graph to obtain at least one maximum independent set; wherein the communication links between the vehicles in the maximum independent set do not interfere with each other in physical space; generate a resource scheduling table between the current vehicle and each neighboring vehicle according to the constraints of at least one maximum independent set and the communication demand information between the current vehicle and each neighboring vehicle; wherein the constraints include that resources in the same time slot and resources in the same frequency are not allocated to communication links that conflict.

[0192] Furthermore, the resource scheduling table includes a broadband resource allocation strategy, which includes the frequency and time slot ultimately allocated to each neighboring vehicle processing broadband services. The second generation module 404 is further specifically used for: determining an initial broadband resource allocation strategy based on the broadband service requirements in the communication demand information and the constraint condition of at least one maximum independent set; wherein the initial broadband resource allocation strategy includes the frequency and time slot initially allocated to each neighboring vehicle processing broadband services; determining the feasibility risk penalty corresponding to the initial broadband resource allocation strategy based on the initial broadband resource allocation strategy and the feasibility risk function; wherein the feasibility risk penalty is the feasibility risk penalty caused to the remaining spectrum resources after executing the initial bandwidth block allocation strategy; and adjusting the initial broadband resource allocation strategy based on the feasibility risk penalty to obtain the broadband resource allocation strategy in the resource scheduling table.

[0193] Furthermore, the resource scheduling table includes a narrowband service resource allocation strategy; the narrowband service resource allocation strategy includes a frequency hopping sequence and a non-uniform frequency hopping probability distribution ultimately allocated to each neighboring vehicle processing narrowband services; the second generation module 404 is further specifically used to: determine the frequency hopping sequence in the narrowband service resource allocation strategy in the resource scheduling table based on the narrowband service requirements in the communication requirement information and the constraint condition of at least one maximum independent set; wherein the frequency hopping sequence includes multiple frequency hopping points selected from the current communication frequency band for communication; process the frequency hopping sequence to obtain the net benefit score of each frequency hopping point in the frequency hopping sequence; wherein the net benefit score characterizes the communication channel quality of the frequency hopping point; and map the net benefit score of each frequency hopping point in the frequency hopping sequence to obtain the non-uniform frequency hopping probability distribution in the narrowband service resource allocation strategy in the resource scheduling table.

[0194] Furthermore, the second generation module 404 is specifically used for: collecting the signal power intensity of each discrete frequency point in the current communication frequency band of the vehicle; generating a frequency point marking table based on the signal power intensity of each discrete frequency point; wherein the frequency point marking table includes discrete frequency points that have serious external interference and are not suitable for use; determining the utility score of each discrete frequency point in the current communication frequency band based on the frequency point marking table; determining the net benefit score of the frequency hopping frequency point based on the utility score of the discrete frequency point corresponding to the frequency hopping frequency point and the overlap penalty; wherein the overlap penalty characterizes the total interference intensity caused by the external interference source and other services within the cluster when the discrete frequency points overlap.

[0195] Furthermore, module 401 is specifically used for: broadcasting the current vehicle's discovery beacon; and receiving discovery beacons sent by neighboring vehicles; wherein the discovery beacon includes vehicle identity information, current acceleration, physical layer timestamp, and phase measurement reference information; determining the phase difference between the current vehicle and neighboring vehicles based on the phase reference information in the discovery beacon sent by the current vehicle and the phase reference information in the discovery beacon sent by neighboring vehicles; determining the physical distance between the current vehicle and neighboring vehicles based on the phase difference between the current vehicle and neighboring vehicles, the physical layer timestamp in the current vehicle's discovery beacon, and the physical layer timestamp in the discovery beacon sent by neighboring vehicles; and determining the relative speed between the current vehicle and neighboring vehicles based on the physical distance between the current vehicle and neighboring vehicles; wherein the vehicle identity information, the physical distance between the current vehicle and each neighboring vehicle, and the relative speed constitute the relative operating state in the neighboring state table.

[0196] Furthermore, the first generation module 402 is specifically used to: generate a local perception topology between the current vehicle and each neighboring vehicle based on the neighbor status table; wherein, the local perception topology represents the topological connection relationship between each vehicle; and generate a communication graph and a conflict graph between the current vehicle and each neighboring vehicle based on the local perception topology.

[0197] Furthermore, the first generation module 402 is specifically configured to: generate a communication graph between the current vehicle and each neighboring vehicle based on the local sensing topology; wherein the communication graph includes a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link; and generate a conflict graph between the current vehicle and each neighboring vehicle based on the communication graph between the current vehicle and each neighboring vehicle; wherein the conflict graph includes a vertex representing each communication link and at least one conflict edge; the conflict edge is determined based on two vertices meeting a communication conflict condition; the communication conflict condition includes that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver of the second vertex is less than a preset minimum reception threshold under communication interference at the transmitter of the first vertex.

[0198] Furthermore, in the second generation module 404, after generating a resource scheduling table between the current vehicle and each neighboring vehicle based on the conflict graph, the device is further configured to: if the monitoring of the operating status between the current vehicle and each neighboring vehicle meets preset conditions, determine the cluster head neighboring vehicle with the largest cluster head capability weight among the neighboring vehicles as the new cluster head; wherein, the preset conditions include any one of the following: the average relative speed between the current vehicle and each neighboring vehicle is greater than a preset threshold, the stability weight of the vehicle is continuously lower than a preset threshold value within a preset time period, the computing power and energy information of the current vehicle cannot meet the conditions for maintaining the operation of the interference coordination algorithm, and the number of vehicles among the neighboring vehicles that are not within the maximum direct communication range of the vehicle is greater than a preset number; the stability weight characterizes the communication connection stability of the vehicle; generate a scheduling context based on the resource scheduling table; and send the scheduling context to the new cluster head; wherein, the scheduling context includes the resource scheduling table and the current scene interference marking table; the scheduling context is used to generate a new resource scheduling table; receive the new resource scheduling table sent by the new cluster head, and communicate according to the new resource scheduling table.

[0199] Furthermore, the device is also configured to: if the cluster head capability weight of a vehicle is determined to be less than the cluster head capability weight of any neighboring vehicle, determine the neighboring vehicle with the largest cluster head capability weight among all neighboring vehicles as the cluster head; generate an access request for the vehicle; and send the access request to the cluster head; wherein the access request is used to obtain a resource scheduling table; receive the resource scheduling table sent by the cluster head; and communicate according to the resource scheduling table sent by the cluster head.

[0200] The apparatus in this embodiment can execute the technical solutions in the above method. Its specific implementation process and technical principles are the same, and will not be repeated here.

[0201] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention, as shown below. Figure 9 As shown, the electronic device includes: a memory 501 and a processor 502; the memory 501 is a memory used to store instructions executable by the processor 502.

[0202] The processor 502 is configured to perform the method provided in the above embodiments.

[0203] The electronic device also includes a receiver 503 and a transmitter 504. The receiver 503 is used to receive instructions and data sent by other devices, and the transmitter 504 is used to send instructions and data to external devices.

[0204] The specific implementation process of the processor can be found in the above method embodiments, and its implementation principle and technical effect are similar, so it will not be repeated here.

[0205] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0206] Embodiments of the present invention also provide a vehicle, including a vehicle body and an electronic device disposed in the vehicle body. The electronic device stores computer execution instructions, which, when executed on a computer, cause the computer to execute the technical solutions of the above embodiments.

[0207] Embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions, which, when executed on a computer, cause the computer to perform the technical solutions of the above embodiments.

[0208] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory, electrically erasable programmable read-only memory, erasable programmable read-only memory, programmable read-only memory, read-only memory, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0209] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. The readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an application-specific integrated circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in a device.

[0210] Embodiments of the present invention also provide a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor can read the computer program from the computer-readable storage medium, and when the at least one processor executes the computer program, it can implement the technical solutions in the above embodiments.

[0211] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as magnetic disks or optical disks.

[0212] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for scheduling communication resources between vehicles, characterized in that, include: Construct a neighbor status table for the current vehicle; wherein, the neighbor status table includes the relative operating status between at least one neighbor vehicle of the current vehicle and the current vehicle; the neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the beacon is higher than a preset minimum communication threshold; Based on the neighbor status table, a communication graph and a conflict graph are generated between the current vehicle and each of the neighboring vehicles; wherein, the communication graph includes the communication links between the current vehicle and each of the neighboring vehicles; and the conflict graph represents the communication conflict situation between each of the communication links. Based on the communication graph, the cluster head capability weight of the current vehicle is determined; and the cluster head capability weight of the neighboring vehicles is determined; wherein, the cluster head capability weight characterizes the vehicle's computing power and the connectivity and stability of the communication connection; If it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each of the neighboring vehicles, the current vehicle is determined to be the cluster head; and according to the conflict graph, a resource scheduling table is generated between the current vehicle and each of the neighboring vehicles; wherein, the resource scheduling table is used to allocate communication resources to each of the neighboring vehicles. The step of generating a communication graph and a conflict graph between the current vehicle and each of the neighboring vehicles based on the neighbor status table includes: Based on the neighbor status table, a local perception topology is generated between the current vehicle and each of the neighboring vehicles; wherein, the local perception topology represents the topological connection relationship between each vehicle; Based on the local perception topology, a communication graph and a conflict graph are generated between the current vehicle and each of the neighboring vehicles; The step of generating a communication graph and a conflict graph between the current vehicle and each of its neighboring vehicles based on the local sensing topology includes: Based on the local perception topology, a communication graph is generated between the current vehicle and each of the neighboring vehicles; wherein the communication graph includes a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link; Based on the communication graph between the current vehicle and each of the neighboring vehicles, a conflict graph is generated between the current vehicle and each of the neighboring vehicles; wherein, the conflict graph includes vertices representing each of the communication links and at least one conflict edge; the conflict edge is determined based on two vertices meeting a communication conflict condition; the communication conflict condition includes that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver of the second vertex is less than a preset minimum reception threshold under communication interference from the transmitter of the first vertex of the two vertices; The step of determining the cluster head capability weight of the current vehicle based on the communication graph, and determining the cluster head capability weight of the neighboring vehicles, includes: The stability weight of the current vehicle is determined based on the relative speed between the current vehicle and each of its neighboring vehicles; wherein the stability weight characterizes the communication connection stability of the vehicle. Based on the degree information of the current vehicle, the connectivity weight of the current vehicle is determined; wherein, the degree information represents the total number of neighboring vehicles connected to the current vehicle in the communication graph; and the connectivity weight represents the vehicle's communication coverage and management capabilities. Based on the current vehicle's computing power and energy information, the resource weight of the current vehicle is determined; wherein, the resource weight represents the vehicle's ability to schedule and execute computing resources. The cluster head capability weight of the current vehicle is determined based on the stability weight, the connectivity weight, and the resource weight; the step of generating a resource scheduling table between the current vehicle and each of its neighboring vehicles based on the conflict graph includes: Based on the communication graph and the conflict graph, the current vehicle and each of the neighboring vehicles are divided to obtain at least one maximum independent set; wherein the communication links between the vehicles in the maximum independent set do not interfere with each other in physical space. Based on the constraints of the at least one maximum independent set and the communication demand information between the current vehicle and each of the neighboring vehicles, a resource scheduling table is generated between the current vehicle and each of the neighboring vehicles; wherein, the constraints include not allocating resources in the same time slot and resources in the same frequency to conflicting communication links.

2. The method according to claim 1, characterized in that, The resource scheduling table includes a broadband resource allocation strategy, which includes the frequency and time slot ultimately allocated to each neighboring vehicle that processes broadband services. The step of generating a resource scheduling table between the current vehicle and each of the neighboring vehicles based on the constraints of the at least one maximum independent set and the communication requirement information between the current vehicle and each of the neighboring vehicles includes: Based on the broadband service requirements in the communication demand information and the constraints of the at least one maximum independent set, an initial broadband resource allocation strategy is determined; wherein, the initial broadband resource allocation strategy includes the frequency and time slot initially allocated to each neighboring vehicle processing broadband services. Based on the initial broadband resource allocation strategy and the feasibility risk function, the feasibility risk penalty corresponding to the initial broadband resource allocation strategy is determined; wherein, the feasibility risk penalty is the feasibility risk penalty caused to the remaining spectrum resources after the initial bandwidth block allocation strategy is executed; Based on the aforementioned feasibility risk penalty, the initial broadband resource allocation strategy is adjusted to obtain the broadband resource allocation strategy in the resource scheduling table.

3. The method according to claim 1, characterized in that, The resource scheduling table includes a narrowband service resource allocation strategy; the narrowband service resource allocation strategy includes the frequency hopping sequence and non-uniform frequency hopping probability distribution that are finally allocated to each neighboring vehicle that processes narrowband services. The step of generating a resource scheduling table between the current vehicle and each of the neighboring vehicles based on the constraints of the at least one maximum independent set and the communication requirement information between the current vehicle and each of the neighboring vehicles includes: Based on the narrowband service requirements in the communication demand information and the constraints of the at least one maximum independent set, the frequency hopping sequence in the narrowband service resource allocation strategy in the resource scheduling table is determined; wherein, the frequency hopping sequence includes multiple frequency points selected from the current communication frequency band for communication; The frequency hopping sequence is processed to obtain the net gain score for each frequency hopping point in the frequency hopping sequence; wherein, the net gain score characterizes the communication channel quality of the frequency hopping point; The net benefit score of each frequency hopping point in the frequency hopping sequence is mapped to obtain the non-uniform frequency hopping probability distribution in the narrowband service resource allocation strategy in the resource scheduling table.

4. The method according to claim 3, characterized in that, The process of processing the frequency hopping sequence to obtain the net gain score for each frequency hopping point in the frequency hopping sequence includes: Collect the signal power strength of each discrete frequency point in the current communication frequency band of the vehicle; A frequency point marking table is generated based on the signal power intensity of each discrete frequency point; wherein, the frequency point marking table includes discrete frequency points that have severe external interference and are not suitable for use; Based on the frequency point marking table, determine the utility score for each discrete frequency point in the current communication frequency band; The net benefit score of the frequency hopping frequency point is determined based on the utility score and overlap penalty of the discrete frequency point corresponding to the frequency hopping frequency point; wherein, the overlap penalty represents the total interference intensity caused by the external interference source and other services within the cluster when the discrete frequency points overlap.

5. The method according to claim 1, characterized in that, The construction of the current vehicle's neighbor status table includes: Broadcast the current vehicle's discovery beacon; and receive the discovery beacon sent by the neighboring vehicle; wherein the discovery beacon includes vehicle identity information, current acceleration, physical layer timestamp, and phase measurement reference information; The phase difference between the current vehicle and the neighboring vehicle is determined based on the phase reference information in the discovery beacon sent by the current vehicle and the phase reference information in the discovery beacon sent by the neighboring vehicle. The physical distance between the current vehicle and the neighboring vehicle is determined based on the phase difference between the current vehicle and the neighboring vehicle, the physical layer timestamp in the discovery beacon of the current vehicle and the physical layer timestamp in the discovery beacon sent by the neighboring vehicle. The relative speed between the current vehicle and the neighboring vehicles is determined based on the physical distance between the current vehicle and the neighboring vehicles; wherein, the vehicle identity information, the physical distance between the current vehicle and each of the neighboring vehicles, and the relative speed constitute the relative operating state in the neighbor status table.

6. The method according to claim 1, characterized in that, After generating a resource scheduling table between the current vehicle and each of its neighboring vehicles based on the conflict graph, the method further includes: If the monitored operating status between the current vehicle and each of the neighboring vehicles meets preset conditions, the cluster head neighbor vehicle with the highest cluster head capability weight among the neighboring vehicles is determined as the new cluster head; wherein, the preset conditions include any one of the following: the average relative speed between the current vehicle and each of the neighboring vehicles is greater than a preset threshold, the stability weight of the vehicle is continuously lower than a preset threshold value within a preset time period, the computing power and energy information of the current vehicle cannot meet the conditions for maintaining the operation of the interference coordination algorithm, and the number of neighboring vehicles that are not within the maximum direct communication range of the vehicle is greater than a preset number; the stability weight characterizes the communication connection stability of the vehicle; A scheduling context is generated based on the resource scheduling table; and the scheduling context is sent to the new cluster head; wherein, the scheduling context includes the resource scheduling table and the current scene interference label table; the scheduling context is used to generate a new resource scheduling table; The system receives the new resource scheduling table sent by the new cluster head and communicates according to the new resource scheduling table.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: If it is determined that the cluster head capability weight of the vehicle is less than the cluster head capability weight of any of the neighboring vehicles, the neighboring vehicle with the largest cluster head capability weight among all the neighboring vehicles is determined as the cluster head; Generate an access request for the vehicle; and send the access request to the cluster head; wherein the access request is used to obtain a resource scheduling table; The cluster head sends a resource scheduling table; and the cluster head sends a resource scheduling table for communication.

8. A vehicle-to-vehicle communication resource scheduling device, characterized in that, include: A construction module is used to construct a neighbor status table for the current vehicle; wherein, the neighbor status table includes the relative operating status between at least one neighbor vehicle of the current vehicle and the current vehicle; the neighbor vehicle is a vehicle that is within the maximum direct connection range of the current vehicle and whose signal-to-noise ratio of the signal corresponding to the discovered beacon is higher than a preset minimum communication threshold; The first generation module is used to generate a communication graph and a conflict graph between the current vehicle and each of the neighboring vehicles based on the neighbor status table; wherein, the communication graph includes communication links between the current vehicle and each of the neighboring vehicles; and the conflict graph represents the communication conflict situation between each of the communication links. The determination module is used to determine the cluster head capability weight of the current vehicle based on the communication graph; and to determine the cluster head capability weight of the neighboring vehicles; wherein the cluster head capability weight characterizes the vehicle's computing power and the connectivity and stability of the communication connection; The second generation module is used to determine the current vehicle as a cluster head if it is determined that the cluster head capability weight of the current vehicle is greater than the cluster head capability weight of each of the neighboring vehicles; and to generate a resource scheduling table between the current vehicle and each of the neighboring vehicles according to the conflict graph; wherein the resource scheduling table is used to allocate communication resources to each of the neighboring vehicles. The step of generating a communication graph and a conflict graph between the current vehicle and each of the neighboring vehicles based on the neighbor status table includes: Based on the neighbor status table, a local perception topology is generated between the current vehicle and each of the neighboring vehicles; wherein, the local perception topology represents the topological connection relationship between each vehicle; Based on the local perception topology, a communication graph and a conflict graph are generated between the current vehicle and each of the neighboring vehicles; The step of generating a communication graph and a conflict graph between the current vehicle and each of its neighboring vehicles based on the local sensing topology includes: Based on the local perception topology, a communication graph is generated between the current vehicle and each of the neighboring vehicles; wherein the communication graph includes a node representing the current vehicle, at least one node representing a neighboring vehicle, and at least one communication edge representing a communication link; Based on the communication graph between the current vehicle and each of the neighboring vehicles, a conflict graph is generated between the current vehicle and each of the neighboring vehicles; wherein, the conflict graph includes vertices representing each of the communication links and at least one conflict edge; the conflict edge is determined based on two vertices meeting a communication conflict condition; the communication conflict condition includes that the signal-to-interference-plus-noise ratio (SIR) of the signal received by the receiver of the second vertex is less than a preset minimum reception threshold under communication interference from the transmitter of the first vertex of the two vertices; The step of determining the cluster head capability weight of the current vehicle based on the communication graph, and determining the cluster head capability weight of the neighboring vehicles, includes: The stability weight of the current vehicle is determined based on the relative speed between the current vehicle and each of its neighboring vehicles; wherein the stability weight characterizes the communication connection stability of the vehicle. Based on the degree information of the current vehicle, the connectivity weight of the current vehicle is determined; wherein, the degree information represents the total number of neighboring vehicles connected to the current vehicle in the communication graph; and the connectivity weight represents the vehicle's communication coverage and management capabilities. Based on the current vehicle's computing power and energy information, the resource weight of the current vehicle is determined; wherein, the resource weight represents the vehicle's ability to schedule and execute computing resources. The cluster head capability weight of the current vehicle is determined based on the stability weight, the connectivity weight, and the resource weight; the step of generating a resource scheduling table between the current vehicle and each of its neighboring vehicles based on the conflict graph includes: Based on the communication graph and the conflict graph, the current vehicle and each of the neighboring vehicles are divided to obtain at least one maximum independent set; wherein the communication links between the vehicles in the maximum independent set do not interfere with each other in physical space. Based on the constraints of the at least one maximum independent set and the communication demand information between the current vehicle and each of the neighboring vehicles, a resource scheduling table is generated between the current vehicle and each of the neighboring vehicles; wherein, the constraints include not allocating resources in the same time slot and resources in the same frequency to conflicting communication links.

9. An electronic device, characterized in that, include: Memory and processor; The memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A vehicle, characterized in that, It includes a vehicle body and an electronic device as described in claim 9 disposed in the vehicle body.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

12. A computer program product, characterized in that, The computer program product includes a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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