Wireless communication method and system between unmanned vehicles

Abstract

The present application relates to the field of wireless communication technology, and specifically to a wireless communication method and system for unmanned vehicles, the method comprising: determining the communication index between a central vehicle and each of its target vehicles at each moment; determining an adjustment coefficient for the next cycle based on the total communication switching frequency of the central vehicle in the preset current cycle, and the difference between the communication index between the central vehicle and all of its target vehicles at each moment and the maximum communication index, and determining an evaluation threshold for the next cycle in combination with the difference between the evaluation threshold of the current cycle and the maximum value of all communication indexes in the cycle; performing communication switching between the central vehicle and its target vehicles in the next cycle based on the evaluation threshold of the next cycle. The present application improves the communication quality between unmanned vehicles by reducing the impact of multipath interference and high communication switching frequency on communication quality.

Description

Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a wireless communication method and system between unmanned vehicles. Background Art

[0002] The Internet of Vehicles (IoV), a large-scale network, adheres to specific communication protocols and data exchange standards. It enables intelligent traffic management, intelligent dynamic information services, and intelligent vehicle control through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication. Autonomous vehicles utilize the IoV for wireless communication, ensuring timely and reliable information transmission. Therefore, the quality of communication within the IoV directly impacts the safety of autonomous vehicles.

[0003] V2V communication in the connected vehicle network enables the sharing and exchange of information such as vehicle and road conditions between autonomous vehicles without the assistance of infrastructure, effectively avoiding the interruptions in V2I communication caused by the fixed, decentralized distribution of infrastructure. Because V2V communication is constantly changing due to the driving environment of autonomous vehicles, autonomous vehicles need to switch between different vehicles to ensure communication quality. Currently, the switching strategies for V2V communication in connected vehicles lack the accuracy to estimate the impact of multi-source data on communication quality in the driving environment, resulting in reduced effectiveness of switching decisions and, in turn, a decline in the quality of wireless communications between autonomous vehicles. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of this application is to provide a wireless communication method and system for unmanned vehicles. The technical solutions adopted are as follows:

[0005] In a first aspect, an embodiment of the present application provides a wireless communication method between unmanned vehicles, the method comprising the following steps:

[0006] S1: Construct a neighborhood with the current unmanned vehicle as the center. The current unmanned vehicle is recorded as the center vehicle, and the unmanned vehicles that have established V2V communication with the center vehicle are recorded as target vehicles. The volume and position of all obstacles in the neighborhood, the number of V2V communication handoffs of the center vehicle, and all class communication parameters of each target vehicle are obtained in real time.

[0007] S2: Based on the communication status between the central vehicle and its target vehicle, the evaluation threshold for communication switching between the central vehicle and its target vehicle is iteratively adjusted. The adjustment process is as follows:

[0008] Based on the distances from the center vehicle to each target vehicle and all obstacles at each moment, as well as the volume of each obstacle, the shape parameter adjustment ratio is determined to determine the shape parameters. Combined with the channel model, the signal-to-interference ratio between the center vehicle and its target vehicles at each moment is obtained.

[0009] At each moment and within a preset time period before it, the dispersion of the signal-to-interference ratio between the central vehicle and each of its target vehicles, as well as the dispersion of each type of communication parameter of each target vehicle, are analyzed to determine the concentration degree. Furthermore, the communication index between the central vehicle and each of its target vehicles at each moment is determined by combining the degree of confusion of the signal-to-interference ratio between the central vehicle and all of its target vehicles at each moment, as well as the degree of confusion of each type of communication parameter among all of its target vehicles.

[0010] Based on the total communication switching frequency of the central vehicle in the preset current cycle and the difference in the maximum communication index between the central vehicle and all its target vehicles at each moment, the adjustment coefficient of the evaluation threshold in the next cycle is determined, and the evaluation threshold for the next cycle is determined in combination with the difference between the evaluation threshold of the current cycle and the maximum value of all communication indices in the current cycle;

[0011] S3: Based on the evaluation threshold of the next cycle, communication switching is performed between the center vehicle and its target vehicle in the next cycle.

[0012] Preferably, the expression for the adjustment ratio of the shape parameter is: Where, represents the adjustment ratio of the shape parameters between the center vehicle and its target vehicle k at time t; represents the distance from the center vehicle to the target vehicle k at time t; 、 They represent the distance from obstacle n to the center vehicle and the distance from obstacle n to the target vehicle k in the neighborhood of the center vehicle at time t respectively; represents the volume of the nth obstacle in the neighborhood of the central vehicle at time t; represents the number of all obstacles in the neighborhood of the central vehicle at time t; norm() represents the normalization function.

[0013] Preferably, the method for determining the shape parameters includes:

[0014] The shape parameter between the center vehicle and its target vehicle k at time t The expression is: Where, , S represent a preset first value and a preset second value respectively, wherein the preset first value is greater than the preset second value.

[0015] Preferably, the method for obtaining the signal-to-interference ratio between the central vehicle and each of its target vehicles at each moment is:

[0016] At each moment, the communication transmission power of all types of communication parameters of each target vehicle is used as the scale parameter of the channel model. Among them, the shape parameter between the central vehicle and its target vehicles at each moment is used as the shape parameter of the channel model. The received power-probability density function of the transmitted signal received by the central vehicle from each target vehicle in the channel model is obtained. The product of all received powers and corresponding probabilities in the received power-probability density function is taken as the received signal power of the central vehicle receiving each target vehicle;

[0017] The signal-to-interference ratio (SIR) between the central vehicle and its target signal k is calculated by dividing the received signal power of the central vehicle receiving target signal k by the sum of the received signal powers of the central vehicle and all other target signals except target signal k. This ratio is then used as the SIR between the central vehicle and its target signal k. This SIR between the central vehicle and each of its target signals is then calculated by traversing all target signals.

[0018] Preferably, the concentration is determined as follows:

[0019] The signal-to-interference ratio between the central vehicle and its target vehicles, as well as all types of communication parameters of each target vehicle, are collectively referred to as the parameters of each target vehicle. The inverse of the standard deviation of each type of parameter of the target vehicle at each moment and within the preset time period before that is calculated as the concentration of each type of parameter.

[0020] Preferably, the expression of the communication index between the central vehicle and each of its target vehicles at each moment is: Where, represents the communication index between the center vehicle and its target vehicle k at time t; The total number of categories representing all class parameters of target vehicle k; represents the entropy weight of the s-th type parameters of all target vehicles at time t; The normalized value of the s-th parameter of target vehicle k at time t; represents the concentration of the s-th type of parameters of target vehicle k at time t; Indicates a preset constant greater than 0.

[0021] Preferably, the expression of the adjustment coefficient of the next cycle is: Where, represents the adjustment coefficient for the next cycle; Q represents the total number of communication switching times of the central vehicle in the current cycle; represents the communication index between the center vehicle and its target vehicle v at time u in the current cycle; It represents the maximum value of the communication index between the central vehicle and all its target vehicles at time u in the current cycle; represents the total number of target vehicles under the central vehicle at time u in the current cycle; Indicates the total duration of the current cycle; represents an exponential function with a natural constant as the base; norm[ ] represents a normalization function.

[0022] Preferably, the evaluation threshold value of the next cycle is expressed as: Where, 、 Respectively represent the evaluation thresholds for the next cycle and the current cycle, wherein the initial evaluation threshold is a preset third value; It represents the maximum value of the communication index between the center vehicle and all its target vehicles at all times in the current cycle.

[0023] Preferably, the switching of communication between the central vehicle and all its target vehicles in the next cycle includes:

[0024] Calculate the cumulative sum of the communication indexes between the central vehicle and all its target vehicles at each moment in the next cycle, and record it as the communication sum value; take the target vehicle whose communication index between the central vehicle and all its target vehicles is greater than the evaluation threshold of the next cycle as the feature vehicle, and calculate the sum of the communication indexes between the central vehicle and all its feature vehicles at each moment in the next cycle;

[0025] In the next cycle, if the sum of the communication indices is continuously greater than the communication sum value for a time greater than a preset time threshold, the V2V communication connection between the center vehicle and the remaining target vehicles other than the characteristic vehicle is disconnected. In a second aspect, an embodiment of the present application also provides a wireless communication system for unmanned vehicles, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, the steps of any one of the above-mentioned methods for wireless communication between unmanned vehicles are implemented.

[0026] This application has at least the following beneficial effects:

[0027] This application obtains multi-source data that affects the quality of V2V communication based on the signals collected in real time by the sensor system of the unmanned vehicle and the signals received from the vehicle network, and further estimates the impact of the current driving environment on the V2V communication of the unmanned vehicle based on this data, so as to avoid the V2V communication between vehicles from switching to a communication link with greater signal interference and fading, so as to improve the communication quality after switching; further, by analyzing the time-varying characteristics of the V2V communication of the unmanned vehicle, an evaluation threshold is constructed to adjust the switching strategy of the wireless communication between vehicles, so as to avoid frequent switching caused by the rapid change of the vehicle communication status, and at the same time ensure that the unmanned vehicle is less subject to signal interference and fading after switching, thereby improving the effectiveness of the switching decision and improving the communication quality between unmanned vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present application or the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0029] Figure 1 A flowchart of a method for wireless communication between unmanned vehicles provided in accordance with an embodiment of the present application;

[0030] Figure 2 A schematic diagram of the evaluation threshold acquisition process provided for one embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to further illustrate the technical means and effects adopted by this application to achieve the predetermined invention objectives, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail the specific implementation methods, structures, features and effects of the wireless communication method and system for unmanned vehicles proposed in this application. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics of one or more embodiments may be combined in any suitable form.

[0032] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0033] The specific solutions of the wireless communication method and system between unmanned vehicles provided by this application are described in detail below with reference to the accompanying drawings.

[0034] See also Figure 1, which shows a flowchart of a wireless communication method between unmanned vehicles provided by an embodiment of the present application, the method comprising the following steps:

[0035] S1: Construct a neighborhood with the current unmanned vehicle as the center. The current unmanned vehicle is recorded as the center vehicle, and the unmanned vehicles that have established V2V communication with the center vehicle are recorded as target vehicles. The volume and position of all obstacles in the neighborhood, the number of V2V communication handoffs of the center vehicle, and all class communication parameters of each target vehicle are obtained in real time.

[0036] The high-speed movement of unmanned vehicles and the complex urban road conditions, on the one hand, lead to differences in the throughput and number of communication connections of V2V communications among different vehicles. On the other hand, the degree of signal attenuation in the channels between unmanned vehicles varies rapidly, resulting in the communication quality of unmanned vehicle V2V communications having strong time-varying properties.

[0037] Unmanned vehicles acquire multi-source data that affects the quality of wireless communication between unmanned vehicles based on signals collected by their onboard sensors and received from the Internet of Vehicles. Unmanned vehicle sensor systems have a wide variety of sensors, with various types and methods of collecting signals. This embodiment targets unmanned vehicles equipped with lidar sensors, and acquires multi-source data specifically as follows:

[0038] A neighborhood is constructed with the current unmanned vehicle as the center and R as the radius. The current unmanned vehicle is recorded as the center vehicle. The lidar sensor is used to obtain the point cloud data within the neighborhood of the center vehicle, and the target detection algorithm is used to obtain the position and number of obstacles in the point cloud data.

[0039] It should be noted that there are many commonly used target detection algorithms. The Complex-YOLO algorithm is used in this embodiment. In actual application, as other implementation methods, implementers can also use other target detection algorithms based on specific circumstances.

[0040] Among them, the Complex-YOLO algorithm is a well-known technology, and its specific principle is not repeated here.

[0041] It should be noted that the value of the neighborhood radius R is set manually. In this embodiment, the value of the neighborhood radius R is 150m. In actual application, the implementer can also set it by himself based on the specific situation. This embodiment does not impose any special restrictions.

[0042] Furthermore, based on the identified obstacle point cloud data, triangulation is used to determine the distance between the vehicle and the obstacle, while a point cloud processing algorithm is used to measure the obstacle size. Specifically, in this embodiment, a minimum bounding box is used to fit the obstacle point cloud, and the volume of the obstacle is the volume of its minimum bounding box.

[0043] Among them, the triangulation method and the minimum bounding box are both well-known technologies, and their specific principles are not described in detail here.

[0044] Furthermore, the unmanned vehicle that conducts V2V communication with the central vehicle is recorded as the target vehicle, and all types of communication parameters of the target vehicle and the number of V2V communication switching times of the central vehicle are collected in real time. In this embodiment, all types of communication parameters include: the signal transmission power of the target vehicle, the switching success rate, the throughput, and the number of connections.

[0045] It should be noted that the relevant data of obstacles in the vicinity of the central vehicle and the acquisition of all types of communication parameters of the target vehicle of the central vehicle are synchronized in real time, and the data acquisition frequency is f. In this embodiment, the data acquisition frequency f is 10 Hz. In actual application, as other implementation methods, the implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0046] S2: Iteratively adjust the evaluation threshold of the communication switching between the central vehicle and its target vehicle based on the communication status between the central vehicle and its target vehicle.

[0047] S201: Based on the distance from the central vehicle to each target vehicle and all obstacles at each moment, as well as the volume of each obstacle, determine the adjustment ratio of the shape parameters to determine the shape parameters. In combination with the channel model, obtain the signal-to-interference ratio between the central vehicle and its target vehicles at each moment.

[0048] Changes in the number, location, and size of obstacles in the vicinity of autonomous vehicles can directly or indirectly affect changes in signal propagation characteristics, thereby reflecting the time-varying characteristics of the V2V wireless communication channel. Specifically, a large number of vehicles means high communication demand, which increases the congestion of the communication channel, leading to increased signal interference and reduced communication quality. The closer the distance between vehicles, the less signal attenuation and the higher the communication quality. The size of vehicles and obstacles directly affects the signal transmission path and strength. Larger vehicles may block the signal propagation path, and in dense urban environments, other types of obstacles such as buildings and trees can also block the signal, affecting communication quality.

[0049] In the driving environment of autonomous vehicles, the path of V2V communication signals from transmitter to receiver is often not a straight line, but rather undergoes multiple reflections, diffractions, and scattering. This multipath propagation causes the received signal amplitude to vary rapidly, resulting in typical Rayleigh fading or, more generally, Nakagami fading.

[0050] To accurately determine the extent to which wireless communication signals between unmanned vehicles are affected by the surrounding driving environment, this embodiment uses the Nakagami-m channel model to reflect signal fading in wireless communications and adjusts the parameters in the channel model in real time based on changes in the driving environment. Specifically, when there are many and large obstacles between unmanned vehicles, signals primarily reach the receiver via diffraction and reflection. The more severe the signal fading, the smaller the shape parameter setting.

[0051] Based on the above analysis, to reduce the error in estimating signal propagation characteristics using fixed shape parameters in a time-varying driving environment, this embodiment determines the shape parameter adjustment ratio based on the distance from the center vehicle to each target vehicle and all obstacles at each moment, as well as the volume of each obstacle. Specifically, the shape parameters are:

[0052] Adjustment ratio of the shape parameters between the center vehicle and its target vehicle k at time t The expression is: Where, represents the distance from the center vehicle to the target vehicle k at time t; 、 They represent the distance from obstacle n to the center vehicle and the distance from obstacle n to the target vehicle k in the neighborhood of the center vehicle at time t respectively; represents the volume of the nth obstacle in the neighborhood of the central vehicle at time t; represents the number of all obstacles in the neighborhood of the central vehicle at time t; norm() represents the normalization function.

[0053] According to the adjustment ratio of the shape parameters between the center vehicle and its target vehicle at the current moment, it can be understood that the closer the distance between the center vehicle and the target vehicle, the more obstacles there are between the center vehicle and the target vehicle, and the closer the obstacles are to the center vehicle and the target vehicle, the greater the possibility of signal fading. At this time, the shape parameter should be reduced. Therefore, the shape parameter is reduced by reducing the adjustment ratio.

[0054] Furthermore, based on the adjustment ratio of the shape parameters, the shape parameters are adjusted. The specific process is as follows:

[0055] The shape parameter between the center vehicle and its target vehicle k at time t The expression is: Where, , S represent a preset first value and a preset second value respectively, wherein the preset first value is greater than the preset second value.

[0056] It should be noted that the preset first value and the preset second value are used to represent the minimum value and the maximum value of the shape parameter in this embodiment. The values ​​of the preset first value and the preset second value are set artificially. In this embodiment, in order to prevent the shape parameter from being too large or too small, the value of the preset first value is 2 and the value of the preset second value is 7. The implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0057] Based on the shape parameters between the center vehicle and its target vehicles at each moment, it can be understood that the greater the possibility of multipath interference in the V2V communication between the center vehicle and the target vehicles, the smaller the adjustment ratio is, the smaller the shape parameters are, and the channel estimation error is reduced.

[0058] Furthermore, based on the shape parameters, the Nakagami-m channel model is used to determine the signal-to-interference ratio between the central vehicle and each of its target vehicles at each moment, specifically:

[0059] At each moment, the communication transmission power of all types of communication parameters of each target vehicle is used as the scale parameter of the Nakagami-m channel model. Among them, the shape parameter between the central vehicle and its target vehicles at each moment is used as the shape parameter of the Nakagami-m channel model. The received power-probability density function of the transmitted signal received by the central vehicle from each target vehicle in the Nakagami-m channel model is obtained. The product of all received powers and corresponding probabilities in the received power-probability density function is taken as the received signal power of the central vehicle receiving each target vehicle;

[0060] The signal-to-interference ratio (SIR) between the central vehicle and its target signal k is calculated by dividing the received signal power of the central vehicle by the sum of the received signal powers of the central vehicle and all target signals except target signal k. The obtained ratio is then traversed over all target signals to obtain the SIR between the central vehicle and each of its target signals. This SIR is used to characterize the communication quality between the central vehicle and its target vehicles during its driving process. The smaller the SIR, the better the communication quality between the central vehicle and its target vehicles, and the greater the impact of environmental interference on its V2V communication.

[0061] So far, by analyzing the interference of multipath effect channel estimation, the signal-to-interference ratio between the center vehicle and the target vehicle is obtained.

[0062] S202: At each moment and within a preset time period before it, analyze the degree of dispersion of the signal-to-interference ratio between the central vehicle and each of its target vehicles, as well as the degree of dispersion of each type of communication parameter of each target vehicle, to determine the concentration. Combined with the degree of confusion of the signal-to-interference ratio between the central vehicle and all of its target vehicles at each moment, as well as the degree of confusion of all target vehicles regarding each type of communication parameter, determine the communication index between the central vehicle and each of its target vehicles at each moment.

[0063] The switching success rate, throughput, and number of connections of the V2V communication of unmanned vehicles reflect the performance of unmanned vehicles in the current V2V communication of the Internet of Vehicles. The switching success rate reflects the stability of communication, the throughput reflects the speed of data transmission during the communication process, and the number of connections shows the utilization of communication resources.

[0064] Therefore, by analyzing the changes in various communication parameters received by the central vehicle from its target vehicles and combining them with the signal-to-interference ratio (SIR) between the central vehicle and the target vehicles, the communication index between the central vehicle and each target vehicle is determined to judge the excellence of the communication quality between the central vehicle and the target vehicles. The specific process is as follows:

[0065] (1) At each moment and within the preset time period before it, the dispersion of the signal-to-interference ratio between the central vehicle and its target vehicles, as well as the dispersion of each parameter of each target vehicle, are analyzed to determine the concentration, specifically:

[0066] The signal-to-interference ratio between the central vehicle and its target vehicles obtained in S202 and all the target vehicle communication parameters are collectively referred to as the target vehicle parameters. The inverse of the standard deviation of each type of target vehicle parameter at each moment and within a preset time period before is calculated as the concentration of each type of parameter. The larger the standard deviation of the current type of parameter, the more drastic the change in this type of parameter before the current moment. The impact of this type of parameter on the switching decision should be reduced in the future to avoid frequent switching of V2V communication between unmanned vehicles.

[0067] (2) Based on the concentration, and in combination with the degree of confusion of the signal-to-interference ratio between the central vehicle and all its target vehicles at each moment, and the degree of confusion of all target vehicles with respect to each type of communication parameter, the communication index between the central vehicle and each of its target vehicles at each moment is determined, specifically:

[0068] In the above content, the signal-to-interference ratio (SIR) between the central vehicle and its target vehicles and all types of communication parameters of the target vehicles are collectively referred to as target vehicle parameters. Therefore, in the following content, the term "parameter" will be used to directly replace the term "SIR" and "all types of communication parameters."

[0069] As an implementation method, in this embodiment, the communication index between the center vehicle and its target vehicle k at time t is The expression is: Where, The total number of categories representing all class parameters of target vehicle k; represents the entropy weight of the s-th type parameters of all target vehicles at time t; The normalized value of the s-th parameter of target vehicle k at time t; represents the concentration of the s-th type of parameters of target vehicle k at time t; Indicates a constant greater than 0 to prevent the denominator from being 0. The value of is set artificially. The value of is 0.01. Under the premise of ensuring that the denominator is not 0 and does not excessively affect the calculation results, the implementer can also set it according to the specific requirements. This embodiment does not impose any special restrictions.

[0070] It is additionally noted that the calculation process of entropy weight is a well-known technology. In this embodiment, the entropy weight TOPSIS algorithm is used to calculate the entropy weights of various parameters, and its specific principle will not be repeated here.

[0071] According to the communication index between the central vehicle and its target vehicles at each moment, it can be understood that if the entropy weight of the current type of parameter is smaller, the change of this type of parameter is more stable, indicating that the communication condition between the current central vehicle and its target vehicles is good, and the greater the concentration, the more stable the change of this type of parameter before the current moment, indicating that this type of parameter has greater reference significance for the communication quality evaluation between unmanned vehicles, the better the current communication quality, and the larger the value of this type of parameter at the current moment within a certain range, the better the communication quality, and the larger the final communication index;

[0072] On the contrary, if the entropy weight of the current class parameter is larger, it means that the change of this class parameter is more unstable, indicating that the communication condition between the current center vehicle and its target vehicle is poor, and the smaller the concentration, the more drastic the change of this class parameter before the current moment, indicating that the current communication quality is poor, and the smaller the final communication index is, the worse the communication quality between the center vehicle and its target vehicle at the current moment.

[0073] At this point, by analyzing the stability of different types of communication parameters and the signal-to-interference ratio, the communication index between the center vehicle and the target vehicle is obtained.

[0074] S203: Based on the total communication switching frequency of the central vehicle in the preset current cycle, and the difference in the maximum communication index between the central vehicle and all its target vehicles at each moment, the adjustment coefficient of the evaluation threshold in the next cycle is determined, and the evaluation threshold for the next cycle is determined in combination with the difference between the evaluation threshold of the current cycle and the maximum value of all communication indices in the current cycle.

[0075] Since the communication status of different vehicles changes rapidly while driving on the road, using a fixed communication switching strategy can easily lead to frequent communication switching between vehicles, resulting in reduced effectiveness of switching decisions. Therefore, this embodiment dynamically adjusts the evaluation threshold of the switching strategy to avoid frequent switching of V2V communication between unmanned vehicles. The specific process is as follows:

[0076] (1) Based on the total communication switching frequency of the center vehicle in the preset current cycle and the difference between the communication index of the center vehicle and its target vehicles at each moment and the maximum communication index, the adjustment coefficient for the next cycle is determined, specifically:

[0077] Adjustment factor for the next period The expression is: ;Where, Q represents the total number of communication switching times of the central vehicle in the current cycle; represents the communication index between the center vehicle and its target vehicle v at time u in the current cycle; It represents the maximum value of the communication index between the central vehicle and all its target vehicles at time u in the current cycle; represents the total number of target vehicles under the central vehicle at time u in the current cycle; Indicates the total duration of the current cycle; represents an exponential function with a natural constant as the base; norm[ ] represents a normalization function.

[0078] It should be noted that the value of the cycle length is a preset value. In this embodiment, the value of the cycle length is 30s. The implementer can also set it according to the specific situation. This embodiment does not impose any special restrictions.

[0079] According to the adjustment coefficient, it can be understood that if the number of communication switching times is smaller, the difference between the communication index and the maximum value of the communication index is smaller, which means that the communication condition between the center vehicle and the target vehicle is good. A smaller adjustment coefficient can be appropriately set to make the evaluation threshold at a smaller value, thereby reducing the frequent communication switching between unmanned vehicles.

[0080] (2) Further, based on the adjustment coefficient of the next cycle and in combination with the difference between the maximum communication quality and the evaluation threshold in the current cycle, the evaluation threshold of the next cycle is determined, specifically:

[0081] The expression of the evaluation threshold for the next cycle is: Where, 、 Respectively represent the evaluation thresholds for the next cycle and the current cycle, wherein the initial evaluation threshold is a preset third value; It represents the maximum value of the communication index between the center vehicle and all its target vehicles at all times in the current cycle.

[0082] It should be noted that if the central vehicle communicates with an unmanned vehicle in the first cycle, the initial evaluation threshold will not be considered until the cycle in which the central vehicle starts communicating. 0.8 times the maximum communication index between the central vehicle and all its target vehicles at the moment of communication will be used as the initial evaluation threshold. The implementer can also set the initial evaluation threshold based on the specific situation. This embodiment does not impose any special restrictions.

[0083] In particular, if the center vehicle does not communicate within a certain period during driving, the evaluation threshold is reset at this time, and 0.8 times the maximum communication index between the center vehicle and all its target vehicles when the center vehicle starts communicating again is used as the initial evaluation threshold for the corresponding period.

[0084] By analyzing the evaluation threshold, we can conclude that if the evaluation threshold of the current cycle is equal to the maximum value The smaller the difference, the better the communication quality between unmanned vehicles in the current cycle, and the smaller the adjustment coefficient. Therefore, the communication frequency between unmanned vehicles in the next cycle can be appropriately reduced. Therefore, the evaluation threshold of the next cycle can be appropriately reduced.

[0085] Preferably, the schematic diagram of the evaluation threshold acquisition process provided in this embodiment is as follows: Figure 2 shown.

[0086] S3: Based on the evaluation threshold of the next cycle, communication switching is performed between the center vehicle and its target vehicle in the next cycle.

[0087] The evaluation threshold is obtained according to S2. Based on the evaluation threshold, the communication switching between the center vehicle and its target vehicle is controlled. The specific process is as follows:

[0088] Calculate the cumulative sum of the communication indexes between the central vehicle and all its target vehicles at each moment in the next cycle, and record it as the communication sum value; take the target vehicle whose communication index between the central vehicle and all its target vehicles is greater than the evaluation threshold of the next cycle as the feature vehicle, and calculate the sum of the communication indexes between the central vehicle and all its feature vehicles at each moment in the next cycle;

[0089] In the next cycle, if the sum of the communication indexes is continuously greater than the communication sum value for a time greater than a preset time threshold, the V2V communication connection between the central vehicle and the remaining target vehicles except the feature vehicle is disconnected.

[0090] It should be noted that the value of the time threshold is set manually. In this embodiment, the value of the time threshold is 1s. In actual application, the implementer can also set it by himself according to the specific situation. This embodiment does not impose any special restrictions.

[0091] Based on the same inventive concept as the above method, an embodiment of the present application also provides a wireless communication system between unmanned vehicles, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, the steps of any one of the above-mentioned wireless communication methods between unmanned vehicles are implemented.

[0092] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0093] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0094] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A wireless communication method between unmanned vehicles, characterized in that: The method comprises the following steps: S1: Construct a neighborhood with the current unmanned vehicle as the center. The current unmanned vehicle is recorded as the center vehicle, and the unmanned vehicles that have established V2V communication with the center vehicle are recorded as target vehicles. The volume and position of all obstacles in the neighborhood, the number of V2V communication handoffs of the center vehicle, and all class communication parameters of each target vehicle are obtained in real time. S2: Based on the communication status between the central vehicle and its target vehicle, the evaluation threshold for communication switching between the central vehicle and its target vehicle is iteratively adjusted. The adjustment process is as follows: Calculate the adjustment ratio of the shape parameters between the center vehicle and its target vehicle k at time t , The expression is: Where, represents the distance from the center vehicle to the target vehicle k at time t; 、 They represent the distance from obstacle n to the center vehicle and the distance from obstacle n to the target vehicle k in the neighborhood of the center vehicle at time t respectively; represents the volume of the nth obstacle in the neighborhood of the central vehicle at time t; represents the number of all obstacles in the neighborhood of the central vehicle at time t; norm() represents the normalization function; Calculate the shape parameters between the center vehicle and its target vehicle k at time t , The expression is: Where, , S represent a preset first value and a preset second value respectively, wherein the preset first value is greater than the preset second value; Obtain the signal-to-interference ratio between the center vehicle and each of its target vehicles at each moment through the shape parameter, in combination with the channel model and the communication transmission power in the vehicle communication parameters; At each moment and within a preset time period before it, the dispersion of the signal-to-interference ratio between the central vehicle and each of its target vehicles, as well as the dispersion of each type of communication parameter of each target vehicle, are analyzed to determine the concentration degree. Furthermore, the communication index between the central vehicle and each of its target vehicles at each moment is determined by combining the degree of confusion of the signal-to-interference ratio between the central vehicle and all of its target vehicles at each moment, as well as the degree of confusion of each type of communication parameter among all of its target vehicles. Based on the total communication switching frequency of the central vehicle in the preset current cycle and the difference in the maximum communication index between the central vehicle and all its target vehicles at each moment, the adjustment coefficient of the evaluation threshold in the next cycle is determined, and the evaluation threshold for the next cycle is determined in combination with the difference between the evaluation threshold of the current cycle and the maximum value of all communication indices in the current cycle; S3: Based on the evaluation threshold of the next cycle, communication switching is performed between the center vehicle and its target vehicle in the next cycle.

2. The wireless communication method between unmanned vehicles according to claim 1, characterized in that: The method for obtaining the signal-to-interference ratio between the central vehicle and each of its target vehicles at each moment is: At each moment, the communication transmission power of all types of communication parameters of each target vehicle is used as the scale parameter of the channel model. Among them, the shape parameter between the central vehicle and its target vehicles at each moment is used as the shape parameter of the channel model. The received power-probability density function of the transmitted signal received by the central vehicle from each target vehicle in the channel model is obtained. The product of all received powers and corresponding probabilities in the received power-probability density function is taken as the received signal power of the central vehicle receiving each target vehicle; The signal-to-interference ratio (SIR) between the central vehicle and its target signal k is calculated by dividing the received signal power of the central vehicle receiving target signal k by the sum of the received signal powers of the central vehicle and all other target signals except target signal k. This ratio is then used as the SIR between the central vehicle and its target signal k. This SIR between the central vehicle and each of its target signals is then calculated by traversing all target signals.

3. The wireless communication method between unmanned vehicles according to claim 1, wherein: The process of determining the concentration is as follows: The signal-to-interference ratio between the central vehicle and its target vehicles, as well as all types of communication parameters of each target vehicle, are collectively referred to as the parameters of each target vehicle. The inverse of the standard deviation of each type of parameter of the target vehicle at each moment and within the preset time period before that is calculated as the concentration of each type of parameter.

4. The wireless communication method between unmanned vehicles according to claim 3, wherein: The expression of the communication index between the central vehicle and each target vehicle at each moment is: Where, represents the communication index between the center vehicle and its target vehicle k at time t; The total number of categories representing all class parameters of target vehicle k; represents the entropy weight of the s-th type parameters of all target vehicles at time t; The normalized value of the s-th parameter of target vehicle k at time t; represents the concentration of the s-th type of parameters of target vehicle k at time t; Indicates a preset constant greater than 0.

5. The wireless communication method between unmanned vehicles according to claim 1, wherein: The expression of the adjustment coefficient of the next cycle is: Where, represents the adjustment coefficient for the next cycle; Q represents the total number of communication switching times of the central vehicle in the current cycle; represents the communication index between the center vehicle and its target vehicle v at time u in the current cycle; It represents the maximum value of the communication index between the central vehicle and all its target vehicles at time u in the current cycle; represents the total number of target vehicles under the central vehicle at time u in the current cycle; Indicates the total duration of the current cycle; represents an exponential function with a natural constant as the base; norm[ ] represents a normalization function.

6. The wireless communication method between unmanned vehicles according to claim 5, characterized in that: The expression of the evaluation threshold of the next cycle is: Where, 、 Respectively represent the evaluation thresholds for the next cycle and the current cycle, wherein the initial evaluation threshold is a preset third value; It represents the maximum value of the communication index between the center vehicle and all its target vehicles at all times in the current cycle.

7. The wireless communication method between unmanned vehicles according to claim 1, wherein: The communication switching between the central vehicle and all its target vehicles in the next cycle includes: Calculate the cumulative sum of the communication indexes between the central vehicle and all its target vehicles at each moment in the next cycle, and record it as the communication sum value; take the target vehicle whose communication index between the central vehicle and all its target vehicles is greater than the evaluation threshold of the next cycle as the feature vehicle, and calculate the sum of the communication indexes between the central vehicle and all its feature vehicles at each moment in the next cycle; In the next cycle, if the sum of the communication indexes is continuously greater than the communication sum value for a time greater than a preset time threshold, the V2V communication connection between the central vehicle and the remaining target vehicles except the feature vehicle is disconnected.

8. A wireless communication system between unmanned vehicles, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the steps of the wireless communication method between unmanned vehicles as described in any one of claims 1 to 7 are implemented.

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