CN111314882B - Transmission mode selection method, device, computer system and readable storage medium - Google Patents
Transmission mode selection method, device, computer system and readable storage medium Download PDFInfo
- Publication number
- CN111314882B CN111314882B CN202010104280.6A CN202010104280A CN111314882B CN 111314882 B CN111314882 B CN 111314882B CN 202010104280 A CN202010104280 A CN 202010104280A CN 111314882 B CN111314882 B CN 111314882B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- index
- decision
- judgment
- weight information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
Landscapes
- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Traffic Control Systems (AREA)
Abstract
The embodiment of the disclosure discloses a transmission mode selection method, a device, a computer system and a readable storage medium, which are used for selecting an information transmission mode between vehicles or between vehicles and roads, and are characterized in that the method comprises the following steps: acquiring weight information of a vehicle judgment index; acquiring a judgment grade matrix of the vehicle judgment index; acquiring an input value of the vehicle judgment index; calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix of the vehicle judgment index; calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix; an information transmission mode is selected according to the decision value. Therefore, the mode switching frequency can be reduced, the transmission time can be reduced, the transmission efficiency can be improved, and the transmission reliability can be ensured.
Description
Technical Field
The present disclosure relates to the field of communications, and in particular, to a transmission mode selection method, apparatus, computer system, and readable storage medium.
Background
Perception, decision and control are three links of automatic driving, and the perception link is used for collecting basic information of the surrounding environment and is also the basis of automatic driving. Autonomous vehicles sense the environment through sensors, which act like the eyes of the vehicle. Sensors are classified into various types, such as a camera, an ultrasonic radar, a millimeter wave radar, and a laser radar. Various information input based on sensors, radars and cameras, and the bicycle can be automatically driven to a certain degree through artificial intelligence technical decision. However, the bicycle has great limitation, and in severe weather such as night, rainy and snowy days, foggy days and the like, in scenes such as intersections, corners and the like, the radar and the camera cannot be seen, cannot be seen clearly and cannot be seen accurately.
This requires V2X (Vehicle to Vehicle) in the internet of vehicles to communicate and provide information far beyond the current sensor sensing range. V2X can be regarded as an elongated and remote "sensor" in nature, and can acquire more information than a single vehicle can obtain through communication with surrounding vehicles, roads and infrastructures, so that the perception of the surrounding environment is greatly enhanced, and the dependence on a high-precision sensor is reduced. The 5G network has the characteristics of ultra-large bandwidth and ultra-low time delay, more and more accurate environment information can be collected and transmitted in real time, and the cloud computing capability is used for the decision of automatic driving of the vehicle.
Meanwhile, V2X includes two modes, V2V and V2I. V2V refers to information communication transmission between vehicles, and V2I refers to information communication transmission between vehicles and infrastructure, such as road side units or base stations, which are the most common way of information transmission in the internet of vehicles. How to reasonably select a communication mode concerns the realization of the vehicle networking communication with low time delay and high reliability. V2I communication is more stable and has higher transmission rate, but it needs to be performed in the area covered by the rsu or the bs, and the access of a large number of vehicles may occupy more spectrum resources and even cause congestion. The V2V communication is established between vehicles, the application range is wider, the communication is more consistent with the trend of data resource sharing in the big data era, but the transmission rate and the connection stability are slightly lower.
In addressing the present disclosure, the inventors discovered that communication mode selection between V2V and V2I is required.
Disclosure of Invention
In order to at least partially solve the related art problems, embodiments of the present disclosure provide a transmission mode selection method, apparatus, computer system, and readable storage medium.
In a first aspect, an embodiment of the present disclosure provides a transmission mode selection method for selecting a vehicle or a vehicle-road information transmission mode, including:
acquiring weight information of a vehicle judgment index;
acquiring a judgment grade matrix of the vehicle judgment index;
acquiring an input value of the vehicle judgment index;
calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix of the vehicle judgment index;
calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix;
an information transmission mode is selected according to the decision value.
With reference to the first aspect, in a first implementation manner of the first aspect, the vehicle determination index includes: a vehicle position; and/or type of information; and/or vehicle caching probability; and/or resource load.
With reference to the first aspect, the present disclosure provides in a second implementation manner of the first aspect, where the vehicle determination index includes a primary determination index and a secondary determination index.
With reference to the first aspect, in a third implementation manner of the first aspect, the obtaining weight information of the vehicle determination index includes:
acquiring mutual weight information of vehicle judgment indexes;
and calculating self-weight information of the vehicle judgment index according to the mutual weight information of the vehicle judgment index.
With reference to the third implementation manner of the first aspect, in a fourth implementation manner of the first aspect, the obtaining weight information of the vehicle determination index further includes:
and carrying out consistency check on the self-weight information of the vehicle judgment index.
With reference to the first aspect, in a fifth implementation manner of the first aspect, the calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix includes:
calculating a decision value vector according to the weight information of the vehicle decision index and the fuzzy relation matrix;
and calculating the average value of the elements of the decision value vector to obtain the decision value.
With reference to the first aspect, in a sixth implementation manner of the first aspect, the selecting an information transmission mode according to the decision value includes:
selecting an inter-vehicle transmission mode when the decision value is greater than a first threshold value; and selecting a transmission mode between the vehicle and the road when the judgment value is less than or equal to the first threshold value.
In a second aspect, an embodiment of the present disclosure provides a transmission mode selection device for selecting a vehicle or a vehicle-road information transmission mode, including:
a weight information acquisition module configured to acquire weight information of the vehicle determination index;
a decision level matrix acquisition module configured to acquire a decision level matrix of the vehicle decision index;
an input value acquisition module configured to acquire an input value of the vehicle determination index;
a fuzzy relation matrix calculation module configured to calculate a fuzzy relation matrix according to the input value of the vehicle decision index and the decision level matrix of the vehicle decision index;
a decision value calculation module configured to calculate a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix;
a transmission mode selection module configured to select an information transmission mode according to the decision value.
With reference to the second aspect, in a first implementation manner of the second aspect, the vehicle determination index includes: a vehicle position; and/or type of information; and/or vehicle caching probability; and/or resource load.
With reference to the second aspect, in a second implementation manner of the second aspect, the vehicle determination index includes a primary determination index and a secondary determination index.
With reference to the second aspect, in a third implementation manner of the second aspect, the weight information obtaining module is further configured to:
acquiring mutual weight information of vehicle judgment indexes;
and calculating self-weight information of the vehicle judgment index according to the mutual weight information of the vehicle judgment index.
With reference to the third implementation manner of the second aspect, in a fourth implementation manner of the second aspect, the weight information obtaining module is further configured to further include:
and carrying out consistency check on the self-weight information of the vehicle judgment index.
With reference to the second aspect, in a fifth implementation manner of the second aspect, the decision value calculation module is further configured to:
calculating a decision value vector according to the weight information of the vehicle decision index and the fuzzy relation matrix;
and calculating the average value of the elements of the decision value vector to obtain the decision value.
With reference to the second aspect, in a sixth implementation manner of the second aspect, the transmission mode selection module is further configured to:
selecting an inter-vehicle transmission mode when the decision value is greater than a first threshold value; and selecting a transmission mode between the vehicle and the road when the judgment value is less than or equal to the first threshold value.
In a third aspect, the disclosed embodiments provide a computer system comprising a memory and a processor; wherein the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method according to the first aspect to the sixth implementation manner of the first aspect.
In a fourth aspect, the present disclosure provides a readable storage medium, on which computer instructions are stored, and when executed by a processor, the computer instructions implement the method according to the first to sixth implementation manners of the first aspect.
The technical scheme provided by the embodiment of the disclosure can have the following beneficial effects:
according to the technical scheme provided by the embodiment of the disclosure, the weight information of the vehicle judgment index is obtained; acquiring a judgment grade matrix of the vehicle judgment index; acquiring an input value of the vehicle judgment index; calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix of the vehicle judgment index; calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix; and selecting an information transmission mode according to the decision value, thereby reducing mode switching frequency, reducing transmission time, improving transmission efficiency and ensuring transmission reliability.
According to the technical scheme provided by the embodiment of the disclosure, the vehicle judgment index comprises: a vehicle position; and/or type of information; and/or vehicle caching probability; and/or resource load, to select the information transfer mode by reasonably selecting the vehicle decision index.
According to the technical scheme provided by the embodiment of the disclosure, the vehicle judgment indexes comprise primary judgment indexes and secondary judgment indexes, so that the vehicle judgment indexes are refined, and the information transmission mode is accurately selected.
According to the technical scheme provided by the embodiment of the disclosure, the obtaining of the weight information of the vehicle judgment index comprises: acquiring mutual weight information of vehicle judgment indexes; and calculating self-weight information of the vehicle judgment indexes according to the mutual weight information of the vehicle judgment indexes, thereby obtaining the independent weight information of each vehicle judgment index and being beneficial to accurately selecting an information transmission mode.
According to the technical scheme provided by the embodiment of the disclosure, the obtaining of the weight information of the vehicle judgment index further comprises: and carrying out consistency check on the self-weight information of the vehicle judgment index so as to ensure that the self-weight information has acceptable consistency.
According to the technical scheme provided by the embodiment of the disclosure, calculating the decision value by the weight information according to the vehicle decision index and the fuzzy relation matrix comprises: calculating a decision value vector according to the weight information of the vehicle decision index and the fuzzy relation matrix; and calculating the average value of the elements of the decision value vector to obtain the decision value, thereby obtaining a more accurate decision value.
According to the technical scheme provided by the embodiment of the present disclosure, selecting an information transmission mode according to the decision value includes: selecting an inter-vehicle transmission mode when the decision value is greater than a first threshold value; and when the judgment value is less than or equal to the first threshold value, selecting a transmission mode between the vehicle and the road, so that a proper transmission mode is selected, the mode switching frequency is reduced, the transmission time is shortened, the transmission efficiency is improved, and the transmission reliability is ensured.
According to the technical scheme provided by the embodiment of the disclosure, the weight information acquisition module is configured to acquire the weight information of the vehicle judgment index; a decision level matrix acquisition module configured to acquire a decision level matrix of the vehicle decision index; an input value acquisition module configured to acquire an input value of the vehicle determination index; a fuzzy relation matrix calculation module configured to calculate a fuzzy relation matrix according to the input value of the vehicle decision index and the decision level matrix of the vehicle decision index; a decision value calculation module configured to calculate a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix; and the transmission mode selection module is configured to select the information transmission mode according to the decision value, so that the mode switching frequency is reduced, the transmission time is reduced, the transmission efficiency is improved, and the transmission reliability is ensured.
Drawings
Other objects and advantages of the present disclosure will become more apparent from the following detailed description of non-limiting embodiments thereof, when taken in conjunction with the accompanying drawings. In the drawings:
fig. 1 shows a flow diagram of a transmission mode selection method according to an embodiment of the present disclosure;
FIG. 2 is a flowchart showing the acquisition of weight information of a vehicle determination index according to the embodiment shown in FIG. 1;
FIG. 3 shows a flowchart according to another embodiment of obtaining weight information of a vehicle decision index in the embodiment shown in FIG. 1;
FIG. 4 is a flowchart showing calculation of a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix in the embodiment shown in FIG. 1;
fig. 5 is a block diagram illustrating a structure of a transmission mode selection apparatus according to an embodiment of the present disclosure;
FIG. 6 shows a block diagram of a computer system, according to an embodiment of the present disclosure;
fig. 7 illustrates a block diagram of a computer architecture suitable for a transmission mode selection method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. Also, for the sake of clarity, parts not relevant to the description of the exemplary embodiments are omitted in the drawings.
In the present disclosure, it is to be understood that terms such as "including" or "having," etc., are intended to indicate the presence of the disclosed features, numbers, steps, behaviors, components, parts, or combinations thereof, and are not intended to preclude the possibility that one or more other features, numbers, steps, behaviors, components, parts, or combinations thereof may be present or added.
It should be further noted that the embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
In addressing the present disclosure, the inventors discovered that communication mode selection between V2V and V2I is required.
According to the technical scheme provided by the embodiment of the disclosure, the weight information of the vehicle judgment index is obtained; acquiring a judgment grade matrix of the vehicle judgment index; acquiring an input value of the vehicle judgment index; calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix of the vehicle judgment index; calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix; and selecting an information transmission mode according to the decision value, thereby reducing mode switching frequency, reducing transmission time, improving transmission efficiency and ensuring transmission reliability.
Fig. 1 shows a flow chart of a transmission mode selection method according to an embodiment of the present disclosure. As shown in fig. 1, the transmission mode selection method includes the steps of: s110, S120, S130, S140, S150 and S160.
In step S110, weight information of the vehicle determination index is acquired.
In step S120, a decision level matrix of the vehicle decision index is acquired.
In step S130, an input value of a vehicle determination index is acquired.
In step S140, a fuzzy relation matrix is calculated based on the input value of the vehicle decision index and the decision level matrix of the vehicle decision index.
In step S150, a decision value is calculated from the weight information of the vehicle decision index and the fuzzy relation matrix.
In step S160, an information transmission mode is selected according to the decision value.
And quantitatively measuring the importance of the vehicle judgment index by acquiring the weight information and the judgment level matrix of the vehicle judgment index. The input value of the vehicle judgment index is measured according to the vehicle judgment index according to the current state of the vehicle. And calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix to obtain the normalized evaluation of the input value of the vehicle judgment index. And calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix, so that the importance and the current value of the vehicle decision index are integrated in the decision value. And finally, selecting an information transmission mode according to the judgment value, and determining that the information of the vehicle is transmitted through a V2V or V2I mode, so that the mode switching frequency is reduced, the transmission time is shortened, the transmission efficiency is improved, and the transmission reliability is ensured.
In one embodiment of the present disclosure, criteria that directly affect the V2V and V2I transmission mode selections may be selected as vehicle decision criteria, such as vehicle location; and/or type of information; and/or vehicle caching probability; and/or resource load. The vehicle position can be the distance between the vehicle and the first base station when the vehicle is positioned between two base stations on the roadside; the information type can be the proportion of safety information in the information to be transmitted, and the safety information can be road condition information, collision and avoidance information and speed information; the vehicle cache probability can be the probability that the vehicle stores information needed by other vehicles and wishes to share and transmit the information; the resource load may be a proportion of the resources of the V2V channel resources that are already occupied. Through reasonable selection of the vehicle judgment index, the selection of a proper transmission mode in V2V and V2I can be ensured.
According to the technical scheme provided by the embodiment of the disclosure, the vehicle judgment indexes comprise: a vehicle position; and/or type of information; and/or vehicle caching probability; and/or resource load, to select the information transfer mode by reasonably selecting the vehicle decision index.
In one embodiment of the present disclosure, a secondary index may be introduced under a primary index of a vehicle decision index "vehicle position, information type, vehicle cache probability, resource load", thereby making the vehicle decision index more detailed. As shown in table 1, secondary indexes "two-cell coverage overlap area" and "single-cell coverage area" are introduced under the primary index "vehicle position". When the vehicle is positioned in a single-cell coverage area, the communication between the vehicle and a base station is stable and transmission is more prone to be carried out by using a VI2 mode; when the vehicle is located in the "two-cell coverage overlap area", the communication stability between the vehicle and the base station is poor, and the vehicle is more prone to transmit by using the V2V mode. And introducing a secondary index of 'safety information' and 'other services' under the 'information type' of the primary index. The "safety information" may include information such as road condition information, collision and avoidance information, speed information, and the "remaining services" may include entertainment information such as multimedia data. The method is characterized in that secondary indexes of ≧ 80% 'and' 50% -80% 'are introduced under a primary index of' vehicle cache probability ', and the fact that the vehicle stores information needed by other vehicles is indicated, and the probability of willing to carry out information sharing transmission is ≧ 80%' and '50% -80%', and when the 'vehicle cache probability' is less than 50%, the vehicle can not store information needed by other vehicles, or does not wish to carry out information sharing, or only has sensing capability but not transmission capability, so that information transmission is not carried out. Introducing secondary indexes of more than or equal to 90 percent, 50-90 percent and less than or equal to 50 percent under the primary index of 'resource load', wherein the occupied proportion of the resources in the V2V channel resources is more than or equal to 90 percent, 50-90 percent and less than or equal to 50 percent.
TABLE 1 vehicle decision index system
According to the technical scheme provided by the embodiment of the disclosure, the vehicle judgment indexes comprise primary judgment indexes and secondary judgment indexes, so that the vehicle judgment indexes are refined, and the information transmission mode is accurately selected.
Fig. 2 shows a flowchart for acquiring weight information of a vehicle determination index according to the embodiment shown in fig. 1.
As shown in fig. 2, obtaining the weight information of the vehicle determination index includes the steps of: s210 and S220.
In step S210, mutual weight information of the vehicle determination index is acquired.
In step S220, self-weight information of the vehicle decision index is calculated from the mutual weight information of the vehicle decision index.
In one embodiment of the present disclosure, the mutual weight information of the vehicle determination indicators may be obtained in a matrix manner, for example, the mutual weight information of the primary vehicle determination indicators is obtained in a matrix manner of table 2. It is composed ofMu in1Indicating the vehicle position, mu2Indicates the type of information, mu3Indicates the vehicle buffer probability, mu4Representing the resource load, while the values of the elements in the matrix represent the importance ratios of the two primary decision indicators. For example, the value of row 2, column 1 in the matrix is 4, representing μ2And mu1Is 4. The mutual weight information of the primary decision index may be obtained through user experience, or may be obtained through a simulation mode, a test mode, or other modes.
TABLE 2 Primary vehicle decision indicator mutual weight information
In one embodiment of the present disclosure, mutual weight information of the secondary vehicle decision indicators under the primary vehicle decision indicator may also be obtained, which represents the importance ratio of the two secondary vehicle decision indicators. In Table 3,. mu.11Is the overlapping area of coverage of two cells, mu12Is a single cell coverage overlap region.
| μ1 | μ11 | μ12 |
| μ11 | 1 | 2 |
| μ12 | 1/2 | 1 |
TABLE 3 vehicle position Secondary vehicle decision index mutual weight information
In Table 4,. mu.21Is a security information, mu22Are the remaining services.
| μ2 | μ21 | μ22 |
| μ21 | 1 | 1/5 |
| μ22 | 5 | 1 |
TABLE 4 information type Secondary vehicle decision index mutual weight information
In Table 5,. mu.31The vehicle buffer probability is more than or equal to 80 percent, mu32The vehicle caching probability is 50% -80%.
| μ3 | μ31 | μ32 |
| μ31 | 1 | 1/3 |
| μ32 | 3 | 1 |
TABLE 5 vehicle cache probability secondary vehicle decision index mutual weight information
In Table 6,. mu.41The resource load is more than or equal to 90 percent, mu42Is 50% -90% of the resource load, mu43The resource load is less than or equal to 50 percent.
| μ4 | μ41 | μ42 | μ43 |
| μ41 | 1 | 2 | 1/2 |
| μ42 | 1/2 | 1 | 1/3 |
| μ43 | 2 | 3 | 1 |
TABLE 6 resource load Secondary vehicle decision index mutual weight information
According to the mutual weight information of the vehicle judgment indexes, the self-weight information of the vehicle judgment indexes in the judgment matrix W can be calculated.
The self-weight information of the primary vehicle judgment index is
The self-weight information of the secondary vehicle judgment index is
For example,
by calculating the self-weight information of the vehicle judgment indexes, the independent importance information of each vehicle judgment index can be obtained, and the accurate selection of the information transmission mode is facilitated.
According to the technical scheme provided by the embodiment of the disclosure, the obtaining of the weight information of the vehicle judgment index comprises: acquiring mutual weight information of vehicle judgment indexes; and calculating self-weight information of the vehicle judgment indexes according to the mutual weight information of the vehicle judgment indexes, thereby obtaining the independent weight information of each vehicle judgment index and being beneficial to accurately selecting an information transmission mode.
Fig. 3 shows a flowchart according to another embodiment of obtaining weight information of a vehicle determination index in the embodiment shown in fig. 1.
As shown in fig. 3, another embodiment of obtaining weight information of a vehicle decision index includes step S310 in addition to steps S210 and S220 similar to those of fig. 2.
In step S310, the self-weight information of the vehicle determination index is subjected to a consistency check.
In one embodiment of the present disclosure, the consistency check CR may be calculated as follows: firstly, the maximum characteristic value is calculated through self-weight information of a vehicle judgment index
Recalculating a consistency indicator
Finally, the consistency ratio is calculated
Wherein, the value of RI is determined by the order of the judgment matrix W, as shown in table 7.
TABLE 7 RI values
If CR <0.1, the consistency of the self-weight information in the judgment matrix can be considered to be acceptable; otherwise, the decision matrix needs to be modified, for example, each row of the decision matrix is multiplied by a specific multiple.
According to the technical scheme provided by the embodiment of the disclosure, the obtaining of the weight information of the vehicle judgment index further comprises: and carrying out consistency check on the self-weight information of the vehicle judgment index so as to ensure that the self-weight information has acceptable consistency.
In one embodiment of the present disclosure, a decision level matrix of vehicle decision indicators may be obtained
V＝{vij},i＝1,2,3,4；j＝1,2,3,4,5
And V is a matrix with 4 rows and 5 columns, each row corresponds to one primary vehicle judgment index, and each column in the rows corresponds to a reasonable value of a secondary vehicle judgment index under the primary vehicle judgment index.
For example, for the primary vehicle determination index "vehicle position", when the distance between two roadside base stations is 100 m, { v ] is set11,v11,……,v1520,40,60,80, 100; for the first-level vehicle judgment index 'information type', setting { v21,v21,……,v2520,40,60,80,100, representing the percentage of safety information in the information stored by the vehicle; for the first-level vehicle judgment index 'vehicle cache probability', setting { v31,v31,……,v3550,65,80,90, 100; for the first-level vehicle judgment index 'resource load', setting { v31,v31,……,v3525,50,70,90, 100. The values of the secondary vehicle judgment indexes in the table 1 and the middle points of the values are covered through reasonable values in V, and the method is favorable forAnd (5) subsequent calculation.
In one embodiment of the present disclosure, an input value of a vehicle determination index may be obtained
Y＝{y1,y2,y3,y4}
Wherein y is1Is the distance between the vehicle's current and the first base station, e.g. 30 m; y is2Is the percentage of safety information in the information currently stored by the vehicle, e.g., 40; y is3Is the current vehicle caching probability, e.g., 70; y is4Is the current resource load, e.g., 50.
In one embodiment of the present disclosure, the fuzzy relation matrix may be calculated based on an input value of the vehicle determination index and a determination level matrix of the vehicle determination index
R＝{rij},i＝1,2,3,4；j＝1,2,3,4,5
Wherein
rij＝yi/vij
Fig. 4 shows a flowchart for calculating a decision value from the weight information of the vehicle decision index and the fuzzy relation matrix in accordance with the embodiment shown in fig. 1. As shown in fig. 4, calculating a decision value based on the weight information of the vehicle decision index and the fuzzy relation matrix includes steps S410, S420.
In step S410, a decision value vector is calculated from the weight information of the vehicle decision index and the fuzzy relation matrix.
In step S420, an average value is calculated for the elements of the decision value vector to obtain a decision value.
In one embodiment of the present disclosure, the weight information W of the index may be decided by the vehicleiAnd calculating a fuzzy relation matrix R to calculate a decision value vector
Si＝wi·R
Then, the decision value vector is averaged to obtain a decision value
In this way, the decision value is made more accurate.
According to the technical scheme provided by the embodiment of the disclosure, calculating the decision value by the weight information according to the vehicle decision index and the fuzzy relation matrix comprises: calculating a decision value vector according to the weight information of the vehicle decision index and the fuzzy relation matrix; and calculating the average value of the elements of the decision value vector to obtain the decision value, thereby obtaining a more accurate decision value.
In one embodiment of the present disclosure, the threshold may be set to 50, when S '> 50, the V2V transmission mode is selected, when S' ≦ 50, the V2I transmission mode is selected. The threshold may be set to other values.
According to the technical scheme provided by the embodiment of the disclosure, selecting the information transmission mode according to the decision value comprises the following steps: selecting an inter-vehicle transmission mode when the decision value is greater than a first threshold value; and when the judgment value is less than or equal to the first threshold value, selecting a transmission mode between the vehicle and the road, so that a proper transmission mode is selected, the mode switching frequency is reduced, the transmission time is shortened, the transmission efficiency is improved, and the transmission reliability is ensured.
Fig. 5 shows a block diagram of a transmission mode selection apparatus according to an embodiment of the present disclosure. As shown in fig. 5, the transmission mode selection apparatus 500 includes: a weight information obtaining module 510, a decision level matrix obtaining module 520, an input value obtaining module 530, a fuzzy relation matrix calculating module 540, a decision value calculating module 550, and a transmission mode selecting module 560.
The weight information acquisition module 510 is configured to acquire weight information of the vehicle decision index. The decision level matrix acquisition module 520 is configured to acquire a decision level matrix of the vehicle decision index. The input value acquisition module 530 is configured to acquire an input value of the vehicle determination index. The fuzzy relation matrix calculation module 540 is configured to calculate a fuzzy relation matrix from the input values of the vehicle decision indicator and the decision level matrix of the vehicle decision indicator. The decision value calculation module 550 is configured to calculate a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix. The transmission mode selection module 560 is configured to select an information transmission mode according to the decision value.
According to the technical scheme provided by the embodiment of the disclosure, the weight information acquisition module is configured to acquire the weight information of the vehicle judgment index; a decision level matrix acquisition module configured to acquire a decision level matrix of the vehicle decision index; an input value acquisition module configured to acquire an input value of the vehicle determination index; a fuzzy relation matrix calculation module configured to calculate a fuzzy relation matrix according to the input value of the vehicle decision index and the decision level matrix of the vehicle decision index; a decision value calculation module configured to calculate a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix; and the transmission mode selection module is configured to select the information transmission mode according to the decision value, so that the mode switching frequency is reduced, the transmission time is reduced, the transmission efficiency is improved, and the transmission reliability is ensured.
FIG. 6 shows a block diagram of a computer system according to an embodiment of the present disclosure.
As shown in fig. 6, the computer system 600 may include one or more processors 601 and one or more memories 602. The one or more memories 602 are used to store one or more executable instructions that, when executed by the one or more processors 601, may perform the steps of: acquiring weight information of a vehicle judgment index;
acquiring a judgment grade matrix of the vehicle judgment index;
acquiring an input value of the vehicle judgment index;
calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix of the vehicle judgment index;
calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix;
an information transmission mode is selected according to the decision value.
In one embodiment of the present disclosure, the vehicle determination index includes: a vehicle position; and/or type of information; and/or vehicle caching probability; and/or resource load.
In one embodiment of the present disclosure, the vehicle decision index includes a primary decision index and a secondary decision index.
In one embodiment of the present disclosure, the obtaining weight information of the vehicle determination index includes: acquiring mutual weight information of vehicle judgment indexes; and calculating self-weight information of the vehicle judgment index according to the mutual weight information of the vehicle judgment index.
In one embodiment of the present disclosure, the obtaining weight information of the vehicle determination index further includes: and carrying out consistency check on the self-weight information of the vehicle judgment index.
In one embodiment of the present disclosure, the calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix includes: calculating a decision value vector according to the weight information of the vehicle decision index and the fuzzy relation matrix; and calculating the average value of the elements of the decision value vector to obtain the decision value.
In one embodiment of the present disclosure, the selecting an information transmission mode according to a decision value includes: selecting an inter-vehicle transmission mode when the decision value is greater than a first threshold value; and selecting a transmission mode between the vehicle and the road when the judgment value is less than or equal to the first threshold value.
According to the embodiment of the present disclosure, the transmission mode selection apparatus may be implemented in a distributed computer system. The distributed computer system may be implemented using a plurality of computers.
Fig. 7 illustrates a block diagram of a computer architecture suitable for a transmission mode selection method according to an embodiment of the present disclosure.
As shown in fig. 7, the computer system 700 includes a processor (CPU)701, which can execute the above-described method according to a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In addition, the methods described above may be implemented as computer software programs, in accordance with embodiments of the present disclosure. For example, embodiments of the present disclosure include a computer program product comprising a computer program tangibly embodied on a medium readable thereby, the computer program comprising program code for performing the above-described method. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711.
According to the embodiment of the present disclosure, the method according to the embodiment of the present disclosure may be implemented by using one computer architecture as described above, or may be implemented by using a plurality of computer architectures as described above in cooperation with each other.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units or modules described in the embodiments of the present disclosure may be implemented by software or by programmable hardware. The units or modules described may also be provided in a processor, and the names of the units or modules do not in some cases constitute a limitation of the units or modules themselves.
As another aspect, the present disclosure also provides a computer-readable storage medium, which may be the computer-readable storage medium included in the apparatus in the above-described embodiment; or it may be a separate computer readable storage medium not incorporated into the device. The computer readable storage medium stores one or more programs for use by one or more processors in performing the methods described in the present disclosure.
The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept. For example, the above features and (but not limited to) the features disclosed in this disclosure having similar functions are replaced with each other to form the technical solution.
Claims (10)
1. A transmission mode selection method for information transmission mode selection between vehicles or between vehicles and roads, the method comprising:
acquiring weight information of a vehicle determination index that is an index that affects selection of an information transmission mode in V2V and V2I;
acquiring a judgment grade matrix of the vehicle judgment index;
acquiring an input value of the vehicle judgment index, wherein the input value of the vehicle judgment index is obtained by measuring according to the vehicle judgment index according to the current state of a vehicle;
calculating a fuzzy relation matrix according to the input value of the vehicle judgment index and the judgment grade matrix of the vehicle judgment index;
calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix;
the information transmission mode is selected among V2V and V2I according to the decision value.
2. The method of claim 1, wherein:
the vehicle determination index includes: a vehicle position; and/or type of information; and/or vehicle caching probability; and/or resource load.
3. The method of claim 1, wherein:
the vehicle judgment indexes comprise primary judgment indexes and secondary judgment indexes.
4. The method of claim 1, wherein:
the acquiring of the weight information of the vehicle determination index includes:
acquiring mutual weight information of vehicle judgment indexes;
and calculating self-weight information of the vehicle judgment index according to the mutual weight information of the vehicle judgment index.
5. The method of claim 4, wherein:
the obtaining of the weight information of the vehicle determination index further includes:
and carrying out consistency check on the self-weight information of the vehicle judgment index.
6. The method of claim 1, wherein:
the calculating a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix comprises:
calculating a decision value vector according to the weight information of the vehicle decision index and the fuzzy relation matrix;
and calculating the average value of the elements of the decision value vector to obtain the decision value.
7. The method of claim 1, wherein:
the selecting an information transmission mode according to the decision value includes:
selecting an inter-vehicle transmission mode when the decision value is greater than a first threshold value; and selecting a transmission mode between the vehicle and the road when the judgment value is less than or equal to the first threshold value.
8. A transmission mode selection apparatus for information transmission mode selection between vehicles or between vehicles and roads, the apparatus comprising:
a weight information acquisition module configured to acquire weight information of a vehicle determination index that is an index that affects selection of an information transmission mode among V2V and V2I;
a decision level matrix acquisition module configured to acquire a decision level matrix of the vehicle decision index;
an input value acquisition module configured to acquire an input value of the vehicle determination index, the input value of the vehicle determination index being measured according to the vehicle determination index according to a current state of a vehicle;
a fuzzy relation matrix calculation module configured to calculate a fuzzy relation matrix according to the input value of the vehicle decision index and the decision level matrix of the vehicle decision index;
a decision value calculation module configured to calculate a decision value according to the weight information of the vehicle decision index and the fuzzy relation matrix;
a transmission mode selection module configured to select an information transmission mode among V2V and V2I according to the decision value.
9. A computer system comprising one or more processors and one or more memories storing computer-executable instructions that, when executed by the processors, implement the method of any of claims 1-7.
10. A computer-readable storage medium, the memory storing computer-executable instructions that, when executed by a processor, implement the method of any one of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010104280.6A CN111314882B (en) | 2020-02-20 | 2020-02-20 | Transmission mode selection method, device, computer system and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010104280.6A CN111314882B (en) | 2020-02-20 | 2020-02-20 | Transmission mode selection method, device, computer system and readable storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN111314882A CN111314882A (en) | 2020-06-19 |
| CN111314882B true CN111314882B (en) | 2021-10-15 |
Family
ID=71148019
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010104280.6A Active CN111314882B (en) | 2020-02-20 | 2020-02-20 | Transmission mode selection method, device, computer system and readable storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111314882B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113543017B (en) * | 2021-06-02 | 2022-07-29 | 北京邮电大学 | Wave beam switching method of millimeter wave internet of vehicles and related equipment |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550515A (en) * | 2015-12-10 | 2016-05-04 | 山东科技大学 | Multi-level comprehensive judgment method for air quality data |
| CN107248284A (en) * | 2017-08-09 | 2017-10-13 | 北方工业大学 | Real-time traffic evaluation method based on Multi-source Information Fusion |
| CN107274093A (en) * | 2017-06-13 | 2017-10-20 | 国网新疆电力公司经济技术研究院 | A kind of methods of risk assessment of safe operation of electric network |
| CN107609728A (en) * | 2017-07-26 | 2018-01-19 | 安徽理工大学 | A kind of bottom plate resistance water isolating evaluation method based on AHP |
| CN109409768A (en) * | 2018-11-12 | 2019-03-01 | 广东工业大学 | The method for early warning of transport truck |
| CN110633449A (en) * | 2019-09-19 | 2019-12-31 | 郑州航空工业管理学院 | Air quality evaluation method based on improved entropy weight method |
| CN110738435A (en) * | 2019-04-10 | 2020-01-31 | 国网浙江省电力有限公司经济技术研究院 | distribution network project investment decision evaluation method |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10210518B2 (en) * | 2016-04-13 | 2019-02-19 | Abdullah Abdulaziz I. Alnajem | Risk-link authentication for optimizing decisions of multi-factor authentications |
-
2020
- 2020-02-20 CN CN202010104280.6A patent/CN111314882B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105550515A (en) * | 2015-12-10 | 2016-05-04 | 山东科技大学 | Multi-level comprehensive judgment method for air quality data |
| CN107274093A (en) * | 2017-06-13 | 2017-10-20 | 国网新疆电力公司经济技术研究院 | A kind of methods of risk assessment of safe operation of electric network |
| CN107609728A (en) * | 2017-07-26 | 2018-01-19 | 安徽理工大学 | A kind of bottom plate resistance water isolating evaluation method based on AHP |
| CN107248284A (en) * | 2017-08-09 | 2017-10-13 | 北方工业大学 | Real-time traffic evaluation method based on Multi-source Information Fusion |
| CN109409768A (en) * | 2018-11-12 | 2019-03-01 | 广东工业大学 | The method for early warning of transport truck |
| CN110738435A (en) * | 2019-04-10 | 2020-01-31 | 国网浙江省电力有限公司经济技术研究院 | distribution network project investment decision evaluation method |
| CN110633449A (en) * | 2019-09-19 | 2019-12-31 | 郑州航空工业管理学院 | Air quality evaluation method based on improved entropy weight method |
Non-Patent Citations (2)
| Title |
|---|
| A p-Opportunistic Channel Access Scheme for Interference Mitigation Between V2V and V2I Communications;Xiangming Wen;《IEEE INTERNET OF THINGS JOURNAL》;20200117;全文 * |
| 城市道路交通流预测与状态判别关键技术研究;马玄;《中国优秀硕士学位论文全文数据库》;20150115;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN111314882A (en) | 2020-06-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11059485B2 (en) | Lane selection method, target vehicle and computer storage medium | |
| EP4235617A1 (en) | Traffic congestion detection method and apparatus, electronic device and storage medium | |
| CN112249034B (en) | Automobile brain system and vehicle driving control method | |
| Sodhro et al. | Link optimization in software defined IoV driven autonomous transportation system | |
| US11567495B2 (en) | Methods and systems for selecting machine learning models to predict distributed computing resources | |
| CN110582072B (en) | Fuzzy matching-based resource allocation method and device in cellular internet of vehicles | |
| CN113596102A (en) | Vehicle-road cooperative traffic system, road side system and data processing method | |
| CN110719570A (en) | Transmission method and communication device for map sensitive information | |
| CN111314882B (en) | Transmission mode selection method, device, computer system and readable storage medium | |
| CN113612844A (en) | Data sharing method and device for vehicle end, medium and electronic equipment | |
| CN113613201A (en) | Data sharing method, device and medium applied to vehicles and electronic equipment | |
| CN110880235A (en) | Road side equipment in road condition information processing system, processing method and device | |
| Lee et al. | Design of V2X-based vehicular contents centric networks for autonomous driving | |
| JP6771559B2 (en) | Mobile communication device, mobile communication method, and mobile communication program | |
| WO2022142870A1 (en) | Data transmission method and apparatus for internet of vehicles, storage medium, and system | |
| CN111327473B (en) | Network regulation and control method, device, network regulation and control system and electronic equipment | |
| Meuser et al. | Relevance-aware information dissemination in vehicular networks | |
| CN115019204A (en) | Knowledge graph battlefield target identification method, device, equipment and medium | |
| CN111586160B (en) | Data processing method, device, data processing equipment and storage medium | |
| CN110290503B (en) | Vehicle data distribution method and device, electronic equipment and readable storage medium | |
| CN113422797A (en) | Method and system for updating map for Internet of vehicles | |
| CN111831931B (en) | Method and device for ordering boarding points and information | |
| Chawky et al. | Cooperative perception: Mitigating messages content duplication | |
| Shah et al. | Novel crash prevention framework for C-V2X using deep learning | |
| WO2022156352A1 (en) | Method and apparatus for updating map, and computer-readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |