CN111582635A - Multi-target processing method based on V2X - Google Patents
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Abstract
The invention relates to a multi-target processing method based on V2X, which comprises the steps of obtaining position information of a vehicle and state information of a target vehicle; calling historical evaluation data of the target vehicle, wherein the historical evaluation data comprises a threat level of the target vehicle, and the threat level is used for evaluating the threat intensity of the target vehicle to the vehicle; screening effective target vehicle state information according to the threat level; analyzing the threat level at the current moment according to the position information of the vehicle and the effective state information of the target vehicle, and generating new evaluation data; and updating the historical evaluation data by using the new evaluation data, and making corresponding early warning according to the threat level. The method can be used for preliminarily screening the acquired state information of the target vehicle, neglecting the data of the target vehicle with low threat intensity, realizing the rapid processing of more effective data under the condition of limited hardware resources, and ensuring the real-time and accurate target early warning capability.
Description
Technical Field
The invention relates to a V2X communication technology, in particular to a V2X-based multi-target processing method.
Background
V2X (vehicle to evolution) is currently one of the key areas for the development of car networking, and its main contents include the following several types of interconnection: Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), Vehicle-to-person (V2P), and Vehicle-to-internet (Vehicle-to-Network). The interconnection of the vehicles can enable the vehicle and other vehicles in the environment to realize information interaction, so that the vehicle can acquire the running states, road condition information and the like of other surrounding vehicles in real time, and early warning and reminding are given to a driver, so that the driving safety is improved, the congestion is reduced, and the traffic efficiency is improved.
The communication distance of the current V2X technology is generally greater than 300m, which means that, in the communication range of the V2X system mounted on the host vehicle, there will generally be a plurality of target vehicle nodes, and each target vehicle node will broadcast information periodically, and the broadcast period is generally 100ms, so the host vehicle will continuously receive data from each target vehicle node, which needs to be processed by the host vehicle V2X system, even the received data of the target vehicle nodes can be increased infinitely within a certain range. However, since the hardware processing capability of the vehicle configuration is limited, after receiving a large amount of target node data, the data cannot be processed in real time, and usually only the data of the target nodes which are not processed in time are stored in the queue, and then the data of the target nodes in the queue are taken out one by one according to the hardware processing capability and are calculated and processed. The processing scheme cannot essentially solve the contradiction between the limited hardware processing capacity and the multi-target node data, and inevitably leads to the continuous increase of the queue and the large backlog of the data, namely the received data cannot be processed in real time, thereby causing serious problems of early warning lag, false alarm, missing alarm and the like, and even causing unnecessary traffic accidents.
How to process more target vehicle node data under the limited hardware resource capacity and keep the real-time and accurate target early warning capacity gradually becomes a technical problem which is urgently needed to be solved at present. At present, in order to improve the processing speed of target vehicle node data and realize real-time processing, part of manufacturers discard part of target node data according to hardware processing capacity after receiving the target node data, so that a large amount of backlog of the data is avoided. Although the method can improve the real-time performance of data processing, the phenomena of untimely early warning, false alarm, missed alarm and the like are caused because part of data is directly discarded and key information is easily missed. Therefore, it is important to develop an information screening method based on the V2X system to achieve accurate and fast processing of multiple targets.
Disclosure of Invention
In order to solve the above-mentioned technical problem, the present invention provides a multi-target processing method based on V2X, based on a host vehicle V2X system mounted on the host vehicle and a V2X system respectively mounted on a plurality of target vehicles, comprising:
acquiring the position information of the vehicle and the state information of a target vehicle;
calling historical evaluation data of the target vehicle, wherein the historical evaluation data comprises a threat level of the target vehicle, and the threat level is used for evaluating the threat intensity of the target vehicle to the vehicle;
screening effective target vehicle state information according to the threat level;
analyzing the threat level at the current moment according to the position information of the vehicle and the effective state information of the target vehicle, and generating new evaluation data;
and updating the historical evaluation data by using the new evaluation data, and making corresponding early warning according to the threat level.
Further, the vehicle position information refers to vehicle coordinate values; the target vehicle state information comprises a target vehicle coordinate value, data acquisition time and a unique identification code, and the unique identification code comprises a frame number or a license plate number.
Further, the historical evaluation data further includes a unique identification code of the target vehicle, a historical evaluation data generation time, and a historical distance between the target vehicle and the own vehicle.
Further, the step of retrieving historical evaluation data of the target vehicle, where the historical evaluation data includes a threat level of the target vehicle, and the threat level is used to evaluate a threat intensity of the target vehicle to the host vehicle, includes:
extracting a unique identification code in the target vehicle state information;
searching historical evaluation data matched with the unique identification code in an information list of the vehicle V2X system, and if the search result exists, calling the historical evaluation data matched with the unique identification code for standby; otherwise, the threat level of the target vehicle is directly set to the highest level, and the distance between the target vehicle and the vehicle is calculated to generate first evaluation data.
Further, the step of screening out effective target vehicle state information according to the threat level includes:
respectively presetting discarding time ranges for different threat levels, wherein the discarding time ranges refer to the shortest time interval required for obtaining effective target vehicle state information twice;
extracting threat levels in historical evaluation data, and determining a discarding time range matched with the threat levels;
calculating the difference between the data acquisition time and the historical evaluation data generation time to acquire a time interval;
judging whether the time interval is within the discarding time range, if so, directly discarding the state information of the target vehicle; otherwise, the target vehicle state information is deemed valid.
Further, the step of calculating the threat level at the current moment according to the vehicle position information and the valid target vehicle state information and generating new evaluation data includes:
calculating the current distance between the target vehicle and the vehicle at the current moment according to the position information of the vehicle and the effective state information of the target vehicle;
analyzing the collision time between the target vehicle and the vehicle according to the current distance;
and determining the threat level of the target vehicle at the current moment according to the collision time, and generating new evaluation data.
Further, the current distance between the target vehicle and the host vehicle at the current moment is calculated according to the host vehicle coordinate value and the target vehicle coordinate value.
Further, the step of analyzing the collision time between the target vehicle and the host vehicle according to the current distance includes:
extracting historical distance between a target vehicle and the vehicle in the historical evaluation data, and making a difference value between the historical distance and the current distance to obtain a distance change value;
the data acquisition time is differenced with the historical evaluation data generation time to acquire a time variation value;
calculating the change speed by taking the ratio of the distance change value to the time change value;
and (4) comparing the current distance with the change speed to obtain the collision time.
Further, the step of determining the threat level of the target vehicle at the current moment according to the collision time and generating new evaluation data comprises:
determining a threat level according to the collision time, wherein the smaller the collision time is, the larger the threat level is;
and acquiring the threat level, the current distance between the target vehicle and the vehicle, the unique identification code and the current system time, and generating new evaluation data.
A V2X system convenient for realizing multi-target processing is based on the multi-target processing method based on V2X, and comprises a vehicle V2X system erected on a vehicle, wherein the vehicle V2X system comprises a data acquisition module, a data screening module, an index calculation module, an evaluation module and an information updating module; the data acquisition module is used for acquiring the position information of the vehicle and the state information of the target vehicle in real time and transmitting the acquired information to the data screening module in real time; the data screening module screens the received target vehicle state information according to the stored historical evaluation data to obtain effective target vehicle state information, and the effective target vehicle state information is transmitted to the index calculation module in time; the index calculation module calculates an evaluation index according to the effective target vehicle state information and transmits the evaluation index to the evaluation module; the evaluation module evaluates the threat level of the target vehicle according to the evaluation index and transmits the evaluated threat level and the effective state information of the target vehicle to the information updating module; the information updating module updates historical data according to the received threat level and the effective target vehicle state information so as to ensure the effectiveness of the data.
The invention has the following beneficial technical effects:
compared with the prior art, the invention discloses a multi-target processing method based on V2X, which can preliminarily screen the acquired state information of a target vehicle according to historical evaluation data, ignore invalid data, enable a vehicle-mounted V2X system to rapidly process more effective state information of the target vehicle under limited hardware processing conditions, ensure real-time and accurate target early warning capability, avoid the occurrence of phenomena such as early warning delay, false alarm, missed alarm and the like, and greatly improve the multi-target processing capability of the V2X system.
Drawings
Fig. 1 is a schematic view of a multi-objective processing flow based on V2X in embodiment 1.
Fig. 2 is a schematic flow chart of the target data screening process in example 1.
Fig. 3 is a schematic diagram showing the connection relationship between the modules in the vehicle V2X system according to example 1.
Reference numerals:
the system comprises a vehicle V2X system 1, a data acquisition module 2, a data screening module 3, an index calculation module 4, an evaluation module 5 and an information updating module 6.
The drawings are for illustrative purposes only and are not to be construed as limiting the patent; for the purpose of better illustrating the embodiments, certain features of the drawings may be omitted, enlarged or reduced, and do not represent the size of an actual product; it will be understood by those skilled in the art that certain well-known structures in the drawings and descriptions thereof may be omitted; the same or similar reference numerals correspond to the same or similar parts; the terms describing positional relationships in the drawings are for illustrative purposes only and are not to be construed as limiting the patent.
Detailed Description
The following detailed description of the preferred embodiments of the present invention, taken in conjunction with the accompanying drawings, will make the advantages and features of the invention easier to understand for those skilled in the art and will therefore make the scope of the invention more clearly defined.
Example 1:
as shown in fig. 1, the present embodiment provides a multi-target processing method based on V2X, based on the own-vehicle V2X system 1 mounted on the own vehicle and the V2X systems respectively mounted on a plurality of target vehicles.
The V2X-based multi-target processing method specifically comprises the following steps:
101. and acquiring the position information of the vehicle and the state information of the target vehicle.
In this embodiment, the vehicle position information and the target vehicle state information are both acquired at a fixed time period, which is typically the information transmission period of the V2X system, such as 1 time/100 ms. The vehicle position information is vehicle coordinate values, usually HvLoc (h)x,hy) Is shown in which (h)x,hy) Is the coordinate value of the coordinate system where the vehicle is located. The target vehicle state information comprises a target vehicle coordinate value, data acquisition time and a unique identification code, wherein the unique identification code comprises a frame number or a license plate number. Target vehicle state information is typically reported in RvInfo (rId, r)x,ry,tnow) Representation, wherein rId represents a unique identification code, (r)x,ry) Then represents the coordinate value of the coordinate system where the target vehicle is located, tnowThen represents the data acquisition time.
102. And calling historical evaluation data of the target vehicle, wherein the historical evaluation data comprises a threat level of the target vehicle, and the threat level is used for evaluating the threat intensity of the target vehicle to the self vehicle.
Preferably, the history evaluation data in the present embodiment further includes a unique identification code of the target vehicle, a history evaluation data generation time, and a history distance between the target vehicle and the own vehicle.
Since the target vehicle state information acquired in step 101 includes the unique identification code, the historical evaluation data stored in the host vehicle V2X system also includes the unique identification code. Therefore, when the history evaluation data of the target vehicle is retrieved, it is necessary to first retrieve the target vehicle state information (rId, r) from the retrieved target vehicle state informationx,ry,tnow) The unique identification code of the target vehicle is extracted, then the unique identification code is input into the information list of the vehicle V2X system 1, and whether historical evaluation data matched with the unique identification code exists or not is searched. The general information list comprises historical evaluation data of a plurality of target vehicles, and is equivalent to a data storage library with a format similar to RvList { Rva（rId,tlast,dislast,Levelm）,....., Rvn（rId,tlast,dislast,Levelk) … } where t islastEvaluating the generation time of data for history, dislastFor historical evaluation of the historical distance, Level, between the target vehicle and the own vehicle in the data*The threat level of the target vehicle in the data is assessed for history. If the search result in the information list is present, that is, the historical evaluation data matched with the unique identification code is stored in the information list, the historical evaluation data matched with the unique identification code is continuously called for later use. If the search result is not present, that is, it means that the target vehicle appears in the coverage of the vehicle V2X system 1 for the first time, in order to draw the importance of the system and avoid the false alarm, the threat level of the target vehicle is directly set to the highest level, and the distance between the target vehicle and the vehicle is calculated to generate the first evaluation report.
103. And screening effective target vehicle state information according to the threat level.
And aiming at the condition that historical evaluation data matched with the unique identification code exists in the information list, further acquiring the threat level of the target vehicle stored in the historical evaluation data according to the retrieved historical evaluation data, and screening effective target vehicle state information according to the threat level.
In specific implementation, as shown in fig. 2, it is first necessary to preset discarding time ranges for different threat levels in advance, where the discarding time range refers to a shortest time interval required for obtaining valid target vehicle state information twice, or may be understood as a time period for obtaining valid target vehicle state information. For example, as Level1Has a discarding time range of (0, T)1）、Level2Has a discarding time range of (0, T)2）、Level3Has a discarding time range of (0, T)3) Etc. if the threat Level is to be1Considered the highest level of threat, then generally T1Will take the minimum value, i.e. T1＜T2＜T3This is because when the Level is used1When the vehicle represents the highest threat level, the threat intensity of the target vehicle to the vehicle is the highest, the target vehicle is closely related to the safe driving of the vehicle, and needs to pay close attention and monitor to the vehicle, so that the value of the state information of the target vehicle needs to be taken frequently, namely the value interval of the state information of the target vehicle is smaller; on the contrary, when the threat level gradually decreases, the threat level means that the threat intensity of the target vehicle to the vehicle is low, namely the influence is not large, and in order to take account of the limited processing capacity of hardware, the value interval of the state information of the target vehicle is relatively large, the value is relatively infrequent, and the data processing speed and the safety early warning are taken account of. After the discarded data range is preset, the stored threat level may be extracted from the historical evaluation data retrieved in step 102, and a discarded time range matching the threat level may be determined according to the discarded time range preset for different threat levels. Then the difference between the data acquisition time and the historical evaluation data generation time is calculated,to obtain the time interval, i.e. △ t = tnow-tlast. Finally, whether the time interval is within the discarding time range corresponding to the threat level is judged, and if yes, the state information of the target vehicle is directly discarded; otherwise, the target vehicle state information is deemed valid. By utilizing the threat level, a large amount of non-critical target vehicle state information can be deleted, and vehicles which can cause direct threat to the vehicle are screened out, so that the calculation task of the vehicle V2X system 1 is greatly reduced, the large accumulation of data is effectively avoided, and the real-time performance and the effectiveness of processing are improved.
104. And analyzing the threat level at the current moment according to the vehicle position information and the effective target vehicle state information, and generating new evaluation data.
Specifically, first, the current distance between the target vehicle and the host vehicle at the current time is calculated based on the host vehicle position information and the valid target vehicle state information. In other words, it is based on the vehicle coordinate value (h)x,hy) And target vehicle coordinate value (r)x,ry) The two-point distance calculation formula dis can be utilizednow 2= （rx- hx）2+（ry- hy）2Obtaining the current distance dis between the target vehicle and the vehicle at the current momentnow. Then, the collision time between the target vehicle and the vehicle can be analyzed according to the current distance. And finally, determining the threat level of the target vehicle at the current moment according to the collision time, and generating new evaluation data.
In this embodiment, in order to calculate the time of collision between the target vehicle and the host vehicle, it is necessary to extract the historical distance dis between the target vehicle and the host vehicle in the historical evaluation datalastAnd compares it with the current distance disnowAnd performing difference to obtain a distance change value D. Then the data is acquired for a time tnowAnd the generation time t of the historical evaluation datalastMaking difference to obtain time variation value △ t, calculating the ratio of distance variation value D to time variation value △ t to obtain variation speed V, i.e. relative variation speed between two vehiclesFront distance disnowThe collision time t can be obtained by taking the ratio of the speed to the change speed Vc. The specific calculation formula is as follows:
tc=disnow*（tnow-tlast）/dislast-disnow；
wherein, tcIs the time of collision, disnowIs the current distance, dis, between the target vehicle and the host vehicle at the current momentlastFor historical evaluation of the historical distance between the target vehicle and the own vehicle in the data, tnowData acquisition time, t, for target vehicle status informationlastThe generation time of the data is evaluated for history.
Once the time to collision is calculated by the above equation, the threat level of the target vehicle at the current time may be determined based on the time to collision. Generally, different collision times will be classified into different threat levels, e.g., when 0 ≦ tc＜Tc1The threat Level of the target vehicle at the current moment is Level1When T isc1≤tc＜Tc2The threat Level of the target vehicle at the current moment is Level2When T isc2≤tc＜Tc3The threat Level of the target vehicle at the current moment is Level3And so on. Of course, 0 < Tc1＜Tc2＜Tc3， Tc1、Tc2、Tc3The threshold values are preset by the system, and the user can set the threshold values according to needs without limitation. As can be seen from the above threat level evaluation method, the smaller the collision time is, the easier the target vehicle collides with the host vehicle, and the larger the corresponding threat level is, the higher the threat intensity of the target vehicle to the host vehicle is, and the closer attention of the system is required. After the threat level is determined, new evaluation data can be generated according to the calculated threat level at the current moment, the current distance between the target vehicle and the vehicle, the unique identification code and the current system time.
It is worth noting that when dislastAnd disnowWhen the difference of (A) is less than 0, it means that the target vehicle is the own vehicleThe distance between the vehicles is gradually increased along with the time, or the two vehicles are understood to move back and forth, the calculated tcIt will be a negative value, and the system will consider the threat of the target vehicle to the vehicle to be small, so as to directly set the threat level of the target vehicle at the current time to the minimum level.
105. And updating the historical evaluation data by using the new evaluation data, and making corresponding early warning according to the threat level.
When new evaluation data is generated, that is, the real-time evaluation of the target vehicle is completed, it is only necessary to store the new evaluation data in the information list of the vehicle V2X system 1 to update the previously stored historical evaluation data. After the data updating is completed, when the target vehicle state information is acquired again next time, the updated evaluation data is used as historical evaluation data for the next round of analysis, so that the accuracy of the analysis is improved.
Meanwhile, the vehicle V2X system 1 also sends the evaluated threat level to the vehicle-mounted control system in time, and the vehicle-mounted control system makes early warning responses of different levels, such as voice prompts and vibrations with different sound levels, to the driver according to the threat level.
The implementation principle of the multi-target processing method disclosed by the embodiment is as follows:
during the driving process of the vehicle, a plurality of target vehicles inevitably exist in the signal coverage range of the vehicle V2X system 1. However, among such multiple target vehicles, there are not many vehicles that may pose a direct threat to the own vehicle, and there may be only a few surrounding vehicles. Therefore, under the condition that the vehicle V2X system 1 cannot bear the calculation tasks of hundreds of target vehicles, only the threatening target vehicles need to be identified and the early warning calculation is carried out on the threatening target vehicles, so that the early warning calculation is not needed to be carried out on all the vehicles. In addition, the threat relationship between the target vehicle and the host vehicle is dynamic, that is, the target vehicle threatening the host vehicle changes continuously along with the driving, so we can not discard all vehicles without threat, but need to classify the threat levels of all target vehicles and periodically calculate and monitor the data of the target vehicles according to the threat levels. The higher the threat level is, the higher the frequency of early warning calculation is, and more target vehicle state parameters can be discarded for target vehicles which hardly have threat at present, so that the calculation amount is greatly reduced, the system can process the target vehicles with high threat level in real time, the real-time and reliable early warning is ensured, and the multi-target processing capability of the system is provided.
Example 2:
the embodiment discloses a V2X system convenient for realizing multi-target processing, and the multi-target processing method based on V2X, which is described in embodiment 1, comprises a vehicle V2X system 1 which is arranged on a vehicle, and the vehicle V2X system 1 is in communication connection with a vehicle-mounted control unit. The vehicle V2X system 1 includes a data acquisition module 2, a data filtering module 3, an index calculation module 4, an evaluation module 5, and an information update module 6. The data acquisition module 2 can be in communication connection with a V2X system on another vehicle, and is configured to acquire the position information of the vehicle and the state information of the target vehicle in real time, and transmit the acquired information to the data screening module 3 in real time. The data screening module 3 screens the received target vehicle state information according to the stored historical evaluation data to obtain effective target vehicle state information, and transmits the effective target vehicle state information to the index calculation module 4 in time. The index calculation module 4 calculates an evaluation index from the valid target vehicle state information, and transmits the evaluation index to the evaluation module 5. The evaluation module 5 evaluates the threat level of the target vehicle according to the evaluation index, and transmits the evaluated threat level and the valid target vehicle state information to the information updating module 6. The information updating module 6 updates the historical data according to the received threat level and the valid target vehicle state information to ensure the validity of the data. Meanwhile, the vehicle V2X system 1 transmits the threat level to the vehicle-mounted control unit, and the vehicle-mounted control unit makes a matched early warning prompt according to the threat level.
It should be understood that the above-described embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not intended to limit the embodiments of the present invention. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. And are neither required nor exhaustive of all embodiments. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the claims of the present invention.
Claims (10)
1. A multi-target processing method based on V2X is characterized in that the method is based on a vehicle V2X system (1) arranged on the vehicle and a V2X system respectively arranged on a plurality of target vehicles, and comprises the following steps:
acquiring the position information of the vehicle and the state information of a target vehicle;
calling historical evaluation data of the target vehicle, wherein the historical evaluation data comprises a threat level of the target vehicle, and the threat level is used for evaluating the threat intensity of the target vehicle to the vehicle;
screening effective target vehicle state information according to the threat level;
analyzing the threat level at the current moment according to the position information of the vehicle and the effective state information of the target vehicle, and generating new evaluation data;
and updating the historical evaluation data by using the new evaluation data, and making corresponding early warning according to the threat level.
2. The V2X-based multi-target processing method according to claim 1, wherein the vehicle position information is vehicle coordinate values; the target vehicle state information comprises a target vehicle coordinate value, data acquisition time and a unique identification code, and the unique identification code comprises a frame number or a license plate number.
3. The V2X-based multi-target processing method according to claim 2, wherein the historical evaluation data further includes a unique identification code of the target vehicle, a historical evaluation data generation time, and a historical distance between the target vehicle and the own vehicle.
4. The multi-target processing method based on V2X, wherein the method for multi-target processing based on V2X is characterized in that historical evaluation data of the target vehicles are retrieved, the historical evaluation data comprise threat levels of the target vehicles, and the threat levels are used for evaluating the threat intensity of the target vehicles to the own vehicles, and the method comprises the following steps:
extracting a unique identification code in the target vehicle state information;
searching historical evaluation data matched with the unique identification code in an information list of the vehicle V2X system, and if the search result exists, calling the historical evaluation data matched with the unique identification code for standby; otherwise, the threat level of the target vehicle is directly set to the highest level, and the distance between the target vehicle and the vehicle is calculated to generate first evaluation data.
5. The multi-target processing method based on V2X, according to the threat level, characterized in that the step of screening out valid target vehicle state information comprises:
respectively presetting discarding time ranges for different threat levels, wherein the discarding time ranges refer to the shortest time interval required for obtaining effective target vehicle state information twice;
extracting threat levels in historical evaluation data, and determining a discarding time range matched with the threat levels;
calculating the difference between the data acquisition time and the historical evaluation data generation time to acquire a time interval;
judging whether the time interval is within the discarding time range, if so, directly discarding the state information of the target vehicle; otherwise, the target vehicle state information is deemed valid.
6. The multi-target processing method based on V2X, wherein the step of calculating the threat level at the current moment according to the vehicle position information and the valid target vehicle state information and generating new evaluation data comprises:
calculating the current distance between the target vehicle and the vehicle at the current moment according to the position information of the vehicle and the effective state information of the target vehicle;
analyzing the collision time between the target vehicle and the vehicle according to the current distance;
and determining the threat level of the target vehicle at the current moment according to the collision time, and generating new evaluation data.
7. The multi-target processing method based on V2X, wherein the current distance between the target vehicle and the host vehicle at the current moment is calculated according to the host vehicle coordinate values and the target vehicle coordinate values.
8. The multi-target processing method based on V2X, wherein the step of analyzing the collision time between the target vehicle and the own vehicle according to the current distance comprises the following steps:
extracting historical distance between a target vehicle and the vehicle in the historical evaluation data, and making a difference value between the historical distance and the current distance to obtain a distance change value;
the data acquisition time is differenced with the historical evaluation data generation time to acquire a time variation value;
calculating the change speed by taking the ratio of the distance change value to the time change value;
and (4) comparing the current distance with the change speed to obtain the collision time.
9. The V2X-based multi-target processing method according to claim 8, wherein the step of determining the threat level of the target vehicle at the current time based on the time of collision and generating new assessment data comprises:
determining a threat level according to the collision time, wherein the smaller the collision time is, the larger the threat level is;
and acquiring the threat level, the current distance between the target vehicle and the vehicle, the unique identification code and the current system time, and generating new evaluation data.
10. A V2X system for facilitating multi-target processing, based on any one of claims 1 to 9, the V2X-based multi-target processing method is characterized by comprising a vehicle V2X system (1) erected on a vehicle, wherein the vehicle V2X system (1) comprises a data acquisition module (2), a data screening module (3), an index calculation module (4), an evaluation module (5) and an information updating module (6); the data acquisition module (2) is used for acquiring the position information of the vehicle and the state information of the target vehicle in real time and transmitting the acquired information to the data screening module (3) in real time; the data screening module (3) screens the received target vehicle state information according to the stored historical evaluation data to obtain effective target vehicle state information, and transmits the effective target vehicle state information to the index calculation module (4) in time; the index calculation module (4) calculates an evaluation index according to the effective target vehicle state information and transmits the evaluation index to the evaluation module (5); the evaluation module (5) evaluates the threat level of the target vehicle according to the evaluation index, and transmits the evaluated threat level and the effective target vehicle state information to the information updating module (6); the information updating module (6) updates the historical data according to the received threat level and the effective target vehicle state information so as to ensure the effectiveness of the data.
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