CN113657514B - Intelligent networking vehicle-oriented distributed information credibility identification and processing method - Google Patents
Intelligent networking vehicle-oriented distributed information credibility identification and processing method Download PDFInfo
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- CN113657514B CN113657514B CN202110957528.8A CN202110957528A CN113657514B CN 113657514 B CN113657514 B CN 113657514B CN 202110957528 A CN202110957528 A CN 202110957528A CN 113657514 B CN113657514 B CN 113657514B
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- 238000012795 verification Methods 0.000 claims abstract description 3
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
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- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
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- G06F18/25—Fusion techniques
- G06F18/251—Fusion techniques of input or preprocessed data
Abstract
In the information acquisition stage, acquiring vehicle end sensing information through a vehicle sensor, and acquiring big data platform information and V2V information as auxiliary information for reliability judgment through a network cloud platform and other vehicle broadcasting information respectively; in the remote information credibility judging stage, credibility indexes of the remote vehicle information to be determined are calculated through auxiliary information, information fusion is carried out when credibility is acceptable, otherwise, information fusion is not carried out, the remote vehicle information to be determined is additionally cached, meanwhile, intrusion signals and information authenticity verification signals are broadcast to other vehicles, and feedback results of the other vehicles are waited for to cooperatively judge the authenticity of the information. The invention judges through the identification and processing of the distributed information credibility facing the intelligent network vehicle and the remote suspicious information credibility judging flow and mechanism, namely, the intelligent network vehicle intelligent network system is assisted in other V2V data.
Description
Technical Field
The invention relates to a technology in the field of intelligent traffic management, in particular to a distributed information credibility identification and processing method for intelligent network vehicles.
Background
In intelligent traffic systems, distributed control systems are a powerful and efficient way to solve the large-scale optimization problem, but when false information invades the system, especially through workshop communication, the wrong information will cause the intelligent vehicle to make wrong decisions, resulting in unnecessary losses. In the prior art, the reliability of information is calculated through a prediction model, but the accuracy of the prediction model is supported by the authenticity of a sample, once the original data has holes, no matter how accurate the algorithm of the prior art is, the obtained calculated value is still wrong, i.e. the prior art cannot solve the security evaluation under the condition of false information.
Disclosure of Invention
Aiming at the problem of the reliability of auxiliary distributed information of the intelligent network vehicle end in the prior art, the invention provides an intelligent network vehicle-oriented distributed information reliability identification and processing method, which is judged by the intelligent network vehicle-oriented distributed information reliability identification and processing and remote suspicious information reliability judgment flow and mechanism, namely, the intelligent network vehicle-oriented distributed information reliability identification and processing method is auxiliary to other V2V data.
The invention is realized by the following technical scheme:
the invention relates to a distributed information credibility identification and processing method for intelligent networking vehicles, which comprises the steps of respectively acquiring vehicle end sensing information through a vehicle sensor, and acquiring big data platform information and V2V information as auxiliary information for credibility judgment through a networking cloud platform and other vehicle broadcast information in an information acquisition stage; in the remote information credibility judging stage, credibility indexes of the remote vehicle information to be determined are calculated through auxiliary information, information fusion is carried out when credibility is acceptable, otherwise, information fusion is not carried out, the remote vehicle information to be determined is additionally cached, meanwhile, intrusion signals and information authenticity verification signals are broadcast to other vehicles, and feedback results of the other vehicles are waited for to cooperatively judge the authenticity of the information.
The vehicle sensors include, but are not limited to: visual sensor, laser radar sensor, millimeter wave sensor, vehicle-mounted positioning system etc. can obtain the multiple sensor of own car motion gesture.
The vehicle end perception information comprises: longitude and latitude altitude information, speed and acceleration information, and travel intention information.
The big data platform information comprises: vehicle end perception information of all vehicles, monitoring information of all roads and all road side information.
The V2V information includes: the perception information broadcast to the host vehicle by other vehicles comprises: vehicle end awareness information of other vehicles and surrounding vehicle state information thereof.
The remote vehicle information to be determined is as follows: V2V information to be identified.
The credibility index, namely the authenticity of other vehicle broadcast information to be identified, is specifically obtained byThe process comprises the following steps: phi is the original information set of the Internet cloud platform, theta is the information set of the remote vehicle information to be determined, and +.>And identifying the empty set, wherein when the empty set is true, the empty set is not trusted, the reliability index is 0, and otherwise, the reliability index is 1.
The information fusion refers to: and splicing the remote vehicle information to be determined and the stored state information of the vehicle before the remote information interaction operation, namely splicing the remote vehicle information and the state information into a matrix form identifiable by a vehicle algorithm.
The additional cache refers to: the remote vehicle information to be determined is stored in an additional cache device for the next cycle of the identification operation.
The collaborative judgment means that: sending confirmation information to other determined real vehicles, judging that the information to be determined is real when the vehicle-mounted sensors of the other vehicles sense the vehicle sending the information of the vehicle to be determined (namely, the other vehicles find the existence of the vehicle), and then fusing the information to be determined with the original data; otherwise, judging the information to be determined as false and reporting the alarm information.
The determined means that: and when the vehicle is on the road, namely one vehicle, all the added new vehicles are the information to be determined.
Technical effects
The invention integrally solves the defect that false information cannot be timely identified to cause vehicle decision errors in the prior art; in the invention, in the original data acquisition stage, an identification and processing mechanism is established, the authenticity of the information is identified and processed from the original data acquisition layer, the vulnerability of the information security is fundamentally compensated, and an information security foundation is laid for all algorithms needing to utilize the original data.
Drawings
FIG. 1 is a schematic diagram of a remote decision information reliability determination flow;
FIG. 2 is a schematic diagram of a remote help-seeking phase flow of a suspicious information source according to an embodiment;
FIG. 3 is a diagram of example information fidelity identification;
in the figure: V1-V4 represent vehicles 1-4, respectively.
Detailed Description
As shown in fig. 1, this embodiment relates to a method for identifying and processing distributed information credibility of an intelligent internet-connected vehicle, in the information acquisition stage, vehicle-end sensing information is acquired through a vehicle sensor, and big data platform information and V2V information are acquired through an internet-connected cloud platform and other vehicle broadcast information as auxiliary information for credibility judgment; in the reliability judging stage of the remote information, the reliability index of the remote vehicle information is calculated through the auxiliary information, the remote vehicle information is fused with the conventional information when the reliability is acceptable, otherwise, the remote vehicle information is additionally cached and is not fused with the conventional information, meanwhile, an intrusion signal and an information authenticity evidence signal are sent to other vehicles, and feedback results of the other vehicles are waited to cooperatively judge the authenticity of the information.
Specific experiments are carried out by deploying 4 vehicles in the environment of the intersection without signal lamps, and experimental parameters are set as follows:
when there are 4 vehicles running normally on the road, the authenticity of the 4 vehicle information has been determined.
Vehicle 1: 90m from the intersection, the speed of the vehicle is 15m/s, and the vehicle passes in the north-south direction;
vehicle 2: 100m from the intersection, and the speed of the vehicle is 15m/s, so that the vehicle runs in east-west direction;
vehicle 3: 90m from the intersection, and the vehicle speed is 13m/s, and the vehicle passes in the north-south direction;
vehicle 4: 90m from the intersection, and the speed of the vehicle is 13m/s, and the vehicle runs in the east-west direction;
vehicle 5 (broadcasting additional information to be confirmed): 120m from the intersection, the speed of the vehicle is 15m/s, and the vehicle runs in the east west direction.
All vehicles recognize and process the distributed information credibility based on the method, and specifically: when the vehicle 1 finds that possible virtual false information exists, the vehicle asks for evidence and sends out warning information to other surrounding vehicles, and the other vehicles recognize the credibility of the information after receiving the evidence and the warning information. The performance of the algorithm is verified by the additional vehicle 5 broadcasting possible false information via V2V.
As shown in fig. 3, surrounding vehicles, such as vehicles 2, 3, 4 assist the vehicle 1 in identifying this information. Vehicles 2, 3 cannot sense the presence of this vehicle by means of the onboard sensors, and therefore the confidence level will be 0; the vehicle 4 can sense the presence of the vehicle that issued the information through the vehicle-end sensor, and therefore, the reliability is 1. And finally, judging the reliability to be 1 through auxiliary information comparison. The technology can rapidly and effectively utilize auxiliary information to identify the false information, and the identification result is fed back to other vehicles through V2V.
Compared with the prior art, the method ensures the safety of the original data of the intelligent automobile in the distributed intelligent traffic field, makes up the security hole of remotely acquired information, and is the basis of all intelligent automobile decision algorithms.
The foregoing embodiments may be partially modified in numerous ways by those skilled in the art without departing from the principles and spirit of the invention, the scope of which is defined in the claims and not by the foregoing embodiments, and all such implementations are within the scope of the invention.
Claims (3)
1. The intelligent network vehicle-oriented distributed information credibility recognition and processing method is characterized in that in an information acquisition stage, vehicle-end sensing information is acquired through a vehicle sensor, and big data platform information and V2V information are acquired through a network cloud platform and other vehicle broadcast information and serve as auxiliary information for credibility judgment; in the remote information credibility judging stage, calculating credibility indexes of remote vehicle information to be determined through auxiliary information, and carrying out information fusion when credibility is acceptable, otherwise, broadcasting intrusion signals and information authenticity verification signals to other vehicles while carrying out no information fusion and additional caching on the remote vehicle information to be determined, and waiting for feedback results of other vehicles to cooperatively judge the authenticity of the information;
the vehicle sensor comprises: the system comprises a visual sensor, a laser radar sensor, a millimeter wave sensor and a vehicle-mounted positioning system;
the vehicle end perception information comprises: longitude and latitude altitude information, speed and acceleration information, and travel intention information;
the big data platform information comprises: vehicle end perception information of all vehicles, monitoring information of all roads and all road side information;
the V2V information includes: the perception information broadcast to the host vehicle by other vehicles comprises: vehicle end sensing information of other vehicles and surrounding vehicle state information thereof;
the remote vehicle information to be determined is as follows: V2V information to be identified;
the credibility index, namely the authenticity of other vehicle broadcast information to be identified, is specifically obtained byThe process comprises the following steps: phi is the original information set of the Internet cloud platform, < >>For the information set of remote vehicle information to be determined, < >>And identifying the empty set, wherein when the empty set is true, the empty set is not trusted, the reliability index is 0, and otherwise, the reliability index is 1.
2. The method for identifying and processing the distributed information credibility of the intelligent network-oriented vehicle according to claim 1, wherein the information fusion is that: and splicing the remote vehicle information to be determined and the stored state information of the vehicle before the remote information interaction operation, namely splicing the remote vehicle information and the state information into a matrix form identifiable by a vehicle algorithm.
3. The method for identifying and processing the reliability of distributed information for intelligent network-connected vehicles according to claim 1, wherein the additional cache is: the remote vehicle information to be determined is stored in an additional cache device for the next cycle of the identification operation.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108407808A (en) * | 2018-04-23 | 2018-08-17 | 安徽车鑫保汽车销售有限公司 | A kind of running car intelligent predicting system |
| CN110850777A (en) * | 2019-11-22 | 2020-02-28 | 温州大学瓯江学院 | Intelligent networking automobile cloud platform control operation system |
| CN111127931A (en) * | 2019-12-24 | 2020-05-08 | 国汽(北京)智能网联汽车研究院有限公司 | Vehicle road cloud cooperation method, device and system for intelligent networked automobile |
| CN111932918A (en) * | 2020-10-14 | 2020-11-13 | 之江实验室 | Traffic signal lamp information fusion decision method for intelligent internet vehicle |
| CN112113578A (en) * | 2020-09-23 | 2020-12-22 | 安徽工业大学 | Obstacle motion prediction method for automatic driving vehicle |
| CN112466141A (en) * | 2020-11-12 | 2021-03-09 | 深圳慧拓无限科技有限公司 | Vehicle-road-collaboration-oriented intelligent network connection end equipment interaction method, system and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108833833B (en) * | 2018-06-20 | 2021-02-02 | 长安大学 | Intelligent networking-oriented automobile scene image data sensing and cooperative processing system |
-
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Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108407808A (en) * | 2018-04-23 | 2018-08-17 | 安徽车鑫保汽车销售有限公司 | A kind of running car intelligent predicting system |
| CN110850777A (en) * | 2019-11-22 | 2020-02-28 | 温州大学瓯江学院 | Intelligent networking automobile cloud platform control operation system |
| CN111127931A (en) * | 2019-12-24 | 2020-05-08 | 国汽(北京)智能网联汽车研究院有限公司 | Vehicle road cloud cooperation method, device and system for intelligent networked automobile |
| CN112113578A (en) * | 2020-09-23 | 2020-12-22 | 安徽工业大学 | Obstacle motion prediction method for automatic driving vehicle |
| CN111932918A (en) * | 2020-10-14 | 2020-11-13 | 之江实验室 | Traffic signal lamp information fusion decision method for intelligent internet vehicle |
| CN112466141A (en) * | 2020-11-12 | 2021-03-09 | 深圳慧拓无限科技有限公司 | Vehicle-road-collaboration-oriented intelligent network connection end equipment interaction method, system and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 基于区块链的智能网联车队协同轨迹预测系统;王仁生 等;网络与信息安全学报;第6卷(第3期);全文 * |
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