CN115022811A - Motorcade collaborative track prediction system and method based on block chain and position information - Google Patents

Abstract

The system and the method for forecasting the team collaborative track based on the block chain and the position information acquire the position information of networked team vehicles in real time based on the position information technology, simultaneously acquire infrastructure information around the vehicles by combining a vehicle-mounted camera and a millimeter wave radar, apply the block chain technology to the networked team through the characteristics of incapability of distorting and decentralizing the information of the block chain technology and the like, ensure that the communication among the vehicles in the networked team is more reliable, forecast the track of the vehicles based on a long-time memory network method, realize that the networked team vehicles can safely and effectively drive complex traffic environments, accurately forecast the future driving track of the surrounding vehicles, and guarantee the driving safety of the vehicles. The invention realizes networking and cooperative driving of the networked motorcade by utilizing a forward-edge block chain technology, a position information technology and a vehicle track prediction technology, and reduces the potential safety hazard of motorcade automobiles in the driving process.

Description

Motorcade collaborative track prediction system and method based on block chain and position information

Technical Field

The invention belongs to the field of Internet of vehicles application, and relates to intelligent Internet fleet collaborative track prediction application based on a block chain and position information.

Background

The automobile industry is a special industry, and because safety of passengers is involved, requirements on safety, reliability and other performances of the vehicle during running are very strict. With the development of communication technology relied on by the internet of vehicles, the security of the internet of vehicles becomes a focus of attention while obtaining convenience brought to the society. The field of the internet of vehicles utilizes information and communication technology to realize cooperative communication among vehicles, between the vehicles and the surrounding environment and between the vehicles and personnel, and is used for judging the relative positions among the vehicles and the positions of the vehicles in the surrounding environment, so that the driving experience and safety guarantee of passengers are improved. However, once the vehicle has accessed itself as a node into the network, exposing itself to the public environment, the security of the passengers is severely compromised when the network communication is tampered with by an attacker, snoops or receives false messages, receives false indications.

The internet of vehicles needs to integrate various information of roads, pedestrians, environments, vehicles and passengers in real time, and meanwhile, the information needs to be shared by other vehicles around. Therefore, effective fusion of information and strong privacy protection are the key for restricting the current development of the internet of vehicles.

In a distributed network structure of a block chain, a network and an encryption algorithm are completed through a distributed consensus algorithm to ensure effective proceeding of point-to-point transmission. The distributed consensus algorithm can ensure that the network can effectively perform self-maintenance and perform information fusion, and the encryption algorithm ensures the safety of point-to-point transmission. The working scene of the block chain technology is similar to that of a vehicle network, and peer-to-peer networks and the vehicle network which are served by the block chain have the characteristics of large number of nodes, frequent node adding and quitting, communication among the nodes through information transmission and the like.

Therefore, the method and the device have the advantages that the good encryption performance and self-maintenance performance of the block chain technology are utilized, and the safety of the vehicle network is improved and the construction and maintenance cost of the infrastructure of the vehicle network is reduced based on the application scene of the block chain in the vehicle network. A blockchain network is formed between networked fleet vehicles and between the vehicles and the surrounding environment based on blockchain technology. The networked fleet vehicle can share the position information and the surrounding environment information with other vehicles or other subjects in the internet of vehicles, so that the networked fleet vehicle can rapidly master the surrounding environment and the vehicle condition in a short time. The networked fleet vehicles acquire images of road traffic conditions through the cameras and the millimeter wave radars, and perform object detection on the vehicles in the images. The detected vehicle is subjected to continuous image tracking, the next driving intention of the vehicle is measured by combining with real-time position information, and the traffic safety in the driving process is improved.

Disclosure of Invention

The invention aims to realize a networked fleet cooperative track prediction system and method based on a block chain technology, a position information technology and an image information processing technology, and aims at realizing fleet cooperative track prediction in a complex driving environment of a networked fleet so as to improve the traffic safety in the driving process.

The purpose of the invention is realized by the following technical scheme:

the motorcade collaborative track prediction system and method based on the block chain and the position information comprise the following steps:

(1) each networked fleet vehicle is equipped with onboard sensors, computers and communication equipment for data collection, processing and sharing.

(2) Acquiring position information of all vehicles of the networked fleet in real time based on a GPS or Beidou satellite positioning system terminal device, and generating running tracks of all vehicles of the networked fleet according to the position information;

(3) acquiring surrounding road condition information of a vehicle and automatically detecting information related to traffic in real time by using a vehicle-mounted camera and a millimeter wave radar;

(4) the position information, the road conditions around the vehicle, the environmental information and the like collected and obtained by the vehicle in the running process are stored in each networked automobile, when the information of a certain vehicle needs to be inquired, the networked automobile only needs to inquire the stored information of the networked automobile, so the possibility that the information is falsified does not exist, but the information stored in each networked automobile needs to be guaranteed to be reliable and effective;

(5) a block chain technology is utilized to establish a distributed trust management mechanism for a vehicle-mounted network to realize safe interaction between internet motorcades;

(6) in an intelligent networked motorcade formed by networked automobiles close to each other, block chain networks are formed among the motorcade vehicles and between the vehicles and the surrounding environment. And each node in the block chain network collects an image of the road traffic condition through a camera and a millimeter wave radar, and detects the object of the vehicle in the image. The detected vehicle is subjected to continuous image tracking, and the next driving intention of the vehicle is detected by combining with real-time position information.

(7) The vehicles in the networked fleet can share the position information and the surrounding environment information of the vehicles with other vehicles or other subjects in the networked vehicle through the information received by the sensors of the vehicles, so that the vehicles can rapidly master the surrounding environment and the vehicle condition in a short time. Therefore, the vehicle can calculate the safe distance between the vehicle and other objects in a short time by combining the parameters of the sensor of the vehicle, and the traffic safety is improved.

Compared with the prior art, the invention has the beneficial effects that:

(1) and (3) multi-information fusion processing: the system fuses various information of roads, pedestrians, environments, vehicles and passengers in real time, and relates to position information processing, image data and video data processing and vehicle track prediction.

(2) And (3) network fleet information sharing based on the block chain: by using the block chain technology, self-maintenance is realized among all vehicles in the networked fleet through a distributed consensus mechanism, the transaction in the network is audited, and when the audit is passed, the information is written into the block, the confirmation is obtained, and meanwhile, the change or the deletion can not be carried out any more. Each networked fleet vehicle node in the system can imitate a block chain, and complete self-organization and self-maintenance of the network in a certain time and area by using a proper distributed consensus mechanism. Meanwhile, by using proper cryptographic algorithms such as an identification cryptographic algorithm and the like, the requirement of rapidly authenticating the identity of each vehicle in the networked fleet can be met, and the privacy of information sharing among the vehicles is ensured. The block chain technology can also restrict the rights and obligations of both sides of the communication vehicle through intelligent contracts, and the decentralization concept is suitable for realizing the direct communication and information sharing between the vehicles in the vehicle self-organizing network.

Drawings

FIG. 1 is a block diagram of intelligent networked fleet collaborative trajectory prediction

FIG. 2 is a flow chart of intelligent networked fleet collaborative trajectory prediction

Detailed Description

The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.

The invention fully utilizes the existing position positioning technology, image processing technology and vehicle track prediction technology, and realizes the accuracy of the networked fleet collaborative track prediction precision by integrating the resources of the existing various technologies.

Fig. 1 is a block diagram of cooperative track prediction of an intelligent networked fleet, wherein vehicles of the networked fleet are all provided with a vehicle-mounted navigation satellite positioning terminal and vehicle-mounted sensors (cameras and millimeter wave radars), and networking and data information sharing are realized among the vehicles in the networked fleet through a wireless network. The block chain realizes the safety and stability of mutual communication when networking of the networked motorcade and data information sharing. The long-time and short-time memory network algorithm carries out networked fleet cooperative track prediction based on the acquired real-time information integrating roads, pedestrians, environments, vehicles and passengers.

Fig. 2 is a flow chart of intelligent networked fleet collaborative trajectory prediction, and it can be seen from fig. 2 that the method of the invention includes the following steps:

firstly, the vehicle collects self parameter information and surrounding environment information by using a vehicle-mounted sensor, combines a block chain technology, encrypts data, adds a digital signature of the vehicle, packages the data into blocks, and can receive messages by other vehicles within a range without passing through a central management node.

After the other vehicles receive the messages and decrypt the messages, the data collected by the sensor devices of the other vehicles are combined with the data received by the vehicles and the data are compared and verified with the data received by the vehicles, the credibility of the verification information is given, and then the verification information is packaged into blocks and uploaded to a block chain.

Finally, after each vehicle uploads verification information to the block chain, after all vehicles within the range receive the block chain verification information, calculating information credibility of data in the block chain, and regarding the message with the credibility higher than a threshold value as a credible message, and broadcasting the credible message; and regarding the messages with the reliability lower than the threshold value as the message sources are not credible, and rejecting the messages. By utilizing the characteristics of the block chain, the information of the secondary communication mode is not easy to be falsified, and the influence of information from forged vehicle information sources can be reduced and the communication safety can be ensured by adopting the mode that a plurality of vehicles combine the surrounding environment to give a verification result.

The vehicles in the networked fleet can share the position information and the surrounding environment information of the vehicles with other vehicles or other subjects in the networked vehicle through the information received by the sensors of the vehicles, so that the vehicles can rapidly master the surrounding environment and the vehicle condition in a short time. By utilizing a long-time memory network method, each node in the roadside infrastructure and the intelligent networked fleet can prejudge the running tracks of surrounding vehicles and share the predicted results.

In a word, the method can support the cooperative track prediction of the intelligent networked fleet, and improve the precision of the vehicle track prediction by introducing multi-source information by fusing various information of roads, pedestrians, environments, vehicles and passengers in real time and relating to position information processing, image data and video data processing and vehicle track prediction.

Claims (1)

1. The motorcade collaborative track prediction system and method based on the block chain and the position information are characterized by comprising the following steps:

(1) each car is equipped with onboard sensors, computer and communication equipment for data collection, processing and sharing.

(2) The method comprises the steps that position information of all vehicles of an internet fleet is collected in real time based on a GPS or Beidou satellite positioning system;

(3) acquiring surrounding road condition information of a vehicle and automatically detecting information related to traffic in real time by using a vehicle-mounted camera and a millimeter wave radar;

(4) the information acquired by the vehicle is stored in each networked automobile, and when the information of a certain vehicle needs to be inquired, the networked automobile only needs to inquire the stored information of the networked automobile, so that the possibility that the information is tampered does not exist, but the information stored in each networked automobile needs to be guaranteed to be reliable and effective.

(5) A distributed trust management mechanism is established for a vehicle-mounted network by using a block chain technology to realize safe interaction among networked fleets;

(6) in an intelligent networked motorcade formed by networked automobiles close to each other, block chain networks are formed among the motorcade vehicles and between the vehicles and the surrounding environment. And each node in the block chain network collects images of road traffic conditions through a camera and a millimeter wave radar, and detects the vehicle in the images. The detected vehicle is subjected to continuous image tracking, and the next driving intention of the vehicle is detected by combining with real-time position information.

(7) The vehicles in the networked fleet can share the position information and the surrounding environment information of the vehicles with other vehicles or other subjects in the networked vehicle through the information received by the sensors of the vehicles, so that the vehicles can rapidly master the surrounding environment and the vehicle condition in a short time. Therefore, the vehicle can calculate the safe distance between the vehicle and other objects in a short time by combining the parameters of the sensor of the vehicle, and the traffic safety is improved.

Images