AU2020104213A4

AU2020104213A4 - Blockchain for 5g-enabled iot for industrial automation

Info

Publication number: AU2020104213A4
Application number: AU2020104213A
Authority: AU
Inventors: Aman Kataria; Sandhya Makkar; Puneet Mittal; Sita Rani; Navjot Sidhu; Rajeev Tiwari
Original assignee: Rani Sita Dr
Current assignee: Rani Sita Dr
Priority date: 2020-12-22
Filing date: 2020-12-22
Publication date: 2021-03-11
Anticipated expiration: 2028-12-22

Abstract

A SYSTEM AND METHOD FOR TRAFFIC SURVEILLANCE TO IDENTIFY MOVING AND STATIONARY VEHICLES IN REAL TIME A driverless automobile control system and a method based on 5G and a blockchain is 5 disclosed. The driverless automobile control system comprises an automobile information acquisition unit (001), an automobile speed calculation unit (003), an automobile control unit (005), an automobile driving track acquisition unit (002), a communication unit (004) and a server (006). The standard speed and the actual speed of the automobile are calculated; a speed adjustment variable quantity at the current time is calculated according 10 to a preset accelerator adjustment factor and a preset vehicle speed adjustment slack variable quantity; the speed adjustment variable quantity is determined according to the speed adjustment variable quantity of the last time and the speed adjustment variable quantity of the current time, so that the automobile driving can be controlled according to the speed adjustment variable quantity, the control response of the automobile speed is 15 fast, and the stability and the safety of the driverless automobile are improved; the actual driving track data of the automobile can be transmitted to the server (006) for standby application in real time through the 5G technology; the blockchain technology is applied to storage of the track data of actual driving, so that the authenticity and reliability of the track data of actual driving are improved. Car information collection Car driving track trace set unit acquisition unit (001) (002) 11 1, Car Speedometer Communication Unit calculation unit (004) (003) Car Control Unit Server 20 (005) (006) Figure 1 Schematic Diagram of the driverless vehicle control system based on 5G and block chain - 17-

Description

Australian Government IP Australia INNOVATION PATENT APPLICATION AUSTRALIA PATENT OFFICE

1. TITLE OF THE INVENTION

BLOCKCHAIN FOR 5G-ENABLED IOT FOR INDUSTRIAL AUTOMATION

2. APPLICANTS (S) NAME NATIONALITY ADDRESS

Aman Kataria INDIAN Department of Electrical and Instrumentation, Thapar Institute of Engineering and Technology, Patiala, India. Dr. Sandhya Makkar INDIAN Department of Operation and System, Lal Bahadur Shastri Institute of Management, Delhi, India.

Dr. Sita Rani INDIAN Department of Computer Science and Engineering, Gulzar Institute of Engineering and Technology, Gulzar Group of Institute,GT Road, Khanna, Ludhiana, Punjab.

Rajeev Tiwari INDIAN Department of Virtualization, School of Computer Science, University of Petroleum and Energy Studies.

Navjot Sidhu INDIAN Department of Computer Science and Engineering, IKG Punjab Technical University, Kapurthala Punjab

Dr. Puneet Mittal INDIAN CSE Department, Baba Banda Singh Bahadur Engineering College, Fatehgarh Sahib, Punjab, India. 3. PREAMBLE TO THE DESCRIPTION COMPLETE SPECIFICATION

The following specification particularly describes the invention and the manner in which it is to be performed

BLOCKCHAIN FOR 5G-ENABLED IOT FOR INDUSTRIAL AUTOMATION

TECHNICAL FIELD

[0001] The present invention relates to blockchain for 5G-enabled IoT for industrial automation, and more particularly to an unmanned car control system and method of unmanned driving based on 5G and blockchain.

BACKGROUND

[0002] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication.

[0003] With rapid development of science and technology, the popularity of automobiles has become more and more widespread, but traditional automobile driving has many safety problems due to the uncertainty of human operation. As a result, smart cars have emerged. In the beginning, smart cars only added some safety-improving auxiliary driving functions on the basis of traditional cars. However, with the continuous development of technology, smart cars have gradually developed into driverless cars.

[0004] At present, in terms of controlling the speed of the existing driverless cars, because of the non-linear relationship between the speed, it is difficult to control the speed in time and accurately through the linear proportional method, which seriously affects the driving of driverless cars.

[0005] The 5G network is the fifth-generation network used in the development of mobile communication networks. Compared with the previous four-generation mobile network (4G), the 5G network exhibits more enhanced functions in the actual application process. The transmission speed can reach tens of gigabytes per second, which is hundreds of times faster than 4G networks. Its high data rate and low latency characteristics can serve driverless cars well. Blockchain technology is also a hot technology in recent years. Its non-tamperable and traceable characteristics can also serve unmanned vehicles well. Therefore, how to apply 5G network and blockchain technology to the field of unmanned driving is a problem that needs to be solved urgently.

[00061 Moreover, the existing image acquisition modules of unmanned vehicles either use a telephoto lens to acquire images in front of the car, or a short focus lens to acquire images in front of the car. In this way, the image acquisition module has a narrow monitoring range for obstacles in front of the car, it is not conducive to the safe driving of driverless cars. In addition, when the collected images are classified, because most of the object-based classification methods are used, the accuracy of classification is not high, and obstacles may be inaccurate.

[0007] Therefore, the present disclosure overcomes the above-mentioned problem of lack of efficiency in prediction associated with the traditionally available method or system, any of the above-mentioned inventions can be used with the presented disclosed technique with or without modification.

[00081 All publications herein are incorporated by reference to the same extent as if each individual publication or patent application were specifically and individually indicated to be incorporated by reference. Where a definition or use of a term in an incorporated reference is inconsistent or contrary to the definition of that term provided herein, the definition of that term provided herein applies and the definition of that term in the reference does not apply.

[0009] As used in the description herein and throughout the claims that follow, the meaning of "a," "an," and "the" includes plural reference unless the context clearly dictates otherwise. Also, as used in the description herein, the meaning of "in" includes "in" and "on" unless the context clearly dictates otherwise.

[0010] All methods described herein can be performed in any suitable order unless otherwise indicated herein or otherwise clearly contradicted by context. The use of any and all examples, or exemplary language (e.g. "such as") provided with respect to certain embodiments herein is intended merely to better illuminate the invention and does not pose a limitation on the scope of the invention otherwise claimed. No language in the specification should be construed as indicating any non-claimed element essential to the practice of the invention.

OBJECTS OF THE INVENTION

[0011] It is an object of the present disclosure to provide a system and method for highly accurate unmanned car control system based on 5G and blockchain.

[0012] It is an object of the present invention to provide system and method for safe driving with image acquisition module having broad monitoring range.

SUMMARY

[0013] The present disclosure relates to a 5G and blockchain-based unmanned car control system and method.

[0014] One should appreciate that although the present disclosure has been explained with respect to a defined set of functional modules, any other module or set of modules can be added/deleted/modified/combined and any such changes in architecture/construction of the proposed system are completely within the scope of the present disclosure. Each module can also be fragmented into one or more functional sub-modules, all of which also completely within the scope of the present disclosure.

[0015] The present invention adopts the following technical solutions: an unmanned car control system based on 5G and blockchain, including a car information collection unit, a car speed calculation unit, a car control unit, a car driving trajectory collection unit, Communication unit and server. The car information collection unit is used to collect position information of the car at the current time; The vehicle speed calculation unit is configured to determine a driving route mark and a route length corresponding to the driving route mark in a built-in map according to the location information, and determine the driving time of the car on the current route, according to the route length; Determine the true speed of the car with the driving time, and determine the standard speed corresponding to the driving route mark according to a preset correspondence set; The automobile control unit is configured to calculate the current speed difference of the automobile according to the standard speed and the real speed, and determine the current time according to the speed difference, a preset throttle adjustment factor and a preset vehicle speed adjustment slack variable According to the speed adjustment change amount of the previous time and the current time speed adjustment change amount, determine the speed adjustment amount, and control the driving of the car according to the speed adjustment amount; The car driving trajectory collecting unit is used to collect trajectory data of the actual driving of the car on the built-in map; The communication unit is used to transmit the collected actual driving trajectory data to the server through the 5G network; The server is used to store the trajectory data of the actual driving, and generate blocks from the trajectory data of the actual driving, and broadcast the generated blocks to the blockchain system, so that the generated blocks are added to the district Blockchain network.

[00161 By calculating the standard speed and actual speed of the car, and then according to the preset throttle adjustment factor and preset vehicle speed adjustment slack variable to determine the current time speed adjustment change, and then adjust the change amount and the current time speed according to the previous time speed By adjusting the amount of change and determining the amount of speed adjustment, the driving of the car can be controlled according to the speed adjustment amount, so that the speed control response of the car is fast, thereby improving the stability and safety of the driverless car; at the same time, through 5G technology, Real-time transmission of the actual driving trajectory data of the car to the server for backup; moreover, the application of the blockchain technology to the storage of the actual driving trajectory data improves the authenticity and reliability of the actual driving trajectory data.

[00171 Further, the collecting the position information of the car at the current time specifically includes the following steps: Collect the positioning information of the car at the current time through the GPS positioning module, and transmit the positioning information to the car speed calculation unit; Collect and process the image data in front of the car through the ultra-wide-angle dual-lens to determine whether there are obstacles in front of the car. Among them, the ultra-wide-angle dual-lens is two ultra-wide-angle lenses of the same model with fixed relative positions and completed calibration; If there is an obstacle, the disparity map and the pitch depth map are calculated according to the two corresponding images collected by the ultra-wide-angle dual lens, and the distance between the obstacle and the car is obtained. If the distance between the obstacles is small, Transmitting the direction and distance information of the obstacle to the car control unit; If the distance between the obstacles is relatively large and is within the monitoring range of the telephoto single lens, the obstacle detection algorithm calculates the position information of the obstacle according to the image collected by the telephoto single lens, and the position of the obstacle Information is transmitted to the car control unit; Obtain forward route information through an obstacle detection algorithm based on the image collected by the telephoto single lens, and transmit the forward route information to the car control unit ; The car control unit controls the driving of the car according to the received information.

[00181 Obstacle information at a close distance in front of the car is collected through the ultra-wide-angle dual lens, and obstacle information at a far distance in front of the car is collected through a telephoto single lens. In this way, the perfect combination of the ultra-wide-angle dual lens and the telephoto single lens realizes the large front of the car. The monitoring of obstacle information in the range greatly improves the safety and reliability of unmanned vehicles.

[0019] Further, the coverage angle of the ultra-wide-angle lens is 115-145°, the detection interval of the ultra-wide-angle lens is 22-28 m, and the focal length of the ultra wide-angle lens is less than 4 mm. The coverage angle of the telephoto single lens is 11 22, the detection distance of the telephoto single lens is 80-145m, and the focal length of the telephoto single lens is greater than 9mm.

[0020] A 5G and blockchain-based driverless car control method includes the following steps: Collect the position information of the car at the current time; Determine the driving route mark and the length of the route corresponding to the driving route mark in the built-in map according to the location information, and determine the driving time of the car on the current route, and determine the true nature of the car according to the route length and the driving time Speed, and determine the standard speed corresponding to the driving route mark according to a preset correspondence set; Calculate the current speed difference of the car according to the standard speed and the real speed, and determine the current time speed adjustment change according to the speed difference, the preset throttle adjustment factor and the preset vehicle speed adjustment slack variable. One-time speed adjustment change amount and current time speed adjustment change amount, determine the speed adjustment amount, and control the driving of the car according to the speed adjustment amount; Collect the actual driving trajectory data of the car on the built-in map; Transmit the collected actual driving trajectory data to the server through the 5G network;

The trajectory data of the actual driving is stored, and the trajectory data of the actual driving is generated into blocks, and the generated blocks are broadcast to the blockchain system at the same time, so that the generated blocks are added to the blockchain network.

[0021] Compared with the existing technology, the advantages of the present invention are: By calculating the standard speed and actual speed of the car, and then according to the preset throttle adjustment factor and preset vehicle speed adjustment slack variable to determine the current time speed adjustment change, and then adjust the change amount and the current time speed according to the previous time speed By adjusting the amount of change and determining the amount of speed adjustment, the driving of the car can be controlled according to the amount of speed adjustment, so that the speed control response of the car is fast, thereby improving the stability and safety of the driverless car; Through the 5G technology, the actual driving trajectory data of the car can be transmitted to the server for backup in real time; at the same time, the blockchain technology is applied to the storage of the actual driving trajectory data, which improves the authenticity and reliability of the actual driving trajectory data Set; Obstacle information at a close distance in front of the car is collected through the ultra-wide-angle dual lens, and obstacle information at a far distance in front of the car is collected through a telephoto single lens. In this way, the perfect combination of the ultra-wide-angle dual lens and the telephoto single lens realizes the large front of the car. Monitoring of obstacle information in the range greatly improves the safety and reliability of driverless cars; The probability function Yp, q(wp, wq) is calculated by the spectral value of the pixel on the image, the three-dimensional coordinate value and the weight and other parameters, and then the object-based classification method is classified by the probability function Yp, q(wp, wq) The resulting classification result map is post-processed to obtain pixel-level three dimensional classification, which greatly improves the accuracy of classification, thereby improving the accuracy of obstacle judgment, and greatly improving the safety of unmanned driving.

BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification.

The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0023] Figure 1, illustrates a schematic diagram of the control system of the present invention.

[0024] Figure 2, Flow diagram of the driverless vehicle control system based on 5G and blockchain.

DETAILED DESCRIPTION

[0025] In the following description, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. It will be apparent to one skilled in the art that embodiments of the present invention may be practiced without some of these specific details.

[0026] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.

[00271 Exemplary embodiments will now be described more fully hereinafter with reference to the accompanying drawings, in which exemplary embodiments are shown. This invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. These embodiments are provided so that this disclosure will be thorough and complete and will fully convey the scope of the invention to those of ordinary skill in the art. Moreover, all statements herein reciting embodiments of the invention, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Additionally, it is intended that such equivalents include both currently known equivalents as well as equivalents developed in the future (i.e., any elements developed that perform the same function, regardless of structure).

[0028] Each of the appended claims defines a separate invention, which for infringement purposes is recognized as including equivalents to the various elements or limitations specified in the claims. Depending on the context, all references below to the "invention" may in some cases refer to certain specific embodiments only. In other cases it will be recognized that references to the "invention" will refer to subject matter recited in one or more, but not necessarily all, of the claims.

[0029] Various terms as used herein are shown below. To the extent a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.

[00301 Referring to Figure 1, provides a 5G and blockchain-based driverless car control system, including a car information collection unit (001), a car speed calculation unit (003), a car control unit (005), a car driving trajectory collection unit (002), a communication unit (004), and a server (006).

[0031] In a preferred embodiment, The car information collection unit (001) is used to collect the position information of the car at the current time, specifically including the following steps: Collect the positioning information of the car at the current time through the GPS positioning module, and transmit the positioning information to the car speed calculation unit (003) (S2); Collect and process the image data in front of the car through the ultra-wide-angle dual-lens to determine whether there are obstacles in front of the car (S3). Among them, the ultra-wide-angle dual-lens is two ultra-wide-angle lenses of the same model with a fixed relative position and calibration. The coverage angle is 115~

145, the detection distance of the ultra-wide-angle lens is 22-28m, and the focal length

of the ultra-wide-angle lens is less than 4mm; If there is an obstacle (S4), the disparity map and the distance depth map are calculated according to the two corresponding images collected by the ultra-wide-angle dual lens, and the distance between the obstacle and the car is obtained (S5). If the distance between the obstacles is small (S6), the direction and distance information of the obstacle is transmitted to the car control unit (001); If the distance between obstacles is large and within the monitoring range of the telephoto single lens, the obstacle detection algorithm calculates the position information of the obstacle according to the image collected by the telephoto single lens (S7), and the position information of the obstacle transmitted to the car control unit (001), the coverage angle of the telephoto single lens is 11-22°, the detection distance of the telephoto single lens is 80

145m, and the focal length of the telephoto single lens is greater than 9mm; Obtain the forward route information through the obstacle detection algorithm based on the image collected by the telephoto single lens, and transmit the forward route information to the car control unit (001) (S8); The car control unit (001) controls the driving of the car according to the received information.

[0032] The car speed calculation unit (003) is used to determine the driving route mark and the length of the route corresponding to the driving route mark according to the positioning information in the built-in map, and determine the driving time of the car on the current route, and determine the real speed of the car according to the length and driving time of the route , and determine the standard speed corresponding to the driving route mark according to the preset correspondence set.

[00331 The car control unit (001) is used to calculate the current speed difference of the car according to the standard speed and the real speed, and determine the current time speed adjustment change according to the speed difference, the preset throttle adjustment factor and the preset vehicle speed adjustment slack variable. One-time speed adjustment change amount and current time speed adjustment change amount, determine speed adjustment amount, and control car driving according to speed adjustment amount; Car driving trajectory acquisition unit (002) is used to collect trajectory data of the actual driving of the car in the built-in map; The communication unit (004) is used to transmit the collected actual driving trajectory data to the server (006) through the 5G network; The server (006) is used to store the actual driving trajectory data and generate blocks from the actual driving trajectory data, and at the same time broadcast the generated blocks to the blockchain system, so that the generated blocks are added to the blockchain network.

[0034] By calculating the standard speed and actual speed of the car, and then according to the preset throttle adjustment factor and preset vehicle speed adjustment slack variable to determine the current time speed adjustment change, and then adjust the change amount and the current time speed according to the previous time speed By adjusting the amount of change and determining the amount of speed adjustment, you can control the driving of the car according to the amount of speed adjustment, so that the speed control response of the car is fast, thereby improving the stability and safety of the driverless car; at the same time, through 5G technology, it can be real-time The actual driving trajectory data of the car is transmitted to the server (006) for backup; moreover, the actual driving trajectory data is stored through the blockchain technology, which improves the authenticity and reliability of the actual driving trajectory data.

[00351 The above-mentioned image data of the front of the car is collected and processed through the ultra-wide-angle dual-lens, specifically: S21: Collect image data in front of the car through the ultra-wide-angle dual lens; S22: Use an object-based classification method to classify the collected images in front of the car, and output a classification result map; S23: According to the output classification result map, obtain a set of vectors W={wl, w2,..., wM} composed of M random variables, where wp is the pixel at position p in the image, and wq is the image The middle position is the pixel of q, M is the total number of pixels in the image, and the probability function Yp, q(wp, wq) of the distribution is calculated: Among them, Ap is the weight of pixel wp, Aq is the weight of pixel wq, Bp is the three-dimensional coordinate of pixel wp, Bq is the three dimensional coordinate of pixel wq, V(wp, wq) is the judgment function, if pixel wp Adjacent to the pixel point wq, then V(wp, wq) = 1. If the pixel point wp is not adjacent to the pixel point wq, then V(wp, wq) = 0, fp is the spectral value of the pixel point wp, fq is The spectral value of the pixel point wq; S24: Use the probability function Yp, q(wp, wq) to post-process the classification result graph to obtain a pixel-level three-dimensional level classification. The probability function Yp, q(wp, wq) is calculated by the spectral value of the pixel on the image, the three-dimensional coordinate value and the weight and other parameters, and then the object-based classification method is classified by the probability function Yp, q(wp, wq) The resulting classification result map is post processed to obtain pixel-level three-dimensional classification, which greatly improves the accuracy of classification, thereby improving the accuracy of obstacle judgment, and greatly improving the safety of unmanned driving. The above-mentioned trajectory data collected from actual driving and transmitted to the server (006) via the 5G network is encrypted trajectory data. The server (006) is a cloud server (006). The consensus mechanism adopted by the blockchain is PoW consensus mechanism or PoS consensus mechanism or DPoS consensus mechanism. The above technical solution also includes a backup server (006), a backup server (006) for obtaining and storing actual driving track data from the server (006) in real time, and the backup server (006) is also a cloud server.

[0036] This embodiment also provides a 5G and blockchain-based unmanned car control method, which includes the following steps: Collect the position information of the car at the current time; Determine the driving route mark and the length of the route corresponding to the driving route mark in the built-in map according to the location information, and determine the driving time of the car in the current route, determine the real speed of the car according to the length of the route and the driving time, and according to the preset correspondence The relationship set determines the standard speed corresponding to the driving route mark; Calculate the current speed difference of the car according to the standard speed and the real speed, determine the current time speed adjustment change according to the speed difference, preset throttle adjustment factor and preset vehicle speed adjustment slack variable, and according to the previous time speed adjustment change The amount of speed adjustment change amount and the current time, determine the speed adjustment amount, and control the driving of the car according to the speed adjustment amount; Collect the actual driving trajectory data of the car on the built in map; Transmit the collected actual driving trajectory data to the server (006) through the 5G network; Store the actual driving trajectory data, and generate blocks from the actual driving trajectory data, and broadcast the generated blocks to the blockchain system, so that the generated blocks are added to the blockchain network.

[00371 In this embodiment, the standard speed and actual speed of the car are calculated, and then the speed adjustment change amount at the current time is determined according to the preset throttle adjustment factor and the preset vehicle speed adjustment slack variable, and then the speed adjustment change amount and the current time are adjusted according to the previous time speed. Time speed adjustment change amount, determine the speed adjustment amount, you can control the car driving according to the speed adjustment amount, so that the speed control response of the car is fast, thus improving the stability and safety of the driverless car; through 5G technology, real-time The actual driving trajectory data of the car is transmitted to the server (006) for backup; at the same time, the blockchain technology is applied to the storage of the actual driving trajectory data, which improves the authenticity and reliability of the actual driving trajectory data; through the ultra-wide-angle dual The lens collects the obstacle information at a close distance in front of the car, and collects the obstacle information at a far distance in front of the car through a telephoto single lens. In this way, the perfect combination of the ultra-wide-angle dual lens and the telephoto single lens realizes the large-scale obstacle information in front of the car The monitoring of unmanned vehicles greatly improves the safety and reliability of driverless cars; the probability function Yp, q(wp, wq) is calculated by the spectral value, three-dimensional coordinate value and weight of the pixels on the image, and then passed The probability function Yp, q(wp, wq) post-processes the classification result map classified by the object-based classification method to obtain a pixel-level three-dimensional classification, which greatly improves the accuracy of the classification, thereby improving the The accuracy of obstacle judgment has greatly improved the safety of unmanned driving.

[0038] The above are only preferred specific embodiments of the present invention, but the protection scope of the present invention is not limited to this. Anyone familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution of the present invention Equivalent replacements or changes to its inventive concept should all fall within the protection scope of the present invention.

Dated this 21" of December 2020:

Claims

We claim: 1. An unmanned car control system based on 5G and blockchain, comprising: A car information collection unit (001), a car speed calculation unit (003), a car control unit (005), a car driving trajectory collection unit (002), a communication unit (004) and a server (006); and characterised in that, a car information collection unit (001) to collect position information of the car at the current time;

a vehicle speed calculation unit (003) to determine a driving route mark, a route length, that corresponds to a driving route mark in a built-in map, that then determines the driving time of the car on the current route, the true speed of the car with the driving time;

an automobile control unit (005) to calculate the current speed difference of the automobile in accordance with the standard speed and the real speed, that then determines the current time in accordance with the speed difference;

a car driving trajectory collecting unit (002) to collect the trajectory data of the actual driving of the car on the built-in map;

a communication unit (004) to transmit the collected actual driving trajectory data to the server (006) through the 5G network;

a server (006) to store the trajectory data of the actual driving, and to generate blocks from the trajectory data of the actual driving, and to broadcast the generated blocks to the blockchain system, so that the generated blocks are added to the district Blockchain network.
2. The unmanned car control system based on 5G and blockchain as claimed in claim 1, wherein, said system collects the position information of the car at the current time involves the steps of: Collecting the positioning information of the car at the current time, using a GPS positioning module, and transmit the positioning information to the car speed calculation unit (003) (S2);

Collecting and processing the image data in front of the car, using the ultra wide-angle dual-lens to determine the obstacles in front of the car, wherein the ultra-wide-angle dual-lens is two ultra-wide-angle lenses of the same model with fixed relative positions and completed calibration (S3);

Calculating, the disparity map and the pitch depth map (S5), in case of an obstacle (S4), based on the two corresponding images collected by the ultra-wide angle dual lens, and then obtaining the distance between the obstacle and the car, checking the distance between the obstacles, and then transmitting the direction and distance information of the obstacle to the car control unit (005) if the distance is small (S6);

Calculating the position information in case the distance between the obstacles is relatively large (S7) and is within the monitoring range of the telephoto single lens, with the help of the obstacle detection algorithm, based on the image collected by the telephoto single lens, and then transmitting the position of the obstacle information to the car control unit (005);

Obtaining forward route information, through an obstacle detection algorithm, based on the image collected by the telephoto single lens, and then transmitting the forward route information to the car control unit (005) (S8);

Controlling the driving of the car by the car control unit (005), based on the received information.
3. The 5G and blockchain-based driverless car control system as claimed in claim 1, wherein the coverage angle of the ultra-wide-angle lens is 115-145°, and the detection distance of the ultra-wide-angle lens is 22-28m , the focal length of the ultra-wide-angle lens is less than 4mm.
4. The unmanned car control system based on 5G and blockchain as claimed in claim 1, wherein the coverage angle of the telephoto single lens is 11-22°, and the detection distance of the telephoto single lens is 80-145m, and the focal length of the telephoto single lens is greater than 9mm.
5. The 5G and blockchain-based driverless car control system as claimed in claim 1, wherein the image data of the front of the car is collected and processed through the ultra-wide-angle dual-lens, specifically:

Collecting (Si) image data in front of the car, using an ultra-wide-angle dual lens; Using an object-based classification method to classify the collected images in front of the car, and output a classification result map;

Obtaining a set of vectors W={wl, w2,...,wM}, composed of M random variables, based on the output classification result map, wherein wp is the pixel at position p in the image, wq is the pixel at position q in the image, and M is the total number of pixels in the image;

Calculating the probability function Yp, q(wp, wq) of the distribution, wherein, Ap is the weight of pixel wp, Aq is the weight of pixel wq, Bp is the three-dimensional coordinate of pixel wp, Bq is the three-dimensional coordinate of pixel wq, V(wp, wq) is the judgment function, wherein the pixel wp, if adjacent to the pixel point wq, then V(wp, wq)= 1, and the pixel point wp, if not adjacent to the pixel point wq, then V(wp, wq)= 0, wherein, fp is the spectral value of the pixel point wp, fq is the spectral value of the pixel point wq;

Using the probability function Yp, q(wp, wq) to post-process the classification result graph to obtain a pixel-level three-dimensional level classification.

Date:

Page 1 of 2 Application no: Applicant name: 22 Dec 2020

Car information collection Car driving track trace set unit acquisition unit (001) (002) 2020104213

Car Speedometer Communication Unit calculation unit (004) (003)

Car Control Unit Server (005) (006)

Figure 1 Schematic Diagram of the driverless vehicle control system based on 5G and blockchain

Page 2 of 2 Application no: Applicant name: 22 Dec 2020 2020104213

Figure 2 Flow diagram of the driverless vehicle control system based on 5G and blockchain