Unmanned vehicle brake control method and device based on network monitoring and storage medium

Abstract

The invention discloses an unmanned vehicle brake control method and device based on network monitoring and a storage medium. The brake control method comprises the steps that a first network data packet sent by an unmanned vehicle to an Internet of Vehicles platform is acquired; acquiring a second network data packet analyzed by the Internet of Vehicles platform according to the first network data packet, and sending the second network data packet to the unmanned vehicle; adding a first timestamp to the sending of the first network data packet; adding a second timestamp to the sending of the second network data packet; calculating a corresponding network delay through a difference value between the first timestamp and the second timestamp; calculating the braking distance of the corresponding vehicle speed according to the network delay; and controlling the vehicle speed according to the braking distance. A driver obtains the safe braking speed through remote control of the safe braking distance. The risk of delayed braking or braking failure caused by network instability can be reduced or avoided in advance, and the safety of unmanned driving is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of brake control for unmanned vehicles, and in particular to a brake control method, device and storage medium for unmanned vehicles based on network monitoring. Background Art

[0002] Port transportation is one of the most important transportation channels in modern times. In the 21st century, the focus of the port transportation industry is to build a new intelligent model to realize the intelligent transportation equipment, automated transportation process control, networked information transmission, scientific management and decision-making. Intelligence has also become an inevitable path for the transformation and upgrading of the port transportation industry. Using intelligence to drive the transformation and upgrading of traditional port transportation, create intelligent and information-based smart ports, and improve the core competitiveness of enterprises.

[0003] With the continuous development of the logistics industry, unmanned vehicles have gradually become an indispensable tool for improving the efficiency of logistics distribution. In order to achieve precise control of the brakes of unmanned vehicles, it is necessary to collect various real-time parameters for analysis and calculation, which leads to excessive calculation volume, inaccurate and intime control results, and increases the risk of unmanned vehicle driving. Summary of the invention

[0004] In order to overcome the above-mentioned background technology, with the continuous development of the logistics industry, unmanned vehicles have gradually become an indispensable tool for improving the efficiency of logistics distribution. In order to achieve precise control of the brakes of unmanned vehicles, it is necessary to collect various real-time parameters for analysis and calculation, which leads to excessive calculation volume, inaccurate and intime control results, and increases the risk of unmanned vehicle driving. The purpose of the present invention is to provide an unmanned vehicle brake control method, device and storage medium based on network monitoring.

[0005] In order to achieve the above purpose, the present invention adopts the following technical solution:

[0006] In a first aspect of the present invention, a brake control method for an unmanned vehicle based on network monitoring is provided, the brake control method comprising:

[0007] Obtaining a first network data packet sent by the unmanned vehicle to the Internet of Vehicles platform;

[0008] Obtain a second network data packet parsed by the Internet of Vehicles platform according to the first network data packet, and send the second network data packet to the unmanned vehicle;

[0009] Adding a first timestamp to the sending of the first network data packet;

[0010] Adding a second timestamp to the sending of the second network data packet;

[0011] Calculate the corresponding network delay by the difference between the first timestamp and the second timestamp;

[0012] Calculate the braking distance corresponding to the vehicle speed according to the network delay;

[0013] The vehicle speed is controlled according to the braking distance.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: network monitoring is used to enable the remote control driver of the unmanned vehicle to better understand the current network status, and the accurate network delay is calculated through the round-trip network data packets interacting between the unmanned vehicle and the vehicle networking platform, and the timestamp difference of the round-trip network data packets, and the braking distance corresponding to the vehicle speed is calculated according to the network delay, so as to ensure that the accurate braking distance and the corresponding speed are obtained, and the driver can remotely obtain a safe braking speed through a safe braking distance. The risk of untimely braking or braking failure caused by network instability can be reduced or avoided in advance, thereby improving the safety of unmanned driving.

[0015] In some possible implementations, the first network data packet includes vehicle behavior data.

[0016] In some possible implementations, the second network data packet includes vehicle decision control data.

[0017] In some possible implementations, the first timestamp and the second timestamp include a start sending timestamp and an end sending timestamp, respectively.

[0018] In some possible implementations, controlling the vehicle speed according to the braking distance specifically includes the following:

[0019] Determine whether the braking distance is a safe distance. If so, brake according to the vehicle speed corresponding to the current braking distance; if not, remotely control the vehicle speed until the braking distance corresponding to the current speed is a safe distance, and control the vehicle to brake at the current speed.

[0020] A second aspect of the present invention provides a brake control device for an unmanned vehicle based on network monitoring, comprising:

[0021] A first data packet acquisition module: acquires a first network data packet sent by the unmanned vehicle to the Internet of Vehicles platform;

[0022] A second data packet acquisition module is used to acquire a second network data packet parsed by the Internet of Vehicles platform according to the first network data packet, and send the second network data packet to the unmanned vehicle;

[0023] A first timestamp adding module: adding a first timestamp to the sending of the first network data packet;

[0024] A second timestamp adding module: adding a second timestamp to the sending of the second network data packet;

[0025] A network delay calculation module: calculating the corresponding network delay by the difference between the first timestamp and the second timestamp;

[0026] Braking distance calculation module: calculates the braking distance of the corresponding vehicle speed according to the network delay;

[0027] Braking control module: controls the vehicle speed according to the braking distance.

[0028] In some possible implementations, the first network data packet includes vehicle behavior data.

[0029] In some possible implementations, the second network data packet includes vehicle decision control data.

[0030] In some possible implementations, the first timestamp and the second timestamp include a start sending timestamp and an end sending timestamp, respectively.

[0031] In some possible implementations, controlling the vehicle speed according to the braking distance specifically includes the following:

[0032] Determine whether the braking distance is a safe distance. If so, brake according to the vehicle speed corresponding to the current braking distance; if not, remotely control the vehicle speed until the braking distance corresponding to the current speed is a safe distance, and control the vehicle to brake at the current speed.

[0033] The third aspect of the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above-mentioned unmanned vehicle braking control method based on network monitoring are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a flowchart of the steps of the unmanned vehicle braking control method based on network monitoring according to an embodiment of the present invention;

[0035] Figure 2 The present invention is a structural flow chart of an unmanned vehicle braking control device based on network monitoring according to an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The preferred embodiments of the present invention are described in detail below in conjunction with the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby making a clearer and more definite definition of the protection scope of the present invention.

[0037] It should be noted that if a directional indication is involved in the embodiment of the present invention, the directional indication is only used to explain the relative position relationship, movement status, etc. between the components in a certain specific posture. If the specific posture changes, the directional indication will also change accordingly.

[0038] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present invention, the descriptions of "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, the meaning of "and / or" appearing in the full text includes three parallel schemes. Taking "A and / or B" as an example, it includes scheme A, or scheme B, or a scheme that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but it must be based on the ability of ordinary technicians in the field to implement. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0039] See attached Figure 1 As shown, this embodiment provides a brake control method for an unmanned vehicle based on network monitoring, and the brake control method includes

[0040] S1: Obtain the first network data packet sent by the unmanned vehicle to the Internet of Vehicles platform.

[0041] The first network data packet includes vehicle behavior data.

[0042] Vehicle behavior data refers to a series of parameters of the vehicle during operation, including monitoring status including vehicle name, real-time location of the vehicle, real-time speed, engine speed, steering wheel angle, vehicle heading angle, real-time gear position of the vehicle, current driving mode and real-time network status, etc.

[0043] S2: Obtain a second network data packet parsed by the Internet of Vehicles platform based on the first network data packet, and send the second network data packet to the unmanned vehicle.

[0044] The second network data packet includes vehicle decision control data. The vehicle decision control data includes controlling the speed and direction of the unmanned vehicle, that is, the lateral control and longitudinal control of the autonomous driving unmanned vehicle. The lateral control mainly controls the steering wheel of the unmanned vehicle, and the longitudinal control mainly controls the acceleration and deceleration of the unmanned vehicle through the pedal / accelerator / shifter.

[0045] The control strategy here can be controlled by PID or S-curve algorithm. PID control has the following advantages: Improve control accuracy: The PID control algorithm can adjust the control output value in time according to the error signal between the actual output value and the expected output value, thereby improving the control accuracy. Strong adaptability: The PID controller is adaptive and can automatically adjust the control parameters according to the actual operating status of the system to adapt to different working conditions. Fast response: The PID controller has a fast response speed and can achieve fast control response, which is suitable for control occasions that require fast adjustment. Good stability: The PID controller can achieve stable control of the system, and can maintain the stability of the system even in the case of external interference or changes in system parameters. Easy to implement: The PID controller algorithm is simple and easy to implement, and can be applied to a variety of control occasions, such as temperature control, speed control, position control, etc.

[0046] The S-shaped speed curve has good flexibility, which solves the problem of sudden acceleration during acceleration and deceleration, avoids the flexible impact of the unmanned vehicle during braking, and makes the braking movement smoother.

[0047] S3: Add a first timestamp to the sending of the first network data packet.

[0048] S4: Add a second timestamp to the sending of the second network data packet.

[0049] S5: Calculate the corresponding network delay by using the difference between the first timestamp and the second timestamp.

[0050] S6: Calculate the braking distance corresponding to the vehicle speed according to the network delay.

[0051] S7: Controlling the vehicle speed according to the braking distance.

[0052] The details are as follows: determine whether the braking distance is a safe distance. If so, brake according to the vehicle speed corresponding to the current braking distance; if not, remotely control the vehicle speed until the braking distance corresponding to the current speed is a safe distance, and control the vehicle to brake at the current speed.

[0053] The purpose of network monitoring is to help the remote control driver of the unmanned vehicle better understand the current network status. Through the round-trip network data packets exchanged between the unmanned vehicle and the Internet of Vehicles platform, and through the timestamp difference of the round-trip network data packets, the accurate network delay is calculated, and the braking distance corresponding to the vehicle speed is calculated based on the network delay to ensure accurate braking distance and corresponding speed. The driver can remotely control the safe braking speed through the safe braking distance. The risk of untimely braking or braking failure caused by network instability can be reduced or avoided in advance, improving the safety of unmanned driving.

[0054] In some implementations, the first timestamp and the second timestamp include a start sending timestamp and an end sending timestamp, respectively.

[0055] The more precise division of timestamps makes the calculation of network delay more accurate, thereby obtaining more accurate braking distance and braking speed, further ensuring the success rate of braking and improving braking safety.

[0056] See attached Figure 2 As shown, this embodiment also provides an unmanned vehicle brake control device based on network monitoring, and the unmanned vehicle brake control method based on network monitoring is applied. The device includes

[0057] A first data packet acquisition module: acquires a first network data packet sent by the unmanned vehicle to the Internet of Vehicles platform;

[0058] A second data packet acquisition module is used to acquire a second network data packet parsed by the Internet of Vehicles platform according to the first network data packet, and send the second network data packet to the unmanned vehicle;

[0059] A first timestamp adding module: adding a first timestamp to the sending of the first network data packet;

[0060] A second timestamp adding module: adding a second timestamp to the sending of the second network data packet;

[0061] A network delay calculation module: calculating the corresponding network delay by the difference between the first timestamp and the second timestamp;

[0062] Braking distance calculation module: calculates the braking distance of the corresponding vehicle speed according to the network delay;

[0063] Braking control module: controls the vehicle speed according to the braking distance.

[0064] In some embodiments, the first network data packet includes vehicle behavior data.

[0065] In some embodiments, the second network data packet includes vehicle decision control data.

[0066] In some implementations, the first timestamp and the second timestamp include a start sending timestamp and an end sending timestamp, respectively.

[0067] In some implementations, controlling the vehicle speed according to the braking distance specifically includes the following:

[0068] Determine whether the braking distance is a safe distance. If so, brake according to the vehicle speed corresponding to the current braking distance; if not, remotely control the vehicle speed until the braking distance corresponding to the current speed is a safe distance, and control the vehicle to brake at the current speed.

[0069] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned unmanned vehicle braking control method based on network monitoring are implemented.

[0070] The storage medium stores program instructions that can implement all the above methods, wherein the program instructions can be stored in the above storage medium in the form of a software product, including several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or a terminal device such as a computer, a server, a mobile phone, or a tablet.

[0071] The processor may also be referred to as a CPU (Central Processing Unit). The processor may be an integrated circuit chip with signal processing capabilities. The processor may also be:

[0072] DSP (Digital Signal Processor, digital signal processor, digital signal processor is a processor composed of large-scale or ultra-large-scale integrated circuit chips to complete certain signal processing tasks. It has gradually developed to meet the needs of high-speed real-time signal processing tasks. With the development of integrated circuit technology and digital signal processing algorithms, the implementation methods of digital signal processors are constantly changing, and the processing functions are constantly improving and expanding.)

[0073] ASIC (Application Specific Integrated Circuit) is an integrated circuit designed and manufactured to meet the needs of specific users and specific electronic systems.

[0074] FPGA (Field Programmable Gate Array) is a product further developed on the basis of programmable devices such as PAL (Programmable Array Logic) and GAL (generic array logic). It emerged as a semi-custom circuit in the field of application-specific integrated circuits (ASICs), which not only solves the shortcomings of custom circuits, but also overcomes the shortcomings of the limited number of gate circuits of the original programmable devices.

[0075] A general-purpose processor may be a microprocessor or any conventional processor.

[0076] The above implementation modes are only for illustrating the technical concept and features of the present invention, and their purpose is to enable people familiar with this technology to understand the content of the present invention and implement it, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made according to the spirit of the present invention should be included in the protection scope of the present invention.

Claims

1. Unmanned vehicle braking control method based on network monitoring, Features: The brake control method comprises Obtaining a first network data packet sent by the unmanned vehicle to the Internet of Vehicles platform; Obtain a second network data packet parsed by the Internet of Vehicles platform according to the first network data packet, and send the second network data packet to the unmanned vehicle; Adding a first timestamp to the sending of the first network data packet; Adding a second timestamp to the sending of the second network data packet; Calculate the corresponding network delay by the difference between the first timestamp and the second timestamp; Calculate the braking distance corresponding to the vehicle speed according to the network delay; The vehicle speed is controlled according to the braking distance.

2. According to the unmanned vehicle braking control method based on network monitoring according to claim 1, Features: The first network data packet includes vehicle behavior data.

3. The unmanned vehicle braking control method based on network monitoring according to claim 1, Features: The second network data packet includes vehicle decision control data.

4. The unmanned vehicle braking control method based on network monitoring according to claim 1, Features: The first timestamp and the second timestamp include a start sending timestamp and an end sending timestamp respectively.

5. The unmanned vehicle braking control method based on network monitoring according to claim 1, Features: Controlling the vehicle speed according to the braking distance specifically includes the following steps: Determine whether the braking distance is a safe distance. If so, brake according to the vehicle speed corresponding to the current braking distance; if not, remotely control the vehicle speed until the braking distance corresponding to the current speed is a safe distance, and control the vehicle to brake at the current speed.

6. Unmanned vehicle brake control device based on network monitoring, Features: include A first data packet acquisition module: acquires a first network data packet sent by the unmanned vehicle to the Internet of Vehicles platform; A second data packet acquisition module is used to acquire a second network data packet parsed by the Internet of Vehicles platform according to the first network data packet, and send the second network data packet to the unmanned vehicle; A first timestamp adding module: adding a first timestamp to the sending of the first network data packet; A second timestamp adding module: adding a second timestamp to the sending of the second network data packet; A network delay calculation module: calculating the corresponding network delay by the difference between the first timestamp and the second timestamp; Braking distance calculation module: calculates the braking distance of the corresponding vehicle speed according to the network delay; Braking control module: controls the vehicle speed according to the braking distance.

7. The unmanned vehicle brake control device based on network monitoring according to claim 6, Features: The first network data packet includes vehicle behavior data, and the second network data packet includes vehicle decision control data.

8. The unmanned vehicle braking control device based on network monitoring according to claim 6, Features: The first timestamp and the second timestamp include a start sending timestamp and an end sending timestamp respectively.

9. The unmanned vehicle brake control device based on network monitoring according to claim 6, Features: Controlling the vehicle speed according to the braking distance specifically includes the following steps: Determine whether the braking distance is a safe distance. If so, brake according to the vehicle speed corresponding to the current braking distance; if not, remotely control the vehicle speed until the braking distance corresponding to the current speed is a safe distance, and control the vehicle to brake at the current speed.

10. A computer-readable storage medium, Features: The computer-readable storage medium stores a computer program, and when the computer program is executed by the processor, the steps of the unmanned vehicle braking control method based on network monitoring according to any one of claims 1 to 6 are implemented.

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