Intelligent braking method and device based on vehicle state prediction and V2X and vehicle

Abstract

The invention discloses an intelligent braking method and device based on vehicle state prediction and V2X and a vehicle, and belongs to the technical field of automobile safety. The intelligent braking method comprises the steps that operation data of a driver, vehicle state data and V2X data are obtained; and obtaining a corresponding trigger condition according to the operation data of the driver, the vehicle state data and the V2X data, and executing a corresponding correction strategy through a time sequence prediction algorithm according to the corresponding trigger condition. Through combination of vehicle state prediction and V2X optimization, the braking system can quickly respond in different traffic scenes, improve the braking performance, effectively shorten the braking distance and reduce the accident risk, the system can obtain external environment information in real time and make an intelligent decision, the early warning and response ability to potential risks is remarkably improved, and the system is suitable for popularization and application. And the safety of the vehicle under complex traffic conditions is enhanced.

Description

Technical Field

[0001] The present invention discloses an intelligent braking method, device and vehicle based on vehicle state prediction and V2X, belonging to the technical field of automobile safety. Background Art

[0002] In the field of intelligent transportation and autonomous driving, the intelligence of the braking system has become an important research direction for driving safety. Traditional braking control technology usually relies on sensors inside the vehicle, such as brake pedal sensors, vehicle speed sensors and other basic sensors. These sensors can collect some important vehicle dynamic information and help traditional electronic braking systems (EBS) achieve basic automatic braking control under certain conditions. However, this braking system based on single vehicle status information still has significant limitations in complex traffic environments.

[0003] In recent years, the rise of V2X (Vehicle-to-Everything) communication technology has enabled vehicles to exchange information with other vehicles, road infrastructure and pedestrians in real time. Although the V2X system has shown good prospects in reducing traffic accident rates and improving traffic efficiency, most of the current V2X braking applications are still in the experimental or preliminary commercialization stage, and the specific application solutions and technical implementation are not yet mature.

[0004] The shortcomings of the existing technology are mainly reflected in the following aspects:

[0005] (1) Slow response speed

[0006] Existing brake control systems often fail to make timely adjustments when faced with unexpected situations. This is because most systems are based only on data from internal vehicle sensors and lack a comprehensive understanding of the surrounding environment, resulting in delayed reactions that may increase the risk of accidents.

[0007] (2) Insufficient information integration

[0008] Although V2X technology can provide rich environmental information, current brake control systems often cannot effectively integrate real-time data from V2X with the vehicle's own status. This means that when the vehicle faces environmental changes, it cannot fully utilize this key information to make intelligent decisions.

[0009] (3) Insufficient prediction of driver behavior

[0010] Current braking systems lack the ability to predict driver behavior and identify potential dangerous situations in advance. This lack of predictive ability means that traditional systems are often unable to effectively reduce braking distances or improve braking processes in emergency situations.

[0011] The existence of these problems not only affects the overall safety of the vehicle, but also restricts the further development of autonomous driving technology. In view of the above shortcomings, current research still encounters many challenges such as sensor and information processing delays, data fusion algorithm complexity, and system implementation costs, making it difficult to achieve a truly intelligent braking strategy. Summary of the invention

[0012] In view of the defects of the prior art, the present invention proposes an intelligent braking method, device and vehicle based on vehicle state prediction and V2X to solve the problems of slow response speed, slow reaction speed and insufficient prediction of driver behavior of the current traditional braking control technology.

[0013] The technical solution of the present invention is as follows:

[0014] According to a first aspect of an embodiment of the present invention, there is provided an intelligent braking method based on vehicle state prediction and V2X, comprising:

[0015] Acquire the driver's operation data, vehicle status data and V2X data respectively;

[0016] Corresponding trigger conditions are obtained according to the driver's operation data, vehicle status data and V2X data, and corresponding correction strategies are executed through a timing prediction algorithm according to the corresponding trigger conditions.

[0017] Preferably, the vehicle status data includes at least: current speed, current acceleration, current braking status and current steering wheel angle.

[0018] Preferably, the V2X data includes at least: front obstacles, traffic flow, road conditions, traffic light status and rear obstacles.

[0019] Preferably, executing a corresponding correction strategy through a timing prediction algorithm according to the corresponding trigger condition includes:

[0020] When the trigger condition is that the distance to the obstacle is less than 2 meters, the correction strategy includes: when an emergency brake signal is detected, activating the braking system, increasing the braking force by 20% and triggering it within 100 milliseconds;

[0021] When the trigger condition is that the current speed is lower than 10 km / h and the vehicle ahead is about to stop within 5 meters, the correction strategy includes: adjusting the throttle output to make the acceleration smoother and reducing the throttle response by 30%.

[0022] Preferably, the executing a corresponding correction strategy through a timing prediction algorithm according to the corresponding trigger condition further includes:

[0023] When the trigger condition is that the crosswind speed exceeds 15 km / h, the correction strategy includes: correcting the steering input and increasing the steering gain by 5%;

[0024] When the trigger condition is that the road friction coefficient is lower than 0.3, the correction strategy includes: reducing the throttle output by 40% and reducing the braking intensity by 20%.

[0025] Preferably, the executing a corresponding correction strategy through a timing prediction algorithm according to the corresponding trigger condition further includes:

[0026] When the trigger condition is that the current speed exceeds 80 km / h and the rear vehicle is detected to be continuously approaching within 15 meters, the correction strategy includes: delaying the acceleration input by 200 milliseconds and reducing the throttle input by 15%;

[0027] When the trigger condition is an emergency ahead, the correction strategy includes: immediately controlling the brakes to ensure that the vehicle stops completely within 0.5 seconds at most.

[0028] According to a second aspect of an embodiment of the present invention, there is provided an intelligent braking device based on vehicle state prediction and V2X, comprising:

[0029] An acquisition module, used to respectively acquire driver operation data, vehicle status data and V2X data;

[0030] The execution module is used to obtain corresponding trigger conditions according to the driver's operation data, vehicle status data and V2X data, and execute corresponding correction strategies through a timing prediction algorithm according to the corresponding trigger conditions.

[0031] Preferably, the execution module is used to:

[0032] When the trigger condition is that the distance to the obstacle is less than 2 meters, the correction strategy includes: when an emergency brake signal is detected, activating the braking system, increasing the braking force by 20% and triggering it within 100 milliseconds;

[0033] When the trigger condition is that the current speed is lower than 10 km / h and the vehicle ahead is about to stop within 5 meters, the correction strategy includes: adjusting the throttle output to make the acceleration smoother and reducing the throttle response by 30%.

[0034] According to a third aspect of an embodiment of the present invention, there is provided a vehicle, comprising:

[0035] one or more processors;

[0036] a memory for storing the one or more processor-executable instructions;

[0037] Wherein, the one or more processors are configured to:

[0038] Execute the method described in the first aspect of the embodiment of the present invention.

[0039] According to a fourth aspect of an embodiment of the present invention, a non-temporary computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of a terminal, the terminal is enabled to execute the method described in the first aspect of the embodiment of the present invention.

[0040] According to a fifth aspect of an embodiment of the present invention, an application product is provided. When the application product is running on a terminal, the terminal executes the method described in the first aspect of the embodiment of the present invention.

[0041] The present invention provides an intelligent braking method, device and vehicle based on vehicle state prediction and V2X, and the beneficial effects are:

[0042] 1. Enhance braking performance and response speed

[0043] Through the combination of vehicle state prediction and V2X optimization, the braking system of the present invention can respond quickly in different traffic scenarios, improve braking performance, effectively shorten braking distance, and reduce accident risks.

[0044] 2. Improve system security

[0045] The system can obtain external environmental information in real time and make intelligent decisions, significantly improving the warning and response capabilities to potential dangers and enhancing the safety of vehicles in complex traffic conditions.

[0046] 3. Optimize driving comfort

[0047] By intelligently adjusting the braking strategy, the shaking and discomfort caused by sudden braking are avoided, the overall driving comfort experience is improved, and the driver and passengers can experience a smoother driving process.

[0048] 4. Improve the level of intelligence

[0049] With the implementation of the present invention, the intelligence level of vehicles will continue to improve, enabling them to have stronger autonomous judgment and decision-making capabilities, helping the country to further develop in the fields of intelligent transportation and autonomous driving.

[0050] In summary, the present invention not only solves a series of related problems by making effective improvements on the deficiencies in the prior art, but also brings about various technical effects, laying a solid foundation for the popularization of future intelligent braking systems and intelligent driving.

[0051] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 The present invention is a flowchart of an intelligent braking method based on vehicle state prediction and V2X according to an exemplary embodiment.

[0053] Figure 2 It is a structural schematic block diagram of an intelligent braking device based on vehicle state prediction and V2X according to an exemplary embodiment.

[0054] Figure 3 The present invention is a schematic block diagram of a vehicle structure according to an exemplary embodiment. DETAILED DESCRIPTION

[0055] The technical solution of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] In the description of the present invention, it should be noted that the terms "center", "up", "down", "left", "right", "vertical", "horizontal", "inside", "outside", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they cannot be understood as limitations on the present invention.

[0057] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0058] The embodiment of the present invention provides a vehicle state prediction and V2X-based intelligent braking method implemented by a terminal, the terminal at least includes a CPU, etc.

[0059] Embodiment 1: Figure 1 An intelligent braking method based on vehicle state prediction and V2X is shown according to an exemplary embodiment, including:

[0060] Step 101, respectively obtain the driver's operation data, vehicle status data and V2X data, wherein:

[0061] The vehicle status data obtained through acceleration sensors, position sensors and wheel speed sensors include at least: current speed, current acceleration, current braking status and current steering wheel angle. The V2X data obtained using DSRC or C-V2X protocol includes at least: front obstacles, traffic flow, road conditions, traffic light status and rear obstacles.

[0062] Step 102, obtaining corresponding trigger conditions according to the driver's operation data, vehicle status data and V2X data, and executing corresponding correction strategies through a timing prediction algorithm according to the corresponding trigger conditions, wherein:

[0063] The driver’s operation data includes at least: throttle, brake and steering wheel angle, etc. When the trigger condition is less than 2 meters away from the obstacle, the correction strategy includes: when an emergency brake signal is detected, activate the brake system in advance, activate the brake system, increase the braking force by 20% and trigger it within 100 milliseconds;

[0064] When the trigger condition is that the current speed is lower than 10km / h and the vehicle ahead is about to stop within 5 meters, the correction strategy includes: adjusting the throttle output to make the acceleration smoother and reducing the throttle response by 30%.

[0065] When the trigger condition is that the crosswind speed exceeds 15km / h, the correction strategy includes: correcting the steering input and increasing the steering gain by 5% to offset the impact of the wind on the vehicle;

[0066] When the trigger condition is that the road friction coefficient is lower than 0.3, the correction strategy includes: reducing the throttle output by 40% and reducing the braking intensity by 20%.

[0067] When the trigger condition is that the current speed exceeds 80km / h and the rear vehicle is detected to be approaching within 15 meters, the correction strategy includes: delaying the acceleration input by 200 milliseconds, maintaining a stable speed, and reducing the throttle input by 15%;

[0068] When the trigger condition is an emergency ahead, the correction strategy includes: immediately controlling the brakes to ensure that the vehicle stops completely within 0.5 seconds at most.

[0069] This application will provide feedback to the driver through visual (dashboard indication), audio (alarm sound), etc. to improve driving safety awareness, facilitate their understanding of the logic of system intervention, and collect various data (including driver input, vehicle status, V2X information, etc.) during driving for subsequent analysis. Use machine learning technology to continuously optimize status assessment and prediction models to improve the system's responsiveness and warning accuracy. Collect driver feedback regularly and adjust system logic to ensure that the system takes into account both safety and driving comfort. Provide personalized driving mode settings to allow drivers to adjust system functions according to their own habits.

[0070] Embodiment 2:

[0071] Figure 2 The present invention is a schematic block diagram of a structure of an intelligent braking device based on vehicle state prediction and V2X according to an exemplary embodiment, the device comprising:

[0072] An acquisition module 210, for respectively acquiring driver's operation data, vehicle status data and V2X data;

[0073] The execution module 220 is used to obtain corresponding trigger conditions according to the driver's operation data, vehicle status data and V2X data, and execute corresponding correction strategies through a timing prediction algorithm according to the corresponding trigger conditions.

[0074] Preferably, the execution module 220 is used to:

[0075] When the trigger condition is that the distance to the obstacle is less than 2 meters, the correction strategy includes: when an emergency brake signal is detected, activating the braking system, increasing the braking force by 20% and triggering it within 100 milliseconds;

[0076] When the trigger condition is that the current speed is lower than 10 km / h and the vehicle ahead is about to stop within 5 meters, the correction strategy includes: adjusting the throttle output to make the acceleration smoother and reducing the throttle response by 30%.

[0077] This application combines vehicle state prediction with V2X optimization, and the braking system of the present invention can respond quickly in different traffic scenarios, improve braking performance, effectively shorten braking distance, and reduce accident risks. The system can obtain external environmental information in real time and make intelligent decisions, significantly improving the warning and response capabilities to potential dangers and enhancing the safety of vehicles under complex traffic conditions. By intelligently adjusting the braking strategy, the shaking and discomfort caused by sudden braking are avoided, the overall driving comfort experience is improved, and the driver and passengers experience a smoother driving process. With the implementation of the present invention, the intelligence level of vehicles continues to improve, enabling them to have stronger autonomous judgment and decision-making capabilities, and help the country's further development in the fields of intelligent transportation and autonomous driving.

[0078] Embodiment three:

[0079] Figure 3 300 is a block diagram of a vehicle 300 provided in an embodiment of the present application. For example, the vehicle 300 may be a hybrid vehicle, a non-hybrid vehicle, an electric vehicle, a fuel cell vehicle, or other types of vehicles. The vehicle 300 may be an autonomous vehicle, a semi-autonomous vehicle, or a non-autonomous vehicle. The vehicle 300 may also be equipped with a brake-by-wire system.

[0080] Reference Figure 3 , the vehicle 300 may include various subsystems, for example, an infotainment system 310, a perception system 320, a decision control system 330, a drive system 340, and a computing platform 350. The vehicle 300 may also include more or fewer subsystems, and each subsystem may include multiple components. In addition, each subsystem and each component of the vehicle 300 may be interconnected by wire or wireless means.

[0081] In some embodiments, the infotainment system 310 may include a communication system, an entertainment system, and a navigation system, among others.

[0082] The perception system 320 may include several sensors for sensing information about the environment around the vehicle 300. For example, the perception system 320 may include a global positioning system (the global positioning system may be a GPS system, or a Beidou system or other positioning systems), an inertial measurement unit (IMU), a laser radar, a millimeter wave radar, an ultrasonic radar, and a camera.

[0083] The decision control system 330 may include a computing system, a vehicle controller, a steering system, a throttle, and a braking system.

[0084] The drive system 340 may include components that provide power movement for the vehicle 300. In one embodiment, the drive system 340 may include an engine, an energy source, a transmission system, and wheels. The engine may be one or a combination of an internal combustion engine, an electric motor, and an air compression engine. The engine is capable of converting energy provided by the energy source into mechanical energy.

[0085] Some or all functions of the vehicle 300 are controlled by a computing platform 350. The computing platform 350 may include at least one processor 351 and a memory 352, and the processor 351 may execute instructions 353 stored in the memory 352.

[0086] The processor 351 may be any conventional processor, such as a commercially available CPU. The processor may also include a graphics processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a system on chip (System on Chip, SOC), an application specific integrated circuit (Application Specific Integrated Circuit, ASIC) or a combination thereof.

[0087] The memory 352 may be implemented by any type of volatile or nonvolatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0088] In addition to instructions 353 , memory 352 may also store data, such as road maps, route information, vehicle location, direction, speed, etc. The data stored in memory 352 may be used by computing platform 350 .

[0089] In the embodiment of the present disclosure, the processor 351 can execute instruction 353 to complete all or part of the steps of the above-mentioned intelligent braking method based on vehicle state prediction and V2X.

[0090] Embodiment 4:

[0091] In an exemplary embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the program is executed by a processor, an intelligent braking method based on vehicle state prediction and V2X as provided in all the inventive embodiments of the present application is implemented.

[0092] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.

[0093] Computer-readable signal media may include a data signal propagated in baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0094] Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0095] Computer program code for performing the operations of the present invention may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0096] Embodiment five:

[0097] In an exemplary embodiment, an application product is also provided, including one or more instructions, which can be executed by the processor 351 of the above-mentioned device to complete the above-mentioned intelligent braking method based on vehicle state prediction and V2X.

[0098] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily realized. Therefore, without departing from the general concept defined by the claims and equivalent scope, the present invention is not limited to the specific details and the illustrations shown and described here.

Claims

1. An intelligent braking method based on vehicle state prediction and V2X, characterized in that: include: Acquire the driver's operation data, vehicle status data and V2X data respectively; Corresponding trigger conditions are obtained according to the driver's operation data, vehicle status data and V2X data, and corresponding correction strategies are executed through a timing prediction algorithm according to the corresponding trigger conditions.

2. The intelligent braking method based on vehicle state prediction and V2X according to claim 1, characterized in that: The vehicle status data includes at least: current speed, current acceleration, current braking status and current steering wheel angle.

3. The intelligent braking method based on vehicle state prediction and V2X according to claim 1 or 2, characterized in that: The V2X data includes at least: obstacles ahead, traffic flow, road conditions, traffic light status and obstacles behind.

4. The intelligent braking method based on vehicle state prediction and V2X according to claim 3 is characterized in that: The executing a corresponding correction strategy through a timing prediction algorithm according to the corresponding trigger condition includes: When the trigger condition is that the distance to the obstacle is less than 2 meters, the correction strategy includes: when an emergency brake signal is detected, activating the braking system, increasing the braking force by 20% and triggering it within 100 milliseconds; When the trigger condition is that the current speed is lower than 10 km / h and the vehicle ahead is about to stop within 5 meters, the correction strategy includes: adjusting the throttle output to make the acceleration smoother and reducing the throttle response by 30%.

5. The intelligent braking method based on vehicle state prediction and V2X according to claim 4 is characterized in that: The executing of the corresponding correction strategy through the timing prediction algorithm according to the corresponding triggering condition also includes: When the trigger condition is that the crosswind speed exceeds 15 km / h, the correction strategy includes: correcting the steering input and increasing the steering gain by 5%; When the trigger condition is that the road friction coefficient is lower than 0.3, the correction strategy includes: reducing the throttle output by 40% and reducing the braking intensity by 20%.

6. The intelligent braking method based on vehicle state prediction and V2X according to claim 5, characterized in that: The executing of the corresponding correction strategy through the timing prediction algorithm according to the corresponding triggering condition also includes: When the trigger condition is that the current speed exceeds 80 km / h and the rear vehicle is detected to be continuously approaching within 15 meters, the correction strategy includes: delaying the acceleration input by 200 milliseconds and reducing the throttle input by 15%; When the trigger condition is an emergency ahead, the correction strategy includes: immediately controlling the brakes to ensure that the vehicle stops completely within 0.5 seconds at most.

7. An intelligent braking device based on vehicle state prediction and V2X, characterized in that: include: An acquisition module, used to respectively acquire driver operation data, vehicle status data and V2X data; The execution module is used to obtain corresponding trigger conditions according to the driver's operation data, vehicle status data and V2X data, and execute corresponding correction strategies through a timing prediction algorithm according to the corresponding trigger conditions.

8. The intelligent braking device based on vehicle state prediction and V2X according to claim 7, characterized in that: The execution module is used to: When the trigger condition is that the distance to the obstacle is less than 2 meters, the correction strategy includes: when an emergency brake signal is detected, activating the braking system, increasing the braking force by 20% and triggering it within 100 milliseconds; When the trigger condition is that the current speed is lower than 10 km / h and the vehicle ahead is about to stop within 5 meters, the correction strategy includes: adjusting the throttle output to make the acceleration smoother and reducing the throttle response by 30%.

9. A vehicle, characterized in that: include: processor; a memory for storing processor-executable instructions; Wherein, the processor is configured to execute the steps of the intelligent braking method based on vehicle state prediction and V2X as described in any one of claims 1 to 6.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the program instructions are executed by a processor, the steps of the intelligent braking method based on vehicle state prediction and V2X as described in any one of claims 1 to 6 are implemented.

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