Vehicle auxiliary driving method based on road surface quality, vehicle and medium

Abstract

The invention discloses a vehicle speed control method, a vehicle and a medium, and relates to the technical field of vehicle control, the method is applied to a road surface intelligent identification system of the vehicle, and the method comprises the following steps: obtaining a road surface satellite picture sent by a satellite for a road in front of the vehicle; recognizing the road surface quality information of the front road according to the road surface satellite picture; and carrying out auxiliary driving on the vehicle according to the road surface quality information. By adopting the method, the road surface recognition precision of the front road can be improved, so that the vehicle can be better assisted in driving, and the driving safety is improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control technology, and in particular to a vehicle assisted driving method based on road quality, a vehicle and a medium. Background Art

[0002] When a vehicle is driving on the road, it will encounter roads with different road surface qualities, which poses a great threat to driving safety. In related technologies, the road surface quality is mainly judged by road surface images, but poor quality road surface images will lead to inaccurate judgment results, thus failing to guarantee the safety and driving experience of the vehicle under complex road conditions. Summary of the invention

[0003] Based on this, it is necessary to provide a vehicle assisted driving method, vehicle and medium based on road quality that can improve driving safety in response to the above technical problems.

[0004] A vehicle assisted driving method based on road quality is applied to a road intelligent recognition system of a vehicle, the method comprising:

[0005] Obtaining satellite road images sent by satellites for the road ahead of the vehicle;

[0006] Identifying road quality information of the road ahead according to the road satellite image;

[0007] The vehicle is assisted in driving according to the road quality information.

[0008] In the above solution, before acquiring the road surface satellite image sent by the satellite for the road ahead of the vehicle, the method further includes:

[0009] The vehicle position information and the driving direction information of the vehicle are sent to the satellite, so that the satellite determines the road satellite image based on the vehicle position information and the driving direction information.

[0010] In the above solution, the assisted driving of the vehicle according to the road quality information includes:

[0011] In response to the road quality information indicating that there is a damaged road area on the road ahead, assisted driving of the vehicle is performed at least according to the remaining power of the vehicle.

[0012] In the above solution, the assisting driving of the vehicle at least according to the remaining power of the vehicle includes:

[0013] If the remaining power is greater than or equal to a first set value, the brake pad is activated;

[0014] If the remaining power is less than the first set value, the braking method is determined according to a safety distance, where the safety distance represents the distance between the vehicle and the damaged road area.

[0015] In the above scheme, the method of determining the braking mode according to the safety distance includes:

[0016] If the safety distance is less than a second set value, energy recovery is started and the brake pad is started;

[0017] If the safety distance is greater than or equal to the second set value, energy recovery is started.

[0018] In the above solution, the road surface quality information includes a damaged road surface area of ​​the road ahead, and the identifying the road surface quality information of the road ahead based on the road surface satellite image includes:

[0019] The road surface damaged area of ​​the road ahead is identified based on the road surface color difference in the road surface satellite image.

[0020] In the above solution, the road surface quality information includes a damaged road surface area of ​​the road ahead, and the identifying the road surface quality information of the road ahead based on the road surface satellite image includes:

[0021] In response to at least two road branches existing in a road ahead of the vehicle, determining whether the vehicle has set a navigation route;

[0022] If it is determined that the vehicle sets the navigation route, identifying whether the road damage area exists in the target road branch according to the road satellite image; the target road branch represents the road branch indicated by the navigation route in each of the road branches;

[0023] If it is determined that the vehicle has not set the navigation route, then identifying whether the road damaged area exists in each of the road branches according to the road satellite image.

[0024] A vehicle assisted driving method based on road quality, applied to a satellite, the method comprising:

[0025] Receiving vehicle location information and driving direction information sent by the vehicle;

[0026] Determine a satellite image of the road surface of the road ahead of the vehicle according to the vehicle position information and the driving direction information;

[0027] The road satellite image is sent to the vehicle, so that the vehicle performs assisted driving according to the road satellite image.

[0028] A vehicle includes a memory and a processor. The memory stores a computer program. When the processor executes the computer program, the vehicle assisted driving method based on road quality applied to the vehicle's road intelligent recognition system is implemented.

[0029] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the vehicle assisted driving method based on road quality applied to the above-mentioned road surface intelligent recognition system for vehicles.

[0030] The above-mentioned vehicle assisted driving method, vehicle and medium based on road quality, the vehicle's road intelligent recognition system obtains road satellite images sent by the satellite for the road ahead of the vehicle. The road satellite images have the characteristics of wide shooting angle and large area, so that the road intelligent recognition system can accurately identify the road quality information of the road ahead in a large area based on the road satellite images, so as to cope with the monitoring of different road surfaces, and then can timely assist the vehicle in driving according to the road quality information, thereby improving the driving safety of the vehicle in different road environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 is a framework diagram of a vehicle assisted driving method based on road quality in one embodiment;

[0032] Figure 2 A schematic diagram of a process flow of a vehicle assisted driving method based on road quality applied to a road intelligence system in one embodiment;

[0033] Figure 3 The figure is a flow chart of a road quality-based vehicle assisted driving method applied to a satellite in an embodiment. DETAILED DESCRIPTION

[0034] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0035] The implementation details of the technical solution of the embodiment of the present application are described in detail below.

[0036] like Figure 1 As shown, Figure 1 The framework diagram of the vehicle assisted driving method based on road quality is shown. The satellite takes satellite images of the road ahead of the vehicle and sends the road satellite images to the vehicle. The vehicle's road intelligent recognition system obtains the road satellite images sent by the satellite, analyzes the road satellite images, and identifies the road quality information of the road ahead, so as to assist the vehicle in driving according to the road quality information.

[0037] The following describes in detail the vehicle assisted driving method based on road quality from the vehicle side and the satellite side through different embodiments.

[0038] In one embodiment, Figure 2 As shown, a vehicle assisted driving method based on road quality applied to a road intelligent recognition system of a vehicle is provided, and the method may include the following steps:

[0039] Step S101, obtaining a road satellite image sent by a satellite for the road ahead of the vehicle.

[0040] The intelligent road surface recognition system is a system installed on the vehicle that uses artificial intelligence algorithms and image processing technology. It is used to process the collected images through AI algorithms and analyze the road conditions in real time during vehicle driving.

[0041] In this embodiment, the image processed by the road intelligent recognition system is a road satellite image, which is taken by a satellite for the road ahead of the vehicle, and then transmitted to the vehicle through a communication network to ensure that the vehicle can obtain the latest image information of the road ahead in real time. Among them, the road satellite image covers a large range of ground areas in the direction of the vehicle's advance, including roads, buildings, vegetation, etc. These features are helpful for analyzing the road conditions ahead.

[0042] Here, the satellite takes pictures of the road in the direction of the vehicle's advance. The vehicle establishes a communication connection with the satellite and receives the satellite pictures of the road sent by the satellite. The acquired satellite pictures of the road can clearly show the real-time road conditions in the direction of the vehicle's advance. In actual applications, the satellite road pictures make it possible to identify the road ahead of the vehicle in a larger range, thereby ensuring the vehicle's driving safety.

[0043] In one embodiment, before obtaining the road satellite image sent by the satellite for the road ahead of the vehicle, the vehicle obtains the current vehicle position information through the global positioning system (GPS) or other positioning technology, and obtains the current driving direction information through the vehicle sensor. The vehicle sends the vehicle position information and driving direction information to the satellite through the communication network. After receiving the vehicle position information and driving direction information, the satellite can calculate the road area at a distance ahead of the vehicle based on the vehicle position information and driving direction information, and perform imaging based on the calculated range to obtain the latest satellite image covering the road area ahead of the vehicle. In this way, the satellite can image the area ahead of the vehicle to avoid capturing images of irrelevant areas, so that the satellite can provide real-time images of the road that the vehicle is about to drive to.

[0044] Step S102, identifying road quality information of the road ahead based on the road satellite image.

[0045] The intelligent road surface recognition system pre-processes road surface satellite images, including improving the resolution of road surface satellite images to maximize the clarity of the image in order to better identify road surface details; it can also remove noise in the image, such as image interference caused by weather, shadows or lighting, so as to better analyze the features in the road surface satellite images.

[0046] After preprocessing, the road intelligent recognition system identifies the road satellite image to obtain the road quality information of the road ahead, where the road quality information mainly refers to various parameters and indicators that can reflect the road surface conditions, such as flatness, damage, surface slipperiness, snow and ice accumulation, etc. Specifically, the road intelligent recognition system can extract image features from road satellite images through the network model in deep learning, such as the texture features and color features of the road surface, so as to help determine the flatness and road conditions (slippery, snow-covered, collapsed, etc.) of the road ahead; in addition, it can also use object detection algorithms to identify obstacles and fallen rocks on the road and detect driving obstacles on the road ahead.

[0047] In practical applications, road satellite images have the characteristics of long detection distance and large area, and can cover a large area of ​​the ground, so they can be used for road condition analysis of long straight roads, intersections, and highway exits. At the same time, because road satellite images can cover a large range of roads ahead, they can timely discover possible dangerous factors on the road ahead, and then help vehicles avoid dangerous factors in advance, ensuring the driving safety of vehicles. In addition, road satellite images usually have a high resolution. High-resolution road satellite images can clearly reflect the road conditions, making the road intelligent recognition system more accurate in identifying road conditions.

[0048] Step S103: Assisting driving of the vehicle according to the road quality information.

[0049] Here, the driving risk of the vehicle on the road ahead can be evaluated based on the road quality information. For example, if the road quality information shows that the road ahead has a severely damaged road surface, it may cause the vehicle to lose control or be damaged, so as to formulate a corresponding assisted driving strategy. For example, when the road surface condition of the road ahead is detected to be poor, the road surface intelligent recognition system can issue a deceleration prompt to the driver; if the road surface of the road ahead is seriously damaged, the road surface intelligent recognition system can suggest that the driver choose an alternative route to avoid driving in dangerous areas. Based on this, driving safety and driving experience can be significantly improved.

[0050] In one embodiment, the road surface quality information refers to data about the surface condition of the road, including damaged road surface areas (such as potholes, collapses, cracks, etc.). Damaged road surface areas in the road will affect the smooth driving of the vehicle, may cause the vehicle to lose control, and increase the risk of accidents. Based on this, the vehicle responds to the road surface quality information indicating that there is a damaged road surface area on the road ahead, and assists the vehicle in driving at least according to the remaining power of the vehicle, comprehensively considers safety and efficient use of energy, and adjusts the speed of the vehicle so that the vehicle can slow down or even stop within an appropriate time, so that the vehicle can smoothly pass or avoid entering the damaged road surface area. In actual applications, when the road surface quality information indicates that there is a damaged road surface area on the road ahead, a warning will be immediately issued to the driver, which can be achieved through sound, visual signals (such as warning lights on the dashboard) or tactile feedback (such as steering wheel vibration).

[0051] It is understandable that a vehicle can achieve braking in two different ways, including energy recovery braking and brake pad braking. Among them, energy recovery braking converts kinetic energy into electrical energy, recovering energy while reducing the vehicle speed, but because the momentum recovery process is gradual, the vehicle deceleration effect is relatively mild and the reaction time is relatively long; brake pad braking directly decelerates the vehicle through friction, using brake pads to generate braking force, so it can quickly reduce the vehicle speed and the reaction time is relatively short.

[0052] Since these two braking methods have different characteristics and are applicable to different scenarios, when the road quality information indicates that there is a damaged road area on the road ahead, it is necessary to select an appropriate braking method so that the vehicle can pass through the damaged road area more smoothly or avoid entering the damaged road area.

[0053] How to select a suitable braking method for a vehicle is described in detail below through different embodiments.

[0054] In one embodiment, if the remaining power is greater than or equal to the first set value, the brake pads are activated. It can be understood that energy recovery braking converts the kinetic energy of the vehicle into electrical energy to achieve vehicle deceleration, wherein the recovered electrical energy will be stored in the vehicle battery. Therefore, the remaining power can determine whether the vehicle can use energy recovery for braking, wherein, when the remaining power is greater than or equal to the first set value (such as 99%), it indicates that the battery is almost fully charged, and the battery may not be able to accept more electrical energy, and continued regenerative braking cannot effectively recover more energy, and it will also cause the battery to be overcharged, affecting the battery life and performance, thereby limiting the effect of vehicle deceleration and energy recovery, so the vehicle is more suitable for reducing the speed by activating the brake pads. If the remaining power is less than the first set value, it indicates that the battery can accept more electrical energy, so that energy recovery braking can be applied, but because the time required for energy recovery braking is longer than the time required for brake pad braking, in order to ensure that the vehicle can complete deceleration or braking in a safe area, when the remaining power is less than the first set value, it is necessary to further consider the distance between the vehicle and the road damage area and select a suitable braking method.

[0055] In one embodiment, the safety distance determines the time required for braking. If the safety distance is less than the second set value, it indicates that the vehicle needs to reduce its speed in a short time and the required braking time is short. At this time, energy recovery and brake pads can be started at the same time. Figure 1 As shown, when energy recovery is started, the motor starts to run in reverse, so that the working mode of the motor is converted from motor mode to generator mode, the kinetic energy of the vehicle is used to generate electrical energy, and the reverse action of the motor is used to generate a braking effect; and the brake pad is started so that the forklift pad is pressed against the brake disc, thereby generating friction, which will resist the movement of the vehicle and cause the vehicle to slow down. The vehicle is braked by two braking methods, so that the vehicle can be quickly decelerated and completely stopped in a short time. If the safety distance is greater than or equal to the second set value, it means that the safety distance is longer, allowing the vehicle to reduce its speed in a relatively long time, then the vehicle can be braked only by starting energy recovery, and the vehicle will slow down smoothly.

[0056] In the above embodiment, the safe distance can be determined by the road intelligent recognition system through road satellite images. Specifically, the real-time location data of the vehicle is obtained, and the latitude and longitude information of the vehicle is usually obtained through a positioning system. The pixel coordinates of the road damage area in the road satellite image are converted into geographic coordinates (latitude and longitude), wherein the coordinate conversion here usually requires knowing the projection information and resolution of the road satellite image. After determining the geographic coordinates of the vehicle and the road damage area, the distance calculation formula between the geographic coordinates (such as the Haversing formula) is used to calculate the safe distance between the vehicle and the road damage area.

[0057] In one embodiment, the road quality information includes the road surface damaged area of ​​the road ahead, that is, the road surface intelligent recognition system can identify whether there is a road surface damaged area on the road ahead through the road surface satellite image. It can be understood that the road surface damaged area is usually accompanied by cracks and other damages, which may cause uneven distribution of road surface color and make the color of the road surface collapse area different from the color of other normal roads. Based on this, the road surface intelligent recognition system identifies the road surface damaged area of ​​the road ahead by analyzing the road surface color difference in the road surface satellite image. Specifically, the road surface satellite image is preprocessed, including color correction of the acquired road surface satellite image to eliminate the influence of illumination changes or other factors on the color, and then the image processing technology is used to remove the noise in the road surface satellite image to improve the accuracy of subsequent analysis. In the process of color difference analysis of the road surface satellite image, the road surface satellite image can be converted from the RGB color space to other color spaces (such as HSV color model, etc.), and then the different color areas in the road surface satellite image are separated by threshold segmentation or clustering algorithm. In general, the color of the normal road surface is uniform, while the collapsed area may show uneven color, darkening or discoloration, and the areas with obvious color changes in the road surface satellite image are identified, which may correspond to road surface damage.

[0058] In practical applications, in addition to color differences, the texture characteristics of the road surface can also be analyzed. The texture of the damaged area is usually different from that of the normal road surface. Features are extracted through texture analysis algorithms, and color and texture features are combined. Shape recognition technology (such as edge detection, contour extraction, etc.) is used to further confirm the boundaries of the damaged area of ​​the road surface.

[0059] In one embodiment, the road quality information includes a damaged road surface area of ​​the road ahead. In the process of identifying the damaged road surface area of ​​the road ahead, the road intelligent recognition system may change the recognition range of the road intelligent recognition system in the road satellite image due to different road types. Specifically, when there are at least two road branches in the road ahead of the vehicle, the road intelligent recognition system will determine whether the vehicle has set a navigation route. The navigation route can clearly indicate the target road branch that the vehicle needs to travel in each road branch, thereby limiting the recognition range of the road intelligent recognition system. If a navigation route is set, the road intelligent recognition system needs to identify whether there is a damaged road surface area in the target road branch in each road branch.

[0060] If the navigation route is not set, the intelligent road recognition system cannot determine the road branch that the vehicle is about to travel. In order to ensure driving safety, the intelligent road recognition system will identify whether there is a damaged road area in each road branch. Therefore, no matter which road branch the vehicle ultimately chooses, the damaged road area can be identified before the vehicle enters the road branch, allowing the vehicle to avoid the damaged road area in the road ahead in advance.

[0061] Furthermore, since identifying the image areas corresponding to all road branches in the road satellite image will bring about a large amount of data processing, in order to further improve the recognition rate of the road damage area, only the road surface about 200 meters ahead of the vehicle in the road branch can be identified.

[0062] In actual applications, the road ahead of the vehicle may also be a long straight road. In this case, the intelligent road surface recognition system needs to complete the recognition of the damaged road area before the vehicle enters the long straight road, so as to effectively avoid traffic jams caused by road damage on the long straight road.

[0063] In the above embodiment, the vehicle's road surface intelligent recognition system obtains road surface satellite images sent by the satellite for the road ahead of the vehicle. Since the road surface satellite images have the characteristics of high resolution, wide shooting angle and large area, the road surface intelligent recognition system can accurately identify the road surface quality of the road ahead in a larger range based on the road surface satellite images, and can adapt to the monitoring of different types of roads, so that the vehicle can be assisted in driving in time according to the road surface quality information, thereby improving the driving safety of the vehicle in different road environments and avoiding the occurrence of safety accidents.

[0064] In one embodiment, Figure 3 As shown, a vehicle assisted driving method based on road quality applied to a satellite is provided, and the method may include the following steps:

[0065] Step S201, receiving vehicle position information and driving direction information sent by the vehicle.

[0066] Here, the satellite can receive the vehicle position information and driving direction information sent by the vehicle through the communication network. The vehicle position information is the current vehicle position information obtained by the vehicle through the global positioning system (GPS) or other positioning technologies, usually expressed in the form of longitude and latitude, and the driving direction information is obtained through the vehicle sensor, usually expressed in angles.

[0067] Step S202: determining a satellite image of the road ahead of the vehicle based on the vehicle position information and the driving direction information.

[0068] Based on the vehicle's location information and driving direction information, the satellite can define a road area ahead, which is usually a rectangle or polygon, representing the road range in front of the vehicle. The satellite then takes satellite images of the road surface in this road range in real time, thereby obtaining satellite images of the road surface ahead of the vehicle.

[0069] Step S203, sending the road satellite image to the vehicle so that the vehicle performs assisted driving according to the road satellite image.

[0070] Satellites send road satellite images to vehicles through communication networks. After receiving the road satellite images, the vehicles can use different image processing algorithms to analyze the road satellite images to obtain road quality information of the road ahead, and then assist the vehicle in driving based on the road quality information, automatically adjust the vehicle's driving strategy on different roads, and improve the safety of the vehicle's driving on different roads.

[0071] Since the road satellite images taken by satellites have the characteristics of high resolution, they can provide rich details, making the road condition, damaged areas and other features more obvious, easy to identify and analyze, thereby improving the recognition accuracy of the road intelligent recognition system. In addition, the high perspective provided by road satellite images can overlook the entire road and its surrounding environment from above, and can also cover a wide area, so that it can be applied to different types of roads, facilitating accurate analysis by the road intelligent recognition system.

[0072] In the above embodiment, the satellite receives the vehicle position information and driving direction information sent by the vehicle, and then determines the road satellite image of the road ahead of the vehicle, and then sends the road satellite image to the vehicle, so that the vehicle can perform assisted driving based on the road satellite image. Since the road satellite image has the characteristics of high resolution, wide shooting angle and large area, the recognition accuracy of the road intelligent recognition system for the road satellite image can be improved, which is more conducive to assisted driving of the vehicle and also conducive to ensuring the driving safety of the vehicle.

[0073] In one embodiment, a vehicle is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, a vehicle assisted driving method based on road quality applied to a road intelligent recognition system of the vehicle is implemented.

[0074] In one embodiment, a computer storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, a vehicle assisted driving method based on road quality applied to a road intelligent recognition system of a vehicle is implemented.

[0075] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0076] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0077] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0078] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present invention, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0079] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.

Claims

1. A vehicle assisted driving method based on road quality, characterized in that: A road surface intelligent recognition system applied to a vehicle, the method comprising: Obtaining satellite road images sent by satellites for the road ahead of the vehicle; Identifying road quality information of the road ahead according to the road satellite image; The vehicle is assisted in driving according to the road quality information.

2. The vehicle assisted driving method based on road quality according to claim 1, characterized in that: Before acquiring the road surface satellite image sent by the satellite to the road ahead of the vehicle, the method further includes: The vehicle position information and the driving direction information of the vehicle are sent to the satellite, so that the satellite determines the road satellite image based on the vehicle position information and the driving direction information.

3. The vehicle assisted driving method based on road quality according to claim 1, characterized in that: The step of assisting the vehicle in driving according to the road quality information includes: In response to the road quality information indicating that there is a damaged road area on the road ahead, assisted driving of the vehicle is performed at least according to the remaining power of the vehicle.

4. The vehicle assisted driving method based on road quality according to claim 3, characterized in that: The assisting driving of the vehicle at least according to the remaining power of the vehicle includes: If the remaining power is greater than or equal to a first set value, the brake pad is activated; If the remaining power is less than the first set value, the braking method is determined according to a safety distance, where the safety distance represents the distance between the vehicle and the damaged road area.

5. The vehicle assisted driving method based on road quality according to claim 4, characterized in that: Determining the braking method according to the safety distance includes: If the safety distance is less than a second set value, energy recovery is started and the brake pad is started; If the safety distance is greater than or equal to the second set value, energy recovery is started.

6. The vehicle assisted driving method based on road quality according to claim 1, characterized in that: The road surface quality information includes a damaged road surface area of ​​the road ahead, and the identifying the road surface quality information of the road ahead according to the road surface satellite image includes: The road surface damaged area of ​​the road ahead is identified based on the road surface color difference in the road surface satellite image.

7. The vehicle assisted driving method based on road quality according to claim 1, characterized in that: The road surface quality information includes a damaged road surface area of ​​the road ahead, and the identifying the road surface quality information of the road ahead according to the road surface satellite image includes: In response to at least two road branches existing in a road ahead of the vehicle, determining whether the vehicle has set a navigation route; If it is determined that the vehicle sets the navigation route, identifying whether the road damage area exists in the target road branch according to the road satellite image; the target road branch represents the road branch indicated by the navigation route in each of the road branches; If it is determined that the vehicle has not set the navigation route, then identifying whether the road damaged area exists in each of the road branches according to the road satellite image.

8. A vehicle assisted driving method based on road quality, characterized in that: Applied to a satellite, the method comprises: Receiving vehicle location information and driving direction information sent by the vehicle; Determine a satellite image of the road surface of the road ahead of the vehicle according to the vehicle position information and the driving direction information; The road satellite image is sent to the vehicle, so that the vehicle performs assisted driving according to the road satellite image.

9. A vehicle, comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the vehicle assisted driving method based on road quality applied to a vehicle road intelligent recognition system as claimed in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the vehicle assisted driving method based on road quality applied to a road intelligent recognition system for a vehicle as claimed in any one of claims 1 to 7 is implemented.

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