Vehicle automatic driving control method, system, electronic device and storage medium

Abstract

The present application relates to a vehicle automatic driving control method, system, electronic device and storage medium, the method comprising: obtaining environmental image information collected by a preset camera device during vehicle driving, when the environmental image information does not meet the preset road condition recognition requirements, controlling the vehicle to drive in a low-speed mode, and obtaining environmental parameter information collected by a preset sensor during vehicle driving, wherein the vehicle's driving speed in the low-speed mode is less than a preset threshold; based on the environmental parameter information, the road condition of the road ahead of the vehicle is recognized, and the road condition recognition information of the road ahead of the vehicle is determined; according to the road condition recognition information and the environmental parameter information, the vehicle's automatic driving is controlled. Through this application, the problem of poor control performance of vehicle automatic driving on roads with poor road conditions in the related technology is solved, and the technical effect of improving the control performance of vehicle automatic driving is achieved.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle automatic driving control method, system, electronic device and storage medium. Background Art

[0002] With the emergence of intelligent transportation and the continuous development and application of automotive electronic technology and intelligent algorithms, how to achieve vehicle autonomous driving or assisted driving has become a very important research topic. The performance of the autonomous driving control system directly affects the vehicle's speed control accuracy and driving safety.

[0003] At present, when faced with poor road conditions, such as crossing a bridge, obstacles ahead, or unclear road conditions ahead, the autonomous driving systems or assisted driving systems in related technologies often pre-process the acquired images and then compare them with existing prior knowledge to obtain road condition recognition results. However, the road condition recognition accuracy of this type of technical solution is low and its applicability is narrow. Therefore, the control performance of vehicles using this autonomous driving system is poor when driving on roads with poor road conditions.

[0004] Currently, no effective solution has been proposed for the problem of poor control performance of vehicle autonomous driving on roads with poor road conditions in related technologies. Summary of the invention

[0005] The embodiments of the present application provide a vehicle automatic driving control method, system, electronic device and storage medium to at least solve the problem of poor control performance of vehicle automatic driving on roads with poor road conditions in the related art.

[0006] In a first aspect, an embodiment of the present application provides a method for controlling an automatic driving of a vehicle, the method comprising: obtaining environmental image information collected by a preset camera device during vehicle driving; when the environmental image information does not meet the preset road condition recognition requirements, controlling the vehicle to travel in a low-speed mode, and obtaining environmental parameter information collected by a preset sensor during vehicle driving, wherein the driving speed of the vehicle in the low-speed mode is less than a preset threshold; identifying the road condition of a road ahead of the vehicle based on the environmental parameter information, and determining the road condition recognition information of the road ahead of the vehicle; and controlling the automatic driving of the vehicle according to the road condition recognition information and the environmental parameter information.

[0007] In some of the embodiments, controlling the automatic driving of the vehicle according to the road condition identification information and the environmental parameter information includes: obtaining the driving status information collected by the sensor during the driving of the vehicle; planning the path of the vehicle according to the road condition identification information and the environmental parameter information, and determining the current planned path of the vehicle; and controlling the automatic driving of the vehicle according to the current planned path and the driving status information.

[0008] In some of the embodiments, controlling the automatic driving of the vehicle according to the current planned path and the driving status information includes: calculating the driving error amount of the vehicle based on the driving status information and the current planned path; converting the driving error amount into a correction amount using a PID control algorithm and / or a fuzzy control algorithm to obtain the driving correction amount of the vehicle; and controlling the automatic driving of the vehicle according to the driving correction amount of the vehicle.

[0009] In some embodiments, the driving correction amount includes: an angle correction amount, a speed correction amount and a sensor parameter correction amount; according to the driving correction amount of the vehicle, controlling the automatic driving of the vehicle includes: according to the angle correction amount, performing closed-loop control on the direction control module of the vehicle; according to the speed correction amount, performing closed-loop control on the speed control module of the vehicle; according to the sensor parameter correction amount, performing parameter configuration on the sensor.

[0010] In some embodiments, the sensor includes: a speed sensor and a distance sensor; the driving status information includes the distance between the vehicle and a preset position, the driving angle of the vehicle and the current driving speed of the vehicle; obtaining the driving status information collected by the sensor during the vehicle's driving process includes: using the distance sensor to collect the distance between the vehicle and the preset position, and the driving angle of the vehicle during the vehicle's driving process; using the speed sensor to collect the current driving speed of the vehicle during the vehicle's driving process.

[0011] In some of the embodiments, before determining the road condition identification information of the road ahead of the vehicle, the method also includes: when the environmental image information meets the preset road condition identification requirements, performing road condition identification on the road ahead of the vehicle based on the environmental image information to determine the road condition identification information of the road ahead of the vehicle.

[0012] In some of the embodiments, road condition identification of the road ahead of the vehicle is performed based on environmental image information, and determining the road condition identification information of the road ahead of the vehicle includes: capturing feature points of the environmental image information to obtain feature information of multiple environmental feature points; obtaining environmental parameter information collected by a preset sensor during vehicle driving; and identifying the road condition of the road ahead of the vehicle based on the feature information of multiple environmental feature points and the environmental parameter information to determine the road condition identification information of the road ahead of the vehicle.

[0013] In a second aspect, an embodiment of the present application provides a vehicle automatic driving control system, the system comprising: a sampling module, a processing module and a control module; wherein the sampling module comprises a camera device and a sensor, wherein the camera device is used to collect environmental image information during vehicle driving, and the sensor is used to collect environmental parameter information and driving status information during vehicle driving; the processing module is communicated with the sampling module and the control module respectively, and is used to execute the vehicle automatic driving control method as described in the first aspect above, and issue control instructions to the control module; the control module is controlled by the control instructions issued by the processing module, and controls the automatic driving of the vehicle.

[0014] In a third aspect, an embodiment of the present application further provides an electronic device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to execute the vehicle automatic driving control method as described in the first aspect above.

[0015] In a fourth aspect, an embodiment of the present application further provides a storage medium, in which a computer program is stored, wherein when the computer program is executed by a processor, the vehicle automatic driving control method as described in the first aspect above is implemented.

[0016] Compared with the related art, the vehicle automatic driving control method, system, electronic device and storage medium provided in the embodiments of the present application obtain environmental image information collected by a preset camera device during vehicle driving; when the environmental image information does not meet the preset road condition recognition requirements, the vehicle is controlled to travel in a low-speed mode, and environmental parameter information collected by a preset sensor during vehicle driving is obtained, wherein the vehicle's driving speed in the low-speed mode is less than a preset threshold; the road condition of the road ahead of the vehicle is recognized based on the environmental parameter information, and the road condition recognition information of the road ahead of the vehicle is determined; and the vehicle automatic driving is controlled according to the road condition recognition information and the environmental parameter information. The problem of poor control performance of vehicle automatic driving on roads with poor road conditions in the related art is solved, and the technical effect of improving the control performance of vehicle automatic driving is achieved.

[0017] Details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0019] Figure 1 is a structural block diagram of a vehicle automatic driving control system according to an embodiment of the present application;

[0020] Figure 2 is a flow chart of a vehicle automatic driving control method according to an embodiment of the present application;

[0021] Figure 3 is a schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated 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 intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in the present application, some changes such as design, manufacturing or production based on the technical contents disclosed in the present application are only conventional technical means, and should not be understood as insufficient contents disclosed in the present application.

[0023] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

[0024] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "a", "the" and the like involved in this application do not indicate a quantitative limitation, and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to greater than or equal to two. "And / or" describes the association relationship of associated objects, indicating that there can be three relationships, for example, "A and / or B" can represent: A exists alone, A and B exist at the same time, and B exists alone. The terms "first", "second", "third" and the like involved in the present application are merely used to distinguish similar objects and do not represent a specific ordering of the objects.

[0025] This embodiment provides a vehicle automatic driving control system. Figure 1 is a structural block diagram of a vehicle automatic driving control system according to an embodiment of the present application, such as Figure 1 As shown, the system includes: a sampling module 11, a processing module 12 and a control module 13; wherein the sampling module 11 includes a camera device 111 and a sensor 112, wherein the camera device 111 is used to collect environmental image information during vehicle driving, and the sensor 112 is used to collect environmental parameter information and driving state information during vehicle driving; the processing module 12 is communicated with the sampling module 11 and the control module 13 respectively, for a vehicle automatic driving control method, and sends control instructions to the control module 13; the control module 13 is controlled by the control instructions sent by the processing module 12, and controls the automatic driving of the vehicle.

[0026] In this embodiment, the camera device 111 can collect environmental images in real time during the driving process of the vehicle according to a preset period, and send the environmental image information to the memory through DMA (Direct Memory Access), obtain the environmental image information after performing pre-processing such as image thumbnail on the environmental image, and send the environmental image information to the processing module 12 for subsequent road condition recognition.

[0027] In this embodiment, the sensor 112 may include a distance sensor and a speed sensor. The distance sensor may include a TOF (Time Of Flight) sensor and an ultrasonic sensor. The speed sensor may include an encoder disposed in a vehicle motor. The sensor 112 also includes an electromagnetic sensor.

[0028] In the above embodiments, the electromagnetic sensor can detect the electromagnetic intensity in the space, and through hardware filtering processing, further detect the electromagnetic change state of the space, and use the electromagnetic change state of the space as one of the environmental parameter information; the TOF sensor can quickly detect the distance between it and the preset position, and during the high-speed driving of the vehicle, it can provide a reasonable basis for the obstacle avoidance and safe driving of the vehicle; the ultrasonic sensor is similar to a lidar, and its monitoring range is larger in a long-distance monitoring environment, so it can be used as a guidance aid for vehicle driving. By reading the I / O (input / output) interface of the ultrasonic sensor, the distance between the vehicle and the surrounding preset angle can be obtained, thereby obtaining the vehicle's driving angle; the encoder set in the vehicle's motor can directly read the rotation speed of the motor shaft, and then convert it to obtain the vehicle's driving speed.

[0029] In this embodiment, by integrating the environmental parameter information obtained by the detection of multiple sensors 112, subsequent road condition identification is performed based on the environmental parameter information obtained by the detection of multiple sensors 112, wherein the environmental parameter information may include distance information between the vehicle and a preset position, distance information between the vehicle and a preset angle, etc., when facing special road conditions or roads with poor road conditions, for example, when the road ahead is a bridge, there are obstacles on the road ahead, the road condition on the road ahead is unclear, etc., the road condition identification information of the road ahead can be accurately and quickly identified, the road condition category of the road ahead of the vehicle can be quickly determined, and then the vehicle's driving path can be planned, which solves the problem of poor control performance of vehicle automatic driving on roads with poor road conditions in related technologies, and achieves the technical effect of improving the control performance of vehicle automatic driving.

[0030] In this embodiment, the control module 13 is communicatively connected with the vehicle's drive module, wherein the vehicle's drive module may include a direction control module and a speed control module. After obtaining the road condition identification information of the road ahead of the vehicle, the processing module 12 sends a control instruction to the control module 13 based on the vehicle's road condition identification information and environmental parameter information. The control module 13 is controlled by the control instruction and performs closed-loop control on the direction control module and / or the speed control module to ensure that the vehicle's driving state meets the requirements of the currently planned path.

[0031] In the above embodiment, the sampling module 11, the processing module 12 and the control module 13 constitute a complete control framework from identification to control for vehicle autonomous driving. The processing module 12 can adopt MCU (Microcontroller Unit), wherein the sensors 112 and chips used in the sampling module 11, the processing module 12 and the control module 13 can be replaced according to different application scenarios, thereby changing the sensitivity of the control framework to adapt to the vehicle autonomous driving requirements in different application scenarios. The control framework has high separability and modularity, and meets the application requirements of multiple vehicles in multi-platform scenarios. At the same time, the control framework can be quickly developed and adapted by replacing different sensors 112, chips and other resources, so that the vehicle autonomous driving control system has better stability and portability.

[0032] In some of the embodiments, the processing module 12 is configured to obtain environmental image information collected by a preset camera device 111 during vehicle driving; when the environmental image information does not meet the preset road condition recognition requirements, control the vehicle to travel in a low-speed mode, and obtain environmental parameter information collected by a preset sensor 112 during vehicle driving, wherein the vehicle's driving speed in the low-speed mode is less than a preset threshold; identify the road condition of the road ahead of the vehicle based on the environmental parameter information, and determine the road condition recognition information of the road ahead of the vehicle; and control the vehicle's automatic driving based on the road condition recognition information and the environmental parameter information.

[0033] In some of the embodiments, the processing module 12 is configured to obtain driving status information collected by the sensor 112 during the driving of the vehicle; plan the path of the vehicle based on the road condition identification information and environmental parameter information to determine the current planned path of the vehicle; and control the automatic driving of the vehicle based on the current planned path and driving status information.

[0034] In some of the embodiments, the processing module 12 is configured to calculate the driving error of the vehicle based on driving state information and the current planned path; convert the driving error into a correction amount using a PID control algorithm and / or a fuzzy control algorithm to obtain a driving correction amount for the vehicle; and control the automatic driving of the vehicle according to the driving correction amount of the vehicle.

[0035] In some of the embodiments, the driving correction amount includes: an angle correction amount, a speed correction amount and a sensor parameter correction amount; the processing module 12 is configured to perform closed-loop control on the vehicle's direction control module 13 according to the angle correction amount; perform closed-loop control on the vehicle's speed control module 13 according to the speed correction amount; and perform parameter configuration on the sensor 112 according to the sensor parameter correction amount.

[0036] In some of the embodiments, the sensor 112 includes: a speed sensor and a distance sensor; the driving state information includes the distance between the vehicle and a preset position, the driving angle of the vehicle and the current driving speed of the vehicle; the processing module 12 is configured to use the distance sensor to collect the distance between the vehicle and the preset position and the driving angle of the vehicle during the vehicle's driving process; and use the speed sensor to collect the current driving speed of the vehicle during the vehicle's driving process.

[0037] In some of the embodiments, the processing module 12 is configured to identify the road condition of the road ahead of the vehicle based on the environmental image information and determine the road condition identification information of the road ahead of the vehicle when the environmental image information meets the preset road condition identification requirements.

[0038] In some of the embodiments, the processing module 12 is configured to capture feature points of environmental image information to obtain feature information of multiple environmental feature points; obtain environmental parameter information collected by a preset sensor 112 during vehicle driving; identify the road condition of the road ahead of the vehicle based on the feature information of multiple environmental feature points and the environmental parameter information, and determine the road condition identification information of the road ahead of the vehicle.

[0039] This embodiment provides a vehicle automatic driving control method, Figure 2 is a flow chart of a vehicle automatic driving control method according to an embodiment of the present application, such as Figure 2 As shown, the method includes:

[0040] Step S201, obtaining environmental image information collected by a preset camera device during vehicle driving.

[0041] In this embodiment, the camera device can collect environmental images in real time during vehicle driving according to a preset period, and transfer them to the memory through DMA, perform pre-processing such as image thumbnail and image filtering on the environmental images to obtain environmental image information.

[0042] Step S202, when the environmental image information does not meet the preset road condition recognition requirements, control the vehicle to travel in a low-speed mode, and obtain environmental parameter information collected by a preset sensor during the vehicle's driving process, wherein the vehicle's driving speed in the low-speed mode is less than a preset threshold.

[0043] In this embodiment, when the environmental image information does not meet the preset road condition recognition requirements, it is determined that the road condition category of the road ahead of the vehicle cannot be determined through the current environmental image. For example, when the vehicle is traveling at high speed, the environmental image captured by the camera device is stretched, blurred, etc. At this time, it is necessary to control the vehicle to travel in a low-speed mode. In the low-speed mode, a longer detection time can be obtained in the same distance, and multiple sensors can obtain more environmental parameter information. The subsequent road condition recognition accuracy based on the environmental parameter information detected by multiple sensors is also higher; similarly, if the environmental image information is still needed to be used to identify the road condition of the road ahead of the vehicle, the environmental image information obtained by the camera device in the low-speed mode is also clearer and more in line with the road condition recognition requirements, wherein the preset threshold value can be 20km / h, 30km / h, etc., and the preset threshold value can be set according to the road condition and user needs. .

[0044] Step S203: identifying the road condition of the road ahead of the vehicle based on the environmental parameter information, and determining the road condition identification information of the road ahead of the vehicle.

[0045] In this embodiment, the road condition categories of the road ahead of the vehicle include the road ahead being a bridge, the road ahead having obstacles, the road ahead having unclear road conditions, etc., and parameter adjustment is performed based on the environmental parameter information detected by multiple sensors, and special road conditions are identified and subsequent path planning is calculated. When the environmental image captured by the camera device cannot meet the road condition identification requirements, the road condition identification information of the road ahead can be accurately and quickly identified, the road condition category of the road ahead of the vehicle can be quickly determined, and the vehicle's driving path can be planned.

[0046] Step S204, controlling the automatic driving of the vehicle according to the road condition identification information and the environmental parameter information.

[0047] In this embodiment, based on the road condition identification information and the environmental parameter information, controlling the automatic driving of the vehicle may include: obtaining the driving status information collected by the sensor during the driving of the vehicle, planning the path of the vehicle based on the road condition identification information and the environmental parameter information, and determining the current planned path of the vehicle; and controlling the automatic driving of the vehicle based on the current planned path and the driving status information.

[0048] In this embodiment, based on the road condition identification information and environmental parameter information, the vehicle path is planned to determine the vehicle's current planned path. Based on the vehicle's driving state information, the error between the vehicle's current driving state and the current planned path can be determined. Error correction is performed based on the error to ensure that the vehicle can correctly drive on the current planned path, thereby realizing automatic driving control of the vehicle.

[0049] Through the above steps S201 to S204, when the environmental image information collected by the preset camera device during the vehicle driving does not meet the preset road condition recognition requirements, the vehicle is controlled to travel in a low-speed mode, and the environmental parameter information collected by the preset sensor during the vehicle driving is obtained, wherein the driving speed of the vehicle in the low-speed mode is less than the preset threshold; the road condition of the road ahead of the vehicle is identified based on the environmental parameter information, and the road condition recognition information of the road ahead of the vehicle is determined; according to the road condition recognition information and the environmental parameter information, the vehicle is controlled to automatically drive. When the environmental image captured by the camera device cannot meet the road condition recognition requirements, the environmental parameter information obtained by the sensor detection is integrated, and the subsequent road condition recognition is performed based on the environmental parameter information obtained by the sensor detection. When facing special road conditions or roads with poor road conditions, such as when the road ahead is a bridge, there are obstacles on the road ahead, and the road condition of the road ahead is unclear, the road condition recognition information of the road ahead can be accurately and quickly identified, and the road condition category of the road ahead of the vehicle can be quickly determined, and then the vehicle's driving path can be planned. Through this application, the problem of poor control performance of vehicle automatic driving on roads with poor road conditions in the related technology is solved, and the technical effect of improving the control performance of vehicle automatic driving is achieved.

[0050] In some of the embodiments, according to the current planned path and driving status information, controlling the vehicle to automatically drive is achieved through the following steps:

[0051] Step 1: Calculate the driving error of the vehicle based on the driving state information and the current planned path.

[0052] Step 2: convert the driving error amount into a correction amount using a PID control algorithm and / or a fuzzy control algorithm to obtain a driving correction amount for the vehicle.

[0053] Step 3, controlling the vehicle to drive automatically according to the vehicle's driving correction amount.

[0054] In this embodiment, the driving correction amount may include: an angle correction amount, a speed correction amount and a sensor parameter correction amount; according to the vehicle's driving correction amount, controlling the vehicle's automatic driving may include: performing closed-loop control on the vehicle's direction control module according to the angle correction amount; performing closed-loop control on the vehicle's speed control module according to the speed correction amount; and performing parameter configuration on the sensor according to the sensor parameter correction amount.

[0055] In the above embodiment, after obtaining the vehicle's driving status information and the current planned path, the driving error amount can be converted to the driving correction amount based on the vehicle's driving status information and the current planned path using a PID control algorithm and / or a fuzzy control algorithm according to the vehicle's current road condition identification information, and the angle correction amount is sent to the vehicle's direction control module (such as the vehicle's servo), and the speed correction amount is sent to the vehicle's speed control module (such as the vehicle's stepper motor), and the direction control module and the speed control module are closed-loop controlled respectively; similarly, the sensor parameters can also be configured based on the sensor parameter correction amount to ensure that the sensor can adapt to the needs of various road conditions and continuously improve the sensor's detection accuracy.

[0056] In some embodiments, the sensor includes: a speed sensor and a distance sensor; the driving state information includes the distance between the vehicle and a preset position, the driving angle of the vehicle, and the current driving speed of the vehicle; obtaining the driving state information collected by the sensor during the driving of the vehicle is achieved by the following steps:

[0057] Step 1: Use a distance measuring sensor to collect the distance between the vehicle and a preset position and the driving angle of the vehicle during the vehicle's driving process.

[0058] Step 2: Use a speed sensor to collect the current speed of the vehicle while the vehicle is traveling.

[0059] In this embodiment, the sensor may include a distance sensor and a speed sensor. The distance sensor may include a TOF (Time Of Flight) sensor and an ultrasonic sensor. The speed sensor may include an encoder disposed in a vehicle motor. The sensor 112 also includes an electromagnetic sensor.

[0060] In the above embodiments, the electromagnetic sensor can detect the electromagnetic intensity in the space, and through hardware filtering processing, further detect the electromagnetic change state of the space, and use the electromagnetic change state of the space as one of the environmental parameter information; the TOF sensor can quickly detect the distance between it and the preset position, and during the high-speed driving of the vehicle, it can provide a reasonable basis for the obstacle avoidance and safe driving of the vehicle; the ultrasonic sensor is similar to a lidar, and its monitoring range is larger in a long-distance monitoring environment, so it can be used as a guidance aid for vehicle driving. By reading the I / O (input / output) interface of the ultrasonic sensor, the distance between the vehicle and the surrounding preset angle can be obtained, thereby obtaining the vehicle's driving angle; the encoder set in the vehicle's motor can directly read the rotation speed of the motor shaft, and then convert it to obtain the vehicle's driving speed.

[0061] In some of the embodiments, before determining the road condition identification information of the road ahead of the vehicle, the method also includes: when the environmental image information meets the preset road condition identification requirements, performing road condition identification on the road ahead of the vehicle based on the environmental image information to determine the road condition identification information of the road ahead of the vehicle.

[0062] In this embodiment, road condition identification of the road ahead of the vehicle is performed based on environmental image information, and determining road condition identification information of the road ahead of the vehicle may include: capturing feature points of the environmental image information to obtain feature information of multiple environmental feature points; obtaining environmental parameter information collected by a preset sensor during vehicle driving; and identifying the road condition of the road ahead of the vehicle based on the feature information and environmental parameter information of multiple environmental feature points to determine road condition identification information of the road ahead of the vehicle.

[0063] In this embodiment, when the environmental image information collected by the camera device meets the preset road condition recognition requirements, it can be determined that the current road condition is good or the camera device is in good working condition, and the vehicle can be controlled to enter the low-speed mode without being controlled to enter the normal speed mode or the high-speed mode, ensuring that the vehicle can travel at a faster speed when the current road condition is good or the camera device is in good working condition, thereby increasing the vehicle's driving speed while ensuring the vehicle's driving safety.

[0064] In the above embodiment, feature points of environmental image information can be captured to obtain feature information of multiple environmental feature points, and the road condition of the road ahead of the vehicle can be identified based on the feature information of multiple environmental feature points and environmental parameter information collected by the sensor during the vehicle's driving process, thereby improving the accuracy of road condition identification of the road ahead of the vehicle, and then improving the reliability and accuracy of planning the vehicle's driving path, ensuring that the vehicle can correctly drive on a more accurately planned path, thereby improving the control performance of the vehicle's automatic driving.

[0065] This embodiment also provides an electronic device, Figure 3 is a schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application, such as Figure 3 As shown, the electronic device includes a memory 304 and a processor 302. The memory 304 stores a computer program, and the processor 302 is configured to run the computer program to execute the steps in any of the above method embodiments.

[0066] Specifically, the processor 302 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application.

[0067] Among them, the memory 304 may include a large-capacity memory for data or instructions. By way of example and not limitation, the memory 304 may include a hard disk drive (HDD), a floppy disk drive, a solid-state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive, or a combination of two or more of these. Where appropriate, the memory 304 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 304 may be inside or outside the vehicle's automatic driving control system. In a specific embodiment, the memory 304 is a non-volatile memory. In a specific embodiment, the memory 304 includes a read-only memory (ROM) and a random access memory (RAM). Where appropriate, the ROM may be a mask-programmed ROM, a programmable ROM (Programmable Read-Only Memory, PROM for short), an erasable PROM (ErasableProgrammable Read-Only Memory, EPROM for short), an electrically erasable PROM (Electrically ErasableProgrammable Read-Only Memory, EEPROM for short), an electrically alterable ROM (ElectricallyAlterable Read-Only Memory, EAROM for short) or a flash memory (FLASH) or a combination of two or more of these. Under appropriate circumstances, the RAM can be a static random access memory (SRAM) or a dynamic random access memory (DRAM), wherein the DRAM can be a fast page mode dynamic random access memory (FPMDRAM), an extended data output dynamic random access memory (EDODRAM), a synchronous dynamic random access memory (SDRAM), etc.

[0068] The memory 304 may be used to store or cache various data files required for processing and / or communication, as well as possible computer program instructions executed by the processor 302 .

[0069] The processor 302 implements any one of the vehicle automatic driving control methods in the above embodiments by reading and executing computer program instructions stored in the memory 304.

[0070] Optionally, the electronic device may further include a transmission device 306 and an input / output device 308 , wherein the transmission device 306 is connected to the processor 302 , and the input / output device 308 is connected to the processor 302 .

[0071] Optionally, in this embodiment, the processor 302 may be configured to perform the following steps through a computer program:

[0072] S1, obtaining environmental image information collected by a preset camera device during vehicle driving.

[0073] S2, when the environmental image information does not meet the preset road condition recognition requirements, control the vehicle to travel in a low-speed mode, and obtain environmental parameter information collected by a preset sensor during the vehicle's driving, wherein the vehicle's driving speed in the low-speed mode is less than a preset threshold.

[0074] S3, identifying the road condition of the road ahead of the vehicle based on the environmental parameter information, and determining the road condition identification information of the road ahead of the vehicle.

[0075] S4, controlling the vehicle to drive automatically based on the road condition recognition information and environmental parameter information.

[0076] It should be noted that the specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementation modes, and this embodiment will not be described in detail here.

[0077] In addition, in combination with the vehicle automatic driving control method in the above embodiments, the present application embodiment can provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any one of the vehicle automatic driving control methods in the above embodiments is implemented.

[0078] Those skilled in the art should understand that the technical features of the above embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0079] The above embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A vehicle automatic driving control method, characterized in that: The method comprises: Acquire environmental image information collected by a preset camera device during vehicle driving; When the environmental image information does not meet the preset road condition recognition requirements, control the vehicle to travel in a low-speed mode, and obtain environmental parameter information collected by a preset sensor during the vehicle's travel, wherein the vehicle's travel speed in the low-speed mode is less than a preset threshold; Based on the environmental parameter information, a road condition identification is performed on a road ahead of the vehicle to determine road condition identification information of the road ahead of the vehicle; According to the road condition identification information and the environmental parameter information, controlling the automatic driving of the vehicle includes: Acquiring the driving state information collected by the sensor during the driving of the vehicle includes: The sensors include: a speed sensor and a distance sensor; the driving state information includes the distance between the vehicle and a preset position, the driving angle of the vehicle and the current driving speed of the vehicle; Using the distance measuring sensor to collect the distance between the vehicle and a preset position and the driving angle of the vehicle during the vehicle driving process; Using the speed sensor to collect the current speed of the vehicle during the vehicle's travel; Performing path planning for the vehicle according to the road condition identification information and the environmental parameter information to determine a current planned path for the vehicle; The vehicle is controlled to drive automatically according to the current planned path and the driving status information.

2. The vehicle automatic driving control method according to claim 1, characterized in that: Controlling the automatic driving of the vehicle according to the current planned path and the driving state information includes: Calculating a driving error amount of the vehicle based on the driving state information and the current planned path; Converting the driving error amount into a correction amount using a PID control algorithm and / or a fuzzy control algorithm to obtain a driving correction amount for the vehicle; The vehicle is controlled to drive automatically according to the driving correction amount of the vehicle.

3. The vehicle automatic driving control method according to claim 2, characterized in that: The driving correction amount includes: an angle correction amount, a speed correction amount and a sensor parameter correction amount; and according to the driving correction amount of the vehicle, controlling the automatic driving of the vehicle includes: Performing closed-loop control on a direction control module of the vehicle according to the angle correction amount; performing closed-loop control on a speed control module of the vehicle according to the speed correction amount; The sensor is configured with parameters according to the sensor parameter correction amount.

4. The vehicle automatic driving control method according to claim 1, characterized in that: Before determining the road condition identification information of the road ahead of the vehicle, the method further includes: When the environmental image information meets the preset road condition recognition requirements, the road condition of the road ahead of the vehicle is recognized based on the environmental image information to determine the road condition recognition information of the road ahead of the vehicle.

5. The vehicle automatic driving control method according to claim 4, characterized in that: The road condition recognition of the road ahead of the vehicle is performed based on the environmental image information, and the road condition recognition information of the road ahead of the vehicle is determined, including: Capturing feature points of the environmental image information to obtain feature information of multiple environmental feature points; Obtaining environmental parameter information collected by preset sensors during vehicle driving; The road condition of the road ahead of the vehicle is identified based on the feature information of a plurality of environmental feature points and the environmental parameter information, and the road condition identification information of the road ahead of the vehicle is determined.

6. A vehicle automatic driving control system, characterized in that: The system comprises: a sampling module, a processing module and a control module; wherein, The sampling module includes a camera device and a sensor, wherein the camera device is used to collect environmental image information during the vehicle's driving process, and the sensor is used to collect environmental parameter information and driving state information during the vehicle's driving process; The processing module is respectively connected to the sampling module and the control module for executing the vehicle automatic driving control method according to any one of claims 1 to 5, and sending control instructions to the control module; The control module is controlled by the control instructions issued by the processing module to control the automatic driving of the vehicle.

7. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to run the computer program to execute the vehicle automatic driving control method according to any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program, when executed by the processor, implements the vehicle automatic driving control method according to any one of claims 1 to 5. System method.

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