Intelligent passenger car road condition automatic identification control method and system

Abstract

The invention discloses an intelligent passenger car road condition automatic identification control method and system, and the method comprises the steps: a main controller carries out the initial road condition identification judgment based on a vehicle environment image digital quantity and an obstacle distance digital quantity, and judges a current first road condition; the auxiliary controller performs secondary road condition recognition judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity, and judges a current second road condition; judging whether the second road condition is consistent with the first road condition or not, if yes, determining the current road condition, and if not, obtaining data again for judgment; whether steering is needed or not is judged based on the current road condition and the obstacle distance digital quantity, if yes, the offset is calculated, the steering angle of the whole vehicle is adjusted based on the offset, and if not, steering is not conducted, and the vehicle runs linearly at a constant speed; and judging whether the vehicle speed needs to be adjusted based on the current road condition and the current vehicle speed digital quantity, if so, adjusting the rotating speed of the motor, and if not, not adjusting. The road condition automatic identification control of whole vehicle driving is realized, and unpredictable errors caused by insufficient concentration of a driver are avoided.

Description

Technical Field

[0001] The present invention relates to the field of automobile research and development, design and manufacturing, and in particular to an intelligent bus road condition automatic identification control method and system. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] As the bus industry enters a critical stage of rapid development and transformation, new models pay more attention to issues such as intelligence, informationization, and safety. Buses operating under complex working conditions and road conditions are a test for inexperienced drivers. The safety of vehicles and passengers during driving cannot be guaranteed 100%. The intelligent assisted driving system is a new breakthrough in identifying various road conditions, such as potholes, mountain roads, steep slopes, and pedestrians. Under the premise of ensuring the safe operation of the whole vehicle, it is a major project to achieve precise identification of different road conditions, different angles, and different directions. Research data shows that the probability of bus accidents in bad road conditions is gradually increasing every year. With the development of science and technology, the performance of vehicle parts is constantly improving. However, in order to reduce costs, some manufacturing industries often use parts with some quality problems. In this case, it is necessary to prevent the problem of vehicle failure.

[0004] At present, most pure electric bus models require drivers to observe changes in road conditions at all times and perform corresponding driving operations according to different road conditions. However, this is a great test for drivers who have been driving fatigued for a long time. They are prone to fatigue and lack of concentration, and are unable to observe changes in road conditions in time, and thus unable to respond in time, which may lead to serious traffic accidents. Summary of the invention

[0005] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a method and system for automatic identification and control of road conditions of an intelligent bus, which innovatively solves the problem of automatic assisted driving of the whole vehicle under different road conditions. The speed of the intelligent bus can be steplessly adjusted according to different road conditions.

[0006] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0007] In a first aspect, the present invention provides a method for automatically identifying and controlling road conditions of an intelligent bus, comprising:

[0008] Initialize the main controller and the auxiliary controller, and pre-set the digital range and vehicle speed corresponding to different road conditions;

[0009] The main controller and the auxiliary controller obtain the vehicle environment image, the current vehicle speed and the obstacle distance in the current driving environment, and convert the obtained data into corresponding digital quantities to obtain the digital quantity of the vehicle environment image, the digital quantity of the current vehicle speed and the digital quantity of the obstacle distance;

[0010] The main controller performs a primary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance, and judges the current first road condition; the auxiliary controller performs a secondary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance, and judges the current second road condition; judges whether the second road condition is consistent with the first road condition, and if so, determines the current road condition, and if not, re-acquires data for judgment;

[0011] Based on the current road condition and the digital quantity of the obstacle distance, determine whether turning is required. If so, calculate the offset and adjust the vehicle's steering angle based on the offset. Otherwise, no turning is performed and the vehicle travels in a straight line at a constant speed. Based on the current road condition and the current digital quantity of the vehicle speed, determine whether the vehicle speed needs to be adjusted. If so, adjust the motor speed. Otherwise, do not adjust it.

[0012] Further technical features, the main controller is a NI myRIO controller, and the auxiliary controller is an STM32 controller.

[0013] As a further technical feature, the NI myRIO controller integrates automatic assisted driving and manual driving modes, which are controlled by two different programs and are controlled in series through rocker switches and voice recognition.

[0014] According to a further technical feature, the NI myRIO controller is also connected to a clock circuit and a watchdog circuit.

[0015] A further technical feature is that the vehicle environment image, current vehicle speed and obstacle distance data are obtained through a camera, a vehicle speed sensor and a distance sensor to identify and judge the road condition.

[0016] A further technical feature is that the interfaces of the camera and the distance sensor are connected point-to-point with the interface of the NI myRIO controller.

[0017] A further technical feature is that the road condition recognition and judgment is specifically carried out by comparing the digital quantities converted from the vehicle environment image and obstacle distance acquired in the current driving environment with the digital quantity ranges corresponding to the preset different road conditions. The road condition corresponding to the digital quantity range that the current digital quantity meets is the current first road condition or the current second road condition.

[0018] In a second aspect, the present invention provides an intelligent passenger car road condition automatic identification control system, comprising:

[0019] A system initialization module, which is configured to: initialize the main controller and the auxiliary controller, and pre-set the digital quantity range and vehicle speed corresponding to different road conditions;

[0020] The data acquisition module is configured as follows: the main controller and the auxiliary controller acquire the vehicle environment image, the current vehicle speed and the obstacle distance in the current driving environment, and convert the acquired data into corresponding digital quantities to obtain the vehicle environment image digital quantity, the current vehicle speed digital quantity and the obstacle distance digital quantity;

[0021] The road condition recognition module is configured as follows: the main controller performs a primary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance to judge the current first road condition; the auxiliary controller performs a secondary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance to judge the current second road condition; judges whether the second road condition is consistent with the first road condition, if so, determines the current road condition, if not, re-acquires data for judgment;

[0022] The adaptive adjustment module is configured as follows: based on the current road condition and the digital quantity of the obstacle distance, determine whether turning is required; if so, calculate the offset; adjust the vehicle direction angle based on the offset; otherwise, do not turn and the vehicle travels in a straight line at a constant speed; based on the current road condition and the digital quantity of the current vehicle speed, determine whether the vehicle speed needs to be adjusted; if so, adjust the motor speed; otherwise, do not adjust.

[0023] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps in the method for automatic identification and control of road conditions of an intelligent bus as described in the first aspect.

[0024] In a fourth aspect, the present invention provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the method for automatic identification and control of road conditions of an intelligent bus as described in the first aspect are implemented.

[0025] One or more of the above technical solutions have the following beneficial effects:

[0026] This invention innovatively solves the problem of automatic assisted driving of the whole vehicle under different road conditions such as straight roads, curves, hillsides, steep roads, pedestrians, and red lights. The speed of the smart bus can be adjusted steplessly according to different road conditions. The innovative application of the NI myRIO controller has been developed to meet the needs of unmanned driving under any working conditions, breaking through the traditional shackles of the bus industry.

[0027] The present invention realizes automatic recognition and control of road conditions for the whole vehicle's intelligent driving, avoiding unpredictable mistakes made by the driver due to lack of concentration. The NI myRIO controller recognizes and judges different road conditions based on real-time digital quantities to automatically control the stopping, moving and speed of the smart bus, thereby improving the safety performance and service life of the whole vehicle, improving the comfort and intelligent driving experience of passengers, and protecting the personal and property safety of the driver and passengers.

[0028] The present invention further arranges an STM32 controller as an auxiliary controller, and performs a secondary judgment on the current road condition through the auxiliary controller. The auxiliary controller recognizes and judges the road condition again to prevent the main controller from making recognition errors, thereby achieving an accurate recognition effect.

[0029] The present invention adopts the NI myRIO controller, which reduces the laying of the wiring harness of the whole vehicle and improves the response time of the control system. The setting of the NI myRIO control system function can be connected through the CAN network communication, and the program is written using the LabVIEW software program flowchart, which improves the work efficiency of research and development and design and reduces the manufacturing cost of the smart bus. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0031] Figure 1 is a flow chart of an automatic identification and control method for intelligent passenger car road conditions according to an embodiment of the present invention;

[0032] Figure 2 It is an architecture diagram of an intelligent bus road condition automatic identification control system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0034] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0035] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0036] Embodiment 1

[0037] like Figure 1 , 2 As shown, this embodiment discloses a method for automatically identifying and controlling road conditions of an intelligent bus, the method comprising the following steps:

[0038] S1: Initialize the main controller and the auxiliary controller, and pre-set the digital range and vehicle speed corresponding to different road conditions;

[0039] In this embodiment, the main controller is the NI myRIO controller, which uses the NI myRIO control circuit, which has an embedded XiLinx Zynq chip and has different degrees of intelligence (memory, perception, recognition, calculation, reasoning, and learning). The NI myRIO controller integrates automatic assisted driving and manual driving modes, which are controlled by two different programs and are controlled in series through rocker switches and voice recognition to ensure the safety and error-freeness of the vehicle during autonomous driving.

[0040] Furthermore, the NI myRIO controller is also connected to the clock circuit and the watchdog circuit. The clock signal and the watchdog are used to ensure that the entire vehicle responds quickly. The clock signal improves the response efficiency and time of the entire control system, and controls the speed of the smart bus through the response time; the watchdog prevents the program from running away or entering an infinite loop due to interference from external signals, ensuring stable operation of the program.

[0041] The auxiliary controller is an STM32 controller, which is connected to the I / O port of the NI myRIO controller and is connected to the automatic assisted driving system through the pins GPIO_SCL and GPIO_SDA. It should be noted that the automatic assisted driving system in this embodiment is an existing system, and the structure and working principle of the system are not further described here.

[0042] The digital quantity range corresponding to various road conditions can be set through program programming, that is, the digital quantity range converted from images collected by the camera and distance data collected by the distance sensor corresponding to road conditions such as straight road (MXP_straightroad), curve (MXP_curve), hillside (MXP_hillside), steep road (MXP_steep road), traffic light (MXP_traffic light), pedestrian (MXP_pedestrian), vehicle (MXP_car), and other (MXP_other).

[0043] The vehicle speed signal MOTOR_speed_ is used to control the vehicle speed according to different road conditions through the program IF statement.

[0044] In some embodiments, the NI myRIO controller supports electrical signals and CAN communications, and is programmed through LabVIEW 2023 software to identify and judge road conditions of input signals. Different functional instructions are then designed and analyzed through the program, and the identified road condition signals are output and processed through serial port communication.

[0045] S2: The main controller and the auxiliary controller obtain the vehicle environment image, the current vehicle speed and the obstacle distance in the current driving environment, and convert the obtained data into corresponding digital quantities to obtain the digital quantity of the vehicle environment image, the digital quantity of the current vehicle speed and the digital quantity of the obstacle distance;

[0046] In this embodiment, various data are obtained through cameras, distance sensors, steering wheel angle sensors and vehicle speed sensors. Preferably, 8 cameras and 24 distance sensors are used to collect environmental data in all directions, 360 degrees, without blind spots, errors or delays, in front of the bus, in front of the left, in front of the right, on the left and on the right of the bus. The appropriate number of devices can be selected according to the actual situation without specific limitation.

[0047] The vehicle environment image refers to the road images in front of the bus, in front of the left, in front of the right, on the left and on the right side of the bus collected by 8 cameras. The road image can represent the corresponding road conditions; the obstacle distance refers to the distance, height and distance between the obstacles in front of the bus, in front of the left, in front of the right, on the left, on the right and on the rear of the bus collected by 24 distance sensors.

[0048] The different conversions between analog and digital quantities can achieve accurate judgment of the entire system. The conversion process is to sample and quantize the analog signals collected by the camera and distance sensor through the A / D converter, convert them into digital signals, and represent the quantized values ​​through binary codes. The binary code is the output signal of the A / D converter, that is, the digital quantity of the image and distance collected by the camera and distance sensor.

[0049] The camera and distance sensor interface DCMI are hard-wired to the NI myRIO controller interface MXP_A. In other words, the 8-way camera and 24-way sensor are externally detected and the detection signals are transmitted to the NI myRIO signal input interface MXP_A through the DCMI interface. The various external road condition signals are converted into analog and digital quantities through program control logic. The straight road (MXP_straight road), curve (MXP_curve), hillside (MXP_hillside), steep road (MXP_steeproad), traffic light (MXP_traffic light), pedestrian (MXP_pedestrian), vehicle (MXP_car), and others (MXP_other) are programmed through the Switch statement, and the corresponding program execution commands are executed for how to adjust the speed of vehicles under different road conditions. The NI myRIO controller will identify and judge the road conditions based on the real-time collected data.

[0050] S3: The main controller performs a primary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance, and judges the current first road condition; the auxiliary controller performs a secondary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance, and judges the current second road condition; judges whether the second road condition is consistent with the first road condition, and if so, determines the current road condition, and if not, re-acquires data for judgment;

[0051] In this embodiment, the auxiliary controller performs a secondary judgment on the current road condition, and the auxiliary controller recognizes and judges the road condition again to prevent the main controller from making mistakes in recognition, thereby achieving the effect of accurate recognition.

[0052] The NI myRIO controller and the STM32 controller are used to analyze and calculate the data collected by the data acquisition module. The two have the same method for identifying and judging road conditions, which is to compare the digital quantity converted from the vehicle environment image and obstacle distance in the current driving environment with the preset digital quantity range corresponding to different road conditions. The road condition corresponding to the digital quantity range that the current digital quantity meets is the current first road condition or the current second road condition. When the current first road condition is consistent with the current second road condition, it is the current road condition for identification and judgment.

[0053] It uses dual-loop serial communication, which consists of two inputs and two outputs. It communicates external signals (i.e. data collected by various sensors and cameras) to the NI myRIO controller SPI bus through the RXD pin, and the real-time road condition signals determined internally are transmitted to the display terminal (vehicle integrated instrument) through the NI myRIO controller for display. The central control display screen of the vehicle integrated instrument is connected to the remote monitoring platform through the CAN communication message 0X17 signal, which displays the running track of the vehicle in real time and can monitor the vehicle safety at any time.

[0054] Furthermore, the display terminal uses LabVIEW software to write the data for the interaction between the LCD screen and the NI myRIO controller in the interface of the program flowchart, and directly calls the program flowchart. The program will automatically recognize and judge the images under different working conditions, and convert the analog quantity read back into digital quantity and display it on the LCD screen interface. In other words, the NImyRIO controller converts the analog quantity read back into digital quantity and sends it to the display terminal for display. The display terminal has a separate subroutine to communicate with the NI myRIO controller main program.

[0055] After the main controller and the auxiliary controller determine the current road conditions (different road conditions include straight roads, curves, hillsides, steep roads, traffic lights, pedestrians, etc.), the vehicle can respond quickly to different road conditions. For example, if it is identified that the current driving environment is a red light road condition, the main controller controls the motor to stop and stop the vehicle. If it is identified that the current driving environment is a green light road condition, the main controller controls the motor to start and drive the vehicle.

[0056] If the vehicle can be automatically assisted in driving without manual control, the auxiliary controller is connected to the automatic assisted driving system through the pins GPIO_SCL and GPIO_SDA, and the identified current road condition signal is sent to the automatic assisted driving system. On the basis of the existing automatic assisted driving system, the ESC angular displacement sensor and EPS coupling mechanism are added to prevent vehicle speed failure, steering failure, and angle deviation.

[0057] Furthermore, to prevent vehicle speed failure, the motor encoder program is connected to the NI myRIO controller and certain conditions are preset for the vehicle speed. That is, when the corresponding road conditions are met, the motor speed is converted, stopped, etc. In other words, when there are obstacles, the vehicle speed will not execute the current speed, and the motor speed will reduce the speed to reach the risk value of failure due to excessive speed.

[0058] S4: Determine whether turning is required based on the current road condition and the digital value of the obstacle distance. If so, calculate the offset and adjust the vehicle's steering angle based on the offset. Otherwise, no turning is performed and the vehicle travels in a straight line at a constant speed. Determine whether the vehicle speed needs to be adjusted based on the current road condition and the current digital value of the vehicle speed. If so, adjust the motor speed. Otherwise, do not adjust it.

[0059] In this embodiment, based on the determination of the current road conditions, the distance sensor detects that there are obstacles in front of the vehicle, in front of the left or in front of the right, etc., and calculates the offset through the PID algorithm, and transmits the calculated offset to the vehicle steering system. The EPS coupling mechanism of the vehicle steering system will control the adjustment of the vehicle's turning angle and direction according to the received instructions (including the offset value data), so as to realize the automatic steering function based on the real-time road conditions. If there are no other obstacles that hinder the vehicle's travel around the external detection, the vehicle will maintain the current speed and drive in a straight line through the main controller instruction. The offset is calculated according to the distance between the vehicle and each position of the obstacle using the existing calculation method.

[0060] Furthermore, on the basis of the existing automatic assisted driving system, the setting of ESC angular displacement sensor and EPS coupling mechanism is added, and the ESC angular displacement sensor and EPS optical system coupling mechanism are used to connect with the vehicle controller NI myRIO in real time, and the self-adjusting steering of the steering wheel is accurately positioned and controlled according to the road conditions around the vehicle to achieve the purpose of steering driving. In other words, the steering adjustment of the vehicle is controlled by combining the current road conditions with the vehicle steering system. Specifically, the ESC angular displacement sensor detects the steering angle of the steering wheel and is generally installed below the steering column combination switch under the steering wheel. The vehicle controller NI myRIO adjusts the steering of the vehicle through the feedback of the detected steering wheel steering angle.

[0061] Furthermore, when the vehicle is adjusting its direction, the road conditions are fed back through the rear radar camera to identify and judge the steering system so that it can be integrated with the vehicle speed.

[0062] In this embodiment, the NI myRIO controller presets different vehicle speeds for different road conditions when it is initialized. After determining the current road condition, the NI myRIO controller sends a control instruction to the motor according to the vehicle speed corresponding to the road condition, so that the vehicle reaches the preset speed and realizes stepless speed regulation. Stepless speed regulation is to control and adjust the vehicle speed accurately through the internal encoder of the motor controller. The vehicle speed is different under different road conditions. The program can be compiled and integrated to judge various road conditions according to the actual situation, so as to control the speed of the whole vehicle.

[0063] For example, if the current road condition is determined to be a straight road (MXP_straight road) through the acquired data recognition, when the NImyRIO controller determines that the road condition is a straight road (MXP_straight road) and the steering wheel angle is 0 degrees, the pre-set vehicle speed is less than 69 km / h, and the vehicle goes straight.

[0064] Embodiment 2

[0065] This embodiment discloses an intelligent passenger car road condition automatic identification control system, including:

[0066] A system initialization module, which is configured to: initialize the main controller and the auxiliary controller, and pre-set the digital quantity range and vehicle speed corresponding to different road conditions;

[0067] The data acquisition module is configured as follows: the main controller and the auxiliary controller acquire the vehicle environment image, the current vehicle speed and the obstacle distance in the current driving environment, and convert the acquired data into corresponding digital quantities to obtain the vehicle environment image digital quantity, the current vehicle speed digital quantity and the obstacle distance digital quantity;

[0068] The road condition recognition module is configured as follows: the main controller performs a primary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance to judge the current first road condition; the auxiliary controller performs a secondary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance to judge the current second road condition; judges whether the second road condition is consistent with the first road condition, if so, determines the current road condition, if not, re-acquires data for judgment;

[0069] The adaptive adjustment module is configured as follows: based on the current road condition and the digital quantity of the obstacle distance, determine whether turning is required; if so, calculate the offset; adjust the vehicle direction angle based on the offset; otherwise, do not turn and the vehicle travels in a straight line at a constant speed; based on the current road condition and the digital quantity of the current vehicle speed, determine whether the vehicle speed needs to be adjusted; if so, adjust the motor speed; otherwise, do not adjust.

[0070] Embodiment 3

[0071] The purpose of this embodiment is to provide a computing device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the method of embodiment 1 when executing the program.

[0072] Embodiment 4

[0073] The purpose of this embodiment is to provide a computer-readable storage medium, a computer-readable storage medium having a computer program stored thereon, and when the program is executed by a processor, the steps of the method of embodiment 1 are performed.

[0074] The steps involved in the apparatus of the above embodiments 3 and 4 correspond to the method embodiment 1, and the specific implementation method can refer to the relevant description part of embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood to include any medium that can store, encode or carry an instruction set for execution by a processor and enable the processor to execute any method of the present invention.

[0075] Those skilled in the art should understand that the modules or steps of the present invention described above can be implemented by a general-purpose computer device, or alternatively, they can be implemented by a program code executable by a computing device, so that they can be stored in a storage device and executed by the computing device, or they can be made into individual integrated circuit modules, or multiple modules or steps therein can be made into a single integrated circuit module for implementation. The present invention is not limited to any specific combination of hardware and software.

[0076] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0077] Although the above describes the specific implementation mode of the present invention in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art on the basis of the technical solution of the present invention without creative work are still within the scope of protection of the present invention.

Claims

1. An intelligent bus road condition automatic recognition control method, characterized in that: include: Initialize the main controller and the auxiliary controller, and pre-set the digital range and vehicle speed corresponding to different road conditions; The main controller and the auxiliary controller obtain the vehicle environment image, the current vehicle speed and the obstacle distance in the current driving environment, and convert the obtained data into corresponding digital quantities to obtain the digital quantity of the vehicle environment image, the digital quantity of the current vehicle speed and the digital quantity of the obstacle distance; The main controller performs a primary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance, and judges the current first road condition; the auxiliary controller performs a secondary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance, and judges the current second road condition; judges whether the second road condition is consistent with the first road condition, and if so, determines the current road condition, and if not, re-acquires data for judgment; Based on the current road condition and the digital quantity of the obstacle distance, determine whether turning is required. If so, calculate the offset and adjust the vehicle's steering angle based on the offset. Otherwise, no turning is performed and the vehicle travels in a straight line at a constant speed. Based on the current road condition and the current digital quantity of the vehicle speed, determine whether the vehicle speed needs to be adjusted. If so, adjust the motor speed. Otherwise, do not adjust it.

2. The method for automatically identifying and controlling intelligent passenger vehicle road conditions according to claim 1, characterized in that: The main controller is a NImyRIO controller, and the auxiliary controller is an STM32 controller.

3. The method for automatically identifying and controlling intelligent passenger vehicle road conditions as claimed in claim 2, characterized in that: The NImyRIO controller integrates automatic assisted driving and manual driving modes, is controlled by two different programs, and is controlled in series through rocker switches and voice recognition.

4. The method for automatically identifying and controlling intelligent passenger vehicle road conditions as claimed in claim 2, characterized in that: The NImyRIO controller is also connected to a clock circuit and a watchdog circuit.

5. The method for automatically identifying and controlling intelligent passenger vehicle road conditions according to claim 1, characterized in that: The camera, speed sensor and distance sensor are used to obtain vehicle environment images, current vehicle speed and obstacle distance data to identify and judge road conditions.

6. The method for automatically identifying and controlling road conditions of an intelligent bus as claimed in claim 5, characterized in that: The interfaces of the camera and the distance sensor are connected point-to-point with the interface of the NI myRIO controller.

7. The method for automatically identifying and controlling intelligent passenger vehicle road conditions as claimed in claim 1, characterized in that: The road condition recognition and judgment is specifically carried out by comparing the digital quantities converted from the vehicle environment image and obstacle distance obtained in the current driving environment with the digital quantity ranges corresponding to the preset different road conditions. The road condition corresponding to the digital quantity range that the current digital quantity meets is the current first road condition or the current second road condition.

8. An intelligent passenger car road condition automatic identification control system, characterized in that: include: A system initialization module, which is configured to: initialize the main controller and the auxiliary controller, and pre-set the digital quantity range and vehicle speed corresponding to different road conditions; The data acquisition module is configured as follows: the main controller and the auxiliary controller acquire the vehicle environment image, the current vehicle speed and the obstacle distance in the current driving environment, and convert the acquired data into corresponding digital quantities to obtain the vehicle environment image digital quantity, the current vehicle speed digital quantity and the obstacle distance digital quantity; The road condition recognition module is configured as follows: the main controller performs a primary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance to judge the current first road condition; the auxiliary controller performs a secondary road condition recognition and judgment based on the digital quantity of the vehicle environment image and the digital quantity of the obstacle distance to judge the current second road condition; judges whether the second road condition is consistent with the first road condition, if so, determines the current road condition, if not, re-acquires data for judgment; The adaptive adjustment module is configured as follows: based on the current road condition and the digital quantity of the obstacle distance, determine whether turning is required; if so, calculate the offset; adjust the vehicle direction angle based on the offset; otherwise, do not turn and the vehicle travels in a straight line at a constant speed; based on the current road condition and the digital quantity of the current vehicle speed, determine whether the vehicle speed needs to be adjusted; if so, adjust the motor speed; otherwise, do not adjust.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the intelligent passenger car road condition automatic identification and control method as described in any one of claims 1-7 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the intelligent passenger car road condition automatic identification and control method as described in any one of claims 1-7 are implemented.

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