Intelligent passenger car road condition automatic identification control method and system

Abstract

The application discloses a kind of intelligent passenger car road condition automatic identification control method and system, and primary road condition identification judgment is carried out based on vehicle environment image digital quantity and obstacle distance digital quantity by main controller, to judge current first road condition;Second road condition identification judgment is carried out based on vehicle environment image digital quantity and obstacle distance digital quantity by auxiliary controller, to judge current second road condition;Second road condition and first road condition are judged whether consistent, if yes, determine current road condition, if not, then reacquire data and judge;Whether need to turn based on current road condition and obstacle distance digital quantity, if yes, then calculate offset, adjust the direction angle of whole vehicle based on offset, if not, then do not turn, vehicle uniform speed straight line travels;Whether need to adjust speed based on current road condition and current speed digital quantity, if yes, then adjust motor speed, if not, do not adjust.It realizes the road condition automatic identification control of whole vehicle driving, avoids the unpredictable failure that driver produces due to insufficient concentration.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of automobile research and development design and manufacturing, and particularly relates to an intelligent bus automatic road condition recognition control method and system. BACKGROUND

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

[0003] With the entry of the bus industry into a key stage of high-speed development and transformation, new vehicle models pay more attention to intelligentization, informatization, and safety. For inexperienced drivers, the operation of buses in complex working conditions and road conditions is a test, and the safety of vehicles and passengers during driving cannot be guaranteed 100%. The intelligent auxiliary driving system is a new breakthrough in the recognition of various road conditions such as potholes, mountain roads, steep slopes, and pedestrians. In the case of ensuring the safe operation of the whole vehicle, precise recognition of different road conditions, different angles, and different directions is a major project. Research data shows that the probability of accidents of buses in harsh road conditions is gradually increasing every year. With the development of science and technology, the performance of vehicle parts is constantly improving, but some manufacturers use parts with quality problems to reduce costs. In this case, the problem of preventing the failure of the whole vehicle needs to be addressed.

[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, but this is a great test for drivers who have been driving for a long time and are prone to fatigue, which can lead to inattention and failure to observe changes in road conditions in a timely manner, and thus fail to respond in a timely manner, which can result in serious traffic accidents. SUMMARY

[0005] To overcome the deficiencies of the prior art, the present application provides an intelligent bus automatic road condition recognition control method and system, which innovatively solves the automatic auxiliary driving of the whole vehicle under different road conditions, and the speed of the intelligent bus can be infinitely adjusted according to different road conditions.

[0006] To achieve the above-mentioned purpose, one or more embodiments of the present application provide the following technical solutions:

[0007] In a first aspect, the present application provides an intelligent bus automatic road condition recognition control method, comprising:

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

[0009] The main controller and the auxiliary controller acquire the vehicle environment image, the current vehicle speed and the obstacle distance under 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.

[0010] The main controller performs primary road condition identification and judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity to determine the current first road condition, and the auxiliary controller performs secondary road condition identification and judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity to determine the current second road condition, and whether the second road condition is consistent with the first road condition is determined, if yes, the current road condition is determined, and if no, the data is re-acquired for judgment.

[0011] Whether the vehicle needs to turn based on the current road condition and the obstacle distance digital quantity is determined, if yes, the offset is calculated, the whole vehicle direction angle is adjusted based on the offset, if no, the vehicle is uniformly and linearly driven, and whether the vehicle speed needs to be adjusted based on the current road condition and the current vehicle speed digital quantity is determined, if yes, the motor speed is adjusted, and if no, the adjustment is not performed.

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

[0013] Further technical features, the NI myRIO controller is integrated with automatic auxiliary driving and manual driving modes, which are controlled by two different programs and are controlled in series through a rocker switch and voice recognition.

[0014] Further technical features, the NI myRIO controller is further connected with a clock circuit and a watchdog circuit.

[0015] Further technical features, the vehicle environment image, the current vehicle speed and the obstacle distance data are acquired through a camera, a vehicle speed sensor and a distance sensor to perform road condition identification and judgment.

[0016] Further technical features, the interface of the camera and the distance sensor is connected with the interface of the NI myRIO controller in point-to-point hard line connection.

[0017] Further technical features, the road condition identification and judgment specifically comprises comparing the digital quantity converted from the acquired vehicle environment image and the obstacle distance under the current driving environment with the digital quantity range corresponding to different road conditions, and the road condition corresponding to the digital quantity range to which the current digital quantity conforms is the current first road condition or the current second road condition.

[0018] In a second aspect, the application provides an intelligent bus road condition automatic identification control system, comprising:

[0019] The system initialization module is configured to initialize the main controller and the auxiliary controller, and preset the digital quantity range corresponding to different road conditions and the vehicle speed.

[0020] The data acquisition module is configured to acquire the vehicle environment image, the current vehicle speed and the obstacle distance under the current driving environment by the main controller and the auxiliary controller, 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 identification module is configured to perform primary road condition identification and judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity by the main controller to determine the current first road condition, and perform secondary road condition identification and judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity by the auxiliary controller to determine the current second road condition, and determine whether the second road condition is consistent with the first road condition, and if yes, determine the current road condition, and if not, re-acquire data for judgment.

[0022] The adaptive adjustment module is configured to determine whether steering is needed based on the current road condition and the obstacle distance digital quantity, and if yes, calculate the offset, and adjust the whole vehicle direction angle based on the offset, and if not, do not perform steering, and the vehicle travels at a constant speed in a straight line, and determine whether the vehicle speed needs to be adjusted based on the current road condition and the current vehicle speed digital quantity, and if yes, adjust the motor speed, and if not, do not perform adjustment.

[0023] In a third aspect, the present application provides a computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the steps of the intelligent bus road condition automatic identification control method according to the first aspect.

[0024] In a fourth aspect, the present application provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the intelligent bus road condition automatic identification control method according to the first aspect when executing the program.

[0025] The above one or more technical solutions have the following beneficial effects:

[0026] The present application innovatively solves the automatic auxiliary driving of the whole vehicle under different road conditions such as straight roads, curved roads, slopes, steep roads, pedestrians and red traffic lights, the speed of the intelligent bus can be infinitely adjusted according to different road conditions, the innovative application of the NI myRIO controller is developed, and the needs of unmanned driving under any working condition are met, and the traditional shackles of the bus industry are broken.

[0027] The application realizes automatic road condition identification control of intelligent driving of the whole vehicle, avoids unpredictable errors caused by insufficient concentration of the driver, and improves the safety performance and service life of the whole vehicle, improves the comfort and intelligent driving experience of passengers, and protects the personal and property safety of the driver and passengers.

[0028] The application also sets an STM32 controller as an auxiliary controller, and the auxiliary controller performs secondary judgment on the current road condition, so that the main controller is prevented from identifying errors and accurate identification is achieved.

[0029] The application adopts the NI myRIO controller, reduces the laying of the whole vehicle wire harness, improves the response time of the control system, and sets the functions of the NI myRIO control system through CAN network communication connection, so that the work efficiency of research and development design is improved and the manufacturing cost of the intelligent bus is reduced. DETAILED DESCRIPTION

[0030] The accompanying drawings, which form a part of this specification, are included to provide a further understanding of the application and are incorporated herein by reference. The detailed description and the specific examples, which follow, are intended to explain the application in detail.

[0031] Figure 1 is a flow chart of the intelligent bus road condition automatic identification control method of the embodiment of the application;

[0032] Figure 2 is an intelligent bus road condition automatic identification control system architecture diagram of the embodiment of the application. DETAILED DESCRIPTION

[0033] It should be noted that the following detailed description is exemplary in nature and is intended to provide further description of the application. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

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

[0035] The embodiments in the application and the features in the embodiments can be combined with each other without conflict.

[0036] Embodiment one

[0037] As shown in Figure 1 , 2 , the embodiment discloses a kind of intelligent bus road condition automatic identification control method, which comprises the following steps:

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

[0039] In the embodiment, the main controller is NI myRIO controller, uses NI myRIO control circuit, its XiLinx Zynq chip is embedded, with different degrees of intelligentization (memory, perception, identification, calculation, reasoning, learning). NI myRIO controller integrates automatic auxiliary driving and manual driving mode, is controlled by two different programs, is controlled in series by two ways of rocker switch and voice recognition, to ensure the safety and misjudgment in the process of automatic driving of whole vehicle.

[0040] Further, NI myRIO controller is also connected with clock circuit and watchdog circuit, clock signal and watchdog are used to ensure that whole vehicle responds quickly, clock signal improves the response efficiency, time of entire control system, and the size of intelligent bus speed is controlled by response time;Watchdog prevents program from flying or entering dead cycle due to external signal interference, to ensure stable operation of program.

[0041] Auxiliary controller is STM32 controller, is connected with the I / 0 port of NI myRIO controller, and is connected to automatic auxiliary driving system through pin GPIO_SCL and GPIO_SDA.It needs to be explained that the automatic auxiliary driving system in the embodiment is existing system, and the structure and working principle of the system will not be described here.

[0042] The digital quantity range corresponding to a variety of road conditions is set by program programming, i.e. the digital quantity range converted by image collected by camera and distance data collected by distance sensor corresponding to 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) and other road conditions.

[0043] The speed signal MOTOR_speed_ is controlled by program IF statement corresponding to different road conditions.

[0044] In some embodiments, the NI myRIO controller supports electrical signals and CAN communication, and the input signals are recognized and judged by programming through LabVIEW 2023 software. Different function instructions are designed and analyzed through the program, and the recognized road condition signals are output and processed through serial communication.

[0045] S2: 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;

[0046] In the embodiment, the data is acquired by the camera, the distance sensor, the steering wheel angle sensor and the vehicle speed sensor. Preferably, the 8-way camera and the 24-way distance sensor are used to collect the environment data without dead angle, error and delay in the front, left front, right front, left side and right side of the passenger car in all directions of 360 degrees. The number of devices can be selected according to the actual situation, and is not specifically limited.

[0047] The vehicle environment image refers to the road image of the front, left front, right front, left side and right side of the passenger car collected by the 8-way camera, and the road image can represent the corresponding road condition. The obstacle distance refers to the distance between the front, left front, right front, left side, right side and rear of the passenger car and the obstacle collected by the 24-way distance sensor.

[0048] The different conversion of analog quantity and digital quantity achieves accurate judgment of the whole system. In the conversion process, the A / D converter is used to sample and quantize the analog signals collected by the camera and the distance sensor, and convert them into digital signals. The quantized numerical value is represented by binary code. 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 the distance sensor.

[0049] The camera, distance sensor interface DCMI and NI myRIO controller interface MXP_A are connected by point-to-point hardwire. That is, the 8-way camera and 24-way sensor are detected externally, and the detection signal is transmitted to the NI myRIO signal input interface MXP_A through the DCMI interface. The external road conditions are converted into analog and digital signals 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 other (MXP_other) are programmed through the Switch statement, and the vehicle speed is adjusted according to the program execution command. The NI myRIO controller will identify and judge the road conditions according to the real-time data collected.

[0050] S3: The main controller performs initial road condition identification and judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity, and judges the current first road condition. The auxiliary controller performs secondary road condition identification and judgment based on the vehicle environment image digital quantity and the obstacle distance digital quantity, and judges the current second road condition. Whether the second road condition is consistent with the first road condition is judged, if yes, the current road condition is determined, if not, the data is reacquired for judgment.

[0051] In this embodiment, the auxiliary controller performs secondary judgment on the current road condition, and the auxiliary controller performs re-identification and judgment on the road condition, which prevents the main controller from making mistakes and achieves accurate identification.

[0052] The NI myRIO controller and the STM32 controller are used to analyze and calculate the data collected by the data acquisition module. The methods of road condition identification and judgment are the same, that is, the digital quantity converted from the vehicle environment image and the obstacle distance in the current driving environment is compared with the 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 identified and judged.

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

[0054] Further, the display terminal writes the data interacted by the liquid crystal display screen and the NI myRIO controller through the application of LabVIEW software in the interface of the program block diagram, directly calls the program block diagram, and the program automatically identifies and judges the images under different working conditions, converts the read analog quantity into digital quantity and displays it on the liquid crystal display screen interface. That is, the NI myRIO controller converts the read analog quantity into digital quantity and sends it to the display terminal for display, and the display terminal is separately provided with a subprogram and a NI myRIO controller main program for communication connection.

[0055] After the main controller and the auxiliary controller determine the current road condition (different road conditions, i.e. straight road, curve, hill, steep road, traffic light, pedestrian, etc.), the vehicle can quickly respond to different road conditions, such as identifying that the current driving environment is a red light condition, the main controller controls the motor to stop, realizing parking, and identifying that the current driving environment is a green light condition, the main controller controls the motor to start, realizing driving.

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

[0057] Further, to prevent the vehicle speed failure, the program of the motor encoder is connected with the NI myRIO controller, and a certain condition is preset for the vehicle speed, i.e. under the condition of meeting the corresponding road condition, the speed of the motor is converted, stopped, etc. That is, under the condition of obstacles, the vehicle speed will not execute the current vehicle speed, and the speed of the motor will make the vehicle speed decrease to the risk value of the vehicle speed failure.

[0058] S4: judging whether steering is needed based on the current road condition and the distance between the vehicle and the obstacle, if yes, calculating the offset, adjusting the steering angle of the vehicle based on the offset, if no, the vehicle travels straight at a constant speed; judging whether the vehicle speed needs to be adjusted based on the current road condition and the current vehicle speed, if yes, adjusting the motor speed, if no, no adjustment is made.

[0059] In the present embodiment, based on the determination of the current road condition, the offset is calculated by the PID algorithm according to the detection of the distance sensor that there is an obstacle in front, left front or right front of the vehicle, and the calculated offset is transmitted to the vehicle steering system. The EPS coupling mechanism will control the adjustment of the steering angle and direction of the vehicle according to the received instructions (including offset value data), so as to realize the automatic steering function based on real-time road conditions. If there is no other obstacle that hinders the vehicle from driving around the vehicle, the vehicle will keep the current speed and travel straight through the main controller instructions. The offset is calculated according to the distance between the vehicle and the obstacle at each position by using the existing calculation method.

[0060] Further, based on the existing automatic auxiliary driving system, the ESC angular displacement sensor and the EPS coupling mechanism are added, and the ESC angular displacement sensor and the EPS optical system coupling mechanism are connected to the vehicle controller NI myRIO in real time to precisely position the steering wheel and adjust the steering direction, so as to achieve the purpose of steering driving. That is, the steering adjustment of the vehicle is controlled by the determined current road condition and the vehicle steering system. Specifically, the ESC angular displacement sensor detects the steering angle of the steering wheel, which is generally installed below the steering column combination switch of the steering wheel, and the vehicle controller NI myRIO adjusts the steering of the vehicle through the feedback of the detected steering angle of the steering wheel.

[0061] Further, when the vehicle adjusts the direction, the rear radar camera feeds back the road condition for identification and judgment, so that the steering system reaches the speed integration.

[0062] In the present embodiment, the NI myRIO controller initializes different vehicle speeds for different road conditions, and after determining the current road condition, the NI myRIO controller sends control instructions to the motor according to the corresponding vehicle speed of the road condition, so that the vehicle reaches the preset speed and realizes stepless speed regulation. Stepless speed regulation is the precise speed control and adjustment through the internal encoder of the motor controller. The vehicle speed is different under different road conditions, and the vehicle speed can be controlled according to the actual situation by programming and integrating the judgment of various road conditions.

[0063] If the current road condition is a straight road (MXP_straight road) as identified by the acquired data, 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 vehicle travels straight at a pre-set speed of less than 69 km / h.

[0064] Embodiment Two

[0065] The embodiment discloses an intelligent bus road condition automatic identification control system, comprising:

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

[0067] A data acquisition module configured to acquire the vehicle environment image, the current vehicle speed and the obstacle distance under the current driving environment by the main controller and the auxiliary controller, 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] A road condition identification module configured to make a first road condition identification judgment by the main controller based on the vehicle environment image digital quantity and the obstacle distance digital quantity, and determine the current first road condition; make a second road condition identification judgment by the auxiliary controller based on the vehicle environment image digital quantity and the obstacle distance digital quantity, and determine the current second road condition; and determine whether the second road condition is consistent with the first road condition, if yes, determine the current road condition, if not, re-acquire data for judgment.

[0069] An adaptive adjustment module configured to determine whether steering is needed based on the current road condition and the obstacle distance digital quantity, if yes, calculate the offset, adjust the whole vehicle direction angle based on the offset, if not, do not steer, and the vehicle travels at a constant speed in a straight line; determine whether the vehicle speed needs to be adjusted based on the current road condition and the current vehicle speed digital quantity, if yes, adjust the motor speed, if not, do not adjust.

[0070] Embodiment Three

[0071] The embodiment aims to provide a computing device, comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to realize the steps of the method of embodiment one.

[0072] Embodiment Four

[0073] The embodiment aims to provide a computer-readable storage medium, a computer-readable storage medium having a computer program stored thereon, wherein the program is executed by a processor to execute the steps of the method of embodiment one.

[0074] The steps and methods involved in the apparatuses of Embodiments 3 and 4 above correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section 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 as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0075] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0076] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

[0077] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this 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 without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A smart bus road condition automatic identification control method, characterized in that, The application relates to an automatic auxiliary driving system. The main controller and the auxiliary controller are initialized, and the digital quantity ranges corresponding to different road conditions and vehicle speeds are preset; The main controller and the auxiliary controller acquire vehicle environment images, current vehicle speeds and obstacle distances under current driving environments, and convert the acquired data into corresponding digital quantities to obtain vehicle environment image digital quantities, current vehicle speed digital quantities and obstacle distance digital quantities; The main controller performs primary road condition identification and judgment based on the vehicle environment image digital quantities and the obstacle distance digital quantities, and judges a current first road condition; the auxiliary controller performs secondary road condition identification and judgment based on the vehicle environment image digital quantities and the obstacle distance digital quantities, and judges a current second road condition; whether the second road condition is consistent with the first road condition is judged, if yes, the current road condition is determined, and if not, data is reacquired for judgment; Whether steering is needed is judged based on the current road condition and the obstacle distance digital quantity, if yes, a deviation is calculated, the whole vehicle direction angle is adjusted based on the deviation, if not, steering is not performed, and the vehicle travels at a constant speed in a straight line; whether the vehicle speed needs to be adjusted is judged based on the current road condition and the current vehicle speed digital quantity, if yes, the motor speed is adjusted, and if not, adjustment is not performed.

2. The intelligent passenger car road condition automatic identification control method of claim 1, wherein, The main controller is an NImyRIO controller, and the auxiliary controller is an STM32 controller.

3. The intelligent passenger car road condition automatic identification control method of claim 2, wherein, The NImyRIO controller is integrated with automatic auxiliary driving and manual driving modes, is controlled by two different programs, and is controlled in series through a rocker switch and voice recognition.

4. The intelligent passenger car road condition automatic identification control method of claim 2, wherein, The NImyRIO controller is also connected with a clock circuit and a watchdog circuit.

5. The intelligent passenger car road condition automatic identification control method of claim 1, wherein, Vehicle environment images, current vehicle speeds and obstacle distance data are acquired through a camera, a vehicle speed sensor and a distance sensor for road condition identification and judgment.

6. The intelligent passenger car road condition automatic identification control method of claim 5, wherein, The interfaces of the camera and the distance sensor are connected with the interfaces of the NImyRIO controller in point-to-point hard line connection.

7. The intelligent passenger car road condition automatic identification control method of claim 1, wherein, The road condition identification and judgment specifically comprises comparing the digital quantities converted from the acquired vehicle environment images and obstacle distances under current driving environments with preset digital quantity ranges corresponding to different road conditions, and the road condition corresponding to the digital quantity range to which the current digital quantity conforms is the current first road condition or the current second road condition.

8. An intelligent bus road condition automatic identification control system, characterized in that, The application relates to an automatic auxiliary driving system. The system initialization module is configured to initialize the main controller and the auxiliary controller, and preset digital quantity ranges corresponding to different road conditions and vehicle speeds; The data acquisition module is configured to acquire vehicle environment images, current vehicle speeds and obstacle distances under current driving environments by the main controller and the auxiliary controller, and convert the acquired data into corresponding digital quantities to obtain vehicle environment image digital quantities, current vehicle speed digital quantities and obstacle distance digital quantities; The road condition identification module is configured to perform primary road condition identification and judgment by the main controller based on the vehicle environment image digital quantities and the obstacle distance digital quantities, and judge a current first road condition; secondary road condition identification and judgment are performed by the auxiliary controller based on the vehicle environment image digital quantities and the obstacle distance digital quantities, and a current second road condition is judged; whether the second road condition is consistent with the first road condition is judged, if yes, the current road condition is determined, and if not, data is reacquired for judgment; An adaptive adjustment module is configured to: judge whether steering is needed based on the current road condition and the obstacle distance digital quantity, calculate the offset if yes, adjust the whole vehicle direction turning angle based on the offset, and not perform steering if no, the vehicle travels in a straight line at a constant speed; judge whether the vehicle speed needs to be adjusted based on the current road condition and the current vehicle speed digital quantity, adjust the motor speed if yes, and not perform adjustment if no.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps in the intelligent passenger car road condition automatic identification control method of any one of claims 1-7.

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

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