Intelligent road inspection system and business model

Abstract

The application provides a smart road inspection system and a business model, and relates to the field of intelligent transportation, which comprises a vehicle chassis and a vehicle body, a central controller, a communication module, an image capture, a video recording and remote transmission module, a voice and video intercom module, a mobile speed measurement device, an emergency rescue kit, a battery power management module, an intelligent road condition prediction and adaptive driving module; the application realizes accurate perception of road conditions, efficient integration and utilization of information, diversified inspection functions and reasonable energy management by integrating multiple layers of road condition detection functions, simultaneously gives the vehicle driving on the highway invisible pressure, makes it self-restraint to abide by traffic rules, and reduces the accident rate; when a traffic accident occurs, traffic control can be performed to avoid the occurrence of traffic accidents caused by the stacking of subsequent vehicles; the traffic accident scene is photographed or videoed to keep evidence, which helps to quickly restore normal driving of the accident section, and improves the efficiency and quality of inspection.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, and in particular to an intelligent road inspection system and its business model. Background Technology

[0002] With the continuous advancement of technology, the field of intelligent transportation has made significant progress. In terms of highway management, the initial manual inspection has gradually shifted to automated and intelligent inspection methods. Early inspections mainly relied on manual patrol vehicles and personnel. This method was not only inefficient but also easily affected by human factors, such as fatigue and lack of concentration of inspection personnel, which may lead to some road safety hazards not being detected in time. Existing inspection systems have limited adaptability to complex road conditions. Road conditions are complex and changeable, such as potholes, water accumulation, and icy surfaces. Some inspection systems cannot detect these changes in a timely and accurate manner, thus failing to take corresponding measures in advance, affecting inspection efficiency, and potentially even endangering the inspection vehicles themselves. Although some systems can collect various types of data, they have deficiencies in information integration and utilization. Different types of data (such as road surface data, vehicle driving data, and traffic incident data) are often scattered across various modules, lacking effective integration and analysis mechanisms. This prevents the system from fully exploring the value of the data and making it difficult to make accurate decisions based on comprehensive information. For example, in handling traffic accidents, it is impossible to quickly integrate on-site information for accident liability determination and loss assessment. Furthermore, many inspection systems have relatively simple functions, mainly focusing on basic functions such as vehicle speed measurement and license plate capture; they lack the ability to handle other problems that may occur on highways, such as fires and vehicle breakdowns, and lack corresponding rescue equipment and emergency measures, making it impossible to provide effective assistance in the first instance. Therefore, there is an urgent need in this field for an intelligent road inspection system to solve the above problems. Summary of the Invention

[0003] This invention provides an intelligent road inspection system and business model, aiming to solve the problems existing in the above-mentioned prior art. By integrating multi-layer road condition detection functions, it achieves accurate perception of road conditions, efficient integration and utilization of information, diversified inspection functions, and reasonable energy management, thereby improving the efficiency and quality of inspection.

[0004] On one hand, the present invention provides an intelligent road inspection system, comprising: The vehicle chassis and body are equipped with an autonomous driving module for unmanned driving, and the body is equipped with a mobile signal light device. The central controller, as the control hub of the entire system, is used for information integration and regulation; The communication module, based on Internet technology, enables wireless information interaction between the central controller and remote terminals, as well as local network operation. The image capture, video recording, and remote transmission module connects to the central controller. The central controller controls the module to capture license plates, photograph and record images at traffic accident scenes, and remotely transmit the data to the traffic command center and the local network operation and accident scene image / video storage environment via a communication module. It also analyzes and processes the captured vehicle images, extracting license plate numbers and vehicle model characteristics. The identification results are compared with a vehicle database to obtain relevant vehicle information, which is then transmitted to the central controller along with the captured images and video data. Furthermore, it analyzes images of accident scenes or surrounding roads, identifying the facial features and clothing characteristics of pedestrians and drivers, as well as scattered objects on the road. The identification results are transmitted to the central controller, providing more detailed information for accident handling or safety monitoring. The voice and video intercom module is connected to the central controller and communicates with the traffic command center remotely via the communication module. It is used for on-site remote accident liability determination and damage assessment of traffic accidents, as well as local network operation and working environment storage. The mobile speed measuring device is connected to the central controller, which controls it to perform high-speed speed measurement and triggers the image capture, video recording and remote transmission modules to capture speeding vehicles and upload information, as well as the local network operation and storage of the speeding vehicle capture environment. An emergency rescue kit should include at least small demolition equipment, a fire extinguisher, a fire blanket, a gas mask, gauze bandages, and hemostatic agents. The battery power management module includes a battery pack, a charging unit, a charging and discharging chip, and a power detection chip. The charging unit includes a solar charging sub-unit and a wired charging sub-unit. The power detection chip includes a CPU, a voltage monitoring device, a current monitoring device, a battery status detection device, and a bus communication device. The intelligent road condition prediction and adaptive driving module collects real-time road information, including road surface smoothness, water depth, and road friction data, through high-precision sensors installed in multiple locations on the chassis and body. It processes the collected data using an optimization analysis model to predict potential road condition changes ahead and adjust driving parameters in advance. This module connects to the central controller, transmitting road condition information and adjustment suggestions to it. The central controller coordinates the work of each module and also handles local storage and processing. It is also equipped with sensors to detect whether other vehicles are on sidewalks or emergency lanes. Based on image recognition algorithms for specific areas, it analyzes the data. Once it detects that another vehicle has entered a prohibited sidewalk or emergency lane, it immediately transmits the information to the central controller. The central controller triggers an alarm and sends violation information to the traffic control center via a communication module.

[0005] According to the present invention, an intelligent road inspection system is provided, wherein the automatic driving module includes: The drive unit is used to control the vehicle's speed and direction. It includes an ECU, which controls the vehicle. The drive unit is equipped with at least two drive wheels located on both sides of the chassis and drive motors that are the same number as the drive wheels and are connected to each drive wheel. A control signal receiving device and a control signal input device are also connected to one side of the drive motor. The path navigation unit includes a memory, input / output ports and a processor. The processor includes a navigation information acquisition module, which is used to acquire navigation pattern information and plan the driving path of the non-motorized vehicle lane. The automatic navigation control unit is used to control the vehicle's driving parameters based on navigation pattern information; The obstacle avoidance unit includes a traffic sign recognition subunit and an obstacle recognition subunit; The traffic sign recognition subunit includes a video recognition device for capturing images of the road ahead of the vehicle, identifying the presence of traffic lights and traffic markings, and recognizing the status of traffic lights. Simultaneously, it calculates the real-time spatial distance between the vehicle and the traffic markings based on the pixel values ​​of the traffic markings in the video image, and sends the continuously decreasing spatial distance values ​​to the next level. It also has a lane recognition function, which, through feature extraction and analysis of lane lines in the video image, combined with the vehicle's position and driving direction information, accurately identifies the current driving lane and transmits the lane information to the data processing unit. The data processing unit adjusts the vehicle's driving position based on the lane information to ensure that the vehicle travels within the designated lane and not on the sidewalk or emergency lane. The obstacle recognition subunit includes a detection device for detecting the distance to obstacles, a road obstacle information storage device for storing the location and distance properties of the detected road obstacles, and an obstacle avoidance calculation code storage device for storing obstacle avoidance calculation codes. A comparator replaces the control signal input device in instructing the vehicle to move away from obstacles by comparing the stored road obstacle information with the stored obstacle avoidance calculation code. The detection device comprises at least one transmitting and receiving device disposed around the perimeter of the electric vehicle body. The transmitting device includes an ultrasonic transmitting element and a trigger circuit, and the receiving device includes an ultrasonic receiving element and a front-end amplification circuit. The data processing unit is used to calculate the data transmitted back from the path navigation unit, obstacle avoidance unit and communication module, draw conclusions and control driving through the drive unit. The data processing unit is also connected to the cloud computing system to send the vehicle driving status to the cloud computing system. The cloud computing system can send back commands to the data processing unit and control the vehicle through the ECU connected to the data processing unit. The communication module is used to communicate with the cloud computing system and to provide feedback on its own operating data and functional data.

[0006] According to the present invention, an intelligent road inspection system is provided, wherein the image capture, video recording, and remote transmission module adopts a high-speed HD camera, and is configured with at least two sets located at the front and rear of the vehicle. The high-speed HD camera has night vision function and is equipped with at least 1TB of ultra-large storage device, and stores the data using a local loop recording method. At the same time, cameras are added on both sides and the top of the vehicle, forming a multi-camera system with the front and rear cameras. Through image stitching and fusion technology, panoramic monitoring and recognition of multiple lanes are achieved. Each camera is responsible for image acquisition of a specific area, and the data processing unit integrates and analyzes the data from each camera to ensure comprehensive and accurate monitoring of vehicles and road conditions on multiple lanes. The communication module uses 5G network communication, satellite communication and other network communication methods to connect to traffic command centers in various places in real time.

[0007] According to the intelligent road inspection system provided by the present invention, the emergency rescue kit is also equipped with an emergency alarm device; the emergency alarm device includes an alarm and a main controller installed on the vehicle body; the alarm includes a control circuit, a voice circuit and a light-emitting circuit. After the alarm is powered on, the main controller automatically reads the voice address set by the digital disk. When the main controller receives the input signal from the dot, contact, overhead line or infrared probe, it automatically controls the voice circuit to emit an alarm sound and simultaneously controls the light-emitting circuit to emit a flashing red signal.

[0008] According to the present invention, a smart road inspection system includes a solar charging subunit comprising a retractable solar charging panel disposed on the periphery and upper surface of the vehicle body; the wired charging subunit charges the battery pack via a generator.

[0009] According to the present invention, an intelligent road inspection system is provided, wherein the intelligent road condition prediction and adaptive driving module includes: The data acquisition unit is used to acquire road surface information through high-precision sensors; the high-precision sensors include pressure sensors, vibration sensors, and humidity sensors; the road surface information includes road surface smoothness data sequences, water depth data sequences, and road friction force data sequences. The road surface smoothness data sequence is as follows: ,in Indicates the first The road surface smoothness values ​​at each sampling point; The water depth data sequence is as follows: ,in Indicates the first The water depth values ​​at each sampling point; The road friction data sequence is as follows: ,in Indicates the first The road friction values ​​at the sample points; The comprehensive condition calculation unit, connected to the data acquisition unit, is used to calculate the comprehensive road surface condition index by combining road surface smoothness data sequence, water depth data sequence, and road friction data sequence. The calculation formula is: , in, This represents the average value of the road surface smoothness data. These are the weighting coefficients; Determined based on physical experiments on the impact of road surface smoothness on driving stability. Based on physical experiments determining the impact of water depth on tire grip and rolling resistance, The comprehensive road surface condition index is determined based on physical experiments examining the impact of road friction on power output and braking performance. It is used to comprehensively reflect the impact of road surface smoothness, water depth, and road friction on the travel process; The ideal speed calculation unit, connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. The ideal driving speed is calculated using the first optimization analysis model. ; The first optimization analysis model is: ,in, This represents the maximum speed the vehicle can travel under ideal road conditions. This refers to the speed adjustment coefficient; the speed adjustment coefficient The calculation formula is: , in, This represents the maximum output power of the drive unit. The total mass of the vehicle body, The effective coefficient of friction between the wheel and the ground. It is the acceleration due to gravity. This is the air resistance coefficient corresponding to the vehicle's maximum speed under ideal road conditions. This refers to the frontal area of ​​the vehicle body. Given the current air density, Based on the comprehensive road surface condition index The first adjustable unit conversion factor is about to be Convert to a dimensionless quantity related to velocity; The ideal suspension stiffness calculation unit, which is connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. The ideal suspension stiffness is calculated using the second optimization analysis model. ; The second optimization analysis model is: ,in, Setting the basic stiffness for the suspension. This refers to the hardness adjustment factor; the hardness adjustment factor The calculation formula is: , in, The spring constant of the suspension; For the damping ratio, The road surface excitation frequency; The natural frequency of the vehicle body's vibration; Based on the comprehensive road surface condition index The second adjustable unit conversion factor is... Converted to a dimensionless quantity related to suspension stiffness; the damping ratio ,in The damping coefficient of the suspension; the natural frequency of the vibration. ; The ideal tire pressure calculation unit, which is connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. Ideal tire pressure is calculated using the third optimization analysis model. ; The third optimization analysis model is: ,in, The standard tire pressure. This refers to the tire pressure adjustment factor; the tire pressure adjustment factor The calculation formula is: ,in, The elastic modulus of the tire. For the volume of the tire, This refers to the contact area between the tire and the road surface. This refers to the initial air pressure inside the tire; Based on the comprehensive road surface condition index The third adjustable unit conversion factor, which is to be Convert to a dimensionless quantity related to tire pressure; The feedback control unit, connected to the ideal speed calculation unit, the ideal suspension stiffness calculation unit, and the ideal tire pressure calculation unit, calculates the ideal driving speed. Ideal suspension stiffness Ideal tire pressure The data is transmitted to the central controller, which then adjusts it according to the ideal value.

[0010] According to the intelligent road inspection system provided by the present invention, the upper part of the vehicle body further includes a solar power generation unit or a wind power generation unit, which is connected to the battery pack for charging. It also includes self-powered equipment that converts solar and wind energy into electrical energy and supplements battery storage through power transformation and voltage stabilization functions.

[0011] According to the intelligent road inspection system provided by the present invention, the emergency rescue kit also includes an automatic fire extinguishing device, cutting tools, a hammer, an iron rod, and other rescue tools. The automatic fire extinguishing device is used to automatically start and extinguish fires when a fire occurs at the accident scene. The automatic fire extinguishing device includes at least a sensor and a video analysis device for fire detection. The sensor is used to detect flame, temperature, and smoke information. The automatic fire extinguishing device is mounted on the upper part of the device via an adjustable robotic arm or slide rail. After determining the location of the flames using a flame sensor and image analysis results, the central controller controls the movement of the robotic arm or slide rail, enabling the fire extinguishing device to automatically aim at the flames and extinguish them.

[0012] According to the intelligent road inspection system provided by the present invention, the vehicle chassis is also equipped with a backup battery pack for providing power support to each module in emergency situations.

[0013] On the other hand, the present invention provides a business model, including: Sales and leasing services; direct sales of intelligent road inspection systems to highway management departments, transportation operation companies, etc., and collection of equipment purchase fees; for customers with limited funds but long-term inspection needs, leasing services are provided, and rental fees are charged according to the lease duration; Data value-added services; collecting a large amount of road condition data and traffic accident data during inspections; conducting in-depth analysis and mining of this data to provide data reports and analysis services to transportation planning departments, road construction companies, and insurance companies; Advertising and cooperative promotion; conducting advertising business using vehicle exterior and voice / video intercom; cooperating with transportation-related companies to display advertisements on vehicle bodies and charging advertisers based on the duration and format of the advertisements. Emergency rescue service fees; when an accident or emergency occurs on the highway, the system responds quickly and provides emergency rescue services; for some rescue needs that are not within the scope of public rescue services, emergency rescue service fees are charged to the relevant parties.

[0014] Compared with the prior art, the beneficial effects of this application are as follows: This application utilizes high-precision sensors in its intelligent road condition prediction and adaptive driving module to collect real-time road condition information such as road surface smoothness, water depth, and road friction. The comprehensive road condition index calculated based on this information accurately reflects the actual road conditions. The system can adjust ideal driving speed, ideal suspension stiffness, and ideal tire pressure. For example, when there is water on the road, the system will reduce driving speed, increase suspension stiffness to improve vehicle stability, and appropriately adjust tire pressure to ensure good tire-road contact. This adaptive adjustment capability allows inspection vehicles to better adapt to complex road conditions, improve inspection efficiency, and reduce the possibility of vehicle accidents. This application uses a central controller as its core, tightly connecting various modules. Information collected by modules such as the automatic driving module, image capture and related modules, voice and video intercom module, and mobile speed measuring device can be transmitted to the central controller for integration. When a traffic accident occurs, the image capture module provides on-site photos and videos, the voice and video intercom module provides communication information with the command center, and the mobile speed measuring device provides vehicle speed information. This information is integrated in the central controller, enabling the command center to quickly and comprehensively understand the accident situation, thereby more accurately determining liability and assessing losses. In addition to basic vehicle speed measurement and license plate capture functions, the inspection system of this application also has a variety of other functions. For example, the image capture, video recording and remote transmission module can take pictures and videos of traffic accident scenes and transmit them to the traffic command center in real time; the voice and video intercom module can realize remote dialogue with the command center, which is convenient for accident liability determination and loss assessment; the emergency rescue kit is equipped with a variety of rescue supplies such as small demolition equipment, fire extinguishers, and fire blankets, as well as emergency alarm equipment, which can provide a certain emergency handling capability in case of emergencies such as fire and vehicle failure, and improve the inspection system's ability to respond to various emergencies on highways. The battery power management module includes a solar charging subunit and a wired charging subunit, providing diversified energy supply methods. The solar charging panel can charge the battery pack when there is sunlight, replenishing energy, improving energy utilization efficiency and vehicle range. At the same time, the power detection chip can monitor the battery's power, voltage, current and other status information in real time. Based on this information, the system can reasonably adjust the charging strategy. For example, when the battery power is low and charging conditions are available, the charging program will be initiated first to ensure that the inspection task is not interrupted due to insufficient energy.

[0015] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0016] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the structure of an intelligent road inspection system provided in an embodiment of the present invention. Detailed Implementation

[0018] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention. Example

[0019] This invention provides an intelligent road inspection system. Please refer to [link / reference]. Figure 1 ,include: The vehicle chassis and body are equipped with an autonomous driving module for unmanned driving, and the body is equipped with a mobile signal light device. The central controller, as the control hub of the entire system, is used for information integration and regulation; The communication module, based on Internet technology, enables wireless information interaction between the central controller and remote terminals, as well as local network operation. The image capture, video recording, and remote transmission module connects to the central controller. The central controller controls the module to capture license plates, photograph and record images at traffic accident scenes, and remotely transmit the data to the traffic command center and the local network operation and accident scene image / video storage environment via a communication module. It also analyzes and processes the captured vehicle images, extracting license plate numbers and vehicle model characteristics. The identification results are compared with a vehicle database to obtain relevant vehicle information, which is then transmitted to the central controller along with the captured images and video data. Furthermore, it analyzes images of accident scenes or surrounding roads, identifying the facial features and clothing characteristics of pedestrians and drivers, as well as scattered objects on the road. The identification results are transmitted to the central controller, providing more detailed information for accident handling or safety monitoring. The voice and video intercom module is connected to the central controller and communicates with the traffic command center remotely via the communication module. It is used for on-site remote accident liability determination and damage assessment of traffic accidents, as well as local network operation and working environment storage. The mobile speed measuring device is connected to the central controller, which controls it to perform high-speed speed measurement and triggers the image capture, video recording and remote transmission modules to capture speeding vehicles and upload information, as well as the local network operation and storage of the speeding vehicle capture environment. An emergency rescue kit should include at least small demolition equipment, a fire extinguisher, a fire blanket, a gas mask, gauze bandages, and hemostatic agents. The battery power management module includes a battery pack, a charging unit, a charging and discharging chip, and a power detection chip. The charging unit includes a solar charging sub-unit and a wired charging sub-unit. The power detection chip includes a CPU, a voltage monitoring device, a current monitoring device, a battery status detection device, and a bus communication device. The intelligent road condition prediction and adaptive driving module collects real-time road information, including road surface smoothness, water depth, and road friction data, through high-precision sensors installed in multiple locations on the chassis and body. It processes the collected data using an optimization analysis model to predict potential road condition changes ahead and adjust driving parameters in advance. This module connects to the central controller, transmitting road condition information and adjustment suggestions to it. The central controller coordinates the work of each module and also handles local storage and processing. It is also equipped with sensors to detect whether other vehicles are on sidewalks or emergency lanes. Based on image recognition algorithms for specific areas, it analyzes the data. Once it detects that another vehicle has entered a prohibited sidewalk or emergency lane, it immediately transmits the information to the central controller. The central controller triggers an alarm and sends violation information to the traffic control center via a communication module.

[0020] The principle and beneficial effects of this embodiment are as follows: automation and technology reduce the possibility of human error and provide a faster and more effective solution for dealing with emergencies; fully automated processes speed up information processing and reduce the time lag between problem discovery and problem resolution; in the long run, unmanned operation reduces labor costs and reduces economic losses caused by accidents due to preventive maintenance and timely response; such a system can provide more accurate and timely information and services for both ordinary drivers and traffic management departments.

[0021] To further optimize the above embodiments, the automatic driving module includes: The drive unit is used to control the vehicle's speed and direction. It includes an ECU, which controls the vehicle. The drive unit is equipped with at least two drive wheels located on both sides of the chassis and drive motors that are the same number as the drive wheels and are connected to each drive wheel. A control signal receiving device and a control signal input device are also connected to one side of the drive motor. The path navigation unit includes a memory, input / output ports and a processor. The processor includes a navigation information acquisition module, which is used to acquire navigation pattern information and plan the driving path of the non-motorized vehicle lane. The automatic navigation control unit is used to control the vehicle's driving parameters based on navigation pattern information; The obstacle avoidance unit includes a traffic sign recognition subunit and an obstacle recognition subunit; The traffic sign recognition subunit includes a video recognition device for capturing images of the road ahead of the vehicle, identifying the presence of traffic lights and traffic markings, and recognizing the status of traffic lights. Simultaneously, it calculates the real-time spatial distance between the vehicle and the traffic markings based on the pixel values ​​of the markings in the video image, and sends the continuously decreasing spatial distance value to the next level. It also has a lane recognition function, which, through feature extraction and analysis of lane lines in the video image, combined with the vehicle's position and driving direction information, accurately identifies the current driving lane and transmits the lane information to the data processing unit. The data processing unit adjusts the vehicle's driving position based on the lane information to ensure that the vehicle travels within the designated lane and not on the sidewalk or emergency lane. The obstacle recognition subunit includes a detection device for detecting the distance to obstacles, an obstacle information storage device for storing the location and distance properties of the detected obstacles, and an obstacle avoidance calculation code storage device for storing obstacle avoidance calculation codes. A comparator replaces the control signal input device in instructing the vehicle to move away from obstacles by comparing the stored obstacle information with the stored obstacle avoidance calculation code. The detection device comprises at least one transmitting and receiving device disposed around the perimeter of the electric vehicle body. The transmitting device includes an ultrasonic transmitting element and a trigger circuit, and the receiving device includes an ultrasonic receiving element and a front-end amplification circuit. The data processing unit is used to calculate the data transmitted back from the path navigation unit, obstacle avoidance unit and communication module, draw conclusions and control driving through the drive unit. The data processing unit is also connected to the cloud computing system to send the vehicle driving status to the cloud computing system. The cloud computing system can send back commands to the data processing unit and control the vehicle through the ECU connected to the data processing unit. The communication module is used to communicate with the cloud computing system and provide feedback on its own operational and functional data.

[0022] It should be noted that the Electronic Control Unit (ECU) precisely controls the drive motor by receiving instructions from the data processing unit. For example, when acceleration is required, the data processing unit calculates the appropriate acceleration command based on road conditions and task requirements, sends it to the ECU, and the ECU then adjusts the current or voltage of the drive motor to change the speed of the drive wheels, thereby controlling the vehicle speed. Having at least two drive wheels on each side of the chassis, each equipped with an independent drive motor, provides better vehicle power distribution and handling performance. For example, when turning, more precise steering can be achieved through differentiated control of the drive motors on different sides. The control signal receiving device on one side of the drive motor receives control signals from the ECU, while the control signal input device can be used to receive external control signals in manual or emergency situations, ensuring the vehicle can still operate under special circumstances. The memory is used to store map data, historical navigation information, etc.; for example, it stores map information of highways, including lane layout, entrance and exit locations, speed limit information, etc., to provide basic data support for navigation. The input port can be used to receive navigation destination information from external devices (such as remote terminals or manual settings), while the output port is used to send the planned navigation route information to the automatic navigation control unit and other related modules. The navigation information acquisition module in the processor analyzes the map data in the memory and the received real-time traffic information (such as traffic congestion information, road construction information, etc.) to obtain navigation pattern information; for example, based on the current location and destination, combined with real-time traffic conditions, it determines the optimal driving route, including which lane to choose, which intersection to turn at, etc., and plans the driving path in the non-motorized vehicle lane to avoid collisions with other vehicles. The automatic navigation control unit controls the vehicle's driving parameters based on the route information planned by the navigation information acquisition module; for example, it adjusts the vehicle speed according to the speed limit information in the route, and adjusts the vehicle's steering angle in advance according to the turning information. A high-resolution camera is used as a video recognition device, installed at a suitable position in front of the vehicle, which can clearly capture road images; through image recognition algorithms, the captured images are analyzed to distinguish the color and status of traffic lights (such as red light, green light, yellow light), as well as to identify the type of traffic markings (such as solid lines, dashed lines, lane dividing lines, etc.). Spatial distance calculation is based on the pixel values ​​of traffic signs in the video footage, combined with camera parameters (such as focal length, viewing angle, etc.) and vehicle position information, to calculate the real-time spatial distance between the vehicle and the traffic signs using geometric calculation methods; for example, when a vehicle approaches the lane dividing line, a warning message is issued in a timely manner to remind the vehicle to stay in the correct lane. Multiple transmitting and receiving devices are installed around the vehicle body. The ultrasonic transmitting element in the transmitting device periodically emits ultrasonic signals under the action of the trigger circuit. After receiving the reflected ultrasonic signals, the ultrasonic receiving element in the receiving device amplifies them through the front-end amplification circuit and then transmits them to the road obstacle information storage device. The obstacle information storage device stores information such as the location, distance, and nature of the detected obstacles, while the obstacle avoidance calculation code storage device stores pre-set obstacle avoidance calculation codes. A comparator compares the information in the obstacle information storage device with the codes in the obstacle avoidance calculation code storage device, and based on the comparison result, it replaces the control signal input device to instruct the vehicle to move to avoid the obstacle. For example, if there is an obstacle ahead and it is close, the vehicle will automatically decelerate or turn to avoid the obstacle. The data processing unit receives data from the path navigation unit, the obstacle avoidance unit, and the communication unit; for example, it receives path information planned by the path navigation unit, obstacle information detected by the obstacle avoidance unit, and cloud computing system instructions fed back by the communication unit. The built-in algorithms and processors analyze and calculate this data; for example, based on path and obstacle information, the optimal driving strategy for the vehicle is calculated, and it is determined whether the speed or steering needs to be adjusted. The calculation results are sent to the ECU of the drive unit to control the vehicle's movement; at the same time, the vehicle's driving status data is sent to the cloud computing system so that the cloud computing system can perform further analysis and provide feedback commands. For the communication module, it uses wireless communication technology (such as 5G or other high-speed wireless networks) to communicate with the cloud computing system; for example, it periodically sends vehicle operation data (such as speed, location, battery power, etc.) and functional data (such as the working status of each module) to the cloud computing system; it receives commands and instructions from the cloud computing system, such as adjusting the driving route, changing the inspection task, etc., and passes these instructions to the data processing unit for processing.

[0023] To further optimize the above embodiments, the image capture, video recording, and remote transmission modules employ high-speed HD cameras, with at least two sets located at the front and rear of the vehicle. These high-speed HD cameras have night vision capabilities and are equipped with at least 1TB of ultra-large storage devices, storing data using a local loop recording method. Simultaneously, cameras are added to the sides and top of the vehicle, forming a multi-camera system with the front and rear cameras. Through image stitching and fusion technology, panoramic monitoring and recognition of multiple lanes are achieved. Each camera is responsible for image acquisition in a specific area, and the data processing unit integrates and analyzes the data from each camera to ensure comprehensive and accurate monitoring of vehicles and road conditions across multiple lanes. The communication module uses 5G network communication, satellite communication and other network communication methods to connect to traffic command centers in various places in real time.

[0024] It should be noted that at least two sets of high-speed HD cameras are installed at the front and rear of the vehicle. This layout can ensure comprehensive coverage of the road conditions in front of and behind the vehicle. The front camera is mainly used to capture the road conditions, vehicle information and possible traffic accidents in front of the vehicle, while the rear camera is used to monitor the traffic dynamics behind the vehicle, such as capturing the following distance of vehicles behind and whether there is any abnormal vehicle behavior. It adopts a high-speed HD (high definition) camera, which can provide clear, high-quality image and video data; its night vision function enables the vehicle to work normally at night or in low light conditions. Through special optical sensors and image processing algorithms, it enhances the ability to identify objects in low-light environments, ensuring that inspection work is not limited by lighting conditions. Equipped with at least 1TB of ultra-large storage devices to meet the storage needs of large amounts of image and video data; since image capture and video recording will be carried out continuously during the inspection process, sufficient storage space is required to save this data; a local loop recording method is adopted, that is, when the storage space of the storage device is almost full, the newly recorded data will automatically overwrite the oldest recorded data; this method can ensure that the latest inspection data is always saved within the limited storage space, and also avoid the problem of data loss due to insufficient storage space; The images and video data captured by the camera are first transmitted to the central controller, which performs preliminary processing and integration of the data, and then transmits the data remotely to the traffic command center through the communication module. For example, in the event of a traffic accident, the central controller will quickly send the images and video data of the accident scene to the traffic command center so that the command center can understand the accident situation in a timely manner and make corresponding decisions.

[0025] To further optimize the above embodiments, the emergency rescue kit is also equipped with an emergency alarm device; the emergency alarm device includes an alarm and a main controller installed on the vehicle body; the alarm includes a control circuit, a voice circuit and a light-emitting circuit. After the alarm is powered on, the main controller automatically reads the voice address set by the digital disk. When the main controller receives the input signal from the dot, contact, overhead line or infrared probe, it automatically controls the voice circuit to emit an alarm sound, and at the same time controls the light-emitting circuit to emit a flashing red signal.

[0026] It should be noted that the control circuit is the core part of the alarm, and it is responsible for coordinating the work between various circuit modules. When the main controller receives a trigger signal, the control circuit will send instructions to the voice circuit and the light circuit according to the preset logic, so that they can work normally. For example, the control circuit can adjust the voice content played by the voice circuit and the flashing frequency of the light circuit according to different trigger signal types. The voice circuit mainly consists of an audio amplifier and a speaker. When the main controller triggers the voice circuit through the control circuit, the audio amplifier amplifies the voice signal stored in the digital disk and then plays it out through the speaker. The voice signal can be a pre-recorded message about vehicle malfunctions, accidents, or other emergencies, so that people around can be informed of the situation in a timely manner. The light-emitting circuit is usually composed of light-emitting diodes (LEDs) and related driving circuits. When the main controller controls the light-emitting circuit to work, the driving circuit will provide the LED with a suitable current, so that the LED emits a flashing red signal. This flashing red signal is very conspicuous in low light environment and can attract the attention of people around and indicate that the vehicle is in an emergency. After powering on, the main controller automatically reads the voice address set by the digital disk. The digital disk can store multiple voice addresses, each corresponding to a different voice message. The main controller determines the voice content to be played by reading the voice address. For example, different voice addresses can be set for different emergency situations, causing the alarm to play corresponding prompts. The main controller continuously monitors input signals from points, contacts, overhead lines, or infrared sensors. These signals can come from the vehicle's own sensor system and are used to detect whether the vehicle has experienced a malfunction, collision, or other emergency. When the main controller receives these signals, it determines whether to trigger the alarm based on the type and intensity of the signal. For example, if a strong signal is received from the vehicle's collision sensor, the main controller will immediately trigger the alarm, emitting an alarm sound and flashing a signal.

[0027] To further optimize the above embodiments, the solar charging subunit includes a retractable solar charging panel, which is installed on the periphery and upper surface of the vehicle body; the wired charging subunit charges the battery pack through a generator.

[0028] It should be noted that the solar charging panels are installed around the vehicle's perimeter and on its top surface. This layout maximizes sunlight absorption and improves solar energy collection efficiency. The solar charging panels around the vehicle's perimeter can receive sunlight from different angles while the vehicle is in motion, while the top panel plays a crucial role when the vehicle is stationary or under direct sunlight. The retractable design allows for flexible adjustment of the solar charging panel area under different environments and usage needs. For example, when there is ample sunlight and the vehicle does not need to move frequently, the solar charging panels can be fully extended to increase the solar energy absorption area. When the vehicle needs to pass through narrow spaces or in inclement weather conditions, the charging panels can be retracted to prevent damage. The retraction function is achieved through mechanical devices such as electric or hydraulic push rods, controlled by the vehicle's control system according to environmental conditions and usage requirements. The wired charging sub-unit charges the battery pack via a generator. The generator can be a generator driven by the vehicle's own engine or a separate generator specifically designed for charging. For example, in some hybrid vehicles, the engine drives the generator to generate electricity and charge the battery pack during operation. In pure electric inspection vehicles, a small fuel generator or other type of generator can be installed to start the generator to charge the battery pack when the battery power is low and solar charging is not available in time.

[0029] To further optimize the above embodiments, the intelligent road condition prediction and adaptive driving module includes: The data acquisition unit is used to collect road surface information through high-precision sensors, including pressure sensors, vibration sensors, and humidity sensors. The road surface information includes road surface smoothness data sequences, water depth data sequences, and road friction force data sequences. Road surface smoothness data sequence is ,in Indicates the first The road surface smoothness values ​​at each sampling point; Water depth data sequence is ,in Indicates the first The water depth values ​​at each sampling point; Road friction data sequence is ,in Indicates the first The road friction force values ​​at each sampling point; The comprehensive condition calculation unit, connected to the data acquisition unit, is used to calculate the comprehensive road condition index by combining road surface smoothness data sequence, water depth data sequence, and road friction data sequence. The calculation formula is: ,in, This represents the average value of the road surface smoothness data. These are the weighting coefficients; Determined based on physical experiments on the impact of road surface smoothness on driving stability. Determined based on physical experiments on the effect of water depth on tire grip and rolling resistance; The comprehensive road surface condition index is determined based on physical experiments examining the impact of road friction on power output and braking performance. It is used to comprehensively reflect the impact of road surface smoothness, water depth, and road friction on the travel process; The ideal speed calculation unit is connected to the comprehensive condition calculation unit, based on the road surface comprehensive condition index. The ideal driving speed is calculated using the first optimization analysis model. ; The first optimization analysis model is: ,in, This represents the maximum speed the vehicle can travel under ideal road conditions. Speed ​​adjustment coefficient; speed adjustment coefficient The calculation formula is: , in, This represents the maximum output power of the drive unit. The total mass of the vehicle body, The effective coefficient of friction between the wheel and the ground. It is the acceleration due to gravity. This is the air resistance coefficient corresponding to the vehicle's maximum speed under ideal road conditions. This refers to the frontal area of ​​the vehicle body. Given the current air density, Based on the comprehensive road surface condition index The first adjustable unit conversion factor is about to be Converted to a speed-dependent dimensionless quantity; the ideal suspension stiffness calculation unit, connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. The ideal suspension stiffness is calculated using the second optimization analysis model. ; The second optimization analysis model is: ,in, Setting the basic stiffness for the suspension. This refers to the hardness adjustment factor; the hardness adjustment factor The calculation formula is: ,in, The spring constant of the suspension; For the damping ratio, The road surface excitation frequency; The natural frequency of the vehicle body's vibration; Based on the comprehensive road surface condition index The second adjustable unit conversion factor is... Converted to a dimensionless quantity related to suspension stiffness; damping ratio ,in The damping coefficient of the suspension; the natural frequency of vibration. ; The ideal tire pressure calculation unit, connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. Ideal tire pressure is calculated using the third optimization analysis model. ; The third optimization analysis model is: ,in, The standard tire pressure. This refers to the tire pressure adjustment factor; tire pressure adjustment factor The calculation formula is: ,in, The elastic modulus of the tire. For the volume of the tire, This refers to the contact area between the tire and the road surface. This refers to the initial air pressure inside the tire; Based on the comprehensive road surface condition index The third adjustable unit conversion factor, which is to be Convert to a dimensionless quantity related to tire pressure; The feedback control unit, connected to the ideal speed calculation unit, ideal suspension stiffness calculation unit, and ideal tire pressure calculation unit, calculates the ideal driving speed. Ideal suspension stiffness Ideal tire pressure The data is transmitted to the central controller, which then adjusts it according to the ideal value.

[0030] It should be noted that the conversion factor for the first adjustable unit... It is necessary to determine this through a large number of experiments under different road conditions. The value; for example, on a specific test section with known road surface smoothness, water depth, and road friction, the inspection vehicle is driven at different speeds, while the actual resistance experienced by the vehicle (including friction, air resistance, etc.) and the vehicle's power output are measured; based on the formula, given other known parameters, the value is continuously adjusted... The value was determined to match the calculated ideal driving speed with the vehicle's optimal driving speed under actual road conditions (obtained through experimental observation and measurement); after multiple experiments and adjustments, a suitable value was finally determined. The value; the second adjustable unit conversion factor Conversion factor with the third adjustable unit The method for determining this is similar, and will not be elaborated further. For weighting coefficients The effect of road surface smoothness on driving stability is determined through physical experiments. For example, on test roads with different smoothness levels, vehicles are driven at the same speed, and parameters such as vibration amplitude and steering stability are measured. Based on the experimental results, the degree of influence of road surface smoothness on driving stability is analyzed, thereby determining the impact. The value; For weighting coefficients Physical experiments were conducted to investigate the effect of water depth on tire grip and rolling resistance. Changes in tire grip and vehicle rolling resistance were measured on test surfaces with varying water depths. Based on the experimental results, the extent of the effect of water depth on tire grip and rolling resistance was determined, thereby determining... The value; For weighting coefficients Physical experiments were conducted to investigate the impact of road friction on power output and braking performance. On test surfaces with varying friction levels (e.g., dry, wet, icy), the vehicle's power output and braking performance (e.g., braking distance, braking time) were measured. Based on the experimental results, the degree of influence of road friction on power output and braking performance was determined, thereby determining... The value of .

[0031] To further optimize the above embodiments, the upper part of the vehicle body also includes a solar power generation unit or a wind power generation unit, which is connected to the battery pack for charging. It also includes self-powered equipment, which is used to convert solar and wind energy into electrical energy and supplement battery storage through power transformation and voltage stabilization functions; The emergency rescue kit also includes rescue tools such as automatic fire extinguishing devices, cutting tools, hammers, and iron bars. The automatic fire extinguishing devices are used to automatically start and extinguish fires when a fire occurs at the accident site. The automatic fire extinguishing devices include at least a fire detection device and a video analysis device. The detection device is used to sense flame, temperature, and smoke information. The automatic fire extinguishing device is installed on the upper part of the equipment via an adjustable robotic arm or slide rail. After determining the location of the flames using flame sensors and image analysis results, the central controller controls the movement of the robotic arm or slide rail so that the fire extinguishing device can automatically aim at the flames and extinguish them.

[0032] The chassis is also equipped with a backup battery pack to provide power to the modules in case of an emergency. Example

[0033] This invention provides a business model, including: Sales and leasing services; direct sales of intelligent road inspection systems to highway management departments, transportation operation companies, etc., and collection of equipment purchase fees; for customers with limited funds but long-term inspection needs, leasing services are provided, and rental fees are charged according to the lease duration; Data value-added services; collecting a large amount of road condition data and traffic accident data during inspections; conducting in-depth analysis and mining of this data to provide data reports and analysis services to transportation planning departments, road construction companies, and insurance companies; Advertising and cooperative promotion; conducting advertising business using vehicle exterior and voice / video intercom; cooperating with transportation-related companies to display advertisements on vehicle bodies and charging advertisers based on the duration and format of the advertisements. Emergency rescue service fees; when an accident or emergency occurs on the highway, the system responds quickly and provides emergency rescue services; for some rescue needs that are not within the scope of public rescue services, emergency rescue service fees are charged to the relevant parties.

[0034] It should be noted that the intelligent road inspection system is sold directly to customers such as highway management departments and transportation operation companies, and the equipment purchase fee is collected. These customers have the ability to purchase the equipment to meet their long-term needs for highway inspection, and the sale of the product can generate a high one-time income. For customers with limited funds but who need to use the inspection system for a long time, we offer leasing services; we charge rent based on the rental period, which can reduce the one-time investment cost for customers, attract more potential customers, and at the same time, the company can obtain a stable cash flow through long-term rental income. During the inspection process, the system collects a large amount of valuable data, such as road condition data (road surface condition, traffic flow, etc.) and traffic accident data; By conducting in-depth analysis and mining of this data, targeted data reports and analysis services can be provided to different industry sectors. For example, transportation planning departments can use this data to optimize road design and traffic signal settings; road construction companies can rationally arrange road maintenance and repair plans based on road condition data; and insurance companies can more accurately assess risks and formulate insurance rates based on accident data, thereby charging data service fees and realizing the added value of data. Utilize the vehicle's exterior and the display functions of its voice and video intercom system to conduct advertising business; collaborate with transportation-related companies such as car brands and tire manufacturers to display advertisements on the vehicle; charge advertisers based on the duration and format of the advertisement (such as static sticker advertisements, video advertisements, etc.) to increase additional revenue streams; Partnering with technology companies to test and promote new smart transportation technologies or sensor products on the platform; achieving mutual benefit and win-win results by charging fees for collaborative research and development and promotion, while also contributing to the technological advancement of the industry; When an accident or emergency occurs on the highway, the inspection system can respond quickly and provide emergency rescue services; For some rescue needs that are not covered by public rescue services, such as providing on-site repair tools and technical support for disabled vehicles that go beyond the basic functions of an emergency rescue kit, or assisting in clearing obstacles from an accident scene, emergency rescue service fees can be charged to the relevant parties. This can not only increase the company's revenue, but also encourage the company to continuously improve its rescue service capabilities.

[0035] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A smart road inspection system, characterized in that, include: The vehicle chassis and body are equipped with an autonomous driving module for unmanned driving, and the body is equipped with a mobile signal light device. The central controller, as the control hub of the entire system, is used for information integration and regulation; The communication module, based on Internet technology, enables wireless information interaction between the central controller and remote terminals, as well as local network operation. The image capture, video recording, and remote transmission module connects to the central controller. The central controller controls the module to capture license plates, photograph and record images at traffic accident scenes, and remotely transmit the data to the traffic command center and the local network operation and accident scene image / video storage environment via a communication module. It also analyzes and processes the captured vehicle images, extracting license plate numbers and vehicle model characteristics. The identification results are compared with a vehicle database to obtain relevant vehicle information, which is then transmitted to the central controller along with the captured images and video data. Furthermore, it analyzes images of accident scenes or surrounding roads, identifying the facial features and clothing characteristics of pedestrians and drivers, as well as scattered objects on the road. The identification results are transmitted to the central controller, providing more detailed information for accident handling or safety monitoring. The voice and video intercom module is connected to the central controller and communicates with the traffic command center remotely via the communication module. It is used for on-site remote accident liability determination and damage assessment of traffic accidents, as well as local network operation and working environment storage. The mobile speed measuring device is connected to the central controller, which controls it to perform high-speed speed measurement and triggers the image capture, video recording and remote transmission modules to capture speeding vehicles and upload information, as well as the local network operation and storage of the speeding vehicle capture environment. An emergency rescue kit should include at least small demolition equipment, a fire extinguisher, a fire blanket, a gas mask, gauze bandages, and hemostatic agents. The battery power management module includes a battery pack, a charging unit, a charging and discharging chip, and a power detection chip. The charging unit includes a solar charging sub-unit and a wired charging sub-unit. The power detection chip includes a CPU, a voltage monitoring device, a current monitoring device, a battery status detection device, and a bus communication device. The intelligent road condition prediction and adaptive driving module collects road information in real time through high-precision sensors installed in multiple locations on the chassis and body, including road surface smoothness, water depth, and road friction data. It processes the collected data using an optimization analysis model to predict possible changes in road conditions ahead and adjust driving parameters in advance. This module is connected to the central controller, which transmits road condition information and adjustment suggestions to the central controller. The central controller coordinates the work of each module and also includes local storage and processing. It is also equipped with sensors to detect whether other vehicles are on the sidewalk or emergency lane, and analyzes the information based on image recognition algorithms for specific areas. Once it is determined that another vehicle has entered a prohibited sidewalk or emergency lane, the information is immediately transmitted to the central controller. The central controller triggers the alarm device and sends the violation information to the traffic control center through the communication module.

2. The intelligent road inspection system according to claim 1, characterized in that, The automatic driving module includes: The drive unit is used to control the vehicle's speed and direction. It includes an ECU, which controls the vehicle. The drive unit is equipped with at least two drive wheels located on both sides of the chassis and drive motors that are the same number as the drive wheels and are connected to each drive wheel. A control signal receiving device and a control signal input device are also connected to one side of the drive motor. The path navigation unit includes a memory, input / output ports and a processor. The processor includes a navigation information acquisition module, which is used to acquire navigation pattern information and plan the driving path of the non-motorized vehicle lane. The automatic navigation control unit is used to control the vehicle's driving parameters based on navigation pattern information; The obstacle avoidance unit includes a traffic sign recognition subunit and an obstacle recognition subunit; The traffic sign recognition subunit includes a video recognition device for capturing images of the road ahead of the vehicle, identifying the presence of traffic lights and traffic markings, and recognizing the status of traffic lights. Simultaneously, it calculates the real-time spatial distance between the vehicle and the traffic markings based on the pixel values ​​of the traffic markings in the video image, and sends the continuously decreasing spatial distance values ​​to the next level. It also has a lane recognition function, which, through feature extraction and analysis of lane lines in the video image, combined with the vehicle's position and driving direction information, accurately identifies the current driving lane and transmits the lane information to the data processing unit. The data processing unit adjusts the vehicle's driving position based on the lane information to ensure that the vehicle travels within the designated lane and not on the sidewalk or emergency lane. The obstacle recognition subunit includes a detection device for detecting the distance to obstacles, a road obstacle information storage device for storing the location and distance properties of the detected road obstacles, and an obstacle avoidance calculation code storage device for storing obstacle avoidance calculation codes. A comparator replaces the control signal input device in instructing the vehicle to move away from obstacles by comparing the stored road obstacle information with the stored obstacle avoidance calculation code. The detection device comprises at least one transmitting and receiving device disposed around the perimeter of the electric vehicle body. The transmitting device includes an ultrasonic transmitting element and a trigger circuit, and the receiving device includes an ultrasonic receiving element and a front-end amplification circuit. The data processing unit is used to calculate the data transmitted back from the path navigation unit, obstacle avoidance unit and communication module, draw conclusions and control driving through the drive unit. The data processing unit is also connected to the cloud computing system to send the vehicle driving status to the cloud computing system. The cloud computing system can send back commands to the data processing unit and control the vehicle through the ECU connected to the data processing unit. The communication module is used to communicate with the cloud computing system and to provide feedback on its own operating data and functional data.

3. The intelligent road inspection system according to claim 2, characterized in that, The image capture, video recording, and remote transmission module employs high-speed HD cameras, with at least two sets located at the front and rear of the vehicle. These high-speed HD cameras feature night vision capabilities and are equipped with at least 1TB of ultra-large storage, storing data through local loop recording. Additionally, cameras are added to the sides and top of the vehicle, forming a multi-camera system with the front and rear cameras. Through image stitching and fusion technology, panoramic monitoring and identification of multiple lanes are achieved. Each camera is responsible for image acquisition in a specific area, and the data processing unit integrates and analyzes the data from each camera to ensure comprehensive and accurate monitoring of vehicles and road conditions across multiple lanes. The communication module uses 5G network communication, satellite communication and other network communication methods to connect to traffic command centers in various places in real time.

4. The intelligent road inspection system according to claim 3, characterized in that, The emergency rescue kit is also equipped with an emergency alarm device; the emergency alarm device includes an alarm and a main controller installed on the vehicle body; the alarm includes a control circuit, a voice circuit and a light-emitting circuit. After the alarm is powered on, the main controller automatically reads the voice address set by the digital disk. When the main controller receives a signal input from a dot, contact point, overhead line or infrared probe, it automatically controls the voice circuit to emit an alarm sound, and at the same time controls the light-emitting circuit to emit a flashing red signal.

5. The intelligent road inspection system according to claim 4, characterized in that, The solar charging subunit includes a retractable solar charging panel, which is disposed on the periphery and upper surface of the vehicle body; the wired charging subunit charges the battery pack through a generator.

6. The intelligent road inspection system according to claim 5, characterized in that, The intelligent road condition prediction and adaptive driving module includes: The data acquisition unit is used to acquire road surface information through high-precision sensors; the high-precision sensors include pressure sensors, vibration sensors, and humidity sensors; the road surface information includes road surface smoothness data sequences, water depth data sequences, and road friction force data sequences. The road surface smoothness data sequence is as follows: ,in Indicates the first The road surface smoothness values ​​at each sampling point; The water depth data sequence is as follows: ,in Indicates the first The water depth values ​​at each sampling point; The road friction data sequence is as follows: ,in Indicates the first The road friction force values ​​at each sampling point; The comprehensive condition calculation unit, connected to the data acquisition unit, is used to calculate the comprehensive road surface condition index by combining road surface smoothness data sequence, water depth data sequence, and road friction data sequence. The calculation formula is: , in, This represents the average value of the road surface smoothness data. These are the weighting coefficients; Determined based on physical experiments on the impact of road surface smoothness on driving stability. Based on physical experiments determining the effect of water depth on tire grip and rolling resistance, The comprehensive road surface condition index is determined based on physical experiments examining the impact of road friction on power output and braking performance. It is used to comprehensively reflect the impact of road surface smoothness, water depth, and road friction on the travel process; The ideal speed calculation unit, connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. The ideal driving speed is calculated using the first optimization analysis model. ; The first optimization analysis model is: ,in, This represents the maximum output power of the drive unit. The total mass of the vehicle body The effective coefficient of friction between the wheel and the ground. It is the acceleration due to gravity. This is the air resistance coefficient corresponding to the vehicle's maximum speed under ideal road conditions. This refers to the frontal area of ​​the vehicle body. Given the current air density, Based on the comprehensive road surface condition index The first adjustable unit conversion factor is about to be Convert to a dimensionless quantity related to velocity; The ideal suspension stiffness calculation unit, which is connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. The ideal suspension stiffness is calculated using the second optimization analysis model. ; The second optimization analysis model is: ,in, Setting the basic stiffness for the suspension. This refers to the hardness adjustment factor; the hardness adjustment factor The calculation formula is: ,in, The spring constant of the suspension; For the damping ratio, The road surface excitation frequency; The natural frequency of the vehicle body's vibration; Based on the comprehensive road surface condition index The second adjustable unit conversion factor is, which is... Converted to a dimensionless quantity related to suspension stiffness; the damping ratio ,in The damping coefficient of the suspension; the natural frequency of the vibration. ; The ideal tire pressure calculation unit, which is connected to the comprehensive condition calculation unit, is based on the road surface comprehensive condition index. Ideal tire pressure is calculated using the third optimization analysis model. ; The third optimization analysis model is: ;in, The elastic modulus of the tire. For the volume of the tire, This refers to the contact area between the tire and the road surface. This refers to the initial air pressure inside the tire; Based on the comprehensive road surface condition index The third adjustable unit conversion factor, which is to be Convert to a dimensionless quantity related to tire pressure; The feedback control unit, connected to the ideal speed calculation unit, the ideal suspension stiffness calculation unit, and the ideal tire pressure calculation unit, calculates the ideal driving speed. Ideal suspension stiffness Ideal tire pressure The data is transmitted to the central controller, which then adjusts it according to the ideal value.

7. The intelligent road inspection system according to claim 6, characterized in that, The upper part of the vehicle body also includes a solar power generation unit or a wind power generation unit, which is connected to the battery pack for charging. It also includes self-powered equipment that converts solar and wind energy into electrical energy and supplements battery storage through power transformation and voltage stabilization functions.

8. The intelligent road inspection system according to claim 7, characterized in that, The emergency rescue kit also includes rescue tools such as an automatic fire extinguishing device, cutting tools, a hammer, and an iron rod. The automatic fire extinguishing device is used to automatically start and extinguish fires when a fire occurs at the accident site. The automatic fire extinguishing device includes at least a sensor and a video analysis device for fire detection. The sensor is used to detect flame, temperature, and smoke information. The automatic fire extinguishing device is mounted on the upper part of the device via an adjustable robotic arm or slide rail. After determining the location of the flames using flame sensors and image analysis results, the central controller controls the movement of the robotic arm or slide rail so that the fire extinguishing device can automatically aim at the flames and extinguish them.

9. The intelligent road inspection system according to claim 8, characterized in that, The vehicle chassis is also equipped with a backup battery pack to provide power to the modules in case of an emergency.

10. A business model based on the intelligent road inspection system described in claims 1-9, characterized in that, include: Sales and leasing services; Directly sell intelligent road inspection systems to highway management departments, transportation operation companies, etc., and collect equipment procurement fees; For customers with limited funds but long-term inspection needs, we offer leasing services and charge rent based on the rental period. Data value-added services; collecting a large amount of road condition data and traffic accident data during inspections; conducting in-depth analysis and mining of this data to provide data reports and analysis services to transportation planning departments, road construction companies, and insurance companies; Advertising and cooperative promotion; conducting advertising business using vehicle exterior and voice / video intercom; cooperating with transportation-related companies to display advertisements on vehicle bodies and charging advertisers based on the duration and format of the advertisements. Emergency rescue services are charged; when an accident or emergency occurs on the highway, the system responds quickly and provides emergency rescue services. For rescue needs that fall outside the scope of public rescue services, emergency rescue service fees will be charged to the relevant parties.

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