Vehicle and pedestrian identification early warning system based on intersection images

Abstract

The invention discloses a vehicle and pedestrian recognition and early warning system based on intersection images, and relates to the technical field of intelligent traffic, the recognition and early warning system comprises an image acquisition module, an image recognition module, a data processing module and an alarm module, the image acquisition module comprises a remote camera and an intersection camera, the system has the advantages that the vehicle data captured by the remote camera is processed through the data processing module in advance, and then the processed vehicle data is cached through the data caching unit, so that the vehicle data are stored in the remote camera, the remote camera is used for shooting the remote data of the road, and the intersection camera is used for shooting the two sides of the intersection. The data processing module is used for analyzing the influence of the driving data of vehicles when pedestrians pass through the intersection, then the driving data are matched with the data in the data caching unit, and when the data are successfully matched, the alarm module gives an alarm through the buzzer, so that the reaction efficiency of the recognition early warning system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent transportation, and specifically provides a vehicle and pedestrian recognition and warning system based on intersection images. Background Technique

[0002] Traditional intersection safety measures mainly rely on traffic lights and markings, but these measures often have limitations in complex traffic environments. Traffic lights can only provide fixed signal indications and cannot adapt to dynamic traffic conditions in real time. Markings may also be ignored due to blocked vision or driver negligence. To improve intersection safety, a vehicle and pedestrian recognition and warning system uses advanced imaging technology and intelligent algorithms to monitor and identify vehicles and pedestrians at intersections in real time. Through cameras installed at intersections, the system can obtain real-time images of the intersections and use image processing and pattern recognition technologies to quickly and accurately detect information such as the positions and motion states of vehicles and pedestrians. When the system detects potential dangerous situations, it can quickly issue warning signals to remind drivers and pedestrians to take corresponding measures to avoid traffic accidents.

[0003] However, to achieve effective warning, the reaction speed of the system is crucial. If the reaction speed of the system is too slow, warning signals may not be issued in time, resulting in dangerous situations not being avoided in time. For this reason, we propose a vehicle and pedestrian recognition and warning system based on intersection images. Summary of the Invention

[0004] The purpose of the present invention is to provide a vehicle and pedestrian recognition and warning system based on intersection images.

[0005] To solve the problems raised in the above background technique, the present invention provides the following technical solution: A vehicle and pedestrian recognition and warning system based on intersection images, the recognition and warning system includes an image acquisition module, an image recognition module, a data processing module, and an alarm module;

[0006] The image acquisition module includes a remote camera and an intersection camera. The remote camera is used to capture data from a distance on the road, and the intersection camera captures both sides of the intersection and transmits the data captured by the image acquisition module to the image recognition module;

[0007] The image recognition module includes a vehicle recognition unit and a pedestrian recognition unit. The intersection data captured by the remote camera is transmitted to the vehicle recognition unit. The vehicle recognition unit is used to identify the vehicle data captured by the remote camera and the intersection camera, and transmits the vehicle data captured by the remote camera to the data processing module. The intersection camera transmits the captured data to the pedestrian recognition unit, and the pedestrian recognition unit is used to identify the pedestrian feature data in the captured data;

[0008] The data processing module includes a data cache unit, a pedestrian feature unit, and a data matching unit. The data processing module is used to calculate the vehicle driving state data captured by a remote camera and transmit the vehicle driving state data to the data cache unit. The pedestrian feature unit is used to identify the pedestrian data captured by an intersection camera, analyze the pedestrian data through the data processing module, and based on the current pedestrian data state, analyze the vehicle driving data of dangerous pedestrians and transmit the analyzed vehicle driving data to the data matching unit. The data matching unit retrieves the vehicle driving data and matches it with the vehicle data in the data cache unit. When the vehicle data matches the data processing module, the data processing module creates alarm instruction data and transmits the alarm instruction data to the alarm module. When the vehicle data does not match the data processing module, the data processing module transmits the processed data to the cloud;

[0009] After receiving the alarm instruction data, the alarm module issues an alarm through a siren.

[0010] As a further solution of the present invention: The pedestrian recognition unit is used to identify the portraits in the intersection camera. After completing the identification of the portraits in the intersection camera, it transmits the data captured by the intersection camera to the vehicle recognition unit. The data cache unit is used to store the data processed by the vehicle recognition unit, and the vehicle recognition unit is used to process the vehicle data captured by the remote camera and the intersection camera. A vehicle matching unit is set in the image recognition module. After the vehicle recognition unit completes the identification of the vehicle data captured by the remote camera, it transmits the identified data to the vehicle matching unit. The vehicle matching unit retrieves the shooting data of the intersection camera and matches the vehicle data of the intersection camera with the vehicle data of the remote camera. Then, as the vehicle moves from the current camera screen to the next camera screen, the intersection camera extracts and obtains the vehicle data.

[0011] As a further solution of the present invention: The data cache unit obtains the traffic light data through the intersection camera and uses the changing time of the traffic lights to clean the cached data. After the data cache unit caches the vehicle driving data, after the traffic lights change orderly three to four times, specific data in the data cache unit is cleared.

[0012] As a further solution of the present invention: The data processing module calculates the average speed of the vehicle through a formula, and the specific formula is as follows:

[0013]

[0014] Among them, V represents the average speed of the vehicle identified in the remote camera, D represents the distance traveled by the vehicle in the remote camera, T represents the time required for the vehicle to travel the distance, and F represents the reduced speed when the vehicle identified by the data processing module brakes.

[0015] As a further solution of the present invention: The data cache unit is used to cache the vehicle data calculated by the data processing module.

[0016] As a further solution of the present invention: A risk assessment module is provided in the pedestrian feature unit. The pedestrian recognition unit transmits the recognized portrait data to the pedestrian feature unit. The pedestrian feature unit uses the risk assessment module to analyze the portrait and analyze the data that the current portrait's passing speed at the intersection and the vehicle's driving speed will affect the pedestrian's safe passage.

[0017] As a further solution of the present invention: The data processing module obtains risk index data through a formula. The specific formula is as follows:

[0018] R = f1·d + f2·P + f3·v i + f4·Q

[0019] Wherein, R represents the risk index data, d represents the distance data between the vehicle and the pedestrian, f1 represents the weight coefficient adjusted by the pedestrian's age, P represents the relative speed data between the vehicle and the pedestrian, f2 represents the weight coefficient of the relative speed between the vehicle and the pedestrian affecting the pedestrian's danger, v i represents the speed data of the i-th vehicle in the remote camera, f3 represents the vehicle speed weight coefficient in the remote camera, Q represents the area data affected by the vehicle's vision, and f4 represents the weight coefficient affected by the vision.

[0020] As a further solution of the present invention: The data matching unit retrieves the vehicle driving data in the data cache unit for matching. When the data matching unit performs the matching and V < v i In this case, the data processing module does not transmit early warning data to the alarm module. When the data matching unit performs the matching and V ≥ v i In this case, the data processing module creates early warning instruction data and transmits the early warning instruction data to the alarm module.

[0021] As a further solution of the present invention: A storage module is provided in the recognition and early warning system. The storage module is used to store various data in the recognition and early warning system, and at the same time, the storage module is used to synchronously store the early warning instruction data with the cloud.

[0022] Adopting the above technical solutions, compared with the prior art, the beneficial effects of the present invention are as follows:

[0023] 1. The present invention processes the vehicle data in the remote camera in advance through a data processing module, then caches the processed vehicle data using a data cache unit, analyzes which vehicle driving data affects pedestrians when passing through an intersection using the data processing module, and then matches the driving data with the data in the data cache unit. Furthermore, when the data matching is successful, the alarm module gives an alarm through a buzzer, achieving an improvement in the reaction efficiency of the recognition and warning system;

[0024] 2. The present invention separately retrieves the license plate feature data of vehicles in the intersection camera and the remote camera through a vehicle matching unit, and analyzes the license plate feature data in the remote camera through a vehicle recognition unit. When the vehicle moves from the field of view captured by the remote camera to the field of view captured by the intersection camera, the vehicle matching unit quickly obtains vehicle data based on the vehicle license plate feature data, thereby facilitating the recognition and warning system to quickly respond to vehicle data when the vehicle enters the intersection;

[0025] 3. The present invention analyzes vehicle data through a data processing module, and the data processing module enables the remote camera to obtain the vehicle data in the remote camera, facilitating the acquisition of the overall vehicle state data in advance when the vehicle enters the vicinity of the intersection. The risk assessment module analyzes human behavior, and then based on the human behavior analysis, obtains the range data where the vehicle needs to stop, and thus can obtain the danger possibility of pedestrians when passing through the intersection, and then determines whether the vehicle speed will affect the danger of pedestrians passing through the intersection;

[0026] 4. The present invention judges risk indicators through data processing, and then analyzes the danger of pedestrians based on the visual blind areas of pedestrians and vehicles, vehicle speed, relative speed, etc. Then, the data cache unit and the risk indicator data are matched through a data matching unit, and further determines whether the alarm module needs to give an alarm, improving the intelligent effect of the recognition and warning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flowchart of the recognition and warning system in an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0029] Embodiment 1

[0030] A vehicle and pedestrian recognition and warning system based on intersection images. Traditional intersection safety measures mainly rely on traffic lights and markings, but these measures often have limitations in complex traffic environments. Traffic lights can only provide fixed signal indications and cannot adapt to dynamic traffic conditions in real time. Markings may also be overlooked due to obstructed vision or driver negligence. To improve intersection safety, the vehicle and pedestrian recognition and warning system uses advanced imaging technology and intelligent algorithms to monitor and identify vehicles and pedestrians at intersections in real time. Through cameras installed at intersections, the system can obtain real-time images of the intersection and use image processing and pattern recognition technologies to quickly and accurately detect information such as the positions and motion states of vehicles and pedestrians. When the system detects potential dangerous situations, it can quickly issue warning signals to remind drivers and pedestrians to take corresponding measures to avoid traffic accidents. However, to achieve effective warning, the reaction speed of the system is crucial. If the reaction speed of the system is too slow, it may not be able to issue warning signals in time, resulting in dangerous situations not being avoided in time.

[0031] Please refer to the appendix Figure 1 , the present invention relates to a vehicle and pedestrian recognition and warning system based on intersection images. The recognition and warning system includes an image acquisition module, an image recognition module, a data processing module, and an alarm module;

[0032] The image acquisition module includes a remote camera and an intersection camera. The remote camera is used to capture data from a distance on the road, and the intersection camera takes pictures on both sides of the intersection and transmits the data captured by the image acquisition module to the image recognition module;

[0033] The image recognition module includes a vehicle recognition unit and a pedestrian recognition unit. The intersection data captured by the remote camera is transmitted to the vehicle recognition unit. The vehicle recognition unit is used to identify the vehicle data captured by the remote camera and the intersection camera, and transmits the vehicle data captured by the remote camera to the data processing module. The intersection camera transmits the captured data to the pedestrian recognition unit, and the pedestrian recognition unit is used to identify the pedestrian feature data in the captured data;

[0034] The data processing module includes a data cache unit, a pedestrian feature unit, and a data matching unit. The data processing module is used to calculate the vehicle driving status data captured by a remote camera and transmit the vehicle driving status data to the data cache unit. The pedestrian feature unit is used to identify the pedestrian data captured by an intersection camera, analyze the pedestrian data through the data processing module, and based on the current pedestrian data status, analyze the vehicle driving data of dangerous pedestrians, and transmit the analyzed vehicle driving data to the data matching unit. The data matching unit retrieves the vehicle driving data and matches it with the vehicle data in the data cache unit. When the vehicle data matches the data processing module, the data processing module creates alarm instruction data and transmits the alarm instruction data to the alarm module. When the vehicle data does not match the data processing module, the data processing module transmits the processed data to the cloud;

[0035] After receiving the alarm instruction data, the alarm module issues an alarm through a buzzer.

[0036] Specific working process: The image acquisition module is used to obtain the vehicles and human figures at the intersection, and then the image recognition module is used to extract the data in the image recognition module. The vehicle recognition unit and the pedestrian recognition unit are used to perform recognition processing for different cameras respectively. Finally, the data processing module is used to recognize the vehicle data, and then the data cache unit is used to cache the vehicle data. The pedestrian feature unit is used to analyze the status of the human figures at the intersection, and based on the status of the human figures, analyze at what vehicle speed it will affect pedestrian safety. Furthermore, the data matching unit retrieves the data in the data cache unit and matches it with the analyzed result, and then judges whether the alarm module needs to perform alarm processing.

[0037] Furthermore, the vehicle data in the remote camera is processed in advance by the data processing module, and then the processed vehicle data is cached by the data cache unit. The data processing module is used to analyze which vehicle driving data affects pedestrians when passing through the intersection, and then the driving data is matched with the data in the data cache unit. Furthermore, when the data matching is successful, the alarm module issues an alarm through a buzzer, achieving the improvement of the reaction efficiency of the recognition and warning system.

[0038] Embodiment 2:

[0039] Based on Embodiment 1, please refer to the appendix Figure 1As shown in the figure, the pedestrian recognition unit is used to recognize the human figures in the intersection camera. After recognizing the human figures in the intersection camera, it transmits the data captured by the intersection camera to the vehicle recognition unit. The data cache unit is used to store the data processed by the vehicle recognition unit, and the vehicle recognition unit is used to process the vehicle data captured by the remote camera and the intersection camera. A vehicle matching unit is set in the image recognition module. After the vehicle recognition unit recognizes the vehicle data captured by the remote camera, it transmits the recognized data to the vehicle matching unit. The vehicle matching unit retrieves the captured data of the intersection camera and matches the vehicle data of the intersection camera with the vehicle data of the remote camera. Then, as the vehicle moves from the current camera view to the next camera view, the intersection camera extracts and obtains the vehicle data. The data cache unit obtains the traffic light data through the intersection camera and uses the changing time of the traffic lights to clean the cached data. After the vehicle driving data is cached in the data cache unit, after the traffic lights are orderly switched three to four times, specific data in the data cache unit is cleared.

[0040] Specific working process: The pedestrian recognition unit recognizes the human figures in the intersection camera to determine information such as the position and movement state of the pedestrians; the vehicle recognition unit receives the vehicle data captured by the intersection camera and the remote camera, and processes the vehicle data, including extracting the features of the vehicle, such as vehicle type, color, license plate, etc. For the vehicle data captured by the remote camera, after recognition, it is transmitted to the vehicle matching unit; after receiving the vehicle data recognized by the remote camera, the vehicle matching unit retrieves the captured data of the intersection camera, matches the vehicle data of the intersection camera with the vehicle data of the remote camera, and determines whether it is the same vehicle moving in different camera views by comparing the features of the vehicle, so as to realize the tracking of the vehicle moving from the current camera view to the next camera view; the data cache unit stores the vehicle data processed by the vehicle recognition unit and the traffic light data obtained through the intersection camera, and uses the changing time of the traffic lights as a trigger condition to clean the cached data. For example, after the vehicle driving data is cached in the data cache unit, when the traffic lights are orderly switched three to four times, specific data in the data cache unit is cleared to release the storage space and ensure the efficient operation of the system.

[0041] Furthermore, the vehicle matching unit retrieves the license plate feature data of the vehicles in the intersection camera and the remote camera respectively, and the vehicle recognition unit analyzes the license plate feature data in the remote camera. When the vehicle moves from the field of view captured by the remote camera to the field of view captured by the intersection camera, the vehicle matching unit quickly obtains the vehicle data according to the vehicle license plate feature data, which is convenient for the vehicle recognition and warning system to quickly respond to the vehicle data when the vehicle enters the intersection.

[0042] Embodiment 3:

[0043] Based on Example 2, please refer to the appendix Figure 1 As shown, the data processing module calculates the average vehicle speed through a formula. The specific formula is as follows:

[0044]

[0045] Among them, V represents the average speed of the vehicle recognized in the remote camera, D represents the distance traveled by the vehicle in the remote camera, T represents the time required for the vehicle to travel the distance, F represents the speed reduction when the vehicle recognized by the data processing module brakes, the data cache unit is used to cache the vehicle data calculated by the data processing module, a risk assessment module is set in the pedestrian feature unit, the pedestrian recognition unit transmits the recognized portrait data to the pedestrian feature unit, and the pedestrian feature unit uses the risk assessment module to analyze the portrait to analyze the data that the current portrait's passing through the intersection and the vehicle's driving speed will affect the pedestrian's safe passage.

[0046] Specific working process: The pedestrian recognition unit transmits the recognized portrait data to the pedestrian feature unit, the risk assessment module in the pedestrian feature unit is activated and prepares to analyze the portrait. The risk assessment module obtains the vehicle-related data calculated by the data processing module, including information such as the average vehicle speed, vehicle travel distance, vehicle travel time, and the speed reduction when the vehicle brakes. The risk assessment module conducts multi-faceted analysis on the portrait, analyzes the position, movement direction and speed of the pedestrian. For example, it determines the states such as whether the pedestrian is waiting at the intersection, crossing the intersection or about to enter the intersection, as well as the walking speed and direction of the pedestrian. Combining the vehicle's driving data, it analyzes the situation where the current portrait's passing through the intersection and the vehicle's driving speed will affect the pedestrian's safe passage, considering factors such as the average vehicle speed, the distance from the intersection, and the angle between the driving direction and the pedestrian's walking direction.

[0047] Furthermore, the data processing module analyzes the vehicle data, and then the data processing module enables the remote camera to obtain the vehicle data in the remote camera, facilitating the acquisition of the overall vehicle state data in advance when the vehicle enters the vicinity of the intersection. The risk assessment module analyzes the portrait behavior, and then based on the portrait behavior, analyzes the range data where the vehicle needs to stop, and then can obtain the risk possibility of the pedestrian when passing through the intersection, and then determines whether the vehicle speed will affect the danger of the pedestrian passing through the intersection.

[0048] Example 4:

[0049] Based on Example 3, please refer to the appendix Figure 1 As shown, the data processing module obtains the risk index data through a formula. The specific formula is as follows:

[0050] R = f1·d + f2·P + f3·v i+f4·Q

[0051] Among them, R represents risk index data, d represents the distance data between the vehicle and the pedestrian, f1 represents the weight coefficient adjusted by the pedestrian's age, P represents the relative speed data between the vehicle and the pedestrian, f2 represents the weight coefficient of the influence of the relative speed between the vehicle and the pedestrian on the pedestrian's danger, v i represents the speed data of the i-th vehicle in the remote camera, f3 represents the vehicle speed weight coefficient in the remote camera, Q represents the area data affected by the vehicle's field of view, f4 represents the weight coefficient due to the influence of the field of view. The data matching unit retrieves the vehicle driving data in the data cache unit for matching. When the data matching unit performs the matching and V < v i In this case, the data processing module does not transmit the early warning data to the alarm module. When the data matching unit performs the matching and V ≥ v i In this case, the data processing module creates early warning instruction data and transmits the early warning instruction data to the alarm module. An identification early warning system is provided with a storage module. The storage module is used to store various data in the identification early warning system, and at the same time, the storage module is used to synchronize and store the early warning instruction data with the cloud.

[0052] Specific working process: Use various sensors and cameras to collect data, including the distance data d between the vehicle and the pedestrian, the relative speed data P between the vehicle and the pedestrian, the speed data vi of the i-th vehicle in the remote camera, and the area data Q affected by the vehicle's field of view. Determine the weight coefficients in different situations, such as the weight coefficient f1 adjusted by the pedestrian's age, the weight coefficient f2 of the influence of the relative speed between the vehicle and the pedestrian on the pedestrian's danger, the vehicle speed weight coefficient f3 in the remote camera, and the weight coefficient f4 due to the influence of the field of view. Calculate the risk index data R according to the formula, considering the distance d between the vehicle and the pedestrian. The closer the distance, the higher the risk. The weight coefficient f1 will be adjusted according to the pedestrian's age. For example, for the elderly and children, the weight may be increased because their actions are relatively slow and their ability to respond to danger may be weak. The relative speed data P between the vehicle and the pedestrian reflects the speed at which the two are approaching. The greater the relative speed, the higher the risk. The weight coefficient f2 reflects the degree of influence of the relative speed on the pedestrian's danger. The speed data vi of the i-th vehicle in the remote camera i is also an important factor. The faster the vehicle speed, the greater the possible danger. The weight coefficient f3 is used to adjust the weight of the vehicle speed in the risk index. The area data Q affected by the vehicle's field of view. If the vehicle blocks the pedestrian's field of view or the pedestrian blocks the vehicle driver's field of view, the risk will increase. The weight coefficient f4 represents the weight due to the influence of the field of view. The data matching unit retrieves the vehicle driving data in the data cache unit for matching, comparing the speed data vi of the i-th vehicle in the remote camera i with a specific speed V. When V < vi When it is, it indicates that the vehicle speed is relatively fast and there are certain risks. However, at this time, the data processing module does not transmit warning data to the warning module. This may be because although the vehicle speed is fast, the risks are still within the acceptable range after considering other factors comprehensively. When V≥v i When it is, the data processing module creates warning instruction data and transmits the warning instruction data to the alarm module. This means that the vehicle speed has exceeded the safety threshold, or after considering other risk factors comprehensively, the system determines that a warning needs to be issued. The storage module in the recognition warning system is used to store various data in the recognition warning system, including the collected original data, calculated risk index data, warning instruction data, etc. At the same time, the storage module synchronously stores the warning instruction data with the cloud for subsequent analysis and query, and can also provide data support for other systems. For example, the traffic management department can use these data for traffic planning and safety assessment.

[0053] Furthermore, the risk index is judged through data processing, and then the danger of pedestrians is analyzed based on the visual blind areas of pedestrians and vehicles, vehicle speed, relative speed, etc. Then, the data caching unit is matched with the risk index data through the data matching unit, and then it is judged whether the alarm module needs to give an alarm, which improves the intelligent effect of the recognition warning system.

[0054] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification only illustrates the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed. The scope of protection claimed by the present invention is defined by the appended claims and their equivalents.

Claims

1. A vehicle and pedestrian recognition and warning system based on intersection images, characterized in that: The described identification and warning system includes an image acquisition module, an image recognition module, a data processing module, and an alarm module; The image acquisition module includes a remote camera and an intersection camera. The remote camera is used to capture data in the distance of the road, and the intersection camera captures both sides of the intersection and transmits the data captured by the image acquisition module to the image recognition module; The image recognition module includes a vehicle recognition unit and a pedestrian recognition unit. The intersection data captured by the remote camera is transmitted to the vehicle recognition unit. The vehicle recognition unit is used to identify the vehicle data captured by the remote camera and the intersection camera, and transmits the vehicle data captured by the remote camera to the data processing module. The intersection camera transmits the captured data to the pedestrian recognition unit, and the pedestrian recognition unit is used to identify the pedestrian feature data in the captured data; The data processing module includes a data cache unit, a pedestrian feature unit, and a data matching unit. The data processing module is used to calculate the vehicle driving state data captured by the remote camera and transmit the vehicle driving state data to the data cache unit. The pedestrian feature unit is used to identify the pedestrian data captured by the intersection camera, analyze the pedestrian data through the data processing module, and based on the current pedestrian data state, analyze the vehicle driving data of dangerous pedestrians and transmit the analyzed vehicle driving data to the data matching unit. The data matching unit retrieves the vehicle driving data and matches it with the vehicle data in the data cache unit. When the vehicle data matches the data processing module, the data processing module creates alarm instruction data and transmits the alarm instruction data to the alarm module. When the vehicle data does not match the data processing module, the data processing module transmits the processed data to the cloud; After receiving the alarm instruction data, the alarm module issues an alarm through a siren.

2. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 1, wherein: The pedestrian recognition unit is used to identify the portraits in the intersection camera. After identifying the portraits in the intersection camera, it transmits the data captured by the intersection camera to the vehicle recognition unit. The data cache unit is used to store the data processed by the vehicle recognition unit, and the vehicle recognition unit is used to process the vehicle data captured by the remote camera and the intersection camera. A vehicle matching unit is set in the image recognition module. After the vehicle recognition unit finishes identifying the vehicle data captured by the remote camera, it transmits the identified data to the vehicle matching unit. The vehicle matching unit retrieves the captured data of the intersection camera and matches the vehicle data of the intersection camera with the vehicle data of the remote camera. Then, as the vehicle moves from the current camera view to the next camera view, the intersection camera extracts and obtains the vehicle data.

3. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 2, wherein: The data cache unit obtains the traffic light data through the intersection camera and clears the cached data using the changing time of the traffic lights. After the vehicle driving data is cached in the data cache unit, after the traffic lights change orderly three to four times, specific data in the data cache unit is cleared.

4. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 2, characterized in that: The data processing module calculates the average vehicle speed through a formula. The specific formula is as follows: Among them, V represents the average speed of the vehicle recognized by the remote camera, D represents the distance traveled by the vehicle in the remote camera, T represents the time required for the vehicle to travel the distance, and F represents the reduced speed when the vehicle brakes recognized by the data processing module.

5. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 4, characterized in that: The data caching unit is used to cache the vehicle data calculated by the data processing module.

6. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 4, characterized in that: A risk assessment module is set in the pedestrian feature unit. The pedestrian recognition unit transmits the recognized portrait data to the pedestrian feature unit, and the pedestrian feature unit uses the risk assessment module to analyze the portrait, analyzing the data that the current portrait and the driving speed of the vehicle will affect the safe passage of pedestrians when passing through the intersection.

7. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 6, characterized in that: The data processing module obtains the risk index data through a formula, and the specific formula is as follows: R = f1·d + f2·P + f3·v i + f4·Q Among them, R represents risk index data, d represents the distance data between the vehicle and the pedestrian, f1 represents the weight coefficient adjusted by the pedestrian's age, P represents the relative speed data between the vehicle and the pedestrian, f2 represents the weight coefficient of the influence of the relative speed between the vehicle and the pedestrian on the pedestrian's danger, v i represents the speed data of the i-th vehicle in the remote camera, f3 represents the vehicle speed weight coefficient in the remote camera, Q represents the area data affected by the vehicle's field of view, and f4 represents the weight coefficient due to the influence of the field of view.

8. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 7, characterized in that: The data matching unit retrieves the vehicle driving data in the data cache unit for matching. When the data matching unit is performing the matching and V < v i in this case, the data processing module does not transmit the early warning data to the alarm module. When the data matching unit is performing the matching and V ≥ v i in this case, the data processing module creates early warning instruction data and transmits the early warning instruction data to the alarm module.

9. The vehicle and pedestrian recognition and warning system based on intersection images according to claim 8, characterized in that: A storage module is set in the recognition and warning system. The storage module is used to store various data in the recognition and warning system, and at the same time, the storage module is used to synchronously store the warning instruction data with the cloud.

Images