WO2021254175A1 - Procédé et système de surveillance de sécurité routière et dispositif informatique - Google Patents

Procédé et système de surveillance de sécurité routière et dispositif informatique Download PDF

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Publication number
WO2021254175A1
WO2021254175A1 PCT/CN2021/098258 CN2021098258W WO2021254175A1 WO 2021254175 A1 WO2021254175 A1 WO 2021254175A1 CN 2021098258 W CN2021098258 W CN 2021098258W WO 2021254175 A1 WO2021254175 A1 WO 2021254175A1
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Prior art keywords
trajectory information
information
road
thrown
attribute
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PCT/CN2021/098258
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English (en)
Chinese (zh)
Inventor
杨阳
冷继南
吕跃强
程林松
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华为技术有限公司
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Publication of WO2021254175A1 publication Critical patent/WO2021254175A1/fr

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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/048—Detecting movement of traffic to be counted or controlled with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors

Definitions

  • the invention relates to the field of computers, and relates to a method, system and computer equipment for road safety monitoring.
  • the present application discloses a road safety monitoring method, computer equipment and system, which can realize the attribute recognition or source location of the scattered objects on the road, and reduce the traffic accidents caused by the scattered objects on the road.
  • this application provides a road safety monitoring method, including:
  • the at least one object includes a spray and/or at least one non-spray; judge the attribute of the spray according to the trajectory information of the at least one object;
  • the accuracy of determining the attributes of the thrown objects can be improved, thereby determining the degree of danger of the throwing objects, and issuing accurate warning information, which can effectively reduce the possibility of traffic accidents caused by the thrown objects.
  • acquiring the trajectory information of at least one object on the road, and judging the attribute of the spray object according to the trajectory information of the at least one object includes:
  • the weight of the thrown object can be accurately judged, and the attribute of the thrown object can be accurately judged, such as whether the material is plastic, paper or metal; through the trajectory information of the non-sprayed object , Such as speed, acceleration, trajectory line, can judge whether the non-sprayed object has evasive behavior against the sprayed object, so as to accurately determine the degree of danger of the sprayed object.
  • obtaining road monitoring information includes: obtaining road monitoring image information through a video monitoring device on the road, and obtaining road monitoring radar information through a radar device.
  • obtaining the trajectory information of at least one object on the road includes:
  • the first trajectory information of at least one object is acquired according to radar information
  • the second trajectory information of at least one object is acquired according to image information
  • the trajectory information of at least one object is obtained by combining the first trajectory information and the second trajectory information.
  • the accuracy of the trajectory information in the image information is higher
  • the accuracy of the trajectory information in the radar information is higher.
  • the method further includes: obtaining the image characteristics of the tossing object according to the image information.
  • the method further includes: judging the attributes of the thrown object according to the image characteristics of the thrown object.
  • Image features such as size and shape, can assist in improving the accuracy of judging the attributes of the sprinkles.
  • the method for judging the attribute of the at least one object sprinkle specifically includes:
  • the characteristic data inventory contains the information of the sprinkles whose attributes have been determined. Through feature comparison, the attributes of the sprinkles can be judged more quickly and accurately.
  • the trajectory information or image feature of the projectile is refreshed into the feature database.
  • Refreshing the characteristic database can continuously enrich the characteristic data of the sprinkles in the characteristic database, and improve the characteristic database through continuous accumulation, so as to achieve the purpose of improving the speed and accuracy of judging the properties of the sprinkles.
  • the attributes of the thrown object include the degree of danger of the thrown object.
  • determining the presence of sprinkles on the road includes:
  • the object in the image information is detected by the optical flow method, the type of the object is recognized, and the object whose type is unknown is determined as a sprinkler.
  • the method further includes:
  • the source of the spray is determined.
  • the trajectory information includes current trajectory information and backward-extended trajectory information of the current trajectory information.
  • the above method can quickly locate the source of the sprays, and the staff can prevent new sprays from appearing on the road and reduce the number of sprays by handling the source of the sprays, thereby reducing the probability of safety accidents.
  • this application provides a road safety monitoring method, including:
  • the above method can quickly locate the source of the sprays, and the staff can prevent new sprays from appearing on the road and reduce the number of sprays by handling the source of the sprays, thereby reducing the probability of safety accidents.
  • acquiring road monitoring information includes: acquiring road monitoring image information through a video monitoring device on the road, and acquiring road monitoring radar information through a radar device.
  • the acquired trajectory information of the projectile on the road includes: obtaining the first trajectory information of the projectile from the radar information, obtaining the second trajectory information of the projectile from the image information, and synthesizing the first trajectory The information and the second trajectory information obtain the trajectory information of the projectile.
  • determining the source of the throwing objects according to the crossover of the trajectory information includes:
  • the spray is from at least one non-spray
  • the non-spray closest to the spray is selected from the at least two sprays as the source of the spray.
  • the trajectory information includes current trajectory information and backward-extended trajectory information of the current trajectory information.
  • the backward extension of the trajectory information supplements the information not obtained by the monitoring equipment, and the more complete trajectory information can improve the accuracy of finding the source of the projectile through the trajectory information.
  • the road safety monitoring method also includes:
  • the attribute of the thrown object is judged.
  • the road safety monitoring method also includes:
  • the image features can assist in judging the attributes of the thrown objects and improve the accuracy of judging the attributes of the thrown objects.
  • the method further includes: judging the attributes of the thrown object according to the image characteristics of the thrown object.
  • this application provides a road safety monitoring system, the system includes: a monitoring device, an attribute detection device, and an alarm device;
  • the detection device is used to obtain road monitoring information and determine that there is a spray on the road; obtain trajectory information of at least one object on the road according to the road monitoring information, and the at least one object includes the spray and/or at least one non-spray;
  • the attribute detection device is used for judging the attribute of the thrown object according to the trajectory information of at least one object;
  • the alarm device is used to issue an alarm according to the properties of the thrown object.
  • the above-mentioned system can quickly locate the properties of the scattered objects, and according to the properties of the scattered objects and the degree of danger, timely safety alarms are issued.
  • the staff can remove the scattered objects from the road in time according to the level of the safety alarms, and reduce the traffic caused by the scattered objects on the road. accident.
  • system further includes: an attribution judging device;
  • the attribution judging device is used to determine the source of the thrown object according to the situation where the trajectory information of the thrown object intersects the trajectory information of at least one non- thrown object.
  • the attribution judging device allows the staff to quickly locate the source of the sprinkles and prevent new sprinkles on the road, reducing the probability of traffic safety accidents.
  • the attribute detection device is used to determine the attribute of the thrown object according to the trajectory information of at least one object, including:
  • the monitoring device includes: video monitoring equipment and radar equipment;
  • the video monitoring equipment obtains road monitoring image information
  • the radar equipment obtains road monitoring radar information.
  • the monitoring device obtains first trajectory information of at least one object according to radar information, obtains second trajectory information of at least one object according to image information, and synthesizes the first trajectory information and the second trajectory information to obtain at least one object Track information.
  • this application provides a road safety monitoring system, which includes: a monitoring device, a belonging judgment device, and an alarm device;
  • the detection device is used to obtain road monitoring information and determine that there is a spray on the road; obtain trajectory information of at least one object on the road according to the road monitoring information, and the at least one object includes the spray and/or at least one non-spray;
  • the attribution judging device is used to determine the source of the thrown object according to the situation where the trajectory information of the thrown object intersects the trajectory information of at least one non-drop object;
  • the alarm device is used to issue an alarm according to the source of the thrown object.
  • the staff can quickly locate the source of the thrown objects on the road, prevent new thrown objects, and effectively reduce the probability of traffic accidents caused by the thrown objects.
  • the system further includes: an attribute detection device;
  • the attribute detection device judges the attribute of the thrown object according to the trajectory information of at least one object.
  • the attribute detection device is used to determine the attribute of the thrown object according to the trajectory information of at least one object, including:
  • the monitoring device includes: video monitoring equipment and radar equipment;
  • the video monitoring equipment obtains road monitoring image information
  • the radar equipment obtains road monitoring radar information.
  • the monitoring device is used to obtain first trajectory information of at least one object according to radar information, obtain second trajectory information of at least one object according to image information, and synthesize the first trajectory information and the second trajectory information to obtain Track information of at least one object.
  • this application provides a computer device for road safety monitoring.
  • the computer device includes a processor and a memory, wherein:
  • Computer instructions are stored in the memory
  • the processor executes computer instructions to make the computer device execute the method of the first aspect and its possible implementations.
  • this application provides a computer device for road safety monitoring.
  • the computer device includes a processor and a memory, wherein:
  • Computer instructions are stored in the memory
  • the processor executes computer instructions to make the computer device execute the method of the second aspect and its possible implementations.
  • the present application provides a computer-readable storage medium that stores computer instructions.
  • the computer instructions in the computer-readable storage medium are executed by a computer device, the computer device executes claim 1 13.
  • this application provides a computer-readable storage medium that stores computer instructions.
  • the computer instructions in the computer-readable storage medium are executed by a computer device, the computer device executes claim 14- 21.
  • the method according to any one of the claims, or the computer equipment can realize the function of the device in the system of the fourth aspect and its possible implementation manners.
  • FIG. 1 is a schematic diagram of a road spraying scene related to an embodiment of the application
  • Figure 2 is a schematic diagram of a system according to an embodiment of the application.
  • 3A is a schematic diagram of another system according to an embodiment of the application.
  • FIG. 3B is a schematic diagram of another system according to an embodiment of the application.
  • FIG. 4 is a schematic diagram of the functions of the monitoring device according to an embodiment of the application.
  • FIG. 5 is a flowchart of a processing method of a monitoring device according to an embodiment of the application.
  • FIG. 6 is a schematic diagram of the function of the attribute detection device according to an embodiment of the application.
  • FIG. 7 is a flowchart of a processing method of an attribute detection device according to an embodiment of the application.
  • FIG. 8 is a flowchart of a processing method of an attribution judging apparatus according to an embodiment of the application.
  • FIG. 9A is a schematic diagram of a scenario for determining the ownership of a thrown object according to an embodiment of the application.
  • FIG. 9B is a schematic diagram of another scenario for determining the attribution of sprays according to an embodiment of the application.
  • FIG. 10 is a schematic diagram of the function of an alarm device according to an embodiment of the application.
  • FIG. 11 is a schematic diagram of hardware of a computer device according to an embodiment of the application.
  • Figure 1 shows a scene diagram, which includes: two trucks 106 and 110, a car 102, a sprinkler 104, and a video surveillance device 112. Wherein, the truck 106 carries goods, and the goods are thrown onto the road as a spray 104. At this time, when the car 102 that is driving fast on the road encounters a sudden spray 104, if it is not avoided in time, it is easy to cause a traffic accident, and the spray 104 becomes a major hidden danger to road safety.
  • the characteristic image is mainly obtained from the video monitoring device 112, and then the sprinkle 104 is identified from the characteristic image.
  • One of the identification technical solutions is to use the average pixel value method by comparing the sprinkle 104 in the characteristic image.
  • the average pixel value and the average pixel value of the road identify the spray 104, but this method can only identify whether there is a spray 104 on the road, and cannot identify the type and degree of danger of the spray 104, nor can it determine the source of the spray 104.
  • Another technical solution is to use the video surveillance equipment 112 to obtain the image information on the road, and use the image recognition method to capture the sprinkles 104, but only the marked sprinkles in the database can be identified, and it is impossible to identify all the sprinkles.
  • the 104 types of objects and their corresponding degree of danger cannot improve the identification and intensive reading of the degree of danger of thrown objects.
  • the system 200 includes a monitoring device 202, an attribute detection device 204, an attribution judgment device 206, and an alarm device 208.
  • the monitoring device 202 obtains road information, which may include video equipment and radar equipment.
  • the video information and image information on the road can be obtained through the video equipment, and the radar information on the road can be obtained through the radar equipment.
  • the first trajectory information of at least one object on the road can be obtained from the radar information.
  • the at least one object includes sprays on the road and other objects.
  • the other objects can be collectively referred to as non-sprays and non-sprays, for example, including driving on the road. Of motor vehicles, non-motor vehicles, and pedestrians.
  • the image information can also obtain the second trajectory information of at least one object, and the trajectory information of the at least one object can be obtained by combining the first trajectory information and the second trajectory information.
  • the attribute detection device 204 is used to detect the attribute of at least one object, including any one or a combination of size, risk level, type, and the like. Specifically, image characteristics and trajectory information of at least one object are obtained through analysis and processing through image information and trajectory information of at least one object.
  • the image features include: color histogram, color set, color moment, color aggregation vector, color correlation graph, texture feature, SIFT (Scale-invariant feature transform) feature, etc.
  • the trajectory information includes: speed (including size and direction), acceleration, stopover time on the trajectory, etc.
  • the attribution judging device 206 obtains the trajectory information of the toss and the non-toss, and the trajectory information includes the currently obtained trajectory information and its reverse extension line. Judge the attribution source of the attribution of the attribution of the attribution of the attribution of the attribution of the attribution of the attribution of the attribution to the attribution of the attribution of the attribution of the attribution of the attribution of the attribution and the discussion based on the intersection of the trajectory of the attribution of the attribution at the same time (the first moment).
  • the warning device 208 obtains the attributes of the thrown objects and the source of the thrown objects, and sends out different levels of safety alarms according to the degree of danger of the thrown objects.
  • the degree of danger is high, the safety alarm is It is red; if the degree of danger is medium, the safety alarm is yellow; if the degree of danger is low, the safety alarm is green.
  • the staff will react differently. For example, when the degree of danger is high, they will immediately intervene manually to deal with the road spills urgently. If the degree of danger is low, the staff can take care of it regularly.
  • the warning device 208 will report the source of the spillage to the staff. For example, if the spillage comes from a truck on the road, the staff will control the truck, determine the responsibility, and modify the box conditions.
  • the system 300 includes a monitoring device 202, an attribute detection device 204, and an alarm device 208.
  • the working principles of the system 300 and the system 200 are similar and will not be repeated here.
  • the monitoring device 202 obtains the monitoring information on the road, and the attribute detection device 204 judges the attributes of the sprinkles based on the monitoring information.
  • the alarm device 208 issues different levels of safety alarms according to the attributes of the sprinkles and the degree of danger of the sprinkles. The source of the material is reported to the staff.
  • the system 310 includes a monitoring device 202, an attribution judgment device 206, and an alarm device 208.
  • the working principles of the system 310 and the system 200 are similar, and will not be repeated here.
  • the monitoring device 202 obtains the monitoring information on the road
  • the attribution judging device 206 judges the source of the scattered objects based on the monitoring information
  • the alarm device 208 issues a safety alarm according to the source of the scattered objects
  • the staff promptly deal with the scattered objects on the road according to the safety alarms. And cut off the source of the sprinkles to prevent additional safety hazards caused by new sprinkles.
  • the monitoring device 202 includes a monitoring device 402 and an information processing module 408.
  • the monitoring device 402 includes a video monitoring device 404 and a radar device 406, the video information on the road is obtained from the video monitoring device 404, and the radar information on the road is obtained from the radar device 406.
  • the information processing module 408 obtains trajectory information 410 and image information 412 of at least one formation according to the video information and radar information, and completes the tossing object identification 414 from the at least one object according to the above information.
  • FIG. 5 introduces the processing flow of the monitoring device 202 in detail.
  • the video information is parsed into video frames to obtain continuous frames of image information.
  • the difference between the image information of the consecutive frames before and after is compared, the object whose position has changed is identified, which is called set A, and the target detection algorithm based on deep learning is used to identify the object in set A
  • set A the difference between the image information of the consecutive frames before and after is compared, the object whose position has changed is identified, which is called set A, and the target detection algorithm based on deep learning is used to identify the object in set A
  • set B Known types of objects such as motor vehicles, non-motor vehicles, and pedestrians.
  • the objects in the set A are removed from the objects in the set B, and then the redundant objects are the sprinkles.
  • the pixel point of at least one object in the image information is converted from the pixel coordinates to the world coordinates to generate the trajectory information of the at least one object, which is called second trajectory information.
  • the radar device 406 directly detects and tracks at least one object, and obtains radar information of the at least one object.
  • the pixel points of the detected at least one object in the radar information are converted from polar coordinates to world coordinates to generate the trajectory information of the at least one object, the first trajectory information.
  • steps 502-506 and steps 510-512 are not limited. Steps 502-506 can be executed before steps 510-512, or steps 510-512 can be executed before steps 502-506. It can also be executed at the same time.
  • the first trajectory information and the second trajectory information are integrated, and finally the trajectory information of at least one object is generated.
  • the specific method is to first establish a one-to-one correspondence between at least one target in the radar information and at least one target in the image information; then, if the accuracy of the image information is higher at the near end, then the second The trajectory information is used as the trajectory information of at least one object of the target.
  • At least one object of the target in the image information is tracked and lost, it is compensated by the first trajectory information of the target at least one object in the corresponding radar information, as the trajectory of the target at least one object Information; if the radar information has a high accuracy rate at the remote end, the first trajectory information of the target at least one object in the radar information is used as the trajectory information of the target at least one object.
  • the obtained image information and trajectory information of at least one object are transferred to the attribute detection device.
  • FIG. 6 introduces the attribute detection device 204 in detail.
  • the attribute detection device 204 includes an attribute judgment module 602 and a feature database 610 of the sprinkler.
  • the attribute judgment 602 of the toss includes the image feature judgment 604 of the toss, the trajectory information judgment 608 of the toss, and the attribute judgment 606 based on the behavior of the surrounding vehicles.
  • the feature database 610 includes an image feature table 614 and a trajectory information table 612.
  • the toss attribute judgment module 602 can determine the attributes of the toss based on the image characteristics, trajectory information, and the behavior of vehicles around the toss, or it can also determine the attributes of the toss based on the image features, trajectory information, and behavior of vehicles around the toss. Any combination can be used to judge the attributes, degree of danger, etc. of the projectile.
  • Figure 7 explains in detail the flow of the attribute detection device.
  • the attribute detection device 204 first obtains the image characteristics from the image information of at least one object, and obtains the trajectory information from the trajectory information.
  • At least one of the objects includes: sprinkles, vehicles and pedestrians around the sprinkles.
  • the attribute detection device 204 compares the obtained image feature and trajectory information of the thrown object with the data in the feature database 610.
  • the image feature table 614 and the trajectory information table 612 in the feature database 610 save the marked The attributes of the object, and the corresponding trajectory information and image characteristics.
  • the image feature and/or trajectory information of the projectile when the image feature and/or trajectory information of the projectile is in the feature database 610, the image feature and/or trajectory information of the object can be corresponded, for example, the similarity can be higher than a threshold, then the attributes of the object are returned Judge 602 the attributes of the drop.
  • the process S708 obtain the trajectory information of the vehicles around the spray during a certain period of time before and after the stationary time of the spray, and compare the trajectory information of the vehicle when there is the spray and the trajectory information of the vehicle when there is no such spray. difference between.
  • the definition of the surrounding area mentioned here in a possible implementation manner, can include the lane where the spatter is located, and the lanes on the left and right sides.
  • a threshold is set based on the distance between the surrounding vehicles and the scattered objects to filter out the trajectory information of some invalid surrounding vehicles.
  • the lane where the scattered objects are located can be taken as well as the scattered objects Lanes on the left and right sides of the lane. The trajectory information of vehicles exceeding this distance range can be ignored.
  • the process S712 first calculate the similarity of the trajectory information of the surrounding vehicles in the vicinity of the spray and then make a judgment. If the similarity is less than a threshold, it is proved that the surrounding vehicles have appeared due to the presence of the spray. Changes in the trajectory and avoidance behavior indicate that the thrown object is dangerous. If the similarity is greater than this threshold, it proves that the surrounding vehicles have not evaded behavior, and the throwing objects are not dangerous.
  • the image feature and trajectory information of the thrown object are bound with the attribute and the degree of danger of the thrown object, and then updated to the feature database for future
  • the system can directly determine the attribute of the sprinkler, and the degree of danger is high.
  • the attribute of the judged toss is obtained, and the attributes may include: the size, the degree of danger, and the type of the toss.
  • FIG. 8 introduces the processing flow of the attribution judging device 206 in detail.
  • At least one of the objects includes sprays and non-sprays, and non-sprays include motor vehicles, non-motor vehicles, and pedestrians.
  • the process S802 first perform a reverse prediction based on the trajectory information of the projectile to obtain the reverse extended trajectory of the projectile trajectory.
  • the current trajectory 908 of the projectile 912 is the part shown by the solid line
  • 904 is the current trajectory
  • the reverse extension line of 908 is represented by a dashed line
  • the complete trajectory of the projectile is represented by the solid line part of 908 and the dashed line part of 904.
  • the trajectory information of the sprinkler is composed of the current trajectory information and the reverse extended trajectory information.
  • process S806 it is judged how many intersections there are at the same time. If there are none, the process jumps directly to the process S814 to output the attribution relationship of the sprinkles. At this time, the attribution relationship is displayed as unknown. If there is an intersection, the process jumps to process S808.
  • the attribute of the thrown object is used to filter out the impossible attribution relationship.
  • FIG. 9B there are three non-sprayers: truck 922, truck 920 and bicycle 940, one sprayer 936, one bicycle trajectory 940, two truck trajectories 940 and 924, and sprayer trajectories 934 and 928. Three intersections 932, 930, and 938 are generated at the same time. Therefore, the drop 936 may belong to the bicycle 940, the truck 920, or the truck 922. However, based on the properties of the sprinkler 936, such as its size, it can be judged that the sprinkler 936 cannot come from the bicycle 940. After eliminating the impossible attribution relationship of the sprinkles, jump to the next process S812.
  • the motor vehicle/non-motor vehicle/person whose starting point and the intersection point are closest is selected as the attribution target.
  • the detected starting point of the spray 936 is the starting point of the current trajectory 934 of the spray 936.
  • the straight line distance from the starting point to the intersection 930 is shorter than the straight line distance to the intersection 938. Therefore, the spray 936 Attribution is truck 922 instead of truck 920.
  • the process S814 outputs the attribution relationship of the sprinkles to the alarm device 208.
  • the warning device 208 includes three sub-modules: a hazard display 1002, a belonging vehicle display 1004, and a manual intervention warning 1006. Firstly, judge the danger of the spray based on the properties of the spray, for example: the spray is large, the spray is heavy, and the vehicles around the spray have evasive behavior. If the risk of the spray is high, then the danger display 1002 is dangerous. High sex. When the hazard is displayed, it is necessary to find the source of the spray immediately to prevent more sprays from appearing on the road.
  • the vehicle display module 1004 is assigned To present the relevant information of the vehicle that the spatter belongs to, such as the license plate of the vehicle, the type of the vehicle, and so on.
  • the manual intervention warning 1006 needs to complete two things. The first is the handling of the spilled objects. When the danger is high, an alarm is required to prompt manual intervention to remove the spilled objects from the road. Then there is the processing of the source of the spray.
  • an alarm is required to prompt manual intervention, such as allowing the staff to find the motor vehicle/non-motor vehicle/pedestrian that generated the spray in time for processing; or through traffic
  • the system queries the phone number of the driver of the vehicle license plate, and informs the driver to stop and deal with it through the phone to prevent the generation of new spills.
  • this system will help find the responsible party and assist in the determination of liability.
  • manual intervention alarm 1006 reminds the staff to deal with the spills on the road in time according to the danger of the spilled objects.
  • the risk is high, the staff needs to deal with it immediately. If the risk is low, you can let The staff handles it regularly.
  • manual intervention alarm 1006 cuts off the source of the sprinkles according to the vehicle ownership of the sprinkles to prevent additional road safety hazards caused by the new sprinkles.
  • the methods of manual intervention include: for example, let the staff find the machine that generates the sprinkles in time. Motor vehicles/non-motor vehicles/pedestrians, to deal with; or through the traffic system, check the phone number of the driver of the vehicle license plate, and inform the driver to stop and deal with it through the phone to prevent the generation of new sprays.
  • this system will help find the responsible party and assist in the determination of liability.
  • the present application also provides a computer device 1100 as shown in FIG. 11, including: a processor 1102, a memory 1104, a communication interface 1106, and a communication bus 1108.
  • the processor 1102 in the computer device 1100 reads a set of computer instructions stored in the memory 1104 to execute the aforementioned road safety monitoring method, and realize the function of any device of any one of the system 200, the system 300, and the system 310.
  • the video monitoring equipment included in the monitoring device may be a smart camera with a certain computing capability.
  • the functions implemented by the information processing module 408 can be completed by the monitoring device 202 or by the attribute detection device 204.
  • the functions implemented by the alarm device 208, the functions implemented by the attribute detection device 204, and the functions implemented by the attribution judgment device 206 may be implemented by a computer device 1100.
  • the disclosed system, device, and method can be implemented in other ways.
  • the device embodiments described above are merely illustrative.
  • the division of the modules is only a logical function division, and there may be other divisions during implementation.
  • multiple modules or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication link may be indirect coupling or communication link through some interfaces, devices or modules, and may be in electrical, mechanical or other forms.
  • the modules described as separate components may or may not be physically separated, and the components displayed as modules may or may not be physical modules, may be located in one place, or may also be distributed to multiple network modules. Some or all of the modules can be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist alone physically, or two or more modules may be integrated into one module.
  • the above-mentioned integrated modules can be implemented in the form of hardware, or in the form of hardware plus software functional modules.
  • the above-mentioned integrated module implemented in the form of a software function module may be stored in a computer readable storage medium.
  • the above-mentioned software function module is stored in a storage medium and includes a number of instructions to make a computer device (which may be a personal computer, a server, or a network device, etc.) execute part of the steps of the method described in each embodiment of the present invention.
  • the aforementioned storage medium may be a readable non-volatile storage medium, including: mobile hard disk, read-only memory (English: Read-Only Memory, ROM for short), random access memory (English: Random Access Memory, for short)

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  • Traffic Control Systems (AREA)

Abstract

La présente demande divulgue un procédé et un système de surveillance de sécurité routière et un dispositif informatique, permettant d'obtenir une reconnaissance d'attribut ou une localisation de source d'un objet projeté sur une route, de fournir une alarme de sécurité routière précise et de réduire les accidents de la circulation sur la route provoqués par l'objet projeté. Le procédé de surveillance de sécurité routière consiste : à acquérir des informations de surveillance de route et à déterminer s'il existe un objet projeté sur une route ; à acquérir des informations de trajectoire d'au moins un objet sur la route en fonction des informations de surveillance de route ; à déterminer l'attribut de l'objet projeté en fonction des informations de trajectoire du ou des objets ; et à émettre une alarme en fonction de l'attribut de l'objet projeté, le ou les objets comprenant l'objet projeté et/ou un objet non projeté. Le procédé de la présente demande peut améliorer la précision de détection d'attribut de l'objet projeté, et un travailleur peut retirer l'objet projeté à temps en fonction d'informations d'alarme, de façon à réduire les accidents de la circulation.
PCT/CN2021/098258 2020-06-17 2021-06-04 Procédé et système de surveillance de sécurité routière et dispositif informatique WO2021254175A1 (fr)

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