A method and device for managing important road section monitoring equipment

Abstract

The present invention is applicable to the field of intelligent transportation, and provides a method and device for managing monitoring equipment of an important road section. In this embodiment, a target vehicle with a small number of lane changes is determined by the monitoring equipment of the important road section, and then a monitoring device deployed at the entrance and exit of the important road section takes a picture of the target vehicle when entering and exiting the important road section, so as to determine whether an accident occurs in the important road section and issue an alarm at the entrance of the important road section. This solves the problem that when an accident occurs without installing monitoring equipment, it cannot be discovered and alarmed in time, which makes secondary accidents prone to occur.

Description

Technical Field

[0001] The present invention belongs to the field of intelligent transportation, and in particular relates to a method and device for managing important road section monitoring equipment. Background Art

[0002] A tunnel is an artificially constructed underground passage, usually used to solve problems in transportation, transportation and communication, allowing vehicles and pedestrians to pass under mountains, water bodies, cities or other obstacles, which helps to reduce traffic congestion, shorten travel time and improve traffic circulation.

[0003] Due to the limited coverage of monitoring equipment, it is not possible to monitor the entire road section in the tunnel. In addition, due to the high cost of installing monitoring equipment in the tunnel, some tunnels do not have monitoring equipment installed. Therefore, when an accident occurs in the tunnel, it cannot be discovered by road maintenance personnel in a timely manner, resulting in congestion in the tunnel and even a secondary accident. Therefore, it is particularly important to detect tunnel accidents in a timely manner and issue alarms at the tunnel entrance.

[0004] In addition, important sections of highways generally include high-speed off-ramps, sharp turns, and other sections. These sections are similar to tunnel sections and require speed reduction. If vehicles change lanes at high speeds, accidents are likely to occur. These scenarios have the same problems as tunnels. It is necessary to track the driving behavior data of vehicles on the road in advance, and judge whether an accident will occur in important sections in advance based on the lane change of vehicles, and issue early warnings for vehicles. However, installing monitoring equipment at intervals on important sections has high operating and maintenance costs. Summary of the invention

[0005] Therefore, the present application provides a method and device for managing important road section monitoring equipment, which is used to solve the problem of how to timely discover accidents in important road sections and issue alarms in important road sections.

[0006] The first object of the present invention is achieved in this way:

[0007] A method for managing monitoring equipment of an important road section, characterized in that it is applied to an intelligent transportation system, wherein the intelligent transportation system comprises a first monitoring device deployed outside the important road section, and a second monitoring device deployed at an entrance and exit of the important road section, wherein the second monitoring device comprises an alarm indicator light, and the method comprises:

[0008] Acquire a plurality of vehicle driving pictures taken by the first monitoring device, determine the number of times the vehicle changes its driving lane through the vehicle driving pictures, and determine a vehicle whose number is less than a threshold as a target vehicle, wherein the vehicle driving picture includes vehicle information and shooting time;

[0009] Obtaining a picture of an important road section entrance including the target vehicle taken by a second monitoring device at the important road section entrance, and obtaining a picture of an important road section exit including the target vehicle taken by a second monitoring device at the important road section exit;

[0010] Determine whether an accident occurs in an important road section through the important road section entrance picture of the target vehicle and the important road section exit picture of the target vehicle. If confirmed, send a command to the second monitoring device to turn on the alarm indicator light of the second monitoring device.

[0011] Another object of the present invention is to provide an important road section monitoring equipment management device, which is applied to an intelligent transportation system, wherein the intelligent transportation system comprises a first monitoring device deployed outside the important road section, and a second monitoring device deployed at the entrance and exit of the important road section, wherein the second monitoring device comprises an alarm indicator light, and the device comprises:

[0012] A target vehicle determination unit is used to obtain a plurality of vehicle driving pictures taken by the first monitoring device, determine the number of times the vehicle changes its driving lane through the vehicle driving pictures, and determine the vehicle whose number is less than a threshold as a target vehicle, wherein the vehicle driving picture includes vehicle information and shooting time;

[0013] A picture acquisition unit, used for acquiring a picture of an important road section entrance including the target vehicle taken by a second monitoring device at the important road section entrance, and acquiring a picture of an important road section exit including the target vehicle taken by a second monitoring device at the important road section exit;

[0014] An accident determination unit is used to determine whether an accident occurs in an important road section through an important road section entrance picture of the target vehicle and an important road section exit picture of the target vehicle. If determined, a command is sent to the second monitoring device to enable the second monitoring device to turn on an alarm indicator light.

[0015] Optionally, the target vehicle determination unit determines the number of times the vehicle changes its driving lane through the vehicle driving picture, including:

[0016] Obtaining N vehicle driving pictures of the same vehicle through the vehicle information, and sorting the multiple vehicle driving pictures according to shooting time, where N>1;

[0017] Divide the sorted N vehicle driving pictures into N-1 picture groups, where each picture group includes two adjacent vehicle driving pictures;

[0018] It is determined whether the driving lane of the vehicle in two vehicle driving pictures in the picture group is consistent, and the number of inconsistent picture groups is determined as the number of times the vehicle changes the driving lane.

[0019] Optionally, the accident determination unit determines whether an accident occurs in an important road section through an important road section entrance picture of the target vehicle and an important road section exit picture of the target vehicle, including:

[0020] Determine the lane of the target vehicle when entering the important road section through the important road section entrance picture of the target vehicle, and determine the lane of the target vehicle when exiting the important road section through the important road section exit picture of the target vehicle, and when the lane when entering the important road section is different from the lane when exiting the important road section, it is determined that an accident has occurred in the important road section; or,

[0021] When the difference between the shooting time of the important road section entrance picture of the target vehicle and the shooting time of the important road section exit picture of the target vehicle exceeds a threshold, it is determined that an accident occurs in the important road section.

[0022] Optionally, the accident determination unit determines whether an accident occurs in an important road section through an important road section entrance picture of the target vehicle and an important road section exit picture of the target vehicle, including:

[0023] Determine the lane of the target vehicle when it enters the important road section through the important road section entrance picture of the target vehicle, determine the lane of the target vehicle when it exits the important road section through the important road section exit picture of the target vehicle, and mark the target vehicle when the lane when entering the important road section is different from the lane when exiting the important road section;

[0024] When the number of marked target vehicles exceeds a threshold within a preset time period, it is determined that an accident occurs in the important road section.

[0025] Optionally, the vehicle information includes a license plate number of the vehicle, and the device further includes:

[0026] A comparison unit is used to cut the unrecognizable license plate number into a single character image when there is an unrecognizable license plate number in the image of the entrance and exit of the important road section taken by the second monitoring device, and compare the single character image with the single character image cut from the license plate number of the target vehicle to determine the single character image similarity value;

[0027] An initial matrix is ​​constructed by using the single character image cut from the single character image, the single character image cut from the license plate number of the target vehicle, and the similarity value. A dynamic programming algorithm is used to traverse the initial matrix to determine the license plate number similarity value between the unrecognizable license plate number and the license plate number of the target vehicle. When the license plate number similarity value exceeds a set threshold, the vehicle with the unrecognizable license plate number is determined to be the target vehicle.

[0028] It can be seen from the above scheme that for important sections where monitoring equipment is not installed, including exit ramps of highways, entrances and exits of service areas, tunnels, and sharp turns, monitoring equipment on important sections such as sections outside tunnels can be used to identify target vehicles with fewer lane changes, and then monitoring equipment deployed at the entrances and exits of important sections can be used to take pictures of the target vehicle entering and exiting the important sections, thereby determining whether an accident has occurred in the important section, such as a tunnel, and issuing an alarm at the entrance of the important section. This solves the problem that accidents in important sections where monitoring equipment is not installed, such as tunnels, cannot be discovered in time and an alarm cannot be issued.

[0029] Furthermore, when the license plate number of a vehicle cannot be identified in the pictures taken by monitoring equipment at important sections of road, such as tunnel entrances, and it is impossible to determine whether it is the target vehicle, the target vehicle can be determined by comparing the similarity of the license plate numbers, thereby avoiding the problem of being unable to determine the target vehicle due to poor lighting caused by rain or fog, which in turn affects the judgment of tunnel accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The accompanying drawings illustrate exemplary embodiments of the present disclosure and together with the description serve to explain the principles of the present disclosure. These drawings are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this specification.

[0031] Figure 1 A flow chart of a tunnel entrance monitoring equipment management method provided in an embodiment of the present application;

[0032] Figure 2 This is a diagram of the device structure provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0034] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in the present disclosure may be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0035] The specific implementation of the present invention is described in detail below in conjunction with specific embodiments.

[0036] This embodiment is described by taking a tunnel as an important road section scenario.

[0037] like Figure 1As shown, it is a flow chart of a tunnel entrance monitoring device management method provided by an embodiment of the present invention, which is applied to an intelligent transportation system, the intelligent transportation system includes a first monitoring device deployed outside the tunnel, and a second monitoring device deployed at the entrance and exit of the tunnel, the second monitoring device includes an alarm indicator light, and the process may include the following steps:

[0038] Step S101, obtaining a plurality of vehicle driving pictures taken by a first monitoring device, determining the number of times a vehicle changes its driving lane through the vehicle driving pictures, and determining a vehicle whose number of times is less than a threshold as a target vehicle.

[0039] In this embodiment, in order to obtain the vehicle lane change data, the above-mentioned vehicle driving picture includes vehicle information and shooting time. The first monitoring device can be a camera deployed at a highway checkpoint, a toll station entrance, an exit, or a gantry, and the camera monitors a fixed area on the road. For roads with less traffic, the camera can capture when the vehicle passes through the fixed area monitored by the camera, thereby generating the above-mentioned vehicle driving picture. For areas with heavy traffic, the camera can capture the monitored fixed area at fixed intervals, thereby generating the above-mentioned vehicle driving picture.

[0040] In another embodiment, the target vehicle can also be determined by obtaining the safe driving history data at the entrances and exits of important road sections, and obtaining vehicles that enter and exit important road sections with few lane changes and whose driving speeds meet speed limit standards, thereby judging that the driver of the target vehicle is a safe driver and thus determining it as the target vehicle.

[0041] In this embodiment, the number of times the vehicle changes lanes can be determined by the number of times the vehicle crosses the lane line. When the vehicle in the vehicle driving picture covers the lane line, or the middle area of ​​the vehicle covers the lane line, it can be estimated that the vehicle is about to change lanes.

[0042] In another embodiment, determining the number of times the vehicle changes lanes through the vehicle driving picture includes:

[0043] Obtaining N vehicle driving pictures of the same vehicle through the vehicle information, and sorting the multiple vehicle driving pictures according to shooting time, where N>1;

[0044] Divide the sorted N vehicle driving pictures into N-1 picture groups, where each picture group includes two adjacent vehicle driving pictures;

[0045] It is determined whether the driving lane of the vehicle in two vehicle driving pictures in the picture group is consistent, and the number of inconsistent picture groups is determined as the number of times the vehicle changes the driving lane.

[0046] Exemplarily, assume that there are three lanes on the left, middle, and right on the above-mentioned road, and there are 8 vehicle driving pictures containing the vehicle with the license plate number "ZJ ZE1234" in the vehicle driving pictures taken by the above-mentioned first monitoring device. Sort these 8 vehicle driving pictures according to the shooting time, and after sorting, group them as [Picture 1, Picture 2], [Picture 2, Picture 3], [Picture 3, Picture 4]... to obtain 7 picture groups. Then judge whether the driving lanes of the vehicle with the license plate number "ZJ ZE1234" in the two vehicle driving pictures in each picture group are the same. When Figure 1 is the left lane, Figure 2 is the middle lane, it can be determined that the vehicle has changed lanes during the shooting time from Figure 1 to Figure 2 of the shooting time.

[0047] In another embodiment for obtaining vehicle lane-changing data, the determination of the target vehicle can also be obtained through the safe driving historical data at the entrances and exits of important sections, including the cameras installed at the entrances and exits, to obtain the vehicles with few lane changes and driving speeds meeting the speed limit standards when entering and leaving important sections, so as to judge that the driver of the target vehicle is a safe driver, and thus determine it as the target vehicle.

[0048] Step S102, obtain the tunnel entrance pictures containing the target vehicle taken by the second monitoring device at the tunnel entrance, and obtain the tunnel exit pictures containing the target vehicle taken by the second monitoring device at the tunnel exit.

[0049] In this embodiment, the second monitoring device deployed at the tunnel entrances and exits monitors the fixed areas at the tunnel entrances and exits. This monitoring device can capture pictures when a vehicle passes through the monitored fixed area, and then the above-mentioned intelligent transportation system determines whether the captured pictures contain the target vehicle based on the vehicle information in the captured pictures, so as to obtain the tunnel entrance pictures and tunnel exit pictures containing the target vehicle. For areas with a large traffic flow, this monitoring device can also capture pictures of the monitored fixed area at regular intervals.

[0050] Step S103, determine whether an accident has occurred in the tunnel through the tunnel entrance pictures and the tunnel exit pictures of the target vehicle. If it is determined, send an instruction to the second monitoring device to make the second monitoring device turn on the warning indicator light.

[0051] In this embodiment, before the intelligent transportation system sends an instruction to the second monitoring device, it can also first notify the road maintenance personnel near the tunnel to check and determine. After the road maintenance personnel determine that an accident has occurred in the tunnel and feedback to this intelligent transportation system, this intelligent transportation system then sends an instruction to the second monitoring device to make it turn on the warning indicator light.

[0052] In another embodiment, determining whether an accident occurs in the tunnel through the tunnel entrance picture of the target vehicle and the tunnel exit picture of the target vehicle includes:

[0053] Determine the lane of the target vehicle when entering the tunnel through the tunnel entrance image of the target vehicle, determine the lane of the target vehicle when exiting the tunnel through the tunnel exit image of the target vehicle, and when the lane when entering the tunnel is different from the lane when exiting the tunnel, determine that an accident has occurred in the tunnel; or,

[0054] When the difference between the shooting time of the tunnel entrance picture of the target vehicle and the shooting time of the tunnel exit picture of the target vehicle exceeds a threshold, it is determined that an accident occurs in the tunnel.

[0055] In this embodiment, the difference between the shooting time of the tunnel entrance picture of the target vehicle and the shooting time of the tunnel exit picture of the target vehicle is the time for the target vehicle to pass through the tunnel. The time for the vehicle to pass through can be estimated according to the length of the tunnel, and the threshold can be set on this basis. For example, when the tunnel length is 5 kilometers, the vehicle speed is 60KM / H, and the estimated time to pass through the tunnel is 5 / 60h, that is, 5 minutes. Then the threshold can be set to 10 minutes, 20 minutes, or 30 minutes. When the time for multiple target vehicles to exit the tunnel exceeds the threshold, that is, much longer than the estimated time, it can be determined that an accident has occurred in the tunnel.

[0056] In another embodiment, determining whether an accident occurs in the tunnel through the tunnel entrance picture of the target vehicle and the tunnel exit picture of the target vehicle includes:

[0057] Determine the lane of the target vehicle when entering the tunnel through the tunnel entrance picture of the target vehicle, determine the lane of the target vehicle when exiting the tunnel through the tunnel exit picture of the target vehicle, and mark the target vehicle when the lane when entering the tunnel is different from the lane when exiting the tunnel;

[0058] When the number of marked target vehicles exceeds a threshold within a preset time period, it is determined that an accident occurs in the tunnel.

[0059] In this embodiment, the preset time period and the threshold of the number of vehicles can be set according to the traffic volume. When the traffic volume is large, there are many target vehicles, the preset time period can be reduced, and the threshold of the number of vehicles can be increased. When an accident occurs in the tunnel, it can be determined in a shorter time. When the traffic volume is small, resulting in a small number of target vehicles, the preset time period can be increased and the threshold of the number of vehicles can be reduced to avoid the situation that "there are too few target vehicles in the preset time period, even if an accident occurs in the tunnel and causes all the target vehicles in the preset time period to change lanes, it is determined that no accident has occurred".

[0060] In another embodiment, the vehicle information includes a license plate number of the vehicle, and the method further includes:

[0061] When the tunnel entrance and exit picture taken by the second monitoring device contains an unrecognizable license plate number, the unrecognizable license plate number is cut into a single character picture, and the single character picture is compared with the single character picture cut from the license plate number of the target vehicle to determine the single character picture similarity value;

[0062] An initial matrix is ​​constructed by using the single character image cut from the single character image, the single character image cut from the license plate number of the target vehicle, and the similarity value. A dynamic programming algorithm is used to traverse the initial matrix to determine the license plate number similarity value between the unrecognizable license plate number and the license plate number of the target vehicle. When the license plate number similarity value exceeds a set threshold, the vehicle with the unrecognizable license plate number is determined to be the target vehicle.

[0063] Exemplarily, taking the target vehicle's license plate number as Zhejiang ZE58U0, due to weather reasons, the second monitoring device cannot determine the letter E and the number 8, and preliminarily identifies it as the letter F and the number 6. At this time, the unrecognizable license plate number Zhejiang ZF56U0 is segmented into 7 single character images, "Zhe", "Z", "F", "5", "6", "U", "0", and compared with the single character images cut from the license plates of each target vehicle. For example, in addition to Zhejiang ZE58U0, the target vehicle also includes Zhejiang ZF48U0. The single character images segmented from Zhejiang ZF56U0 are compared with them for similarity, and there are many methods for comparison, such as average hash algorithm, perceptual hash algorithm, mean square error, structural similarity algorithm, etc. Taking the structural similarity algorithm as an example, the initial matrix established by the comparison results of Zhejiang ZF56U0 and Zhejiang ZE58U0 is as follows:

[0064] Zhejiang Z F 5 6 U 0 Zhejiang 1.00 0.19 0.15 0.17 0.17 0.22 0.19 Z 0.19 1.00 0.31 0.26 0.25 0.54 0.13 E 0.15 0.31 0.66 0.26 0.29 0.29 0.22 5 0.17 0.26 0.26 1.00 0.06 0.29 0.38 8 0.17 0.25 0.29 0.06 0.22 0.34 0.12 U 0.22 0.54 0.29 0.29 0.34 1.00 0.12 0 0.19 0.13 0.22 0.38 0.12 0.12 1.00

[0065] Then use the dynamic programming algorithm to traverse from left to right and from top to bottom to find the path with the maximum similarity:

[0066] Zhejiang Z F 5 6 U 0 Zhejiang 1.000000 0.595000 0.446667 0.377500 0.336000 0.316667 0.298571 Z 0.595000 1.000000 0.770000 0.642500 0.564000 0.560000 0.498571 E 0.443333 0.773333 0.886667 0.730000 0.642000 0.583333 0.531429 5 0.375000 0.645000 0.722500 0.915000 0.744000 0.668333 0.627143 8 0.338000 0.592000 0.644000 0.798000 0.776000 0.703333 0.620000 U 0.318333 0.583333 0.580000 0.713333 0.693333 0.813333 0.714286 0 0.300000 0.518571 0.544286 0.665714 0.620000 0.714286 0.840000

[0067] It can be seen that the similarity value of the license plate numbers of Zhejiang ZF56U0 and Zhejiang ZE58U0 is 0.84. When the set threshold is less than 0.84, the vehicle with the license plate number initially identified as Zhejiang ZF56U0 is determined as the target vehicle.

[0068] So far, completed Figure 1 The process shown.

[0069] In an embodiment of the present application, the intelligent transportation system determines the target vehicle with fewer lane changes through monitoring equipment on the road section outside the tunnel, and then uses monitoring equipment deployed at the tunnel entrance to take pictures of the target vehicle entering and exiting the tunnel, thereby determining whether an accident has occurred in the tunnel and issuing an alarm at the tunnel entrance. This solves the problem that when an accident occurs in a tunnel without monitoring equipment installed, it cannot be discovered and alarmed in time, which makes secondary accidents prone to occur.

[0070] like Figure 2 As shown, an embodiment of the present invention also provides a tunnel entrance monitoring equipment management device, which is applied to an intelligent transportation system, wherein the intelligent transportation system includes a first monitoring device deployed outside the tunnel, and a second monitoring device deployed at the entrance and exit of the tunnel, wherein the second monitoring device includes an alarm indicator light, and the device includes:

[0071] The target vehicle determination unit 201 is used to obtain a plurality of vehicle driving pictures taken by the first monitoring device, determine the number of times the vehicle changes its driving lane through the vehicle driving pictures, and determine the vehicle whose number is less than a threshold as the target vehicle, wherein the vehicle driving picture includes vehicle information and shooting time;

[0072] The image acquisition unit 202 is used to acquire a tunnel entrance image including the target vehicle taken by the second monitoring device at the tunnel entrance, and acquire a tunnel exit image including the target vehicle taken by the second monitoring device at the tunnel exit;

[0073] The accident determination unit 203 is used to determine whether an accident occurs in the tunnel through the tunnel entrance picture of the target vehicle and the tunnel exit picture of the target vehicle. If determined, a command is sent to the first monitoring device to turn on the alarm indicator light of the first monitoring device.

[0074] Optionally, the target vehicle determination unit determines the number of times the vehicle changes its driving lane through the vehicle driving picture, including:

[0075] Obtaining N vehicle driving pictures of the same vehicle through the vehicle information, and sorting the multiple vehicle driving pictures according to shooting time, where N>1;

[0076] Divide the sorted N vehicle driving pictures into N-1 picture groups, where each picture group includes two adjacent vehicle driving pictures;

[0077] It is determined whether the driving lane of the vehicle in two vehicle driving pictures in the picture group is consistent, and the number of inconsistent picture groups is determined as the number of times the vehicle changes the driving lane.

[0078] Optionally, the accident determination unit determines whether an accident occurs in the tunnel through the tunnel entrance picture of the target vehicle and the tunnel exit picture of the target vehicle, including:

[0079] Determine the lane of the target vehicle when entering the tunnel through the tunnel entrance image of the target vehicle, determine the lane of the target vehicle when exiting the tunnel through the tunnel exit image of the target vehicle, and when the lane when entering the tunnel is different from the lane when exiting the tunnel, determine that an accident has occurred in the tunnel; or,

[0080] When the difference between the shooting time of the tunnel entrance picture of the target vehicle and the shooting time of the tunnel exit picture of the target vehicle exceeds a threshold, it is determined that an accident occurs in the tunnel.

[0081] Optionally, the accident determination unit determines whether an accident occurs in the tunnel through the tunnel entrance picture of the target vehicle and the tunnel exit picture of the target vehicle, including:

[0082] Determine the lane of the target vehicle when entering the tunnel through the tunnel entrance picture of the target vehicle, determine the lane of the target vehicle when exiting the tunnel through the tunnel exit picture of the target vehicle, and mark the target vehicle when the lane when entering the tunnel is different from the lane when exiting the tunnel;

[0083] When the number of marked target vehicles exceeds a threshold within a preset time period, it is determined that an accident occurs in the tunnel.

[0084] Optionally, the vehicle information includes a license plate number of the vehicle, and the device further includes:

[0085] The comparison unit 204 is used to cut the unrecognizable license plate number into a single character image when there is an unrecognizable license plate number in the tunnel entrance and exit image taken by the second monitoring device, and compare the single character image with the single character image cut from the license plate number of the target vehicle to determine a similarity value of the single character image;

[0086] An initial matrix is ​​constructed by using the single character image cut from the single character image, the single character image cut from the license plate number of the target vehicle, and the similarity value. A dynamic programming algorithm is used to traverse the initial matrix to determine the license plate number similarity value between the unrecognizable license plate number and the license plate number of the target vehicle. When the license plate number similarity value exceeds a set threshold, the vehicle with the unrecognizable license plate number is determined to be the target vehicle.

[0087] The above embodiment of the present invention provides a tunnel entrance monitoring equipment management method, and based on the tunnel entrance monitoring equipment management method, provides a tunnel entrance monitoring equipment management device. Through the above method and device, tunnel accidents can be discovered in time and alarms can be issued at the tunnel entrance, thereby reducing the occurrence of traffic accidents.

[0088] This embodiment also discloses a computer device, which includes a processor and a memory, wherein the memory stores at least one instruction, and the at least one instruction is loaded and executed by the processor to implement any of the above-mentioned tunnel entrance monitoring equipment management methods.

[0089] In addition, in the implementation of the tunnel entrance monitoring equipment management device in the above-mentioned example, the logical division of each program module is only an example. In actual application, the above-mentioned functions can be assigned to different program modules as needed, for example, for the configuration requirements of the corresponding hardware or the convenience of software implementation. That is, the internal structure of the tunnel entrance monitoring equipment management device is divided into different program modules to complete all or part of the functions described above.

[0090] Another embodiment of the present invention is a method for managing monitoring equipment of important road sections, where the important road sections include exit ramps for exiting highways, entrances and exits of service areas, tunnels, and sharp turns.

[0091] The important road section monitoring equipment management method is applied to an intelligent transportation system, the intelligent transportation system includes a first monitoring device deployed outside the important road section, and a second monitoring device deployed at the entrance and exit of the important road section, the second monitoring device includes an alarm indicator light, and the method includes:

[0092] Acquire a plurality of vehicle driving pictures taken by the first monitoring device, determine the number of times the vehicle changes its driving lane through the vehicle driving pictures, and determine a vehicle whose number is less than a threshold as a target vehicle, wherein the vehicle driving picture includes vehicle information and shooting time;

[0093] Obtaining a picture of an important road section entrance including the target vehicle taken by a second monitoring device at the important road section entrance, and obtaining a picture of an important road section exit including the target vehicle taken by a second monitoring device at the important road section exit;

[0094] Determine whether an accident occurs in an important road section through the important road section entrance picture of the target vehicle and the important road section exit picture of the target vehicle. If confirmed, send a command to the second monitoring device to turn on the alarm indicator light of the second monitoring device.

[0095] The method of determining the number of times the vehicle changes its lane through the vehicle driving pictures includes: obtaining N vehicle driving pictures of the same vehicle through the vehicle information, and sorting the multiple vehicle driving pictures according to shooting time, N>1; dividing the sorted N vehicle driving pictures into N-1 picture groups, the picture group including two adjacent vehicle driving pictures; judging whether the driving lanes of the vehicle in the two vehicle driving pictures in the picture group are consistent, and determining the number of inconsistent picture groups as the number of times the vehicle changes its lane.

[0096] The rest of the method process is the same as the tunnel entrance monitoring equipment management method.

[0097] In the description of this specification, the description with reference to the terms "one embodiment / method", "some embodiments / methods", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment / method or example are included in at least one embodiment / method or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment / method or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments / methods or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments / methods or examples described in this specification and the features of the different embodiments / methods or examples, unless they are contradictory.

[0098] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0099] It should be understood by those skilled in the art that the above embodiments are only for the purpose of clearly illustrating the present disclosure, and are not intended to limit the scope of analysis of the present disclosure. For those skilled in the art, other changes or modifications may be made based on the above disclosure, and these changes or modifications are still within the scope of analysis of the present disclosure.

Claims

1. A method for managing important road section monitoring equipment, characterized in that: Applied to an intelligent transportation system, the intelligent transportation system includes a first monitoring device deployed outside an important road section, and a second monitoring device deployed at an entrance and exit of the important road section, the second monitoring device includes an alarm indicator light, and the method includes: Acquire a plurality of vehicle driving pictures taken by the first monitoring device, determine the number of times the vehicle changes its driving lane through the vehicle driving pictures, and determine a vehicle whose number is less than a threshold as a target vehicle, wherein the vehicle driving picture includes vehicle information and shooting time; Obtaining a picture of an important road section entrance including the target vehicle taken by a second monitoring device at the important road section entrance, and obtaining a picture of an important road section exit including the target vehicle taken by a second monitoring device at the important road section exit; Determining whether an accident occurs in an important road section by using the important road section entrance picture of the target vehicle and the important road section exit picture of the target vehicle specifically includes: Determine the lane of the target vehicle when it enters the important road section through the important road section entrance picture of the target vehicle, determine the lane of the target vehicle when it exits the important road section through the important road section exit picture of the target vehicle, and mark the target vehicle when the lane when entering the important road section is different from the lane when exiting the important road section; When the number of marked target vehicles exceeds a threshold value within a preset time period, it is determined that an accident has occurred in the important road section, and an instruction is sent to the second monitoring device to turn on a warning indicator light.

2. The method according to claim 1, characterized in that The important road sections include the exit ramps for highways, entrances and exits of service areas, tunnels, and sharp turns.

3. The method according to claim 1, characterized in that The determining the number of times the vehicle changes its lane through the vehicle driving picture includes: Obtaining N vehicle driving pictures of the same vehicle through the vehicle information, and sorting the N vehicle driving pictures according to shooting time, where N>1; Divide the sorted N vehicle driving pictures into N-1 picture groups, where each picture group includes two adjacent vehicle driving pictures; It is determined whether the driving lane of the vehicle in two vehicle driving pictures in the picture group is consistent, and the number of inconsistent picture groups is determined as the number of times the vehicle changes the driving lane.

4. The method according to claim 1, characterized in that: Determining whether an accident occurs in an important road section by using the important road section entrance picture of the target vehicle and the important road section exit picture of the target vehicle includes: Determine the lane of the target vehicle when entering the important road section through the important road section entrance picture of the target vehicle, and determine the lane of the target vehicle when exiting the important road section through the important road section exit picture of the target vehicle, and when the lane when entering the important road section is different from the lane when exiting the important road section, it is determined that an accident has occurred in the important road section; or, When the difference between the shooting time of the important road section entrance picture of the target vehicle and the shooting time of the important road section exit picture of the target vehicle exceeds a threshold, it is determined that an accident occurs in the important road section.

5. The method according to claim 1, characterized in that The vehicle information includes a license plate number of the vehicle, and the method further includes: When the tunnel entrance and exit picture taken by the second monitoring device contains an unrecognizable license plate number, the unrecognizable license plate number is cut into a single character picture, and the single character picture is compared with the single character picture cut from the license plate number of the target vehicle to determine the single character picture similarity value; An initial matrix is ​​constructed by using the single character image cut from the single character image, the single character image cut from the license plate number of the target vehicle, and the similarity value. A dynamic programming algorithm is used to traverse the initial matrix to determine the license plate number similarity value between the unrecognizable license plate number and the license plate number of the target vehicle. When the license plate number similarity value exceeds a set threshold, the vehicle with the unrecognizable license plate number is determined to be the target vehicle.

6. An important road section monitoring equipment management device, characterized in that: Applied to an intelligent transportation system, the intelligent transportation system includes a first monitoring device deployed outside an important road section, and a second monitoring device deployed at an entrance and exit of the important road section, the second monitoring device includes an alarm indicator light, and the device includes: A target vehicle determination unit is used to obtain a plurality of vehicle driving pictures taken by the first monitoring device, determine the number of times the vehicle changes its driving lane through the vehicle driving pictures, and determine the vehicle whose number is less than a threshold as a target vehicle, wherein the vehicle driving picture includes vehicle information and shooting time; A picture acquisition unit, used for acquiring a picture of an important road section entrance including the target vehicle taken by a second monitoring device at the important road section entrance, and acquiring a picture of an important road section exit including the target vehicle taken by a second monitoring device at the important road section exit; The accident determination unit is used to determine whether an accident occurs in an important road section through the important road section entrance picture of the target vehicle and the important road section exit picture of the target vehicle, specifically including: Determine the lane of the target vehicle when it enters the important road section through the important road section entrance picture of the target vehicle, determine the lane of the target vehicle when it exits the important road section through the important road section exit picture of the target vehicle, and mark the target vehicle when the lane when entering the important road section is different from the lane when exiting the important road section; When the number of marked target vehicles exceeds a threshold value within a preset time period, it is determined that an accident has occurred in the important road section, and an instruction is sent to the second monitoring device to turn on a warning indicator light.

7. The device according to claim 6, characterized in that The target vehicle determination unit determines the number of times the vehicle changes its driving lane through the vehicle driving picture, including: Obtaining N vehicle driving pictures of the same vehicle through the vehicle information, and sorting the N vehicle driving pictures according to shooting time, where N>1; Divide the sorted N vehicle driving pictures into N-1 picture groups, where each picture group includes two adjacent vehicle driving pictures; It is determined whether the driving lane of the vehicle in two vehicle driving pictures in the picture group is consistent, and the number of inconsistent picture groups is determined as the number of times the vehicle changes the driving lane.

8. The device according to claim 6, characterized in that The accident determination unit determines whether an accident occurs in an important road section through the important road section entrance picture of the target vehicle and the important road section exit picture of the target vehicle, including: Determine the lane of the target vehicle when entering the important road section through the important road section entrance picture of the target vehicle, and determine the lane of the target vehicle when exiting the important road section through the important road section exit picture of the target vehicle, and when the lane when entering the important road section is different from the lane when exiting the important road section, it is determined that an accident has occurred in the important road section; or, When the difference between the shooting time of the important road section entrance picture of the target vehicle and the shooting time of the important road section exit picture of the target vehicle exceeds a threshold, it is determined that an accident occurs in the important road section.

9. The device according to claim 6, characterized in that The vehicle information includes a license plate number of the vehicle, and the device further includes: A comparison unit is used for, when there is an unrecognizable license plate number in the pictures of the entrances and exits of important road sections taken by the second monitoring device, cutting the unrecognizable license plate number into single character pictures, and comparing the single character pictures with the single character pictures cut from the license plate number of the target vehicle to determine the similarity values ​​of the single character pictures; constructing an initial matrix through the single character pictures cut from the single character pictures, the single character pictures cut from the license plate number of the target vehicle, and the similarity values, traversing the initial matrix using a dynamic programming algorithm to determine the license plate number similarity value between the unrecognizable license plate number and the license plate number of the target vehicle; when the license plate number similarity value exceeds a set threshold, determining that the vehicle with the unrecognizable license plate number is the target vehicle.

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