CN113611124A - Intelligent identification method based on intelligent city vehicle violation - Google Patents
Intelligent identification method based on intelligent city vehicle violation Download PDFInfo
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- CN113611124A CN113611124A CN202110909024.9A CN202110909024A CN113611124A CN 113611124 A CN113611124 A CN 113611124A CN 202110909024 A CN202110909024 A CN 202110909024A CN 113611124 A CN113611124 A CN 113611124A
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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
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
Abstract
The invention discloses an intelligent identification method based on intelligent city vehicle violation, which comprises the following steps: shooting a first vehicle picture on a road surface by using a camera; analyzing the license plate number of the motor vehicle and the corresponding position thereof from the first vehicle picture, and counting a first distance value between the vehicle of the license plate number and a first reference point; shooting a second vehicle picture on the road surface by using the camera; analyzing the license plate number and the corresponding position of the motor vehicle from the second vehicle picture, selecting the vehicle with the same license plate number from the second vehicle picture, and counting a second distance value between the vehicle with the same license plate number and the first reference point; and when the first reference point is positioned behind the vehicle in the first wheel picture, if the second distance value is smaller than the first distance value, judging that the vehicle with the license plate number belongs to the wrong-way violation. Through the mode, whether the vehicle drives in the wrong direction or not can be judged according to the distance between the motor vehicle and the reference point, the wrong-direction driving behavior of the vehicle can be recognized, and the intelligent degree is higher.
Description
Technical Field
The invention relates to the technical field of intelligent traffic, in particular to an intelligent identification method based on intelligent city vehicle violation.
Background
With the improvement of the living standard of residents, nowadays, basically every family has a private car. Therefore, the phenomenon of vehicle parking is also endless, and the vehicle parking not only can cause the taste and image of the city to be influenced, but also can increase the occurrence of collision accidents and rear-end accidents, and can also cause unnecessary blockage to influence the normal traffic of other vehicles and pedestrians.
In order to reduce vehicle violation on the road surface, whether the vehicle violates is identified by adopting a traffic camera in a photographing and evidence obtaining mode on the market, however, in the traditional mode, the traffic camera only can realize the behaviors of snapping red light running, pressing lines and the like, and cannot identify whether the vehicle runs in the wrong direction, so that the user experience is greatly reduced.
Disclosure of Invention
The invention mainly solves the technical problem of providing an intelligent recognition method based on vehicle violation of a smart city, which can recognize the vehicle behavior in the wrong direction so as to meet the high-quality requirement of the smart city and greatly improve the user experience.
In order to solve the technical problems, the invention adopts a technical scheme that: the invention provides an intelligent identification method based on intelligent city vehicle violation, which is characterized by comprising the following steps: step S101: shooting a first vehicle picture on a road surface towards a first direction at a first time point by using a camera, wherein the first direction is a vehicle reverse running direction; step S102: analyzing a motor vehicle from a first vehicle picture, analyzing a license plate number and a corresponding position of the vehicle, selecting a fixed object as a first reference point, and counting a first distance value between the vehicle of the license plate number and the first reference point along a first direction; step S103: taking a second picture of the vehicle on the road surface in a first direction at a second time point by using the camera, wherein the second time point is later than the first time point; step S104: analyzing the motor vehicle from the second vehicle picture, analyzing the license plate number of the vehicle and the corresponding position of the license plate number, selecting the vehicle with the license plate number same as that in the first vehicle picture from the second vehicle picture, and counting a second distance value between the vehicle with the license plate number same as that in the first vehicle picture and the first reference point along the first direction; step S105: and when the first reference point is positioned behind the vehicle in the first wheel picture, if the second distance value is smaller than the first distance value, judging that the vehicle with the license plate number belongs to the wrong-way violation.
Further, the method further comprises: step S106: when the first reference point is positioned in front of the vehicle in the first wheel picture, if the second distance value is larger than the first distance value, the vehicle of the license plate number is judged to belong to the wrong-way violation.
Further, the first reference point comprises a camera, a house beside the road surface and a tree beside the road surface.
Further, the method further comprises: step S201: shooting a third vehicle picture on the road surface towards a second direction at a third time point by using the camera, wherein the second direction is a forward direction of the vehicle; step S202: analyzing the license plate number of the vehicle and the corresponding position of the license plate number from the third vehicle picture, selecting a fixed object as a second reference point, and counting a third distance value between the vehicle of the license plate number and the second reference point along a second direction; step S203: shooting a fourth vehicle picture on the road surface towards the second direction at a fourth time point by using the camera, wherein the fourth time point is later than the third time point; step S204: analyzing the license plate number of the vehicle and the corresponding position of the license plate number from the fourth vehicle picture, selecting the vehicle with the same license plate number as the third vehicle picture from the fourth vehicle picture, and counting a fourth distance value between the vehicle with the same license plate number as the third vehicle picture and the second reference point along the second direction; step S205: and when the first reference point is positioned behind the vehicle in the third wheel picture, if the fourth distance value is smaller than the third distance value, determining that the vehicle with the license plate number belongs to the wrong-way violation.
Further, the method further comprises: step S206: and when the second reference point is positioned in front of the vehicle in the third wheel picture, if the fourth distance value is greater than the third distance value, determining that the vehicle with the license plate number belongs to the wrong-way violation.
Further, the second reference point comprises a camera, a house beside the road surface and a tree beside the road surface.
Further, the road surface is a one-way lane road surface, the camera is rotatably arranged in a control panel of the support frame above the road surface, the control panel is provided with a red light, a green light and a yellow light, and the method comprises the following steps: when the green light is on, controlling the camera to face the reverse direction, and executing the steps S101-S106; when the red light is on, the camera is controlled to rotate and face the forward direction, and the steps S201 to S206 are executed.
Further, the road surface is a one-way lane road surface, the camera is rotatably arranged in a control panel of the support frame above the road surface, and a red light, a green light and a yellow light are arranged in the control panel, and the method comprises the following steps: when the green light is turned on, the camera is controlled to face the reverse direction, and the steps S101 to S106 are executed, and when the steps S101 to S106 are executed, the camera is controlled to rotate and face the forward direction, the steps S201 to S206 are executed, and after the steps S201 to S206 are executed, the camera is controlled to face the reverse direction again.
Further, the method further comprises: when the red light is on, analyzing the vehicles stopped and queued on the road surface from the first vehicle picture, and counting the total length of the queued vehicles stopped on each lane; judging whether the length of the queued vehicle stopped by the lane with the longest total length of the queued vehicles stopped on each lane is larger than a preset length value or not; if yes, a new lighting time length mode is provided for the green light in the corresponding control panel, wherein the lighting time length of the new lighting time length mode is longer than the normal lighting time length.
The invention has the beneficial effects that: different from the situation of the prior art, the intelligent identification method based on the intelligent city vehicle violation, disclosed by the invention, comprises the following steps: shooting a first vehicle picture on a road surface by using a camera; analyzing the license plate number of the motor vehicle and the corresponding position thereof from the first vehicle picture, and counting a first distance value between the vehicle of the license plate number and a first reference point; shooting a second vehicle picture on the road surface by using the camera; analyzing the license plate number and the corresponding position of the motor vehicle from the second vehicle picture, selecting the vehicle with the same license plate number from the second vehicle picture, and counting a second distance value between the vehicle with the same license plate number and the first reference point; and when the first reference point is positioned behind the vehicle in the first wheel picture, if the second distance value is smaller than the first distance value, judging that the vehicle with the license plate number belongs to the wrong-way violation. Through the mode, whether the vehicle drives in the wrong direction or not can be judged according to the distance between the motor vehicle and the reference point, the wrong-direction driving behavior of the vehicle can be recognized, and the intelligent degree is higher.
Drawings
Fig. 1 is a schematic flow chart of an intelligent identification method for vehicle violations in a smart city according to the present invention.
Detailed Description
Referring to fig. 1, the intelligent identification method based on the intelligent city vehicle violation includes the following steps:
step S101: a first vehicle picture on a road surface is taken by a camera towards a first direction at a first time point.
Preferably, the first direction is a vehicle reverse direction.
Step S102: the method comprises the steps of analyzing a motor vehicle from a first vehicle picture, analyzing a license plate number of the motor vehicle and a position corresponding to the license plate number, selecting a fixed object as a first reference point, and counting a first distance value between the motor vehicle with the license plate number and the first reference point along a first direction.
It should be understood that in step S102, it is only analyzed from the first vehicle picture that the vehicle belongs to the motor vehicle, and the bicycle and the pedestrian are not analyzed.
It should be appreciated that in some embodiments, the step of parsing the automotive vehicle from the first vehicle picture comprises: selecting outlines, in the first vehicle picture, of which the width is larger than the preset width and the height is larger than the preset height, of which the board is fixedly arranged and the board is provided with characters, letters and numbers as motor vehicles. It is noted that the predetermined width is a width that satisfies the width of the vehicle, the predetermined height is a height that satisfies the height of the vehicle, and the plaque is a license plate that satisfies the license plate of the vehicle.
In this embodiment, the first reference point is stationary, and preferably the first reference point includes a camera, a house beside the road surface, and a tree beside the road surface.
Step S103: and taking a second picture of the vehicle on the road surface towards the first direction at a second time point by using the camera.
In this embodiment, the second time point is later than the first time point, and preferably, the second time point is later than the first time point by a time in a range of 1 to 3 seconds.
Step S104: and analyzing the motor vehicle from the second vehicle picture, analyzing the license plate number of the vehicle and the corresponding position of the license plate number, selecting the vehicle with the license plate number same as that in the first vehicle picture from the second vehicle picture, and counting a second distance value between the vehicle with the license plate number same as that in the first vehicle picture and the first reference point along the first direction.
It should be understood that in step S104, it is only analyzed from the second vehicle picture that the vehicle belongs to the motor vehicle, and the bicycle and the pedestrian are not analyzed.
It should be appreciated that in some embodiments, the step of parsing the automotive vehicle from the second vehicle picture comprises: and selecting the outlines of the second vehicle picture, which have the width larger than the preset width and the height larger than the preset height, are fixedly provided with the board, and the board is provided with characters, letters and numbers, as the motor vehicle. It is noted that the predetermined width is a width that satisfies the width of the vehicle, the predetermined height is a height that satisfies the height of the vehicle, and the plaque is a license plate that satisfies the license plate of the vehicle.
Step S105: and when the first reference point is positioned behind the vehicle in the first wheel picture, if the second distance value is smaller than the first distance value, judging that the vehicle with the license plate number belongs to the wrong-way violation.
It should be understood that when the first reference point is located behind the vehicle in the first wheel picture, if the second distance value is smaller than the first distance value, it indicates that the vehicle with the same license plate number is moving in a direction close to the first reference point, which indicates a reverse driving.
Further, the intelligent identification method based on the intelligent city vehicle violation further comprises the following steps:
step S106: when the first reference point is positioned in front of the vehicle in the first wheel picture, if the second distance value is larger than the first distance value, the vehicle of the license plate number is judged to belong to the wrong-way violation.
It should be understood that when the first reference point is in front of the vehicle in the first wheel picture, if the second distance value is greater than the first distance value, it indicates that the vehicle of the same license plate number is moving away from the first reference point, which indicates a reverse driving.
In the present embodiment, in steps S101 to S106, the camera is used for shooting in the reverse direction of the vehicle, so that the camera is used for shooting whether the vehicle in the reverse direction of the vehicle has reverse running.
Further, the intelligent identification method based on the intelligent city vehicle violation further comprises the following steps:
step S201: and shooting a third vehicle picture on the road surface towards the second direction at a third time point by using the camera.
Preferably, the second direction is a vehicle forward direction.
Step S202: and analyzing the license plate number of the vehicle and the corresponding position of the license plate number from the third vehicle picture, selecting a fixed object as a second reference point, and counting a third distance value between the vehicle of the license plate number and the second reference point along a second direction.
It should be understood that in step S202, only the vehicle belonging to the automobile is analyzed from the third vehicle picture, and the bicycle and the pedestrian are not analyzed.
It should be appreciated that in some embodiments, the step of parsing the automotive vehicle from the third vehicle picture includes: and selecting the outlines of the third vehicle picture, which have the width larger than the preset width and the height larger than the preset height, are fixedly provided with the board, and are provided with characters, letters and numbers, as the motor vehicle. It is noted that the predetermined width is a width that satisfies the width of the vehicle, the predetermined height is a height that satisfies the height of the vehicle, and the plaque is a license plate that satisfies the license plate of the vehicle.
In this embodiment, the second reference point is stationary, and preferably the first reference point comprises a camera, a house beside the road surface, and a tree beside the road surface.
Step S203: and shooting a fourth vehicle picture on the road surface towards the second direction at a fourth time point by using the camera.
In the present embodiment, the fourth time point is later than the third time point, and preferably, the fourth time point is later than the third time point by a time in the range of 1 to 3 seconds.
Step S204: and analyzing the license plate number of the vehicle and the corresponding position of the license plate number from the fourth vehicle picture, selecting the vehicle with the same license plate number as that in the third vehicle picture from the fourth vehicle picture, and counting a fourth distance value between the vehicle with the same license plate number as that in the third vehicle picture and the second reference point along the second direction.
It should be understood that in step S204, it is only analyzed from the fourth vehicle picture that the vehicle belongs to the motor vehicle, and the bicycle and the pedestrian are not analyzed.
It should be appreciated that in some embodiments, the step of parsing the automotive vehicle from the fourth vehicle picture comprises: selecting the outlines of the fourth vehicle picture, which have the width larger than the preset width and the height larger than the preset height, are fixedly provided with the board, and the board is provided with characters, letters and numbers, as the motor vehicle. It is noted that the predetermined width is a width that satisfies the width of the vehicle, the predetermined height is a height that satisfies the height of the vehicle, and the plaque is a license plate that satisfies the license plate of the vehicle.
Step S205: and when the first reference point is positioned behind the vehicle in the third wheel picture, if the fourth distance value is smaller than the third distance value, determining that the vehicle with the license plate number belongs to the wrong-way violation.
It should be understood that when the first reference point is located behind the vehicle in the third wheel picture, if the fourth distance value is smaller than the third distance value, it indicates that the vehicle with the same license plate number is moving closer to the second reference point, which indicates a reverse driving.
Further, the intelligent identification method based on the intelligent city vehicle violation further comprises the following steps:
step S206: and when the second reference point is positioned in front of the vehicle in the third wheel picture, if the fourth distance value is greater than the third distance value, determining that the vehicle with the license plate number belongs to the wrong-way violation.
It should be understood that when the second reference point is in front of the vehicle in the third wheel picture, if the fourth distance value is greater than the third distance value, it indicates that the vehicle of the same license plate number is moving away from the second reference point, which indicates a reverse movement.
In addition, in some embodiments, the road surface is a one-way lane road surface, the camera is rotatably arranged in a control panel of a support frame above the road surface, the control panel is provided with a red light, a green light and a yellow light, and the intelligent identification method based on the intelligent city vehicle violation comprises the following steps: when the green light is on, controlling the camera to face the reverse direction, and executing the steps S101-S106; when the red light is on, the camera is controlled to rotate and face the forward direction, and the steps S201 to S206 are executed.
In addition, in some embodiments, the road surface is a one-way lane road surface, the camera is rotatably arranged in a control panel of a support frame above the road surface, and a red light, a green light and a yellow light are arranged in the control panel, and the intelligent identification method based on the smart city vehicle violation comprises the following steps: when the green light is turned on, the camera is controlled to face the reverse direction, and the steps S101 to S106 are executed, and when the steps S101 to S106 are executed, the camera is controlled to rotate and face the forward direction, the steps S201 to S206 are executed, and after the steps S201 to S206 are executed, the camera is controlled to face the reverse direction again.
Further, the intelligent identification method based on the intelligent city vehicle violation further comprises the following steps:
step S301: when the red light is on, the vehicles stopped and queued on the road surface are analyzed from the first vehicle picture, and the total length of the queued vehicles stopped on each lane is counted.
Step S302: and judging whether the length of the queued vehicle stopped by the lane with the longest total length of the queued vehicles stopped on each lane is larger than a preset length value.
Step S303: if yes, a new light-on duration mode is provided for the green light in the corresponding control panel.
Preferably, the new lighting time period mode has a lighting time period longer than the normal lighting time period.
It should be understood that steps S301 to S303 can control the display duration of the traffic light according to the queuing length of the red light of the vehicle and the like.
Further, in some embodiments, the road surface is not a single lane, the road surface is a crossroad road surface, the control panel is provided with a first red light corresponding to a left-turn lane, a first green light corresponding to the left-turn lane, a first yellow light corresponding to the left-turn lane, a first red light corresponding to an intermediate lane, a first green light corresponding to the intermediate lane, a first yellow light corresponding to the intermediate lane, a first red light corresponding to a right-turn lane, a first green light corresponding to the right-turn lane, and a first yellow light corresponding to the right-turn lane, the first red light, the second red light, and the third red light in the control panel are turned on for the same time, the first green light, the second green light, and the third green light in the control panel are turned off for the same time, and the first yellow light, the second yellow light, and the third yellow light in the control panel are turned on for the same time. The intelligent identification method based on the intelligent city vehicle violation further comprises the following steps:
step S401: when the first red light corresponding to the left-turning lane, the second red light corresponding to the middle lane and the third red light corresponding to the right-turning lane are determined to be on, a camera in the control panel is used for shooting a road surface picture of a road surface corresponding to the control panel.
Step S402: and analyzing a left-turn lane, a middle lane and a right-turn lane corresponding to the road surface in the road surface picture.
Step S403: vehicles in the road surface picture are identified, and vehicles in a left-turn lane, a middle lane and a right-turn lane are identified.
Step S404: and counting the length of vehicle queue in the left-turn lane, the middle lane and the right-turn lane.
Step S405: and judging whether the queuing lengths of the vehicles in the left-turn lane, the middle lane and the right-turn lane meet the standard length.
Step S406: if so, the first red light corresponding to the left-turn lane, the first green light corresponding to the left-turn lane, the first yellow light corresponding to the left-turn lane, the second red light corresponding to the middle lane, the second green light corresponding to the middle lane, the second yellow light corresponding to the middle lane, the third red light corresponding to the right-turn lane, the third green light corresponding to the right-turn lane and the third yellow light corresponding to the right-turn lane are turned on and off according to normal standard time.
In conclusion, the invention can realize the recognition of the vehicles in the wrong direction, and can control the on-off time of the traffic lights according to the queuing length of the vehicles, for example, when the queuing length of the vehicles is longer, the on-time of the green light is prolonged, and when the queuing length of the vehicles is shorter, the on-time of the green light is shortened, the flexibility is high, the intellectualization is high, and the high-quality requirement of the smart city can be met.
The above description is only an embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes performed by the present specification and drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (9)
1. An intelligent identification method based on intelligent city vehicle violation is characterized by comprising the following steps:
step S101: shooting a first vehicle picture on a road surface towards a first direction at a first time point by using a camera, wherein the first direction is a vehicle reverse running direction;
step S102: analyzing a motor vehicle from a first vehicle picture, analyzing a license plate number and a corresponding position of the vehicle, selecting a fixed object as a first reference point, and counting a first distance value between the vehicle of the license plate number and the first reference point along a first direction;
step S103: taking a second picture of the vehicle on the road surface in a first direction at a second time point by using the camera, wherein the second time point is later than the first time point;
step S104: analyzing the motor vehicle from the second vehicle picture, analyzing the license plate number of the vehicle and the corresponding position of the license plate number, selecting the vehicle with the license plate number same as that in the first vehicle picture from the second vehicle picture, and counting a second distance value between the vehicle with the license plate number same as that in the first vehicle picture and the first reference point along the first direction;
step S105: and when the first reference point is positioned behind the vehicle in the first wheel picture, if the second distance value is smaller than the first distance value, judging that the vehicle with the license plate number belongs to the wrong-way violation.
2. The smart city vehicle violation based intelligent identification method of claim 1, further comprising:
step S106: when the first reference point is positioned in front of the vehicle in the first wheel picture, if the second distance value is larger than the first distance value, the vehicle of the license plate number is judged to belong to the wrong-way violation.
3. The smart city vehicle violation based intelligent recognition method of claim 2, wherein the first reference point comprises a camera, a house beside a road surface, and a tree beside a road surface.
4. The smart city vehicle violation based intelligent identification method of claim 3, further comprising:
step S201: shooting a third vehicle picture on the road surface towards a second direction at a third time point by using the camera, wherein the second direction is a forward direction of the vehicle;
step S202: analyzing the license plate number of the vehicle and the corresponding position of the license plate number from the third vehicle picture, selecting a fixed object as a second reference point, and counting a third distance value between the vehicle of the license plate number and the second reference point along a second direction;
step S203: shooting a fourth vehicle picture on the road surface towards the second direction at a fourth time point by using the camera, wherein the fourth time point is later than the third time point;
step S204: analyzing the license plate number of the vehicle and the corresponding position of the license plate number from the fourth vehicle picture, selecting the vehicle with the same license plate number as the third vehicle picture from the fourth vehicle picture, and counting a fourth distance value between the vehicle with the same license plate number as the third vehicle picture and the second reference point along the second direction;
step S205: and when the first reference point is positioned behind the vehicle in the third wheel picture, if the fourth distance value is smaller than the third distance value, determining that the vehicle with the license plate number belongs to the wrong-way violation.
5. The smart city vehicle violation based intelligent identification method of claim 4, further comprising:
step S206: and when the second reference point is positioned in front of the vehicle in the third wheel picture, if the fourth distance value is greater than the third distance value, determining that the vehicle with the license plate number belongs to the wrong-way violation.
6. The smart city vehicle violation based intelligent recognition method of claim 5, wherein the second reference point comprises a camera, a house beside a road surface, and a tree beside a road surface.
7. The intelligent urban vehicle violation identification method according to claim 6, wherein the road surface is a one-way lane road surface, the camera is rotatably disposed in a control panel of a support frame above the road surface, the control panel is provided with a red light, a green light and a yellow light, and the method comprises:
when the green light is on, controlling the camera to face the reverse direction, and executing the steps S101-S106;
when the red light is on, the camera is controlled to rotate and face the forward direction, and the steps S201 to S206 are executed.
8. The intelligent recognition method for smart city vehicle violations as claimed in claim 6, wherein the road surface is a one-way lane road surface, the camera is rotatably disposed in a control panel of a support frame above the road surface, and red, green and yellow lights are disposed in the control panel, the method comprising:
when the green light is turned on, the camera is controlled to face the reverse direction, and the steps S101 to S106 are executed, and when the steps S101 to S106 are executed, the camera is controlled to rotate and face the forward direction, the steps S201 to S206 are executed, and after the steps S201 to S206 are executed, the camera is controlled to face the reverse direction again.
9. The smart city vehicle violation based identification method according to claim 7 or 8, further comprising:
when the red light is on, analyzing the vehicles stopped and queued on the road surface from the first vehicle picture, and counting the total length of the queued vehicles stopped on each lane;
judging whether the length of the queued vehicle stopped by the lane with the longest total length of the queued vehicles stopped on each lane is larger than a preset length value or not;
if yes, a new lighting time length mode is provided for the green light in the corresponding control panel, wherein the lighting time length of the new lighting time length mode is longer than the normal lighting time length.
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| CN111832376A (en) * | 2019-07-18 | 2020-10-27 | 北京骑胜科技有限公司 | Vehicle reverse running detection method and device, electronic equipment and storage medium |
| CN110689734A (en) * | 2019-09-24 | 2020-01-14 | 成都通甲优博科技有限责任公司 | Vehicle running condition identification method and device and electronic equipment |
| CN213582567U (en) * | 2020-09-29 | 2021-06-29 | 安徽思普泰克智能制造科技有限公司 | Automatic control system for time length of traffic signal lamp at crossroad based on machine vision |
| CN112489456A (en) * | 2020-12-01 | 2021-03-12 | 山东交通学院 | Signal lamp regulation and control method and system based on urban trunk line vehicle queuing length |
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| CN114596704A (en) * | 2022-03-14 | 2022-06-07 | 阿波罗智联(北京)科技有限公司 | Traffic event processing method, device, equipment and storage medium |
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