CN112907992A - Traffic signal lamp control method, device, equipment and storage medium - Google Patents

Traffic signal lamp control method, device, equipment and storage medium Download PDF

Info

Publication number
CN112907992A
CN112907992A CN202110209006.XA CN202110209006A CN112907992A CN 112907992 A CN112907992 A CN 112907992A CN 202110209006 A CN202110209006 A CN 202110209006A CN 112907992 A CN112907992 A CN 112907992A
Authority
CN
China
Prior art keywords
signal lamp
vehicles
vehicle passing
lamp control
vehicle
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202110209006.XA
Other languages
Chinese (zh)
Inventor
甘丰
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Ping An Puhui Enterprise Management Co Ltd
Original Assignee
Ping An Puhui Enterprise Management Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Ping An Puhui Enterprise Management Co Ltd filed Critical Ping An Puhui Enterprise Management Co Ltd
Priority to CN202110209006.XA priority Critical patent/CN112907992A/en
Publication of CN112907992A publication Critical patent/CN112907992A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/24—Classification techniques
    • G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16—Human faces, e.g. facial parts, sketches or expressions
    • G06V40/161—Detection; Localisation; Normalisation
    • 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
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/07—Controlling traffic signals
    • G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/095—Traffic lights
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • General Engineering & Computer Science (AREA)
  • Artificial Intelligence (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Human Computer Interaction (AREA)
  • Multimedia (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention relates to the field of artificial intelligence, and discloses a traffic signal lamp control method, a traffic signal lamp control device, traffic signal lamp control equipment and a traffic signal lamp storage medium, which are applied to the field of intelligent traffic, are used for monitoring traffic conditions in real time through an OCR (optical character recognition) algorithm, relieve the problem of urban road congestion and improve the travel efficiency of people. The control method of the traffic signal lamp comprises the following steps: extracting real-time data of the intersection to be passed; analyzing real-time data of the intersection to be passed, judging an analysis result and selecting a signal lamp control strategy; when the signal lamp control strategy is a non-intersection signal lamp control strategy, counting the number of pedestrians at a non-intersection to obtain a pedestrian number counting result, and outputting a first signal lamp instruction; and when the signal lamp control strategy is the crossroad signal lamp control strategy, counting the number of vehicles at the crossroad to obtain a vehicle number counting result, judging according to the vehicle number counting result, and outputting a second signal lamp instruction.

Description

Traffic signal lamp control method, device, equipment and storage medium
Technical Field
The invention relates to the field of OCR recognition, in particular to a control method, a control device, control equipment and a storage medium of a traffic signal lamp.
Background
The OCR image recognition algorithm tends to be mature, is widely used in various industries, provides great convenience for life of people, and has great influence on urban traffic due to rapid urban development, increasing number of automobiles and great influence on road utilization rate.
In the prior art, traffic lights are switched at fixed times, and there may be three typical unreasonable situations, a situation: when no non-motor vehicle exists, the signal lamp of the motor vehicle is red, and the motor vehicle is in an empty state; case two: when no motor vehicle exists, the pedestrian signal lamp is red, and the non-motor vehicle is in an empty state; case three: the crossroad has more transverse vehicles, the congestion condition occurs, the longitudinal vehicles are fewer or even no vehicles, but the traffic lights show longitudinal passing and transverse waiting. And part of pedestrian crossing signal lamps have a pedestrian prompting function, so that the problem of the second condition is solved, other two conditions frequently occur on urban roads, the utilization rate of the urban roads is low, and the traveling efficiency of people is reduced.
Disclosure of Invention
The invention provides a traffic signal lamp control method, a traffic signal lamp control device, traffic signal lamp control equipment and a traffic signal lamp storage medium, which are used for monitoring traffic conditions in real time through an OCR image recognition algorithm and analyzing and scheduling the traffic signal lamps according to the real-time conditions of current intersections, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved.
The invention provides a control method of a traffic signal lamp in a first aspect, which comprises the following steps: extracting real-time data of an intersection to be passed through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles; analyzing the real-time data of the intersection to be passed to generate an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy; when the signal lamp control strategy is a non-intersection signal lamp control strategy, counting the number of pedestrians at a non-intersection to obtain a pedestrian number counting result, judging according to the pedestrian number counting result, and outputting a first signal lamp instruction; and when the signal lamp control strategy is an intersection signal lamp control strategy, counting the number of vehicles at the intersection to obtain a vehicle number counting result, judging according to the vehicle number counting result, and outputting a second signal lamp instruction.
Optionally, in a first implementation manner of the first aspect of the present invention, the analyzing the real-time data of the intersection to be passed to generate an analysis result, determining the analysis result, and selecting a signal lamp control policy, where the signal lamp control policy includes an intersection signal lamp control policy and a non-intersection signal lamp control policy, and the method includes: acquiring real-time data of the intersection to be passed, and preprocessing the real-time data of the intersection to be passed, wherein the preprocessing process comprises the steps of removing blur, enhancing an image and correcting light; identifying pedestrians through a face identification algorithm, identifying license plate numbers of vehicles through an OCR image identification algorithm to obtain identification data, analyzing different shooting road sections corresponding to the identification data, and generating an analysis result; judging the analysis result according to a preset classification standard, and selecting a non-crossroad signal lamp control strategy when the analysis result belongs to a non-crossroad section; and when the analysis result belongs to the crossroad section, selecting a crossroad signal lamp control strategy.
Optionally, in a second implementation manner of the first aspect of the present invention, when the signal lamp control strategy is a non-intersection signal lamp control strategy, counting the number of pedestrians at a non-intersection to obtain a statistical result of the number of pedestrians, performing a judgment according to the statistical result of the number of pedestrians, and outputting the first signal lamp instruction includes: carrying out face recognition through an image processing tool library OpenCV, carrying out target image detection according to preset human eyes and a face classifier, extracting face contour data of pedestrians to obtain a face recognition result, and counting the number of people to pass according to the face recognition result to obtain a pedestrian number counting result; when the statistical result of the number of the pedestrians exceeds a preset standard number of the pedestrians, generating a pedestrian passing pre-instruction; when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians, comparing the vehicle passing time length with the preset standard vehicle passing time length to generate a vehicle passing pre-instruction or a pedestrian passing pre-instruction; and outputting a first signal lamp instruction according to the vehicle passing pre-instruction or the pedestrian passing pre-instruction.
Optionally, in a third implementation manner of the first aspect of the present invention, when the statistical result of the number of pedestrians is less than a preset standard number of pedestrians, the comparing the vehicle passing time length with a preset standard vehicle passing time length, and the generating the vehicle passing pre-command or the pedestrian passing pre-command includes: when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is smaller than the preset standard vehicle passing time length, generating a vehicle passing pre-instruction; and when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is greater than or equal to the preset standard vehicle passing time length, generating a pedestrian passing pre-instruction.
Optionally, in a fourth implementation manner of the first aspect of the present invention, when the signal lamp control strategy is an intersection signal lamp control strategy, counting the number of vehicles at an intersection to obtain a vehicle number statistical result, performing judgment according to the vehicle number statistical result, and outputting the second signal lamp instruction includes: recognizing license plate numbers of vehicles transversely and longitudinally at the crossroad through an OCR recognition algorithm, obtaining the corresponding vehicle number according to the recognized license plate number, and generating a vehicle number statistical result, wherein the vehicle number statistical result comprises the transverse vehicle number and the longitudinal vehicle number; judging based on the vehicle quantity statistical result, and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles, judging according to the vehicle passing duration of the longitudinal vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; when the number of the transverse vehicles is larger than that of the longitudinal vehicles, judging according to the vehicle passing duration of the transverse vehicles to generate a longitudinal vehicle passing pre-command or a transverse vehicle passing pre-command; when the number of the transverse vehicles is zero, generating a longitudinal vehicle passing pre-command; and outputting a second signal lamp instruction according to the longitudinal vehicle communication pre-instruction or the transverse vehicle communication pre-instruction.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the determining based on the statistical result of the number of vehicles, and when the number of transverse vehicles is smaller than the number of longitudinal vehicles, determining according to the vehicle passage duration of longitudinal vehicles, and generating a longitudinal vehicle passage pre-command or a transverse vehicle passage pre-command includes: when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is smaller than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command; and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is longer than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command.
Optionally, in a sixth implementation manner of the first aspect of the present invention, when the number of the transverse vehicles is greater than the number of the longitudinal vehicles, the determining according to the vehicle passage duration of the transverse vehicles, and generating the longitudinal vehicle passage preliminary instruction or the transverse vehicle passage preliminary instruction includes: when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is smaller than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is greater than the preset standard vehicle passing time, generating a longitudinal vehicle passing pre-command.
A second aspect of the present invention provides a control apparatus for a traffic signal lamp, including: the system comprises an extraction module, a monitoring module and a control module, wherein the extraction module is used for extracting real-time data of an intersection to be passed through preset monitoring equipment, and the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles; the analysis module is used for analyzing the real-time data of the intersection to be passed, generating an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy; the first output module is used for counting the number of pedestrians at the non-intersection to obtain a statistical result of the number of the pedestrians, judging according to the statistical result of the number of the pedestrians and outputting a first signal lamp instruction when the signal lamp control strategy is a non-intersection signal lamp control strategy; and the second output module is used for counting the number of vehicles at the crossroad to obtain a vehicle number counting result when the signal lamp control strategy is a crossroad signal lamp control strategy, judging according to the vehicle number counting result and outputting a second signal lamp instruction.
Optionally, in a first implementation manner of the second aspect of the present invention, the analysis module includes: the preprocessing unit is used for acquiring the real-time data of the intersection to be passed and preprocessing the real-time data of the intersection to be passed, wherein the preprocessing process comprises the steps of removing blur, enhancing images and correcting light rays; the identification unit is used for identifying pedestrians through a face identification algorithm, identifying license plate numbers of vehicles through an OCR image identification algorithm to obtain identification data, analyzing different shooting road sections corresponding to the identification data and generating an analysis result; the first selection unit is used for judging the analysis result according to a preset classification standard and selecting a non-crossroad signal lamp control strategy when the analysis result belongs to a non-crossroad section; and the second selection unit is used for selecting a crossroad signal lamp control strategy when the analysis result belongs to a crossroad section.
Optionally, in a second implementation manner of the second aspect of the present invention, the first output module includes: the first statistical unit is used for carrying out face recognition through an image processing tool library OpenCV, carrying out target image detection according to preset human eyes and a face classifier, extracting face contour data of pedestrians to obtain a face recognition result, and counting the number of people to pass according to the face recognition result to obtain a pedestrian number counting result; the first generation unit is used for generating a pedestrian passing pre-instruction when the statistical result of the number of the pedestrians exceeds the preset standard number of the pedestrians; the second generation unit is used for comparing the vehicle passing time length with a preset standard vehicle passing time length to generate a vehicle passing pre-instruction or a pedestrian passing pre-instruction when the pedestrian number statistical result is smaller than the preset standard pedestrian number; and the first output unit is used for outputting a first signal lamp instruction according to the vehicle passing pre-instruction or the pedestrian passing pre-instruction.
Optionally, in a third implementation manner of the second aspect of the present invention, the second generating unit is specifically configured to: when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is smaller than the preset standard vehicle passing time length, generating a vehicle passing pre-instruction; and when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is greater than or equal to the preset standard vehicle passing time length, generating a pedestrian passing pre-instruction.
Optionally, in a fourth implementation manner of the second aspect of the present invention, the second output module includes: the second statistical unit is used for recognizing the license plate numbers of the vehicles in the transverse direction and the longitudinal direction of the crossroad through an OCR recognition algorithm, obtaining the corresponding vehicle number according to the recognized license plate number, and generating a vehicle number statistical result, wherein the vehicle number statistical result comprises the transverse vehicle number and the longitudinal vehicle number; the third generating unit is used for judging based on the vehicle quantity statistical result, and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles, judging according to the vehicle passing duration of the longitudinal vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; the fourth generating unit is used for judging according to the vehicle passing time length of the transverse vehicles when the number of the transverse vehicles is larger than that of the longitudinal vehicles, and generating a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; a fifth generating unit, configured to generate a longitudinal vehicle passing pre-command when the number of the transverse vehicles is zero; and the second output unit is used for outputting a second signal lamp instruction according to the longitudinal vehicle communication pre-instruction or the transverse vehicle communication pre-instruction.
Optionally, in a fifth implementation manner of the second aspect of the present invention, the third generating unit is specifically configured to: when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is smaller than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command; and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is longer than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command.
Optionally, in a sixth implementation manner of the second aspect of the present invention, the fourth generating unit is specifically configured to: when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is smaller than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is greater than the preset standard vehicle passing time, generating a longitudinal vehicle passing pre-command.
A third aspect of the present invention provides a control apparatus of a traffic signal lamp, including: a memory and at least one processor, the memory having instructions stored therein; the at least one processor invokes the instructions in the memory to cause the control device of the traffic signal to execute the above-described control method of the traffic signal.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to execute the above-described control method of a traffic signal lamp.
In the technical scheme provided by the invention, the real-time data of the intersection to be passed are extracted through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles; analyzing the real-time data of the intersection to be passed to generate an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy; when the signal lamp control strategy is a non-intersection signal lamp control strategy, counting the number of pedestrians at a non-intersection to obtain a pedestrian number counting result, judging according to the pedestrian number counting result, and outputting a first signal lamp instruction; and when the signal lamp control strategy is an intersection signal lamp control strategy, counting the number of vehicles at the intersection to obtain a vehicle number counting result, judging according to the vehicle number counting result, and outputting a second signal lamp instruction. In the embodiment of the invention, the traffic condition is monitored in real time through an OCR image recognition algorithm, and the traffic signal lamps are analyzed and dispatched according to the real-time condition of the current intersection, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a method for controlling a traffic signal lamp according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of another embodiment of a method for controlling a traffic signal lamp according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of an embodiment of a traffic signal control apparatus according to an embodiment of the present invention;
fig. 4 is a schematic diagram of another embodiment of the control device of the traffic signal lamp in the embodiment of the invention;
fig. 5 is a schematic diagram of an embodiment of a control device of a traffic signal lamp in the embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a traffic signal lamp control method, a traffic signal lamp control device, traffic signal lamp control equipment and a storage medium, which are used for monitoring traffic conditions in real time through an OCR image recognition algorithm and analyzing and scheduling the traffic signal lamps according to the real-time conditions of current intersections, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of an embodiment of the present invention is described below, and referring to fig. 1, an embodiment of a method for controlling a traffic signal lamp according to an embodiment of the present invention includes:
101. the method comprises the steps of extracting real-time data of the intersection to be passed through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles.
The server extracts real-time data of the intersection to be passed through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles. In this embodiment, a preset monitoring device is disposed near a signal lamp for extracting field data, and an Optical Character Recognition (OCR) algorithm is used to monitor a situation near the current signal lamp in real time, where a main monitoring target is a natural person and a motor vehicle, and a non-motor vehicle and the natural person may exist at the same time, so that only the natural person needs to be monitored, OCR refers to a process of analyzing and recognizing an image file of Text data to obtain Text and layout information, i.e., recognizing characters in an image and returning the characters in a Text form, and has a wide application Scene, such as Scene image character Recognition, document image Recognition, card identification, bill Recognition, and the like, and Scene character Recognition (STR) does not need to be customized for a special Scene, and can recognize characters in any Scene image.
It is to be understood that the executing subject of the present invention may be a control device of a traffic light, and may also be a terminal or a server, which is not limited herein. The embodiment of the present invention is described by taking a server as an execution subject.
102. Analyzing the real-time data of the intersection to be passed to generate an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy.
The server analyzes the real-time data of the intersection to be passed, generates an analysis result, judges the analysis result and selects a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy. Specifically, the server acquires real-time data of the intersection to be passed and preprocesses the real-time data of the intersection to be passed, wherein the preprocessing process comprises the steps of removing blur, enhancing images and correcting light; the server identifies the pedestrians through a face identification algorithm, identifies the license plate numbers of the vehicles through an OCR image identification algorithm to obtain identification data, analyzes different shooting road sections corresponding to the identification data and generates an analysis result; the server judges the analysis result according to a preset classification standard, and selects a non-crossroad signal lamp control strategy when the analysis result belongs to a non-crossroad section; and when the analysis result belongs to the crossroad section, selecting a crossroad signal lamp control strategy. The preprocessing process comprises geometric transformation, distortion correction, blur removal, image enhancement, light ray correction and the like, and the preprocessing is to make the apparent characteristics of each image, such as color distribution, integral brightness, size and the like, as consistent as possible on the premise of not changing the essential information borne by the image as far as possible so as to facilitate the subsequent processing, for example, when the number of the automobile license plate is identified from the image, the license plate needs to be found out from the image first, then the license plate is divided, each number is divided respectively, and finally the statistical data of the number of the vehicles is obtained.
The real-time data extracted by the monitoring equipment is a plurality of intersections and a plurality of groups of data extracted by the monitoring equipment, so that the data needs to be classified according to preset classification standards, and the monitoring data at the intersections and the monitoring data at non-intersections are distinguished. The crossroad section refers in particular to a crossroad section where motor vehicles pass, and comprises the driving condition of transverse and longitudinal vehicles on a lane, the non-crossroad section comprises sections where vehicles such as pedestrian crossings and the like and pedestrians collect, the OCR image recognition algorithm provides assistance in various scenes in life, and the life convenience is improved.
103. When the signal lamp control strategy is a non-intersection signal lamp control strategy, the number of pedestrians at a non-intersection is counted to obtain a statistical result of the number of the pedestrians, judgment is carried out according to the statistical result of the number of the pedestrians, and a first signal lamp instruction is output.
When the signal lamp control strategy is a non-intersection signal lamp control strategy, the server counts the number of pedestrians at the non-intersection to obtain a statistical result of the number of the pedestrians, judges according to the statistical result of the number of the pedestrians, and outputs a first signal lamp instruction. Since the main participants of road traffic are motor vehicles, the default road is motor vehicle traffic, the embodiment adopts an OCR recognition algorithm to count the number of the pedestrians at the intersection to be passed in the road field, the number of the pedestrians to be passed in 10 seconds is counted, when the statistical result of the number of the pedestrians exceeds 10 people, a pedestrian passing pre-instruction is generated, when the statistical result of the number of the pedestrians is less than 10 people, and the time length for switching from the pedestrian traffic to the motor vehicle traffic last time is less than 5 minutes, a vehicle passing pre-instruction is generated, when the statistical result of the number of the pedestrians is less than 10 people, and the time length for switching from the pedestrian traffic to the motor vehicle traffic last time exceeds 5 minutes, a pedestrian passing pre-instruction is generated, and when the statistical result of the number of the pedestrians is.
104. And when the signal lamp control strategy is the crossroad signal lamp control strategy, counting the number of vehicles at the crossroad to obtain a vehicle number counting result, judging according to the vehicle number counting result, and outputting a second signal lamp instruction.
And when the signal lamp control strategy is the crossroad signal lamp control strategy, the server counts the number of vehicles at the crossroad to obtain a vehicle number counting result, judges according to the vehicle number counting result and outputs a second signal lamp instruction. Specifically, the server identifies license plate numbers of vehicles in the transverse direction and the longitudinal direction of the crossroad through an OCR (optical character recognition) algorithm, obtains the corresponding vehicle number according to the identified license plate number, and generates a vehicle number statistical result, wherein the vehicle number statistical result comprises the transverse vehicle number and the longitudinal vehicle number; the server judges based on the statistical result of the number of the vehicles, and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles, the server judges according to the vehicle passing duration of the longitudinal vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; when the number of the transverse vehicles is larger than that of the longitudinal vehicles, the server judges according to the vehicle passing duration of the transverse vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; when the number of the transverse vehicles is zero, the server generates a longitudinal vehicle passing pre-instruction; and the server outputs a second signal lamp instruction according to the longitudinal vehicle communication preaction or the transverse vehicle communication preaction.
The number plate number of the vehicle on the site lane is recognized and counted based on an OCR image recognition algorithm, so that the backlog condition of the transverse and longitudinal vehicles within 10 seconds is obtained, the number of the transverse and longitudinal vehicles which are about to pass through the intersection at present is counted, the transverse and longitudinal traffic signal indicator lamps are switched according to the comparison result by comparing the number of the transverse and longitudinal vehicles to be passed, and the condition that the transverse and longitudinal traffic signals are idle and blocked transversely is avoided. When the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is smaller than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command; when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is larger than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is smaller than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is greater than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command. Specifically, when the number of transverse vehicles is smaller than that of longitudinal vehicles and the vehicle passing time of the longitudinal vehicles is smaller than 5 minutes, generating a longitudinal vehicle passing pre-command; when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time of the longitudinal vehicles is longer than 5 minutes, generating a transverse vehicle passing pre-command; when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is less than 5 minutes, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is greater than 5 minutes, generating a longitudinal vehicle passing pre-command. For example, when the number of the transverse vehicles at the current intersection is 10, the number of the longitudinal vehicles is 15, and the time length from the last time of switching from the transverse traffic to the longitudinal traffic is longer than 5 minutes, a transverse vehicle traffic pre-command is generated, and after the time is counted down for 10 seconds, a signal lamp outputs the transverse vehicle traffic command.
In the embodiment of the invention, the traffic condition is monitored in real time through an OCR image recognition algorithm, and the traffic signal lamps are analyzed and dispatched according to the real-time condition of the current intersection, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved. This scheme can be applied to in the wisdom traffic field to promote the construction in wisdom city.
Referring to fig. 2, another embodiment of the method for controlling a traffic signal lamp according to the embodiment of the present invention includes:
201. the method comprises the steps of extracting real-time data of the intersection to be passed through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles.
The server extracts real-time data of the intersection to be passed through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles. In this embodiment, a preset monitoring device is disposed near a signal lamp for extracting field data, and an Optical Character Recognition (OCR) algorithm is used to monitor a situation near the current signal lamp in real time, where a main monitoring target is a natural person and a motor vehicle, and a non-motor vehicle and the natural person may exist at the same time, so that only the natural person needs to be monitored, OCR refers to a process of analyzing and recognizing an image file of Text data to obtain Text and layout information, i.e., recognizing characters in an image and returning the characters in a Text form, and has a wide application Scene, such as Scene image character Recognition, document image Recognition, card identification, bill Recognition, and the like, and Scene character Recognition (STR) does not need to be customized for a special Scene, and can recognize characters in any Scene image.
202. Analyzing the real-time data of the intersection to be passed to generate an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy.
The server analyzes the real-time data of the intersection to be passed, generates an analysis result, judges the analysis result and selects a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy. Specifically, the server acquires real-time data of the intersection to be passed and preprocesses the real-time data of the intersection to be passed, wherein the preprocessing process comprises the steps of removing blur, enhancing images and correcting light; the server identifies the pedestrians through a face identification algorithm, identifies the license plate numbers of the vehicles through an OCR image identification algorithm to obtain identification data, analyzes different shooting road sections corresponding to the identification data and generates an analysis result; the server judges the analysis result according to a preset classification standard, and selects a non-crossroad signal lamp control strategy when the analysis result belongs to a non-crossroad section; and when the analysis result belongs to the crossroad section, selecting a crossroad signal lamp control strategy. The preprocessing process comprises geometric transformation, distortion correction, blur removal, image enhancement, light ray correction and the like, and the preprocessing is to make the apparent characteristics of each image, such as color distribution, integral brightness, size and the like, as consistent as possible on the premise of not changing the essential information borne by the image as far as possible so as to facilitate the subsequent processing, for example, when the number of the automobile license plate is identified from the image, the license plate needs to be found out from the image first, then the license plate is divided, each number is divided respectively, and finally the statistical data of the number of the vehicles is obtained.
The real-time data extracted by the monitoring equipment is a plurality of intersections and a plurality of groups of data extracted by the monitoring equipment, so that the data needs to be classified according to preset classification standards, and the monitoring data at the intersections and the monitoring data at non-intersections are distinguished. The crossroad section refers in particular to a crossroad section where motor vehicles pass, and comprises the driving condition of transverse and longitudinal vehicles on a lane, the non-crossroad section comprises sections where vehicles such as pedestrian crossings and the like and pedestrians collect, the OCR image recognition algorithm provides assistance in various scenes in life, and the life convenience is improved.
203. The method comprises the steps of carrying out face recognition through an image processing tool library OpenCV, carrying out target image detection according to preset human eyes and a face classifier, extracting face contour data of pedestrians to obtain a face recognition result, and counting the number of people to pass according to the face recognition result to obtain a pedestrian number counting result.
The server carries out face recognition through an image processing tool library OpenCV, carries out target image detection according to preset human eyes and a face classifier, extracts face contour data of pedestrians to obtain a face recognition result, and carries out statistics on the number of people to pass according to the face recognition result to obtain a pedestrian number statistical result. The common video people counting process mainly comprises the following steps: the method includes the steps of obtaining video image data from a camera or a video file, segmenting a moving area in the video image from the video image, and obtaining a specific target according to target feature analysis.
204. And when the statistical result of the number of the pedestrians exceeds the preset standard number of the pedestrians, generating a pedestrian passing pre-instruction.
And when the statistical result of the number of the pedestrians exceeds the preset standard number of the pedestrians, the server generates a pedestrian passing pre-instruction. When the statistical result of the number of pedestrians exceeds 10 people, a pedestrian passing pre-instruction is generated, the pre-instruction in the embodiment comprises a 10-second countdown, and a signal lamp outputs a final instruction after the 10-second countdown is finished, for example, when the number of people waiting to pass at the current intersection within 10 seconds is 12, the pedestrian passes through a vehicle forbidden countdown 10-second stage directly, and the signal lamp outputs a pedestrian passing instruction after 10 seconds.
205. And when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians, comparing the vehicle passing time length with the preset standard vehicle passing time length to generate a vehicle passing pre-instruction or a pedestrian passing pre-instruction.
When the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians, the server compares the vehicle passing time length with the preset standard vehicle passing time length to generate a vehicle passing pre-instruction or a pedestrian passing pre-instruction. When the statistical result of the number of pedestrians is less than 10 people and the time length from the last time of switching from the pedestrian traffic to the motor vehicle traffic is less than 5 minutes, a vehicle traffic pre-instruction is generated, when the statistical result of the number of pedestrians is less than 10 people and the time length from the last time of switching from the pedestrian traffic to the motor vehicle traffic exceeds 5 minutes, the pedestrian traffic pre-instruction is generated, and when the statistical result of the number of pedestrians is zero, no operation is performed. For example, the number of people waiting for passing at the current intersection within 10 seconds is 8, the passing time of the motor vehicle is 6 minutes, the passing time of the motor vehicle is greater than the preset 5 minutes, the pedestrian passing vehicle enters a 10-second stage of the count-down of the disabled vehicle, and a pedestrian passing instruction is output by a signal lamp after 10 seconds.
206. And outputting a first signal lamp instruction according to the vehicle passing pre-instruction or the pedestrian passing pre-instruction.
The server outputs a first signal lamp instruction according to the vehicle passing pre-instruction or the pedestrian passing pre-instruction. And finally outputting a first signal lamp instruction after the countdown of 10 seconds is finished, namely outputting a vehicle passing instruction or a pedestrian passing instruction.
207. And when the signal lamp control strategy is the crossroad signal lamp control strategy, counting the number of vehicles at the crossroad to obtain a vehicle number counting result, judging according to the vehicle number counting result, and outputting a second signal lamp instruction.
And when the signal lamp control strategy is the crossroad signal lamp control strategy, the server counts the number of vehicles at the crossroad to obtain a vehicle number counting result, judges according to the vehicle number counting result and outputs a second signal lamp instruction. Specifically, the server identifies license plate numbers of vehicles in the transverse direction and the longitudinal direction of the crossroad through an OCR (optical character recognition) algorithm, obtains the corresponding vehicle number according to the identified license plate number, and generates a vehicle number statistical result, wherein the vehicle number statistical result comprises the transverse vehicle number and the longitudinal vehicle number; the server judges based on the statistical result of the number of the vehicles, and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles, the server judges according to the vehicle passing duration of the longitudinal vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; when the number of the transverse vehicles is larger than that of the longitudinal vehicles, the server judges according to the vehicle passing duration of the transverse vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction; when the number of the transverse vehicles is zero, the server generates a longitudinal vehicle passing pre-instruction; and the server outputs a second signal lamp instruction according to the longitudinal vehicle communication preaction or the transverse vehicle communication preaction.
The number plate number of the vehicle on the site lane is recognized and counted based on an OCR image recognition algorithm, so that the backlog condition of the transverse and longitudinal vehicles within 10 seconds is obtained, the number of the transverse and longitudinal vehicles which are about to pass through the intersection at present is counted, the transverse and longitudinal traffic signal indicator lamps are switched according to the comparison result by comparing the number of the transverse and longitudinal vehicles to be passed, and the condition that the transverse and longitudinal traffic signals are idle and blocked transversely is avoided. When the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is smaller than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command; when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is larger than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is smaller than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is greater than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command. Specifically, when the number of transverse vehicles is smaller than that of longitudinal vehicles and the vehicle passing time of the longitudinal vehicles is smaller than 5 minutes, generating a longitudinal vehicle passing pre-command; when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time of the longitudinal vehicles is longer than 5 minutes, generating a transverse vehicle passing pre-command; when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is less than 5 minutes, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is greater than 5 minutes, generating a longitudinal vehicle passing pre-command. For example, when the number of the transverse vehicles at the current intersection is 10, the number of the longitudinal vehicles is 15, and the time length from the last time of switching from the transverse traffic to the longitudinal traffic is longer than 5 minutes, a transverse vehicle traffic pre-command is generated, and after the time is counted down for 10 seconds, a signal lamp outputs the transverse vehicle traffic command.
In the embodiment of the invention, the traffic condition is monitored in real time through an OCR image recognition algorithm, and the traffic signal lamps are analyzed and dispatched according to the real-time condition of the current intersection, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved. This scheme can be applied to in the wisdom traffic field to promote the construction in wisdom city.
With reference to fig. 3, the method for controlling a traffic signal lamp in an embodiment of the present invention is described above, and a control device for a traffic signal lamp in an embodiment of the present invention is described below, where an embodiment of the control device for a traffic signal lamp in an embodiment of the present invention includes:
the extraction module 301 is configured to extract real-time data of an intersection to be passed through preset monitoring equipment, where the real-time data of the intersection to be passed include the number of pedestrians, the number of vehicles, and the vehicle passing duration;
the analysis module 302 is configured to analyze real-time data of the intersection to be passed, generate an analysis result, determine the analysis result, and select a signal lamp control strategy, where the signal lamp control strategy includes an intersection signal lamp control strategy and a non-intersection signal lamp control strategy;
the first output module 303 is configured to, when the signal lamp control strategy is a non-intersection signal lamp control strategy, count the number of pedestrians at a non-intersection to obtain a statistical result of the number of pedestrians, perform judgment according to the statistical result of the number of pedestrians, and output a first signal lamp instruction;
and the second output module 304 is configured to, when the signal lamp control strategy is an intersection signal lamp control strategy, count the number of vehicles at the intersection to obtain a vehicle number statistical result, perform judgment according to the vehicle number statistical result, and output a second signal lamp instruction.
In the embodiment of the invention, the traffic condition is monitored in real time through an OCR image recognition algorithm, and the traffic signal lamps are analyzed and dispatched according to the real-time condition of the current intersection, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved. This scheme can be applied to in the wisdom traffic field to promote the construction in wisdom city.
Referring to fig. 4, another embodiment of the control device for a traffic signal lamp according to the embodiment of the present invention includes:
the extraction module 301 is configured to extract real-time data of an intersection to be passed through preset monitoring equipment, where the real-time data of the intersection to be passed include the number of pedestrians, the number of vehicles, and the vehicle passing duration;
the analysis module 302 is configured to analyze real-time data of the intersection to be passed, generate an analysis result, determine the analysis result, and select a signal lamp control strategy, where the signal lamp control strategy includes an intersection signal lamp control strategy and a non-intersection signal lamp control strategy;
the first output module 303 is configured to, when the signal lamp control strategy is a non-intersection signal lamp control strategy, count the number of pedestrians at a non-intersection to obtain a statistical result of the number of pedestrians, perform judgment according to the statistical result of the number of pedestrians, and output a first signal lamp instruction;
and the second output module 304 is configured to, when the signal lamp control strategy is an intersection signal lamp control strategy, count the number of vehicles at the intersection to obtain a vehicle number statistical result, perform judgment according to the vehicle number statistical result, and output a second signal lamp instruction.
Optionally, the analysis module 302 includes:
the preprocessing unit 3021 is configured to obtain real-time data of the intersection to be passed, and preprocess the real-time data of the intersection to be passed, where the preprocessing includes blur removal, image enhancement, and light correction;
the recognition unit 3022 is configured to recognize pedestrians through a face recognition algorithm, recognize the license plate number of the vehicle through an OCR image recognition algorithm to obtain recognition data, analyze different shooting road sections corresponding to the recognition data, and generate an analysis result;
the first selecting unit 3023 is configured to determine an analysis result according to a preset classification standard, and select a non-intersection signal lamp control strategy when the analysis result belongs to a non-intersection road segment;
a second selecting unit 3024 configured to select an intersection signal light control strategy when the analysis result belongs to the intersection section.
Optionally, the first output module 303 includes:
the first statistical unit 3031 is configured to perform face recognition through an image processing tool library OpenCV, perform target image detection according to preset human eyes and a face classifier, extract face contour data of pedestrians, obtain a face recognition result, and perform statistics on the number of people to pass according to the face recognition result to obtain a pedestrian number statistical result;
a first generating unit 3032, configured to generate a pedestrian passing pre-instruction when the statistical result of the number of pedestrians exceeds a preset standard number of pedestrians;
a second generating unit 3033, configured to compare the vehicle passing time length with a preset standard vehicle passing time length when the statistical result of the number of pedestrians is smaller than the preset standard number of pedestrians, and generate a vehicle passing pre-instruction or a pedestrian passing pre-instruction;
the first output unit 3034 is configured to output a first signal lamp instruction according to the vehicle passing pre-instruction or the pedestrian passing pre-instruction.
Optionally, the second generating unit 3033 is specifically configured to:
when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is smaller than the preset standard vehicle passing time length, generating a vehicle passing pre-command; and when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is greater than or equal to the preset standard vehicle passing time length, generating a pedestrian passing pre-instruction.
Optionally, the second output module 304 includes:
a second statistical unit 3041, configured to recognize license plate numbers of vehicles in the transverse and longitudinal directions at the intersection through an OCR recognition algorithm, obtain the number of corresponding vehicles according to the number of recognized license plates, and generate a vehicle number statistical result, where the vehicle number statistical result includes the number of transverse vehicles and the number of longitudinal vehicles;
a third generating unit 3042, configured to perform judgment based on the statistical result of the number of vehicles, and when the number of transverse vehicles is smaller than the number of longitudinal vehicles, perform judgment according to the vehicle passing duration of the longitudinal vehicles, and generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction;
a fourth generating unit 3043, configured to, when the number of the horizontal vehicles is greater than the number of the vertical vehicles, perform judgment according to the vehicle passing duration of the horizontal vehicle, and generate a vertical vehicle passing pre-instruction or a horizontal vehicle passing pre-instruction;
a fifth generating unit 3044 for generating a longitudinal vehicle passing pre-instruction when the number of lateral vehicles is zero;
a second output unit 3045 configured to output a second signal light instruction according to the longitudinal vehicle communication pre-instruction or the lateral vehicle communication pre-instruction.
Optionally, the third generating unit 3042 is specifically configured to:
when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is smaller than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command; and when the number of the transverse vehicles is less than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is greater than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command.
Optionally, the fourth generating unit 3043 is specifically configured to:
when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is smaller than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command; and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is greater than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command.
In the embodiment of the invention, the traffic condition is monitored in real time through an OCR image recognition algorithm, and the traffic signal lamps are analyzed and dispatched according to the real-time condition of the current intersection, so that the utilization rate of urban roads is improved, the problem of urban road congestion is relieved, and the travel efficiency of people is improved. This scheme can be applied to in the wisdom traffic field to promote the construction in wisdom city.
Fig. 3 and 4 describe the control device of the traffic signal lamp in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the control device of the traffic signal lamp in the embodiment of the present invention is described in detail from the perspective of the hardware processing.
Fig. 5 is a schematic structural diagram of a control device of a traffic signal according to an embodiment of the present invention, where the control device 500 of the traffic signal may have relatively large differences due to different configurations or performances, and may include one or more processors (CPUs) 510 (e.g., one or more processors) and a memory 520, and one or more storage media 530 (e.g., one or more mass storage devices) storing applications 533 or data 532. Memory 520 and storage media 530 may be, among other things, transient or persistent storage. The program stored in the storage medium 530 may include one or more modules (not shown), each of which may include a series of instruction operations in the control apparatus 500 for a traffic signal lamp. Still further, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the control device 500 of the traffic signal lamp.
The control apparatus 500 for traffic lights may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input-output interfaces 560, and/or one or more operating systems 531, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. It will be appreciated by those skilled in the art that the arrangement of the control device of the traffic signal shown in fig. 5 does not constitute a limitation of the control device of the traffic signal, and may comprise more or less components than those shown, or some components may be combined, or a different arrangement of components.
The invention further provides a control device of a traffic signal lamp, the computer device comprises a memory and a processor, the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the steps of the control method of the traffic signal lamp in the above embodiments.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and which may also be a volatile computer-readable storage medium, having stored therein instructions that, when executed on a computer, cause the computer to perform the steps of the method for controlling a traffic signal.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A control method of a traffic signal lamp is characterized by comprising the following steps:
extracting real-time data of an intersection to be passed through preset monitoring equipment, wherein the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles;
analyzing the real-time data of the intersection to be passed to generate an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy;
when the signal lamp control strategy is a non-intersection signal lamp control strategy, counting the number of pedestrians at a non-intersection to obtain a pedestrian number counting result, judging according to the pedestrian number counting result, and outputting a first signal lamp instruction;
and when the signal lamp control strategy is an intersection signal lamp control strategy, counting the number of vehicles at the intersection to obtain a vehicle number counting result, judging according to the vehicle number counting result, and outputting a second signal lamp instruction.
2. The method for controlling traffic signal lamps according to claim 1, wherein the analyzing the real-time data of the intersection to be passed to generate an analysis result, judging the analysis result, and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises an intersection signal lamp control strategy and a non-intersection signal lamp control strategy, and comprises the following steps:
acquiring real-time data of the intersection to be passed, and preprocessing the real-time data of the intersection to be passed, wherein the preprocessing process comprises the steps of removing blur, enhancing an image and correcting light;
identifying pedestrians through a face identification algorithm, identifying license plate numbers of vehicles through an OCR image identification algorithm to obtain identification data, analyzing different shooting road sections corresponding to the identification data, and generating an analysis result;
judging the analysis result according to a preset classification standard, and selecting a non-crossroad signal lamp control strategy when the analysis result belongs to a non-crossroad section;
and when the analysis result belongs to the crossroad section, selecting a crossroad signal lamp control strategy.
3. The method according to claim 1, wherein when the signal lamp control strategy is a non-intersection signal lamp control strategy, counting the number of pedestrians at a non-intersection to obtain a statistical result of the number of pedestrians, and performing a judgment according to the statistical result of the number of pedestrians to output a first signal lamp command comprises:
carrying out face recognition through an image processing tool library OpenCV, carrying out target image detection according to preset human eyes and a face classifier, extracting face contour data of pedestrians to obtain a face recognition result, and counting the number of people to pass according to the face recognition result to obtain a pedestrian number counting result;
when the statistical result of the number of the pedestrians exceeds a preset standard number of the pedestrians, generating a pedestrian passing pre-instruction;
when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians, comparing the vehicle passing time length with the preset standard vehicle passing time length to generate a vehicle passing pre-instruction or a pedestrian passing pre-instruction;
and outputting a first signal lamp instruction according to the vehicle passing pre-instruction or the pedestrian passing pre-instruction.
4. The method for controlling a traffic signal lamp according to claim 3, wherein when the statistical result of the number of pedestrians is smaller than a preset standard number of pedestrians, the comparing the vehicle passing time length with a preset standard vehicle passing time length, and the generating a vehicle passing pre-command or a pedestrian passing pre-command comprises:
when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is smaller than the preset standard vehicle passing time length, generating a vehicle passing pre-instruction;
and when the statistical result of the number of the pedestrians is smaller than the preset standard number of the pedestrians and the vehicle passing time length is greater than or equal to the preset standard vehicle passing time length, generating a pedestrian passing pre-instruction.
5. The method for controlling a traffic signal lamp according to claim 1, wherein when the signal lamp control strategy is an intersection signal lamp control strategy, counting the number of vehicles at an intersection to obtain a vehicle number statistical result, and outputting a second signal lamp instruction according to the judgment made by the vehicle number statistical result comprises:
recognizing license plate numbers of vehicles transversely and longitudinally at the crossroad through an OCR recognition algorithm, obtaining the corresponding vehicle number according to the recognized license plate number, and generating a vehicle number statistical result, wherein the vehicle number statistical result comprises the transverse vehicle number and the longitudinal vehicle number;
judging based on the vehicle quantity statistical result, and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles, judging according to the vehicle passing duration of the longitudinal vehicles to generate a longitudinal vehicle passing pre-instruction or a transverse vehicle passing pre-instruction;
when the number of the transverse vehicles is larger than that of the longitudinal vehicles, judging according to the vehicle passing duration of the transverse vehicles to generate a longitudinal vehicle passing pre-command or a transverse vehicle passing pre-command;
when the number of the transverse vehicles is zero, generating a longitudinal vehicle passing pre-command;
and outputting a second signal lamp instruction according to the longitudinal vehicle communication pre-instruction or the transverse vehicle communication pre-instruction.
6. The method for controlling a traffic signal lamp according to claim 5, wherein the judging based on the statistical result of the number of vehicles is performed, when the number of the transverse vehicles is smaller than the number of the longitudinal vehicles, the judging is performed according to the vehicle passing time length of the longitudinal vehicles, and the generating of the longitudinal vehicle passing pre-command or the transverse vehicle passing pre-command comprises:
when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is smaller than the preset standard vehicle passing time length, generating a longitudinal vehicle passing pre-command;
and when the number of the transverse vehicles is smaller than that of the longitudinal vehicles and the vehicle passing time length of the longitudinal vehicles is longer than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command.
7. The method for controlling a traffic signal lamp according to claim 5, wherein when the number of the transverse vehicles is greater than the number of the longitudinal vehicles, the judgment is performed according to the vehicle passing time length of the transverse vehicles, and the generation of the longitudinal vehicle passing pre-command or the transverse vehicle passing pre-command comprises:
when the number of the transverse vehicles is larger than that of the longitudinal vehicles and the vehicle passing time length of the transverse vehicles is smaller than the preset standard vehicle passing time length, generating a transverse vehicle passing pre-command;
and when the number of the transverse vehicles is greater than that of the longitudinal vehicles and the vehicle passing time of the transverse vehicles is greater than the preset standard vehicle passing time, generating a longitudinal vehicle passing pre-command.
8. A control apparatus of a traffic signal, characterized by comprising:
the system comprises an extraction module, a monitoring module and a control module, wherein the extraction module is used for extracting real-time data of an intersection to be passed through preset monitoring equipment, and the real-time data of the intersection to be passed comprise the number of pedestrians, the number of vehicles and the passing time of the vehicles;
the analysis module is used for analyzing the real-time data of the intersection to be passed, generating an analysis result, judging the analysis result and selecting a signal lamp control strategy, wherein the signal lamp control strategy comprises a crossroad signal lamp control strategy and a non-crossroad signal lamp control strategy;
the first output module is used for counting the number of pedestrians at the non-intersection to obtain a statistical result of the number of the pedestrians, judging according to the statistical result of the number of the pedestrians and outputting a first signal lamp instruction when the signal lamp control strategy is a non-intersection signal lamp control strategy;
and the second output module is used for counting the number of vehicles at the crossroad to obtain a vehicle number counting result when the signal lamp control strategy is a crossroad signal lamp control strategy, judging according to the vehicle number counting result and outputting a second signal lamp instruction.
9. A control apparatus of a traffic signal, characterized by comprising: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invokes the instructions in the memory to cause the traffic signal control apparatus to perform the traffic signal control method of any of claims 1-7.
10. A computer-readable storage medium having instructions stored thereon, wherein the instructions, when executed by a processor, implement a method of controlling a traffic signal lamp as claimed in any one of claims 1 to 7.
CN202110209006.XA 2021-02-25 2021-02-25 Traffic signal lamp control method, device, equipment and storage medium Pending CN112907992A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110209006.XA CN112907992A (en) 2021-02-25 2021-02-25 Traffic signal lamp control method, device, equipment and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110209006.XA CN112907992A (en) 2021-02-25 2021-02-25 Traffic signal lamp control method, device, equipment and storage medium

Publications (1)

Publication Number Publication Date
CN112907992A true CN112907992A (en) 2021-06-04

Family

ID=76108145

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110209006.XA Pending CN112907992A (en) 2021-02-25 2021-02-25 Traffic signal lamp control method, device, equipment and storage medium

Country Status (1)

Country Link
CN (1) CN112907992A (en)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114973661A (en) * 2022-05-16 2022-08-30 深圳市中建恒峰电子有限公司 Traffic signal lamp with intelligent control and traffic flow data storage functions
CN115440063A (en) * 2022-09-01 2022-12-06 的卢技术有限公司 Traffic signal lamp control method and device, computer equipment and storage medium

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20100047202A (en) * 2010-03-24 2010-05-07 주식회사 청림엔지니어링 Apparatus and method for controlling traffic signal-lamp in cross roads
CN101763734A (en) * 2010-01-21 2010-06-30 上海交通大学 Traffic signal light intelligent control system and control method thereof
KR101412214B1 (en) * 2014-04-21 2014-06-25 (주) 금성산업 Intelligent intersection traffic signal control system and method
CN208689753U (en) * 2018-10-11 2019-04-02 赵佳锦 Optimization-type intelligent traffic lamp regulator control system
CN109785643A (en) * 2019-03-08 2019-05-21 百度在线网络技术（北京）有限公司 Method, apparatus, storage medium and the terminal device that traffic lights is adjusted
CN111462505A (en) * 2020-03-30 2020-07-28 安徽嘉亨软件开发有限公司 Smart city system
CN111613070A (en) * 2019-02-25 2020-09-01 北京嘀嘀无限科技发展有限公司 Traffic signal lamp control method, traffic signal lamp control device, electronic equipment and computer storage medium

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101763734A (en) * 2010-01-21 2010-06-30 上海交通大学 Traffic signal light intelligent control system and control method thereof
KR20100047202A (en) * 2010-03-24 2010-05-07 주식회사 청림엔지니어링 Apparatus and method for controlling traffic signal-lamp in cross roads
KR101412214B1 (en) * 2014-04-21 2014-06-25 (주) 금성산업 Intelligent intersection traffic signal control system and method
CN208689753U (en) * 2018-10-11 2019-04-02 赵佳锦 Optimization-type intelligent traffic lamp regulator control system
CN111613070A (en) * 2019-02-25 2020-09-01 北京嘀嘀无限科技发展有限公司 Traffic signal lamp control method, traffic signal lamp control device, electronic equipment and computer storage medium
CN109785643A (en) * 2019-03-08 2019-05-21 百度在线网络技术（北京）有限公司 Method, apparatus, storage medium and the terminal device that traffic lights is adjusted
CN111462505A (en) * 2020-03-30 2020-07-28 安徽嘉亨软件开发有限公司 Smart city system

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114973661A (en) * 2022-05-16 2022-08-30 深圳市中建恒峰电子有限公司 Traffic signal lamp with intelligent control and traffic flow data storage functions
CN114973661B (en) * 2022-05-16 2024-05-10 深圳市中建恒峰电子有限公司 Traffic signal lamp with intelligent control and traffic flow data storage
CN115440063A (en) * 2022-09-01 2022-12-06 的卢技术有限公司 Traffic signal lamp control method and device, computer equipment and storage medium
CN115440063B (en) * 2022-09-01 2023-12-05 的卢技术有限公司 Traffic signal lamp control method, device, computer equipment and storage medium

Similar Documents

Publication Publication Date Title
Wei et al. Multi-vehicle detection algorithm through combining Harr and HOG features
CN110164152B (en) Traffic signal lamp control system for single-cross intersection
Jadhav et al. Smart traffic control system using image processing
Arunmozhi et al. Comparison of HOG, LBP and Haar-like features for on-road vehicle detection
CN107105207A (en) Target monitoring method, target monitoring device and video camera
CN112339773B (en) Monocular vision-based non-active lane departure early warning method and system
CN112907992A (en) Traffic signal lamp control method, device, equipment and storage medium
CN108197544B (en) Face analysis method, face filtering method, face analysis device, face filtering device, embedded equipment, medium and integrated circuit
CN109543648B (en) Method for extracting face in car passing picture
CN101369312B (en) Method and equipment for detecting intersection in image
US11482012B2 (en) Method for driving assistance and mobile device using the method
CN114329074B (en) Traffic energy efficiency detection method and system for ramp road section
Helala et al. Road boundary detection in challenging scenarios
KR102499340B1 (en) Hybrid video analysis device based on object filters and method
Wang et al. Vision-based highway traffic accident detection
CN113076852A (en) Vehicle-mounted snapshot processing system occupying bus lane based on 5G communication
CN112733851A (en) License plate recognition method for optimizing grain warehouse truck based on convolutional neural network
Gupta et al. Real-time traffic control and monitoring
Zhang et al. A front vehicle detection algorithm for intelligent vehicle based on improved gabor filter and SVM
Vinothini et al. Road sign recognition system for autonomous vehicle using Raspberry Pi
Anagnostopoulos et al. Intelligent traffic management through MPEG-7 vehicle flow surveillance
CN114494968A (en) Method and device for identifying abnormal intrusion behavior in forbidden area
Panda et al. Application of Image Processing In Road Traffic Control
CN114926791A (en) Method and device for detecting abnormal lane change of vehicles at intersection, storage medium and electronic equipment
CN112633062A (en) Deep learning bus lane occupation detection method based on embedded terminal

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication
RJ01 Rejection of invention patent application after publication

Application publication date: 20210604