CN110796865B - Intelligent traffic control method and device, electronic equipment and storage medium - Google Patents
Intelligent traffic control method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
At least one embodiment of the application provides an intelligent traffic control method, an intelligent traffic control device, electronic equipment and a storage medium, and relates to the technical field of intelligent traffic. The specific implementation scheme is as follows: acquiring source data provided by a plurality of data providing guidelines to intersections to be processed; acquiring time alignment relations among a plurality of data providers; performing time alignment processing on all source data according to the time alignment relation; determining traffic index data of the intersection to be processed according to the aligned source data; and determining a signal control scheme of a traffic signal machine at the intersection to be processed according to the traffic index data. By means of the technical scheme of at least one embodiment of the application, the technical problems that in the related technology, intersection calculation results are inaccurate due to the fact that source data of a plurality of different sources are directly aligned, and therefore the intelligent traffic optimization effect is not ideal are effectively solved.
Description
Technical Field
The present application relates to the field of traffic technologies, and in particular, to an intelligent traffic control method, apparatus, electronic device, and storage medium.
Background
With the continuous and high-speed development of national economy in China, the living standard of people is continuously improved, and the number of private vehicles is continuously increased, so that most cities in China face traffic jam and crowding.
In the related art, the traffic condition of a corresponding intersection is generally analyzed comprehensively by combining source data provided by a plurality of data providers (such as cameras, navigation terminals, etc.) at the corresponding intersection, and a signal control scheme of the corresponding intersection is controlled according to an analysis result. At present, source data provided by each data provider is generally aligned directly, however, in the process of implementing the present application, the applicant finds that directly aligning the source data easily causes inaccurate calculation of traffic data, and then affects the intelligent traffic optimization effect.
Disclosure of Invention
The application provides an intelligent traffic control method, an intelligent traffic control device, electronic equipment and a storage medium, time alignment is carried out on traffic video data provided by cameras by combining timestamp offset between the cameras, traffic index data of an intersection is determined by combining the aligned traffic video data, and traffic signal lamps of the intersection are controlled according to the determined traffic index data, so that the calculation accuracy of the traffic data can be improved, the road utilization rate can be further improved, the occurrence of congestion is reduced, and the intelligent traffic optimization effect is improved.
An embodiment of one aspect of the present application provides an intelligent traffic control method, including: acquiring source data provided by a plurality of data providing guidelines to intersections to be processed; acquiring time alignment relations among the data providers; according to the time alignment relation, performing time alignment processing on all source data; determining traffic index data of the intersection to be processed according to the aligned source data; and determining a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data.
In an embodiment of the present application, the plurality of data providers include a camera and a navigation terminal, and the method further includes: acquiring traffic video data collected by the camera aiming at the intersection to be processed; determining a target video frame corresponding to a target vehicle when the target vehicle is changed from a static state to a motion state according to the traffic video data, and acquiring a first time stamp corresponding to the target video frame, wherein the target vehicle is a vehicle which is positioned at the intersection to be processed and is closest to a stop line; determining a second timestamp corresponding to the target vehicle when the target vehicle changes from a static state to a motion state at the intersection to be processed according to navigation track data provided by a navigation terminal corresponding to the target vehicle; and determining a time alignment relation between the camera and the navigation terminal according to the first time stamp and the second time stamp.
In an embodiment of the present application, the data provider includes a first camera and a second camera, and both the first camera and the second camera are disposed on the intersection to be processed, and the method further includes: acquiring first historical traffic video data of the first camera and second historical traffic video data of the second camera; determining that the same moving object appears in an overlapping image area of the first historical traffic video data and the second historical traffic video data; determining a first target video frame from the first historical traffic video data, and determining a second target video frame from the second historical traffic video data, wherein the first target video frame is a video frame corresponding to the first occurrence of the moving object in an overlapping image area of the first historical traffic video data, and the second target video frame is a video frame corresponding to the first occurrence of the moving object in an overlapping image area of the second historical traffic video data; and determining a time alignment relation between the first camera and the second camera according to the first time stamp of the first target video frame and the second time stamp of the second target video frame.
In one embodiment of the present application, the plurality of data providers include cameras and vehicle detection devices, and the method further includes: acquiring first time information recorded by the vehicle detection equipment, wherein the first time information is corresponding time information when a target vehicle passes through a road surface provided with the vehicle detection equipment; acquiring a target video frame acquired by the camera, wherein the target video frame is a video frame corresponding to the target vehicle when the target vehicle passes through a road surface provided with vehicle detection equipment; and determining a time alignment relation between the camera and the vehicle detection equipment according to the second time information of the target video frame and the first time information.
In an embodiment of the present application, the performing, according to the time alignment relationship, time alignment processing on all source data includes: acquiring the alignment sequence of the data provider; and performing time alignment processing on all source data according to the alignment sequence and the time alignment relation.
According to the intelligent traffic control method, when the traffic index data of the intersection to be processed is calculated according to the source data provided by the data providers, the time alignment relation among the data providers is obtained, the source data provided by the data providers are time aligned, the traffic index data of the intersection to be processed is determined by combining the aligned source data, and the signal control scheme of the traffic signal machine on the intersection to be processed is controlled according to the determined traffic index data.
An embodiment of another aspect of the present application provides an intelligent traffic control device, including: the first acquisition module is used for acquiring source data provided by a plurality of data providing guidelines to intersections to be processed; the second acquisition module is used for acquiring the time alignment relation among the data providers; the alignment module is used for performing time alignment processing on all source data according to the time alignment relation; the first determining module is used for determining the traffic index data of the intersection to be processed according to the aligned source data; and the control module is used for determining a signal control scheme of the traffic signal machine on the intersection to be processed according to the traffic index data.
In an embodiment of the present application, the plurality of data providers include a camera and a navigation terminal, and the apparatus further includes: the third acquisition module is used for acquiring traffic video data acquired by the camera aiming at the intersection to be processed; the second determining module is used for determining a target video frame corresponding to a target vehicle when the target vehicle is changed from a static state to a motion state according to the traffic video data, and acquiring a first time stamp corresponding to the target video frame, wherein the target vehicle is a vehicle which is positioned at the intersection to be processed and is closest to a stop line; the third determining module is used for determining a second timestamp corresponding to the target vehicle when the target vehicle changes from a static state to a moving state at the intersection to be processed according to navigation track data provided by a navigation terminal corresponding to the target vehicle; and the fourth determining module is used for determining the time alignment relationship between the camera and the navigation terminal according to the first time stamp and the second time stamp.
In an embodiment of the present application, the data provider includes a first camera and a second camera, the first camera and the second camera are both disposed on the intersection to be processed, and the apparatus further includes: the fourth acquisition module is used for acquiring first historical traffic video data of the first camera and second historical traffic video data of the second camera; a fifth determining module, configured to determine that a moving object appears in an overlapping image area of the first historical traffic video data and the second historical traffic video data; a sixth determining module, configured to determine a first target video frame from the first historical traffic video data, and determine a second target video frame from the second historical traffic video data, where the first target video frame is a video frame corresponding to a first occurrence of the moving object in an overlapping image region of the first historical traffic video data, and the second target video frame is a video frame corresponding to a first occurrence of the moving object in an overlapping image region of the second historical traffic video data; a seventh determining module, configured to determine a time alignment relationship between the first camera and the second camera according to the first timestamp of the first target video frame and the second timestamp of the second target video frame.
In one embodiment of the present application, the plurality of data providers include a camera and a vehicle detection device, and the apparatus further includes: the fifth acquisition module is used for acquiring first time information recorded by the vehicle detection equipment, wherein the first time information is corresponding time information when the target vehicle passes through a road surface provided with the vehicle detection equipment; a sixth obtaining module, configured to obtain a target video frame acquired by the camera, where the target video frame is a video frame corresponding to the target vehicle when the target vehicle passes through a road surface where vehicle detection equipment is installed; and the eighth determining module is used for determining the time alignment relationship between the camera and the vehicle detection equipment according to the second time information of the target video frame and the first time information.
In an embodiment of the present application, the alignment module is specifically configured to: acquiring the alignment sequence of the data provider; and performing time alignment processing on all source data according to the alignment sequence and the time alignment relation.
According to the intelligent traffic control device, when the traffic index data of the intersection to be processed are calculated according to the source data provided by the data providers, the time alignment relation among the data providers is obtained, the source data provided by the data providers are time aligned, the aligned source data are combined, the traffic index data of the intersection to be processed are determined, and the signal control scheme of a traffic signal machine on the intersection to be processed is controlled according to the determined traffic index data.
An embodiment of another aspect of the present application provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the intelligent traffic control method according to the embodiment of the application.
Another embodiment of the present application provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute an intelligent traffic control method disclosed in an embodiment of the present application.
An embodiment of another aspect of the present application provides an intelligent traffic control method, including: acquiring source data provided by a plurality of data providing directions for intersections to be processed; acquiring time alignment relations among the data providers; determining traffic index data of the intersection to be processed according to the time alignment relation and the source data; and determining a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data.
One embodiment in the above application has the following advantages or benefits: the traffic data calculation accuracy can be improved, the road utilization rate can be further improved, the occurrence of congestion is reduced, and the intelligent traffic optimization effect is improved. The technical means that all source data are time-aligned by combining the time alignment relations among a plurality of data providers and the time alignment relations, the traffic index data of the intersection to be processed are determined according to the aligned source data, and the traffic signal lamps of the intersection are controlled according to the determined traffic index data are combined, so that the technical problems that in the related technology, the calculation results of the intersection are inaccurate due to the fact that the source data of a plurality of different sources are directly aligned, the intelligent traffic optimization effect is not ideal are solved, the calculation accuracy of the traffic data is improved, the road utilization rate is improved, the occurrence of congestion is reduced, and the technical effect of the intelligent traffic optimization effect is improved.
Other effects of the above-described alternative will be described below with reference to specific embodiments.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present application. Wherein:
FIG. 1 is a schematic diagram according to a first embodiment of the present application;
FIG. 2 is a schematic diagram according to a second embodiment of the present application;
FIG. 3 is a schematic illustration according to a third embodiment of the present application;
FIG. 4 is a schematic illustration according to a fourth embodiment of the present application;
FIG. 5 is a schematic illustration according to a fifth embodiment of the present application;
FIG. 6 is a schematic illustration according to a sixth embodiment of the present application;
FIG. 7 is a schematic illustration according to a seventh embodiment of the present application;
FIG. 8 is a schematic illustration according to an eighth embodiment of the present application;
fig. 9 is a block diagram of an electronic device for implementing an intelligent traffic control method according to an embodiment of the present application;
FIG. 10 is a schematic illustration of a ninth embodiment according to the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application to assist in understanding, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the related art, after source data provided by a plurality of data providers at a corresponding intersection are obtained, time alignment processing is usually directly performed on each source data, however, because each data provider is isolated and clocks of different data providers are usually different, the time given by different data providers is very different, and the source data provided by each data provider are directly aligned, so that the situation of inaccurate actual alignment exists, and further, traffic data calculation is inaccurate, and the intelligent traffic optimization effect is poor. Therefore, the intelligent traffic control method includes the steps of obtaining time alignment relations among a plurality of data providers when calculating traffic index data of an intersection to be processed according to source data provided by the data providers, performing time alignment on the source data provided by the data providers, determining the traffic index data of the intersection to be processed by combining the aligned source data, and controlling a signal control scheme of a traffic signal machine on the intersection to be processed according to the determined traffic index data.
The intelligent traffic control method, device and electronic device according to the embodiments of the present application are described below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram according to a first embodiment of the present application. It should be noted that an execution subject of the intelligent traffic control method provided in this embodiment is an intelligent traffic control device, and the intelligent traffic control device may be a terminal device, a server, or other hardware devices, or software installed on the hardware devices, and this embodiment is described by taking the intelligent traffic control device as a server as an example.
As shown in fig. 1, the intelligent traffic control method may include:
The data provider may include, but is not limited to, a camera, a vehicle detection device, a traffic signal, and the like.
The vehicle detection device may include a pressure detector, a magnetic induction detector, an ultrasonic detector, a radar detector, a loop coil detector, or the like.
The present embodiment is described taking a vehicle detection apparatus as an example of a magnetic induction detector.
The intersection to be processed can be a cross intersection, an X-shaped intersection, a T-shaped intersection, a Y-shaped intersection, and the like, and the intersection to be processed is not particularly limited in this embodiment.
In the embodiment of the application, in order to improve the accurate control of the traffic signal machine of the subsequent intersection to be processed, the time alignment relation between the corresponding data providers can be obtained according to the pre-stored time alignment relation between the data providers.
For example, the time alignment relationship between the two data providers can be determined by acquiring clock information of the corresponding data providers and determining timestamp offsets between the two data providers according to the clock information between the two data providers.
And 103, performing time alignment processing on all source data according to the time alignment relation.
In the present embodiment, in order to improve the alignment efficiency of a plurality of source data, as an exemplary embodiment, an alignment order of a data provider is acquired; and performing time alignment processing on all source data according to the alignment sequence and the time alignment relation.
For example, assuming that the data providers include three data providers, which are a camera, a magnetic induction detector and a navigation terminal, after the source data provided by each data provider is obtained, if the alignment sequence is: now, the source data of the camera and the magnetic induction detector are aligned, and then the source data of the navigation terminal and the corresponding source data of the camera and the magnetic induction detector are aligned again.
And step 104, determining traffic index data of the intersection to be processed according to the aligned source data.
In this embodiment, after the plurality of source data are aligned, the source data in the corresponding time period in the source data that can be aligned are analyzed to obtain traffic index data corresponding to the intersection to be processed in the corresponding time period.
The traffic index data may include a traffic flow, a congestion condition, and the like, and this embodiment is not particularly limited thereto.
And 105, determining a signal control scheme of the traffic signal machine on the intersection to be processed according to the traffic index data.
In this embodiment, after the number of traffic indicators of the intersection to be processed is obtained, a signal control scheme corresponding to the number of traffic indicators of the intersection to be processed may be obtained, and the traffic signal machine at the intersection to be processed is controlled according to the signal control scheme.
Specifically, after the signal control scheme of the traffic signal machine at the intersection to be processed is determined, the signal control scheme can be sent to the traffic signal machine, and correspondingly, the traffic signal machine controls the traffic signal lamp according to the received signal control scheme.
The signal control scheme may include, but is not limited to, parameters of a traffic signal, such as a traffic light period, a phase sequence, and a green signal ratio, which is not limited in this embodiment.
According to the intelligent traffic control method, when the traffic index data of the intersection to be processed is calculated according to the source data provided by the data providers, the time alignment relation among the data providers is obtained, the source data provided by the data providers are time aligned, the traffic index data of the intersection to be processed is determined by combining the aligned source data, and the signal control scheme of the traffic signal machine on the intersection to be processed is controlled according to the determined traffic index data.
Fig. 2 is a schematic diagram according to a second embodiment of the present application. It should be noted that, in this embodiment, a data provider is described as an example of a camera and a navigation terminal.
As shown in fig. 2, the method may include:
The target vehicle is a vehicle located closest to a stop line of the intersection to be processed.
And 203, determining a second timestamp corresponding to the target vehicle when the target vehicle changes from a static state to a moving state at the road junction to be processed according to the navigation track data provided by the navigation terminal corresponding to the target vehicle.
And 204, determining the time alignment relation between the camera and the navigation terminal according to the first time stamp and the second time stamp.
The embodiment provides a mode for determining the time alignment relationship between the navigation terminal and the camera, so that the time alignment relationship between the navigation terminal and the camera is conveniently determined, and the source data provided by the navigation terminal and the camera is conveniently fused together in the time dimension by subsequently combining the time alignment relationship.
And step 206, acquiring a time alignment relation between the camera and the navigation terminal.
And step 207, performing time alignment processing on all the source data according to the time alignment relation.
And step 208, determining traffic index data of the intersection to be processed according to the aligned source data.
And step 209, determining a signal control scheme of a traffic signal machine at the intersection to be processed according to the traffic index data.
It should be noted that, the description related to the foregoing embodiment also applies to this embodiment, and the description may refer to the foregoing embodiment, which is not repeated herein.
According to the intelligent traffic control method, the time alignment relation between the camera and the navigation terminal is determined by combining traffic video data acquired by the camera and navigation track data provided by the navigation terminal, the traffic index data of the intersection to be processed is determined according to the source data provided by the camera and the navigation terminal and the time alignment relation between the camera and the navigation terminal, and the signal control scheme of a traffic signal machine on the intersection to be processed is controlled according to the determined traffic index data.
Fig. 3 is a schematic diagram according to a third embodiment of the present application. It should be noted that, in the present embodiment, a data provider is taken as an example to describe the first camera and the second camera, and it can be understood that both the first camera and the second camera are disposed at the intersection to be processed, and are used for performing data acquisition on the traffic condition of the intersection to be processed.
As shown in fig. 3, the intelligent traffic control method may include:
And history sections corresponding to the first historical traffic video data and the second historical traffic video data are the same.
Wherein, it is understood that the first historical traffic video data and the second historical traffic video data have overlapping image areas, indicating that there is a public field of view between the first camera and the second camera.
The moving object may include, but is not limited to, an automobile, an electric vehicle, or a bicycle.
The first target video frame is a video frame corresponding to the first occurrence of a moving object in the overlapping image area of the first historical traffic video data, and the second target video frame is a video frame corresponding to the first occurrence of a moving object in the overlapping image area of the second historical traffic video data.
And 305, acquiring current first traffic video data and second traffic video data of the intersection to be processed.
And 307, aligning the timestamps of the first traffic video data and the second traffic video data according to the time alignment relation.
And 308, determining traffic index data of the intersection to be processed according to the aligned first traffic video data and the aligned second traffic video data.
And 309, controlling a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data.
The intelligent traffic control method of the embodiment of the application determines the time alignment relation between the first camera and the second camera by combining with moving objects in the overlapped image area in the historical traffic video data acquired by the first camera and the second camera respectively, determines the traffic video data currently acquired by the intersection to be processed by combining the first camera and the second camera, acquires the time alignment relation between the first camera and the second camera when calculating the traffic index data of the intersection to be processed, performs time alignment on the traffic video data acquired by the first camera and the second camera respectively by combining the time alignment relation, determines the traffic index data of the intersection to be processed by combining the aligned traffic video data, and controls the signal control scheme of a traffic signal machine at the intersection to be processed according to the determined traffic index data, therefore, the traffic data calculation accuracy can be improved, the road utilization rate can be improved, the occurrence of congestion can be reduced, and the intelligent traffic optimization effect is improved.
Fig. 4 is a schematic diagram of a fourth embodiment according to the present application. It should be noted that, the present embodiment is described by taking multiple data providers as a first camera and a second camera as an example, wherein,
as shown in fig. 4, the intelligent traffic control method may include:
step 401, acquiring first historical traffic video data of a first camera and second historical traffic video data of a second camera.
And history sections corresponding to the first historical traffic video data and the second historical traffic video data are the same.
In this embodiment, the specific implementation manner of step 402 may be: identifying video frames in the first historical traffic video data to determine a detection area including a traffic signal lamp; and extracting signal lamp characteristic information in the detection area, and inputting the signal lamp characteristic information into a signal lamp identification model trained in advance to acquire the lamp state of the traffic signal lamp.
The light states of the traffic signal light may include, but are not limited to, red light, green light, yellow light, and the like.
In this embodiment, the specific implementation manner of step 403 may be: identifying video frames in the second historical traffic video data to determine a detection area containing traffic signal lamps; and extracting signal lamp characteristic information in the detection area, and inputting the signal lamp characteristic information into a signal lamp recognition model trained in advance to acquire the lamp state of the traffic signal lamp.
It should be noted that, the execution of the step 402 and the step 403 are not in sequence.
And step 404, according to the first corresponding relation and the second corresponding relation, the time alignment relation between the first camera and the second camera.
And step 408, determining traffic index data of the intersection to be processed according to the aligned first traffic video data and the aligned second traffic video data.
And step 409, controlling a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data.
The intelligent traffic control method of the embodiment of the application determines a first corresponding relation between a timestamp of a video frame acquired by a first camera and a light state of a traffic light and a second corresponding relation between a timestamp of a video frame of a second camera and the light state of the traffic light by combining historical traffic video data acquired by the first camera and the second camera respectively, determines a time alignment relation between the first camera and the second camera according to the first corresponding relation and the second corresponding relation, performs time alignment on traffic video data acquired by the first camera and the second camera respectively by combining the time alignment relation between the first camera and the second camera when calculating traffic index data of an intersection to be processed, and the aligned traffic video data is combined to determine the traffic index data of the intersection to be processed, and the signal control scheme of the traffic signal machine on the intersection to be processed is controlled according to the determined traffic index data, so that the calculation accuracy of the traffic data can be improved, the road utilization rate can be improved, the occurrence of congestion can be reduced, and the intelligent traffic optimization effect can be improved.
In one embodiment of the present application, in a case where the plurality of data providers include a camera and a vehicle detection device, as shown in fig. 5, determining a time alignment relationship between the camera and the vehicle detection device may include:
Wherein, the vehicle detection device can comprise a pressure detector, a magnetic induction detector, an ultrasonic detector, a radar detector, a loop coil detector or the like.
The present embodiment is described taking a vehicle detection apparatus as an example of a magnetic induction detector.
And step 503, determining the time alignment relationship between the camera and the vehicle detection device according to the second time information and the first time information of the target video frame.
According to the embodiment of the application, the time information corresponding to the target vehicle when the target vehicle passes through the road surface of the vehicle detection equipment is combined with the vehicle detection equipment, and the time information corresponding to the target vehicle when the target vehicle passes through the road surface of the vehicle detection equipment is collected by the camera to be analyzed, so that the time alignment relation between the camera and the vehicle detection equipment is accurately determined.
Corresponding to the intelligent traffic control methods provided in the foregoing several embodiments, an embodiment of the present application further provides an intelligent traffic control device, and since the intelligent traffic control device provided in the embodiment of the present application corresponds to the intelligent traffic control methods provided in the foregoing several embodiments, the implementation manner of the intelligent traffic control method is also applicable to the intelligent traffic control device provided in the embodiment, and is not described in detail in the embodiment. Fig. 6 is a schematic diagram according to a sixth embodiment of the present application.
The intelligent traffic control device 600 includes:
a first obtaining module 601, configured to obtain source data provided by each intersection to be processed by a plurality of data providing guidelines;
a second obtaining module 602, configured to obtain time alignment relationships among multiple data providers;
an alignment module 603, configured to perform time alignment processing on all source data according to the time alignment relationship;
a first determining module 604, configured to determine traffic indicator data of the intersection to be processed according to the aligned source data;
the control module 605 is configured to determine a signal control scheme of a traffic signal machine at the intersection to be processed according to the traffic index data.
In an embodiment of the present application, the multiple data providers include a camera and a navigation terminal, and on the basis of the embodiment of the apparatus shown in fig. 6, as shown in fig. 7, the apparatus further includes:
a third obtaining module 606, configured to obtain traffic video data collected by a camera for a road junction to be processed;
a second determining module 607, configured to determine, according to the traffic video data, a target video frame corresponding to a target vehicle when the target vehicle changes from a static state to a moving state, and obtain a first timestamp corresponding to the target video frame, where the target vehicle is a vehicle closest to a stop line at the intersection to be processed;
a third determining module 608, configured to determine, according to navigation trajectory data provided by a navigation terminal corresponding to the target vehicle, a second timestamp corresponding to the target vehicle when the target vehicle changes from a stationary state to a moving state at the intersection to be processed;
a fourth determining module 609, configured to determine a time alignment relationship between the camera and the navigation terminal according to the first timestamp and the second timestamp.
In an embodiment of the present application, the data provider includes a first camera and a second camera, and both the first camera and the second camera are disposed at the intersection to be processed, as shown in fig. 8, the apparatus further includes:
a fourth obtaining module 610, configured to obtain first historical traffic video data of the first camera and second historical traffic video data of the second camera;
a fifth determining module 611, configured to determine that the same moving object appears in an overlapping image area of the first historical traffic video data and the second historical traffic video data;
a sixth determining module 612, configured to determine a first target video frame from the first historical traffic video data, and determine a second target video frame from the second historical traffic video data, where the first target video frame is a video frame corresponding to a first occurrence of a moving object in an overlapping image area of the first historical traffic video data, and the second target video frame is a video frame corresponding to a first occurrence of a moving object in an overlapping image area of the second historical traffic video data;
a seventh determining module 613, configured to determine a time alignment relationship between the first camera and the second camera according to the first timestamp of the first target video frame and the second timestamp of the second target video frame.
In one embodiment of the present application, the plurality of data providers include a camera and a vehicle detection device, and the apparatus further includes:
the fifth acquisition module is used for acquiring first time information recorded by the vehicle detection equipment, wherein the first time information is corresponding time information when the target vehicle passes through a road surface provided with the vehicle detection equipment;
the sixth acquisition module is used for acquiring a target video frame acquired by the camera, wherein the target video frame is a video frame corresponding to a target vehicle passing through a road surface provided with the vehicle detection equipment;
and the eighth determining module is used for determining the time alignment relation between the camera and the vehicle detection equipment according to the second time information and the first time information of the target video frame.
In an embodiment of the present application, the alignment module 603 is specifically configured to: acquiring an alignment sequence of a data provider; and performing time alignment processing on all source data according to the alignment sequence and the time alignment relation.
The intelligent traffic control device of the embodiment of the application, when calculating the traffic index data of the intersection to be processed according to the source data provided by the plurality of data providers, acquire the time alignment relation among the plurality of data providers, time align the source data provided by the data providers, and determine the traffic index data of the intersection to be processed by combining the aligned source data, and control the signal control scheme of the traffic signal machine on the intersection to be processed according to the determined traffic index data, so that the calculation accuracy of the traffic data can be improved, the road utilization rate can be improved, the occurrence of congestion can be reduced, and the intelligent traffic optimization effect is improved.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
Fig. 9 is a block diagram of an electronic device of an intelligent traffic control method according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not intended to limit implementations of the applications described and/or claimed herein.
As shown in fig. 9, the electronic apparatus includes: one or more processors 901, memory 902, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, if desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 9 illustrates an example of a processor 901.
The memory 902, which is a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the intelligent transportation control method in the embodiment of the present application (for example, the first obtaining module 601, the second obtaining module 602, the aligning module 603, the first determining module 604, and the control module 605 shown in fig. 6). The processor 901 executes various functional applications of the server and data processing by running non-transitory software programs, instructions, and modules stored in the memory 902, that is, implements the intelligent traffic control method in the above method embodiments.
The memory 902 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the intelligent traffic-controlled electronic device, and the like. Further, the memory 902 may include high speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 902 may optionally include memory located remotely from the processor 901, which may be connected to intelligent traffic control electronics over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device of the intelligent traffic control method may further include: an input device 903 and an output device 904. The processor 901, the memory 902, the input device 903 and the output device 904 may be connected by a bus or other means, and fig. 9 illustrates a connection by a bus as an example.
The input device 903 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the intelligent traffic controlled electronic device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, a pointing stick, one or more mouse buttons, a track ball, a joystick, and the like. The output devices 904 may include a display device, auxiliary lighting devices (e.g., LEDs), tactile feedback devices (e.g., vibrating motors), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
FIG. 10 is a schematic illustration of a ninth embodiment according to the present application. It should be noted that an execution subject of the intelligent traffic control method provided in this embodiment is an intelligent traffic control device, and the intelligent traffic control device may be a terminal device, a server, or other hardware devices, or software installed on the hardware devices, and this embodiment is described by taking the intelligent traffic control device as a server as an example.
As shown in fig. 10, the intelligent traffic control method may include:
and step 111, acquiring source data provided by a plurality of data providing directions to the intersection to be processed.
And step 113, determining traffic index data of the intersection to be processed according to the time alignment relation and the source data.
The specific implementation of step 113 may be: and time alignment processing can be carried out on all the metadata according to the time alignment relation, and traffic index data of the intersection to be processed is calculated according to the source data after the alignment processing.
And step 114, determining a signal control scheme of the traffic signal machine on the intersection to be processed according to the traffic index data.
According to the intelligent traffic control method, when the traffic index data of the intersection to be processed is calculated according to the source data provided by the data providers, the time alignment relation among the data providers is obtained, the traffic index data of the intersection to be processed is determined by combining the time alignment relation with the source data, and the signal control scheme of the traffic signal machine on the intersection to be processed is controlled according to the determined traffic index data.
It should be noted that the foregoing explanation of the intelligent traffic control method is also applicable to the intelligent traffic control method of this embodiment, and relevant descriptions may refer to relevant parts, which are described herein in detail.
It should be understood that various forms of the flows shown above, reordering, adding or deleting steps, may be used. For example, the steps described in the present application may be executed in parallel, sequentially or in different orders, and are not limited herein as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations and substitutions are possible, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (11)
1. An intelligent traffic control method, comprising:
acquiring source data provided by a plurality of data providing guidelines to intersections to be processed;
acquiring time alignment relations among the plurality of data providers;
according to the time alignment relation, performing time alignment processing on all source data;
determining traffic index data of the intersection to be processed according to the aligned source data;
determining a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data;
the data provider comprises a first camera and a second camera, the first camera and the second camera are both arranged on the intersection to be processed, and the method further comprises the following steps:
acquiring first historical traffic video data of the first camera and second historical traffic video data of the second camera;
determining that the same moving object appears in an overlapped image area of the first historical traffic video data and the second historical traffic video data;
determining a first target video frame from the first historical traffic video data, and determining a second target video frame from the second historical traffic video data, wherein the first target video frame is when the moving object appears for the first time in an overlapped image area of the first historical traffic video data;
the corresponding video frame, the second target video frame is a video frame corresponding to the first occurrence of the moving object in the overlapping image area of the second historical traffic video data;
and determining a time alignment relation between the first camera and the second camera according to the first time stamp of the first target video frame and the second time stamp of the second target video frame.
2. The method of claim 1, wherein the plurality of data providers comprise a camera and a navigation terminal, the method further comprising:
acquiring traffic video data collected by the camera aiming at the intersection to be processed;
determining a target video frame corresponding to a target vehicle when the target vehicle is changed from a static state to a motion state according to the traffic video data, and acquiring a first time stamp corresponding to the target video frame, wherein the target vehicle is a vehicle which is positioned at the intersection to be processed and is closest to a stop line;
determining a second timestamp corresponding to the target vehicle when the target vehicle changes from a static state to a motion state at the intersection to be processed according to navigation track data provided by a navigation terminal corresponding to the target vehicle;
and determining a time alignment relation between the camera and the navigation terminal according to the first time stamp and the second time stamp.
3. The method of claim 1, wherein the plurality of data providers comprise a camera and a vehicle detection device, the method further comprising:
acquiring first time information recorded by the vehicle detection equipment, wherein the first time information is corresponding time information when a target vehicle passes through a road surface provided with the vehicle detection equipment;
acquiring a target video frame acquired by the camera, wherein the target video frame is a video frame corresponding to the target vehicle when the target vehicle passes through a road surface provided with vehicle detection equipment;
and determining a time alignment relation between the camera and the vehicle detection equipment according to the second time information of the target video frame and the first time information.
4. The method according to any one of claims 1 to 3, wherein the performing time alignment processing on all source data according to the time alignment relationship comprises:
acquiring the alignment sequence of the data provider;
and performing time alignment processing on all source data according to the alignment sequence and the time alignment relation.
5. An intelligent traffic control device, comprising:
the first acquisition module is used for acquiring source data provided by each intersection to be processed by a plurality of data providing directions;
the second acquisition module is used for acquiring time alignment relations among the plurality of data providers;
the alignment module is used for performing time alignment processing on all source data according to the time alignment relation;
the first determining module is used for determining the traffic index data of the intersection to be processed according to the aligned source data;
the control module is used for determining a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data;
the data provider includes first camera and second camera, first camera with the second camera all sets up treat processing crossing is last, the device still includes:
the fourth acquisition module is used for acquiring first historical traffic video data of the first camera and second historical traffic video data of the second camera;
a fifth determining module, configured to determine that a same moving object appears in an overlapping image region of the first historical traffic video data and the second historical traffic video data;
a sixth determining module, configured to determine a first target video frame from the first historical traffic video data, and determine a second target video frame from the second historical traffic video data, where the first target video frame is a video frame corresponding to a first occurrence of the moving object in an overlapping image region of the first historical traffic video data, and the second target video frame is a video frame corresponding to a first occurrence of the moving object in an overlapping image region of the second historical traffic video data;
a seventh determining module, configured to determine a time alignment relationship between the first camera and the second camera according to the first timestamp of the first target video frame and the second timestamp of the second target video frame.
6. The apparatus of claim 5, wherein the plurality of data providers comprise a camera and a navigation terminal, the apparatus further comprising:
the third acquisition module is used for acquiring traffic video data acquired by the camera aiming at the intersection to be processed;
the second determining module is used for determining a target video frame corresponding to a target vehicle when the target vehicle is changed from a static state to a motion state according to the traffic video data, and acquiring a first time stamp corresponding to the target video frame, wherein the target vehicle is a vehicle which is positioned at the intersection to be processed and is closest to a stop line;
the third determining module is used for determining a second timestamp corresponding to the target vehicle when the target vehicle changes from a static state to a moving state at the intersection to be processed according to navigation track data provided by a navigation terminal corresponding to the target vehicle;
and the fourth determining module is used for determining the time alignment relationship between the camera and the navigation terminal according to the first time stamp and the second time stamp.
7. The apparatus of claim 5, wherein the plurality of data providers comprise a camera and a vehicle detection device, the apparatus further comprising:
the fifth acquisition module is used for acquiring first time information recorded by the vehicle detection equipment, wherein the first time information is corresponding time information when a target vehicle passes through a road surface provided with the vehicle detection equipment;
a sixth obtaining module, configured to obtain a target video frame acquired by the camera, where the target video frame is a video frame corresponding to the target vehicle passing through a road surface equipped with a vehicle detection device;
an eighth determining module, configured to determine, according to the second time information of the target video frame and the first time information, a time alignment relationship between the camera and the vehicle detection device.
8. The device according to any one of claims 5 to 7, wherein the alignment module is specifically configured to:
acquiring the alignment sequence of the data provider;
and performing time alignment processing on all source data according to the alignment sequence and the time alignment relation.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-4.
10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-4.
11. An intelligent traffic control method, comprising:
acquiring source data provided by a plurality of data providing directions for intersections to be processed;
acquiring time alignment relations among the plurality of data providers;
determining traffic index data of the intersection to be processed according to the time alignment relation and the source data;
determining a signal control scheme of a traffic signal machine on the intersection to be processed according to the traffic index data;
the data provider comprises a first camera and a second camera, the first camera and the second camera are both arranged on the intersection to be processed, and the method further comprises the following steps:
acquiring first historical traffic video data of the first camera and second historical traffic video data of the second camera;
determining that the same moving object appears in an overlapping image area of the first historical traffic video data and the second historical traffic video data;
determining a first target video frame from the first historical traffic video data, and determining a second target video frame from the second historical traffic video data, wherein the first target video frame is when the moving object appears for the first time in an overlapped image area of the first historical traffic video data;
the corresponding video frame, wherein the second target video frame is a video frame corresponding to the first occurrence of the moving object in the overlapping image area of the second historical traffic video data;
and determining a time alignment relationship between the first camera and the second camera according to the first time stamp of the first target video frame and the second time stamp of the second target video frame.
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| CN111597700B (en) * | 2020-05-09 | 2023-08-15 | 北京百度网讯科技有限公司 | Signal control algorithm evaluation method and device, electronic equipment and readable storage medium |
| CN111862593B (en) * | 2020-06-03 | 2022-04-01 | 阿波罗智联(北京)科技有限公司 | Method and device for reporting traffic events, electronic equipment and storage medium |
| CN114093170B (en) * | 2021-11-26 | 2023-01-24 | 阿波罗智联(北京)科技有限公司 | Generation method, system and device of annunciator control scheme and electronic equipment |
| CN114446047A (en) * | 2021-12-28 | 2022-05-06 | 阿波罗智联(北京)科技有限公司 | Traffic index data processing method and device and electronic equipment |
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