CN110930735A - Intelligent traffic control method, device, equipment and storage medium - Google Patents
Intelligent traffic control method, device, equipment and storage medium Download PDFInfo
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Abstract
The application provides an intelligent traffic control method and device, electronic equipment and a storage medium. Wherein at least one embodiment of the intelligent traffic control method comprises: acquiring current traffic video data and current traffic light information of an intersection to be processed; according to the offset of the timestamp between the camera and the traffic signal machine, aligning the timestamp of the current traffic video data and the current traffic light information; determining current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information; and controlling a signal control scheme of the traffic signal machine according to the current traffic index data. By utilizing the technical scheme of at least one embodiment of the application, the problem that the time stamp in the signal lamp scheme and the time stamp in the video collected by the camera cannot be aligned accurately can be effectively solved.
Description
Technical Field
The present application relates to the field of transportation, and in particular, to the field of intelligent transportation technologies, and in particular, to an intelligent transportation control method, apparatus, electronic device, and non-transitory computer-readable storage medium storing computer instructions.
Background
At the current traffic road intersection, there are usually traffic lights and cameras for photographing traffic roads. Wherein the change of the traffic light is controlled by a traffic signal.
Because traffic signal machine and camera can divide usually to belong to different producers, do not interact each other, and the clock is difficult to align, therefore can have the timestamp of the traffic light signal of traffic signal machine output and the actual inaccurate condition of aligning of timestamp in the video is gathered to the camera. At this time, if the traffic data calculation is performed by using the traffic light signal and the video collected by the camera, the result is often inaccurate, and especially in the control of intelligent traffic, the design of the subsequent scheme is further influenced.
Disclosure of Invention
The present application aims to solve at least one of the technical problems in the related art to some extent.
Therefore, a first objective of the present application is to provide an intelligent traffic control method, which can achieve accurate alignment of timestamps of current traffic video data and current traffic light information, improve accuracy of traffic data calculation, and improve optimization effect of intelligent traffic.
A second object of the present application is to provide an intelligent traffic control device.
A third object of the present application is to provide an electronic device.
A fourth object of the present application is to propose a non-transitory computer readable storage medium storing computer instructions.
A fifth object of the present application is to provide an intelligent traffic control method.
In order to achieve the above object, an embodiment of the first aspect of the present application provides an intelligent traffic control method, including: acquiring current traffic video data of an intersection to be processed and current traffic light information of the intersection to be processed, wherein the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed;
acquiring a timestamp offset between the camera and the traffic signal machine;
aligning the timestamp of the current traffic video data and the timestamp of the current traffic light information based on the timestamp offset;
determining the current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information;
and controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
According to an embodiment of the application, the obtaining of the timestamp offset between the camera and the traffic signal comprises: acquiring historical traffic video data of the camera and historical traffic light information of the traffic signal machine related to the historical traffic video data time, wherein the historical traffic light information comprises a corresponding relation between a light state of a traffic light and a timestamp; analyzing vehicle behavior information in the historical traffic video data to determine a corresponding relationship between a timestamp of a video frame in the historical traffic video data and a light state of a traffic light; and acquiring the timestamp offset between the camera and the traffic signal machine according to the corresponding relation between the timestamp of the video frame and the light state of the traffic light and the corresponding relation between the light state of the traffic light and the timestamp.
According to an embodiment of the application, the analyzing the vehicle behavior information in the historical traffic video data to determine the correspondence between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light includes: according to the historical traffic video data, if it is determined that a target vehicle closest to a stop line of the intersection to be processed is changed from a static state to a moving state, determining that the light state of the traffic light is in a green light state, and acquiring a corresponding target video frame when the target vehicle is changed from the static state to the moving state; and determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the timestamp of the target video frame and the determined light state of the traffic light.
According to an embodiment of the application, the determining a correspondence between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the timestamp of the target video frame and the determined light state of the traffic light includes: acquiring awakening time consumption required by the target vehicle to be switched from a parking state to a running state; subtracting the awakening time consumption from the timestamp of the target video frame to obtain a target timestamp; and determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the target timestamp and the determined light state of the traffic light.
According to an embodiment of the application, the acquiring the wake-up time required by the target vehicle to switch from the parking state to the driving state includes: determining a vehicle type of the target vehicle; and determining the awakening time consumption required by the target vehicle to be switched from the parking state to the running state according to the vehicle type. In order to achieve the above object, an embodiment of a second aspect of the present application provides an intelligent traffic control device, including:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring current traffic video data of an intersection to be processed and current traffic light information of the intersection to be processed, the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed;
the second acquisition module is used for acquiring the timestamp offset between the camera and the traffic signal machine;
the processing module is used for aligning the timestamp of the current traffic video data and the timestamp of the current traffic light information based on the timestamp offset;
the first determining module is used for determining the current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information;
and the control module is used for controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
In order to achieve the above object, an electronic device according to a third aspect of the present application includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the intelligent traffic control method of the first aspect of the present application.
To achieve the above object, a non-transitory computer readable storage medium storing computer instructions according to a fourth aspect of the present application includes: the computer instructions are configured to cause the computer to perform the intelligent traffic control method according to the first aspect of the present application.
In order to achieve the above object, an embodiment of a fifth aspect of the present application provides an intelligent traffic control method, including: acquiring current traffic video data and current traffic light information of an intersection to be processed, wherein the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed; aligning the timestamps of the current traffic video data and the current traffic light information according to the timestamp offset between the camera and the traffic signal machine; and controlling a signal control scheme of the traffic signal machine according to the aligned current traffic video data and the current traffic light information.
One embodiment in the above application has the following advantages or benefits: the time stamps of the current traffic video data and the current traffic light information can be accurately aligned, the accuracy of traffic data calculation is improved, and the optimization effect of intelligent traffic is improved. The method comprises the steps of acquiring current traffic video data and current traffic light information of an intersection to be processed, wherein the current traffic video data is acquired by a camera arranged on the intersection to be processed, the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed, aligning timestamps of the current traffic video data and the current traffic light information according to timestamp offset between the camera and the traffic signal machine, determining current traffic index data of the intersection to be processed according to the aligned current traffic video data and the aligned current traffic light information, and controlling a signal control scheme of the traffic signal machine according to the current traffic index data. Therefore, the technical problems that in the related art, the time stamps in the signal lamp scheme are aligned with the time stamps in the video collected by the camera, actual alignment is inaccurate, traffic data calculation is inaccurate, the optimization effect is poor and the like are solved, the time stamps for realizing the current traffic video data and the current traffic light information are accurately aligned, the accuracy of traffic data calculation is improved, and the technical effect of the optimization effect of intelligent traffic is improved.
Other effects of the above-described alternative will be described below with reference to specific embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is a schematic diagram according to a first embodiment of the present application.
Fig. 2 is a detailed schematic diagram according to a first embodiment of the present application.
Fig. 3 is a schematic diagram of a second embodiment according to the present application.
Fig. 4 is a detailed schematic diagram of a second embodiment according to the present application.
Fig. 5 is a block diagram of an electronic device for implementing the intelligent traffic control method according to the embodiment of the present application.
Fig. 6 is a schematic diagram according to a third embodiment of 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 for the understanding of the same, 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.
The application provides an intelligent traffic control method, an intelligent traffic control device, electronic equipment and a non-transitory computer-readable storage medium storing computer instructions, and solves the technical problems that in the related art, due to the fact that signal lamps and cameras belong to different manufacturers, interaction does not exist between the signal lamps and the cameras, clocks are difficult to align, time stamps in a signal lamp scheme and time stamps in video collected by the cameras are aligned, actual alignment is inaccurate, further traffic data are inaccurate in calculation, the optimization effect is poor and the like. Specifically, the intelligent traffic control method, apparatus, electronic device, and non-transitory computer-readable storage medium storing computer instructions of 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 hardware electronic device such as a terminal device and a server, or software installed on the hardware electronic device, 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:
s110, obtaining current traffic video data of the intersection to be processed and current traffic light information of the intersection to be processed, wherein the current traffic video data is collected by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed.
For example, the camera arranged on the intersection to be processed can be used for collecting the traffic condition on the intersection to be processed, time collection is carried out, the traffic signal machine arranged on the intersection to be processed provides current traffic light information, and the current traffic video data and the current traffic light information of the intersection to be processed are sent to the electronic equipment, so that the electronic equipment can obtain the current traffic video data and the current traffic light information of the intersection to be processed.
And S120, acquiring the timestamp offset between the camera and the traffic signal machine.
In the embodiment of the application, the timestamp offset between the camera and the traffic signal machine can be acquired according to the timestamp offset corresponding relation of the camera and the traffic signal machine which are stored in advance. In an embodiment of the application, historical traffic video data of a camera and historical traffic light information of a traffic signal machine time-correlated to the historical traffic video data may be acquired, wherein the historical traffic light information includes a correspondence between a light state of a traffic light and a time stamp, then vehicle behavior information in the historical traffic video data is analyzed to determine a correspondence between a time stamp of a video frame and a light state of the traffic light in the historical traffic video data, and then a timestamp offset between the camera and the traffic signal machine is acquired according to the correspondence between the time stamp of the video frame and the light state of the traffic light and the correspondence between the light state of the traffic light and the time stamp. The specific implementation process can be referred to the description of the subsequent embodiments.
In the embodiment of the present application, the correspondence between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light can be implemented in the following two ways.
As a possible implementation manner, the historical traffic video data of the camera is acquired, the video frames of the historical traffic video may be acquired, the image of the image area is extracted to identify the color of the traffic light, the light state of the traffic light is further determined, and the corresponding relationship between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light is recorded.
As another possible implementation manner, the historical traffic video data of the camera is acquired, and according to the historical traffic video data, if it is determined that the target vehicle closest to the stop line of the intersection to be processed changes from the stationary state to the moving state, it is determined that the light state of the traffic light is in the green light state, and a target video frame corresponding to the target vehicle when the target vehicle changes from the stationary state to the moving state is acquired, and then according to the timestamp of the target video frame and the determined light state of the traffic light, the correspondence relationship between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light is determined.
As one possible implementation manner, clock information of the camera and clock information of the traffic signal machine may be acquired, and a timestamp offset between the camera and the traffic signal machine may be determined according to the clock information of the camera and the clock information of the traffic signal machine.
And S130, aligning the time stamp of the current traffic video data and the time stamp of the current traffic light information based on the time stamp offset.
In the embodiment of the application, after obtaining the current traffic video data and the current traffic light information of the intersection to be processed, time correction can be carried out on the timestamp of the current traffic video data according to the timestamp offset, and alignment processing is carried out according to the timestamp of the current traffic video data and the timestamp of the current traffic light information after the deviation correction, or time correction is carried out on the timestamp of the current traffic light information according to the timestamp offset, and alignment processing is carried out according to the timestamp of the current traffic light information and the timestamp of the current traffic video data after the deviation correction.
And S140, determining the current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information.
In the embodiment of the application, after the alignment processing is performed on the timestamps of the current traffic video data and the current traffic light information according to the timestamp offset between the camera and the traffic signal machine, the current traffic index data of the intersection to be processed can be determined according to the aligned current traffic video data and the aligned current traffic light information, wherein the traffic index data can include, but is not limited to, intersection congestion indexes, traffic flow and the like.
And S150, controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
That is, after determining the current traffic index data of the intersection to be processed, the signal control scheme of the traffic signal machine may be controlled according to the current traffic index data.
The signal control scheme comprises parameters such as a traffic light period, a phase sequence and a green signal ratio of the traffic signal light.
For example, when the current congestion index of the intersection to be processed is determined to be high, the display state of the traffic signal lamp can be controlled to be green, and the display time duration is controlled to be two minutes.
According to the intelligent traffic control method, the current traffic video data collected by the camera on the intersection to be processed and the current traffic light information of the traffic signal machine can be obtained, the timestamp offset between the camera and the traffic signal machine is obtained, the timestamp of the current traffic video data and the timestamp of the current traffic light information are aligned based on the timestamp offset, then the current traffic index data of the intersection to be processed is determined according to the aligned current traffic video data and the aligned current traffic light information, and finally the signal control scheme of the traffic signal machine is controlled according to the current traffic index data. According to the method, the timestamp offset between the camera and the traffic signal machine is used, so that the timestamp of the current traffic video data and the timestamp of the current traffic light information can be accurately aligned, the accuracy of traffic data calculation is improved, and the optimization effect of intelligent traffic is improved.
Fig. 2 is a detailed schematic diagram according to a first embodiment of the present application. As shown in fig. 2, the intelligent traffic control method may include:
s210, historical traffic video data of the camera and historical traffic light information of the traffic signal machine relevant to the historical traffic video data time are obtained, and the historical traffic light information comprises a corresponding relation between a light state of the traffic light and a time stamp.
For example, the camera sends the collected historical traffic video data and the historical traffic light information provided by the traffic signal machine to the electronic device, so that the electronic device obtains the historical traffic video data of the camera and obtains the historical traffic light information of the traffic signal machine, wherein the historical traffic light information comprises the corresponding relation between the light state of the traffic light and the timestamp.
S220, vehicle behavior information in the historical traffic video data is analyzed to determine the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light.
Optionally, in an embodiment of the present application, after obtaining the historical traffic video data of the camera, according to the historical traffic video data, if it is determined that the target vehicle closest to the stop line of the intersection to be processed changes from the stationary state to the moving state, it is determined that the light state of the traffic light is in the green light state, and a target video frame corresponding to the target vehicle when the target vehicle changes from the stationary state to the moving state is obtained, and then according to the timestamp of the target video frame and the determined light state of the traffic light, a correspondence relationship between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light is determined.
That is to say, after the historical traffic video data of the camera is obtained, whether a target vehicle closest to a stop line of the intersection to be processed is started or not can be determined according to the historical traffic video data, and the stop line is pressed, if the target vehicle closest to the stop line of the intersection to be processed is determined to be started and the stop line is pressed, the light state of the traffic light at the current intersection is determined to be in a green light state, for example, a straight-going vehicle in the west direction starts to be started, the straight-going light corresponding to the west direction is in a green light state, and a target video frame corresponding to the start of the target vehicle and the stop line is pressed is obtained; and/or
The method comprises the steps of collecting vehicle information in historical traffic video data according to a camera, determining that a signal lamp of a current intersection is changed from a red lamp to a green lamp when the vehicle of the current intersection is changed from a static state to a moving state according to collected frame images, determining a corresponding video timestamp when the vehicle of the current intersection is changed from the static state to the moving state, and taking the determined video timestamp as a time point corresponding to the state that the signal lamp is in the green lamp state, so that the corresponding relation between the timestamp of the video frame in the historical traffic video data and the lamp state of the traffic lamp is obtained.
In order to more accurately determine the corresponding relationship between the timestamp of the video frame and the light state of the traffic light, optionally, in the embodiment of the application, after the target vehicle is started and the target video frame corresponding to the stop line is pressed, the wakeup time required for switching the target vehicle from the parking state to the driving state can be obtained, then the wakeup time is subtracted from the timestamp of the target video frame to obtain the target timestamp, and then the corresponding relationship between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light is determined according to the target timestamp and the determined light state of the traffic light.
Here, the wake-up elapsed time is an empirical value obtained in advance by comprehensively analyzing the time required for a large number of vehicles to switch from a parking state to a driving state.
In the embodiment of this application, in order to further determine the timestamp offset between camera and the traffic signal machine accurately, still can combine the vehicle type of target vehicle, determine that the target vehicle switches from the parking state to the required time consuming of awaking of running state to can improve the accuracy of the corresponding relation between the lamp state of the timestamp of the video frame that determines and the traffic light, and then can improve the accuracy of the timestamp offset between camera and the traffic signal machine that determines.
The types of vehicles include, but are not limited to, cars, automobiles, passenger cars, and the like.
And S230, acquiring the offset of the timestamp between the camera and the traffic signal machine according to the corresponding relation between the timestamp of the video frame and the light state of the traffic light and the corresponding relation between the light state of the traffic light and the timestamp.
That is, after determining the correspondence between the time stamps of the video frames and the light states of the traffic lights in the historical traffic video data, the time stamp offset between the camera and the traffic signal machine may be determined according to the correspondence between the time stamps of the video frames and the light states of the traffic lights and the correspondence between the light states of the traffic lights and the time stamps.
S240, acquiring current traffic video data of the intersection to be processed and current traffic light information of the intersection to be processed, wherein the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed.
And S250, aligning the time stamp of the current traffic video data and the time stamp of the current traffic light information based on the time stamp offset.
For example, after the timestamp offset between the camera and the traffic signal machine is determined, the timestamp of the current traffic video data can be time-corrected according to the timestamp offset, and the current traffic video data timestamp and the current traffic light information timestamp are aligned according to the offset, or the current traffic light information timestamp is time-corrected according to the timestamp offset, and the current traffic light information timestamp and the current traffic video data timestamp are aligned according to the offset.
And S260, determining the current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information.
And S270, controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
It should be noted that, in the embodiment of the present application, the implementation manners of the steps S260 to S270 may refer to the implementation manners of the steps S140 to S1540, and are not described herein again.
According to the intelligent traffic control method of the embodiment of the application, historical traffic video data of a camera is obtained, historical traffic light information of a traffic signal machine is obtained, wherein the historical traffic light information comprises a corresponding relation between the light state of the traffic light and the time stamp, and then the vehicle behavior information in the historical traffic video data is analyzed, to determine a correspondence between timestamps of video frames in the historical traffic video data and light states of the traffic lights, further determining the offset of the time stamp between the camera and the traffic signal according to the corresponding relation between the time stamp of the video frame and the light state of the traffic light and the corresponding relation between the light state of the traffic light and the time stamp, the time stamps of the current traffic video data and the current traffic light information can be accurately aligned, the accuracy of traffic data calculation is improved, and the optimization effect of intelligent traffic is improved.
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. 3 is a schematic diagram of a second embodiment according to the present application.
As shown in fig. 3, the intelligent traffic control device 300 includes: a first acquisition module 310, a second acquisition module 320, a processing module 330, a first determination module 340, and a control module 350. Wherein:
the first obtaining module 310 is configured to obtain current traffic video data of an intersection to be processed and current traffic light information of the intersection to be processed, where the current traffic video data is collected by a camera disposed at the intersection to be processed, and the current traffic light information is provided by a traffic signal machine disposed at the intersection to be processed;
the second obtaining module 320 is configured to obtain a timestamp offset between the camera and the traffic signal machine;
the processing module 330 is configured to perform alignment processing on the timestamp of the current traffic video data and the timestamp of the current traffic light information based on the timestamp offset;
the first determining module 340 is configured to determine current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information;
the control module 350 is configured to control a signal control scheme of the traffic signal according to the current traffic index data.
In an embodiment of the present application, as shown in fig. 4, the second obtaining module includes: a third obtaining module 360, a second determining module 370, and a third determining module 380, where the third obtaining module 360 is configured to obtain historical traffic video data of the camera and historical traffic light information of the traffic signal machine that is time-dependent on the historical traffic video data, and the historical traffic light information includes a correspondence between a light state of a traffic light and a timestamp; the second determining module 370 is configured to analyze the vehicle behavior information in the historical traffic video data to determine a corresponding relationship between a timestamp of a video frame in the historical traffic video data and a light state of a traffic light; the third determining module 380 is configured to obtain a timestamp offset between the camera and the traffic signal according to a correspondence between the timestamp of the video frame and the light state of the traffic light and a correspondence between the light state of the traffic light and the timestamp.
In an embodiment of the present application, the second determining module 370 includes: the video data processing unit is used for determining that the light state of the traffic light is in the green light state and acquiring a corresponding target video frame when the target vehicle changes from the static state to the motion state if the target vehicle closest to the stop line of the intersection to be processed is determined to change from the static state to the motion state according to the historical traffic video data; and the corresponding relation processing unit is used for determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the timestamp of the target video frame and the determined light state of the traffic light.
In an embodiment of the present application, the correspondence processing unit includes: the acquiring subunit is used for acquiring the awakening time consumption required by the target vehicle to be switched from the parking state to the running state; the processing subunit is configured to subtract the wakeup time from the timestamp of the target video frame to obtain a target timestamp; and the determining subunit is used for determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the target timestamp and the determined light state of the traffic light.
In an embodiment of the present application, the obtaining subunit is specifically configured to: determining a vehicle type of the target vehicle; and determining the awakening time consumption required by the target vehicle to be switched from the parking state to the running state according to the vehicle type.
According to the intelligent traffic control device of the embodiment of the application, the current traffic video data collected by the camera on the intersection to be processed and the current traffic light information of the traffic signal machine can be obtained, the offset of the timestamp between the camera and the traffic signal machine is obtained, the timestamp of the current traffic video data and the timestamp of the current traffic light information are aligned based on the offset of the timestamp, then the current traffic index data of the intersection to be processed is determined according to the aligned current traffic video data and the aligned current traffic light information, and finally the signal control scheme of the traffic signal machine is controlled according to the current traffic index data. Therefore, the timestamps of the current traffic video data and the current traffic light information can be accurately aligned according to the timestamp offset between the camera and the traffic signal machine, the accuracy of traffic data calculation is improved, and the optimization effect of intelligent traffic is improved.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
As shown in fig. 5, a block diagram of an electronic device for implementing the intelligent traffic control method according to the embodiment of the present application is shown. 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 examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 5, the electronic apparatus includes: one or more processors 501, memory 502, and interfaces for connecting the various components, including high-speed interfaces and low-speed interfaces. 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, as 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). In fig. 5, one processor 501 is taken as an example.
The memory 502, 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 location first obtaining module 310, the processing module 320, the first determining module 330, and the control module 340 shown in fig. 3). The processor 501 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 502, that is, implements the intelligent traffic control method in the above method embodiment.
The memory 502 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 502 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, memory 502 optionally includes memory located remotely from processor 501, 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 503 and an output device 504. The processor 501, the memory 502, the input device 503 and the output device 504 may be connected by a bus or other means, and fig. 5 illustrates the connection by a bus as an example.
The input device 503 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 apparatus, 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, or other input devices. The output devices 504 may include a display device, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibrating motors), among others. 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.
According to the technical scheme of the embodiment of the application, the current traffic video data collected by the camera on the intersection to be processed and the current traffic light information of the traffic signal machine can be obtained, the timestamp offset between the camera and the traffic signal machine is combined, the current traffic video data and the timestamp of the current traffic light information are aligned, then the current traffic index data of the intersection to be processed is determined according to the aligned current traffic video data and the aligned current traffic light information, and finally the signal control scheme of the traffic signal machine is controlled according to the current traffic index data. According to the method, the timestamp offset between the camera and the traffic signal machine is used, so that the timestamp of the current traffic video data and the timestamp of the current traffic light information can be accurately aligned, the accuracy of traffic data calculation is improved, and the optimization effect of intelligent traffic is improved.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto 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. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with 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.
Fig. 6 is a schematic diagram according to a third embodiment of the present application.
As shown in fig. 6, the intelligent traffic control method may include:
s610, obtaining current traffic video data of the intersection to be processed and current traffic light information of the intersection to be processed, wherein the current traffic video data is collected by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed.
And S620, acquiring the timestamp offset between the camera and the traffic signal machine.
S630, based on the timestamp offset, performing an alignment process on the timestamp of the current traffic video data and the timestamp of the current traffic light information.
And S640, controlling a signal control scheme of the traffic signal machine according to the aligned current traffic video data and the current traffic light information.
In this embodiment of the present application, a specific implementation manner of S640 may be: determining current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information; and controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
According to the intelligent traffic control method, the timestamp offset between the camera and the traffic signal machine is combined, the timestamp of the current traffic video data and the timestamp of the current traffic light information are aligned, and then the signal control scheme of the traffic signal machine is controlled according to the aligned current traffic video data and the aligned current traffic light information, so that the calculation accuracy of the traffic data can be improved, and the intelligent traffic optimization effect is improved.
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.
Claims (13)
1. An intelligent traffic control method, comprising:
acquiring current traffic video data of an intersection to be processed and current traffic light information of the intersection to be processed, wherein the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed;
acquiring a timestamp offset between the camera and the traffic signal machine;
aligning the timestamp of the current traffic video data and the timestamp of the current traffic light information based on the timestamp offset;
determining the current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information;
and controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
2. The method of claim 1, wherein the obtaining the timestamp offset between the camera and the traffic signal comprises:
acquiring historical traffic video data of the camera and historical traffic light information of the traffic signal machine related to the historical traffic video data time, wherein the historical traffic light information comprises a corresponding relation between a light state of a traffic light and a timestamp;
analyzing the vehicle behavior information in the historical traffic video data to determine the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light;
and acquiring the timestamp offset between the camera and the traffic signal machine according to the corresponding relation between the timestamp of the video frame and the light state of the traffic light and the corresponding relation between the light state of the traffic light and the timestamp.
3. The method of claim 2, wherein analyzing the vehicle behavior information in the historical traffic video data to determine a correspondence between timestamps of video frames in the historical traffic video data and light states of traffic lights comprises:
according to the historical traffic video data, if it is determined that a target vehicle closest to a stop line of the intersection to be processed is changed from a static state to a moving state, determining that the light state of the traffic light is in a green light state, and acquiring a corresponding target video frame when the target vehicle is changed from the static state to the moving state;
and determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the timestamp of the target video frame and the determined light state of the traffic light.
4. The method of claim 3, wherein determining the correspondence between the timestamps of the video frames in the historical traffic video data and the light states of the traffic lights according to the timestamps of the target video frames and the determined light states of the traffic lights comprises:
acquiring awakening time consumption required by the target vehicle to be switched from a parking state to a running state;
subtracting the awakening time consumption from the timestamp of the target video frame to obtain a target timestamp;
and determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the target timestamp and the determined light state of the traffic light.
5. The method of claim 4, wherein the obtaining of the wake-up elapsed time required for the target vehicle to switch from the parked state to the driven state comprises:
determining a vehicle type of the target vehicle;
and determining the awakening time consumption required by the target vehicle to be switched from the parking state to the running state according to the vehicle type.
6. An intelligent traffic control device, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring current traffic video data of an intersection to be processed and current traffic light information of the intersection to be processed, the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed;
the second acquisition module is used for acquiring the timestamp offset between the camera and the traffic signal machine;
the processing module is used for aligning the timestamp of the current traffic video data and the timestamp of the current traffic light information based on the timestamp offset;
the first determining module is used for determining the current traffic index data of the intersection to be processed according to the aligned current traffic video data and the current traffic light information;
and the control module is used for controlling a signal control scheme of the traffic signal machine according to the current traffic index data.
7. The apparatus of claim 6, wherein the second obtaining module comprises:
the third acquisition module is used for acquiring historical traffic video data of the camera and historical traffic light information of the traffic signal machine related to the historical traffic video data in time, wherein the historical traffic light information comprises a corresponding relation between a light state of a traffic light and a timestamp;
the second determination module is used for analyzing the vehicle behavior information in the historical traffic video data to determine the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light;
and the third determining module is used for acquiring the timestamp offset between the camera and the traffic signal machine according to the corresponding relation between the timestamp of the video frame and the light state of the traffic light and the corresponding relation between the light state of the traffic light and the timestamp.
8. The apparatus of claim 7, wherein the second determining module comprises:
the video data processing unit is used for determining that the light state of the traffic light is in the green light state and acquiring a corresponding target video frame when the target vehicle changes from the static state to the motion state if the target vehicle closest to the stop line of the intersection to be processed is determined to change from the static state to the motion state according to the historical traffic video data;
and the corresponding relation processing unit is used for determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the timestamp of the target video frame and the determined light state of the traffic light.
9. The apparatus according to claim 8, wherein the correspondence processing unit includes:
the acquiring subunit is used for acquiring the awakening time consumption required by the target vehicle to be switched from the parking state to the running state;
the processing subunit is configured to subtract the wakeup time from the timestamp of the target video frame to obtain a target timestamp;
and the determining subunit is used for determining the corresponding relation between the timestamp of the video frame in the historical traffic video data and the light state of the traffic light according to the target timestamp and the determined light state of the traffic light.
10. The apparatus according to claim 8, wherein the obtaining subunit is specifically configured to:
determining a vehicle type of the target vehicle;
and determining the awakening time consumption required by the target vehicle to be switched from the parking state to the running state according to the vehicle type.
11. 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 intelligent traffic control method of any of claims 1-5.
12. A non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the intelligent transportation control method according to any one of claims 1 to 5.
13. An intelligent traffic control method, comprising:
acquiring current traffic video data of an intersection to be processed and current traffic light information of the intersection to be processed, wherein the current traffic video data is acquired by a camera arranged on the intersection to be processed, and the current traffic light information is provided by a traffic signal machine arranged on the intersection to be processed;
acquiring a timestamp offset between the camera and the traffic signal machine;
aligning the timestamp of the current traffic video data and the timestamp of the current traffic light information based on the timestamp offset;
and controlling a signal control scheme of the traffic signal machine according to the aligned current traffic video data and the current traffic light information.
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