CN111667701A - Method and device for adjusting signal control equipment - Google Patents
Method and device for adjusting signal control equipment Download PDFInfo
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- CN111667701A CN111667701A CN202010460364.3A CN202010460364A CN111667701A CN 111667701 A CN111667701 A CN 111667701A CN 202010460364 A CN202010460364 A CN 202010460364A CN 111667701 A CN111667701 A CN 111667701A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/08—Controlling traffic signals according to detected number or speed of vehicles
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
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Abstract
The application discloses a method and a device for adjusting a signal control device, which relate to the technical field of intelligent traffic, wherein the method comprises the following steps: responding to a received green light signal of the signal control equipment, and acquiring the vehicle queuing length corresponding to the green light signal in the target flow direction and the vehicle passing track characteristic of passing through a traffic intersection in a green light period; processing the vehicle passing track characteristics according to the evanescent wave model to obtain the vehicle evanescent wave speed corresponding to the target flow direction; and acquiring the vehicle emptying time of the target flow direction according to the speed of the vehicle evanescent wave and the vehicle queuing length, and adjusting the signal period of the signal control equipment according to the vehicle emptying time. Therefore, the intelligent determination of the signal period is realized, so that the signal period not only accords with the real traffic condition, but also has higher precision.
Description
Technical Field
The application relates to the technical field of intelligent traffic in data processing, in particular to a method and a device for adjusting a signal control device.
Background
With the increase of the holding amount of vehicles, urban traffic roads develop faster and faster, and in order to meet the traffic demands of pedestrians, vehicles and different vehicles, the traffic operation is controlled according to signal lamps in the signal control equipment.
However, since the road traffic condition changes constantly, if the period setting of the signal lamps is not reasonable, the road may be crowded, and even traffic accidents may be caused.
Disclosure of Invention
The application provides a method and a device for adjusting a signal control device, so that the intelligent determination of a signal period is realized, the signal period not only accords with the real traffic condition, but also has higher determination precision.
According to a first aspect, there is provided a method for adjusting a signaling device, including: responding to a received green light signal of the signal control equipment, and acquiring the vehicle queuing length corresponding to the green light signal in the target flow direction and the vehicle passing track characteristic of a traffic intersection in a green light period; processing the vehicle passing track characteristics according to an evanescent wave model to obtain the speed of vehicle evanescent waves corresponding to the target flow direction; and acquiring the vehicle emptying time of the target flow direction according to the speed of the vehicle evanescent wave and the vehicle queuing length, and adjusting the signal period of the signal control equipment according to the vehicle emptying time.
Optionally, before the acquiring the vehicle passing track characteristic passing through the traffic intersection in the green light period, the method further includes: acquiring a video track of the target flow direction, analyzing the video track, and extracting sample GPS data carrying time characteristics and position characteristics; comparing the time characteristic with the green light time of the signal control equipment to acquire target GPS data corresponding to the green light time; analyzing the position characteristics of the target GPS data, extracting vehicle passing sample track characteristics, and calculating a true value of the velocity of the evanescent wave corresponding to the vehicle passing sample track characteristics according to a preset algorithm; training the velocity true value of the evanescent wave corresponding to the vehicle passing sample track characteristic according to a preset objective function, acquiring corresponding model parameters, and generating the model of the evanescent wave according to the model parameters.
Optionally, before comparing the time characteristic with the green light time of the information control device, the method further includes: determining whether the corresponding sample GPS data meets a preset normal driving condition or not according to the time characteristic and the position characteristic; deleting the sample GPS data which does not satisfy the normal driving condition.
Optionally, the analyzing the location features of the target GPS data to extract track features of vehicle passing samples includes: extracting the distance between the vehicle corresponding to the target GPS data and the stop line at the moment of turning on the green light according to the position characteristics; extracting the speed of the vehicle corresponding to the target GPS data passing through the stop line according to the position characteristics; extracting the running speed of the vehicle corresponding to the target GPS data in the stop line according to the position characteristics; extracting the stable speed of the vehicle corresponding to the target GPS data in the parking line according to the position characteristics; and extracting the acceleration of the target GPS data from rest to the stable speed according to the position characteristics.
Optionally, the obtaining, according to the speed of the vehicle evanescent wave and the vehicle queuing length, the vehicle emptying time of the target flow direction includes: acquiring a stable speed of the vehicle; calculating a first ratio of the vehicle queue length to the steady speed; calculating a second ratio of the vehicle queue length and the speed of the vehicle evanescent wave; and calculating the sum of the first ratio and the second ratio to obtain the vehicle emptying time.
In a second aspect of the present application, there is provided a device for adjusting a signaling device, including: the first acquisition module is used for responding to a received green light signal of the signal control equipment, and acquiring the vehicle queuing length corresponding to the green light signal in the target flow direction and the vehicle passing track characteristic passing through a traffic intersection in a green light period; the second acquisition module is used for processing the vehicle passing track characteristics according to an evanescent wave model and acquiring the speed of vehicle evanescent waves corresponding to the target flow direction; the third acquisition module is used for acquiring the vehicle emptying time of the target flow direction according to the speed of the vehicle evanescent wave and the vehicle queuing length; and the adjusting module is used for adjusting the signal period of the signal control equipment according to the vehicle emptying time.
Optionally, the method further includes: the analysis module is used for acquiring a video track of the target flow direction, analyzing the video track and extracting sample GPS data carrying time characteristics and position characteristics; the fourth acquisition module is used for comparing the time characteristic with the green light time of the signal control equipment and acquiring target GPS data corresponding to the green light time; the calculation module is used for analyzing the position characteristics of the target GPS data, extracting vehicle passing sample track characteristics and calculating a true value of the velocity of the evanescent wave corresponding to the vehicle passing sample track characteristics according to a preset algorithm; and the fifth obtaining module is used for training the true value of the velocity of the evanescent wave corresponding to the track characteristic of the vehicle passing sample according to a preset objective function, obtaining corresponding model parameters and generating a model of the evanescent wave according to the model parameters.
Optionally, the third obtaining module is specifically configured to: acquiring a stable speed of the vehicle;
calculating a first ratio of the vehicle queue length to the steady speed; calculating a second ratio of the vehicle queue length and the speed of the vehicle evanescent wave; and calculating the sum of the first ratio and the second ratio to obtain the vehicle emptying time.
In a third aspect of the present application, there is provided 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 method for adjusting the signaling device described in the above embodiments.
In a fourth aspect of the present application, a non-transitory computer-readable storage medium is provided, in which computer instructions are stored, and the computer instructions are configured to cause the computer to execute the method for adjusting the signal control device described in the foregoing embodiment.
The technical scheme provided by the embodiment of the application has the following technical effects:
responding to a green light signal of the signal control equipment, acquiring a vehicle queue length corresponding to a target flow direction corresponding to the green light signal, acquiring vehicle passing track characteristics of a traffic intersection passing through a green light period, processing the vehicle passing track characteristics according to an evanescent wave model, acquiring a vehicle evanescent wave speed corresponding to the target flow direction, further acquiring a vehicle emptying time of the target flow direction according to the vehicle evanescent wave speed and the vehicle queue length, and adjusting the signal period of the signal control equipment according to the vehicle emptying time. Therefore, the intelligent determination of the signal period is realized, so that the signal period not only accords with the real traffic condition, but also has higher determination precision.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is a schematic flow chart of a method for adjusting a signaling device according to a first embodiment of the present application;
fig. 2-1 is a schematic diagram of a signaling scenario of a signaling device according to a second embodiment of the present application;
FIG. 2-2 is a schematic diagram of a queuing length determination scenario according to a third embodiment of the present application;
FIG. 3 is a schematic diagram of a stabilization speed determination scenario according to a fourth embodiment of the present application;
fig. 4 is a schematic flow chart of a method for adjusting a signaling device according to a fifth embodiment of the present application;
fig. 5 is a schematic structural diagram of an adjusting apparatus of a signaling device according to a sixth embodiment of the present application;
fig. 6 is a schematic structural diagram of a signal control device adjusting apparatus according to a seventh embodiment of the present application;
fig. 7 is a block diagram of an electronic device for implementing the method for adjusting the signaling device according to the 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.
In order to solve the technical problems of low setting efficiency and low setting accuracy caused by manual setting of the signal lamp period in the background art, the application provides a signal control equipment adjusting method, in the method, various traffic characteristics of vehicles can be extracted based on GPS track data of a map, the vehicle can be matched with video detection to obtain the true values of the queuing length and the evanescent wave in a machine learning calculation mode, training is carried out, a trained model can obtain a better calculation effect of the signal lamp period, and the accuracy rate is over 90% through experimental verification.
Specifically, fig. 1 is a flowchart of a method for adjusting a signaling device according to an embodiment of the present application, and as shown in fig. 1, the method includes:
The target flow direction in this embodiment is a flow direction indicated by a green light, and the green light period is a period corresponding to the lighting time of the green light. For example, as shown in fig. 2-1, when the signaling device is green and the signal corresponds to an east-west flow, the target flow is east-west. With continued reference to fig. 2-1, when the signaling device in the east-west flow direction is a green light signal (gray represents the corresponding signaling light on state in the figure), and in a control period with a duration of 60 seconds (each control period consists of one green light period and one red light period), the green light is turned on at the 21 st second of the control period until turned off at 60 seconds, and the corresponding green light period is the time for which the green light is turned on in the control period, in this example, the green light period is 40 seconds.
In one embodiment, when the signal control device is a green light signal, in response to the received green light signal of the signal control device, the vehicle queue length of the target flow direction corresponding to the green light signal is acquired, and the vehicle passing track characteristic of the vehicle passing through the traffic intersection in the green light period is acquired. Wherein, the pass track characteristics may include: the distance from the parking line position at the moment of green light turning on, the time required for passing the parking line, the acceleration from rest to stable speed, the speed of the vehicle passing the parking line in the crossing and the like. In addition, whether the signal control lamp of the current signal control equipment is a green lamp signal or not can be analyzed by detecting the light color of the signal control equipment or shooting the image of the signal control equipment.
It should be noted that, in different application scenarios, the manner of obtaining the corresponding vehicle queue length and obtaining the vehicle passing track characteristics through the traffic intersection in the green light period is different, and the following examples are given:
example one:
in this example, video data of the target stream is acquired, and the queue length of the vehicle is extracted according to information contained in the video data, wherein as shown in fig. 2-2, when the target stream corresponding to the current green light is downward and the vehicle contains 1-5, 5 waiting vehicles, the queue length is calculated according to the distance from the head of the vehicle 1 to the tail of the vehicle 5 in the image, wherein the queue length may be calculated according to the zoom ratio of the video image, and the like.
Further, the video images of the vehicles passing through the traffic intersection in the green light period are extracted, and the corresponding vehicle passing track features are extracted according to the video images, for example, when the vehicle passing track features include the stable speed of the vehicles and the stable speed of the vehicle a is analyzed, as shown in fig. 3, if the green light period includes 100 video frames, according to the variation situation of the traveling distance of the vehicle a between the adjacent video frames in the 100 video frames, when the traveling distance of the video frame time is stable, that is, not changed, for example, between the video frames 50-53, the traveling distances corresponding to the video frames of 3 consecutive periods are all almost equal, it is considered that the vehicle a reaches the stable speed at 50 frames, and the stable speed is calculated according to the traveling distance between the adjacent frames and the corresponding time difference.
Example two:
in this example, at the time of the green light being turned on, the position of the first wheel to the last wheel of the queued vehicle corresponding to the target flow down is determined based on the position information and the weight information of the wheels detected by the road surface sensor, and the queuing length is determined based on the distance of the link covered between the positions.
Further, from the position information and the weight information of the vehicles detected during the green light period, the position where the wheel belonging to one vehicle travels on the road surface and the distance to the traveling section are identified based on the difference between the weights of the vehicles or the mutual positions between the wheels, and the vehicle passing track characteristic is determined.
And 102, processing the vehicle passing track characteristics according to the evanescent wave model, and acquiring the vehicle evanescent wave speed corresponding to the target flow direction.
It can be understood that the evanescent wave model is trained in advance, and the evanescent wave model can output the velocity of the evanescent wave according to the input vehicle passing track characteristics, wherein the velocity of the evanescent wave refers to the time when all the queued traffic flows pass through the corresponding traffic intersection before the green light is turned on.
In an embodiment of the application, in order to improve the calculation efficiency, the number of queued vehicles may also be obtained, and it is determined whether the number of the vehicles is greater than a preset threshold, if so, for example, greater than 10, the vehicle trajectory passing characteristics of the vehicles behind 10 vehicles are obtained, the calculation for the front 10 vehicles is not needed, and when less than 10 vehicles are queued, the vehicle trajectory passing characteristics are directly ignored, and the signal control device in the flow direction is not adjusted.
And 103, acquiring the vehicle emptying time of the target flow direction according to the speed of the vehicle evanescent wave and the vehicle queuing length, and adjusting the signal period of the signal control equipment according to the vehicle emptying time.
In one embodiment of the application, the vehicle emptying time of the target flow direction is obtained according to the speed of the vehicle evanescent wave and the vehicle queuing length, and the signal period of the signal control device is adjusted according to the vehicle emptying time, so that the queued vehicles can be emptied in the signal period, and smooth traffic is guaranteed. The signal period in this embodiment can be understood as the duration of the green light.
It should be noted that, in different application scenarios, the way of obtaining the vehicle emptying time of the target flow direction is different according to the speed of the vehicle evanescent wave and the vehicle queuing length, and the following examples are given:
example one:
in this example, the steady speed of the vehicle is calculated, which may be calculated by referring to the above-mentioned embodiment, further, a first ratio of the vehicle queue length and the steady speed is calculated, a second ratio of the vehicle queue length and the speed of the vehicle evanescent wave is calculated, and the sum of the first ratio and the second ratio is calculated to obtain the vehicle emptying time.
Example two:
in this embodiment, the stable speed of the vehicle and the instantaneous speed of the vehicle passing through the stop line are calculated in a manner that reference is made to the above embodiment, the instantaneous speed of the vehicle may be obtained according to the speed value detected by the sensor under the stop line, further, the difference between the stable speed and the instantaneous speed is calculated, the third ratio of the vehicle queuing length to the difference is calculated, the fourth ratio of the vehicle queuing length to the speed of the vehicle evanescent wave is calculated, and the sum of the third ratio and the fourth ratio is calculated to obtain the vehicle emptying time.
In summary, the method for adjusting the signal control device according to the embodiment of the present application responds to a green light signal of the signal control device, obtains a vehicle queuing length of a target flow direction corresponding to the green light signal, obtains a vehicle passing track characteristic of a traffic intersection passing through a green light period, processes the vehicle passing track characteristic according to a pre-trained evanescent wave model, obtains a vehicle evanescent wave speed corresponding to the target flow direction, further obtains a vehicle clearing time of the target flow direction according to the vehicle evanescent wave speed and the vehicle queuing length, and adjusts a signal period of the signal control device according to the vehicle clearing time. Therefore, the intelligent determination of the signal period is realized, so that the signal period not only accords with the real traffic condition, but also has higher determination precision.
According to the above embodiment, the evanescent wave model can be obtained in different manners according to different scene needs, in an embodiment of the present application, the evanescent wave model is obtained by pre-training, as shown in fig. 4, and the method for training the evanescent wave model may include:
In one embodiment, a video track of a target flow direction is obtained, the video track may be a video image containing image information of a vehicle flow, the video track is analyzed to extract sample GPS data carrying time characteristics and position characteristics, the position characteristics are characteristics of a road sign such as a relative stop line of the vehicle, the time characteristics refer to characteristics of each stage of a green light, and in short, the time characteristics may be time characteristics that a signal light is a green light, and the time characteristics may be obtained through analysis according to color characteristics of the signal light in the video.
It will also be appreciated that in this embodiment, sample GPS data containing time and location features is extracted. The sample GPS data may be a video image containing GPS positioning data, and the position information of the video image is extracted during subsequent analysis, or may be corresponding specific data containing a vehicle position, which may be a distance from the vehicle head to a stop line, a length of a vehicle tail and a time of the vehicle head, and the like.
The green light time may include a green light turning-on time, a green light cycle time, a green light stopping time, and the like, the shooting time point of the video frame corresponding to the time characteristic is corresponding to each stage time of turning on the green light, and target GPS data corresponding to the green light time is determined, for example, when the green light time is from a time point a to a time point B, the target GPS data is GPS data from the time point a to the time point B, where the GPS data corresponding to the target GPS data corresponds to each stage time of turning on the green light.
Of course, in the actual implementation process, there may be some abnormal trajectory data such as long-time no-hit, reverse, abnormal parking, etc. of the GPS data, and therefore, in order to remove these noise data, in this embodiment, it is further determined whether the corresponding sample GPS data meets the preset normal driving condition according to the time characteristic and the location characteristic, where the normal driving condition includes the above-mentioned driving trajectory such as long-time no-hit, reverse, abnormal parking, etc., and then the sample GPS data that does not meet the normal driving condition is deleted.
For example, when the normal driving condition is abnormal parking, it is extracted whether the position of the vehicle in the target flow direction at different time points changes according to the sample GPS data, and if not, and the corresponding time is at the green light on time, it is determined that the vehicle may have an abnormal parking behavior, so that the sample GPS data corresponding to the vehicle is deleted.
And 203, analyzing the position characteristics of the target GPS data, extracting vehicle passing sample track characteristics, and calculating the true value of the velocity of the evanescent wave corresponding to the vehicle passing sample track characteristics according to a preset algorithm.
In an embodiment of the present application, the position feature of the target GPS data is analyzed to extract a vehicle passing sample track feature, and as for the above embodiment, the extraction process of the sample track feature may be to extract a vehicle corresponding to the target GPS data according to the position feature, a distance from a stop line at a time when a green light is turned on, a vehicle corresponding to the target GPS data according to the position feature, a speed passing through the stop line, a vehicle corresponding to the target GPS data according to the position feature, a shape running speed inside the stop line, a vehicle corresponding to the target GPS data according to the position feature, a stable speed inside the stop line, an acceleration at which the target GPS data reaches the stable speed from a standstill according to the position feature, and the like.
For example, when the vehicle passing sample track characteristic is the distance from the green light starting time to the stop line, the target GPS data corresponding to the green light starting time is extracted, and the distance between the vehicle head and the stop line in the target GPS data is extracted.
And further, calculating a true velocity value of the evanescent wave corresponding to the vehicle passing sample track characteristic according to a preset algorithm, wherein the preset algorithm can be used for obtaining the passing time of each vehicle according to the difference value between the distance of each vehicle from the traffic lane and the stable velocity mean value in the queued vehicles, and taking the sum of the passing times of all the queued vehicles as the true velocity value of the evanescent wave.
And 204, training the velocity true value of the evanescent wave corresponding to the track characteristic of the vehicle passing sample according to a preset objective function, acquiring corresponding model parameters, and generating an evanescent wave model according to the model parameters.
In some examples, a corresponding relation between the vehicle passing sample track characteristic and the velocity of the evanescent wave is labeled in advance, a true velocity value of the evanescent wave corresponding to the vehicle passing sample track characteristic is trained according to a preset objective function, corresponding model parameters are obtained, and a model of the evanescent wave is generated according to the model parameters.
In summary, the method for adjusting the signal control device according to the embodiment of the present application trains the evanescent wave model in advance according to the target GPS data at the green time, so that the accuracy of the velocity of the evanescent wave obtained according to the evanescent wave model is ensured, the improvement of the setting practicability of the target signal period of the signal control device is facilitated, and the smooth traffic is ensured.
In order to implement the foregoing embodiment, the present application further provides a device for adjusting a signal control device, and fig. 5 is a schematic structural diagram of the device for adjusting a signal control device according to an embodiment of the present application, and as shown in fig. 5, the device for adjusting a signal control device includes: a first obtaining module 10, a second obtaining module 20, a third obtaining module 30, and an adjusting module 40, wherein,
the first acquisition module 10 is used for acquiring the vehicle queuing length of a target flow direction corresponding to a received green light signal of the signal control equipment and the vehicle passing track characteristics of a passing intersection in a green light period when the vehicle queuing length corresponds to the green light signal;
the second obtaining module 20 is configured to process the vehicle passing trajectory characteristics according to the evanescent wave model, and obtain a speed of vehicle evanescent waves corresponding to a target flow direction;
the third obtaining module 30 is configured to obtain a vehicle emptying time of a target flow direction according to a speed of vehicle evanescent waves and a vehicle queuing length;
and the adjusting module 40 is used for adjusting the signal period of the signal control equipment according to the vehicle emptying time.
In one embodiment of the present application, as shown in fig. 6, on the basis of fig. 5, the apparatus further comprises: an analysis module 50, a fourth acquisition module 60, a calculation module 70 and a fifth acquisition module 80, wherein,
the analysis module 50 is used for acquiring a video track of a target flow direction, analyzing the video track and extracting sample GPS data carrying time characteristics and position characteristics;
a fourth obtaining module 60, configured to compare the time characteristic with a green light time of the signal control device, and obtain target GPS data corresponding to the green light time;
the calculation module 70 is configured to analyze the position characteristics of the target GPS data, extract vehicle passing sample track characteristics, and calculate a true value of the velocity of the evanescent wave corresponding to the vehicle passing sample track characteristics according to a preset algorithm;
the fifth obtaining module 80 is configured to train a true value of the velocity of the evanescent wave corresponding to the track characteristic of the vehicle passing sample according to a preset objective function, obtain corresponding model parameters, and generate an evanescent wave model according to the model parameters.
In an embodiment of the present application, the third obtaining module 30 is specifically configured to:
acquiring the stable speed of the vehicle;
calculating a first ratio of the vehicle queuing length to the stable speed;
calculating a second ratio of the vehicle queue length to the velocity of the vehicle evanescent wave;
and calculating the sum of the first ratio and the second ratio to obtain the vehicle emptying time.
It should be noted that the foregoing explanation of the method for adjusting the information control device is also applicable to the apparatus for adjusting the information control device in the embodiment of the present application, and the implementation principle is similar, and is not repeated herein.
In summary, the adjusting device of the signaling control device in the embodiment of the present application, in response to a green light signal of the signaling control device, obtains a vehicle queuing length of a target flow direction corresponding to the green light signal, and obtains a vehicle passing track characteristic of a traffic intersection passing through a green light period, processes the vehicle passing track characteristic according to a pre-trained evanescent wave model, obtains a vehicle evanescent wave speed corresponding to the target flow direction, further obtains a vehicle clearing time of the target flow direction according to the vehicle evanescent wave speed and the vehicle queuing length, and adjusts a signal period of the signaling control device according to the vehicle clearing time. Therefore, the intelligent determination of the signal period is realized, so that the signal period not only accords with the real traffic condition, but also has higher determination precision. According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
Fig. 7 is a block diagram of an electronic device 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 examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 7, the electronic apparatus includes: one or more processors 701, a memory 702, 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, 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. 7, one processor 701 is taken as an example.
The memory 702 is a non-transitory computer readable storage medium as provided herein. The memory stores instructions executable by at least one processor to cause the at least one processor to perform the method for coordinating a trusted device provided herein. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to perform the method of trusted device adjustment provided herein.
The memory 702 serves as a non-transitory computer readable storage medium, and may be used for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules (e.g., the first obtaining module 10, the second obtaining module 20, the third obtaining module 30, and the adjusting module 40 shown in fig. 5) corresponding to the method for adjusting the communication device in the embodiment of the present application. The processor 701 executes various functional applications of the server and data processing by running non-transitory software programs, instructions and modules stored in the memory 702, that is, implements the method for the trusted device adjustment in the above method embodiments.
The memory 702 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 electronic device that performs the trusted device adjustment method, and the like. Further, the memory 702 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 702 may optionally include a memory remotely located from the processor 701, and these remote memories may be connected via a network to an electronic device that performs the trusted device adjustment method. 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 performing the method of adjusting the communication device may further include: an input device 703 and an output device 704. The processor 701, the memory 702, the input device 703 and the output device 704 may be connected by a bus or other means, and fig. 7 illustrates an example of a connection by a bus.
The input device 703 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device adjusted by the signal control device, such as a touch screen, keypad, mouse, track pad, touch pad, pointer stick, one or more mouse buttons, track ball, joystick, or other input device. The output devices 704 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile 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.
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.
Claims (10)
1. A method for adjusting a signal control device is characterized by comprising the following steps:
responding to a received green light signal of the signal control equipment, and acquiring the vehicle queuing length corresponding to the green light signal in the target flow direction and the vehicle passing track characteristic of a traffic intersection in a green light period;
processing the vehicle passing track characteristics according to an evanescent wave model to obtain the speed of vehicle evanescent waves corresponding to the target flow direction;
and acquiring the vehicle emptying time of the target flow direction according to the speed of the vehicle evanescent wave and the vehicle queuing length, and acquiring the target signal period of the signal control equipment according to the vehicle emptying time.
2. The method of claim 1, further comprising, prior to said processing said vehicle transit trajectory feature according to an evanescent wave model:
acquiring a video track of the target flow direction, analyzing the video track, and extracting sample GPS data carrying time characteristics and position characteristics;
comparing the time characteristic with the green light time of the signal control equipment to acquire target GPS data corresponding to the green light time;
analyzing the position characteristics of the target GPS data, extracting vehicle passing sample track characteristics, and calculating a true value of the velocity of the evanescent wave corresponding to the vehicle passing sample track characteristics according to a preset algorithm;
training the velocity true value of the evanescent wave corresponding to the vehicle passing sample track characteristic according to a preset objective function, acquiring corresponding model parameters, and generating the evanescent wave model according to the model parameters.
3. The method of claim 2, wherein prior to comparing the time signature to the green light time of the signal controlled device, further comprising:
determining whether the corresponding sample GPS data meets a preset normal driving condition or not according to the time characteristic and the position characteristic;
deleting the sample GPS data which does not satisfy the normal driving condition.
4. The method of claim 2, wherein said analyzing location features of said target GPS data to extract vehicle transit sample trajectory features comprises:
extracting the distance between the vehicle corresponding to the target GPS data and the stop line at the moment of turning on the green light according to the position characteristics;
extracting the speed of the vehicle corresponding to the target GPS data passing through the stop line according to the position characteristics;
extracting the running speed of the vehicle corresponding to the target GPS data in the stop line according to the position characteristics;
extracting the stable speed of the vehicle corresponding to the target GPS data in the parking line according to the position characteristics;
and extracting the acceleration of the target GPS data from rest to the stable speed according to the position characteristics.
5. The method of claim 1, wherein the obtaining a vehicle clearance time for the target flow direction based on the speed of the vehicle evanescent wave and the vehicle queue length comprises:
acquiring a stable speed of the vehicle;
calculating a first ratio of the vehicle queue length to the steady speed;
calculating a second ratio of the vehicle queue length and the speed of the vehicle evanescent wave;
and calculating the sum of the first ratio and the second ratio to obtain the vehicle emptying time.
6. A signal control device adjustment apparatus, comprising:
the first acquisition module is used for responding to a received green light signal of the signal control equipment, and acquiring the vehicle queuing length corresponding to the green light signal in the target flow direction and the vehicle passing track characteristic passing through a traffic intersection in a green light period;
the second acquisition module is used for processing the vehicle passing track characteristics according to an evanescent wave model and acquiring the speed of vehicle evanescent waves corresponding to the target flow direction;
the third acquisition module is used for acquiring the vehicle emptying time of the target flow direction according to the speed of the vehicle evanescent wave and the vehicle queuing length;
and the adjusting module is used for adjusting the target signal period of the signal control equipment according to the vehicle emptying time.
7. The apparatus of claim 6, further comprising:
the analysis module is used for acquiring a video track of the target flow direction, analyzing the video track and extracting sample GPS data carrying time characteristics and position characteristics;
the fourth acquisition module is used for comparing the time characteristic with the green light time of the signal control equipment and acquiring target GPS data corresponding to the green light time;
the calculation module is used for analyzing the position characteristics of the target GPS data, extracting vehicle passing sample track characteristics and calculating a true value of the velocity of the evanescent wave corresponding to the vehicle passing sample track characteristics according to a preset algorithm;
and the fifth obtaining module is used for training the true value of the velocity of the evanescent wave corresponding to the track characteristic of the vehicle passing sample according to a preset objective function, obtaining corresponding model parameters and generating a model of the evanescent wave according to the model parameters.
8. The apparatus of claim 6, wherein the third obtaining module is specifically configured to:
acquiring a stable speed of the vehicle;
calculating a first ratio of the vehicle queue length to the steady speed;
calculating a second ratio of the vehicle queue length and the speed of the vehicle evanescent wave;
and calculating the sum of the first ratio and the second ratio to obtain the vehicle emptying time.
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 trusted device adjustment of any one of claims 1-5.
10. A non-transitory computer readable storage medium storing computer instructions for causing a computer to execute the method for adjusting a trusted device according to any one of claims 1 to 5.
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