CN110942631B - Traffic signal control method based on flight time camera - Google Patents
Traffic signal control method based on flight time camera Download PDFInfo
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- CN110942631B CN110942631B CN201911214432.1A CN201911214432A CN110942631B CN 110942631 B CN110942631 B CN 110942631B CN 201911214432 A CN201911214432 A CN 201911214432A CN 110942631 B CN110942631 B CN 110942631B
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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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
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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
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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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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Abstract
The invention provides a traffic signal control method based on a flight time camera, which comprises the steps that a flight time TOF camera collects an environment image of a traffic road section area according to a received image collection instruction, generates three-dimensional point cloud data and sends the three-dimensional point cloud data to a monitoring processor; the monitoring processor carries out denoising processing on the three-dimensional point cloud data and carries out vehicle characteristic data extraction based on a vehicle characteristic data model to obtain a monitoring list corresponding to the characteristic data of each vehicle; the monitoring processor calculates the vehicle traffic volume count corresponding to the ID of the traffic section area according to the preset statistical duration, normalizes the vehicle traffic volume counts of other traffic section areas in the preset range, and calculates the maximum time period relative traffic volume difference.
Description
Technical Field
The invention relates to the field of data processing, in particular to a traffic signal control method based on a flight time camera.
Background
In recent years, with the continuous improvement of living standard of people, the traveling mode of people is greatly changed, and private cars also become one of indispensable transportation means in the life of people. The mode of selecting self-driving when going to work, work and holiday is also generally a preferred mode, a traffic passage road bears huge traffic flow, and the problems of traffic flow control and traffic jam of the traffic passage road are difficult to avoid.
With the continuous development of information technology, people use advanced information technology, communication technology, computer processing technology and the like in the control of traffic communication. With the progress of technology, variable lanes appear on main traffic roads in cities, which brings high traffic efficiency for vehicle communication and has a certain relieving effect on traffic congestion. At present, traffic managers generally judge the lane-variable control according to the current traffic flow condition and then change the lane direction to control the lane, and the manual operation mode has low efficiency and low accuracy.
Disclosure of Invention
In view Of the defects Of the prior art, an embodiment Of the present invention provides a traffic signal control method based on a Time Of Flight (TOF) camera, which collects an environment image Of each traffic segment area according to a preset frequency by using the TOF camera, generates a plurality Of three-dimensional point cloud data, sends the three-dimensional point cloud data to a monitoring processor, is not affected by external illumination light for collecting the image data, and can collect the image data Of the environment Of the traffic segment area even in a dark environment. The monitoring processor analyzes the received three-dimensional point cloud data to obtain vehicle traffic volume counting information of the vehicle, judges the traffic condition of the traffic road section area according to the vehicle traffic volume counting information, and generates a lane adjustment control signal for changing the traffic direction of the variable lane so as to achieve the purpose of changing the number of the traffic lanes of the traffic road section area. And the monitoring processor analyzes the vehicle traffic counting information of each traffic road section area and generates a signal lamp control command according to the analysis result to control the traffic signal lamp of the intersection.
In order to achieve the above object, the present invention provides a traffic signal control method based on a TOF camera, including:
the time of flight TOF camera collects an environment image of a traffic road section area according to a received image collecting instruction to generate three-dimensional point cloud data; wherein the TOF camera has a traffic segment region ID; the three-dimensional point cloud data has a timestamp of data acquisition time;
the TOF camera sends the three-dimensional point cloud data and the traffic section area ID to a monitoring processor;
the monitoring processor carries out denoising processing on the three-dimensional point cloud data to obtain denoised three-dimensional point cloud data;
the monitoring processor extracts vehicle characteristic data from the de-noised three-dimensional point cloud data based on a vehicle characteristic data model to obtain characteristic data of each vehicle, and stores the characteristic data in a monitoring list corresponding to the traffic road section area ID; the monitoring list also comprises a traffic section area ID and the data acquisition time;
the monitoring processor counts the vehicle characteristic data in the monitoring list corresponding to each traffic section area ID according to a preset statistical duration to obtain the vehicle traffic volume count corresponding to the traffic section area ID in the preset statistical duration;
the monitoring processor acquires the vehicle traffic volume counts of other traffic road sections in a preset range according to the traffic road section area ID, and normalizes the vehicle traffic volume counts corresponding to the traffic road section area ID and the vehicle traffic volume counts of other traffic road sections to obtain the time interval relative traffic rate of the traffic road section area in the preset range;
the monitoring processor calculates the difference value between the maximum time interval relative traffic rate and the minimum time interval relative traffic rate in the time interval relative traffic rates of the traffic road section areas in the preset range to obtain the maximum time interval relative traffic rate difference, and records a first traffic road section area ID corresponding to the maximum time interval relative traffic rate and a second traffic road section area ID corresponding to the minimum time interval relative traffic rate;
the monitoring processor judges whether the relative traffic difference in the maximum time period is greater than a preset value;
when the maximum time period relative traffic difference is larger than a preset value, the monitoring processor searches traffic road section area data relative to a first traffic road section area in the traffic road section area relation data according to the first traffic road section area ID to obtain a first opposite traffic road section area ID;
the monitoring processor determining whether the first opposing traffic segment area ID is the same as the second traffic segment area ID;
when the first opposite traffic section area ID is the same as the second traffic section area ID, the monitoring processor generates a first lane adjustment control signal for instructing to increase the number of lanes of a first lane corresponding to the first traffic section area ID and to decrease the number of lanes of an opposite lane of the first lane.
Preferably, the generating of the first lane adjustment control signal by the monitoring processor is to instruct to increase the number of lanes of the first lane corresponding to the first traffic section area ID and decrease the number of lanes of the opposite lane of the first lane, specifically:
the monitoring processor sends the first lane adjusting control signal to a first lane controller;
the first lane controller displays and sends a forbidden state instruction to a first opposite variable lane indicator according to the first lane adjusting control signal; and displaying and sending a passing state instruction to the first variable lane indicating plate.
Preferably, when the monitoring processor determines that the first opposite traffic segment area ID is different from the second traffic segment area ID, the method further comprises:
the monitoring processor searches traffic road section area data relative to a second traffic road section area in the traffic road section area relation data according to the second traffic road section area ID to obtain a second opposite traffic road section area ID;
the monitoring processor calculates the sum of the first traffic section area ID and the vehicle traffic volume count corresponding to the first opposite traffic section area ID to obtain a first comparative vehicle traffic volume count;
the monitoring processor calculates the sum of the vehicle traffic volume counts corresponding to the second traffic section area ID and the second opposite traffic section area ID to obtain a second comparison vehicle traffic volume count;
and the monitoring processor generates a signal lamp control command according to the preset control time of the signal lamp, the first comparison vehicle traffic volume count and the second comparison vehicle traffic volume count so as to control the traffic signal lamp.
Further preferably, the traffic signal lamps include a first traffic signal lamp, a first directional traffic signal lamp, a second traffic signal lamp and a second object traffic signal lamp; the monitoring processor generates a signal lamp control command according to the preset control time of the signal lamp, the first comparison vehicle traffic volume count and the second comparison vehicle traffic volume count, and is used for controlling the traffic signal lamp specifically as follows:
the monitoring processor calculates a transit time ratio according to the first comparison vehicle transit amount count and the second comparison vehicle transit amount count;
the monitoring processor judges whether the traffic time ratio exceeds a preset traffic time ratio range;
when the passing time ratio exceeds the range of a preset passing time ratio, the monitoring processor calculates according to the preset monitoring time and the passing time ratio to obtain first passing time and first no-passing time;
and the monitoring processor generates a signal lamp control command according to the first passing time and the first no-passing time and sends the signal lamp control command to the first traffic signal controller, the first opposite traffic signal controller, the second traffic signal controller and the second opposite traffic signal controller.
Preferably, the traffic control method includes:
the monitoring processor counts the characteristic data of the vehicles in a first monitoring list corresponding to the first traffic section area ID within 24 hours before the preset time at the preset time according to the set time length to obtain the vehicle traffic volume count of each time period;
the monitoring processor carries out statistical analysis on the vehicle traffic volume counts in each time period to obtain peak time period information and a first peak vehicle traffic volume count total amount;
the monitoring processor searches traffic road section area data relative to a first traffic road section area in the traffic road section area relation data according to the first traffic road section area ID to obtain a first opposite traffic road section area ID;
the monitoring processor counts the vehicle characteristic data in a first opposite monitoring list corresponding to the first opposite traffic road section area ID according to the first opposite traffic road section area ID and the peak time period information to obtain the total counted quantity of the first peak opposite vehicle traffic volume;
the monitoring processor generates a first peak lane adjustment control signal according to a first traffic section area ID, the first peak vehicle traffic count total amount, a first peak oncoming vehicle traffic count total amount, and the peak time period information for adjusting lanes.
Further preferably, the monitoring processor generates a first peak lane adjustment control signal according to the first traffic section area ID, the first peak vehicle traffic count total amount, the first peak oncoming vehicle traffic count total amount, and the peak hour information, and the adjusting the lane specifically includes:
the monitoring processor finds the lane number information in the lane information data according to the first traffic section area ID to obtain the total number of the lanes of the traffic section of the first traffic section area ID;
the monitoring processor calculates according to the total traffic volume count of the first peak vehicles, the total traffic volume count of the first peak oncoming vehicles and the total number of lanes of the traffic road section to obtain the number of lanes of a first lane corresponding to the first traffic road section area ID and the number of lanes of an oncoming lane of the first lane;
the monitoring processor generates a first peak lane adjusting control signal according to the number of lanes of the first lane, the number of lanes of an opposite lane of the first lane and the peak time period information, and sends the first peak lane adjusting control signal to a lane controller;
and the lane controller performs lane display control on a lane indication board according to the first peak lane adjustment control signal.
Further preferably, the lane display controlling of the lane indication board by the lane controller according to the first peak lane adjustment control signal specifically includes:
the lane controller analyzes a first peak lane adjustment control signal to obtain the number of lanes of the first lane, the number of lanes of an opposite lane of the first lane and the peak time period information; wherein the first rush hour information comprises a start time and an end time;
and when the lane controller judges that the starting time is up, performing lane display control on the lane indication board according to the number of lanes of the first lane and the number of lanes of the opposite lane of the first lane.
Further preferably, the controlling the lane isolation device by the lane controller according to the peak lane control instruction further includes:
and when the lane controller judges that the ending time is up, performing lane display control on the lane indication boards according to the preset first lane number and the preset first opposite lane number.
Preferably, before the TOF camera acquires the environment image of the traffic section area according to the received image acquisition instruction, the method further includes:
and the monitoring processing generates the image acquisition instruction according to a received monitoring starting command and a preset monitoring time interval, and sends the image acquisition instruction to the TOF camera.
According to the traffic signal control method based on the TOF camera, the TOF camera is used, the characteristic that the TOF camera is not influenced by ambient light when collecting the ambient image is utilized, the image collection is carried out on the passing environment of each traffic road section area, and three-dimensional point cloud data are generated and sent to the monitoring processor. The monitoring processing analyzes the three-dimensional point cloud data, the vehicle traffic volume of each traffic section area is counted according to preset counting time, data in a preset range of each traffic section area are analyzed according to the obtained vehicle traffic technical information, and lane adjusting control signals are generated according to the analysis results to control the traffic direction of the variable lanes of each traffic section area, so that the traffic is automatically controlled according to the traffic flow condition, and the purposes of efficiently and accurately relieving the traffic jam condition and improving the traffic efficiency are achieved.
Drawings
Fig. 1 is a flowchart of a traffic signal control method based on a time-of-flight camera according to an embodiment of the present invention;
fig. 2 is a flowchart of another traffic signal control method based on a time-of-flight camera according to an embodiment of the present invention.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be further noted that, for the convenience of description, only the portions related to the related invention are shown in the drawings.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
The invention provides a traffic signal control method based on a TOF camera. Fig. 1 is a flowchart of a traffic signal control method based on a time-of-flight camera according to an embodiment of the present invention, as shown in the figure, including the following steps:
Specifically, when a traffic signal control network is erected, a traffic data acquisition system is laid in advance, wherein the traffic data acquisition system comprises a TOF camera and a monitoring processor. The TOF camera and the monitoring processor are connected by a wired or wireless communication network.
And the TOF time cameras are erected in different areas of each traffic road section, and are used for collecting environment images of the different traffic road section areas. TOF cameras can be respectively arranged in different areas of the traffic section. The traffic section area is a traffic section area where the TOF camera is erected, and when the TOF camera is erected, the shooting range of the TOF camera is manually confirmed, so that each shooting range of the TOF camera is ensured to include the environment area of the traffic section where the TOF camera is erected.
When the traffic manager confirms that the traffic signal control method provided by the invention needs to be used, a monitoring starting command can be generated by pressing an external button, or the monitoring starting command can be input on a display screen of a monitoring processor. This monitor start command is sent to the monitor processor. Of course, when the instruction is issued, the specified road section may be set by operation, or the global road network may be monitored and started synchronously.
And monitoring processing generates an image acquisition instruction according to a received monitoring starting command and a preset monitoring time interval, and sends the image acquisition instruction to TOF cameras erected in different traffic road section areas.
Wherein the preset time interval is used for controlling the frequency of collecting the monitoring data. The preset time interval is a time interval value estimated after comprehensive analysis and evaluation are performed according to the traffic flow of each traffic section area, and in a specific example of the embodiment of the present invention, the preset time interval is 30 seconds.
And after receiving the image acquisition instruction sent by the monitoring processor, the TOF time camera shoots an environment image of the traffic road section area at one time to obtain three-dimensional point cloud data which is generated after the TOF time camera is processed by the TOF camera processor. Wherein, the TOF camera has a traffic section area ID, and the three-dimensional point cloud data has a time stamp of data acquisition time.
The TOF camera adopted in the embodiment of the invention transmits the optical signal through the built-in laser emission module and acquires the distance field depth data of the three-dimensional scene through the built-in Complementary Metal Oxide Semiconductor (CMOS) pixel array, the imaging rate can reach hundreds of frames per second, and meanwhile, the TOF camera has a compact structure and low power consumption. The three-dimensional data acquisition mode for the target scene is as follows: TOF cameras use an amplitude modulated light source that actively illuminates the target scene and is coupled to an associated sensor that is locked onto each pixel of the same frequency. The emission light of the built-in laser emission and the reflected light emitted after the emission light irradiates on the scene object have phase shift, and multiple measurements are obtained by detecting different phase shift amounts between the emission light and the reflected light. The amplitude modulation of the built-in laser transmitter is in the modulation frequency interval of 10-100MH, while the frequency controls the TOF camera sensor depth range and depth resolution. Meanwhile, a processing unit of the TOF camera independently executes phase difference calculation on each pixel to obtain depth data of a target scene, the processing unit of the TOF camera analyzes and calculates the reflection intensity of the reflected light to obtain intensity data of the target scene, and the intensity data of the target scene is analyzed and processed by combining the acquired two-dimensional data to obtain three-dimensional point cloud data of the target scene.
In a specific example of the embodiment of the present invention, the TOF camera uses a solid-state laser or an LED array as a built-in laser transmitter that transmits light waves with a wavelength around 850 nm. The emitting light source is continuous square wave or sine wave obtained by continuous modulation. The TOF camera processing unit obtains intensity data by calculating phase angles of emitted light and reflected light in a plurality of sampling samples and distances of target objects, analyzing and calculating current intensity converted by reflected light intensity, and then performing fusion processing by combining two-dimensional image data obtained by the optical camera to obtain three-dimensional point cloud data of a target scene.
In the process of collecting the environment image of the traffic road section area, due to the fact that scene shooting is carried out through non-visible light actively emitted by the TOF camera, clear three-dimensional point cloud data of the environment image of the traffic road section area can be obtained even under the dark condition. Therefore, the method provided by the embodiment of the invention is also suitable for use in night or dark environment with poor lighting state or even without lighting.
In order to accurately monitor the traffic section area, reduce the processed data volume and ensure the processing speed, the resolution of the first TOF camera preferably adopted in the embodiment of the invention is 320 × 240.
And 102, the TOF camera sends the three-dimensional point cloud data and the traffic section area ID to a monitoring processor.
Specifically, the TOF camera sends the three-dimensional point cloud data and the traffic section area ID to the monitoring processor through a wired network or a wireless network.
And 103, denoising the three-dimensional point cloud data by the monitoring processor to obtain denoised three-dimensional point cloud data.
Specifically, the monitoring processor performs denoising processing on the received three-dimensional point cloud data by using a specific denoising processing method to obtain denoised three-dimensional point cloud data.
In the embodiment of the invention, the resolution of the TOF camera is M multiplied by N, so that one frame of three-dimensional point cloud data acquired by the TOF camera has M multiplied by N pixel points, and each pixel point further comprises X, Y, Z three-dimensional coordinate values. Wherein, the TOF camera is used for converting original depth data into required 3-dimensional point cloud data: firstly, carrying out preliminary correction and temperature calibration on original depth data; secondly, distortion correction processing is carried out on the image; thirdly, the depth image coordinate system (x0, y0, z0) is converted into a camera coordinate system (x1, y1, z1), and the depth information on the image is converted into a three-dimensional coordinate system with the camera as an origin; finally, the camera coordinate system (x1, y1, z1) is converted to the required world coordinate system (x2, y2, z2) and the camera coordinate system is converted to the coordinate system required by the project, i.e. the coordinate system of the final point cloud. The data values of the X axis and the Y axis represent plane coordinate positions of scene points, and the data value of the Z axis represents an acquired actual depth value of the acquired scene.
The monitoring processor converts the three-dimensional point cloud data into an mxnx3 matrix, with each row representing a pixel arranged in the time-of-flight sensor. By resetting the M × N × 3 matrix to an M × N matrix and expressing the value of each element in the reset matrix with a depth value, the three-dimensional point cloud data is converted into two-dimensional planar image data.
The monitoring processor calculates the depth value of each pixel point of the two-dimensional plane image data by adopting a 3 multiplied by 3 space filtering operator based on the three-dimensional point cloud, and calculates the depth difference between the pixel of the central point and the pixel around the central point. And comparing the depth difference with a preset global threshold, judging that the depth value measured by the pixel point is a noise point when the depth difference is greater than the preset global threshold, and filtering the pixel point in the corresponding three-dimensional point cloud data. Otherwise, the corresponding pixel points in the three-dimensional point cloud data are reserved. And processing to obtain de-noised three-dimensional point cloud data.
In a specific example of the embodiment of the present invention, the three-dimensional point cloud data acquired by the TOF camera with a resolution of 320 × 240 is subjected to a denoising processor by using the denoising processor algorithm, so as to obtain denoised three-dimensional point cloud data.
And 104, the monitoring processor extracts the vehicle characteristic data of the de-noised three-dimensional point cloud data based on the vehicle characteristic data model to obtain the characteristic data of each vehicle, and stores the characteristic data in a monitoring list corresponding to the traffic road section area ID.
Specifically, the monitoring processor analyzes the depth data according to the three-dimensional point cloud data, the monitoring processor determines depth contour lines according to the characteristics of the vehicle through the depth data, and a plurality of closed loop graphic data sets are obtained through analysis in the data of the contour line plane of the height data. And if the closed loop image data can be successfully matched with the vehicle characteristic data models stored in the storage device, the closed loop image and the data are vehicle characteristic data, and the characteristic data of the vehicle is stored in a monitoring list corresponding to the traffic section area ID. Each value stored in the monitoring list is a closed-loop graphic data set, i.e., a vehicle characteristic data, and it is understood that each vehicle characteristic data represents a specific vehicle. The monitoring list further comprises a traffic section area ID and data acquisition time.
And 105, counting the vehicle characteristic data in the monitoring list corresponding to each traffic section area ID by the monitoring processor according to the preset counting time length to obtain the vehicle traffic volume count corresponding to the traffic section area ID in the preset counting time length.
Specifically, each traffic section area ID corresponds to one monitoring list. The monitoring processor counts the characteristic data of the vehicles in the monitoring list corresponding to each traffic section area ID in the monitoring list every preset statistical time, and the monitoring processor counts the number of the characteristic data of all the vehicles from the moment before the preset statistical time to the calculation moment at the current moment according to the data acquisition time. For example, in a specific example of the embodiment of the present invention, the preset statistical duration is 30 minutes, the monitoring processor searches the monitoring list for a time 30 minutes before the current time, calculates the number of the feature data of the vehicle from the found time, and obtains a vehicle traffic volume count corresponding to the traffic road section area ID within 30 minutes.
And 106, acquiring the vehicle traffic volume counts of other traffic road sections in the preset range by the monitoring processor according to the traffic road section area IDs, and normalizing the vehicle traffic volume counts corresponding to the traffic road section area IDs and the vehicle traffic volume counts of other traffic road sections to obtain the time interval relative traffic rate of the traffic road section area in the preset range.
Specifically, the storage unit of the monitoring processor stores position relation data of all traffic section areas, that is, traffic section area relation data. And the monitoring processor searches the traffic section area ID related to the traffic section area within the preset range of the traffic section area ID in the traffic section area relation data according to the traffic section area ID, and then searches the corresponding vehicle traffic volume count according to the related traffic section area ID.
And the monitoring processor performs normalization processing on the vehicle traffic volume count corresponding to the ID of each searched traffic section area to obtain normalization processing data of each traffic section area in a preset range, and the normalization processing data is recorded as the relative traffic rate of the time interval.
Specifically, the monitoring processor determines the maximum value and the minimum value of the relative traffic rate of the time periods corresponding to all the traffic section area IDs within the preset range, and then calculates the difference value between the maximum value and the minimum value, namely the maximum time period relative traffic rate difference. The difference value indicates whether the traffic pressure of each traffic section area in the preset range is balanced or not, and the larger the difference value is, the larger the traffic pressure difference distance of each traffic section area is, the more the traffic pressure difference distance is, the traffic pressure of each traffic section area needs to be adjusted so as to achieve the balance of the traffic pressure of each traffic section area and improve the traffic efficiency. The monitoring processor records a first traffic section area ID corresponding to the maximum relative traffic rate and a second traffic section area ID corresponding to the minimum relative traffic rate.
And 108, judging whether the maximum time period relative traffic rate difference is greater than a preset value by the monitoring processor, and when the maximum time period relative traffic rate difference is greater than the preset value, searching the traffic section area data corresponding to the first traffic section area in the traffic section area relation data according to the first traffic section area ID by the monitoring processor to obtain the first opposite traffic section area ID.
Specifically, the monitoring processor determines whether the maximum time period relative traffic flow difference is greater than a preset threshold, and when the maximum time period relative traffic flow difference is greater than a preset value, it indicates that the traffic flow difference of the first traffic section area is greater than the traffic flow difference of the second traffic section area, and also indicates that the traffic flow of each traffic section area within the preset range of the first traffic section area needs to be adjusted, so that the traffic passing efficiency of the preset area is improved. At this time, the monitoring processor searches the traffic section area ID of the traffic section area corresponding to the first traffic section area in the traffic section area relation data according to the first traffic section area ID to obtain a first object traffic section area ID.
In step 109, the monitoring processor determines whether the first paired traffic segment area ID is the same as the second traffic segment area ID.
Specifically, when the first opposite traffic link zone ID is the same as the second traffic link zone ID, it is described that the time-interval relative traffic rate of the opposite traffic link zone within the preset range of the first traffic zone ID is the smallest, that is, the traffic flow of the first traffic link zone is the largest, and the traffic flow of the opposite first opposite traffic link zone is the smallest. The traffic situation can be performed by adjusting the traffic lane. In one specific example of the present invention, if the direction of the first traffic segment area is from south to north, then the direction of the first counter traffic segment area is from north to south. At this point, step 110 is performed.
And when the monitoring processor judges that the first opposite traffic section area ID is different from the second traffic section area ID, the second traffic section area corresponding to the minimum time interval relative traffic rate is not the opposite direction to the first traffic section area within the preset range of the first traffic section.
For example, in one specific example of the present invention, the direction of the first traffic segment area is from south to north, and the direction of the first counter traffic segment area is from north to south, while the direction of the second traffic segment area is not north to south, and may be from west to east, or east to west. At this time, it is explained that the adjustment of the traffic flow may be performed by changing the time of the traffic signal lamp within the preset range of the first traffic segment region, and steps 111 to 113 are performed.
In step 110, the monitoring processor generates a first lane adjustment control signal for instructing to increase the number of lanes of the first lane corresponding to the first traffic section area ID and to decrease the number of lanes of the opposite lane of the first lane.
Specifically, the monitoring processor searches the lane number information in the lane information data according to the first traffic section area ID to obtain the variable lane number in the direction of the first traffic section area and the total number of the variable lanes of the first traffic section area ID, and the monitoring processor determines the lane increase number of the first lane corresponding to the first traffic section area ID according to the maximum time period relative traffic difference and the total number of the variable lanes. The monitoring processor generates a first lane adjustment control signal according to the lane increase number of the first lane. The monitoring processor then sends a first lane adjustment control signal to the first lane controller.
For example, in a specific example of the implementation of the present invention, the first traffic section area and the first opposite traffic section area have two variable lanes in common, and the current direction of one variable lane is the same as the passing direction of the first traffic section area; at this time, the difference between the relative traffic flow in the traffic direction of the first traffic road section area and the opposite traffic flow is greater than the preset value, which indicates that the number of the traffic lanes in the first traffic road section area direction needs to be increased, so the monitoring processor generates a first lane adjustment control signal to adjust the traffic direction of the variable lane of the first opposite traffic road section area, and the first opposite traffic road section area is changed into the traffic direction of the first traffic road section area. Accordingly, the number of passing lanes in the direction of the first opposing traffic segment area is reduced. The first lane adjustment control signal comprises a first traffic road section area ID, a first opposite traffic road section area ID and a control signal of a variable lane indicator of an adjusted lane.
And the first lane controller sends a forbidding state instruction to a first opposite variable lane indicator board erected on the lane according to the first lane adjusting control signal, and sends a passing state instruction to the first variable lane indicator board erected on the lane. For example, in a specific example of the embodiment of the present invention, the monitoring processor changes the display of one variable lane of the first direction-variable lane indicator from the passage state to the no-passage state for display; meanwhile, the monitoring processor changes the display of one of the variable lanes of the first variable lane indicator from the no-go state to the straight state or the left-turn state, etc., the change of the state being determined by a preset variable lane change policy.
And step 111, the monitoring processor searches the traffic section area data corresponding to the second traffic section area in the traffic section area relation data according to the second traffic section area ID to obtain a second opposite traffic section area ID.
Specifically, the passing direction of the second traffic road section area is different from the passing direction of the first traffic road section area. At this time, the monitoring processor searches for an object traffic section region corresponding to the second traffic section region ID in order to calculate relative traffic flow data in the crossing direction of the intersection within the preset range of the first traffic region ID.
Specifically, the monitoring processor calculates relative traffic flow data in the crossing direction of the intersection of the first traffic link region ID, that is, calculates the sum of the vehicle traffic volume counts corresponding to the first traffic link region ID and the first opposite traffic link region ID, to obtain a first comparative vehicle traffic volume count. The monitoring processor calculates the sum of the vehicle traffic volume counts corresponding to the second traffic section area ID and the second opposite traffic section area ID to obtain a second comparison vehicle traffic volume count.
In a specific example of the present invention, the traffic direction of the first traffic section area is from west to east, the traffic direction of the first opposite traffic section area is from east to west, the traffic direction of the second traffic section area is from south to north, and the traffic direction of the second object traffic section area is from north to south. The first comparative vehicle traffic count obtained by the calculation is a vehicle traffic count in the east-west direction, and the second comparative vehicle traffic count is a vehicle traffic count in the north-south direction.
And 113, generating a signal lamp control command by the monitoring processor according to the preset control time of the signal lamp, the first comparison vehicle traffic volume count and the second comparison vehicle traffic volume count so as to control the traffic signal lamp.
Specifically, the monitoring processor calculates a transit time ratio according to the first comparison vehicle transit amount count and the second comparison vehicle transit amount count, and then judges whether the transit time ratio exceeds a preset transit time ratio range. When the transit time ratio is beyond the preset transit time ratio range, the traffic flow in the crossing direction of the intersection indicating the preset range of the first traffic section area needs to be adjusted. The storage unit of the monitoring processor can search corresponding preset control time, namely the total time of the passing time of each direction of the intersection, and can be written into the storage unit of the monitoring processor in advance according to the traffic flow condition of the intersection. And the monitoring processor calculates according to the preset monitoring time and the passing time ratio to obtain first passing time and first forbidden time. And then, the monitoring processor generates a signal lamp control command according to the first passing time and the first forbidden time and sends the signal lamp control command to the first traffic signal controller, the first opposite traffic signal controller, the second traffic signal controller and the second opposite traffic signal controller.
The first passing time represents the time for passing in the passing direction of the first traffic section area, namely the green light time length of the passing direction of the first traffic section area. The first no-go time represents a time when the first pass time represents a no-go in the passing direction of the first traffic section area, that is, a red light time length in the passing direction of the first traffic section area. The first passing time and the first forbidding time can be used for carrying out linkage control on traffic lights in the first traffic section area. The red and green light conversion time of the traffic signal lights in each direction of the second traffic road section area and the second opposite traffic road section area has linkage correlation with the first passing time and the second passing time. This correlation can be determined according to preset signal light switching principles.
In an alternative of this embodiment of the invention, the first transit time is associated with a first contra-transit time of a first contra-transit leg area, the first forbidden time is associated with a first contra-transit time of the first contra-transit leg area, the first transit time is associated with a second forbidden time of a second traffic leg area, the first forbidden time is associated with a second transit time of the second traffic leg area, the second forbidden time is associated with a second contra-transit time of a second contra-transit leg, and the second transit time is associated with a second contra-transit time of the second contra-transit leg area. For example, the first passing time is 5 minutes, the first forbidden time is 4 minutes, the first contra-passing time is 5 minutes, the first contra-forbidden time is 4 minutes, the second passing time is 4 minutes, the second forbidden time is 5 minutes, the second contra-passing time is 4 minutes, and the second contra-forbidden time is 5 minutes.
The first traffic signal controller performs traffic light conversion control on the first traffic signal light according to the first passing time and the first traffic forbidding time; the first opposite traffic signal controller carries out traffic light conversion control on the first opposite traffic signal light according to the first opposite traffic time and the first opposite forbidding time; the second traffic signal controller performs traffic light conversion control on the second traffic signal light according to the second traffic time and the second traffic forbidding time; and the second opposite traffic signal controller performs traffic light conversion control on the second opposite traffic signal light according to the second opposite traffic time and the second opposite forbidding time.
The traffic signal control method based on the TOF camera provided by the embodiment of the invention is a method for carrying out statistics on vehicle traffic volume counting within a preset statistical time length by analyzing and processing three-dimensional point cloud data acquired by each TOF, and controlling traffic signals according to a statistical result so as to relieve traffic jam or improve traffic efficiency.
In addition, the embodiment of the invention also provides another traffic signal control method based on the TOF camera, which is a method for acquiring and analyzing three-dimensional point cloud data of each traffic section area acquired by the TOF camera within 24 hours at a preset moment to obtain traffic peak time and peak traffic data within 24 hours, analyzing the traffic data according to the peak time and controlling a variable lane to relieve traffic jam and improve traffic efficiency. Fig. 2 is a flowchart of another traffic signal control method based on a time-of-flight camera according to an embodiment of the present invention. As shown in the figure, the method specifically comprises the following steps:
Specifically, the monitoring processor counts the characteristic data of the vehicles in the first monitoring list corresponding to the first traffic road section area ID within 24 hours before the preset time at the preset time, for example, 0:00 a day early morning, and performs counting processing according to the preset time length to obtain continuous vehicle traffic volume counting according to the set time length. In one specific example of the invention, the characteristic data of the vehicles in the first monitoring list are counted according to a preset time length of 30 minutes in the morning of 0:00 every day, and a continuous 48-vehicle passing count within 24 hours is obtained.
Specifically, the monitoring processor performs statistical analysis on the vehicle traffic volume counts at each time interval, for example, the vehicle traffic volume counts at each time interval may be sorted from large to small to obtain the time interval information of a plurality of time intervals in the first preset time interval, and then it is determined whether the time interval information of the plurality of time intervals in the first preset time interval is continuous, and then the peak time interval information is determined according to the time interval information of the plurality of time intervals in the first preset time interval. The start time of the several periods is the start time of the peak period and the end time of the latest period is the end time of the peak period. And accumulating the vehicle traffic counts at each peak time period to obtain a first peak vehicle traffic count total.
In step 230, the monitoring processor searches the traffic road section area data corresponding to the first traffic road section area in the traffic road section area relation data according to the first traffic road section area ID to obtain a first opposite traffic road section area ID.
In step 240, the monitoring processor counts the vehicle feature data in the first opposite monitoring list corresponding to the first opposite traffic road section area ID according to the first opposite traffic road section area ID and the peak hour information, so as to obtain the total counted amount of the first peak opposite vehicle traffic volume.
Specifically, the monitoring processor counts the characteristic data of the vehicles between the starting time of the peak period and the ending time of the peak period in the monitoring list corresponding to the first opposite traffic section area ID to obtain the total amount of the first peak counter vehicle traffic volume count of the first opposite traffic section area in the peak period.
In step 250, the monitoring processor generates a first peak lane adjustment control signal for adjusting the lane according to the first traffic section area ID, the first peak vehicle traffic count total amount, the first peak oncoming vehicle traffic count total amount, and the peak time period information.
Specifically, the monitoring processor finds the lane number information in the lane information data according to the first traffic section area ID to obtain the total number of the traffic sections and lanes of the first traffic section area ID. The total number of the traffic section lanes of the first traffic section area ID comprises all the number of the lanes of the traffic section area passing direction and the opposite passing direction. That is, the total number of traffic segment lanes includes the total number of bi-directionally variable lanes, the number of non-variable lanes in the first traffic segment zone direction, and the number of non-variable lanes in the first opposite traffic segment zone direction.
And the monitoring processor calculates according to the total traffic volume count of the first peak vehicles, the total traffic volume count of the first peak oncoming vehicles and the total number of lanes of the traffic road section to obtain the number of lanes of the first lane and the number of lanes of the oncoming lanes of the first lane corresponding to the first traffic road section area ID. It should be noted that, in the calculation process, it is ensured that the calculated number of lanes of the first lane is greater than or equal to the number of the non-variable lanes in the direction of the first traffic section area and less than or equal to the sum of the total number of the bidirectional variable lanes and the number of the non-variable lanes in the direction of the first traffic section area. For example, at the time of calculation, when the calculated number of lanes in the first traffic section area direction is greater than the sum of the total number of bidirectional variable lanes and the number of invariable lanes in the first traffic section area direction, the number of lanes in the first lane is set to the sum of the total number of bidirectional variable lanes and the number of invariable lanes in the first traffic section area direction. And when the calculated number of the lanes in the first traffic road section area direction is less than the number of the invariable lanes in the first traffic road section area direction, setting the number of the lanes in the first lane as the number of the invariable lanes in the first traffic road section area direction.
The monitoring processor generates a first peak lane adjustment control signal according to the number of lanes of the first lane, the number of lanes of an opposite lane of the first lane and the peak time period information, and sends the first peak lane adjustment control signal to the lane controller.
And the lane controller performs lane display control on the lane indication board according to the first peak lane adjustment control signal.
In an alternative of the embodiment of the present invention, the lane indication control of the lane signboard by the lane controller according to the first rush hour lane adjustment control signal may be implemented through the following steps.
First, the lane controller analyzes the first rush hour lane adjustment control signal to obtain the number of lanes of the first lane, the number of lanes of the first lane opposite to the first lane, and rush hour information. Wherein the first rush hour information includes a start time and an end time.
And then, when judging that the starting time is up, the lane controller performs lane display control on the lane indication boards according to the number of lanes of the first lane and the number of lanes of the opposite lane of the first lane. More specifically, the lane controller analyzes the first peak lane adjustment control signal to obtain the number of lanes of the first lane, the number of lanes of an opposite lane of the first lane, and peak time information. Wherein the first rush hour information includes a start time and an end time.
And finally, when the lane controller judges that the starting time is up, performing lane display control on the lane indication boards according to the number of lanes of the first lane and the number of lanes of opposite lanes of the first lane.
In a preferred scheme of the invention, when the lane controller judges that the ending time is reached, lane display control is carried out on the lane indication boards according to the preset first lane number and the preset first opposite lane number. That is, the number of lanes in the passing direction of the first traffic segment area and the number of lanes in the passing direction opposite thereto are set by default.
According to the traffic signal control method based on the TOF camera, the TOF camera is used, the characteristic that the TOF camera is not influenced by ambient light when collecting the ambient image is utilized, the image collection is carried out on the passing environment of each traffic road section area, and three-dimensional point cloud data are generated and sent to the monitoring processor. The monitoring processing analyzes the three-dimensional point cloud data, the vehicle traffic volume of each traffic section area is counted according to preset counting time, data in a preset range of each traffic section area are analyzed according to the obtained vehicle traffic technical information, and lane adjusting control signals are generated according to the analysis results to control the traffic direction of the variable lanes of each traffic section area, so that the traffic is automatically controlled according to the traffic flow condition, and the purpose of efficiently and accurately relieving the traffic jam condition is achieved.
Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
The above embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (8)
1. A traffic signal control method based on a time-of-flight camera, the traffic signal control method comprising:
the time of flight TOF camera collects an environment image of a traffic road section area according to a received image collecting instruction to generate three-dimensional point cloud data; wherein the TOF camera has a traffic segment region ID; the three-dimensional point cloud data has a timestamp of data acquisition time;
the TOF camera sends the three-dimensional point cloud data and the traffic section area ID to a monitoring processor;
the monitoring processor carries out denoising processing on the three-dimensional point cloud data to obtain denoised three-dimensional point cloud data;
the monitoring processor extracts vehicle characteristic data from the de-noised three-dimensional point cloud data based on a vehicle characteristic data model to obtain characteristic data of each vehicle, and stores the characteristic data in a monitoring list corresponding to the traffic road section area ID; the monitoring list also comprises a traffic section area ID and the data acquisition time;
the monitoring processor counts the vehicle characteristic data in the monitoring list corresponding to each traffic section area ID according to a preset statistical duration to obtain the vehicle traffic volume count corresponding to the traffic section area ID in the preset statistical duration;
the monitoring processor acquires the vehicle traffic volume counts of other traffic road sections in a preset range according to the traffic road section area ID, and normalizes the vehicle traffic volume counts corresponding to the traffic road section area ID and the vehicle traffic volume counts of other traffic road sections to obtain the time interval relative traffic rate of the traffic road section area in the preset range;
the monitoring processor calculates the difference value between the maximum time interval relative traffic rate and the minimum time interval relative traffic rate in the time interval relative traffic rates of the traffic road section areas in the preset range to obtain the maximum time interval relative traffic rate difference, and records a first traffic road section area ID corresponding to the maximum time interval relative traffic rate and a second traffic road section area ID corresponding to the minimum time interval relative traffic rate;
the monitoring processor judges whether the relative traffic difference in the maximum time period is greater than a preset value;
when the maximum time period relative traffic difference is larger than a preset value, the monitoring processor searches traffic road section area data relative to a first traffic road section area in the traffic road section area relation data according to the first traffic road section area ID to obtain a first opposite traffic road section area ID;
the monitoring processor determining whether the first opposing traffic segment area ID is the same as the second traffic segment area ID;
when the first opposite traffic section area ID is the same as the second traffic section area ID, the monitoring processor generates a first lane adjustment control signal for instructing to increase the number of lanes of a first lane corresponding to the first traffic section area ID and to decrease the number of lanes of an opposite lane of the first lane;
when the monitoring processor determines that the first opposing traffic segment area ID is different from the second traffic segment area ID, the method further comprises:
the monitoring processor searches traffic road section area data relative to a second traffic road section area in the traffic road section area relation data according to the second traffic road section area ID to obtain a second opposite traffic road section area ID;
the monitoring processor calculates the sum of the first traffic section area ID and the vehicle traffic volume count corresponding to the first opposite traffic section area ID to obtain a first comparative vehicle traffic volume count;
the monitoring processor calculates the sum of the vehicle traffic volume counts corresponding to the second traffic section area ID and the second opposite traffic section area ID to obtain a second comparison vehicle traffic volume count;
and the monitoring processor generates a signal lamp control command according to the preset control time of the signal lamp, the first comparison vehicle traffic volume count and the second comparison vehicle traffic volume count so as to control the traffic signal lamp.
2. The method as claimed in claim 1, wherein the monitoring processor generates a first lane adjustment control signal for instructing to increase the number of lanes of the first lane corresponding to the first traffic section area ID and to decrease the number of lanes of the opposite lane of the first lane by:
the monitoring processor sends the first lane adjusting control signal to a first lane controller;
the first lane controller displays and sends a forbidden state instruction to a first opposite variable lane indicator according to the first lane adjusting control signal; and displaying and sending a passing state instruction to the first variable lane indicating plate.
3. The time-of-flight camera-based traffic signal control method of claim 1, wherein the traffic signal lights comprise a first traffic signal light, a first opposing traffic signal light, a second traffic signal light, and a second opposing traffic signal light; the monitoring processor generates a signal lamp control command according to the preset control time of the signal lamp, the first comparison vehicle traffic volume count and the second comparison vehicle traffic volume count, and is used for controlling the traffic signal lamp specifically as follows:
the monitoring processor calculates a transit time ratio according to the first comparison vehicle transit amount count and the second comparison vehicle transit amount count;
the monitoring processor judges whether the traffic time ratio exceeds a preset traffic time ratio range;
when the passing time ratio exceeds the range of a preset passing time ratio, the monitoring processor calculates according to the preset monitoring time and the passing time ratio to obtain first passing time and first no-passing time;
and the monitoring processor generates a signal lamp control command according to the first passing time and the first no-passing time and sends the signal lamp control command to the first traffic signal controller, the first opposite traffic signal controller, the second traffic signal controller and the second opposite traffic signal controller.
4. The time-of-flight camera-based traffic signal control method of claim 1, comprising:
the monitoring processor counts the characteristic data of the vehicles in a first monitoring list corresponding to the first traffic section area ID within 24 hours before the preset time at the preset time according to the set time length to obtain the vehicle traffic volume count of each time period;
the monitoring processor carries out statistical analysis on the vehicle traffic volume counts in each time period to obtain peak time period information and a first peak vehicle traffic volume count total amount;
the monitoring processor searches traffic road section area data relative to a first traffic road section area in the traffic road section area relation data according to the first traffic road section area ID to obtain the first opposite traffic road section area ID;
the monitoring processor counts the vehicle characteristic data in a first opposite monitoring list corresponding to the first opposite traffic road section area ID according to the first opposite traffic road section area ID and the peak time period information to obtain a first peak opposite vehicle traffic volume counting total amount;
and the monitoring processor generates a first peak lane adjusting control signal according to the first traffic section area ID, the first peak vehicle traffic counting total amount, the first peak opposite vehicle traffic counting total amount and the peak time period information so as to adjust lanes.
5. The time-of-flight camera-based traffic signal control method of claim 4, wherein the monitoring processor generates a first peak lane adjustment control signal based on the first traffic segment area ID, the first peak vehicle traffic count total, first peak oncoming vehicle traffic count total, and the peak hour information to adjust lanes, in particular:
the monitoring processor finds the lane number information in the lane information data according to the first traffic section area ID to obtain the total number of the lanes of the traffic section of the first traffic section area ID;
the monitoring processor calculates according to the total traffic volume count of the first peak vehicles, the total traffic volume count of the first peak oncoming vehicles and the total number of lanes of the traffic road section to obtain the number of lanes of the first lane and the number of lanes of the oncoming lanes of the first lane corresponding to the first traffic road section area ID;
the monitoring processor generates a first peak lane adjusting control signal according to the number of lanes of the first lane, the number of lanes of an opposite lane of the first lane and the peak time period information, and sends the first peak lane adjusting control signal to a lane controller;
and the lane controller performs lane display control on a lane indication board according to the first peak lane adjustment control signal.
6. The method of claim 5, wherein the lane controller performing lane display control on the lane indicator according to the first peak lane adjustment control signal comprises:
the lane controller analyzes a first peak lane adjustment control signal to obtain the number of lanes of the first lane, the number of lanes of an opposite lane of the first lane and the peak time period information; wherein the first rush hour information comprises a start time and an end time;
and when the lane controller judges that the starting time is up, performing lane display control on the lane indication board according to the number of lanes of the first lane and the number of lanes of the opposite lane of the first lane.
7. The time-of-flight camera-based traffic signal control method of claim 6, wherein the lane controller controlling the lane isolation device according to the peak lane control command further comprises:
and when the lane controller judges that the ending time is up, performing lane display control on the lane indication boards according to the preset first lane number and the preset first opposite lane number.
8. The time-of-flight camera-based traffic signal control method of claim 1, wherein before the TOF camera acquires the environmental image of the traffic segment region according to the received image acquisition instruction, the method further comprises:
and the monitoring processing generates the image acquisition instruction according to a received monitoring starting command and a preset monitoring time interval, and sends the image acquisition instruction to the TOF camera.
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