CN113240704A - LED scale device and method for analyzing abnormal video frame rate and determining vehicle speed - Google Patents

LED scale device and method for analyzing abnormal video frame rate and determining vehicle speed Download PDF

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Publication number
CN113240704A
CN113240704A CN202110506127.0A CN202110506127A CN113240704A CN 113240704 A CN113240704 A CN 113240704A CN 202110506127 A CN202110506127 A CN 202110506127A CN 113240704 A CN113240704 A CN 113240704A
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frame
led lamp
speed
video
scale
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CN113240704B (en
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魏然
李平凡
李毅
宋耀鑫
严永
秦朗朗
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Traffic Management Research Institute of Ministry of Public Security
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Traffic Management Research Institute of Ministry of Public Security
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/20—Analysis of motion
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P3/00—Measuring linear or angular speed; Measuring differences of linear or angular speeds
    • G01P3/64—Devices characterised by the determination of the time taken to traverse a fixed distance
    • G01P3/68—Devices characterised by the determination of the time taken to traverse a fixed distance using optical means, i.e. using infrared, visible, or ultraviolet light
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30236—Traffic on road, railway or crossing

Abstract

The invention provides an LED scale device for analyzing abnormal video frame rate and determining vehicle speed, which does not need to be carried out by using an actual vehicle, is convenient to operate and low in cost and achieves the same calculation result as a field simulation experiment. It includes: a scale body and a remote controller; the scale main body includes: the main ruler body is provided with a control module, a main scale area and a main LED lamp strip; the control module includes: the LED lamp comprises a control chip, a wireless communication module and a power module, wherein the anode and the cathode of the power module are respectively connected with a voltage wire and a grounding wire to supply power to the control chip, the wireless communication module and a main LED lamp strip; the wireless communication module is in communication connection with the control chip, and an input/output pin of the control chip is connected with a signal wire of the main LED lamp strip; the remote controller controls the on and off of the LED lamp beads on the main LED lamp strip based on a wireless communication mode. Meanwhile, the patent also discloses a method for analyzing the abnormal frame rate and determining the vehicle speed based on the video.

Description

LED scale device and method for analyzing abnormal video frame rate and determining vehicle speed
Technical Field
The invention relates to the technical field of traffic data analysis, in particular to an LED scale device and method for analyzing an abnormal video frame rate and determining a vehicle speed.
Background
The method for identifying the vehicle speed in the traffic accident based on the video image is an analysis method widely applied in daily life. The basic principle is that the speed v of the vehicle passing through a specific area is calculated to be S/T according to the time interval T of the target vehicle passing through the reference objects and the distance S between the two reference objects in the video image. However, the problem of video data blurring occurs due to equipment failure, weather, temperature abnormality and the like of the acquisition equipment, and the problems of frame missing, repeated frames, overlapping time and the like of video images occur, that is, the problem of frame rate abnormality of the video data occurs; if the accurate video image frame rate f cannot be obtained and the time interval T cannot be accurately determined, the vehicle speed v of the target vehicle cannot be accurately calculated, and thus whether the target vehicle has illegal behaviors cannot be accurately judged.
Aiming at the calculation of the vehicle speed in the abnormal video, currently, an appraiser can only calculate by using methods such as a simulation test or accident reconstruction, namely: the accident vehicle or the vehicles of the same type are required to be used for running at the accident site, so that the motion state of the vehicle at the time of accident can be reproduced. In the existing simulation test method, a vehicle of a specified type is required to be simulated according to the same driving speed each time. However, in the simulation, because data needs to be repeatedly acquired, the vehicle must be driven to repeatedly run at the accident site, and many vehicles with accidents have very high driving speed and repeatedly run at high speed, so that the time cost in the data acquisition process is high, and the safety of testers is difficult to guarantee.
Disclosure of Invention
In order to solve the problems of high cost, difficulty in implementation and the like of the existing method for analyzing the speed of the target vehicle based on the abnormal video, the invention provides the LED scale device for analyzing the abnormal video frame rate and determining the speed, which is not required to be carried out by using an actual vehicle, is convenient to operate and low in cost and achieves the same calculation result as a field simulation experiment. Meanwhile, the patent also discloses a method for analyzing the abnormal frame rate and determining the vehicle speed based on the video.
The technical scheme of the invention is as follows: an LED scale device for analyzing abnormal video frame rate and determining vehicle speed is characterized by comprising: a scale body and a remote controller;
the scale main body includes: the main ruler body is provided with a control module, a main scale area and a main LED lamp belt; LED lamp beads on the main LED lamp strip are uniformly arranged along the length direction of the main ruler body; the main scale area and the main LED lamp strip are arranged in parallel and adjacently in the length direction of the main ruler body;
the control module includes: the LED lamp comprises a control chip, a wireless communication module and a power module, wherein the anode and the cathode of the power module are respectively connected with a voltage wire and a grounding wire to supply power to the control chip, the wireless communication module and the main LED lamp strip; the wireless communication module is in communication connection with the control chip, and an input/output pin of the control chip is connected with a signal wire of the main LED lamp strip;
the remote controller is in data communication with the wireless communication module based on a wireless communication mode, and controls the on and off of the LED lamp beads on the main LED lamp strip.
It is further characterized in that:
the extension ruler body is arranged in an inner cavity of the main ruler body;
an extension scale area and an extension LED lamp strip are arranged on the surface of the extension ruler body in the same direction as the main scale area along the length direction in parallel; the scale unit of the extension scale area is the same as that of the main scale area, and the scale starting scale is continued behind the scale of the main scale area of the main ruler body; the model of the extension LED lamp strip is the same as that of the lamp strip on the main ruler body;
the extension ruler body also comprises a signal wire, a voltage wire and a grounding wire which are respectively lapped with the signal wire, the voltage wire and the grounding wire on the main ruler body through metal lapping pieces;
the LED lamp beads on the LED lamp strip are LED lamp beads with changeable colors;
the wireless communication module includes: the system comprises a Wifi module, a Bluetooth module and an infrared module;
the control module also comprises a USB data port and an extension port; the USB data port is connected with the control chip; the extension port is provided with a voltage wire, a grounding wire and a data wire and is used for connecting the other extension ruler body.
A method for analyzing abnormal video frame rate and determining vehicle speed is characterized by comprising the following steps:
s1: acquiring a video to be analyzed, and finding an abnormal frame in the video to be analyzed;
s2: according to the abnormal frame occurrence environment, the simulation environment information is determined; the simulated environmental information includes: environmental parameters, monitoring equipment;
the environmental parameters include: the road section, the lane, the road marking and the ground reference object are driven by the target vehicle when the abnormal frame occurs;
the monitoring equipment is shooting equipment of the video to be analyzed;
s3: analyzing the data of the video to be analyzed based on a video analysis technology; acquiring simulation experiment reference parameters from the video to be analyzed; the simulation experiment reference parameters comprise:
the abnormal occurrence frequency N of the abnormal frame;
the frame rate value range of the video to be analyzed is as follows: [ F1, F2], wherein: f1 and F2 are the two extremes of the frame rate of the variations present in the video to be analyzed, F1< F2;
possible travel speed range of the target vehicle: [ P m/s, Q m/s ], wherein: p and Q are speed values, P < Q;
s4: calculating the length L of a scale area of the scale main body required in the simulation experiment based on the simulation experiment reference parameter;
s5: confirming a simulation experiment environment, and placing the scale main body on the simulation experiment road;
s6: sending control information to the scale body based on a remote controller;
the control information includes: starting a command and lighting speed of the LED lamp beads;
the lighting speed range of the LED lamp beads is [ P m/s, Q m/s ];
adjusting the step length value according to a preset speed, and sequentially obtaining the values of the lighting speed of the LED lamp beads from the range of [ P m/s, Q m/s ];
sequentially sending the control information to the scale main body according to different values of the lighting speed of the LED lamp beads until all the values of the lighting speed of the LED lamp beads are tested;
s7: collecting all videos in the simulation experiment from the detection equipment; grouping video data according to different lighting speeds of the LED lamp beads, and recording the video data as grouped experimental video data;
s8: based on the grouped experimental video data and the video to be analyzed, comparing the distance difference between the motion trail of the target vehicle and the motion trail of the LED lamp beads, and finding out the speed upper limit value v of the running speed v of the target vehiclemaxLower speed limit vminDetermining a range of a running speed v of the target vehicle;
s9: finding out any group of video data with the abnormal frame from the grouped experimental video data, and recording the video data as simulated vehicle video data;
finding the abnormal frame, and based on the running speed v of the LED lamp beads corresponding to the simulated vehicle video dataLEDThe distance between frames in the simulated vehicle video data and the simulated track between the frames, the frame interval time and the frame rate f of the abnormal frame are calculated;
and after the range of the running speed v of the target vehicle corresponding to the abnormal frame and the frame rate f corresponding to the abnormal frame are obtained, ending the experiment.
It is further characterized in that:
the step S8 further includes the steps of:
if the upper limit value and the lower limit value of the running speed of the target vehicle cannot be obtained based on the grouped experimental video data, adjusting the value range of a frame rate, the possible running speed range of the target vehicle and the speed adjustment step length according to the comparison difference between the simulated track between frames in the simulated vehicle video data and the running track of the target vehicle in the video to be analyzed, and then circularly executing the steps S3-S8 until the upper limit value and the lower limit value of the running speed of the target vehicle can be found by the simulated vehicle video data;
in step S6, the scale region length L has a range of:
Figure BDA0003058452420000021
the control information further includes: the method comprises the following steps of (1) LED lamp bead color, an ending command, LED lamp bead lighting length and LED lamp bead cycle number C;
the lighting length of the LED lamp beads is less than or equal to the length L of the scale area;
the cycle number C is a positive integer;
in step S8, the speed upper limit value v is determinedmaxThe lower speed limit value vminThe method comprises the following specific steps:
a 1: extracting all normal frames from the grouped experimental video data, and recording as follows: a group of experimental frames;
setting x groups of the grouped experimental video data, wherein x groups of normal frame data exist in the experimental frame group;
a 2: extracting a normal frame in the video to be analyzed, and recording as follows: comparing the frame groups;
a 3: extracting each group of data in the experiment frame group, and respectively calculating the distance between the motion tracks of the LED lamp beads between framesAverage value, recorded as the experimental group spacing SPt；
Then: total x experimental group spacing SPtData: SPt1，SPt2，....,SPtx；
a 4: calculating the motion track of the target vehicle, averaging the track intervals between frames in the comparison frame group, and recording as the comparison group interval SPc；
a 5: comparing the interval SP of each experimental group one by onetWith the comparison group spacing SPcFinding the set of said grouped experimental video data that meets the following condition:
SPc-SPtnot less than 0 and SPc-SPtThe value of (d) is minimal;
and the corresponding lighting speed of the LED lamp beads is the lower limit value of the running speed v of the target vehicle, and is recorded as: lower limit value v of speedmin：
a 6: comparing the distances SP of each of the experimental groupstWith the comparison group spacing SPcFinding the set of said grouped experimental video data that meets the following condition:
SPt-SPcnot less than 0 and SPt-SPcThe value of (d) is minimal;
the corresponding lighting speed of the LED lamp beads is the upper limit value of the running speed v of the target vehicle, and is recorded as follows: upper limit value v of speedmax；
In step S9, the calculating the frame rate f of the abnormal frame includes:
b 1: finding out the video image corresponding to the abnormal frame in the simulated vehicle video data, setting the video image as the ith frame, and setting the corresponding LED lighting speed as vLED；
b 2: calculating the physical distance of the simulated track between frames by using the scales of the LED scale;
then: the physical distance of the simulated track between the (i-1) th frame and the (i) th frame is Di，
The physical distance of the simulated track between the ith frame and the (i + 1) th frame is Di+1，
...........
The physical distance between the (i + n) -1 st frame and the (i + n) th frame is Di+n；
b 3: calculating the frame interval time;
then: frame interval time t between the i-1 th frame and the i-th frameiComprises the following steps: t is ti＝Di/vLED；
Frame interval time t between ith frame and (i + 1) th framei+1Comprises the following steps: t is ti+1＝Di+1/vLED；
.......
Frame interval time t between (i + n) -1 st frame and (i + n) th framei+nComprises the following steps: t is ti+n＝Di+n/vLED；
b 4: calculating the frame rate f of the abnormal frame:
summing the frame interval time frame by frame, when the time interval T from the (i-1) th frame to the (i + n) th frame approaches 1s, namely:
T＝ti+ti+1+ti+2....+ti+n→1s
the frame rate f of the abnormal frame is as follows: and f is n + 2.
According to the LED scale device for analyzing the abnormal video frame rate and determining the vehicle speed, a target vehicle is simulated through the LED lamp beads on the scale body, the scale body is placed on an accident occurring road section in an accident site, the LED lamp beads are controlled to be sequentially lightened through the remote controller, the accident vehicle in each frame of video is simulated, the time interval of the target vehicle passing through a reference object and the distance between two reference objects can be determined based on the scale area and the lighting-off speed of the LED lamp beads, the motion state of the vehicle in the accident can be further reproduced, and the video frame rate corresponding to the abnormal frame and the speed of the target vehicle can be obtained; the whole process does not need to use actual vehicles, does not need real high-speed driving on roads by appraisers, reduces the experiment cost, ensures the personal safety of the appraisers, and has simple and convenient experiment process and accurate result.
Drawings
Fig. 1 is a schematic structural diagram of a scale main body of the LED scale device of the present patent;
FIG. 2 is an enlarged schematic view of a portion A of FIG. 1;
FIG. 3 is a schematic structural diagram of a control module in the LED scale device;
FIG. 4 is a schematic view of the structural relationship between the extended blade and the main body of the scale;
FIG. 5 is a schematic sectional view taken along line B-B in FIG. 4;
FIG. 6 is a schematic diagram of the image positions of target vehicles in each frame of video image in the video to be analyzed;
FIG. 7 is a schematic diagram showing the positions of LED lamp beads in each frame of video image in simulated vehicle video data;
FIG. 8 is a schematic diagram of the positions of the images between the video frames corresponding to the abnormal frames in the simulated vehicle video data and the adjacent frames;
FIG. 9 is an embodiment of a remote control;
fig. 10 is a schematic diagram of the distance between the motion tracks of the LED lamp beads between frames of the grouped experimental video data.
Detailed Description
As shown in fig. 1 to 5, an LED scale device for analyzing an abnormal video frame rate and determining a vehicle speed according to the present invention includes: scale main part, remote controller, the scale main part includes: the ruler comprises a main ruler body 1, a control module 4, a main scale area 5 and a main LED lamp strip 3, wherein the control module 4, the main scale area 5 and the main LED lamp strip 3 are arranged on the main ruler body 1; LED lamp beads on the main LED lamp strip 3 are uniformly arranged along the length direction of the main ruler body 1; the main scale area 5 and the main LED lamp strip 3 are arranged in parallel and adjacently in the length direction of the main ruler body 1; during the concrete implementation, set up 0 scale end in scale district and be the initial position of lighting of LED lamp pearl, when implementing the simulation experiment, with the initial position of lighting of LED lamp pearl towards the direction of getting into of target vehicle, the direction of going according to the target vehicle of LED lamp pearl lights in proper order. And determining the frame interval time of the video image according to the controllable LED lamp bead lighting speed and lighting length, thereby determining the frame rate of the video image.
The control module 4 includes: the device comprises a control chip 4-1, a wireless communication module 4-2, a power supply module 4-4 and a USB data port 4-3; the power supply module 4-4 can be realized by an internal power supply module or an external mobile power supply, and is selected according to specific requirements; in the embodiment of fig. 3, the control module 4 is provided with a built-in power module 4-4, and the positive electrode and the negative electrode of the power module 4-4 are respectively connected with the voltage line 1-1 and the grounding line 1-3 to supply power to the control chip 4-1, the wireless communication module 4-2 and the main LED strip 3; the wireless communication module 4-2 is in communication connection with the control chip 4-1, and an input/output interface of the control chip 4-1 is connected with a signal wire of the main LED lamp strip 3.
The USB data port 4-3 is connected with the control chip 4-1; the control module 4 is connected with a computer through the USB data port 4-3 to input, modify and update the firmware program of the LED lamp strip, so that the technical scheme of the patent can update the firmware at any time according to actual needs.
In the embodiment, the main ruler body 1 and the extension ruler body 6 are made of hard wear-resistant materials such as wood, hard plastic, rubber and silica gel materials, so that the service life of the device is long enough; the control chip 4-1 is realized based on a microcontroller with computing power, such as an Arduino Uno module, and the wireless communication module 4-2 is realized based on a Wifi module, such as an esp 8266; the LED lamp strip can be realized on the basis of the existing commercially available FPC flexible circuit board lamp strip or PCB hard board lamp strip; the Arduino Uno module is provided with 13 input/output PINs, and only one PIN wire connected with the LED lamp strip is appointed; the USB data port 4-3 can be realized based on the existing commercially available USB serial port module.
As shown in fig. 1, 4 and 5, the extension blade 6 is arranged in the inner cavity 1-4 of the main blade 1; an extended scale area 6-1 and an extended LED lamp strip 6-2 are arranged on the surface of the extended ruler body 6 in the same direction as the main scale area 5 in parallel along the length direction; the scale unit of the extension scale area 6-1 is the same as that of the main scale area 5, and the scale starting scale is continued behind the scale of the main scale area 5 of the main scale body 1; the extended LED lamp strip 6-2 has the same type as the lamp strip on the main ruler body 1; the extension ruler body 6 further comprises an extension signal wire 6-5, an extension voltage wire 6-4 and an extension grounding wire 6-6, and connecting parts made of metal lapping sheet materials are respectively arranged on the main ruler body 1 and the extension ruler body 6: a main connecting piece 7 and an extension piece 6-3; in the embodiment, when the extension ruler body 6 is completely pulled out of the inner cavity 1-4 of the main ruler body 1, the extension piece 6-3 is lapped with the main connecting piece 7; the extension signal wire 6-5, the extension voltage wire 6-4 and the extension grounding wire 6-6 are communicated with the signal wire 1-2, the voltage wire 1-1 and the grounding wire 1-3 on the main ruler body 1 through the lap joint of the main connecting piece 7 and the extension piece 6-3; and power supply and signal transmission between the main ruler body 1 and the extension ruler body 6 are realized.
As shown in fig. 3, the control module 4 is provided with a connection port 4-6 and an extension port 4-5, the connection port 4-6 and the extension port 4-5 are respectively provided with a voltage line, a ground line and a data line, the connection port 4-6 is used for connecting the main blade 1, and the extension port 4-5 is used for connecting another external extension blade 6; the two ends of the extension ruler body 6 are respectively provided with a connector 9, and the connectors 9 are arranged on an extension signal line 6-5, an extension voltage line 6-4, an extension grounding line 6-6 and a signal line, a voltage line, a grounding line and an extension piece end head communicated with the extension ruler body 6-3. When the connector 9 is connected to the extension port 4-5 on the control module 4, the length of the LED scale device is extended from the other end. In this patent, guarantee through built-in extension blade 6, external extension blade 6, extension port 4-5 that the scale device can prolong according to actual need, make the technical scheme of this patent can be nimble be applicable to in the actual scene of difference. However, in practical applications, the total length of the LED scale device needs to be controlled within 10m, the overlong scale device is inconvenient to use when the experimental environment is arranged, videos with too many abnormal frames and too high target vehicle speed use the overlong LED scale device, and video data with too many abnormal frames are not easy to be accurately analyzed.
The LED lamp beads on the main LED lamp strip 3 and the extended LED lamp strip 6-2 are all selected from LED lamp beads with changeable colors; in the pictures collected by the monitoring equipment, the LED lamp beads can be separated from the background color, so that the identifiability of video data is improved, and the technical scheme of the patent has higher practicability; in this embodiment, the default color of the LED lamp bead is green.
The remote controller 10 performs data communication with the wireless communication module 4-2 based on a wireless communication mode, and controls the lighting of the LED lamp beads on the main LED lamp strip 3, the color is red, and the lighting speed is high. The wireless communication module 4-2 may be based on: the system is realized by a Wifi module, a Bluetooth module and an infrared module; the remote controller 10 can be realized by a mobile terminal APP, a control program running on a server, and an embedded remote controller based on infrared, Bluetooth and Wifi; in the embodiment, the wireless communication module 4-2 is realized based on a Wifi chip; the remote controller 10 is implemented based on a tool-side program, and as shown in fig. 9, is a schematic user interface diagram of the remote controller 10; the LED lamp strip lighting control system comprises a display area 10-1 and a key control area 10-2, key parameters such as the length, color and speed of an LED lamp strip to be turned on are selected through a setting key 10-3, the parameters are changed through an increasing key 10-4 and a decreasing key 10-5, the parameters of the turning-on time, sequence, speed and color of the LED lamp strip are controlled to be sent to a wireless communication module 4-2 based on a mobile phone end communication module, then the parameters are transmitted to a control chip 4-1, and the control chip 4-1 controls the turning-on of LED lamp beads on the LED lamp strip; ensure the control LED lamp area that the user can be nimble, make this patent technical scheme have more the practicality.
The method for analyzing the abnormal video frame rate and determining the vehicle speed based on the scale device comprises the following steps.
S1: acquiring a video to be analyzed, and finding an abnormal frame in the video to be analyzed based on the existing video analysis technology; usually, the abnormal frame needing to be analyzed later is a video frame which plays a key role in analyzing the driving behavior of the target vehicle.
S2: according to the abnormal frame occurrence environment, the simulation environment information is determined; the simulated environmental information includes: environmental parameters, monitoring equipment;
the environmental parameters include: the road section, the lane, the road marking and the ground reference object are traveled by the target vehicle when the abnormal frame occurs;
the monitoring equipment is shooting equipment of a video to be analyzed;
the simulation experiment is also carried out by placing the main ruler body 1 and the extension ruler body 6 on a road section and a lane for video shooting, the experiment video shooting is carried out by setting the same monitoring equipment for shooting the video to be analyzed on the road, and the same environmental parameters and the same monitoring equipment are required to be used for ensuring that the video data which are the same as the video to be analyzed are collected. Some intersection ball machine monitoring sometimes under the operation of background monitoring platform, its shooting angle, focus can change, and video monitoring center's operating personnel may remove the ball machine, and this kind of condition needs to monitor equipment's parameter in advance: parameters such as shooting angle, resolution, focal length and the like are adjusted back to the state of the accident, so that the equipment state of the accident can be completely simulated.
S3: analyzing data of a video to be analyzed based on a video analysis technology; acquiring simulation experiment reference parameters from a video to be analyzed; the simulated experiment reference parameters include:
the abnormal occurrence frequency N of the abnormal frames is N, namely, in the video to be analyzed, the abnormal frames occur once in the video of how many frames; if not, the maximum or average value can be taken;
the frame rate value range of the video to be analyzed is as follows: [ F1, F2], wherein: f1 and F2 are the two extremes of the frame rate of the changes present in the video to be analyzed, F1< frame rate of anomalous frames < F2; based on the existing video analysis technology, F1 and F2 can be obtained;
possible travel speed range of the target vehicle: [ P m/s, Q m/s ], wherein: p and Q are speed values, P < Q;
since the purpose of the experiment is to confirm the driving speed of the vehicle when the abnormal frame occurs, but the driving behavior is a continuous behavior, the driving speed of the vehicle can be obtained to an approximate range according to the data in the video to be analyzed; the frame rate when the abnormal frame occurs is included, and although the abnormal frame rate is abnormal due to some special conditions, a range can be given according to the physical parameters of the device and the video data. The frame rate range and the driving speed range are not required to be accurate, and only one range needs to be given. And the range parameters can be further adjusted according to the difference between the motion trail of the LED lamp beads in the grouped experimental video data and the motion trail of the target vehicle in the video to be analyzed.
S4: calculating the length L of a scale area of a scale main body required in a simulation experiment based on the simulation experiment reference parameter;
the scale region length L has the value range:
Figure BDA0003058452420000061
the unit is m.
When the value of N is 5, namely, an abnormal frame appears in every 5 frames of the video data to be analyzed; the frame rate of the video to be analyzed is in a value range of [25,30 ]; possible travel speed range of the target vehicle: [9m/s,10m/s ]; then:
the value range of L is as follows:
Figure BDA0003058452420000062
namely: l is more than or equal to 4, and the longest L is set to be 4 m.
And calculating to obtain experiment parameters used in the simulation experiment based on the abnormal occurrence frequency N of the abnormal frame, the possible running speed range of the target vehicle and the value range of the frame rate of the video to be analyzed. Light LED lamp pearl on the scale main part from beginning to end once and write down an experiment once, then: the value-taking rule of the length L of the scale area of the scale main body is to ensure that abnormal frames appear at least once in each experiment, if conditions allow, namely under the condition that L does not exceed 10m, the abnormal frames can appear for 2 times in one experiment, and ensure that one experiment can provide more characteristic data of a simulated track; if the length of the main ruler body 1 cannot meet the L length, the extension ruler body 6 in the inner cavity of the main ruler body 1 can be drawn out, and if the length is not enough, an extension ruler body is externally connected through an extension port 4-5 on the control module 4.
S5: confirming a simulation experiment environment, and placing the scale main body on a simulation experiment road;
putting the scale body on the scale body, ensuring that the scale body is placed on an actual road section and a lane which are traveled by a target vehicle when the abnormal frame occurs, and ensuring that the placed position is the same as the position when the abnormal frame occurs; the color of the LED lamp beads is selected according to the occurrence time of the simulation experiment and the current background color, so that the LED lamp beads can be collected by monitoring equipment to obtain clear video images, and the accuracy of subsequent analysis results is further ensured.
S6: transmitting control information to the scale main body based on the remote controller 10;
the control information includes: the method comprises the following steps of starting a command, lighting speed of the LED lamp beads, the color of the LED lamp beads, a finishing command, the lighting length of the LED lamp beads and the cycle number C of the LED lamp beads;
the lighting speed range of the LED lamp beads is [ P m/s, Q m/s ];
the lighting length of the LED lamp beads is less than or equal to the length L of the scale area, and when the length of the main ruler body exceeds the length required by the experiment, the lighting length of the LED lamp beads is controlled through the parameter of the lighting length of the LED lamp beads; the scale device can flexibly meet different experimental requirements; the experiment time is not wasted, and the scale devices with different lengths are not required to be replaced every time.
Carrying out value taking according to a preset speed adjusting step length, and sequentially obtaining the values of the lighting speed of the LED lamp beads from the range of [ P m/s, Q m/s ]; the speed adjustment step length is set according to the range of [ P m/s, Q m/s ], such as: can be set as 1 km/h, also can be set as 10 km/h;
taking values of different lighting speeds of the LED lamp beads, in the embodiment, starting from P m/s, increasing the speed of one step length each time, and sequentially sending control information to the scale main body; and after each speed value is circulated for C times, changing the speed value into the next speed value until all the lighting speed values of the LED lamp beads are tested.
The cycle number C of the LED lamp beads is set only when needed; because the simulation laboratory is carried out on an actual traffic road, if the interference factors in the test environment are more, various abnormal conditions occur, such as the passing pedestrians, passing vehicles and the like shield LED lamp beads, and the subsequent calculation is influenced; by cycling through the simulations many times, it is ensured that sufficient experimental data can be provided. The specific value of the cycle number C of the LED lamp beads is set according to the field condition and can be set as a positive integer.
If N is 5, namely an abnormal frame occurs every 5 frames, the frame rate of the video to be analyzed is in a value range of [25,30]]Namely, the monitoring equipment shoots 30 frames in at most one second; if 10 frames need to be collected each time the LED lamp bead is turned on, 2 abnormal frames may occur, then: can be circulated at least within 1 minute (60s)
Figure BDA0003058452420000071
That is, the LED scale device simulates the driving behavior of a target vehicle, can be circularly implemented for 180 times in 1 minute at least, and has the efficiency far higher than that of the conventional vehicle based on repeated testsThe simulation experiment of real vehicle has greatly reduced the cost of simulation experiment, has improved efficiency, because need not real person and drives simultaneously, has also ensured appraisal personnel's personal safety.
In this embodiment, the remote controller 10 is implemented based on APP on the mobile phone, the appraiser sends the control signal to the Wifi chip of the wireless communication module in the control module 4 through the communication module of the mobile phone, the Wifi chip sends to the control chip 4-1, the control chip 4-1 sends to the LED lamp strip after parsing, and the LED lamp bead on the control lamp strip is lighted according to the control information.
S7: collecting all videos in the simulation experiment from detection equipment; and according to the different lighting speeds of the LED lamp beads, grouping the video data and recording as grouped experimental video data.
S8: based on the grouped experimental video data and the video to be analyzed, the distance difference between the motion trail of the target vehicle and the motion trail of the LED lamp beads is compared, and the speed upper limit value v of the running speed v of the target vehicle is foundmaxLower speed limit vminAnd determining the range of the running speed v of the target vehicle, and the specific steps comprise:
a 1: in the video data of the grouping experiment, all normal frames are extracted and recorded as: a group of experimental frames;
setting total x +1 component experimental video data, wherein x +1 normal frame data exist in the experimental frame group;
a 2: extracting a normal frame in a video to be analyzed, and recording as follows: comparing the frame groups;
a 3: extracting each group of data in the experiment frame group, respectively calculating the average value of the distances between the motion tracks of the LED lamp beads between the frames, and recording the average value as the interval SP of the experiment groupt；
Then: between x groups of normal frame data, there are x experimental group intervals SPtData: SPt1，SPt2，....,SPtx；
a 4: calculating the motion track of the target vehicle, averaging the track intervals between frames in the comparison frame group, and recording as the comparison group interval SPc；
a 5: compare the interval SP of each experimental group one by onetAnd comparison withGroup spacing SPcFinding the set of experimental video data meeting the following conditions:
SPc-SPtnot less than 0 and SPc-SPtThe value of (d) is minimal;
the corresponding lighting speed of the LED lamp beads is the lower limit value of the running speed v of the target vehicle, and is recorded as: lower limit value v of speedmin：
a 6: comparison of Each experimental group spacing SPtAnd comparison group spacing SPcFinding the set of experimental video data meeting the following conditions:
SPt-SPcnot less than 0 and SPt-SPcThe value of (d) is minimal;
the corresponding LED lamp bead lighting speed is the upper limit value of the target vehicle running speed v, and is recorded as follows: upper limit value v of speedmax。
FIG. 10 shows a group of experimental video data, in which 4 frames of normal frame data exist; the distance of the pixels is utilized to calculate the distance between the motion tracks of the LED lamp beads between frames, and the distance is respectively as follows: s1, S2, S3;
the average value of the intervals of the motion tracks of the LED lamp beads between frames;
distance between experimental groups
Figure BDA0003058452420000081
In the same way, x experimental group spacings SP were foundtData: SPt1，SPt2，....,SPtx；
Then compare SP one by onet1，SPt2，....,SPtxAnd SPcFinding the upper limit value v of the velocitymaxLower speed limit vminThe range of the running speed v of the target vehicle is determined.
In step S8, if the upper limit value and the lower limit value of the target vehicle driving speed cannot be obtained based on the grouped experimental video data, adjusting the frame rate value range, the possible driving speed range of the target vehicle and the speed adjustment step length according to the comparison difference between the simulated track between the frames in the simulated vehicle video data and the target vehicle driving track in the video to be analyzed, and then executing steps S3-S8 in a circulating manner until the upper limit value and the lower limit value of the target vehicle driving speed can be found in the simulated vehicle video data; because the execution efficiency of the steps S3-S8 in the technical scheme of the patent is very high, the steps are implemented again after each parameter is repeatedly adjusted, and compared with the existing method, the overall efficiency is also greatly improved.
S9: finding out any group of video data with abnormal frames from the grouped experimental video data, and recording the video data as simulated vehicle video data;
finding out abnormal frames, and based on the running speed v of the LED lamp beads corresponding to the video data of the simulated vehicleLEDSimulating the space between frames in the vehicle video data and the simulated track between the frames, and calculating the frame rate f of the abnormal frames according to the frame interval time;
after the range of the running speed v of the target vehicle corresponding to the abnormal frame and the frame rate f corresponding to the abnormal frame are both obtained, the experiment is ended.
As shown in fig. 6, the motion trajectory of the target vehicle in the video to be analyzed is: wherein C1, C2, C3 and C4 constitute a continuous motion track for the target vehicle in consecutive video frames captured by the monitoring device 10, but a frame missing phenomenon, i.e., the lack of C5 in the track, is obviously occurred in the video frames between C4 and C6.
In the simulation experiment, the main scale body 1 is placed on a simulation experiment road 8, and video frames in grouped experiment video data are shot through the monitoring equipment 10. In specific implementation, because the same monitoring device is used, multiple groups of grouped experimental video data have the same abnormal frame as that in the video to be analyzed, and one group is selected to calculate the frame rate f of the abnormal frame.
As shown in fig. 7, the motion trajectory of the continuously lit LED lamp bead 3 can be seen: c '1, C '2, C '3, C '4, C ' 6. Because the same frame missing phenomenon occurs, the motion trail C'5 of the LED lamp bead 3 is not displayed in the corresponding video frame.
As shown in fig. 8, calculating the frame rate f of the abnormal frame specifically includes the following steps:
b1：finding out the video image corresponding to the abnormal frame in the simulated vehicle video data, setting the video image as the ith frame, and setting the corresponding LED lighting speed as vLED；
b 2: calculating the physical distance of the simulated track between frames by using the scales of the LED scale;
then: the physical distance of the simulated track between the (i-1) th frame and the (i) th frame is Di，
The physical distance of the simulated track between the ith frame and the (i + 1) th frame is Di+1，
...........
The physical distance between the (i + n) -1 st frame and the (i + n) th frame is Di+n；
b 3: calculating the frame interval time;
then: frame interval time t between the i-1 th frame and the i-th frameiComprises the following steps: t is ti＝Di/vLED；
Frame interval time t between ith frame and (i + 1) th framei+1Comprises the following steps: t is ti+1＝Di+1/vLED；
.......
Frame interval time t between (i + n) -1 st frame and (i + n) th framei+nComprises the following steps: t is ti+n＝Di+n/vLED；
b 4: calculating the frame rate f of the abnormal frame:
summing the frame interval time frame by frame, when the time interval T from the (i-1) th frame to the (i + n) th frame approaches 1s, namely:
T＝ti+ti+1+ti+2....+ti+n→1s
the frame rate f of the abnormal frame is: and f is n + 2.
If the frame rate of the video image is normal, the frame interval time of each frame is fixed, and the reciprocal of the frame interval time is the frame rate; and once the frame rate is abnormal due to some reasons, when abnormal frames occur, the number of frames shot per second is not a fixed value, in the technical scheme of the patent, the frame rate of the abnormal frames is calculated by summing up video frames simulating vehicle video data minutes, and the number of the shot frames within 1s is calculated. In the method for calculating the frame rate f of the abnormal frame in the technical scheme of the patent, the calculation is performed based on the simulated vehicle video data acquired by the monitoring equipment 10 with the abnormal frame under the same environmental parameters, so that the obtained result is in accordance with the actual condition, and the obtained result is accurate.
In fact, there is also a case where D is found while step b2 is being performedi＝Di+1＝...＝Di+n(ii) a That is, although the video data to be analyzed has frame skipping, frame missing, and other abnormal situations, the frame rate of the monitoring device 10 does not change, and at this time, the frame rate f is calculated without performing the steps b3 and b4, and the frame rate of the abnormal frame is obtained according to the calculation method of the video with a normal frame rate.

Claims (10)

1. An LED scale device for analyzing abnormal video frame rate and determining vehicle speed is characterized by comprising: a scale body and a remote controller;
the scale main body includes: the main ruler body is provided with a control module, a main scale area and a main LED lamp belt; LED lamp beads on the main LED lamp strip are uniformly arranged along the length direction of the main ruler body; the main scale area and the main LED lamp strip are arranged in parallel and adjacently in the length direction of the main ruler body;
the control module includes: the LED lamp comprises a control chip, a wireless communication module and a power module, wherein the anode and the cathode of the power module are respectively connected with a voltage wire and a grounding wire to supply power to the control chip, the wireless communication module and the main LED lamp strip; the wireless communication module is in communication connection with the control chip, and an input/output pin of the control chip is connected with a signal wire of the main LED lamp strip;
the remote controller is in data communication with the wireless communication module based on a wireless communication mode, and controls the on and off of the LED lamp beads on the main LED lamp strip.
2. The LED scale apparatus for analyzing abnormal video frame rate and determining vehicle speed as claimed in claim 1, wherein: the extension ruler body is arranged in an inner cavity of the main ruler body;
an extension scale area and an extension LED lamp strip are arranged on the surface of the extension ruler body in the same direction as the main scale area along the length direction in parallel; the scale unit of the extension scale area is the same as that of the main scale area, and the scale starting scale is continued behind the scale of the main scale area of the main ruler body; the model of the extension LED lamp strip is the same as that of the lamp strip on the main ruler body;
the extension chi body still includes signal line, voltage line, earth connection, respectively through the metal take the piece with signal line, voltage line, earth connection overlap joint on the main scale body.
3. The LED scale apparatus for analyzing abnormal video frame rate and determining vehicle speed as claimed in claim 1, wherein: the LED lamp beads on the LED lamp strip are LED lamp beads with changeable colors.
4. The LED scale apparatus for analyzing abnormal video frame rate and determining vehicle speed as claimed in claim 1, wherein: the control module also comprises a USB data port and an extension port; the USB data port is connected with the control chip; the extension port is provided with a voltage wire, a grounding wire and a data wire and is used for connecting the other extension ruler body.
5. A method for analyzing abnormal video frame rate and determining vehicle speed is characterized by comprising the following steps:
s1: acquiring a video to be analyzed, and finding an abnormal frame in the video to be analyzed;
s2: according to the abnormal frame occurrence environment, the simulation environment information is determined; the simulated environmental information includes: environmental parameters, monitoring equipment;
the environmental parameters include: the road section, the lane, the road marking and the ground reference object are driven by the target vehicle when the abnormal frame occurs;
the monitoring equipment is shooting equipment of the video to be analyzed;
s3: analyzing the data of the video to be analyzed based on a video analysis technology; acquiring simulation experiment reference parameters from the video to be analyzed; the simulation experiment reference parameters comprise:
the abnormal occurrence frequency N of the abnormal frame;
the frame rate value range of the video to be analyzed is as follows: [ F1, F2], wherein: f1 and F2 are the two extremes of the frame rate of the variations present in the video to be analyzed, F1< F2;
possible travel speed range of the target vehicle: [ Pm/s, Qm/s ], wherein: p and Q are speed values, P < Q;
s4: calculating the length L of a scale area of the scale main body required in the simulation experiment based on the simulation experiment reference parameter;
s5: confirming a simulation experiment environment, and placing the scale main body on the simulation experiment road;
s6: sending control information to the scale body based on a remote controller;
the control information includes: starting a command and lighting speed of the LED lamp beads;
the lighting speed range of the LED lamp bead is [ Pm/s, Qm/s ];
adjusting the step length value according to a preset speed, and sequentially obtaining the values of the lighting speed of the LED lamp beads from the range of [ Pm/s and Qm/s ];
sequentially sending the control information to the scale main body according to different values of the lighting speed of the LED lamp beads until all the values of the lighting speed of the LED lamp beads are tested;
s7: collecting all videos in the simulation experiment from the detection equipment; grouping video data according to different lighting speeds of the LED lamp beads, and recording the video data as grouped experimental video data;
s8: based on the grouped experimental video data and the video to be analyzed, comparing the distance difference between the motion trail of the target vehicle and the motion trail of the LED lamp beads, and finding out the speed upper limit value v of the running speed v of the target vehiclemaxLower speed limit vminDetermining a range of the target vehicle's travel speed v；
S9: finding out any group of video data with the abnormal frame from the grouped experimental video data, and recording the video data as simulated vehicle video data;
finding the abnormal frame, and based on the running speed v of the LED lamp beads corresponding to the simulated vehicle video dataLEDThe distance between frames in the simulated vehicle video data and the simulated track between the frames, the frame interval time and the frame rate f of the abnormal frame are calculated;
and after the range of the running speed v of the target vehicle corresponding to the abnormal frame and the frame rate f corresponding to the abnormal frame are obtained, ending the experiment.
6. The method of claim 5, wherein the method further comprises: the step S8 further includes the steps of:
if the upper limit value and the lower limit value of the running speed of the target vehicle cannot be obtained based on the grouped experimental video data, adjusting the value range of a frame rate, the possible running speed range of the target vehicle and the speed adjustment step length according to the comparison difference between the simulated track between frames in the simulated vehicle video data and the running track of the target vehicle in the video to be analyzed, and then circularly executing the steps S3-S8 until the upper limit value and the lower limit value of the running speed of the target vehicle can be found by the simulated vehicle video data.
7. The method of claim 5, wherein the method further comprises: in step S6, the scale region length L has a range of:
Figure FDA0003058452410000021
8. the method of claim 5, wherein the method further comprises: the control information further includes: the method comprises the following steps of (1) LED lamp bead color, an ending command, LED lamp bead lighting length and LED lamp bead cycle number C;
the lighting length of the LED lamp beads is less than or equal to the length L of the scale area;
the cycle number C is a positive integer.
9. The method of claim 5, wherein the method further comprises: in step S8, the speed upper limit value v is determinedmaxThe lower speed limit value vminThe method comprises the following specific steps:
a 1: extracting all normal frames from the grouped experimental video data, and recording as follows: a group of experimental frames;
setting x groups of the grouped experimental video data, wherein x groups of normal frame data exist in the experimental frame group;
a 2: extracting a normal frame in the video to be analyzed, and recording as follows: comparing the frame groups;
a 3: extracting each group of data in the experiment frame group, respectively calculating the average value of the distances between the motion tracks of the LED lamp beads between the frames, and recording the average value as the experiment group distance SPt；
Then: total x experimental group spacing SPtData: SPt1，SPt2，....,SPtx；
a 4: calculating the motion track of the target vehicle, averaging the track intervals between frames in the comparison frame group, and recording as the comparison group interval SPc；
a 5: comparing the interval SP of each experimental group one by onetWith the comparison group spacing SPcFinding the set of said grouped experimental video data that meets the following condition:
SPc-SPtnot less than 0 and SPc-SPtThe value of (d) is minimal;
and the corresponding lighting speed of the LED lamp beads is the lower limit value of the running speed v of the target vehicle, and is recorded as: lower limit value v of speedmin：
a 6: comparing the distances SP of each of the experimental groupstWith the comparison group spacing SPcFinding the followingThe set of the grouped experimental video data:
SPt-SPcnot less than 0 and SPt-SPcThe value of (d) is minimal;
the corresponding lighting speed of the LED lamp beads is the upper limit value of the running speed v of the target vehicle, and is recorded as follows: upper limit value v of speedmax。
10. The method of claim 5, wherein the method further comprises: in step S9, the calculating the frame rate f of the abnormal frame includes:
b 1: finding out the video image corresponding to the abnormal frame in the simulated vehicle video data, setting the video image as the ith frame, and setting the corresponding LED lighting speed as vLED；
b 2: calculating the physical distance of the simulated track between frames by using the scales of the LED scale;
then: the physical distance of the simulated track between the (i-1) th frame and the (i) th frame is Di，
The physical distance of the simulated track between the ith frame and the (i + 1) th frame is Di+1，
...........
The physical distance between the (i + n) -1 st frame and the (i + n) th frame is Di+n；
b 3: calculating the frame interval time;
then: frame interval time t between the i-1 th frame and the i-th frameiComprises the following steps: t is ti＝Di/vLED；
Frame interval time t between ith frame and (i + 1) th framei+1Comprises the following steps: t is ti+1＝Di+1/vLED；
.......
Frame interval time t between (i + n) -1 st frame and (i + n) th framei+nComprises the following steps: t is ti+n＝Di+n/vLED；
b 4: calculating the frame rate f of the abnormal frame:
summing the frame interval time frame by frame, when the time interval T from the (i-1) th frame to the (i + n) th frame approaches 1s, namely:
T＝ti+ti+1+ti+2....+ti+n→1s
the frame rate f of the abnormal frame is as follows: and f is n + 2.
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Publication number Priority date Publication date Assignee Title
CN104299430A (en) * 2014-10-13 2015-01-21 上海市城市建设设计研究总院 Off-road green wave vehicle speed guide method based on vehicle and road cooperation
CN108765462A (en) * 2018-05-29 2018-11-06 公安部交通管理科学研究所 A kind of car speed identification method
CN110286248A (en) * 2019-06-26 2019-09-27 贵州警察学院 A kind of vehicle speed measuring method based on video image

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104299430A (en) * 2014-10-13 2015-01-21 上海市城市建设设计研究总院 Off-road green wave vehicle speed guide method based on vehicle and road cooperation
CN108765462A (en) * 2018-05-29 2018-11-06 公安部交通管理科学研究所 A kind of car speed identification method
CN110286248A (en) * 2019-06-26 2019-09-27 贵州警察学院 A kind of vehicle speed measuring method based on video image

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