CN110682917A - Vehicle positioning drift calibration system and method based on video intelligent analysis - Google Patents

Vehicle positioning drift calibration system and method based on video intelligent analysis Download PDF

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CN110682917A
CN110682917A CN201910835954.7A CN201910835954A CN110682917A CN 110682917 A CN110682917 A CN 110682917A CN 201910835954 A CN201910835954 A CN 201910835954A CN 110682917 A CN110682917 A CN 110682917A
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positioning
vehicle
information
acquisition module
acc signal
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CN110682917B (en
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王春波
谢波
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CHENGDU YIMENG HENGXIN TECHNOLOGY Co Ltd
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CHENGDU YIMENG HENGXIN TECHNOLOGY Co Ltd
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0062—Adapting control system settings
    • B60W2050/0075—Automatic parameter input, automatic initialising or calibrating means
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
    • B60W2050/0062—Adapting control system settings
    • B60W2050/0075—Automatic parameter input, automatic initialising or calibrating means
    • B60W2050/0083—Setting, resetting, calibration
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/06—Direction of travel
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2520/00—Input parameters relating to overall vehicle dynamics
    • B60W2520/10—Longitudinal speed
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W2556/00—Input parameters relating to data
    • B60W2556/45—External transmission of data to or from the vehicle
    • B60W2556/50—External transmission of data to or from the vehicle for navigation systems

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  • Engineering & Computer Science (AREA)
  • Automation & Control Theory (AREA)
  • Human Computer Interaction (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Image Analysis (AREA)
  • Traffic Control Systems (AREA)

Abstract

The invention discloses a vehicle positioning drift calibration system and method based on video intelligent analysis. The method comprises the steps of judging the motion state of the vehicle according to an ACC signal of the vehicle and a video image outside the vehicle, keeping the positioning position of the vehicle at the position with the highest positioning precision all the time when the vehicle is in a parking state, avoiding the continuous random movement of the positioning position of the vehicle, effectively inhibiting the drift of the positioning data and ensuring the precision of the positioning information of the vehicle in the parking state; when the vehicle is in a driving state, an obvious drift event can be detected according to the motion characteristics of the vehicle, different weights are configured according to the difference of the positioning quality and the positioning time, and then the positioning information after the drift processing is obtained on average, so that the effective restraining effect on the positioning drift is achieved.

Description

Vehicle positioning drift calibration system and method based on video intelligent analysis
Technical Field
The invention relates to vehicle drift calibration, in particular to a vehicle positioning drift calibration system and method based on video intelligent analysis.
Background
With the development of science and technology and the continuous progress of the social life level, vehicles become essential transportation means in the life of people, and great convenience is provided for the traveling of people. At present, the positioning data of the vehicle-mounted terminal depends on a positioning module to receive a positioning satellite signal, and then current position information of a vehicle, such as longitude and latitude, altitude, direction and speed, is calculated and output. The positioning module receives positioning satellite signals from all directions through a positioning antenna, and obtains the current positioning information of the vehicle through a positioning algorithm. However, the following errors exist between the satellite signals and the distance from the positioning module antenna:
(1) ionospheric delay induced errors
In an ionized layer between 50-100 km above the earth and the ground, gas molecules are strongly ionized by various rays radiated by celestial bodies such as the sun, and a large amount of free electrons and positive ions are formed. When satellite signals pass through the ionosphere, the path of the signals is bent and the propagation velocity is changed, as with other electromagnetic waves, thereby causing a deviation in the measured distance, an effect called ionospheric delay.
(2) Errors caused by tropospheric delay
The troposphere has a greater atmospheric density than the ionosphere and is also complex. As the satellite signal passes through the troposphere, the propagation path of the signal bends, thereby biasing the distance measurement, a phenomenon known as troposphere delay.
(3) Errors due to multipath effects
Satellite signals (reflected waves) reflected by reflectors around the survey station enter the receiver antenna, interfere with signals (direct waves) directly from the satellite, and cause a deviation in the observed values, resulting in a so-called "multipath error". Such an interference delay effect due to multipath signal propagation is called a multipath effect.
(4) Errors due to weak signals
Since the vehicle is driven in a place where a high-rise forest or a canyon is erected, and is influenced by the shielding of buildings or mountains, the satellite signals which can be received are limited, and the position of the receiver obtained by calculation naturally has a large error.
Therefore, when the positioning module is affected by the above adverse factors, a certain error exists between the positioning information output by the positioning module and the actual real position information, and a positioning drift phenomenon occurs. Particularly, when the vehicle is stationary, the vehicle is more prone to drift, and when the vehicle is stationary, the position output by the positioning module is continuously changed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, provides a vehicle positioning drift calibration system and method based on video intelligent analysis, and effectively improves the accuracy of vehicle positioning information.
The purpose of the invention is realized by the following technical scheme: a vehicle positioning drift calibration system based on video intelligent analysis comprises a video image acquisition module, an ACC signal acquisition module, a positioning data acquisition module and a central processing module; the output ends of the video image acquisition module, the ACC signal acquisition module and the positioning data acquisition module are all connected with the central processing module;
the ACC signal acquisition module is used for acquiring an ACC signal of the vehicle and transmitting the ACC signal to the central processing module;
the video image acquisition module is used for acquiring video image information outside the vehicle and transmitting the video image information to the central processing module;
and the central processing module is used for comprehensively judging the motion state of the vehicle according to the information from the video image acquisition module and the ACC signal acquisition module, and processing the positioning data from the positioning data acquisition module to realize the inhibition of positioning drift.
The method comprises the following steps that an ACC signal of the vehicle, namely a vehicle ignition switch signal, is collected through an I/O port, the ACC signal is high level and represents ignition, and the ACC signal is low level and represents flameout; the video image acquisition module comprises a camera which is right opposite to the front of the vehicle; the positioning data of the positioning data acquisition module comprises real-time, longitude and latitude of the vehicle, altitude of the vehicle, driving direction of the vehicle and driving speed.
The central processing module includes:
the ACC signal analysis unit is used for carrying out preliminary judgment on the vehicle state according to an ACC signal of the vehicle, indicating that the vehicle is flameout when the ACC signal is at a low level, and indicating that the vehicle is ignited when the ACC signal is at a high level;
the video image analysis unit is used for carrying out brightness difference analysis on each frame of image and the previous frame of image in the video image information;
the comprehensive vehicle motion state judging unit is used for comprehensively judging the motion state of the vehicle by combining the ACC signal analysis result and the video image analysis result;
and the positioning drift processing unit is used for processing the positioning data from the positioning data acquisition module by combining the motion state of the vehicle, so that the positioning drift is restrained.
A calibration method of a vehicle positioning drift calibration system based on video intelligent analysis comprises the following steps:
s1, basic information acquisition: the ACC signal acquisition module acquires an ACC signal of the vehicle in real time, the video image acquisition module acquires video image information outside the vehicle in real time, and the positioning module acquires vehicle positioning information in real time and transmits the vehicle positioning information to the central processing module;
s2, judging the motion state of the vehicle: the central processing module comprehensively judges the motion state of the vehicle according to the received ACC signal and the video image of the vehicle; the motion state of the vehicle comprises a parking state and a driving state;
s3, positioning drift suppression: the central processing module is combined with the motion state of the vehicle to process the positioning data from the positioning data acquisition module, so that the positioning drift is restrained.
Wherein the step S2 includes the following substeps:
s201, the central processing module performs primary judgment on the vehicle state according to the vehicle ACC signal:
when the ACC signal is at a low level, the vehicle is turned off and is in an inactive parking state, and the process proceeds to step S204;
when the ACC signal is high, indicating that the vehicle is on, the process proceeds to step S202;
s202, the central processing module analyzes the brightness difference value of each frame of image and the previous frame of image in the video image information;
s203, the central processing module compares the obtained brightness difference value with a preset threshold value, and judges whether the brightness difference values of the continuous N frames of video images and the previous frame of video image are larger than the set threshold value;
if yes, determining that the vehicle is in a driving state;
if not, determining that the vehicle is in an idling stop state.
The step S202 includes:
the central processing module converts the video image from the image acquisition module into YUV420 format, removes the UV component representing the color difference in the video frame data, retains the Y component representing the brightness information, and then calculates the brightness difference value of two adjacent frames of images by the interframe brightness difference method.
In step S3, when the vehicle is in a parking state, the processing procedure of the positioning data by the central processing module includes:
storing a first piece of positioning information in a parking state;
for each piece of new positioning information input later, when the positioning quality index corresponding to the new positioning information is higher than the positioning quality index corresponding to the currently stored positioning information and the difference of the positioning quality indexes of the new positioning information and the currently stored positioning information reaches a set threshold value, updating the stored positioning information by using the newly input positioning information, otherwise, keeping the stored positioning information unchanged; the stored positioning information is used as the real-time positioning information of the vehicle;
the parking state includes an inactivated parking state and an idling parking state.
In step S3, when the vehicle is in a driving state, the processing procedure of the positioning data by the central processing module includes:
according to the acceleration change characteristic and the highest speed characteristic of the vehicle, when the acceleration change exceeds a set threshold or the speed exceeds a set threshold, determining that a drift event occurs in the positioning; the speed of the vehicle is acquired from the positioning data of the positioning data acquisition module, and the acceleration of the vehicle is calculated according to the speed of the vehicle;
when the drift event occurs in the positioning, the best positioning quality index LQ in the latest positioning data is taken as the real-time positioning information of the vehicle:
when the vehicle speed is less than 30km/h, searching the best positioning information of the positioning quality index LQ in the latest 5 positioning data;
and when the vehicle speed is more than 30km/h, searching the positioning information with the best positioning quality index LQ in the latest 3 pieces of positioning data.
The positioning quality index quantization mode corresponding to the positioning information is as follows:
wherein LQ represents a positioning quality index of positioning information, n represents the number of satellites participating in positioning operation, cn0iRepresenting the carrier-to-noise ratio of the ith satellite signal participating in positioning operation, and PDOP representing a position precision factor;
setting the positioning quality index corresponding to the new input positioning information as LQ1The positioning quality index corresponding to the currently stored positioning information is LQ0Then LQ1-LQ0>When k, the positioning quality index corresponding to the new positioning information is considered to be higher than the positioning quality index corresponding to the currently stored positioning information, and the difference of the positioning quality indexes of the new positioning information and the positioning information reaches a set threshold; where k is the set threshold.
The invention has the beneficial effects that: firstly, the motion state of the vehicle is judged according to the ACC signal of the vehicle and the video image outside the vehicle, when the vehicle is in a parking state, the positioning position of the vehicle is always kept at the position with the highest positioning precision, the continuous random movement of the positioning position of the vehicle is avoided, the drift of the positioning data is effectively inhibited, the precision of the positioning information of the vehicle in the parking state is ensured, and the accuracy of the positioning information of the vehicle is effectively improved; when the vehicle is in a driving state, the obvious drift event can be detected according to the motion characteristic of the vehicle, different weights are configured according to the difference of the positioning quality and the positioning time, and then the positioning information after the drift processing is obtained on average, so that the effective restraining effect on the positioning drift is achieved, and the accuracy of the positioning information of the vehicle is effectively improved.
Drawings
FIG. 1 is a schematic block diagram of the system of the present invention;
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
The technical solutions of the present invention are further described in detail below with reference to the accompanying drawings, but the scope of the present invention is not limited to the following.
As shown in fig. 1, a vehicle positioning drift calibration system based on video intelligent analysis includes a video image acquisition module, an ACC signal acquisition module, a positioning data acquisition module and a central processing module; the output ends of the video image acquisition module, the ACC signal acquisition module and the positioning data acquisition module are all connected with the central processing module;
the ACC signal acquisition module is used for acquiring an ACC signal of the vehicle and transmitting the ACC signal to the central processing module;
the video image acquisition module is used for acquiring video image information outside the vehicle and transmitting the video image information to the central processing module;
and the central processing module is used for comprehensively judging the motion state of the vehicle according to the information from the video image acquisition module and the ACC signal acquisition module, and processing the positioning data from the positioning data acquisition module to realize the inhibition of positioning drift.
In the embodiment of the application, the vehicle ACC signal is generally transmitted to the central processing module through the I/O port, and generally, a high level indicates ignition, a low level indicates flameout, and flameout can clearly determine that the vehicle is in a stopped state, but ignition cannot clearly determine a driving state of the vehicle. After the vehicle is ignited, the vehicle may be in a driving state or an idling state, so that the motion state of the vehicle cannot be clearly determined by an ACC signal after the vehicle is ignited, and the motion state of the vehicle during the ignition needs to be confirmed through video analysis; the video image acquisition module comprises a camera which is right opposite to the front of the vehicle; the positioning data of the positioning data acquisition module comprises real-time, longitude and latitude of the vehicle, altitude of the vehicle, driving direction of the vehicle and driving speed.
The central processing module includes:
the ACC signal analysis unit is used for carrying out preliminary judgment on the vehicle state according to an ACC signal of the vehicle, indicating that the vehicle is flameout when the ACC signal is at a low level, and indicating that the vehicle is ignited when the ACC signal is at a high level;
the video image analysis unit is used for carrying out brightness difference analysis on each frame of image and the previous frame of image in the video image information;
the comprehensive vehicle motion state judging unit is used for comprehensively judging the motion state of the vehicle by combining the ACC signal analysis result and the video image analysis result;
and the positioning drift processing unit is used for processing the positioning data from the positioning data acquisition module by combining the motion state of the vehicle, so that the positioning drift is restrained.
As shown in fig. 2, a calibration method of a vehicle positioning drift calibration system based on video intelligent analysis includes the following steps:
s1, basic information acquisition: the ACC signal acquisition module acquires an ACC signal of the vehicle in real time, the video image acquisition module acquires video image information outside the vehicle in real time, and the positioning module acquires vehicle positioning information in real time and transmits the vehicle positioning information to the central processing module;
s2, judging the motion state of the vehicle: the central processing module comprehensively judges the motion state of the vehicle according to the received ACC signal and the video image of the vehicle; the motion state of the vehicle comprises a parking state and a driving state;
s3, positioning drift suppression: the central processing module is combined with the motion state of the vehicle to process the positioning data from the positioning data acquisition module, so that the positioning drift is restrained.
Wherein the step S2 includes the following substeps:
s201, the central processing module performs primary judgment on the vehicle state according to the vehicle ACC signal:
when the ACC signal is at a low level, the vehicle is turned off and is in an inactive parking state, and the process proceeds to step S204;
when the ACC signal is high, indicating that the vehicle is on, the process proceeds to step S202;
s202, the central processing module analyzes the brightness difference value of each frame of image and the previous frame of image in the video image information;
s203, the central processing module compares the obtained brightness difference value with a preset threshold value, and judges whether the brightness difference values of the continuous N frames of video images and the previous frame of video image are larger than the set threshold value;
if yes, determining that the vehicle is in a driving state;
if not, determining that the vehicle is in an idling stop state.
In the embodiment of the application, the value of N is determined by presetting, and if the ACC signal line is connected incorrectly or not, the driving state and the parking state of the vehicle are determined directly according to steps S202 to S203.
The step S202 includes:
the central processing module converts the video image from the image acquisition module into YUV420 format, removes the UV component representing the color difference in the video frame data, retains the Y component representing the brightness information, and then calculates the brightness difference value of two adjacent frames of images by the interframe brightness difference method.
The method comprises the steps of obtaining an absolute value of brightness difference of two frames of images by subtracting the brightness values of the two frames to obtain the absolute value of the brightness difference of the two frames of images, judging whether the absolute value is greater than a set threshold value or not to analyze the motion characteristic of a video sequence, if the continuous video frames are greater than the set threshold value, determining that the vehicle is in a motion state, otherwise, determining that the vehicle is in a static state. The frame-by-frame brightness difference of the video frame sequence is compared with a set threshold value, which is equivalent to that the time-domain high-pass filtering is carried out on the frame-by-frame brightness difference of the video frame sequence, and the anti-interference capability is enhanced.
In step S3, the positioning information should remain unchanged in theory when the vehicle is parked, but the positioning information output by the positioning module has drift due to various interferences in practice, and the processing procedure of the positioning data by the central processing module includes:
storing a first piece of positioning information in a parking state;
for each piece of new positioning information input later, when the positioning quality index corresponding to the new positioning information is higher than the positioning quality index corresponding to the currently stored positioning information and the difference of the positioning quality indexes of the new positioning information and the currently stored positioning information reaches a set threshold value, updating the stored positioning information by using the newly input positioning information, otherwise, keeping the stored positioning information unchanged; the stored positioning information is used as the real-time positioning information of the vehicle;
therefore, iteration is carried out continuously, the positioning accuracy and the position change quantity of the parking positioning information are guaranteed, and the index range for measuring the quality of the positioning information is controllable and limited, so that the positioning information can be locked at a point with the best positioning quality and is kept unchanged until the vehicle is driven again. In addition, when the vehicle is parked, the vehicle is initially in a positioning state and is not positioned due to external influence (such as signal weakening), the central processing module can still output the previously stored effective positioning data outwards because the central processing module knows that the vehicle is parked and the position of the vehicle is not changed, and only the positioning time adopts real-time clock time.
The parking state includes an inactivated parking state and an idling parking state.
In step S3, when the vehicle is in a driving state, the processing procedure of the positioning data by the central processing module includes:
according to the acceleration change characteristic and the highest speed characteristic of the vehicle, when the acceleration change exceeds a set threshold or the speed exceeds a set threshold, determining that a drift event occurs in the positioning; the speed of the vehicle is acquired from the positioning data of the positioning data acquisition module, and the acceleration of the vehicle is calculated according to the speed of the vehicle; specifically, the difference between the speed information in the current positioning data and the speed information of the previous positioning data is divided by the time interval of the two positioning data, so that the acceleration corresponding to the current positioning data can be obtained, and the acceleration change can be obtained by making the difference between the corresponding accelerations of any two positioning data;
when a drift event occurs in positioning, the best positioning quality index LQ in the latest positioning data is taken as the real-time positioning information of the vehicle; and judging according to the current vehicle speed, when the vehicle speed is less than 30km/h, searching the best positioning information in the latest 5 positioning data, and when the vehicle speed is more than 30km/h, searching in the latest 3 positioning data.
The positioning quality index quantization mode corresponding to the positioning information is as follows:
Figure BDA0002192168020000071
wherein LQ represents a positioning quality index of positioning information, n represents the number of satellites participating in positioning operation, cn0iRepresenting the carrier-to-noise ratio of the ith satellite signal participating in positioning operation, and PDOP representing a position precision factor;
the carrier-to-noise ratio refers to the ratio of the carrier power and the noise power at the input end of the receiver, and the value range is 0-99, and the unit is dB-Hz. PDOP: the Position Precision factor (Position Dilution of Precision) translates to "Precision strength", usually to "relative error". The specific meanings are as follows: since the quality of the observation result is related to the geometry between the satellite and the receiver to be measured and has a great influence, the amount of error caused by the calculation is referred to as the degree of accuracy. The better the satellite distribution in the sky, the higher the positioning accuracy (the smaller the value, the higher the accuracy). PDOP represents a parameter of the relation between the three-dimensional position positioning precision and the geometric configuration of the navigation platform, and the value range of the PDOP is 0.5-99.9.
Setting the positioning quality index corresponding to the new input positioning information as LQ1The positioning quality index corresponding to the currently stored positioning information is LQ0Then LQ1-LQ0>When k, the positioning quality index corresponding to the new positioning information is considered to be higher than the positioning quality index corresponding to the currently stored positioning information, and the difference of the positioning quality indexes of the new positioning information and the positioning information reaches a set threshold; where k is the set threshold.
The method comprises the steps of judging the motion state of the vehicle according to an ACC signal of the vehicle and a video image outside the vehicle, keeping the positioning position of the vehicle at the position with the highest positioning precision all the time when the vehicle is in a parking state, avoiding the continuous random movement of the positioning position of the vehicle, effectively inhibiting the drift of the positioning data and ensuring the precision of the positioning information of the vehicle in the parking state; when the vehicle is in a driving state, an obvious drift event can be detected according to the motion characteristics of the vehicle, different weights are configured according to the difference of the positioning quality and the positioning time, and then the positioning information after the drift processing is obtained on average, so that the effective restraining effect on the positioning drift is achieved.
It is to be understood that the foregoing is not to be construed as limiting the invention to the forms disclosed herein, but is to be construed not as excluding other embodiments and from consideration of the specification and/or practice of the invention as may be practiced in other combinations, modifications, and environments and as may be modified within the scope of the concepts described herein by applying the teachings or the teachings disclosed herein. And that modifications and variations may be effected by those skilled in the art without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (10)

1. The utility model provides a vehicle location drift calibration system based on video intelligent analysis which characterized in that: the device comprises a video image acquisition module, an ACC signal acquisition module, a positioning data acquisition module and a central processing module; the output ends of the video image acquisition module, the ACC signal acquisition module and the positioning data acquisition module are all connected with the central processing module;
the ACC signal acquisition module is used for acquiring an ACC signal of the vehicle and transmitting the ACC signal to the central processing module;
the video image acquisition module is used for acquiring video image information outside the vehicle and transmitting the video image information to the central processing module;
and the central processing module is used for comprehensively judging the motion state of the vehicle according to the information from the video image acquisition module and the ACC signal acquisition module, and processing the positioning data from the positioning data acquisition module to realize the inhibition of positioning drift.
2. The system of claim 1, wherein the system comprises: the vehicle ACC signal, namely a vehicle ignition switch signal, is collected through the I/O port, the ACC signal is high level and indicates ignition, and the ACC signal is low level and indicates flameout; the positioning data of the positioning data acquisition module comprises real-time, longitude and latitude of the vehicle, altitude of the vehicle, driving direction of the vehicle and driving speed.
3. The system of claim 1, wherein the system comprises: the video image acquisition module comprises a camera which is right opposite to the front of the vehicle.
4. The system of claim 1, wherein the system comprises: the central processing module includes:
the ACC signal analysis unit is used for carrying out preliminary judgment on the vehicle state according to an ACC signal of the vehicle, indicating that the vehicle is flameout when the ACC signal is at a low level, and indicating that the vehicle is ignited when the ACC signal is at a high level;
the video image analysis unit is used for carrying out brightness difference analysis on each frame of image and the previous frame of image in the video image information;
the comprehensive vehicle motion state judging unit is used for comprehensively judging the motion state of the vehicle by combining the ACC signal analysis result and the video image analysis result;
and the positioning drift processing unit is used for processing the positioning data from the positioning data acquisition module by combining the motion state of the vehicle, so that the positioning drift is restrained.
5. The calibration method of the vehicle positioning drift calibration system based on the video intelligent analysis as claimed in any one of claims 1 to 4, wherein: the method comprises the following steps:
s1, basic information acquisition: the ACC signal acquisition module acquires an ACC signal of the vehicle in real time, the video image acquisition module acquires video image information outside the vehicle in real time, and the positioning module acquires vehicle positioning information in real time and transmits the vehicle positioning information to the central processing module;
s2, judging the motion state of the vehicle: the central processing module comprehensively judges the motion state of the vehicle according to the received ACC signal and the video image of the vehicle; the motion state of the vehicle comprises a parking state and a driving state;
s3, positioning drift suppression: the central processing module is combined with the motion state of the vehicle to process the positioning data from the positioning data acquisition module, so that the positioning drift is restrained.
6. The calibration method of the vehicle positioning drift calibration system based on the video intelligent analysis as claimed in claim 5, wherein: the step S2 includes the following sub-steps:
s201, the central processing module performs primary judgment on the vehicle state according to the vehicle ACC signal:
when the ACC signal is at a low level, the vehicle is turned off and is in an inactive parking state, and the process proceeds to step S204;
when the ACC signal is high, indicating that the vehicle is on, the process proceeds to step S202;
s202, the central processing module analyzes the brightness difference value of each frame of image and the previous frame of image in the video image information;
s203, the central processing module compares the obtained brightness difference value with a preset threshold value, and judges whether the brightness difference values of the continuous N frames of video images and the previous frame of video image are larger than the set threshold value;
if yes, determining that the vehicle is in a driving state;
if not, determining that the vehicle is in an idling stop state.
7. The calibration method of the vehicle positioning drift calibration system based on the video intelligent analysis as claimed in claim 6, wherein: the step S202 includes:
the central processing module converts the video image from the image acquisition module into YUV420 format, removes the UV component representing the color difference in the video frame data, retains the Y component representing the brightness information, and then calculates the brightness difference value of two adjacent frames of images by the interframe brightness difference method.
8. The calibration method of the vehicle positioning drift calibration system based on the video intelligent analysis as claimed in claim 5, wherein: in step S3, when the vehicle is in a parking state, the processing procedure of the positioning data by the central processing module includes:
storing a first piece of positioning information in a parking state;
for each piece of new positioning information input later, when the positioning quality index corresponding to the new positioning information is higher than the positioning quality index corresponding to the currently stored positioning information and the difference of the positioning quality indexes of the new positioning information and the currently stored positioning information reaches a set threshold value, updating the stored positioning information by using the newly input positioning information, otherwise, keeping the stored positioning information unchanged; the stored positioning information is used as the real-time positioning information of the vehicle;
the parking state includes an inactivated parking state and an idling parking state.
9. The calibration method of the vehicle positioning drift calibration system based on the video intelligent analysis as claimed in claim 6, wherein: in step S3, when the vehicle is in a driving state, the processing procedure of the positioning data by the central processing module includes:
according to the acceleration change characteristic and the highest speed characteristic of the vehicle, when the acceleration change exceeds a set threshold or the speed exceeds a set threshold, determining that a drift event occurs in the positioning; the speed of the vehicle is acquired from the positioning data of the positioning data acquisition module, and the acceleration of the vehicle is calculated according to the speed of the vehicle;
when the drift event occurs in the positioning, the best positioning quality index LQ in the latest positioning data is taken as the real-time positioning information of the vehicle:
when the vehicle speed is less than 30km/h, searching the best positioning information of the positioning quality index LQ in the latest 5 positioning data;
and when the vehicle speed is more than 30km/h, searching the positioning information with the best positioning quality index LQ in the latest 3 pieces of positioning data.
10. The calibration method of the vehicle positioning drift calibration system based on the video intelligent analysis according to claim 8 or 9, characterized in that: the quantization mode of the positioning quality index corresponding to the positioning information is as follows:
Figure FDA0002192168010000031
wherein LQ represents a positioning quality index of positioning information, n represents the number of satellites participating in positioning operation, cn0iRepresenting the carrier-to-noise ratio of the ith satellite signal participating in positioning operation, and PDOP representing a position precision factor;
setting the positioning quality index corresponding to the new input positioning information as LQ1The positioning quality index corresponding to the currently stored positioning information is LQ0Then LQ1-LQ0>When k, the positioning quality index corresponding to the new positioning information is considered to be higher than the positioning quality index corresponding to the currently stored positioning information, and the difference of the positioning quality indexes of the new positioning information and the positioning information reaches a set threshold; where k is the set threshold.
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