CN113108808B - Vehicle odometer online verification system and method - Google Patents

Vehicle odometer online verification system and method Download PDF

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CN113108808B
CN113108808B CN202110280143.2A CN202110280143A CN113108808B CN 113108808 B CN113108808 B CN 113108808B CN 202110280143 A CN202110280143 A CN 202110280143A CN 113108808 B CN113108808 B CN 113108808B
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value
vehicle
odometer
driving
running
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CN113108808A (en
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费庆
邵勇强
刘其志
郑子伟
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Beijing Institute of Technology BIT
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C25/00—Manufacturing, calibrating, cleaning, or repairing instruments or devices referred to in the other groups of this subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
    • G01S19/47—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being an inertial measurement, e.g. tightly coupled inertial
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
    • G07B13/00—Taximeters

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  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Automation & Control Theory (AREA)
  • Manufacturing & Machinery (AREA)
  • Navigation (AREA)

Abstract

The invention discloses an online verification system and a verification method for a vehicle odometer, and belongs to the technical field of vehicle detection. The invention adopts the combined navigation system (GNSS + INS) to automatically calibrate the vehicle odometer, and can automatically select the road section meeting the calibration standard and the driving state meeting the calibration standard to calibrate the odometer when the GPS positioning effect is good. When the vehicle is considered to have the change of the driving condition, the verified odometer K value is automatically put into use, and the calibration data is automatically updated, so that the stability of the K value is ensured, and the automatic adjustment is carried out when the vehicle condition is changed for a long time. Meanwhile, the method saves verification key data, can perform historical backtracking and is convenient for analyzing verification results. The method can be widely applied to the field of vehicle travel mileage verification such as taximeters, freight vehicle odometers and the like.

Description

Vehicle odometer online verification system and method
Technical Field
The invention relates to a vehicle odometer and a verification system and method, belonging to the technical field of vehicle detection.
Background
In the course of the certification of a vehicle Odometer, a vehicle Odometer (Odometer) is generally used. The vehicle odometer is a wheel revolution pulse detection device which is arranged on a wheel spindle or a speed reducer and is used for counting the running mileage of a vehicle.
For example, a taximeter is a typical odometer application, and the mileage of the taximeter is calculated by the following method:
the odometer was first calibrated. The vehicle runs a certain distance L in a standard verification scene cal (e.g., 1 km, or a number of revolutions of the wheel equivalent to 1 km on the verification device), recording the number of pulses n detected by the odometer during the trip cal Then calculating the K value of the odometer, K = n cal /L cal The unit of K is: number of pulses per kilometer. In normal driving, the relationship between the driving mileage of the vehicle and the number of pulses detected by the odometer is: l = n/K, thereby obtainingAnd obtaining the driving mileage of the vehicle.
The traditional vehicle odometer verification method comprises a drum-type verification method and is generally applied to verification work of a taxi odometer. The method comprises the steps of placing a front wheel of a vehicle on a rotary roller device, enabling the vehicle to run (front wheel to rotate) for a period of time, and calculating the K value of a speedometer according to the running mileage calculated by a detection device and the number of pulses displayed by the speedometer of the taxi.
However, this assay method requires dedicated assay equipment, a field, and an assay worker, and is prone to assay errors due to equipment or human factors. In addition, the verification method only simulates the actual running state of the vehicle, and although some compensation can be performed on the temperature, the tire pressure and the like in the process, the method still cannot completely meet the actual operating conditions.
Another more commonly used odometer calibration scheme utilizes a vehicle calibration site with a standard straight road built therein, the length of which can meet the calibration requirements. And during detection, the detected vehicle is enabled to run linearly from the starting point to the end point of the road, and then the K value is calculated according to the actual running distance and the odometer pulse number. However, the method needs larger site conditions and standard lanes, has high site requirements and low use efficiency, is only suitable for specific occasions requiring high-precision vehicle mileage calibration, and is not suitable for large-scale application.
Currently, there are several new vehicle odometer verification methods disclosed. For example, chinese patent application "a taximeter calibrating apparatus based on high precision positioning technology" (CN 201420363714.4) discloses a method for calibrating using a high precision navigation system (RTK differential GPS), which is to install a high precision GPS device on a vehicle, then obtain the precise position and the driving mileage in real time during the normal driving of the vehicle, and calculate the K value of the odometer together with the actual number of pulses of the odometer. The method adopts high-precision differential GPS positioning, and the positioning precision reaches centimeter level. However, since this method requires a communication link to be established with the RTK reference station, there are various problems such as complicated equipment, narrow use range, and payment for use, and it cannot be used when the satellite fails.
In addition, in documents such as the chinese patent application "taxi pricing and monitoring system based on GPS-GPRS" (CN 201710170212.8), and the chinese master paper "research on GPS-GPRS taxi pricing monitoring system" (china marine university, 2011), a method for measuring and detecting mileage based on an electronic map using GPS and an electronic map and wireless communication is proposed. The method uses an electronic map for auxiliary positioning, improves positioning precision and mileage calculation precision, and is commonly used in navigation positioning systems of mobile phones, such as Goods navigation and Baidu navigation. Although the method for detecting the odometer can improve the positioning accuracy of the vehicle through an accurate map, the method has the problems of high use cost, limited application range and the like because the method needs to carry out wireless communication with an electronic map server or a vehicle-mounted electronic map needs to be updated in time.
In documents such as 'design and development of BJ-a type multifunctional taximeter verification instrument system' (modern measurement and laboratory management, 2016), a method for implementing taximeter verification by using a combined navigation system is proposed. This method uses integrated navigation to verify odometers in a process similar to that described above using differential GPS. However, the positioning accuracy of the integrated navigation system is generally in the meter level and is subjected to fixed-point test and experiment, so that the problems of manually specified calibration road sections, complex operation process and the like exist.
In summary, the existing vehicle odometer verification method mainly has the following problems and disadvantages:
1. the drum-type odometer identification method needs special equipment, sites and personnel, the identification result is influenced by tire pressure, temperature, load and the like, and the identification result can be maliciously adjusted by drivers (such as changing small-size tires, reducing tire pressure and the like), so that the measurement error is increased during actual use.
2. The method for carrying out the odometer calibration on the standard road section needs a larger field, has long detection time and is not suitable for large-scale popularization.
3. The method of differential GPS positioning needs to establish communication with a reference station, requires good communication signals without interference, and has high equipment cost and limited use.
4. By adopting the method of the common GPS and the electronic map, the communication connection with the map server is required to be established, the map is required to be ensured to be accurate, the use cost is increased, and the use scene is limited.
5. The existing method for calibrating the odometer by adopting combined navigation needs human participation, specifies a detection road section and length, and cannot reduce malicious adjustment of users by real-time updating.
Disclosure of Invention
The invention aims to overcome the problems and the defects of the conventional vehicle odometer calibrating method, provides a novel vehicle odometer online calibrating system and a novel vehicle odometer online calibrating method, and can be widely applied to the field of vehicle travel mileage calibration such as taximeters, freight car odometers and the like.
The innovation points of the invention are as follows: when the pulse type wheel revolution detecting device is used for calculating the running distance of a vehicle (namely, the vehicle odometer), a combined navigation system (GNSS + INS) is used for automatically calibrating the vehicle odometer, and a road section meeting the calibration standard and a running state meeting the calibration standard can be automatically selected for calibrating the odometer when the GPS positioning effect is good. When the vehicle is considered to have the change of the driving condition, the verified K value is automatically put into use, and the calibration data is automatically updated, so that the stability of the K value is ensured, and the automatic adjustment is carried out when the vehicle condition changes for a long time. Meanwhile, the method saves verification key data, can perform historical backtracking and is convenient for analyzing verification results.
The technical scheme adopted by the invention is as follows:
an on-line verification system for a vehicle odometer comprises a GNSS antenna, a pulse wheel revolution detecting device interface, a GNSS module, an inertial navigation device, a processor, a storage unit and an odometer display screen. The GNSS module and the inertial navigation device form a basic navigation unit of the integrated navigation system, the processor is used for completing integrated navigation calculation and milemeter verification calculation, the storage unit is used for storing verification results and intermediate data elements, and the milemeter display screen is used for displaying the driving mileage of the vehicle and verification result information.
The GNSS module, the inertial navigation device, the processor, the storage unit and the odometer display screen are arranged in the odometer of the detected vehicle. The GNSS antenna is connected with the GNSS module, the pulse type wheel revolution detecting device is connected with the processor, the inertial navigation device is connected with the GNSS module, and the processor is respectively connected with the GNSS module, the storage unit and the odometer display. The pulse type wheel revolution detecting device interface is connected with a pulse type wheel revolution detecting device of the detected vehicle. The GNSS antenna can be placed under the front windshield of the detected vehicle, and good reception of satellite signals is guaranteed.
Based on the system, the invention provides an online verification method for the vehicle odometer.
When the vehicle runs, the processor calculates the running mileage according to the number of wheel revolutions and the initial K value. The vehicle mileage calculation formula is as follows: mileage = wheel revolutions K value. The method comprises the following steps:
step 1: and judging whether the GNSS signal is effective or not, and judging that the vehicle speed is greater than a set threshold value T. And (3) if the signal is effective and the vehicle speed is greater than the set threshold value T, executing the step 2, otherwise, continuously detecting and judging until the requirements are met, and then entering the next step.
Specifically, when the number of satellites in the navigation system is not less than 4, the GNSS signal is determined to be a valid signal, and the vehicle speed threshold T is required to be not less than 20 km/h.
And 2, step: and processing and storing the vehicle running data at fixed time, setting a sliding time window for judging straight line running, and judging whether the vehicle is in a straight line running state according to the running data in the time window. If the vehicle is in the straight-line driving state, continuously storing the vehicle driving data until the vehicle does not meet the straight-line driving state, judging whether the straight-line driving distance of the vehicle is more than 1 kilometer, if so, executing the step 3, if not, clearing the vehicle driving data, restarting to store the data and judging the straight-line driving state.
When the step is executed, if any one of the situations that the GNSS signal is invalid or the running speed is lower than the threshold value T occurs, the vehicle running data is cleared, and the step 1 is returned again.
The vehicle running data processed in a timing mode comprises the following steps: and the attitude angle of the vehicle obtained by the combined navigation system comprises a pitch angle, a roll angle and a course angle after filtering. The timed interval may be set to 1 second and the sliding time window size may be determined based on the speed of travel, or may be fixed to 10 seconds or other values. The window is scrolled as it moves once per second.
The straight-line running of the vehicle is judged according to the data in the sliding window, and the standards comprise:
a. whether the vehicle is in horizontal travel. That is, whether the pitch angle and the roll angle of the vehicle are smaller than given threshold values, if smaller, it indicates a horizontal running state, and if not, it indicates no horizontal running state.
b. Whether the vehicle is traveling in one direction. That is, whether the heading angle of the vehicle is always consistent or not is within a set threshold range.
The stored running data at least comprises accumulated running time (seconds) t and the pulse number n of the odometer from the start of entering a straight running state, the average running speed of the vehicle, the average attitude angle, the minimum value and the maximum value of the speed, the minimum value and the maximum value of the attitude angle, the minimum value and the maximum value of the altitude, the time for starting the straight running of the vehicle, longitude and latitude coordinates, and a running mileage value L calculated by combined navigation start And the K value currently used by the odometer.
And 3, step 3: and calculating the K value and judging whether the K value is valid or not. If the data is valid, executing the step 4, otherwise, clearing the vehicle running data and returning to the step 1.
Wherein the K value is based on the mileage value L recorded from the start of straight-line running of the vehicle start (unit: centimeter) combined navigation driving range L when finishing straight line driving end (unit: cm) and the accumulated pulse number n (unit: pulse) of the odometer are calculated, and the specific formula is as follows:
K＝n*100000/(L end -L start ) [ pulse/km] (1)
Judging whether the K value is valid or not, if so, calculating the current valueK value and theoretical value K ini For comparison, the formula is:
Δ＝Abs(K-K ini )/K ini (2)
wherein Abs represents an absolute value.
If the calculated change Δ is greater than a given threshold, for example 10%, the newly calculated value of K is considered invalid.
And 4, step 4: and calculating the reliability correlation quantity of the K value, and storing the correlation data in a K value table of the current day.
The reliability related quantity of the K value at least comprises the vehicle running distance, the altitude range, the heading angle range and the speed range for calculating the K value.
The data stored in the K-value-of-day table at least includes: the vehicle driving starting time, the longitude and latitude coordinates of the starting point, the longitude and latitude coordinates of the driving end point, the calculated K value, the K value reliability, the vehicle driving average speed, the vehicle driving average attitude angle, the vehicle driving speed minimum value and maximum value, and the vehicle driving attitude angle minimum value and maximum value.
And 5: and judging whether the vehicle running time reaches 24 hours or not, namely whether the day is finished or not. And if not, clearing the driving data, returning to the step 1, and continuously calculating and storing a new K value. If so, step 6 is performed.
And 6: if the records in the K value table of the day exceed the set upper limit value (for example, 10 records), deleting the records in the table which are sorted from high to low according to the credibility, and then arranging the records which are arranged at the end and exceed the set record upper limit in the record table, so that the record number in the K value table is the upper limit value, and then executing the step 7; if the records are smaller than the set lower limit value (such as 5), clearing the running data, returning to the step 1, and continuing to calculate and store a new K value. If the record is between the upper and lower limits, step 7 is performed directly.
Wherein, the reliability is in direct proportion to the driving distance of the vehicle and in inverse proportion to the non-linear uniform speed driving. The confidence level is calculated according to the following formula:
confidence = coefficient travel distance/(range of elevation variation linear travel range speed variation range)
And 7: and saving the data in the current-day K value table into a total K value table. And judging whether the records of the total K value table exceed a set upper record limit (such as 20), if so, deleting the K value records which are sorted from near to far according to time and have the earliest time and exceed the upper record number limit, and maintaining the record number at the upper limit. And then calculating whether the standard deviation of the K values in the total K value table is within an allowable range, if so, such as: the standard deviation of the K value/mean of the K value <5%, step 8 is performed. Otherwise, the data is not processed, the driving data is cleared, the step 1 is returned, and the data of the next 24 hours is collected.
And 8: judging whether the difference between the K value average value in the total K value table and the currently used K value is larger than a given threshold value, such as: k average value-K current value)/K current value >2%, if greater than, executing step 9, otherwise, not updating the K value, clearing the driving data, and returning to step 1. Therefore, the updating rate of the K value can be reduced, and the stability of the K value is kept.
And step 9: the currently used value of K is updated. Then, the running data is cleared, and the procedure returns to step 1.
The updating of the K value can be directly replaced by the average value of the K value in the record table. Alternatively, partial correction may be performed by the following method:
updated K value = α current K value + (1- α) K average value (3)
Wherein, alpha is a forgetting factor and takes a value between [0,1 ].
Thus, the online verification of the vehicle odometer is completed.
Advantageous effects
Compared with the prior art, the method has the advantages of low cost and convenient use, and can automatically finish the K value verification work of the odometer in the normal running process of the vehicle and ensure the long-term accuracy of the metering of the odometer.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
FIG. 2 is a flow chart of the method of the present invention.
Detailed Description
The method of the present invention is further described in detail below with reference to the drawings and examples.
Examples
As shown in fig. 1, an on-line verification system for a vehicle odometer.
The system (with the built-in GNSS antenna) is fixed below a front windshield, a 12V power supply interface is connected to a vehicle-mounted power supply, and a wheel revolution input interface is connected to the output of a wheel revolution detection device of a vehicle. The vehicle driving mileage of the system is calculated according to the wheel rotating speed and the K value, and the calculation formula is as follows: mileage = wheel revolutions K value. The mileage value is displayed on the display screen.
An on-line verification system for a vehicle odometer comprises a GNSS antenna, a pulse wheel revolution detecting device interface, a GNSS module, an inertial navigation device, a processor, a storage unit and an odometer display screen. The GNSS module and the inertial navigation device form a basic navigation unit of the integrated navigation system, the processor is used for finishing integrated navigation calculation and odometer verification calculation, the storage unit is used for storing verification results and intermediate data elements, and the odometer display screen is used for displaying the vehicle mileage and verification result information.
The GNSS module, the inertial navigation device, the processor, the storage unit and the odometer display screen are arranged in the odometer of the detected vehicle. The GNSS antenna is connected with the GNSS module, the pulse type wheel revolution detecting device is connected with the processor, the inertial navigation device is connected with the GNSS module, and the processor is respectively connected with the GNSS module, the storage unit and the odometer display. The pulse type wheel revolution detecting device interface is connected with a pulse type wheel revolution detecting device of the detected vehicle. The GNSS antenna can be placed under the front windshield of the detected vehicle, and good satellite signal receiving is guaranteed.
As shown in fig. 2, a method for online verification of a vehicle odometer.
When the vehicle runs, the processor calculates the running mileage according to the number of wheel revolutions and the initial K value. The vehicle mileage calculation formula is as follows: mileage = wheel revolutions K value. The method comprises the following steps:
step 1: and according to the satellite number received by the GNSS, whether the GNSS signal is effective or not is judged. When the number of satellites is more than 4, the GNSS positioning is considered to be effective, and whether the vehicle running speed is more than a speed threshold value T (30 km/h) or not is judged according to the running speed output by the GNSS. When the GNSS is active and the travel speed is greater than the threshold T, the next step may be entered. Otherwise, continuously detecting until the conditions are met and then entering the next step. Meanwhile, in the subsequent step, once the GNSS signal is invalid or the driving speed is lower than the threshold value T, the step 1 is returned again.
Step 2: the pitch angle and the roll angle of the vehicle are sampled periodically at intervals of 0.2 seconds, and the data in the intervals are filtered (for example, moving average filtering) at intervals of 1 second. The driving data of the vehicle is saved every second. And judging whether the vehicle is in a straight-line driving state according to the sliding time window of 10 seconds. If the vehicle is in straight line driving and the driving distance is more than 1 kilometer, continuously storing the vehicle driving data until the vehicle is in a state of no straight line driving, and recording the driving mileage value L at the moment end Executing the step 3; if not, the vehicle driving data is cleared, the data storage is restarted, and the straight line driving judgment is carried out.
Whether the vehicle is in straight line running is judged by data in the sliding window, and the judging method can be as follows:
a. judging horizontal driving: and the standard deviation of the pitch angle and the roll angle in the sliding window is less than 5 degrees. If yes, the vehicle is in the horizontal running state, and if not, the vehicle is not in the horizontal running state.
b. Judging straight line driving: the standard deviation of the heading angle within the sliding window is less than 5 degrees. If yes, the straight driving state is indicated, and if not, the straight driving state is not indicated.
The stored travel data per second includes the accumulated travel time (seconds) and the number of pulses n of the odometer from the start of entering the straight-line travel state, the average vehicle travel speed, the average attitude angle, the minimum value and the maximum value of the speed, the minimum value and the maximum value of the attitude angle, the minimum value and the maximum value of the altitude, the time for starting the straight-line travel of the vehicle, the longitude and latitude coordinates, and the travel mileage value L calculated by the integrated navigation start And the K value currently used by the odometer.
And 3, step 3: and calculating the K value and judging whether the K value is effective or not. If yes, executing step 4, otherwise, returning to step 2.
Wherein, the K value is the driving mileage value L recorded according to the straight driving start of the vehicle start (unit: centimeter) combined navigation driving range L when finishing straight line driving end (unit: cm) and the number of accumulated pulses n (unit: pulse) of the odometer. The formula is as follows:
K＝n*100000/(L end -L start ) [ pulse/km] (1)
Judging whether the K value is effective or not, namely judging whether the currently calculated K value is effective or not and whether the theoretical value is effective or not ini For comparison, the formula is:
Δ＝Abs(K-K ini )/K ini (2)
wherein Abs represents an absolute value.
If the calculated change Δ is greater than a given threshold, e.g., 10%, the newly calculated value of K is considered invalid.
Here, the mileage value at the start of straight-line running is set to 15.2 km, i.e., L start =1520000 cm, and a mileage value for ending straight-line travel of 18.3 km, i.e. L end =1830000 cm, and the cumulative number of pulses n =1820, then the K value is calculated as: k =1820 × 100000/(1830000-1520000) =587. If the current K is ini With a value of 600, the variance is: Δ = Abs (587-600)/600 =2.16%.
And 4, step 4: and calculating the reliability correlation quantity of the K value, and storing the correlation data in a K value table of the current day.
And acquiring the driving mileage, the altitude change extreme difference (the maximum altitude minus the minimum altitude), the straight line driving extreme difference (the maximum difference of course angles) and the speed change extreme difference when the K value is calculated according to the data when the K value is calculated. These data serve as K-value reliability-related quantities.
The data stored in the K-value table for the current day includes: the vehicle driving starting time, the longitude and latitude coordinates of the starting point, the longitude and latitude coordinates of the driving ending point, the calculated K value, the reliability related quantity of the K value, the average vehicle driving speed, the average vehicle driving attitude angle, the minimum value and the maximum value of the vehicle driving speed and the minimum value and the maximum value of the vehicle driving attitude angle.
And 5: and judging whether the vehicle running time reaches 24 hours or not, namely ending the current day. If not, returning to the step 1, and continuing to calculate and save the new K value. If so, step 6 is performed.
And 6: if the number of records in the K value table exceeds 10, the records with lower reliability of the table are deleted, and then step 7 is executed. If the number of records is less than 5, returning to the step 1, and continuing to calculate and save the new K value. If between the upper and lower limits, step 7 is performed directly.
The confidence level is calculated according to the following formula:
reliability = coefficient distance traveled/(range of altitude change linear travel range speed change range)
And 7: and saving the data in the current-day K value table into a total K value table. And judging whether the records of the total K value table exceed the upper limit of the records by 20, and if so, deleting the early K value records. And then calculating whether the standard deviation of the K values in the total K value table is within an allowable range. If it is within the allowable range (e.g., standard deviation of K value/mean of K value < 5%), then step 8 is performed. Otherwise, the processing is not carried out, and the step 1 is returned to collect the data of the next day.
And step 8: whether the average value of the K values in the total K value table is within the requirement of the threshold value (2%) is calculated according to the following formula:
(K mean-K current)/K current value (3)
If the threshold value is exceeded, step 9 is executed, otherwise, the K value is not updated, and the step 1 is directly returned. Therefore, the updating rate of the K value can be reduced, and the stability of the K value is kept.
And step 9: the currently used K value is updated as follows. Then, the procedure returns to step 1.
Updated K value = α current K value + (1- α) K mean value (4)
Wherein alpha is a forgetting factor, the value is between [0,1], and can be set to 0.5.
Thus, the online verification of the vehicle odometer is completed.
In the method, the driving data which can be used for verifying the K value is selected on line (namely, the driving data of a longer straight line driving road section is selected as verification calculation data by acquiring the driving information in real time).
The K value table is divided into a K value table of the day and a total K value table. The daily K value table can acquire the latest K value verification data, and the total K value table can ensure the stability of the K value.
And finally, updating the K value by adopting an updating formula in the total K value table, so that the stability of the K value is ensured, and the K value can be changed to the latest driving state.

Claims (7)

1. A vehicle odometer online verification method of a vehicle odometer online verification system comprises a GNSS antenna, a pulse type wheel revolution detecting device interface, a GNSS module, an inertial navigation device, a processor, a storage unit and an odometer display screen;
the GNSS module and the inertial navigation device form a basic navigation unit of the integrated navigation system, the processor is used for completing integrated navigation calculation and odometer verification calculation, the storage unit is used for storing verification results and intermediate data elements, and the odometer display screen is used for displaying vehicle driving mileage and verification result information;
the GNSS module, the inertial navigation device, the processor, the storage unit and the odometer display screen are arranged in an odometer of the detected vehicle; the device comprises a GNSS antenna, a pulse type wheel revolution detecting device, an inertial navigation device, a processor, a memory unit and a milemeter display, wherein the GNSS antenna is connected with the GNSS module; the interface of the pulse wheel revolution detecting device is connected with a pulse wheel revolution detecting device of the detected vehicle;
the method is characterized in that:
when the vehicle runs, the processor calculates the running mileage according to the wheel revolution and the initial K value, and the calculation formula of the running mileage of the vehicle is as follows: mileage = wheel revolutions K value;
the method comprises the following steps:
step 1: judging whether the GNSS signal is effective or not, and judging that the vehicle speed is greater than a set threshold value T; if the signal is valid and the vehicle speed is greater than the set threshold value T, executing the step 2, otherwise, continuously detecting and judging until the requirements are met, and then entering the next step;
step 2: processing and storing vehicle running data at fixed time, setting a sliding time window for judging straight line running, and judging whether the vehicle is in a straight line running state according to the running data in the time window;
if the vehicle is in the straight-line driving state, continuously storing the vehicle driving data until the vehicle does not meet the straight-line driving state, judging whether the straight-line driving distance of the vehicle is more than 1 kilometer, if so, executing the step 3, if not, clearing the vehicle driving data, restarting to store the data and judging the straight-line driving state;
when the step is executed, if any one of the situations that the GNSS signal is invalid or the running speed is lower than the threshold value T occurs, the vehicle running data is cleared, and the step 1 is returned again;
wherein the vehicle driving data processed at regular time includes: the attitude angle of the vehicle obtained by the integrated navigation system comprises a pitch angle, a roll angle and a course angle after filtering;
the straight-line running of the vehicle is judged according to the data in the sliding window, and the standards comprise:
a. whether the vehicle is in horizontal travel; that is, whether the pitch angle and the roll angle of the vehicle are smaller than given threshold values, if so, indicating that the vehicle is in a horizontal running state, and if not, indicating that the vehicle is not in the horizontal running state;
b. whether the vehicle runs along one direction, namely whether the course angles of the vehicle are consistent all the time, is within a set threshold value range;
and 3, step 3: calculating a K value and judging whether the K value is valid or not; if the vehicle driving data are valid, executing the step 4, otherwise, clearing the vehicle driving data and returning to the step 1;
wherein, the K value is the driving mileage value L recorded according to the straight driving start of the vehicle start Combined navigation mileage L at the end of straight-line travel end And the accumulated pulse number n of the odometer is calculated, and the formula is as follows:
K＝n*100000/(L end -L start )
wherein the unit of the K value is [ pulse/km ];
judging whether the K value is effective or not, namely judging whether the currently calculated K value is effective or not and judging whether the currently calculated K value is effective or not according to the theoretical value K ini For comparison, the formula is:
Δ＝Abs(K-K ini )/K ini
wherein Abs represents an absolute value;
if the calculated variation delta is larger than a given threshold value, the newly calculated K value is considered to be invalid;
and 4, step 4: calculating the reliability correlation quantity of the K value, and storing the correlation data in a K value table on the current day;
the credibility related quantity of the K value comprises a vehicle running distance, a height range, a course angle range and a speed range which are used for calculating the K value;
the data stored in the K value table of the current day comprises vehicle running starting time, longitude and latitude coordinates of a starting point, longitude and latitude coordinates of a running ending point, a calculated K value, K value reliability, vehicle running average speed, vehicle running average attitude angle, minimum and maximum values of vehicle running speed and minimum and maximum values of vehicle running attitude angle;
and 5: judging whether the vehicle running time reaches 24 hours, namely whether the current day is finished; if not, clearing the driving data, returning to the step 1, and continuously calculating and storing a new K value; if yes, executing step 6;
and 6: if the records in the K value table of the current day exceed the set upper limit value, deleting the records in the table which are sorted from high to low according to the reliability, and then arranging the records which exceed the set upper limit of the records in the record table to enable the number of the records in the K value table to be the upper limit value, and then executing the step 7; if the record is smaller than the set lower limit value, clearing the driving data, returning to the step 1, and continuously calculating and storing a new K value; if the record is between the upper limit and the lower limit, directly executing the step 7;
the reliability is in direct proportion to the driving distance of the vehicle and in inverse proportion to the non-linear uniform speed driving;
the confidence level is calculated according to the following formula:
reliability = coefficient distance traveled/(range of altitude change linear travel range speed change range)
And 7: storing the data in the K value table of the current day into a total K value table;
judging whether the record of the total K value table exceeds a set record upper limit, if so, deleting the K value record which is sorted from near to far according to time and has the earliest time and exceeds the record number upper limit, and maintaining the record number at the upper limit; then calculating whether the standard deviation of the K value in the total K value table is in an allowable range, and if the standard deviation/the average value of the K value is less than 5% in the set allowable range, executing a step 8; otherwise, the running data is cleared without processing, the step 1 is returned, and the data of the next 24 hours is collected;
and 8: judging whether the difference between the K value average value in the total K value table and the currently used K value is larger than a given threshold value or not, if so, executing the step 9, otherwise, not updating the K value, clearing the driving data, and returning to the step 1;
and step 9: and updating the currently used K value, clearing the driving data and returning to the step 1.
2. An on-line verification method for the vehicle odometer of the on-line verification system for the vehicle odometer according to claim 1, wherein in the step 1, when the number of satellites in the navigation system is not less than 4, the GNSS signal is determined to be a valid signal, and the vehicle speed threshold T is not less than 20 km/h.
3. A method for on-line verification of vehicle odometer of the on-line verification system of vehicle odometer according to claim 1, wherein in step 2, the timing time interval is set to 1 second, the size of the sliding time window is determined according to the driving speed, and the window is rolled at 1 movement per second.
4. A vehicle odometer on-line verification method for a vehicle odometer on-line verification system according to claim 1, wherein in step 2, the sliding time window is fixed to 10 seconds in size.
5. An on-line verification method for odometer of vehicle of on-line verification system for odometer of vehicle according to claim 1, wherein the driving data stored in step 2 includes the accumulated driving time t and the number of pulses n of the odometer from the start of entering the straight driving state, the average driving speed of the vehicle, the average attitude angle, the minimum and maximum values of the speed, the minimum and maximum values of the attitude angle, the minimum and maximum values of the altitude, and the time, longitude and latitude coordinates of the vehicle to start the straight driving, the mileage value L calculated by the integrated navigation start And the K value currently used by the odometer.
6. A vehicle odometer online verification method of the vehicle odometer online verification system according to claim 1, wherein the K value updating method in step 9 is: directly replacing the K value average value in the record table.
7. An on-line verification method for the vehicle odometer of the on-line verification system for the vehicle odometer according to claim 1, wherein the K value in step 9 is updated by partially correcting the K value by:
updated K value = α x current K value + (1- α) x K average value, where α is a forgetting factor, and takes a value between [0,1 ].
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