CN113108808A - Vehicle odometer online verification system and method - Google Patents
Vehicle odometer online verification system and method Download PDFInfo
- Publication number
- CN113108808A CN113108808A CN202110280143.2A CN202110280143A CN113108808A CN 113108808 A CN113108808 A CN 113108808A CN 202110280143 A CN202110280143 A CN 202110280143A CN 113108808 A CN113108808 A CN 113108808A
- Authority
- CN
- China
- Prior art keywords
- value
- vehicle
- odometer
- driving
- running
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
Landscapes
- Engineering & Computer Science (AREA)
- 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
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 for a certain distance L under a standard verification scenecal(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 tripcalThen calculating the K value of the odometer, K being ncal/LcalThe 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: and L is n/K, so that the driving mileage of the vehicle is obtained.
The traditional vehicle odometer verification method comprises a roller-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 (the front wheel rotates) for a period of time, and calculating the K value of a speedometer according to the running mileage calculated by detection equipment and the number of pulses displayed by the speedometer of the taxi.
However, this assay method requires dedicated assay equipment, field, and assay personnel, 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 operation condition.
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" (CN201420363714.4) 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 distance 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 required in 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" (CN201710170212.8), and the chinese master paper "research on GPS-GPRS taxi pricing monitoring system" (china marine university, 2011), methods for measuring and calibrating mileage based on an electronic map using GPS and an electronic map, wireless communication are 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 calibrate the odometer 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, places 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 replacing 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, a vehicle odometer), a combined navigation system (GNSS + INS) is used for automatically calibrating the vehicle odometer, and when the GPS positioning effect is good, a road section meeting the calibration standard and a running state meeting the calibration standard are automatically selected for calibrating the odometer. 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 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.
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: and the driving mileage is equal to the value of the wheel revolution K. 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 an effective signal, and the vehicle speed threshold T is required to be not less than 20 km/h.
Step 2: 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.
Wherein the vehicle driving data processed at regular time includes: 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 at 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 the accumulated running time (seconds) t from the time of entering the straight running state, the pulse number n of the odometer, the average running speed, the average attitude angle and the speed of the vehicleMinimum and maximum values of degree, minimum and maximum values of attitude angle, minimum and maximum values of altitude, time for starting straight-line driving of vehicle, longitude and latitude coordinates, and driving mileage value L calculated by combined navigationstartAnd the K value currently used by the odometer.
And step 3: and calculating the K value and judging whether the K value is effective 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 the driving mileage value L recorded according to the straight driving start of the vehiclestart(unit: centimeter) combined navigation driving range L when finishing straight line drivingend(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/(Lend-Lstart) [ 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 notiniFor comparison, the formula is:
Δ＝Abs(K-Kini)/Kini (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 on the 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 table of the current day at least comprises: 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 current 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.
Step 6: if the records in the K value table of the current day exceed the set upper limit (for example, 10 records), deleting the records in the table sorted from high to low according to the reliability, and then arranging the records which are sorted at the end and exceed the set record upper limit in the record table, so that the number of the records in the K value table is the upper limit, 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.
The reliability is in direct proportion to the running distance of the vehicle and in inverse proportion to the non-linear uniform speed running. The confidence level is calculated according to the following formula:
reliability coefficient driving distance/(height variation range linear driving 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 limit (such as 20) of the records, 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 limit of the record number, and keeping 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 and 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: and the driving mileage is equal to the value of the wheel revolution K. 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: and the driving mileage is equal to the value of the wheel revolution K. 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 roll angle of the vehicle are sampled periodically at 0.2 second intervals, and the data are filtered (e.g., moving average filtered) at 1 second intervals. 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 momentendExecuting the step 3; if not, the vehicle driving data is cleared, and the data is restarted to be stored and the straight line driving is judged.
Whether the vehicle is in straight line driving 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 driving state, and if not, the vehicle is not in the horizontal driving 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 navigationstartAnd the K value currently used by the odometer.
And 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 vehiclestart(unit: centimeter) combined navigation driving range L when finishing straight line drivingend(unit: cm) and the number of accumulated pulses n (unit: pulse) of the odometer. The formula is as follows:
K＝n*100000/(Lend-Lstart) [ 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 notiniFor comparison, the formula is:
Δ＝Abs(K-Kini)/Kini (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., LstartThe mileage for ending straight line travel is 18.3 km, L1520000 cmendWhen the accumulated pulse number n is 1820 and 1830000 cm, K is calculated as: k1820 × 100000/(1830000-. If the current K isiniWith 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 travel mileage, the altitude change range (the maximum altitude minus the minimum altitude), the straight line travel range (the maximum difference of course angles) and the speed change range 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.
Step 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 driving distance/(height variation range linear driving 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 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 data is not processed and the data of the next day is collected in the step 1.
And 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 average 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 current K value table and a total K value table. The day 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 (8)
1. An on-line verification system for a vehicle odometer is characterized by comprising 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 pulse type wheel revolution detecting device interface is connected with a pulse type wheel revolution detecting device of the detected vehicle.
2. An on-line vehicle odometer verification method according to the system of claim 1, wherein the processor calculates the mileage as the vehicle travels based on the number of wheel revolutions and the initial K value, and the vehicle mileage is calculated by the formula: driving mileage is equal to the value of the wheel revolution K;
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 step 3: and calculating the K value and judging whether the K value is effective 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 vehiclestartCombined navigation mileage L at the end of straight-line travelendAnd calculating the accumulated pulse number n of the odometer by the specific formula:
K＝n*100000/(Lend-Lstart) [ 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 notiniFor comparison, the formula is:
Δ＝Abs(K-Kini)/Kini (2)
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 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 reliability 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;
step 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;
wherein, the reliability is in direct proportion to the running distance of the vehicle and in inverse proportion to the non-linear uniform speed running;
the confidence level is calculated according to the following formula:
reliability coefficient driving distance/(height variation range linear driving range speed variation 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; 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: if the standard deviation/K value mean of the K values is less than 5%, executing the 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.
3. An on-line verification method for the vehicle odometer according to claim 2, wherein in 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.
4. An on-line verification method for the vehicle odometer according to claim 2, wherein in step 2, the timing interval is set to 1 second, and the size of the sliding time window is determined according to the running speed, and the window is scrolled by moving 1 time per second.
5. An on-line verification method for the vehicle odometer according to claim 2, wherein in step 2, the sliding time window is fixed to 10 seconds.
6. An on-line verification method for vehicle odometer according to claim 2, 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 speed, 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 at which the vehicle starts to drive straight, the driving mileage value L calculated by the integrated navigation, and the likestartAnd the K value currently used by the odometer.
7. The on-line verification method for the vehicle odometer according to claim 2, wherein the updating method for the K value in step 9 is as follows: directly replacing the K value average value in the record table.
8. An on-line verification method for the vehicle odometer according to claim 2, wherein the K value in step 9 is updated by partially correcting the K value 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 and 1 ].
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110280143.2A CN113108808B (en) | 2021-03-16 | 2021-03-16 | Vehicle odometer online verification system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110280143.2A CN113108808B (en) | 2021-03-16 | 2021-03-16 | Vehicle odometer online verification system and method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113108808A true CN113108808A (en) | 2021-07-13 |
| CN113108808B CN113108808B (en) | 2023-02-10 |
Family
ID=76711360
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110280143.2A Active CN113108808B (en) | 2021-03-16 | 2021-03-16 | Vehicle odometer online verification system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113108808B (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113674450A (en) * | 2021-10-08 | 2021-11-19 | 杭州车厘子智能科技有限公司 | Anti-cheating travel vehicle-mounted intelligent terminal based on artificial intelligence |
| CN114013285A (en) * | 2021-11-08 | 2022-02-08 | 北京理工新源信息科技有限公司 | Method for evaluating actual driving range of electric automobile |
| CN114132339A (en) * | 2021-12-29 | 2022-03-04 | 阿维塔科技(重庆)有限公司 | Automobile display method and system, vehicle and computer storage medium |
| CN114162136A (en) * | 2021-12-29 | 2022-03-11 | 阿维塔科技(重庆)有限公司 | Automobile driving route display method and system, vehicle and computer storage medium |
| CN114659539A (en) * | 2022-03-28 | 2022-06-24 | 安徽博泰微电子有限公司 | Misalignment judgment method for automobile electronic metering equipment |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101545781A (en) * | 2008-03-26 | 2009-09-30 | 高德软件有限公司 | Method for determining pulse equivalent of speedometer in on-board integrated navigation |
| CN102980592A (en) * | 2012-11-27 | 2013-03-20 | 厦门雅迅网络股份有限公司 | Method and device for automatically computing vehicle pulse factor via GPS (global positioning system) longitude and latitude |
| CN106595715A (en) * | 2016-12-30 | 2017-04-26 | 中国人民解放军信息工程大学 | Method and device for calibrating odometer based on strapdown inertial navigation/satellite integrated navigation system |
| CN110411476A (en) * | 2019-07-29 | 2019-11-05 | 视辰信息科技(上海)有限公司 | Vision inertia odometer calibration adaptation and evaluation method and system |
| US20200400821A1 (en) * | 2019-06-21 | 2020-12-24 | Blackmore Sensors & Analytics, Llc | Method and system for vehicle odometry using coherent range doppler optical sensors |
| CN112229422A (en) * | 2020-09-30 | 2021-01-15 | 深兰人工智能(深圳)有限公司 | Speedometer quick calibration method and system based on FPGA time synchronization |
-
2021
- 2021-03-16 CN CN202110280143.2A patent/CN113108808B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101545781A (en) * | 2008-03-26 | 2009-09-30 | 高德软件有限公司 | Method for determining pulse equivalent of speedometer in on-board integrated navigation |
| CN102980592A (en) * | 2012-11-27 | 2013-03-20 | 厦门雅迅网络股份有限公司 | Method and device for automatically computing vehicle pulse factor via GPS (global positioning system) longitude and latitude |
| CN106595715A (en) * | 2016-12-30 | 2017-04-26 | 中国人民解放军信息工程大学 | Method and device for calibrating odometer based on strapdown inertial navigation/satellite integrated navigation system |
| US20200400821A1 (en) * | 2019-06-21 | 2020-12-24 | Blackmore Sensors & Analytics, Llc | Method and system for vehicle odometry using coherent range doppler optical sensors |
| CN110411476A (en) * | 2019-07-29 | 2019-11-05 | 视辰信息科技(上海)有限公司 | Vision inertia odometer calibration adaptation and evaluation method and system |
| CN112229422A (en) * | 2020-09-30 | 2021-01-15 | 深兰人工智能(深圳)有限公司 | Speedometer quick calibration method and system based on FPGA time synchronization |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113674450A (en) * | 2021-10-08 | 2021-11-19 | 杭州车厘子智能科技有限公司 | Anti-cheating travel vehicle-mounted intelligent terminal based on artificial intelligence |
| CN114013285A (en) * | 2021-11-08 | 2022-02-08 | 北京理工新源信息科技有限公司 | Method for evaluating actual driving range of electric automobile |
| CN114013285B (en) * | 2021-11-08 | 2023-11-21 | 北京理工新源信息科技有限公司 | Actual driving range evaluation method for electric automobile |
| CN114132339A (en) * | 2021-12-29 | 2022-03-04 | 阿维塔科技(重庆)有限公司 | Automobile display method and system, vehicle and computer storage medium |
| CN114162136A (en) * | 2021-12-29 | 2022-03-11 | 阿维塔科技(重庆)有限公司 | Automobile driving route display method and system, vehicle and computer storage medium |
| CN114659539A (en) * | 2022-03-28 | 2022-06-24 | 安徽博泰微电子有限公司 | Misalignment judgment method for automobile electronic metering equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113108808B (en) | 2023-02-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113108808B (en) | Vehicle odometer online verification system and method | |
| JP3157923B2 (en) | Distance error correction method for navigation device | |
| US5483456A (en) | Navigation system and a method of calculating GPS measuring deviation | |
| US8326521B2 (en) | Traffic situation determination systems, methods, and programs | |
| CN100578153C (en) | Calibration method for vehicle speed measuring instrument | |
| CN103162689B (en) | The assisted location method of auxiliary vehicle positioning system and vehicle | |
| US6597987B1 (en) | Method for improving vehicle positioning in a navigation system | |
| CN103335655A (en) | Navigator and navigation method | |
| EP3224104A1 (en) | Apparatus and method for vehicle economy improvement | |
| CN111998828B (en) | Road gradient estimation method based on portable GPS | |
| CN101556160B (en) | Onboard navigation system and method capable of realizing vehicle speed signal self-learning | |
| CN104790283A (en) | Quick road surface roughness detection system based on vehicle-mounted accelerometer | |
| CN102980589A (en) | Method and device for automatically computing vehicle pulse factor via GPS (global positioning system) speed | |
| JP2008174193A (en) | Fuel residual quantity display system | |
| WO2010137309A1 (en) | Vehicle position measurement device and vehicle position measurement method | |
| CN204256792U (en) | A kind of taximeter pick-up unit based on high-accuracy position system | |
| CN112629530B (en) | Vehicle positioning method, device, equipment and storage medium | |
| CN111267912B (en) | Train positioning method and system based on multi-source information fusion | |
| CN102980592A (en) | Method and device for automatically computing vehicle pulse factor via GPS (global positioning system) longitude and latitude | |
| CN100510637C (en) | Method for safety early warning for track curve and recording journey in navigation system | |
| CN110285789B (en) | Comprehensive field vehicle detector, detection system and detection method | |
| CN204630738U (en) | Based on inertial navigation motor racing Performance Test System | |
| CN205158456U (en) | Distance measurement and tariff metering apparatus based on global navigation satellite system and inertia subassembly | |
| CN110398243A (en) | A kind of vehicle positioning method and device | |
| CN108151763A (en) | A kind of taximeter in-line calibration method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |