CN-118116094-B - Online verification method for taximeter

CN118116094BCN 118116094 BCN118116094 BCN 118116094BCN-118116094-B

Abstract

The invention discloses an online verification method for taximeters, which relates to the technical field of target verification and comprises the steps of deploying road side sensing equipment to sense vehicles and track targets, constructing a dynamic matching algorithm to analyze and match track data collected in real time, deploying road side ETC equipment to interact with the taximeters in the taximeters, updating the collected track data and the meter data into global data computing equipment in real time through optical fibers, extracting all track data from stored track data, and performing mileage verification and compensation. According to the invention, by deploying road side sensing and ETC equipment, a dynamic matching algorithm is constructed, and the vehicle identity information, the track and the pricing data are combined through the global data computing equipment to carry out mileage verification, so that accurate dynamic detection of the vehicle can be realized under various traffic conditions, anomalies in the track data can be quickly identified and corrected, high-precision calculation of the verification mileage of the pricing device is ensured, and the accuracy and the instantaneity of the verification method are remarkably improved.

Inventors

WU YANG
LI ZHI
YANG XUEKAI
GUO LEI
ZHANG LIN
LIU JIAJING
HAN CHAO
DAI JINZHOU
Lv Qingbin
YAO YAO
Zhou Bichen
ZHONG YING

Assignees

北京市计量检测科学研究院

Dates

Publication Date: 20260512
Application Date: 20240325

Claims (9)

1. An online verification method for a taximeter is characterized by comprising the steps of, Deploying road side sensing equipment to sense a vehicle and tracking a target; Constructing a dynamic matching algorithm to analyze and match the track data collected in real time; deploying the road side ETC equipment to interact with the taximeter in the taxi; Updating the collected track data and the meter data into the global data computing equipment in real time through an optical fiber; Extracting all track data from the stored track data and performing mileage verification and compensation; The construction dynamic matching algorithm is used for analyzing and matching track data collected in real time for constructing the dynamic matching algorithm and selecting an optimal track: calculating trajectory similarity scores Expressed as: Wherein, the Is the similarity score between the trajectory r and the preset trajectory r', Representing the position vector of the real-time trajectory at time t, Representing the position vector of the preset trajectory at time t, a and b representing the considered time period, Is a real-time track And a preset track Squaring the Euclidean distance at time t; Calculating dynamic weights for time windows Expressed as: Wherein, the Is a normalization factor that is used to normalize the data, Is the magnitude of the nth fourier component, Is the frequency of the nth component, Is the phase of the nth component, Is the coefficient of the mth wavelet component, Is based on translation parameters As the m-th wavelet function of the center, Is the decay rate, t is the time, Is the current point in time; calculating geographic information weights Expressed as: Wherein, the And Respectively representing the geographical coordinates of the real-time trajectory r and the preset trajectory r', Representing the maximum geographic location difference under consideration, And The average altitude of the real-time track and the preset track are respectively represented, Is the maximum altitude difference; Analysis of speed variation Expressed as: Wherein, the The speed is indicated by the velocity of the light, The acceleration is indicated by the fact that, The rate of change of the acceleration is indicated, Representing the function of the standard deviation of the signal, Is a hyperbolic tangent function; comprehensive construction dynamic matching algorithm Expressed as: Wherein, the Is a dynamic matching score that is a function of the matching score, And Is the weight coefficient of the weight of the object, Is a score for the similarity of the trajectories, Is the dynamic weight of the time window, Is a weight of the geographic information, The speed change analysis is carried out, and the track with the highest matching score is selected as the optimal track.
2. The online verification method of taxi meters according to claim 1, wherein the deployment roadside sensing device senses that the vehicle is deployed on a selected road section, a license plate capturing camera is deployed on the roadside sensing device at the first starting point, and the roadside sensing device senses the vehicle as basic information of a target capturing target after the vehicle passes through the starting point position.
3. The online verification method of the taxi meter of claim 2, wherein the tracking of the target is to unify the identity of the target information perceived at the front and rear moments, assign a unique ID to the perceived target, trigger a snapshot instruction to the target when the target passes through a snapshot area, acquire a head photo and identify a license plate, and bind the perceived target ID with license plate information to obtain a perceived target ID-license plate number.
4. The online verification method of taxi meters according to claim 3, wherein the step of deploying the road side ETC device to interact with the taximeters in the taxi is to enable the road side ETC device to interact with the taximeter device in the taxi in a selected road section, when the taxi passes through an ETC trigger area of a verification starting point, the taxi meters upload own data to the ETC device, the ETC antenna starts to interact with the real-time passing taxi meters, the mileage calculated by the meters is reset to 0, and the moment is taken as the verification starting point moment to establish a meter mileage information dictionary.
5. The online verification method of the taxi meter of claim 4, wherein the collected track data and meter data are updated to the global data computing device in real time through optical fibers, all road side sensing device information is received through optical fibers, sensing data at front and rear moments and in a plurality of different detection ranges are endowed with unique identity global IDs through target tracking, track data under a global ID target are obtained, the track data obtained in real time are associated with license plate numbers to obtain the global target ID-sensing target ID-license plate number, the associated data are saved and a folder is named as the global ID, initializing operation is carried out on road side ETC devices when the global data computing device is started, the primary power of the ETC antennas is set, GPS time service is carried out on the ETC antennas, and the meter data uploaded by the ETC devices are received.
6. The online verification method of the taximeter according to claim 5, wherein extracting all track data from the stored track data comprises searching the stored taxi track data in the global data computing device according to license plate number information of the taximeter data dictionary, finding a taxi track data folder, traversing time information Tt corresponding to the track data, comparing with all mileage moments in the taximeter data dictionary, finding track time Tt corresponding to the mileage moments, including T0, T1, T2, T3 and T4, and sequentially obtaining all track data among the initial moments corresponding to the track data according to T0-T1, T0-T2, T0-T3 and T0-T4.
7. The online verification method of taxi meters of claim 6, wherein the steps of performing mileage verification and compensation include clustering the trajectory data during calculation, merging the repeated points into one trajectory point, and calculating verification mileage: Wherein L is the verification mileage, Is the value of the i-th abscissa, Is the value of the ith ordinate, Is the first The values of the individual abscissas are, Is the first Values of the respective ordinate; And (3) verifying mileage compensation: Wherein, the Is the time difference of the initial moment of time, Is the initial moment of the track and, Is the initial moment of the mileage, Is the time difference of the time n, Is the time n of the track, Is the time n of the mileage, Is the mileage compensation at the initial moment, Is the speed of the vehicle at the 0 point of the track, Is the mileage compensation for the time n, Is the speed of the vehicle at the point n of the trajectory, Is the verification mileage after the compensation, Is to verify the mileage of the user, Is the mileage of the price meter, Is the percentage of error; judging the accuracy of the price calculator according to the error percentage: If the error percentage is smaller than the specified error range, the description price calculator is accurate, the price calculator is marked to be qualified in verification, verification results are recorded in detail and recorded in files, and a periodic verification plan of the price calculator is formulated; if the error percentage is larger than the specified error range, the price meter is inaccurate, the price meter is marked to be unqualified in verification, the price meter is immediately stopped for use, the specific problem of the price meter is detected, the price meter is calibrated and maintained, and the price meter is re-verified after the calibration and maintenance.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, carries out the steps of the method for online verification of a taxi meter according to any one of claims 1 to 7.
9. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the taxi meter online verification method of any one of claims 1 to 7.

Description

Online verification method for taximeter Technical Field The invention relates to the technical field of target verification, in particular to an online verification method for a taximeter. Background For the forced verification work of taximeters carried out in China, the existing taximeter verification method mainly comprises a roller ranging method and a driving ranging method, the method needs to verify that a taxi is going to a specific detection site, the traditional method is mostly dependent on manual operation, the methods are long in time consumption, high in cost and low in efficiency, the problems that the taxi is easy to be gathered and jammed, normal operation of the taxi is affected, carbon emission is too large, remote price adjustment is not supported are solved, complex and changeable traffic conditions are difficult to deal with in the implementation process, the method is easy to be affected by environmental factors, the requirements of efficient, accurate and real-time verification cannot be met, and with the development of intelligent network technology, the laser radar sensor detection, the real-time track tracking positioning technology, the road cooperation and other new technology are applied, a reliable technical basis is provided for online verification of the taximeter. Disclosure of Invention The present invention has been made in view of the above-mentioned problems occurring in the existing online verification method of taximeters. Therefore, the problems to be solved by the invention are that the traditional methods depend on manual operation, are long in time consumption, high in cost and low in efficiency, have the problems of easily causing taxi aggregation congestion, influencing normal operation of taxis, being too large in carbon emission and not supporting remote price adjustment, are difficult to cope with complex and changeable traffic conditions in the implementation process, are easily influenced by environmental factors, and cannot meet the requirements of efficient, accurate and real-time verification. The technical scheme includes that a road side sensing device is deployed to sense a vehicle and track targets, a dynamic matching algorithm is constructed to analyze and match track data collected in real time, road side ETC equipment is deployed to interact with a taximeter in the taxi, the collected track data and the data of the taximeter are updated to a global data computing device in real time through optical fibers, and all track data are extracted from stored track data and subjected to mileage verification and compensation. The method for online verification of the taximeter is characterized in that the road side sensing equipment is used for sensing the vehicle to deploy road side sensing equipment in a selected road section, a license plate capturing camera is deployed in the road side sensing equipment at the first starting point, and when the vehicle passes through the starting point position, the road side sensing equipment senses the vehicle and then takes the vehicle as basic information of a target capturing target. The taxi meter online verification method comprises the following steps of carrying out target tracking, namely carrying out identity unification on target information perceived at the front and rear moments, endowing a unique ID for a perceived target, triggering a snapshot instruction on the target when the target passes through a snapshot area, acquiring a vehicle head photo, identifying a license plate, and binding the perceived target ID with license plate information to obtain a perceived target ID-license plate number. As a preferable scheme of the online verification method of the taxi meter, the invention comprises the steps that the dynamic matching algorithm is constructed to analyze and match track data collected in real time to select an optimal track: calculating trajectory similarity scores Expressed as: ; Wherein, the Is the similarity score between the trajectory r and the preset trajectory r',Representing the position vector of the real-time trajectory at time t,Representing the position vector of the preset trajectory at time t, a and b representing the considered time period,Is a real-time trackAnd a preset trackSquaring the Euclidean distance at time t; Calculating dynamic weights for time windows Expressed as: ; Wherein, the Is a normalization factor that is used to normalize the data,Is the magnitude of the nth fourier component,Is the frequency of the nth component,Is the phase of the nth component,Is the coefficient of the mth wavelet component,Is based on translation parametersAs the m-th wavelet function of the center,Is the decay rate, t is the time,Is the current point in time; calculating geographic information weights Expressed as: ; Wherein, the AndRespectively representing the geographical coordinates of the real-time trajectory r and the preset trajectory r',Representing the maximum geographic loca