CN-121980513-A - New energy truck bill and track fusion acquisition method and system

CN121980513ACN 121980513 ACN121980513 ACN 121980513ACN-121980513-A

Abstract

The application provides a new energy wagon bill and track fusion acquisition method and system, and relates to the technical field of data processing. The method comprises the steps of obtaining vehicle CAN speed data, GNSS positioning time sequence data and transportation business bill data, identifying a vehicle target state and determining a target analysis section, then determining a bill constraint window by combining the bill data, taking an intersection set as a candidate analysis section with the target analysis section, then identifying GNSS and CAN static and dynamic conflict sections based on GNSS data time sequence and speed characteristics, calculating a compensation confidence index reflecting data distortion degree, judging and determining a section to be compensated, finally implementing business constraint on mileage compensation amount according to the bill data, correcting track mileage data and outputting a fusion acquisition result. By carrying out credible correction on the track mileage under the document constraint, the authenticity and traceability of track data in a transportation service scene can be improved.

Inventors

JIANG MINGHUI
LU JIANXIN
WANG KANGKANG
ZHANG YUXI

Assignees

江苏零浩网络科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260126

Claims (10)

1. The new energy truck bill and track fusion acquisition method is characterized by comprising the following steps of: acquiring vehicle CAN speed data, GNSS positioning time sequence data and bill data of transportation service of a target vehicle; identifying a target state of a vehicle based on the vehicle CAN speed data, and determining a target analysis section corresponding to the target state; Determining a bill constraint window based on the bill data, and determining an intersection of the target analysis section and the bill constraint window as a candidate analysis section; in the candidate analysis section, determining a time section meeting a preset difference condition as a GNSS and CAN static and dynamic conflict section based on time sequence characteristics and speed characteristics of the GNSS positioning time sequence data; Generating a compensation confidence index for representing the distortion degree of the GNSS and CAN static and dynamic conflict section data based on the quality characteristics of the GNSS positioning time sequence data in the GNSS and CAN static and dynamic conflict section; Judging whether the GNSS and CAN static and dynamic conflict section meets a preset judging condition according to the compensation confidence index, and determining the GNSS and CAN static and dynamic conflict section meeting the preset judging condition as a section to be compensated; Determining a section mileage compensation amount based on the duration time and the space position information of the section to be compensated, wherein the section mileage compensation amount is constrained by the document data; and correcting the vehicle track mileage data based on the section mileage compensation amount to obtain a compensated track mileage output result.
2. The new energy wagon bill and track fusion collection method according to claim 1, wherein the bill data comprises a loading and unloading timestamp set, a starting point geofence, an ending point geofence, a bill mileage and loading and unloading weight information, and the determining the bill constraint window based on the bill data comprises: performing median absolute deviation screening on the loading and unloading timestamp set to eliminate outlier time points, and generating a shrinkage loading and unloading time window; Performing anisotropic morphological expansion according to expansion coefficients different from a major axis and a minor axis based on geometric major axes of the starting point geofence and the ending point geofence to form a space buffer zone; And constructing a constraint elliptical belt which takes the connecting line of the centroid of the starting point geofence and the centroid of the ending point geofence as a long axis and has the length of the long axis proportional to the document mileage according to the document mileage, and determining the intersection of the shrinkage loading and unloading time window and the space buffer belt and the constraint elliptical belt as a document constraint window.
3. The new energy wagon bill and track fusion acquisition method as defined in claim 2, wherein the anisotropic morphological expansion comprises: Calculating a second-order center moment based on the boundary point set of the starting point geofence and the ending point geofence to construct a covariance matrix, and obtaining a geometric principal axis and a geometric auxiliary axis and corresponding standard deviations thereof through feature decomposition; Setting a major axis expansion radius as an increasing function of a standard deviation of the major axis and an azimuth sequence circular variance calculated based on the GNSS positioning time sequence data in the bill constraint window, setting a minor axis expansion radius as a decreasing function of a standard deviation of the minor axis and a boundary curvature absolute value of the geofence, and contracting a boundary section with a curvature exceeding a preset curvature threshold according to the decreasing function; And then carrying out morphological expansion by adopting elliptical structural elements with the major axis direction consistent with the geometric major axis and the major axis radius and the minor axis radius respectively as the major axis expansion radius and the minor axis expansion radius to form the space buffer zone.
4. The new energy wagon bill and track fusion acquisition method according to claim 1, wherein the target state comprises a vehicle stationary state, and the vehicle stationary state is determined based on the vehicle CAN speed data being lower than a preset speed threshold; the timing characteristics include sampling intervals of the GNSS positioning timing data, and the velocity characteristics include GNSS derived velocities determined based on the GNSS positioning timing data; the meeting of the preset difference condition includes that the GNSS derived speed is greater than a first speed threshold and a sampling interval of the GNSS positioning time sequence data is greater than a conventional sampling threshold.
5. The new energy wagon bill and trajectory fusion collection method according to claim 4, wherein the conventional sampling threshold is used for representing whether the GNSS positioning time sequence data is in an energy-saving sleep state.
6. The new energy wagon bill and track fusion acquisition method according to claim 1, wherein the quality features comprise at least one of a GNSS positioning accuracy index and a time sequence cavity feature; the time sequence hole feature comprises a sampling hole duration or sampling interval proportion exceeding a preset sampling interval, and the determining the section mileage compensation amount based on the duration and the space position information of the section to be compensated comprises the following steps: identifying an effective travel zone that is temporally adjacent to the zone to be compensated; determining a compensation reference speed of the section to be compensated based on the average running speed of the effective running section; calculating the mileage compensation amount of the initial section according to the compensation reference speed and the duration of the section to be compensated; And combining the bill data, and determining the section mileage compensation amount based on the initial section mileage compensation amount.
7. The new energy wagon bill and track fusion collection method according to claim 6, wherein the determining the section mileage compensation amount based on the initial section mileage compensation amount in combination with the bill data includes: Extracting bill mileage information from the bill data; determining a mileage constraint threshold based on the document mileage information; And comparing the initial section mileage compensation amount with the mileage constraint threshold value to obtain a comparison result, and determining the section mileage compensation amount based on the comparison result and a preset constraint rule.
8. The new energy wagon bill and track fusion acquisition method according to claim 7, wherein the determining the section mileage compensation amount based on the comparison result and a preset constraint rule includes: Determining the zone mileage compensation amount as the mileage constraint threshold value in response to the comparison result indicating that the initial zone mileage compensation amount is greater than the mileage constraint threshold value; and determining the initial section mileage compensation amount as the section mileage compensation amount in response to the comparison result indicating that the initial section mileage compensation amount is less than or equal to the mileage constraint threshold value.
9. The new energy wagon bill and track fusion acquisition method according to claim 1, further comprising: Based on the boundary of the bill constraint window, respectively shifting inwards and outwards by a preset boundary distance to form a buffer zone, and determining the union of the inner buffer zone and the outer buffer zone as a boundary neighborhood; Calculating a boundary correction factor for the GNSS and CAN static and dynamic conflict section intersected with the boundary neighborhood based on the quality characteristics of the GNSS positioning time sequence data and the nearest distance between the GNSS and CAN static and dynamic conflict section and the boundary of the bill constraint window, and combining the compensation confidence index with the boundary correction factor to obtain a boundary weighted compensation confidence index; determining the corresponding GNSS and CAN static and dynamic conflict section as the section to be compensated according to the boundary weighting compensation confidence index meeting a boundary judgment condition; When determining the section mileage compensation amount, limiting the section mileage compensation amount to be the smallest value of the compensation amount constrained by the document data and the geometric upper bound determined based on the section head-end position information to be compensated for the section to be compensated intersecting with the boundary neighborhood.
10. New energy truck bill and track fusion acquisition system, its characterized in that includes: The acquisition module is used for acquiring vehicle CAN speed data, GNSS positioning time sequence data and bill data of transportation service of the target vehicle; The processing module is used for identifying the target state of the vehicle based on the CAN speed data of the vehicle, determining a target analysis section corresponding to the target state, determining a bill constraint window based on the bill data, and determining the intersection of the target analysis section and the bill constraint window as a candidate analysis section; the compensation module is used for generating a compensation confidence coefficient index used for representing the distortion degree of the GNSS and CAN static and dynamic conflict section data based on the quality characteristics of the GNSS positioning time sequence data in the GNSS and CAN static and dynamic conflict section, judging whether the GNSS and CAN static and dynamic conflict section meets a preset judging condition according to the compensation confidence coefficient index, determining the GNSS and CAN static and dynamic conflict section meeting the preset judging condition as a section to be compensated, determining a section mileage compensation amount based on the duration time and the space position information of the section to be compensated, wherein the section mileage compensation amount is constrained by the receipt data, and correcting vehicle track mileage data based on the section mileage compensation amount to obtain a compensated track mileage output result.

Description

New energy truck bill and track fusion acquisition method and system Technical Field The application relates to the technical field of data processing, in particular to a new energy truck bill and track fusion acquisition method and system. Background In the monitoring, reporting and verifying mechanism related to carbon emission transaction, the consistency among time, space position, driving mileage and business bill of the transportation process is often used for supporting the authenticity verification of the transportation activity and the compliance of the emission verification caliber. In the traffic and transportation service data verification and carbon emission accounting scenarios, track acquisition is generally required to be performed by combining GNSS (global navigation satellite system) positioning data with vehicle state data, so as to ensure the authenticity and data accuracy of transportation service. However, in the actual transportation scene of the new energy truck, especially when the vehicle is in a static state or a low-speed slow-moving state near a park or a loading and unloading site, the GNSS positioning system is easily influenced by signal shielding, terminal energy-saving dormancy, downsampling or signal drift to generate positioning errors or false speeds, so that GNSS positioning data are obviously inconsistent with the actual state of the vehicle, thus causing track mileage calculation errors, and reducing data accuracy and reliability. Therefore, how to handle the mileage error caused by inconsistent GNSS positioning data and the actual state of the vehicle in the process of vehicle track acquisition, so as to improve the accuracy and reliability of the data in the transportation service scene, is a technical problem to be solved urgently. Disclosure of Invention Aiming at the defects of the prior art, the application provides a new energy truck bill and track fusion acquisition method and system. In a first aspect, the application provides a new energy wagon bill and track fusion acquisition method, which comprises the following steps: acquiring vehicle CAN speed data, GNSS positioning time sequence data and bill data of transportation service of a target vehicle; identifying a target state of a vehicle based on the vehicle CAN speed data, and determining a target analysis section corresponding to the target state; Determining a bill constraint window based on the bill data, and determining an intersection of the target analysis section and the bill constraint window as a candidate analysis section; in the candidate analysis section, determining a time section meeting a preset difference condition as a GNSS and CAN static and dynamic conflict section based on time sequence characteristics and speed characteristics of the GNSS positioning time sequence data; Generating a compensation confidence index for representing the distortion degree of the GNSS and CAN static and dynamic conflict section data based on the quality characteristics of the GNSS positioning time sequence data in the GNSS and CAN static and dynamic conflict section; Judging whether the GNSS and CAN static and dynamic conflict section meets a preset judging condition according to the compensation confidence index, and determining the GNSS and CAN static and dynamic conflict section meeting the preset judging condition as a section to be compensated; Determining a section mileage compensation amount based on the duration time and the space position information of the section to be compensated, wherein the section mileage compensation amount is constrained by the document data; and correcting the vehicle track mileage data based on the section mileage compensation amount to obtain a compensated track mileage output result. Optionally, the bill data comprises loading and unloading timestamp sets, a starting point geofence, a finishing point geofence, bill mileage and loading and unloading weight information, and the determining the bill constraint window based on the bill data comprises: performing median absolute deviation screening on the loading and unloading timestamp set to eliminate outlier time points, and generating a shrinkage loading and unloading time window; Performing anisotropic morphological expansion according to expansion coefficients different from a major axis and a minor axis based on geometric major axes of the starting point geofence and the ending point geofence to form a space buffer zone; And constructing a constraint elliptical belt which takes the connecting line of the centroid of the starting point geofence and the centroid of the ending point geofence as a long axis and has the length of the long axis proportional to the document mileage according to the document mileage, and determining the intersection of the shrinkage loading and unloading time window and the space buffer belt and the constraint elliptical belt as a document constraint window. Optionally, the anisotropic morpho