CN110514276B - Method for checking vehicle off-site overrun detection data - Google Patents
Method for checking vehicle off-site overrun detection data Download PDFInfo
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- CN110514276B CN110514276B CN201910763839.3A CN201910763839A CN110514276B CN 110514276 B CN110514276 B CN 110514276B CN 201910763839 A CN201910763839 A CN 201910763839A CN 110514276 B CN110514276 B CN 110514276B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
- G01G19/02—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles
- G01G19/03—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing wheeled or rolling bodies, e.g. vehicles for weighing during motion
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01G—WEIGHING
- G01G23/00—Auxiliary devices for weighing apparatus
- G01G23/01—Testing or calibrating of weighing apparatus
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
- G08G1/0133—Traffic data processing for classifying traffic situation
Abstract
The invention relates to a method for checking vehicle off-site overrun detection data, which comprises the following steps: s1: when the vehicle transports goods, the vehicle passes through a high-speed access detection point and an off-site detection point of a national and provincial road, and a preset weighing system measures related data of the vehicle; s2: the relevant data of the vehicle measured by the weighing system in the step S1 are collected to a cloud platform and participate in calculation; s3: calculating effective deviation according to the summarized data; s4: repeating the steps S1 to S3, obtaining multiple groups of effective deviations and multiple groups of vehicle related data in a preset time range, and judging whether the vehicle related data are effective or not; s5: and analyzing a plurality of groups of effective deviations in the step S4 to judge whether the data detected by the off-site detection points of the national and provinces have the problem of overlarge deviation. The invention sets detection points at the high-speed entrance, and the high-speed entrance is provided with the passing barrier and the lane guide, so that the vehicle passing speed is stable, the driving path is standard, and the test data is more accurate.
Description
Technical Field
The invention relates to the field of traffic management equipment, in particular to a method for checking vehicle off-site overrun detection data.
Background
The measurement data of the off-site detection point location is an important basis for the off-site over-limit transportation administrative penalty, and the validity and the accuracy of the data must be ensured.
The method is characterized in that the dynamic road vehicle automatic weighing apparatus verification of the off-site detection point positions of national and provincial roads is performed once every half year according to verification regulations, and the standards conforming to the standard that the total mass accuracy of the whole vehicle is 10 grades (the vehicle speed is not more than 60 km/h), namely the maximum allowable error is +/-5 percent, or the total mass accuracy of the whole vehicle is 5 grades (the vehicle speed is not more than 60 km/h), namely the maximum allowable error is +/-2.5 percent are taken as the main standards.
The verification of the automatic weighing apparatus of the dynamic road vehicles at the high-speed entrance and exit is performed once every half year according to regulations, but the main standard is that the total mass accuracy of the whole vehicle meets 2 grades (the vehicle speed is not more than 60 km/h), namely the maximum allowable error is plus/1.0 percent, or the total mass accuracy of the whole vehicle meets 1 grade (the vehicle speed is not more than 60 km/h), namely the maximum allowable error is plus/minus 0.5 percent.
When the vehicle is driven on the road of national province, in order to avoid the detection of overrun, the phenomenon of artificial driving abnormity is easy to occur, such as: sudden braking, queuing and passing, long-time weighing, large S driving, repeated weighing, unilateral detour and the like all can cause inaccuracy of weighing data; these abnormal driving phenomena easily cause the damage of the automatic weighing apparatus of the dynamic road vehicle, and can not be found in time.
Disclosure of Invention
In order to solve the problems, the invention provides a method for checking the off-site overrun detection data of the vehicle, which can solve the problem of inaccurate weighing data caused by artificial abnormal driving phenomena and can protect the automatic weighing machine of the dynamic road vehicle from being damaged by abnormal driving behaviors.
The technical scheme of the invention is as follows: a method of verifying vehicle off-site overrun detection data, comprising the steps of: s1: when the vehicle transports goods, the vehicle passes through a high-speed entrance detection point and an off-site detection point of a national and provincial road, and the weighing systems arranged at the two detection points measure the relevant data of the vehicle.
S2: and (5) collecting the relevant data of the vehicle measured by the weighing system in the step S1 to a cloud platform and participating in calculation.
S3: and calculating the effective deviation according to the summarized data and a preset deviation rule.
S4: and repeating the steps S1 to S3, obtaining a plurality of groups of valid deviations and relevant data of a plurality of groups of vehicles within a preset time range, and judging whether the relevant data of the plurality of groups of vehicles are valid.
S5: and analyzing the multiple groups of effective deviations in the step S4, judging whether the data detected by the off-site detection points of the national province roads have the problem of overlarge deviation, and using the weighing data detected by the high-speed entrance detection points for checking the overrun detection data detected by the off-site detection points of the national province roads.
The method includes the steps that when a vehicle passes through a high-speed entrance detection point or an off-site detection point of a national province road, a weighing system arranged at the measurement point measures multiple groups of related data, the data are gathered to a cloud platform end to carry out effective deviation calculation, whether the data detected by the off-site detection point of the national province road have the problem of overlarge deviation or not is judged, effective data are screened out, the weighing data detected by the high-speed entrance detection point are used for checking overrun detection data detected by the off-site detection point of the national province road, overrun detection is carried out on the vehicle, due to the fact that a traffic barrier and a traffic lane guide are arranged at the high-speed entrance, the vehicle traffic speed is stable, the driving path is standard, abnormal driving behaviors cannot occur, and the test data.
Preferably, the relevant data of the vehicle detected by the high-speed entrance/exit detection point comprises a passing time t1, a passing picture, a gross weight w1 of the vehicle and the goods, and the number ax1 of the vehicle shafts; the relevant data of the vehicle detected by the off-site detection point of the national province road comprise passing time t2, passing pictures, gross weight w2 of the vehicle and goods and the number ax2 of the vehicle axle; and simultaneously measuring the longitude and latitude of a high-speed entrance detection point and an off-site detection point of the province road, and respectively recording the measured longitude and latitude as loc1 and loc 2.
Preferably, the method for determining whether the plurality of sets of relevant data of the vehicle are valid in step S4 includes: s4.1: with loc1 and loc2 known, Δ (loc 1-loc 2) can be obtained after docking the map, positioning ranging.
S4.2: the average time delta t of the vehicle running delta (loc 1-loc 2) is calculated according to the average running speed of the vehicle preset in the cloud platform.
S4.3: if the vehicle is driven in the night time, when delta (t 1-t 2) < delta t +8, judging that the passing time t1 and t2 of the vehicle are valid data; when the vehicle is driven in the daytime and delta (t 1-t 2) < delta t +2, the passing time t1 and t2 of the vehicle are judged to be valid data.
S4.4: according to the verification standard, the weight measurement deviation degree of the non-field detection points of the national and provincial roads is +/-5%, w1 is considered to be a theoretical deviation value, when the non-field detection points of the national and provincial roads have deviation, the deviation value is not more than w 1% 5% 2 on the premise that no damage is generated, namely when delta (w 1-w 2) < (w 1% 5), the total weight w1 and w2 of the effective vehicle and goods are judged to be effective data.
S4.5: when any one of the groups of the relevant data of the vehicles t1, t2 and w1, w2 simultaneously satisfies the conditions of S3.3 and S3.4, the group of the relevant data is valid data.
The above calculation results of Δ (loc 1-loc 2) are equivalent to the absolute value of the subtraction of loc1 and loc2, as well as Δ (w 1-w 2).
The deviation degree ± 5% described in the step S3.4 is a verification allowable deviation value of the off-site inspection site of the national and provincial roads, and satisfies a specific verification standard level, while the verification standard of the weighing system of the high-speed entrance/exit inspection site is the highest level, and the verification frequency is also high, so that the deviation is considered to be negligible.
Preferably, the deviation rule in step S3 is that the running distance deviation of the vehicle conforms to the daily vehicle running habit and to the law.
Preferably, the preset time range in step S4 is a time range in which sufficient sampling data can be acquired, which is determined by referring to the periodic vehicle passage record in the section from the entrance/exit detection point to the off-site detection point of the national and provincial road, and the value of the time range is not constant.
More preferably, the vehicle comprises a 2-6 axle freight vehicle which meets the national standard.
The invention has the beneficial effects that: the method of the invention sets detection points at the high-speed entrance, and the high-speed entrance is provided with the passing barrier and the traffic lane guide, so that the vehicle passing speed is stable, the driving path is standard, the test data is more accurate, the data deviation of the non-field detection point positions of the national and provincial roads can be found in time, and the decision and the method for effectively reducing the non-field overrun rate and reducing the occurrence of overrun illegal behaviors are made by the highway administration unit; and abnormal driving phenomenon can not appear at the detection point, whether the dynamic road vehicle automatic weighing apparatus at the point position is damaged or not can be found in time, and the road administration unit is helped to make measures to protect road property.
Drawings
FIG. 1 is a flow chart of the steps of the method of the present invention.
Fig. 2 shows the detection result of the overrun detection data of the vehicle in embodiment 1 of the present invention.
Fig. 3 is a result of detecting overrun detection data of a vehicle passing a national provincial road detection point in embodiment 2 of the present invention.
Detailed Description
Embodiments of the present invention are described below with reference to the accompanying drawings.
Example 1.
As shown in FIG. 1, the present invention provides a method for verifying vehicle off-site overrun detection data, comprising the steps of: the weighing system arranged at the detection point of the high-speed gateway measures the passing time t1, the passing picture, the total weight w1 of the vehicle and the number ax1 of the vehicle axle of the vehicle A, and the weighing system arranged at the off-site detection point of the national province road measures the passing time t2, the passing picture, the total weight w2 of the vehicle and the number ax2 of the vehicle axle of the vehicle A; and simultaneously measuring the longitude and latitude of a high-speed entrance detection point and an off-site detection point of the province road, and respectively recording the measured longitude and latitude as loc1 and loc 2.
And summarizing the measured relevant data of the vehicle A to a cloud platform and participating in calculation.
The valid deviation is calculated according to the summarized data and a preset deviation rule, and whether the data related to the vehicle A is valid or not is judged, and the judgment steps are as follows.
1. And knowing loc1 and loc2, and knowing delta (loc 1-loc 2) according to a docking map and positioning distance measurement.
2. According to the average running speed of the vehicle of 60km/h, the average time Deltat of the running Deltas (loc 1-loc 2) can be calculated.
3. If t1, t2 is 20: 06 for 00-the next day: 00, delta (t 1-t 2) < delta t +8h (night driving).
4. If t1, t2 is 06: 00-20: 00, Δ (t 1-t 2) < Δ t +2 h.
5. If Δ (t 1-t 2) satisfies the condition of step 3 or step 4, it is judged to be valid.
6. According to the verification standard, the weight measurement deviation degree of the off-site detection points of the national and provinces is +/-5% at most, and w1 x 5% is considered as the theoretical deviation value.
7. Assuming that the off-site detection point measurement of provinces has deviation, the deviation value is not more than w1 × 5% × 2 on the premise that no damage is generated, so that delta (w 1-w 2) < (w 1 × 5% × 2) is judged to be effective.
8. When the delta (t 1-t 2) and the delta (w 1-w 2) simultaneously satisfy the step 5 and the step 7, the result is judged to be valid.
The coefficients and parameters in the above operation formula are example values set according to a common theory, and are only description methods, and the actual application is set as required.
The steps are applied to measure and record the relevant data of a plurality of vehicles and perform summary calculation, a plurality of groups of effective deviations in a preset time range are obtained, the plurality of groups of effective deviations are analyzed, whether the data detected by the off-site detection points of the national and provincial roads have the problem of overlarge deviation or not is judged, the weighing data detected by the high-speed access detection points are used for checking the overrun detection data detected by the off-site detection points of the national and provincial roads, and finally, a corresponding data table is obtained on the cloud platform, as shown in fig. 2.
The deviation rule in the above steps means that the deviation of the running distance of the vehicle conforms to the daily vehicle running habit and the routine.
The preset time range in the above steps refers to a time range in which enough sampling data can be acquired by referring to a periodic vehicle passing record in a road section from a high-speed entrance detection point to an off-site detection point of a national road, and the value of the time range is not fixed.
Example 2.
The vehicle passes through a point position 1 in an off-site detection point of a national provincial road on a passing line for transporting a certain cargo, and the point position 1 measures relevant information of the vehicle in the current transportation, including passing time, passing pictures, total weight of the vehicle and the cargo, the number of vehicle axles, weather conditions and the like.
The vehicle passes through a point position 2 of an off-site detection point of a national and provincial road on a passing line for transporting the same time of goods, and the point position 2 also measures related information of the vehicle for the transportation, including passing time, passing pictures, total weight of the vehicle and the goods, the number of vehicle axles, weather conditions and the like.
The vehicle passes through a point 3 of an off-site detection point of a national provincial road on a passing line for transporting the same time of goods, and the point 3 also measures related information of the vehicle in the current transportation, including passing time, passing pictures, total weight of the vehicle and the goods, the number of vehicle axles, weather conditions and the like.
And summarizing data such as the related vehicle transportation condition and the measurement results of passing point positions 1, 2 and 3 in the steps to the cloud platform for calculation.
And according to the summarized data, the influence of weather factors is eliminated by a certain deviation rule, the condition that the transportation goods are changed in the midway of the vehicle is eliminated, the difference of the passing time measured when the vehicle passes through the points 1, 2 and 3 is taken as the calculation time, the average value of the measurement speed is taken as the calculation speed, and when the passing distance of the vehicle and the distances among the points 1, 2 and 3 meet the deviation rule, the measured data in the step are considered to be valid data.
The difference between the average value of the gross weights of the vehicles and the cargos measured at the point positions 1, 2 and 3 and the gross weights of the vehicles and the cargos measured at the point positions 1, 2 and 3 is effective deviation.
The above steps are repeated, and a certain number of effective deviations within a preset time range are collected, as shown in fig. 3.
And analyzing effective deviation, judging whether the detection data of the point positions 1, 2 and 3 has the problem of overlarge deviation or not, and checking the overrun detection data of each point position in the off-site detection points of the national province and the road.
The method for calculating the effective deviation, determining whether the acquired data is effective, the deviation rule and the preset time range in the above steps are the same as those in embodiment 1, and therefore, detailed description is not required here.
The two preferred embodiments of the present invention have been described in detail above. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.
Claims (4)
1. A method for verifying vehicle off-site overrun detection data, comprising the steps of:
s1: when a vehicle transports goods, the vehicle passes through a high-speed entrance detection point and an off-site detection point of a national and provincial road, and related data of the vehicle are measured by weighing systems arranged at the two detection points;
s2: the relevant data of the vehicle measured by the weighing system in the step S1 are collected to a cloud platform and participate in calculation;
s3: calculating effective deviation according to the summarized data and a preset deviation rule;
s4: repeating the steps S1 to S3, obtaining multiple groups of effective deviations and relevant data of multiple groups of vehicles within a preset time range, and judging whether the relevant data of the multiple groups of vehicles are effective or not;
s5: analyzing the multiple groups of effective deviations in the step S4, judging whether the data detected by the off-site detection points of the national province roads have the problem of overlarge deviation, and using the weighing data detected by the high-speed entrance/exit detection points for checking the overrun detection data detected by the off-site detection points of the national province roads;
the relevant data of the vehicle detected by the high-speed entrance/exit detection point comprises passing time t1, passing pictures, total weight w1 of the vehicle and goods and the number ax1 of vehicle axles; the relevant data of the vehicle detected by the off-site detection point of the national province road comprise passing time t2, passing pictures, gross weight w2 of the vehicle and goods and the number ax2 of the vehicle axle; simultaneously measuring the longitude and latitude of a high-speed entrance detection point and an off-site detection point of a provincial road, and respectively recording the longitude and latitude as loc1 and loc 2;
the method for determining whether the plurality of sets of relevant data of the vehicle are valid in step S4 is as follows:
s4.1: with loc1 and loc2 known, Δ (loc 1-loc 2) can be obtained after docking the map, positioning ranging;
s4.2: calculating the average time delta t of vehicle running delta (loc 1-loc 2) according to the preset average running speed of the vehicle in the cloud platform;
s4.3: if the vehicle is driven in the night time, when delta (t 1-t 2) < delta t +8, judging that the passing time t1 and t2 of the vehicle are valid data; if the vehicle is driven in the daytime, when delta (t 1-t 2) < delta t +2, judging that the passing time t1 and t2 of the vehicle are valid data;
s4.4: according to the verification standard, the deviation degree of the weight measurement of the off-site detection points of the national and provincial roads is up to +/-5%, and then w1 is considered as a theoretical deviation value, when the off-site detection points of the national and provincial roads have deviation, the deviation value is not more than w 1% 5% 2 on the premise that no damage is generated, namely when delta (w 1-w 2) < (w 1% 5% 2), the total weight w1 and w2 of the effective vehicle and goods are judged as effective data;
s4.5: when any one of the groups of the relevant data of the vehicles t1, t2 and w1, w2 simultaneously satisfies the conditions of S3.3 and S3.4, the group of the relevant data is valid data.
2. The method for verifying the vehicle off-site overrun detection data as claimed in claim 1, wherein the deviation rule in step S3 is that the running distance deviation of the vehicle conforms to the daily vehicle running habit and the law.
3. The method for verifying the vehicle offsite over-limit detection data according to claim 1, wherein the preset time range in step S4 refers to a reference periodic vehicle passing record in a section from the entrance/exit detection point of the high speed to the offsite detection point of the national and provincial roads, and the time range for obtaining enough sampling data is determined and its value is not fixed.
4. A method for verifying vehicle off-site over-limit detection data as recited in claim 1 wherein said vehicle comprises a 2-6 axle freight vehicle in accordance with national standards.
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| CN2349562Y (en) * | 1998-09-29 | 1999-11-17 | 济南金钟电子衡器股份有限公司 | Weighing apparatus with comparative check |
| JP5904715B2 (en) * | 2011-03-28 | 2016-04-20 | 大和製衡株式会社 | Conveyor scale |
| CN202267529U (en) * | 2011-09-21 | 2012-06-06 | 博爱县电业公司 | Calibration device for electrical belt weigher |
| CN203203696U (en) * | 2013-03-13 | 2013-09-18 | 马钢(集团)控股有限公司 | Cantilever belt weigher material object calibration measurement accuracy automatic realization system |
| JP6305827B2 (en) * | 2014-05-22 | 2018-04-04 | 大和製衡株式会社 | Vehicle weighing scale |
| CN104063906B (en) * | 2014-06-26 | 2016-02-03 | 山东高速股份有限公司 | Modification method of weighing in Free Way Networking weight metering charging |
| US10140618B2 (en) * | 2016-06-21 | 2018-11-27 | International Business Machines Corporation | System, method, and recording medium for vehicle weight detection |
| CN106530737A (en) * | 2016-12-01 | 2017-03-22 | 郑州海为电子科技有限公司 | Non-scene law enforcement high-speed dynamic weighing detection system and method |
| CN108665710A (en) * | 2017-03-31 | 2018-10-16 | 深圳市凯通物流有限公司 | Logistics monitoring method and system based on internet of things |
| CN107525575A (en) * | 2017-07-27 | 2017-12-29 | 沈阳科汇生产力促进中心有限公司 | A kind of hardware computation calibration method of the Internet of Things gravity measure device with automatic calibration function |
| CN108225533A (en) * | 2018-01-16 | 2018-06-29 | 广州发展集团股份有限公司 | A kind of method of calibration of weighing of belt conveyer scale |
| CN108519139A (en) * | 2018-04-27 | 2018-09-11 | 徐州依科电气有限公司 | Belt balance with high precision |
| CN109741607A (en) * | 2018-12-19 | 2019-05-10 | 广东赛诺科技股份有限公司 | A kind of filter method of traffic overrun and overload lorry abnormal data |
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