CN113990078A - Multi-source information judgment-based highway vehicle overrun detection method and system and storage medium - Google Patents
Multi-source information judgment-based highway vehicle overrun detection method and system and storage medium Download PDFInfo
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Abstract
A method, a system and a storage medium for detecting vehicle overrun on a highway based on multi-source information judgment comprise first judgment of whether vehicles overrun and second judgment of whether vehicles overrun, second judgment of whether vehicles overrun and calculation of a weighted value Q and a matching degree between exit stations according to the similarity of feature information ZC of a current exit station of a vehicle and exit station passing records RC of historical passing information, and combination of historical passing information RV of the vehicle and current overrun information Vmax of the vehicle. According to the invention, on the basis of data sampling, a big data analysis and correction algorithm is introduced, and the transfinite system has an intelligent processing and judging function through a feedback repair mechanism, so that the accuracy is higher and is close to the most real actual use level particularly along with the long-term application of big data.
Description
Technical Field
The invention relates to the technical field of regulation road vehicle overrun control, in particular to a method and a system for detecting overrun of vehicles on a highway based on multi-source information judgment and a storage medium.
Background
With the implementation of a large amount of Chinese capital construction, the highway becomes an important traffic route, and a large amount of freight vehicles run on the highway. The boxer driver usually wants to increase the income of single transportation for economic benefit, so more goods are transported, but the overloading behaviors including overweight, superelevation, superwidth, superlength and the like of the vehicle are not allowed no matter from the angle of safe driving or the angle of road maintenance. Traditional detection means often can only detect vehicle overrun action under the simpler condition, and the condition of lou examining, false retrieval takes place occasionally simultaneously, in order to improve the precision that detects, often needs complicated check out test set for check out test set's expense is expensive. Often invest in huge expense, can not obtain satisfactory detection effect, simultaneously, huge investment also wastes national resources. If the overrun behavior of the vehicle cannot be judged effectively and economically, driving safety cannot be guaranteed, and misjudgment on a driver is possibly caused, so that the vehicle overrun detection method based on the big data is provided, accurate judgment on the overrun vehicle is achieved, and good economic performance indexes are achieved.
Disclosure of Invention
The invention aims to provide a method, a system and a storage medium for detecting vehicle overrun on a highway based on multi-source information judgment.
The invention is realized by the technical scheme, which comprises the following steps:
1) defining station characteristic information ZC for each exit of the expressway;
2) acquiring license plate information and overrun information Vmax of a passing vehicle at a target exit site;
3) comparing the overrun information Vmax with threshold values V0 and VC respectively to obtain first judgment on whether the vehicle is overrun, if not overrun, releasing, and if overrun, turning to step 4);
4) according to the license plate information of the vehicle, calling historical information R of the vehicle passing through an exit station of the highway in a historical record within a specified time period FCT;
5) and calculating a weight value Q and a matching degree between each exit station according to the similarity of the feature information ZC of the current exit station of the vehicle and the exit station passing record RC of the historical passing information, and judging whether the vehicle is out of limit for the second time by combining the historical passing information RV of the vehicle and the current out-of-limit information Vmax of the vehicle.
Further, the site characteristic information ZC in step 1) includes the following: station size information ZC1, lane width information ZC2, lane height information ZC3, and lane depth information ZC 4.
Further, the overrun information Vmax in step 2) includes the following contents: a maximum width Wmax of the vehicle, a maximum height Hmax of the vehicle, a maximum length Lmax of the vehicle and a maximum weight Gmax of the vehicle.
Further, the specific method for the first judgment on whether the vehicle is out of limit in the step 3) is as follows:
if Vc < Vmax < ═ V0, the limit is not exceeded; if Vmax < Vc, the sampled data is abnormal; if Vc < Vmax, the first judgment is overrun.
Further, the history information R in step 4) includes the following contents: a historical exit station passage record RC passed by the vehicle; the past exit site information RC for the vehicle to pass through includes the exit site feature code RZT, the detection value RV at the time of passing, and the passing time RRT.
Further, the specific method for judging whether the vehicle is out of limit for the second time in the step 5) is as follows:
5-1) obtaining the current weight Q of each historical exit station passed by the vehicle;
5-2) comparing the similarity F of the target exit station characteristic information ZC and the historical exit station traffic record RC;
5-3) substituting the similarity F into a self-defined judgment formula to judge whether the secondary vehicle exceeds the limit;
the historical exit station weight Q in the step 5-1) is a preset value QI in an initial state, and is dynamically adjusted in the running process, wherein the adjustment formula is QM (QM) QI + (ZP1/ZPT), wherein ZP1 is the total times that the vehicle passes through the station, and ZPT is the total times that the vehicle passes through all stations;
the calculation formula of the current weight Q of the vehicle passing through the historical exit station is as follows: q is QM (ZCP1/ZCPT), where ZCP1 is the total number of times that the vehicle passes through the station at the current time, and ZCPT is the total number of times that the vehicle passes at the current time;
the specific formula for comparing whether the similarity F between the target exit station characteristic information ZC and the historical exit station traffic record RC meets the requirement in the step 5-2) is as follows: f ═ ZRF1+ ZRF2+. ZRFM)/M, where ZRF1 ═ (1- | ZC1-RC1|/ZC1) × 100%, ZRFM ═ 100%;
the specific method for judging whether the secondary vehicle exceeds the limit in the step 5-3) comprises the following steps:
making the total passing frequency I equal to 0, and making the allowed passing frequency PB;
selecting a history record of F × Q ═ PA, obtaining a pass value RV, and if Vmax < RV, then I ═ I + 1; if the calculated result is I > - < PB >, the calculation result is not overrun, namely the historical similar conditions are released, otherwise, the calculation result is overrun.
Further, the expressway vehicle overrun detection system based on multi-source information judgment comprises a cloud subsystem and a local subsystem, wherein remote communication is performed between the cloud subsystem and the local subsystem;
the cloud subsystem comprises a site information base, an alarm record base, a vehicle information base, a traffic record base and a cloud analysis module; the site information base is used for storing outlet site characteristic information ZC; the alarm record library is used for storing the historical overrun records of the vehicle; the vehicle information base is used for storing vehicle license plate information and overrun information Vmax; the passage record library is used for storing the passage record RC of the historical exit station passed by the vehicle; the cloud analysis module is used for calculating first judgment and second judgment of whether the vehicle is out of limit;
the system comprises a local subsystem and a cloud subsystem, wherein the local subsystem comprises a local processor, a height detector, a length detector, a license plate recognizer, a weight detector and a width detector, the height detector, the length detector, the license plate recognizer, the weight detector and the width detector are in data interaction with the local processor, and the local processor is in data interaction with the cloud subsystem.
Further, a computer-readable storage medium storing computer-executable instructions for a computer to perform the method for detecting vehicle overrun on an expressway based on multi-source information determination according to any one of claims 1 to 6.
Due to the adoption of the technical scheme, the invention has the following advantages:
the method is different from the traditional overrun monitoring method, and introduces a big data analysis correction algorithm on the basis of data sampling, so that data is intelligently analyzed, an alarm can be given in time, and an overrun system has an intelligent processing and judging function through a feedback repairing mechanism, so that the overrun judgment with higher precision is realized through a software method, the problem is efficiently and timely found and solved by an overrun manager, and meanwhile, the error report is avoided, and particularly along with the long-term application of the big data, the accuracy is higher and is close to the real actual use level.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof.
Drawings
The drawings of the present invention are described below.
Fig. 1 is a schematic block diagram of communication between a cloud subsystem and a local subsystem according to the present invention;
FIG. 2 is a schematic block diagram of the communication between a plurality of sites and a cloud subsystem;
FIG. 3 is a flow chart of the overrun detection of the present invention;
fig. 4 is a flowchart of the matching degree calculation.
Detailed Description
The invention is further illustrated by the following figures and examples.
Example (b):
and each site from the station 1 to the station N is provided with a local processor, an overrun detector and a license plate recognizer, and each local recognizer is in remote communication with the cloud analysis system.
Defining FCT 30 days, station characteristic dimension N6, T1 station size, T2 station height, T3 station width, T4 station length, T5 station geographical information, T6 station security level. A comparison feature array is defined, where M is 3, C1 is T2, C2 is T3, and C3 is T4. PA is 0.95 and PB is 1.
For the example station definition, the station 1 attributes are: ZT1 ═ 5, ZT2 ═ 6, ZT3 ═ 12, ZT4 ═ 30, ZT5 ═ 2, ZT6 ═ 4, Q1 ═ 1;
the station 2 attributes are: ZT1 ═ 4, ZT2 ═ 6, ZT3 ═ 8, ZT4 ═ 25, ZT5 ═ 1, ZT6 ═ 0, Q2 ═ 0.8; the station 3 attributes are: ZT1 ═ 6, ZT2 ═ 7, ZT3 ═ 15, ZT4 ═ 30, ZT5 ═ 2, ZT6 ═ 4, Q3 ═ 1.2; the station 4 attributes are: ZT1 is 5, ZT2 is 6, ZT3 is 11.8, ZT4 is 29, ZT5 is 2, ZT6 is 3, and Q4 is 1.
When a vehicle enters a station, the width detector continuously detects the change, and transmits the detected width value to the local processor, and the local processor acquires the maximum width value Wmax of the vehicle in real time; meanwhile, the height detector continuously detects the change and transmits the detected height value to the local processor, and the local processor acquires the maximum height value Hmax of the vehicle in real time; the length detector continuously detects the change, and transmits the detected length value to the local processor, and the local processor acquires the maximum length value Lmax of the vehicle in real time; the weight detector continuously detects changes, the detected weight value is transmitted to the local processor, and the local processor acquires the maximum weight Gmax of the vehicle in real time. Meanwhile, the license plate recognizer recognizes the license plate of the vehicle and transmits the license plate number to the local processor. The invention can select the vehicle overrun information to measure, and can also be other vehicle overrun information.
The local processor transmits the geographic coordinates, the license plate number, the Wmax, the Hmax, the Lmax and the Gmax which are acquired from the GPS or the Beidou to the cloud analysis system; the cloud analysis system obtains vehicle information from a vehicle information base according to the license plate number, obtains corresponding station information from the station information base according to the geographic coordinate, obtains the historical record of the vehicle passing the station from a traffic record base according to the license plate number and the geographic coordinate, and respectively judges whether the width, the height, the length and the weight are out of limit according to the station out-of-limit detection flow of the figure 2.
The cloud analysis system obtains the passing track of the vehicle from the passing record library according to the license plate number, and judges whether the width, the height, the length and the weight are out of limit respectively according to the vehicle track out-of-limit detection flow shown in the figure 3.
The cloud analysis system processes according to the overrun inspection result: 1. if the exceeding limit is detected, the exceeding limit record is stored in an alarm record library, and the exceeding limit result is notified to the local processor; 2. if not, the pass record is saved in a pass record library, and the local processor is informed of the result of not exceeding the limit.
The local processor informs the owner of the vehicle according to the received processing result, and meanwhile, the system can receive the feedback of the site to correct the data.
If the vehicle smoothly passes through the station 1, the station 2 and the station 3 within 30 days, at the station 4, because the width threshold value set by the station 4 enables Wmax to be larger than W0, the following steps are performed during cloud inspection:
1. FCT, i.e., the traffic record for 30 days, is obtained for 3 pieces, R1 is the traffic record for station 1, R2 is the traffic record for station 2, and R3 is the traffic record for station 3. The information ZC1 of the station 4 is obtained 6, ZC2 is 11.8, and ZC3 is 29.
2. Calculation F1: the station weight Q1 in R1 is taken to be 1, the comparison array R1C1 is taken to be 6, R1C2 is taken to be 12, and R1C3 is taken to be 30. ZRF11 (1- |6-6|/6) · 100% ═ 100%, ZRF12 (1- |11.8-12|/11.8) · 100% · 98%, ZRF13 (1- |29-30|/29) · 100% · 96%, F1 (100% + 98% + 96%)/3 ═ 98%.
3. F1Q 1 was 98% 1 was 98%, and as a result, the value was greater than 0.95(PA), W1 of R1 was obtained, and when W1> Wmax, I was 1.
Calculation F2: the station weight Q2 in R2 is taken to be 0.8, the comparison array R2C1 is taken to be 6, R2C2 is taken to be 8, and R2C3 is taken to be 25. ZRF21 (1- |6-6|/6) · 100% ═ 100%, ZRF22 (1- |11.8-8|/11.8) · 100% · 67%, ZRF23 (1- |29-25|/29) · 100% · 86%, F2 (100% + 67% + 86%)/3 ═ 84%.
F2Q 2 ═ 84% × 0.8 ═ 67%, result less than 0.95(PA), match did not match.
Calculation F3: the station weight Q3 in R3 is taken to be 1.2, the comparison array R3C1 is taken to be 7, R3C2 is taken to be 15, and R3C3 is taken to be 30. ZRF31 ═ 83%, (1- |6-7|/6) — 100% >, ZRF32 ═ 73%, (1- |11.8-15|/11.8) —, 73% >, ZRF33 ═ 100% >, 1| 30-30|/30 |, F3 ═ 85% (83% + 73% + 100%)/3 ═ 85%.
F3 × Q3 was 85% by 1.2% by 100.2%, and as a result, W3 of R3 was obtained, and W3< Wmax was judged without changing the I value, which was greater than 0.95 (PA).
4. In summary, since I > is 1(PB), the determination result is not exceeded.
If W1< Wmax in the above situation, the cloud determines that the vehicle is out of limit.
If the owner initiates a complaint and the station manager judges that the vehicle is not overrun, feedback is initiated in the system according to the specified flow of the system, and the cloud system can correct the record to be not overrun.
The site characteristic information ZC in step 1) may include, but is not limited to, the following: station size information ZC1, lane width information ZC2, lane height information ZC3, and lane depth information ZC 4. When the overrun judgment is carried out, any one or more items of information can be selected and substituted into the formula for comparison.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered by the claims.
Claims (8)
1. A method for detecting vehicle overrun on a highway based on multi-source information judgment is characterized by comprising the following steps:
1) defining station characteristic information ZC for each exit of the expressway;
2) acquiring license plate information and overrun information Vmax of a passing vehicle at a target exit site;
3) comparing the overrun information Vmax with threshold values V0 and VC respectively to obtain first judgment on whether the vehicle is overrun, if not overrun, releasing, and if overrun, turning to step 4);
4) according to the license plate information of the vehicle, calling historical information R of the vehicle passing through an exit station of the highway in a historical record within a specified time period FCT;
5) and calculating a weight value Q and a matching degree between each exit station according to the similarity of the feature information ZC of the current exit station of the vehicle and the exit station passing record RC of the historical passing information, and judging whether the vehicle is out of limit for the second time by combining the historical passing information RV of the vehicle and the current out-of-limit information Vmax of the vehicle.
2. The method for detecting vehicle overrun in expressway based on multi-source information determination as claimed in claim 1, wherein the station characteristic information ZC in step 1) includes the following contents: station size information ZC1, lane width information ZC2, lane height information ZC3, and lane depth information ZC 4.
3. The method for detecting the vehicle overrun of the expressway based on the multi-source information judgment of claim 1, wherein the overrun information Vmax in the step 2) comprises the following contents: a maximum width Wmax of the vehicle, a maximum height Hmax of the vehicle, a maximum length Lmax of the vehicle and a maximum weight Gmax of the vehicle.
4. The method for detecting the vehicle overrun of the expressway based on the multi-source information judgment as claimed in claim 1, wherein the specific method for the first judgment of whether the vehicle overrun in step 3) is as follows:
if Vc < Vmax < ═ V0, the limit is not exceeded; if Vmax < Vc, the sampled data is abnormal; if Vc < Vmax, the first judgment is overrun.
5. The method for detecting the overrun of the vehicle on the expressway based on multi-source information judgment according to claim 1, wherein the historical information R in the step 4) comprises the following contents: a historical exit station passage record RC passed by the vehicle; the past exit site information RC for the vehicle to pass through includes the exit site feature code RZT, the detection value RV at the time of passing, and the passing time RRT.
6. The method for detecting vehicle overrun in expressway based on multi-source information judgment as claimed in claim 1, wherein the specific method for judging whether the vehicle overrun in step 5) for the second time is as follows:
5-1) obtaining the current weight Q of each historical exit station passed by the vehicle;
5-2) comparing the similarity F of the target exit station characteristic information ZC and the historical exit station traffic record RC;
5-3) substituting the similarity F into a self-defined judgment formula to judge whether the secondary vehicle exceeds the limit;
the historical exit station weight Q in the step 5-1) is a preset value QI in an initial state, and is dynamically adjusted in the running process, wherein the adjustment formula is QM (QM) QI + (ZP1/ZPT), wherein ZP1 is the total times that the vehicle passes through the station, and ZPT is the total times that the vehicle passes through all stations;
the calculation formula of the current weight Q of the vehicle passing through the historical exit station is as follows: q is QM (ZCP1/ZCPT), where ZCP1 is the total number of times that the vehicle passes through the station at the current time, and ZCPT is the total number of times that the vehicle passes at the current time;
the specific formula for comparing whether the similarity F between the target exit station characteristic information ZC and the historical exit station traffic record RC meets the requirement in the step 5-2) is as follows: f ═ ZRF1+ ZRF2+. ZRFM)/M, where ZRF1 ═ (1- | ZC1-RC1|/ZC1) × 100%, ZRFM ═ 100%;
the specific method for judging whether the secondary vehicle exceeds the limit in the step 5-3) comprises the following steps:
making the total passing frequency I equal to 0, and making the allowed passing frequency PB;
selecting a history record of F × Q ═ PA, obtaining a pass value RV, and if Vmax < RV, then I ═ I + 1; if the calculated result is I > - < PB >, the calculation result is not overrun, namely the historical similar conditions are released, otherwise, the calculation result is overrun.
7. The system for detecting vehicle overrun on the expressway based on multi-source information judgment according to the method of claim 6, wherein the system comprises a cloud subsystem and a local subsystem, and remote communication is performed between the cloud subsystem and the local subsystem;
the cloud subsystem comprises a site information base, an alarm record base, a vehicle information base, a traffic record base and a cloud analysis module; the site information base is used for storing outlet site characteristic information ZC; the alarm record library is used for storing the historical overrun records of the vehicle; the vehicle information base is used for storing vehicle license plate information and overrun information Vmax; the passage record library is used for storing the passage record RC of the historical exit station passed by the vehicle; the cloud analysis module is used for calculating first judgment and second judgment of whether the vehicle is out of limit;
the system comprises a local subsystem and a cloud subsystem, wherein the local subsystem comprises a local processor, a height detector, a length detector, a license plate recognizer, a weight detector and a width detector, the height detector, the length detector, the license plate recognizer, the weight detector and the width detector are in data interaction with the local processor, and the local processor is in data interaction with the cloud subsystem.
8. A computer-readable storage medium storing computer-executable instructions for executing the method for detecting vehicle overrun on an expressway based on multi-source information determination according to any one of claims 1 to 6.
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