CN108460502B - Expressway passing card quantity monitoring device and card quantity prediction method thereof - Google Patents
Expressway passing card quantity monitoring device and card quantity prediction method thereof Download PDFInfo
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Abstract
The invention discloses a highway passing card quantity monitoring device and a card quantity prediction method thereof, comprising the following steps: the color block combined patterns are transversely arranged on the entrance lane of the toll station, and the image information of the vehicles passing through the color block combined patterns is collected through the camera; the computer processes and analyzes the image information collected by the camera to judge whether the vehicle passes through the toll station, namely, the vehicle is indicated to take or return a pass card; the change of the card quantity of each card sender in the toll station is monitored in real time by a computer, and the change condition of the card quantity of the toll station is predicted according to the historical information of the card quantity change. The invention has simple structure, rapid and accurate detection, can conveniently monitor the card quantity distribution in the area and the inventory of the passing card quantity of each toll station in real time, and forecast the change condition of the card quantity of each toll station in a period of the future, thereby being beneficial to the expressway passing card allocating and allocating department to allocate the passing cards timely and reasonably, improving the working efficiency of expressway networking charging and reducing the operation cost.
Description
Technical Field
The invention relates to a highway passing card quantity monitoring device and a card quantity prediction method thereof, belonging to the field of intelligent traffic highway charging.
Background
Along with the continuous increase of expressway mileage and traffic flow in China, how to further strengthen the management level of expressways and improve the operation efficiency of the expressways becomes an important content of expressway management research. Construction and optimization of highway tolling is one of the important tasks of highway management, which directly affects the efficiency of highway traffic and the economic benefits of operation.
At present, the pass cards are used as main pass media for highway tolling in China in a circulating way, a toll station mostly adopts a closed management mode, a driver obtains the pass cards from an entrance, and the pass cards are transported and paid on an exit. However, as the toll road of the expressway is continuously prolonged, the number of toll gates is continuously increased, the traffic flow is increasingly increased, and the number of managed pass cards is also sharply increased. This places a heavy burden on highway management personnel if the management is not good due to the dispersion, flowability, and distribution imbalance of the pass cards. Therefore, how to accurately track and manage the number and distribution of the pass cards in the road section in the area, and timely allocate the pass cards, and meanwhile, prevent the loss of the pass cards, becomes a key problem for ensuring whether the network charging operation management of the expressway can normally operate.
Disclosure of Invention
The invention aims to: in order to overcome the defects in the prior art, the invention provides the expressway passing card quantity monitoring device and the card quantity predicting method thereof, which can monitor the card quantity distribution in an area conveniently and in real time and predict the change condition of the card quantity of each toll station in a period in the future, thereby being beneficial to an expressway passing card allocating department to allocate passing cards timely and reasonably, improving the working efficiency of expressway networking charging and reducing the operation cost.
The technical scheme is as follows: in order to achieve the above purpose, the invention adopts the following technical scheme:
the highway passing card amount monitoring device comprises a color block combination pattern, a camera, a computer, a bracket and a signal cable;
the color block combined patterns are transversely arranged on the entrance lane of the toll station, and the camera is arranged above the lane through the bracket, so that the vehicle is ensured to be in the visual angle range of the camera when passing through the color block combined patterns; the computer is connected with the camera through the signal cable, and when a vehicle passes through the color block combination pattern, the computer processes and analyzes the image information collected by the camera to judge whether the vehicle passes through a toll station, namely, the vehicle is indicated to take or return a pass card; the change of the card quantity of each card sender in the toll station is monitored in real time by a computer, and the change condition of the card quantity of the toll station is predicted according to the historical information of the card quantity change.
Further, the color lump combination pattern comprises at least two color lumps, and the color lumps of various colors are arranged at intervals.
Furthermore, the camera is used for judging whether the vehicle enters or exits from the toll station or not in the daytime and night, and an infrared camera with a good night vision effect is adopted.
Further, the computer comprises a client computer and a remote server computer, and the client computer and the remote server computer realize information transmission through the internet.
In the invention, the card quantity of each card sender in the toll station is monitored in real time through the client computer, the card quantity information of the toll station is transmitted to the remote server computer through the Internet, the server can monitor the card quantity change condition of all toll stations in the whole monitoring area in real time, and the change condition of the card quantity of each toll station in the future can be predicted according to the history information of the card quantity change, thereby providing a certain decision basis for the card quantity allocation of the expressway passing card allocation department.
A method for predicting the card quantity of a highway passing card comprises the following steps:
s1: for each year in history, calculating the card taking amount or card returning amount of the toll station by taking month as a unit to form a characteristic vector A i ＝[a i1 ,…,a ij ,…,a i12 ]Where i denotes a year, j denotes a month, and we form a feature vector set a= { a assuming that we observe for N years 1 ,…,A N }；
S2: for the 1 st month to the 1 st month of the current year, we obtain the characteristic vector B= [ B ] of the card taking amount or card returning amount of the toll station 1 ,…,b l ]Similarly, for each feature vector A of the ith year in the feature vector set A i Also only the element value of the previous month is taken to form a characteristic vector A' i ＝[a i1 ,…,a il ]The new set of feature vectors is denoted as a '= { a' 1 ,…,A′ N }；
S3: for each element A 'in the feature vector set A' i Calculating a feature directionThe Euclidean distance between the quantity B and the quantity B, adopting a k nearest neighbor algorithm to find k eigenvectors closest to the eigenvector B from A', then corresponding the k eigenvectors to complete eigenvectors in the original A, taking out the k complete eigenvectors, adding corresponding elements in the k eigenvectors and taking an average value to obtain a predictive vector C= [ C ] 1 ,…,c l+1 ,…,c 12 ]I.e. estimated to get the predicted value of the card amount per month after the current year, i.
Furthermore, 3-5 k are taken, so that the calculation is convenient, and the prediction is accurate.
Further, in order to evaluate the error range of the predicted value, the absolute value difference is taken by using the values of the first l elements in the actual measurement vector B and the predicted vector C of the last month of the current year, and then the difference is averaged to be used as the error estimation of each month.
The beneficial effects are that: the expressway passing card quantity monitoring device and the card quantity prediction method provided by the invention have the following advantages compared with the prior art: 1. the device is simple, the installation and the operation are convenient, the detection method is rapid and accurate, the detection cost is low, and the device has good economic and practical values; 2. the system can monitor the card quantity distribution in the area and the inventory of the card quantity of the toll stations conveniently in real time, and forecast the change condition of the card quantity of each toll station in a period of time in the future, which is helpful for the expressway toll card allocating department to allocate the toll cards timely and reasonably, improves the work efficiency of expressway networking toll collection, and reduces the operation cost.
Drawings
FIG. 1 is a schematic diagram of a card quantity monitoring device according to an embodiment of the present invention;
the drawings include: 1. the color block combination pattern comprises 2 parts of a camera, 3 parts of a bracket, 4 parts of a signal cable, 5 parts of a vehicle, 6 parts of a client computer, 7 parts of a remote server computer, 8 parts of an internet.
Detailed Description
The invention will be further described with reference to the accompanying drawings.
FIG. 1 shows a highway passing card quantity monitoring device, which comprises a color block combination pattern 1, a camera 2, a computer, a bracket 3 and a signal cable 4;
the color block combined pattern 1 is transversely arranged on an entrance lane of a toll station, and the camera 2 is arranged above the lane through the bracket 3, so that the vehicle 5 is ensured to be in the visual angle range of the camera 2 when passing through the color block combined pattern 1; the computer is connected with the camera 2 through the signal cable 4, and when the vehicle 5 passes through the color block combined pattern 1, the computer processes and analyzes the image information collected by the camera 2 to judge whether the vehicle 5 passes through a toll station or not, namely, the vehicle is indicated to take or return a pass card; the change of the card quantity of each card sender in the toll station is monitored in real time by a computer, and the change condition of the card quantity of the toll station is predicted according to the historical information of the card quantity change.
In this embodiment, the color patch combination pattern 1 includes two color patches, and the two color patches are arranged at intervals; the camera 2 is an infrared camera.
The computer comprises a client computer 6 and a remote server computer 7, and the client computer 6 and the remote server computer 7 realize information transmission through an internet 8.
The card quantity of each card sender in the toll station is monitored in real time through the client computer, card quantity information of the toll station is transmitted to the remote server computer through the computer network, the server can monitor the card quantity change condition of all toll stations in the whole monitoring area in real time, and the change condition of the card quantity of each toll station in the future can be predicted according to the history information of the card quantity change, so that a certain decision basis is provided for the card quantity allocation of the expressway passing card allocation department.
The monitoring of the amount of the expressway access card specifically comprises:
(1) When no vehicle passes through the color block combination pattern 1, the client computer 6 records the pattern color combination S1 acquired by the camera 2, namely, the color values in each picture block in the clear pattern;
(2) When the vehicle is detected, the camera 2 acquires an image of a corresponding detection area, calculates a color combination S2 of the detection area, judges whether the color combination S2 of the detection area is the same as the color combination S1 obtained when the vehicle does not pass through the detection area, if so, the detection area does not pass through the detection area, otherwise, the vehicle passes through the detection area;
(3) If the vehicle enters or leaves the toll station, the vehicle indicates to take or return a pass card, the client computer 6 executes 1 subtracting or 1 adding operation on the card sender and the residual card quantity of the toll station, and the residual card quantity information of the toll station is transmitted to the remote server computer 7 through a computer network;
(4) The server computer 7 feeds back the residual card quantity information of all toll stations in the monitored area in real time, and can predict the change condition of the card quantity of a certain toll station in a certain period of time in the future. The specific prediction method is as follows:
s1: for each year in history, calculating the card taking amount or card returning amount of the toll station by taking month as a unit to form a characteristic vector A i ＝[a i1 ,…,a ij ,…,a i12 ]Where i denotes a year, j denotes a month, and we form a feature vector set a= { a assuming that we observe for N years 1 ,…,A N }；
S2: for the 1 st month to the 1 st month of the current year, we obtain the characteristic vector B= [ B ] of the card taking amount or card returning amount of the toll station 1 ,…,b l ]Similarly, for each feature vector A of the ith year in the feature vector set A i Also only the element value of the previous month is taken to form a characteristic vector A' i ＝[a i1 ,…,a il ]The new set of feature vectors is denoted as a '= { a' 1 ,…,A′ N }；
S3: for each element A 'in the feature vector set A' i Calculating the Euclidean distance between the feature vector B and the feature vector B, adopting a k nearest neighbor algorithm to find k (k is 3) feature vectors closest to the feature vector B from A', then corresponding the k nearest neighbor algorithm to the complete feature vector in the original A, taking the k complete feature vectors, adding the corresponding elements in the k feature vectors and averaging to obtain a predictive vector C= [ C ] 1 ,…,c l+1 ,…,c 12 ]I.e. estimated to be after the current year/monthPredicted amount of cards per month.
In addition, in order to evaluate the error range of the predicted value, the absolute value difference is taken by the values of the previous l elements in the actual measurement vector B and the predicted vector C of the previous month of the current year, and then the difference is averaged to be used as the error estimation of each subsequent month.
The foregoing is only a preferred embodiment of the invention, it being noted that: it will be apparent to those skilled in the art that various modifications and adaptations can be made without departing from the principles of the present invention, and such modifications and adaptations are intended to be comprehended within the scope of the invention.
Claims (1)
1. A method for predicting the card quantity of a highway passing card is characterized in that,
the monitoring device in the expressway passing card quantity prediction method comprises a color block combination pattern (1), a camera (2), a computer, a bracket (3) and a signal cable (4);
the color block combined pattern (1) is transversely arranged on an entrance lane of a toll station, and the camera (2) is arranged above the lane through the bracket (3) so as to ensure that a vehicle (5) passes through the color block combined pattern (1) within the visual angle range of the camera (2); the computer is connected with the camera (2) through the signal cable (4), and when the vehicle (5) passes through the color block combined pattern (1), the computer processes and analyzes the image information collected by the camera (2) to judge whether the vehicle (5) passes through a toll station or not, namely, the vehicle is indicated to take a pass card; monitoring the change of the card taking amount of the toll station in real time through a computer, and predicting the change condition of the card taking amount of the toll station according to the historical information of the change of the card taking amount;
the color lump combination pattern (1) comprises at least two color lumps, and the color lumps of various colors are arranged at intervals;
the camera (2) adopts an infrared camera;
the computer comprises a client computer (6) and a remote server computer (7), and the client computer (6) and the remote server computer (7) realize information transmission through an internet (8);
the method for predicting the card quantity of the expressway access card comprises the following steps:
step 1: for each year of history, calculating the card taking amount of the toll station by taking month as a unit to form a characteristic vector A i ＝[a i1 ,…,a ij ,…,a i12 ]Wherein i represents a year, j represents a month, a ij Representing the card taking amount of the j th month of the i year; assuming N years of observation, a feature vector set A= { A is formed 1 ,…,A N }；
Step 2: for the 1 st month to the L th month of the current year, a characteristic vector B= [ B ] of the card taking amount of the toll station is obtained 1 ,…,b L ]，b L Representing the amount of pickup of the card at the L-th month in the current year, and similarly, for each feature vector A of the i-th year in the feature vector set A i The element values of the previous L months are taken to form a characteristic vector A' i ＝[a i1 ,…,a iL ]The new set of feature vectors is denoted as a '= { a' 1 ,…,A′ N }；
Step 3: for each element A 'in the feature vector set A' i Calculating the Euclidean distance between the feature vector B and the feature vector B, adopting a k nearest neighbor algorithm to find k feature vectors closest to the feature vector B from A', then corresponding the k nearest neighbor algorithm to the complete feature vector in the original A, taking out the k complete feature vectors, adding corresponding elements in the k feature vectors, and taking an average value to obtain a prediction vector C= [ C ] 1 ,…,c L+1 ,…,c 12 ]，c L+1 The average value of the (L+1) th component in the k nearest neighbor feature vectors is represented, L represents the current month under the current year, namely, the predicted value of the card taking amount of each month after the current year L month is estimated;
the highway passing card quantity monitoring specifically comprises the following steps:
(1) When no vehicle passes through the color block combination pattern (1), the client computer (6) records the pattern color combination S1 acquired by the camera (2), namely, the color value in each picture block in the pattern is clear;
(2) When the vehicle is detected, the camera (2) acquires an image of a corresponding detection area, calculates a color combination S2 of the detection area, judges whether the color combination S2 of the detection area is the same as a color combination S1 when the detection area does not pass by a vehicle, if so, the detection area does not pass by the vehicle, otherwise, the vehicle passes by the detection area;
(3) If the vehicle enters the toll station, the vehicle indicates to take away a pass card, the client computer (6) performs 1 adding operation on the card taking amount variable of the toll station in a month of a certain year, and the remaining card taking amount information of the toll station is transmitted to the remote server computer (7) through a computer network;
(4) The information of the card taking amount of the toll station in the detected area is fed back in real time through the server computer (7), and the change condition of the card taking amount of the toll station in a certain period of time in the future can be predicted.
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| KR20010017659A (en) * | 1999-08-13 | 2001-03-05 | 김도현 | Application Method Of Rewritable Visual Card For Toll Passage Card |
| CN101777197A (en) * | 2010-01-06 | 2010-07-14 | 广东省电子技术研究所 | Passing card management system |
| CN103366581A (en) * | 2013-06-28 | 2013-10-23 | 南京云创存储科技有限公司 | Traffic flow counting device and counting method |
| CN106373208A (en) * | 2016-08-30 | 2017-02-01 | 山东高速信息工程有限公司 | Highway toll-gate monitoring system based on ZigBee |
| CN107330989A (en) * | 2017-06-28 | 2017-11-07 | 云南建设基础设施投资股份有限公司滇南分公司 | A kind of highway tolling system based on mobile payment |
| CN209417789U (en) * | 2018-06-12 | 2019-09-20 | 徐州工程学院 | A kind of highway passing card card amount monitoring device |
-
2018
- 2018-06-12 CN CN201810599183.1A patent/CN108460502B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR20010017659A (en) * | 1999-08-13 | 2001-03-05 | 김도현 | Application Method Of Rewritable Visual Card For Toll Passage Card |
| CN101777197A (en) * | 2010-01-06 | 2010-07-14 | 广东省电子技术研究所 | Passing card management system |
| CN103366581A (en) * | 2013-06-28 | 2013-10-23 | 南京云创存储科技有限公司 | Traffic flow counting device and counting method |
| CN106373208A (en) * | 2016-08-30 | 2017-02-01 | 山东高速信息工程有限公司 | Highway toll-gate monitoring system based on ZigBee |
| CN107330989A (en) * | 2017-06-28 | 2017-11-07 | 云南建设基础设施投资股份有限公司滇南分公司 | A kind of highway tolling system based on mobile payment |
| CN209417789U (en) * | 2018-06-12 | 2019-09-20 | 徐州工程学院 | A kind of highway passing card card amount monitoring device |
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