CN112785856A - Traffic density detection device and method - Google Patents
Traffic density detection device and method Download PDFInfo
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- CN112785856A CN112785856A CN202110310201.1A CN202110310201A CN112785856A CN 112785856 A CN112785856 A CN 112785856A CN 202110310201 A CN202110310201 A CN 202110310201A CN 112785856 A CN112785856 A CN 112785856A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/065—Traffic control systems for road vehicles by counting the vehicles in a section of the road or in a parking area, i.e. comparing incoming count with outgoing count
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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
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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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0141—Measuring and analyzing of parameters relative to traffic conditions for specific applications for traffic information dissemination
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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
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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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
- G08G1/042—Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
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Abstract
The invention discloses a traffic density detection device and a method, the device comprises a vehicle detection device, a traffic density data processing module, a traffic density judging module and a traffic density display module, wherein the vehicle detection device is arranged on each road of traffic density to be detected and is used for counting vehicles passing through a detection position; the traffic density data processing module is used for preprocessing the vehicle data passing through the detection position and counting and analyzing the vehicle data in real time; the traffic density judging module judges the grade of the traffic flow of each road section according to the analyzed data; the traffic density display module is used for displaying the result of the traffic density judgment to warn the rear vehicles. The invention can count the traffic flow density of each road section in time and provide the traffic flow condition of the front road section for the car owner in real time.
Description
Technical Field
The invention relates to a traffic density detection device and method, and belongs to the technical field of robot calibration.
Background
The traffic density refers to the density of vehicles on a lane, i.e. the number of vehicles on a lane per unit length at a certain instant, and is also called traffic density. The density can directly judge the degree of congestion, thereby deciding which traffic management and control measures to adopt.
The existing observation density mainly includes an access method for observing the number of existing vehicles or the travel time in a section where no access traffic is present in the middle of the section, and a road occupancy method for setting vehicle detectors on a road, in which a loop coil is mostly used, that is, 1 or two vehicle detectors are set on a lane to detect the time occupancy of traffic on the lane, and the density is calculated based on the time occupancy.
The frequent rear-end collisions on the highway cause great property loss and casualties. The accident characteristics of the expressway are researched from the perspective of driving environment, and the expressway is considered to be more likely to have traffic accidents in severe weather such as rain, snow, fog and the like. At present, the functions of the electromechanical facilities of the highway are more and more complete, but the problems that the real-time monitoring of the traffic flow is not accurate and timely and the like caused by unreasonable layout of vehicle detectors, incapability of accurately describing different states of the traffic flow of the highway by collecting data, unscientific control method and the like exist. In order to accurately set up a targeted traffic management method for different road conditions, firstly, the road traffic flow density needs to be accurately detected.
Disclosure of Invention
In order to solve the problems, the invention provides a traffic density detection device and a traffic density detection method, which can be used for timely counting the traffic flow density of each road section and providing the traffic flow condition of the front road section for a vehicle owner in real time.
The technical scheme adopted for solving the technical problems is as follows:
in a first aspect, the traffic density detection device provided by the embodiment of the present invention includes a vehicle detection device, a traffic density data processing module, a traffic density determination module, and a traffic density display module, where the vehicle detection device is installed on each road to be detected with traffic density and is used to count vehicles passing through a detection position; the traffic density data processing module is used for preprocessing the vehicle data passing through the detection position and counting and analyzing the vehicle data in real time; the traffic density judging module judges the grade of the traffic flow of each road section according to the analyzed data; the traffic density display module is used for displaying the result of the traffic density judgment to warn the rear vehicles.
As a possible implementation manner of this embodiment, the vehicle detection device includes a laser generation device and a photoresistor receiver, the laser generation device is installed on the gantry above the road, and the photoresistor receiver is installed on the road surface right below the laser generation device.
As a possible implementation manner of this embodiment, the vehicle detection device includes a geomagnetic sensor, the geomagnetic sensor is installed on each road to be detected with traffic density, an output end of the geomagnetic sensor is connected to an input end of the traffic density data processing module, an output end of the traffic density data processing module is connected to an input end of the traffic density determination module, and an output end of the traffic density determination module is connected to an input end of the traffic density display module.
As a possible implementation manner of this embodiment, the vehicle detection devices are installed in groups at intervals (one kilometer).
In a second aspect, a traffic density detection method provided in an embodiment of the present invention includes the following steps:
step 4, calculating the traffic flow density according to the detected vehicles;
step 5, judging the traffic level grade according to the traffic flow density;
and 6, transmitting the traffic level grade information to a rear LED display screen for displaying and warning, and sending to a background server.
As a possible implementation manner of this embodiment, in step 1, a group of vehicle detection devices is arranged at intervals (one kilometer) on each road of which the traffic density is to be detected.
As a possible implementation manner of this embodiment, the vehicle detection device includes a laser generation device and a photoresistor receiver, the laser generation device is installed on the gantry above the road, and the photoresistor receiver is installed on the road surface right below the laser generation device.
As a possible implementation manner of this embodiment, the vehicle detection device includes a geomagnetic sensor, the geomagnetic sensor is installed on each road to be detected with traffic density, an output end of the geomagnetic sensor is connected to an input end of the traffic density data processing module, an output end of the traffic density data processing module is connected to an input end of the traffic density determination module, and an output end of the traffic density determination module is connected to an input end of the traffic density display module.
As a possible implementation manner of this embodiment, in step 4, the process of calculating the traffic flow density between two sets of vehicle detection devices on the road includes the following steps:
the section a between the vehicle detection device A and the vehicle detection device B is at T1The number of vehicles running at that time is: q ═ NA1-QB1Wherein: qA1The cumulative flow rate, Q, of the vehicle detecting device A at time T1B1The cumulative passing flow rate of the vehicle detection device B at time T1;
the link traffic flow density between the vehicle detection device a and the vehicle detection device B is: k ═ QA1-QB1)/XABWherein: xABThe distance between the vehicle detection device a and the vehicle detection device B.
Number of vehicles N ═ Q in road segment between any two consecutive vehicle detection devicesαi-QβiDensity ofK is respectively K ═ N/XαβWherein: qαiIs TiCumulative flow rate, Q, of the vehicle detecting device alpha at that momentβiIs TiCumulative flow rate, X, of the vehicle detecting device beta at that momentαβThe vehicle detection devices alpha and beta are separated by a distance.
As one possible implementation of the present embodiment, the levels include five levels of "clear", "substantially clear", "light congestion", "medium congestion", and "heavy congestion".
As a possible implementation manner of this embodiment, the background server stores the received occlusion time data in a classified manner, performs fuzzy clustering analysis on the accumulated data to obtain a more accurate feature vector interval, and periodically sends the feature vector interval to the microcontroller as an updated feature vector sample set.
The technical scheme of the embodiment of the invention has the following beneficial effects:
the invention not only fuses traffic flow density of each road section in time to provide traffic flow conditions of the front road section for car owners in real time, but also reduces accident rate under severe weather, thereby providing further guarantee for life and property safety of people.
Description of the drawings:
FIG. 1 is a block diagram illustrating a traffic density detection device in accordance with an exemplary embodiment;
FIG. 2 is a flow chart illustrating a traffic density detection method according to an exemplary embodiment;
FIG. 3 is a schematic illustration of an installation of a vehicle sensing device according to an exemplary embodiment.
Detailed Description
The invention is further illustrated by the following examples in conjunction with the accompanying drawings:
in order to clearly explain the technical features of the present invention, the following detailed description of the present invention is provided with reference to the accompanying drawings. The following disclosure provides many different embodiments, or examples, for implementing different features of the invention. To simplify the disclosure of the present invention, the components and arrangements of specific examples are described below. Furthermore, the present invention may repeat reference numerals and/or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not in itself dictate a relationship between the various embodiments and/or configurations discussed. It should be noted that the components illustrated in the figures are not necessarily drawn to scale. Descriptions of well-known components and processing techniques and procedures are omitted so as to not unnecessarily limit the invention.
Fig. 1 is a schematic diagram illustrating a traffic density detection apparatus according to an exemplary embodiment. As shown in fig. 1, a traffic density detection device provided in an embodiment of the present invention includes a vehicle detection device, a traffic density data processing module, a traffic density determination module, and a traffic density display module, where the vehicle detection device is installed on each road to be detected with traffic density and is used for counting vehicles passing through a detection position; the traffic density data processing module is used for preprocessing the vehicle data passing through the detection position and counting and analyzing the vehicle data in real time; the traffic density judging module judges the grade of the traffic flow of each road section according to the analyzed data; the traffic density display module is used for displaying the result of the traffic density judgment to warn the rear vehicles.
As a possible implementation manner of this embodiment, as shown in fig. 3, the vehicle detection device includes a laser generator 2 and a photoresistor receiver 3, the laser generator 2 is installed on the gantry 1 above the road, and the photoresistor receiver 3 is installed on the road surface right below the laser generator 2.
As a possible implementation manner of this embodiment, the vehicle detection device includes a geomagnetic sensor, the geomagnetic sensor is installed on each road to be detected with traffic density, an output end of the geomagnetic sensor is connected to an input end of the traffic density data processing module, an output end of the traffic density data processing module is connected to an input end of the traffic density determination module, and an output end of the traffic density determination module is connected to an input end of the traffic density display module.
As a possible implementation manner of this embodiment, the vehicle detection devices are installed in one group at a certain distance (one kilometer), and the traffic density between the two groups of vehicle detection devices is measured and calculated.
FIG. 2 is a flow chart illustrating a traffic density detection method according to an exemplary embodiment. As shown in fig. 2, a traffic density detection method provided in an embodiment of the present invention includes the following steps:
step 4, calculating the traffic flow density according to the detected vehicles;
step 5, judging the traffic level grade according to the traffic flow density;
and 6, transmitting the traffic level grade information to a rear LED display screen for displaying and warning, and sending to a background server.
As a possible implementation manner of this embodiment, in step 1, a group of vehicle detection devices is arranged at intervals (one kilometer) on each road of which the traffic density is to be detected. And comparing the detection data of the former group of vehicle detection devices with the detection data of the next group of vehicle detection devices to obtain the traffic flow density of each kilometer section.
As a possible implementation manner of this embodiment, as shown in fig. 3, the vehicle detection device includes a laser generator 2 and a photoresistor receiver 3, the laser generator 2 is installed on the gantry 1 above the road, and the photoresistor receiver 3 is installed on the road surface right below the laser generator 2. Each group of vehicle detection devices corresponds to two laser-photoresistor combination devices, and double detection is adopted to reduce errors. The laser-photoresistor combination device is used for detecting the passing object, and after the laser is shielded by the object, the photoresistor receiver transmits a low-level signal to the control end.
Each group of vehicle detection devices consists of a portal frame, a laser generation device, a photoresistor receiver, a microcontroller and a Zigbee communication module. The realization elements of the system are a photoresistor receiver data transmitting end, an access end, a transmission line, a control end and a microcontroller data transmission serial port. The portal frame is located two lane tops, and the laser generating device of road top installation combines with the road surface photo resistance receiver that corresponds under with, and near the photo resistance receiver installation Zigbee communication module for data transmission to microcontroller.
The specific process of detection is as follows: when the laser is not shielded, the photoresistor is triggered frequently, the microcontroller receives a high-level signal, and the output of the AB section is 1; when the laser path is shielded, the photoresistor is not triggered, and the microcontroller cannot receive a high level signal and outputs a low level 0. Whether an object passes through is detected in the process, and then the detected object is preprocessed to judge whether the vehicle is a vehicle.
As a possible implementation manner of this embodiment, in step 4, the process of calculating the traffic flow density between two sets of vehicle detection devices on the road includes the following steps:
the section a between the vehicle detection device A and the vehicle detection device B is at T1The number of vehicles running at that time is: q ═ NA1-QB1Wherein: qA1The cumulative flow rate, Q, of the vehicle detecting device A at time T1B1The cumulative passing flow rate of the vehicle detection device B at time T1;
the link traffic flow density between the vehicle detection device a and the vehicle detection device B is: k ═ QA1-QB1)/XABWherein: xABThe distance between the vehicle detection device a and the vehicle detection device B.
Number of vehicles N ═ Q in road segment between any two consecutive vehicle detection devicesαi-QβiThe density K is respectively K ═ N/XαβWherein: qαiIs TiCumulative flow rate, Q, of the vehicle detecting device alpha at that momentβiIs TiCumulative flow rate, X, of the vehicle detecting device beta at that momentαβThe vehicle detection devices alpha and beta are separated by a distance. As one of the embodimentsAccording to the possible implementation mode, the traffic level of the road section is judged to be five levels of 'smooth', 'basically smooth', 'light congestion', 'medium congestion' and 'severe congestion' according to the analyzed traffic flow density of each set road section and the maximum traffic density value of the road section.
According to the technical requirements of road network operation monitoring and temporary service, the traffic jam state of the expressway is classified into different levels by using the average travel speed of the road sections. The lower the average travel speed of the link, the higher the congestion degree. The road section congestion degree grading standard of the road network operation monitoring and temporary service technical requirement is shown in a table 1.
TABLE 1 Highway segment crowding degree grading Standard
The three-parameter basic relation of the traffic flow is as follows: and K is Q V, and according to the table, when the road traffic flow is obtained, the grade division standard of the congestion degree of the highway section with the road density as an index can be deduced.
As a possible implementation manner of this embodiment, the judged traffic level grade information is transmitted to a rear LED display screen to perform warning by a warning light at the same time, and the road information is fed back to the driver in real time.
The specific process of transmitting the judged traffic level grade information to a rear LED display screen and simultaneously carrying out warning by a warning lamp is as follows: through analyzing the data that the photoresistor receiver spreads into, according to the jam condition of this highway section of data analysis that spreads into, data transmission shows and starts the warning light to warn to the LED display screen. And (3) graded evaluation of road states: when the traffic flow density K is less than or equal to the optimal density KmJudging the road to run normally; when K ismAnd when the road is less than K, judging that the road is congested, and transmitting a judgment result to a rear warning board.
And the background server stores the received shielding time data in a classified manner, performs fuzzy clustering analysis on the accumulated data to obtain a more accurate characteristic vector interval, and periodically sends the characteristic vector interval to the microcontroller as an updated characteristic vector sample set.
The background server judges the detection data as follows: the background server analyzes data transmitted by the photoresistor receiver, calculates the times of animal body shielding and shielding time according to the transmitted data, and judges whether the shielding is signal change caused by vehicle passing.
The specific process of carrying out fuzzy clustering analysis on the accumulated data comprises the following steps:
the background server takes the latest n groups of collected data transmitted by the photoresistor receivers from the database as a group of initial sample domains, and the collected data is assumed to be nine data of S1(X1, Y1), S2(X2, Y2), S3(X3, Y3), S4(X4, Y4), S5(X5, Y5), S6(X6, Y6), S7(X7, Y7), S8(X8, Y8), and S9(X9, Y9), wherein X represents the shielding time, Y represents the number of shielded lasers, and Y is 1 or 2.
The following steps are used for clustering and calculating the shielding time by using a K-Means algorithm:
four centroids (invalid data cluster, car cluster, medium truck cluster, large trailer cluster) are selected at random as E1, E2, E3, E4.
Then, the distances between Xi (i ═ 1,2,3 … … 8,9) and the four centroids E1, E2, E3, and E4 are calculated respectively, that is:
ΔXi1＝|Xi-E1|
ΔXi2＝|Xi-E2|
ΔXi3＝|Xi-E3|
ΔXi4＝|Xi-E4|
judging the sizes of the delta Xi1, the delta Xi2, the delta Xi3 and the delta Xi4, and if the delta Xi1 is minimum, classifying S1 into an invalid data cluster; if Δ Xi2 is minimal, then assign S1 to the minicar cluster; if Δ Xi3 is minimal, then assign S1 to the pickup truck cluster; if Δ Xi4 is minimal, then S1 is assigned to the large trailer cluster.
When all the data are clustered, the average value of the sum of Xi in each cluster is recalculated, and the value is used as a new centroid, namely the centroid
(in the formula, n1, n2, n3 and n4 respectively represent the number of elements in each of four clusters, and Xi1, Xi2, Xi3 and Xi4 respectively represent elements in four clusters of invalid data cluster, small car cluster, medium truck cluster and large trailer cluster)
And repeating the above 4 steps according to the obtained four new centroids of E1 ', E2', E3 'and E4' until the calculated centroids are not changed any more.
As a possible implementation manner of this embodiment, the vehicle detection device may further employ a geomagnetic sensor, the geomagnetic sensor is installed on each road to be detected with traffic density, an output end of the geomagnetic sensor is connected to an input end of the traffic density data processing module, an output end of the traffic density data processing module is connected to an input end of the traffic density determination module, and an output end of the traffic density determination module is connected to an input end of the traffic density display module.
The invention provides the traffic flow congestion condition in front for the driver in real time in severe weather (haze, rain, snow, fog and the like), improves the traffic flow and reduces the occurrence of rear-end collisions.
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 (10)
1. A traffic density detection device is characterized by comprising a vehicle detection device, a traffic density data processing module, a traffic density judging module and a traffic density display module, wherein the vehicle detection device is arranged on each road with traffic density to be detected and is used for counting vehicles passing through a detection position; the traffic density data processing module is used for preprocessing the vehicle data passing through the detection position and counting and analyzing the vehicle data in real time; the traffic density judging module judges the grade of the traffic flow of each road section according to the analyzed data; the traffic density display module is used for displaying the result of the traffic density judgment to warn the rear vehicles.
2. The traffic density detecting device according to claim 1, wherein the vehicle detecting device comprises a laser generating device and a photoresistor receiver, the laser generating device is mounted on a portal frame above the road, and the photoresistor receiver is mounted on the road surface right below the laser generating device.
3. The traffic density detection device according to claim 1, wherein the vehicle detection device comprises a geomagnetic sensor, the geomagnetic sensor is installed on each road where the traffic density is to be detected, an output end of the geomagnetic sensor is connected with an input end of the traffic density data processing module, an output end of the traffic density data processing module is connected with an input end of the traffic density determination module, and an output end of the traffic density determination module is connected with an input end of the traffic density display module.
4. A traffic density detecting device according to any one of claims 1 to 3, wherein said vehicle detecting means are installed in a group at a certain distance.
5. A traffic density detection method is characterized by comprising the following steps:
step 1, arranging a vehicle detection device on each road to be detected for traffic density;
step 2, detecting the moving object on the road by a vehicle detection device;
step 3, judging whether the detected moving object is a vehicle or not, and counting the vehicles;
step 4, calculating the traffic flow density according to the detected vehicles;
step 5, judging the traffic level grade according to the traffic flow density;
and 6, transmitting the traffic level grade information to a rear LED display screen for displaying and warning, and sending to a background server.
6. The traffic density detecting method according to claim 5, wherein in step 1, a group of vehicle detecting devices is provided at every certain distance on each road where the traffic density is to be detected.
7. The traffic density detecting method according to claim 6, wherein the vehicle detecting device comprises a laser generating device and a photoresistor receiver, the laser generating device is installed on a portal frame above the road, and the photoresistor receiver is installed on the road surface right below the laser generating device.
8. The traffic density detection method according to claim 6, wherein the vehicle detection device comprises a geomagnetic sensor, the geomagnetic sensor is installed on each road where the traffic density is to be detected, an output end of the geomagnetic sensor is connected with an input end of the traffic density data processing module, an output end of the traffic density data processing module is connected with an input end of the traffic density determination module, and an output end of the traffic density determination module is connected with an input end of the traffic density display module.
9. The traffic density detection method according to any one of claims 6 to 8, wherein in the step 4, the calculation process of the traffic flow density between the two groups of vehicle detection devices on the road comprises the following steps:
the section a between the vehicle detection device A and the vehicle detection device B is at T1The number of vehicles running at that time is: q ═ NA1-QB1Wherein: qA1The cumulative flow rate, Q, of the vehicle detecting device A at time T1B1The cumulative passing flow rate of the vehicle detection device B at time T1;
the link traffic flow density between the vehicle detection device a and the vehicle detection device B is: k ═ QA1-QB1)/XABWherein: xABThe distance between the vehicle detection device a and the vehicle detection device B.
Number of vehicles N ═ Q in road segment between any two consecutive vehicle detection devicesαi-QβiThe density K is respectively K ═ N/XαβWherein: qαiIs TiCumulative flow rate, Q, of the vehicle detecting device alpha at that momentβiIs TiCumulative flow rate, X, of the vehicle detecting device beta at that momentαβThe vehicle detection devices alpha and beta are separated by a distance.
10. The traffic density detection method according to claim 9, wherein the background server stores the received occlusion time data in a classified manner, performs fuzzy clustering analysis on the accumulated data to obtain a more accurate feature vector interval, and periodically sends the feature vector interval to the microcontroller as an updated feature vector sample set.
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| CN112785856B (en) | 2022-04-01 |
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