KR20240099675A - Road traffic situation monitoring system and method - Google Patents

Abstract

The present invention discloses a technology for providing image information by photographing vehicles on the road for monitoring road traffic conditions. The present invention can display driving images of vehicles even in blank sections where cameras are not installed when displaying vehicles driving on the road using images captured through cameras installed at regular intervals on the road in a road traffic situation room. It relates to a road traffic situation monitoring system and method.

Description

Road traffic situation monitoring system and method}

The present invention relates to a technology for providing image information by photographing vehicles on the road for monitoring road traffic conditions. More specifically, the present invention relates to a technology for providing image information by photographing vehicles on the road in order to monitor road traffic conditions. More specifically, the present invention relates to a technology for providing image information by filming vehicles on the road in order to monitor road traffic conditions. The present invention relates to a road traffic situation monitoring system and method that allows displaying driving images of vehicles even in blank sections where cameras are not installed when displaying vehicles driving on the road.

Cameras are installed at certain sections on highways and automobile-only roads, and the images captured through them are transmitted to the road traffic situation room. Therefore, the road traffic situation room can monitor road traffic conditions in real time using images captured through cameras.

In addition, the road traffic situation room informs drivers of the results of road traffic monitoring through traffic bulletin boards or broadcasts, and takes appropriate measures when the vehicle's driving speed falls below a certain level or an accident occurs. Therefore, drivers can drive while recognizing the road conditions on which they are driving in real time.

However, due to cost issues, there are many restrictions on installing cameras on roads. Therefore, among all roads, cameras are installed and operated only in special sections such as those where traffic congestion occurs regularly or many accidents occur, and cameras are not installed in most sections.

For this reason, in the conventional road traffic situation monitoring technology, there is a problem in that monitoring images of vehicles cannot be obtained for blank sections where cameras are not installed on the road, and thus monitoring information cannot be provided.

The purpose of the present invention is to display vehicles driving on the road using images captured through cameras installed at regular intervals on the road in a road traffic situation room, and to display vehicle driving images in a blank section where cameras are not installed. The goal is to provide a road traffic situation monitoring system and method that can be fused and displayed from images.

To achieve the above object, the road traffic situation monitoring system according to the present invention acquires images of vehicles driving on the first road section through a CCTV camera based on absolute coordinates, and images of the vehicles driving on the first road section through a radar sensor are obtained. Subsequently, a traffic information collection device that acquires and transmits sensing data of vehicles driving on a continuous second road section based on absolute coordinates; And the images and sensed data of the vehicles are transmitted from the traffic information collection device through a network, and the images of the vehicles are displayed on the screen of the monitor in the first road section, and the images of the vehicles are displayed in the second road section. It includes an integrated control server that maps the objects recognized by the radar sensor, the entire area, and the background space based on the absolute coordinates and displays them on the monitor.

In addition, the CCTV camera is installed on a support stand installed around the edge of the road, and the radar sensor is installed at a vertical distance from the CCTV camera on the support pole in the upper vertical direction.

In addition, the traffic information collection device automatically labels images captured by the CCTV camera to obtain the length and license plate number of the vehicle in question based on absolute coordinates, and identifies unique objects for the vehicles based on the detection results of the radar sensor. A traffic information collection unit that recognizes ID, lane information, entry time, passing time, occupancy time, vehicle type, vertical and horizontal coordinates, and vehicle speed, and obtains corresponding sensing data based on absolute coordinates; and a traffic information transmission unit that transmits the captured images of the CCTV camera and the sensed data collected through the traffic information collection unit to the integrated control server through the network.

Additionally, the absolute coordinates include GPS information.

In addition, the integrated control server includes an image conversion unit that labels the data received from the traffic information collection device as the same object as the video captured by the CCTV camera, objects the vehicles, analyzes them, and converts them into images; and an image mapping unit that maps the converted vehicle image to the entire screen area and background space based on the absolute coordinates.

Additionally, the background space is characterized by including an image generated through 3D GIS (Geographic Information System) modeling.

In addition, the image mapping unit is characterized by using a wavelet (Wavelet transform) image fusion algorithm.

In addition, the mapping unit is characterized in that it continuously displays the mapped vehicle image in the form of driving at the corresponding speed in the corresponding lane according to the detection data acquired through the radar sensor.

The road traffic situation monitoring method according to the present invention to achieve the above purpose automatically labels images captured by CCTV cameras that capture vehicles driving on the first road section and obtains the length and vehicle number of the vehicle based on absolute coordinates. And, based on the detection results of a radar sensor that detects vehicles driving on a second road section following the first road section, unique object ID, lane information, entry time, passing time, and occupancy for the corresponding vehicles. A traffic information collection step of recognizing time, vehicle type, vertical and horizontal coordinates, and vehicle speed, and obtaining corresponding sensing data based on absolute coordinates; A traffic information transmission step of transmitting the captured images of the CCTV camera and the sensed data collected through the traffic information collection step to an integrated control server through a network; An image conversion step of objectifying and analyzing the vehicles by labeling the data transmitted through the traffic information collection step as the same object as the video captured by the CCTV camera and converting it into an image; and an image mapping step of mapping the converted vehicle image to the entire area and background space of the monitor screen of the integrated control server based on the absolute coordinates.

The road traffic situation monitoring system and method according to the present invention has the following effects.

First, a certain section of road is filmed with a CCTV camera and displayed on the monitor of the integrated control center, and a much longer section that follows is detected with a data sensor, and the detection result of the radar sensor is fused with the video captured by the CCTV camera to control the vehicle. By being able to display images of people driving, it is possible to collect traffic information on longer road sections while minimizing the cost of road traffic monitoring.

Second, since the integrated control center can detect and track hundreds of vehicles per second in real time based on the images displayed on the monitor, it is effective in collecting and managing data intensively.

Third, real-time traffic flow and target analysis for specific road sections is possible, and the analysis results can be used for statistical traffic analysis.

Fourth, accurate vehicle information and traffic conditions can be obtained even in conditions of extremely low visibility due to heavy rain, night time, fog, and fire, which has the effect of monitoring and controlling traffic flow without being significantly affected by changes in the road environment.

Fifth, it has the effect of acting as a tracer that tracks a moving vehicle using the detection signal of a radar sensor.

Sixth, in areas with high multi-lane traffic, for example, highways and main roads, where many vehicles drive at high speeds, hundreds of vehicles per second can be detected and tracked in real time, making it possible to intensively collect and manage traffic information. There is a possible effect.

Seventh, the present invention can be applied to a tunnel section, and in this case, there is an effect of displaying an image similar to an image captured through a CCTV camera without photographing vehicles driving in the tunnel through a CCTV camera.

Eighth, the present invention has the effect of managing roads through on-site vehicle flow and analysis by applying it not only to the road traffic field but also to ports, schools, and smart city fields.

1 is a block diagram of a road traffic situation monitoring system according to an embodiment of the present invention.
Figure 2 is a detailed block diagram of the traffic information collection unit.
Figure 3 is an example of the installation of a traffic information collection device.
Figure 4 is a detailed block diagram of the integrated control server.
Figure 5 is an example of a road traffic situation monitoring screen according to the present invention.
Figure 6 is a flowchart of a method for monitoring road traffic conditions according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the attached drawings. First, it should be noted that when adding reference numerals to components in each drawing, the same components are given the same reference numerals as much as possible even if they are shown in different drawings. Additionally, in describing the present invention, if a detailed description of a related known configuration or function is determined to be obvious to those skilled in the art or may obscure the gist of the present invention, the detailed description will be omitted.

Figure 1 is a block diagram of a road traffic situation monitoring system according to an embodiment of the present invention, Figure 2 is a detailed block diagram of the traffic information collection unit, Figure 3 is an example installation of a traffic information collection device, and Figure 4 is an integrated control system. This is a detailed block diagram of the server, and Figure 5 is an example of a road traffic situation monitoring screen according to the present invention.

Referring to FIG. 1, the road traffic situation monitoring system 1000 according to an embodiment of the present invention includes a traffic information collection device 100, a network 200, an integrated control server 300, and a user terminal 400. .

The operation of the road traffic situation monitoring system 1000 according to the present invention configured as described above will be described with reference to FIGS. 2 to 5 as follows.

The traffic information collection device 100 captures images of vehicles traveling on the road in the first section through a CCTV camera installed on a support pole installed around the edge of the road, and is installed above the CCTV camera on the support pole and Signals that detect vehicles driving on the road in the second section, which is connected to and extends from section 1, are collected and transmitted through the network 200.

For this purpose, the traffic information collection device 100 includes a traffic information detection unit 110, a traffic information collection unit 120, and a traffic information transmission unit 130.

The traffic information detection unit 110 acquires driving images of vehicles by photographing vehicles traveling on the road within a certain section of the road based on absolute coordinates (e.g., GPS), and in the section from the certain section to a predetermined distance, After irradiating electromagnetic waves on the road, the driving direction, distance, and speed of vehicles are measured based on absolute coordinates based on the reflected waves that return.

For this purpose, the traffic information detection unit 110 includes a CCTV camera 112 and a radar sensor 113 installed at vertical intervals on a support 111 installed around the edge of the road. Here, the type of road is not particularly limited, but it is preferable that the road be a straight road, including a highway or automobile road.

The vehicle detection distance of the CCTV camera 112 and the radar sensor 113 is not particularly limited. For example, the CCTV camera 112 is installed on the road within 200M (first road section) ahead of the support stand 111. Driving images of vehicles are obtained by filming vehicles driving on the road based on absolute coordinates, and the radar sensor 113 uses electromagnetic waves to detect hundreds of vehicles driving on the road within 200 to 500 meters ahead (second road section). Their distance and speed can be detected based on absolute coordinates.

Although not shown in FIG. 3, there may be a section (e.g., 190 to 200M) where the first road section, which is the shooting section of the CCTV camera 112, and the second road section, which is the detection section of the radar sensor 113, overlap. The reason for having such an overlapping section is to secure the processing time from 200M ahead to mapping the image captured in the shooting section to the object (vehicle) detected in the second road section, as described later. .

Therefore, it is preferable that the CCTV camera 112 is installed at a certain height of the support stand 111, and the radar sensor 113 is installed at a certain distance or more in the vertical direction from the installation position of the CCTV camera 112. do.

The radar sensor 113 may be an FMCW-based radar sensor. The radar sensor 113 transmits a chirp signal whose frequency changes linearly according to the time domain, and detects distance and speed based on absolute coordinates using the signal reflected from the target (vehicle) in front. The difference between the frequency of the received signal and the transmitted frequency is obtained through the mixer of the RF module, and this is called the beat frequency. Since the beat frequency has a linear value depending on the time delay, the distance to the target can be estimated. Additionally, since a Doppler frequency shift occurs in the received beat frequency depending on the relative speed of the forward moving target, the relative speed can be obtained using this.

The traffic information collection unit 120 collects traffic information based on absolute coordinates as described above. For example, based on the captured image of the CCTV camera 112, the length and license plate number of the vehicle are recognized through automatic labeling, and the unique object ID for the vehicle is based on the detection result of the radar sensor 113. (e.g. vehicle number), absolute coordinates, lane information, entry and exit times of the detection line, occupancy time, vehicle type, vertical and horizontal coordinates, vehicle speed, etc. are recognized and the corresponding detection data is collected.

Here, the labeling method is not particularly limited and can be performed in various ways. For example, the labeling method may use any one of Bounding Box, Polygon, Polyline, Point, and Cuboid.

The traffic information transmission unit 130 controls the integrated control center through the network 200 with the captured images of the CCTV camera 112 and the sensed data collected based on absolute coordinates through the traffic information collection unit 120. Transmitted to the server 300. Here, the collected data can be gradually transmitted to the control center through an Internet of Things (IoT) communication sensor (wireless sensor). Here, the Internet of Things (IoT) may include all objects that can be wirelessly connected to an Internet network.

When displaying images of vehicles driving on the road on a display device (e.g., LCD panel), the integrated control server 300 displays the traffic information for vehicles traveling in the section up to 200M from the support stand 111. The image of the CCTV camera 112 received from the transmission unit 130 is displayed as is. However, in the road section from 200 to 500 m from the support stand 111, the integrated control server 300 detects the signal by the CCTV camera 112 based on the signal detected by the radar sensor 113 and the sensed data. The image of the vehicle captured in the section is mapped (fused) to the object recognized by the radar sensor 113, the entire area, and the background space based on the absolute coordinates and displayed in real time.

However, in order to map and display vehicle images as described above, it is necessary to match the data properties of the CCTV camera 112 and the data properties of the radar sensor 113. Additionally, it is necessary to convert the object recognized by the radar sensor 113 into an image of the same vehicle captured by the CCTV camera 112. These operations are performed in the integrated control server 300.

For this purpose, the integrated control server 300 includes an image conversion unit 310 and an image mapping unit 320.

The image conversion unit 310 labels the data received from the traffic information transmission unit 130 as the same object as the image captured by the CCTV camera 112, objectifies the target, analyzes it, and converts it into an image.

The image mapping unit 320 accurately maps the image converted as described above to the entire area and background space of the screen. To this end, the image mapping unit 320 maps based on the absolute coordinates set by the traffic information collection unit 120 and with reference to the sensed data.

For this purpose, the image mapping unit 320 may use a wavelet (Wavelet transform) image fusion algorithm. Here, a road image of a 200 to 300M section previously captured with a drone may be used as the image of the background space. As another example, an image generated by 3D (Three Dimension) GIS (Geographic Information System) modeling may be used. The image mapping unit 320 displays the image of the vehicle mapped as above on the monitor in the form of the vehicle traveling at the corresponding speed in the corresponding lane according to the detection data acquired through the radar sensor 113.

Therefore, on the monitor screen of the integrated control center, a section that is continuous with the section (e.g., 200M) actually photographed through the CCTV camera 112, that is, a section detected through the radar sensor 113 (200 to 500M) is driving. Videos of vehicles are displayed continuously in real time.

As a result, without installing the CCTV camera 112 in the second road section based on the strut 111, the image is so similar that it is difficult to distinguish it from the image actually captured through the CCTV camera 112 in the first road section. Videos of vehicles driving can be displayed on the monitor in real time.

Accordingly, the integrated control center can detect and track hundreds of vehicles per second in real time based on the images displayed on the monitor, allowing intensive data collection and effective management. In addition, real-time traffic flow and target analysis for specific road sections is possible, and the analysis results can be used for traffic statistical analysis, etc. In particular, when the weather is bad, for example, due to heavy rain, night time, fog, and fire, accurate vehicle information and traffic conditions can be identified even in extremely low visibility conditions, contributing to smooth traffic flow.

In addition, it can serve as a tracer to track a moving vehicle using the detection signal of the radar sensor 113.

In addition, in areas with high multi-lane traffic, such as highways and main roads, where many vehicles drive at high speeds, hundreds of vehicles per second can be detected and tracked in real time, making it possible to intensively collect and manage traffic information. You can.

Additionally, the present invention can be applied to a tunnel section, and in this case, the tunnel section corresponds to the second road section. Therefore, even in this case, it is possible to display images that are so similar to the images actually captured by CCTV cameras that they are difficult to distinguish, without having to film vehicles driving in the tunnel through CCTV cameras. As another example, the present invention can be applied not only to the road traffic field but also to ports, schools, and smart city fields to manage roads through on-site vehicle flow and analysis.

Users, including vehicle drivers, can receive video information displayed in real time as described above on the monitor of the integrated control center through the user terminal 400.

Figure 5 shows an example of the present invention being applied around a toll booth on a highway. In this case, in some lanes, the image captured by the CCTV camera 112 is displayed as is, and in the remaining lanes, the image captured by the CCTV camera 112 is mapped to the object (vehicle) detected by the radar sensor 113. It is displayed as Accordingly, an image as if the entire road was captured by the CCTV camera 112 is displayed.

Meanwhile, Figure 6 is a flowchart of a road traffic situation monitoring method according to an embodiment of the present invention.

Referring to Figure 6, the road traffic situation monitoring method according to an embodiment of the present invention includes a traffic information collection step (S1), a traffic information transmission step (S2), an image conversion step (S3), and an image mapping step (S4). Includes.

The road traffic situation monitoring method of the present invention will be described with reference to FIGS. 1 to 4 as follows.

In the traffic information collection step (S1), the traffic information collection unit 120 automatically labels the captured images of the CCTV camera 112, which captures vehicles driving on the first road section based on absolute coordinates, to determine the length and vehicle length of the vehicle. Based on the detection results of the radar sensor 113 that obtains the number and detects vehicles driving on the second road section following the first road section, unique object ID, lane information, and entry for the corresponding vehicles It recognizes time, passing time, occupied time, vehicle type, vertical and horizontal coordinates, and vehicle speed, and acquires corresponding sensing data based on absolute coordinates.

In the traffic information transmission step (S2), the traffic information transmission unit 130 integrates the captured images of the CCTV camera 112 and the sensed data collected through the traffic information collection step (S1) through the network 200. Transmitted to the control server 300.

In the image conversion step (S3), the image conversion unit 310 labels the data transmitted through the traffic information collection step (S2) as the same object as the image captured by the CCTV camera 112 to objectify and analyze the vehicles. Convert to image.

In the image mapping step (S4), the image mapping unit 320 maps the converted vehicle image to the entire area and background space of the monitor screen of the integrated control server 300 based on the absolute coordinates.

Although the preferred embodiments have been described and illustrated above to illustrate the technical idea of the present invention, the present invention is not limited to the configuration and operation as shown and described, and does not depart from the scope of the technical idea. Those skilled in the art will appreciate that many changes and modifications are possible to the present invention. Accordingly, all such appropriate changes, modifications and equivalents shall be considered to fall within the scope of the present invention.

100: Traffic information collection device 110: Traffic information detection unit
111: Holder 112: CCTV camera
113: Radar sensor 120: Traffic information collection unit
130: Traffic information transmission unit 200: Network
300: Integrated control west 310: Video conversion unit
320: video mapping unit 400: user terminal
1000: Road traffic situation monitoring system

Claims (9)

Through a CCTV camera, images of vehicles driving on the first road section are acquired based on absolute coordinates, and through a radar sensor, detection data of vehicles driving on a second road section following the first road section are captured in absolute coordinates. A traffic information collection device that acquires and transmits data based on traffic information; and
Images and detection data of the vehicles are transmitted from the traffic information collection device through a network, and the images of the vehicles are displayed on the screen of the monitor in the first road section, and the images of the vehicles are displayed in the second road section. an integrated control server that maps the objects recognized by the radar sensor, the entire area, and the background space based on the absolute coordinates and displays them on the monitor; Road traffic situation monitoring system including. According to paragraph 1,
The CCTV camera is
It is installed on supports installed around the edge of the road,
A road traffic situation monitoring system, wherein the radar sensor is installed at a vertical distance from the CCTV camera on the support. According to paragraph 1,
The traffic information collection device is,
By automatically labeling the video captured by the CCTV camera, the length and license plate number of the vehicle are obtained based on absolute coordinates, and based on the detection results of the radar sensor, unique object ID, lane information, entry time, A traffic information collection unit that recognizes passing time, occupied time, vehicle type, vertical and horizontal coordinates, and vehicle speed, and obtains corresponding sensing data based on absolute coordinates; and
A road traffic situation monitoring system comprising a traffic information transmission unit that transmits the captured images of the CCTV camera and the sensed data collected through the traffic information collection unit to the integrated control server through the network. According to claim 1 or 3,
The absolute coordinates are
A road traffic situation monitoring system comprising GPS information. According to paragraph 1,
The integrated control server,
An image conversion unit that labels the data received from the traffic information collection device as the same object as the video captured by the CCTV camera, objects the vehicles, analyzes them, and converts them into images; and
A road traffic situation monitoring system comprising: an image mapping unit that maps the converted vehicle image to the entire screen area and background space based on the absolute coordinates. According to clause 5,
The background space is,
A road traffic situation monitoring system characterized by including images generated through 3D GIS (Geographic Information System) modeling. According to clause 5,
The image mapping unit
A road traffic situation monitoring system characterized by using a wavelet (Wavelet transform) image fusion algorithm. According to clause 5,
The mapping unit
A road traffic situation monitoring system that continuously displays the mapped vehicle image in the form of driving at a corresponding speed in the corresponding lane according to detection data acquired through the radar sensor. By automatically labeling images captured by CCTV cameras that capture vehicles driving on the first road section, the length and license plate number of the vehicle in question are obtained based on absolute coordinates, and the second road section continues after the first road section. Based on the detection results of the radar sensor that detects vehicles, the unique object ID, lane information, entry time, passing time, occupation time, vehicle type, vertical and horizontal coordinates, and vehicle speed for the vehicles are recognized and detected accordingly. Traffic information collection step of acquiring data based on absolute coordinates;
A traffic information transmission step of transmitting the captured images of the CCTV camera and the sensed data collected through the traffic information collection step to an integrated control server through a network;
An image conversion step of objectifying and analyzing the vehicles by labeling the data transmitted through the traffic information collection step as the same object as the video captured by the CCTV camera and converting it into an image; and
A road traffic situation monitoring method comprising: an image mapping step of mapping the converted vehicle image to the entire area and background space of the monitor screen of the integrated control server based on the absolute coordinates.

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