CN114299715A - Expressway information detection system based on videos, laser radar and DSRC - Google Patents
Expressway information detection system based on videos, laser radar and DSRC Download PDFInfo
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Abstract
The invention discloses a highway information detection system based on information fusion of a video, a laser radar and a DSRC multi-source sensor, which comprises: the road side subsystem is arranged according to road sections divided by a set distance and used for detecting road information and integrating the road information and then sending the road information; the DSRC communication module is used for receiving and transmitting road information sent by the roadside subsystem; and the vehicle-mounted subsystem is arranged on the vehicle and used for receiving the road information transmitted by the DSRC communication module, processing the road information and converting a processing result into sound and light information which can be understood by a driver. This system can realize road information with real-time wireless to navigating mate of sound, light form with road information wireless to on-vehicle unit to guarantee that the navigating mate need not to observe information such as the sign of roadside just can know traffic conditions, access & exit information on the highway, increased the convenience and the security of people's trip.
Description
Technical Field
The invention relates to the technical field of highway roadside equipment, in particular to a highway information detection system based on videos, laser radars and DSRC.
Background
The highway needs to be managed, maintained, flow induced and the like, can inform drivers of road traffic conditions through various means, and can ensure that the road is smooth and can be used as normal as possible under various weather conditions.
At present, highway management is still in a relatively preliminary stage, and road indication still uses static signs marked beside or above the road in a conspicuous font, such as "accident-prone section, attention safety", "next exit 200 m", and the like. The driver controls the speed of the vehicle at a proper level (too fast, cannot see information clearly, too slow, and influences the road traffic efficiency), and the information on the indicating signs is observed to judge the measures to be taken.
The problems of the prior art are as follows:
the prior art has limited information that can be conveyed to the driver.
Because of the limitation of field conditions, some large and striking characters or patterns are adopted on the roadside sign as much as possible so that a driver can watch the roadside sign, and the area of the sign is limited, so that the number of prompt characters on the sign is small, prompt information is not comprehensive enough, and for the understanding of the images, everyone can understand the sign with deviation and some signs which cannot be understood by the people can appear. These problems all result in a diminished or even lost prompting capability of the prompting device.
② the prior art has limited guiding ability.
Under the condition that the prior road side information indicating signs meet the weather such as rain, fog, snow and the like, the prompting information signs can be unclear or even invisible, the using effect of the road signs is influenced, and if the weather condition is severe, the road signs even completely fail to play any prompting role.
In addition, the branch road information indicator in the prior art can only be arranged at the branch road and cannot be displayed to the driver in advance, but at the safe distance from the branch road, the driver cannot clearly see the content of the indicator due to the fact that the information indicator is too far away, and cannot select a lane in advance according to the information provided by the information indicator; the speed of vehicles on the highway is very fast, and when the vehicles arrive at a turnout and see the indication board clearly, the lane is selected later. Therefore, in order to see the intersection information indicator clearly, the driver can only start to slow down and walk slowly from a far place, and the passing efficiency of the road is influenced.
And the potential safety hazard of the prior art is high.
Because the speed of a vehicle on the highway is relatively fast, a driver needs to pay attention to traffic safety, and the condition that the driver misses a highway exit or walks by mistake at a fork road due to missed and mislooked sign information at the side of the road is avoided. Particularly, in the area of a fork, it is difficult for the driver to clearly see the sign in a short time and select the correct road. Once the user walks in a wrong way, the user needs to open a far distance to have an exit or a turning place, so that energy and time are wasted; in order to avoid information omission, some drivers stop at the branch road junction, continuously change lanes at the branch road junction, and even some drivers reverse and drive reversely on the expressway after missing the junction. These are very dangerous behaviors and are very likely to cause traffic accidents.
And fourthly, the information updating in the prior art is lagged and the cost is high.
The prior art can only place static sign once only, can't implement the condition according to the road, in time adjusts the wayside sign information that needs to transmit to the driver according to the road surface condition at any time. The expressway is often hundreds of kilometers, and the updating of the roadside indicating signs along the line is high in cost, labor is wasted, and the updating period is very long.
Therefore, how to provide a highway information detection system based on video, lidar and DSRC is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
In view of the above, the present invention provides a video, lidar and DSRC-based highway information detection system, which can interconnect road information and vehicle-mounted information, and transmit the road information to a driver in the form of sound and light, thereby ensuring that the driver can know traffic conditions, entrance and exit information and the like on a highway without observing information such as a sign board and the like on a road.
In order to achieve the purpose, the invention adopts the following technical scheme:
a video, lidar and DSRC-based highway information detection system comprising:
the road side subsystem is arranged according to road sections divided by a set distance and used for detecting road information and integrating the road information and then sending the road information;
the DSRC communication module is used for receiving and transmitting road information sent by the road side subsystem;
and the vehicle-mounted subsystem is arranged on the vehicle and used for receiving the road information transmitted by the DSRC communication module, processing the road information and converting a processing result into sound and light information which can be understood by a driver.
Compared with the prior art, the highway information detection system based on the video, the laser radar and the DSRC can interconnect road information and vehicle-mounted information, and the road information is transmitted to a driver in a sound and light mode, so that the driver can know traffic conditions, entrance and exit information and the like on the highway without observing information such as signs beside the road, and convenience and safety of people in traveling are improved.
In order to optimize the above technical solution, the road side subsystem includes a road side sensor, a road side processing unit and a road side communication unit, wherein:
the roadside sensor is used for acquiring road information of the expressway;
the roadside processing unit is used for receiving road information acquired by the roadside sensor, converting the road information into a unified world coordinate system after identification processing, fusing and marking the converted data into a high-precision map, splicing the high-precision maps of adjacent road sections to form road environment information and transmitting the road environment information to the roadside communication unit;
and the roadside communication unit is connected with the DSRC communication module, is used for receiving the road environment information sent by the roadside processing unit, and sends the road environment information to the vehicle-mounted subsystem through the DSRC communication module.
In order to optimize the technical scheme, the roadside sensor comprises a camera and a laser radar,
the camera is used for acquiring a road video image, identifying the type, shape and position information of objects in the video image, including but not limited to surrounding pedestrians, vehicles, traffic signs, lane lines, signal lamps and the like, and transmitting the information to the roadside processing unit;
the laser radar is used for detecting information of the obstacles, generating laser point cloud from the information of the obstacles and transmitting the laser point cloud to the road side processing unit.
In order to optimize the technical scheme, the roadside sensor further comprises a meteorological detection sensor, and meteorological data acquired by the meteorological detection sensor are transmitted to the roadside processing unit.
In order to optimize the technical scheme, the roadside communication unit is further configured to receive road state information issued by a management center and send the road state information to the roadside processing unit, and the roadside processing unit is further configured to receive the road state information sent by the roadside communication unit and mark the road state information in a high-precision map.
In order to optimize the technical scheme, when the roadside processing unit receives the road information collected by the roadside sensor, identifies the road information and converts the road information into a unified world coordinate system, the roadside processing unit executes the following operations:
adding all roadside sensors to a unified world coordinate system;
receiving the video image acquired by the camera, identifying the types, shapes and positions of objects in the video image, including but not limited to surrounding pedestrians, vehicles, traffic signs, lane lines, signal lamps and the like, and converting the objects into a unified world coordinate system;
receiving laser point cloud generated by the laser radar, identifying whether obstacles exist or not and corresponding positions, and converting the obstacles into a unified world coordinate system;
and receiving meteorological data acquired by the meteorological detection sensor, and converting the meteorological data into a unified world coordinate system.
In order to optimize the technical scheme, the high-precision map comprises four layers, wherein the first layer is a preset road static high-precision map information layer, the second layer is a road state information layer, the third layer is a road dynamic environment information layer, and the fourth layer is a road traffic state information layer.
In order to optimize the above technical solution, the fusing and labeling the converted data in the high-precision map includes:
marking the road state information received by the road side communication unit on a second layer;
marking road information obtained by the road side sensor on a third layer;
and according to the road state information received by the road side communication unit and the road information obtained by the road side sensor, macroscopic traffic flow condition information is generated by fusion and is marked on the fourth layer.
In order to optimize the technical scheme, the vehicle-mounted subsystem comprises a wireless transceiver module, a calculation processing module and an output module which are connected in a bus mode,
the wireless transceiving module is used for receiving the road information transmitted by the DSRC communication module and transmitting the road information to the computing processing module through a bus;
the calculation processing module is used for processing the received road information and generating a calculation result to be transmitted to the output device through a bus,
and the output module is used for receiving the data sent by the calculation processing module and displaying the road condition information to the driver through sound or light output.
In order to optimize the technical scheme, the camera comprises a camera module, a video encoder module and a preprocessing module between the camera module and the video encoder module, wherein the preprocessing module comprises a camera parameter adjusting module, a video image quality detecting module, an image quality enhancement degree control module and an image quality enhancement module.
The video image quality detection module is arranged to be triggered periodically at set time intervals so as to detect and evaluate the quality of the video image signal output by the camera module;
the camera parameter adjusting module is set to adjust the camera parameters of one or more attributes of the image quality according to the detection evaluation result of the video image quality detection module, control and improve the acquisition capability of the camera at the corresponding attributes, and output the video image signals to the encoder module when the camera attribute parameters are adjusted to reach steady state balance;
the image quality enhancement degree control module is set to determine the enhancement degree of the image quality attribute to be enhanced when one or more attributes of the image quality still need to be enhanced after the camera parameter adjusting module adjusts the camera parameters;
the image quality enhancement module is configured to enhance the image quality attribute to be enhanced according to the enhancement degree determined by the image quality enhancement degree control module, and then output the video image signal to the encoder module.
By the technical scheme, the self-adaptive control and adjustment capacity of the camera can be improved, the quality of a video image is effectively enhanced, and the accuracy of road information is improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
Fig. 1 is a block diagram of a structure of a highway information detection system based on video, lidar and DSRC according to the present invention.
FIG. 2 is a block diagram of a roadside sensor.
Fig. 3 is a block diagram of a camera structure.
Fig. 4 is a wind direction detection circuit diagram.
FIG. 5 is a circuit diagram of wind speed detection.
FIG. 6 is a view showing a structure of the installation of the roadside subsystem on the road.
Wherein: the system comprises a 1-roadside subsystem, an 11-roadside sensor, a 111-camera, a 1111-camera module, a 1112-video encoder module, a 1113-preprocessing module, a 11131-camera parameter adjusting module, a 11132-video image quality detecting module, a 11133-image quality enhancement degree control module, a 11134-image quality enhancement module, a 112-laser radar, a 113-meteorological detection sensor, a 12-roadside processing unit, a 13-roadside communication unit, a 2-DSRC communication module, a 3-vehicle-mounted subsystem, a 31-wireless transceiving module, a 32-calculation processing module and a 33-output module.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-6, an embodiment of the present invention discloses a video, lidar and DSRC-based highway information detection system, including:
the road side subsystem 1 is arranged on road sections divided according to a set distance (for example, each road section is 400 meters) and used for detecting road information and integrating the road information and then sending the road information;
the DSRC communication module 2 is used for receiving and transmitting road information sent by the roadside subsystem 1 by the DSRC communication module 2;
and the vehicle-mounted subsystem 3 is arranged on the vehicle and used for receiving the road information transmitted by the DSRC communication module 2, processing the road information and converting the processing result into sound and light information which can be understood by a driver.
In some embodiments provided by the present invention, the roadside subsystem 1 includes a roadside sensor 11, a roadside processing unit 12 and a roadside communication unit 13, wherein:
the road side sensor 11 is used for acquiring road information of the expressway;
the roadside processing unit 12 is used for receiving the road information acquired by the roadside sensor 11, performing identification processing, converting the road information into a unified world coordinate system, fusing and marking the converted data into a high-precision map, splicing the high-precision maps of adjacent road sections to form road environment information, and transmitting the road environment information to the roadside communication unit 13;
the roadside communication unit 13, the roadside communication unit 13 is connected with the DSRC communication module 2, and is used for receiving the road environment information sent by the roadside processing unit 12, and sending the road environment information to the vehicle-mounted subsystem through the DSRC communication module 2.
The roadside sensor 11 includes a camera 111 and a laser radar 112,
the camera 111 is configured to collect a road video image, identify the type, shape, and position information of an object in the video image, and transmit the information to the roadside processing unit 12;
the laser radar 112 is used for detecting information of obstacles, generating laser point cloud from the information of the obstacles and transmitting the laser point cloud to the roadside processing unit 12;
the weather detection sensor 113, and the weather data collected by the weather detection sensor 113 are transmitted to the roadside processing unit 12.
The camera 111 of the present invention comprises a camera module 1111 and a video encoder module 1112, and a pre-processing module 1113 located between the camera module 1111 and the video encoder module 1112, wherein the pre-processing module 1113 comprises a camera parameter adjusting module 11131, a video image quality detecting module 11132, an image quality enhancement degree controlling module 11133, an image quality enhancing module 11134,
the video image quality detection module 11132 is configured to be triggered periodically at set time intervals to perform detection and evaluation on the quality of the video image signal output by the camera module 1111;
the camera parameter adjusting module 11131 is configured to adjust the camera parameters of one or more attributes of the image quality according to the detection and evaluation result of the video image quality detecting module 11132, control and improve the acquisition capability of the camera at the corresponding attributes, and output the video image signals to the encoder module 1112 when the camera attribute parameters are adjusted to reach a steady state balance;
the image quality enhancement degree control module 11133 is configured to determine the enhancement degree of the image quality attribute to be enhanced when one or more attributes of the image quality still need to be enhanced after the camera parameter adjusting module 11131 adjusts the camera parameters;
the image quality enhancement module 11134 is configured to enhance the image quality attribute to be enhanced according to the enhancement degree determined by the image quality enhancement degree control module 11133, and then output the video image signal to the encoder module 1112.
The camera parameter adjusting module realizes the function through the interface driven by the bottom layer of the camera, the circuit structure of the existing camera does not need to be changed, and the function can be realized as long as a system capable of providing an application layer parameter control interface.
The video image quality detection module: for a given video image, the detection and analysis of each quality attribute can be performed simultaneously and in parallel; different attributes have different detection discrimination models, the dependent characteristics are different, and the judgment results of different image quality attributes are obtained through the characteristic extraction and characteristic analysis processes of the respective attributes. Existing discrimination methods and hardware may be employed here.
An image quality enhancement degree control module: different video images have different degrees of quality of image quality attributes, and thus the degree of enhancement required is different. The module may control the degree of image quality enhancement through the communication of the corresponding parameter size. For example, in the exposure enhancement model, there are parameters for controlling the brightness of the image, and the degree to which the image needs to be enhanced is determined according to the brightness of the current relevant image. Different quality attributes, the parameters are different.
An image quality enhancement module: the image quality enhancement module adopts different methods for different quality attributes. Either as a generic algorithm or as a self-designed method or model. The exposure enhancement can adopt a Retinex enhancement model; the noise removal can adopt a median filtering denoising algorithm and the like.
The invention can adopt a YS-MUWS-6P type six-element meteorological sensor which integrates six meteorological elements of wind speed, wind direction, rainfall, temperature, humidity and air pressure into a whole, and has the characteristics of compact structure, no moving part, firmness and durability, convenient installation and maintenance-free performance; meanwhile, the sensor is low in power consumption, can be provided with a solar charging panel and is suitable for meteorological monitoring on roads.
The sensor fusion algorithm is required to be uniformly distributed on the road side so as to ensure that the sensors cover the road section completely. For example, the cameras are arranged on the rod members above the road, the arrangement density is one for every 2 lanes in the transverse direction and one row is arranged for every 200 meters in the longitudinal direction based on the performance of the cameras, and meanwhile, the height of the rod members can be properly increased to 8 meters to ensure the coverage of the visual field of the cameras. The laser radar is arranged on a road central separation belt, is 100 meters away from the camera rod piece, is displayed by adopting a low-beam multi-laser radar and is uniformly arranged on the rod piece with the height of 2 meters. The roadside processing unit and the roadside communication unit are both arranged on a rod piece beside the road.
The roadside communication unit 13 is further configured to receive the road state information issued by the management center 4 and send the road state information to the roadside processing unit 12, and the roadside processing unit 12 is further configured to receive the road state information sent by the roadside communication unit 13 and mark the road state information in the high-precision map. Wherein the management center may be a traffic management center.
The roadside processing unit 12, when receiving the road information collected by the roadside sensor 11, identifying and converting the road information into the unified world coordinate system, executes the following operations:
adding all roadside sensors 11 to the unified world coordinate system;
receiving the video image collected by the camera 111, identifying the types, shapes and positions of objects in the video image, including but not limited to surrounding pedestrians, vehicles, traffic signs, lane lines, signal lamps and the like, and converting the objects into a unified world coordinate system;
receiving laser point cloud generated by the laser radar 112, identifying whether obstacles exist and corresponding positions, and converting the obstacles into a unified world coordinate system;
receiving the meteorological data collected by the meteorological detection sensor 113, and converting the meteorological data into a unified world coordinate system.
The method includes the steps that a camera collects video images, after basic image processing such as image transformation and noise reduction is carried out, information such as object types, approximate shapes and positions in video streams including but not limited to surrounding pedestrians, vehicles, traffic signs, lane lines and signal lamps is obtained in real time through an image recognition algorithm based on deep learning and a three-dimensional extraction method based on vision, and then obtained data are unified to a world coordinate system.
The laser radar acquires the accurate three-dimensional outline and position information of the obstacle obtained by the reflected processing point cloud picture, performs three-dimensional reconstruction on the peripheral ring, and then unifies the acquired data to a world coordinate system, which adopts a UTM coordinate system in the embodiment.
In some embodiments provided by the invention, the high-precision map comprises four layers, wherein the first layer is a preset static high-precision map information layer of a road, and an abstract high-precision map formed by actual road modeling, such as a road three-dimensional structure diagram, is marked with information such as a road name and a lane driving direction; the second layer is a road state information layer, such as speed limit and whether lane change is available. Information such as the distance between the entrance and the exit; the third layer is a road dynamic environment information layer, such as abstract structures, positions, speeds, moving directions and the like of vehicles, obstacles and the like; the fourth layer is a road traffic state information layer, such as an accident high-speed road section.
Fusing and marking the converted data in a high-precision map, comprising the following steps:
labeling the road state information received by the roadside communication unit 13 on the second layer;
marking the road information obtained by the roadside sensor 11 on the third layer;
and according to the road state information received by the road side communication unit 13 and the road information obtained by the road side sensor 11, macroscopic traffic flow condition information is generated by fusion and is marked on the fourth layer.
In some embodiments of the present invention, the onboard subsystem 3 includes a wireless transceiver module 31, a calculation processing module 32 and an output module 33 connected by a bus,
the wireless transceiving module 31 is used for receiving the road information transmitted by the DSRC communication module 2 and transmitting the road information to the calculation processing module 32 through a bus;
a calculation processing module 32 for processing the received road information and generating a calculation result to be transmitted to an output device 33 through a bus,
and the output module 33 is used for receiving the data sent by the calculation processing module 32 and outputting the information through sound or light for the driver to refer to, for example, the voice prompt of '200 meters ahead is the accident-prone road section and please drive cautiously' is sent by using multi-national languages or languages of selected countries.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. The device disclosed by the embodiment corresponds to the method disclosed by the embodiment, so that the description is simple, and the relevant points can be referred to the method part for description.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A highway information detection system based on video, lidar and DSRC, comprising:
the road side subsystem (1) is arranged according to road sections divided by a set distance and used for detecting road information and integrating the road information and then sending the road information;
the DSRC communication module (2) is used for receiving and transmitting road information sent by the road side subsystem (1);
and the vehicle-mounted subsystem (3), the vehicle-mounted subsystem (1) is arranged on the vehicle and is used for receiving the road information transmitted by the DSRC communication module (2), processing the road information and converting the processing result into sound and light information which can be understood by a driver.
2. The video, lidar and DSRC-based highway information detection system of claim 1 wherein said roadside subsystem (1) comprises a roadside sensor (11), a roadside processing unit (12) and a roadside communication unit (13), wherein:
the roadside sensor (11) is used for acquiring road information of an expressway;
the roadside processing unit (12) is used for receiving road information collected by the roadside sensor (11), converting the road information into a unified world coordinate system after identification processing, fusing and marking the converted data into a high-precision map, splicing the high-precision maps of adjacent road sections to form road environment information, and transmitting the road environment information to the roadside communication unit (13);
the roadside communication unit (13) is connected with the DSRC communication module (2) and is used for receiving the road environment information sent by the roadside processing unit (12) and sending the road environment information to a vehicle-mounted subsystem through the DSRC communication module (2).
3. The video, lidar and DSRC-based highway information detection system of claim 2 wherein said roadside sensor (11) comprises a camera (111) and a lidar (112),
the camera (111) is used for acquiring a road video image, identifying the type, shape and position information of objects in the video image, including but not limited to surrounding pedestrians, vehicles, traffic signs, lane lines, signal lamps and the like, and transmitting the information to the roadside processing unit (12);
the laser radar (112) is used for detecting information of obstacles, generating laser point cloud from the information of the obstacles and transmitting the laser point cloud to the road side processing unit (12).
4. The video, lidar and DSRC-based highway information detection system of claim 3 wherein said roadside sensor (11) further comprises a weather detection sensor (113), and weather data collected by said weather detection sensor (113) is transmitted to said roadside processing unit (12).
5. The video, lidar and DSRC-based highway information detection system according to claim 4, wherein said roadside communication unit (13) is further configured to receive road status information sent by the management center (4) and send the road status information to the roadside processing unit (12), and said roadside processing unit (12) is further configured to receive the road status information sent by said roadside communication unit (13) and mark the road status information in a high-precision map.
6. The video, lidar and DSRC-based highway information detection system according to claim 5 wherein said roadside processing unit (12) receives road information collected by said roadside sensor (11), identifies and converts into a unified world coordinate system, and performs the following operations:
adding all roadside sensors (11) to a unified world coordinate system;
receiving the video image collected by the camera (111), identifying the types, shapes and positions of objects in the video image, including but not limited to surrounding pedestrians, vehicles, traffic signs, lane lines, signal lamps and the like, and converting the objects into a unified world coordinate system;
receiving the laser point cloud generated by the laser radar (112), identifying whether obstacles exist and corresponding positions, and converting the obstacles into a unified world coordinate system;
and receiving meteorological data collected by the meteorological detection sensor (113), and converting the meteorological data into a unified world coordinate system.
7. The video, lidar and DSRC-based highway information detection system of claim 6 wherein said high accuracy map comprises four layers, a first layer being a predetermined static high accuracy map information layer for the road, a second layer being a road status information layer, a third layer being a dynamic environmental information layer for the road, and a fourth layer being a road traffic status information layer.
8. The video, lidar and DSRC-based highway information detection system of claim 7 wherein said fusing the converted data into a high precision map comprises:
marking road state information received by the roadside communication unit (13) on a second layer;
marking road information obtained by the roadside sensor (11) on a third layer;
and according to the road state information received by the road side communication unit (13) and the road information obtained by the road side sensor (11), macroscopic traffic flow condition information is generated by fusion and is marked on the fourth layer.
9. The system for detecting the information on the expressway based on the video, the laser radar and the DSRC as recited in claim 8, wherein the vehicle-mounted subsystem (3) comprises a wireless transceiver module (31), a calculation processing module (32) and an output module (33) which are connected in a bus manner,
the wireless transceiving module (31) is used for receiving the road information transmitted by the DSRC communication module (2) and transmitting the road information to the computing processing module (32) through a bus;
the calculation processing module (32) is used for processing the received road information and generating a calculation result to be transmitted to the output device (33) through a bus;
and the output module (33) is used for receiving the data sent by the calculation processing module (32) and displaying road condition information to a driver through sound or light output.
10. The video, lidar and DSRC-based highway information detection system according to any of claims 3-8, wherein said camera (111) comprises a camera module (1111) and a video encoder module (1112), and a preprocessing module (1113) located between said camera module (1111) and said video encoder module (1112), said preprocessing module (1113) comprising a camera parameter adjustment module (11131), a video image quality detection module (11132), an image quality enhancement degree control module (11133), an image quality enhancement module (11134),
the video image quality detection module (11132) is arranged to be triggered periodically at set time intervals so as to detect and evaluate the quality of the video image signal output by the camera module (1111);
the camera parameter adjusting module (11131) is configured to adjust camera parameters of one or more attributes of the image quality according to the detection and evaluation result of the video image quality detecting module (11132), control and improve the acquisition capability of the camera at the corresponding attributes, and output video image signals to the encoder module (1112) when the camera attribute parameters are adjusted to reach steady state balance;
the image quality enhancement degree control module (11133) is configured to determine the enhancement degree of the image quality attribute to be enhanced when one or more attributes of the image quality still need to be enhanced after the camera parameter adjusting module (11131) adjusts the camera parameter;
the image quality enhancement module (11134) is configured to enhance the image quality attribute to be enhanced according to the enhancement degree determined by the image quality enhancement degree control module (11133), and then output the video image signal to the encoder module (1112).
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115641719A (en) * | 2022-10-25 | 2023-01-24 | 东南大学 | Method and device for detecting pedestrians on expressway |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115641719A (en) * | 2022-10-25 | 2023-01-24 | 东南大学 | Method and device for detecting pedestrians on expressway |
| CN115641719B (en) * | 2022-10-25 | 2024-03-19 | 东南大学 | Expressway pedestrian detection method and device |
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