CN111986476A - Vehicle speed prompting method and system based on real image haze concentration sensing - Google Patents

Vehicle speed prompting method and system based on real image haze concentration sensing Download PDF

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CN111986476A
CN111986476A CN202010776210.5A CN202010776210A CN111986476A CN 111986476 A CN111986476 A CN 111986476A CN 202010776210 A CN202010776210 A CN 202010776210A CN 111986476 A CN111986476 A CN 111986476A
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image
haze concentration
haze
vehicle speed
controller
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赵丽玲
宣新潮
王炎
蔡秦烨
郁浩
高轩
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Nanjing University of Information Science and Technology
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Nanjing University of Information Science and Technology
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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
    • G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/90—Determination of colour characteristics
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30192—Weather; Meteorology

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Abstract

The invention discloses a vehicle speed prompting method and system based on real-scene image haze concentration sensing, wherein a radar velocimeter is used for monitoring the movement speed of a vehicle to be detected; acquiring a live-action image by using a camera, and sending the image to a controller; the controller is used for realizing instruction sending and speed limit value calculation of the whole system; dynamically displaying the real-time speed and the speed limit value of the detected vehicle by using a display screen; and a haze concentration sensing module is preset in the controller and used for calculating haze concentration from the real scene image and converting the haze concentration into a corresponding vehicle speed limit value. The prompting method automatically finishes vehicle speed limit prompting in real time in haze days based on an intelligent image analysis method, and solves the problem that highway traffic accidents are frequently caused by overspeed of vehicles in severe weather.

Description

Vehicle speed prompting method and system based on real image haze concentration sensing
Technical Field
The invention relates to the technical field of electronic information, in particular to an intelligent analysis and processing technology of traffic road information, and particularly relates to a vehicle speed prompting method and system based on real-scene image haze concentration perception.
Background
The number of highway traffic accidents caused by the influence of severe weather such as haze and the like is increased year by year. In the actual situation, related departments mostly set the speed limit value on the speed prompt screen manually according to information provided by weather forecast to prompt the driver for overspeed. The system has low automation degree and instantaneity, and is easy to generate wrong reminding or invalid reminding due to false alarm and missing report of weather forecast or transient change of weather state.
At present, can implement the automatic system that whether traffic road surface haze detected and reminded driver's vehicle hypervelocity, mainly divide into two types. One type is devices integrated in vehicles, such as: a vehicle-mounted weather auxiliary monitoring and variable speed limit reminding system (patent publication No. CN 108986507A);
another class is devices mounted on traffic surfaces, such as: a vehicle speed limit reminding device for haze weather (patent publication No. CN204315094U) and a haze traffic speed limit reminding device (patent publication No. CN207809065U) are provided.
However, the above system capable of automatically performing speed limit reminding on the vehicle in the haze weather still has disadvantages.
For example: the speed limiting device integrated in the vehicle needs to be installed on the vehicle, and a user needs to modify a vehicle circuit or power system and other systems by using the device, so that potential safety hazards caused by modification of the vehicle can be brought; the speed limiting device installed on the traffic road surface mainly depends on an air sensor for sensing the haze, but the accuracy requirements of the sensors on the data such as air temperature, humidity, air flow rate and the like are very strict, and the monitoring results can be greatly different by a little deviation. Therefore, the design automation degree is high, and the vehicle speed limit reminding system on the haze day is more stable and intelligent, and is an effective means for reducing the number of highway traffic accidents.
Disclosure of Invention
Aiming at the technical problem, the invention provides a vehicle speed prompting method and system based on real-scene image haze concentration perception. The prompting system can automatically complete vehicle speed limit prompting in real time in haze days based on an intelligent image analysis method, and solves the problem that highway traffic accidents are frequent due to overspeed of vehicles in severe weather.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
a vehicle speed prompting method based on real-scene image haze concentration perception,
monitoring the movement speed of the vehicle to be detected by using a radar velocimeter;
acquiring a live-action image by using a camera, and sending the image to a controller;
the controller is used for realizing instruction sending and speed limit value calculation of the whole system;
dynamically displaying the moving speed and the speed limit value of the passing vehicle by using a display screen;
a haze concentration sensing system is preset in the controller and used for calculating haze concentration from the live-action image and converting the haze concentration into a corresponding vehicle speed limit value, wherein the haze concentration is obtained through the following formula:
Df(x) 1-t (x), wherein,
t (x) is light transmittance;
Df(x) The haze concentration is adopted;
the light transmittance is obtained by the following formula:
Figure BDA0002618507280000021
wherein the content of the first and second substances,
omega is a haze scene depth parameter;
c is an image color channel comprising R, G, B three channels;
Ic(y) is an arbitrary region on the corresponding color channel image;
Acatmospheric light for corresponding color channelStrong;
the controller is internally provided with a haze weather vehicle speed limit value table in road traffic, and a vehicle motion speed limit value under the corresponding haze concentration is found out according to a haze concentration calculation result.
And for the non-uniform haze day image, the live-action image is subjected to blocking processing, then each sub-image is subjected to haze concentration perception, and finally the average value of the first fifty percent of the perceived haze concentration value is taken as the haze concentration value of the group haze image.
A vehicle speed prompt system based on real image haze concentration perception comprises:
the radar speed measuring instrument is used for monitoring the movement speed of the detected vehicle and sending the detected vehicle speed to the controller;
the camera is used for acquiring a live-action image and sending the image to the controller;
the controller is used for calculating the haze concentration from the live-action image and converting the haze concentration into a corresponding vehicle speed limit value, and comprises:
the instruction sending module is used for sending the instruction;
the haze concentration sensing module is used for calculating the haze concentration from the live-action image and converting the haze concentration into a corresponding vehicle speed limit value;
the LED display screen is used for dynamically displaying the real-time speed and the speed limit value of the detected vehicle;
and the power supply is used for supplying power to the whole vehicle speed prompting system.
The radar speed measuring instrument is a K-wave directional Doppler radar.
The camera is a TELESKY ov7670 camera.
The controller is a system on chip of texas instruments DM6446 da vinci series of processors.
The LED screen is a P10LED information guide screen.
The power supply is a Zhongde ZD-85W solar power supply system.
Has the advantages that:
the invention discloses a vehicle speed prompting system based on real-scene image haze concentration sensing, which works through a radar velocimeter, a camera, an LED screen, a power supply and the like connected to a computer system. The invention can automatically analyze the image acquired by the camera to calculate the haze concentration of the highway scene, can give the vehicle speed limit value according to the haze day speed limit rule required by traffic safety, and can prompt whether the vehicle is overspeed or not on the display screen. The method has the advantages that the speed prompt of the highway is more automatic and intelligent, and the problem that the highway traffic accidents are frequent due to overspeed of vehicles in severe weather is solved.
Drawings
Fig. 1 is a schematic block diagram of the present invention.
Fig. 2 is an embodiment of the present invention.
Wherein, 1 is the radar velocimeter, and 2 is speed of a motor vehicle suggestion screen.
Detailed Description
The following describes embodiments of the present invention in detail.
As shown in FIG. 1, the invention designs a vehicle speed prompting system based on real-scene image haze concentration sensing, which comprises a radar velocimeter, a camera, a computer system, an LED display screen and a power supply. Wherein the content of the first and second substances,
the radar velocimeter is used for monitoring the movement speed of the vehicle to be detected;
the camera is used for acquiring a live-action image and sending the image to the controller;
the controller is used for realizing instruction sending and speed limit value calculation of the whole system;
the LED display screen is used for displaying the vehicle movement speed and the speed limit numerical value and providing overspeed reminding for a driver;
the power supply is used for supplying power to the whole system.
The working process of the invention is as follows: the radar velocimeter detects the movement speed of the vehicle and sends the detected vehicle speed to the controller; the controller displays the speed of the moving vehicle on the lower half part of the LED display screen;
the controller controls the camera to shoot the current real-scene image of the highway at regular time; the controller reads the live-action image and processes the image to calculate the haze concentration, then the current vehicle speed limit value is given according to the haze concentration, and the current vehicle speed limit value is displayed on the upper half part of the LED display screen in yellow; if the speed of the vehicle exceeds the speed limit, the vehicle speed is displayed in red, and if the speed of the vehicle does not exceed the speed limit, the vehicle speed is displayed in green.
The calculation principle of the speed limit value is as follows:
reading a haze image J;
② calculating dark channel J of image Jdark；
Figure BDA0002618507280000041
According to the dark channel theory, when image J is a fog-free image, Jdark→ 0; when J isdarkWhen the value is not equal to 0, the image J must contain haze.
3 calculating the transmittance;
solving the minimum value of the atmosphere scattering model formula for any y ∈ Ω (x) region in the image J, then:
Figure BDA0002618507280000042
both sides are simultaneously divided by AcNamely:
Figure BDA0002618507280000043
then, the R, G, B channel of the pixel is solved for the minimum value in the formula (3), that is:
Figure BDA0002618507280000044
where c is the color channel (comprising R, G, B three channels).
Also because the dark channel tends towards 0, we can get:
Figure BDA0002618507280000045
and because of AcIs always positive, so equation (5) can be divided by AcNamely:
Figure BDA0002618507280000046
the transmittance estimate is obtained according to equation (2) and equation (6), i.e.:
Figure BDA0002618507280000047
because no image absolutely without haze exists, the fog scene depth parameter omega is added, the value range is usually (0-1), the empirical value is 0.95, and the formula of the transmittance is as follows:
Figure BDA0002618507280000048
fourthly, calculating the haze concentration
Fourthly-1 even haze concentration calculation
The transmittance t (x) exhibits an exponential decay with increasing β (λ) d. This results in a linear increase in 1-t (x), and for better representation, we introduce a new concept, optical thickness d (x), and let β d (x) when we denote the pixel points in the image as x. As can be seen from the above formula, the light transmittance t (x) is exponentially changed according to the optical thickness d (x), and thus directly reflects the haze concentration. The calculation of the transmittance is specifically described in the above section, and will not be described herein. After obtaining the light transmittance, we can make Df(x) For the mist concentration, the mist concentration can be estimated as:
Df(x)＝1-t(x) (9)
fourthly-2 non-uniform haze concentration
For non-uniform haze day images, such as fog of highways. The system firstly carries out blocking processing on live-action images, then carries out fog concentration perception on each sub-image, and finally takes the average value of fifty percent of the perceived fog concentration value as the fog concentration value of the group of fog-haze images.
Fifthly, calculating the speed limit value
And according to the haze concentration estimation calculation result, finding out the vehicle motion speed limit value under the corresponding haze concentration by automatically inquiring a haze weather vehicle speed limit value table in the road traffic which is well built in the computer system.
As shown in fig. 2, in an embodiment of the present invention, the radar speed measuring instrument is installed at a position 1-3 meters away from the highway, has an included angle of 30 degrees with the oncoming lane, can cover three lanes, and is located 300 meters ahead of the prompt screen;
the camera, the computer system, the LED display screen, the solar power supply system and the switch are arranged at the position 300 meters behind the radar.
In the actual work of the system, firstly, the switch is opened, and the system starts to work; the radar velocimeter detects the vehicle speed in the measuring range and transmits the vehicle speed to the computer system through a serial port, and the computer system displays the vehicle speed on an LED screen; the camera shoots the current scene, then the image is transmitted to the computer system, the computer system calculates the speed limit value, and the speed limit value is displayed on the LED display screen.
If the speed of the vehicle exceeds the speed limit, the vehicle speed is displayed in red, and if the speed of the vehicle does not exceed the speed limit, the vehicle speed is displayed in green.

Claims (8)

1. A vehicle speed prompting method based on real image haze concentration perception is characterized in that,
monitoring the moving speed of the detected vehicle by using a radar velocimeter, sending the detected vehicle speed to a controller, and displaying the speed of the moving vehicle on a display screen by using the controller;
acquiring a live-action image by using a camera, and sending the image to a controller;
a haze concentration sensing system is preset in the controller and used for calculating haze concentration from the live-action image and converting the haze concentration into a corresponding vehicle speed limit value, wherein the haze concentration is obtained through the following formula:
Df(x) 1-t (x), wherein,
t (x) is light transmittance;
Df(x) The haze concentration is adopted;
the light transmittance is obtained by the following formula:
Figure FDA0002618507270000011
wherein the content of the first and second substances,
omega is a haze scene depth parameter;
c is a color channel comprising R, G, B three channels;
Ic(y) is an arbitrary region on the corresponding color channel image;
Acthe atmospheric light intensity of the corresponding color channel;
the controller is internally provided with a road traffic haze weather vehicle speed limit value table, and according to a haze concentration calculation result, vehicle motion speed limit values under corresponding haze concentrations are found out and displayed on the display screen.
2. The vehicle speed prompting method based on real image haze concentration perception according to claim 1, wherein for the non-uniform haze day image, the real image is subjected to blocking processing, then haze concentration perception is performed on each sub-image, and finally the mean value of the first fifty percent of the perceived haze concentration value is taken as the haze concentration value of the group haze image.
3. The utility model provides a speed of a motor vehicle reminder system based on perception of outdoor scene image haze concentration which characterized in that includes:
the radar speed measuring instrument is used for monitoring the movement speed of the detected vehicle and sending the detected vehicle speed to the controller;
the camera is used for acquiring a live-action image and sending the image to the controller;
the controller is used for calculating the haze concentration from the live-action image and converting the haze concentration into a corresponding vehicle speed limit value, and comprises:
the instruction sending module is used for sending the instruction;
the haze concentration sensing module is used for calculating the haze concentration from the live-action image and converting the haze concentration into a corresponding vehicle speed limit value;
the LED display screen is used for dynamically displaying the real-time speed and the speed limit value of the detected vehicle;
and the power supply is used for supplying power to the whole vehicle speed prompting system.
4. The vehicle speed prompting system based on real-scene image haze concentration perception according to claim 3, wherein the radar velocimeter is a K-wave directional Doppler radar.
5. The vehicle speed prompting system based on real image haze concentration perception according to claim 3, wherein the camera is a TELESKY ov7670 camera.
6. The vehicle speed prompting system based on real-scene image haze concentration perception according to claim 3, wherein the controller is a system on chip of a Texas instruments DM6446 DaVinci series processor.
7. The vehicle speed prompting system based on real-scene image haze concentration perception according to claim 1, wherein the LED screen is a P10LED information guide screen.
8. The vehicle speed prompting system based on real-scene image haze concentration perception according to claim 1, wherein the power supply is a Zhongde ZD-85W solar power supply system.
CN202010776210.5A 2020-08-05 2020-08-05 Vehicle speed prompting method and system based on real image haze concentration sensing Pending CN111986476A (en)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103116876A (en) * 2013-02-22 2013-05-22 北京京东世纪贸易有限公司 Method and device for image defogging
CN103218778A (en) * 2013-03-22 2013-07-24 华为技术有限公司 Image and video processing method and device
CN204719971U (en) * 2015-05-29 2015-10-21 安徽四创电子股份有限公司 A kind of wireless remote car monitoring system based on radar velocity measurement
US20160055384A1 (en) * 2014-08-20 2016-02-25 Hyundai Mobis Co., Ltd. Vehicle control method for safety driving and device thereof
CN205375857U (en) * 2015-12-31 2016-07-06 张永堂 A induced collision avoidance system of fog -zone intelligence for highway
CN110782689A (en) * 2019-11-22 2020-02-11 杭州普乐科技有限公司 Road speed limit prompt system

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103116876A (en) * 2013-02-22 2013-05-22 北京京东世纪贸易有限公司 Method and device for image defogging
CN103218778A (en) * 2013-03-22 2013-07-24 华为技术有限公司 Image and video processing method and device
US20160055384A1 (en) * 2014-08-20 2016-02-25 Hyundai Mobis Co., Ltd. Vehicle control method for safety driving and device thereof
CN204719971U (en) * 2015-05-29 2015-10-21 安徽四创电子股份有限公司 A kind of wireless remote car monitoring system based on radar velocity measurement
CN205375857U (en) * 2015-12-31 2016-07-06 张永堂 A induced collision avoidance system of fog -zone intelligence for highway
CN110782689A (en) * 2019-11-22 2020-02-11 杭州普乐科技有限公司 Road speed limit prompt system

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
HE KAIMING ET AL.: "Single Image Haze Removal Using Dark Channel Prior", 《IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION CVPR 2009》 *
龚建伟: "单幅图像雾霾浓度感知与去雾算法研究", 《万方学位论文》 *

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Application publication date: 20201124