CN103413441A - Road weather condition monitoring system and monitoring method - Google Patents
Road weather condition monitoring system and monitoring method Download PDFInfo
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Abstract
The invention discloses a road weather condition monitoring system and a monitoring method, wherein the monitoring system comprises a road weather data acquisition system, a road meteorological data processing system and a road condition execution system; the highway weather data acquisition system acquires meteorological information of a road surface and uploads the meteorological information to the highway meteorological data processing system, the highway meteorological data processing system judges meteorological conditions, and traffic operation environment early warning and control measures are issued through the road condition execution system according to requirements. The monitoring method provided by the invention has the advantages that the multiple sensors are used for fusion and identification, the accuracy of road condition identification is greatly improved, the cost is low, and the installation is convenient.
Description
Technical field
The present invention relates to automatic detection field technology, refer in particular to a kind of road weather conditions supervisory system and method for supervising.
Background technology
According to statistics, under weather condition, 75% of traffic hazard occurs in the wet-skid road surface environment, and 47% occurs in the rainy weather environment, and 15% accident and snow, hail are relevant, and 11% accident is by due to snow day road surface and muddy road face, and 2% accident is by due to the greasy weather insufficient visibility.Therefore, be necessary to carry out road conditions early warning and control under weather, with guarantee driving safety.
At present, road Weather information system (RWIS, Road Weather Information System) is the Main Means that obtains road condition data under weather with burying people's formula road surface sensor.The uncertainty that has space-time due to the weather traffic information, desirable highway weather data acquisition system should cover the system-wide section, and the RIWS cost is higher at present, flush type road surface sensor O&M is not convenient, and there is road condition monitoring facility along the line in domestic highway, and generally incomplete, monitored density and key element do not reach the problems such as requirement.
Summary of the invention
In view of this, the present invention is directed to the disappearance of prior art existence, its fundamental purpose is to provide a kind of road weather conditions supervisory system and method for supervising, uses Multi-sensor Fusion identification, greatly improves the accuracy of road conditions identification, low-cost, install convenient.
For achieving the above object, the present invention adopts following technical scheme:
A kind of road weather conditions supervisory system, comprise highway weather data acquisition system, road weather data handling system and road conditions executive system; This highway weather data acquisition system gathers the weather information on road surface and uploads to the road weather data handling system, Meteorlogical Data Handling System is judged meteorological condition by road, according to needing by the running environment early warning of road conditions executive system issuing traffic and control measure.
Preferably, described highway weather data acquisition system comprises
One road image subsystems, comprise imageing sensor and the image acquisition device that is connected in imageing sensor;
The meteorological subsystem of one road, comprise meteorological sensor and the A/D converter that is connected in meteorological sensor;
One road noise subsystem, comprise road noise sensor and the high resolution A/D converter that is connected in the road noise transducer;
One road temperature subsystem, comprise pavement temperature telemetering pickup and the image acquisition device that is connected in the pavement temperature telemetering pickup;
Wherein, meteorological the two cooperation of subsystem of described road image subsystem and road realizes the collection of road visibility situation; Described road image subsystem, the meteorological subsystem of road, road noise subsystem, path temperature subsystem coordinate realizes the wet and slippery situation collection of road.
Preferably, described imageing sensor is selected the video camera of 470 lines, low-light (level); Described pavement temperature telemetering pickup is selected the thermal camera of 8 frames/s, 120 * 80 picture numbers; Described meteorological sensor comprises that atmosphere temperature transducer, precision take barometric pressure sensor, the 1 pulse air velocity transducer as the rain sensor of 0.1mm, resolution as 0.1m/s of interior atmospheric humidity sensor, 150Pa for ± 3%RH; Described road noise sensor is selected the noise transducer of sensitivity 50Mv/Pa.
Preferably, described weather data acquisition system comprises the data transmission subsystem, and this data transmission subsystem comprises be used to the optical fiber that transmits data and be used to receiving the optical transmitter and receiver of fiber-optic signal.
Preferably, described weather data acquisition system comprises the affiliated facility subsystem, and this affiliated facility subsystem is included as system provides the power supply of electric energy be used to supporting the support of sensor.
Preferably, described road weather data handling system comprises be used to carrying out the processor of road conditions information gathering, and this processor is electrically connected with road image subsystem, the meteorological subsystem of road, road noise subsystem, path temperature subsystem respectively.
Preferably, described processor is selected the PCI04 embedded computer.
A kind of road weather conditions method for supervising comprises the following steps:
Step 1, weather conditions collection:
A, by demoder, drive the running of The Cloud Terrace and imageing sensor with embedded computer, gather video data; The road scene image that this imageing sensor photographs and pavement image are transported to embedded computer by the bus image pick-up card;
B, detect respectively atmospheric temperature, humidity, pressure and upload to embedded computer by atmosphere temperature transducer, atmosphere temperature transducer, barometric pressure sensor, by rain sensor, rainfall detected and upload to the bus image pick-up card, air velocity transducer detects the atmosphere wind speed and uploads to the bus image pick-up card, then by bus, delivers in embedded computer in the lump;
C, road noise sensor detect tire road noise, by the bus image pick-up card, are delivered in embedded computer by bus after the A/D conversion;
D, pavement temperature telemetering pickup detect the road surface infrared thermal imagery, and the road surface infrared image is transported on bus by the bus image pick-up card, thereby deliver to embedded computer;
Step 2, carry out weather Multi-sensor Fusion road conditions identification: various pavement behavior information is carried out analyzing and processing by the Information Gathering Software in embedded computer, judges the meteorological condition of road, finally uploads in the road conditions spot database.
Preferably, in step 2, Information Gathering Software comprises pretreatment module, visibility identification module, the pavement behavior identification module of road conditions sensing data.
Preferably, the pretreatment module of described road conditions sensing data to the pre-service of weather road conditions information gathering sensor, method is: the road image acquisition subsystem is after small wave converting method, Gaussian radial basis function SAM filter process, obtain road image data filtering result, deliver in the road condition data storehouse, in addition, road gas as acquisition subsystem after specified data is adopted the art frequency, gliding smoothing filtering is processed, and obtains road weather data filtering result, delivers in the road condition data storehouse;
The identification of described visibility identification module to weather road visibility, method is: at first, take the target image sample characteristics as inputting, pass through color notation conversion space RGB to HIS, obtain the target image set of eigenvectors through feature extraction stream table learning algorithm; Then, the road data set of eigenvectors of road weather data and three set of road visibility measured data collection are processed through the AdaBoost learning algorithm, and visibility numerical value is the visibility data network sorter of output design, and then identification visibility;
Described pavement behavior identification module is identified weather pavement behavior, method is: adopt histogram analysis and wavelet analysis to extract the statistical nature of pavement image spatial domain and frequency domain, design is based on the wet and slippery situation image recognition in the weather road surface neural network classifier of AdaBoost algorithm; Utilize small echo tire road noise spectrum feature, the weather road surface wet and slippery situation noise identification sorter of design support vector machine; Utilize Fourier transform to extract pavement temperature field picture spectrum signature, design is based on the wet and slippery situation sorter in weather road surface of pavement temperature spectrum; Study the data characteristics such as air humidity, rainfall amount, wind speed of different road conditions, foundation is based on the wet and slippery situation model of cognition in the road surface of road weather data, according to the sorter service condition, dynamically utilize fuzzy method to determine the weights that sorter is integrated, realize the multi-categorizer selective ensemble.
The present invention compared with prior art has obvious advantage and beneficial effect, particularly, as shown from the above technical solution: native system has merged the weather data acquisition system of the sensors such as video monitoring system and rainfall, temperature, humidity, wind speed, atmospheric pressure, pavement temperature remote measurement, noise, designed Multi-sensor Fusion identification weather road conditions information collecting platform is provided, use Multi-sensor Fusion identification to help to improve the accuracy of road conditions identification, low-cost, install convenient.
For more clearly setting forth architectural feature of the present invention and effect, the present invention is described in detail below in conjunction with accompanying drawing and specific embodiment.
The accompanying drawing explanation
Fig. 1 is Freeway Conditions early warning and the control procedure schematic diagram of the present invention's embodiment;
Fig. 2 is the information acquisition system composition diagram of the present invention's embodiment high speed highway condition;
Fig. 3 is the road conditions information gathering process flow diagram of the present invention's embodiment;
Fig. 4 is the road condition data pretreatment process figure of the present invention's embodiment;
Fig. 5 is that the present invention's the road visibility chart of embodiment is as identification process figure;
Fig. 6 is the pavement behavior identification process figure of the present invention's embodiment.
The accompanying drawing identifier declaration:
10, highway weather data acquisition system 11, road image subsystem
12, the meteorological subsystem 13 of road, road noise subsystem
14, path temperature subsystem 15, data transmission subsystem
16, affiliated facility subsystem 20, road weather data handling system
30, road conditions executive system.
Embodiment
Please refer to shown in Figure 1ly, the concrete structure that it has demonstrated the present invention's preferred embodiment, comprise highway weather data acquisition system 10, road weather data handling system 20 and road conditions executive system 30; On the one hand, these highway weather data acquisition system 10 road condition acquirings based on the trackside sensor, by road surface real-time road signal, process and deliver to road weather data handling system 20, on the other hand, the information such as (3h, 6h, 12h, 24h) temperature, rainfall in the setting-up time of road weather forecast system detection highway, also deliver to road weather data handling system 20, thereby according to special weather, report traffic circulation environmental warning and control measure by road conditions executive system 30, comprise roadupkeep, if spilt salt etc. and other Traffic Control and Guidance measure.
Described highway weather data acquisition system 10 comprises data sampling and processing and transmission three large basic functions, and it is to design according to low-cost, convenient, the high-precision principle of installation.This highway weather data acquisition system 10 forms and function is shown in Fig. 2.Road weather conditions supervisory system comprises road image subsystem 11, the meteorological subsystem 12 of road, road noise subsystem 13, path temperature subsystem 14, data transmission subsystem 15, affiliated facility subsystem 16 and the processor that is connected in each subsystem.This road image subsystem 11 comprises video camera, image acquisition device etc.; The meteorological subsystem 12 of this road comprises meteorology " five elements " sensor, A/D converter etc.; This road noise subsystem 13 comprises noise transducer, high resolution A/D converter; This path temperature subsystem 14 comprises thermal camera, image acquisition device etc.; This data transmission subsystem 15 comprises optical transmitter and receiver, optical fiber etc.; This affiliated facility subsystem 16 comprises power supply and support etc.
Wherein, meteorological subsystem 12 the two cooperation of described road image subsystem 11 and road realize the collection of road visibility situation; Described road image subsystem 11, the meteorological subsystem 12 of road, road noise subsystem 13, path temperature subsystem 14 4 coordinate realizes the wet and slippery situation collection of road; Described data transmission subsystem 15 is realized data-transformation facility, and affiliated facility subsystem 16 provides power supply and bracing frame for system.
In the design of road Weather information acquisition system, one of key reduced costs is to select rational sensor.Function according to highway weather data acquisition system 10, the sensor that needs to select has imageing sensor, remote temperature sensing sensor, meteorology " five elements " (wind speed, temperature, humidity, rainfall, atmospheric pressure) sensor and noise transducer, and design parameter is in Table 1.
According to the type of sensor in table 1 and the requirement of highway weather data acquisition system 10 low-power consumption, as the processor of road conditions information gathering, select the PCI04 embedded computer, utilize PCI04 bus image pick-up card to gather the road conditions image information, and control The Cloud Terrace and regulate camera parameters by 485 interfaces.The road noise signal gathers by the A/D in PCI04 bus data acquisition card, and the signals such as atmospheric temperature, humidity, pressure are directly by 485 interface collections of PCI04 embedded computer.The road conditions information gathering flow process as shown in Figure 3.
In road image subsystem 11,458 interfaces of PC104 embedded computer drive The Cloud Terrace and camera lens (imageing sensor) running by demoder, gather video data.The road scene image that this imageing sensor photographs and pavement image, through passage 1, are transported on the PC104 bus by PC104 bus image pick-up card, thereby deliver to the PC104 embedded computer.
In the meteorological subsystem 12 of road, by meteorological " five elements " sensor, be that atmosphere temperature transducer, atmosphere temperature transducer, barometric pressure sensor detect respectively atmospheric temperature, humidity, pressure, by 485 interfaces 2, upload to the PC104 embedded computer, in addition, rain sensor detects the atmosphere wind speed, through counter 1, upload to PC104 bus image pick-up card, air velocity transducer detects rainfall and uploads to PC104 bus image pick-up card through counter 2, then by the PC104 bus, delivers in the PC104 embedded computer in the lump.
In road noise subsystem 13, the road noise sensor detects tire road noise, by PC104 bus image pick-up card, is delivered in the PC104 embedded computer by the PC104 bus after the A/D conversion.
In path temperature subsystem 14, the pavement temperature telemetering pickup detects the road surface infrared thermal imagery, and the road surface infrared image is transported on the PC104 bus by PC104 bus image pick-up card through passage 2, thereby delivers to the PC104 embedded computer.
The pavement behavior information that each sensor detects, by the PC104 embedded computer information acquisition software analyzing and processing in the PC104 embedded computer, draws, judges the meteorological condition of road, finally uploads in the road conditions spot database.
PC104 embedded computer information acquisition software has the recognition methods of weather Multi-sensor Fusion road conditions to analyze, pretreatment module, visibility identification module, pavement behavior identification module that the road conditions sensing data is specifically arranged, the corresponding weather road conditions information gathering of each module sensor preconditioning technique, the recognition methods analysis of weather road visibility, the recognition methods of weather pavement behavior are analyzed.
Wherein, the pre-service of road conditions information gathering sensing data is the basis of road conditions identification, comprises the filtering of road weather data, road image noise remove etc., and the data pretreatment process is shown in Fig. 4.The road image acquisition subsystem, after small wave converting method, Gaussian radial basis function SAM filter process, obtains road image data filtering result, delivers in the road condition data storehouse.In addition, the meteorological acquisition subsystem of road is after the specified data sample frequency, and gliding smoothing filtering is processed, and obtains road weather data filtering result, also delivers in the road condition data storehouse.
Gliding smoothing filtering is adopted in the present invention's road weather data and the pre-service of pavement temperature data, and the proportion of data is 1s, far above the requirement of RIWS 3 min.In rain, snow weather, in road scene image, inevitably superposeed raindrop and snowflake picture noise, affect the road conditions recognition effect, needs analyze the characteristics of image of raindrop and snowflake and remove its noise.While removing the road scene image noise, noise in area-of-interest to be suppressed on the one hand, image border and grain details information will be kept on the other hand.Picture noise filtering method (as mean filter, medium filtering etc.) at present commonly used is all undesirable, this paper adopts the least square method supporting vector machine wave filter of wavelet transformation in conjunction with the gaussian radial basis function kernel function, and with penalty factor and picture noise detection threshold, determines method according to the analysis of experimental data gaussian kernel function.
In the recognition methods of weather road visibility is analyzed, visibility detection algorithm based on image processing techniques mainly is divided into two classes: the one, and utilize high resolving power, high-precision digital camera to gather visibility and calculate parameter, utilize the Kosehmieder law to calculate visibility.The method is high to equipment requirement, and the service condition harshness is promoted difficulty large.The 2nd, utilize video monitoring camera cheaply to detect road visibility.At present, in road visibility identification, target image is characterized as statistical nature or the spectrum signature of area-of-interest brightness, has ignored the edge of area-of-interest and shape details etc., can adopt manifold learning arithmetic to carry out target image feature extraction and dimensionality reduction, detailed process as shown in Figure 5.At first, take the target image sample characteristics as inputting, pass through color notation conversion space RGB to HIS, obtain the target image set of eigenvectors through feature extraction stream table learning algorithm; Then, the road data set of eigenvectors of road weather data and three set of road visibility measured data collection are processed through the AdaBoost learning algorithm, and visibility numerical value is the visibility data network sorter of output design, and then identification visibility.
In the recognition methods of weather pavement behavior was analyzed, the wet and slippery situation in road surface comprised 8 kinds of patterns, and namely road surface is dry, Wei Shi, road surface, road surface is moist, road surface is micro-wets and deicer is arranged, road surface is moist and deicer, the solidifying frost in road surface, road snow and road surface icing are arranged.Road surface wet and slippery situation picture material complexity, can only gather finite sample under study for action.
The wet and slippery situation sorter in road surface adopted image spatial domain statistical nature the simple neural network classifier that uses mostly in the past, and identification accuracy and generalization ability all have much room for improvement.Therefore, how to extract and yojan pavement image spatial domain and frequency domain characteristics of image, and utilize one of key problem that finite sample design road conditions image recognition sorter efficient, that generalization is good is the research of weather road surface road conditions image recognition from now on.Utilize multi-sensor information fusion to help to improve the accuracy of pattern-recognition.In the wet and slippery situation identification in road surface, adopt histogram analysis and wavelet analysis to extract the statistical nature of pavement image spatial domain and frequency domain, design is based on the wet and slippery situation image recognition in the weather road surface neural network classifier of AdaBoost algorithm; Utilize small echo tire road noise spectrum feature, the weather road surface wet and slippery situation noise identification sorter of design support vector machine; Utilize Fourier transform to extract pavement temperature field picture spectrum signature, design is based on the wet and slippery situation sorter in weather road surface of pavement temperature spectrum; Study the data characteristicses such as air humidity, rainfall amount, wind speed of different road conditions, set up based on the wet and slippery situation model of cognition in the road surface of road weather data.According to the sorter service condition, dynamically utilize fuzzy method to determine the weights that sorter is integrated, realize the multi-categorizer selective ensemble.Concrete real Fig. 6 pavement behavior identification process.
During the modular design of weather road conditions recognition system software function, road condition acquiring software should have the functions such as data acquisition, data processing, data storage, data transmission and Long-distance Control.Data acquisition comprises: whether normal 1. sensor selftest module, detect each sensor; 2. road scene and pavement image acquisition module, every 3 min gather a width pavement image and road sign images; 3. the pavement temperature acquisition module, gather pavement temperature and pass through to regulate the cradle head control sampled point; 4. road meteorological data collection module, gather the data such as atmospheric temperature, humidity, pressure, wind speed, rainfall, and proportion is 1 Hz; 5. road noise acquisition module, collection vehicle track noise, proportion 200 Hz.Data are processed and to be comprised: 1. traffic information pretreatment module, the filtering of road weather data and pavement temperature, the noise characteristic extraction of road scene image noise remove ,Tai road etc.; 2. road visibility identification module, detect road visibility, sense cycle 3 min; 3. the pavement behavior identification module, detect the wet and slippery situation in road surface, sense cycle 3min.
Data storages comprises: 1. data memory module, and the storage Various types of data, data item is as shown in table 2, represents 8 kinds of road conditions patterns with 1～8; 2. the data query module, inquire about Various types of data.Data transmission and Long-distance Control comprise: 1. data transmission module uploads to Surveillance center's database by network programming by the road conditions recognition result; 2. remote data control module, in Surveillance center by the network control Spot Data Acquisition System.
In addition, as a kind of preferred version, the highway weather data acquisition system 10 of the present invention's design is experiment porch, can also further carry out following research:
1) road conditions information gathering sensing data preprocess method research under weather.Analyze traffic information demand for services under weather, clear and definite road condition data item and frequency acquisition, development data management system.On this basis, carry out weather data filtering weather road conditions information gathering sensing data pre-service (comprising sensing data smothing filtering, the removal of weather road conditions picture noise etc.) method research.
2) based on the road visibility identification of video image, study with correction algorithm.Goal in research image characteristics extraction and dimension reduction method, design road visibility sorter; The space length of evaluating objects image is to knowing
Other result affect rule, determine the parameters such as lens focus of target image optimal spatial distance and CCTV camera; Analyze simultaneously the meteorological condition of road environment
3) the wet and slippery situation multi-sensor information fusion in road surface recognition methods research under weather.Extract pavement image ,Tai road noise and weather data feature, for the wet and slippery situation Finite Samples in road surface, study effective learning algorithm and design the wet and slippery recognition classifier of road conditions of various kinds of sensors; Analyze the service condition of various sorters, research weather road surface wet and slippery situation multi-categorizer selective ensemble method.
4) road conditions information gathering commercialization technical research under weather.Utilize DSP and MCU exploitation highway weather data acquisition system 10, reduce volume and the power consumption of system, improve the reliability of system.
To sum up, the present invention studies low-cost highway weather data acquisition system 10 framework scheme under weather, the basic design principles that proposes road Weather information acquisition system is low-cost, convenient, the high precision of installation, and should have the basic functions such as data sampling and processing and transmission; Designed on this basis the road Weather information acquisition system framework formed by sensors such as the existing video monitoring system of highway and rainfall, temperature, humidity, wind speed, atmospheric pressure, pavement temperature remote measurement, noises; Analyze the filtering of road weather data and video image moderate rain, snow noise remove method, proposed the wet and slippery situation identification process in weather road visibility and road surface; Propose road condition acquiring software and should have the functions such as data acquisition, data processing, data storage, data transmission and Long-distance Control, and each function of road conditions acquisition software has been carried out to modular design.Solved that the current highway of highway road condition monitoring facility along the line is incomplete, monitored density and key element generally do not reach and require and the low situation of road conditions identification intelligent degree.
The above, it is only preferred embodiment of the present invention, not technical scope of the present invention is imposed any restrictions, therefore every foundation technical spirit of the present invention all still belongs in the scope of technical solution of the present invention any trickle modification, equivalent variations and modification that above embodiment does.
Claims (10)
1. a road weather conditions supervisory system, is characterized in that: comprise highway weather data acquisition system, road weather data handling system and road conditions executive system; This highway weather data acquisition system gathers the weather information on road surface and uploads to the road weather data handling system, Meteorlogical Data Handling System is judged meteorological condition by road, according to needing by the running environment early warning of road conditions executive system issuing traffic and control measure.
2. road weather conditions supervisory system according to claim 1, it is characterized in that: described highway weather data acquisition system comprises:
One road image subsystems, comprise imageing sensor and the image acquisition device that is connected in imageing sensor;
The meteorological subsystem of one road, comprise meteorological sensor and the A/D converter that is connected in meteorological sensor;
One road noise subsystem, comprise road noise sensor and the high resolution A/D converter that is connected in the road noise transducer;
One road temperature subsystem, comprise pavement temperature telemetering pickup and the image acquisition device that is connected in the pavement temperature telemetering pickup;
Wherein, meteorological the two cooperation of subsystem of described road image subsystem and road realizes the collection of road visibility situation; Described road image subsystem, the meteorological subsystem of road, road noise subsystem, path temperature subsystem coordinate realizes the wet and slippery situation collection of road.
3. road weather conditions supervisory system according to claim 2, it is characterized in that: described imageing sensor is selected the video camera of 470 lines, low-light (level); Described pavement temperature telemetering pickup is selected the thermal camera of 8 frames/s, 120 * 80 picture numbers; Described meteorological sensor comprises that atmosphere temperature transducer, precision take barometric pressure sensor, the 1 pulse air velocity transducer as the rain sensor of 0.1mm, resolution as 0.1m/s of interior atmospheric humidity sensor, 150Pa for ± 3%RH; Described road noise sensor is selected the noise transducer of sensitivity 50Mv/Pa.
4. road weather conditions supervisory system according to claim 1, it is characterized in that: described weather data acquisition system comprises the data transmission subsystem, and this data transmission subsystem comprises be used to the optical fiber that transmits data and be used to receiving the optical transmitter and receiver of fiber-optic signal.
5. road weather conditions supervisory system according to claim 1, it is characterized in that: described weather data acquisition system comprises the affiliated facility subsystem, this affiliated facility subsystem is included as system provides the power supply of electric energy be used to supporting the support of sensor.
6. road weather conditions supervisory system according to claim 2, it is characterized in that: described road weather data handling system comprises be used to carrying out the processor of road conditions information gathering, and this processor is electrically connected with road image subsystem, the meteorological subsystem of road, road noise subsystem, path temperature subsystem respectively.
7. road weather conditions supervisory system according to claim 6, it is characterized in that: described processor is selected the PCI04 embedded computer.
8. road weather conditions method for supervising is characterized in that: comprise the following steps:
Step 1, weather conditions collection:
A, by demoder, drive the running of The Cloud Terrace and imageing sensor with embedded computer, gather video data; The road scene image that this imageing sensor photographs and pavement image are transported to embedded computer by the bus image pick-up card;
B, detect respectively atmospheric temperature, humidity, pressure and upload to embedded computer by atmosphere temperature transducer, atmosphere temperature transducer, barometric pressure sensor, by rain sensor, rainfall detected and upload to the bus image pick-up card, air velocity transducer detects the atmosphere wind speed and uploads to the bus image pick-up card, then by bus, delivers in embedded computer in the lump;
C, road noise sensor detect tire road noise, by the bus image pick-up card, are delivered in embedded computer by bus after the A/D conversion;
D, pavement temperature telemetering pickup detect the road surface infrared thermal imagery, and the road surface infrared image is transported on bus by the bus image pick-up card, thereby deliver to embedded computer;
Step 2, carry out weather Multi-sensor Fusion road conditions identification: various pavement behavior information is carried out analyzing and processing by the Information Gathering Software in embedded computer, judges the meteorological condition of road, finally uploads in the road conditions spot database.
9. road weather conditions method for supervising according to claim 8, it is characterized in that: in step 2, Information Gathering Software comprises pretreatment module, visibility identification module, the pavement behavior identification module of road conditions sensing data.
10. road weather conditions method for supervising according to claim 9 is characterized in that:
The pretreatment module of described road conditions sensing data to the pre-service of weather road conditions information gathering sensor, method is: the road image acquisition subsystem is after small wave converting method, Gaussian radial basis function SAM filter process, obtain road image data filtering result, deliver in the road condition data storehouse, in addition, road gas is as acquisition subsystem after specified data is adopted the art frequency, and gliding smoothing filtering is processed, obtain road weather data filtering result, deliver in the road condition data storehouse;
The identification of described visibility identification module to weather road visibility, method is: at first, take the target image sample characteristics as inputting, pass through color notation conversion space RGB to HIS, obtain the target image set of eigenvectors through feature extraction stream table learning algorithm; Then, the road data set of eigenvectors of road weather data and three set of road visibility measured data collection are processed through the AdaBoost learning algorithm, and visibility numerical value is the visibility data network sorter of output design, and then identification visibility;
Described pavement behavior identification module is identified weather pavement behavior, method is: adopt histogram analysis and wavelet analysis to extract the statistical nature of pavement image spatial domain and frequency domain, design is based on the wet and slippery situation image recognition in the weather road surface neural network classifier of AdaBoost algorithm; Utilize small echo tire road noise spectrum feature, the weather road surface wet and slippery situation noise identification sorter of design support vector machine; Utilize Fourier transform to extract pavement temperature field picture spectrum signature, design is based on the wet and slippery situation sorter in weather road surface of pavement temperature spectrum; Study the data characteristics such as air humidity, rainfall amount, wind speed of different road conditions, foundation is based on the wet and slippery situation model of cognition in the road surface of road weather data, according to the sorter service condition, dynamically utilize fuzzy method to determine the weights that sorter is integrated, realize the multi-categorizer selective ensemble.
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Cited By (33)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103971523A (en) * | 2014-05-21 | 2014-08-06 | 南通大学 | Mountainous road traffic safety dynamic early-warning system |
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| CN103971523A (en) * | 2014-05-21 | 2014-08-06 | 南通大学 | Mountainous road traffic safety dynamic early-warning system |
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| CN104269051A (en) * | 2014-10-17 | 2015-01-07 | 成都四为电子信息股份有限公司 | Expressway monitoring and management system |
| CN104269051B (en) * | 2014-10-17 | 2017-02-15 | 成都四为电子信息股份有限公司 | Expressway monitoring and management system |
| CN104318780A (en) * | 2014-10-31 | 2015-01-28 | 重庆大学 | Expressway event detection method with meteorological factor and road alignment factor considered |
| CN104318780B (en) * | 2014-10-31 | 2016-07-13 | 重庆大学 | Consider the freeway incident detection method of meteorological factor, road alignment factor |
| CN105702024A (en) * | 2014-11-24 | 2016-06-22 | 北京卓越信通电子股份有限公司 | Method and system for surveying road condition through terminal |
| CN107408202B (en) * | 2015-03-05 | 2020-09-15 | Kpit技术有限责任公司 | Method and system for detecting ambient light |
| CN107408202A (en) * | 2015-03-05 | 2017-11-28 | Kpit技术有限责任公司 | For detecting the method and system of ambient light |
| US10636099B1 (en) | 2015-04-30 | 2020-04-28 | Allstate Insurance Company | Enhanced unmanned aerial vehicles for damage inspection |
| CN104978418A (en) * | 2015-06-29 | 2015-10-14 | 杨昕吉 | Intelligent weather image acquisition and identification method and system |
| CN105021528A (en) * | 2015-07-15 | 2015-11-04 | 安徽皖通科技股份有限公司 | Road weather detection device based on videos |
| US10650235B2 (en) | 2015-09-11 | 2020-05-12 | SZ DJI Technology Co., Ltd. | Systems and methods for detecting and tracking movable objects |
| US10198634B2 (en) | 2015-09-11 | 2019-02-05 | SZ DJI Technology Co., Ltd. | Systems and methods for detecting and tracking movable objects |
| CN105425318A (en) * | 2015-12-21 | 2016-03-23 | 无锡信大气象传感网科技有限公司 | Expressway weather monitoring system with self-detection function |
| CN105675055A (en) * | 2016-01-26 | 2016-06-15 | 云南电网有限责任公司电力科学研究院 | Icing prediction and early-warning method and system of power transmission lines |
| US9802599B2 (en) | 2016-03-08 | 2017-10-31 | Ford Global Technologies, Llc | Vehicle lane placement |
| US11727495B1 (en) | 2016-04-11 | 2023-08-15 | State Farm Mutual Automobile Insurance Company | Collision risk-based engagement and disengagement of autonomous control of a vehicle |
| US11656094B1 (en) | 2016-04-11 | 2023-05-23 | State Farm Mutual Automobile Insurance Company | System for driver's education |
| US20230042735A1 (en) * | 2016-04-11 | 2023-02-09 | State Farm Mutual Automobile Insurance Company | System for Determining Road Slipperiness in Bad Weather Conditions |
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| CN107463141A (en) * | 2016-06-03 | 2017-12-12 | 通用汽车环球科技运作有限责任公司 | Delivery vehicle intelligent perception detects road and the method and apparatus of weather condition data |
| CN106097744B (en) * | 2016-08-15 | 2018-05-22 | 山东交通学院 | A kind of expressway fog real-time monitoring system and method based on generalized information system |
| CN106097744A (en) * | 2016-08-15 | 2016-11-09 | 山东交通学院 | A kind of expressway fog real-time monitoring system and method based on generalized information system |
| US10739258B2 (en) | 2016-09-30 | 2020-08-11 | Ford Global Technologies, Llc | Device that generates salt-state information of a road |
| CN106781591A (en) * | 2016-12-19 | 2017-05-31 | 吉林大学 | A kind of city vehicle navigation system based on bus or train route collaboration |
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| CN109532670A (en) * | 2018-11-28 | 2019-03-29 | 广州市网拓信息技术有限公司 | A kind of on-vehicle safety Distance Judgment device extremely software uses principle |
| CN109686083B (en) * | 2018-12-10 | 2021-10-08 | 山东交通学院 | Road camera-based road icing monitoring method and system |
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| CN111016903A (en) * | 2019-12-30 | 2020-04-17 | 广州赛特智能科技有限公司 | System and method for guaranteeing driving safety of automatic driving vehicle in rainy days |
| CN113034902A (en) * | 2021-03-05 | 2021-06-25 | 阿里云计算有限公司 | Traffic control method and device and electronic equipment |
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