CN110728841B - Traffic flow acquisition method, device and system based on vehicle-road cooperation - Google Patents
Traffic flow acquisition method, device and system based on vehicle-road cooperation Download PDFInfo
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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Abstract
The embodiment of the application discloses a traffic flow acquisition method, a traffic flow acquisition device and a traffic flow acquisition system based on vehicle-road cooperation, wherein a data acquisition mode recommendation request sent by an application terminal is received; determining an environmental mode; according to the environment mode and a preset error analysis mode, a dynamic traffic flow acquisition model is established according to the dynamic traffic flow acquisition mode, error data are calculated, the error data calculated according to the dynamic traffic flow acquisition model are pushed to a database, the database calculates traffic flow according to terminal acquisition data and the error data and pushes the traffic flow to an application terminal display interface, and the problem that the accuracy of road traffic flow is influenced due to poor errors of road vehicle data acquisition caused by natural environments such as illumination, water mist, sand storm and the like is solved.
Description
Technical Field
The invention relates to the technical field of traffic internet, in particular to a traffic flow acquisition method, a traffic flow acquisition device and a traffic flow acquisition system based on vehicle-road cooperation.
Background
With the continuous development of internet technology, with the development trend of internet of things, vehicle connection, big data and cloud computing technology, vehicle coordination needs to be vigorously developed because vehicles are objects moving on roads. The system is an object, and real-time information of a vehicle is acquired when the system is connected to a traffic control center; in addition, it is also an object managed by traffic management as an end, and it is a set of two objects of "car" and "person", and information collection thereof is also very important. Although many cameras, sensors and vehicle-mounted mobile GPS systems are installed on roads in many cities in China at present, the cameras, the sensors and the vehicle-mounted mobile GPS systems can transmit a large amount of real-time traffic images and data back to a traffic monitoring and commanding center, and a traffic management and commanding department judges road conditions according to information acquired by a terminal, for example, the traffic management and commanding department judges the traffic flow of the roads by acquiring the data by the terminal and plans the traffic management according to the traffic flow of the roads.
The existing terminal acquisition equipment such as a camera is characterized in that sensors are installed outdoors, outdoor natural environment changes more, for example, windy sand in northern China is large, southern China is wet and has much rainwater, the temperature in Yangtze river basin is high, sunlight irradiation is sufficient, in order to reduce road temperature, a watering cart is generally adopted to spray water to roads, however, sunlight irradiates the road surface after water spraying and illumination reflection occurs, sunlight irradiates vehicles and illumination reflection also occurs, the illumination reflection caused by various natural environments can cause errors on data acquisition of equipment such as cameras, and therefore the accuracy of road traffic flow acquisition is reduced. In order to solve the problem that natural environment has great influence on terminal acquisition equipment, a traffic flow acquisition method, a traffic flow acquisition device and a traffic flow acquisition system based on vehicle-road cooperation are developed.
Disclosure of Invention
The invention aims to provide a traffic flow acquisition method, a traffic flow acquisition device and a traffic flow acquisition system based on vehicle-road cooperation, and aims to solve the problems that the accuracy of road traffic flow is influenced due to poor error of road vehicle data acquisition in the conventional natural environment.
In a first aspect, an embodiment of the present invention provides a traffic flow collecting method based on vehicle-road coordination, including:
receiving a data acquisition mode recommendation request sent by an application terminal;
determining an environmental mode;
determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode;
creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic vehicle acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode;
the dynamic traffic flow acquisition model analyzes according to terminal acquisition data, calculates error data, pushes the error data calculated according to the dynamic traffic flow acquisition model to a database, calculates traffic flow according to the terminal acquisition data and the error data, and pushes the traffic flow to an application terminal display interface.
With reference to the first aspect, in a first possible implementation manner of the first aspect, the determining an environmental mode includes:
acquiring a terminal acquisition environment parameter value;
according to the environmental parameter values collected by the terminal, inquiring historical contemporaneous environmental parameter values of the database, and verifying the accuracy of the environmental parameter values collected by the terminal;
if the terminal acquisition environment parameter value accords with the preset range value, determining an environment mode according to the terminal acquisition environment parameter;
and if the terminal acquisition environment parameter value does not accord with the preset range value, acquiring the terminal acquisition environment parameter again.
With reference to the first aspect, in a second possible implementation manner of the first aspect, the traffic simulation dynamic prediction sub-mode includes:
acquiring a traffic flow acquisition mode;
simulating a road condition model in a matching way according to the traffic flow acquisition mode;
carrying out environmental error marking on the acquired parameters according to a ground simulation road condition model, and measuring and calculating the moving speed of the environmental error mark to obtain a static object image mark;
and determining an error value according to the traffic flow acquisition data and the static object image mark.
With reference to the first aspect, in a third possible implementation manner of the first aspect, the traffic flow data collection and processing sub-mode includes:
acquiring a traffic flow acquisition mode;
acquiring real-time data according to a traffic flow acquisition mode, and measuring and calculating the position, the speed and the angle parameters of an illumination reflection target according to the real-time data;
acquiring road data of a database, and determining a dynamic target moving track according to the road data and real-time acquired data;
and determining a real-time acquisition data error value according to the dynamic target moving track.
In a second aspect, an embodiment of the present invention provides a traffic flow collecting device based on vehicle-road coordination, including:
the first receiving unit is used for receiving a data acquisition mode recommendation request sent by an application terminal;
an environment mode determination unit that determines an environment mode;
the first error analysis unit determines a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode;
the data processing unit is used for creating a traffic flow dynamic acquisition model according to the traffic flow acquisition mode, and the vehicle dynamic acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode;
and the vehicle data dynamic analysis unit is used for analyzing the traffic flow dynamic acquisition model according to the terminal acquisition data, calculating error data, pushing the error data calculated according to the traffic flow dynamic acquisition model to a database, calculating the traffic flow according to the terminal acquisition data and the error data by the database, and pushing the traffic flow to an application terminal display interface.
With reference to the second aspect, in a first possible implementation manner of the second aspect,
the second receiving unit is used for receiving a data acquisition mode recommendation request sent by the application terminal;
the environment parameter acquisition unit is used for acquiring the environment parameter value acquired by the terminal;
the terminal data acquisition unit is used for inquiring the historical contemporaneous environment parameter values of the database according to the terminal acquisition environment parameter values and verifying the accuracy of the terminal acquisition environment parameter values;
the first parameter determining unit is used for determining an environment mode according to the environment parameter acquired by the terminal if the environment parameter acquired by the terminal accords with a preset range value;
and the second parameter determining unit is used for acquiring the terminal acquisition environment parameters again if the terminal acquisition environment parameter values do not accord with the preset range values.
With reference to the second aspect, in a second possible implementation manner of the second aspect,
the first acquisition unit is used for acquiring a traffic flow acquisition mode;
the road condition matching unit is used for simulating a road condition model in a matching way according to the traffic flow acquisition mode;
the error marking unit is used for marking environmental errors of the acquired parameters according to the ground simulation road condition model, measuring and calculating the moving speed of the environmental error marks and obtaining static object image marks;
and the first error determining unit determines an error value according to the traffic flow acquisition data and the static object image mark.
With reference to the second aspect, in a third possible implementation manner of the second aspect,
the second acquisition unit is used for acquiring a traffic flow acquisition mode;
the real-time data acquisition unit is used for acquiring real-time data according to a traffic flow acquisition mode and measuring and calculating the position, the speed and the angle parameters of an illumination reflection target according to the real-time data;
the dynamic target determining unit is used for acquiring road data of a database and determining a moving track of a dynamic target according to the road data and the real-time acquired data;
and the second error determining unit determines the error value of the real-time acquired data according to the moving track of the dynamic target.
In a third aspect, an embodiment of the present invention provides a system for acquiring traffic flow based on vehicle-road coordination, where the system includes: the server and the data acquisition terminal are connected with the application terminal through the Internet;
the data acquisition terminal is used for sending acquired data and road real-time data to the server;
the server is used for receiving a data acquisition mode recommendation request sent by the application terminal; determining an environmental mode;
determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode; creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic vehicle acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode; the dynamic traffic flow acquisition model analyzes according to terminal acquisition data, calculates error data, pushes the error data calculated according to the dynamic traffic flow acquisition model to a database, calculates traffic flow according to the terminal acquisition data and the error data, and pushes the traffic flow to an application terminal display interface.
And the application terminal is used for receiving error data calculated according to the dynamic traffic flow acquisition model to a database, and the database calculates the traffic flow according to the terminal acquisition data and the error data.
According to the technical scheme, the traffic flow acquisition method, the traffic flow acquisition device and the traffic flow acquisition system based on vehicle-road cooperation provided by the embodiment of the application recommend a request by receiving a data acquisition mode sent by an application terminal; determining an environmental mode; determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode; creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic vehicle acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode; the dynamic traffic flow acquisition model analyzes according to terminal acquisition data, calculates error data, pushes the error data calculated according to the dynamic traffic flow acquisition model to a database, calculates traffic flow according to the terminal acquisition data and the error data by the database, and pushes the traffic flow to an application terminal display interface, so that the problem that the accuracy of road traffic flow is influenced due to poor errors of road vehicle data acquisition caused by natural environments such as illumination, water mist, wind sand and the like is solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart illustrating a method for vehicle-to-road coordination based traffic flow collection in accordance with a preferred embodiment;
FIG. 2 is a flow chart illustrating a method for vehicle-to-road coordination based traffic flow collection in accordance with yet another preferred embodiment;
FIG. 3 is a flow chart illustrating a method for vehicle-to-road coordination based traffic flow collection in accordance with yet another preferred embodiment;
FIG. 4 is a flow chart illustrating a method for vehicle-to-road coordination based traffic flow collection in accordance with yet another preferred embodiment;
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying 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, an embodiment of the present invention provides a traffic flow collecting method based on vehicle-road cooperation, where the method includes the following steps:
step S101, receiving a data acquisition mode recommendation request sent by an application terminal;
step S102, determining an environment mode;
step S103, determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode;
step S104, creating a traffic flow dynamic acquisition model according to the traffic flow acquisition mode, wherein the vehicle dynamic acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode;
and S105, analyzing the traffic flow dynamic acquisition model according to the terminal acquisition data, calculating error data, pushing the error data calculated according to the traffic flow dynamic acquisition model to a database, calculating the traffic flow according to the terminal acquisition data and the error data by the database, and pushing the traffic flow to an application terminal display interface.
And step S106, the recharging server pushes the recharging page to a display interface of the application terminal to provide multiple alternative money amounts and a user-defined money amount input box for the user, so that the recharging mode is diversified, the recharging efficiency is improved, the situation that an application platform server bearing a platform with the recharging function needs to wait is avoided, and the utilization rate of resources such as system bandwidth and a database is improved.
The embodiment recommends a request by receiving a data acquisition mode sent by an application terminal; determining environment modes, for example, natural environments such as a sand wind environment, a rainwater environment and a haze environment, wherein each natural environment mode has an independent environment mode parameter, for example, the rainwater environment is increased to enter an illumination reflection error elimination mode, according to the environment modes and a preset error analysis mode, an error value is preset in each natural environment mode, so that a traffic flow statistical error caused by errors of data information collected by terminal equipment is prevented, a traffic flow collection mode is determined, and after the traffic flow collection mode is determined, the traffic flow collection mode comprises: the system comprises a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode, wherein the user-defined traffic flow acquisition mode can set parameters according to actual conditions; creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic vehicle acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode; the dynamic traffic flow acquisition model analyzes according to terminal acquisition data, calculates error data, pushes the error data calculated according to the dynamic traffic flow acquisition model to a database, calculates traffic flow according to the terminal acquisition data and the error data, and pushes the traffic flow to an application terminal display interface.
Referring to fig. 2, an embodiment of the present invention provides another traffic flow collecting method based on vehicle-road coordination, where the method includes the following steps:
step S201, acquiring a terminal acquisition environment parameter value.
And S202, inquiring historical contemporaneous environment parameter values of the database according to the environment parameter values collected by the terminal, and verifying the accuracy of the environment parameter values collected by the terminal.
Step S203, if the terminal acquisition environment parameter value meets the preset range value, determining an environment mode according to the terminal acquisition environment parameter.
And step S204, if the terminal acquisition environment parameter value does not accord with the preset range value, acquiring the terminal acquisition environment parameter again.
In this embodiment, a terminal acquisition environment parameter value is obtained, a current environment state needs to be judged first, a database historical contemporaneous environment parameter value is queried according to the terminal acquisition environment parameter value, for example, the date is 2 months and 1 day, the terminal acquisition temperature is 0 ℃, the database query historical contemporaneous temperature is minus 1 ℃, then the current season is judged to be winter, the mode progress winter mode parameter is changed accordingly, the accuracy of the terminal acquisition environment parameter value is verified, if the terminal acquisition environment parameter value conforms to a preset range value, an environment mode is determined according to the terminal acquisition environment parameter, and if the terminal acquisition environment parameter value does not conform to the preset range value, the terminal acquisition environment parameter is obtained again.
Referring to fig. 3, an embodiment of the present invention provides another traffic flow collecting method based on vehicle-road cooperation, where the method includes the following steps:
step S301, a traffic flow acquisition mode is acquired.
And step S302, simulating a road condition model in a matching way according to the traffic flow acquisition mode.
And S303, carrying out environmental error marking on the acquired parameters according to the ground simulation road condition model, measuring and calculating the moving speed of the environmental error mark, and obtaining the static object image mark.
Step S304, determining an error value according to the traffic flow acquisition data and the static object image mark.
In this embodiment, a traffic flow acquisition mode is obtained, a road condition model is simulated in a matching manner according to the traffic flow acquisition mode, an environmental error marker is performed on acquisition parameters according to the ground simulated road condition model, the moving speed of the environmental error marker is measured and calculated to obtain a static object image marker, and an error value is determined according to traffic flow acquisition data and the static object image marker.
Referring to fig. 4, an embodiment of the present invention provides another traffic flow collecting method based on vehicle-road cooperation, where the method includes the following steps:
and S401, acquiring a traffic flow acquisition mode.
And S402, acquiring real-time data according to a traffic flow acquisition mode, and measuring and calculating the position, the speed and the angle parameters of the illumination reflection target according to the real-time data.
And step S403, acquiring road data of a database, and determining the moving track of the dynamic target according to the road data and the real-time acquired data.
And S404, determining a real-time collected data error value according to the moving track of the dynamic target.
In this embodiment, a traffic flow collection mode is acquired. And obtaining real-time data according to a traffic flow acquisition mode, and measuring and calculating the position, the speed and the angle parameters of the illumination reflection target according to the real-time data. And matching the corresponding calculation model according to the environment mode to analyze the real-time collected data, acquiring road data of the database, and determining the moving track of the dynamic target according to the road data and the real-time collected data. And determining the combination of the dynamic target moving track and road real-time collected data according to the dynamic target moving track, and determining a real-time collected data error value.
According to the technical scheme, the traffic flow acquisition method based on vehicle-road cooperation provided by the embodiment of the application judges the natural environment state by acquiring the natural environment parameters, selects the matched natural environment error calculation model according to the natural environment state, performs error elimination on images acquired by the terminal equipment through the natural environment error model, and calculates accurate traffic flow data.
The embodiment of the invention also provides a traffic flow acquisition device based on vehicle-road cooperation, which comprises:
the first receiving unit is used for receiving a data acquisition mode recommendation request sent by an application terminal;
an environment mode determination unit that determines an environment mode;
the error analysis unit determines a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode;
the data processing unit is used for creating a traffic flow dynamic acquisition model according to the traffic flow acquisition mode, and the vehicle dynamic acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode;
and the vehicle data dynamic analysis unit is used for analyzing the traffic flow dynamic acquisition model according to the terminal acquisition data, calculating error data, pushing the error data calculated according to the traffic flow dynamic acquisition model to a database, calculating the traffic flow according to the terminal acquisition data and the error data by the database, and pushing the traffic flow to an application terminal display interface.
Optionally, the environment mode determining unit includes:
the second receiving unit is used for receiving a data acquisition mode recommendation request sent by the application terminal;
the environment parameter acquisition unit is used for acquiring the environment parameter value acquired by the terminal;
the terminal data acquisition unit is used for inquiring the historical contemporaneous environment parameter values of the database according to the terminal acquisition environment parameter values and verifying the accuracy of the terminal acquisition environment parameter values;
the first parameter determining unit is used for determining an environment mode according to the environment parameter acquired by the terminal if the environment parameter acquired by the terminal accords with a preset range value;
and the second parameter determining unit is used for acquiring the terminal acquisition environment parameters again if the terminal acquisition environment parameter values do not accord with the preset range values.
Optionally, the data processing unit includes:
the first acquisition unit is used for acquiring a traffic flow acquisition mode;
the road condition matching unit is used for simulating a road condition model in a matching way according to the traffic flow acquisition mode;
the error marking unit is used for marking environmental errors of the acquired parameters according to the ground simulation road condition model, measuring and calculating the moving speed of the environmental error marks and obtaining static object image marks;
and the first error determining unit determines an error value according to the traffic flow acquisition data and the static object image mark.
Optionally, the data processing unit includes:
the second acquisition unit is used for acquiring a traffic flow acquisition mode;
the real-time data acquisition unit is used for acquiring real-time data according to a traffic flow acquisition mode and measuring and calculating the position, the speed and the angle parameters of an illumination reflection target according to the real-time data;
the dynamic target determining unit is used for acquiring road data of a database and determining a moving track of a dynamic target according to the road data and the real-time acquired data;
and the second error determining unit determines the error value of the real-time acquired data according to the moving track of the dynamic target.
According to the technical scheme, the system for acquiring the traffic flow based on the vehicle-road cooperation provided by the embodiment of the application comprises: the server and the data acquisition terminal are connected with the application terminal through the Internet;
the data acquisition terminal is used for sending acquired data and road real-time data to the server;
the server is used for receiving a data acquisition mode recommendation request sent by the application terminal; determining an environmental mode;
determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode; creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic vehicle acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode; the dynamic traffic flow acquisition model analyzes according to terminal acquisition data, calculates error data, pushes the error data calculated according to the dynamic traffic flow acquisition model to a database, calculates traffic flow according to the terminal acquisition data and the error data, and pushes the traffic flow to an application terminal display interface.
And the application terminal is used for receiving error data calculated according to the dynamic traffic flow acquisition model to a database, and the database calculates the traffic flow according to the terminal acquisition data and the error data.
The application relates to a traffic flow acquisition method, a traffic flow acquisition device and a traffic flow acquisition system based on vehicle-road cooperation, which are characterized in that a data acquisition mode recommendation request sent by an application terminal is received; determining an environmental mode; determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode; creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic vehicle acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode; the dynamic traffic flow acquisition model analyzes according to terminal acquisition data, calculates error data, pushes the error data calculated according to the dynamic traffic flow acquisition model to a database, calculates traffic flow according to the terminal acquisition data and the error data by the database, and pushes the traffic flow to an application terminal display interface, so that the problem that the accuracy of road traffic flow is influenced due to poor errors of road vehicle data acquisition caused by natural environments such as illumination, water mist, wind sand and the like is solved.
Other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the invention being indicated by the following claims.
It will be understood that the invention is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the invention is limited only by the appended claims.
Claims (2)
1. A traffic flow collection method based on vehicle-road cooperation is characterized by comprising the following steps:
receiving a data acquisition mode recommendation request sent by an application terminal;
determining an environmental mode;
determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode;
creating a dynamic traffic flow acquisition model according to the dynamic traffic flow acquisition mode, wherein the dynamic traffic flow acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode;
analyzing by the traffic flow dynamic acquisition model according to terminal acquisition data, calculating error data, pushing the error data calculated by the traffic flow dynamic acquisition model to a database, calculating traffic flow by the database according to the terminal acquisition data and the error data, and pushing the traffic flow to an application terminal display interface;
determining an environmental pattern, comprising:
acquiring a terminal acquisition environment parameter value;
according to the environmental parameter values collected by the terminal, inquiring historical contemporaneous environmental parameter values of the database, and verifying the accuracy of the environmental parameter values collected by the terminal;
if the terminal acquisition environment parameter value accords with the preset range value, determining an environment mode according to the terminal acquisition environment parameter; if the terminal acquisition environment parameter value does not accord with the preset range value, acquiring the terminal acquisition environment parameter again;
the traffic simulation dynamic prediction submode comprises the following steps:
acquiring a traffic flow acquisition mode;
simulating a road condition model in a matching way according to a traffic flow acquisition mode;
carrying out environmental error marking on the acquired parameters according to a ground simulation road condition model, and measuring and calculating the moving speed of the environmental error mark to obtain a static object image mark;
determining an error value according to the traffic flow acquisition data and the static object image mark;
the sub-mode for collecting and processing the traffic flow data comprises the following steps:
acquiring a traffic flow acquisition mode;
acquiring real-time data according to a traffic flow acquisition mode, and measuring and calculating the position, the speed and the angle parameters of an illumination reflection target according to the real-time data;
acquiring road data of a database, and determining a dynamic target moving track according to the road data and real-time acquired data;
and determining a real-time acquisition data error value according to the dynamic target moving track.
2. The utility model provides a traffic flow collection system based on vehicle and road is in coordination which characterized in that includes:
the first receiving unit is used for receiving a data acquisition mode recommendation request sent by an application terminal;
an environment mode determination unit that determines an environment mode;
the error analysis unit is used for determining a traffic flow acquisition mode according to the environment mode and a preset error analysis mode, wherein the traffic flow acquisition mode comprises the following steps: a diversified traffic flow acquisition mode and a user-defined traffic flow acquisition mode;
the data processing unit is used for creating a traffic flow dynamic acquisition model according to the traffic flow acquisition model, and the traffic flow dynamic acquisition model comprises a traffic simulation dynamic prediction sub-mode and a traffic flow data acquisition processing sub-mode; the vehicle data dynamic analysis unit is used for analyzing the traffic flow dynamic acquisition model according to the terminal acquisition data, calculating error data, pushing the error data calculated according to the traffic flow dynamic acquisition model to a database, calculating the traffic flow according to the terminal acquisition data and the error data by the database, and pushing the traffic flow to an application terminal display interface;
an ambient mode determination unit comprising:
the second receiving unit is used for receiving a data acquisition mode recommendation request sent by the application terminal;
the environment parameter acquisition unit is used for acquiring the environment parameter value acquired by the terminal;
the terminal data acquisition unit is used for inquiring the historical contemporaneous environment parameter values of the database according to the terminal acquisition environment parameter values and verifying the accuracy of the terminal acquisition environment parameter values;
the first parameter determining unit is used for determining an environment mode according to the environment parameter acquired by the terminal if the environment parameter acquired by the terminal accords with a preset range value;
the second parameter determining unit is used for acquiring the terminal acquisition environment parameters again if the terminal acquisition environment parameter values do not accord with the preset range values;
a data processing unit comprising:
the first acquisition unit is used for acquiring a traffic flow acquisition mode;
the road condition matching unit is used for simulating a road condition model in a matching way according to the traffic flow acquisition mode;
the error marking unit is used for marking environmental errors of the acquired parameters according to the ground simulation road condition model, measuring and calculating the moving speed of the environmental error marks and obtaining static object image marks;
the first error determining unit is used for determining an error value according to the traffic flow acquisition data and the static object image mark;
a data processing unit, further comprising:
the second acquisition unit is used for acquiring a traffic flow acquisition mode;
the real-time data acquisition unit is used for acquiring real-time data according to a traffic flow acquisition mode and measuring and calculating the position, the speed and the angle parameters of an illumination reflection target according to the real-time data;
the dynamic target determining unit is used for acquiring road data of a database and determining a moving track of a dynamic target according to the road data and the real-time acquired data;
and the second error determining unit determines the error value of the real-time acquired data according to the moving track of the dynamic target.
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2000011289A (en) * | 1998-06-23 | 2000-01-14 | Matsushita Electric Ind Co Ltd | Device and method for traffic flow data prediction |
TW200827670A (en) * | 2006-12-19 | 2008-07-01 | Cham-Pion Lu | Collecting apparatus for traffic flow |
CN103295403A (en) * | 2013-06-17 | 2013-09-11 | 湘潭大学 | Traffic flow visual inspection method |
CN104103183A (en) * | 2014-07-28 | 2014-10-15 | 张蕾 | Automatic modification method and system of environmental self-adaptive traffic management parameters |
US9965951B1 (en) * | 2017-01-23 | 2018-05-08 | International Business Machines Corporation | Cognitive traffic signal control |
CN207946937U (en) * | 2018-02-07 | 2018-10-09 | 南京南邮信息产业技术研究院有限公司 | Municipal intelligent traffic control system based on mobile Internet |
CN109191846A (en) * | 2018-10-12 | 2019-01-11 | 国网浙江省电力有限公司温州供电公司 | A kind of traffic trip method for predicting |
Family Cites Families (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105931458B (en) * | 2016-05-05 | 2019-02-12 | 杭州智诚惠通科技有限公司 | A kind of method of road traffic flow detection device reliability assessment |
CN107563563A (en) * | 2017-09-07 | 2018-01-09 | 深圳市蓝泰源信息技术股份有限公司 | A kind of public transit system based on big data passenger flow forecasting |
CN109683501A (en) * | 2017-10-18 | 2019-04-26 | 江苏卡威汽车工业集团股份有限公司 | A kind of intelligent automobile driving system for prompting |
US20190212153A1 (en) * | 2018-01-11 | 2019-07-11 | Continental Automotive Systems, Inc. | Vehicle position estimate using information from infrastructure |
CN109448367B (en) * | 2018-10-22 | 2020-04-10 | 南京理工大学 | Intelligent road traffic tracking management system based on big data image acquisition |
-
2019
- 2019-10-23 CN CN201911010600.5A patent/CN110728841B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2000011289A (en) * | 1998-06-23 | 2000-01-14 | Matsushita Electric Ind Co Ltd | Device and method for traffic flow data prediction |
TW200827670A (en) * | 2006-12-19 | 2008-07-01 | Cham-Pion Lu | Collecting apparatus for traffic flow |
CN103295403A (en) * | 2013-06-17 | 2013-09-11 | 湘潭大学 | Traffic flow visual inspection method |
CN104103183A (en) * | 2014-07-28 | 2014-10-15 | 张蕾 | Automatic modification method and system of environmental self-adaptive traffic management parameters |
US9965951B1 (en) * | 2017-01-23 | 2018-05-08 | International Business Machines Corporation | Cognitive traffic signal control |
CN207946937U (en) * | 2018-02-07 | 2018-10-09 | 南京南邮信息产业技术研究院有限公司 | Municipal intelligent traffic control system based on mobile Internet |
CN109191846A (en) * | 2018-10-12 | 2019-01-11 | 国网浙江省电力有限公司温州供电公司 | A kind of traffic trip method for predicting |
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