CN113781779A - 5G communication-based highway weather early warning method, equipment and medium - Google Patents
5G communication-based highway weather early warning method, equipment and medium Download PDFInfo
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- CN113781779A CN113781779A CN202111057431.8A CN202111057431A CN113781779A CN 113781779 A CN113781779 A CN 113781779A CN 202111057431 A CN202111057431 A CN 202111057431A CN 113781779 A CN113781779 A CN 113781779A
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
The application discloses a 5G communication-based highway traffic early warning method, equipment and medium, wherein the method comprises the steps of obtaining a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of a highway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the highway through the 5G base station; according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value; and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station. The driving safety of the highway is improved, and the frequency of traffic accidents is reduced.
Description
Technical Field
The application relates to the field of meteorological early warning, in particular to a 5G communication-based highway meteorological early warning method, equipment and medium.
Background
At present, with the increase of the traffic mileage of the highway, the influence of the disastrous weather on the traffic safety of the highway is increasingly obvious. Under the condition of severe weather, a driver is difficult to acquire warning information in time, and a highway administration department is also difficult to make targeted adjustment in time according to road conditions, so that congestion of a highway is caused, and even serious traffic accidents happen sometimes.
In the current weather early warning technology for the expressway, corresponding early warning is only made for the weather condition of the current road section, and the specific early warning and road management are made for different positions of the expressway without combining the weather condition of a large-scale area and the real-time road condition of the expressway.
In addition, in the prior art, when road information and weather information are acquired or early warning information is issued, the road information and the weather information are generally transmitted through a 4G communication technology, and the transmission speed is low, so that the information is difficult to acquire or issue in time.
Disclosure of Invention
In order to solve the above problems, that is, to solve the problems that it is difficult to combine the weather conditions of a large area and the real-time road conditions of a highway, make targeted early warning and road management for different positions of the highway, and the information transmission speed is slow, and it is difficult to obtain or issue information in time, the application provides a 5G communication-based highway weather early warning method, device and medium, including:
on one hand, the application provides a 5G communication-based highway traffic early warning method, which comprises the following steps: acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station; according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value; and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station so as to display the traffic early warning scheme on the information release module at the corresponding position.
In one example, prior to obtaining the plurality of weather information and traffic flow information, the method further comprises: acquiring multiple groups of historical early warning information, training an initial traffic early warning model through the historical early warning information, and obtaining a trained traffic early warning model, wherein the historical early warning information comprises: historical weather information, historical traffic flow information, historical speed limit value, historical safe interval value, the initial traffic early warning model includes: the system comprises an input layer, a fuzzy layer, a rule front-part layer, a normalization layer and an output layer; the method specifically comprises the following steps: dividing a plurality of first parameters contained in the historical meteorological information and the historical traffic flow information into a plurality of grades according to a first preset rule, and dividing a plurality of second parameters contained in the historical speed limit value and the historical safety interval value into a plurality of grades according to a second preset rule; inputting a plurality of graded first parameters to the input layer and a plurality of graded second parameters to the output layer, wherein the input layer is used for transmitting the plurality of graded first parameters to the blurring layer; inputting an initial fuzzy segmentation number, a central value of a membership function and a width value into the fuzzification layer, so that the fuzzification layer obtains the ranked first parameters and the membership values of the corresponding ranks thereof according to the membership function and the ranked first parameters, wherein the fuzzification layer is used for transmitting a plurality of first parameters with membership value identifications to the rule front-part layer; inputting a plurality of fuzzy rules to the rule front-part layer so that the rule front-part layer obtains the applicability of the first parameter with the membership value identifier and the corresponding fuzzy rule according to the fuzzy rules, the first parameter with the membership value identifier and an applicability function, wherein the rule front-part layer is used for transmitting the plurality of the applicability to the normalization layer; obtaining a normalized suitability degree through a normalization function contained in the normalization layer and the suitability degree, wherein the normalization layer is used for transmitting a plurality of normalized suitability degrees to the output layer; and inputting the connection weight value into the output layer so that the output layer obtains an output value which is the same as the second parameter according to an output function and the normalized applicability.
In one example, after inputting a connection weight value to the output layer to make the output layer obtain an output value identical to the second parameter according to an output function and the normalized applicability, the method further includes: acquiring real weather information and real traffic flow information, and acquiring corresponding recommended speed limit values and recommended safe spacing values; obtaining an actually output speed limit value and an actually output safety interval value through the real weather information, the real traffic flow information and the trained traffic early warning model; obtaining a first error between the actually output speed limit value and the recommended speed limit value and a second error between the actually output safety interval value and the recommended safety interval value according to the actually output speed limit value, the actually output safety interval value, the recommended speed limit value, the recommended safety interval value and a preset error function; if at least one of the first error and the second error is greater than a first preset threshold, adjusting one or more of the initial fuzzy partition number, the central value of the membership function, the width value of the membership function and the connection weight value until all of the first error and the second error are not greater than the first preset threshold; and obtaining a traffic early warning model.
In one example, after acquiring a plurality of traffic early warning schemes for different positions of the highway according to a pre-trained traffic early warning model and the meteorological information and the traffic flow information, the method further comprises: for any first position in different positions of the expressway, determining a corresponding second position and a corresponding third position, wherein the second position is behind a reference direction of the first position, the third position is in front of the reference direction of the first position, and the reference direction is a vehicle traveling direction; acquiring parameters of a first road section between the first position and the second position; obtaining the safe vehicle capacity of the first road section according to the parameters of the first road section, the speed limit value and the safe distance value at the first position and a prestored safe vehicle capacity function; according to the traffic flow monitoring module of the first road section, acquiring the first real-time vehicle quantity of the first road section through the 5G base station; if the number of the first real-time vehicles is larger than the safety vehicle capacity, reducing the speed limit value at the second position and/or improving the safety distance value at the second position until the number of the first real-time vehicles is not larger than the safety vehicle capacity.
In one example, if the first number of real-time vehicles is greater than the safe vehicle capacity, the speed limit value at the second position is decreased and/or the safe distance value at the second position is increased until after the first number of real-time vehicles is not greater than the safe vehicle capacity, the method further comprises: acquiring data of a second road section between the first position and the third position, and acquiring a second real-time vehicle quantity of the second road section through the 5G base station according to a traffic flow monitoring module of the second road section; obtaining the congestion rate of the second road section according to the data of the second road section, the second real-time vehicle quantity and a prestored vehicle congestion function; if the congestion rate is larger than a second preset threshold value, reducing the speed limit value at the first position and/or the safe distance value at the third position until the congestion rate is not larger than the second preset threshold value.
In one example, after obtaining the congestion rate of the second road segment according to the data of the second road segment, the second real-time vehicle number and a pre-stored vehicle congestion function, the method further includes: determining whether the third location is an entrance of the highway; if yes, generating an entrance closing instruction, and closing the entrance according to the entrance closing instruction, wherein the congestion rate is greater than a third preset threshold; if not, and the congestion rate is larger than the third preset threshold, generating a local closing instruction, and performing local closing on the first position according to the local closing instruction.
In one example, after the traffic early warning scheme is sent to the information publishing module in the corresponding location through the 5G base station, the method further includes: determining that extreme severe weather exists at the corresponding position according to the meteorological information; determining a terminal which can communicate with the 5G base station within a preset range at the corresponding position; and sending the corresponding traffic early warning scheme at the corresponding position to the terminal.
In one example, the method further comprises: determining that a vehicle is about to exit the highway; acquiring a running track and running time of the vehicle on the expressway according to the traffic flow monitoring module; according to the traffic flow monitoring module, determining that the vehicle complies with a corresponding traffic early warning scheme on the driving track within the driving time; and obtaining the high-speed fee of the vehicle, carrying out discount processing on the high-speed fee according to a prestored discount, and sending the discounted high-speed fee to an exit toll station corresponding to the vehicle.
On the other hand, this application has still provided a highway traffic early warning equipment based on 5G communication, includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to: acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station; according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value; and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station.
In another aspect, the present application further provides a non-volatile computer storage medium storing computer-executable instructions configured to: acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station; according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value; and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station.
The 5G communication-based highway weather early warning method, equipment and medium can bring the following beneficial effects: according to the traffic flow information and the weather information of different positions of the highway, a corresponding traffic early warning scheme is customized for the position instead of managing vehicles by using a unified standard, so that the driving safety of the highway is improved, and the occurrence frequency of traffic accidents is reduced. In addition, the traffic early warning in this application belongs to real-time dynamic's computational process, consequently, introduces 5G communication technology and carries out data transmission and can effectively guarantee the ageing of data, promotes traffic early warning's efficiency, and then has ensured public driving safety.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of a 5G communication-based highway weather early warning method in an embodiment of the present application;
fig. 2 is a schematic diagram of a 5G communication-based highway weather warning device in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, 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 application.
First, it should be noted that the highway traffic early warning method based on 5G communication described in the embodiments of the present application is stored or installed in a corresponding system or server, and a user may log in the system or server through a corresponding terminal, where the terminal may be a hardware device with a corresponding function, such as a mobile phone, a tablet computer, and a personal computer. The system can be pre-installed in the terminal or can be communicated with the server in a corresponding mode, for example, the system or the server can be logged in through modes such as APP, WEB pages and the like, so that traffic early warning on a highway is realized.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
As shown in fig. 1, an expressway traffic early warning method based on 5G communication provided in an embodiment of the present application includes:
s101: the method comprises the steps of obtaining a plurality of weather information and traffic flow information, wherein the weather information is sent by weather monitoring modules distributed at different positions of the highway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the highway through the 5G base station.
Specifically, a set of meteorological monitoring module and traffic flow monitoring module are arranged at certain intervals in the highway road test, various sensors are arranged in the meteorological monitoring module and the traffic flow monitoring module, and meteorological information and traffic flow information of the road section can be obtained through a sensor data fusion technology.
The fifth Generation Mobile Communication Technology (5th Generation Mobile Communication Technology, 5G) is a new Generation broadband Mobile Communication Technology with the characteristics of high speed, low time delay and large connection, and is a network infrastructure for realizing man-machine interconnection. The 5G base station is a core device of the 5G network, provides wireless coverage, and realizes signal transmission between a wired communication network and a wireless terminal. The 5G base station is mainly used for providing a 5G air interface protocol function to support communication between the user equipment and the core network.
Further, the system can obtain weather information and traffic flow information through a 5G base station arranged near the expressway, wherein the weather information at least comprises: temperature, humidity, wind speed, wind direction, atmospheric pressure, rainfall, snowfall etc. traffic flow information may include at least: vehicle speed, traffic flow, vehicle information, license plate number, etc.
Traffic early warning in this application belongs to real-time dynamic computational process, consequently, introduces 5G communication technology and carries out data transmission and can effectively guarantee the timeliness of data, promotes traffic early warning's efficiency, and then has ensured public driving safety.
S102: according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value.
Specifically, the system embeds has the traffic early warning model of training in advance, and this traffic early warning model's input layer is used for inputing meteorological information and traffic flow information, and further, through the inside data transfer of traffic early warning model and corresponding fuzzy rule, can be through output layer output traffic early warning scheme, traffic early warning scheme includes at least: speed limit value, safety interval value, overtaking limit, lane change limit, etc.
Through the traffic early warning model, the system can generate an optimal traffic early warning scheme in real time according to the received weather information and traffic flow information so as to give optimal suggestions in a targeted manner according to the weather information and the traffic flow information of the road section, thereby ensuring the driving safety to the maximum extent and avoiding traffic accidents.
S103: and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station so as to display the traffic early warning scheme on the information release module at the corresponding position.
Specifically, each set of weather monitoring module and traffic flow monitoring module is provided with a matched information publishing module nearby, in the embodiment of the application, the information publishing module takes a display screen as an example for explanation, characters or pictures can be displayed through the display screen, meanwhile, the area and the display brightness of the display screen all accord with corresponding standards, and a driver can be ensured to accurately acquire information from the display screen.
Based on the system, according to the weather information and the traffic flow information at different positions, corresponding traffic early warning schemes are generated, namely, each traffic early warning scheme has a corresponding applicable position. The system can send the traffic early warning scheme to the information release module at the corresponding position through the 5G base station.
According to different weather information and traffic flow information, different traffic early warning schemes are customized for different positions, driving safety can be improved to the greatest extent, and traffic accidents are avoided.
In one embodiment, the system may further train a traffic early warning model before acquiring the plurality of weather information and traffic flow information.
Firstly, the system acquires a plurality of groups of historical early warning information, trains an initial traffic early warning model through the historical early warning information, and obtains the trained traffic early warning model, wherein the historical early warning information at least comprises: historical weather information, historical traffic flow information, historical speed limit value, historical safe interval value etc. and initial traffic early warning model includes at least: the system comprises an input layer, a fuzzy layer, a rule front-part layer, a normalization layer and an output layer.
Specifically, historical weather information and historical traffic flow information are used as input layer data, and historical speed limit values and historical safety spacing values are used as output layer data.
Dividing a plurality of first parameters contained in the historical weather information and the historical traffic flow information into a plurality of grades according to a first rule, wherein the first parameters can comprise: temperature, humidity, wind speed, wind direction, air pressure, rainfall, snowfall, vehicle speed, vehicle flow, vehicle information, license plate number, and the like. Specifically, the input layer is represented as x ═ { x ═ x1,x2,x3,...,xnWhere n denotes the number of the first parameters, n is an integer of 1 or more, and x1,x2,...xnRespectively, representing specific first parameters.
The first parameter is divided into 5 levels according to the sequence from small to large, wherein NB is negative and large, NS is negative and small, Z is zero, PS is positive and small, and PB is positive and large, and the meaning is that the index value of the first parameter is small, medium, large and large.
In addition, the system also divides a plurality of second parameters contained in the historical speed limit value and the historical safety interval value into a plurality of levels according to a second preset rule, the second parameters are used as output layers, the division mode is the same as that of the above, and the description is omitted here.
Further, the plurality of graded first parameters are input to the input layer, and the plurality of graded second parameters are input to the output layer, wherein the input layer may transmit the graded first parameters to the blurring layer after receiving the graded first parameters.
And inputting the initial fuzzy segmentation number, the central value of the membership function and the width value into the fuzzy layer, so that the fuzzy layer obtains the first parameter after grading and the membership value of the corresponding grade according to the membership function and the first parameter after grading. In particular, the membership function is
Wherein j is 1 to miInteger of (1), miIs xiNumber of fuzzy partitions, here mi＝5；cijAnd σijRepresenting the center and width of the membership function, respectively.
The fuzzy layer can transmit the plurality of first parameters with the membership value identifications to the rule front-part layer, so that the rule front-part layer obtains the applicability of the first parameters with the membership value identifications and the corresponding fuzzy rules according to the fuzzy rules, the first parameters with the membership value identifications and the applicability function. Wherein the fitness function is
Or
Wherein a isjI.e. for expressing the fitness of the fuzzy rule.
Wherein the content of the first and second substances,
representing an input xiAnd the membership degree of the jth grade, j is an integer between 1 and m, and m is an integer greater than or equal to 1.
The rule front-part layer transmits the plurality of the suitability degrees to the normalization layer so as to obtain the normalized suitability degrees through the normalization function and the suitability degrees contained in the normalization layer. Specifically, the normalization function is
Wherein j is an integer between 1 and m, and m is an integer greater than or equal to 1.
The normalization layer transmits the normalized degrees of applicability to the output layer, and the system inputs the connection weight to the output layer, so that the output layer obtains an output value identical to the second parameter according to the output function and the normalized degrees of applicability. In particular, the output function is
Wherein, wrIs connected toAnd according to the weight, r is an integer between 1 and m, and m is an integer greater than or equal to 1.
And taking the model as a trained traffic early warning model.
The system acquires real weather information and real traffic flow information, acquires corresponding recommended speed limit values and recommended safe spacing values, takes the real weather information and the real traffic flow information as input data of a verification set, and takes the recommended speed limit values and the recommended safe spacing values as output data of the verification set.
And inputting the real weather information and the real traffic flow information into an input layer of the trained traffic early warning model through the real weather information, the real traffic flow information and the trained traffic early warning model to obtain a first error between an actually output speed limit value and a recommended speed limit value and a second error between an actually output safety interval value and a recommended safety interval value.
Further, if at least one of the first error and the second error is greater than a first preset threshold, adjusting one or more of the initial fuzzy partition number, the central value of the membership function, the width value of the membership function, and the connection weight value until all of the first error and the second error are not greater than the first preset threshold, so as to obtain the traffic early warning model.
Through the training and verifying processes, a relatively accurate traffic early warning model can be obtained, and the traffic early warning model can output a proper and appropriate traffic early warning scheme according to weather information and traffic flow information.
In one embodiment, after a plurality of traffic early warning schemes for different positions of an expressway are acquired according to a pre-trained traffic early warning model, meteorological information and traffic flow information, a corresponding second position and a corresponding third position can be determined for any one first position in the different positions of the expressway.
It should be noted that the second position is behind the reference direction of the first position, and the third position is in front of the reference direction of the first position, and the reference direction is the traveling direction of the vehicle, and is a bidirectional lane based on the expressway, so in the embodiment of the present application, the traveling direction of the vehicle is selected as the right side.
Obtaining parameters of the first road segment between the first location and the second location, including but not limited to: road length, road width.
Further, the safe vehicle capacity of the first road section is obtained according to the parameters of the first road section, the speed limit value and the safe distance value at the first position and a pre-stored safe vehicle capacity function. And calculating the safe vehicle capacity of the first road section, namely the number of vehicles which exist in the first road section at most according to a prestored safe vehicle capacity function based on the fact that the speed limit value and the safe distance value at the first position can represent the traffic scheme of the whole first road section after the reference direction of the second position at the first position.
Further, according to the traffic flow monitoring module of the first road section, namely the traffic flow monitoring module at the first position and the traffic flow monitoring module at the second position, the first real-time vehicle number of the first road section is obtained through the 5G base station.
Further, the first real-time vehicle quantity is compared with the safety vehicle capacity, if the first real-time vehicle quantity is larger than the safety vehicle capacity, the fact that the vehicle quantity in the first road section is too high at the moment is indicated, the system adjusts the traffic early warning scheme at the second position, namely, the speed limit value at the second position is reduced and/or the safety distance value at the second position is improved, the vehicle quantity entering the first road section in unit time is reduced, and then the first real-time vehicle quantity is reduced until the first vehicle quantity is not larger than the safety vehicle capacity.
In one embodiment, if the first number of real-time vehicles is greater than the safe vehicle capacity, the speed limit value at the second location is decreased and/or the safe distance value at the second location is increased until after the first number of real-time vehicles is not greater than the safe vehicle capacity, the system may further obtain data of the second road segment between the first location and the third location, including but not limited to: road length, road width.
And acquiring a second real-time vehicle quantity of the second road section through the 5G base station according to the traffic flow monitoring module of the second road section, namely the traffic flow monitoring module at the third position and the traffic flow monitoring module at the first position.
And obtaining the congestion rate of the second road section according to the data of the second road section, the number of the second real-time vehicles and the pre-stored vehicle congestion function, wherein if the congestion rate is greater than a second preset threshold value, the situation that the redundancy of the vehicles in the second road section is too much is indicated, at the moment, the speed limit value at the first position and/or the safety spacing value at the third position can be reduced, at the moment, more vehicles can be ensured to drive out of the second road section in unit time, and the road congestion is avoided.
In one embodiment, after obtaining the congestion rate of the second road segment according to the data of the second road segment, the second real-time vehicle number and the pre-stored vehicle congestion function, the system may further determine whether the third location is an entrance of the expressway. If so, it is indicated that the congestion may be caused by a large number of vehicles driving at a high speed, and meanwhile, if the congestion rate is greater than a third preset threshold, it is indicated that the congestion is serious, at this time, the system may generate an entrance closing instruction, and close an entrance according to the entrance closing instruction, that is, an entrance of the expressway at a third position.
If not, and the congestion rate is greater than a third preset threshold value, it is indicated that congestion at the third position is serious, at this time, the system can generate a local closing instruction, and locally close the first position according to the local closing instruction, so that the vehicle is prevented from entering the second road segment, and further serious congestion is caused at the third position. By the mode, the congested road sections are scattered rather than centralized, so that the driving safety of the expressway is improved, and the possibility of traffic accidents is reduced.
In one embodiment, after the system sends the traffic early warning scheme to the information publishing module at the corresponding location through the 5G base station, the system may further determine that severe weather exists at the corresponding location according to the weather information at the corresponding location, for example: to solve the problem, the system may determine a terminal capable of communicating with the 5G base station within a preset range at the corresponding location, that is, a terminal driving inside a vehicle on the expressway within an effective range of the traffic early warning scheme, the terminal including but not limited to: a mobile phone, a tablet computer or other hardware equipment with corresponding communication function.
Further, the system sends the traffic early warning scheme at the corresponding position to all terminals within the range so as to remind the driver.
In one embodiment, when the system determines that the vehicle is about to exit the highway, the driving track and the driving time of the vehicle on the highway can be acquired according to the traffic flow monitoring module.
And determining that the vehicle complies with the traffic early warning scheme corresponding to the running track within the running time according to the traffic flow monitoring module.
And acquiring the high-speed cost of the vehicle, carrying out discount processing on the high-speed cost according to the prestored discount, and sending the discounted high-speed cost to an exit toll station corresponding to the vehicle. By the method, drivers can be further encouraged to obey a traffic early warning scheme, and the overall driving safety of the expressway is improved.
In an embodiment, as shown in fig. 2, an embodiment of the present application further provides a highway traffic early warning device based on 5G communication, including: at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform instructions for:
acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station;
according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value;
and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station.
In one embodiment, the present application further provides a non-transitory computer storage medium storing computer-executable instructions configured to:
acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station;
according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value;
and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station.
The embodiments in the present application are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the device and media embodiments, the description is relatively simple as it is substantially similar to the method embodiments, and reference may be made to some descriptions of the method embodiments for relevant points.
The device and the medium provided by the embodiment of the application correspond to the method one to one, so the device and the medium also have the similar beneficial technical effects as the corresponding method, and the beneficial technical effects of the method are explained in detail above, so the beneficial technical effects of the device and the medium are not repeated herein.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (10)
1. A highway traffic early warning method based on 5G communication is characterized by comprising the following steps:
acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station;
according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value;
and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station so as to display the traffic early warning scheme on the information release module at the corresponding position.
2. The highway traffic early warning method based on 5G communication according to claim 1, wherein before acquiring a plurality of meteorological information and traffic flow information, the method further comprises:
acquiring multiple groups of historical early warning information, training an initial traffic early warning model through the historical early warning information, and obtaining a trained traffic early warning model, wherein the historical early warning information comprises: historical weather information, historical traffic flow information, historical speed limit value, historical safe interval value, the initial traffic early warning model includes: the system comprises an input layer, a fuzzy layer, a rule front-part layer, a normalization layer and an output layer;
training an initial traffic early warning model through the historical early warning information, and specifically comprising the following steps:
dividing a plurality of first parameters contained in the historical meteorological information and the historical traffic flow information into a plurality of grades according to a first preset rule, and dividing a plurality of second parameters contained in the historical speed limit value and the historical safety interval value into a plurality of grades according to a second preset rule;
inputting a plurality of graded first parameters to the input layer and a plurality of graded second parameters to the output layer, wherein the input layer is used for transmitting the plurality of graded first parameters to the blurring layer;
inputting an initial fuzzy segmentation number, a central value of a membership function and a width value into the fuzzification layer, so that the fuzzification layer obtains the ranked first parameters and the membership values of the corresponding ranks thereof according to the membership function and the ranked first parameters, wherein the fuzzification layer is used for transmitting a plurality of first parameters with membership value identifications to the rule front-part layer;
inputting a plurality of fuzzy rules to the rule front-part layer so that the rule front-part layer obtains the applicability of the first parameter with the membership value identifier and the corresponding fuzzy rule according to the fuzzy rules, the first parameter with the membership value identifier and an applicability function, wherein the rule front-part layer is used for transmitting the plurality of the applicability to the normalization layer;
obtaining a normalized suitability degree through a normalization function contained in the normalization layer and the suitability degree, wherein the normalization layer is used for transmitting a plurality of normalized suitability degrees to the output layer;
and inputting the connection weight value into the output layer so that the output layer obtains an output value which is the same as the second parameter according to an output function and the normalized applicability.
3. The method as claimed in claim 2, wherein after inputting the link weight value to the output layer to make the output layer obtain the same output value as the second parameter according to the output function and the normalized applicability, the method further comprises:
acquiring real weather information and real traffic flow information, and acquiring corresponding recommended speed limit values and recommended safe spacing values;
obtaining an actually output speed limit value and an actually output safety interval value through the real weather information, the real traffic flow information and the trained traffic early warning model;
obtaining a first error between the actually output speed limit value and the recommended speed limit value and a second error between the actually output safety interval value and the recommended safety interval value according to the actually output speed limit value, the actually output safety interval value, the recommended speed limit value, the recommended safety interval value and a preset error function;
if at least one of the first error and the second error is greater than a first preset threshold, adjusting one or more of the initial fuzzy partition number, the central value of the membership function, the width value of the membership function and the connection weight value until all of the first error and the second error are not greater than the first preset threshold;
and obtaining a traffic early warning model.
4. The highway traffic early warning method based on 5G communication as claimed in claim 1, wherein after acquiring a plurality of traffic early warning schemes for different positions of the highway according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, the method further comprises:
for any first position in different positions of the expressway, determining a corresponding second position and a corresponding third position, wherein the second position is behind a reference direction of the first position, the third position is in front of the reference direction of the first position, and the reference direction is a vehicle traveling direction;
acquiring parameters of a first road section between the first position and the second position;
obtaining the safe vehicle capacity of the first road section according to the parameters of the first road section, the speed limit value and the safe distance value at the first position and a prestored safe vehicle capacity function;
according to the traffic flow monitoring module of the first road section, acquiring the first real-time vehicle quantity of the first road section through the 5G base station;
if the number of the first real-time vehicles is larger than the safety vehicle capacity, reducing the speed limit value at the second position and/or improving the safety distance value at the second position until the number of the first real-time vehicles is not larger than the safety vehicle capacity.
5. The highway traffic early warning method based on 5G communication according to claim 4, wherein if the first real-time vehicle number is greater than the safety vehicle capacity, the speed limit value at the second position is lowered and/or the safety distance value at the second position is raised until the first real-time vehicle number is not greater than the safety vehicle capacity, and the method further comprises:
acquiring data of a second road section between the first position and the third position, and acquiring a second real-time vehicle quantity of the second road section through the 5G base station according to a traffic flow monitoring module of the second road section;
obtaining the congestion rate of the second road section according to the data of the second road section, the second real-time vehicle quantity and a prestored vehicle congestion function;
if the congestion rate is larger than a second preset threshold value, reducing the speed limit value at the first position and/or the safe distance value at the third position until the congestion rate is not larger than the second preset threshold value.
6. The highway traffic early warning method based on 5G communication as claimed in claim 5, wherein after obtaining the congestion rate of the second road segment according to the data of the second road segment, the second real-time vehicle number and a pre-stored vehicle congestion function, the method further comprises:
determining whether the third location is an entrance of the highway;
if yes, generating an entrance closing instruction, and closing the entrance according to the entrance closing instruction, wherein the congestion rate is greater than a third preset threshold;
if not, and the congestion rate is larger than the third preset threshold, generating a local closing instruction, and performing local closing on the first position according to the local closing instruction.
7. The highway traffic early warning method based on 5G communication as claimed in claim 1, wherein after the traffic early warning scheme is sent to the information publishing module at the corresponding position through the 5G base station, the method further comprises:
determining that extreme severe weather exists at the corresponding position according to the meteorological information;
determining a terminal which can communicate with the 5G base station within a preset range at the corresponding position;
and sending the corresponding traffic early warning scheme at the corresponding position to the terminal.
8. The highway traffic early warning method based on 5G communication as claimed in claim 1, wherein the method further comprises:
determining that a vehicle is about to exit the highway;
acquiring a running track and running time of the vehicle on the expressway according to the traffic flow monitoring module;
according to the traffic flow monitoring module, determining that the vehicle complies with a corresponding traffic early warning scheme on the driving track within the driving time;
and obtaining the high-speed fee of the vehicle, carrying out discount processing on the high-speed fee according to a prestored discount, and sending the discounted high-speed fee to an exit toll station corresponding to the vehicle.
9. The utility model provides a highway traffic early warning equipment based on 5G communication which characterized in that includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to cause the at least one processor to perform instructions for:
acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station;
according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value;
and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station.
10. A non-transitory computer storage medium storing computer-executable instructions, the computer-executable instructions configured to:
acquiring a plurality of meteorological information and traffic flow information, wherein the meteorological information is sent by meteorological monitoring modules distributed at different positions of an expressway through a 5G base station, and the traffic flow information is sent by traffic flow monitoring modules distributed at different positions of the expressway through the 5G base station;
according to a pre-trained traffic early warning model, the meteorological information and the traffic flow information, a plurality of traffic early warning schemes aiming at different positions of the highway are obtained, wherein the traffic early warning schemes comprise at least one of the following: speed limit value and safety interval value;
and sending the traffic early warning scheme to an information release module at a corresponding position through the 5G base station.
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