CN112735136A - 5G traffic monitoring planning method, mobile terminal, traffic service platform and system - Google Patents
5G traffic monitoring planning method, mobile terminal, traffic service platform and system Download PDFInfo
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- CN112735136A CN112735136A CN202011644085.9A CN202011644085A CN112735136A CN 112735136 A CN112735136 A CN 112735136A CN 202011644085 A CN202011644085 A CN 202011644085A CN 112735136 A CN112735136 A CN 112735136A
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/21—Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F18/214—Generating training patterns; Bootstrap methods, e.g. bagging or boosting
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0108—Measuring and analyzing of parameters relative to traffic conditions based on the source of data
- G08G1/0112—Measuring and analyzing of parameters relative to traffic conditions based on the source of data from the vehicle, e.g. floating car data [FCD]
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
- G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
Abstract
The invention discloses a 5G traffic monitoring planning method, which comprises the following steps: acquiring image data of a vehicle-mounted camera; identifying abnormal road condition information according to the image data; and sending the abnormal road condition information to a traffic service platform, retrieving associated mobile terminals by the traffic service platform according to the abnormal road condition information, calculating the latest road planning information for all the associated mobile terminals, and sending the latest road planning information to the corresponding associated mobile terminals. The invention also discloses a mobile terminal, a system and a readable storage medium. The method and the device solve the technical problems that in the prior art, traffic accidents are artificially and actively reported with poor timeliness and wrong or incomplete reports, so that large-area congestion caused by abnormal road conditions is caused to traffic conditions, and vehicle traffic path planning is based on a single basis, so that the intelligent process of urban road traffic is further promoted.
Description
Technical Field
The invention relates to the technical field of traffic monitoring planning, in particular to a 5G traffic monitoring planning method, a mobile terminal, a traffic service platform and a system.
Background
In the construction of urban intelligent traffic, a large number of monitoring cameras are arranged to monitor the traffic dynamics of a city. However, these monitoring cameras are arranged in fixed positions and cannot move, so that the monitoring range of each camera is limited. The existing road traffic accidents are scattered in cities, and huge network transmission and calculation expenses are brought if real-time identification and tracking are carried out by relying on monitoring cameras in the cities. Therefore, the manual and active reporting of traffic accidents is an important means to solve the problem.
However, manual active reporting has problems of poor timeliness, reporting errors, or incompleteness. In the process of actively reporting the traffic accident, even if the driver reports the traffic accident through voice, the driver still can not drive safely due to the distracted reporting, so that a new traffic accident is caused, and higher risk is brought to the urban traffic safety. In addition, currently, apparatuses having an image pickup function, such as a drive recorder, are commonly installed in vehicles. But these devices are relatively simple and do not have the feature of intelligence. Especially, the image data shot by the cameras of these devices can be mined and utilized by intelligent means because of the abundant information contained therein, so as to serve as an important support for urban intelligent transportation (such as intelligent traffic monitoring and dynamic traffic planning). However, these image data are only used as the post-incident evidence of traffic accidents, and have single functions, and cannot exert their potential value.
In summary, an intelligent 5G traffic monitoring planning method, a mobile terminal, a system and a storage medium are needed to solve the problems of poor timeliness, wrong reporting or incompleteness in the manual active reporting of traffic accidents, avoid large-area congestion caused by abnormal road conditions in traffic conditions, and further promote the intelligent progress of urban road traffic by planning vehicle traffic paths according to a single basis.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide a 5G traffic monitoring and planning method, a mobile terminal, a traffic service platform and a 5G traffic monitoring and planning system, aiming at solving the technical problems that traffic accidents are artificially and actively reported with poor timeliness and wrong or incomplete reports in the prior art, so that the traffic condition is large-area crowded caused by abnormal road conditions, and the vehicle traffic path planning is based on a single basis, so as to further promote the intelligent process of urban road traffic.
In order to achieve the above object, the present invention provides a 5G traffic monitoring planning method, wherein the 5G traffic monitoring planning method comprises the following steps:
acquiring image data of a vehicle-mounted camera;
identifying abnormal road condition information according to the image data;
and sending the abnormal road condition information to a traffic service platform, retrieving associated mobile terminals by the traffic service platform according to the abnormal road condition information, calculating the latest road planning information for all the associated mobile terminals, and sending the latest road planning information to the corresponding associated mobile terminals.
Further, the step of sending the abnormal road condition information to a traffic service platform includes:
searching for a neighboring 5G base station;
sending the abnormal road condition information to the adjacent 5G base station in a broadcasting mode; and the adjacent 5G base station sends the abnormal road condition information to a data uplink receiving controller of the traffic service platform.
Further, the 5G traffic monitoring planning method further includes:
uploading the position information and the channel state of the mobile terminal to an SDN controller of the traffic service platform at regular time, and selecting at least one appointed 5G base station by the SDN controller according to the position information and the channel state, wherein the base station is used for sending the latest road planning information.
Further, the 5G traffic monitoring planning method further includes:
acquiring current vehicle type information;
selecting different road planning models according to the vehicle types;
acquiring a starting place and a destination of the current vehicle;
acquiring real-time road traffic information;
and calculating to obtain the road planning information of the current vehicle according to the starting place and the destination of the current vehicle and the real-time road traffic information.
In addition, to achieve the above object, the present invention also provides a mobile terminal, including: the system comprises a memory, a 5G communication module, a processor and a 5G traffic monitoring planning program which is stored on the memory and can run on the processor, wherein the 5G traffic monitoring planning program realizes the steps of the 5G traffic monitoring planning method when being executed by the processor.
In addition, in order to achieve the above object, the present invention further provides a 5G traffic monitoring planning method, where the 5G traffic monitoring planning method includes the following steps:
receiving abnormal road condition information;
retrieving the associated mobile terminal according to the abnormal road condition information;
calculating the latest road planning information for all the associated mobile terminals;
and sending the latest road planning information to the corresponding associated mobile terminal.
Further, the step of receiving the abnormal traffic information includes:
a data uplink receiving controller of the traffic service platform receives the abnormal road condition information sent from a 5G base station;
after the step of receiving the abnormal road condition information, the 5G traffic monitoring planning method further includes:
and the data uplink receiving controller of the traffic service platform sends the abnormal road condition information to a data processing unit of the traffic service platform.
Further, the step of retrieving the associated mobile terminal according to the abnormal traffic information includes:
an SDN controller of the traffic service platform receives the position information and the channel state of the associated mobile terminal;
the SDN controller selects at least one appointed 5G base station according to the position information and the channel state of the associated mobile terminal, and the base station is used for sending the latest road planning information;
the step of sending the latest road planning information to the corresponding associated mobile terminal includes:
the data processing unit sends the latest road planning information to a data downlink transmission controller of the traffic service platform;
and the data downlink transmission controller sends the latest road planning information to the specified 5G base station according to the selection of the SDN controller, and the specified 5G base station sends the latest road planning information to the associated mobile terminal.
In addition, to achieve the above object, the present invention further provides a traffic service platform, including:
the data uplink receiving controller is used for receiving the abnormal road condition information sent by the 5G base station;
the data processing unit is used for calculating the corresponding latest road planning information for all the associated mobile terminals;
the data downlink transmission controller is used for sending the latest road planning information to the corresponding 5G base station;
and the SDN controller is used for receiving the position information and the channel state of the associated mobile terminal, and selecting at least one appointed 5G base station according to the position information and the channel state of the associated mobile terminal, and the SDN controller is used for sending the latest road planning information.
In addition, to achieve the above object, the present invention further provides a 5G traffic monitoring planning system, where the 5G traffic monitoring planning system includes: the mobile terminal as described above, the traffic service platform as described above; and the number of the first and second groups,
the vehicle-mounted camera is used for acquiring image data of the vehicle-mounted camera;
and the 5G base station is used for transmitting the information data between the traffic service platform and the mobile terminal.
The invention obtains the image data of the vehicle-mounted camera; identifying abnormal road condition information according to the image data; sending the abnormal road condition information to a traffic service platform; according to the abnormal road condition information, the traffic service platform calculates and generates latest road planning information; and the traffic service platform sends the latest road planning information to the mobile terminal. The image data collected by the vehicle-mounted camera is directly processed and uploaded to the traffic service platform, so that the technical problems of poor timeliness, wrong report or incompleteness of road traffic accidents do not exist, meanwhile, the abnormal road conditions are uploaded to the traffic service platform, the traffic service platform can conveniently reformulate a road plan for each mobile terminal associated with the abnormal road condition section according to the abnormal road condition information, the associated mobile terminals can avoid the abnormal road condition section according to the latest road plan information, and the large-area congestion caused by the abnormal road condition in the traffic condition is avoided.
Drawings
Fig. 1 is a schematic device structure diagram of a mobile terminal hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart illustrating a first embodiment of a 5G traffic monitoring planning method according to the present invention;
FIG. 3 is a schematic diagram of a network structure of the 5G traffic monitoring planning system according to the present invention;
FIG. 4 is a schematic diagram of a network structure of the 5G traffic monitoring planning system of the present invention;
fig. 5 is a schematic flow chart of a 5G traffic monitoring planning method according to a second embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The main solution of the embodiment of the invention is as follows:
acquiring image data of a vehicle-mounted camera;
identifying abnormal road condition information according to the image data;
and sending the abnormal road condition information to a traffic service platform, retrieving associated mobile terminals by the traffic service platform according to the abnormal road condition information, calculating the latest road planning information for all the associated mobile terminals, and sending the latest road planning information to the corresponding associated mobile terminals.
Because the road traffic accidents are reported actively by manpower, the problems of poor timeliness and incomplete report exist. Further, the image data captured by the in-vehicle camera cannot be effectively used only as evidence of a traffic accident.
The invention provides a solution, which is to obtain the image data of a vehicle-mounted camera; identifying abnormal road condition information according to the image data; sending the abnormal road condition information to a traffic service platform; according to the abnormal road condition information, the traffic service platform calculates and generates latest road planning information; and the traffic service platform sends the latest road planning information to the mobile terminal. The image data collected by the vehicle-mounted camera is directly processed and uploaded to the traffic service platform, so that the technical problems of poor timeliness, wrong report or incompleteness of road traffic accidents do not exist, meanwhile, the abnormal road conditions are uploaded to the traffic service platform, the traffic service platform can conveniently reformulate a road plan for each mobile terminal associated with the abnormal road condition section according to the abnormal road condition information, the associated mobile terminals can avoid the abnormal road condition section according to the latest road plan information, and the large-area congestion caused by the abnormal road condition in the traffic condition is avoided.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present invention.
The device of the embodiment of the invention can be a mobile phone, a control device connected with a vehicle, such as a vehicle-mounted controller, or a wearable device; or the device can also be a server and carries out data transmission with the wearable equipment through the communication module.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU or GPU, a communication bus 1002, a communication module 1003, and a memory 1004. Wherein a communication bus 1002 is used to enable connective communication between these components. The communication module 1003 is a 5G communication module communicating with a 5G micro base station, a 5G pico base station, and a 5G macro base station, and may also be a WIFI module or a bluetooth module. The memory 1004 may be a high-speed RAM memory or a non-volatile memory (e.g., a disk memory). The memory 1004 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the terminal structure shown in fig. 1 is not intended to be limiting and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, the memory 1004, which is a kind of computer storage medium, includes an operating system and programs for road traffic planning and monitoring.
In the terminal shown in fig. 1, the processor 1001 may be configured to call a program for road traffic planning and monitoring stored in the memory 1004 and perform operations in the following embodiments of the 5G traffic monitoring planning method.
The invention also provides a 5G traffic monitoring planning method, and referring to FIG. 2, FIG. 2 is a schematic flow chart of a first embodiment of the 5G traffic monitoring planning method.
In this embodiment, the 5G traffic monitoring planning method is applied to a mobile terminal, and the 5G traffic monitoring planning method includes:
step S110, acquiring image data of a vehicle-mounted camera;
step S120, identifying abnormal road condition information according to the image data;
step S130, the abnormal road condition information is sent to a traffic service platform, the traffic service platform retrieves the associated mobile terminals according to the abnormal road condition information, calculates the latest road planning information for all the associated mobile terminals, and sends the latest road planning information to the corresponding associated mobile terminals.
In this embodiment, the mobile terminal takes a mobile phone as an example, and the mobile phone identifies abnormal road condition information by acquiring image data of the vehicle-mounted camera. And when the abnormal road condition information is identified, the abnormal road condition information is sent to the traffic service platform. And calculating and generating the latest road planning information by the traffic service platform according to the abnormal road condition information, and sending the latest road planning information to the mobile terminal.
Specifically, the mobile terminal that sends the abnormal road condition information to the traffic service platform is not a related mobile terminal, for example, the mobile terminal in the vehicle a uploads the abnormal road condition information (traffic accident) acquired by the camera in real time to the traffic service platform, and in fact, after the acquisition process is completed, the vehicle a is likely to pass through the place where the accident is located, or the place where the accident is deeply trapped cannot be separated, so that it is meaningless to plan a path for the mobile terminal in the vehicle a, but instead, the vehicle a may pass through or predict the mobile terminal that passes through the place where the accident is located, and road planning needs to be performed again, so as to avoid large-area congestion caused by the abnormal road condition in the traffic condition.
It can be understood that, in this embodiment, as shown in fig. 4, the traffic service platform may generate a correlation decision according to the specific situation of the abnormal road condition information, and send the correlation decision to the third party platform, in addition to generating the latest road planning information by calculation according to the abnormal road condition information. For example, if a fire condition occurs in the abnormal traffic information, the traffic service platform can also send a rescue request to a third party platform where other related units such as a fire protection system and a medical system are located.
Further, in an embodiment, the step S120 of identifying abnormal traffic information according to the image data includes:
designing an abnormal road condition identification model system structure;
constructing an initialized abnormal road condition identification model;
constructing an abnormal road condition data set;
dividing an abnormal road condition data set into a training set, a verification set and a test set;
preprocessing the divided abnormal road condition data set;
respectively inputting the preprocessed data sets, and training the initialized abnormal road condition recognition model to obtain a trained abnormal road condition recognition model;
preprocessing the image data;
and inputting the preprocessed image data into the trained abnormal road condition identification model to identify abnormal road conditions.
It can be understood that, in this embodiment, the model is trained by using a deep learning-based method, so that the model can effectively identify abnormal road conditions. The method is characterized in that an abnormal road condition identification model is built, is essentially a multi-classification problem, and can be trained by adopting neural networks such as ResNet and EfficientNet.
Further, in step S130, the step of sending the abnormal road condition information to a traffic service platform includes:
searching for a neighboring 5G base station;
sending the abnormal road condition information to the adjacent 5G base station in a broadcasting mode; and the adjacent 5G base station sends the abnormal road condition information to a data uplink receiving controller of the traffic service platform.
In the technical scheme disclosed in this embodiment, the mobile terminal searches for neighboring 5G base stations, sends the abnormal traffic information to a plurality of neighboring base stations simultaneously in a broadcast manner, and the neighboring base stations transmit data to the uplink receiving controller, and the uplink receiving controller performs data summarization and then transmits the data to the traffic service platform. Therefore, the neighboring 5G base station is not a certain base station, but is selected according to the signal strength, and the base station with a stronger signal is preferentially selected as the neighboring base station. The mobile terminal may send the abnormal road condition information to one or more of the neighboring 5G base stations. The mobile terminal and the 5G base station have no binding relation before establishing communication.
Specifically, unlike the prior art, a UE (user equipment, i.e. a mobile terminal in this example) generally performs a 1-to-1 connection with 1 base station to complete data transmission. Because the connection process (i.e. the network access process) between the UE and the specific base station is extremely complex, the present application avoids the complex network access process by connecting with multiple 5G base stations simultaneously in a broadcast manner.
Further, the 5G traffic monitoring planning method further includes:
uploading the position information and the channel state of the mobile terminal to an SDN controller of the traffic service platform at regular time, and selecting at least one appointed 5G base station by the SDN controller according to the position information and the channel state, wherein the base station is used for sending the latest road planning information.
In the technical solution disclosed in the present embodiment,
it can be understood that, in this embodiment, the 5G base station receives the location information and the channel state of the mobile terminal, and sends the location information and the channel state to an sdn (software Defined network) controller for processing. The traffic service platform sends the latest route planning information (when the route changes) to the SDN controller. The SDN controller selects one or more 5G base stations for downlink data joint transmission based on the position of a vehicle where the associated mobile terminal is located and the channel state around the vehicle where the associated mobile terminal is located. And the vehicle where the associated mobile terminal is located receives the downlink data of the 5G base station through the 5G module of the vehicle-mounted equipment.
Further, in this embodiment, the 5G traffic monitoring planning method further includes:
acquiring current vehicle type information;
selecting different road planning models according to the vehicle types;
acquiring a starting place and a destination of the current vehicle;
acquiring real-time road traffic information;
and calculating to obtain the road planning information of the current vehicle according to the starting place and the destination of the current vehicle and the real-time road traffic information.
In this example, the model is a road weight model, wherein the road weight model is obtained by an analytic hierarchy process. The traditional hierarchical analysis model generally models all the influencing factors to obtain one model. The method includes the steps of firstly dividing vehicles into three categories (namely passenger cars, trucks and passenger cars), and then modeling each category by using an analytic hierarchy process to obtain three models. Judging the type of the vehicle, and loading a bus route planning model if the vehicle is a bus (such as a bus); if the truck is a truck (such as a heavy-duty dump truck and a medium-duty dump truck), loading the truck route planning model; and if the vehicle is a passenger vehicle, loading the passenger vehicle route planning model. The preprocessed vehicle data, the driving start point and end point data, and the urban traffic state data are input shapes accepted by the loaded model. And inputting the data into the model for calculation to obtain the specific route planning and the attributes (such as required time, the number of traffic lights and road condition information) under the planning.
It is understood that, in the present embodiment, the adopted general influencing factors include: departure place, destination, travel time, road state, license plate number, driver information. The road state is obtained by constructing a road state data set, training a model by adopting a deep learning method and predicting by using the model. Proprietary influencing factors for passenger car modeling include: the bus stop station comprises a bus running lane, bus speed limit information and a bus stop station. Proprietary influencing factors for truck modeling include: the vehicle driving lane, the vehicle speed limit information and the vehicle traffic limit information. Proprietary influencing factors for passenger car modeling include: passenger car speed limit information and passenger car traffic limit information. And comparing the factors pairwise, and obtaining a comparison matrix according to the importance of the factors by using a 3-point or 5-point Likert-Scale Scale table. And calculating the importance index of each influencing factor. And constructing a judgment matrix and solving the eigenvector of the judgment matrix. And normalizing to obtain the road weight model.
Further, in an embodiment, first, it is required to determine whether to register the vehicle, and if not, enter a registration process; otherwise, executing the next step: vehicle registration information, such as vehicle type, license plate number, driver, is obtained.
In addition, the present invention also provides a mobile terminal, including: a memory, a processor and a program of road traffic planning and monitoring stored on the memory and executable on the processor, the program of road traffic planning and monitoring when executed by the processor implementing the steps of:
acquiring image data of a vehicle-mounted camera;
identifying abnormal road condition information according to the image data;
sending the abnormal road condition information to a traffic service platform;
and sending the abnormal road condition information to a traffic service platform, retrieving associated mobile terminals by the traffic service platform according to the abnormal road condition information, calculating the latest road planning information for all the associated mobile terminals, and sending the latest road planning information to the corresponding associated mobile terminals.
It should be noted that each embodiment of the mobile terminal is substantially the same as each embodiment of the above 5G traffic monitoring and planning method, and details are not repeated herein.
The invention also provides a 5G traffic monitoring planning method, and referring to FIG. 5, FIG. 5 is a schematic flow chart of a first embodiment of the 5G traffic monitoring planning method.
In this embodiment, the 5G traffic monitoring planning method is applied to a mobile terminal, and the 5G traffic monitoring planning method includes:
step S210, receiving abnormal road condition information;
step S220, retrieving the associated mobile terminal according to the abnormal road condition information;
step S230, calculating the latest road planning information for all the associated mobile terminals;
step S240, sending the latest road planning information to the corresponding associated mobile terminal.
In this embodiment, the traffic service platform receives the abnormal road condition information, and retrieves the mobile terminal associated with the abnormal road condition information according to the abnormal road condition information, so as to enable the mobile terminal of the road section with the abnormal road condition contained in the original road planning information to be far away from the road section with the abnormal road condition. Therefore, the traffic service platform recalculates and generates the latest road planning information according to the original road planning and abnormal road condition information of the associated mobile terminal, and sends the latest road planning information to the associated mobile terminal.
It can be understood that, in this embodiment, the traffic service platform may generate the latest road planning information by calculation according to the abnormal road condition information, and may also generate the association decision according to the specific situation of the abnormal road condition information. For example, if a fire condition occurs in the abnormal traffic information, the traffic service platform can also send a rescue request to other relevant units such as a fire protection system and a medical system.
Further, in step S210, the step of receiving the abnormal traffic information includes:
a data uplink receiving controller of the traffic service platform receives the abnormal road condition information sent from a 5G base station;
after the step of receiving the abnormal road condition information, the 5G traffic monitoring planning method further includes:
and the data uplink receiving controller of the traffic service platform sends the abnormal road condition information to a data processing unit of the traffic service platform.
Further, in step S220, the step of retrieving the associated mobile terminal according to the abnormal road condition information includes:
an SDN controller of the traffic service platform receives the position information and the channel state of the associated mobile terminal;
and the SDN controller selects at least one appointed 5G base station according to the position information and the channel state of the associated mobile terminal, and the base station is used for sending the latest road planning information.
Specifically, in this embodiment, the 5G base station receives the location information and the channel state of the mobile terminal, and sends the location information and the channel state to an sdn (software Defined network) controller for processing. The traffic service platform sends the latest route planning information (when the route changes) to the SDN controller. The SDN controller selects one or more 5G base stations for downlink data joint transmission based on the position of a vehicle where the associated mobile terminal is located and the channel state around the vehicle where the associated mobile terminal is located. And the vehicle where the associated mobile terminal is located receives the downlink data of the 5G base station through the 5G module of the vehicle-mounted equipment.
It can be understood that in this embodiment, the uplink data transmission process and the downlink data transmission process are independent, and the SDN controller receives the location information and the channel state of the associated mobile terminal through the uplink receiving controller, mainly to let the server know where the mobile terminal devices are located, and which 5G base station(s) should be selected to communicate with which mobile terminal(s). The SDN controller is mainly used in a downlink data transmission process, and receiving the location information and the channel state of the associated mobile terminal by the SDN controller is a long-term and continuous action.
Further, in step S240, the step of sending the latest road planning information to the corresponding associated mobile terminal includes:
the data processing unit of the traffic service platform sends the latest road planning information to a data downlink transmission controller of the traffic service platform;
and the data downlink transmission controller sends the latest road planning information to the specified 5G base station according to the selection of the SDN controller, and the specified 5G base station sends the latest road planning information to the associated mobile terminal.
Further, in this embodiment, the 5G traffic monitoring planning method further includes:
acquiring current vehicle type information;
selecting different road planning models according to the vehicle types;
acquiring a starting place and a destination of the current vehicle;
acquiring real-time road traffic information;
and calculating to obtain the road planning information of the current vehicle according to the starting place and the destination of the current vehicle and the real-time road traffic information.
In this example, the model is a road weight model, wherein the road weight model is obtained by an analytic hierarchy process. The traditional hierarchical analysis model generally models all the influencing factors to obtain one model. The method includes the steps of firstly dividing vehicles into three categories (namely passenger cars, trucks and passenger cars), and then modeling each category by using an analytic hierarchy process to obtain three models. Judging the type of the vehicle, and loading a bus route planning model if the vehicle is a bus (such as a bus); if the truck is a truck (such as a heavy-duty dump truck and a medium-duty dump truck), loading the truck route planning model; and if the vehicle is a passenger vehicle, loading the passenger vehicle route planning model. The preprocessed vehicle data, the driving start point and end point data, and the urban traffic state data are input shapes accepted by the loaded model. And inputting the data into the model for calculation to obtain the specific route planning and the attributes (such as required time, the number of traffic lights and road condition information) under the planning.
It is understood that, in the present embodiment, the adopted general influencing factors include: departure place, destination, travel time, road state, license plate number, driver information. The road state is obtained by constructing a road state data set, training a model by adopting a deep learning method and predicting by using the model. Proprietary influencing factors for passenger car modeling include: the bus stop station comprises a bus running lane, bus speed limit information and a bus stop station. Proprietary influencing factors for truck modeling include: the vehicle driving lane, the vehicle speed limit information and the vehicle traffic limit information. Proprietary influencing factors for passenger car modeling include: passenger car speed limit information and passenger car traffic limit information. And comparing the factors pairwise, and obtaining a comparison matrix according to the importance of the factors by using a 3-point or 5-point Likert-Scale Scale table. And calculating the importance index of each influencing factor. And constructing a judgment matrix and solving the eigenvector of the judgment matrix. And normalizing to obtain the road weight model.
Further, in an embodiment, first, it is required to determine whether to register the vehicle, and if not, enter a registration process; otherwise, executing the next step: vehicle registration information, such as vehicle type, license plate number, driver, is obtained.
In addition, the invention also provides a traffic service platform, which comprises:
the data uplink receiving controller is used for receiving the abnormal road condition information sent by the 5G base station;
the data processing unit is used for calculating the corresponding latest road planning information for all the associated mobile terminals;
the data downlink transmission controller is used for sending the latest road planning information to the corresponding 5G base station;
and the SDN controller is used for receiving the position information and the channel state of the associated mobile terminal, and selecting at least one appointed 5G base station according to the position information and the channel state of the associated mobile terminal, and the SDN controller is used for sending the latest road planning information.
The traffic service platform realizes the following steps when executed:
receiving abnormal road condition information;
retrieving the associated mobile terminal according to the abnormal road condition information;
calculating the latest road planning information for all the associated mobile terminals;
and sending the latest road planning information to the corresponding associated mobile terminal.
It should be noted that each embodiment of the traffic service platform is substantially the same as each embodiment of the 5G traffic monitoring and planning method, and details are not repeated herein.
In addition, the invention also provides a 5G traffic monitoring planning system, and the 5G traffic monitoring planning system comprises: the mobile terminal as described above, the traffic service platform as described above; and the number of the first and second groups,
the vehicle-mounted camera is used for acquiring image data of the vehicle-mounted camera;
and the 5G base station is used for transmitting the information data between the traffic service platform and the mobile terminal.
It should be noted that each embodiment of the 5G traffic monitoring planning system is substantially the same as each embodiment of the 5G traffic monitoring planning method described above, and details are not repeated here.
In addition, the present invention further provides a computer readable storage medium, in which a road traffic planning and monitoring program is stored, and when the road traffic planning and monitoring program is executed by a processor, the steps of the 5G traffic monitoring planning method described above are implemented.
The specific embodiment of the computer-readable storage medium of the present invention is substantially the same as the embodiments of the 5G traffic monitoring and planning method described above, and will not be described in detail herein.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention 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 invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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.
It should be noted that in the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A5G traffic monitoring and planning method is characterized by comprising the following steps:
acquiring image data of a vehicle-mounted camera;
identifying abnormal road condition information according to the image data;
and sending the abnormal road condition information to a traffic service platform, retrieving associated mobile terminals by the traffic service platform according to the abnormal road condition information, calculating the latest road planning information for all the associated mobile terminals, and sending the latest road planning information to the corresponding associated mobile terminals.
2. The 5G traffic monitoring and planning method according to claim 1, wherein the step of sending the abnormal road condition information to a traffic service platform comprises:
searching for a neighboring 5G base station;
sending the abnormal road condition information to the adjacent 5G base station in a broadcasting mode; and the adjacent 5G base station sends the abnormal road condition information to a data uplink receiving controller of the traffic service platform.
3. The 5G traffic monitoring planning method of claim 1, further comprising:
uploading the position information and the channel state of the mobile terminal to an SDN controller of the traffic service platform at regular time, and selecting at least one appointed 5G base station by the SDN controller according to the position information and the channel state, wherein the base station is used for sending the latest road planning information.
4. The 5G traffic monitoring planning method of claim 1, further comprising:
acquiring current vehicle type information;
selecting different road planning models according to the vehicle types;
acquiring a starting place and a destination of the current vehicle;
acquiring real-time road traffic information;
and calculating to obtain the road planning information of the current vehicle according to the starting place and the destination of the current vehicle and the real-time road traffic information.
5. A mobile terminal, characterized in that the mobile terminal comprises: memory, a 5G communication module, a processor and a program of a 5G traffic monitoring plan stored on the memory and executable on the processor, the program of a 5G traffic monitoring plan when executed by the processor implementing the steps of the 5G traffic monitoring planning method of any one of claims 1 to 4.
6. A5G traffic monitoring and planning method is characterized by comprising the following steps:
receiving abnormal road condition information;
retrieving the associated mobile terminal according to the abnormal road condition information;
calculating the latest road planning information for all the associated mobile terminals;
and sending the latest road planning information to the corresponding associated mobile terminal.
7. The 5G traffic monitoring and planning method according to claim 6, wherein the step of receiving the abnormal road condition information comprises:
a data uplink receiving controller of the traffic service platform receives the abnormal road condition information sent from a 5G base station;
after the step of receiving the abnormal road condition information, the 5G traffic monitoring planning method further includes:
and the data uplink receiving controller of the traffic service platform sends the abnormal road condition information to a data processing unit of the traffic service platform.
8. The 5G traffic monitoring and planning method according to claim 7, wherein the step of retrieving the associated mobile terminal according to the abnormal road condition information comprises:
an SDN controller of the traffic service platform receives the position information and the channel state of the associated mobile terminal;
the SDN controller selects at least one appointed 5G base station according to the position information and the channel state of the associated mobile terminal, and the base station is used for sending the latest road planning information;
the step of sending the latest road planning information to the corresponding associated mobile terminal includes:
the data processing unit sends the latest road planning information to a data downlink transmission controller of the traffic service platform;
and the data downlink transmission controller sends the latest road planning information to the specified 5G base station according to the selection of the SDN controller, and the specified 5G base station sends the latest road planning information to the associated mobile terminal.
9. A traffic service platform, comprising:
the data uplink receiving controller is used for receiving the abnormal road condition information sent by the 5G base station;
the data processing unit is used for calculating the corresponding latest road planning information for all the associated mobile terminals;
the data downlink transmission controller is used for sending the latest road planning information to the corresponding 5G base station;
and the SDN controller is used for receiving the position information and the channel state of the associated mobile terminal, and selecting at least one appointed 5G base station according to the position information and the channel state of the associated mobile terminal, and the SDN controller is used for sending the latest road planning information.
10. A5G traffic monitoring planning system, characterized in that the 5G traffic monitoring planning system comprises: the mobile terminal of claim 5, the transportation service platform of claim 9; and the number of the first and second groups,
the vehicle-mounted camera is used for acquiring image data of the vehicle-mounted camera;
and the 5G base station is used for transmitting the information data between the traffic service platform and the mobile terminal.
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