CN110619748A - Traffic condition analysis and prediction method, device and system based on traffic big data - Google Patents
Traffic condition analysis and prediction method, device and system based on traffic big data Download PDFInfo
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- CN110619748A CN110619748A CN201911003484.4A CN201911003484A CN110619748A CN 110619748 A CN110619748 A CN 110619748A CN 201911003484 A CN201911003484 A CN 201911003484A CN 110619748 A CN110619748 A CN 110619748A
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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
- G08G1/0129—Traffic data processing for creating historical data or processing based on historical data
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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Abstract
The invention discloses a traffic condition analysis and prediction method, a device and a system based on traffic big data, the method searches the median of the historical traffic flow speed average value in the time period to be inquired in the previous seven historical days of the road section to be inquired in a preset database, acquires the vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, calculates the vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment according to the vehicle instantaneous speed data set, calculates the median of the historical traffic flow speed average value and the average value of the vehicle instantaneous speed as the traffic flow speed prediction value of the road section to be inquired in the time period to be inquired for providing reference for the trip plan of a user in the time period to be inquired and the road section to be inquired, and enables the user to more intuitively perceive the actual traffic condition of a section of traffic road, necessary preparation is made for traveling.
Description
Technical Field
The invention relates to the technical field of traffic big data, in particular to a traffic condition analysis and prediction method, device and system based on traffic big data.
Background
With the development of science and technology and the progress of society, the living standard consumption level of people is gradually improved. The requirements of residents on the quality of life are gradually improved, and the number of domestic automobiles is increased day by day at present. The automobile provides convenience for people to travel, and simultaneously, a series of problems are generated, such as: traffic congestion, which presents some new challenges to the development of cities. The improvement of the urban traffic jam condition is not only the guarantee of the normal operation of the city, but also the urgent need of satisfying the increasingly beautiful life of people.
With the continuous development of big data technology, the application of big data technology in traffic condition analysis and prediction is increasing. The current traffic condition analysis and prediction method based on traffic big data generally utilizes a data acquisition terminal to acquire data such as traffic flow and the like, and then utilizes a server to predict the traffic condition of a section of traffic road based on traffic flow density, so that a user can inquire the result of the traffic condition analysis and prediction through a mobile terminal, and convenience is provided for traveling. Generally, the traffic flow density on a section of road is high, and it can be generally predicted that the traffic condition of the section of road in a certain future time is likely to be congested.
However, in some cases, the density of the traffic flow does not truly reflect the actual traffic condition of the road segment. For example, on an urban expressway, the traffic density may not be lower than that on a general road, but the clear traffic on the urban expressway may be better than that on the general road. Or, on some roads, although the traffic density is low, if there is a slow travel of individual vehicles, the traffic condition of the road section is influenced to some extent. Therefore, when the traffic condition is analyzed and predicted based on the traffic flow density, the user sometimes cannot accurately know the actual traffic condition of a section of traffic road.
Disclosure of Invention
The invention provides a traffic condition analysis and prediction method, a device and a system based on traffic big data, which aim to solve the problem that sometimes a user cannot accurately know the actual traffic condition of a section of traffic road in the traditional traffic condition analysis and prediction method.
In a first aspect, the present invention provides a traffic condition analysis and prediction method based on traffic big data, including:
receiving a traffic condition query request sent by a mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried;
searching a median of historical traffic flow speed average values of the road section to be inquired in the previous seven historical days and the time section to be inquired in a preset database according to the road section to be inquired and the time section to be inquired, wherein the historical traffic flow speed average values of a plurality of different road sections in each analysis time section of each historical day are stored in the preset database;
acquiring a vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, wherein the vehicle instantaneous speed data set comprises the last real-time data acquisition moment, instantaneous speed data of vehicles passing through the road section to be inquired is acquired by a data acquisition terminal of the road section to be inquired;
calculating the average value of the instantaneous speed of the vehicle of the road section to be inquired at the last real-time data acquisition moment according to the data set of the instantaneous speed of the vehicle;
calculating the median of the historical traffic flow speed average value and the average of the vehicle instantaneous speed average value to serve as a traffic flow speed predicted value of the road section to be inquired in the time period to be inquired;
and sending the traffic flow speed predicted value to the mobile terminal.
With reference to the first aspect, in a first implementation manner of the first aspect, a traffic condition query request sent by a mobile terminal is received, where the traffic condition query request carries a road segment to be queried and a time segment to be queried, and the road segment to be queried includes a road name to be queried and a driving direction.
With reference to the first aspect, in a second implementation manner of the first aspect, calculating an average value of the instantaneous speed of the vehicle of the road segment to be queried at the previous real-time data acquisition time according to the instantaneous speed data set of the vehicle includes:
identifying whether the instantaneous speed data of the vehicle within the set of vehicle instantaneous speed data is 0;
if the instantaneous speed data of the vehicle is 0, deleting the instantaneous speed data of the vehicle which is 0 from the instantaneous speed data set of the vehicle to obtain an instantaneous speed data set of the non-stationary vehicle;
calculating a vehicle instantaneous speed average of the non-stationary vehicle instantaneous speed data set.
With reference to the first aspect, in a third implementation manner of the first aspect, the step of sending the predicted traffic flow speed value to the mobile terminal further includes:
and sending the median of the historical traffic flow speed average value and the vehicle instantaneous speed average value to the mobile terminal.
In a second aspect, the present invention provides a traffic condition analyzing and predicting device based on traffic big data, including:
the receiving unit is used for receiving a traffic condition query request sent by the mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried;
the searching unit is used for searching a median of historical traffic flow speed average values of the road section to be inquired in the previous seven historical days in a preset database according to the road section to be inquired and the time section to be inquired, wherein the historical traffic flow speed average values of a plurality of different road sections in each analysis time section of each historical day are stored in the preset database;
the acquisition unit is used for acquiring a vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, wherein the vehicle instantaneous speed data set comprises the last real-time data acquisition moment, instantaneous speed data of vehicles passing through the road section to be inquired are acquired by a data acquisition terminal of the road section to be inquired;
the first calculation unit is used for calculating the vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment according to the vehicle instantaneous speed data set;
the second calculating unit is used for calculating the median of the historical traffic flow speed average value and the average of the vehicle instantaneous speed average value to serve as a traffic flow speed predicted value of the road section to be inquired in the time period to be inquired;
and the sending unit is used for sending the traffic flow speed predicted value to the mobile terminal.
With reference to the second aspect, in a first implementation manner of the second aspect, the road segment to be queried includes a road name and a driving direction to be queried.
With reference to the second aspect, in a second implementable manner of the second aspect, the first computing unit includes:
an identifying subunit for identifying whether the instantaneous speed data of the vehicle within the set of instantaneous speed data of the vehicle is 0;
the deleting subunit is used for deleting the instantaneous speed data of the vehicle, which is 0, from the vehicle instantaneous speed data set under the condition that the instantaneous speed data of the vehicle is 0, so as to obtain a non-stationary vehicle instantaneous speed data set;
a calculating subunit for calculating a vehicle instantaneous speed average of the non-stationary vehicle instantaneous speed data set.
With reference to the second aspect, in a third implementable manner of the second aspect, the sending unit is further configured to send the median of the historical traffic speed average and the vehicle instantaneous speed average to the mobile terminal.
In a third aspect, the present invention provides a traffic condition analysis and prediction system based on traffic big data, including: the system comprises a data acquisition terminal, a server and a mobile terminal, wherein the data acquisition terminal and the mobile terminal are respectively in communication connection with the server;
the data acquisition terminal is used for acquiring instantaneous speed data of vehicles passing by a road section at a preset real-time data acquisition moment;
the server is used for receiving a traffic condition query request sent by a mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried, and according to the road section to be queried and the time period to be queried, a preset database is searched for the median of historical traffic flow speed average values of the road section to be queried in the previous seven historical days and the time period to be queried, wherein the preset database stores the historical traffic flow speed average values of a plurality of different road sections in each analysis time period of each historical day, a vehicle instantaneous speed data set of the road section to be queried at the last real-time data acquisition time is obtained, the vehicle instantaneous speed data set comprises the last real-time data acquisition time, the instantaneous speed data of vehicles passing through the road section to be queried are acquired by a data acquisition terminal of the road section to be queried, according to the vehicle instantaneous speed data set, calculating a vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment, calculating a median of the historical traffic flow speed average value and an average value of the vehicle instantaneous speed average value, taking the median of the historical traffic flow speed average value and the average value as a traffic flow speed predicted value of the road section to be inquired in a time period to be inquired, and sending the traffic flow speed predicted value to the mobile terminal;
the mobile terminal is used for sending a traffic condition query request to the server.
The invention has the following beneficial effects: the invention provides a traffic condition analysis and prediction method, a device and a system based on traffic big data, which search the median of the historical traffic flow speed average value in the time period to be inquired in the previous seven historical days of the road section to be inquired in a preset database, acquire the vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, calculate the vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment according to the vehicle instantaneous speed data set, then calculate the median of the historical traffic flow speed average value and the average value of the vehicle instantaneous speed as the traffic flow speed predicted value of the road section to be inquired in the time period to be inquired and the trip plan of the road section to be inquired by a user, and provide reference for the trip plan of the user in the time period to be inquired and the road section to be inquired based on the average speed of the historical vehicles in the, and the current instantaneous speed of the vehicle on the road section to be inquired is used for predicting the estimated traffic flow speed in the time period to be inquired and the road section to be inquired.
Drawings
In order to more clearly illustrate the technical solution of the present invention, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious to those skilled in the art that other drawings can be obtained according to the drawings without any inventive exercise.
Fig. 1 is a flowchart of a traffic condition analysis and prediction method based on traffic big data according to an embodiment of the present invention.
Fig. 2 is a flowchart of step S104.
Fig. 3 is a schematic diagram of data stored in a preset database in a traffic condition analysis and prediction method based on traffic big data according to an embodiment of the present invention.
Fig. 4 is a schematic structural diagram of a traffic condition analysis and prediction device based on traffic big data according to an embodiment of the present invention.
Fig. 5 is a schematic diagram of a traffic condition analysis and prediction system based on traffic big data according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the specific embodiments of the present invention and the accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention. The technical solutions provided by the embodiments of the present invention are described in detail below with reference to the accompanying drawings.
Referring to fig. 1, an executing subject of the traffic condition analyzing and predicting method based on traffic big data according to an embodiment of the present invention may be a server, and the method may include the following steps:
step S101, receiving a traffic condition query request sent by a mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried.
In this embodiment, the mobile terminal may be in communication connection with the server through the internet, and when the user wants to query the traffic condition of a certain road segment, the mobile terminal may be used to initiate a traffic condition query request to the server. The mobile terminal may be a smart phone, a tablet computer, or the like. The road section to be inquired comprises the name of the road to be inquired and the driving direction. When the movie tiger initiates a traffic condition query request, the name of the road segment to be queried and the driving direction, for example, the XX road (XX direction) need to be input or selected, and the starting time of the time period to be queried, for example, 8: 00-9: 00.
step S102, searching a median of historical traffic flow speed average values of the road section to be inquired in the previous seven historical days and the time section to be inquired in a preset database according to the road section to be inquired and the time section to be inquired, wherein the historical traffic flow speed average values of a plurality of different road sections in each analysis time section of each historical day are stored in the preset database.
As shown in fig. 2, the preset database may store historical traffic flow speed averages (e.g., v1, v2, etc.) of various analysis time periods (e.g., 8: 00-9: 00, 9: 00-10: 00, etc.) of each historical day (e.g., x month 1 day, x month 2 day, etc.) in different driving directions (e.g., forward lane, reverse lane) of some roads (e.g., road 1, road 2).
The method comprises the steps that the time used by a vehicle passing through a front lane and a reverse lane of a road in each analysis time period can be collected by a data collection terminal arranged on the road in advance, the server calculates the average speed of each vehicle passing through the road in the analysis time period according to the time of the vehicle passing through the road and the mileage of the road, and the average speed is obtained to obtain the average value of the historical traffic flow speed on the road in a certain analysis time period of a historical day. The road can be divided into sections according to preset mileage. The duration of the analysis period may also be set to half an hour, one hour, or the like. The invention takes the median of the average value of the historical traffic flow speed in the time period to be inquired in the previous seven historical days, and aims to obtain enough samples and reduce the deviation caused by the difference of the number of people going on a working day, a weekend or a holiday.
Step S103, acquiring a vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, wherein the vehicle instantaneous speed data set comprises the last real-time data acquisition moment and the instantaneous speed data of the passing vehicle on the road section to be inquired, and the instantaneous speed data of the vehicle is acquired by a data acquisition terminal of the road section to be inquired.
Specifically, the data acquisition terminals may be respectively disposed on each road segment, and the real-time data acquisition time may be set to 1min, 30s, and the like. The data acquisition terminal acquires the instantaneous speed of the vehicle at the current moment on the next road section once every other real-time data acquisition moment to obtain a vehicle instantaneous speed data set.
And step S104, calculating the average value of the instantaneous speed of the vehicle of the road section to be inquired at the previous real-time data acquisition moment according to the data set of the instantaneous speed of the vehicle.
As shown in fig. 3, in this embodiment, step S104 may specifically include:
in step S1041, it is identified whether the instantaneous speed data of the vehicle in the vehicle instantaneous speed data set is 0.
Step S1042, if the instantaneous speed data of the vehicle is 0, deleting the instantaneous speed data of the vehicle which is 0 from the vehicle instantaneous speed data set to obtain a non-stationary vehicle instantaneous speed data set.
Step S1043, calculating a vehicle instantaneous speed average of the non-stationary vehicle instantaneous speed data set.
Because stationary vehicles may exist in the road section, and the speed of the stationary vehicles is 0, the speed is removed to obtain a non-stationary vehicle instantaneous speed data set, and then the vehicle instantaneous speed average value of the non-stationary vehicle instantaneous speed data set is calculated, so that the obtained result is more accurate and has more reference significance.
And step S105, calculating the median of the historical traffic flow speed average value and the average of the vehicle instantaneous speed average value to serve as a traffic flow speed predicted value of the road section to be inquired in the time period to be inquired.
And step S106, sending the predicted traffic flow speed value to the mobile terminal.
In this embodiment, the server may further send the median of the historical traffic speed average and the vehicle instantaneous speed average to the mobile terminal for the user to refer to.
According to the technical scheme, the traffic condition analysis and prediction method based on the traffic big data searches the preset database for the median of the historical traffic flow speed average value in the time period to be inquired in the previous seven historical days of the road section to be inquired, acquires the vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, calculates the vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment according to the vehicle instantaneous speed data set, calculates the median of the historical traffic flow speed average value and the average value of the vehicle instantaneous speed as the traffic flow speed predicted value of the road section to be inquired in the time period to be inquired and provides reference for the trip plan of a user in the time period to be inquired and the road section to be inquired, and is based on the historical vehicle average speeds in the time period to be inquired and the road section to be inquired, and the current instantaneous speed of the vehicle on the road section to be inquired is used for predicting the estimated traffic flow speed in the time period to be inquired and the road section to be inquired.
Referring to fig. 4, an embodiment of the present application further provides a traffic condition analyzing and predicting device based on traffic big data, including:
the receiving unit 401 is configured to receive a traffic condition query request sent by a mobile terminal, where the traffic condition query request carries a road segment to be queried and a time segment to be queried.
The searching unit 402 is configured to search, according to the road segment to be queried and the time segment to be queried, a preset database for a median of historical traffic flow speed averages of the road segment to be queried in previous seven historical days in the time segment to be queried, where the preset database stores historical traffic flow speed averages of a plurality of different road segments in each analysis time segment of each historical day.
The acquiring unit 403 is configured to acquire a vehicle instantaneous speed data set of the road segment to be queried at the previous real-time data acquisition time, where the vehicle instantaneous speed data set includes the previous real-time data acquisition time and instantaneous speed data of a vehicle passing through the road segment to be queried, and the instantaneous speed data of the vehicle is acquired by a data acquisition terminal of the road segment to be queried.
The first calculating unit 404 is configured to calculate an average value of the instantaneous speed of the vehicle at the previous real-time data acquisition time of the road segment to be queried according to the instantaneous speed data set of the vehicle.
And the second calculating unit 405 is configured to calculate an average value of the median of the historical traffic flow speed average values and the vehicle instantaneous speed average value as a traffic flow speed predicted value of the road section to be queried in the time period to be queried.
And a sending unit 406, configured to send the predicted traffic flow speed value to the mobile terminal.
In this embodiment, the road section to be queried includes a road name and a driving direction to be queried. The first calculating unit may specifically include: and the identification subunit is used for identifying whether the instantaneous speed data of the vehicle in the vehicle instantaneous speed data set is 0 or not. And the deleting subunit is used for deleting the instantaneous speed data of the vehicle of which the speed is 0 from the vehicle instantaneous speed data set under the condition that the instantaneous speed data of the vehicle is 0 to obtain a non-stationary vehicle instantaneous speed data set. And the calculating subunit is used for calculating the vehicle instantaneous speed average value of the non-stationary vehicle instantaneous speed data set. And the sending unit is also used for sending the median of the historical traffic flow speed average value and the vehicle instantaneous speed average value to the mobile terminal.
Referring to fig. 5, an embodiment of the present application further provides a traffic condition analysis and prediction system based on traffic big data, including: the mobile terminal comprises a data acquisition terminal 1, a server 3 and a mobile terminal 2, wherein the data acquisition terminal 1 and the mobile terminal 2 are respectively in communication connection with the server 3. And the data acquisition terminal 1 is used for acquiring instantaneous speed data of vehicles passing by a road section at a preset real-time data acquisition moment. The server 3 is used for receiving a traffic condition query request sent by the mobile terminal, the traffic condition query request carries a road section to be queried and a time section to be queried, and according to the road section to be queried and the time section to be queried, searching a preset database for a median of historical traffic flow speed average values of the road section to be queried in previous seven historical days and the time section to be queried, wherein the preset database stores the historical traffic flow speed average values of a plurality of different road sections in each analysis time section of each historical day, acquiring a vehicle instantaneous speed data set of the road section to be queried at the previous real-time data acquisition time, the vehicle instantaneous speed data set comprises the previous real-time data acquisition time and the instantaneous speed data of vehicles passing through the road section to be queried, the instantaneous speed data of the vehicles are acquired by a data acquisition terminal of the road section to be queried, and according to the vehicle instantaneous speed data set, calculating the average value of the instantaneous speed of the vehicle of the road section to be inquired at the last real-time data acquisition moment, calculating the median of the average value of the historical traffic flow speed and the average value of the instantaneous speed of the vehicle, taking the average value as the predicted value of the traffic flow speed of the road section to be inquired in the time period to be inquired, and sending the predicted value of the traffic flow speed to the mobile terminal;
and the mobile terminal 2 is used for sending a traffic condition inquiry request to the server.
The embodiment of the present invention further provides a storage medium, and the storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements part or all of the steps of the traffic condition analysis and prediction method based on traffic big data provided by the present invention. The storage medium may be a magnetic disk, an optical disk, a Read-only memory (ROM) or a Random Access Memory (RAM).
Those skilled in the art will readily appreciate that the techniques of the embodiments of the present invention may be implemented as software plus a required general purpose hardware platform. Based on such understanding, the technical solutions in the embodiments of the present invention may be essentially or partially implemented in the form of a software product, which may be stored in a storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments or some parts of the embodiments.
The same and similar parts in the various embodiments in this specification may be referred to each other. Particularly, as for the embodiment of the regional ecological quality evaluation device and the system, since the embodiment is basically similar to the embodiment of the method, the description is simple, and the relevant points can be referred to the description in the embodiment of the method.
The above-described embodiments of the present invention should not be construed as limiting the scope of the present invention.
Claims (9)
1. A traffic condition analysis and prediction method based on traffic big data is characterized by comprising the following steps:
receiving a traffic condition query request sent by a mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried;
searching a median of historical traffic flow speed average values of the road section to be inquired in the previous seven historical days and the time section to be inquired in a preset database according to the road section to be inquired and the time section to be inquired, wherein the historical traffic flow speed average values of a plurality of different road sections in each analysis time section of each historical day are stored in the preset database;
acquiring a vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, wherein the vehicle instantaneous speed data set comprises the last real-time data acquisition moment, instantaneous speed data of vehicles passing through the road section to be inquired is acquired by a data acquisition terminal of the road section to be inquired;
calculating the average value of the instantaneous speed of the vehicle of the road section to be inquired at the last real-time data acquisition moment according to the data set of the instantaneous speed of the vehicle;
calculating the median of the historical traffic flow speed average value and the average of the vehicle instantaneous speed average value to serve as a traffic flow speed predicted value of the road section to be inquired in the time period to be inquired;
and sending the traffic flow speed predicted value to the mobile terminal.
2. The method according to claim 1, wherein a traffic condition query request sent by a mobile terminal is received, and the traffic condition query request carries a road section to be queried and a time period to be queried, wherein the road section to be queried comprises a road name to be queried and a driving direction.
3. The method of claim 1, wherein calculating the average value of the instantaneous speed of the vehicle of the road segment to be queried at the last real-time data acquisition time according to the data set of the instantaneous speed of the vehicle comprises:
identifying whether the instantaneous speed data of the vehicle within the set of vehicle instantaneous speed data is 0;
if the instantaneous speed data of the vehicle is 0, deleting the instantaneous speed data of the vehicle which is 0 from the instantaneous speed data set of the vehicle to obtain an instantaneous speed data set of the non-stationary vehicle;
calculating a vehicle instantaneous speed average of the non-stationary vehicle instantaneous speed data set.
4. The method of claim 1, wherein the step of sending the predicted traffic flow speed value to the mobile terminal further comprises:
and sending the median of the historical traffic flow speed average value and the vehicle instantaneous speed average value to the mobile terminal.
5. A traffic condition analysis and prediction device based on traffic big data is characterized by comprising:
the receiving unit is used for receiving a traffic condition query request sent by the mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried;
the searching unit is used for searching a median of historical traffic flow speed average values of the road section to be inquired in the previous seven historical days in a preset database according to the road section to be inquired and the time section to be inquired, wherein the historical traffic flow speed average values of a plurality of different road sections in each analysis time section of each historical day are stored in the preset database;
the acquisition unit is used for acquiring a vehicle instantaneous speed data set of the road section to be inquired at the last real-time data acquisition moment, wherein the vehicle instantaneous speed data set comprises the last real-time data acquisition moment, instantaneous speed data of vehicles passing through the road section to be inquired are acquired by a data acquisition terminal of the road section to be inquired;
the first calculation unit is used for calculating the vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment according to the vehicle instantaneous speed data set;
the second calculating unit is used for calculating the median of the historical traffic flow speed average value and the average of the vehicle instantaneous speed average value to serve as a traffic flow speed predicted value of the road section to be inquired in the time period to be inquired;
and the sending unit is used for sending the traffic flow speed predicted value to the mobile terminal.
6. The apparatus of claim 5, wherein the road segment to be queried comprises a road name and a driving direction to be queried.
7. The apparatus of claim 5, wherein the first computing unit comprises:
an identifying subunit for identifying whether the instantaneous speed data of the vehicle within the set of instantaneous speed data of the vehicle is 0;
the deleting subunit is used for deleting the instantaneous speed data of the vehicle, which is 0, from the vehicle instantaneous speed data set under the condition that the instantaneous speed data of the vehicle is 0, so as to obtain a non-stationary vehicle instantaneous speed data set;
a calculating subunit for calculating a vehicle instantaneous speed average of the non-stationary vehicle instantaneous speed data set.
8. The apparatus of claim 5, wherein the transmitting unit is further configured to transmit a median of the historical traffic speed averages and the vehicle instantaneous speed average to the mobile terminal.
9. A traffic condition analysis and prediction system based on traffic big data is characterized by comprising: the system comprises a data acquisition terminal, a server and a mobile terminal, wherein the data acquisition terminal and the mobile terminal are respectively in communication connection with the server;
the data acquisition terminal is used for acquiring instantaneous speed data of vehicles passing by a road section at a preset real-time data acquisition moment;
the server is used for receiving a traffic condition query request sent by a mobile terminal, wherein the traffic condition query request carries a road section to be queried and a time period to be queried, and according to the road section to be queried and the time period to be queried, a preset database is searched for the median of historical traffic flow speed average values of the road section to be queried in the previous seven historical days and the time period to be queried, wherein the preset database stores the historical traffic flow speed average values of a plurality of different road sections in each analysis time period of each historical day, a vehicle instantaneous speed data set of the road section to be queried at the last real-time data acquisition time is obtained, the vehicle instantaneous speed data set comprises the last real-time data acquisition time, the instantaneous speed data of vehicles passing through the road section to be queried are acquired by a data acquisition terminal of the road section to be queried, according to the vehicle instantaneous speed data set, calculating a vehicle instantaneous speed average value of the road section to be inquired at the last real-time data acquisition moment, calculating a median of the historical traffic flow speed average value and an average value of the vehicle instantaneous speed average value, taking the median of the historical traffic flow speed average value and the average value as a traffic flow speed predicted value of the road section to be inquired in a time period to be inquired, and sending the traffic flow speed predicted value to the mobile terminal;
the mobile terminal is used for sending a traffic condition query request to the server.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114566046A (en) * | 2022-03-01 | 2022-05-31 | 海南大学 | Short-time traffic condition prediction system and method thereof |
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