CN114613145A - Passenger traffic flow perception early warning system and method under big data - Google Patents
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Abstract
The invention discloses a passenger traffic flow perception early warning system and a method under big data, which comprises a cloud service platform, a data acquisition module, a warning module, an intelligent terminal, a Beidou positioning service unit, a database and an information transmission unit, wherein the cloud service platform is used for carrying out platform-type control management on the perception early warning system, and the system can calculate and predict the road condition of a road section which is passed by each time period when a user arrives at a destination to drive through the road section through the use of the cloud service platform, the data acquisition module, the warning module, the intelligent terminal, the Beidou positioning service unit, the database and the information transmission unit, thereby pre-judging whether the road is unblocked or blocked when the user passes through the road section at a certain moment in advance, and making corresponding early warning prompt for the user to make corresponding measures or change a driving route in time and avoiding driving into the road blocked road section, meanwhile, accidents caused by road congestion are reduced.
Description
Technical Field
The invention relates to the field of big data, in particular to a passenger traffic flow perception early warning system and method under the big data.
Background
Big data (big data), or huge data, refers to the data volume is huge enough that the data volume can not be captured, managed, processed and arranged in a reasonable time to become information which helps the enterprise to make business decision more positive; at present, with the rapid development of social economy, the living standard of people is gradually improved, the use of automobiles is gradually increased, such as driving to work and traveling for playing, and along with the occurrence of convenience, the increase of vehicles and the increasing occurrence of traffic accidents, an early warning system is generally adopted for early warning in order to reduce the occurrence of accidents, so that certain preparation is made in time for knowing the road condition, and the occurrence of accidents is reduced.
Some existing early warning systems can only display real-time road conditions in road sections in a navigation route and display current road condition congestion conditions, but cannot correspondingly predict whether roads are congested when passing through a certain road section at a certain time period, and the like, so that route changes or corresponding measures cannot be timely made.
Disclosure of Invention
The invention aims to provide a passenger traffic flow perception early warning system and method under big data to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: the utility model provides a passenger traffic flow perception early warning system under big data, includes cloud service platform, data acquisition module, warning module, intelligent terminal, big dipper location service unit, database and information transmission unit, cloud service platform is used for carrying out platform formula control management to perception early warning system, data acquisition module carries out data acquisition to the route of traveling, warning module is used for carrying out the early warning suggestion to corresponding measure is reminded, intelligent terminal is used for looking over perception early warning system data and route data information of traveling, cloud service platform's input is connected with data acquisition module, intelligent terminal, big dipper location service unit, database and information transmission unit's output respectively, cloud service platform's output is connected with data acquisition module, warning module, intelligent terminal, big dipper location service unit, The input of database and information transmission unit is connected, intelligent terminal and database communication connection, the data acquisition module includes traffic flow data acquisition unit, the circuit acquisition unit and the speed of a motor vehicle of traveling, traffic flow data acquisition unit is used for the data acquisition to the traffic flow on the same circuit of same period of the day, the circuit acquisition unit that traveles is gathered the circuit data of traveling, the speed of a motor vehicle acquisition unit is gathered and is transmitted the update to the real-time speed of a motor vehicle data of vehicle to know the time of traveling to a certain highway section, thereby can carry out the early warning more accurately and judge.
Further, the cloud service platform comprises a central processing unit, an information receiving and sending unit and a storage unit, wherein the central processing unit is used for analyzing, integrating and processing data, the information receiving and sending unit is used for receiving and sending information, and the storage unit is used for storing and using data.
Further, the storage unit comprises a body memory and a cloud memory.
Further, the warning module comprises a road condition warning unit and a traffic accident warning unit, the road condition warning unit is used for carrying out corresponding early warning according to whether the road condition of the driving route is smooth or jammed, and the traffic accident warning unit is used for carrying out real-time monitoring and early warning on a traffic accident which occurs on the driving route, so that a driver can timely carry out route changing driving.
Furthermore, the intelligent terminal comprises an input unit and a display unit, wherein the input unit is used for inputting data to the intelligent terminal, and the display unit is used for displaying system data.
Furthermore, the Beidou positioning service unit is used for providing positioning and navigation services for users through a Beidou navigation system.
Further, the database is used for providing comparison data and storing new data.
Further, the information transmission unit is used for mutual information transmission between the user and the cloud service platform through the big data and internet system.
The invention also provides a method of the passenger traffic perception early warning system under big data, which comprises the following steps:
a) the intelligent terminal starts a system, passenger traffic flow sensing and early warning processing is carried out, data acquisition modules are used for acquiring traffic flow data on the same route at the same time period in the same day, acquiring data information of a driving route and monitoring and acquiring the speed of the vehicle in real time, and the acquired data are transmitted to the cloud service platform;
b) the cloud service platform analyzes and integrates the acquired data, the warning module senses and pre-warns passenger traffic flow, and in the process of analyzing, processing and integrating the data, the traffic flow data of the same road section at the same time period on a certain day is AnmWhere n denotes a certain day from monday to sunday, m denotes a certain time period from twenty-four hours to twenty-four times a day, and when n =1 and m =1, a11The traffic flow of the same line in the period from zero point to one point in the morning of Monday is represented, and when n =1 and m =2, A12The method comprises the steps that the traffic flow of the same line in one-point to two-point time periods in Monday morning is shown, when n =1 and m =24, the traffic flow of the same line in one-point to zero-point time periods in Monday 23 is shown, and when n =2 and m =1, the traffic flow of the same line in one-point time periods in Tuesday morning is shown;
c) The average traffic flow of the same road section in a certain time period on a certain day in the last year called from the database is designated as H, and H = 0.5M1nm+0.25*M2nm+0.15*M3nm+0.1*M4nm，M1nmRepresenting data proximity A in the databasenmAverage traffic flow, M, in the 1 st to 3 rd month period2nmRepresenting data proximity A in the databasenmAverage traffic flow, M, in the 4 th to 6 th month period of (1)3nmRepresenting data proximity A in the databasenmAverage traffic flow, M, in the 7 th to 9 th month period of (1)4nmRepresenting proximity A in the databasenmAverage traffic flow in the 10 th-12 th month period of (a);
d）0.5*M1nm=0.5*（∑b1nm/z），b1nmrepresenting adjacent A in said databasenmThe traffic flow in the 1 st-3 rd month period of (a), z represents the total number in the taken time period range;
0.25*M2nm=0.25*（∑b2nm/z），b2nmrepresenting adjacent A in said databasenmThe traffic flow in the 4 th-6 th month time period;
0.15*M3nm=0.15*（∑b3nm/z），b3nmrepresenting adjacent A in said databasenmThe traffic flow in the 7 th-9 th month time period;
0.1*M4nm=0.1*（∑b4nm/z），b4nmrepresenting adjacent A in said databasenmThe traffic flow in the 10 th-12 th month time period;
e) the road shape judging value is F = AnmWhen F is more than or equal to 0 and less than or equal to 0.7, the road condition is good and the road is smooth when the road passes through the same road section in the same time period on the same day, and the road condition alarm unit is used for performing the first-stage early warning prompt of the road smoothness;
f) when F is more than 0.7 and less than or equal to 1, judging that vehicles passing through the road tend to be saturated and can normally run through the road when passing through the same road section in the same time period on the same day, and performing secondary early warning reminding through the road condition warning unit, and paying attention to control the speed of the vehicle when running on the road section and keeping the distance between the vehicles to run;
g) When the distance is less than 1 and less than F, predicting and judging that the traffic flow of the road section exceeds the amount of the road which can be borne by the road when the vehicle runs to the road section, the road is jammed, accidents are easy to occur, early warning prompting is carried out through the road condition warning unit, the road jam and the accidents are easy to occur when the vehicle passes through the road section in a certain time period, route changing is reminded, meanwhile, the Beidou positioning service unit is used for giving other routes which lead to a destination and have good road conditions after the data judgment is carried out on the routes of the same direction of the destination around the vehicle.
Compared with the prior art, the invention has the following beneficial effects:
the invention can predict the real-time condition of the road of the route which is passed by the user when the user reaches the destination through the use of the cloud service platform, the data acquisition module, the warning module, the intelligent terminal, the Beidou positioning service unit, the database and the information transmission unit, calculate and predict the road condition when the same time period passes through the same road section, judge whether the road of the road section is smooth when the user reaches and enters the road section in advance, compare and judge whether the road is smooth, the road is saturated and can be normally run at the same time and the road is crowded according to the calculated result and recommend the route with good road condition, meanwhile, the system can update the data in real time and can carry out the change of the real-time pre-judging result according to the self speed and the like, thereby ensuring the accuracy of the pre-judging result, and the system can pre-judge whether the road is smooth or crowded when the certain time passes through the road section in advance, and corresponding early warning reminding is given, so that a user can make corresponding measures or change a driving route in time, the use is more convenient, the phenomenon that the user drives into a road congestion section is avoided, and accidents caused by road congestion are reduced.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of the module connection of the present invention as a whole;
in the figure: 1. a cloud service platform; 2. a data acquisition module; 3. a warning module; 4. an intelligent terminal; 5. a Beidou positioning service unit; 6. a database; 7. an information transmission unit; 8. a central processing unit; 9. an information transmitting/receiving unit; 10. a storage unit; 11. a traffic flow data acquisition unit; 12. a driving route acquisition unit; 13. a vehicle speed acquisition unit; 14. an input unit; 15. a display unit; 16. a road condition warning unit; 17. and a traffic accident alarm unit.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
As shown in figure 1, passenger traffic flow perception early warning system under big data comprises a cloud service platform 1, a data acquisition module 2, a warning module 3, an intelligent terminal 4, a Beidou positioning service unit 5, a database 6 and an information transmission unit 7, wherein the cloud service platform 1 is used for carrying out platform type control management on the perception early warning system, the data acquisition module 2 is used for carrying out data acquisition on a driving route, the warning module 3 is used for carrying out early warning prompt and providing corresponding measure reminding, the intelligent terminal 4 is used for checking perception early warning system data and driving route data information, the input end of the cloud service platform 1 is respectively connected with the output ends of the data acquisition module 2, the intelligent terminal 4, the Beidou positioning service unit 5, the database 6 and the information transmission unit 7, and the output end of the cloud service platform 1 is respectively connected with the data acquisition module 2, Warning module 3, intelligent terminal 4, big dipper location service unit 5, database 6 and information transmission unit 7's input is connected, intelligent terminal 4 and database 6 communication connection, data acquisition module 2 includes traffic flow data acquisition unit 11, the line acquisition unit 12 and the speed of a motor vehicle acquisition unit 13 of traveling, traffic flow data acquisition unit 11 is used for the data acquisition to the traffic flow on same day same period same circuit, the line acquisition unit 12 that travels gathers the line data of traveling, speed of a motor vehicle acquisition unit 13 gathers and transmits the update to the real-time speed of a motor vehicle data of vehicle to know the time of traveling to a certain highway section, thereby can carry out early warning judgement more accurately.
The cloud service platform 1 comprises a central processing unit 8, an information transceiving unit 9 and a storage unit 10, wherein the central processing unit 8 is used for analyzing, integrating and processing data, the information transceiving unit 9 is used for transceiving information, and the storage unit 10 is used for storing and using data.
The storage unit 10 includes a body memory and a cloud memory.
The warning module 3 comprises a road condition warning unit 16 and a traffic accident warning unit 17, wherein the road condition warning unit 16 is used for carrying out corresponding early warning according to whether the road condition of a driving line is smooth or jammed, and the traffic accident warning unit 17 is used for carrying out real-time monitoring and early warning on a traffic accident which occurs on the driving line so that a driver can timely carry out route changing driving.
The intelligent terminal 4 comprises an input unit 14 and a display unit 15, wherein the input unit 14 is used for inputting data to the intelligent terminal 4, and the display unit 15 is used for displaying system data.
And the Beidou positioning service unit 5 is used for providing positioning and navigation services for users through a Beidou navigation system.
The database 6 is used for providing comparison data and storing new data.
The information transmission unit 7 is used for mutual information transmission between the user and the cloud service platform 1 through a big data and internet system.
The invention also provides a use method of the passenger traffic perception early warning system under the big data, which comprises the following steps:
a) the intelligent terminal 4 is used for starting a system, sensing and early warning passenger traffic flow, acquiring data of the traffic flow on the same route at the same time period in the same day, acquiring data information of a driving route and monitoring and acquiring the speed of the vehicle in real time through the data acquisition module 2, and transmitting the acquired data to the cloud service platform 1;
b) the cloud service platform 1 analyzes and integrates the acquired data, the warning module 3 senses and pre-warns passenger traffic flow, and in the process of analyzing, processing and integrating the data, the traffic flow data of the same road section at the same time period on a certain day is AnmWhere n denotes a certain day from monday to sunday, m denotes a certain time period from twenty-four hours to twenty-four times a day, and when n =1 and m =1, a11To indicate the weekWhen the traffic flow passing through the same line in the period from zero point to one point in morning is n =1 and m =2, A12The method comprises the steps that the traffic flow of the same line in one-point to two-point time periods in Monday morning is shown, when n =1 and m =24, the traffic flow of the same line in one-point to zero-point time periods in Monday 23 is shown, and when n =2 and m =1, the traffic flow of the same line in one-point time periods in Tuesday morning is shown;
c) The average traffic flow of the same road section in a certain time period on a day in the last year called from the database 6 is called H, H = 0.5M1nm+0.25*M2nm+0.15*M3nm+0.1*M4nmThe data acquisition module 2 comprises a traffic flow data acquisition unit 11, a driving line acquisition unit 12 and a vehicle speed acquisition unit 13, the traffic flow data acquisition unit 11 is used for acquiring the data of traffic flow on the same line in the same time period in the same day, the driving line acquisition unit 12 acquires driving line data, and the vehicle speed acquisition unit 13 acquires and transmits and updates real-time vehicle speed data of a vehicle so as to know the time of driving to a certain road section, so that early warning judgment can be performed more accurately, and M is a vehicle speed acquisition unit1nmIndicates the proximity of data A in the database 6nmAverage traffic flow, M, in the 1 st to 3 rd month period of2nmIndicating the proximity of data A in said database 6nmAverage traffic flow, M, in the 4 th to 6 th month period of (1)3nmIndicating the proximity of data A in said database 6nmAverage traffic flow, M, in the 7 th-9 th month period of (1)4nmRepresenting adjacent A in said database 6nmAverage traffic flow in the 10 th-12 th month period of (a);
d）0.5*M1nm=0.5*（∑b1nm/z），b1nmrepresenting adjacent A in said database 6nmThe traffic flow in the 1 st-3 rd month period of (a), z represents the total number in the taken time period range;
0.25*M2nm=0.25*（∑b2nm/z），b2nmRepresenting neighbors A in said database 6nmThe traffic flow in the 4 th-6 th month time period;
0.15*M3nm=0.15*（∑b3nm/z），b3nmrepresenting adjacent A in said database 6nmThe traffic flow in the 7 th-9 th month time period;
0.1*M4nm=0.1*（∑b4nm/z），b4nmrepresenting adjacent A in said database 6nmThe traffic flow in the 10 th-12 th month time period;
e) the road shape judging value is F = AnmWhen F is more than or equal to 0 and less than or equal to 0.7, the road condition is good and the road is smooth when the road passes through the same road section in the same time period on the same day, and the road condition alarm unit 16 is used for carrying out the first-stage early warning prompt of the road smoothness;
f) when F is more than 0.7 and less than or equal to 1, judging that the passing vehicles on the road tend to be saturated and can normally run through the same road section in the same time period on the same day, and performing secondary early warning reminding through the road condition warning unit 16, and paying attention to control the speed of the vehicle and keeping the distance between the vehicles to run when the vehicle runs on the road section;
g) when the distance is less than 1 and less than F, when the vehicle is predicted and judged to run to the road section, the traffic flow of the road section exceeds the amount of the road which can be borne by the road, the road is jammed, accidents are easy to occur, the warning prompt is carried out through the road condition warning unit 16, the road jam and the accidents are easy to occur when the vehicle passes through the road section in a certain time period, the route is reminded to be changed, meanwhile, the route of the surrounding equidirectional destination is judged through data, the other routes which are good in road condition and lead to the destination are given through the Beidou positioning service unit 5 after the prediction judgment is carried out.
The embodiment specifically solves the problems that some existing early warning systems mentioned in the background art can only display the real-time road unobstructed congestion situation of a certain road section on navigation in real time, and cannot pre-judge whether the road section is unobstructed or congested when the road section passes through the certain road section in a certain time period in advance for early warning and reminding
The working principle of the invention is as follows:
referring to the attached drawing 1 of the specification, by using a cloud service platform 1, a data acquisition module 2, a warning module 3, an intelligent terminal 4, a Beidou positioning service unit 5, a database 6 and an information transmission unit 7, whether a road of a road section is smooth or congested when the road passes through the road section at a certain time period on a navigation route to a destination can be judged in advance and the result is early warned, so that a user can timely make corresponding selection measures, the phenomenon that the time is urgent to drive into the congested road section is avoided, the time is influenced, and the use is more convenient;
finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a passenger traffic flow perception early warning system under big data, includes cloud service platform (1), data acquisition module (2), warning module (3), intelligent terminal (4), big dipper location service unit (5), database (6) and information transmission unit (7), its characterized in that: the cloud service platform (1) is used for carrying out platform-type control management on the perception early warning system, the data acquisition module (2) is used for carrying out data acquisition on a driving route, the warning module (3) is used for carrying out early warning prompt and providing corresponding measure reminding, the intelligent terminal (4) is used for checking perception early warning system data and driving route data information, the input end of the cloud service platform (1) is respectively connected with the output ends of the data acquisition module (2), the intelligent terminal (4), the Beidou positioning service unit (5), the database (6) and the information transmission unit (7), the output end of the cloud service platform (1) is respectively connected with the input ends of the data acquisition module (2), the warning module (3), the intelligent terminal (4), the Beidou positioning service unit (5), the database (6) and the information transmission unit (7), intelligent terminal (4) and database (6) communication connection, data acquisition module (2) include traffic flow data acquisition unit (11), the circuit acquisition unit (12) and the speed of a motor vehicle acquisition unit (13) of traveling, traffic flow data acquisition unit (11) are used for the data acquisition to the traffic flow on the same circuit of same period of time on the same day, the circuit acquisition unit (12) of traveling gathers the circuit data of traveling, speed of a motor vehicle acquisition unit (13) are gathered the real-time speed of a motor vehicle data of vehicle and are transmitted the update to know the time of traveling to a certain highway section, thereby can carry out early warning judgement more accurately.
2. The passenger traffic flow perception early warning system under big data according to claim 1, characterized in that: the cloud service platform (1) comprises a central processing unit (8), an information transceiving unit (9) and a storage unit (10), wherein the central processing unit (8) is used for analyzing, integrating and processing data, the information transceiving unit (9) is used for transceiving and processing information, and the storage unit (10) is used for storing and using data.
3. The passenger traffic flow perception early warning system under big data according to claim 2, characterized in that: the storage unit (10) comprises a body memory and a cloud memory.
4. The passenger traffic flow perception early warning system under big data according to claim 1, characterized in that: the warning module (3) comprises a road condition warning unit (16) and a traffic accident warning unit (17), wherein the road condition warning unit (16) is used for carrying out corresponding early warning according to whether the road condition of a driving line is smooth or jammed, and the traffic accident warning unit (17) is used for carrying out real-time monitoring and early warning on a traffic accident which occurs on the driving line so that a driver can timely drive the driving line.
5. The passenger traffic perception early warning system under big data as claimed in claim 1, wherein: the intelligent terminal (4) comprises an input unit (14) and a display unit (15), wherein the input unit (14) is used for inputting data to the intelligent terminal (4), and the display unit (15) is used for displaying system data.
6. The passenger traffic perception early warning system under big data as claimed in claim 1, wherein: the Beidou positioning service unit (5) is used for providing positioning and navigation services for users through a Beidou navigation system.
7. The passenger traffic flow perception early warning system under big data according to claim 1, characterized in that: the database (6) is used for providing comparison data and storing new data.
8. The passenger traffic flow perception early warning system under big data according to claim 1, characterized in that: the information transmission unit (7) is used for transmitting information between the user and the cloud service platform (1) through the big data and the internet system.
9. The use method of the passenger traffic perception early warning system under big data according to any one of claims 1-8, characterized in that: the method comprises the following steps:
a) The intelligent terminal (4) is used for starting a system, sensing and early warning passenger traffic flow, acquiring data of the traffic flow on the same route at the same time period in the same day, acquiring data information of a driving route and monitoring and acquiring the speed in real time, and transmitting the acquired data to the cloud service platform (1);
b) the cloud service platform (1) analyzes and integrates the acquired data, the warning module (3) senses and pre-warns passenger traffic flow, and in the process of analyzing, processing and integrating the data, the traffic flow data of the same road section in the same time period on a certain day is AnmWhere n denotes a day from monday to sunday, m denotes a time period from twenty-four hours to twenty-four times a day, and when n =1 and m =1, a11The traffic flow of the same line in the period from zero point to one point in morning on Monday is represented, and when n =1 and m =2, A12The flow rate of the traffic passing through the same line in one-point to two-point time in the morning of Monday is shown, and when n =1 and m =24, the tableWhen n =2 and m =1, the traffic flow passing through the same end line in the time period from 23 monday points to zero points is represented by the traffic flow passing through the same end line in the time period from zero point to one point in the morning of tuesday;
c) The average traffic flow of the same road section in a certain time period on a day in the last year called from the database (6) is designated as H, and H = 0.5M1nm+0.25*M2nm+0.15*M3nm+0.1*M4nm，M1nmIndicating data proximity A in said database (6)nmAverage traffic flow, M, in the 1 st to 3 rd month period of2nmIndicating data proximity A in said database (6)nmAverage traffic flow, M, in the 4 th to 6 th month period of (1)3nmIndicating data proximity A in said database (6)nmAverage traffic flow, M, in the 7 th to 9 th month period of (1)4nmRepresenting adjacent A in said database (6)nmAverage traffic flow in the 10 th-12 th month period of (a);
d）0.5*M1nm=0.5*（∑b1nm/z），b1nmrepresenting adjacent A in said database (6)nmThe traffic flow in the 1 st-3 rd month period of (a), z represents the total number in the taken time period range;
0.25*M2nm=0.25*（∑b2nm/z），b2nmrepresenting adjacent A in said database (6)nmThe traffic flow in the 4 th-6 th month time period;
0.15*M3nm=0.15*（∑b3nm/z），b3nmrepresenting adjacent A in said database (6)nmThe traffic flow in the 7 th-9 th month time period;
0.1*M4nm=0.1*（∑b4nm/z），b4nmrepresenting adjacent A in said database (6)nmThe traffic flow in the 10 th-12 th month time period;
e) the road shape judging value is F = AnmWhen F is more than or equal to 0 and less than or equal to 0.7, the road condition is good and the road is smooth when the road passes through the same road section in the same time period on the same day, and the road condition alarming unit (16) is used for carrying out the first-stage early warning prompt of the road smoothness;
f) When F is more than 0.7 and less than or equal to 1, judging that vehicles passing through the road tend to be saturated and can normally run through the same road section in the same time period on the same day, and performing secondary early warning reminding through the road condition warning unit (16), wherein the speed of the vehicles is controlled by attention when the vehicles run on the road section, and the distance between the vehicles is kept to run;
g) when the distance is less than 1 and less than F, when the vehicle is predicted and judged to run to the road section, the traffic flow of the road section exceeds the amount of the road which can be borne by the road, the road is blocked, accidents are easy to occur, the road condition alarming unit (16) is used for carrying out early warning prompt, the road is blocked, accidents are easy to occur when the vehicle passes through the road section in a certain period of time, the route is reminded to be changed, meanwhile, the route of the surrounding equidirectional destination is judged through data, and other routes which have good road conditions and lead to the destination are given through the Beidou positioning service unit (5).
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| CN115273480B (en) * | 2022-09-28 | 2023-01-20 | 南京智慧交通信息股份有限公司 | Traffic early warning system and method based on big data analysis |
| CN116740974A (en) * | 2023-07-31 | 2023-09-12 | 武汉中交交通工程有限责任公司 | Highway road condition early warning system based on road network big data |
| CN116740974B (en) * | 2023-07-31 | 2024-03-22 | 武汉中交交通工程有限责任公司 | Highway road condition early warning system based on road network big data |
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