CN116453360A - Traffic management system based on big data - Google Patents
Traffic management system based on big data Download PDFInfo
- Publication number
- CN116453360A CN116453360A CN202310507819.6A CN202310507819A CN116453360A CN 116453360 A CN116453360 A CN 116453360A CN 202310507819 A CN202310507819 A CN 202310507819A CN 116453360 A CN116453360 A CN 116453360A
- Authority
- CN
- China
- Prior art keywords
- traffic
- congestion
- information
- navigation
- management system
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 208000027744 congestion Diseases 0.000 claims description 91
- 238000000034 method Methods 0.000 claims description 15
- 230000000903 blocking effect Effects 0.000 claims description 13
- 238000004806 packaging method and process Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 description 7
- 206010039203 Road traffic accident Diseases 0.000 description 5
- 238000001514 detection method Methods 0.000 description 5
- 238000004590 computer program Methods 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000010977 unit operation Methods 0.000 description 3
- 230000002457 bidirectional effect Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 238000005192 partition Methods 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/091—Traffic information broadcasting
-
- 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
- G08G1/0133—Traffic data processing for classifying traffic situation
-
- 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
- G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
- G08G1/0145—Measuring and analyzing of parameters relative to traffic conditions for specific applications for active traffic flow control
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Chemical & Material Sciences (AREA)
- Analytical Chemistry (AREA)
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Navigation (AREA)
Abstract
The invention provides a traffic management system based on big data, comprising: the traffic information acquisition module is used for acquiring past traffic information; the traffic information analysis module is used for analyzing traffic information and determining future traffic jam conditions; the navigation information pushing module is used for establishing navigation diversion suggestions based on future traffic jam conditions. According to the invention, the navigation information pushing module is adopted, so that the navigation advice can be sent based on the future traffic jam condition, and the navigation user can change the navigation route in advance, thereby reducing the road jam condition.
Description
Technical Field
The invention relates to a management system, in particular to a traffic management system based on big data.
Background
As economies develop, vehicles have moved from a once luxury to a vast number of households. The vehicle can effectively enlarge the radius of the movement of the person, and has obvious promotion for work, leisure and travel. However, along with the popularization of vehicles, serious loads are caused on urban streets, particularly during business hours, the vehicles are jammed on the roads in a large amount, so that the street is jammed, while the existing traffic management system mainly focuses on the management of traffic lights and the allocation of traffic police, and the traffic police lack to early warning and dredge the jam in advance through navigation.
Disclosure of Invention
The invention provides a traffic management system based on big data, which is used for sending navigation advice before congestion and guiding automobiles to shunt in advance.
The invention provides a traffic management system based on big data, comprising:
the traffic information acquisition module is used for acquiring past traffic information;
the traffic information analysis module is used for analyzing traffic information and determining future traffic jam conditions;
the navigation information pushing module is used for establishing navigation diversion suggestions based on future traffic jam conditions.
Further, the traffic information analysis module includes:
the early warning unit is used for analyzing traffic information and determining congestion risk, and if the congestion risk meets a first threshold value, the traffic jam condition can be determined to occur in the future.
Still further, the traffic information analysis module includes a congestion model analysis unit, where the congestion model analysis unit is configured to collect past traffic information and build a congestion model based on the past traffic information.
Still further, the first threshold is that the matching degree of the current traffic information and the congestion model is higher than 80%.
Further, the past traffic information at least comprises weather information, traffic congestion positions, traffic congestion time and traffic flow.
Still further, the traffic information collection module includes a traffic information collection process:
acquiring a current traffic jam node;
acquiring traffic conditions around the blocking node;
and packaging the position of the blocked node and the surrounding traffic condition, marking a time stamp, and storing.
Still further, the navigation information pushing module comprises a navigation unit, wherein the navigation unit is used for acquiring the blocking position in the future traffic blocking situation, collecting the alternative roads around the blocking position, and setting the navigation priority of the alternative roads to be higher than the road where the blocking position is located.
Still further, the navigation information pushing module further includes an information reminding unit, and if the congestion risk meets the second threshold, the information reminding unit sends congestion reminding information to the user passing through the congestion position of the navigation route.
Still further, the second threshold is that the matching degree of the current traffic information and the congestion model is higher than 70%.
Still further, the over-living traffic information further includes a congestion cause, and if the congestion risk satisfies a second threshold, the information reminding unit sends congestion reminding information to the user passing through the congestion position of the navigation route, where the congestion reminding information includes the congestion cause.
Compared with the prior art, the navigation information pushing module is adopted, so that navigation advice can be sent based on future traffic jam conditions, a navigation user can change a navigation route in advance, and the road jam condition is further reduced.
Drawings
FIG. 1 is a first threshold-based analysis process according to an embodiment of the present invention;
FIG. 2 is a second threshold based analysis process according to an embodiment of the present invention.
Description of the embodiments
In order that those skilled in the art will better understand the present invention, a technical solution of the embodiments of the present invention will be clearly and completely described below, and it is apparent that the described embodiments are only some embodiments of the present invention, not all embodiments.
A first aspect of an embodiment of the present invention provides a traffic management system based on big data, including:
the traffic information acquisition module is used for acquiring past traffic information;
the traffic information acquisition module can monitor and acquire road conditions based on navigation software or other software so as to acquire road congestion information in real time;
the traffic information analysis module is used for analyzing traffic information and determining future traffic jam conditions;
the traffic information analysis module establishes a congestion model through past traffic information and analyzes the congestion model and current traffic information in real time to determine the possibility of congestion;
the navigation information pushing module is used for establishing navigation diversion suggestions based on future traffic jam conditions.
The navigation information pushing module can be communicated with navigation software and sends related navigation diversion suggestions to users in the congestion area when congestion possibly occurs in the future.
According to the embodiment of the invention, the navigation information pushing module is adopted, so that the navigation advice can be sent based on the future traffic jam condition, and a navigation user can change the navigation route in advance, so that the road jam condition is reduced.
Optionally, the traffic information analysis module includes:
the early warning unit is used for analyzing traffic information and determining congestion risk, and if the congestion risk meets a first threshold value, the traffic jam condition can be determined to occur in the future.
The early warning unit can conduct congestion analysis based on traffic information to determine the risk of congestion; by matching the current traffic environment with the congestion model, if the matching degree is too high, the first threshold is met, the risk of congestion is high, and the early warning unit recognizes that traffic congestion occurs in the future.
According to the embodiment of the invention, the early warning unit is arranged to judge the future congestion occurrence risk degree, the early warning unit is used for analyzing the congestion risk based on the first threshold value, if the matching degree of the current road environment and the congestion model is too high, the situation that congestion occurs easily is indicated, the traffic information analysis module can identify that the future traffic congestion has larger risk based on the situation, and the navigation information pushing module establishes navigation diversion suggestions.
Particularly, the traffic information analysis module comprises a congestion model analysis unit, wherein the congestion model analysis unit is used for collecting past traffic information and establishing a congestion model based on the past traffic information.
In particular, the past traffic information at least comprises weather information, traffic congestion positions, traffic congestion time and traffic flow.
In particular, the congestion model analysis unit operation process includes:
s301, collecting traffic flow change conditions of traffic vehicles with the radius of 5-10km by taking the traffic jam position as the center;
s302, a congestion model analysis unit collects the traffic flow change condition in the process from the beginning to the end of the traffic congestion time;
s303, establishing a model of weather information, traffic flow and traffic jam conditions, thereby determining the influence of the weather information and traffic flow change on the traffic jam, and establishing a jam model.
A second aspect of an embodiment of the present invention provides a traffic management system based on big data, including:
the traffic information acquisition module is used for acquiring past traffic information;
the traffic information analysis module is used for analyzing traffic information and determining future traffic jam conditions;
the navigation information pushing module is used for establishing navigation diversion suggestions based on future traffic jam conditions.
The traffic information analysis module includes:
the early warning unit is used for analyzing traffic information and determining congestion risk, and if the congestion risk meets a first threshold value, the traffic jam condition can be determined to occur in the future.
The traffic information analysis module comprises a congestion model analysis unit, wherein the congestion model analysis unit is used for collecting past traffic information and establishing a congestion model based on the past traffic information.
In particular, the past traffic information at least comprises weather information, traffic congestion positions, traffic congestion time and traffic flow.
In particular, the congestion model analysis unit operation process includes:
s301, collecting traffic flow change conditions of traffic vehicles with the radius of 5-10km by taking the traffic jam position as the center;
s302, a congestion model analysis unit collects the traffic flow change condition in the process from the beginning to the end of the traffic congestion time;
s303, establishing a model of weather information, traffic flow and traffic jam conditions, thereby determining the influence of the weather information and traffic flow change on the traffic jam, and establishing a jam model.
Particularly, S301, taking a traffic jam position as a center, and collecting traffic flow change conditions with the radius of 5-10km specifically comprises:
s3011, collecting traffic jam areas in the past traffic information and guiding traffic flows of the traffic jam areas;
s3012, if the traffic flow guiding of the traffic congestion area is a single lane, taking the point of the traffic congestion area at the front end of the traffic flow guiding as a traffic congestion position;
the front end of the traffic flow guide specifically refers to a position located at the front section of the traffic flow direction along the traffic flow direction;
s3013, if the traffic flow of the traffic jam area is guided to be a bidirectional lane, identifying whether the traffic jam area has a turn-around area, if not, splitting the bidirectional lane of the traffic jam area, and identifying the traffic jam position according to the single-lane condition;
if the traffic congestion area has a turn-around area, acquiring the congestion condition of a lane corresponding to the turn-around area, and if the turn-around area is positioned at one end of the traffic congestion area of the lane and the turn-around area is positioned at the front end of the traffic congestion area in the traffic flow direction, setting the turn-around area as the traffic congestion area;
s3014, if the traffic flow of the traffic congestion area is guided to be a multi-directional lane, identifying the congestion route situation of the traffic congestion area, and if the congestion route situation of the traffic congestion area is in a cross shape and each lane in the multi-directional lane has congestion situation, identifying the intersection at the intersection as a traffic congestion position;
if the congestion route condition of the traffic congestion area is in a cross shape, but at least one lane in the multi-directional lanes does not have congestion condition, acquiring the traffic flow direction of the multi-directional lanes, identifying the traffic flow direction of the lane with congestion condition, extracting the traffic flow direction of the lane with the traffic flow direction being a departure intersection, and taking the point of the traffic congestion area of the lane at the front end of the traffic flow direction as the traffic congestion position;
if the traffic lane at the departure road opening has no congestion condition, identifying the traffic direction of the traffic lane with the congestion condition, and taking the point of the traffic congestion area of the traffic lane at the front end of the traffic congestion area as the traffic congestion position;
the third aspect of the embodiment of the invention provides a traffic management system based on big data, and the traffic management system further comprises that the first threshold value is that the matching degree of the current traffic information and the congestion model is higher than 80% on the basis of the second aspect.
As shown in fig. 1, the specific analysis procedure is as follows:
s101, collecting weather information at the current moment;
s102, determining the relation between the traffic flow and traffic jam in a congestion model based on the weather information;
s103, collecting current traffic flow, and if the current traffic flow exceeds 80% of the traffic flow when traffic jam occurs and is still continuously increased in unit time, determining that a first threshold is met;
if the number of times per unit time is not increased, the first threshold is determined not to be satisfied.
The unit time is specifically 5-10min, the change of the vehicle flow rate at the beginning and the end of the unit time is matched, and if the vehicle flow rate is increased, the vehicle flow rate in the unit time is determined to be continuously increased.
In particular, the traffic information acquisition module includes a traffic information acquisition process:
acquiring a current traffic jam node;
acquiring traffic conditions and weather conditions around the blocked node;
and packaging the position of the blocked node and the surrounding traffic condition, marking a time stamp, and storing.
Particularly, the navigation information pushing module comprises a navigation unit, wherein the navigation unit is used for acquiring the blocking position in the future traffic blocking situation, collecting the alternative roads around the blocking position, and setting the navigation priority of the alternative roads to be higher than that of the road where the blocking position is located.
And when the first threshold value is met, the navigation unit sends a navigation scheme for replacing the road to the user.
In particular, the navigation unit operation process includes:
s401, establishing a navigation route according to the requirements of a user;
s402, identifying each traffic congestion position of a navigation route path;
s403, acquiring traffic flow information of each current traffic congestion position, and if the traffic flow information of the traffic congestion position meets a first threshold; acquiring a plurality of front traffic nodes and a plurality of rear traffic nodes of the navigation route at the traffic jam position along the navigation route;
wherein the traffic node specifically refers to the junction of other roads and the current lane,
s404, establishing a navigation route for the former one or more traffic nodes and the latter one or more traffic nodes, and acquiring navigation route information;
s405, repeating the steps S402-S404 until the traffic flow information of each traffic jam position of the newly obtained navigation route is lower than a first threshold value, deriving the newly obtained navigation route, setting the newly obtained navigation route as the navigation of the alternative road, and setting the navigation priority of the alternative road to be higher than that of the road where the jam position is located.
According to the embodiment of the invention, the navigation unit is arranged, and the navigation unit is used for collecting the alternative roads around the blocking position, so that a user can quickly obtain the navigation scheme of the alternative roads when the blocking risk is high, the user has various driving schemes to select, navigation diversion is realized in advance, and the traffic flow of the blocking position is reduced, so that the congestion risk is relieved or avoided.
Particularly, the navigation information pushing module further comprises an information reminding unit, and if the congestion risk meets a second threshold, the information reminding unit sends congestion reminding information to a user passing through the congestion position of the navigation route.
The information reminding unit is used for sending blockage reminding information to the user which has navigation software and is navigating through the blockage position or the user frequently passes through the blockage position before and after the moment.
According to the embodiment of the invention, the jam reminding is realized in advance by setting the second threshold value, so that a user is reminded of road jam attention, and further, the driving attention can be improved or the travel plan can be changed in advance.
In particular, the second threshold is that the matching degree of the current traffic information and the congestion model is higher than 70%.
As shown in fig. 2, the specific analysis procedure is as follows:
s201, collecting weather information at the current moment;
s202, determining the relation between the traffic flow and traffic jam in a congestion model based on the weather information;
s203, collecting current traffic flow, and if the current traffic flow exceeds 70% of the traffic flow when traffic jam occurs and is still continuously increased in unit time, determining that a second threshold is met;
if the number of times per unit time is not increased, the second threshold is determined not to be satisfied.
The unit time is specifically 5-10min, the change of the vehicle flow rate at the beginning and the end of the unit time is matched, and if the vehicle flow rate is increased, the vehicle flow rate in the unit time is determined to be continuously increased.
According to the embodiment of the invention, the second threshold value is set, so that the blockage reminding can be performed in advance, and a user can conveniently prepare alternative navigation schemes in advance.
Particularly, the over-living traffic information further comprises a congestion reason, and if the congestion risk meets a second threshold, the information reminding unit sends congestion reminding information to a user passing through a congestion position of the navigation route, and the congestion reminding information comprises the congestion reason.
Most of the congestion is caused by traffic accidents, and some of the traffic accidents are caused by the conditions of merging of traffic roads and the like, so that the traffic flow is high, the probability of occurrence of the traffic accidents is increased, and traffic jam is caused.
By collecting the congestion reasons, when the traffic flow is large but the congestion does not occur, the embodiment of the invention leads the congestion reasons (such as the fact that vehicles are merged on the right side of a road and rear-end collision accidents are easy to occur, please pay attention to the like) to be easily caused to the area in advance, so that the user can pay attention to the congestion risk, improve the driving attention, and avoid traffic accidents than the case of occurrence of traffic accidents.
Corresponding to the above embodiment, the embodiment of the present application further provides an external storage medium detection device for storing and implementing a traffic management system, including:
a memory for storing a computer program;
and the processor is used for realizing the steps of the external storage medium detection method when executing the computer program.
The external storage medium detection device may include: a processor, a memory, a communication interface, and a communication bus. The processor, the memory and the communication interface all complete the communication with each other through the communication bus.
In the embodiments of the present application, the processor may be a central processing unit (Central Processing Unit, CPU), an application specific integrated circuit, a digital signal processor, a field programmable gate array, or other programmable logic device, etc.
The processor may call a program stored in the memory, and in particular, the processor may perform operations in an embodiment of the external storage medium detection method.
The memory is used for storing one or more programs, the programs may include program codes, the program codes include computer operation instructions, in the embodiment of the application, at least the programs for realizing the following functions are stored in the memory:
in the starting process, searching a first storage medium externally connected with the BMC in the equipment catalog;
if the file system is found and at least one partition exists in the first storage medium, creating the file system in the first storage medium, and mounting the file system of the first storage medium into the file system of the BMC;
creating a target file in a file system of the first storage medium according to the received file generation instruction, and writing a test completion character string in the target file;
if the writing is successful, it is determined that the first storage medium is successfully initialized.
In one possible implementation, the memory may include a storage program area and a storage data area, where the storage program area may store an operating system, and applications required for at least one function (e.g., file creation function, data read/write function), etc.; the store data area may store data created during use, such as initialization data, etc.
In addition, the memory may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device or other volatile solid state storage device.
The communication interface may be an interface of a communication module for connecting with other devices or systems.
Of course, it should be noted that the structure is not limited to the external storage medium detecting device in the embodiment of the present application, and the external storage medium detecting device may include more or fewer components or may combine some components in practical applications.
Corresponding to the above method embodiments, the present application further provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps of the external storage medium detection method are implemented.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, so that the same or similar parts between the embodiments are referred to each other.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative elements and steps are described above generally in terms of functionality in order to clearly illustrate the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. The software modules may be disposed in Random Access Memory (RAM), memory, read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.
Finally, it should be noted that the above-mentioned embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above-mentioned embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the specific embodiments of the present invention after reading the present specification, and these modifications and variations do not depart from the scope of the invention as claimed in the pending claims.
Claims (10)
1. A big data based traffic management system, the traffic management system comprising:
the traffic information acquisition module is used for acquiring past traffic information;
the traffic information analysis module is used for analyzing traffic information and determining future traffic jam conditions;
the navigation information pushing module is used for establishing navigation diversion suggestions based on future traffic jam conditions.
2. The big data based traffic management system of claim 1, wherein the traffic information analysis module comprises:
the early warning unit is used for analyzing traffic information and determining congestion risk, and if the congestion risk meets a first threshold value, the traffic jam condition can be determined to occur in the future.
3. The traffic management system according to claim 2, wherein the traffic information analysis module includes a congestion model analysis unit for collecting past traffic information and building a congestion model based on the past traffic information.
4. The traffic management system according to claim 3, wherein the first threshold is a degree of matching of current traffic information with a congestion model higher than 80%.
5. The traffic management system according to claim 4, wherein the past traffic information includes at least weather information, traffic congestion location, traffic congestion time, traffic flow.
6. The traffic management system according to claim 5, wherein the traffic information collection module includes a traffic information collection process:
acquiring a current traffic jam node;
acquiring traffic conditions around the blocking node;
and packaging the position of the blocked node and the surrounding traffic condition, marking a time stamp, and storing.
7. The traffic management system according to claim 6, wherein the navigation information pushing module includes a navigation unit, the navigation unit is configured to obtain a congestion location in a future traffic congestion situation, collect alternative roads around the congestion location, and set a navigation priority of the alternative roads higher than a road where the congestion location is located.
8. The traffic management system according to claim 7, wherein the navigation information pushing module further comprises an information reminding unit, and if the congestion risk meets the second threshold, the information reminding unit sends congestion reminding information to the user passing through the congestion position on the route.
9. The big data based traffic management system of claim 8, wherein the second threshold is a degree of matching of current traffic information to the congestion model higher than 70%.
10. The traffic management system according to claim 8, wherein the overlived traffic information further includes a congestion cause, and the information reminding unit sends congestion reminding information to a user passing through the congestion location on the route if the congestion risk satisfies a second threshold, the congestion reminding information including the congestion cause.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310507819.6A CN116453360B (en) | 2023-05-08 | 2023-05-08 | Traffic management system based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310507819.6A CN116453360B (en) | 2023-05-08 | 2023-05-08 | Traffic management system based on big data |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116453360A true CN116453360A (en) | 2023-07-18 |
| CN116453360B CN116453360B (en) | 2024-07-16 |
Family
ID=87135674
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310507819.6A Active CN116453360B (en) | 2023-05-08 | 2023-05-08 | Traffic management system based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116453360B (en) |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070135990A1 (en) * | 2005-12-08 | 2007-06-14 | Seymour Shafer B | Navigation route information for traffic management |
| JP2007256020A (en) * | 2006-03-22 | 2007-10-04 | Clarion Co Ltd | Navigation device, navigation method, and navigation program |
| CN106781592A (en) * | 2017-01-04 | 2017-05-31 | 成都四方伟业软件股份有限公司 | A kind of traffic navigation system and method based on big data |
| CN110580807A (en) * | 2019-09-06 | 2019-12-17 | 杭州思源信息技术股份有限公司 | Intelligent traffic management system capable of relieving traffic jam |
| CN111882867A (en) * | 2020-07-03 | 2020-11-03 | 多伦科技股份有限公司 | City wisdom traffic early warning system based on thing networking |
-
2023
- 2023-05-08 CN CN202310507819.6A patent/CN116453360B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070135990A1 (en) * | 2005-12-08 | 2007-06-14 | Seymour Shafer B | Navigation route information for traffic management |
| JP2007256020A (en) * | 2006-03-22 | 2007-10-04 | Clarion Co Ltd | Navigation device, navigation method, and navigation program |
| CN106781592A (en) * | 2017-01-04 | 2017-05-31 | 成都四方伟业软件股份有限公司 | A kind of traffic navigation system and method based on big data |
| CN110580807A (en) * | 2019-09-06 | 2019-12-17 | 杭州思源信息技术股份有限公司 | Intelligent traffic management system capable of relieving traffic jam |
| CN111882867A (en) * | 2020-07-03 | 2020-11-03 | 多伦科技股份有限公司 | City wisdom traffic early warning system based on thing networking |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116453360B (en) | 2024-07-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109949611B (en) | Lane changing method and device for unmanned vehicle and storage medium | |
| EP3460409A1 (en) | Route searching device, route searching system, and computer program | |
| CN113335276A (en) | Obstacle trajectory prediction method, obstacle trajectory prediction device, electronic device, and storage medium | |
| CN110222131A (en) | The beginning and the end information extracting method and device | |
| CN114078327B (en) | Road congestion state detection method, device, equipment and storage medium | |
| US10354456B2 (en) | Apparatus and method for determining toll gate section | |
| CN105026890B (en) | Vehicle location display control unit and vehicle position determination method | |
| CN109782776B (en) | Lane selection method and device for unmanned vehicle and storage medium | |
| JP2011214914A (en) | Front environment recognition device, and vehicle guiding system including the same | |
| CN113870564B (en) | Traffic jam classification method and system for closed road section, electronic device and storage medium | |
| CN109859505B (en) | Early warning processing method, device, server and medium for high-speed station | |
| CN111341105A (en) | Vehicle speed guiding method, device, equipment and medium based on adjacent intersection association degree | |
| CN110648526B (en) | Road condition early warning method and device based on key intersection | |
| CN108592927B (en) | Destination prediction method and system based on historical travel route | |
| CN111160480A (en) | Underground parking lot entrance and exit excavation method and device and electronic equipment | |
| CN111915893A (en) | Road bottleneck point identification method and device, electronic equipment and storage medium | |
| CN115273512A (en) | Anti-collision auxiliary method, device, equipment and medium for automatically driving vehicle | |
| CN116453360B (en) | Traffic management system based on big data | |
| CN113978481A (en) | Lane abnormity reminding method and device, storage medium and terminal | |
| CN115116154A (en) | Method and system for guiding the passage of vehicles at a highway toll station | |
| CN115257771B (en) | Intersection identification method, electronic equipment and storage medium | |
| CN116009046A (en) | Vehicle positioning method and device | |
| CN110497906A (en) | Control method for vehicle, device, equipment and medium | |
| CN113514073A (en) | Internet of vehicles intelligent navigation obstacle crossing method and device and electronic equipment | |
| CN114596704A (en) | Traffic event processing method, device, equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20240624 Address after: 233500 South Huayuan Commercial Complex, 2nd Floor, Intersection of Wangyue Road and Bacai Road, Mengcheng County, Bozhou City, Anhui Province Applicant after: Mengcheng County Mengdie Public Utility Construction Investment Co.,Ltd. Country or region after: China Address before: Room 917, 1933-3 Huaguan Road, Tianhe District, Guangzhou City, Guangdong Province, 510000 (for office use only) Applicant before: Guangdong Junsi Information Technology Co.,Ltd. Country or region before: China |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |