CN118781806A - Intelligent traffic information sharing method and system - Google Patents
Intelligent traffic information sharing method and system Download PDFInfo
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- CN118781806A CN118781806A CN202410910478.1A CN202410910478A CN118781806A CN 118781806 A CN118781806 A CN 118781806A CN 202410910478 A CN202410910478 A CN 202410910478A CN 118781806 A CN118781806 A CN 118781806A
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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
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G—PHYSICS
- 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
- G08G1/04—Detecting movement of traffic to be counted or controlled using optical or ultrasonic detectors
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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
- G08G1/042—Detecting movement of traffic to be counted or controlled using inductive or magnetic detectors
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
- Y02T10/00—Road transport of goods or passengers
- Y02T10/10—Internal combustion engine [ICE] based vehicles
- Y02T10/40—Engine management systems
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Abstract
本发明公开了一种智能化交通信息共享其方法及系统，涉及交通共享技术领域，本发明与之前的交通管理系统相比，解决了传统交通管理系统的数据实时性和准确性不足，且需要大量计算和存储资源，成本高昂，极易涉及用户隐私和数据安全，难以针对个体提供个性化交通服务的问题，通过边缘计算技术将数据处理能力推向网络边缘，结合分布式计算能力，在接近数据源的地方进行交通数据的局部处理和分析，减少传输带宽需求和中心服务器的负担，提高实时数据的处理速度和响应能力，且结合人工智能技术进行实时交通流预测和优化调整，改善交通流畅度和减少交通拥堵，同时，结合人工智能技术为用户提供个性化的交通信息推荐和服务，提升用户体验和服务精准度。
The present invention discloses an intelligent traffic information sharing method and system, and relates to the technical field of traffic sharing. Compared with previous traffic management systems, the present invention solves the problems that traditional traffic management systems lack real-time and accuracy of data, require a large amount of computing and storage resources, are costly, easily involve user privacy and data security, and are difficult to provide personalized traffic services for individuals. The data processing capability is pushed to the edge of the network through edge computing technology, and combined with distributed computing capabilities, local processing and analysis of traffic data are performed close to the data source, reducing the transmission bandwidth demand and the burden of the central server, improving the processing speed and response capability of real-time data, and combining artificial intelligence technology to perform real-time traffic flow prediction and optimization adjustment, improve traffic smoothness and reduce traffic congestion. At the same time, combined with artificial intelligence technology, personalized traffic information recommendations and services are provided to users, improving user experience and service accuracy.
Description
Technical Field
The invention relates to the technical field of traffic sharing, in particular to an intelligent traffic information sharing method and system.
Background
With the acceleration of the urban process, the urban traffic problem is increasingly prominent. Traffic jams, traffic confusion and frequent traffic accidents have become one of the important problems to be solved in modern city management. The traditional traffic management system mostly depends on fixed monitoring equipment and manual command and dispatch, has the problems of low real-time data acquisition efficiency, insufficient data processing capacity, information feedback lag and the like, and is difficult to meet the complex and changeable urban traffic management requirements.
With the development of society, the number of vehicles is increasing, and the problems of traffic accidents, congestion and the like on the road surface are also increasing. Therefore, an intelligent traffic system is generated, the system integrates various information through an information sharing platform, a more accurate auxiliary scheme is provided for the travel of users, more accurate data is provided for the decision of traffic management departments, and more convenient travel service is provided for travelers.
However, the conventional centralized traffic management system may face a problem of high data processing delay, resulting in insufficient real-time and accuracy of traffic information. And conventional centralized traffic management systems may require significant computational and memory resources at high cost. Large-scale data collection and processing may involve user privacy and data security issues. Conventional traffic management systems have difficulty providing personalized traffic information and optimizing route services for individual users or vehicles.
With the development of internet of things, artificial intelligence and edge computing, intelligent traffic systems are becoming an important means for solving urban traffic problems. The intelligent traffic system monitors traffic conditions in real time by comprehensively utilizing devices such as cameras, radar sensors, electromagnetic sensors and the like, analyzes traffic flow data, and achieves intelligent guidance and dynamic regulation and control of traffic flow. However, existing intelligent transportation systems still have many challenges in terms of continuous and stable operation and energy supply.
In order to solve the above problems, the present invention provides a method and a system for sharing intelligent traffic information.
Disclosure of Invention
The invention aims to provide an intelligent traffic information sharing method and system for solving the problems in the background technology:
Traditional centralized traffic management systems may face the problem of high data processing latency, resulting in insufficient real-time and accuracy of traffic information. And conventional centralized traffic management systems may require significant computational and memory resources at high cost. Large-scale data collection and processing may involve user privacy and data security issues. Conventional traffic management systems have difficulty providing personalized traffic information and optimizing route services for individual users or vehicles.
In order to achieve the above purpose, the present invention adopts the following technical scheme:
An intelligent traffic information sharing method comprises the following steps:
S1: deploying edge computing equipment at each key traffic node of the city, and collecting traffic data based on the edge computing equipment;
S2: deploying an artificial intelligent model on the edge equipment, and analyzing and predicting traffic data in real time;
S3: the processed traffic data is sent to an information sharing system for centralized processing and storage;
s4: optimizing the artificial intelligence model based on the data updated in real time;
s5: publishing the integrated real-time traffic information through different channels;
s6: and collecting user feedback and data feedback, and optimizing the traffic information sharing system according to the user feedback and the data feedback.
Preferably, the step of deploying the artificial intelligence model in S2 includes the following steps:
s2.1: taking a road section or an intersection in a traffic network as a node of the graph, and defining a connection relationship between the nodes;
S2.2: feature learning and updating are carried out on the features of each node by using a graph rolling network;
s2.3: establishing a mathematical model of the driver behavior based on BHAR models according to the historical data and the driver behavior mode;
S2.4: constructing a hierarchical structure model of the traffic system by combining the traffic network structure and the characteristics learned by the graph convolution neural network;
s2.5: based on the states of nodes and edges of the real-time traffic data update graph, generating prediction output related to traffic by combining the graph rolling network and learning results of BHAR models;
S2.6: parameters of the graph convolution network and BHAR model are optimized through real-time data feedback.
Preferably, the deploying artificial intelligence model in S2 is specifically as follows:
The nodes defined in the S2.1 include related traffic feature information, and a traffic network formed by N nodes is defined as a weighted directed graph r= (X, Y, Z), where X is a node set, i X i=n is the number of nodes, and Y represents an edge set in the graph; z= (Z ij)N×N represents an adaptive weighted adjacency matrix of node adjacencies;
Wherein, reLU represents an activation function; is a sharing operator; t represents the transpose of the vector; the & represent merge operation; r ij、rik are all attention coefficients; w represents a directed edge weight vector;
Using C (x, t) to represent the actual observed value of the traffic at time t for node x, its corresponding true value is characterized by a potentially random process B (x, t), both satisfying the following measurement error model:
C(x,t)＝AT(x,t)λ+B(x,t)+σ(x,t)
Wherein x=x 1,x2,Λ,xn represents the observation vectors of n monitoring nodes; t=1, 2, Λ, τ is the acquisition time; a (x, t) represents a d-dimensional observation vector; lambda is the regression coefficient; sigma (x, t) is the error term;
A first-order autoregressive model is established for the potential abnormal level B (x, t) of the current traffic:
B(x,t)＝δ·B(x,t-1)+ξ(x,t)
Wherein, xi (x, t) is a residual random term used for describing space-time random effect of potential abnormal level; ζ (x, t) are independent in time, spatially satisfy a gaussian process GP (0, Φ ξ), wherein, Representing the variance that does not change over time; η ξ denotes a covariance matrix related to space;
according to the traffic layering model, respectively corresponding to a vehicle level, a road network level and an overall traffic flow level;
And carrying out parameter estimation of the BHAR model based on the Gaussian mixture model, carrying out weighted fusion on the weighted directed graph and the output result of the BHAR model, and carrying out prediction on traffic conditions.
Preferably, in the step S2, real-time traffic optimization suggestions are also provided based on the analysis result;
Encryption techniques are used to secure the transfer and storage of data during the collection, processing and sharing of the data.
Preferably, the information sharing system in S3 further provides an API interface for the user and the third party.
Preferably, the channels in S5 include mobile applications, driving stations, dynamic signposts and LED displays, and social media platforms and websites.
Preferably, the intelligent traffic information sharing system comprises edge computing equipment arranged at a key traffic node, wherein the output end of the edge computing equipment is electrically connected with a data storage module and a data transceiver, the input end of the edge computing equipment is electrically connected with an electric appliance control module, a camera, a radar sensor and a geomagnetic sensor, the input end of the electric appliance control module is electrically connected with a cruising guarantee module, and the output end of the data transceiver is electrically connected with an area radio broadcasting module;
the data transceiver is in communication connection with a cloud data sharing module, the cloud data sharing module is opened with an API (application program interface) for external data access, the input end of the API is electrically connected with an app feedback module, and the app feedback module and the regional radio broadcasting module are both in communication connection with a vehicle-mounted terminal.
Preferably, the cloud data sharing module and a plurality of key traffic nodes are jointly accessed into a traffic management system for unified management.
Preferably, the endurance guarantee module comprises a control seat, wherein the inner wall of the control seat is rotatably provided with a lifting deflection rod group, the surface of the lifting deflection rod group is provided with folding fan blades, and the surface of the control seat is fixedly connected with a cabinet body;
the edge computing equipment and the electrical control module are arranged in the cabinet body, and a battery pack is arranged on the inner wall of the cabinet body;
the upper surface of the cabinet body is fixedly connected with a top guard, and the lifting deflection rod group penetrates through and rotates on the surface of the top guard;
The photovoltaic lifting support is characterized in that supporting frames are fixedly connected to two sides of the top protection, positioning frames penetrate through the surfaces of the two supporting frames, side covers are fixedly connected to the top ends of the two positioning frames together, a photovoltaic plate is fixedly connected to the inner wall of the side cover, a cleaning assembly is arranged on the upper surface of the photovoltaic plate, and the cleaning assembly is fixedly connected to the surface of the lifting deflection rod group;
the upper surface of the positioning frame is fixedly connected with a retainer, the top end of the retainer is fixedly connected with a speed reduction platform, the speed reduction platform is fixedly connected with the top end of the lifting deflection rod group, and the upper surface of the speed reduction platform is provided with a detection head;
The inner wall of the cabinet body is fixedly connected with an air pump, and the air pump is communicated with the inner wall of the control seat through a communicating pipe;
The tail end of the one side supporting frame is fixedly connected with a motor, the output end of the motor is fixedly connected with a driving wheel, and the surface of the driving wheel is in driving connection with the folding fan blade through a driving belt.
Preferably, the control seat comprises a lower seat body which is fixedly penetrated on the lower surface of the cabinet body, a bottom column is fixedly connected to the lower surface of the lower seat body, a protective cylinder is fixedly connected to the upper surface of the lower seat body, a retaining spring is fixedly connected to the lower surface of the inner wall of the lower seat body, a pressurizing piston which is hermetically sliding on the inner wall of the lower seat body is fixedly connected to the top end of the retaining spring, an airtight rotating piece is fixedly connected to the inner wall of the lower seat body, and the control seat further comprises a rotary electric connector which is fixedly arranged at the bottom end of the lifting deflection rod group;
The lifting deflection rod group comprises a spin column, the spin column rotates on the inner wall of the airtight rotating piece in a sealing way, the surface of the spin column rotates to penetrate through the upper surface of the top protection, a first airtight plug is axially sealed and slid on the inner wall of the spin column, a middle lifting cylinder is fixedly connected to the inner wall of the first airtight plug, a second airtight plug is axially sealed and slid on the inner wall of the middle lifting cylinder, a lifting rod is fixedly connected to the inner wall of the second airtight plug, the lifting rod penetrates through the surface of the photovoltaic panel, a lower guide sleeve is fixedly connected to the inner wall of the spin column, and an upper guide sleeve is fixedly connected to the top end of the middle lifting cylinder;
The arc-shaped side wall of the middle lifting cylinder is provided with a first arc-shaped groove, the arc-shaped side wall of the lifting rod is provided with a second arc-shaped groove, the inner wall of the lower guide sleeve is fixedly connected with a first guide block matched with the first arc-shaped groove to slide, and the inner wall of the upper guide sleeve is fixedly connected with a second guide block matched with the second arc-shaped groove to slide;
The folding fan blade comprises a rotating wheel fixedly connected to the top end of the spin column, the surface of the rotating wheel is in transmission fit with a transmission belt, the folding fan blade further comprises a middle supporting ring fixedly connected to the top end of the middle lifting cylinder, the folding fan blade further comprises a top supporting frame fixedly arranged on the top end of the lifting rod, two lower fan blades are jointly fixed on the opposite surfaces of the rotating wheel and the middle supporting ring, and two upper fan blades are jointly fixedly connected to the opposite surfaces of the middle supporting ring and the top supporting frame;
The arc-shaped side wall of the photovoltaic panel is fixedly connected with a side cover;
The cleaning assembly comprises an axle seat fixedly connected to the surface of the lifting rod, a plurality of brush wheels are rotatably connected to the surface of the axle seat, grinding wheels are fixedly connected to the other ends of the brush wheels, and the grinding wheels are attached to the inner wall of the side cover in a rolling manner;
the speed reducing platform comprises an inner gear ring seat fixed at the top end of the retainer, a rotary top cover is arranged on the arc-shaped side wall of the inner gear ring seat in a limiting sliding mode, a plurality of speed reducing gears are arranged on the lower surface of the rotary top cover in a rotating mode, the surfaces of the plurality of speed reducing gears are meshed with the inner wall of the inner gear ring seat jointly, a central gear is meshed with the surfaces of the plurality of speed reducing gears jointly, the central gear is fixedly connected to the top end of a lifting rod, and the lifting rod penetrates through the lower surface of the inner gear ring seat in a rotating mode.
Compared with the prior art, the invention provides a method and a system for sharing intelligent traffic information, which have the following beneficial effects:
According to the scheme, the edge computing equipment is set up through the key traffic nodes, the system detects traffic flow state, density and speed data through the edge computing equipment through the cameras, the radar sensor and the electromagnetic sensor, the data are encrypted and transmitted through the data transceiver after being stored, the data are transmitted to the cloud data sharing module, the data are integrated by combining the data of different key traffic nodes, the traffic management system and the API interface can index the data, the regional radio broadcasting module is used for broadcasting road information on traffic radio stations in a certain region, the mobile application program comprises navigation software for data support, the traffic flow can be guided by matching, comprehensive, accurate and comprehensive data support is provided for improving traffic, the whole system can operate under the comprehensive supervision of the traffic management system, and the reliability is high;
The invention pushes the data processing capability to the network edge through the edge computing technology, combines the distributed computing capability, so that the traffic data can be locally processed and analyzed at a place close to a data source, the transmission bandwidth requirement and the burden of a central server are reduced, and the processing speed and the response capability of the real-time data are greatly improved. The low delay and high throughput capability provided by edge calculation are utilized, and the artificial intelligence technology is combined to conduct real-time traffic flow prediction, optimization and adjustment, so that the traffic fluency is improved, and the traffic jam is reduced; meanwhile, historical data and behaviors of the user are analyzed through an artificial intelligence technology, personalized traffic information recommendation and service are provided for the user, and user experience and service accuracy are improved. The intelligent traffic information sharing method utilizes the edge calculation and artificial intelligence technology, can improve the efficiency and instantaneity of traffic management, improves the traveling experience of urban residents, and provides technical support and solution for the construction of future intelligent cities;
in order to ensure a continuous and reliable operation mode, the continuous voyage ensuring module is introduced to supply standby energy to the whole body through the built-in battery pack, when the commercial power is disconnected, the continuous operation of the commercial power pack is met, meanwhile, after the commercial power is disconnected, the air pump is started, high-pressure air is injected into the control seat through the communicating pipe, under the action of air pressure, the lifting deflection rod group starts to stretch, so that the folding fan blade of the continuous voyage ensuring module deflects to a certain extent along with the lifting deflection rod group in the unfolding process, further, the folding fan blade of the continuous voyage ensuring module is twisted after being unfolded to form a rotating structure capable of acting along with wind force, and when the air flow acts, the driving belt of the continuous voyage ensuring module drives the motor to rotate and stores the sent electric energy into the battery pack, and the continuous and stable operation can be realized after the commercial power is disconnected due to the action of unreliability factors during normal use;
Simultaneously when using, when folding fan blade rotates, take the clearance subassembly to rotate at the surface of photovoltaic board, make it clean the photovoltaic board, and then carry out the electric power storage through the photovoltaic board to the group battery when realizing inserting external power source, and the electricity is mended again in a period of discharging, when the outage, can combine the cooperation of photoelectricity and wind-powered electricity generation, satisfy the needs of electric power duration, when the outage simultaneously, the monitored control system of traffic is all paralyzed, and the detection head of slow rotation carries out annular all around under the wind-force effect this moment, realizes the continuous operation of low energy consumption.
Drawings
FIG. 1 is a flow chart of the method mentioned in example 1 of the present invention;
FIG. 2 is a diagram showing the predicted results of the different algorithms according to embodiment 1 of the present invention;
FIG. 3 is a block diagram of a system of the present invention;
FIG. 4 is a schematic diagram of a key traffic node of the present invention in a three-dimensional configuration;
FIG. 5 is a schematic view of a three-dimensional cross-sectional structure of a cabinet according to the present invention;
FIG. 6 is a schematic cross-sectional view of the present invention with the bottom pillar removed;
FIG. 7 is a schematic cross-sectional view of a detail hunting head according to the present invention;
FIG. 8 is a schematic view of another partial position section of the present invention;
FIG. 9 is a schematic diagram of an explosion structure of a folding fan blade according to the present invention;
FIG. 10 is a schematic view of a cross-section of a deceleration platform according to the present invention;
fig. 11 is a schematic diagram of a state structure of the invention when the utility power is supplied.
In the figure: 1. a cabinet body; 2. roof protection; 3. a control base; 31. a lower base; 32. a protective barrel; 33. a holding spring; 34. a pressurizing piston; 35. an airtight rotating member; 36. a rotary joint; 4. lifting and lowering the partial rod group; 41. a spin column; 42. a middle lifting cylinder; 43. a lifting rod; 44. a first gas-tight plug; 45. a second airtight plug; 46. a lower guide sleeve; 47. an upper guide sleeve; 5. folding the fan blade; 51. a rotating wheel; 52. a middle support ring; 53. a top bracket; 54. lower fan blades; 55. the upper fan blade; 6. a deceleration platform; 61. an inner gear ring seat; 62. rotating the top cover; 63. a sun gear; 64. a reduction gear; 65. a mounting table; 7. cleaning the assembly; 71. a shaft seat; 72. a brush wheel; 73. grinding wheel; 8. an edge computing device; 9. an electrical control module; 10. a battery pack; 11. an air pump; 12. a communicating pipe; 13. a drive belt; 14. a driving wheel; 15. a motor; 16. a supporting frame; 17. a photovoltaic panel; 18. a side cover; 19. a first guide block; 20. a second guide block; 21. a probe; 22. a retainer; 23. a bottom post; 24. a positioning frame; 25. a first arc-shaped groove; 26. a second arcuate slot.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments.
The invention pushes the data processing capability to the network edge through the edge computing technology, combines the distributed computing capability, so that the traffic data can be locally processed and analyzed at a place close to a data source, the transmission bandwidth requirement and the burden of a central server are reduced, and the processing speed and the response capability of the real-time data are greatly improved. The low delay and high throughput capability provided by edge calculation are utilized, and the artificial intelligence technology is combined to conduct real-time traffic flow prediction, optimization and adjustment, so that the traffic fluency is improved, and the traffic jam is reduced; meanwhile, historical data and behaviors of the user are analyzed through an artificial intelligence technology, personalized traffic information recommendation and service are provided for the user, and user experience and service accuracy are improved. The intelligent traffic information sharing method can improve the efficiency and real-time performance of traffic management by utilizing the edge calculation and artificial intelligence technology, improve the traveling experience of urban residents, and provide technical support and solution for the construction of future intelligent cities. Specifically, the following are included.
Example 1:
Referring to fig. 1-2, the intelligent traffic information sharing method of the present invention includes the following steps:
S1: deploying edge computing equipment at each key traffic node of the city, and collecting traffic data based on the edge computing equipment; the method comprises the following steps:
Edge devices, such as intelligent traffic lights, roadside sensors, etc., are deployed in areas of heavy traffic for collecting real-time traffic data. Preliminary data processing and analysis, such as real-time vehicle detection, traffic monitoring, etc., is performed at the edge device.
S2: deploying an artificial intelligent model on the edge equipment, and analyzing and predicting traffic data in real time; the method comprises the following steps:
the collected traffic data is analyzed and predicted in real time using machine learning algorithms and deep learning models. For example, predicting traffic congestion, accident probability, etc. The method comprises the following steps:
Road segments or intersections in the traffic network are used as nodes of the graph, and each node can comprise relevant characteristic information such as road segment length, road type, historical average speed and the like. Connection relationships between nodes, i.e. connection or influence relationships between road segments, are defined. This may construct edges of the graph based on road connection relationships, proximity relationships of intersections, and so on.
Defining a traffic network formed by N nodes as a weighted directed graph R= (X, Y, Z), wherein X is a node set, X is the number of nodes, and Y represents an edge set in the graph; z= (Z ij)N×N represents an adaptive weighted adjacency matrix of node adjacencies;
Wherein, reLU represents an activation function; is a sharing operator; t represents the transpose of the vector; the & represent merge operation; r ij、rik are all attention coefficients; w represents a directed edge weight vector;
The characteristics of each node (road segment or intersection) may be learned and updated by the GCN. The GCN can consider characteristics of the node itself and information of surrounding nodes, thereby more accurately representing the state and influence of the node. A graph level characterization of the entire traffic network can be obtained through the GCN, which characterizes the dynamics and status of the overall traffic system.
The BHAR model is used to model the driver behavior, such as predicting the driver's path selection, speed adjustment, etc. And carrying out hierarchical modeling in combination with the traffic network structure and the characteristics learned by the GCN, and carrying out prediction and analysis from the whole system to different layers of a specific road section.
Using C (x, t) to represent the actual observed value of the traffic at time t for node x, its corresponding true value is characterized by a potentially random process B (x, t), both satisfying the following measurement error model:
C(x,t)＝AT(x,t)λ+B(x,t)+σ(x,t)
Wherein x=x 1,x2,Λ,xn represents the observation vectors of n monitoring nodes; t=1, 2, Λ, τ is the acquisition time; a (x, t) represents a d-dimensional observation vector; lambda is the regression coefficient; sigma (x, t) is the error term;
A first-order autoregressive model is established for the potential abnormal level B (x, t) of the current traffic:
B(x,t)＝δ·B(x,t-1)+ξ(x,t)
Wherein, xi (x, t) is a residual random term used for describing space-time random effect of potential abnormal level; ζ (x, t) are independent in time, spatially satisfy a gaussian process GP (0, Φ ξ), wherein, Representing the variance that does not change over time; η ξ denotes a covariance matrix related to space; and according to the traffic layering model, respectively corresponding to the vehicle level, the road network level and the overall traffic flow level, and carrying out BHAR model parameter estimation based on the Gaussian mixture model.
The states of nodes and edges of the graph, such as real-time vehicle speed, traffic flow, weather conditions, etc., are updated based on real-time traffic data. And combining the learning results of the GCN model and the BHAR model, carrying out weighted fusion on the weighted directed graph and the output result of the BHAR model, and generating prediction output related to traffic jam, accident probability and the like. These outputs may reflect the expected traffic conditions and potential risks at different road segments and intersections.
Parameters of the GCN model and the BHAR model are optimized through real-time data feedback, so that prediction accuracy and practicality are improved. And the effect of the integrated model is evaluated regularly, including indexes such as prediction accuracy, response time and the like, so that the effectiveness of the model in actual traffic management is ensured.
By combining BHAR models and graph rolling networks, the structure and dynamic characteristics of the traffic system can be fully utilized, so that the accuracy and instantaneity of traffic jam and accident probability prediction are improved.
Finally, performing error comparison analysis on the simple BHAR model prediction data, the simple graph convolution model prediction data, the traditional regression algorithm prediction data, the prediction data of the embodiment and the original data based on two measurement indexes of the root mean square error RMSE and the average absolute error MAE, wherein the simple BHAR model prediction data is taken as an algorithm 1, the simple graph convolution model prediction data is taken as an algorithm 2, the traditional regression algorithm is taken as an algorithm 3, and specific reference can be made to a table 1:
TABLE 1 comparison of the prediction effect of different models
It can be seen from the table that the RMSE and MAE of the model proposed in this embodiment are lower than the algorithm 1, the algorithm 2 and the algorithm 3, and referring to fig. 2, it can be seen that the model predicted value of this embodiment is closest to the actual value, so that the model of this embodiment has good prediction performance.
Real-time traffic optimization suggestions, such as time adjustment of traffic lights, route recommendation, etc., are provided based on the analysis results.
S3: the processed traffic data is sent to an information sharing system for centralized processing and storage; the method comprises the following steps:
And sending the data collected by the edge computing equipment to a cloud platform for centralized processing and storage. And simultaneously, an open API interface is provided for third-party applications and service developers to access real-time traffic information and analysis results.
S4: optimizing the artificial intelligence model based on the data updated in real time; the method comprises the following steps:
the artificial intelligence model is continually updated and optimized to accommodate changes in traffic conditions and new data patterns.
S5: publishing the integrated real-time traffic information through different channels; the method comprises the following steps:
The processed real-time traffic information is released through various channels, including:
mobile application: and providing real-time road conditions and navigation suggestions for the user.
Dynamic road sign and LED display screen: real-time traffic conditions and early warning information are displayed at major intersections or on highways.
Social media platform and website: real-time updates are posted through social media and official websites.
S6: and collecting user feedback and data feedback, and optimizing the traffic information sharing system according to the user feedback and the data feedback. The method comprises the following steps:
User feedback and data feedback are collected for adjusting and improving the performance and accuracy of the traffic information processing system. The public is encouraged to participate in the sharing and reporting of traffic information, such as submitting traffic events or road condition updates through mobile applications. Real-time traffic information update is provided for users to help them make more intelligent and effective travel decisions.
In the process of data collection, processing and sharing, relevant data security and privacy protection regulations are ensured to be met. And meanwhile, the encryption technology is used for protecting the transmission and storage safety of data, so that the personal information of the user is ensured not to be revealed and abused.
The intelligent traffic information sharing system comprises edge computing equipment 8 arranged at a key traffic node, wherein the output end of the edge computing equipment 8 is electrically connected with a data storage module and a data transceiver, the input end of the edge computing equipment 8 is electrically connected with an electric appliance control module, a camera, a radar sensor and a geomagnetic sensor, the input end of the electric appliance control module is electrically connected with a endurance guarantee module, and the output end of the data transceiver is electrically connected with a regional radio broadcasting module;
The data transceiver is in communication connection with a cloud data sharing module, the cloud data sharing module is provided with an API (application program interface) for external data access, the input end of the API is electrically connected with an app feedback module, and the app feedback module and the regional radio broadcasting module are both in communication connection with a vehicle-mounted terminal.
According to the scheme, the edge computing device 8 is set up through the key traffic nodes, the system detects traffic flow state, density and speed data through the edge computing device 8 through the camera, the radar sensor and the electromagnetic sensor, encryption transmission is carried out through the data transceiver after data storage, the data are transmitted to the cloud data sharing module, the data are integrated through combining with the data of different key traffic nodes, the traffic management system and the API interface can carry out data index, the regional radio broadcasting module is used for broadcasting road information on the traffic radio stations in a certain region, the mobile application program comprises navigation software for carrying out data support, the matching can be used for guiding traffic flow, comprehensive, accurate and comprehensive data support is provided for improving traffic, the whole system can operate under the comprehensive supervision of the traffic management system, and the reliability is high.
Preferably, the cloud data sharing module and a plurality of key traffic nodes are jointly accessed into a traffic management system for unified management.
Preferably, the endurance guarantee module comprises a control seat 3, wherein the inner wall of the control seat 3 is rotatably provided with a lifting deflection rod group 4, the surface of the lifting deflection rod group 4 is provided with a folding fan blade 5, and the surface of the control seat 3 is fixedly connected with a cabinet body 1;
The edge computing equipment 8 and the electrical control module 9 are arranged in the cabinet body 1, and a battery pack 10 is arranged on the inner wall of the cabinet body 1;
the upper surface of the cabinet body 1 is fixedly connected with a top guard 2, and the lifting deflection rod group 4 penetrates through and rotates on the surface of the top guard 2;
The two sides of the top guard 2 are fixedly connected with supporting frames 16, the surfaces of the two supporting frames 16 penetrate through and slide with positioning frames 24, the top ends of the two positioning frames 24 are fixedly connected with side covers 18 together, the inner walls of the side covers 18 are fixedly connected with photovoltaic panels 17, cleaning assemblies 7 are arranged on the upper surfaces of the photovoltaic panels 17, and the cleaning assemblies 7 are fixedly connected to the surfaces of the lifting deflection rod groups 4;
the upper surface of the positioning frame 24 is fixedly connected with a retainer 22, the top end of the retainer 22 is fixedly connected with a speed reduction platform 6, the speed reduction platform 6 is fixedly connected with the top end of the lifting deflection rod group 4, and the upper surface of the speed reduction platform 6 is provided with a detection head 21;
The inner wall of the cabinet body 1 is fixedly connected with an air pump 11, and the air pump 11 is communicated with the inner wall of the control seat 3 through a communicating pipe 12;
The tail end of a side support 16 is fixedly connected with a motor 15, the output end of the motor 15 is fixedly connected with a driving wheel 14, and the surface of the driving wheel 14 is in driving connection with the folding fan blade 5 through a driving belt 13.
The control seat 3 comprises a lower seat body 31 which is fixedly penetrated on the lower surface of the cabinet body 1, a bottom post 23 is fixedly connected to the lower surface of the lower seat body 31, a protective cylinder 32 is fixedly connected to the upper surface of the lower seat body 31, a retaining spring 33 is fixedly connected to the lower surface of the inner wall of the lower seat body 31, a pressurizing piston 34 which is hermetically sliding on the inner wall of the lower seat body 31 is fixedly connected to the top end of the retaining spring 33, an airtight rotating part 35 is fixedly connected to the inner wall of the lower seat body 31, and the control seat 3 further comprises a rotary connector 36 which is fixedly arranged at the bottom end of the lifting deflection rod group 4;
The rotary electric connector 36 can be fixed at the bottom end of the spin column 41, and can achieve electric connection and matching in a rotary state when the probe 21 rotates along with the rotary electric connector, which is a well-known technology at present, and will not be described in detail.
The lifting partial rod group 4 comprises a spin column 41, the spin column 41 rotates on the inner wall of the airtight rotating piece 35 in a sealing way, the surface of the spin column 41 rotates to penetrate through the upper surface of the protecting top 2, a first airtight plug 44 is axially sealed and slid on the inner wall of the spin column 41, a middle lifting cylinder 42 is fixedly connected to the inner wall of the first airtight plug 44, a second airtight plug 45 is axially sealed and slid on the inner wall of the middle lifting cylinder 42, a lifting rod 43 is fixedly connected to the inner wall of the second airtight plug 45, the lifting rod 43 penetrates through the surface of the photovoltaic panel 17, a lower guide sleeve 46 is fixedly connected to the inner wall of the spin column 41, and an upper guide sleeve 47 is fixedly connected to the top end of the middle lifting cylinder 42;
The arc side wall of the middle lifting cylinder 42 is provided with a first arc groove 25, the arc side wall of the lifting rod 43 is provided with a second arc groove 26, the inner wall of the lower guide sleeve 46 is fixedly connected with a first guide block 19 matched with the first arc groove 25 to slide, and the inner wall of the upper guide sleeve 47 is fixedly connected with a second guide block 20 matched with the second arc groove 26 to slide;
The folding fan blade 5 comprises a rotating wheel 51 fixedly connected to the top end of the spin column 41, the surface of the rotating wheel 51 is in transmission fit with the transmission belt 13, the folding fan blade 5 further comprises a middle supporting ring 52 fixedly connected to the top end of the middle lifting cylinder 42, the folding fan blade 5 further comprises a top supporting frame 1653 fixed to the top end of the lifting rod 43, two lower fan blades 54 are jointly fixed to the opposite surfaces of the rotating wheel 51 and the middle supporting ring 52, and two upper fan blades 55 are jointly fixedly connected to the opposite surfaces of the middle supporting ring 52 and the top supporting frame 1653;
the arc-shaped side wall of the photovoltaic panel 17 is fixedly connected with a side cover 18;
the cleaning assembly 7 comprises an axle seat 71 fixedly connected to the surface of the lifting rod 43, a plurality of brush wheels 72 are rotatably connected to the surface of the axle seat 71, grinding wheels 73 are fixedly connected to the other ends of the brush wheels 72, and the grinding wheels 73 are attached to the inner wall of the side cover 18 in a rolling manner;
The speed reduction platform 6 comprises an inner gear ring seat 61 fixed at the top end of the retainer 22, a rotary top cover 62 is limited and slides on the arc-shaped side wall of the inner gear ring seat 61, a plurality of speed reduction gears 64 are rotatably arranged on the lower surface of the rotary top cover 62, the surfaces of the plurality of speed reduction gears 64 are jointly meshed with the inner wall of the inner gear ring seat 61, the surfaces of the plurality of speed reduction gears 64 are jointly meshed with a central gear 63, the central gear 63 is fixedly connected with the top end of a lifting rod 43, and the lifting rod 43 penetrates through the lower surface of the inner gear ring seat 61.
In order to ensure a continuous and reliable operation mode, the whole battery pack 10 is supplied with standby energy, when the commercial power is disconnected, the battery pack 10 is automatically switched to meet continuous operation in a period of time, meanwhile, after the power is off, the air pump 11 is started, high-pressure air is injected into the control seat 3 through the communicating pipe 12, high pressure is formed in the spin column 41 of the lifting deflection rod group 4 under the action of air pressure, the first airtight plug 44 slides with the middle lifting cylinder 42 under the action of air pressure until the first airtight plug 44 is limited by the lower guide sleeve 46, meanwhile, the first guide block 19 on the inner wall of the lower guide sleeve 46 slides in the first arc-shaped groove 25 on the side wall of the middle lifting cylinder 42, so that small-angle spin starts when the middle lifting cylinder 42 is lifted, and similarly, the lifting rod 43 is upwards moved by the second airtight plug 45 under the action of air pressure until the second airtight plug 45 contacts the upper guide sleeve 47, and starts spinning under the limitation of the second guide block 20 and the second arc-shaped groove 26.
It should be clear that the middle lifting cylinder 42 rotates based on the spin column 41, the rotation action of the spin column 41 does not affect the height change of the middle lifting cylinder 42, meanwhile, the middle lifting cylinder 42 can lift and twist with the middle supporting ring 52 when in rotation, so that the two lower fan blades 54 are subjected to the torsion action of the middle supporting ring 52 and the rotating wheel 51 in the unfolding process to form a spiral structure, the rotation of the lifting rod 43 is further rotated based on the rotation amplitude of the middle lifting cylinder 42, the top supporting frame 1653 rotates with the rotation of the middle supporting ring 52 by a larger amplitude, the torsion and unfolding of the two upper fan blades 55 are completed, the upper fan blades 55 and the lower fan blades 54 are sectionally twisted to form a complete fan blade structure, the folding can be realized when not in use, the placement protection under the severe road environment is satisfied, the use is required, the stability for a long time is greatly ensured, after the airflow action, the rotating wheel 51 rotates with the motor 15 through the driving belt 13, the generated electric energy is stored in the battery pack 10, and the normal power failure resistance can be realized when the battery pack is in a normal power failure mode, and the normal power failure resistance can be realized when the electric power failure is continuously realized;
The photovoltaic panel 17 can be cleaned, the battery pack is stored through the photovoltaic panel 17 when an external power supply is connected, discharging is carried out for a period of time to supplement electricity again, when power is off, the cooperation of photoelectricity and wind power can be combined, the requirement of power endurance is met, meanwhile, when power is off, a traffic monitoring system is paralyzed, at the moment, the detection heads 21 which slowly rotate under the action of wind power detect the periphery in a ring shape, and continuous operation with low energy consumption is realized.
Under the condition of supplying commercial power, the motor 15 can be electrified to actively regulate and control the rotation angle of the detecting head 21, and compared with the energy-saving use mode of self-rotation snapshot under the action of wind power, the energy-saving use mode of self-rotation snapshot can realize active self-adaptive regulation and control.
Meanwhile, when the folding fan blade 5 rotates, the cleaning assembly 7 is driven to rotate on the surface of the photovoltaic panel 17, the grinding wheel 73 is attached to the inner wall of the side cover 18, and the brush wheel 72 is driven to rotate, so that the photovoltaic panel 17 is cleaned in the rotating and spinning process, cleaning is carried out after long-time standing, and the optimal power generation state under the power failure state is guaranteed.
The probe 21 integrates a camera for video recording and snapshot, a radar sensor for speed measurement, and a geomagnetic sensor for measuring vehicle type and flow.
Further, the probe 21 is disposed on the surface of the reduction platform 6, and when in use, the sun gear 63 is driven to rotate by the rotation of the lifting shaft, the sun gear 63 rotates and revolves through a plurality of reduction gears 64 on the engagement surface, the plurality of reduction gears 64 revolve under the engagement action of the inner ring gear 61 and slide along the side wall of the inner ring gear 61 with the rotary top cover 62, so that the rotary top cover 62 can rotate under the mounting table 65, and the mounting table 65 can complete the mounting and fixing of the probe 21.
According to the scheme, the edge computing equipment 8 is arranged at the key traffic node, and the cameras, radar sensors and electromagnetic sensors in the equipment are utilized to detect traffic flow state, density, speed and other data in real time. After the data are stored locally, the data are transmitted in an encrypted mode through a data transceiver and are transmitted to a cloud data sharing module. Through integration and analysis of cloud data, traffic management systems and API interfaces can efficiently index data and provide data support for regional radio broadcasting and mobile applications (e.g., navigation software). The comprehensive system can effectively guide traffic flow, improve traffic conditions, provide comprehensive and accurate data support, and operate under the comprehensive supervision of traffic management systems, and has high reliability.
In order to ensure the continuous and reliable operation of the system, a cruising guarantee module is introduced. The module provides standby energy through the built-in battery pack 10, and when the commercial power is disconnected, the system can be automatically switched to the battery pack 10, so that continuous operation for a period of time is met. Simultaneously, after the outage, the air pump 11 is started, the lifting deflection rod group 4 is driven by high-pressure air, the folding fan blades 5 are unfolded and form a wind power generation structure, and then the motor 15 is driven by the driving belt 13 to rotate, so that electric energy is stored in the battery pack 10, and continuous and stable operation is realized.
In addition, in the scheme, the folding fan blade 5 can drive the cleaning assembly 7 to clean the photovoltaic panel 17 in the rotation process, so that the high-efficiency power generation capacity of the photovoltaic panel 17 is ensured. Thus, the electric power can be stored for the battery pack through the commercial power and the photovoltaic panel 17 in normal use, and the electric power endurance requirement can be met by means of the combination of photoelectricity and wind power in outage. The detector head 21 slowly rotates under the action of wind power, so that low-energy-consumption continuous monitoring of the annular area is realized, and the traffic monitoring system can still operate under the influence of power failure.
The scheme not only can improve traffic management efficiency and traffic conditions through real-time data detection and intelligent analysis, but also has continuous operation capability when the mains supply is disconnected, and ensures the stability and reliability of the system. By combining wind power and photoelectricity, the energy source supplying capability of the system is further improved, and continuous and efficient operation of the system in various complex environments is ensured. Meanwhile, the self-cleaning function of the system effectively improves the use efficiency of the photovoltaic module, and comprehensively achieves the aims of reducing maintenance cost, improving system reliability and optimizing traffic management.
In conclusion, the invention applies the edge calculation and artificial intelligence technology to the traffic information sharing system innovatively, thereby not only realizing the high efficiency and real-time data processing, but also improving the intelligent level of traffic management, obviously improving the urban traffic condition and the traveling experience of users, combining with specific implementation equipment to stably guarantee, and integrally meeting the requirements of practical application.
The present invention is not limited to the above-mentioned embodiments, and any person skilled in the art, based on the technical solution of the present invention and the inventive concept thereof, can be replaced or changed within the scope of the present invention.
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