Traffic information transmission method and system based on dual-mode communication network

Abstract

The invention discloses a traffic information transmission method and system based on a dual-mode communication network, and the method comprises the steps: collecting the position information of a vehicle and a road facility through a radio frequency identification technology, and obtaining an original signal; edge-cloud cooperative computing is executed, and filtering processing and positioning computing are carried out on the original signals; constructing a dynamic dual-mode communication network based on vehicle-to-vehicle communication and vehicle-to-road communication technologies, and performing global traffic situation prediction and path planning through a positioning calculation result; and providing an information transmission service for the target user terminal. According to the invention, through integration of RFID accurate positioning, vehicle-vehicle and vehicle-road cooperative communication and a multi-source data fusion technology, accurate positioning is realized and time delay deviation is reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent traffic communication, and in particular relates to a traffic information transmission method and system based on a dual-mode communication network. Background Art

[0002] Intelligent transportation systems are an essential component of smart city development. They can significantly improve urban traffic management services, reduce congestion and accidents, and inject vitality into the development of related technology industries. In practice, they must be given full attention. In conjunction with the city's medium- and long-term development plans, the feasibility of IoT sensing technologies, dynamic routing guidance technologies, and traffic flow prediction technologies must be analyzed. The development of intelligent transportation infrastructure must be accelerated, and professional management personnel must be deployed to support the construction and development of intelligent transportation systems.

[0003] With the rapid development of connected vehicle technology, traditional traffic information collection methods face challenges such as low positioning accuracy, high communication latency, and difficulty fusing multi-source data. For example, single-source radio frequency identification (RFID) technology is susceptible to environmental interference, resulting in significant positioning errors. Traditional vehicle-to-vehicle and vehicle-to-road communications lack dynamic routing mechanisms, making data loss more likely when network topology changes occur. Isolated system architectures also lead to time delays between traffic information services (such as route guidance and signal control) and actual road conditions. Summary of the Invention

[0004] The main purpose of the present invention is to overcome the shortcomings and deficiencies of the existing technology and provide a traffic information transmission method and system based on a dual-mode communication network, which achieves precise positioning and reduces delay deviation by integrating RFID precise positioning, vehicle-to-vehicle / vehicle-road collaborative communication and multi-source data fusion technology.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions: In a first aspect, the present invention provides a method for transmitting traffic information based on a dual-mode communication network, comprising the following steps: Collect the location information of vehicles and road facilities through radio frequency identification technology to obtain the original signal; Perform edge-cloud collaborative computing to filter and calculate the original signal; Build a dynamic dual-mode communication network based on vehicle-to-vehicle communication and vehicle-to-road communication technologies, and use positioning calculation results to perform global traffic situation prediction and route planning; Provide information transmission services to target user terminals.

[0006] As a preferred technical solution, radio frequency identification technology is implemented using an RFID intelligent system. The RFID intelligent system includes a vehicle-mounted mobile tag unit, a multi-channel reader array, a reader processing center, a switch, and a distributed antenna. The vehicle-mounted mobile tag unit includes a microcontroller that stores a unique identity identification code and a positioning information storage module.

[0007] As a preferred technical solution, the method of collecting the location information of vehicles and road facilities by radio frequency identification technology includes: When a vehicle enters the sensing area, the multi-channel reader array transmits a specific frequency to activate the on-board mobile tag unit. The on-board mobile tag unit obtains an induced current through electromagnetic induction and uses the induced current to activate the microcontroller of the on-board mobile tag unit. The microcontroller establishes an encrypted communication link with the multi-channel reader array and executes the identity authentication protocol. After authentication, the vehicle-mounted mobile tag unit will transmit the stored information to the multi-channel reader array using backscatter modulation technology. The reader processing center will encrypt the information and transmit it to the command center through the switch to obtain positioning information.

[0008] As a preferred technical solution, the method of collecting the location information of vehicles and road facilities through radio frequency identification technology includes: a multi-channel reader array collects RSSI signals from a fixed reference tag network through electromagnetic backscattering; the fixed reference tag network is deployed in parking spaces, road intersections and traffic signs, and pre-stores location coordinates.

[0009] As a preferred technical solution, the execution of edge-cloud collaborative computing, filtering processing and positioning calculation of the original signal includes: Edge layer processing: Kalman filtering is performed on the original signal to eliminate multipath interference; Cloud platform processing: Use fingerprint positioning algorithm or weighted centroid algorithm to solve coordinates, restore vehicle trajectory, and detect and record abnormal behavior; transmit the processed data to the vehicle positioning function part, and integrate multi-source positioning information through the data fusion module to generate the final positioning result.

[0010] As a preferred technical solution, the vehicle-to-vehicle communication includes: Build a self-organizing mobile vehicle network, where each vehicle acts as a network node with routing and forwarding capabilities; Carrier sense multiple access / collision avoidance mechanism is used to achieve communication link management; Supports real-time exchange of dynamic driving parameters between vehicles, including speed, position and acceleration.

[0011] As a preferred technical solution, the vehicle-road communication technology implementation includes: Deploy a dedicated short-range communication module on the roadside unit to establish a two-way communication link with the vehicle terminal; Use time division multiple access protocol to manage communication time slots between roadside equipment and multiple vehicles; Supports the transmission of traffic signal phase information, variable information board content and event warning data.

[0012] As a preferred technical solution, it also includes a multimedia video monitoring system and a vehicle-mounted integrated navigation module; the vehicle-mounted integrated navigation module integrates an inertial measurement unit and a satellite positioning receiver; Traffic flow image data is collected through a multimedia video surveillance system, and computer vision algorithms are used to identify vehicle types and detect traffic incidents. The video analysis results are then temporally and spatially correlated with radio frequency positioning data. Through the on-board integrated navigation module, an adaptive Kalman filter is designed to realize multi-sensor data fusion, and a road digital map matching model is constructed to correct positioning drift errors.

[0013] As a preferred technical solution, the provision of information transmission services to target user terminals further includes: Push dynamic route guidance instructions and estimated arrival time to vehicle terminals; Provide lane-by-lane traffic flow statistics to road operating units; Pre-allocate dedicated communication time slots and signal priority control instructions to emergency vehicles.

[0014] In a second aspect, the present invention provides a traffic information transmission system based on a dual-mode communication network, which is applied to a traffic information transmission method based on a dual-mode communication network, comprising: an information collection layer, an edge computing layer, a cloud computing platform, and a mobile terminal application layer; The information collection layer collects all RSSI signals through a distributed reader array; the information collection layer connects to the edge computing layer, cloud computing platform, and mobile terminal application layer through wireless or wired mode and transmits data; The edge computing layer is deployed on the roadside unit to perform real-time data processing, including data filtering and positioning calculation; Cloud computing platform to perform global traffic situation prediction and route planning; The mobile terminal application layer supports human-computer interactive display of multimodal traffic information.

[0015] Compared with the prior art, the present invention has the following advantages and beneficial effects: (1) The present invention reduces the error by 60% compared with the traditional RFID system through a dual-mode communication network, that is, the combination of vehicle-to-vehicle communication and vehicle-to-road communication. At the same time, the dual-mode communication network provides a dynamic routing mechanism, which can effectively solve the problem of data packet loss caused by changes in network topology, thereby significantly improving the data packet delivery rate.

[0016] (2) The present invention combines edge computing with cloud computing. On the one hand, edge computing enables local decision-making to be autonomous and reduces data transmission delays. At the same time, it ensures that when data is processed locally, some sensitive information can be desensitized or encrypted locally, reducing the risk of data being stolen or tampered with during network transmission. On the other hand, the cloud computing platform can realize global traffic situation prediction and path planning, providing users with comprehensive and detailed information transmission services to meet users' diverse needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 Flowchart of a traffic information transmission method based on a dual-mode communication network according to an embodiment of the present invention; Figure 2 This is a schematic diagram of a vehicle-to-vehicle communication technology according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the vehicle-road communication technology according to an embodiment of the present invention; Figure 4 Schematic diagram of a traffic information transmission system based on a dual-mode communication network according to an embodiment of the present invention. DETAILED DESCRIPTION

[0019] In order to enable those skilled in the art to better understand the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0020] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it constitute an independent or alternative embodiment that is mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0021] See also Figure 1 This embodiment provides a traffic information transmission method based on a dual-mode communication network, comprising the following steps: S1. Collect the location information of vehicles and road facilities through radio frequency identification technology to obtain the original signal.

[0022] In this embodiment, radio frequency identification technology is implemented using an RFID intelligent system. The RFID intelligent system is provided with a vehicle-mounted mobile tag unit, a multi-channel reader array, a reader processing center, a switch, and a distributed antenna. The vehicle-mounted mobile tag unit includes a microcontroller, which stores a unique identity identification code and a positioning information storage module.

[0023] When a vehicle enters the sensing area, the multi-channel reader array transmits a specific frequency to activate the on-board mobile tag unit. The on-board mobile tag unit obtains an induced current through electromagnetic induction and uses the induced current to activate the microcontroller of the on-board mobile tag unit. The microcontroller establishes an encrypted communication link with the multi-channel reader array and executes the identity authentication protocol.

[0024] Specifically, the activated microcontroller establishes an encrypted communication link with the multi-channel reader array and executes a triple authentication protocol: 1. Challenge-response verification: The reader generates a random number as a challenge value, and the tag uses a pre-stored key to perform encryption operations and returns a response value; 2. Anti-replay attack: A dynamic encryption seed is generated for each session to ensure that the communication content cannot be tampered with; 3. Black and white list verification: The reader compares the tag ID with the background database in real time to filter out illegal or cancelled tags.

[0025] After authentication, the vehicle-mounted mobile tag unit and the fixed reference tag network will transmit the stored information to the multi-channel reader array using backscatter modulation technology. The reader processing center will encrypt the information and transmit it to the command center through a switch to obtain positioning information.

[0026] It's worth noting that the multi-channel reader array uses four channels and supports MIMO technology. Scattering modulation technology modulates stored information onto the carrier transmitted by the multi-channel reader array. The multi-channel reader array uses the AES-256 algorithm to encrypt and encapsulate the original data, which is then transmitted to the edge computing node via the RS-485 / TCP / IP interface through the switch. The stored information includes the vehicle's VIN, owner's identity, and payment account.

[0027] S2. Execute edge-cloud collaborative computing to filter and calculate the original signal.

[0028] This embodiment implements edge-cloud collaborative processing. First, for edge layer processing, the roadside unit (RSU) is equipped with an NVIDIA Jetson AGX Xavier edge computing module. Kalman filtering is performed on the raw signal to eliminate multipath interference. Second, real-time data from the edge node and the cloud platform is synchronized via a Kafka message queue. Coordinates are calculated using a weighted centroid algorithm or a fingerprint positioning algorithm to restore the vehicle trajectory and detect and record abnormal behavior. This processed data is then transmitted to the vehicle positioning function, where a data fusion module integrates multi-source positioning information to generate the final positioning result. Path planning utilizes the Dijkstra algorithm to generate a set of candidate paths (up to three) and annotate them with congestion probabilities. The fingerprint positioning algorithm loads a pre-built RSSI-to-position mapping table and calculates initial coordinates using a K-nearest neighbor (K=5) algorithm. The weighted centroid algorithm integrates data from adjacent readers, achieving a final positioning error of ≤0.8m.

[0029] S3. Build a dynamic dual-mode communication network based on vehicle-to-vehicle communication and vehicle-to-road communication technologies, and use positioning calculation results to perform global traffic situation prediction and path planning.

[0030] In this embodiment, vehicle-to-vehicle (V2V) communication uses the IEEE 802.11p protocol, with a communication range of 300 meters and support for periodic safety message (BSM) broadcasts. The dynamic routing protocol, based on an improvement to AODV, incorporates the vehicle velocity vector as a routing metric to reduce the probability of link disconnection. The roadside units (RSUs) deploy DSRC modules operating in the 5.9 GHz frequency band and supporting a 10 Mbps data rate. Communication time slots are allocated using a TDMA mechanism, with dedicated time slots reserved for emergency vehicles (20 ms, with the highest priority). These two communication modes form a dual-mode communication network.

[0031] Through the dual-mode communication network, global traffic situation prediction and path planning are performed based on positioning calculation results, including the following steps: S31. Build a self-organizing mobile vehicle network, where each vehicle acts as a network node and has routing and forwarding capabilities. S32, using carrier sense multiple access / collision avoidance mechanism to achieve communication link management; S33, support real-time exchange of dynamic driving parameters between vehicles, including speed, position and acceleration; S34. Deploy a dedicated short-range communication module on the roadside unit to establish a two-way communication link with the vehicle terminal; S35, using a time division multiple access protocol to manage communication time slots between roadside equipment and multiple vehicles; S36, supports the transmission of traffic signal phase information, variable information board content and event warning data.

[0032] In addition, this embodiment utilizes a multimedia video surveillance system and an on-board integrated navigation module; the module integrates an inertial measurement unit (IMU) and a satellite positioning receiver. The multimedia video surveillance system collects road traffic flow image data, employs computer vision algorithms for vehicle type identification and traffic event detection, and verifies the spatiotemporal correlation between the video analysis results and radio frequency positioning data. The module also incorporates an adaptive Kalman filter for multi-sensor data fusion and a road digital map matching model to correct positioning drift errors. The combination of this multimedia video surveillance system and the module further improves vehicle positioning accuracy and the effectiveness of abnormal behavior identification.

[0033] S4. Provide information transmission service to the target user terminal.

[0034] In this embodiment, dynamic route guidance instructions and estimated arrival times are pushed to vehicle terminals, lane-by-lane traffic flow statistics are provided to road operating units, and dedicated communication time slots and signal priority control instructions are pre-allocated to emergency vehicles.

[0035] In typical scenarios, this embodiment can achieve the functions of underground parking lot management and highway vehicle-road coordination. For example, in the underground parking lot management scenario, (1) reverse car search: the user enters the license plate number through the mobile phone APP, and the system retrieves the most recent RFID positioning record (accuracy ±1m); (2) parking space guidance: the LED indicator changes color according to the number of remaining parking spaces (green > 80%, yellow 50%-80%, red < 50%).

[0036] It is also implemented in the highway vehicle-road collaboration scenario: (1) Abnormal weather warning: RSU detects visibility through millimeter-wave radar, and triggers a speed limit instruction when it is ≤100m, and sends it to the user terminal through V2I; (2) Platoon driving: The leading vehicle broadcasts acceleration instructions through V2V, and the following vehicles use PID control to maintain the distance between vehicles (target distance 15m, error ±0.5m).

[0037] It should be noted that, for the sake of convenience, the aforementioned method embodiments are all expressed as a series of action combinations, but those skilled in the art should know that the present invention is not limited to the described order of actions, because according to the present invention, certain steps can be performed in other orders or simultaneously.

[0038] Based on the same principles as the dual-mode communication network-based traffic information transmission method described in the aforementioned embodiment, the present invention also provides a dual-mode communication network-based traffic information transmission system, which can be used to implement the aforementioned dual-mode communication network-based traffic information transmission method. For ease of illustration, the schematic diagram of the embodiment of the dual-mode communication network-based traffic information transmission system only shows the parts relevant to the embodiment of the present invention. Those skilled in the art will understand that the illustrated structure does not constitute a limitation of the device, and the device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0039] See also Figure 4 In another embodiment of the present application, a traffic information transmission system 10 based on a dual-mode communication network is provided, the system comprising: The information collection layer 11 collects all RSSI signals through a distributed reader array; the information collection layer 11 connects to the edge computing layer 12, the cloud computing platform 13, and the mobile terminal application layer 14 via wireless or wired mode and transmits data; Edge computing layer 12, deployed on roadside units to perform real-time data processing, including data filtering and positioning calculations; Cloud computing platform 13, performs global traffic situation prediction and route planning; The mobile terminal application layer 14 supports human-computer interactive display of multimodal traffic information.

[0040] It should be noted that the traffic information transmission system based on the dual-mode communication network of the present invention corresponds one-to-one to the traffic information transmission method based on the dual-mode communication network of the present invention. The technical features and beneficial effects described in the above-mentioned embodiment of the traffic information transmission method based on the dual-mode communication network are applicable to the embodiment of the traffic information transmission method based on the dual-mode communication network. For specific contents, please refer to the description in the embodiment of the method of the present invention. No further details will be given here. This is hereby declared.

[0041] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0042] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be considered as equivalent replacement methods and are included in the scope of protection of the present invention.

Claims

1. A traffic information transmission method based on a dual-mode communication network, characterized in that: The steps include: Collect the location information of vehicles and road facilities through radio frequency identification technology to obtain the original signal; Perform edge-cloud collaborative computing to filter and calculate the original signal; Build a dynamic dual-mode communication network based on vehicle-to-vehicle communication and vehicle-to-road communication technologies, and use positioning calculation results to perform global traffic situation prediction and route planning; Provide information transmission services to target user terminals.

2. The traffic information transmission method based on the dual-mode communication network according to claim 1, characterized in that: Radio frequency identification technology is implemented using an RFID intelligent system, which includes a vehicle-mounted mobile tag unit, a multi-channel reader array, a reader processing center, a switch, and a distributed antenna. The vehicle-mounted mobile tag unit includes a microcontroller that stores a unique identity code and a positioning information storage module.

3. The traffic information transmission method based on the dual-mode communication network according to claim 2 is characterized in that: The location information of vehicles and road facilities collected by radio frequency identification technology includes: When a vehicle enters the sensing area, the multi-channel reader array transmits a specific frequency to activate the on-board mobile tag unit. The on-board mobile tag unit obtains an induced current through electromagnetic induction and uses the induced current to activate the microcontroller of the on-board mobile tag unit. The microcontroller establishes an encrypted communication link with the multi-channel reader array and executes the identity authentication protocol. After authentication, the vehicle-mounted mobile tag unit will transmit the stored information to the multi-channel reader array using backscatter modulation technology. The reader processing center will encrypt the information and transmit it to the command center through the switch to obtain positioning information.

4. The traffic information transmission method based on a dual-mode communication network according to claim 2, characterized in that: The method of collecting the location information of vehicles and road facilities through radio frequency identification technology includes: a multi-channel reader array collects RSSI signals from a fixed reference tag network through electromagnetic backscattering; the fixed reference tag network is deployed in parking spaces, road intersections and traffic signs, and pre-stores location coordinates.

5. The traffic information transmission method based on a dual-mode communication network according to claim 1, characterized in that: The execution of edge-cloud collaborative computing, filtering processing and positioning calculation of the original signal, includes: Edge layer processing: Kalman filtering is performed on the original signal to eliminate multipath interference; Cloud platform processing: Use fingerprint positioning algorithm or weighted centroid algorithm to solve coordinates, restore vehicle trajectory, and detect and record abnormal behavior; transmit the processed data to the vehicle positioning function part, and integrate multi-source positioning information through the data fusion module to generate the final positioning result.

6. The traffic information transmission method based on a dual-mode communication network according to claim 1, characterized in that: The vehicle-to-vehicle communication includes: Build a self-organizing mobile vehicle network, where each vehicle acts as a network node with routing and forwarding capabilities; Carrier sense multiple access / collision avoidance mechanism is used to achieve communication link management; Supports real-time exchange of dynamic driving parameters between vehicles, including speed, position and acceleration.

7. The traffic information transmission method based on a dual-mode communication network according to claim 1, characterized in that: The vehicle-road communication technology implementation includes: Deploy a dedicated short-range communication module on the roadside unit to establish a two-way communication link with the vehicle terminal; Use time division multiple access protocol to manage communication time slots between roadside equipment and multiple vehicles; Supports the transmission of traffic signal phase information, variable information board content and event warning data.

8. The traffic information transmission method based on a dual-mode communication network according to claim 1, characterized in that: It also includes a multimedia video monitoring system and a vehicle-mounted integrated navigation module; the vehicle-mounted integrated navigation module integrates an inertial measurement unit and a satellite positioning receiver; Traffic flow image data is collected through a multimedia video surveillance system, and computer vision algorithms are used to identify vehicle types and detect traffic incidents. The video analysis results are then temporally and spatially correlated with radio frequency positioning data. Through the on-board integrated navigation module, an adaptive Kalman filter is designed to realize multi-sensor data fusion, and a road digital map matching model is constructed to correct positioning drift errors.

9. The traffic information transmission method based on a dual-mode communication network according to claim 1, characterized in that: The providing of information transmission service to the target user terminal further includes: Push dynamic route guidance instructions and estimated arrival time to vehicle terminals; Provide lane-by-lane traffic flow statistics to road operating units; Pre-allocate dedicated communication time slots and signal priority control instructions to emergency vehicles.

10. A traffic information transmission system based on a dual-mode communication network, characterized in that: A traffic information transmission method based on a dual-mode communication network applicable to any one of claims 1 to 9, comprising: an information collection layer, an edge computing layer, a cloud computing platform, and a mobile terminal application layer; The information collection layer collects all RSSI signals through a distributed reader array; the information collection layer connects to the edge computing layer, cloud computing platform, and mobile terminal application layer through wireless or wired mode and transmits data; The edge computing layer is deployed on the roadside unit to perform real-time data processing, including data filtering and positioning calculation; Cloud computing platform to perform global traffic situation prediction and route planning; The mobile terminal application layer supports human-computer interactive display of multimodal traffic information.

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