A remote location traffic monitoring system based on satellite communication
By adjusting the transmission threshold in real time by comparing traffic trajectory deviation and road curvature at the vehicle end, the utilization of satellite communication resources is optimized, solving the problems of high cost and response lag in traffic monitoring under satellite communication environment, and realizing high-precision and fast traffic status monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- MINJIANG UNIVERSITY
- Filing Date
- 2026-04-20
- Publication Date
- 2026-07-07
Smart Images
Figure CN122067425B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of traffic control system technology, and in particular relates to a remote location traffic monitoring system based on satellite communication. Background Technology
[0002] Currently, in wide-area highways and cross-border transportation corridors lacking terrestrial cellular network coverage, satellite-based remote monitoring systems are the core means of achieving traffic status awareness. Conventional technical approaches obtain the spatial coordinates of traffic entities through vehicle-mounted satellite terminals and transmit the location data to the monitoring center via satellite uplink. Existing monitoring systems adopt a location data pass-through mode based on fixed periods. This mode ignores the physical continuity of traffic entity movement trajectories. Satellite communication links have physical attributes such as narrow bandwidth, high cost, and discontinuous coverage. As the number of monitored entities increases, redundant coordinate sequences that conform to normal driving expectations frequently occupy channel resources. This data flow method, which deviates from the inherent physical attributes of traffic, causes satellite channels to be overloaded most of the time, increasing the overall communication cost of the system.
[0003] Existing location monitoring methods exhibit significant lag in responding to sudden traffic situations. When traffic entities experience state distortions such as skidding, collisions, or abnormal stops, the characteristic data representing these physical state transitions suffers queuing delays due to the backlog of redundant data in the transmission link. Monitoring centers lose their ability to capture traffic events in real time when faced with high-entropy events, failing to respond to abnormal situations in remote road sections within seconds. Simply increasing hardware redundancy or compressing the capacity of a single data packet cannot reconcile the contradiction between satellite spectrum energy limitations and the need for high-precision sensing. For example, Chinese invention patent application CN119449144A discloses a data transmission optimization method and system based on satellite channel congestion scenarios, which mainly relies on the packet loss rate fed back from the network layer. This approach assigns scheduling weights to messages of different service types to optimize resource utilization after channel congestion. However, this technical solution is based on a passive feedback mechanism after congestion has occurred. Its technical premise implicitly relies on the statistical characteristics of service traffic and does not penetrate to the underlying physical semantics of traffic monitoring data. In the objective environment of wide-area road network monitoring, the massive amount of repetitive coordinate data generated by straight road sections constitutes an ineffective load on the source side. General message weight adjustment cannot identify the dynamic expectations of the trajectory itself. It is not only difficult to cut off redundant data streams at the source, but also unable to ensure the instantaneous capture of key situational change information under extremely narrow bandwidth conditions. As a result, the response efficiency of the monitoring center to traffic accidents on remote road sections is still limited by the physical bottleneck of the satellite link.
[0004] Therefore, the technical problem to be solved by this invention is how to extract state change semantics at the vehicle edge based on the dynamic properties of traffic entities and road physical constraints, and realize on-demand transmission so as to ensure the real-time performance of remote monitoring under low channel load. Summary of the Invention
[0005] This invention provides a remote location traffic monitoring system based on satellite communication, including a positioning sensing module, a map data module, a satellite communication module, and an edge processing module:
[0006] The positioning and sensing module is used to acquire real-time coordinate data of traffic entities;
[0007] The map data module is used to store vector road network maps containing road geometry attributes and preset driving routes;
[0008] The edge processing module is electrically connected to the positioning and sensing module, the map data module, and the satellite communication module. The edge processing module monitors traffic entities through the following steps: Step S11, comparing real-time coordinate data with a preset driving path to calculate the trajectory deviation vector; Step S12, retrieving the road curvature radius of the corresponding road segment from the map data module based on the geographic location corresponding to the real-time coordinate data; Step S13, calculating the deviation threshold based on the road curvature radius using a preset mapping rule; Step S14, determining whether the trajectory deviation vector exceeds the deviation threshold; Step S15, if the trajectory deviation vector exceeds the deviation threshold, encapsulating a traffic state change data packet representing the instantaneous motion state of the traffic entity; Step S16, controlling the satellite communication module to upload the traffic state change data packet to the remote management system. The remote management system stores a dynamic extrapolation model synchronized with the edge processing module, used to extrapolate the trajectory of the traffic entity based on the dynamic extrapolation model during silent periods when no traffic state change data packet is received.
[0009] Preferably, the traffic state change data packet includes the real-time velocity vector, real-time heading angle, and instantaneous acceleration vector of the traffic entity; the remote management system is used to correct the parameters of the dynamic extrapolation model based on the traffic state change data packet, and update the driving trajectory generated by trajectory extrapolation based on the corrected dynamic extrapolation model.
[0010] Preferably, the edge processing module is used to monitor the physical impact signals of traffic entities, and when the detected acceleration fluctuation exceeds a preset safety threshold, it marks the traffic state change data packet as an emergency data packet; the edge processing module controls the emergency data packet to preempt the satellite uplink channel through the satellite communication module.
[0011] Preferably, it also includes: a signal quality detection module for real-time monitoring of the satellite link signal-to-noise ratio of the satellite communication module; and an edge processing module for initiating a data forwarding mechanism when the satellite link signal-to-noise ratio is lower than a preset signal-to-noise ratio threshold.
[0012] Preferably, the edge processing module operates in the data forwarding mechanism through the following sub-steps: Step S41, searching for adjacent traffic entities and establishing a temporary communication topology through a short-range wireless link; Step S42, sending traffic status change data packets to adjacent traffic entities in the temporary communication topology that have satellite link connectivity; Step S43, using the satellite link of the adjacent traffic entities to forward the traffic status change data packets to the remote management system.
[0013] Preferably, the edge processing module is used to adjust the sampling frequency of the positioning sensing module according to the real-time value of the road curvature radius; the sampling frequency increases linearly as the road curvature radius decreases.
[0014] Preferably, the remote management system is used to calculate the positional deviation between the predicted coordinates generated by trajectory extrapolation and the real-time coordinate data recorded in the subsequently received traffic state change data packet; when the positional deviation exceeds a preset range of 5m to 15m, the remote management system sends a sensor calibration command to the edge processing module.
[0015] Preferably, the edge processing module is used to shut down the coordinate pass-through function of the satellite communication module and control the satellite communication module to enter a low-power standby mode when the track deviation vector is lower than the deviation discrimination threshold.
[0016] Preferably, it also includes: an antenna pointing control module, connected to the satellite communication module, used to adjust the directional antenna beam pointing of the satellite communication module according to the road orientation parameters in the vector road network map when a traffic entity enters a ground signal blind zone.
[0017] Compared with existing technologies, the remote location traffic monitoring system based on satellite communication of this invention has the following advantages:
[0018] 1. In remote location traffic monitoring, the deviation between the physical trajectory collected by the sensor and the predicted trajectory is compared in real time by the vehicle terminal. The abnormal semantic features that characterize the nonlinear motion of traffic entities are extracted. This changes the strong positive correlation between positioning accuracy and communication frequency in the traditional monitoring system. It enables high-precision restoration of massive traffic entity trajectories in a narrow bandwidth satellite link environment, effectively solving the physical contradiction between channel resource crowding and state update lag in large-scale road network monitoring in remote areas.
[0019] 2. The trigger threshold for data reporting is deeply coupled with the road geometry curvature. The vehicle-mounted processing unit adjusts the discrimination criteria of the deviation vector in real time based on the vector electronic map, so that the monitoring sensitivity dynamically evolves with the complexity of road conditions. This enables the system to maximize the suppression of redundant coordinate transfer on straight road sections while maintaining a high-frequency state distortion capture capability in high-risk areas such as mountain roads. This avoids the risk of missing sudden sideslip or deviation accidents caused by fixed step size collection and enhances the system's perception depth of potential risks in extreme geographical environments.
[0020] 3. The vehicle-mounted monitoring terminal and the remote traffic monitoring center work together to operate the kinematic state transition matrix. By using the mirror simulation of the silent period, a digital twin mapping of traffic entities is achieved. This ensures that the system only occupies the satellite uplink channel when a physical state transition occurs. Through this logical-level data truncation, it is ensured that feature frames of high-entropy events such as traffic accidents or abnormal emergency stops can be accessed through the transmission link with the highest priority. This reduces the detection delay of abnormal events in the wide-area road network to the second level, and significantly improves the response efficiency of the emergency dispatch center to sudden traffic situations. Attached Figure Description
[0021] Figure 1 This is a schematic diagram of the system's functional modules and data interaction architecture of the present invention;
[0022] Figure 2 This is a schematic diagram of the monitoring status switching control and emergency response logic of the present invention. Detailed Implementation
[0023] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.
[0024] It should be noted that all directional and positional terms used in this invention, such as: up, down, left, right, front, back, vertical, horizontal, inner, outer, top, bottom, transverse, longitudinal, center, etc., are only used to explain the relative positional relationship and connection between components in a specific state (as shown in the accompanying drawings). They are only for the convenience of describing this invention and do not require that this invention be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention. In addition, the descriptions of "first," "second," etc., in this invention are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated.
[0025] In the description of this invention, unless otherwise explicitly specified and limited, the terms installation, connection, and linking should be interpreted broadly. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections; they can refer to direct connections or indirect connections through an intermediate medium; they can refer to the internal connection of two components. For those skilled in the art, the specific meaning of the above terms in this invention can be understood according to the specific circumstances.
[0026] In the description of this specification, references to the terms "an embodiment," "some embodiments," "illustrative embodiments," "examples," "specific examples," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example, and the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.
[0027] A remote location traffic monitoring system based on satellite communication includes a location sensing module, a map data module, a satellite communication module, and an edge processing module.
[0028] The positioning and sensing module is used to acquire real-time coordinate data of traffic entities;
[0029] The map data module is used to store vector road network maps containing road geometry attributes and preset driving routes;
[0030] The edge processing module is electrically connected to the positioning and sensing module, the map data module, and the satellite communication module. The edge processing module monitors traffic entities through the following steps: Step S11, comparing real-time coordinate data with a preset driving path to calculate the trajectory deviation vector; Step S12, retrieving the road curvature radius of the corresponding road segment from the map data module based on the geographic location corresponding to the real-time coordinate data; Step S13, calculating the deviation threshold based on the road curvature radius using a preset mapping rule; Step S14, determining whether the trajectory deviation vector exceeds the deviation threshold; Step S15, if the trajectory deviation vector exceeds the deviation threshold, encapsulating a traffic state change data packet representing the instantaneous motion state of the traffic entity; Step S16, controlling the satellite communication module to upload the traffic state change data packet to the remote management system. The remote management system stores a dynamic extrapolation model synchronized with the edge processing module, used to extrapolate the trajectory of the traffic entity based on the dynamic extrapolation model during silent periods when no traffic state change data packet is received.
[0031] Preferably, the traffic state change data packet includes the real-time velocity vector, real-time heading angle, and instantaneous acceleration vector of the traffic entity; the remote management system is used to correct the parameters of the dynamic extrapolation model based on the traffic state change data packet, and update the driving trajectory generated by trajectory extrapolation based on the corrected dynamic extrapolation model.
[0032] Preferably, the edge processing module is used to monitor the physical impact signals of traffic entities, and when the detected acceleration fluctuation exceeds a preset safety threshold, it marks the traffic state change data packet as an emergency data packet; the edge processing module controls the emergency data packet to preempt the satellite uplink channel through the satellite communication module.
[0033] Preferably, it also includes: a signal quality detection module for real-time monitoring of the satellite link signal-to-noise ratio of the satellite communication module; and an edge processing module for initiating a data forwarding mechanism when the satellite link signal-to-noise ratio is lower than a preset signal-to-noise ratio threshold.
[0034] Preferably, the edge processing module operates in the data forwarding mechanism through the following sub-steps: Step S41: Search for adjacent traffic entities and establish a temporary communication topology through short-range wireless links; Step S42: Send traffic status change data packets to adjacent traffic entities in the temporary communication topology that have satellite link connectivity; Step S43: Use the satellite links of the adjacent traffic entities to forward the traffic status change data packets to the remote management system.
[0035] Preferably, the edge processing module is used to adjust the sampling frequency of the positioning sensing module according to the real-time value of the road curvature radius; the sampling frequency increases linearly as the road curvature radius decreases.
[0036] Preferably, the remote management system is used to calculate the positional deviation between the predicted coordinates generated by trajectory extrapolation and the real-time coordinate data recorded in the subsequently received traffic state change data packet; when the positional deviation exceeds a preset range of 5m to 15m, the remote management system sends a sensor calibration command to the edge processing module.
[0037] Preferably, the edge processing module is used to shut down the coordinate pass-through function of the satellite communication module and control the satellite communication module to enter a low-power standby mode when the track deviation vector is lower than the deviation discrimination threshold.
[0038] Preferably, it also includes: an antenna pointing control module, connected to the satellite communication module, used to adjust the directional antenna beam pointing of the satellite communication module according to the road orientation parameters in the vector road network map when a traffic entity enters a ground signal blind zone.
[0039] Example 1: In cross-border transportation scenarios lacking terrestrial cellular network coverage, an onboard monitoring terminal is deployed, comprising a positioning and sensing module, a map data module, a satellite communication module, and an edge processing module. The positioning and sensing module acquires real-time coordinate data of traffic entities at a sampling frequency of 1Hz and transmits it to the edge processing module. The edge processing module retrieves a vector road network map containing a preset driving path from the map data module, compares the real-time coordinate data with the preset driving path, and calculates the trajectory deviation vector. Based on the principle of orthogonal projection, the edge processing module traverses the discrete path node sequence within the vector road network map, extracts the line segment connecting adjacent nodes with the shortest straight-line distance to the real-time coordinate data, calculates the vertical distance vector from the real-time coordinate data point to the connecting line segment, and uses the vertical distance vector as the track deviation vector. Based on the fact that the constructed vertical distance vector is a second-order spatial feature parameter with dual geometric attributes of direction and absolute displacement, in order to make it meet the algebraic operation premise of single-value comparison in the subsequent system discrimination logic, the edge processing module further calls the built-in mathematical coprocessor to calculate the vector norm of the trajectory deviation vector in the Cartesian plane according to the Euclidean distance metric. By extracting the absolute magnitude parameter of the spatial vector, the system removes the implicit directional factors and accurately separates the non-negative scalar physical projection value that represents the degree of lateral offset of traffic entities. This opens up a feature dimensionality reduction path for the multi-dimensional vector set to legally progress to the subsequent one-dimensional scalar distance judgment process. Based on the continuous sampling theorem, the system maintains the feature restoration degree of discrete coordinate points to the real physical trajectory, executes the sampling frequency closed-loop adjustment procedure, calculates the sampling frequency value according to the road curvature radius, and the mathematical constraints of the calculation logic are expressed as follows: ,in, This indicates the real-time refresh frequency of the data output by the positioning and sensing module. This indicates the upper limit of the operating frequency constant supported by the positioning baseband chip. Indicates the downsampling adjustment slope. This indicates the radius of curvature of the current road segment, and the calculated sampling frequency is obtained. Initiate the hard constraint lower limit truncation determination procedure when the sampling frequency is calculated and generated. When the hardware wake-up frequency is below 1Hz, a fixed control command is sent to lock the actual sampling frequency to 1Hz, preventing the system task from being suspended due to physical variable overflow on straight road segments with large curvature radii. The edge processing module retrieves the road curvature radius of the corresponding road segment from the map data module based on the geographic location corresponding to the real-time coordinate data. The edge processing module is based on the road curvature radius. The deviation threshold is determined by a preset mapping rule. .
[0040] When a traffic entity travels on a straight road section, the radius of curvature of that road is... For values above 500m, the deviation threshold determined by the edge processing module... It is located in the preset high-level range; the real-time trajectory of the traffic entity conforms to the preset driving path, and the trajectory deviates from the vector. At this deviation threshold The edge processing module is in a silent monitoring state, controlling the satellite communication module to stop writing data to the satellite channel; the remote management system stores a dynamic extrapolation model, which is synchronized with the vehicle-mounted monitoring terminal. During the period when the satellite communication module stops uploading data, the remote management system generates virtual trajectory points based on the dynamic extrapolation model, maintaining the dynamic trajectory output of the traffic entity; the traffic entity is within the road curvature radius... When driving on a curved road section less than 50m long, the edge processing module lowers the deviation detection threshold. The value improves the sensitivity to capturing positional fluctuations; when the traffic entity deviates from its trajectory, a track deviation vector is generated. At that time, the edge processing module determines that the track deviates from the vector. Does it exceed the deviation threshold? ; deviating from the vector on the track Reaching the deviation threshold At that time, the edge processing module collects the real-time velocity vector, real-time heading angle, and instantaneous acceleration vector of the traffic entity and encapsulates the traffic state change data packet; the edge processing module drives the satellite communication module to open the uplink and upload the traffic state change data packet to the remote management system; the remote management system receives the traffic state change data packet, extracts the motion parameters in it to correct the dynamic extrapolation model, so that the inferred trajectory generated by the remote management system converges to the actual driving trajectory of the traffic entity, realizing real-time monitoring of complex road conditions under low communication frequency.
[0041] Example 2: To verify the stability and data compression performance of the traffic control system in a narrow-bandwidth satellite channel environment, the experiment used a traffic flow simulation platform based on multibody dynamics modeling. A 25km long cross-border highway vector map was retrieved as the input source. This vector map includes a 15km straight road section and a 10km continuous winding mountain road section. The sampling frequency of the positioning and sensing module was set to 1Hz. This parameter setting needs to balance the continuity of position updates with the computational load of the edge processing module. If the sampling frequency is lower than 0.5Hz, the trajectory will deviate from the vector. The calculation accuracy is insufficient to support instantaneous deviation determination. If the sampling frequency is higher than 5Hz, the hardware power consumption of the edge processing module will increase. In order to simulate the signal disturbance in the real highway environment, Gaussian white noise with a signal-to-noise ratio of 20dB is superimposed on the original coordinate data.
[0042] The experiment set up three control groups, with the test group using the road curvature radius. Deviation detection threshold of the drive The adjustment methods are as follows: Control group A uses a fixed-period reporting method with a reporting period set to 10 seconds, while control group B uses a fixed threshold triggering method based on the track deviation vector, and the deviation discrimination threshold is set to... The constant setting was 5.0m; during the driving phase on this straight road section, the test group determined the road's radius of curvature based on this. Physical features exceeding 500m will deviate from the discrimination threshold. When the range was adjusted to 8.0m, since the setting of this range was higher than the coordinate jitter amplitude caused by the Gaussian white noise, the edge processing module maintained the silent state of the satellite communication module during this stage. Test data showed that the average channel occupancy rate of the test group on the straight road section was 0.04kbps, which was a 96.6% reduction in bandwidth overhead compared to 1.2kbps of the control group A. However, the control group B, due to its inability to identify the physical attributes of the road section, was frequently triggered by random coordinate drift at a fixed threshold of 5.0m, resulting in redundant data packets.
[0043] When a traffic entity enters the radius of curvature of this road In mountain bends less than 50m, the road network topology constraint units in this test group are based on the road curvature radius. The decreasing trend will cause the deviation to fall below the discrimination threshold. The system was adjusted to 0.8m to improve its sensitivity to fluctuations in motion. The test simulated a skidding scenario on the traffic entity, where the real-time coordinates of the traffic entity deviated from the preset travel path, generating a trajectory deviation vector. The deviation reached 1.2m; the edge processing module determined that the track deviated from the vector. Exceeding the current adjusted deviation threshold This triggers the satellite communication module to activate the uplink, maintaining the transmission delay of traffic status change data packets within 2.5 seconds; in contrast, control group B, due to an excessively high fixed threshold, experienced delays in the transmission of data packets deviating from the vector. When the deviation was 1.2m, no data reporting action was triggered. The root mean square error between the trajectory generated by the remote management system based on the dynamic extrapolation model and the actual trajectory of the traffic entity increased to over 15.0m over time. This deviation threshold was then addressed. Performance inflection point tests were conducted on the numerical boundaries, and data analysis revealed that when this deviation from the discrimination threshold occurred... After setting an upper limit threshold exceeding 10.0m, the system's success rate in detecting curve skidding events drops below 45.0%, indicating that this parameter range loses its effectiveness in safety monitoring; when this deviation from the threshold occurs... After setting a lower threshold below 0.3m, the satellite channel occupancy rate showed a non-linear increasing trend. The edge processing module was unable to filter out positioning noise, causing the satellite communication module to remain constantly active. This test result confirms that the road curvature radius... The deviation threshold Dynamic logic correction was performed, which reduced the satellite communication load under non-abnormal conditions while ensuring the trajectory restoration accuracy was within 2.0m, thus proving the engineering feasibility of this technical solution in a narrow bandwidth satellite communication environment.
[0044] Example 3: During the parameter calibration process for high-altitude mountain roads, the edge processing module retrieves the vector road network map stored in the map data module to obtain the road curvature radius of the current traffic entity location. The edge processing module is based on the road curvature radius. Determine the deviation threshold This process transforms the physical constraints of road geometry design into logical criteria for triggering satellite communication links; this deviation threshold... The determination follows the formula below: ;in, To deviate from the discrimination threshold, The calibration coefficient is determined by the preset early warning response time and the road surface adhesion coefficient. The calculation process for the road curvature radius ensures that the traffic entity enters the road at that curvature radius. When there are continuous curves less than 50m, this deviation threshold is considered. It automatically narrows to a range of 0.6m to 1.1m to improve the sensitivity of detecting minor deviations in the driving trajectory, while the road curvature radius is within this range. For straight road sections longer than 500m, this deviation threshold is considered. The width is automatically increased to 7.5m or more, thereby reducing the impact of coordinate jitter caused by satellite signal multipath effect on the uplink channel through physical filtering.
[0045] The remote management system incorporates a dynamic extrapolation model, which maintains a state variable register group consisting of coordinate vectors, velocity vectors, and heading angles. During the duration of the satellite communication module's silent period, the remote management system retrieves the motion parameters stored in the state variable register group from the previous moment and calculates the predicted spatiotemporal coordinates of the traffic entity according to the kinematic differential equations, maintaining the trajectory output of the traffic entity. In the specific implementation of the extrapolation calculation, the remote management system relies on the constant turning rate and acceleration (CTRA) nonlinear dynamic mathematical analytical framework, using the latest coordinate lattice, instantaneous tangential velocity, and yaw rate retained in the state variable register group as the initial state vector of the system. The algorithm's master node initiates a fourth-order Runge-Kutta numerical integral iterative solver, using a preset millisecond-level time baseline as the step size, to perform time-domain discretized extrapolation of the vehicle's lateral and longitudinal kinematic differential equations constrained by nonholonomic constraints. This iteratively outputs continuous parameterized spatial predicted trajectory coordinates that match the satellite's silent blind zone. The edge processing module then determines the trajectory deviation vector. Reaching the deviation threshold After driving the satellite communication module to upload traffic state change data packets, the remote management system parses the real-time three-dimensional coordinates, real-time velocity vectors, real-time heading angles, and instantaneous acceleration vectors contained in the traffic state change data packets. The remote management system writes the parsed real-time motion parameters into the storage address corresponding to the state variable register group according to the field mapping relationship, completing the physical coverage of the predicted state of the dynamic extrapolation model. This physical coverage action resets the input benchmark of the dynamic extrapolation model, eliminates the accumulated errors caused by long-term extrapolation, and makes the monitoring trajectory output by the remote management system converge to the driving trajectory of the traffic entity.
[0046] Example 4: During the connection of the vehicle monitoring terminal to the traffic control system, the edge processing module determines the deviation discrimination threshold by running a dynamic test process on the pre-selected road segment. calibration coefficients in The edge processing module controls traffic entities to pass through the road curvature radius at intervals ranging from 20 km / h to 80 km / h. On a constant curved road section, real-time coordinate data output by the positioning and sensing module is collected, and the variance of the positioning error distribution between the real-time coordinate data and the centerline of the test road section is calculated. The edge processing module will use the preset safety tolerance distance and the variance of the positioning error distribution. The ratio is determined as the calibration coefficient. ;in, For calibration coefficients, To deviate from the discrimination threshold, The radius of curvature of the road. This calibration coefficient represents the variance of the positioning error distribution. Deviate the track from the vector The false alarm rate under stable driving conditions is less than 0.1%; this process determines the road curvature radius by quantifying the physical characteristics corresponding to the accuracy level of the positioning hardware. The deviation from the discrimination threshold The mapping relationship between them is the benchmark.
[0047] When a traffic entity initiates a transportation task at the starting node of a preset travel path, the vehicle-mounted monitoring terminal performs a static alignment process to initialize the initial values of the dynamic extrapolation model in the remote management system. When the traffic entity is stationary and the positioning and sensing module has locked onto at least six satellites, the positioning and sensing module collects real-time three-dimensional coordinates for a duration of 60 seconds, calculates the center point coordinates, and uses them as the initial position vector of the state variable register group. The vehicle-mounted monitoring terminal retrieves the zero-velocity pulse signal output by the traffic entity's electronic control unit, clears the velocity vector and instantaneous acceleration vector to zero, and sends the initial state vector, composed of the initial position vector, velocity vector, and instantaneous acceleration vector, to the remote management system via the satellite communication module. The remote management system receives the initial state vector, updates its local state variable register group, and ensures that the dynamic calculation benchmark of the remote management system and the vehicle-mounted monitoring terminal is consistent before the start of the silent period. This alignment process, by correcting the initial values of the motion parameters, suppresses the cumulative deviation of the dynamic extrapolation model generated by time integration during trajectory extrapolation.
[0048] Example 5: In a wide-area road network deployment scenario of a traffic control system, the edge processing module achieves physical spatial alignment between the real-time coordinate data output by the positioning sensing module and the vector road network map stored in the map data module through coordinate projection transformation. When the traffic entity is at a preset physical marker point and is stationary, the edge processing module acquires the native coordinate vector output by the positioning sensing module. And compare it with the standard reference coordinates of the physical marker point in the vector road network map. Perform vector subtraction to obtain the spatial bias vector. ;in, It is the original coordinate vector. As the standard reference coordinate, This is the spatial offset vector; the edge processing module utilizes this spatial offset vector in subsequent monitoring loops. The real-time coordinate data acquired at each moment is translated and corrected to make the calculated track deviate from the vector. The edge processing module accurately reflects the displacement fluctuations of the traffic entity relative to the preset travel path, matches the positional offset caused by map projection differences, and adjusts the processing benchmark of the real-time coordinate data. Under operating conditions where the traffic control system faces changes in the intensity of multipath interference with the positioning signal, the edge processing module redetermines the deviation discrimination threshold using road surface environmental noise measurement. The calibration coefficient in Based on the waveform frequency domain distribution isolation characteristics, the edge processing module loads an interference removal procedure before performing variance calculation. It synchronously acquires the steering wheel angle parameter sequence and the vehicle suspension displacement parameter sequence via the vehicle controller's local area network data bus. A time-domain sliding comparison window is established to extract the original coordinate queue within the window where the steering wheel angle remains constant and the suspension displacement parameters are below the mechanical limit reference. The original coordinate queue is processed by calling a fast Fourier transform function, and the low-frequency mechanical vibration components of the vehicle (below 2Hz) in the separated frequency domain are calculated. The high-frequency fluctuation data sequence caused by electromagnetic refraction is extracted separately as the pure input matrix for subsequent environmental noise measurement. In this environmental noise measurement procedure, it is used to execute the time-domain... The original coordinate queue of the Fourier transform is not directly generated from the satellite-based positioning signal with a refresh rate of only 1Hz. Instead, the edge processing module controls the built-in high-frequency microelectromechanical inertial measurement unit (IMU) to enter a transient high-frequency sampling state. It synchronously acquires the vehicle's three-axis acceleration and angular velocity signals at a characteristic capture frequency of 100Hz, and integrates the chassis kinematic parameters to reconstruct a high-density physical displacement coordinate array in the internal buffer through short-time dead reckoning. The intervention of this high-frequency sampling mechanism establishes a digital domain Nyquist analysis limit of up to 50Hz, thus providing a continuous physical data basis that conforms to the sampling theorem for separating and extracting frequency domain fluctuation components above 2Hz.
[0049] The vehicle-mounted monitoring terminal determined that the traffic entity was traveling at a constant speed and the road curvature radius was... In conditions exceeding 1000m, the edge processing module continuously acquires... Calculate the variance of position coordinate fluctuation caused by external electromagnetic disturbances using the real-time coordinate data for each period. The edge processing module adjusts the variance based on the location coordinate fluctuation. With the radius of curvature of the road The ratio of the square roots determines the calibration coefficient. The current correction value makes this deviation from the discrimination threshold. The value range covers the positioning drift amplitude under the current environment; among which, For calibration coefficients, The variance of position coordinate fluctuation. The radius of curvature of the road. The total number of sampling periods. To avoid deviation from the discrimination threshold; this calibration method enables the traffic control system to detect a decrease in external positioning accuracy using this calibration coefficient. Increase the action to broaden the deviation discrimination threshold The tolerance range is set to suppress the satellite communication module from reporting inaccurate traffic status change data packets to the remote management system due to positioning noise. Given the highly discrete physical characteristics of the spatial distribution of traffic entities in the wide-area road network, the edge processing module embeds an online calibration procedure for isolated node data degradation caching. After the control antenna radio frequency unit sends a short-range wireless handshake signal, it starts an internal clock counter. This wireless radio frequency detection and connection action is specifically executed based on the underlying physical protocol stack specification of the Vehicle Ad Hoc Network (VANET). Its Media Access Control (MAC) layer periodically broadcasts paging beacon data frames carrying local physical address fingerprints and remaining uplink bandwidth load status flags within the pre-allocated control channel. When a neighboring traffic network entity enters the current beacon radio frequency coverage area and successfully demodulates the broadcast frame, it will return a confirmation permission command with the available route hops according to the standard three-order wireless handshake anti-collision negotiation criteria. The main control process of the edge processing module... Subsequently, based on the shortest path first dynamic route estimation, the collected permission of adjacent nodes is merged and filtered, thereby constructing a dynamic multi-hop cascaded topology logical network layer with physical radio frequency connectivity and unique routing data transfer flow among multiple isolated mobile nodes. When no feedback pulse from adjacent traffic entities is detected within the 5-second communication waiting period after the clock count value, the short-range wireless transceiver link is shut down and the memory reconstruction program is initiated. The extreme value feature frame with instantaneous acceleration vector magnitude exceeding the preset collision braking limit is extracted from the backlog traffic state change data packet. The queue cleaning action is performed to discard the regular coordinate frames that do not reach the limit, and the retained extreme value feature frames are written to the non-volatile storage medium on the control circuit board. When the signal quality detection module monitors the satellite link signal-to-noise ratio and it recovers to above the reference fading threshold, the extreme value feature frame in the non-volatile storage medium is extracted and sent in batches to the remote management system through the main control bus and satellite uplink in ascending order of timestamp identifier, thus closing the physical state data link in the offline communication blind zone.
[0050] The embodiments of this application have been described above with reference to the accompanying drawings. Unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other. This application is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of this application without departing from the spirit of this application and the scope of protection of this invention, and all of these forms are within the protection scope of this application.
Claims
1. A remote location traffic monitoring system based on satellite communication, characterized in that, It includes a positioning and sensing module, a map data module, a satellite communication module, and an edge processing module: The positioning and sensing module is used to acquire real-time coordinate data of traffic entities; The map data module is used to store vector road network maps containing road geometry attributes and preset driving routes; The edge processing module is electrically connected to the positioning and sensing module, the map data module, and the satellite communication module. The edge processing module monitors traffic entities through the following steps: Step S11, comparing real-time coordinate data with a preset driving path to calculate the trajectory deviation vector; Step S12, retrieving the road curvature radius of the corresponding road segment from the map data module based on the geographic location corresponding to the real-time coordinate data; Step S13, calculating the deviation threshold based on the road curvature radius using a preset mapping rule; Step S14, determining whether the trajectory deviation vector exceeds the deviation threshold; Step S15, if the trajectory deviation vector exceeds the deviation threshold, encapsulating a traffic state change data packet representing the instantaneous motion state of the traffic entity; Step S16, controlling the satellite communication module to upload the traffic state change data packet to the remote management system. The remote management system stores a dynamic extrapolation model synchronized with the edge processing module, used to extrapolate the trajectory of the traffic entity based on the dynamic extrapolation model during silent periods when no traffic state change data packet is received.
2. The remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, The traffic state change data packet contains the real-time velocity vector, real-time heading angle, and instantaneous acceleration vector of the traffic entity; the remote management system is used to correct the parameters of the dynamic extrapolation model based on the traffic state change data packet, and update the driving trajectory generated by trajectory extrapolation based on the corrected dynamic extrapolation model.
3. The remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, The edge processing module is used to monitor physical impact signals of traffic entities and, when it detects acceleration fluctuations exceeding a preset safety threshold, marks traffic state change data packets as emergency data packets. The edge processing module controls emergency data packets to preempt the satellite uplink channel via the satellite communication module.
4. The remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, Also includes: The signal quality detection module is used to monitor the signal-to-noise ratio of the satellite link of the satellite communication module in real time. The edge processing module is used to initiate the data forwarding mechanism when the signal-to-noise ratio of the satellite link is lower than a preset signal-to-noise ratio threshold.
5. A remote location traffic monitoring system based on satellite communication according to claim 4, characterized in that, The edge processing module operates in the data forwarding mechanism through the following sub-steps: Step S41, searching for adjacent traffic entities and establishing a temporary communication topology through short-range wireless links; Step S42, sending traffic status change data packets to adjacent traffic entities in the temporary communication topology that have satellite link connectivity; Step S43, using the satellite links of the adjacent traffic entities to forward the traffic status change data packets to the remote management system.
6. A remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, The edge processing module is used to adjust the sampling frequency of the positioning sensing module based on the real-time value of the road curvature radius; the sampling frequency increases linearly as the road curvature radius decreases.
7. A remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, The remote management system calculates the positional deviation between the predicted coordinates generated by trajectory extrapolation and the real-time coordinate data recorded in the subsequently received traffic state change data packets; when the positional deviation exceeds a preset range of 5m to 15m, the remote management system sends a sensor calibration command to the edge processing module.
8. A remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, The edge processing module is used to shut down the coordinate pass-through function of the satellite communication module and control the satellite communication module to enter a low-power standby mode when the track deviation vector is lower than the deviation discrimination threshold.
9. A remote location traffic monitoring system based on satellite communication according to claim 1, characterized in that, Also includes: The antenna pointing control module, connected to the satellite communication module, is used to adjust the directional antenna beam pointing of the satellite communication module according to the road orientation parameters in the vector road network map when a traffic entity enters a ground signal blind zone.