Multi-terminal positioning intelligent collaborative management system based on Beidou satellite

Abstract

The invention discloses a multi-terminal positioning intelligent collaborative management system based on a Beidou satellite, and relates to the technical field of operation and maintenance data intelligent management. The system collects crossroad vehicle information, sets a collection period and a monitoring range, counts the vehicle information, calls historical data, extracts historical reference vehicle data, and calculates historical traffic demands; the traffic prediction influence degree is analyzed, the traffic demand of the next monitoring period is obtained, a congested intersection is monitored, the green light adjustment demand is analyzed, the green light duration is adjusted, after the congested intersection is adjusted, the congested condition of an adjacent intersection is monitored, and the green light duration of the adjacent intersection is adjusted. According to the invention, through combination of historical data and traffic prediction, traffic demands in all directions are accurately analyzed, traffic conditions of adjacent intersections are monitored, adaptive adjustment is carried out, the transfer of traffic pressure is avoided, and the traffic operation of the whole area is smoother.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent management of operation and maintenance data, and specifically to a Beidou satellite-based multi-terminal positioning intelligent collaborative management system. Background Art

[0002] Urban traffic congestion is becoming increasingly severe, causing significant inconvenience for citizens. Traditional traffic management methods rely primarily on fixed traffic light durations, making it difficult to flexibly adjust to real-time traffic flows. Under this model, traffic signals cannot adapt to traffic fluctuations during peak and off-peak periods, often resulting in a backlog of vehicles in some directions while roads in other directions remain idle. This leads to poor utilization of road resources and exacerbated traffic congestion. While existing traffic management systems incorporate some intelligent technologies, they suffer from significant deficiencies in data collection and analysis. Some systems collect incomplete traffic information, capturing only traffic flow data at select intersections and failing to capture a comprehensive picture of traffic flow across the entire region. Furthermore, data analysis often relies on simple statistics, failing to fully exploit the potential value of historical and real-time data. This results in limited forecasting of future traffic flows, making it difficult to achieve precise traffic control. Furthermore, most traffic management systems lack collaborative mechanisms. The traffic signals at each intersection operate independently. When congestion occurs at one intersection and the traffic lights are adjusted, the adjacent intersections cannot respond in time, which can easily cause traffic pressure to be transferred and the congestion to expand. This management model cannot achieve the overall optimization of regional traffic and restricts the improvement of urban traffic operation efficiency. Summary of the Invention

[0003] The purpose of the present invention is to provide a multi-terminal positioning intelligent collaborative management system based on Beidou satellites to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a multi-terminal positioning intelligent collaborative management system based on Beidou satellites, comprising: a Beidou traffic data acquisition module, a historical traffic demand analysis module, an adjustment demand analysis module, a road intersection green light control module, a road intersection chain control module, and a traffic light linkage module; The Beidou traffic flow data acquisition module is used to collect vehicle information at intersections, set the collection cycle and monitoring range, and count vehicle information; The historical traffic demand analysis module is used to call historical data, extract historical reference vehicle data, and calculate historical traffic demand; The regulation demand analysis module is used to analyze the impact of traffic prediction and obtain the traffic demand in the next monitoring period; The intersection green light control module is used to monitor congested intersections, analyze green light adjustment needs, and adjust the green light duration; The intersection interlocking control module is used to monitor the congestion situation of adjacent intersections after adjusting the congested intersection and adjust the green light duration of the adjacent intersections; The traffic light linkage module is used to adjust the green light duration while synchronously and reversely adjusting the red light duration.

[0005] Furthermore, the BeiDou traffic flow data collection module is based on BeiDou satellites. After authorization, it collects vehicle information and monitors any intersection with a traffic light. The collection cycle duration is set to β, the number of reference collection cycles is set to T, and the most recent collection cycle is set to the Tth collection cycle. In the Tth collection cycle, the total number of vehicles passing through any straight road within a distance α from the intersection is collected. The total number of vehicles is A. T , where the number of vehicles traveling in either direction is a1, and the number of vehicles traveling in the other direction is a2, a1+a2=A T , where the larger value of a1 and a2 is the reference number of vehicles a on any straight road; in the Tth collection cycle, the total number of vehicles passing through another straight road within the range of α from the intersection is collected, and the total number of vehicles is B T , where the number of vehicles traveling in either direction is b1, and the number of vehicles traveling in the other direction is b2, b1+b2=B T , where the larger value of b1 and b2 is the reference number of vehicles b on any straight road T The Beidou traffic data collection module efficiently monitors traffic conditions at intersections. It accurately captures vehicle information near intersections and, by analyzing traffic flow in different directions, provides intuitive reference for traffic management. This module helps monitor intersection traffic conditions in real time, promptly detects signs of congestion, and provides a basis for adjusting traffic light durations, enabling more targeted traffic management. Furthermore, the continuously collected data helps analyze traffic flow patterns, supporting road planning and traffic flow optimization. This improves the scientific nature and effectiveness of overall traffic management, ensuring smoother traffic at intersections and creating a more convenient transportation environment for citizens.

[0006] Furthermore, the historical traffic demand analysis module uses the historical data obtained by BeiDou satellites to call the monitoring data of any intersection with traffic lights, and obtains the total number of vehicles in T reference collection cycles on any straight road as {A1, A2, ..., A t ,…,A T}, where A t Indicates that the total number of vehicles in the tth reference collection cycle on any straight road and the number of reference vehicles in T reference collection cycles on any straight road are {a1, a2, …, a t ,…,a T}, where a t represents the number of reference vehicles in the tth reference collection cycle on any straight road; In the historical data, the number of cycles with two-way congestion is k1, and the number of cycles with one-way congestion is k2. Then the historical traffic demand P of any straight road is calculated. A : ; The same method is used to calculate the historical traffic demand P of another straight road B The historical traffic demand analysis module can deeply explore the value of historical traffic flow data at intersections collected by Beidou satellites. It can systematically sort out the vehicle traffic conditions in different periods, accurately identify the frequency of two-way congestion and one-way congestion, and quantify the historical traffic demand of the road. By analyzing long-term data patterns, this module can provide a scientific basis for traffic management: it can not only assist in optimizing signal timing to make intersections smoother, but also provide support for planning decisions such as road widening and lane addition, fundamentally alleviating the pain points of historical congestion. At the same time, its summary of historical congestion patterns can also provide a reference for real-time congestion warnings and predictions of future traffic trends, helping to improve the scientificity and foresight of the overall transportation system and create a more orderly traffic environment for citizens to travel.

[0007] Furthermore, the adjustment demand analysis module is based on the multi-terminal positioning function of Beidou satellites. Through the navigation system, it is predicted that the total number of vehicles passing through any straight road within the range of α from the intersection within the time length β is q A , the total number of vehicles that pass through another straight road within the distance α from the intersection within the time length β is predicted to be q B , and then get the traffic prediction impact degree K of any straight road A =(q A +A T ) / A T , get the traffic prediction impact degree K of another straight road B =(q B +B T ) / B T , the traffic demand of any straight road in the next monitoring period is calculated to be X A =K A *P A , the traffic demand of the other straight road in the next monitoring period is calculated to be X B =K B *P BThe adjustment demand analysis module leverages the Beidou satellite multi-terminal positioning capabilities and navigation system prediction functions to accurately estimate the number of vehicles passing through an intersection within a short period of time. This module combines predicted traffic flow with current, real-time traffic data, incorporating historical traffic demand analysis results, and scientifically assesses road traffic pressure for the next cycle through dynamic calculations. Its advantage lies in its ability to perceive traffic flow trends in advance, providing a basis for dynamic adjustments in traffic management. It can assist in optimizing signal timing plans, ensuring more reasonable allocation of traffic resources at intersections, and can also predict congestion risks in advance, providing forward-looking reference for road diversion and planning decisions. It effectively improves the transportation system's ability to adapt to traffic flow fluctuations, making urban road traffic more efficient and intelligent.

[0008] Furthermore, the intersection green light control module monitors any congested intersection. The congested section can be determined by calculating the average vehicle dwell time at the intersection. When the average vehicle dwell time exceeds a preset dwell time threshold, the intersection is determined to be a congested intersection. The green light duration of any straight lane in the Tth collection cycle is queried as Y. T_A , the green light duration of the other straight lane is Y T_B , calculate the green light adjustment demand F at any intersection: ; Set the adjustment error threshold F0. When F≤F0, set the green light duration for the next collection cycle unchanged; when F>F0, adjust the green light duration. The intersection green light control module can intelligently optimize intersection traffic efficiency. It can monitor the green light duration at congested intersections in real time, and accurately calculate the green light adjustment requirements by combining historical traffic demand with predicted traffic flow data. When it is found that there is a deviation between the current green light timing and the actual traffic demand, the module will automatically start the adjustment mechanism to reasonably adjust the green light duration in different directions; if the deviation is within a reasonable range, the existing timing will be maintained to avoid frequent adjustments. This dynamic control method can make the green light duration more compatible with traffic changes, effectively alleviate intersection congestion, reduce vehicle waiting time, and improve road traffic capacity. At the same time, it provides support for regional traffic coordination control and priority passage for special vehicles, making urban traffic management smarter and more efficient.

[0009] Furthermore, the green light control module at the intersection adjusts the green light duration by distributing the green light duration of any straight channel with the green light duration of another straight channel, so that the green light duration of any straight channel is adjusted to x=[X A / (X A +X B )]*(Y T_A +Y T_B ), and adjust the green light duration of the other straight lane to y=[X B / (X A +X B )]*(Y T_A +YT_B ), after adjusting any congested intersection, the intersection chain control module monitors the congestion situation of the adjacent intersection. If the adjacent intersection is congested, the green light adjustment of the adjacent intersection is performed in the same way; if the adjacent intersection is not congested, the adjacent intersection is adaptively adjusted.

[0010] Furthermore, the adaptive adjustment used by the intersection chain control module includes: if the adjacent intersection is on any straight lane of the congested intersection, the green light duration is adjusted to X0+M*(xY T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight lane at the adjacent intersection to Y0+M*(Y T_A -x) / Y T_A *(X0+Y0), where M is the existing intersection adjustment coefficient, X0 represents the original green light duration of the adjacent intersection and the congested intersection on the same road, and Y0 represents the original green light duration of the adjacent intersection and the congested intersection on different roads; if the adjacent intersection is on the other straight lane of the congested intersection, the green light duration is adjusted to X0+M*(yY T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight lane at the adjacent intersection to Y0+M*(Y T_A -y) / Y T_A *(X0+Y0); The intersection green light control module can dynamically optimize the green light duration based on real-time traffic demand. By allocating the two-way green light time proportionally, the timing can be more closely matched with traffic pressure, thus avoiding waste of resources. On this basis, the intersection chain control module can link adjacent intersections for collaborative optimization: if the adjacent intersection is congested, the green light duration is adjusted using the same logic; if it is not congested, adaptive fine-tuning is implemented based on the adjustment amplitude and direction of the congested intersection, combined with the intersection adjustment coefficient, to ensure smooth connection of traffic on adjacent roads. This control mode not only achieves precise timing for a single intersection, but also forms a regional traffic signal coordination mechanism through the linkage response of adjacent intersections, effectively alleviating regional congestion, improving the overall traffic efficiency of the road network, and making urban traffic operations smarter and more orderly.

[0011] Furthermore, when the traffic light linkage module adjusts the duration of the green light, it also adjusts the duration of the red light in the opposite direction.

[0012] Compared with existing technologies, this invention achieves the following benefits: First, it precisely regulates traffic flow. By collecting real-time information about vehicles at intersections and combining it with historical data and traffic forecasts, the system accurately analyzes traffic demand in each direction. Based on this, it dynamically adjusts the duration of green lights, allowing vehicles to efficiently pass through intersections and avoiding long waits caused by inappropriate signal settings. This effectively alleviates traffic congestion and improves road efficiency.

[0013] First, it enables coordinated intersection management. When congestion occurs at one intersection and the green light duration is adjusted, the system automatically monitors traffic conditions at adjacent intersections. If the adjacent intersection is congested, the green light adjustment is made in the same manner; if not, adaptive adjustments are made. This interlocking control mechanism avoids the transfer of traffic pressure and ensures more balanced and smooth traffic flow throughout the area.

[0014] Secondly, it innovates traffic management models. Leveraging Beidou satellite technology, the system integrates data from multiple terminals, transforming traditional passive traffic management into proactive intelligent control. Through in-depth mining and analysis of traffic data, it provides scientific decision-making for traffic management departments, driving the transition from experience-driven to data-driven traffic management and helping to build a new smart transportation ecosystem. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 This is a structural diagram of a Beidou satellite-based multi-terminal positioning intelligent collaborative management system of the present invention. DETAILED DESCRIPTION

[0016] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0017] See also Figure 1 The present invention provides a technical solution: a multi-terminal positioning intelligent collaborative management system based on Beidou satellite, including: Beidou traffic data acquisition module, historical traffic demand analysis module, regulation demand analysis module, intersection green light control module, intersection chain control module and traffic light linkage module; The Beidou traffic flow data collection module is used to collect vehicle information at intersections, set the collection cycle and monitoring range, and count vehicle information; The historical traffic demand analysis module is used to call historical data, extract historical reference vehicle data, and calculate historical traffic demand; The regulation demand analysis module is used to analyze the impact of traffic forecast and derive the traffic demand for the next monitoring period; The intersection green light control module is used to monitor congested intersections, analyze green light adjustment needs, and adjust the green light duration; The intersection interlocking control module is used to monitor the congestion situation of adjacent intersections after adjusting the congested intersection and adjust the green light duration of the adjacent intersections; The traffic light linkage module is used to adjust the duration of the green light while adjusting the duration of the red light in the opposite direction.

[0018] The BeiDou traffic flow data collection module is based on BeiDou satellites. After authorization, it collects vehicle information and monitors any intersection with a traffic light. The collection cycle duration is set to β, the number of reference collection cycles is set to T, and the most recent collection cycle is set to the Tth collection cycle. In the Tth collection cycle, the total number of vehicles passing through any straight road within the distance α from the intersection is collected. The total number of vehicles is A. T , where the number of vehicles traveling in either direction is a1, and the number of vehicles traveling in the other direction is a2, a1+a2=A T , where the larger value of a1 and a2 is the reference number of vehicles a on any straight road; in the Tth collection cycle, the total number of vehicles passing through another straight road within the range of α from the intersection is collected, and the total number of vehicles is B T , where the number of vehicles traveling in either direction is b1, and the number of vehicles traveling in the other direction is b2, b1+b2=B T , where the larger value of b1 and b2 is the reference number of vehicles b on any straight road T The Beidou traffic data collection module efficiently monitors traffic conditions at intersections. It accurately captures vehicle information near intersections and, by analyzing traffic flow in different directions, provides intuitive reference for traffic management. This module helps monitor intersection traffic conditions in real time, promptly detects signs of congestion, and provides a basis for adjusting traffic light durations, enabling more targeted traffic management. Furthermore, the continuously collected data helps analyze traffic flow patterns, supporting road planning and traffic flow optimization. This improves the scientific nature and effectiveness of overall traffic management, ensuring smoother traffic at intersections and creating a more convenient transportation environment for citizens.

[0019] The historical traffic demand analysis module is based on the historical data obtained by BeiDou satellites. It calls the monitoring data of any intersection with traffic lights and obtains the total number of vehicles in T reference collection cycles on any straight road as {A1, A2, ..., A t ,…,A T}, where A t Indicates that the total number of vehicles in the tth reference collection cycle on any straight road and the number of reference vehicles in T reference collection cycles on any straight road are {a1, a2, …, a t ,…,a T}, where a t represents the number of reference vehicles in the tth reference collection cycle on any straight road; In the historical data, the number of cycles with two-way congestion is k1, and the number of cycles with one-way congestion is k2. Then the historical traffic demand P of any straight road is calculated. A : ; The same method is used to calculate the historical traffic demand P of another straight road B The historical traffic demand analysis module can deeply explore the value of historical traffic flow data at intersections collected by Beidou satellites. It can systematically sort out the vehicle traffic conditions in different periods, accurately identify the frequency of two-way congestion and one-way congestion, and quantify the historical traffic demand of the road. By analyzing long-term data patterns, this module can provide a scientific basis for traffic management: it can not only assist in optimizing signal timing to make intersections smoother, but also provide support for planning decisions such as road widening and lane addition, fundamentally alleviating the pain points of historical congestion. At the same time, its summary of historical congestion patterns can also provide a reference for real-time congestion warnings and predictions of future traffic trends, helping to improve the scientificity and foresight of the overall transportation system and create a more orderly traffic environment for citizens to travel.

[0020] The regulation demand analysis module is based on the multi-terminal positioning function of Beidou satellites. The navigation system predicts that the total number of vehicles passing through any straight road within the distance α from the intersection within the time length β is q A , the total number of vehicles that pass through another straight road within the distance α from the intersection within the time length β is predicted to be q B , and then get the traffic prediction impact degree K of any straight road A =(q A +A T ) / A T , get the traffic prediction impact degree K of another straight road B =(q B +B T ) / B T , the traffic demand of any straight road in the next monitoring period is calculated to be X A =K A *P A , the traffic demand of the other straight road in the next monitoring period is calculated to be X B =K B *P BThe adjustment demand analysis module leverages the Beidou satellite multi-terminal positioning capabilities and navigation system prediction functions to accurately estimate the number of vehicles passing through an intersection within a short period of time. This module combines predicted traffic flow with current, real-time traffic data, incorporating historical traffic demand analysis results, and scientifically assesses road traffic pressure for the next cycle through dynamic calculations. Its advantage lies in its ability to perceive traffic flow trends in advance, providing a basis for dynamic adjustments in traffic management. It can assist in optimizing signal timing plans, ensuring more reasonable allocation of traffic resources at intersections, and can also predict congestion risks in advance, providing forward-looking reference for road diversion and planning decisions. It effectively improves the transportation system's ability to adapt to traffic flow fluctuations, making urban road traffic more efficient and intelligent.

[0021] Furthermore, the intersection green light control module monitors any congested intersection. The congested section can be determined by calculating the average vehicle dwell time at the intersection. When the average vehicle dwell time exceeds a preset dwell time threshold, the intersection is determined to be a congested intersection. The green light duration of any straight lane in the Tth collection cycle is queried as Y. T_A , the green light duration of the other straight lane is Y T_B , calculate the green light adjustment demand F at any intersection: ; Set the adjustment error threshold F0. When F≤F0, set the green light duration for the next collection cycle unchanged; when F>F0, adjust the green light duration. The intersection green light control module can intelligently optimize intersection traffic efficiency. It can monitor the green light duration at congested intersections in real time, and accurately calculate the green light adjustment requirements by combining historical traffic demand with predicted traffic flow data. When it is found that there is a deviation between the current green light timing and the actual traffic demand, the module will automatically start the adjustment mechanism to reasonably adjust the green light duration in different directions; if the deviation is within a reasonable range, the existing timing will be maintained to avoid frequent adjustments. This dynamic control method can make the green light duration more compatible with traffic changes, effectively alleviate intersection congestion, reduce vehicle waiting time, and improve road traffic capacity. At the same time, it provides support for regional traffic coordination control and priority passage for special vehicles, making urban traffic management smarter and more efficient.

[0022] The green light control module at the intersection adjusts the green light duration by distributing the green light duration of any straight channel with the green light duration of another straight channel, so that the green light duration of any straight channel is adjusted to x=[X A / (X A +X B )]*(Y T_A +Y T_B ), and adjust the green light duration of the other straight lane to y=[X B / (X A +X B )]*(Y T_A +YT_B ), after adjusting any congested intersection, the intersection chain control module monitors the congestion situation of the adjacent intersection. If the adjacent intersection is congested, the green light adjustment of the adjacent intersection is performed in the same way; if the adjacent intersection is not congested, the adjacent intersection is adaptively adjusted.

[0023] The adaptive adjustment used by the intersection chain control module includes: if the adjacent intersection is on any straight lane of the congested intersection, the green light duration is adjusted to X0+M*(xY T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight lane at the adjacent intersection to Y0+M*(Y T_A -x) / Y T_A *(X0+Y0), where M is the existing intersection adjustment coefficient, X0 represents the original green light duration of the adjacent intersection and the congested intersection on the same road, and Y0 represents the original green light duration of the adjacent intersection and the congested intersection on different roads; if the adjacent intersection is on the other straight lane of the congested intersection, the green light duration is adjusted to X0+M*(yY T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight lane at the adjacent intersection to Y0+M*(Y T_A -y) / Y T_A *(X0+Y0); The intersection green light control module can dynamically optimize the green light duration based on real-time traffic demand. By allocating the two-way green light time proportionally, the timing can be more closely matched with traffic pressure, thus avoiding waste of resources. On this basis, the intersection chain control module can link adjacent intersections for collaborative optimization: if the adjacent intersection is congested, the green light duration is adjusted using the same logic; if it is not congested, adaptive fine-tuning is implemented based on the adjustment amplitude and direction of the congested intersection, combined with the intersection adjustment coefficient, to ensure smooth connection of traffic on adjacent roads. This control mode not only achieves precise timing for a single intersection, but also forms a regional traffic signal coordination mechanism through the linkage response of adjacent intersections, effectively alleviating regional congestion, improving the overall traffic efficiency of the road network, and making urban traffic operations smarter and more orderly.

[0024] When the traffic light linkage module adjusts the duration of the green light, it will also adjust the duration of the red light in the opposite direction.

[0025] Example 1: Within a traffic monitoring area, a BeiDou satellite-powered data acquisition module continuously monitors intersection dynamics. On straight roads within a certain distance of the intersection, the system captures the traffic flow of vehicles in both directions in real time, collecting traffic data in both directions at regular intervals. This data is synchronously transmitted to the backend, providing basic support for subsequent traffic control.

[0026] The historical traffic demand analysis module then activated, retrieving traffic records from multiple past cycles at the intersection. The system conducted an in-depth analysis of this historical data: Over past monitoring periods, the intersection had experienced multiple instances of saturated two-way traffic flow and slow one-way traffic. By categorizing and analyzing these historical conditions, the module was able to accurately assess the long-term traffic pressure distribution at the intersection, providing a reference for current traffic control decisions.

[0027] At the same time, the navigation system predicts traffic flow for the next cycle based on real-time road conditions and multi-terminal positioning information. The forecast indicates a significant increase in traffic on arterial roads and an upward trend in traffic towards commercial districts. The demand adjustment analysis module combines measured and predicted data from the current cycle to comprehensively assess traffic pressure trends in both directions, identifying potential fluctuations in traffic demand in each direction over the next cycle.

[0028] Based on this analysis, the intersection green light control module evaluates the current green light duration. The system compares the historical traffic demand in both through-traffic directions with the predicted impact and calculates the required adjustment to the green light duration. If the adjustment exceeds a preset reasonable range, the module activates an optimization mechanism: it reallocates the green light duration based on the traffic demand ratio between the two directions. If the traffic demand in the main road direction is higher, the green light duration in that direction will be appropriately extended to alleviate traffic pressure.

[0029] After the green light duration adjustment is complete, the intersection interlocking control module begins monitoring the status of adjacent intersections. If traffic flow anomalies are detected at adjacent intersections due to adjustments to the main intersection, the system will implement adaptive control based on the adjacent intersection's relative position. If the adjacent intersection is located on an extension of the main road, the system will simultaneously fine-tune the green light duration at that intersection according to the preset adjustment logic to prevent new congestion points at adjacent intersections caused by traffic flow optimization at the main intersection.

[0030] As the green light duration is adjusted, the traffic light linkage module simultaneously activates a reverse adjustment mechanism. When the green light duration in one direction is extended, the red light duration in that direction is shortened accordingly, and the duration of the traffic light in the other direction is dynamically adjusted accordingly, ensuring a balanced signal cycle across the intersection and preventing adjustments in a single direction from impacting overall traffic order.

[0031] After this series of coordinated controls, traffic flow at the intersection gradually returned to a smooth state. The system continuously monitors the effectiveness of these adjustments and dynamically optimizes control strategies based on real-time feedback, forming a closed-loop management model encompassing data collection, analysis and prediction, intelligent control, and feedback. This Beidou satellite-based intelligent collaborative management system, through the coordinated collaboration of multiple modules, has achieved an upgrade from single-intersection control to regional traffic network optimization, effectively improving urban traffic efficiency and management precision.

[0032] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the invention can be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims, not the foregoing description, and all variations within the meaning and range of equivalents of the claims are intended to be included therein. Any reference sign in a claim should not be construed as limiting the claim to which it relates.

Claims

1. A multi-terminal positioning intelligent collaborative management system based on Beidou satellites, the system comprising: Beidou traffic flow data collection module, historical traffic demand analysis module, regulation demand analysis module, intersection green light control module, intersection chain control module and traffic light linkage module; The Beidou traffic flow data acquisition module is used to collect vehicle information at intersections, set the collection cycle and monitoring range, and count vehicle information; The historical traffic demand analysis module is used to call historical data, extract historical reference vehicle data, and calculate historical traffic demand; The regulation demand analysis module is used to analyze the impact of traffic prediction and obtain the traffic demand in the next monitoring period; The intersection green light control module is used to monitor congested intersections, analyze green light adjustment needs, and adjust the green light duration; The intersection interlocking control module is used to monitor the congestion situation of adjacent intersections after adjusting the congested intersection and adjust the green light duration of the adjacent intersections; The traffic light linkage module is used to adjust the green light duration while synchronously and reversely adjusting the red light duration.

2. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 1, characterized in that: The BeiDou traffic flow data collection module is based on BeiDou satellites. After authorization, it collects vehicle information and monitors any intersection with a traffic light. The collection cycle duration is set to β, the number of reference collection cycles is set to T, and the most recent collection cycle is set to the Tth collection cycle. In the Tth collection cycle, the total number of vehicles passing through any straight road within the distance α from the intersection is collected. The total number of vehicles is A. T , where the number of vehicles traveling in either direction is a1, and the number of vehicles traveling in the other direction is a2, a1+a2=A T , where the larger value of a1 and a2 is the reference number of vehicles a on any straight road; in the Tth collection cycle, the total number of vehicles passing through another straight road within the range of α from the intersection is collected, and the total number of vehicles is B T , where the number of vehicles traveling in either direction is b1, and the number of vehicles traveling in the other direction is b2, b1+b2=B T , where the larger value of b1 and b2 is the reference number of vehicles b on any straight road T .

3. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 2, characterized in that: The historical traffic demand analysis module is based on the historical data obtained by BeiDou satellites. It calls the monitoring data of any intersection with traffic lights and obtains the total number of vehicles in T reference collection cycles on any straight road as {A1, A2, ..., A t ,…,A T }, where A t Indicates that the total number of vehicles in the tth reference collection cycle on any straight road and the number of reference vehicles in T reference collection cycles on any straight road are {a1, a2, …, a t ,…,a T }, where a t represents the number of reference vehicles in the tth reference collection cycle on any straight road; In the historical data, the number of cycles with two-way congestion is k1, and the number of cycles with one-way congestion is k2. Then the historical traffic demand P of any straight road is calculated. A : ； The same method is used to calculate the historical traffic demand P of another straight road B .

4. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 3, characterized in that: The regulation demand analysis module is based on the multi-terminal positioning function of Beidou satellites. The navigation system predicts that the total number of vehicles passing through any straight road within the distance α from the intersection within the time length β is q A , the total number of vehicles that pass through another straight road within the distance α from the intersection within the time length β is predicted to be q B , and then get the traffic prediction impact degree K of any straight road A =(q A +A T ) / A T , get the traffic prediction impact degree K of another straight road B =(q B +B T ) / B T , the traffic demand of any straight road in the next monitoring period is calculated to be X A =K A *P A , the traffic demand of the other straight road in the next monitoring period is calculated to be X B =K B *P B .

5. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 4, characterized in that: The intersection green light control module monitors any congested intersection and queries the green light duration of any straight lane in the Tth collection cycle as Y. T_A , the green light duration of the other straight lane is Y T_B , calculate the green light adjustment demand F at any intersection: ； Set the adjustment error threshold F0. When F≤F0, set the green light duration of the next collection cycle unchanged; when F>F0, adjust the green light duration.

6. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 5, characterized in that: The method for adjusting the green light duration of the intersection green light control module is: the green light duration of any straight channel is distributed with the green light duration of another straight channel, and the green light duration of any straight channel is adjusted to x=[X A / (X A +X B )]*(Y T_A +Y T_B ), and adjust the green light duration of the other straight lane to y=[X B / (X A +X B )]*(Y T_A +Y T_B ).

7. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 6, characterized in that: After adjusting any congested intersection, the intersection chain control module monitors the congestion situation of the adjacent intersection. If the adjacent intersection is congested, the green light adjustment of the adjacent intersection is performed in the same way; if the adjacent intersection is not congested, the adjacent intersection is adaptively adjusted.

8. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 7, characterized in that: The adaptive adjustment used by the intersection chain control module includes: if the adjacent intersection is on any straight lane of the congested intersection, the green light duration is adjusted to X0+M*(xY T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight lane at the adjacent intersection to Y0+M*(Y T_A -x) / Y T_A *(X0+Y0), where M is the existing intersection adjustment coefficient, X0 represents the original green light duration of the adjacent intersection and the congested intersection on the same road, and Y0 represents the original green light duration of the adjacent intersection and the congested intersection on different roads; if the adjacent intersection is on the other straight lane of the congested intersection, the green light duration is adjusted to X0+M*(yY T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight lane at the adjacent intersection to Y0+M*(Y T_A -y) / Y T_A *(X0+Y0).

9. The BeiDou satellite-based multi-terminal positioning intelligent collaborative management system according to claim 8, characterized in that: When the traffic light linkage module adjusts the duration of the green light, it will also adjust the duration of the red light in the opposite direction.

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