A multi-terminal positioning intelligent collaborative management system based on Beidou satellite

Abstract

The application discloses a multi-terminal positioning intelligent cooperative management system based on Beidou satellites and relates to the technical field of operation and maintenance data intelligent management. The application collects crossroad vehicle information, sets a collection period and a monitoring range, counts vehicle information, calls historical data, extracts historical reference vehicle data, calculates historical traffic demand, analyzes the influence degree of traffic prediction, obtains traffic demand of the next monitoring period, monitors congestion crossroads, analyzes green light adjustment demand, adjusts the green light duration, monitors the congestion of adjacent crossroads after adjusting the congestion crossroads, adjusts the green light duration of the adjacent crossroads, and is used for synchronously and reversely adjusting the red light duration while adjusting the green light duration. The application accurately analyzes the traffic demand of each direction, monitors the traffic conditions of adjacent crossroads, and is adaptively adjusted to avoid the transfer of traffic pressure, so that the traffic operation of the whole region is more smooth.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology for operation and maintenance data, specifically a multi-terminal positioning intelligent collaborative management system based on the BeiDou satellite system. Background Technology

[0002] Currently, urban traffic congestion is becoming increasingly severe, causing considerable inconvenience to citizens. Traditional traffic management methods mainly rely on fixed-duration traffic light settings, which are difficult to adjust flexibly according to real-time traffic flow. Under this model, traffic signals cannot adapt to changes in traffic flow during peak and off-peak hours, often resulting in traffic congestion in some directions while other directions remain idle, leading to low road resource utilization and exacerbating traffic congestion. Although existing traffic management systems have incorporated some intelligent technologies, they have significant shortcomings in data collection and analysis. Some systems do not collect comprehensive traffic information, only obtaining traffic flow data from a few intersections, making it difficult to grasp the overall traffic situation in the entire area. Furthermore, the data analysis phase often relies on simple statistics, failing to deeply explore the potential value of historical and real-time data, resulting in weak predictive capabilities for future traffic flow and difficulty in achieving precise traffic control. In addition, most traffic management systems lack a coordinated and collaborative mechanism. Traffic signals at each intersection operate independently. When congestion occurs at one intersection and the traffic lights are adjusted, adjacent intersections cannot respond in time, which can easily cause traffic pressure to shift and the congestion area to expand. This management model cannot achieve overall optimization of regional traffic and restricts the improvement of urban traffic efficiency. Summary of the Invention

[0003] The purpose of this invention is to provide a multi-terminal positioning intelligent collaborative management system based on BeiDou satellites to solve the problems mentioned in the background art.

[0004] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a multi-terminal positioning intelligent collaborative management system based on Beidou satellite, comprising: a Beidou traffic flow data acquisition module, a historical traffic demand analysis module, a regulation demand analysis module, an intersection green light control module, an intersection interlocking control module, and a traffic light linkage module;

[0005] The Beidou vehicle flow data acquisition module is used to collect vehicle information at intersections, set the collection cycle and monitoring range, and collect vehicle information.

[0006] The historical traffic demand analysis module is used to call historical data, extract historical reference vehicle data, and calculate historical traffic demand.

[0007] The adjustment demand analysis module is used to analyze the impact of traffic forecast and determine the traffic demand for the next monitoring cycle.

[0008] The intersection green light control module is used to monitor congested intersections, analyze green light adjustment needs, and adjust the green light duration.

[0009] The intersection interlocking control module is used to monitor the congestion of adjacent intersections after adjusting the congested intersections, and to adjust the green light duration of adjacent intersections.

[0010] The traffic light linkage module is used to simultaneously adjust the red light duration in the opposite direction while adjusting the green light duration.

[0011] Furthermore, the BeiDou traffic flow data acquisition module, based on the BeiDou satellite, collects vehicle information after authorization. It monitors any intersection with traffic lights, sets the collection cycle duration to β, the number of reference collection cycles to T, and the most recent collection cycle to the Tth collection cycle. In the Tth collection cycle, it collects the total number of vehicles passing within a distance α from any straight road and intersection, and the total number of vehicles is A. T Let a1 be the number of vehicles traveling in any direction and a2 be the number of vehicles traveling in the opposite direction, then a1 + a2 = A. T The larger of a1 and a2 is the reference number 'a' of any straight road; in the T-th collection period, the total number of vehicles passing through the intersection within a distance 'α' of another straight road is collected, and the total number of vehicles is B. T Let b1 be the number of vehicles traveling in any direction and b2 be the number of vehicles traveling in the other direction, then b1 + b2 = B. T The larger of b1 and b2 is the reference number of vehicles for any straight road, b. T The Beidou traffic flow data acquisition module can efficiently monitor traffic flow at intersections. It accurately acquires vehicle information near intersections and provides intuitive references for traffic management by analyzing traffic flow in different directions. This module helps to grasp the real-time traffic situation at intersections, promptly detect potential congestion, and provide a basis for adjusting traffic light timings, making traffic management more targeted. Simultaneously, its continuously collected data helps to analyze traffic flow patterns, providing support for road planning and traffic flow optimization, improving the scientific and effective nature of overall traffic management, making intersections smoother, and creating a more convenient traffic environment for citizens.

[0012] Furthermore, the historical traffic demand analysis module, based on historical data obtained through the BeiDou satellite system, calls upon monitoring data from any intersection with traffic lights to obtain the total number of vehicles {A1, A2, ..., A...} over T reference collection periods on any straight-ahead road. t ,…,A T}, where A t This indicates that the total number of vehicles in the t-th reference collection period on any straight road, and the number of reference vehicles in the T-th reference collection period on any straight road are {a1, a2, ..., at ,…,a T}, where a t This represents the number of reference vehicles in the t-th reference data collection period on any straight road.

[0013] In historical data, the number of cycles with two-way congestion is k1, and the number of cycles with one-way congestion is k2. The historical traffic demand P for any straight-ahead road is then calculated. A :

[0014] ;

[0015] The historical traffic demand P for another straight road was calculated using the same method. B The historical traffic demand analysis module can deeply mine the value of historical traffic flow data collected by BeiDou satellites at intersections. It can systematically analyze vehicle traffic conditions across different periods, accurately identify the frequency of two-way and one-way congestion, and thus quantify historical road traffic demand. By analyzing long-term data patterns, this module can provide a scientific basis for traffic management: it can assist in optimizing traffic light timing to make intersections smoother, and it can support planning decisions such as road widening and lane addition, fundamentally alleviating historical congestion problems. Furthermore, its summary of historical congestion patterns can provide a reference for real-time congestion warnings and future traffic trend predictions, helping to improve the scientific and forward-looking nature of the overall transportation system and creating a more orderly traffic environment for citizens.

[0016] Furthermore, the demand analysis module, based on the multi-terminal positioning function of the BeiDou satellite, predicts the total number of vehicles q within a time period β that pass through any straight road and intersection within a distance α. A The predicted total number of vehicles that pass through the intersection within a distance α from another straight road within a time period β is q. B This allows us to obtain the traffic prediction impact K for any straight road. A =(q A +A T ) / A T The predicted impact K of traffic flow on another straight road is obtained. B =(q B +B T ) / B T The traffic demand for any straight road in the next monitoring period is calculated as X. A =K A *P A The traffic demand for the other straight road in the next monitoring period is calculated to be X. B =K B *P BThe demand analysis module, leveraging the multi-terminal positioning capabilities of the BeiDou satellite system and the predictive functions of the navigation system, can accurately estimate the number of vehicles passing through intersections within a short period. This module combines the predicted traffic flow with currently collected real-time traffic data, and incorporates historical traffic demand analysis results to dynamically calculate and scientifically assess road traffic pressure for the next cycle. Its advantage lies in its ability to anticipate traffic flow trends, providing a dynamic basis for traffic management adjustments: it can assist in optimizing traffic light timing schemes, making the allocation of intersection resources more rational, and it can also predict congestion risks in advance, providing forward-looking references for road management and planning decisions. This effectively improves the traffic system's adaptability to traffic flow fluctuations, making urban road traffic more efficient and intelligent.

[0017] Furthermore, the intersection green light control module monitors any congested intersection. Congestion 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 congested, and the green light duration Y for any straight-ahead lane in the Tth data collection period is queried. T_A The green light duration for the other straight-ahead lane is Y. T_B Calculate the green light adjustment demand F at any intersection:

[0018] ;

[0019] A threshold F0 is set for the adjustment error. When F ≤ F0, the green light duration for the next data collection cycle remains unchanged; when F > F0, the green light duration is adjusted. The intersection green light control module can intelligently optimize intersection traffic efficiency. It can monitor the green light duration of congested intersections in real time, and accurately calculate the green light adjustment needs by combining historical traffic demand and predicted traffic flow data. When a deviation is detected between the current green light timing and actual traffic demand, the module will automatically activate the adjustment mechanism to reasonably adjust the green light duration for different directions; if the deviation is within a reasonable range, the existing timing will be maintained to avoid frequent adjustments. This dynamic control method allows the green light duration to better match traffic flow changes, effectively alleviating intersection congestion, reducing vehicle waiting time, and improving road capacity. It also supports regional traffic coordination control and priority passage for special vehicles, making urban traffic management smarter and more efficient.

[0020] Furthermore, the method by which the intersection green light control module adjusts the green light duration is as follows: the green light duration of any straight-ahead lane and the green light duration of another straight-ahead lane are allocated, so that the green light duration of any straight-ahead lane is adjusted to x=[X A / (X A +X B )]*(Y T_A +Y T_B ), adjust the green light duration of the other straight lane to y=[X B / (X A +XB )]*(Y T_A +Y T_B The intersection interlocking control module adjusts the traffic flow at any congested intersection and then monitors the congestion at adjacent intersections. If the adjacent intersection is congested, the green light at the adjacent intersection is adjusted in the same way; if the adjacent intersection is not congested, the green light at the adjacent intersection is adjusted accordingly.

[0021] Furthermore, the adaptive adjustment used by the intersection interlocking control module includes: if an adjacent intersection is on any straight-ahead lane of a 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-ahead lane at the adjacent intersection to Y0+M*(Y T_A -x) / Y T_A *(X0+Y0), where M is the pre-set intersection adjustment coefficient, X0 represents the original green light duration when the adjacent intersection and the congested intersection are on the same road, and Y0 represents the original green light duration when the adjacent intersection and the congested intersection are not on the same road; if the adjacent intersection is on another straight-ahead lane of the congested intersection, the green light duration will be adjusted to X0+M*(yY). T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight-ahead 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 green light duration based on real-time traffic demand. By allocating green light time in both directions proportionally, it better matches timing with traffic flow pressure, avoiding resource waste. Building upon this, the intersection interlocking control module can coordinate with adjacent intersections for collaborative optimization: if adjacent intersections are congested, the same logic is used to adjust green light duration; if not congested, adaptive fine-tuning is implemented based on the adjustment magnitude and direction of the congested intersection, combined with the intersection adjustment coefficient, to ensure smooth traffic flow between adjacent roads. This control mode achieves precise timing at individual intersections and, through the coordinated response of adjacent intersections, forms a regional traffic signal coordination mechanism, effectively alleviating regional congestion, improving the overall traffic efficiency of the road network, and making urban traffic operation more intelligent and orderly.

[0022] Furthermore, the traffic light linkage module adjusts the duration of the red light in sync with the duration of the green light.

[0023] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: Firstly, it precisely regulates traffic flow. By collecting real-time vehicle information at intersections and combining it with historical data and traffic forecasts, the system can accurately analyze traffic demand in each direction. Based on this, it dynamically adjusts the green light duration, allowing vehicles to pass through intersections efficiently, avoiding long waits caused by unreasonable signal settings, effectively alleviating traffic congestion, and improving road traffic efficiency.

[0024] On the one hand, it enables coordinated management of intersections. When congestion occurs at one intersection and the green light duration is adjusted, the system automatically monitors the traffic conditions at adjacent intersections. If the adjacent intersections are congested, the green light is adjusted in the same way; if there is no congestion, adaptive adjustments are made. This chain-reaction control mechanism avoids the transfer of traffic pressure, making traffic operation in the entire area more balanced and smooth.

[0025] On the other hand, it innovates traffic management models. Relying on BeiDou satellite technology, the system integrates multi-terminal data resources, transforming traditional passive traffic management into proactive intelligent control. Through in-depth mining and analysis of traffic data, it provides traffic management departments with scientific decision-making support, promoting the transformation of traffic management from experience-driven to data-driven, and contributing to the construction of a new smart transportation ecosystem. Attached Figure Description

[0026] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0027] Figure 1 This is a structural diagram of a multi-terminal positioning intelligent collaborative management system based on the BeiDou satellite system according to the present invention. Detailed Implementation

[0028] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0029] Please see Figure 1 The present invention provides a technical solution: a multi-terminal positioning intelligent collaborative management system based on Beidou satellite, including: a Beidou traffic flow data acquisition module, a historical traffic demand analysis module, a regulation demand analysis module, an intersection green light control module, an intersection interlocking control module, and a traffic light linkage module;

[0030] The Beidou vehicle flow data acquisition module is used to collect vehicle information at intersections, set the collection cycle and monitoring range, and collect vehicle information statistics.

[0031] The historical traffic demand analysis module is used to call up historical data, extract historical reference vehicle data, and calculate historical traffic demand.

[0032] The demand analysis module is used to analyze the impact of traffic forecasts and determine the traffic demand for the next monitoring period.

[0033] The intersection green light control module is used to monitor congested intersections, analyze green light adjustment needs, and adjust the green light duration.

[0034] The intersection interlocking control module is used to monitor the congestion situation of adjacent intersections after adjusting congested intersections, and adjust the green light duration of adjacent intersections accordingly.

[0035] The traffic light linkage module is used to simultaneously adjust the red light duration in the opposite direction while adjusting the green light duration.

[0036] The BeiDou traffic flow data acquisition module, based on the BeiDou satellite, collects vehicle information after authorization. It monitors any intersection with traffic lights, setting the acquisition cycle duration to β, the number of reference acquisition cycles to T, and the most recent acquisition cycle to the T-th acquisition cycle. In the T-th acquisition cycle, it collects the total number of vehicles passing within a distance α from any straight road to the intersection, denoted as A. T Let a1 be the number of vehicles traveling in any direction and a2 be the number of vehicles traveling in the opposite direction, then a1 + a2 = A. T The larger of a1 and a2 is the reference number 'a' of any straight road; in the T-th collection period, the total number of vehicles passing through the intersection within a distance 'α' of another straight road is collected, and the total number of vehicles is B. T Let b1 be the number of vehicles traveling in any direction and b2 be the number of vehicles traveling in the other direction, then b1 + b2 = B. T The larger of b1 and b2 is the reference number of vehicles for any straight road, b. T The Beidou traffic flow data acquisition module can efficiently monitor traffic flow at intersections. It accurately acquires vehicle information near intersections and provides intuitive references for traffic management by analyzing traffic flow in different directions. This module helps to grasp the real-time traffic situation at intersections, promptly detect potential congestion, and provide a basis for adjusting traffic light timings, making traffic management more targeted. Simultaneously, its continuously collected data helps to analyze traffic flow patterns, providing support for road planning and traffic flow optimization, improving the scientific and effective nature of overall traffic management, making intersections smoother, and creating a more convenient traffic environment for citizens.

[0037] The historical traffic demand analysis module, based on historical data obtained via BeiDou satellite, calls upon monitoring data from any intersection with traffic lights to obtain the total number of vehicles {A1, A2, ..., A...} over T reference collection periods on any straight-ahead road. t ,…,A T}, where A t This indicates that the total number of vehicles in the t-th reference collection period on any straight road, and the number of reference vehicles in the T-th reference collection period on any straight road are {a1, a2, ..., a t ,…,a T}, where a t This represents the number of reference vehicles in the t-th reference data collection period on any straight road.

[0038] In historical data, the number of cycles with two-way congestion is k1, and the number of cycles with one-way congestion is k2. The historical traffic demand P for any straight-ahead road is then calculated. A :

[0039] ;

[0040] The historical traffic demand P for another straight road was calculated using the same method. B The historical traffic demand analysis module can deeply mine the value of historical traffic flow data collected by BeiDou satellites at intersections. It can systematically analyze vehicle traffic conditions across different periods, accurately identify the frequency of two-way and one-way congestion, and thus quantify historical road traffic demand. By analyzing long-term data patterns, this module can provide a scientific basis for traffic management: it can assist in optimizing traffic light timing to make intersections smoother, and it can support planning decisions such as road widening and lane addition, fundamentally alleviating historical congestion problems. Furthermore, its summary of historical congestion patterns can provide a reference for real-time congestion warnings and future traffic trend predictions, helping to improve the scientific and forward-looking nature of the overall transportation system and creating a more orderly traffic environment for citizens.

[0041] The demand analysis module, based on the multi-terminal positioning function of the BeiDou satellite, predicts the total number of vehicles (q) within a time period β that will pass through any straight road and intersection within a distance α. A The predicted total number of vehicles that pass through the intersection within a distance α from another straight road within a time period β is q. B This allows us to obtain the traffic prediction impact K for any straight road. A =(q A +A T ) / A T The predicted impact K of traffic flow on another straight road is obtained. B =(q B +B T ) / BT The traffic demand for any straight road in the next monitoring period is calculated as X. A =K A *P A The traffic demand for the other straight road in the next monitoring period is calculated to be X. B =K B *P B The demand analysis module, leveraging the multi-terminal positioning capabilities of the BeiDou satellite system and the predictive functions of the navigation system, can accurately estimate the number of vehicles passing through intersections within a short period. This module combines the predicted traffic flow with currently collected real-time traffic data, and incorporates historical traffic demand analysis results to dynamically calculate and scientifically assess road traffic pressure for the next cycle. Its advantage lies in its ability to anticipate traffic flow trends, providing a dynamic basis for traffic management adjustments: it can assist in optimizing traffic light timing schemes, making the allocation of intersection resources more rational, and it can also predict congestion risks in advance, providing forward-looking references for road management and planning decisions. This effectively improves the traffic system's adaptability to traffic flow fluctuations, making urban road traffic more efficient and intelligent.

[0042] Furthermore, the intersection green light control module monitors any congested intersection. Congestion 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 congested, and the green light duration Y for any straight-ahead lane in the Tth data collection period is queried. T_A The green light duration for the other straight-ahead lane is Y. T_B Calculate the green light adjustment demand F at any intersection:

[0043] ;

[0044] A threshold F0 is set for the adjustment error. When F ≤ F0, the green light duration for the next data collection cycle remains unchanged; when F > F0, the green light duration is adjusted. The intersection green light control module can intelligently optimize intersection traffic efficiency. It can monitor the green light duration of congested intersections in real time, and accurately calculate the green light adjustment needs by combining historical traffic demand and predicted traffic flow data. When a deviation is detected between the current green light timing and actual traffic demand, the module will automatically activate the adjustment mechanism to reasonably adjust the green light duration for different directions; if the deviation is within a reasonable range, the existing timing will be maintained to avoid frequent adjustments. This dynamic control method allows the green light duration to better match traffic flow changes, effectively alleviating intersection congestion, reducing vehicle waiting time, and improving road capacity. It also supports regional traffic coordination control and priority passage for special vehicles, making urban traffic management smarter and more efficient.

[0045] The method by which the intersection green light control module adjusts the green light duration is as follows: The green light duration of any straight-ahead lane and the green light duration of another straight-ahead lane are allocated, and the green light duration of any straight-ahead lane is adjusted to x = [X]. A / (X A +X B )]*(Y T_A +Y T_B ), adjust the green light duration of the other straight lane to y=[X B / (X A +X B )]*(Y T_A +Y T_B The intersection interlocking control module adjusts the traffic flow at any congested intersection and then monitors the congestion at adjacent intersections. If the adjacent intersection is congested, the green light at the adjacent intersection is adjusted in the same way; if the adjacent intersection is not congested, the green light at the adjacent intersection is adjusted accordingly.

[0046] The adaptive adjustments used in the intersection interlocking control module include: if an adjacent intersection is on any straight-ahead lane of a congested intersection, the green light duration will be adjusted to X0 + M * (xY). T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight-ahead lane at the adjacent intersection to Y0+M*(Y T_A -x) / Y T_A *(X0+Y0), where M is the pre-set intersection adjustment coefficient, X0 represents the original green light duration when the adjacent intersection and the congested intersection are on the same road, and Y0 represents the original green light duration when the adjacent intersection and the congested intersection are not on the same road; if the adjacent intersection is on another straight-ahead lane of the congested intersection, the green light duration will be adjusted to X0+M*(yY). T_A ) / Y T_A *(X0+Y0), adjust the green light duration of the other straight-ahead 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 green light duration based on real-time traffic demand. By allocating green light time in both directions proportionally, it better matches timing with traffic flow pressure, avoiding resource waste. Building upon this, the intersection interlocking control module can coordinate with adjacent intersections for collaborative optimization: if adjacent intersections are congested, the same logic is used to adjust green light duration; if not congested, adaptive fine-tuning is implemented based on the adjustment magnitude and direction of the congested intersection, combined with the intersection adjustment coefficient, to ensure smooth traffic flow between adjacent roads. This control mode achieves precise timing at individual intersections and, through the coordinated response of adjacent intersections, forms a regional traffic signal coordination mechanism, effectively alleviating regional congestion, improving the overall traffic efficiency of the road network, and making urban traffic operation more intelligent and orderly.

[0047] The traffic light linkage module adjusts the duration of the red light in sync with the duration of the green light.

[0048] Example 1: Within a traffic monitoring area, a data acquisition module authorized by the BeiDou satellite system continuously monitors the intersection's dynamics. On the straight-ahead road within a certain range of the intersection, the system captures the real-time traffic flow of vehicles, collecting traffic flow data from both directions at fixed intervals. This data is synchronously transmitted to the backend, providing basic support for subsequent traffic control.

[0049] The historical traffic demand analysis module was then activated, retrieving traffic flow records from multiple past periods at the intersection. The system performed in-depth analysis of the historical data: during past monitoring periods, the intersection had repeatedly experienced two-way traffic saturation, as well as instances of slow one-way traffic. By categorizing and statistically analyzing these historical conditions, the module can accurately assess the long-term traffic pressure distribution at the intersection, providing a reference for current traffic control decisions.

[0050] Meanwhile, the navigation system predicts traffic flow for the next cycle based on real-time traffic conditions and multi-terminal positioning information. The predictions show a significant increase in traffic flow along main roads, while traffic flow towards commercial districts is also trending upwards. The demand analysis module combines measured and predicted data from the current cycle to comprehensively assess the changing trends in traffic pressure in both directions, clarifying the potential fluctuations in traffic demand for each direction in the next cycle.

[0051] Based on the above analysis results, the intersection green light control module assesses the current green light duration. The system compares historical traffic demand and predicted impact levels for both straight-ahead directions to calculate the required adjustment of the green light duration. When the adjustment requirement exceeds a preset reasonable range, the module activates an optimization mechanism: based on the traffic demand ratio of the two directions, the green light duration is reallocated. If the traffic demand on the main road is higher, the green light time for that direction is appropriately extended to alleviate traffic congestion.

[0052] After the green light duration adjustment is completed, the intersection interlocking control module begins monitoring the status of adjacent intersections. If abnormal traffic flow is detected at an adjacent intersection due to the adjustment of the main intersection, the system will implement adaptive control based on the positional relationship between the adjacent intersection and the main intersection. When the adjacent intersection is located on the extension line of the main road, the system will simultaneously fine-tune the green light duration of that intersection according to the preset adjustment logic to avoid the optimization of traffic flow at the main intersection causing new congestion points at the adjacent intersection.

[0053] While the green light duration is adjusted, the traffic light linkage module simultaneously activates a reverse adjustment mechanism. When the green light time in one direction is extended, the red light time in that direction is shortened accordingly, and the traffic light duration in the other direction is also dynamically adjusted to ensure that the signal cycle of the entire intersection remains balanced and to avoid affecting the overall traffic order of the intersection due to adjustments in a single direction.

[0054] After a series of coordinated adjustments, traffic flow at the intersection gradually returned to normal. The system continuously monitors the effects of the adjustments and dynamically optimizes the control strategies based on real-time feedback data, forming a closed-loop management model of data collection, analysis and prediction, intelligent control, and effect feedback. This intelligent collaborative management system based on the BeiDou satellite system, through the coordinated operation of multiple modules, has upgraded from single-intersection control to regional traffic network optimization, effectively improving urban traffic efficiency and management accuracy.

[0055] 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 implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A multi-terminal positioning intelligent collaborative management system based on BeiDou satellite, the system comprising: The system includes a Beidou traffic flow data acquisition module, a historical traffic demand analysis module, a regulation demand analysis module, an intersection green light control module, an intersection interlocking control module, and a traffic light timing linkage module. The Beidou vehicle flow data acquisition module is used to collect vehicle information at intersections, set the collection cycle and monitoring range, and collect 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 adjustment demand analysis module is used to analyze the impact of traffic forecast and determine the traffic demand for the next monitoring cycle. 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 of adjacent intersections after adjusting the congested intersections, and to adjust the green light duration of adjacent intersections. The traffic light linkage module is used to simultaneously adjust the red light duration in the opposite direction while adjusting the green light duration. The BeiDou traffic flow data acquisition module, based on the BeiDou satellite, collects vehicle information after authorization. It monitors any intersection with traffic lights, setting the acquisition cycle duration to β, the number of reference acquisition cycles to T, and the most recent acquisition cycle to the T-th acquisition cycle. In the T-th acquisition cycle, it collects the total number of vehicles passing within a distance α from any straight road to the intersection, denoted as A. T Let a1 be the number of vehicles traveling in any direction and a2 be the number of vehicles traveling in the opposite direction, then a1 + a2 = A. T The larger of a1 and a2 is the reference number 'a' of any straight road; in the T-th collection period, the total number of vehicles passing through the intersection within a distance 'α' of another straight road is collected, and the total number of vehicles is B. T Let b1 be the number of vehicles traveling in any direction and b2 be the number of vehicles traveling in the other direction, then b1 + b2 = B. T The larger of b1 and b2 is the reference number of vehicles for any straight road, b. T ; The historical traffic demand analysis module, based on historical data obtained via BeiDou satellite, calls upon monitoring data from any intersection with traffic lights to obtain the total number of vehicles {A1, A2, ..., A...} over T reference collection periods on any straight-ahead road. t ,…,A T }, where A t Let represent the total number of vehicles in the t-th reference data collection period on any straight road, and let {a1, a2, ..., a} represent the number of reference vehicles in the T-th reference data collection period on any straight road. t ,…,a T }, where a t This represents the number of reference vehicles in the t-th reference data collection period on any straight road. In historical data, the number of cycles with two-way congestion is k1, and the number of cycles with one-way congestion is k2. The historical traffic demand P for any straight-ahead road is then calculated. A : ； The historical traffic demand P for another straight road was calculated using the same method. B .

2. The intelligent collaborative management system for multi-terminal positioning based on BeiDou satellite as described in claim 1, characterized in that: The demand analysis module, based on the multi-terminal positioning function of the BeiDou satellite, predicts the total number of vehicles (q) within a time period β that will pass through any straight road and intersection within a distance α. A The predicted total number of vehicles that pass through the intersection within a distance α from another straight road within a time period β is q. B This allows us to obtain the traffic prediction impact K for any straight road. A =(q A +A T ) / A T The predicted impact K of traffic flow on another straight road is obtained. B =(q B +B T ) / B T The traffic demand for any straight road in the next monitoring period is calculated as X. A =K A P A The traffic demand for the other straight road in the next monitoring period is calculated to be X. B =K B P B .

3. The intelligent collaborative management system for multi-terminal positioning based on BeiDou satellite as described in claim 2, characterized in that: The intersection green light control module monitors any congested intersection and queries the green light duration Y for any straight-ahead lane in the Tth data collection period. T_A The green light duration for the other straight-ahead lane is Y. T_B Calculate the green light adjustment demand F at any intersection: ； Set the adjustment error threshold F0. When F≤F0, the green light duration for the next collection cycle remains unchanged; when F>F0, the green light duration is adjusted.

4. The multi-terminal positioning intelligent collaborative management system based on BeiDou satellite as described in claim 3, characterized in that: The method by which the intersection green light control module adjusts the green light duration is as follows: The green light duration of any straight-ahead lane and the green light duration of another straight-ahead lane are allocated, and the green light duration of any straight-ahead lane is adjusted to x = [X...]. A / (X A +X B )] (Y T_A +Y T_B ), adjust the green light duration of the other straight lane to y=[X B / (X A +X B )] (Y T_A +Y T_B ).

5. The multi-terminal positioning intelligent collaborative management system based on BeiDou satellite as described in claim 4, characterized in that: After adjusting any congested intersection, the intersection interlocking control module monitors the congestion of adjacent intersections. If the adjacent intersection is congested, it adjusts the green light of the adjacent intersection in the same way; if the adjacent intersection is not congested, it makes adaptive adjustments to the adjacent intersection.

6. The intelligent collaborative management system for multi-terminal positioning based on BeiDou satellite as described in claim 5, characterized in that: The adaptive adjustments used in the intersection interlocking control module include: if an adjacent intersection is on any straight-ahead lane of a congested intersection, the green light duration will be adjusted to X0+M. (xY T_A ) / Y T_A (X0+Y0), adjust the green light duration of the other straight-ahead lane at the adjacent intersection to Y0+M. (Y T_A -x) / Y T_A (X0+Y0), where M is the pre-set intersection adjustment coefficient, X0 represents the original green light duration when the adjacent intersection and the congested intersection are on the same road, and Y0 represents the original green light duration when the adjacent intersection and the congested intersection are not on the same road; if the adjacent intersection is on another straight-ahead lane of the congested intersection, the green light duration will be adjusted to X0+M. (yY T_A ) / Y T_A (X0+Y0), adjust the green light duration of the other straight-ahead lane at the adjacent intersection to Y0+M. (Y T_A -y) / Y T_A (X0+Y0).

7. The multi-terminal positioning intelligent collaborative management system based on BeiDou satellite as described in claim 6, characterized in that: The traffic light linkage module adjusts the duration of the red light in sync with the duration of the green light.

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