Traffic congestion alleviation method and system based on road network coordinated control
By constructing a road network and interconnected traffic circles, and optimizing traffic management strategies, the congestion problem caused by the rigid coordination of the road network has been solved, and the efficiency of urban road traffic has been improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- INTELLIGENT INTER CONNECTION TECH CO LTD
- Filing Date
- 2026-03-11
- Publication Date
- 2026-06-19
Smart Images
Figure CN122245096A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of traffic management technology, specifically to a method and system for alleviating traffic congestion based on road network coordination control. Background Technology
[0002] Currently, urban road traffic signal control mainly adopts single-point timing control, which relies solely on historical traffic flow data of individual intersections to pre-set fixed timing schemes. This lack of dynamic adjustment based on real-time traffic flow fluctuations often makes it difficult to alleviate sudden congestion at intersections in a timely manner. As urban road network density continues to increase, the mutual influence between intersections becomes increasingly complex, highlighting the limitations of traditional control methods. When congestion occurs at a central intersection, due to a lack of accurate assessment of the impact on surrounding intersections and their paths, existing signal systems often can only implement localized, passive control measures. This not only fails to prevent congestion from spreading to surrounding road networks but may even exacerbate local traffic pressure due to the control direction contradicting the actual direction of traffic flow, leading to a decrease in overall road network efficiency and a significant increase in travel delays.
[0003] In summary, existing technologies suffer from technical problems such as isolated traffic signal control ranges, rigid coordination relationships, and single control dimensions, leading to poor congestion management and even negative effects, which further affect the overall traffic efficiency of the road network. Summary of the Invention
[0004] The purpose of this application is to provide a traffic congestion mitigation method and system based on road network coordinated control, in order to solve the technical problems in the prior art, which are that the traffic signal control range is isolated, the coordination relationship is rigid and the control dimension is single, resulting in poor congestion handling effect or even negative effects, which further affect the overall traffic efficiency of the road network.
[0005] To achieve the above objectives, this application provides a traffic congestion mitigation method and system based on road network coordinated control.
[0006] Firstly, this application provides a traffic congestion mitigation method based on road network coordination control. This method is implemented through a traffic congestion mitigation system based on road network coordination control. The method includes: analyzing traffic relationships between road networks to construct a traffic relationship road network, including road network connection numbers and associated traffic circles; obtaining associated traffic monitoring data packets for the associated traffic circles through the traffic relationship road network; optimizing traffic congestion strategies based on the associated traffic monitoring data packets and the correlation coefficients between central intersections and corresponding intersections within the circles to generate traffic diversion strategies; and locating the target intersection set of the associated traffic circles based on the traffic diversion strategies to generate traffic light control instructions.
[0007] Optionally, the following steps are taken: First, obtain intersection topology and traffic detection data. Second, perform time alignment, spatial mapping, and anomaly removal on the multi-source data to form a temporal state vector for each intersection. Third, construct a candidate intersection pair set based on topological adjacency, path sharing, and data correlation. Fourth, based on the temporal state vector, perform intersection data propagation association analysis on each candidate intersection pair to obtain the road-gateway connection number. Fifth, construct a traffic relationship road network using intersections as nodes and the road network association relationships between candidate intersection pairs as edges, and store the road-gateway connection number as an edge attribute. Sixth, based on the traffic relationship road network, use the central intersection as a seed node to perform association expansion on the traffic relationship road network to construct an associated traffic circle.
[0008] Optionally, based on the temporal state vectors of candidate intersection pairs, traffic flow propagation time delay analysis and propagation intensity calculation are performed to obtain the propagation impact coefficient; based on the queue length, occupancy rate, or speed changes of candidate intersection pairs, spillover event detection is performed, and the spillover congestion coefficient is obtained through upstream intersection congestion consistency analysis; based on the congestion state differential changes of candidate intersection pairs and detour cost correction analysis, the alternative diversion coefficient is obtained; based on the historical control response, the control response relationship of candidate intersection pairs is analyzed to obtain the controllable coupling coefficient; based on the propagation impact coefficient, spillover congestion coefficient, alternative diversion coefficient, and controllable coupling coefficient, the road-gateway connection coefficient is obtained.
[0009] Optionally, based on the traffic relationship road network, a propagation circle is constructed along the traffic flow propagation relationship in the traffic relationship road network, and a replacement circle is constructed along the alternative diversion relationship in the traffic relationship road network; according to the topological hop number between intersections, detour cost and road carrying capacity, the propagation circle and replacement circle are hierarchically divided to form a multi-gradient associated traffic circle.
[0010] Optionally, the associated traffic monitoring data package includes one or more of the following: traffic flow, average vehicle speed, queue length, road occupancy, signal timing parameters, and road capacity information at each intersection within the associated traffic circle.
[0011] Optionally, based on the congestion status of the central intersection and the traffic status of intersections within the associated traffic circle, and combined with the road gateway connection number, the associated intersections are weighted and evaluated; the control priority and control range of different intersections are determined based on the weight evaluation results; and a traffic diversion strategy is generated based on the control priority and control range.
[0012] Optionally, based on the congestion status of the central intersection and the traffic status of intersections at various gradients within the associated traffic circle, and combined with the road gateway connection coefficient, the congestion propagation relationship and alternative diversion relationship between intersections are analyzed to determine the congestion impact propagation path; based on the congestion impact propagation path and the hierarchical relationship of the multi-gradient associated traffic circle, gradient transfer analysis is performed on the associated intersections to determine the control direction and control impact intensity of different gradient intersections; based on the control direction and control impact intensity, a weight evaluation is performed to generate a weight evaluation result.
[0013] Secondly, this application also provides a traffic congestion mitigation system based on road network coordination control, used to execute the traffic congestion mitigation method based on road network coordination control as described in the first aspect. The traffic congestion mitigation system based on road network coordination control includes: a road network analysis module, used to analyze the traffic relationships between road networks and construct a traffic relationship road network, including road network connection numbers and associated traffic circles; a traffic data acquisition module, used to obtain associated traffic monitoring data packets of the associated traffic circles through the traffic relationship road network; a traffic congestion strategy optimization module, used to optimize the traffic congestion strategy based on the associated traffic monitoring data packets and the correlation coefficient between the central intersection and the corresponding intersection within the circle, generating a traffic diversion strategy; and a control instruction generation module, used to locate the target intersection set of the associated traffic circles according to the traffic diversion strategy and generate traffic signal control instructions.
[0014] One or more technical solutions provided in this application have at least the following technical effects or advantages:
[0015] By analyzing the traffic relationships between road networks, a traffic relationship road network is constructed, including road network gateway connections and associated traffic circles. Through this traffic relationship road network, associated traffic monitoring data packets for the associated traffic circles are obtained. Based on these associated traffic monitoring data packets, and combined with the correlation coefficient between the central intersection and the corresponding intersection within the circle, traffic congestion strategies are optimized to generate traffic management strategies. Based on these traffic management strategies, the target intersection set of the associated traffic circles is located, and traffic signal control instructions are generated. In other words, by analyzing the traffic relationships between road networks, constructing a traffic relationship road network, obtaining associated traffic monitoring data packets for associated traffic circles, optimizing traffic congestion strategies by combining the correlation coefficient between the central intersection and the corresponding intersection within the circle, generating traffic management strategies, locating the target intersection set of the associated traffic circles, and generating traffic signal control instructions, effective alleviation of urban traffic congestion and improvement of road traffic efficiency are achieved.
[0016] The above description is merely an overview of the technical solution of this application. To better understand the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description
[0017] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.
[0018] Figure 1 This is a flowchart illustrating the traffic congestion mitigation method based on road network coordination control proposed in this application.
[0019] Figure 2 This is a schematic diagram of the traffic congestion mitigation system based on road network coordination control in this application.
[0020] Figure labeling: Road network analysis module 11, traffic data acquisition module 12, traffic congestion strategy optimization module 13, control instruction generation module 14. Detailed Implementation
[0021] This application provides a traffic congestion mitigation method and system based on road network coordinated control. It addresses the technical problems in existing technologies where isolated traffic signal control ranges, rigid coordination relationships, and single control dimensions lead to poor congestion mitigation effects or even negative consequences, further impacting the overall traffic efficiency of the road network. By analyzing traffic relationships between road networks, a traffic relationship road network is constructed, obtaining associated traffic monitoring data packets for related traffic circles. Traffic congestion strategies are optimized by combining the correlation coefficients between central intersections and corresponding intersections within the circles, generating traffic diversion strategies, locating the target intersection set of related traffic circles, and generating traffic signal control instructions. This effectively alleviates urban traffic congestion and improves road traffic efficiency.
[0022] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. It should be understood that this application is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application. It should also be noted that, for ease of description, only the parts related to this application are shown in the accompanying drawings, not all of them.
[0023] Example 1, please refer to the appendix. Figure 1 This application provides a traffic congestion mitigation method based on road network coordination control, wherein the traffic congestion mitigation method based on road network coordination control is applied to a traffic congestion mitigation system based on road network coordination control, and the traffic congestion mitigation method based on road network coordination control specifically includes the following steps:
[0024] S100: Analyze the traffic relationships between road networks and construct a traffic relationship road network, including the number of road gateway connections and associated traffic circles.
[0025] Furthermore, S100 of this application includes: acquiring intersection topology and traffic detection data; performing time alignment, spatial mapping, and anomaly removal on multi-source data to form a temporal state vector for each intersection; constructing a candidate intersection pair set based on topological adjacency, path sharing, and data correlation; performing intersection data propagation association analysis on the candidate intersection pairs based on the temporal state vector to obtain the road gateway connection number; constructing a traffic relationship road network with intersections as nodes and the road network association relationship between candidate intersection pairs as edges, and storing the road gateway connection number as an edge attribute; and constructing an associated traffic circle based on the traffic relationship road network, with the central intersection as the seed node and performing association expansion on the traffic relationship road network.
[0026] Furthermore, this application also includes the following steps: performing traffic flow propagation time delay analysis and propagation intensity calculation based on the temporal state vector of the candidate intersection pair to obtain the propagation influence coefficient; performing spillover event detection based on the queue length, occupancy rate, or speed changes of the candidate intersection pair, and obtaining the spillover congestion coefficient through upstream intersection congestion consistency analysis; obtaining the alternative diversion coefficient based on the congestion state differential change and detour cost correction analysis of the candidate intersection pair; obtaining the controllable coupling coefficient by performing the control response relationship of the candidate intersection pair according to the historical control response; and obtaining the road gateway connection number based on the propagation influence coefficient, spillover congestion coefficient, alternative diversion coefficient, and controllable coupling coefficient.
[0027] Specifically, this involves collecting information on the location, road connections, road lengths, and traffic capacity of all intersections in the urban road network. Simultaneously, it acquires traffic monitoring data for each intersection, including traffic flow, average speed, queue length, road occupancy, and traffic light timing parameters. Intersection topology refers to the spatial geographical location of intersections and the network structure connecting them via roads, such as which intersections are adjacent and the direction of the roads. Traffic monitoring data consists of raw data collected by sensors deployed at intersections, typically including traffic flow, lane occupancy, vehicle speed, and queue length.
[0028] Because the acquisition frequency and reporting time of coil data, radar data, and video detection data may differ by milliseconds or even seconds, a time synchronization service is initiated to calibrate the timestamps of all data according to a unified network time protocol and resample at a fixed period to achieve time alignment. Based on the pre-entered intersection number, approach direction, and lane function of each detector, the cleaned data points are accurately mapped to the corresponding road network nodes. Data that significantly exceeds the threshold or is generated during detector offline periods is marked as invalid and discarded. For each intersection, a time-series state vector is generated, containing parameters such as continuous timestamps, average vehicle speed, traffic flow, lane occupancy rate, and queue length.
[0029] Based on geographic information system data from electronic maps, all intersections are traversed, and intersection pairs with directly connected road segments are directly included in the candidate set. Historical floating car or checkpoint data is retrieved to analyze vehicle trajectories, identifying intersection combinations that, although geographically distant, are frequently passed by the same vehicle in sequence—i.e., path-sharing pairs. Pearson correlation coefficients are calculated on the temporal state vectors of all intersections, and intersection pairs with highly consistent traffic flow or speed trends are selected and included in the candidate set as data-correlated pairs. In short, intersection pairs are selected based on topological adjacency (directly connected intersections); distant intersection pairs are added based on path-sharing degree (vehicles may take the same path); and intersection pairs that may have traffic impacts are further selected based on temporal data correlation. Through these three-stage selections, a comprehensive candidate set of intersection pairs is constructed, covering physical connectivity, actual paths, and statistical correlation.
[0030] For candidate intersection pairs, key parameters are extracted from the time-series state vector, typically traffic flow or lane occupancy rate. For example, for upstream intersection A and downstream intersection B, the time-series data of intersection B is shifted forward or backward on the time axis and correlated with the data of intersection A. The time offset that maximizes the correlation coefficient between the two is identified; this is the time required for traffic flow to propagate from A to B, i.e., the time lag. After determining the time lag, the data segment at this time offset is locked, and a regression model is constructed to calculate the marginal impact of the traffic flow change rate at intersection A on the traffic flow change rate at intersection B, thus obtaining the propagation intensity. The reciprocal of the time lag is multiplied by the propagation intensity or a weighted sum is obtained to get a propagation influence coefficient between 0 and 1. The larger the coefficient, the stronger the dynamic influence of the upstream on the downstream.
[0031] The system acquires real-time queue length data for candidate intersections and their downstream intersections, as well as the length of the road segment connecting the two intersections. A potential spillover event is identified when the ratio of the downstream intersection's queue length to the road segment length consistently exceeds a preset threshold. The system retrieves operational status data for each exit direction of the upstream intersection during the event period. If all exits of the upstream intersection, except those leading to the downstream intersection, are also congested or blocked, or if the overall outbound traffic flow of the upstream intersection drops sharply, the event is confirmed as a spillover event. The frequency and duration of spillover events at this intersection are statistically analyzed over a certain historical period. Combined with the severity of the impact on the upstream intersection in each event, a spillover congestion coefficient is calculated. A higher coefficient indicates a greater risk of downstream congestion causing upstream blockage. Upstream intersection congestion consistency analysis checks whether all exit directions of the upstream intersection are also blocked when a spillover occurs, confirming that the spillover is caused by downstream congestion rather than a problem upstream itself.
[0032] The system monitors the main traffic paths between candidate intersections. When a significant increase in travel time or congestion index is detected on the main path, traffic flow changes on the other path, the potential alternative path, are simultaneously observed. The ratio between the increase in congestion on the main path and the increase in traffic flow on the alternative path is calculated to obtain the initial diversion coefficient. The differential change in congestion status analyzes how traffic volume on surrounding alternative paths changes when congestion occurs on the main path. For example, if congestion on the main road worsens, traffic flow on surrounding side roads increases; this change is the differential change. Simultaneously, the additional detour distance and travel time of the alternative path compared to the main path under normal conditions are calculated, and these detour costs are normalized as a discount factor. If the detour cost is too high, the diversion coefficient will be reduced accordingly. Finally, the initial diversion coefficient is multiplied by the detour cost discount to obtain the alternative diversion coefficient. Detour cost correction considers factors such as the distance and travel time of the alternative path to adjust the diversion effect. If the detour distance is too far, even if the main road is congested, drivers may be unwilling to detour.
[0033] Historical databases were retrieved to collect records of signal timing adjustments made to any intersection within a candidate intersection pair over a past period. For each adjustment event, the changes in key indicators of the intersection before and after the adjustment were analyzed. If the indicators show significant and stable changes in the expected direction after each adjustment, the intersection is considered to have high controllability. The success rate and effect magnitude of all adjustment events were statistically analyzed, and the controllability coefficient of the intersection was obtained after normalization. If the problem involves a pair of intersections, it may be necessary to comprehensively consider the response characteristics of each intersection, or analyze the linkage effect of adjusting one intersection on the other. The controllable coupling coefficient quantifies the ease and effectiveness of controlling the traffic state of the intersection through signal timing adjustments.
[0034] For the same candidate intersection, the calculated propagation impact coefficient, spillover congestion coefficient, alternative diversion coefficient, and controllable coupling coefficient are aggregated. Different weights are assigned to these coefficients based on different business scenario requirements. For example, during peak hours, the propagation impact coefficient and spillover congestion coefficient have higher weights; during off-peak hours, the alternative diversion coefficient has a higher weight. The four coefficients are normalized and then weighted to obtain a final value. This final value, along with the identification identifiers of the two intersections, is stored as a weighted edge in the traffic relationship network database. The road gateway connection coefficient transforms complex traffic impact relationships into measurable indicators, identifies central intersections and their key influencing intersections, and constructs a multi-gradient control layer.
[0035] Furthermore, this application also includes the following steps: based on the traffic relationship road network, constructing a propagation circle along the traffic flow propagation relationship in the traffic relationship road network, and constructing a replacement circle along the alternative diversion relationship in the traffic relationship road network; according to the topological hop count between intersections, detour costs, and road carrying capacity, the propagation circle and replacement circle are hierarchically divided to form a multi-gradient associated traffic circle.
[0036] Specifically, starting from the central intersection in the traffic network, the system expands outwards along the traffic flow propagation relationships, including only intersection pairs with a correlation coefficient higher than a threshold with the central intersection. This expansion continues until the correlation coefficient between the outer intersections and the central intersection falls below the threshold or reaches a preset concentric circle radius. The result is a propagation circle covering key intersections directly or indirectly affected by congestion at the central intersection.
[0037] Similarly, the replacement circle expands along alternative traffic flow relationships, using the central intersection as its core. Unlike the propagation circle, the expansion of the replacement circle does not strictly follow a single direction of travel, but rather focuses on the connectivity and path diversity of the road network. It searches for intersections with at least two independent connecting paths to the central intersection, or those located on critical detour routes. It analyzes multiple routes from the central intersection to the same target intersection via different paths, including those intersections and connecting edges that constitute alternative paths in the replacement circle. The boundary of the replacement circle is typically determined by detour costs or road grade; expansion stops when the detour distance of the alternative path is too long or the road capacity is too low.
[0038] A multi-dimensional quantitative evaluation is performed on each intersection within the propagation and replacement circles. Evaluation dimensions include topology hop count, detour cost, and road capacity margin. Topology hop count is calculated by taking the shortest path from the intersection to the central intersection within the road network; fewer hops indicate a higher level. Detour cost: For intersections within the replacement circle, the additional travel time or distance of the alternative path relative to the main path is calculated; lower costs indicate a more convenient alternative path, higher replacement value, and potentially a higher level. Road capacity margin is assessed by evaluating the current idle capacity of the intersection; a larger capacity margin means it is better able to receive vehicles diverted from the central intersection, resulting in a higher level. After normalizing the values of these three dimensions, all intersections within the circle are divided into three or more gradients using preset threshold ranges. For example, intersections with a travel time of one hop or less, a detour cost of less than two minutes, and a capacity margin of more than 30% are classified as the first tier, i.e., the core coordination layer; intersections with a travel time of two to three hops and a moderate detour cost are classified as the second tier, i.e., the close coordination layer; and the rest are classified as the third tier, i.e., the impact and concern layer. This final set of intersections with hierarchical labels constitutes the multi-tiered traffic circle. The multi-tiered traffic circle divides all intersections within the propagation and replacement circles into different tiers, such as the core layer, close layer, and impact layer, based on their influence on the central intersection, spatial distance, or functional attributes. Intersections of different tiers will receive different priorities and control in subsequent control strategies.
[0039] By dividing the intersection into multi-tiered levels of propagation and replacement zones, the degree to which each intersection is affected by the central intersection is clearly defined. The inner layer focuses on key control, the middle layer provides auxiliary guidance, and the outer layer monitors, forming a hierarchical control strategy. By combining detour costs and road capacity, vehicles are guided to roads with sufficient capacity to avoid secondary congestion.
[0040] S200: Obtain the associated traffic monitoring data packet of the associated traffic circle through the traffic relationship road network.
[0041] Furthermore, S200 of this application includes: the associated traffic monitoring data package includes one or more of the following: traffic flow, average vehicle speed, queue length, road occupancy, signal timing parameters, and road capacity information of each intersection within the associated traffic circle.
[0042] Specifically, traffic detection equipment, including geomagnetic detectors, cameras, radar, or roadside traffic sensors, is deployed at all intersections within the associated traffic circle. Real-time data collection of vehicle traffic status at each intersection is conducted, including traffic flow, average vehicle speed, queue length, and road occupancy. Multi-source data is synchronized to ensure comparability of data from different intersections and different types of sensors within the same time period. Missing or abnormal data is removed or corrected, such as replacing extreme values with nearest-neighbor averages. Real-time signal timing parameters for intersections are obtained from the traffic signal control system, including the duration of green, yellow, and red lights in the current cycle, as well as the overall signal cycle. Based on road design parameters, number of lanes, lane width, intersection control methods, and historical traffic data, the capacity of each road under the current traffic conditions is estimated. Records for each intersection are integrated, including at least one or more indicators: traffic flow, average vehicle speed, queue length, road occupancy, signal timing parameters, and road capacity. Data from each intersection forms a data record, and all intersection records constitute an associated traffic monitoring data package.
[0043] By comprehensively assessing the degree of intersection congestion through indicators such as traffic flow, speed, queue length, and road occupancy, and combining signal timing parameters and road capacity, an executable control basis is formed to ensure the operability of traffic management strategies.
[0044] S300: Based on the associated traffic monitoring data package, and combined with the correlation coefficient between the central intersection and the corresponding intersection within the circle, traffic congestion strategies are optimized to generate traffic diversion strategies.
[0045] Furthermore, S300 of this application includes: weighting the associated intersections based on the congestion status of the central intersection and the traffic status of intersections within the associated traffic circle, combined with the road gateway connection number; determining the control priority and control range of different intersections based on the weighting assessment results; and generating a traffic diversion strategy based on the control priority and control range.
[0046] Furthermore, this application also includes the following steps: based on the congestion status of the central intersection and the traffic status of each gradient intersection within the associated traffic circle, and combined with the road gateway connection number, analyze the congestion propagation relationship and alternative diversion relationship between intersections to determine the congestion impact propagation path; based on the congestion impact propagation path and the hierarchical relationship of the multi-gradient associated traffic circle, perform gradient transfer analysis on the associated intersections to determine the control direction and control impact intensity of different gradient intersections; based on the control direction and control impact intensity, perform weight evaluation to generate weight evaluation results.
[0047] Specifically, the real-time congestion status of the central intersection is obtained, such as a traffic flow of 1500 vehicles / hour, a queue length of 40 vehicles, and an average speed of 15 km / h. Starting from the central intersection, a graph search is performed along strongly correlated edges in the traffic network. During the search, high-weighted edges dominated by the propagation impact coefficient and spillover congestion coefficient are given priority, as these edges represent the main channels for congestion propagation. The path from the central intersection through which the congestion status can be transmitted is identified, forming one or more propagation paths. Simultaneously, edges dominated by the alternative diversion coefficient are analyzed; these edges represent potential outlets for releasing congestion pressure, constituting easing paths. These paths are presented in the form of a tree diagram or network diagram, clearly indicating the direction in which congestion spreads preferentially and which intersections are at key nodes on these propagation paths. The congestion impact propagation path is the possible direction of congestion flow spreading outward from the central intersection along the road network and the sequence of key nodes it passes through, depicting the main roads and key turning points of congestion propagation.
[0048] Based on the congestion impact propagation path and the hierarchical relationship of multi-tiered traffic circles, this study analyzes how congestion pressure is transmitted layer by layer. For each intersection, the control direction is calculated: if congestion is severe, diversion capacity should be increased; if congestion is mild or acceptable, control intensity can be maintained or slightly reduced. For intersections located in the core segment of the propagation path, such as first-tier intersections upstream of the center, the control direction is mainly interception, i.e., reducing the amount of traffic flowing towards the center intersection, with a typical intensity of strong. For first-tier intersections downstream of the center, the control direction is mainly diversion, i.e., accelerating the emptying speed to avoid congestion accumulation, with a strong intensity. For intersections located on key alternative paths, such as second-tier intersections in the downstream extension, the control direction is coordinated diversion, with a medium intensity. For second-tier intersections on alternative paths, the control direction is induced diversion, i.e., attracting traffic to choose this path through information dissemination or signal optimization, with the intensity depending on its capacity margin. For intersections far from the core propagation path or with excessively high detour costs, the control direction is mainly monitoring and attention, with a weak intensity.
[0049] For each intersection within the control zone, a base score is assigned based on the intensity of its control impact: strong = 100 points, medium = 60 points, weak = 20 points. Intersections with higher weights have the greatest impact on alleviating overall road network congestion and are given priority for control. For each intersection within the control zone, the current real-time road gateway connection number with the central intersection is directly multiplied by the base score. The higher the coefficient, the greater the weight. For intersections whose control direction is diversion, the higher their capacity margin, the higher their weight, because they have the capacity to divert traffic; for intersections whose control direction is interception, the lower their capacity margin, the higher their weight, because they will collapse if they don't intercept traffic. Although gradients have been defined, intersections with fewer topological hops within the same gradient have slightly higher weights. These factors are weighted or multiplied to obtain the comprehensive weight value for each intersection, which is then sorted from highest to lowest to generate a weight evaluation result list. The higher the weight, the more priority and focus the control needs for that intersection.
[0050] Based on the weighted assessment results, the control priority is directly determined: the intersection with the highest weight has the highest control priority. Combining the control direction at that intersection, current traffic conditions, and road capacity, the control magnitude is calculated. Control priority determines the order in which controls are implemented based on the weighted assessment results; typically, the intersection with the highest weight is controlled first and most urgently. The control magnitude refers to the specific amount of the control measure, such as how many seconds the green light time needs to be increased or decreased; or the recommendation level for detours shown on the guidance screen.
[0051] Traffic management strategies are generated based on control priorities and magnitudes. Each strategy is identified by its strategy ID, generation time, corresponding central intersection ID, and associated traffic circle ID. Sorted by control priority, each target intersection's ID, control direction, specific control actions, and action parameters are listed. Examples include extending east-west green lights by 15 seconds, adjusting the phase difference to 5 seconds, and displaying the text "X" on the guidance screen. If multiple intersections require coordinated control, the strategy includes an execution time sequence, such as executing traffic control at intersection C at second 0 and traffic diversion at intersection B at second 30, ensuring synchronicity and coordination. Boundary conditions are also set; if the queue at an intersection exceeds a certain threshold, the current strategy is automatically terminated or adjusted. The generated strategy is sent to two locations: the signal control system and the guidance system for execution; and feedback is sent to the evaluation module for subsequent strategy effectiveness evaluation and model optimization.
[0052] Through weighted and gradient propagation analysis, scientific control of each intersection is achieved. Central and inner-layer intersections are prioritized for traffic management to reduce congestion spreading to outer intersections. A gradient strategy ensures that the control intensity at inner, middle, and outer-layer intersections is matched, avoiding over- or under-regulation.
[0053] S400: Based on the traffic management strategy, locate the set of target intersections in the associated traffic circle and generate traffic light control instructions.
[0054] Specifically, based on the weight and control priority of each intersection in the traffic management strategy, intersections requiring control are selected from the associated traffic circles. For example, intersections with weights higher than a set threshold are added to the target set, while intersections with weights lower than the threshold maintain their original signal timings. For each target intersection, the strategy parameters are converted into traffic light operation instructions based on the control amplitude determined in the traffic management strategy, including extending / shortening green and red light times, and adjusting signal cycles. The generated traffic light instructions are matched with the actual signal control capabilities of the intersection to ensure that the instructions are executable and do not exceed the maximum adjustable range of the equipment. If the equipment at a certain intersection is limited, the control amplitude is automatically adjusted, and the target intersection set is updated synchronously. The generated traffic light control instructions are sent to the traffic signal controller for real-time execution. The control cycle can be set to 1 minute, 5 minutes, or dynamically adjusted according to the intersection's congestion situation, forming a closed-loop control. Traffic light control instructions are specific operation instructions that directly control the traffic lights at the intersection, including extending or shortening the green light time, adjusting the red and yellow light times, and adjusting the signal cycle ratio, used to actually implement the traffic management strategy. Traffic management strategies are translated into actionable traffic light commands, achieving closed-loop control from decision-making to execution. By prioritizing high-weight intersections, the spread of traffic pressure to surrounding intersections is reduced.
[0055] In summary, the traffic congestion mitigation method based on road network coordination control provided in this application has the following technical effects:
[0056] By analyzing the traffic relationships between road networks, a traffic relationship road network is constructed, including road network gateway connections and associated traffic circles. Through this traffic relationship road network, associated traffic monitoring data packets for the associated traffic circles are obtained. Based on these associated traffic monitoring data packets, and combined with the correlation coefficient between the central intersection and the corresponding intersection within the circle, traffic congestion strategies are optimized to generate traffic management strategies. Based on these traffic management strategies, the target intersection set of the associated traffic circles is located, and traffic signal control instructions are generated. In other words, by analyzing the traffic relationships between road networks, constructing a traffic relationship road network, obtaining associated traffic monitoring data packets for associated traffic circles, optimizing traffic congestion strategies by combining the correlation coefficient between the central intersection and the corresponding intersection within the circle, generating traffic management strategies, locating the target intersection set of the associated traffic circles, and generating traffic signal control instructions, effective alleviation of urban traffic congestion and improvement of road traffic efficiency are achieved.
[0057] Example 2: Based on the same inventive concept as the traffic congestion mitigation method based on road network coordination control in Example 1, this application also provides a traffic congestion mitigation system based on road network coordination control. Please refer to the appendix. Figure 2 The traffic congestion mitigation system based on road network coordination control includes:
[0058] The road network analysis module 11 is used to analyze the traffic relationships between road networks and construct a traffic relationship road network, including the road network connection number and associated traffic circles; the traffic data acquisition module 12 is used to obtain the associated traffic monitoring data packets of the associated traffic circles through the traffic relationship road network; the traffic congestion strategy optimization module 13 is used to optimize the traffic congestion strategy based on the associated traffic monitoring data packets and the correlation coefficient between the central intersection and the corresponding intersection within the circle, and generate a traffic diversion strategy; the control instruction generation module 14 is used to locate the target intersection set of the associated traffic circles according to the traffic diversion strategy and generate traffic signal control instructions.
[0059] Furthermore, the road network parsing module 11 in the traffic congestion mitigation system based on road network coordination control is also used for: acquiring intersection topology and traffic detection data; performing time alignment, spatial mapping, and anomaly removal on multi-source data to form a temporal state vector for each intersection; constructing a candidate intersection pair set based on topological adjacency, path sharing, and data correlation; performing intersection data propagation association analysis on the candidate intersection pairs based on the temporal state vector to obtain the road gateway connection number; constructing a traffic relationship road network with intersections as nodes and the road network association relationship between candidate intersection pairs as edges, and storing the road gateway connection number as an edge attribute; and constructing an associated traffic circle based on the traffic relationship road network, with the central intersection as the seed node and association expansion on the traffic relationship road network.
[0060] Furthermore, the road network analysis module 11 in the traffic congestion mitigation system based on road network coordinated control is also used for: performing traffic flow propagation time delay analysis and propagation intensity calculation based on the temporal state vector of candidate intersection pairs to obtain the propagation influence coefficient; performing spillover event detection based on queue length, occupancy rate, or speed changes of candidate intersection pairs, and obtaining the spillover congestion coefficient through upstream intersection congestion consistency analysis; obtaining the alternative diversion coefficient based on the congestion state differential change and detour cost correction analysis of candidate intersection pairs; obtaining the controllable coupling coefficient based on the control response relationship of candidate intersection pairs according to historical control responses; and obtaining the road network connection coefficient based on the propagation influence coefficient, spillover congestion coefficient, alternative diversion coefficient, and controllable coupling coefficient.
[0061] Furthermore, the road network analysis module 11 in the traffic congestion mitigation system based on road network coordination control is also used to: construct a propagation circle along the traffic flow propagation relationship in the traffic relationship road network, and construct a replacement circle along the alternative diversion relationship in the traffic relationship road network; and divide the propagation circle and replacement circle into levels according to the topological hop count between intersections, detour costs, and road carrying capacity, to form a multi-gradient associated traffic circle.
[0062] Furthermore, the traffic data acquisition module 12 in the traffic congestion mitigation system based on road network coordination control is also used to: include one or more of the following in the associated traffic monitoring data package: traffic flow, average vehicle speed, queue length, road occupancy, signal timing parameters, and road capacity information of each intersection within the associated traffic circle.
[0063] Furthermore, the traffic congestion strategy optimization module 13 in the traffic congestion mitigation system based on road network coordination control is also used to: evaluate the weight of related intersections based on the congestion status of the central intersection and the traffic status of intersections within the related traffic circle, combined with the road network connection number; determine the control priority and control range of different intersections based on the weight evaluation results; and generate traffic diversion strategies based on the control priority and control range.
[0064] Furthermore, the traffic congestion strategy optimization module 13 in the traffic congestion mitigation system based on road network coordination control is also used to: analyze the congestion propagation relationship and alternative diversion relationship between intersections based on the congestion status of the central intersection and the traffic status of each gradient intersection within the associated traffic circle, combined with the road network connection number, to determine the congestion impact propagation path; perform gradient transmission analysis on the associated intersections based on the congestion impact propagation path and the hierarchical relationship of the multi-gradient associated traffic circle, to determine the control direction and control impact intensity of different gradient intersections; and perform weight evaluation based on the control direction and control impact intensity to generate weight evaluation results.
[0065] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The traffic congestion mitigation method and specific examples based on road network coordination control in the aforementioned embodiment 1 are also applicable to the traffic congestion mitigation system based on road network coordination control in this embodiment. Through the foregoing detailed description of the traffic congestion mitigation method based on road network coordination control, those skilled in the art can clearly understand the traffic congestion mitigation system based on road network coordination control in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.
[0066] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
[0067] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of this application and its equivalents, this application also intends to include such modifications and variations.
Claims
1. A traffic congestion mitigation method based on road network coordinated control, characterized in that, include: Analyze the traffic relationships between road networks and construct a traffic relationship road network, including the number of road gateway connections and associated traffic circles; Through the aforementioned traffic network, the associated traffic monitoring data packets of the associated traffic circles are obtained; Based on the associated traffic monitoring data packets, and combined with the correlation coefficient between the central intersection and the corresponding intersection within the circle, traffic congestion strategies are optimized to generate traffic diversion strategies. Based on the traffic management strategy, the target intersection set of the associated traffic circle is located, and traffic signal control instructions are generated.
2. The traffic congestion mitigation method based on road network coordinated control according to claim 1, characterized in that, Analyze the traffic relationships between road networks and construct a traffic relationship road network, including: Acquire intersection topology and traffic detection data, perform time alignment, spatial mapping and anomaly removal on multi-source data, and form the temporal state vector of each intersection; A set of candidate intersection pairs is constructed based on topological adjacency, path sharing, and data correlation. Based on the time-series state vector, intersection data propagation correlation analysis is performed on each candidate intersection pair to obtain the number of intersection-gateway connections. A traffic relationship road network is constructed using intersections as nodes and the road network association relationships between candidate intersection pairs as edges, and the number of road network association relationships is stored as an edge attribute; Based on the traffic relationship road network, with the central intersection as the seed node, the network is extended to form a related traffic circle.
3. The traffic congestion mitigation method based on road network coordinated control according to claim 2, characterized in that, For each candidate intersection pair, perform intersection data propagation correlation analysis to obtain the number of road-gateway connections, including: Based on the temporal state vectors of candidate intersection pairs, traffic flow propagation time delay analysis and propagation intensity calculation are performed to obtain the propagation impact coefficient; Overflow events are detected based on changes in queue length, occupancy, or speed of candidate intersection pairs, and overflow congestion coefficients are obtained through upstream intersection congestion consistency analysis. Based on the differential changes in congestion status of candidate intersection pairs and the analysis of detour cost correction, the alternative diversion coefficient is obtained. Based on historical control responses, the control response relationship of candidate intersection pairs is determined to obtain a controllable coupling coefficient; The number of gateway connections is obtained based on the propagation influence coefficient, overflow blocking coefficient, substitution diversion coefficient, and controllable coupling coefficient.
4. The traffic congestion mitigation method based on road network coordinated control according to claim 2, characterized in that, Constructing interconnected transportation networks, including: Based on the road network of traffic relationships, a propagation circle is constructed along the traffic flow propagation relationships in the road network of traffic relationships, and a replacement circle is constructed along the alternative diversion relationships in the road network of traffic relationships; Based on the topological hop count between intersections, detour costs, and road capacity, the propagation and replacement circles are hierarchically divided to form a multi-gradient interconnected traffic circle.
5. The traffic congestion mitigation method based on road network coordinated control according to claim 1, characterized in that, The associated traffic monitoring data package includes one or more of the following: traffic flow, average vehicle speed, queue length, road occupancy, signal timing parameters, and road capacity information at each intersection within the associated traffic circle.
6. The traffic congestion mitigation method based on road network coordinated control according to claim 4, characterized in that, Based on the associated traffic monitoring data packets, and combined with the correlation coefficient between the central intersection and the corresponding intersections within the ring, traffic congestion strategies are optimized to generate traffic management strategies, including: Based on the congestion status of the central intersection and the traffic status of intersections within the associated traffic circle, the associated intersections are weighted and evaluated in conjunction with the number of road gateway connections. The control priorities and control magnitudes for different intersections are determined based on the weight assessment results. Traffic management strategies are generated based on the aforementioned control priorities and control amplitudes.
7. The traffic congestion mitigation method based on road network coordinated control according to claim 6, characterized in that, Based on the congestion status of the central intersection and the traffic status of intersections within the associated traffic circle, and combined with the road gateway connectivity, the associated intersections are weighted and evaluated, including: Based on the congestion status of the central intersection and the traffic status of intersections at various levels within the associated traffic circle, and combined with the road gateway connection number, the congestion propagation relationship and alternative diversion relationship between intersections are analyzed to determine the congestion impact propagation path; Based on the congestion impact propagation path and the hierarchical relationship of multi-gradient traffic circles, gradient transmission analysis is performed on the associated intersections to determine the control direction and control impact intensity of intersections at different gradients. Based on the stated direction of regulation and the intensity of its impact, a weight assessment is performed, and a weight assessment result is generated.
8. A traffic congestion mitigation system based on road network coordinated control, characterized in that, The steps for implementing the traffic congestion mitigation method based on road network coordination control according to any one of claims 1 to 7, wherein the traffic congestion mitigation system based on road network coordination control comprises: The road network parsing module is used to parse the traffic relationships between road networks and construct the traffic relationship road network, including the number of road network connections and associated traffic circles; The traffic data acquisition module is used to obtain the associated traffic monitoring data packets of the associated traffic circles through the traffic relationship road network; The traffic congestion strategy optimization module is used to optimize traffic congestion strategies based on the associated traffic monitoring data packets and the correlation coefficient between the central intersection and the corresponding intersections within the circle, and to generate traffic diversion strategies. The control instruction generation module is used to locate the set of target intersections in the associated traffic circle according to the traffic management strategy and generate traffic light control instructions.