A method and system for dynamic timing control of intelligent traffic signals based on real-time vehicle speed and road network level anchoring

Abstract

This invention relates to the field of intelligent traffic control technology, and discloses a method and system for dynamic timing control of intelligent traffic signals based on real-time vehicle speed and road network level anchoring. The method constructs a traffic network topology model and determines timing reference intersections, acquires real-time vehicle speed data for each road segment, and performs smoothing, anomaly identification, and missing data compensation to obtain the effective vehicle speed. Based on the road segment length and the effective vehicle speed, it calculates the target travel time and recursively generates multi-intersection phase difference parameters based on the target travel time. It combines traffic flow or queue length to generate timing parameters such as cycle length, green light duration, and offset, and outputs signal control commands without changing the existing signal phase structure and safety control logic. This invention can realize multi-intersection coordinated control under multi-level road networks, improving traffic efficiency and system stability.

Description

Technical Field

[0001] This invention relates to the field of intelligent traffic control technology, specifically to a method and system for dynamic timing control of intelligent traffic signals based on real-time vehicle speed and road network level anchoring. Background Technology

[0002] With the continuous growth of urban motor vehicle ownership, urban road traffic operation exhibits significant time-varying, spatially correlated, and directionally uneven characteristics. During peak hours, holidays, and sudden congestion, traffic flows between roads of different grades couple with each other, and congestion in local sections can easily propagate along the road network, affecting the overall traffic efficiency of arterial, secondary, and local roads. Traffic signal control, as a crucial technical means of urban traffic management, directly impacts vehicle delays, number of stops, and road network efficiency if its timing parameters accurately reflect real-time traffic conditions.

[0003] Existing traffic signal control methods mainly include timed control, inductive control, and arterial coordinated control. Timed control typically pre-sets fixed timing schemes based on historical traffic data and executes them according to a predetermined cycle during actual operation. It has a simple structure but lacks the ability to respond to changes in traffic conditions. Inductive control can adaptively adjust a single intersection to a certain extent based on local traffic information obtained from devices such as geomagnetic sensors, loop detectors, or video detection. However, its control range is usually limited to a single intersection and lacks the ability to coordinate control between multiple intersections. Although arterial coordinated control can create a green wave band within a certain range on arterial roads, its control objects are mainly concentrated on fixed corridors, with insufficient coverage of secondary roads and lower-grade roads, making it difficult to adapt to the overall coordination needs in complex road network environments.

[0004] Furthermore, with the widespread availability of third-party traffic data such as floating car data and navigation data, some existing traffic systems are able to obtain vehicle speed information for road segments. However, this type of data is mostly used for traffic status display or route planning and is not deeply involved in the calculation of signal timing parameters, resulting in a certain degree of disconnect between signal control results and actual traffic conditions. For example, when congestion occurs on upstream road segments, downstream intersections may still release traffic according to the predetermined timing, which can easily lead to a mismatch between vehicle arrivals and green light windows, thereby increasing the number of stops and traffic delays.

[0005] On the other hand, existing multi-intersection coordinated control methods typically rely on pre-defined arterial structures and fixed timing benchmark intersections, lacking a unified timing benchmark determination mechanism for roads of different levels. When roads of different levels converge at intersections, if each road adjusts its timing parameters independently, control conflicts can easily arise; while if a fixed timing scheme is used for a long period, it is difficult to cope with dynamic changes in traffic flow. Therefore, in complex road network environments, how to establish a unified coordination benchmark based on real-time traffic conditions and achieve continuous transmission and collaborative optimization of timing parameters among multiple intersections remains a significant technical challenge.

[0006] Meanwhile, urban traffic exhibits a distinct tidal characteristic, meaning that different directions bear the primary traffic demand at different times. Existing technologies typically achieve directional offset by manually dividing time periods or pre-setting peak schedules, lacking a dynamic direction recognition and smooth switching mechanism based on real-time traffic conditions. This can easily lead to abrupt changes in timing parameters, thereby affecting the stability of traffic operations.

[0007] Furthermore, in actual operation, traffic systems also face complex situations such as data gaps, communication anomalies, and sudden congestion. Existing dynamic timing methods often lack effective alternative strategies when real-time data is unavailable, easily reverting to default schemes that are unsuitable for the current traffic conditions, thus affecting road network recovery efficiency. At the same time, existing systems do not adequately utilize historical timing schemes and lack a mechanism for invoking historically optimal schemes based on traffic condition matching.

[0008] Furthermore, many existing traffic signal devices in the city vary widely in model and interface capabilities, with some only supporting limited parameter adjustments or preset scheme calls. If the new timing control method relies on modifying the hardware structure of the traffic signals, it will significantly increase implementation costs and reduce the feasibility of widespread adoption. Therefore, achieving dynamic timing control without altering the existing phase structure and safety control logic of the traffic signals is a pressing issue that needs to be addressed.

[0009] In summary, the existing technology has at least the following shortcomings: First, it lacks the ability to coordinate and control the entire road network across multiple road levels; second, real-time traffic status data such as vehicle speed is not effectively used for signal timing calculation; third, it lacks a unified mechanism for determining timing benchmarks and a recursive method for multi-intersection phase difference calculation; fourth, it lacks a mechanism for dynamic direction determination and smooth switching based on real-time traffic conditions; fifth, it lacks effective fault tolerance and recovery strategies in the event of data anomalies or emergencies; and sixth, it lacks compatibility with existing traffic signal equipment.

[0010] Therefore, it is necessary to propose an intelligent traffic signal dynamic timing control method and system that can dynamically coordinate timing of multi-level traffic networks based on real-time vehicle speed data, and achieve efficient control while ensuring system stability and equipment compatibility. Summary of the Invention

[0011] In view of this, the purpose of this invention is to provide an intelligent traffic signal dynamic timing control method and system based on real-time vehicle speed and road network level anchoring, to solve the problems of insufficient response to real-time traffic conditions, limited multi-intersection coordination capability, and poor adaptability in complex multi-level road network environments of existing traffic signal timing methods, thereby achieving coordinated control between multiple intersections, improving road traffic efficiency, and enhancing system operational stability. To achieve the above objectives, this invention provides the following technical solution: In one possible implementation, a dynamic timing control method for intelligent traffic signals based on real-time vehicle speed and road network level anchoring is provided, applied to a traffic network signal control system composed of multi-level roads. The method includes: Construct a traffic network topology model, classify roads into levels, and determine timing benchmark intersections based on road level relationships; Real-time vehicle speed data for each road segment is obtained, as well as traffic flow data and / or queue length data for each road segment. The vehicle speed data is then smoothed, anomaly identified, and missing data is compensated to obtain the effective vehicle speed. The target travel time for a vehicle to travel from the upstream intersection to the downstream intersection is calculated based on the road segment length and the effective vehicle speed. Starting from the timing reference intersection, the phase difference parameters of multiple intersections are recursively calculated along the road network topology based on the target travel time of adjacent road segments, and constraint correction is performed when the phase difference exceeds the allowable range. Based on the phase difference parameter and combined with the traffic flow data and / or queue length data, calculate at least one timing parameter among the cycle length, green light duration and offset of each intersection; The timing parameters are converted into signal control commands and sent to the signal controller for execution to achieve coordinated control of multiple intersections.

[0012] In one possible implementation, step S2 includes: smoothing the vehicle speed data using a sliding time window average or an exponentially weighted average; identifying anomalies in data that exceed a preset range, have a change amplitude exceeding a threshold, or have insufficient sample size; and performing removal, amplitude limiting, or weight reduction processing on the abnormal data.

[0013] In one possible implementation, when vehicle speed data is missing or the confidence level is insufficient, a fusion compensation is performed based on the vehicle speeds of adjacent road segments, historical vehicle speeds, and the most recent effective vehicle speed to obtain a compensated vehicle speed.

[0014] In one possible implementation, the target travel time is calculated based on the ratio of road segment length to effective vehicle speed, and a base travel time is added in addition to start-up loss time and queuing correction.

[0015] In one possible implementation, step S4 includes: using the timing reference intersection offset as the initial value, generating the offset of each intersection by progressively accumulating it according to the target travel time between adjacent intersections; and performing amplitude limiting processing when the offset exceeds the allowable range, and using error feedback to correct the recursive results of adjacent intersections.

[0016] In one possible implementation, the green light duration is based on a base green light duration and dynamically adjusted in conjunction with vehicle speed, traffic flow, and queue length, while satisfying minimum and maximum green light constraints.

[0017] In one possible implementation, it further includes: determining a coordination priority direction based on bidirectional vehicle speed, flow rate, or queue length, and prioritizing the generation of a timing scheme for continuous release in said direction.

[0018] In one possible implementation, the coordinated direction switching adopts a dual-threshold triggering and continuous cycle determination mechanism, and achieves a smooth transition through parameter gradual change.

[0019] In one possible implementation, the method further includes: when real-time data is abnormal, communication is abnormal, or the calculation result is outside the control range, matching a timing scheme similar to the current traffic state from the historical timing scheme library and outputting it for execution.

[0020] In one possible implementation, an intelligent traffic signal dynamic timing control system based on real-time vehicle speed and road network level anchoring is provided, comprising: The road network modeling module is configured to build a traffic road network topology model, classify roads into levels, and determine timing benchmark intersections based on road level relationships. The data processing module, connected to the road network modeling module, is configured to acquire real-time vehicle speed data for each road segment and traffic flow data and / or queue length data for each road segment, perform smoothing processing, anomaly identification and missing data compensation on the vehicle speed data, and output the effective vehicle speed. The travel time calculation module, connected to the data processing module, is configured to calculate the target travel time for a vehicle to travel from the upstream intersection to the downstream intersection based on the road segment length and the effective vehicle speed. The phase difference recursion module, connected to the travel time calculation module and the road network modeling module, is configured to recursively calculate the phase difference parameters of multiple intersections based on the target travel time of adjacent road segments along the road network topology, starting from the timing reference intersection, and to perform constraint correction when the phase difference exceeds the allowable range. The timing generation module, connected to the phase difference recursion module, is configured to generate at least one timing parameter among cycle length, green light duration, and offset for each intersection based on the phase difference parameter and in combination with the traffic flow data and / or queue length data. The control output module, connected to the timing generation module, is configured to convert the timing parameters into signal control commands and send them to the signal controller for execution.

[0021] Furthermore, in step S6, without changing the original phase structure and safety control logic of the signal, the timing parameters are converted into signal control commands and sent to the signal for execution.

[0022] Based on the above technical solutions, the present invention provides a method and system for dynamic timing control of intelligent traffic signals based on real-time vehicle speed and road network level anchoring. By constructing a traffic road network topology model and determining the timing reference intersection, and combining smoothing processing, anomaly identification, and missing data compensation of real-time vehicle speed data, an effective vehicle speed that reflects the actual traffic operation status is obtained. Based on the road segment length and the effective vehicle speed, the target travel time of vehicles between adjacent intersections is calculated. On this basis, starting from the timing reference intersection, the phase difference parameters of multiple intersections are recursively calculated along the road network topology. During the recursive process, constraint correction and error feedback mechanisms are introduced to generate coordinated timing parameters that meet the control constraints of the traffic signal controller.

[0023] Furthermore, by integrating the phase difference parameter with traffic state parameters such as traffic flow and queue length, the cycle length, green light duration, and offset of each intersection are dynamically generated. Without changing the existing signal phase structure and safety control logic, the timing parameters are directly converted into signal control commands and output to the signal controller for execution, thereby achieving continuous and coordinated release between multiple intersections.

[0024] Compared with existing signal timing methods based on simulation evaluation or optimization search, this invention does not rely on complex traffic simulation models or multi-round iterative calculation processes. Instead, it constructs a closed-loop calculation mechanism of "vehicle speed - travel time - phase difference recursion - timing output" to achieve rapid generation and real-time updating of signal timing parameters, thereby significantly improving the timing calculation efficiency and reducing the system's computational complexity.

[0025] Furthermore, by introducing a timing reference intersection anchoring mechanism for multi-level roads, this invention establishes a unified coordination reference system between low-level and high-level roads, effectively avoiding conflicts caused by independent timing between different roads, thereby improving the collaborative control capability across the entire road network.

[0026] Meanwhile, by setting up a vehicle speed data compensation mechanism and a historical timing scheme recall mechanism, this invention can still output an alternative timing scheme that matches the current traffic conditions even when real-time data is abnormal, communication is interrupted, or calculation results are unavailable. This improves the stability and robustness of the system under abnormal conditions and enhances the continuous operation capability of the traffic system.

[0027] Furthermore, this invention achieves dynamic identification and gradual transition of traffic tidal direction by determining the coordinated priority direction based on two-way traffic conditions and a smooth switching mechanism triggered by dual thresholds, thereby avoiding traffic fluctuations caused by sudden changes in signal timing parameters and improving the continuity and comfort of vehicle operation.

[0028] In summary, this invention enables real-time dynamic coordination and timing control of multi-level traffic networks without altering the existing signal hardware structure. This not only improves road traffic efficiency and reduces vehicle delays and stops, but also significantly enhances the adaptive capability and overall operational stability of the traffic system in complex environments and abnormal situations. Attached Figure Description

[0029] Figure 1 This is a schematic diagram of the overall process of the intelligent traffic signal dynamic timing control method in an embodiment of the present invention; Figure 2 This is a structural block diagram of the intelligent traffic signal dynamic timing control system in an embodiment of the present invention. Detailed Implementation

[0030] To enable those skilled in the art to more clearly understand the technical solution of the present invention, the technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the following embodiments are only used to explain the technical concept, technical features, and implementation process of the present invention, and are not intended to limit the scope of protection of the present invention. All equivalent substitutions, simple transformations, or corresponding adjustments made within the spirit and principles of the present invention based on the disclosure of the present invention should fall within the scope of protection of the present invention.

[0031] It should be noted that the core of this invention lies in: based on the topological relationship of the traffic network and the road grade relationship, using real-time vehicle speed data as the main driving parameter, processing the vehicle speed data, calculating the target travel time, recursively extrapolating the phase difference of multiple intersections, and combining traffic state information such as traffic flow and queue length to generate signal timing parameters, ultimately forming dynamic control commands that can directly act on the signal controller, thereby realizing coordinated control of multiple intersections in a traffic network composed of multi-grade roads.

[0032] It should also be understood that the descriptions of "upstream," "downstream," "preceding," and "following" mentioned in the following embodiments are mainly relative to the vehicle's direction of travel, the direction of traffic flow propagation, or the road network topology, and are used to describe the relative positional relationship between each intersection and each road segment; the terms "real-time vehicle speed," "effective vehicle speed," "target travel time," "phase difference parameter," "offset," and "timing reference intersection," unless otherwise explicitly defined, should be understood in conjunction with the overall technical solution of this invention.

[0033] Based on the above description, the overall implementation of the present invention will first be described in conjunction with the accompanying drawings, and then the method flow, system structure, parameter calculation process and operation effect of the present invention will be described in detail in conjunction with specific embodiments.

[0034] I. General Implementation Method Description In one embodiment of the present invention, a method and system for dynamic timing control of intelligent traffic signals based on real-time vehicle speed and road network level are provided to solve the problems of insufficient response to real-time traffic conditions, limited multi-intersection coordination capability, and poor adaptability to complex road networks in existing traffic signal control methods.

[0035] The method of the present invention can be derived from, for example Figure 2 The intelligent traffic signal dynamic timing control system shown executes, and follows, as follows: Figure 1 The system operates according to the illustrated process. It can be deployed on a traffic management center server, regional control sub-center, edge computing node, or cloud platform, and interacts with traffic signals at intersections, traffic detection equipment, and third-party data platforms via wired or wireless communication networks.

[0036] In a specific implementation, the system preferably establishes a communication connection with the following data sources: Roadside detection equipment (such as geomagnetic detectors, video detectors, radar detectors, etc.) is used to obtain real-time traffic flow and vehicle speed information; Third-party data platforms (such as navigation platforms or floating car data platforms) are used to obtain regional vehicle speed distribution information; Traffic signal control equipment is used to receive and execute timing control commands; The traffic management platform database is used to store historical traffic status data and historical timing schemes.

[0037] The core idea of ​​this invention is: based on the traffic network topology, using real-time vehicle speed data as the main driving parameter, calculating the travel time of vehicles on road segments, and using this as a basis to recursively generate phase difference parameters between multiple intersections, thereby generating signal control parameters and directly acting on the signal controller to achieve coordinated control between multiple levels of roads.

[0038] Unlike traditional timing methods based on simulation or empirical rules, this invention constructs a closed-loop computational chain of "data processing—travel time calculation—phase difference recursion—timing generation—control output" to achieve real-time generation and dynamic adjustment of signal timing parameters. This process does not rely on complex simulation models or multiple rounds of optimization searches, thereby reducing computational complexity and improving system response speed.

[0039] In this invention, "road network level anchoring" is a crucial foundation for achieving multi-intersection coordination. Specifically, by classifying roads into different levels and selecting intersections where lower-level roads merge with higher-level roads as timing reference intersections, a unified timing reference system is established between roads of different levels. Based on this, the phase difference parameters of other intersections are recursively calculated based on the timing reference intersections, thereby achieving coordinated control across intersections and road levels.

[0040] In terms of data processing, this invention addresses the common problems of noise, anomalies, and missing data in actual traffic data by designing a vehicle speed processing mechanism that includes smoothing, anomaly identification, and multi-source data compensation to improve the accuracy and stability of the vehicle speed data used for calculation. Through this processing, timing calculation deviations caused by single-point anomalies can be effectively avoided.

[0041] In terms of control execution, this invention dynamically adjusts only adjustable parameters such as cycle length, green light duration, and offset without changing the existing signal phase structure, phase sequence logic, and safety control parameters (such as yellow light time and all-red light time). This ensures the compatibility and safety of the system in actual deployment and avoids hardware modifications to existing traffic control equipment.

[0042] Furthermore, in a preferred embodiment, the present invention can also incorporate auxiliary parameters such as traffic flow and queue length to correct the timing results, thereby improving control accuracy; and by setting a tidal direction determination mechanism, dynamic coordinated control under changing traffic demand in different directions can be achieved. In addition, in the event of abnormal real-time data or communication interruption, historical timing schemes can be called as alternative outputs to ensure the continuity and stability of system operation.

[0043] Through the above overall design, the present invention can realize dynamic coordinated timing control of multiple intersections based on real-time traffic conditions in complex multi-level traffic network environments, improve road traffic efficiency, reduce vehicle delays and stops, and enhance the robustness and adaptability of the system under abnormal conditions.

[0044] It should be noted that the above embodiments are only one of the preferred embodiments of the present invention. Without departing from the spirit of the technical solution of the present invention, those skilled in the art can make appropriate adjustments or substitutions to the system structure and method steps according to actual application needs, and all such adjustments or substitutions should be considered to fall within the protection scope of the present invention.

[0045] II. Combined with Appendix Figure 1 Method implementation process like Figure 1 As shown, the intelligent traffic signal dynamic timing control method based on real-time vehicle speed and road network level anchoring provided by the present invention includes the following steps: S1. Road network modeling and determination of timing benchmark intersections First, the traffic network of the target area is modeled, constructing a topological model that includes intersection nodes and road segment connections. The topological model can be represented as a graph structure G = (V, E), where V represents the set of intersection nodes and E represents the set of road segments connecting adjacent intersections.

[0046] During the modeling process, the following basic attribute information is acquired and stored: Road segment length; Road classification (e.g., arterial road, secondary road, local road); Number of lanes; Intersection phase structure; Road segment connectivity (upstream and downstream relationships).

[0047] Based on this, roads are classified into different levels, and timing reference intersections are determined according to the road level relationships. Preferably, intersections where lower-level roads merge into higher-level roads are used as candidate timing reference intersections, and the final timing reference intersection can be determined by combining traffic flow or historical traffic efficiency.

[0048] The timing reference intersection serves as the starting reference point for multi-intersection coordination calculations, and its phase offset can be set to an initial value.

[0049] S2. Real-time vehicle speed data acquisition and processing Obtain real-time traffic data for each road segment, including at least vehicle speed data. The data may be sourced from: Roadside detection equipment; Video recognition system; Data from floating car or navigation platform.

[0050] Processing the vehicle speed data includes: (1) Smoothing Using sliding time window averaging or exponential weighted averaging methods can reduce the impact of random fluctuations on the data.

[0051] (2) Anomaly detection Identify the following situations: Vehicle speed exceeding the physical limits; The amplitude of changes between adjacent sampling periods is abnormal; The number of data samples is insufficient.

[0052] (3) Exception handling Abnormal data can be removed, its magnitude limited, or its weight reduced.

[0053] (4) Missing compensation When vehicle speed data is missing or has insufficient confidence, compensation is performed based on the following data: Vehicle speed on adjacent road sections; Nearest effective speed; Vehicle speeds during the same historical period.

[0054] The above processing yields the effective vehicle speed for subsequent calculations.

[0055] S3, Target travel time calculation Based on the length of each road segment and the corresponding effective speed, calculate the target travel time for a vehicle to travel from the upstream intersection to the downstream intersection.

[0056] Specifically, it includes: Calculate the basic travel time (determined by road segment length and vehicle speed); In a preferred embodiment, the start-up loss time is superimposed; Queue correction terms are introduced based on queue length and lane conditions.

[0057] The target travel time is used to describe the propagation characteristics of vehicle clusters in the road network and serves as a basic parameter for subsequent multi-intersection coordination calculations.

[0058] S4. Multi-intersection phase difference recursive calculation Starting from the time-matching reference intersection, the phase difference parameters of multiple intersections are generated by recursively calculating based on the target travel time of adjacent road segments along the road travel direction.

[0059] The specific process includes: Use the phase offset of the timing reference intersection as the initial value; The target travel time is accumulated level by level according to the road network topology to obtain the offset of the downstream intersection; Constraints are applied to the calculated phase difference parameters.

[0060] When the phase difference parameter exceeds the allowable adjustment range of the signal controller, the following procedure is performed: Phase difference is limited and corrected; The excess portion is fed back as error to the recursive calculation process of adjacent intersections to reduce the overall deviation.

[0061] Through the above recursive mechanism, the coordination relationship between multiple intersections can be continuously established.

[0062] S5, Signal Timing Parameter Generation Based on the phase difference parameter and combined with real-time traffic conditions, signal control parameters are generated, including but not limited to: Intersection control cycle; Green light duration for each phase; Intersection offset.

[0063] During the generation process, the following factors can be considered for correction: Real-time traffic flow; Queue length; Number of lanes and traffic capacity.

[0064] Meanwhile, the generated timing parameters must meet the following constraints: Without changing the original phase structure; The green light duration is within the preset range; The cycle length meets the control range requirements; The parameter adjustment range shall not exceed the set threshold.

[0065] S6. Signal Control Command Generation and Output The timing parameters are converted into signal control commands and sent to the corresponding signal controllers for execution via the communication interface.

[0066] Depending on the type of signal, one of the following methods can be used: Directly write the cycle, green light duration, and offset parameters; Call the closest preset timing scheme; Send an incremental adjustment command to correct the current scheme.

[0067] The control command takes effect at the moment of execution and remains effective within a set period.

[0068] S7, Extended Control and Fault Tolerance Mechanisms In this embodiment, to further enhance the system's adaptability to complex traffic environments and its stable operation under abnormal conditions, extended control and fault-tolerant mechanisms can be introduced in addition to the basic timing control process described above. These mechanisms mainly include a tidal direction control mechanism, a historical timing scheme database matching mechanism, and an anomaly detection and handling mechanism.

[0069] 7.1 Tidal Direction Control Mechanism In urban traffic operations, traffic demand typically exhibits significant directional differences across different time periods. To improve the efficiency of traffic flow in the dominant traffic direction, this embodiment introduces a tidal direction control mechanism based on real-time traffic conditions.

[0070] Specifically, the system constructs a direction priority determination index based on parameters such as two-way vehicle speed, traffic flow, and queue length. Let direction A and direction B be the two directions of a certain road segment, then the direction priority index can be defined as: ; in: The priority index represents the direction d; This indicates the traffic flow in that direction; Indicates the queue length in that direction; Indicates the effective speed in that direction; Indicates the free-flow velocity; To prevent extremely small positive numbers with a denominator of zero; This is the direction priority index weighting coefficient, used to adjust the influence of traffic flow, queue length, and vehicle speed on the direction priority determination result. Preferably, ++=1. .

[0071] When the effective vehicle speed decreases, the priority index for the corresponding direction increases, thereby enhancing the system's ability to coordinate and release traffic in congested directions.

[0072] When the priority index of one direction is significantly higher than that of another direction, the system determines that direction as the current priority direction for coordination, and appropriately extends the green light duration or optimizes the phase offset in the timing generation process to achieve continuous passage.

[0073] To avoid traffic fluctuations caused by frequent direction changes, this embodiment preferably employs a dual-threshold triggering mechanism. A direction change is triggered when the following conditions are met: When the priority index of one direction is significantly higher than that of another direction, the system determines that direction as the current priority direction for coordination, and appropriately extends the green light duration or optimizes the phase offset in the timing generation process to achieve continuous passage.

[0074] To avoid traffic fluctuations caused by frequent direction changes, this embodiment preferably employs a dual-threshold triggering mechanism. A direction change is triggered when the following conditions are met: ; When the difference falls back to: ; Cancel state switching at time, where ; In addition, during the direction switching process, it is preferable to smoothly adjust the green light duration and offset by gradually changing the parameters in order to avoid sudden changes in control parameters from impacting traffic operations.

[0075] In a preferred embodiment, the coordination control mechanism is applicable to both four-phase symmetrical release mode and four-phase asymmetrical release mode.

[0076] When the target road adopts a four-phase symmetrical release mode, the system recursively generates a two-way coordinated release window based on the arrival time of vehicles in both directions, so that vehicles in the coordinated direction can obtain continuous green light release at multiple subsequent consecutive intersections after passing through the coordination starting intersection or experiencing the first stop.

[0077] Preferably, for the highest-level coordinated arterial roads, in the morning and evening peak tidal traffic scenarios, the system can establish continuous coordination relationships for two-way traffic flow, so that after the vehicle passes through the first stop, it can continuously obtain green light release at subsequent coordinated intersections, thereby reducing repeated stops and vehicle start-stop losses.

[0078] For a low-level road that has only one intersection reference point with a higher-level road, the system uses the intersection reference point as the only timing anchor point and recursively generates the phase difference of subsequent intersections along the straight direction of the low-level road, so that after the vehicle passes through the intersection reference point, it can obtain continuous green light passage at subsequent consecutive intersections.

[0079] When the target road adopts a four-phase asymmetric release mode, the system prioritizes generating a continuous coordinated release window based on the tidal main direction, and performs subordinate compensation adjustment on the traffic flow in the opposite direction according to the timing results of the main direction.

[0080] In a preferred embodiment, the timing adjustment of traffic flow in the opposite direction prioritizes meeting the continuous release constraint of the main direction, and dynamically corrects the offset of the opposite direction and the green light duration within the remaining adjustable range, thereby taking into account both the efficiency of two-way traffic and the continuous coordination effect of the main direction.

[0081] 7.2 Historical Timing Scheme Database Matching Mechanism In a preferred embodiment, to improve the stability of the system under data anomalies or computational anomalies, the present invention also introduces a historical timing scheme database matching mechanism.

[0082] Specifically, the system pre-builds a historical timing scheme library to store signal timing schemes under different traffic conditions. Each historical timing scheme is associated with a corresponding traffic condition feature, which includes at least vehicle speed, traffic flow, queue length, road grade, and time period information.

[0083] During real-time operation, if any of the following conditions are detected: Real-time vehicle speed data is missing or the confidence level is below a preset threshold; Communication errors prevented data retrieval; The timing calculation results are outside the control range or do not meet the constraints; The system triggers the historical timing scheme matching process.

[0084] Specifically, the current traffic state feature vector is first constructed: ; Subsequently, historical state vectors are extracted from the historical timing scheme library. And calculate the similarity: ; The historical solution with the smallest distance is selected as the candidate solution.

[0085] In a further implementation, a similarity threshold can be set, and a degradation control strategy can be executed when the optimal matching result does not meet the threshold condition.

[0086] Finally, the matched historical timing schemes are converted into signal control commands and output to the signal controller for execution, thereby ensuring the continuity of system operation in abnormal situations.

[0087] 7.3 Anomaly Detection and Handling Mechanism To further improve the robustness of the system, this embodiment also includes an anomaly detection and handling mechanism to monitor the system's operating status in real time.

[0088] Specifically, the system detects the following abnormal situations: Data anomalies include vehicle speed data exceeding limits, sudden changes, or missing data; Communication anomalies, including data transmission interruptions or excessive delays; Control anomalies include signals not executing commands or providing abnormal feedback.

[0089] When an anomaly is detected, the system takes appropriate action based on the anomaly type: For data anomalies, it is preferable to use a data compensation mechanism to recover the input data; In case of communication failure, a retransmission mechanism or switching to a backup communication link can be used; In case of control anomalies, either the historical timing scheme or the default safe timing scheme can be triggered.

[0090] In a further implementation, the system can also set an exception priority and select different processing strategies according to the severity of the exception to achieve hierarchical fault-tolerant control.

[0091] Through the above-mentioned anomaly detection and handling mechanisms, the system can maintain good stability and reliability even in complex environments.

[0092] III. In conjunction with the appendix Figure 2 System architecture description like Figure 2 As shown, the intelligent traffic signal dynamic timing control system based on real-time vehicle speed and road network level anchoring provided by the present invention includes a road network modeling module, a data processing module, a travel time calculation module, a phase difference recursion module, a timing generation module, and a control output module. The modules are connected to each other through a data interface to complete the dynamic calculation and control output of signal timing parameters.

[0093] The system can be deployed as software on a server or edge computing device, or it can be implemented using a combination of software and hardware. The modules can be deployed either centrally or in a distributed manner.

[0094] (1) Road network modeling module The road network modeling module is used to construct a traffic road network topology model and determine timing reference intersections.

[0095] Specifically, it includes: Acquire basic road network data, including intersection locations, road segment connections, road class, number of lanes, and signal phase structure; Construct a road network topology model and establish upstream and downstream connections between intersections; Roads are classified into different levels, and candidate timing reference intersections are determined based on the merging relationship between low-level and high-level roads. The final timing reference intersection is determined based on preset rules or traffic characteristics, and the timing reference intersection information is output.

[0096] The output of the road network modeling module provides the basic topology and reference starting point for subsequent phase difference recursive calculations.

[0097] (2) Data processing module The data processing module is used to acquire and process real-time traffic data and generate effective vehicle speeds for timing calculations.

[0098] Specifically, it includes: Data acquisition unit: used to acquire vehicle speed data from roadside detection equipment, video detection systems or third-party data platforms; Smoothing unit: used to perform time window averaging or exponential weighting on the raw vehicle speed data; Anomaly detection unit: used to identify data that exceeds a preset range or changes abnormally; Data correction unit: used to remove, limit, or reduce the weight of abnormal data; Compensation calculation unit: used to generate compensated vehicle speeds based on adjacent road segments and historical data when data is missing or confidence is insufficient.

[0099] The effective vehicle speed output by the data processing module is used as the input parameter for the passage time calculation module.

[0100] (3) Travel time calculation module The travel time calculation module is used to calculate the target travel time based on the road segment length and effective vehicle speed.

[0101] Specifically, it includes: Basic time calculation unit: Calculates the basic time required for vehicle passage based on road segment length and effective vehicle speed; Correction calculation unit: Corrects the basic passage time based on the start-up loss time and queue length; Output unit: Outputs the target travel time for each road segment.

[0102] The target travel time is used to describe the propagation characteristics of vehicles in the road network and is the core input for phase difference recursive calculation.

[0103] (4) Phase difference recursion module The phase difference recursion module is used to recursively calculate the phase difference parameters of multiple intersections based on the target travel time and the road network topology.

[0104] Specifically, it includes: Initial setting unit: The phase offset of the timing reference intersection is used as the initial value; Recursive calculation unit: The target travel time is accumulated step by step according to the road network topology, and the offset of each intersection is calculated. Constraint judgment unit: Determines whether the calculation result exceeds the allowable range of the signal; Correction Feedback Unit: Limits the amplitude of results that exceed the range and feeds the error back to adjacent nodes for correction.

[0105] The above modules enable the establishment of coordination relationships between multiple intersections.

[0106] (5) Timing generation module The timing generation module is used to generate signal timing parameters based on phase difference parameters and traffic conditions.

[0107] Specifically, it includes: Parameter calculation unit: Calculates the offset of each intersection based on the phase difference parameter; Green light allocation unit: Calculates the green light duration for each phase by combining vehicle speed, traffic flow, and queue length; Cycle calculation unit: determines the intersection control cycle; Constraint control unit: Performs legality verification on the generated timing parameters to ensure that constraints such as minimum green light, maximum green light, and cycle range are met.

[0108] The timing parameters output by the module are used as input to the control output module.

[0109] (6) Control output module The control output module is used to convert timing parameters into control commands that can be executed by the signal and send them to the corresponding signal.

[0110] Specifically, it includes: The instruction generation unit is used to encapsulate timing parameters such as cycle length, green light duration, and offset into standardized control parameters. The signal controller capability identification unit is used to identify the parameter adjustment capability, communication protocol and control mode supported by the target signal controller. The parameter adjustment capability includes at least one of the following: cycle length adjustment capability, green light duration adjustment capability, phase offset adjustment capability, preset scheme recall capability and parameter increment adjustment capability. The control mode selection unit is used to select one of the following control modes based on the capability information identified by the signal capability identification unit: direct parameter issuance, preset scheme invocation, or incremental parameter adjustment. The mode adaptation unit is used to convert the standardized control parameters into protocol messages, scheme call instructions or incremental adjustment instructions that can be recognized by the target signal machine according to the selected control method and the communication protocol of the target signal machine. The communication transmitting unit is used to send the protocol message, scheme call instruction, or incremental adjustment instruction to the target signal via a communication interface. The execution monitoring unit is used to monitor the execution status of the target signal and provide feedback on the execution results.

[0111] (7) Extended functional modules (optional) In a preferred embodiment, the system may further include the following expansion modules: Tidal direction control module: used to determine the priority direction for coordination based on the two-way traffic conditions and to realize direction switching control.

[0112] Historical timing management module: Used to store historical timing schemes and to match and call them in abnormal situations.

[0113] Anomaly detection module: Used to detect data anomalies, communication anomalies, and control anomalies, and trigger fault tolerance mechanisms.

[0114] (8) Explanation of module collaboration relationship During system operation, the collaborative relationships between the modules are as follows: 1. The road network modeling module provides the topology and timing reference intersections; 2. The data processing module provides the effective vehicle speed; 3. The passage time calculation module generates the target passage time; 4. The phase difference recursion module generates coordination parameters; 5. The timing generation module generates control parameters; 6. The control output module completes the instruction issuance.

[0115] This forms a complete closed-loop control link.

[0116] Through the above system structure design, the present invention can realize real-time dynamic timing control of multi-level traffic networks, and improve the coordination control effect of multi-intersections and overall traffic efficiency while ensuring system stability and compatibility.

[0117] IV. Implementation Results Description Through the above implementation methods, the intelligent traffic signal dynamic timing control method and system based on real-time vehicle speed and road network level anchoring proposed in this invention can achieve the following significant technical effects in practical traffic control applications: (1) Achieve coordinated control of multi-level road networks This invention constructs a traffic network topology model and introduces a timing benchmark intersection anchoring mechanism based on road level, establishing a unified coordination reference system between roads of different levels. Compared to control methods that only target main roads or single intersections, this invention can form a coordinated relationship between main roads, secondary roads, and branch roads, thereby effectively avoiding timing conflicts between low-level and high-level roads.

[0118] (2) Improve the responsiveness of signal control to real-time traffic conditions. This invention uses real-time vehicle speed as the core input parameter and dynamically generates timing parameters through data processing, travel time calculation, and phase difference recursion. Compared to control methods that rely on historical data or fixed time periods, this invention can reflect traffic flow changes in a timely manner, reduce signal control mismatch problems caused by traffic condition lags, and thus improve the real-time performance and accuracy of control.

[0119] (3) Reduce system computational complexity and improve response speed Compared to existing timing methods based on simulation evaluation or optimization search, this invention eliminates the need to construct complex simulation models or perform multiple rounds of iterative optimization. Instead, it directly generates signal timing parameters through analytical calculation, thereby significantly reducing computational resource consumption. In practical applications, timing updates can be achieved at the second level or even shorter periods, improving the overall system response speed.

[0120] (4) Achieve continuous and coordinated release of traffic at multiple intersections By using a phase difference recursive calculation mechanism based on target travel time, this invention can establish a continuous coordination relationship between multiple adjacent intersections, enabling vehicles to form a smooth "green wave" effect between multiple intersections, reducing the number of stops and start-stop losses, thereby improving road traffic efficiency.

[0121] (5) Enhance the stability and robustness of the system under abnormal operating conditions. This invention introduces anomaly identification and multi-source compensation mechanisms into vehicle speed data processing, effectively avoiding the impact of single-point data anomalies on the overall control results. Simultaneously, by setting a historical timing scheme recall mechanism, it can still output reasonable alternative control schemes in the event of real-time data interruption, communication anomalies, or unavailable calculation results, thereby ensuring continuous system operation and enhancing system robustness.

[0122] (6) Improve the control effect in tidal traffic scenarios This invention introduces a direction priority determination mechanism based on two-way traffic conditions, combined with a dual-threshold triggering and gradual transition strategy, to achieve dynamic identification and smooth switching of traffic tidal directions. Compared to traditional direction control methods based on fixed time periods, this invention can more accurately match changes in actual traffic demand and avoid traffic fluctuations during direction switching.

[0123] (7) Improve system compatibility and reduce implementation costs This invention does not alter the phase structure, phase sequence logic, or safety control parameters of existing traffic signals during control execution; it only adjusts parameters such as the cycle, green light duration, and offset. Therefore, it can be directly deployed on existing traffic signal equipment without hardware modification or equipment replacement, significantly reducing system implementation costs and improving the feasibility of project implementation.

[0124] (8) Overall performance improvement effect In a typical urban road network test environment, the present invention can achieve the following effects compared to traditional control methods (exemplary data): Average vehicle delays decreased by approximately 15% to 30%; The average number of parking incidents decreased by approximately 10% to 25%; The overall traffic efficiency of the road network will improve by approximately 20%. The congestion recovery time has been significantly shortened.

[0125] (9) Wide range of applications This invention is applicable not only to urban main road corridor control scenarios, but also to complex road network areas with interwoven multi-level roads. It is particularly suitable for old urban areas, densely populated secondary road areas, and areas with mixed deployment of multiple brands of traffic signal controllers, and has good promotion and application value.

[0126] In summary, this invention incorporates real-time vehicle speed data into signal timing calculations and combines road network level anchoring and phase difference recursion mechanisms to achieve dynamic coordinated control of multiple intersections and multi-level roads. While improving traffic efficiency, it also takes into account system stability, compatibility, and engineering feasibility, demonstrating significant technological advancements and application value.

[0127] Example 1: Dynamic Timing Control at Multiple Intersections Based on Real-Time Vehicle Speed In this embodiment, a typical urban road corridor in a city is used as the application object to illustrate the specific implementation process of the method of the present invention. The road corridor consists of a secondary arterial road and its two side branches, including four consecutive signal-controlled intersections, denoted as follows: and ,in As a timing reference intersection.

[0128] (I) Application Scenarios and Basic Parameters In this embodiment, the intelligent traffic signal dynamic timing control method of the present invention is applied to a traffic corridor area composed of typical multi-level roads in a city. This area consists of a secondary arterial road as the main traffic corridor, with several branch roads distributed on both sides, forming multiple consecutive signal-controlled intersections. For ease of explanation, four adjacent signal-controlled intersections are selected as the research object, and are denoted as follows: and The intersection located upstream The selected intersection is the timing reference intersection, and the remaining intersections are distributed sequentially along the direction of vehicle travel.

[0129] In the road network, roads are classified into different levels according to their function, including primary arterial roads, secondary arterial roads, and tertiary local roads. Secondary arterial roads bear the primary traffic flow function, while local roads are mainly used for the merging and dispersing of traffic within the area. Road segments are connected by intersections to form continuous traffic paths. The length of road segments between adjacent intersections is determined based on actual measurement data, for example... to The road section is approximately 400 to 450 meters long. to The road section is approximately 350 to 400 meters long. to The road sections are approximately 400 to 500 meters long. Each section typically has 2 to 3 lanes, which is sufficient to meet medium to high traffic demand.

[0130] Regarding signal control parameters, a unified initial control cycle is adopted at each intersection, preferably set within the range of 60 to 120 seconds; in this embodiment, 90 seconds is selected as the initial cycle. The green light duration for each phase is subject to upper and lower limits, with the minimum green light duration generally not less than 10 seconds to ensure basic traffic flow, and the maximum green light duration not exceeding 60 seconds to avoid excessive traffic resource occupation in one direction. Simultaneously, each intersection's signal controller has the ability to adjust the cycle, green light duration, and offset parameters, but its phase structure, phase sequence logic, and the yellow and all-red safety times remain unchanged.

[0131] Regarding traffic flow parameters, the saturation flow rate of the road segment is set according to road conditions and lane conditions, typically set at approximately 1800 standard vehicles per lane per hour. Traffic status information includes vehicle speed, traffic volume, and queue length, with vehicle speed data obtained through roadside detection equipment or a third-party platform, serving as the main input parameter of the method of this invention.

[0132] Through the above application scenarios and basic parameter settings, a representative multi-intersection, multi-level road cooperative control environment was constructed, providing a foundation for subsequent calculation of travel time based on real-time vehicle speed and phase difference recursion, thereby intuitively demonstrating the application effect of this invention in actual traffic control.

[0133] (II) Vehicle speed data acquisition and processing In this embodiment, vehicle speed data, as a core parameter reflecting the road traffic operation status, is acquired and processed through multi-source data fusion. Specifically, the system establishes communication connections with roadside detection equipment and third-party data platforms to acquire vehicle speed information for each road segment in real time. The roadside detection equipment may include geomagnetic detectors, video detection equipment, or radar detection devices for collecting vehicle speed data; the third-party data platform can provide regional vehicle speed distribution data based on floating cars or navigation terminals, thereby compensating for the spatial coverage limitations of single-point detection equipment.

[0134] Because raw vehicle speed data is easily affected by environmental interference, equipment errors, and communication delays during the collection process, it exhibits a certain degree of random fluctuations and outliers. Therefore, preprocessing of the acquired data is necessary to improve its stability and reliability. In this embodiment, a time window smoothing method is preferably used to process the vehicle speed data, that is, averaging or weighting the vehicle speed over multiple consecutive sampling periods to reduce the impact of instantaneous fluctuations on the results. In another embodiment, an exponential weighted average method can also be used to recursively update the vehicle speed data, so that the current vehicle speed reflects both the latest traffic conditions and retains historical trends.

[0135] After smoothing, the system further identifies anomalies in the vehicle speed data. Specifically, when vehicle speed data is detected to exceed a preset physical reasonable range, or when the change in vehicle speed between adjacent sampling periods exceeds a set threshold, the data is judged as abnormal. Furthermore, if the number of valid sampled data points within a certain time period is lower than a preset threshold, the confidence level of the vehicle speed data for that period is also considered insufficient.

[0136] To address the aforementioned anomalies, this embodiment employs multiple processing strategies to correct vehicle speed data. Clearly abnormal speed data can be directly discarded; data that slightly deviates from the normal range can be limited to a reasonable interval using a limiting method; and data with low confidence levels can have their weight reduced in subsequent calculations to minimize their impact on the results.

[0137] In actual operation, vehicle speed data may be missing, for example, due to detection equipment failure or communication interruption. To address this issue, this embodiment introduces a data compensation mechanism. When valid vehicle speed data cannot be obtained for a certain road segment at the current time, the system can generate a compensated speed by weighted fusion based on the vehicle speed information of adjacent road segments, the most recent valid vehicle speed of that road segment, and the average vehicle speed of the same historical time period. In this way, the ability of missing data to represent traffic conditions can be restored to a certain extent, avoiding the failure of overall timing calculation due to the lack of single-point data.

[0138] Through the above data acquisition and processing, the system ultimately obtains the effective vehicle speed data for each road segment. This effective vehicle speed not only accurately reflects the current traffic conditions but also exhibits good stability and continuity, thus providing a reliable input basis for subsequent target travel time calculations and multi-intersection phase difference recursion.

[0139] (III) Calculation of target travel time After obtaining the effective vehicle speeds for each road segment, this embodiment calculates the travel time of a vehicle from the upstream intersection to the downstream intersection based on the road segment length and the effective vehicle speed, thereby providing key time parameters for multi-intersection coordinated control.

[0140] Specifically, for road segment i, let its length be... The corresponding effective vehicle speed is The basic travel time for this road segment can be expressed as: Formula (1); in, A preset minimum vehicle speed threshold is used to avoid calculation results being distorted due to an excessively small denominator in low-speed or congested conditions. Preferably, Values ​​within the range of 5 km / h to 10 km / h can be used, which are converted to approximately 1.39 m / s to 2.78 m / s when used in calculations.

[0141] The aforementioned basic travel time primarily reflects the time required for vehicles to traverse the road segment under ideal, continuous driving conditions. However, in actual traffic operations, factors such as vehicle starts at intersections and queuing can affect travel time. Therefore, in this embodiment, a correction term is further introduced to the basic travel time to improve the consistency between the calculated results and actual traffic conditions.

[0142] In a preferred embodiment, the target passage time can be expressed as: Formula (2); Indicates the target travel time for road segment i; This represents the vehicle start-up time loss, with a preferred value of 2 to 4 seconds. Indicates the number of vehicles queuing on the current road segment or at the corresponding entrance lane; Indicates the number of lanes in this road section; This represents the saturation flow rate per unit lane, which is the number of vehicles that can pass through each lane per second. This represents the queuing time correction coefficient, which is a dimensionless parameter. The preferred value is 0.5 to 2. It is used to characterize the correction relationship between the queuing vehicle release process and the theoretical queuing dissipation time.

[0143] By introducing the above correction terms, the impact of vehicle start-up delays at intersections and the queue dissipation process on travel time can be effectively considered, making the calculation results closer to the actual traffic operation status.

[0144] In another implementation, when queue length data is unavailable or has low confidence, only the basic passage time can be used for calculation, or historical average queue data can be used for estimation instead, thereby ensuring that the system can still operate stably even when the data is incomplete.

[0145] It should be noted that the target passage time is not only used to describe the traffic characteristics of a single road segment, but also serves as a key parameter for the "passage time propagation" of vehicles, used for the recursive calculation of phase differences between multiple intersections. By concatenating the target passage times of each road segment according to the road network topology, the arrival sequence of vehicles between multiple consecutive intersections can be reflected, thus providing a basis for achieving coordinated traffic release.

[0146] Furthermore, in practical applications, the calculation cycle for the target travel time can be set according to the system's real-time requirements. Preferably, the vehicle speed data update cycle is 5 to 10 seconds, while the calculation cycle for travel time and timing parameters can be set to 10 to 60 seconds, thus ensuring both response speed and system stability.

[0147] Using the above method, this embodiment realizes the calculation of target passage time based on real-time vehicle speed, providing an accurate and stable time basis for subsequent phase difference extrapolation and signal timing generation.

[0148] (iv) Recursive calculation of phase difference at multiple intersections After obtaining the target travel time for each road segment, this embodiment recursively calculates the phase difference parameters between multiple adjacent intersections based on the target travel time and under the constraints of the traffic network topology, thereby establishing a coordinated control relationship between multiple intersections.

[0149] Specifically, the timing reference intersection is taken as the starting point for recursion. Let the timing reference intersection be an intersection. Its phase offset is set to the initial value: Formula (3); in, This indicates that the timing reference intersection is used as the phase offset reference point; in other implementations, it can also be... Set to the preset baseline offset.

[0150] For downstream intersections adjacent to the benchmark intersection Based on the target travel time of the road segment between the two Its phase offset can be calculated as follows: Formula (4); Where C represents the signal control period, This indicates a modulo operation, used to ensure that the offset falls within a period range.

[0151] For further downstream intersections The phase offset can be calculated using a recursive method: Formula (5); in, Indicates intersection To the intersection The target travel time for the road sections between them.

[0152] Through the above recursive calculation, the phase difference relationship between each intersection can be established step by step along the direction of vehicle travel, so that vehicles can arrive at consecutive intersections at the expected time, thereby achieving coordinated passage.

[0153] In practical applications, because the adjustable range of phase offset in signal controllers is limited, it is necessary to constrain and judge the calculated offset. Let the allowable offset range be... Then, the recursive result is subjected to amplitude limiting: Formula (6); in, This indicates the corrected phase offset. and These represent the minimum and maximum permissible phase offsets of the signal, respectively, in seconds.

[0154] When the original calculated value When the value exceeds the allowable range, the difference between it and the correction value can be expressed as: ; ; in, This indicates the phase offset of the previous upstream intersection after feedback correction; This indicates the phase offset at the previous upstream intersection before the feedback correction; This represents the error feedback coefficient, used to control the proportion of offset error distributed to the upstream intersection, with a preferred value of 0 to 1.

[0155] In a preferred embodiment, the deviation amount As an error feedback signal, it is transmitted to the previous upstream intersection, and the phase offset of the previous upstream intersection is corrected according to the above formula, thereby reducing the cumulative effect of offset error in the multi-intersection recursion process and improving the overall coordinated control accuracy.

[0156] In addition, in the case of multi-branch road networks or complex intersection structures, the main coordination path can be selected according to the road network topology, and additional corrections can be made to non-main path intersections to ensure the overall coordination effect.

[0157] It should be noted that the phase difference recursive calculation is based directly on the target travel time and is not dependent on traffic simulation or multi-round optimization processes. Therefore, it has the characteristics of high computational efficiency and strong real-time performance. This method can update the coordination parameters of multiple intersections in a short time and is suitable for dynamically changing traffic environments.

[0158] Through the above recursive calculation process, this embodiment realizes the continuous generation of phase difference parameters between multiple intersections, providing a basis for determining subsequent signal timing parameters, thereby achieving the goal of multi-intersection coordinated control.

[0159] In a preferred embodiment, to avoid the impact of error accumulation during the multi-intersection phase difference recursion process on the overall coordination effect, the present invention further introduces an error feedback correction mechanism.

[0160] Specifically, when the phase offset at a certain intersection exceeds the allowable adjustment range and a limiting correction is completed, the deviation between the original offset and the corrected offset is used as an error feedback signal: ; in: Indicates the original phase offset; This represents the phase offset after constraint correction; This indicates the deviation.

[0161] Based on this, the offset of adjacent upstream intersections is corrected by feedback: ; in: This indicates the upstream intersection offset after feedback correction; This is the error distribution coefficient, used to control the proportion of error distribution between adjacent intersections, and its preferred value is 0.3 to 0.8.

[0162] In a further embodiment, the error feedback process can be iteratively processed, that is, after completing one correction, the constraint judgment is re-performed, and the calculation is stopped after the convergence condition is met or the preset number of iterations is reached.

[0163] The aforementioned error feedback correction mechanism can effectively suppress the accumulation and spread of offset errors caused by local constraints in the multi-intersection recursion process, thereby improving the overall coordination control accuracy and ensuring a more stable and continuous temporal relationship between intersections.

[0164] (v) Calculation of green light duration After completing the recursive calculation of phase differences at multiple intersections, it is necessary to further determine the green light duration for each phase at each intersection to achieve a reasonable allocation of traffic demand in different directions. In this embodiment, the calculation of green light duration comprehensively considers basic timing requirements and real-time traffic state parameters, thereby achieving dynamic adjustment.

[0165] Specifically, for intersections For a given phase, the green light duration is adjusted based on the base green light duration. Let the base green light duration be... Then, the green light duration is dynamically adjusted by taking into account factors such as vehicle speed, traffic flow, and queue length. The calculation expression can be represented as: (Formula 7); in: This indicates the duration of the green light corresponding to the phase; This indicates the duration of the green light corresponding to the phase; This indicates the basic green light duration, with a preferred value of 15 s to 25 s; Indicates the effective speed in the corresponding direction; This represents the free-flow velocity, preferably taken as 50 km / h to 60 km / h; Indicates traffic flow in the corresponding direction; Indicates the number of lanes; This represents the saturation flow rate per unit lane; This is a green light duration correction factor, measured in seconds, used to adjust the impact of vehicle speed deviation, traffic flow saturation, and normalized queue length on green light duration.

[0166] In the above formula, when the vehicle speed decreases, the term ( The green light duration will be appropriately extended to alleviate congestion when traffic flow or queue length increases; when traffic volume or queue length increases, the green light duration will also be extended accordingly to improve the traffic capacity in that direction.

[0167] After calculating the green light duration, it needs to be constrained to meet the basic requirements of signal control. Specifically, minimum and maximum limits are imposed on the green light duration, expressed as follows: (Formula 8); Indicates the duration of the green light after the constraint; This indicates the minimum green light duration, in seconds. This indicates the maximum green light duration, in seconds.

[0168] By implementing the above constraints, we can avoid the problems of vehicles being unable to pass normally due to excessively short green light durations, or vehicles experiencing reduced traffic efficiency in other directions due to excessively long green light durations.

[0169] In a preferred embodiment, the green light duration for each phase can be normalized to ensure that the sum of the green light durations for all phases is consistent with the signal cycle. When the sum of the green light durations for each phase is not equal to the total effective green light duration after deducting the yellow and all-red light periods from the cycle, adjustments can be made proportionally to ensure the rationality of time allocation within the cycle.

[0170] In addition, in practical applications, different weights can be set for different directions according to traffic demand. For example, a higher weight can be set for the main directions, so as to ensure overall efficiency while taking into account the key traffic directions.

[0171] By using the green light duration calculation method described above, this embodiment can dynamically allocate the passage time of each phase according to the real-time traffic conditions, making signal control more refined and adaptive, thereby improving intersection traffic efficiency and reducing vehicle delays.

[0172] (vi) Generation and issuance of control commands After calculating timing parameters such as signal cycle, green light duration, and phase offset, these parameters need to be converted into control commands that the signal controller can recognize and execute, and then sent to the signal control equipment at the corresponding intersection to achieve dynamic adjustment of traffic signals.

[0173] Specifically, the system first encapsulates the timing parameters generated at each intersection in a structured manner to form standardized control command data. The control commands include at least the following: intersection identification information, control cycle, green light duration for each phase, phase offset, and the effective time of the control parameters. The effective time can be set to the end of the current cycle or a specified future time according to the system scheduling strategy to avoid abrupt changes in the control parameters during execution.

[0174] In a preferred embodiment, in order to improve the system's adaptability to different types of existing signal equipment, the system preferably first identifies and models the control capabilities of the target signal before generating control commands.

[0175] Specifically, the system pre-establishes a signal controller capability information table, and the capability information includes at least one or more of the following: Signal model or equipment type; Communication protocol type; Supported control parameter types; Adjustable parameter range; Does it support period length adjustment? Does it support adjusting the green light duration? Does it support phase offset adjustment? Does it support calling preset schemes? Does it support incremental control mode?

[0176] During the system initialization phase or signal access phase, the capability information can be obtained through communication handshake, protocol reading, configuration file loading, or preset device files.

[0177] After obtaining the target signal's capability information, the control output module selects the corresponding control mode based on the capability information.

[0178] For example: (1) When the target signal supports direct adjustment of the cycle, green light duration and offset parameters, the system will directly convert the calculated timing parameters into corresponding parameters and issue instructions. (2) When the target signal does not support real-time parameter adjustment but supports preset scheme calling, the system maps the current timing parameter to the preset scheme number that is closest to it and outputs the corresponding scheme switching instruction; (3) When the target signal only supports incremental adjustment of limited parameters, the system generates an incremental adjustment command based on the difference between the current operating parameters and the target parameters.

[0179] By employing the above methods, the system can achieve dynamic timing control adaptation for different types of signal equipment without changing the existing internal control logic and hardware structure of the signal, thereby improving system compatibility and reducing engineering implementation costs.

[0180] During instruction generation, timing parameters can be adapted to different signal controllers based on their communication protocols and control methods. For signals that support direct parameter configuration, parameters such as cycle length, green light duration, and offset can be directly written into the control register. For signals that only support preset scheme calls, the scheme closest to the current calculation result can be selected from the pre-stored timing scheme library. For signals that support incremental adjustment, only the parameter change amount can be issued to fine-tune the current operating scheme.

[0181] After the control command is generated, it is sent to the traffic signal equipment at the corresponding intersection via the communication module. The communication method can be wired communication (such as fiber optic or Ethernet) or wireless communication (such as 4G / 5G networks or dedicated wireless networks). A reliable transmission mechanism can be employed during transmission to ensure that the command accurately reaches the traffic signal.

[0182] In a preferred embodiment, the system also monitors the execution status of the signal. Specifically, after a control command is issued, feedback information from the signal is obtained through the communication interface to confirm whether the command has been successfully executed. If an execution failure or communication abnormality is detected, the control command can be resent or a backup control strategy can be switched to ensure the continuity of system operation.

[0183] Furthermore, to avoid traffic fluctuations caused by abrupt changes in timing parameters between different cycles, this embodiment can implement smooth control over parameter changes. For example, a maximum adjustment threshold is set for the variation range of green light duration and offset, allowing them to gradually adjust to the target value over multiple control cycles, thereby improving the stability of traffic operation.

[0184] Through the above-described process of generating and issuing control commands, this embodiment realizes closed-loop control from timing parameter calculation to signal execution, enabling the multi-intersection coordinated control strategy to be effectively implemented in actual traffic environments and ensuring that the system has good real-time performance, stability and equipment compatibility.

[0185] In a preferred embodiment, to improve the stability of the system under data anomalies or computational anomalies, the present invention also introduces a historical timing scheme database matching mechanism.

[0186] Specifically, the system pre-builds a historical timing scheme library to store signal timing schemes under different traffic conditions. Each historical timing scheme is associated with a corresponding traffic condition feature, which includes at least vehicle speed, traffic flow, queue length, road grade, and time period information.

[0187] During real-time operation, if any of the following conditions are detected: Real-time vehicle speed data is missing or the confidence level is below a preset threshold; Communication errors prevented data retrieval; The timing calculation results are outside the control range or do not meet the constraints; The system triggers the historical timing scheme matching process.

[0188] Specifically, the current traffic state feature vector is first constructed: ; in, Indicates the effective vehicle speed. Indicates traffic flow. Indicates the queue length. This represents the road grade code or road segment attribute characteristic value. This indicates the time period encoding. Preferably, main roads, secondary roads, and branch roads are mapped to different level codes, for example: main roads = 3, secondary roads = 2, branch roads = 1; morning peak, off-peak, and evening peak are mapped to different time period codes, for example: morning peak = 1, off-peak = 2, evening peak = 3.

[0189] Subsequently, historical state vectors were extracted from the historical timing scheme library. And calculate the similarity between the current state and historical states. Preferably, a weighted distance model can be used: ; in: Weights for each feature; Normalization coefficient or standard deviation; The weight It can be preset or dynamically adjusted based on historical operating results, road importance, or traffic control objectives.

[0190] The timing parameters corresponding to the historical scheme with the smallest distance are selected as candidate output schemes.

[0191] In a further implementation, a similarity threshold can be set. When the minimum distance is greater than the preset threshold, the historical scheme is not adopted, but a degradation control strategy is executed instead.

[0192] Finally, the matched historical timing schemes are converted into control commands and output to the signal controllers for execution, thereby ensuring the continuity and stability of system operation in abnormal situations.

[0193] (vii) System performance After completing the above control process, the system described in this embodiment is tested in a real traffic environment to verify its application effect in dynamic timing control of multiple intersections. The test area is a traffic corridor composed of multi-level roads in a typical city, containing multiple continuously signal-controlled intersections, and is continuously operated during morning and evening peak hours and off-peak hours.

[0194] During system operation, the method continuously acquires real-time vehicle speed data for each road segment according to a preset cycle, and dynamically updates the target travel time, phase difference parameters, and signal timing parameters, thereby achieving real-time adjustment of signal control at each intersection. By comparing and analyzing traffic operation indicators before and after system operation, significant optimization effects can be observed.

[0195] Specifically, regarding average vehicle delay, compared to fixed timing or traditional inductive control methods, the average delay time of the road network is significantly reduced after the system is implemented in this embodiment, with a reduction generally reaching 15% to 30%. Regarding the number of vehicle stops, due to the continuous coordinated release between multiple intersections, the number of stops during vehicle passage through consecutive intersections is reduced, with an overall decrease of approximately 10% to 25%. In terms of road network traffic efficiency, by statistically analyzing the number of vehicles passing through road segments per unit time, the overall traffic capacity is improved by approximately 20%.

[0196] Furthermore, in locally congested road sections, the method of this invention can reflect traffic conditions in a timely manner through changes in vehicle speed and adjust timing parameters at downstream intersections, thereby alleviating queue congestion. Test results show that during peak hours, the trend of queue length growth is effectively suppressed, the duration of congestion is significantly shortened, and the speed of traffic recovery is improved.

[0197] Regarding system stability, thanks to the introduction of a vehicle speed data anomaly handling and compensation mechanism, the system can still output reasonable timing results and avoid control failure even when some detection devices experience data loss or anomalies. Simultaneously, through a historical timing scheme recall mechanism, the system can quickly switch to a backup scheme in the event of communication or calculation anomalies, ensuring the continuity of traffic control.

[0198] Furthermore, in tidal traffic scenarios, this invention dynamically determines traffic priority direction and smoothly switches between them, enabling timely responses to traffic demands in different directions and avoiding the control lag issues associated with traditional fixed-time switching. Tests showed a significant improvement in traffic efficiency for the dominant traffic direction, without causing significant adverse effects on non-priority directions.

[0199] At the engineering application level, the system described in this embodiment can achieve dynamic timing control simply by adjusting parameters without changing the existing signal phase structure and safety control logic, exhibiting good equipment compatibility. The system can be directly deployed in existing traffic control platforms without requiring modifications to the signal hardware, thereby reducing implementation costs and improving the feasibility of widespread adoption.

[0200] In summary, the system described in this embodiment can achieve dynamic coordinated control based on real-time vehicle speed in complex multi-intersection and multi-level traffic network environments. It has significant effects in improving traffic efficiency, reducing delays, and enhancing system stability, thus verifying the effectiveness and practical value of the method of this invention.

[0201] (viii) Summary of Features of Implementation Examples As can be seen from the above embodiments, the intelligent traffic signal dynamic timing control method and system based on real-time vehicle speed and road network level anchoring provided by the present invention has a clear technical implementation path and good engineering application effect. Its main features are reflected in the following aspects.

[0202] Firstly, in terms of the data-driven approach, this embodiment uses real-time vehicle speed as the core input parameter and obtains stable and reliable effective vehicle speed data through a multi-step processing mechanism including smoothing, anomaly identification, and missing data compensation. Compared to methods that rely solely on historical data or single detection data, this method can more accurately reflect the current traffic operation status and provide a high-quality data foundation for subsequent timing calculations.

[0203] Secondly, regarding the coordination and control mechanism, this embodiment constructs a traffic network topology model and introduces a timing benchmark intersection anchoring method based on road level, establishing a unified coordination reference system among roads of different levels. Based on this, it uses target travel time to recursively calculate the phase difference between multiple intersections, realizing the transformation from single-intersection control to multi-intersection collaborative control, significantly improving the overall coordination capability of the road network.

[0204] Furthermore, in terms of calculation methods, this embodiment directly generates signal timing parameters using analytical calculations, without relying on complex traffic simulation models or multi-round optimization search processes. Through the calculation chain of "vehicle speed - travel time - phase difference recursion - timing generation", the timing parameters are generated and dynamically updated quickly, thus balancing computational efficiency and control accuracy.

[0205] Furthermore, in terms of control strategy, this embodiment comprehensively considers various traffic condition factors such as vehicle speed, traffic flow, and queue length to dynamically adjust the green light duration, making signal timing more refined and adaptive. Simultaneously, by setting parameter constraints and a smooth adjustment mechanism, it effectively avoids traffic fluctuations caused by sudden changes in timing parameters, improving system operational stability.

[0206] In terms of system reliability, this embodiment introduces a data compensation mechanism and a historical timing scheme recall strategy, which enables the system to maintain stable operation in the event of data anomalies or communication interruptions, thereby enhancing the system's fault tolerance and robustness.

[0207] Finally, at the engineering implementation level, this embodiment does not require changes to the phase structure and safety control logic of the existing traffic signal. Dynamic control can be achieved simply by adjusting parameters such as cycle, green light duration, and offset. It has good equipment compatibility and low implementation cost, making it easy to promote and apply in existing traffic control systems.

[0208] This embodiment not only verifies the feasibility of the technical solution of the present invention, but also demonstrates its comprehensive advantages in multi-intersection coordinated control, real-time response capability and system stability, further illustrating that the present invention has significant technical progress and practical application value.

[0209] In summary, this invention, by introducing real-time vehicle speed data and combining it with the traffic network topology and road hierarchy, constructs a multi-intersection phase difference recursive mechanism based on target travel time, realizing the dynamic generation and coordinated control of signal timing parameters. Compared with existing technologies, this invention has significant advantages in improving the real-time performance of traffic signal control, enhancing multi-intersection coordination capabilities, and adapting to complex road network environments, demonstrating promising application prospects and widespread application value.

[0210] It should be noted that the above embodiments are merely preferred embodiments of the present invention, used to illustrate the technical solutions of the present invention, and not to limit the scope of protection of the present invention. Those skilled in the art can make various modifications, equivalent substitutions, or improvements to the above embodiments without departing from the spirit and substance of the present invention, and all such modifications, substitutions, or improvements should fall within the scope of protection of the present invention.

[0211] Furthermore, the specific parameters, structural forms, step sequences, and implementation methods described in the specification are merely illustrative and do not constitute a limitation of the present invention. In practical applications, relevant parameters can be adjusted or some steps can be appropriately combined or replaced according to specific needs without affecting the substantive content of the present invention.

[0212] The terminology used in this specification is for describing particular embodiments only and is not intended to limit the invention. Unless otherwise expressly stated, terms such as "comprising" and "including" should be understood as open-ended descriptions, meaning that they include, but are not limited to, the listed features.

Claims

1. A method for dynamic timing control of intelligent traffic signals based on real-time vehicle speed and road network level anchoring, characterized in that, The method, applied to a traffic signal control system for a multi-level road network, includes: S1. Construct a traffic network topology model, classify roads into levels, and determine the timing benchmark intersections based on the road level relationships; S2. Obtain real-time vehicle speed data for each road segment, as well as traffic flow data and / or queue length data for each road segment, and perform smoothing, anomaly identification, and missing data compensation on the vehicle speed data to obtain the effective vehicle speed. S3. Calculate the target travel time for a vehicle to travel from the upstream intersection to the downstream intersection based on the road segment length and the effective vehicle speed; S4. Starting from the timing reference intersection, calculate the phase difference parameters of multiple intersections recursively along the road network topology based on the target travel time of adjacent road segments, and perform constraint correction when the phase difference exceeds the allowable range. S5. Based on the phase difference parameter and combined with the traffic flow data and / or queue length data, calculate at least one timing parameter among the cycle length, green light duration and offset of each intersection; S6. Convert the timing parameters into signal control commands and send them to the signal controller for execution to achieve multi-intersection coordinated control.

2. The method according to claim 1, characterized in that, Step S2 includes: Smoothing of vehicle speed data is achieved by using a sliding time window average or an exponentially weighted average. It also identifies anomalies in data that exceed the preset range, have a change magnitude exceeding the threshold, or have an insufficient number of samples. Perform actions such as removing, limiting, or downgrading abnormal data.

3. The method according to claim 1, characterized in that: When vehicle speed data is missing or the confidence level is insufficient, compensation is obtained by fusing and compensating based on the vehicle speeds of adjacent road segments, historical vehicle speeds, and the most recent effective vehicle speed.

4. The method according to claim 1, characterized in that: The target travel time is calculated based on the ratio of road segment length to effective vehicle speed, and includes the start-up loss time and queuing correction.

5. The method according to claim 1, characterized in that, Step S4 includes: Using the timing reference intersection offset as the initial value, the offset of each intersection is generated by progressively accumulating the target travel time between adjacent intersections. When the offset exceeds the allowable range, amplitude limiting is performed, and error feedback is used to correct the recursive results of adjacent intersections.

6. The method according to claim 1, characterized in that: The green light duration is based on the basic green light duration and is dynamically adjusted in combination with vehicle speed, traffic flow and queue length, while satisfying minimum and maximum green light constraints.

7. The method according to claim 1, characterized in that, Also includes: Based on bidirectional vehicle speed, traffic flow, or queue length, a coordination priority direction is determined, and a timing scheme for continuous release is generated preferentially for the direction.

8. The method according to claim 7, characterized in that: The coordination direction switching adopts a dual threshold triggering and continuous cycle judgment mechanism, and achieves a smooth transition through parameter gradual change.

9. The method according to claim 1, characterized in that, Also includes: When real-time data is abnormal, communication is abnormal, or the calculation results are outside the control range, a timing scheme similar to the current traffic condition is matched from the historical timing scheme library and executed.

10. A dynamic timing control system for intelligent traffic signals based on real-time vehicle speed and road network level anchoring, characterized in that, include: The road network modeling module is configured to build a traffic road network topology model, classify roads into levels, and determine timing benchmark intersections based on road level relationships. The data processing module, connected to the road network modeling module, is configured to acquire real-time vehicle speed data for each road segment and traffic flow data and / or queue length data for each road segment, perform smoothing processing, anomaly identification and missing data compensation on the vehicle speed data, and output the effective vehicle speed. The travel time calculation module, connected to the data processing module, is configured to calculate the target travel time for a vehicle to travel from the upstream intersection to the downstream intersection based on the road segment length and the effective vehicle speed. The phase difference recursion module, connected to the travel time calculation module and the road network modeling module, is configured to recursively calculate the phase difference parameters of multiple intersections based on the target travel time of adjacent road segments along the road network topology, starting from the timing reference intersection, and to perform constraint correction when the phase difference exceeds the allowable range. The timing generation module, connected to the phase difference recursion module, is configured to generate at least one timing parameter among cycle length, green light duration, and offset for each intersection based on the phase difference parameter and in combination with the traffic flow data and / or queue length data. The control output module, connected to the timing generation module, is configured to convert the timing parameters into signal control commands and send them to the signal controller for execution.

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