A traffic comprehensive command and dispatching system and method based on internet of things perception

Abstract

The application belongs to the technical field of intelligent traffic internet of things application, and discloses a traffic comprehensive command and dispatching system and method based on internet of things sensing, which comprises a traffic situation sensing module, which is used for collecting the operation data of each traffic section in real time through internet of things equipment, aligning the operation data according to time, and obtaining the time sequence situation data of the traffic section; a section intervention judgment module, which is used for quantitatively analyzing the natural evolution characteristics of each traffic section according to the time sequence situation data, and judging each traffic section as an intervenable section or an uninterivable section; a dispatch generation and execution module, which is used for generating and executing the corresponding dispatch instruction for the traffic section in the intervenable section, and prohibiting generating any dispatch instruction for the traffic section in the uninterivable section; and effectively improving the overall dispatching efficiency and operation reliability of the urban traffic command system under complex and changeable traffic environment.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation Internet of Things (IoT) application technology, and more specifically, to a comprehensive traffic command and dispatch system and method based on IoT sensing. Background Technology

[0002] Existing integrated traffic command and dispatch systems and methods mainly suffer from the following problems: In existing technologies, most integrated traffic command and dispatch systems typically intervene in traffic sections based on threshold triggering, rule matching, or human experience. Their dispatch decisions primarily focus on whether traffic conditions deviate from set thresholds or exhibit abnormal states, with little distinction between whether these abnormal states are caused by the natural evolution of the traffic system itself and whether they can be effectively improved through external dispatching measures. Even when traffic conditions are relatively stable, change slowly, or remain within a safe operating range, unnecessary dispatching operations may still be triggered, easily leading to over-dispatching or ineffective dispatching, thus adversely affecting the continuous and stable operation of the traffic system.

[0003] Furthermore, existing technologies for analyzing traffic situation changes primarily focus on absolute indicators, such as average vehicle speed, traffic flow, and congestion index, lacking a quantitative characterization of the rate of change of traffic situation over time. This makes it difficult to distinguish whether changes in traffic conditions are caused by system fluctuations, random noise, external disturbances, or available scheduling space. These shortcomings make scheduling systems more sensitive to short-term fluctuations and random disturbances, resulting in poor overall stability and robustness.

[0004] In complex traffic scenarios involving multiple sections and road networks, different traffic sections vary significantly in length, capacity, traffic composition, and operational characteristics. Existing integrated traffic command and dispatch systems typically use uniform thresholds or manually configured rules to determine the dispatchability of different sections. This lacks a reusable, quantifiable, and interpretable method for determining the suitability of section intervention, making it difficult to establish stable constraints on the feasibility and risks of dispatching different traffic sections at the system level.

[0005] On the other hand, existing technologies have significant shortcomings in the cancellation mechanism once a dispatch instruction is issued and executed. Current cancellation timing largely relies on manual judgment or fixed-time configuration, lacking time constraints that match the physical characteristics and operational status of traffic sections. Furthermore, they fail to clearly distinguish between the timeframe within which a dispatch instruction can still be safely cancelled and the timeframe within which irreversible traffic impacts have occurred. Attempting to cancel a dispatch instruction when its effects have already spread to distant road sections or affected a large number of vehicles can easily trigger secondary traffic disturbances and even pose traffic safety risks.

[0006] Even when existing systems have scheduling cancellation windows, they generally use a uniform, static rollback time, failing to fully consider the differences in segment length, capacity, and actual vehicle speed across different traffic sections. This results in missed cancellation opportunities when the rollback window is set too short, and unnecessary scheduling uncertainty when set too long, making it difficult to adapt to different traffic conditions such as peak hours, smooth traffic, or congestion. Furthermore, existing cancellation mechanisms typically ignore system response delays in the perception, communication, computing, and execution links, as well as random fluctuations and differences in driving behavior during traffic operations, failing to effectively control the risk of further disturbances that the rollback operation itself may introduce.

[0007] Furthermore, existing technologies often employ the immediate restoration of original control parameters for dispatch cancellation, causing significant jumps in traffic signal timing, lane control, or restriction strategies within a short period. This can easily trigger new traffic shockwaves, leading to secondary congestion or localized traffic instability. Traditional systems typically rely on human experience or simple rules for triggering cancellation, lacking a quantitative assessment mechanism based on changes in traffic conditions. This makes it difficult to distinguish between acceptable and unacceptable disturbances, resulting in unclear cancellation conditions. Existing cancellation strategies are simplistic and cannot flexibly adjust the magnitude and pace of cancellation based on traffic conditions. They struggle to balance dispatch safety with traffic continuity, and in complex traffic environments, the cancellation itself may even introduce greater negative impacts than the original dispatch instructions.

[0008] In view of this, the present invention proposes a traffic integrated command and dispatch system and method based on Internet of Things (IoT) sensing to solve the above problems. Summary of the Invention

[0009] To overcome the aforementioned shortcomings of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a traffic integrated command and dispatch system based on Internet of Things (IoT) sensing, comprising: The traffic situation awareness module is used to collect operational data of each traffic segment in real time through IoT devices, align the operational data according to time, and obtain the time-series situation data of the traffic segment. The section intervention determination module is used to quantitatively analyze the natural evolution characteristics of each traffic section based on time-series situation data, and determine each traffic section as an interventionable or non-interventionable zone. The dispatch generation and execution module is used to generate and execute corresponding dispatch instructions for traffic segments within the interventionable zone. For traffic segments within the non-interventionable zone, the generation of any dispatch instructions is prohibited. The rollback window management module is used to save the original configuration state of the corresponding traffic segment before the dispatch instruction takes effect, and to determine whether the dispatch instruction is revocable. If it is revocable, a revocable rollback window is created for the traffic segment affected by the dispatch instruction. The scheduling effect evaluation module is used to evaluate the changes in traffic situation in each traffic segment after the scheduling command is executed, calculate the situation increment caused by the scheduling, and trigger cancellation and rollback when the situation increment exceeds the preset situation increment threshold. The scheduling command configuration is gradually restored to the original configuration state according to the preset rollback ratio.

[0010] Preferably, the method for collecting operational data for each traffic section includes: The operation data of traffic sections is collected in real time by IoT sensing devices deployed in various traffic sections. The IoT sensing devices include roadside sensing devices, vehicle sensing devices and communication access devices. Roadside sensing devices are installed on the roadside of traffic sections to collect information related to vehicle traffic passing through the traffic section. This information includes the number of vehicles, driving speed, lane occupancy data, queue status data, and passage duration. Vehicle sensing devices are used to obtain the driving status information of the vehicles themselves and associate the driving status information with the corresponding traffic sections. The communication access equipment is used to upload vehicle traffic-related information and driving status information collected by roadside sensing devices and vehicle sensing devices to the traffic integrated command and dispatch system in real time via wired or wireless communication. During the data collection process, each IoT sensing device continuously senses the operational status within the traffic section according to a preset sampling period, and encapsulates the collected vehicle traffic-related information and driving status information into data units containing traffic section identifiers and collection time identifiers, forming operational data that reflects the current operational status of each traffic section.

[0011] Preferably, the method for acquiring the time-series situational data of traffic sections includes: The data collection time identifier carried in the operation data is parsed, and a unified time reference sequence is constructed based on a preset time resolution. The operation data from different IoT sensing devices are collected by segment according to the traffic segment identifier, and the collected operation data is mapped to the corresponding time position in the unified time reference sequence. During the mapping process, when multiple sources of operational data exist for the same traffic segment at the same time location, the multi-source operational data are fused to generate segment status data that characterizes the operational status of the traffic segment at that time location. When corresponding operational data is missing at any time point, that time point is marked as a placeholder or left empty to ensure that each traffic segment forms a structurally continuous time series; through time-unified alignment and mapping processing, time-series situational data of traffic segments are formed in chronological order.

[0012] Preferably, the method for determining each traffic section as an intervention-friendly or non-intervention-friendly zone includes: For each traffic segment, the traffic situation intensity corresponding to the traffic segment at different times is obtained under continuous time sampling conditions, and the traffic situation changes at adjacent time locations are calculated in units of a preset situation sampling time interval. By analyzing the relationship between the magnitude of traffic situation changes and the time interval between adjacent sampling times, the natural evolution rate of traffic situation, which reflects the intensity of natural changes in the traffic operation status of a traffic segment, is obtained. After obtaining the natural evolution rate of traffic situation, the operation status of the traffic segment is comprehensively evaluated in combination with the traffic situation intensity at the current time. When the natural evolution rate of traffic conditions in a traffic segment is within a preset threshold for the natural evolution rate of traffic conditions, and the corresponding traffic condition intensity is within a preset threshold for the intensity of traffic conditions, it is determined that the operation state of the traffic segment is dominated by the natural evolution of traffic itself, and thus the traffic segment is determined to be an area that cannot be intervened in. When the natural evolution rate of traffic conditions exceeds the preset threshold for the natural evolution rate of traffic conditions, or when the intensity of traffic conditions exceeds the preset threshold for the intensity of traffic conditions, it is determined that there is room for adjustment and optimization of the traffic section through external scheduling, and the traffic section is determined to be an area that can be intervened.

[0013] Preferably, the method for generating and executing the corresponding scheduling instructions includes: After determining the intervenable and non-intervenable zones of each traffic segment, the determination results of the traffic segments are used as the prerequisite constraints for dispatch control, and the generation and execution of dispatch instructions are selectively controlled. For traffic sections that are identified as intervention zones, based on the time-series situation data corresponding to the traffic section, a dispatch instruction matching the traffic section is generated according to the preset traffic dispatch strategy, and the dispatch instruction is sent to the corresponding field control equipment for execution. For traffic sections that are determined to be non-intervention zones, a dispatch suppression flag is set during the dispatch control process to exclude the traffic section from the dispatch instruction generation process, and prohibit the generation and issuance of any dispatch instructions for the traffic section.

[0014] Preferably, the method for determining whether a scheduling instruction is revocable includes: Before the dispatching instruction officially takes effect, for the traffic section in the intervention zone, the original control configuration status of the traffic section before the dispatching is read and saved. The original control configuration status includes signal timing parameters, lane function configuration parameters, and speed limit or guidance information release parameters. After saving the original control configuration state, the system performs type determination on the generated scheduling instructions, reads the control type identifier carried in the scheduling instructions, and matches the control type identifier with the pre-set set of revocable control types to determine whether the scheduling instructions belong to the revocable type; among them, parameter adjustment type scheduling instructions are determined to be revocable type.

[0015] Preferably, the method for creating a reversible rollback window includes: When a dispatch instruction is determined to be revocable, a revocable rollback window is created for the traffic segment affected by the corresponding dispatch instruction. The time length of the revocable rollback window is calculated based on the segment length of the traffic segment affected by the dispatch instruction and the average driving speed of the traffic segment before the dispatch instruction was executed. A safety factor is introduced into the calculation result to determine the revocable time range from the time the dispatch instruction takes effect to the time the rollback window ends.

[0016] Preferably, the method for calculating the situational increment caused by scheduling includes: After the dispatching instruction is executed, the traffic operation status of the traffic segment affected by the dispatching instruction is continuously monitored, and the time of the dispatching instruction taking effect is used as the evaluation start time. Within the revocable rollback window, the time-series status data of the traffic segment after the dispatching instruction is executed is obtained. The time-series situation data of the traffic segment after the execution of the dispatching instruction is compared with the time-series situation data of the corresponding traffic segment before the execution of the dispatching instruction to obtain the traffic situation difference before and after the execution of the dispatching instruction within the evaluation time window; and the traffic situation difference is accumulated and normalized on the time scale to calculate the situation increment that represents the degree of influence of the dispatching instruction on the overall operation status of the traffic segment.

[0017] Preferably, the method for progressively restoring the scheduling instruction configuration to its original configuration state includes: A preset situation increment threshold is set. The situation increment of the traffic segment affected by the dispatch instruction is compared with the preset situation increment threshold. When the situation increment exceeds the preset situation increment threshold, it is determined that the current dispatch instruction has caused an unacceptable disturbance to the traffic situation and the dispatch is canceled and rolled back. After the scheduling cancellation rollback is triggered, the system does not directly restore the original control configuration state before scheduling. Instead, it proportionally merges the original control configuration state saved before scheduling with the current scheduling control configuration state according to the preset rollback ratio coefficient, and sends the merged control configuration state to the corresponding traffic control equipment for execution, so that the traffic control parameters are restored to the original control configuration state in a gradual manner.

[0018] A traffic integrated command and dispatch method based on Internet of Things (IoT) sensing includes: S1. Real-time collection of operational data from each traffic segment through IoT devices, and alignment of the operational data according to time to obtain temporal status data of the traffic segment; S2. Based on the time-series situation data, the natural evolution characteristics of each traffic section are quantitatively analyzed, and each traffic section is determined as an area that can be intervened or an area that cannot be intervened. S3. Generate and execute corresponding dispatch instructions for traffic segments within the interventionable zone; for traffic segments within the non-interventionable zone, it is prohibited to generate any dispatch instructions. S4. Before the dispatch instruction takes effect, save the original configuration state of the corresponding traffic segment and determine whether the dispatch instruction is revocable. If it is revocable, create a revocable rollback window for the traffic segment affected by the dispatch instruction. S5. After the dispatching instruction is executed, the traffic situation changes in each traffic section are evaluated, the situation increment caused by the dispatching is calculated, and when the situation increment exceeds the preset situation increment threshold, the cancellation rollback is triggered, and the dispatching instruction configuration is gradually restored to the original configuration state according to the preset rollback ratio.

[0019] Compared with the prior art, the present invention has the following beneficial effects: By introducing the natural evolution rate of traffic conditions and combining it with the intensity of the conditions, it is possible to effectively identify sections dominated by the stable operation of the traffic system itself, avoiding meaningless scheduling interventions in such sections, thereby reducing the risk of disturbance to traffic operations by the scheduling system. Instead of relying solely on instantaneous situation indicators, it characterizes the changing patterns of traffic conditions over time, enabling the scheduling system to distinguish between short-term random fluctuations and continuous evolutionary trends. This reduces misjudgments caused by noisy data or occasional changes, improving the system's stability and robustness in complex and dynamic traffic environments. By clearly dividing traffic sections into intervention-friendly and non-intervention-friendly zones, it provides clear spatial constraints for the generation, execution, and rollback mechanisms of scheduling instructions, shifting scheduling control from post-event correction to pre-event screening. This is conducive to building a hierarchical and logically consistent comprehensive traffic command and dispatch system.

[0020] By correlating the length of the revocable rollback window with the length of the traffic segment and vehicle speed, the propagation timescale of scheduling effects within the traffic segment can be accurately characterized. This limits the revocation operation to a safe timeframe before irreversible traffic impacts occur, reducing the likelihood of traffic risks caused by revocation. Dynamically calculating the rollback window for different traffic segments and time periods allows the revocation mechanism to adapt to different road conditions and traffic states, improving the overall applicability of the system. Introducing a safety factor provides a buffer against system response delays and traffic uncertainties, giving the revocation rollback mechanism higher fault tolerance in real-world deployment environments and preventing revocation failures or malfunctions due to link delays or sudden traffic fluctuations. A clearly defined revocable rollback window provides a unified time reference framework for subsequent scheduling effect evaluation, rollback triggering criteria, and proportional rollback execution.

[0021] By comparing the incremental situation of traffic segments affected by dispatch instructions with a preset threshold for incremental situation, cancellation and rollback are triggered only when the dispatch disturbance exceeds the system's acceptable range. This transforms cancellation decisions from experience-based judgments to quantitative assessments based on situation evolution, improving the scientific rigor and stability of the dispatch system. After triggering dispatch cancellation, the system does not directly revert to the original control configuration state before dispatch. Instead, it proportionally merges the original and current configuration states, allowing traffic control parameters to change continuously and gradually, significantly reducing the traffic impact caused by sudden changes in control parameters during cancellation. By setting a rollback coefficient, a one-time rollback or multi-step gradual rollback can be flexibly implemented based on traffic operation status, enhancing the dispatch system's adaptability to different traffic scenarios, time periods, and disturbance intensities. By explicitly modeling the relationship between the pre-dispatch state, current state, and rollback ratio, the dispatch cancellation process has clear control boundaries and predictable behavior, reducing the impact of system anomaly handling on traffic safety. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of the structure of a traffic integrated command and dispatch system based on Internet of Things (IoT) sensing according to the present invention. Figure 2 This is a schematic diagram of a traffic integrated command and dispatch method based on Internet of Things (IoT) sensing according to the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention. Example

[0024] Please see Figure 1 As shown, this embodiment provides a comprehensive traffic command and dispatch system based on Internet of Things (IoT) sensing, specifically including the following steps: The traffic situation awareness module is used to collect operational data of each traffic segment in real time through IoT devices, align the operational data according to time, and obtain the time-series situation data of the traffic segment. The section intervention determination module is used to quantitatively analyze the natural evolution characteristics of each traffic section based on time-series situation data, and determine each traffic section as an interventionable or non-interventionable zone. The dispatch generation and execution module is used to generate and execute corresponding dispatch instructions for traffic segments within the interventionable zone. For traffic segments within the non-interventionable zone, the generation of any dispatch instructions is prohibited. The rollback window management module is used to save the original configuration state of the corresponding traffic segment before the dispatch instruction takes effect, and to determine whether the dispatch instruction is revocable. If it is revocable, a revocable rollback window is created for the traffic segment affected by the dispatch instruction. The scheduling effect evaluation module is used to evaluate the changes in traffic situation in each traffic segment after the scheduling command is executed, calculate the situation increment caused by the scheduling, and trigger cancellation and rollback when the situation increment exceeds the preset situation increment threshold. The scheduling command configuration is gradually restored to the original configuration state according to the preset rollback ratio.

[0025] Methods for collecting operational data for each traffic section include: The operation data of traffic sections is collected in real time by IoT sensing devices deployed in various traffic sections. The IoT sensing devices include roadside sensing devices, vehicle sensing devices and communication access devices. Roadside sensing devices are installed on the roadside of traffic sections to collect information related to vehicle traffic passing through the traffic section. This information includes the number of vehicles, driving speed, lane occupancy data, queue status data, and passage duration. Vehicle sensing devices are used to obtain the driving status information of the vehicles themselves and associate the driving status information with the corresponding traffic sections. The communication access equipment is used to upload vehicle traffic-related information and driving status information collected by roadside sensing devices and vehicle sensing devices to the traffic integrated command and dispatch system in real time via wired or wireless communication. During the data collection process, each IoT sensing device continuously senses the operational status within the traffic section according to a preset sampling period, and encapsulates the collected vehicle traffic-related information and driving status information into data units containing traffic section identifiers and collection time identifiers, forming operational data that reflects the current operational status of each traffic section.

[0026] Methods for obtaining temporal situational data of traffic sections include: The data collection time identifier carried in the operation data is parsed, and a unified time reference sequence is constructed based on a preset time resolution. The operation data from different IoT sensing devices are collected by segment according to the traffic segment identifier, and the collected operation data is mapped to the corresponding time position in the unified time reference sequence. During the mapping process, when multiple sources of operational data exist for the same traffic segment at the same time location, the multi-source operational data are fused to generate segment status data that characterizes the operational status of the traffic segment at that time location. When corresponding operational data is missing at any time point, that time point is marked as a placeholder or left empty to ensure that each traffic segment forms a structurally continuous time series; through time-unified alignment and mapping processing, time-series situational data of traffic segments are formed in chronological order.

[0027] Methods for determining whether a traffic section is an area that can be intervened or not include: For each traffic segment, the traffic situation intensity corresponding to the traffic segment at different times is obtained under continuous time sampling conditions, and the traffic situation changes at adjacent time locations are calculated in units of a preset situation sampling time interval. By analyzing the relationship between the magnitude of traffic situation changes and the time interval between adjacent sampling times, the natural evolution rate of traffic situation is obtained, which reflects the intensity of natural changes in the traffic operation status of a traffic segment and characterizes the spontaneous evolution level of a traffic segment without external scheduling intervention. After obtaining the natural evolution rate of traffic situation, the operation status of the traffic segment is comprehensively evaluated in combination with the traffic situation intensity at the current time. The natural rate of change of traffic conditions is: ;in, Indicates traffic section At the present moment The natural evolution rate of traffic conditions is used to measure the magnitude of natural changes in traffic conditions over time in a traffic segment. Indicates traffic section At the present moment The traffic situation intensity value is used to comprehensively characterize the operational status level of the traffic section at that moment. The traffic situation intensity value can be obtained by normalizing and weighting the characteristics of traffic density, average vehicle speed, traffic flow and occupancy. Indicates traffic section At the previous sampling time (i.e., the current time) Backtracking Traffic situation intensity value corresponding to (time); The status sampling time interval describes the time span between two adjacent traffic status assessments. This time interval is preset by the system or adaptively determined based on the sampling frequency. When the natural evolution rate of traffic conditions in a traffic segment is within a preset threshold for the natural evolution rate of traffic conditions, and the corresponding traffic condition intensity is within a preset threshold for the intensity of traffic conditions, it is determined that the operation state of the traffic segment is dominated by the natural evolution of traffic itself, and scheduling intervention is unlikely to produce an improvement effect, thus the traffic segment is determined to be an area that cannot be intervened in. When the natural evolution rate of traffic conditions exceeds the preset threshold for the natural evolution rate of traffic conditions, or when the intensity of traffic conditions exceeds the preset threshold for the intensity of traffic conditions, it is determined that there is room for adjustment and optimization of the traffic section through external scheduling, and the traffic section is determined to be an area that can be intervened.

[0028] Methods for generating and executing corresponding scheduling instructions include: After determining the intervenable and non-intervenable zones of each traffic segment, the determination results of the traffic segments are used as the prerequisite constraints for dispatch control, and the generation and execution of dispatch instructions are selectively controlled. For traffic sections that are identified as intervention zones, based on the time-series situation data corresponding to the traffic section, a dispatch instruction matching the traffic section is generated according to the preset traffic dispatch strategy, and the dispatch instruction is sent to the corresponding field control equipment for execution. It should be noted that the preset traffic dispatch strategy refers to a set of traffic control rules pre-constructed based on traffic engineering experience and existing traffic control rules before the system runs. This set describes the adjustment objectives and methods to be adopted under different traffic operation conditions. The traffic dispatch strategy uses the time-series situation data of the traffic segment as input. By matching the traffic situation intensity, change trend, and segment operation status, it determines whether active adjustment of the traffic segment is necessary and what type of adjustment should be adopted. After determining that a traffic segment is an intervention-accessible area, the system analyzes the current traffic operation status based on the corresponding time-series situation data and matches the analysis results with the trigger conditions in the preset traffic dispatch strategy. When the trigger conditions of the corresponding dispatch strategy are met, the system determines the adjustment objective and method for the traffic segment and generates a dispatch instruction that matches the spatial location, controlled object, and operation status of the traffic segment. The generated dispatch instruction describes the specific adjustment content in a parameterized form, enabling it to be directly recognized and executed by the corresponding field control equipment.

[0029] Dispatch instructions include instructions for adjusting signal timing parameters, instructions for dynamically switching lane functions, and instructions for issuing speed limits or guidance information. Instructions for adjusting signal timing parameters refer to control commands issued to traffic signal control equipment within a traffic section or adjacent intersections, used to dynamically adjust the timing parameters of traffic lights. Timing parameters include, but are not limited to, the green light duration, red light duration, signal cycle, and phase switching sequence for each signal phase. By adjusting the proportion of signal release time allocation, the flow of vehicles is guided, thereby alleviating traffic pressure in specific directions or improving intersection efficiency.

[0030] The lane function dynamic switching command refers to the control command issued to traffic sections equipped with reversible lanes or controllable lane facilities to change the traffic function of lanes. Through this command, the traffic direction, usage attributes, or service objects of lanes can be dynamically configured. For example, the direction of tidal flow lanes can be switched at different times, or ordinary lanes can be temporarily adjusted to lanes with specific driving functions to adapt to the changing characteristics of traffic flow in time and space.

[0031] Speed ​​limit or guidance information dissemination instructions refer to the instructions issued to traffic participants through traffic guidance screens, variable speed limit signs, or vehicle-to-everything (V2X) information dissemination devices to control or guide traffic. These instructions are used to guide vehicles to rationally choose driving speeds and routes by dynamically adjusting speed limits or issuing route guidance and congestion alerts, without directly altering the road structure, thereby reducing the risk of localized traffic conflicts and improving the overall stability of traffic operations.

[0032] For traffic sections that are determined to be non-intervention zones, a dispatch suppression flag is set during the dispatch control process to exclude the traffic section from the dispatch instruction generation process, and prohibit the generation and issuance of any dispatch instructions for the traffic section.

[0033] Methods for determining whether a scheduling instruction is revocable include: Before the dispatching instruction officially takes effect, for the traffic section in the intervention zone, the original control configuration status of the traffic section before the dispatching is read and saved. The original control configuration status includes signal timing parameters, lane function configuration parameters, and speed limit or guidance information release parameters. After saving the original control configuration state, the system performs type determination on the generated scheduling instructions, reads the control type identifier carried in the scheduling instructions, and matches the control type identifier with the pre-set set of revocable control types to determine whether the scheduling instructions belong to the revocable type; among them, parameter adjustment type scheduling instructions are determined to be revocable type.

[0034] It should be noted that parameter adjustment type dispatch instructions refer to dispatch instructions that only adjust the operating parameters of existing traffic control equipment without changing the physical structure or long-term operating logic of traffic facilities, such as signal timing parameter adjustment, speed limit value adjustment, or guidance information content switching; for irrevocable type dispatch instructions, no rollback mechanism is established and the execution process is directly initiated.

[0035] Methods for creating an undoable rollback window include: When a dispatch instruction is determined to be revocable, a revocable rollback window is created for the traffic segment affected by the corresponding dispatch instruction. The duration of the revocable rollback window is calculated based on the segment length of the traffic segment affected by the dispatch instruction and the average speed of the traffic segment before the dispatch instruction was executed. The duration of the revocable rollback window is: ;in, Indicates traffic section The corresponding time length of the revocable rollback window; Indicates the length of the traffic segment affected by the dispatch instruction; This indicates the traffic section before the dispatch instruction is executed. The average driving speed; This represents a safety factor used to adjust the rollback window length to provide a safety margin between traffic operation uncertainty and system response delay. A safety factor is introduced into the calculation results to determine the revocable time range from the time the scheduling instruction takes effect to the time the rollback window ends.

[0036] Cancellable time range: ;in, Indicates the traffic section A reversible rollback window is constructed; Indicates the time when the scheduling instruction takes effect; This indicates the end time of the rollback window.

[0037] Methods for calculating the situation increment caused by scheduling include: After the dispatching instruction is executed, the traffic operation status of the traffic segment affected by the dispatching instruction is continuously monitored, and the time of the dispatching instruction taking effect is used as the evaluation start time. Within the revocable rollback window, the time-series status data of the traffic segment after the dispatching instruction is executed is obtained. The time-series situation data of the traffic segment after the execution of the dispatching instruction is compared with the time-series situation data of the corresponding traffic segment before the execution of the dispatching instruction to obtain the traffic situation difference before and after the execution of the dispatching instruction within the evaluation time window; and the traffic situation difference is accumulated and normalized on the time scale to calculate the situation increment that represents the degree of influence of the dispatching instruction on the overall operation status of the traffic segment.

[0038] The situation increment is: ;in, Indicates traffic section The incremental scheduling status within the revocable rollback window is used to quantify the overall impact of scheduling instructions on the traffic situation of the traffic segment relative to the natural operating state. Indicates traffic section The baseline traffic situation intensity value at a given time is used to describe the reference situation state of the traffic segment according to natural evolution or historical operating rules under the condition that no current dispatch instructions are applied. It can be predicted by historical data of the same period or by a time evolution model based on historical statistical rules, such as a situation evolution curve established by weekdays / weekends and morning / evening peak hours. Baseline traffic situation intensity value: ;in, Indicates traffic section At a historical moment The baseline traffic situation intensity value; This represents the backtracking index variable, used to identify the first... At a historical sampling moment, when At that time, it corresponds to the most recent historical sampling situation; when At that time, it corresponds to the earliest historical situation included in the retrospective calculation; Indicates the backtracking order, used to limit the number of historical samples used in the calculation of the baseline situation strength value; Methods for progressively restoring scheduling command configurations to their original state include: A preset situation increment threshold is set. The situation increment of the traffic segment affected by the dispatch instruction is compared with the preset situation increment threshold. When the situation increment exceeds the preset situation increment threshold, it is determined that the current dispatch instruction has caused an unacceptable disturbance to the traffic situation and the dispatch is canceled and rolled back. After the scheduling cancellation rollback is triggered, the system does not directly restore the original control configuration state before scheduling. Instead, it proportionally merges the original control configuration state saved before scheduling with the current scheduling control configuration state according to the preset rollback ratio coefficient. The merged control configuration state is then sent to the corresponding traffic control equipment for execution, so that the traffic control parameters are restored to the original control configuration state in a gradual manner, thereby reducing the impact of the scheduling cancellation process on the stability of traffic operation.

[0039] The merged control configuration status is as follows: ;in, Indicates the control configuration status after fusion; This indicates the original traffic control configuration state saved before the dispatch instruction took effect; Indicates the control configuration status corresponding to the current scheduling command; This represents the rollback coefficient, which is used to control the rollback magnitude. By adjusting the value of the rollback coefficient, a one-time rollback or a multi-step gradual rollback can be achieved, so that the traffic control parameters can be smoothly restored to the state before scheduling.

[0040] The preset situation increment threshold is set by staff. By collecting different situation increments, the average value of multiple situation increments is taken as the preset situation increment threshold. Similarly, preset traffic situation natural evolution rate threshold and preset traffic situation intensity threshold are set.

[0041] This embodiment, by introducing the natural evolution rate of traffic conditions and combining it with the intensity of the conditions, can effectively identify sections dominated by the stable operation of the traffic system itself, avoiding meaningless scheduling interventions in such sections, thereby reducing the risk of disturbance to traffic operations by the scheduling system. Instead of relying solely on instantaneous situation indicators, it characterizes the changing patterns of traffic conditions through a time dimension, enabling the scheduling system to distinguish between short-term random fluctuations and continuous evolutionary trends, reducing misjudgments caused by noisy data or occasional changes, and improving the system's stability and robustness in complex and dynamic traffic environments. By clearly dividing traffic sections into intervention-friendly and non-intervention-friendly zones, it provides clear spatial constraints for the generation, execution, and rollback mechanisms of scheduling instructions, transforming scheduling control from post-event correction to pre-event screening, which is conducive to building a hierarchical and logically consistent comprehensive traffic command and dispatch system.

[0042] By correlating the length of the revocable rollback window with the length of the traffic segment and vehicle speed, the propagation timescale of scheduling effects within the traffic segment can be accurately characterized. This limits the revocation operation to a safe timeframe before irreversible traffic impacts occur, reducing the likelihood of traffic risks caused by revocation. Dynamically calculating the rollback window for different traffic segments and time periods allows the revocation mechanism to adapt to different road conditions and traffic states, improving the overall applicability of the system. Introducing a safety factor provides a buffer against system response delays and traffic uncertainties, giving the revocation rollback mechanism higher fault tolerance in real-world deployment environments and preventing revocation failures or malfunctions due to link delays or sudden traffic fluctuations. A clearly defined revocable rollback window provides a unified time reference framework for subsequent scheduling effect evaluation, rollback triggering criteria, and proportional rollback execution.

[0043] By comparing the incremental situation of traffic segments affected by dispatch instructions with a preset threshold for incremental situation, cancellation and rollback are triggered only when the dispatch disturbance exceeds the system's acceptable range. This transforms cancellation decisions from experience-based judgments to quantitative assessments based on situation evolution, improving the scientific rigor and stability of the dispatch system. After triggering dispatch cancellation, the system does not directly revert to the original control configuration state before dispatch. Instead, it proportionally merges the original and current configuration states, allowing traffic control parameters to change continuously and gradually, significantly reducing the traffic impact caused by sudden changes in control parameters during cancellation. By setting a rollback coefficient, a one-time rollback or multi-step gradual rollback can be flexibly implemented based on traffic operation status, enhancing the dispatch system's adaptability to different traffic scenarios, time periods, and disturbance intensities. By explicitly modeling the relationship between the pre-dispatch state, current state, and rollback ratio, the dispatch cancellation process has clear control boundaries and predictable behavior, reducing the impact of system anomaly handling on traffic safety. Example

[0044] Please see Figure 2 As shown, parts not described in detail in this embodiment are described in Embodiment 1. A comprehensive traffic command and dispatch method based on Internet of Things (IoT) sensing is provided, including: S1. Real-time collection of operational data from each traffic segment through IoT devices, and alignment of the operational data according to time to obtain temporal status data of the traffic segment; S2. Based on the time-series situation data, the natural evolution characteristics of each traffic section are quantitatively analyzed, and each traffic section is determined as an area that can be intervened or an area that cannot be intervened. S3. Generate and execute corresponding dispatch instructions for traffic segments within the interventionable zone; for traffic segments within the non-interventionable zone, it is prohibited to generate any dispatch instructions. S4. Before the dispatch instruction takes effect, save the original configuration state of the corresponding traffic segment and determine whether the dispatch instruction is revocable. If it is revocable, create a revocable rollback window for the traffic segment affected by the dispatch instruction. S5. After the dispatching instruction is executed, the traffic situation changes in each traffic section are evaluated, the situation increment caused by the dispatching is calculated, and when the situation increment exceeds the preset situation increment threshold, the cancellation rollback is triggered, and the dispatching instruction configuration is gradually restored to the original configuration state according to the preset rollback ratio.

[0045] Since the electronic device described in this embodiment is the electronic device used to implement the traffic integrated command and dispatch system and method based on Internet of Things (IoT) sensing in the embodiments of this application, those skilled in the art can understand the specific implementation methods and various variations of the electronic device in this embodiment based on the traffic integrated command and dispatch system and method based on IoT sensing described in the embodiments of this application. Therefore, how the electronic device implements the method in the embodiments of this application will not be described in detail here. As long as those skilled in the art implement the electronic device used in the traffic integrated command and dispatch system and method based on IoT sensing in the embodiments of this application, it falls within the scope of protection of this application.

[0046] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters and thresholds in the formulas are set by those skilled in the art according to the actual situation.

[0047] The above description is merely a preferred embodiment of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for users of ordinary technical skills, any improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A traffic integrated command and dispatch system based on Internet of Things (IoT) sensing, characterized in that, include: The traffic situation awareness module is used to collect operational data of each traffic segment in real time through IoT devices, align the operational data according to time, and obtain the time-series situation data of the traffic segment. The section intervention determination module is used to quantitatively analyze the natural evolution characteristics of each traffic section based on time-series situation data, and determine each traffic section as an interventionable or non-interventionable zone. The dispatch generation and execution module is used to generate and execute corresponding dispatch instructions for traffic segments within the interventionable zone. For traffic segments within the non-interventionable zone, the generation of any dispatch instructions is prohibited. The rollback window management module is used to save the original configuration state of the corresponding traffic segment before the dispatch instruction takes effect, and to determine whether the dispatch instruction is revocable. If it is revocable, a revocable rollback window is created for the traffic segment affected by the dispatch instruction. The scheduling effect evaluation module is used to evaluate the changes in traffic situation in each traffic segment after the scheduling command is executed, calculate the situation increment caused by the scheduling, and trigger cancellation and rollback when the situation increment exceeds the preset situation increment threshold. The scheduling command configuration is gradually restored to the original configuration state according to the preset rollback ratio.

2. The traffic integrated command and dispatch system based on Internet of Things sensing according to claim 1, characterized in that, The method for collecting operational data from each traffic section includes: The operation data of traffic sections is collected in real time by IoT sensing devices deployed in various traffic sections. The IoT sensing devices include roadside sensing devices, vehicle sensing devices and communication access devices. Roadside sensing devices are installed on the roadside of traffic sections to collect information related to vehicle traffic passing through the traffic section. This information includes the number of vehicles, driving speed, lane occupancy data, queue status data, and passage duration. Vehicle sensing devices are used to obtain the driving status information of the vehicles themselves and associate the driving status information with the corresponding traffic sections. The communication access equipment is used to upload vehicle traffic-related information and driving status information collected by roadside sensing devices and vehicle sensing devices to the traffic integrated command and dispatch system in real time via wired or wireless communication. During the data collection process, each IoT sensing device continuously senses the operational status within the traffic section according to a preset sampling period, and encapsulates the collected vehicle traffic-related information and driving status information into data units containing traffic section identifiers and collection time identifiers, forming operational data that reflects the current operational status of each traffic section.

3. The traffic integrated command and dispatch system based on Internet of Things sensing according to claim 2, characterized in that, The method for obtaining the temporal situation data of traffic sections includes: The data collection time identifier carried in the operation data is parsed, and a unified time reference sequence is constructed based on a preset time resolution. The operation data from different IoT sensing devices are collected by segment according to the traffic segment identifier, and the collected operation data is mapped to the corresponding time position in the unified time reference sequence. During the mapping process, when multiple sources of operational data exist for the same traffic segment at the same time location, the multi-source operational data are fused to generate segment status data that characterizes the operational status of the traffic segment at that time location. When corresponding operational data is missing at any time point, that time point is marked as a placeholder or left empty to ensure that each traffic segment forms a structurally continuous time series; through time-unified alignment and mapping processing, time-series situational data of traffic segments are formed in chronological order.

4. A traffic integrated command and dispatch system based on Internet of Things sensing according to claim 3, characterized in that, The method for determining each traffic section as an area that can be intervened or is not to be intervened includes: For each traffic segment, the traffic situation intensity corresponding to the traffic segment at different times is obtained under continuous time sampling conditions, and the traffic situation changes at adjacent time locations are calculated in units of a preset situation sampling time interval. By analyzing the relationship between the magnitude of traffic situation changes and the time interval between adjacent sampling times, the natural evolution rate of traffic situation, which reflects the intensity of natural changes in the traffic operation status of a traffic segment, is obtained. After obtaining the natural evolution rate of traffic situation, the operation status of the traffic segment is comprehensively evaluated in combination with the traffic situation intensity at the current time. When the natural evolution rate of traffic conditions in a traffic segment is within a preset threshold for the natural evolution rate of traffic conditions, and the corresponding traffic condition intensity is within a preset threshold for the intensity of traffic conditions, it is determined that the operation state of the traffic segment is dominated by the natural evolution of traffic itself, and thus the traffic segment is determined to be an area that cannot be intervened in. When the natural evolution rate of traffic conditions exceeds the preset threshold for the natural evolution rate of traffic conditions, or when the intensity of traffic conditions exceeds the preset threshold for the intensity of traffic conditions, it is determined that there is room for adjustment and optimization of the traffic section through external scheduling, and the traffic section is determined to be an area that can be intervened.

5. A traffic integrated command and dispatch system based on Internet of Things (IoT) sensing according to claim 4, characterized in that, The method for generating and executing the corresponding scheduling instructions includes: After determining the intervenable and non-intervenable zones of each traffic segment, the determination results of the traffic segments are used as the prerequisite constraints for dispatch control, and the generation and execution of dispatch instructions are selectively controlled. For traffic sections that are identified as intervention zones, based on the time-series situation data corresponding to the traffic section, a dispatch instruction matching the traffic section is generated according to the preset traffic dispatch strategy, and the dispatch instruction is sent to the corresponding field control equipment for execution. For traffic sections that are determined to be non-intervention zones, a dispatch suppression flag is set during the dispatch control process to exclude the traffic section from the dispatch instruction generation process, and prohibit the generation and issuance of any dispatch instructions for the traffic section.

6. A traffic integrated command and dispatch system based on Internet of Things sensing according to claim 5, characterized in that, The method for determining whether a scheduling instruction is revocable includes: Before the dispatching instruction officially takes effect, for the traffic section in the intervention zone, the original control configuration status of the traffic section before the dispatching is read and saved. The original control configuration status includes signal timing parameters, lane function configuration parameters, and speed limit or guidance information release parameters. After saving the original control configuration state, the system performs type determination on the generated scheduling instructions, reads the control type identifier carried in the scheduling instructions, and matches the control type identifier with the pre-set set of revocable control types to determine whether the scheduling instructions belong to the revocable type; among them, parameter adjustment type scheduling instructions are determined to be revocable type.

7. A traffic integrated command and dispatch system based on Internet of Things sensing according to claim 6, characterized in that, The method for creating an undoable rollback window includes: When a dispatch instruction is determined to be revocable, a revocable rollback window is created for the traffic segment affected by the corresponding dispatch instruction. The time length of the revocable rollback window is calculated based on the segment length of the traffic segment affected by the dispatch instruction and the average driving speed of the traffic segment before the dispatch instruction was executed. A safety factor is introduced into the calculation result to determine the revocable time range from the time the dispatch instruction takes effect to the time the rollback window ends.

8. A traffic integrated command and dispatch system based on Internet of Things sensing according to claim 7, characterized in that, The methods for calculating the situational increments caused by scheduling include: After the dispatching instruction is executed, the traffic operation status of the traffic segment affected by the dispatching instruction is continuously monitored, and the time of the dispatching instruction taking effect is used as the evaluation start time. Within the revocable rollback window, the time-series status data of the traffic segment after the dispatching instruction is executed is obtained. The time-series situation data of the traffic segment after the execution of the dispatching instruction is compared with the time-series situation data of the corresponding traffic segment before the execution of the dispatching instruction to obtain the traffic situation difference before and after the execution of the dispatching instruction within the evaluation time window; and the traffic situation difference is accumulated and normalized on the time scale to calculate the situation increment that represents the degree of influence of the dispatching instruction on the overall operation status of the traffic segment.

9. A traffic integrated command and dispatch system based on Internet of Things sensing according to claim 8, characterized in that, The method for progressively restoring the scheduling instruction configuration to its original configuration state includes: A preset situation increment threshold is set. The situation increment of the traffic segment affected by the dispatch instruction is compared with the preset situation increment threshold. When the situation increment exceeds the preset situation increment threshold, it is determined that the current dispatch instruction has caused an unacceptable disturbance to the traffic situation and the dispatch is canceled and rolled back. After the scheduling cancellation rollback is triggered, the system does not directly restore the original control configuration state before scheduling. Instead, it proportionally merges the original control configuration state saved before scheduling with the current scheduling control configuration state according to the preset rollback ratio coefficient, and sends the merged control configuration state to the corresponding traffic control equipment for execution, so that the traffic control parameters are restored to the original control configuration state in a gradual manner.

10. A traffic integrated command and dispatch method based on Internet of Things (IoT) sensing, implemented by any one of claims 1 to 9, characterized in that, include: S1. Real-time collection of operational data from each traffic segment through IoT devices, and alignment of the operational data according to time to obtain temporal status data of the traffic segment; S2. Based on the time-series situation data, the natural evolution characteristics of each traffic section are quantitatively analyzed, and each traffic section is determined as an area that can be intervened or an area that cannot be intervened. S3. Generate and execute corresponding dispatch instructions for traffic segments within the interventionable zone; for traffic segments within the non-interventionable zone, it is prohibited to generate any dispatch instructions. S4. Before the dispatch instruction takes effect, save the original configuration status of the corresponding traffic segment and determine whether the dispatch instruction is revocable. If it is a revocable type, then a revocable rollback window is created for the traffic segment affected by the dispatch instruction; S5. After the dispatching instruction is executed, the traffic situation changes in each traffic section are evaluated, the situation increment caused by the dispatching is calculated, and when the situation increment exceeds the preset situation increment threshold, the cancellation rollback is triggered, and the dispatching instruction configuration is gradually restored to the original configuration state according to the preset rollback ratio.

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