Road traffic flow adaptive control method, device and storage medium

Abstract

The embodiments of the present application relate to the field of traffic management technology and disclose a method, device, and storage medium for adaptively controlling road traffic flow. The method first obtains flooding information such as the flooding depth, flooding depth change rate, and water flow velocity of a target traffic section, then inputs this flooding information into a hazard prediction model to derive a vehicle wading risk coefficient. When the risk coefficient exceeds a threshold, the method obtains distance information of each target entrance whose distance from the target traffic section is less than or equal to the length threshold, and corrects the distance information based on historical travel time to obtain target distance information, thereby controlling the traffic flow of each target entrance merging into the target traffic section. In this way, based on the real-time flooding hazard condition of the road and the actual conditions of different confluence entrances and flooded sections, the traffic flow is adaptively and accurately controlled to effectively prevent vehicles from excessively merging into flooded sections in dangerous situations, thereby improving traffic safety and traffic efficiency under adverse conditions such as flooding.

Description

Technical Field

[0001] The present invention relates to the technical field of traffic management, and in particular to a method, device and storage medium for adaptive control of road traffic flow. Background Art

[0002] In road traffic management, road flooding caused by inclement weather poses a serious challenge to traffic safety and efficiency. Extreme weather conditions such as heavy rain or flooding can easily lead to varying degrees of waterlogging in low-lying areas, along bridges and culverts, and on roads with inadequate drainage systems. When vehicles wade through flooded roads, they face numerous potential dangers, including stalling and loss of control, which can easily lead to traffic jams.

[0003] In related technologies, road traffic flow control methods mostly focus on conventional traffic congestion relief, and are unable to timely and effectively adaptively adjust traffic flow according to waterlogging conditions, thereby failing to effectively prevent excessive concentration of vehicles into flooded sections, making it difficult to ensure road traffic safety and smooth flow. Summary of the Invention

[0004] The main purpose of the present invention is to provide a method, device and storage medium for adaptive control of road traffic flow, aiming to solve the technical problem in the prior art that traffic flow cannot be adaptively adjusted in a timely and effective manner according to the waterlogging situation, thereby being unable to effectively avoid excessive concentration of vehicles into flooded sections of road.

[0005] To achieve the above objectives, in a first aspect, an embodiment of the present application provides a method for adaptively controlling road traffic flow, the method comprising:

[0006] Acquiring flooding information of a target traffic section according to a traffic flow adaptive control instruction, wherein the flooding information includes at least a flooding depth, a flooding depth change rate, and a water flow velocity;

[0007] Inputting the flooding depth, flooding depth change rate, and water flow velocity of the target traffic section into a hazard prediction model to obtain a hazard coefficient when a vehicle wades through the target traffic section;

[0008] When the risk factor is greater than or equal to the risk factor threshold, obtaining distance information from each target entrance to the target traffic section, wherein the target entrance is a downstream confluence entrance whose distance from the target traffic section is less than or equal to the length threshold;

[0009] Correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain target distance information;

[0010] The traffic flow of each target entrance merging into the target traffic section is controlled according to the target distance information.

[0011] In a possible implementation, controlling the traffic flow of each target entrance merging into the target traffic section according to the target distance information includes:

[0012] Correcting the initial total traffic flow control amount of the target traffic section according to the risk coefficient to obtain a target total traffic flow control amount;

[0013] Traffic flow distribution is performed on the target total traffic flow control quantity according to the target distance information to obtain traffic flow information of each target entrance entering the target traffic section.

[0014] In a possible implementation, performing traffic flow distribution on the target total traffic flow control amount according to the target distance information to obtain traffic flow information of each target entrance entering the target traffic section includes:

[0015] Obtaining a target allocation ratio according to target distance information corresponding to each target entrance, wherein the target allocation ratio is negatively correlated with the target distance;

[0016] Traffic flow distribution is performed according to the target allocation ratio corresponding to each target entrance and the target total traffic flow control amount to obtain traffic flow information of each target entrance entering the target traffic section.

[0017] In a possible implementation, obtaining the target allocation ratio according to the target distance information corresponding to each target entrance includes:

[0018] Obtaining the pre-allocation ratio corresponding to each target entrance according to the target distance information corresponding to each target entrance;

[0019] The pre-allocation ratio corresponding to each target entrance is corrected according to the traffic flow saturation factor of each target entrance to obtain the target allocation ratio, wherein the target allocation ratio is positively correlated with the traffic flow saturation factor.

[0020] In a possible implementation, after obtaining the traffic flow information of each target entrance merging into the target traffic section, the method further includes:

[0021] Generate corresponding traffic light control information according to the traffic flow information corresponding to each target entrance;

[0022] controlling the traffic lights corresponding to the target entrances according to the traffic light control information to control the traffic flow of each target entrance merging into the target traffic section;

[0023] and / or generating corresponding roadside warning information according to the traffic flow information corresponding to each target entrance, wherein the roadside warning information is used to prompt vehicles to avoid merging into the target traffic section;

[0024] The roadside warning information is sent to the target vehicle to prompt the target vehicle to change the driving route in advance.

[0025] In a possible implementation, generating corresponding roadside warning information according to the traffic flow information corresponding to each target entrance includes:

[0026] The sending frequency of roadside warning information for each target entrance is determined based on the traffic flow information, wherein the traffic flow size is negatively correlated with the sending frequency.

[0027] In a possible implementation, after controlling the traffic flow of each target entrance merging into the target traffic section according to the target distance information, the method includes:

[0028] Obtain water flow direction information in the lane width direction of the target traffic section;

[0029] Determine a target lane of the target traffic section according to the water flow direction information, wherein the target lane is an end lane in the water flow direction;

[0030] Controlling a traffic indicator light to indicate a no-entry status on the target lane, wherein the traffic indicator light is arranged within a preset distance range downstream of the target traffic section;

[0031] And / or, controlling the traffic light at the upstream exit of the target traffic section to shorten the red light duration to accelerate vehicles to leave the target traffic section.

[0032] In a possible implementation, the correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain the target distance information includes:

[0033] The average historical travel time corresponding to each target entrance is input into the distance correction model to obtain the target distance information corresponding to each target entrance, wherein the distance correction model satisfies the following expression:

[0034] ;

[0035] in, The target distance value corresponding to the i-th target entrance; is the original distance from the i-th target entrance to the target traffic section; is the average historical travel time from the i-th target entrance to the target traffic section; is the benchmark travel time; η is the historical travel sensitivity coefficient (η>0), which represents the amplifying effect of historical congestion on distance.

[0036] In a second aspect, an embodiment of the present application further provides a traffic flow control device, comprising:

[0037] An instruction acquisition module is used to obtain traffic flow adaptive control instructions;

[0038] A flooding information acquisition module is used to acquire flooding information of a target traffic section according to a traffic flow adaptive control instruction, wherein the flooding information includes at least flooding depth, flooding depth change rate, and water flow speed;

[0039] a hazard prediction module, configured to input the flooding depth, flooding depth change rate, and water flow velocity of a target traffic section into a hazard prediction model to obtain a hazard coefficient when a vehicle wades through the target traffic section;

[0040] A distance information acquisition module is used to obtain the distance information from each target entrance to the target traffic section when the risk factor is greater than or equal to the risk factor threshold;

[0041] a correction module, configured to correct the distance information according to the historical travel time of vehicles from each target entrance to the target traffic section to obtain target distance information;

[0042] The traffic flow control module is used to control the traffic flow of each target entrance into the target traffic section according to the target distance information.

[0043] In a third aspect, an embodiment of the present application further provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps of the method described in the first aspect are implemented.

[0044] Different from existing technologies, the adaptive road traffic flow control method provided in the embodiments of this application first obtains flooding information such as the flooding depth, flooding depth change rate, and water flow velocity of the target traffic section. This flooding information is then input into a hazard prediction model to derive a vehicle wading risk factor. When the risk factor exceeds a threshold, the method obtains distance information for each target entrance whose distance from the target traffic section is less than or equal to the length threshold. This distance information is then corrected based on historical travel time to obtain target distance information, and the traffic flow from each target entrance into the target traffic section is then controlled accordingly. This technical solution can adaptively and precisely regulate traffic flow based on the real-time flooding risk conditions of the road, combined with the actual conditions of different entrances and flooded sections, effectively preventing vehicles from excessively merging into flooded sections in dangerous situations, thereby improving traffic safety and traffic efficiency under adverse conditions such as flooding. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the structures shown in these drawings without paying any creative work.

[0046] Figure 1 This is a schematic diagram of the application background of the road traffic flow adaptive control method in some embodiments of the present application;

[0047] Figure 2 This is a flowchart of a method for adaptively controlling road traffic flow in some embodiments of the present application;

[0048] Figure 3 This is a flowchart of step S500 of the road traffic flow adaptive control method in some embodiments of the present application;

[0049] Figure 4 This is a schematic diagram of the hardware structure of the traffic flow control device in some embodiments of the present application.

[0050] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0052] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0053] In addition, the descriptions of "first", "second", etc. in the present invention are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In addition, "and / or" in the full text includes three solutions. Taking A and / or B as an example, it includes technical solution A, technical solution B, and technical solution that satisfies both A and B. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the ability of ordinary technicians in this field to implement them. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by the present invention.

[0054] In road traffic management, road flooding caused by inclement weather poses a serious challenge to traffic safety and efficiency. Extreme weather conditions such as heavy rain or flooding can easily lead to varying degrees of waterlogging in low-lying areas, along bridges and culverts, and on roads with inadequate drainage systems. When vehicles wade through flooded roads, they face numerous potential dangers, including stalling and loss of control, which can easily lead to traffic jams.

[0055] In related technologies, road traffic flow control methods mostly focus on conventional traffic congestion relief, and are unable to timely and effectively adaptively adjust traffic flow according to waterlogging conditions, thereby failing to effectively prevent excessive concentration of vehicles into flooded sections, making it difficult to ensure road traffic safety and smooth flow.

[0056] like Figure 1 As shown, Figure 1 This is a schematic diagram illustrating the application background of the adaptive road traffic flow control method in some embodiments of this application. In the figure, region M is a low-lying, water-prone section of a main road. This application refers to this section as the target traffic section. Lane L is a lane for east-to-west traffic, and lane R is a lane for west-to-east traffic. Branch roads H1 and H2 are branches that merge into the main road. This application refers to branch roads H1 and H2 as target entrances or target exits. Lanes R1 and R2 are the first and second lanes for west-to-east traffic, respectively.

[0057] like Figure 1-Figure 3 As shown, the following takes the road traffic flow control system executing the road traffic flow adaptive control method as an example for description. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than here. Figure 2 The method includes the following steps S100 to S500:

[0058] Step S100: acquiring flooding information of a target traffic section according to a traffic flow adaptive control instruction, wherein the flooding information includes at least flooding depth, flooding depth change rate, and water flow velocity;

[0059] Specifically, adaptive traffic flow control instructions can be automatically triggered by the system. For example, by monitoring rainfall or duration, adaptive traffic flow control instructions are automatically triggered when rainfall reaches preset conditions, allowing for rapid response to the impact of severe weather on traffic. Adaptive traffic flow control instructions can also be triggered by management personnel. Based on actual observations, for example, if water depth in a low-lying road section exceeds a safe range, managers can manually issue adaptive traffic flow control instructions by operating relevant equipment or system interfaces, thereby flexibly responding to various unexpected traffic conditions.

[0060] For example, in the embodiments of the present application, the system is equipped with meteorological monitoring equipment, such as a rain sensor and a timing device, for real-time monitoring of rainfall or rainfall duration. When rainfall reaches a preset rainfall threshold, or rainfall duration reaches a preset rainfall threshold, the system automatically determines that the conditions for inclement weather affecting traffic have been met, thereby triggering adaptive traffic flow control instructions. For example, if the preset rainfall threshold is 50 mm / hour, the system automatically triggers the instruction when rainfall reaches this value; or if the preset rainfall duration threshold is 2 hours, the system automatically triggers the instruction when continuous rainfall reaches this duration.

[0061] After obtaining the traffic flow adaptive control instruction, the system obtains the flooding information of the target traffic section according to the control instruction.

[0062] Specifically, to detect water depth and its rate of change, water depth sensors can be installed at key locations along the target road section, such as low-lying areas, the bottom of bridges and culverts, areas prone to water accumulation, or along the sides of the road. This monitoring provides real-time water depth data for the target road section. Sensors can utilize various principles, such as pressure, ultrasonic, or capacitive, to adapt to different application scenarios and environmental conditions. The data processing center continuously records the water depth data collected by the sensors and stores it at regular intervals (e.g., every minute). By comparing and calculating water depth data at adjacent time points, the change in water depth is determined. This change is then divided by the time interval to obtain the rate of change in water depth.

[0063] To measure water flow velocity, vector flow sensors can be installed on both sides of the target traffic section. These sensors not only accurately measure the speed of the water flow but also determine its direction. To improve the accuracy of water flow velocity detection, the water flow velocity data collected by the vector flow sensors on both sides of the road can be weighted summed or averaged to obtain the water flow velocity for the target traffic section.

[0064] Step S200: Inputting the flooding depth, flooding depth change rate, and water flow velocity of the target traffic section into a risk prediction model to obtain a risk coefficient when a vehicle wades through the target traffic section;

[0065] Specifically, to reduce the cost of model training, the linear regression model is used as the risk prediction model in the embodiment of this application. Linear regression is a simple and effective regression analysis method. Its basic principle is to assume that there is a linear relationship between the dependent variable (the risk coefficient Y in this example) and the independent variables (the immersion depth H, the immersion depth change rate Hb, and the water flow velocity V). Its form is Y=a*H+b*H b +c*V+d, where Y is the risk factor, which is used to measure the risk level of a vehicle wading through the target traffic section; a, b, c, d are model parameters; H is the immersion depth, which indicates the depth of water accumulation in the target traffic section; H b is the rate of change of flooding depth, reflecting the change of water depth over time; V is the water flow velocity, reflecting the speed of water flow on the road section.

[0066] When training the model, you can first collect multiple sets of historical data (including actual hazardous conditions under different combinations of flooding depth, flooding depth change rate, and water flow rate, and quantify these hazardous conditions as hazard coefficients). For example, after a rainstorm, you can record the flooding depth, flooding depth change rate, and water flow rate at different road sections at different times, as well as the breakdowns and difficulty encountered when vehicles waded through these sections. These hazardous conditions can be quantified as hazard coefficients. The hazard coefficients can be quantified using an expert scoring method, where they are classified into different levels based on the degree of hazard and assigned corresponding numerical values. The collected data is then cleaned and organized to remove outliers and missing values ​​to ensure data accuracy and completeness. Furthermore, the data is standardized or normalized to eliminate the dimensionality effects of different variables and make the data comparable. Finally, the parameters a, b, c, and d of the linear regression model are fitted using methods such as the least squares method. The least squares method aims to minimize the sum of squared errors between the observed values ​​and the model's predicted values. By solving the corresponding system of equations, the optimal parameter estimates are obtained. For example, after fitting, we get a=0.3, b=0.4, c=0.2, and d=0.1.

[0067] For example, assume that during a monitoring session, the flood depth H of the target road section was 0.5 meters, the rate of change of flood depth Hb was 0.03 meters per minute, and the water velocity V was 1.2 meters per second. Substituting these values ​​into the fitted linear regression model: Y = 0.3 × 0.5 + 0.4 × 0.03 + 0.2 × 1.2 + 0.1, we obtain Y = 0.502, which is the risk factor for vehicles wading through the target road section.

[0068] In other embodiments, in order to improve the calculation accuracy of the risk coefficient, other regression models may also be used, such as a polynomial regression model, a ridge regression model, a Lasso regression model, etc.

[0069] Step S300: When the risk factor is greater than or equal to a risk factor threshold, obtaining distance information from each target entrance to the target traffic section, wherein the target entrance is a downstream confluence entrance whose distance from the target traffic section is less than or equal to a length threshold;

[0070] After completing step S200 and determining the risk factor for vehicles wading through the target traffic section, the risk factor must be assessed. If the risk factor is greater than or equal to a pre-set risk factor threshold, this indicates that the target traffic section is currently at a high risk, and vehicles are highly susceptible to stalling or other malfunctions when wading through this section. In this scenario, maintaining the existing traffic flow design would likely result in severe traffic congestion on the target traffic section, leading to a series of traffic safety issues.

[0071] In order to avoid or effectively reduce the risk of traffic congestion in the target traffic section and achieve precise control of traffic flow, the embodiment of the present application proposes to carry out traffic flow control based on distance information. Specifically, when the risk factor reaches or exceeds the risk factor threshold, it is necessary to obtain the distance information from each target entrance to the target traffic section. The target entrance here refers to the downstream confluence entrance whose length from the target traffic section is less than or equal to the set length threshold. By obtaining this distance information, it is possible to more comprehensively understand the spatial relationship between the target entrance and the target traffic section, and provide a strong basis for the subsequent formulation of scientific and reasonable traffic flow control strategies, thereby achieving precise control of traffic flow and ensuring road traffic safety and smoothness.

[0072] In one embodiment, as shown in Figure 1, among the numerous downstream confluence points, target confluence points H1 and H2 possess unique locational attributes: their distances to target traffic segment M are less than or equal to a pre-set length threshold, such as 500 meters or 1 kilometer. This means that vehicles merging onto the main road from target confluence point H1 will enter target traffic segment M relatively quickly. Similarly, vehicles merging onto the main road from target confluence point H2 will also pass through target traffic segment M shortly thereafter. This close spatial connection means that traffic flow at target confluence points H1 and H2 will directly impact traffic conditions on target traffic segment M. Therefore, to effectively avoid or mitigate the risk of traffic congestion on target traffic segment M and achieve precise traffic flow control, it is necessary to obtain distance information from each target confluence point (e.g., H1 and H2) to the target traffic segment.

[0073] Step S400: Correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain target distance information;

[0074] The historical travel time refers to the travel time of vehicles from each target entrance to the target traffic section during the historical travel process. For example, the historical travel time of 10 vehicles from a certain target entrance to the target traffic section is 10 time data respectively. The historical travel time can be obtained by calculating the average of these 10 time data.

[0075] It should be noted that in traffic flow control, allocating traffic based solely on the raw distance information from the target entrance to the target traffic section may not be accurate enough. This is because the actual traffic conditions from different target entrances to the target traffic section may be affected by various factors, such as road congestion, traffic signal settings, and road construction. These factors can cause the actual travel time from the target entrance to the target traffic section to differ from the time estimated based solely on distance. Therefore, it is necessary to correct the distance information based on the historical travel time from each target entrance to the target traffic section to obtain target distance information that better reflects the actual traffic conditions, thereby providing a more accurate basis for subsequent traffic allocation.

[0076] In one embodiment, the step of correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain target distance information includes:

[0077] The average historical travel time corresponding to each target entrance is input into the distance correction model to obtain the target distance information corresponding to each target entrance, wherein the distance correction model satisfies the following expression:

[0078] ;

[0079] in, The target distance value corresponding to the i-th target entrance; is the original distance from the i-th target entrance to the target traffic section; is the average historical travel time from the i-th target entrance to the target traffic section; is the benchmark travel time; η is the historical travel sensitivity coefficient (η>0), which represents the amplifying effect of historical congestion on distance.

[0080] It should be noted that the larger the value of η is, the greater the impact of historical congestion on distance correction is. η can be 0.5 or 1.

[0081] Specifically, in the embodiments of the present application, the ratio of the average historical travel duration to the benchmark travel duration is used to reflect the deviation degree of the actual travel condition from the ideal condition of the target entrance to the target traffic section. When T li > T0, it indicates that the actual travel duration of the target entrance to the target traffic section is relatively long, and there may be congestion or other situations. At this time, the target distance value D mi calculated by the model will be greater than the original distance D i . This is equivalent to magnifying the distance of the target entrance, so that the traffic flow assigned to the target entrance may increase in the subsequent traffic flow distribution. On the contrary, when T li < T0, the target distance value D mi will be less than the original distance D i , and the traffic flow assigned to the target entrance may be reduced. In this way, it is possible to more reasonably allocate the traffic flow according to the actual travel conditions, and improve the accuracy and effectiveness of traffic flow control.

[0082] Step S500: Control the traffic flow of each target entrance into the target traffic section according to the target distance information.

[0083] After obtaining the target distance information corresponding to each target entrance, based on this target distance information, accurately control the traffic flow of each target entrance into the target traffic section.

[0084] In one embodiment, step S500: Control the traffic flow of each target entrance into the target traffic section according to the target distance information, including:

[0085] S510: Calibrate the initial total traffic flow control amount of the target traffic section according to the risk coefficient to obtain the target total traffic flow control amount;

[0086] S520: Allocate the target total traffic flow control amount according to the target distance information to obtain the traffic flow information of each target entrance into the target traffic section.

[0087] It should be noted that in daily travel, a total traffic flow control amount is set for the main road or the target traffic section. This amount is determined based on normal traffic conditions, road design and other factors, and is used to maintain the normal traffic order and traffic efficiency of the road. That is, the initial total traffic flow control amount refers to the total traffic flow control amount of the main road or the target traffic section in daily travel. The target total traffic flow control amount is the result of targeted adjustment of the initial total traffic flow control amount in order to effectively avoid or reduce the possible traffic congestion risk when there is a dangerous situation in the target traffic section.

[0088] Specifically, after determining the hazard factor of the target traffic section in step S200, the initial total traffic flow control quantity is adjusted to avoid or mitigate the risk of traffic congestion, taking into account the high hazard level of the section. This adjustment comprehensively considers the hazard factor. A higher hazard factor indicates a more dangerous section, requiring stricter traffic flow control, and thus a corresponding decrease in the target total traffic flow control quantity. Conversely, if the hazard factor is lower, the target total traffic flow control quantity may be close to or slightly smaller than the initial total traffic flow control quantity.

[0089] After determining the target total traffic flow control volume, traffic flow can be scientifically and rationally allocated based on the target distance information, thereby obtaining traffic flow information for each target entrance entering the target traffic section. Target distance information reflects the spatial relationship between each target entrance and the target traffic section. The closer the target entrance, the more direct impact the incoming vehicles will have on the traffic conditions of the target traffic section in a short period of time. Therefore, by fully utilizing target distance information, traffic flow can be accurately allocated, ensuring that the traffic volume from each target entrance entering the target traffic section matches the actual situation, thereby effectively ensuring traffic safety and smoothness in the target traffic section.

[0090] In one embodiment, step S520: performing traffic flow distribution on the target total traffic control amount according to the target distance information to obtain traffic flow information of each target entrance entering the target traffic section, including: obtaining a target distribution ratio according to the target distance information corresponding to each target entrance, wherein the target distribution ratio is negatively correlated with the target distance; performing traffic flow distribution according to the target distribution ratio corresponding to each target entrance and the target total traffic control amount to obtain traffic flow information of each target entrance entering the target traffic section.

[0091] Specifically, vehicles merging from target entrances that are closer to the target traffic section (the distance here refers to the target distance, which takes into account traffic conditions) will reach the target section more quickly, thus having a more direct and immediate impact on traffic conditions within the target section. Without stricter control over traffic flow at these close target entrances, a large number of vehicles could enter the target section in a short period of time, causing traffic congestion. Therefore, to more effectively control traffic flow within the target section, it is necessary to allocate a relatively low traffic flow ratio to close target entrances. After determining the target allocation ratio for each target entrance, traffic flow allocation is performed based on the target total traffic flow control volume. Specifically, the target total traffic flow control volume is divided according to the target allocation ratio for each target entrance.

[0092] For example, assuming the target total traffic volume is 1000 vehicles / hour, the target allocation ratio for target entrance H1 is 60%, and the target allocation ratio for target entrance H2 is 40%. Then, according to the traffic flow allocation principle, the traffic flow from target entrance H1 merging into the target traffic section is 1000 × 60% = 600 vehicles / hour, and the traffic flow from target entrance H2 merging into the target traffic section is 1000 × 40% = 400 vehicles / hour.

[0093] In other embodiments, the step of obtaining a target allocation ratio based on target distance information corresponding to each target entrance includes: obtaining a pre-allocation ratio corresponding to each target entrance based on the target distance information corresponding to each target entrance; and correcting the pre-allocation ratio corresponding to each target entrance based on a traffic flow saturation factor of each target entrance to obtain a target allocation ratio, wherein the target allocation ratio is positively correlated with the traffic flow saturation factor.

[0094] It's important to note that the traffic saturation factor reflects the traffic carrying capacity of each target entrance under current traffic conditions. It takes into account a variety of factors, including the number of lanes at the target entrance, road width, traffic signal configuration, and the surrounding traffic environment. The higher the saturation factor of a target entrance, the smaller the traffic volume it can handle under current conditions, and the greater the likelihood of congestion at the target entrance itself.

[0095] Specifically, in the initial stage, the pre-allocation ratio is determined based on the target distance information corresponding to each target entrance. Since vehicles from target entrances closer to the target traffic section reach the target traffic section faster, their impact on traffic conditions is more direct and immediate. To avoid congestion caused by a large influx of vehicles within a short period of time, the pre-allocation ratio is initially set to be negatively correlated with the target distance. That is, the closer the distance, the lower the pre-allocation ratio, thereby initially controlling the traffic flow at the nearby target entrances.

[0096] After determining the pre-allocation ratio, to mitigate the congestion risk at the target entrances themselves, it is necessary to further adjust the pre-allocation ratio based on the traffic flow saturation factor of each target entrance. The adjusted target allocation ratio is positively correlated with the traffic flow saturation factor: the higher the saturation factor, the higher the target allocation ratio. Target entrances with high saturation factors have traffic conditions approaching or reaching their capacity, making them highly susceptible to congestion. If not promptly managed, the backlog at these entrances will rapidly spread, causing a chain reaction on surrounding traffic and even the entire road network. Therefore, by allocating a relatively high traffic flow ratio, vehicles at these entrances can more quickly merge onto the main road, preventing excessive congestion at the target entrances and thus alleviating potential congestion. Target entrances with low saturation factors, on the other hand, have relatively strong traffic carrying capacity and can be allocated a relatively low traffic flow ratio. This not only prevents excessive traffic influx and wastes resources, but also ensures the rational allocation and efficient utilization of road resources, making the entire transportation system more smoothly and orderly.

[0097] In this way, through such a correction mechanism based on the traffic flow saturation factor, it is possible to achieve precise control of the traffic flow at each target entrance, while ensuring smooth traffic, minimizing the risk of congestion and improving the overall traffic operation efficiency.

[0098] In other specific scenarios (such as holiday highway entrance control and optimization of urban expressway connecting sections), it is necessary to prioritize traffic efficiency on main roads to avoid systemic paralysis caused by local congestion. In these cases, the "distance weight > saturation factor weight" allocation strategy can be adopted.

[0099] In one embodiment, after obtaining the traffic flow information of each target entrance merging into the target traffic section, the method further includes: generating corresponding traffic light control information according to the traffic flow information corresponding to each target entrance; controlling the traffic light corresponding to the target entrance according to the traffic light control information to control the traffic flow of each target entrance merging into the target traffic section;

[0100] and / or generating corresponding roadside warning information according to the traffic flow information corresponding to each target entrance, wherein the roadside warning information is used to prompt vehicles to avoid merging into the target traffic section;

[0101] The roadside warning information is sent to the target vehicle to prompt the target vehicle to change the driving route in advance.

[0102] Specifically, after obtaining the traffic flow information of each target entrance merging into the target traffic section, corresponding traffic signal light control information, such as a traffic light alternation control strategy, can be generated based on the traffic flow information corresponding to each target entrance, so as to achieve traffic flow control at the target entrance through alternating traffic light control. For example, for a target entrance with a large traffic flow, since the traffic flow that needs to be merged into the main road is large, the total green light pass time can be appropriately extended and the total red light no-go time can be reduced. Conversely, for a target entrance with a small traffic flow, since the traffic flow that needs to be merged into the main road is small, the total green light pass time can be appropriately reduced and the total red light no-go time can be extended.

[0103] In other embodiments, corresponding roadside warning information can also be generated based on the traffic flow information corresponding to each target entrance. For example, this roadside warning information can be sent to the target vehicle to prompt the target vehicle to change its route in advance. The target vehicles can be all vehicles passing through the target entrance, or the roadside warning can be issued specifically for vehicles with low water wading ability.

[0104] For example, the frequency of sending roadside warning information for each target entrance is determined based on traffic flow information. When the target entrance has a high traffic volume, indicating that a large amount of traffic needs to merge into the main road, the frequency of sending roadside warning information can be reduced or even not sent to vehicles. When the target entrance has a low traffic volume, indicating that a small amount of traffic needs to merge into the main road, the frequency of sending roadside warning information can be increased to allow more vehicles to receive roadside warning information and change their routes in advance, thus avoiding entering the target traffic section and causing traffic congestion.

[0105] In another embodiment, after controlling the traffic flow of each target entrance merging into the target traffic section according to the target distance information, the method further includes:

[0106] Obtain water flow direction information in the lane width direction of the target traffic section;

[0107] Determine a target lane of the target traffic section according to the water flow direction information, wherein the target lane is an end lane in the water flow direction;

[0108] Controlling a traffic indicator light to indicate a no-entry status on the target lane, wherein the traffic indicator light is arranged within a preset distance range downstream of the target traffic section;

[0109] Specifically, the water flow direction information in the lane width direction can be accurately determined based on the vector flow velocity sensor and the analysis of the movement trajectory of floating objects in combination with road monitoring video. After obtaining the water flow direction information, the end lane in the water flow direction can be used as the target lane of the target traffic section. It can be understood that the end lane in the water flow direction is usually the location of the drainage pipe. In this way, obstacles such as road garbage or stones are likely to accumulate in the target lane, which can easily pose a driving safety hazard. Figure 1 As shown in the figure, lane R1 is a drainage lane, which is prone to accumulation of garbage, stones and other obstacles and is a dangerous lane. Lane R2 is a green safety lane and is suitable for traffic.

[0110] Based on this, the embodiment of the present application sets up traffic lights within a preset distance downstream of the target traffic section. Using red stop signals, vehicles are prohibited from entering dangerous lanes in advance, thus preventing vehicles from colliding with obstacles. Furthermore, the activation conditions and duration of the stop signal can be dynamically adjusted based on the real-time water flow intensity and the risk of obstacle accumulation.

[0111] In other embodiments, after controlling the traffic flow of each target entrance into the target traffic section according to the target distance information, the traffic lights at the upstream exit of the target traffic section can also be controlled to shorten the red light duration to accelerate vehicles to leave the target traffic section.

[0112] Based on this, the adaptive road traffic flow control method provided in the embodiments of the present application first obtains flooding information such as the flooding depth, flooding depth change rate, and water flow velocity of the target traffic section. This flooding information is then input into a hazard prediction model to derive a vehicle wading risk coefficient. When the risk coefficient exceeds a threshold, the method obtains distance information for each target entrance whose distance from the target traffic section is less than or equal to the length threshold. This distance information is then corrected based on historical travel time to obtain target distance information, and the traffic flow from each target entrance into the target traffic section is then controlled accordingly. This technical solution can adaptively and precisely regulate traffic flow based on the real-time flooding hazard conditions of the road, combined with the actual conditions of different entrances and flooded sections, effectively preventing vehicles from excessively merging into flooded sections in dangerous situations, thereby improving traffic safety and traffic efficiency under adverse conditions such as flooding.

[0113] like Figure 4 As shown, Figure 4The present invention provides a hardware structure diagram of a traffic flow control device in some embodiments of the present invention. The traffic flow control device provided in the embodiments of the present invention includes: an instruction acquisition module 100 for acquiring traffic flow adaptive control instructions; a flooding information acquisition module 200 for acquiring flooding information of a target traffic section according to the traffic flow adaptive control instructions, the flooding information including at least flooding depth, flooding depth change rate, and water flow velocity; a hazard estimation module 300 for inputting the flooding depth, flooding depth change rate, and water flow velocity of the target traffic section into a hazard estimation model to obtain a hazard coefficient when a vehicle wades through the target traffic section; a distance information acquisition module 400 for acquiring distance information from each target entrance to the target traffic section when the hazard coefficient is greater than or equal to a hazard coefficient threshold; a correction module 500 for correcting the distance information based on the historical travel time of vehicles from each target entrance to the target traffic section to obtain target distance information; and a traffic flow control module 600 for controlling the traffic flow from each target entrance into the target traffic section according to the target distance information.

[0114] An embodiment of the present application also provides a road traffic flow control system, which includes a memory and a processor, wherein the memory is used to store computer-readable instructions, and the processor is used to call the computer-readable instructions to execute the road traffic flow adaptive control method as described above.

[0115] Among them, the processor is used to provide computing and control capabilities to control the road traffic flow control system to perform corresponding tasks, for example, controlling the road traffic flow control system to perform the road traffic flow adaptive control method in any of the above method embodiments, the method comprising: obtaining flooding information of the target traffic section according to the traffic flow adaptive control instruction, the flooding information at least including the flooding depth, the flooding depth change rate and the water flow velocity; inputting the flooding depth, the flooding depth change rate and the water flow velocity of the target traffic section into the hazard prediction model to obtain the hazard coefficient when the vehicle wades through the target traffic section; when the hazard coefficient is greater than or equal to the hazard coefficient threshold, obtaining the distance information of each target entrance to the target traffic section, wherein the target entrance is a downstream confluence entrance with a length less than or equal to a length threshold from the target traffic section; correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain target distance information; and controlling the traffic flow of each target entrance converging into the target traffic section according to the target distance information.

[0116] The processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), a hardware chip, or any combination thereof; it may also be a digital signal processing (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or any combination thereof. The aforementioned PLD may be a complex programmable logic device (CPLD), a field-programmable gate array (FPGA), a generic array logic (GAL), or any combination thereof.

[0117] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the road traffic flow adaptive control method in the embodiments of the present application. By executing the non-transitory software programs, instructions, and modules stored in memory, the processor can implement the road traffic flow adaptive control method in any of the above method embodiments.

[0118] Specifically, the memory may include volatile memory (VM), such as random access memory (RAM); the memory may also include non-volatile memory (NVM), such as read-only memory (ROM), flash memory, hard disk drive (HDD) or solid-state drive (SSD) or other non-transitory solid-state storage devices; the memory may also include a combination of the above types of memory.

[0119] In summary, the road traffic flow control system of the present application adopts the technical solution of any one of the above-mentioned road traffic flow adaptive control method embodiments, and therefore, has at least the beneficial effects brought by the technical solutions of the above-mentioned embodiments, which will not be described one by one here.

[0120] The present application also provides a computer-readable storage medium, such as a memory device including program code. The program code can be executed by a processor to implement the road traffic flow adaptive control method described in the above embodiment. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CDROM), a magnetic tape, a floppy disk, or an optical data storage device.

[0121] The present application also provides a computer program product comprising one or more program codes stored in a computer-readable storage medium. A processor of a road traffic flow control system reads the program code from the computer-readable storage medium and executes the program code to perform the steps of the road traffic flow adaptive control method provided in the above embodiment.

[0122] Those skilled in the art will understand that all or part of the steps of implementing the above embodiments can be completed by hardware, or by hardware related to program code, and the program can be stored in a computer-readable storage medium. The above-mentioned storage medium can be a read-only memory, a disk or an optical disk, etc.

[0123] It should be noted that the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0124] Through the description of the above embodiments, it is clear to those skilled in the art that each embodiment can be implemented by means of software plus a general hardware platform, or of course by hardware. It is understood by those skilled in the art that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0125] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made by using the contents of the present invention description and drawings under the inventive concept of the present invention, or direct / indirect application in other related technical fields are included in the patent protection scope of the present invention.

Claims

1. A road traffic flow adaptive control method, characterized in that: The method comprises: Acquiring flooding information of a target traffic section according to a traffic flow adaptive control instruction, wherein the flooding information includes at least a flooding depth, a flooding depth change rate, and a water flow velocity; Inputting the flooding depth, flooding depth change rate, and water flow velocity of the target traffic section into a hazard prediction model to obtain a hazard coefficient when a vehicle wades through the target traffic section; When the risk factor is greater than or equal to the risk factor threshold, obtaining distance information from each target entrance to the target traffic section, wherein the target entrance is a downstream confluence entrance whose distance from the target traffic section is less than or equal to the length threshold; Correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain target distance information; Correcting the initial total traffic flow control amount of the target traffic section according to the risk coefficient to obtain a target total traffic flow control amount; Traffic flow distribution is performed on the target total traffic flow control quantity according to the target distance information to obtain traffic flow information of each target entrance entering the target traffic section.

2. The road traffic flow adaptive control method according to claim 1, characterized in that: The method of performing traffic flow distribution on the target total traffic flow control amount according to the target distance information to obtain traffic flow information of each target entrance entering the target traffic section includes: Obtaining a target allocation ratio according to target distance information corresponding to each target entrance, wherein the target allocation ratio is negatively correlated with the target distance; Traffic flow distribution is performed according to the target allocation ratio corresponding to each target entrance and the target total traffic flow control amount to obtain traffic flow information of each target entrance entering the target traffic section.

3. The road traffic flow adaptive control method according to claim 2, characterized in that: The target allocation ratio is obtained according to the target distance information corresponding to each target entrance, including: Obtaining the pre-allocation ratio corresponding to each target entrance according to the target distance information corresponding to each target entrance; The pre-allocation ratio corresponding to each target entrance is corrected according to the traffic flow saturation factor of each target entrance to obtain the target allocation ratio, wherein the target allocation ratio is positively correlated with the traffic flow saturation factor.

4. The road traffic flow adaptive control method according to claim 2, characterized in that: After obtaining the traffic flow information of each target entrance entering the target traffic section, the method further includes: Generate corresponding traffic light control information according to the traffic flow information corresponding to each target entrance; controlling the traffic lights corresponding to the target entrances according to the traffic light control information to control the traffic flow of each target entrance merging into the target traffic section; and / or generating corresponding roadside warning information according to the traffic flow information corresponding to each target entrance, wherein the roadside warning information is used to prompt vehicles to avoid merging into the target traffic section; The roadside warning information is sent to the target vehicle to prompt the target vehicle to change the driving route in advance.

5. The road traffic flow adaptive control method according to claim 4, characterized in that: The generating of corresponding roadside warning information according to the traffic flow information corresponding to each target entrance includes: The sending frequency of roadside warning information for each target entrance is determined based on the traffic flow information, wherein the traffic flow size is negatively correlated with the sending frequency.

6. The road traffic flow adaptive control method according to claim 1, characterized in that: After controlling the traffic flow of each target entrance merging into the target traffic section according to the target distance information, the method includes: Obtain water flow direction information in the lane width direction of the target traffic section; Determine a target lane of the target traffic section according to the water flow direction information, wherein the target lane is an end lane in the water flow direction; Controlling a traffic indicator light to indicate a no-entry status on the target lane, wherein the traffic indicator light is arranged within a preset distance range downstream of the target traffic section; And / or, controlling the traffic light at the upstream exit of the target traffic section to shorten the red light duration to accelerate vehicles to leave the target traffic section.

7. The road traffic flow adaptive control method according to claim 1, characterized in that: The step of correcting the distance information according to the historical travel time from each target entrance to the target traffic section to obtain target distance information includes: The average historical travel time corresponding to each target entrance is input into the distance correction model to obtain the target distance information corresponding to each target entrance, wherein the distance correction model satisfies the following expression: Among them, D mi is the target distance value corresponding to the i-th target entrance; D i is the original distance from the i-th target entrance to the target traffic section; T li is the average historical travel time from the i-th target entrance to the target traffic section; T0 is the benchmark travel time; η is the historical travel sensitivity coefficient, and the historical travel sensitivity coefficient η>0 represents the amplification effect of historical congestion on distance.

8. A traffic flow control device, characterized in that: include: An instruction acquisition module is used to obtain traffic flow adaptive control instructions; A flooding information acquisition module is used to acquire flooding information of a target traffic section according to a traffic flow adaptive control instruction, wherein the flooding information includes at least flooding depth, flooding depth change rate, and water flow speed; a hazard prediction module, configured to input the flooding depth, flooding depth change rate, and water flow velocity of a target traffic section into a hazard prediction model to obtain a hazard coefficient when a vehicle wades through the target traffic section; A distance information acquisition module is used to obtain the distance information from each target entrance to the target traffic section when the risk factor is greater than or equal to the risk factor threshold; a correction module, configured to correct the distance information according to the historical travel time of vehicles from each target entrance to the target traffic section to obtain target distance information; The traffic flow control module is used to correct the initial total traffic flow control quantity of the target traffic section according to the risk coefficient to obtain the target total traffic flow control quantity, and to distribute the traffic flow of the target total traffic flow control quantity according to the target distance information to obtain the traffic flow information of each target entrance entering the target traffic section.

9. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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