A method and system for managing and controlling a congestion section of an expressway based on a dynamic lane-dividing variable speed limit strategy

Abstract

The application discloses a highway congestion section management and control method and system based on a dynamic lane-dividing variable speed limit strategy, first constructs traffic event detection conditions, adverse weather detection conditions and large-flow congestion detection conditions, then establishes dynamic lane-dividing variable speed limit strategy starting conditions according to the traffic event detection conditions, the adverse weather detection conditions and the large-flow congestion detection conditions, and then calculates a flow load factor, a speed ratio factor, a historical traffic data correction factor and a weather influence factor; the application realizes the function of automatically and intelligently implementing lane-dividing differentiated speed limit control on a highway congestion section, and can reasonably construct a large-flow congestion quantitative judgment decision model and judge large-flow congestion occurrence by calculating saturation indexes and speed indexes of main line road traffic flow, can not only actively prevent traffic deterioration, but also can improve driving safety while relieving congestion, and is suitable for being widely promoted and used.

Description

Technical Field

[0001] This invention relates to the field of highway congestion control technology, specifically to a highway congestion control method and system based on a dynamic lane-specific variable speed limit strategy. Background Technology

[0002] With the continuous expansion of the national expressway network and the sustained growth of motor vehicle ownership, traffic congestion has become a key issue restricting the improvement of expressway traffic efficiency and service levels. Especially in scenarios such as traffic incidents, severe weather, or high-volume congestion, the traditional fixed speed limit control mode is difficult to adapt to dynamically changing traffic flow conditions and cannot achieve precise allocation of road space resources. Instead, it may become a bottleneck or safety hazard.

[0003] Currently, most existing highway speed limit management systems rely on static information signs to apply uniform speed limits to all lanes along the entire road segment. This fails to fully consider the differences in traffic flow characteristics between different lanes. For example, inner lanes are used by more cars and travel at higher speeds, while outer lanes are used by more trucks and travel at lower speeds. This makes it difficult to effectively guide the orderly separation of traffic flow when congestion occurs, and it is difficult to maximize the use of road capacity. At the same time, the activation and deactivation of existing highway speed limit management strategies generally rely on manual judgment, resulting in a lack of scientific decision-making basis for highway speed limit management strategies. This not only leads to slow response speeds but also limited management effectiveness. Therefore, it is necessary to design a highway congestion management method and system based on a dynamic lane-specific variable speed limit strategy. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and to better and more effectively address the problem that current highway speed limit management largely relies on static information signs to implement uniform speed limits for all lanes along the entire road segment. This results in an inability to fully consider the differences in traffic flow characteristics between different lanes. For example, inner lanes are used by more cars and travel at higher speeds, while outer lanes are used by more trucks and travel at lower speeds. This makes it difficult to effectively guide the orderly separation of traffic flow when congestion occurs, and it is difficult to maximize the use of road capacity. At the same time, the activation and deactivation of existing highway speed limit management strategies generally rely on manual judgment, resulting in a lack of scientific decision-making basis for highway speed limit management strategies. This leads to slow response speeds and limited management effectiveness. This invention provides a method and system for highway congestion management based on a dynamic lane-specific variable speed limit strategy. It realizes the function of automatically and intelligently implementing lane-specific differentiated speed limit control on highway congestion segments. Furthermore, by calculating the saturation index and speed index of the main road traffic flow, it can reasonably construct a quantitative judgment and decision-making model for large-volume congestion and determine the occurrence of large-volume congestion. This not only proactively prevents traffic deterioration but also improves driving safety while alleviating congestion.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0006] A method for managing congested highway sections based on a dynamic lane-specific variable speed limit strategy includes the following steps:

[0007] Step A: Construct traffic incident detection conditions, severe weather detection conditions, and high-volume congestion detection conditions;

[0008] Step B: Establish the activation conditions for the dynamic lane-specific variable speed limit strategy based on traffic incident detection conditions, severe weather detection conditions, and high-volume congestion detection conditions;

[0009] Step C: Calculate the traffic load factor, speed ratio factor, historical traffic data correction factor, and weather impact factor;

[0010] Step D: Establish a dynamic lane-specific speed limit calculation model for congested road sections based on traffic load factor, speed ratio factor, historical traffic data correction factor, and weather impact factor;

[0011] Step E: Construct detection conditions for traffic incidents that have been resolved, severe weather that have been eliminated, and heavy traffic congestion that has been alleviated.

[0012] Step F: Establish dynamic lane-specific variable speed limit strategy closure conditions based on the detection conditions that traffic incidents have been resolved, adverse weather conditions have been eliminated, and high-volume congestion has been alleviated.

[0013] Step G involves generating a dynamic lane-specific variable speed limit strategy for congested road sections based on the activation conditions of the dynamic lane-specific variable speed limit strategy, the calculation model of the dynamic lane-specific speed limit value for congested road sections, and the deactivation conditions of the dynamic lane-specific variable speed limit strategy. Then, the congested road sections of the highway are controlled according to the dynamic lane-specific variable speed limit strategy for congested road sections, and the highway congestion control operation is completed.

[0014] The aforementioned method for managing highway congestion based on a dynamic lane-specific variable speed limit strategy includes step A, which involves constructing traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. The specific steps are as follows:

[0015] Step A1: Construct traffic incident detection conditions, wherein the traffic incident detection conditions consist of traffic incident detection sub-conditions, which include traffic accidents and vehicle malfunctions, as shown in formula (1).

[0016] (1)

[0017] in, This is a Boolean value representing the traffic incident detection criteria. For the Boolean value of the sub-condition of traffic incident detection, The logical operator for OR;

[0018] Step A2: Construct severe weather detection conditions, which are composed of severe weather detection sub-conditions. These sub-conditions include rain, fog, wind, snowfall, snow accumulation, sandstorm, and high road surface temperature, as shown in formula (2).

[0019] (2)

[0020] in, This represents a Boolean value for detection conditions under severe weather conditions. Boolean values ​​for sub-conditions for detecting severe weather;

[0021] Step A3: Construct high-flow congestion detection conditions, wherein the high-flow congestion detection conditions consist of high-flow congestion detection sub-conditions, which include flow saturation and average velocity, as shown in formula (3).

[0022] (3)

[0023] in, For high-volume congestion detection conditions, Boolean value. The Boolean value for the high-volume congestion detection sub-condition. The total traffic flow across all lanes of the main road. The total theoretical capacity of all lanes on the main road. The main road traffic saturation threshold. Lane number, The total number of lanes. for Lane traffic flow for Theoretical lane capacity The logical operator for AND. The average section speed of all lanes on the main road for Average lane section speed, The speed threshold for the main road section.

[0024] In the aforementioned method for managing highway congestion based on a dynamic lane-specific variable speed limit strategy, step B involves establishing the activation conditions for the dynamic lane-specific variable speed limit strategy based on traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions, as shown in formula (4).

[0025] (4)

[0026] in, This is a Boolean value representing the start / stop condition of the strategy.

[0027] The aforementioned method for managing highway congestion based on a dynamic lane-specific variable speed limit strategy, step C, involves calculating the flow load factor, speed ratio factor, historical traffic data correction factor, and weather impact factor. The specific steps are as follows:

[0028] Step C1: Calculate the flow load factor, as shown in formula (5).

[0029] (5)

[0030] in, For the first Lane flow load factor;

[0031] Step C2, calculate the speed ratio factor, as shown in formula (6).

[0032] (6)

[0033] in, For the first Lane speed ratio factor Main road Lane design speed;

[0034] Step C3: Calculate the historical passage data correction factor, as shown in formula (7).

[0035] (7)

[0036] in, For the first Lane historical traffic data correction factor, For the first The lane's historical best average speed For the first The lane currently displays the speed limit.

[0037] Step C4: Calculate the weather influencing factors, as shown in formula (8).

[0038] (8)

[0039] in, Weather influencing factors , and These correspond to Level 2, Level 3, and Level 4 meteorological conditions, respectively.

[0040] The aforementioned method for managing congested highway sections based on a dynamic lane-specific variable speed limit strategy, in step D, establishes a dynamic lane-specific speed limit calculation model for congested sections based on traffic load factor, speed ratio factor, historical traffic data correction factor, and weather influence factor, as shown in formula (9).

[0041] (9)

[0042] in, Dynamic speed limits for each lane in congested road sections. The minimum speed limit allowed by regulations. , and All are weighting coefficients, and .

[0043] The aforementioned method for managing highway congestion based on a dynamic lane-specific variable speed limit strategy, step E, involves constructing detection conditions for traffic incidents being resolved, adverse weather effects being eliminated, and high-volume congestion being alleviated. The specific steps are as follows:

[0044] Step E1: Construct the detection conditions for traffic incidents that have been processed, as shown in formula (10).

[0045] (10)

[0046] in, The traffic incident has been resolved. This is the Boolean value for the sub-condition that no traffic incident was detected.

[0047] Step E2: Construct detection conditions where the impact of severe weather has been eliminated, as shown in formula (11).

[0048] (11)

[0049] in, The effects of the severe weather have been eliminated. This is the Boolean value for the sub-condition that no severe weather was detected.

[0050] Step E3: Construct the detection conditions for high-volume congestion mitigation, as shown in formula (12).

[0051] (12)

[0052] in, The congestion caused by high traffic volume has been alleviated.

[0053] The aforementioned method for managing congested highway sections based on a dynamic lane-specific variable speed limit strategy, in step F, establishes the closing conditions for the dynamic lane-specific variable speed limit strategy based on the detection conditions that traffic incidents have been resolved, adverse weather conditions have been eliminated, and high-volume congestion has been alleviated, as shown in formula (13).

[0054] (13)

[0055] in, The dynamic lane-specific variable speed limit strategy is turned off.

[0056] The aforementioned method for managing congested highway sections based on a dynamic lane-specific variable speed limit strategy includes step G, which involves generating a dynamic lane-specific variable speed limit strategy for congested sections based on the activation conditions of the dynamic lane-specific variable speed limit strategy, a calculation model for the dynamic lane-specific speed limit values ​​of congested sections, and the deactivation conditions of the dynamic lane-specific variable speed limit strategy. Then, the congested highway section is managed according to the dynamic lane-specific variable speed limit strategy, and the management of the congested highway section is completed. The dynamic lane-specific variable speed limit strategy for congested sections includes the activation and deactivation of the dynamic lane-specific variable speed limit strategy, lane-specific speed limit values, and the publication of corresponding strategy content on information publishing devices.

[0057] A highway congestion control system based on a dynamic lane-specific variable speed limit strategy includes a first detection condition construction module, an activation condition establishment module, an influence factor calculation module, a speed limit calculation module, a second detection condition construction module, a closure condition establishment module, and a congestion control module. The first detection condition construction module is used to construct traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. The activation condition establishment module is used to establish activation conditions for the dynamic lane-specific variable speed limit strategy based on the traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. The influence factor calculation module is used to calculate the flow load factor, speed ratio factor, historical traffic data correction factor, and weather influence factor. The speed limit calculation module is used to calculate the flow load factor, speed ratio factor, and historical traffic data correction factor. A dynamic lane-specific speed limit calculation model for congested road sections is established based on weather influencing factors. The second detection condition construction module is used to construct detection conditions for traffic incidents being resolved, severe weather impacts being eliminated, and high-volume congestion being alleviated. The closing condition establishment module is used to establish closing conditions for the dynamic lane-specific variable speed limit strategy based on the detection conditions for traffic incidents being resolved, severe weather impacts being eliminated, and high-volume congestion being alleviated. The congested road section control module is used to generate a dynamic lane-specific variable speed limit strategy for congested road sections based on the activation conditions of the dynamic lane-specific variable speed limit strategy, the dynamic lane-specific speed limit calculation model for congested road sections, and the closing conditions of the dynamic lane-specific variable speed limit strategy. Then, the congested road sections on the highway are controlled according to the dynamic lane-specific variable speed limit strategy for congested road sections, and the highway congested road section control operation is completed.

[0058] The beneficial effects of this invention are as follows: This invention provides a method and system for managing congested highway sections based on a dynamic lane-specific variable speed limit strategy. First, it constructs traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. Then, based on these conditions, it establishes activation conditions for the dynamic lane-specific variable speed limit strategy. Next, it calculates traffic load factors, speed ratio factors, historical traffic data correction factors, and weather impact factors. Then, based on these factors, it establishes a calculation model for the dynamic lane-specific speed limit value of congested road sections. Subsequently, it constructs detection conditions for traffic events being resolved, severe weather impacts being eliminated, and high-volume congestion being alleviated. Then, based on these conditions, it establishes deactivation conditions for the dynamic lane-specific variable speed limit strategy. Finally, based on the activation conditions, the calculation model, and deactivation conditions, it generates the dynamic lane-specific variable speed limit value for congested road sections. The system employs a variable speed limit strategy, and then uses this strategy to manage congested sections of highways, effectively implementing automated and intelligent lane-specific speed limit control. By combining traffic event detection capabilities, severe weather monitoring results, and a quantitative judgment and decision-making model for high-volume congestion with checkpoints, radar, meteorological detectors, weather forecasts, and public alarms, the system can automatically detect mainline traffic events, severe weather, and high-volume congestion, determining whether to activate or deactivate the dynamic lane-specific variable speed limit strategy. Furthermore, by calculating the saturation and speed indices of mainline traffic flow, it can rationally construct a quantitative judgment and decision-making model for high-volume congestion and identify its occurrence. The dynamic lane-specific speed limit calculation model for congested sections integrates real-time traffic load, current speed ratio, historical traffic data correction, and global weather influences to calculate differentiated suggested speed limits for each lane and generate precise control strategies. This not only proactively prevents traffic deterioration but also improves driving safety while alleviating congestion. Attached Figure Description

[0059] Figure 1 This is an overall flowchart of a highway congestion control method based on a dynamic lane-specific variable speed limit strategy according to the present invention.

[0060] Figure 2 This is a schematic diagram illustrating the working principle of a highway congestion control system based on a dynamic lane-specific variable speed limit strategy, according to the present invention.

[0061] Figure 3This is a schematic diagram of the dynamic lane-specific variable speed limit strategy for congested highway sections according to the present invention. Detailed Implementation

[0062] The present invention will now be further described with reference to the accompanying drawings.

[0063] like Figure 1 As shown, the present invention provides a method for managing highway congestion based on a dynamic lane-specific variable speed limit strategy, comprising the following steps:

[0064] Step A involves constructing traffic incident detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. The specific steps are as follows:

[0065] Step A1: Construct traffic incident detection conditions, wherein the traffic incident detection conditions consist of traffic incident detection sub-conditions, which include traffic accidents and vehicle malfunctions, as shown in formula (1).

[0066] (1)

[0067] in, This is a Boolean value representing the traffic incident detection criteria. For the Boolean value of the sub-condition of traffic incident detection, The logical operator for OR;

[0068] A boolean value of true indicates that the virus was detected, while a boolean value of false indicates that the virus was not detected.

[0069] Step A2: Construct severe weather detection conditions, which are composed of severe weather detection sub-conditions. These sub-conditions include rain, fog, wind, snowfall, snow accumulation, sandstorm, and high road surface temperature, as shown in formula (2).

[0070] (2)

[0071] in, This represents a Boolean value for detection conditions under severe weather conditions. This is the Boolean value for the severe weather detection sub-condition. The threshold for the severe weather detection sub-condition is Level 2 in the meteorological industry standard "Meteorological Condition Classification of Highway Traffic". The classification standards for this level are as follows: 1. Rain, with a rainfall intensity of... And visibility 2. Fog 3. Wind, average wind force 7 or gusts force 8; 4. Snowfall, weather forecast: moderate snow; 5. Snow accumulation. 6. Sandstorm 7. High road surface temperature ;

[0072] Step A3: Construct high-flow congestion detection conditions, wherein the high-flow congestion detection conditions consist of high-flow congestion detection sub-conditions, which include flow saturation and average velocity, as shown in formula (3).

[0073] (3)

[0074] in, For high-volume congestion detection conditions, Boolean value. The Boolean value for the high-volume congestion detection sub-condition. The total traffic flow across all lanes of the main road. The total theoretical capacity of all lanes on the main road. The main road traffic saturation threshold. Lane number, The total number of lanes. for Lane traffic flow for Theoretical lane capacity The logical operator for AND. The average section speed of all lanes on the main road for Average lane section speed, The speed threshold for the main road section;

[0075] Main road traffic saturation threshold The value is 0.8. The mainline road traffic saturation is divided into four levels: Level 1 (smooth traffic, 0-0.6), Level 2 (slight congestion, 0.6-0.8), Level 3 (congestion, 0.8-1), and Level 4 (severe congestion, greater than 1). The mainline road section speed threshold is 50 km / h. .

[0076] Step B involves establishing the activation conditions for the dynamic lane-specific variable speed limit strategy based on traffic incident detection conditions, severe weather detection conditions, and high-volume congestion detection conditions, as shown in formula (4).

[0077] (4)

[0078] in, This is a Boolean value representing the start / stop condition of the strategy.

[0079] Step C involves calculating the traffic load factor, speed ratio factor, historical traffic data correction factor, and weather impact factor. The specific steps are as follows:

[0080] Step C1: Calculate the flow load factor, as shown in formula (5).

[0081] (5)

[0082] in, For the first Lane flow load factor;

[0083] Step C2, calculate the speed ratio factor, as shown in formula (6).

[0084] (6)

[0085] in, For the first Lane speed ratio factor Main road Lane design speed;

[0086] Step C3: Calculate the historical passage data correction factor, as shown in formula (7).

[0087] (7)

[0088] in, For the first Lane historical traffic data correction factor, For the first The lane's historical best average speed For the first The lane currently displays the speed limit.

[0089] Step C4: Calculate the weather influencing factors, as shown in formula (8).

[0090] (8)

[0091] in, Weather influencing factors , and These correspond to Level 2, Level 3, and Level 4 meteorological conditions, respectively.

[0092] , and The range of values ​​is ,and .

[0093] Step D involves establishing a dynamic lane-specific speed limit calculation model for congested road sections based on traffic load factor, speed ratio factor, historical traffic data correction factor, and weather impact factor, as shown in formula (9).

[0094] (9)

[0095] in, Dynamic speed limits for each lane in congested road sections. The minimum speed limit allowed by regulations. , and All are weighting coefficients, and .

[0096] Step E establishes the detection conditions for traffic incidents being resolved, severe weather impacts being eliminated, and heavy traffic congestion being alleviated. The specific steps are as follows:

[0097] Step E1: Construct the detection conditions for traffic incidents that have been processed, as shown in formula (10).

[0098] (10)

[0099] in, The traffic incident has been resolved. This is the Boolean value for the sub-condition that no traffic incident was detected.

[0100] Step E2: Construct detection conditions where the impact of severe weather has been eliminated, as shown in formula (11).

[0101] (11)

[0102] in, The effects of the severe weather have been eliminated. This is the Boolean value for the sub-condition that no severe weather was detected.

[0103] Step E3: Construct the detection conditions for high-volume congestion mitigation, as shown in formula (12).

[0104] (12)

[0105] in, The congestion caused by high traffic volume has been alleviated.

[0106] Step F involves establishing dynamic lane-specific variable speed limit strategy closure conditions based on the detection conditions that traffic incidents have been resolved, severe weather effects have been eliminated, and high-volume congestion has been alleviated, as shown in formula (13).

[0107] (13)

[0108] in, The dynamic lane-specific variable speed limit strategy is turned off.

[0109] like Figure 3As shown, step G involves generating a dynamic lane-specific variable speed limit strategy for congested road sections based on the activation conditions of the dynamic lane-specific variable speed limit strategy, the calculation model of the dynamic lane-specific speed limit value for congested road sections, and the deactivation conditions of the dynamic lane-specific variable speed limit strategy. Then, the congested road sections of the highway are controlled according to the dynamic lane-specific variable speed limit strategy, and the highway congestion control operation is completed. The dynamic lane-specific variable speed limit strategy for congested road sections includes the activation and deactivation of the dynamic lane-specific variable speed limit strategy, the lane-specific speed limit value, and the publication of the corresponding strategy content on the information publishing device.

[0110] The specific lane-specific speed limits are the recommended speed limits calculated for each lane, such as 100 km / h for the first lane. Second lane 80 Third lane 60 Information dissemination equipment includes roadside variable message signs (CMS), audio-visual equipment, and various navigation platforms; corresponding strategy content includes text and graphic information displayed by the roadside CMS, triggering and controlling audio, visual, and electrical warning signals, and data interface information for navigation platforms.

[0111] like Figure 2 As shown, a highway congestion control system based on a dynamic lane-specific variable speed limit strategy includes a first detection condition construction module, an activation condition establishment module, an influence factor calculation module, a speed limit calculation module, a second detection condition construction module, a closure condition establishment module, and a congestion control module. The first detection condition construction module is used to construct traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. The activation condition establishment module is used to establish activation conditions for the dynamic lane-specific variable speed limit strategy based on the traffic event detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. The influence factor calculation module is used to calculate the flow load factor, speed ratio factor, historical traffic data correction factor, and weather influence factor. The speed limit calculation module is used to calculate the flow load factor, speed ratio factor, and historical traffic data correction factor. The system establishes a dynamic lane-specific speed limit calculation model for congested road sections based on factors such as traffic incident handling, weather impact elimination, and high-volume congestion mitigation. The second detection condition construction module is used to construct detection conditions for traffic incident handling completion, severe weather impact elimination, and high-volume congestion mitigation. The closing condition establishment module is used to establish closing conditions for the dynamic lane-specific variable speed limit strategy based on these conditions. The congested road section control module generates a dynamic lane-specific variable speed limit strategy for congested road sections based on the dynamic lane-specific variable speed limit strategy activation conditions, the dynamic lane-specific speed limit calculation model for congested road sections, and the dynamic lane-specific variable speed limit strategy closing conditions. Then, it controls and manages congested road sections on highways according to the dynamic lane-specific variable speed limit strategy and completes the highway congestion control operation.

[0112] To better illustrate the effects of the present invention, a specific embodiment of using the present invention to manage congested sections of highways is described below.

[0113] This embodiment applies to a congested section of a three-lane highway. This section has a combination of slopes and curves, and the traffic flow consists of mixed passenger cars and trucks, making it prone to congestion in severe weather or under high traffic conditions.

[0114] 1. Traffic operation status perception data is collected through checkpoint equipment, radar equipment, and weather detectors, including: traffic flow in each lane of the main line, average section speed, traffic incident information, severe weather information, and historical traffic volume. Specific data are shown in Table 1.

[0115] Table 1. Traffic Operation Status Sensing Data

[0116]

[0117] 2. Determine the activation conditions of the dynamic lane-specific variable speed limit strategy according to formula (4). Moderate rain, rainfall intensity 20mm / h, visibility 200m, reaching level 2 impact, severe weather detection conditions. If true, the Boolean state indicating the activation of the dynamic lane-specific variable speed limit strategy. If true, the system will automatically activate the dynamic lane-specific speed limit strategy.

[0118] 3. Calculate the speed limit for each lane according to formula (9). Parameter settings are as follows: Weather Influence Factor =0.95; weighting coefficient =0.3、 =0.3、 =0.4; Flow load factor Speed ​​ratio factor Historical data correction factor The calculations were performed using formulas (5), (6), and (7). The results of the dynamic lane-specific speed limit calculations for congested road sections are shown in Table 2.

[0119] Table 2. Calculation Results of Dynamic Lane-Specific Speed ​​Limits for Congested Road Sections

[0120]

[0121] 4. Dynamic lane-specific variable speed limit strategy for congested road sections generates a strategy with a speed limit of 90 km / h for lane 1, 75 km / h for lane 2, and 75 km / h for lane 3, and forms an information dissemination plan. Then, the text and graphics are displayed through the roadside variable information sign CMS, and the sound, light, and electricity warning devices are triggered simultaneously, and the data is pushed to the navigation platform.

[0122] 5. Use formula (13) to determine the closing conditions. When severe weather is eliminated and congestion is alleviated, the Boolean state of the dynamic lane-specific variable speed limit strategy is closed. If true, the system automatically disables the policy. Table 3 shows the data comparison results between this invention and existing technologies in data testing.

[0123] Table 3. Data comparison results in data testing

[0124]

[0125] In summary, the present invention provides a method and system for managing highway congestion based on a dynamic lane-specific variable speed limit strategy. First, it establishes traffic incident detection conditions, severe weather detection conditions, and high-volume congestion detection conditions. Then, it establishes activation conditions for the dynamic lane-specific variable speed limit strategy based on these conditions. Next, it calculates traffic load factors, speed ratio factors, historical traffic data correction factors, and weather impact factors. Then, it establishes a calculation model for the dynamic lane-specific speed limit value of congested road sections based on these factors. Subsequently, it constructs detection conditions for traffic incident resolution, elimination of severe weather impact, and relief of high-volume congestion. Then, it establishes deactivation conditions for the dynamic lane-specific variable speed limit strategy based on these conditions. Finally, it generates the dynamic lane-specific variable speed limit for congested road sections based on the activation conditions, the calculation model, and the deactivation conditions. The strategy, based on the dynamic lane-specific variable speed limit strategy for congested road sections, manages and controls congested sections of highways, completing the management and control operations. This effectively enables the automated and intelligent implementation of lane-specific differentiated speed limit control for congested highway sections. Furthermore, by combining traffic event detection capabilities, severe weather monitoring results, and a quantitative judgment and decision-making model for high-volume congestion through checkpoints, radar, meteorological detectors, weather forecasts, or public alarms, it can automatically detect mainline road traffic events, severe weather, and high-volume congestion, determining whether to activate or deactivate the dynamic lane-specific variable speed limit strategy. Simultaneously, by calculating the saturation and speed indices of mainline road traffic flow, it can reasonably construct a quantitative judgment and decision-making model for high-volume congestion and determine its occurrence. The dynamic lane-specific speed limit calculation model for congested road sections calculates differentiated suggested speed limits for each lane by integrating real-time traffic load, current speed ratio, historical traffic data correction, and multiple factors including global weather influences, generating precise management strategies. This not only proactively prevents traffic deterioration but also improves driving safety while alleviating congestion.

[0126] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for managing a congestion section of an expressway based on a dynamic lane-dividing variable speed limit strategy, characterized in that: Comprising the following steps, Step A, constructing traffic incident detection condition, severe weather detection condition and heavy traffic congestion detection condition; Step B, establishing dynamic lane-based variable speed limit strategy start condition according to traffic incident detection condition, severe weather detection condition and heavy traffic congestion detection condition; Step C, calculating traffic load factor, speed ratio factor, historical traffic data correction factor and weather influence factor, the specific steps are as follows, Step C1, calculating traffic load factor, specifically as shown in formula (5), （5） wherein, is the lane flow load factor, is the lane traffic flow, is the lane theoretical capacity; Step C2, calculating speed ratio factor, specifically as shown in formula (6), （6） wherein, is the first lane speed ratio factor, is the mainline road first lane design speed, is the lane average segment speed; Step C3, calculating historical traffic data correction factor, specifically as shown in formula (7), （7） wherein, is the first lane history average speed, is the first lane history best average speed, is the first lane current posted speed value; Step C4, calculating weather influence factor, specifically as shown in formula (8), （8） wherein, is a weather influencing factor, , and are the corresponding 2nd, 3rd and 4th order weather conditions, respectively. Step D, establishing congestion road dynamic lane-based speed limit value calculation model based on traffic load factor, speed ratio factor, historical traffic data correction factor and weather influence factor, specifically as shown in formula (9), （9） wherein, is a dynamic lane speed limit value for a congested road segment, is a minimum speed limit value allowed by law, , and are weight coefficients, and ; Step E, constructing traffic incident processed detection condition, severe weather influence eliminated detection condition and heavy traffic congestion relieved detection condition; Step F, establishing dynamic lane-based variable speed limit strategy closing condition according to traffic incident processed detection condition, severe weather influence eliminated detection condition and heavy traffic congestion relieved detection condition; Step G, generating congestion road dynamic lane-based variable speed limit strategy based on dynamic lane-based variable speed limit strategy start condition, congestion road dynamic lane-based speed limit value calculation model and dynamic lane-based variable speed limit strategy closing condition, and then controlling and completing the control work of expressway congestion road according to the congestion road dynamic lane-based variable speed limit strategy.

2. The method according to claim 1, wherein the method is characterized in that: Step A, constructing traffic incident detection condition, severe weather detection condition and heavy traffic congestion detection condition, the specific steps are as follows, Step A1, constructing traffic incident detection condition, wherein the traffic incident detection condition is composed of traffic incident detection sub-condition, and the traffic incident detection sub-condition includes traffic accident and vehicle breakdown, specifically as shown in formula (1), （1） wherein, is a Boolean value for a traffic event detection condition, is a Boolean value for a traffic event detection sub-condition, is a logical operator for OR. Step A2, constructing severe weather detection condition, wherein the severe weather detection condition is composed of severe weather detection sub-condition, and the severe weather detection sub-condition includes rain, fog, wind, snowfall, snow accumulation, sandstorm and road surface high temperature, specifically as shown in formula (2), （2） wherein, a Boolean value for a severe weather detection condition, a Boolean value for a severe weather detection sub-condition; Step A3, constructing heavy traffic congestion detection condition, wherein the heavy traffic congestion detection condition is composed of heavy traffic congestion detection sub-condition, and the heavy traffic congestion detection sub-condition includes traffic saturation and average speed, specifically as shown in formula (3), （3） wherein, is a Boolean value for the large flow congestion detection condition, is a Boolean value for the large flow congestion detection sub-condition, is the total traffic flow of all lanes of the mainline road, is the total theoretical capacity of all lanes of the mainline road, is the flow saturation threshold of the mainline road, is the lane number, is the total number of lanes, is the lane traffic flow, is the lane theoretical capacity, is a logical operator with, is the average segment speed of all lanes of the mainline road, is the lane average segment speed, is the segment speed threshold of the mainline road.

3. The method according to claim 2, wherein the method is characterized in that: Step B, establishing dynamic lane-based variable speed limit strategy start condition according to traffic incident detection condition, severe weather detection condition and heavy traffic congestion detection condition, specifically as shown in formula (4), （4） wherein, Boolean value for policy on / off condition.

4. The method according to claim 3, wherein the method is characterized in that: Step E, constructing traffic incident processed detection condition, severe weather influence eliminated detection condition and heavy traffic congestion relieved detection condition, the specific steps are as follows, Step E1, constructing traffic incident processed detection condition, specifically as shown in formula (10), （10） wherein, is a Boolean value that traffic incident has been processed, is a Boolean value that no traffic incident detection sub-conditions are detected; Step E2, constructing severe weather influence eliminated detection condition, specifically as shown in formula (11), （11） wherein, the severe weather has dissipated, is a Boolean value indicating whether the severe weather detection sub-condition was not detected. Step E3, the large flow congestion has been relieved detection condition is constructed, and it is specifically shown as formula (12), （12） wherein is a large flow congestion has eased.

5. The method according to claim 4, wherein the method is characterized in that: Step F, the dynamic lane variable speed limit strategy closing condition is established according to the traffic event has been processed detection condition, the bad weather influence has been eliminated detection condition and the large flow congestion has been relieved detection condition, and it is specifically shown as formula (13), （13） wherein, is off for dynamic lane-variable speed limit strategy.

6. The method according to claim 5, wherein the method further comprises: Step G, the congestion road section dynamic lane variable speed limit strategy is generated based on the dynamic lane variable speed limit strategy starting condition, the congestion road section dynamic lane speed limit value calculation model and the dynamic lane variable speed limit strategy closing condition, and the congestion road section dynamic lane variable speed limit strategy is generated according to the congestion road section dynamic lane variable speed limit strategy for the expressway congestion road section management and completes the expressway congestion road section management work, wherein the congestion road section dynamic lane variable speed limit strategy includes dynamic lane variable speed limit strategy opening and closing, lane speed limit value and the corresponding strategy content is published on the information publishing equipment.

7. A highway congestion section management system based on a dynamic lane-division variable speed limit strategy, wherein the operation process of the highway congestion section management system is based on the highway congestion section management method according to any one of claims 1-6, characterized in that: It includes a first detection condition construction module, a starting condition establishment module, an influence factor calculation module, a speed limit value calculation module, a second detection condition construction module, a closing condition establishment module and a congestion road section management module, the first detection condition construction module is used to construct traffic event detection condition, bad weather detection condition and large flow congestion detection condition; The starting condition establishment module is used to establish the dynamic lane variable speed limit strategy starting condition according to the traffic event detection condition, the bad weather detection condition and the large flow congestion detection condition; The influence factor calculation module is used to calculate the flow load factor, the speed ratio factor, the historical traffic data correction factor and the weather influence factor; The speed limit value calculation module is used to establish the congestion road section dynamic lane speed limit value calculation model based on the flow load factor, the speed ratio factor, the historical traffic data correction factor and the weather influence factor; The second detection condition construction module is used to construct the traffic event has been processed detection condition, the bad weather influence has been eliminated detection condition and the large flow congestion has been relieved detection condition; The closing condition establishment module is used to establish the dynamic lane variable speed limit strategy closing condition according to the traffic event has been processed detection condition, the bad weather influence has been eliminated detection condition and the large flow congestion has been relieved detection condition; The congestion road section management module is used to generate the congestion road section dynamic lane variable speed limit strategy based on the dynamic lane variable speed limit strategy starting condition, the congestion road section dynamic lane speed limit value calculation model and the dynamic lane variable speed limit strategy closing condition, and the congestion road section dynamic lane variable speed limit strategy is generated according to the congestion road section dynamic lane variable speed limit strategy for the expressway congestion road section management and completes the expressway congestion road section management work.

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