Tidal lane control method, system and medium based on daily and event-based modes

Abstract

This invention discloses a tidal lane control method, system, and medium based on daily and event-based dual modes, relating to the field of intelligent transportation technology. It improves upon existing control technologies by establishing a switching logic between daily and event modes, thus solving the problem of the separation between the two modes. When a sudden event occurs, the event mode is activated to quickly and accurately adjust the lane configuration, avoiding waste of lane resources or insufficient traffic capacity.

Description

Technical Field

[0001] This invention relates to the field of intelligent transportation technology, specifically to a tidal lane control method, system, and medium based on both daily and event-based modes. Background Technology

[0002] Reversible lanes (also known as variable-direction lanes) are an effective engineering measure to alleviate the problem of uneven traffic flow in urban roads. Their basic principle is to dynamically adjust the lane's direction of travel based on the directional distribution characteristics of traffic flow at different times, thus matching road resource allocation with actual traffic demand. Currently, the control methods for reversible lanes are mainly divided into three categories: fixed-time control, reactive control, and predictive control.

[0003] Fixed-time control is based on historical traffic flow statistics. It pre-analyzes the regularity of road direction imbalances (e.g., heavy traffic entering the city during the morning rush hour and heavy traffic leaving the city during the evening rush hour), and then sets fixed time points (e.g., 7:00 to 9:00 AM during the morning rush hour) and a fixed number of lane changes (usually one lane). The lane change is executed when the preset time is reached. This scheme is highly reliable and widely used in tidal flow lane systems. However, this method is essentially open-loop control; the control commands rely solely on historical patterns and do not incorporate feedback from real-time traffic flow data. When actual traffic flow experiences random fluctuations or non-periodic changes, it cannot make timely adjustments.

[0004] Reactive control methods use embedded coils, radar, or video detectors to collect real-time data on two-way traffic flow and average speed, calculating the current saturation level (V / C ratio, i.e., the ratio of actual traffic flow to road capacity). When the saturation level exceeds a preset threshold, lane direction changes are triggered. Compared to fixed-time control, reactive control achieves closed-loop feedback and can respond to a certain degree of traffic flow fluctuations. However, this type of method has an inherent lag; changes are only triggered when congestion is detected, by which time congestion has already formed, with a response delay typically ranging from 3 to 10 minutes. In situations of rapid traffic flow changes (such as instantaneous peaks caused by the end of large events or road closures due to sudden accidents), this lag means that before the response, congestion has already spread to upstream sections, significantly reducing the effectiveness of carpool lane changes.

[0005] Predictive control methods utilize short-term traffic flow prediction models (such as time series analysis and LSTM recurrent neural networks) to predict the one-way design hourly traffic volume for the next 15 to 30 minutes, proactively adjusting the number of lanes before congestion occurs. Predictive control represents a shift from passive response to proactive prevention compared to reactive control; however, the effectiveness of this type of method highly depends on the accuracy of the prediction model, which is essentially an extrapolation based on historical patterns. Predictive results are good when the actual traffic flow pattern matches historical patterns; however, when the actual traffic flow exhibits non-periodic changes (i.e., events without historical patterns), the error of the prediction model increases significantly, or even fails completely.

[0006] The three existing technologies mentioned above share a common core defect: they are mainly designed to deal with periodic traffic flow changes that follow historical patterns, but cannot effectively respond to random fluctuations and non-periodic changes in traffic flow. When the actual traffic flow pattern on a given day does not conform to historical patterns, lane resources are easily wasted or traffic capacity is insufficient.

[0007] The aforementioned shortcomings are particularly prominent in emergency response scenarios and in scenarios with random fluctuations in daily traffic flow. When sudden events occur on roads (such as the end of large-scale events, traffic accidents, evacuations from natural disasters, severe weather, etc.), traffic flow patterns can instantly deviate from historical patterns. In directions where demand surges, severe congestion may occur due to insufficient lanes, while in directions where demand drops sharply, resources may be idle due to excess lanes. Even on non-event days, actual traffic flow does not strictly follow historical patterns. Sudden weather changes (such as a sudden afternoon downpour), road closures due to construction, traffic light malfunctions, and other unforeseen factors can all cause traffic flow to deviate from predicted values ​​in a short period of time. Although existing control methods can partially respond to such fluctuations, their prediction models mostly assume that traffic flow is regular and lack an effective adaptive correction mechanism for the deviation between predicted and actual values, still resulting in problems of untimely or over-response. Summary of the Invention

[0008] To address the challenge of ensuring that tidal flow lane systems can quickly and accurately adjust lane configurations even during random fluctuations or non-periodic changes in traffic flow, especially during sudden events where actual patterns significantly deviate from historical norms, thus preventing wasted lane resources or insufficient capacity, this invention aims to provide a tidal flow lane control method, system, and medium based on both daily and event-based modes. This method improves upon existing control technologies by establishing a switching logic between daily and event modes, resolving the issue of their disconnect. In the event of a sudden event, the event mode is activated to quickly and accurately adjust lane configurations, preventing wasted lane resources or insufficient capacity.

[0009] The above-mentioned technical objective of the present invention is achieved through the following technical solution:

[0010] This solution provides a tidal lane control method based on both daily and event-based modes, the method including:

[0011] Configuration steps: Preset daily mode parameter set and event mode parameter set, wherein the daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target service level is selected from the first service level as defined in the highway engineering technical standards, and the event mode parameter set includes the event tolerance target service level (LOS). emer and additional constraint vector {L max ,T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L max Indicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level;

[0012] Detection steps: Real-time detection of traffic flow data and event triggering signals on the target road;

[0013] Mode determination steps: When there is no event trigger signal, select the normal mode and determine the current service level of the target road accordingly; when an event trigger signal is received, select the event mode and determine the current service level of the target road accordingly.

[0014] Lane number calculation steps: Calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min = Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints;

[0015] Execution steps: Based on the minimum number of lanes N min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions;

[0016] Rollback steps: After the event trigger signal disappears, the current service level of the target road is gradually adjusted to the service level level of the normal mode at set time intervals; after each adjustment, the lane number calculation step and the execution step are repeated.

[0017] A further optimization scheme is that the method for setting the daily mode parameter set includes:

[0018] Multiple daily time period types are set, and the basic service level is determined according to the daily time period type; the time period types include: morning peak, off-peak, evening peak and night; wherein, the lower the traffic volume of the time period type, the higher the basic service level is configured;

[0019] Multiple weather conditions are set, and the basic service level is adjusted according to the weather conditions. The weather conditions include: sunny, light rain, moderate rain, heavy rain, snow, and fog. When the weather condition is sunny, the basic service level is not adjusted. When the weather condition is light rain, moderate rain, heavy rain, snow, or fog, the basic service level is downgraded. The greater the impact of the weather condition on traffic capacity, the greater the downgrade.

[0020] A further optimized solution is that the event triggering signal includes at least one of the following: disaster warning signal, traffic accident signal, large-scale event signal, and severe weather signal.

[0021] A further optimization scheme is to select the event mode according to a preset priority when multiple event trigger signals are received simultaneously; the preset priority includes: disaster warning signals take precedence over traffic accident signals, traffic accident signals take precedence over large-scale event signals, and large-scale event signals take precedence over severe weather signals.

[0022] A further optimization scheme is that, in event mode, the minimum number of lanes N min The calculation methods include:

[0023] Based on the shock wave model in traffic wave theory, the predicted queue length and predicted duration are calculated. The predicted queue length and predicted duration both decrease monotonically with the increase of the number of open lanes N.

[0024] Increment the number of open lanes N sequentially and verify the attached constraints: predict queue length L0≤L max And the predicted duration T0≤T max Find the minimum number of lanes that satisfy the constraints.

[0025] A further optimization scheme is that the calculation methods for the predicted queue length and predicted duration include:

[0026] The evacuation capacity flow Q is calculated based on the number of open lanes N of the target road and the maximum service traffic volume Q2 corresponding to the current service level. out (N) = N × Q2;

[0027] When the target demand flow Q in Q out When (N), the predicted queue length L0 is:

[0028] ;

[0029] The predicted total evacuation time T0 is:

[0030] ;

[0031] When the target demand flow Q in ≤Q out When (N), the predicted queue length L0 is: L0 = 0; the predicted total evacuation time T0 is: ;

[0032] Among them, V tota Indicates the total number of vehicles that need to be evacuated; T d Indicates the duration of demand; k a Indicates blockage density; k o This indicates the traffic density in the evacuation direction.

[0033] A further optimization scheme is that, in the rollback step, the minimum time interval between two adjacent target service level switching is △T, and the minimum number of lanes is recalculated after each switching, and a lane change command is generated only when the minimum number of lanes changes.

[0034] The further optimized solution also includes the following steps:

[0035] When switching from daily mode to event mode, within the first preset time window after receiving the event trigger signal, the service level level is gradually adjusted from the daily mode service level to the target service level of the event mode in a linear or exponential manner.

[0036] When executing a lane change command, within the first preset time window, some lanes are changed first, and after a second preset time window, the remaining lanes are changed.

[0037] This solution also provides a tidal flow lane control system based on both daily and event-based modes, used to implement the aforementioned tidal flow lane control method based on both daily and event-based modes; the system includes:

[0038] The configuration module is used to preset daily mode parameter sets and event mode parameter sets. The daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target service level is selected from the first service level as defined in the highway engineering technical standards; the event mode parameter set includes the event tolerance target service level (LOS). emer and additional constraint vector {L max ,T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L max Indicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level;

[0039] The detection module is used to detect traffic flow data and event trigger signals of the target road in real time.

[0040] The mode determination module is used to select the normal mode and determine the current service level of the target road when there is no event trigger signal; when an event trigger signal is received, it selects the event mode and determines the current service level of the target road according to the event mode.

[0041] The lane number calculation module is used to calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min = Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints;

[0042] The execution module is used to determine the minimum number of lanes N. min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions;

[0043] The rollback module gradually adjusts the current service level of the target road to the service level level of the normal mode at set time intervals after the event trigger signal disappears; after each adjustment, the lane number calculation step and the execution step are repeated.

[0044] This solution also provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, can implement the tidal lane control method based on daily and event-driven dual modes as described above.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. This invention provides a tidal lane control method, system, and medium based on daily and event dual modes. It improves the method on the basis of existing control technology. By establishing a switching logic relationship between daily mode and event mode, it solves the problem of the separation between daily mode and event mode. When a sudden event occurs, the event mode is activated to quickly and accurately adjust the lane configuration, so as to avoid waste of lane resources or insufficient traffic capacity.

[0047] 2. This invention provides a tidal lane control method, system, and medium based on daily and event-based dual modes. In daily mode, the target service level is dynamically adjusted according to time period, weather, and date type. Compared with the fixed service level threshold of existing technologies, this solution can achieve refined control based on the trade-off between traffic efficiency and traffic safety requirements in different scenarios. In event mode, queue length constraints and evacuation time constraints are introduced, ensuring that the determination of the number of lanes not only meets the traffic capacity requirements but also guarantees that queuing will not cause downstream overflow and evacuation will not exceed the safe time window. Compared with existing technologies that only use whether traffic capacity exceeds demand as the sole constraint, this invention provides more comprehensive safety assurance.

[0048] 3. This invention provides a tidal lane control method, system, and medium based on daily and event-based dual modes. After an event ends, a gradual rollback mechanism is adopted to gradually restore the target service level from the event mode level to the daily mode level. Each step pauses at a fixed time interval, and changes are only executed when the number of lanes changes. Compared with immediate switching or manual restoration, this invention can avoid abrupt changes in road capacity and reduce the risk of secondary congestion and rear-end collisions.

[0049] 4. This invention provides a tidal lane control method, system, and medium based on daily and event dual modes. When switching from daily mode to event mode, the lanes are gradually adjusted in a linear or exponential manner within the first preset time window, and the lanes are changed in batches instead of all lanes at once, giving the driver time to react and avoiding accidents such as rear-end collisions and traffic flow chaos caused by instantaneous changes in traffic capacity. Attached Figure Description

[0050] To more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly described below. It should be understood that the following drawings only show some embodiments of the present invention and should not be considered as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort. In the drawings:

[0051] Figure 1 This is a schematic diagram of the tidal lane control method based on both daily and event-based modes;

[0052] Figure 2 This is a schematic diagram of a tidal lane control system based on both daily and event-based modes.

[0053] Figure 3 This diagram illustrates the comparison between the traditional approach and the proposed approach. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the embodiments and accompanying drawings. The illustrative embodiments and descriptions of the present invention are only used to explain the present invention and are not intended to limit the present invention.

[0055] The core deficiency of existing tidal flow lane control technology is how to enable the system to quickly and accurately adjust lane configurations when traffic flow experiences random fluctuations or non-periodic changes, especially when there are sudden events where the actual pattern is significantly different from historical patterns, in order to avoid wasting lane resources or insufficient capacity. In view of this, this solution provides the following embodiments to solve the above-mentioned technical problems.

[0056] Example 1

[0057] This embodiment provides a tidal lane control method based on both daily and event-based modes, such as... Figure 1 The method specifically includes the following steps:

[0058] Configuration steps: Preset daily mode parameter set and event mode parameter set. The daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target level of service (LOS) is selected from the first level of service as defined in the highway engineering technical standards; the event mode parameter set includes the event tolerance target level of service (LOS). emer and additional constraint vector {L max T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L max Indicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level;

[0059] Specifically, the "Highway Engineering Technical Standards" defines service levels as six levels, from Level 1 to Level 6. Level 1 is free flow, with low traffic density and high speed, allowing drivers to freely choose their speed. Level 2 is relatively free stable flow, with increased traffic density but still relatively high speed. Level 3 is near-congested stable flow, with high traffic density and speed restrictions. Level 4 is high-density stable flow, with high traffic density and significantly reduced speed. Level 5 is congested flow, with traffic near saturation, low and unstable speed. Level 6 is forced flow, with severe congestion, intermittent or completely stopped traffic. In this embodiment, the daily mode uses Level 3 or Level 4, corresponding to a stable flow but close to the congestion limit. The event mode uses Level 5 or Level 6, corresponding to congested or forced flow, allowing for longer queues and lower driving speeds.

[0060] The configuration steps include the following methods for setting the daily mode parameter set;

[0061] Multiple daily time period types are set, and the basic service level is determined according to the daily time period type; the time period types include: morning peak, off-peak, evening peak and night; wherein, the lower the traffic volume of the time period type, the higher the basic service level is configured;

[0062] Specifically, during the morning rush hour, traffic flow is severely uneven, and this is a period of essential commuting demand. Prioritizing capacity is crucial; quantity is more important than speed. A lower service level is tolerated, and the basic service level is set at Level 4. During off-peak hours, traffic volume is relatively balanced, and efficiency is prioritized. Speed ​​is more important than capacity, and a higher service level is required. The basic service level is set at Level 2 or 3. The evening rush hour is similar to the morning rush hour but lasts longer. A balance between capacity and speed is needed, and a moderate service level is tolerated. The basic service level is set at Level 3 or 4. At night, traffic volume is low, congestion is almost negligible, and the focus is on rapid passage. The highest service level is required, and the basic service level is set at Level 2.

[0063] Multiple weather conditions are set, and the basic service level is adjusted according to the weather conditions. The weather conditions include: sunny, light rain, moderate rain, heavy rain, snow, and fog. When the weather condition is sunny, the basic service level is not adjusted. When the weather condition is light rain, moderate rain, heavy rain, snow, or fog, the basic service level is downgraded. The greater the impact of the weather condition on traffic capacity, the greater the downgrade.

[0064] Light rain makes roads slippery and slightly increases headroom, which slightly reduces traffic capacity. Therefore, the basic service level can be downgraded by 1 level. Moderate rain or light snow reduces visibility and vehicle speed, which moderately reduces traffic capacity. Therefore, the basic service level can be downgraded by 2 levels. Heavy rain or heavy snow results in extremely low visibility and may trigger event mode, which severely reduces traffic capacity. Therefore, the basic service level can be downgraded by 3 levels. Fog mainly affects visibility and severely reduces traffic capacity. Therefore, the basic service level can be downgraded by 2 levels.

[0065] The worse the weather, the lower the actual traffic capacity. If the target service level is not downgraded, the system will consider the current service level to be substandard, thus frequently triggering lane changes. However, in severe weather, even lane changes cannot restore the original traffic efficiency. Therefore, proactively downgrading the target service level can avoid meaningless frequent lane changes, allowing adjustments to be made based on the reality that the road can only achieve a lower service level, thus optimizing the control process.

[0066] In the configuration steps, the event triggering signal includes at least one of the following: disaster warning signal, traffic accident signal, large-scale event signal, and severe weather signal.

[0067] Specifically, in normal operation, the target service level (SLP) is not set arbitrarily. Instead, a base SLP is determined based on the current time period, and then adjusted according to the weather conditions, usually by downgrading it. For example, during a sunny off-peak period, the base SLP is configured as Level 3. Since it's sunny, the adjustment is zero, and the final SLP is Level 3. During a heavy rainstorm during the morning rush hour, priority is given to ensuring traffic capacity and tolerating a lower service level, so the base SLP is configured as Level 4. However, due to the heavy rain, the base SLP is downgraded by two levels, resulting in a final SLP of Level 6.

[0068] In this embodiment, the basic service level is configured as Level 4 during the morning peak, Level 3 during the off-peak, Level 4 during the evening peak, and Level 3 at night. The correction is zero for sunny days, -1 level for rainy days, -2 levels for moderate rain / light snow, -3 levels for heavy rain, and -2 levels for foggy days. The final service level table is shown below:

[0069] Table 1 Final Service Levels Table

[0070] Morning rush hour (7:00-9:00) Level 4 Level 4 Level 5 Level 6 Level 5 Off-peak hours (9:00-17:00) Level 3 Level 4 Level 4 Level 5 Level 4 Evening rush hour (5:00 PM - 7:00 PM) Level 4 Level 4 Level 5 Level 6 Level 5 Nighttime (7:00 PM - 7:00 AM) Level 3 Level 4 Level 4 Level 5 Level 4

[0071] Detection steps: Real-time detection of traffic flow data and event triggering signals on the target road;

[0072] Mode determination steps: When there is no event trigger signal, select the normal mode and determine the current service level of the target road accordingly; when an event trigger signal is received, select the event mode and determine the current service level of the target road accordingly.

[0073] In the mode determination step, when multiple event trigger signals are received simultaneously, the event mode is selected according to a preset priority. The preset priority includes: disaster warning signals take precedence over traffic accident signals, traffic accident signals take precedence over large-scale event signals, and large-scale event signals take precedence over severe weather signals.

[0074] Lane number calculation steps: Calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min =Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints;

[0075] In event mode, the minimum number of lanes N min The calculation methods include:

[0076] S1, based on the shock wave model in traffic wave theory, calculates the predicted queue length and predicted duration. The predicted queue length decreases monotonically with the increase of the number of open lanes N, and the predicted duration decreases monotonically with the increase of the number of open lanes N.

[0077] In step S1, the calculation methods for the predicted queue length and predicted duration include:

[0078] S11, calculate the evacuation capacity flow Q based on the number of open lanes N of the target road and the maximum service traffic volume Q2 corresponding to the current service level. out (N) = N × Q2;

[0079] S12, when the target demand flow Q in Q out When (N), under this condition, demand exceeds capacity, vehicles cannot be completely evacuated, resulting in queues and road saturation. The queues continue to grow during the evacuation process until the demand ends. At this point, the predicted queue length L0 is:

[0080] ;

[0081] The predicted total evacuation time T0 is:

[0082] ;

[0083] S13, when the target demand flow Q in ≤Q out When (N), under this condition, demand is less than or equal to capacity, all arriving vehicles can be evacuated, the queue will not continue to grow, the peak queue occurs in the initial stage, and is usually close to zero, the road is not saturated; the total evacuation time is mainly determined by the total number of vehicles and the evacuation flow; at this time, the predicted queue length L0 is: L0 = 0; the predicted total evacuation time T0 is: ;

[0084] Among them, V tota Indicates the total number of vehicles that need to be evacuated; T d Indicates the duration of demand; k a Indicates blockage density; k o This indicates the traffic density in the evacuation direction.

[0085] S2, incrementally increase the number of open lanes N and verify the attached constraints: predict the queue length L0≤L max And the predicted duration T0≤T max Find the minimum number of lanes that satisfy the constraints.

[0086] Execution steps: Based on the minimum number of lanes N min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions;

[0087] Rollback steps: After the event trigger signal disappears, the current service level of the target road is gradually adjusted to the service level level of the normal mode at set time intervals; after each adjustment, the lane number calculation step and the execution step are repeated.

[0088] In the rollback step, the minimum time interval between two adjacent target service level switching is △T, and the minimum number of lanes is recalculated after each switching. Lane change instructions are generated only when the minimum number of lanes changes.

[0089] It also includes the following steps:

[0090] When switching from daily mode to event mode, within the first preset time window after receiving the event trigger signal, the service level level is gradually adjusted from the daily mode service level to the target service level of the event mode in a linear or exponential manner.

[0091] When executing a lane change command, some lanes are changed within the first preset time window, and the remaining lanes are changed after the second preset time window.

[0092] In this embodiment, when switching from daily mode to event mode, lanes are gradually adjusted in a linear or exponential manner within the first preset time window, and lanes are changed in batches instead of all lanes at once, giving drivers time to react and avoiding accidents such as rear-end collisions and traffic flow chaos caused by instantaneous changes in traffic capacity.

[0093] Example 2

[0094] This embodiment provides a tidal lane control system based on both daily and event-based modes, such as... Figure 2 As shown, the system is used to implement the tidal lane control method based on daily and event-based dual modes as described in Embodiment 1; the system includes:

[0095] The configuration module is used to preset daily mode parameter sets and event mode parameter sets. The daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target service level is selected from the first service level as defined in the highway engineering technical standards; the event mode parameter set includes the event tolerance target service level (LOS). emer and additional constraint vector {L max ,T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L maxIndicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level;

[0096] The detection module is used to detect traffic flow data and event trigger signals of the target road in real time.

[0097] The mode determination module is used to select the normal mode and determine the current service level of the target road when there is no event trigger signal; when an event trigger signal is received, it selects the event mode and determines the current service level of the target road according to the event mode.

[0098] The lane number calculation module is used to calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min = Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints;

[0099] The execution module is used to determine the minimum number of lanes N. min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions;

[0100] The rollback module gradually adjusts the current service level of the target road to the service level level of the normal mode at set time intervals after the event trigger signal disappears; after each adjustment, the lane number calculation step and the execution step are repeated.

[0101] Example 3

[0102] This embodiment provides a computer-readable medium storing a computer program, characterized in that the computer program, when executed by a processor, can implement the tidal lane control method based on daily and event-driven dual modes as described in Embodiment 1; specifically, it performs the following steps:

[0103] Configuration steps: Preset daily mode parameter set and event mode parameter set, wherein the daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target service level is selected from the first service level as defined in the highway engineering technical standards, and the event mode parameter set includes the event tolerance target service level (LOS). emer and additional constraint vector {L max T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L max Indicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level;

[0104] Detection steps: Real-time detection of traffic flow data and event triggering signals on the target road;

[0105] Mode determination steps: When there is no event trigger signal, select the normal mode and determine the current service level of the target road accordingly; when an event trigger signal is received, select the event mode and determine the current service level of the target road accordingly.

[0106] Lane number calculation steps: Calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min = Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints;

[0107] Execution steps: Based on the minimum number of lanes N min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions;

[0108] Rollback steps: After the event trigger signal disappears, the current service level of the target road is gradually adjusted to the service level level of the normal mode at set time intervals; after each adjustment, the lane number calculation step and the execution step are repeated.

[0109] Example 4

[0110] This embodiment takes the roads surrounding a city stadium as an example to illustrate the specific implementation of the present invention in the scenario of dispersing a large event; the stadium can accommodate 30,000 people, and the surrounding roads are two-way six lanes including variable lanes. The game is expected to end at 21:30, and the dispersal method is: to guide people out in batches, with each batch consisting of about 8,000 people.

[0111] During the match (19:00 to 21:00), the system is in normal mode. The current time period is after the evening rush hour, and the weather is sunny. The target service level (LOS) is determined by referring to the table. target =LOS norm =Level 3; Real-time detection of two-way traffic flow, outputting the short-term traffic volume in the direction of entry for the next 15 minutes via a short-term prediction model: Q1 = 2800 pcu / h; The maximum service traffic volume per lane corresponding to Level 3 is Q2 = 1400 pcu / h / ln, and the minimum number of lanes N is calculated. min :

[0112] Minimum number of lanes N min =2800 / 1400=2 items;

[0113] There are currently 3 lanes for entering the direction, and the configuration meets the requirements, so no changes will be made.

[0114] The match ended at 21:00. The ticketing system issued a dispersal event signal (warning 30 minutes before the end of the match). There were no higher priority events at the moment. The event type was confirmed to be a large-scale event. The system switched from daily mode to event mode and set the LOS (Loss on Demand). target =LOS emer =Level 6, Additional Constraints L max =300 meters, T max =60 minutes.

[0115] Based on parameters such as the number of people leaving the venue and the average passenger load factor, the predicted short-term traffic volume is Q1 = 8000 pcu / h, and the maximum service traffic volume of a single lane corresponding to Level 6 is Q2 = 2200 pcu / h / ln; the maximum number of available evacuation lanes is 6 (original 3 lanes + 1 lane in the opposite direction + 1 shoulder).

[0116] The basic number of lanes N0 is calculated based on the shock wave model in traffic wave theory:

[0117] N0 = 8000 / 2200 = 3.64, so N0 is set to 4.

[0118] Due to the target demand flow Q in =Q1 =8000 pcu / h<Q out (4) = 4 × 2200 = 8800 pcu / h; belongs to the condition of supply exceeding demand, the queue length is basically 0: L0(4) = 0; the predicted total evacuation time T0(4) is: T0(4) = 30 minutes; meets the maximum allowable duration constraint and the maximum allowable queue length constraint; no additional lanes are needed.

[0119] Since there are already 3 lanes for daily departures, an additional lane is needed, which will utilize one lane in the opposite direction or a shoulder lane.

[0120] Once the event has essentially ended and traffic volume in the departing direction has been detected to drop to within 1.2 times the normal level (≤3,360 pcu / h) for 15 consecutive minutes, the event is confirmed to be over, and the event enters rollback mode.

[0121] The rollback process takes 10 minutes, and the rollback path is: Level 6 → Level 5 → Level 4 → Level 3. The corresponding rollback process records are shown in the table below.

[0122] Table 2 Rollback Process Record Sheet

[0123] 22:00 Level 6 - 3000 - 4 - Start rolling back 22:10 Level 5 1900 2900 2 4 yes Close the oncoming lane or shoulder lane. 22:20 Level 4 1600 2800 2 3 no Do not execute 22:30 Level 3 1400 2800 2 3 no Do not execute

[0124] After the rollback is completed, the system resumes normal daily operation. The results of this solution compared with the traditional static solution are as follows: Figure 3 As shown.

[0125] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above description is only a specific embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A tidal flow lane control method based on daily and event-based dual modes, characterized in that, The method includes: Configuration steps: Preset daily mode parameter set and event mode parameter set, wherein the daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target service level is selected from the first service level as defined in the highway engineering technical standards, and the event mode parameter set includes the event tolerance target service level (LOS). emer and additional constraint vector {L max ,T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L max Indicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level; Detection steps: Real-time detection of traffic flow data and event trigger signals on the target road; Mode determination steps: When there is no event trigger signal, select the normal mode and determine the current service level of the target road accordingly; when an event trigger signal is received, select the event mode and determine the current service level of the target road accordingly. Lane number calculation steps: Calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min = Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints; Execution steps: Based on the minimum number of lanes N min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions; Rollback steps: After the event trigger signal disappears, the current service level of the target road is gradually adjusted to the service level level of the normal mode at set time intervals; after each adjustment, the lane number calculation step and the execution step are repeated.

2. The tidal lane control method based on daily and event-driven dual modes according to claim 1, characterized in that, The method for setting the daily mode parameter set includes: Set multiple daily time period types, and determine the basic service level based on the daily time period types; The time periods include: morning peak, off-peak, evening peak, and nighttime; among them, the lower the traffic volume of a time period, the higher the level of basic service configured. Multiple weather conditions are set, and the basic service level is adjusted according to the weather conditions. The weather conditions include: sunny, light rain, moderate rain, heavy rain, snow, and fog. When the weather condition is sunny, the basic service level is not adjusted. When the weather condition is light rain, moderate rain, heavy rain, snow, or fog, the basic service level is downgraded. The greater the impact of the weather condition on traffic capacity, the greater the downgrade.

3. The tidal lane control method based on daily and event-driven dual modes according to claim 1, characterized in that, The event triggering signal includes at least one of the following: disaster warning signal, traffic accident signal, large-scale event signal, and severe weather signal.

4. The tidal lane control method based on daily and event-driven dual modes according to claim 3, characterized in that, When multiple event trigger signals are received simultaneously, the event mode is selected according to a preset priority. The preset priority includes: disaster warning signals take precedence over traffic accident signals, traffic accident signals take precedence over large-scale event signals, and large-scale event signals take precedence over severe weather signals.

5. The tidal lane control method based on daily and event-driven dual modes according to claim 1, characterized in that, In event mode, the minimum number of lanes N min The calculation methods include: Based on the shock wave model in traffic wave theory, the predicted queue length and predicted duration are calculated. The predicted queue length and predicted duration both decrease monotonically with the increase of the number of open lanes N. Increment the number of open lanes N sequentially and verify the attached constraints: predict queue length L0≤L max And the predicted duration T0≤T max Find the minimum number of lanes that satisfy the constraints.

6. The tidal lane control method based on daily and event-driven dual modes according to claim 5, characterized in that, The methods for calculating the predicted queue length and predicted duration include: The evacuation capacity flow Q is calculated based on the number of open lanes N of the target road and the maximum service traffic volume Q2 corresponding to the current service level. out (N) = N × Q2; When the target demand flow Q in Q out When (N), the predicted queue length L0 is: ； The predicted total evacuation time T0 is: ； When the target demand flow Q in ≤Q out When (N), the predicted queue length L0 is: L0 = 0; the predicted total evacuation time T0 is: ; Among them, V tota Indicates the total number of vehicles that need to be evacuated; T d Indicates the duration of demand; k a Indicates blockage density; k o This indicates the traffic density in the evacuation direction.

7. The tidal lane control method based on daily and event-driven dual modes according to claim 1, characterized in that, In the rollback step, the minimum time interval between two adjacent target service level switching is △T, and the minimum number of lanes is recalculated after each switching. A lane change command is generated only when the minimum number of lanes changes.

8. The tidal lane control method based on daily and event-driven dual modes according to claim 1, characterized in that, It also includes the following steps: When switching from daily mode to event mode, within the first preset time window after receiving the event trigger signal, the service level level is gradually adjusted from the daily mode service level to the target service level of the event mode in a linear or exponential manner. When executing a lane change command, within the first preset time window, some lanes are changed first, and after a second preset time window, the remaining lanes are changed.

9. A tidal flow lane control system based on daily and event-driven dual modes, characterized in that, The system is used to implement the tidal lane control method based on daily and event-based dual modes as described in any one of claims 1-8; the system comprises: The configuration module is used to preset daily mode parameter sets and event mode parameter sets. The daily mode parameter set includes target service level (LOS) corresponding to multiple time period-weather combinations. norm The target service level is selected from the first service level as defined in the highway engineering technical standards; the event mode parameter set includes the event tolerance target service level (LOS). emer and additional constraint vector {L max ,T max The event tolerance target service level is selected from the second-level service level as defined in the highway engineering technical standards; where L max Indicates the maximum allowed queue length; T max Indicates the maximum allowed duration; Level 1 service level is higher than Level 2 service level; The detection module is used to detect traffic flow data and event trigger signals of the target road in real time. The mode determination module is used to select the normal mode and determine the current service level of the target road when there is no event trigger signal; when an event trigger signal is received, it selects the event mode and determines the current service level of the target road according to the event mode. The lane number calculation module is used to calculate the minimum required number of lanes N based on the predicted future short-term traffic volume Q1 and the maximum service traffic volume Q2 corresponding to the current service level of the target road. min = Q1 / Q2; where, in event mode, the calculation process for the minimum number of lanes also needs to satisfy additional constraints; The execution module is used to determine the minimum number of lanes N. min Generate lane change instructions, and change the direction and number of lanes according to the lane change instructions; The rollback module gradually adjusts the current service level of the target road to the service level level of the normal mode at set time intervals after the event trigger signal disappears; after each adjustment, the lane number calculation step and the execution step are repeated.

10. A computer-readable medium having a computer program stored thereon, characterized in that, The computer program, when executed by a processor, can implement the tidal lane control method based on daily and event-based dual modes as described in any one of claims 1-8.

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