Variable lane automatic control method based on card police data
By utilizing traffic police data for real-time analysis and dynamically adjusting variable lanes and signal control, the problem of insufficient flexibility in variable lane control methods has been solved, thereby improving traffic efficiency and urban traffic quality.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-22
- Publication Date
- 2026-04-03
AI Technical Summary
Existing variable lane control methods are not flexible enough to adapt to real-time changes in traffic demand, resulting in low traffic efficiency.
By utilizing traffic police data for real-time analysis, the lane attributes and signal control strategies of reversible lanes can be dynamically adjusted. Based on multi-dimensional information such as traffic flow, speed, and vehicle type, the coordinated optimization of reversible lanes and signal control can be achieved.
It improves the efficiency of vehicle traffic at intersections, reduces the number and duration of vehicle stops, lowers fuel consumption and exhaust emissions, and enhances the quality and image of urban traffic operations.
Smart Images
Figure CN121789482A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of intelligent traffic control technology, and in particular to an automatic control method for variable lanes based on traffic card and police data. Background Technology
[0002] With the acceleration of urbanization, urban traffic congestion has become increasingly serious, with a rapid increase in car ownership and a limited supply of road resources leading to an imbalance. To improve traffic efficiency, various traffic organization methods have emerged, such as reversible lanes, straight-ahead waiting areas, integrated waiting areas, queue-based traffic flow, and left-turn lane sharing. Among these, reversible lanes, due to their ability to dynamically change lane attributes, have become an important means of improving intersection capacity and are widely used.
[0003] Variable lane control effectively improves traffic efficiency by dynamically reconfiguring lanes that were originally for straight-ahead traffic into left-turn lanes, or vice versa, to match the number of lanes with traffic flow. However, existing variable lane control systems primarily rely on fixed time periods and control rules, resulting in poor flexibility and difficulty in adapting to real-time changes in traffic demands. Summary of the Invention
[0004] This application addresses the aforementioned problems and technical requirements by proposing a variable lane automatic control method based on traffic card and police data. The technical solution of this application is as follows: A variable lane automatic control method based on traffic card alarm data includes the following steps: Based on the traffic data of the target intersection and its upstream and downstream intersections during the current time period, determine the traffic data of the target entrance direction of the target intersection and the traffic data of the downstream intersection from the target entrance direction. Variable lanes are deployed in the target entrance direction. The speed of traffic flowing into the target intersection from the target entrance direction is determined based on the traffic data from the target entrance direction; the travel time for each direction of traffic from the target entrance direction to the downstream intersection is determined based on the traffic data from the target entrance direction and the traffic data from the downstream intersection from the target entrance direction. Based on the traffic flow speed at the target intersection and the travel time of each direction of traffic from the target entrance to the downstream intersection, determine the degree of congestion for each direction of traffic from the target entrance to the downstream intersection. The signal controller at the target intersection switches the lane attributes of the reversible lanes according to the congestion level in each direction of traffic. The lane attribute indicates whether the reversible lane is a straight-ahead lane or a left-turn lane.
[0005] The further technical solution includes congestion levels ranging from no congestion to light to heavy congestion, moderate to severe congestion, and driving directions including straight-ahead and left-turn directions. The lane attributes for switching reversible lanes include: When the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is higher than the congestion level of the left-turn direction, the lane attribute of the reversible lane is switched to a left-turn lane; when the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is lower than the congestion level of the left-turn direction, the lane attribute of the reversible lane is switched to a straight-ahead lane. When the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is equal to the congestion level of the left-turn direction, and both the straight-ahead and left-turn directions are congested, the lane attributes of the reversible lane remain unchanged. When the congestion level of both the straight-ahead and left-turn directions from the target entrance to the downstream intersection is not congested, the switching status of the reversible lane is determined based on the traffic data of the target entrance.
[0006] The further technical solution involves using traffic data, including license plate information and vehicle passage time, to determine the switching status of the reversible lane based on traffic data from the target entrance direction, including: Based on license plate information, determine the passage time of all vehicles entering the target intersection from the target entrance direction in the current time period at the upstream intersection of the target entrance direction and the target intersection, and calculate the travel time of each vehicle from the upstream intersection of the target entrance direction to the target intersection. The travel times of each vehicle are filtered, and based on the filtered travel times of all vehicles, the average travel time of all straight-going vehicles traveling from the target entrance to the downstream intersection is determined from the upstream intersection to the target intersection in the target entrance direction. And the average travel time of all left-turning vehicles traveling from the target entrance direction to the downstream intersection from the upstream intersection to the target intersection in the target entrance direction. ; Based on the average travel time of all straight-going vehicles and the average travel time of all left-turning vehicles Determine the switching status of the reversible lane.
[0007] The further technical solution involves determining the switching state of the reversible lane, including: When the current variable lane attribute for the target approach direction is a left-turn lane, determine the average travel time for all straight-through vehicles. and the average travel time of all left-turning vehicles The travel time is longer than And when the travel time is longer than TTR 1. When the switching threshold Th1 is exceeded, the lane attribute of the variable lane is switched to a straight lane; When the current variable lane attribute for the target approach direction is a straight-ahead lane, determine the average travel time of all straight-ahead vehicles. and the average travel time of all left-turning vehicles The travel time is longer than And when the travel time is longer than TTR 2. When the switching threshold Th2 is exceeded, the lane attribute of the variable lane will be switched to the left turn lane.
[0008] A further technical solution involves determining the current time period based on traffic data from the target import direction. k The number of vehicles traveling in each direction from the inner target entrance to the downstream intersection; based on the current time period. k The green light execution time and traffic volume of each driving direction corresponding to the phase of the inner target entrance direction to the downstream intersection are determined to establish the traffic saturation flow reference value of each driving direction corresponding to the phase. The traffic saturation flow reference value of each driving direction represents the lane carrying capacity of the driving direction. According to the current time period k The number of vehicles traveling from the inner target entrance direction to the downstream intersection in each driving direction is determined, and the lane inflow coefficient for each driving direction is determined. The lane inflow coefficient for each driving direction represents the traffic demand intensity of the driving direction. When the current variable lane attribute of the target entrance direction is a left-turn lane, the variable lane switching threshold Th1 is determined to be the ratio of the lane inflow coefficient of the corresponding phase of the straight direction to the reference value of the traffic saturation flow of the straight direction; when the current variable lane attribute of the target entrance direction is a straight lane, the variable lane switching threshold Th2 is determined to be the ratio of the lane inflow coefficient of the corresponding phase of the left-turn direction to the reference value of the traffic saturation flow of the left-turn direction.
[0009] Its further technical solution is, for the current time period k Any direction of traffic from the target entrance to the downstream intersection p , According to the direction of travel p Green light execution time for the corresponding phase and driving direction p Determine the driving direction based on the traffic volume in each lane. p Traffic saturation flow reference value for the corresponding phase , It is a time period k -1 Inner driving direction p Traffic saturation flow reference value for the corresponding phase, It is the direction of travel. p The i Traffic volume in each lane m It is the direction of travel. p Total number of lanes, integer parameter k ≥2; According to the direction of travel p The corresponding number of vehicles determines the direction of travel. p Corresponding lane inflow coefficient , Vol It represents the number of vehicles traveling in all directions from the target entrance direction to the downstream intersection.
[0010] A further technical solution is that the automatic control method for variable lanes also includes: For any direction of travel from the target entrance to the downstream intersection p When driving direction p When the congestion level is severe, the signal controller at the target intersection will adjust the direction of traffic. p The green light execution time for the corresponding phase is reduced to 0; When driving direction p When the congestion level is moderate, the signal controller at the target intersection will adjust the traffic direction. p The green light execution time for the corresponding phase is adjusted to the minimum green light time for the overflow phase; When driving direction p When the congestion level is light or no congestion, it depends on the direction of travel. p The corresponding phase's current green light execution time, green light requirement time, and direction of travel. p The corresponding number of vehicles determines the direction of travel. p The corresponding phase-adjusted green light execution time is used to control the signal controller at the target intersection.
[0011] Its further technical solution is to determine the driving direction. p The green light execution time after phase adjustment includes: According to the direction of travel p The current green light execution time for the corresponding phase Green light requirement time and driving direction p Determine the driving direction based on the traffic volume in each lane. p Traffic saturation flow reference value for the corresponding phase and green light time compensation value ; According to the direction of travel p Traffic saturation flow reference value for the corresponding phase and green light time compensation value Determine the driving direction p Green light execution time correction value , It is a compensation correction factor; when Determine driving direction in time p The green light execution time after phase adjustment is ,when Determine driving direction in time pThe green light execution time after phase adjustment is ,when Determine driving direction in time p The green light execution time after phase adjustment is , This is the maximum green light execution time. It is the minimum green light execution time.
[0012] Its further technical solution is, according to the driving direction p Green light execution time for the corresponding phase and driving direction p Determine the driving direction based on the traffic volume in each lane. p Traffic saturation flow reference value for the corresponding phase , It is a time period k -1 Inner driving direction p Traffic saturation flow reference value for the corresponding phase, It is the direction of travel. p The i Traffic volume in each lane m It is the direction of travel. p The total number of lanes; According to the direction of travel p Green light execution time for the corresponding phase and green light demand time Determine the driving direction p Green light time compensation value for the corresponding phase , It is a time period k -1 Inner driving direction p Green light time compensation value for the corresponding phase, integer parameter k ≥2.
[0013] A further technical solution involves determining any driving direction from the target entrance direction towards the downstream intersection. p The level of congestion includes: Determine any direction of travel from the target entrance to the downstream intersection within the current time period. p The average speed of all vehicles at the target intersection is in the direction of travel. p Traffic flow speed; determine driving direction p The average travel time of all vehicles between the target intersection and the downstream intersection is the travel time in the direction of travel. p Travel time; When driving direction p The travel time exceeds n1 times the target travel time but does not exceed n2 times the target travel time, and the direction of travel... p When the traffic flow speed is lower than the first speed threshold, determine the driving direction.p The congestion level is mild. When driving direction p The travel time exceeds n² times the target travel time but does not exceed n³ times the target travel time, and the direction of travel... p When the traffic flow speed is below the first speed threshold but above the second speed threshold, determine the driving direction. p The congestion level is moderate. When driving direction p The travel time exceeds n3 times the target travel time, and the direction of travel... p When the traffic flow speed is lower than the second speed threshold, determine the driving direction. p The congestion level is classified as severe or mild; where n1 < n2 < n3, the first speed threshold is greater than the second speed threshold, and the target travel time is the travel time when the traffic is smooth.
[0014] The beneficial technical effects of this application are: This application discloses an automatic control method for variable lanes based on traffic enforcement data. It eliminates the need for additional traffic sensing equipment at intersections, reducing construction and maintenance costs by reusing existing traffic enforcement cameras. Real-time, in-depth analysis of traffic enforcement data allows for precise capture of dynamic changes in traffic flow. Based on traffic demand at different times and in different directions, the method dynamically adjusts the turning and signaling schemes of the variable lanes, achieving coordinated optimization of variable lanes and signal control. This enhances the flexibility and adaptability of the control strategy to meet real-time traffic demands, improves intersection throughput, avoids lane idling or congestion, and increases the utilization rate of intersection space and time resources. Ultimately, this effectively alleviates urban traffic congestion and improves the overall quality of urban traffic operation.
[0015] This method goes beyond simple time-segmentation or fixed control rules. Instead, it comprehensively considers traffic pressure in all directions based on real-time traffic flow, speed, vehicle type, and transit time, making optimal variable lane turning decisions and signal control strategies. This makes it more adaptable to complex and ever-changing traffic environments. Furthermore, without altering the road surface, this method improves intersection efficiency in both time and space, effectively reducing vehicle stops and stopping times. It not only improves the travel efficiency of road users and reduces commuting time but also lowers fuel consumption and emissions caused by traffic congestion, thus contributing positively to environmental protection. Simultaneously, good traffic order and a smooth traffic environment help enhance a city's image and competitiveness, promoting sustainable urban development. Attached Figure Description
[0016] Figure 1 This is a flowchart of the automatic control method for variable lanes.
[0017] Figure 2 This is a schematic diagram of an intersection section in an example.
[0018] Figure 3 This is a schematic diagram of the deployment location of a reversible lane in an example. Detailed Implementation
[0019] The specific embodiments of this application will be further described below with reference to the accompanying drawings.
[0020] This application discloses a variable lane automatic control method based on card alarm data. Please refer to [the relevant documentation]. Figure 1 The flowchart shown illustrates the specific steps of this method as follows: Step 1: Based on the traffic data of the target intersection and its upstream and downstream intersections during the current time period, determine the traffic data of the target entrance direction of the target intersection and the traffic data of the downstream intersection from the target entrance direction. Variable lanes are deployed in the target entrance direction.
[0021] Based on the advantages of checkpoint-type electronic traffic enforcement equipment, such as high coverage, high operation and maintenance efficiency, readily available, accurate, real-time, and rich data types, this application uses readily available checkpoint-type electronic traffic enforcement data as the data source. Checkpoint-type electronic traffic enforcement data refers to various types of traffic data provided by checkpoint-type electronic traffic enforcement equipment. This data includes rich information such as vehicle passage time, speed, vehicle type, license plate, intersection name, direction, and lane number, effectively reflecting the traffic operation status.
[0022] The target intersection is a traffic intersection with reversible lanes that requires reversible lane control. Each target intersection corresponds to multiple approach directions; for example, a crossroads has four approach directions: east, west, south, and north. Reversible lanes can be deployed in any of these approach directions, but are generally deployed in the direction with higher traffic volume. Figure 2 Taking a scenario with multiple intersections as an example, the target intersection is the second intersection in the figure. The south entrance direction (R2 entrance) of the second intersection has a variable lane, so the south entrance direction is the target entrance direction. The upstream intersection of the target intersection is the first intersection. The downstream intersection from the target entrance direction is the third intersection. The downstream intersection from the target entrance direction is the fourth intersection.
[0023] Collecting and processing traffic data from traffic cameras at the target intersection and its upstream and downstream intersections yields traffic data for upstream intersections in the direction of the target entrance, traffic data for the target entrance direction of the target intersection, and traffic data for downstream intersections from the target entrance direction. Furthermore, because traffic camera data is highly accurate and has good real-time performance, it ensures that variable lane control is based on accurate and real-time traffic data, thus contributing to the accuracy and reliability of variable lane control.
[0024] Step 2: Determine the speed of traffic flowing into the target intersection from the target entrance direction based on the traffic data from the target entrance direction; determine the travel time for each direction of traffic from the target entrance direction to the downstream intersection based on the traffic data from the target entrance direction and the traffic data from the downstream intersection from the target entrance direction.
[0025] Traffic data includes vehicle passage time, speed, and license plate information. Based on license plate information, the data includes the passage time and speed of the same vehicle passing through the target intersection from the target entrance direction within the current time period; and the passage time of the same vehicle traveling from the target entrance direction to the downstream intersection within the current time period at both the target intersection and the downstream intersection. For example... Figure 2 As shown, the section between the second and third intersections is designated as the second section, and the section between the second and fourth intersections is designated as the third section.
[0026] For any straight-going vehicle at the R2 entrance of the second intersection i Straight-going vehicles i The crossing time at the second intersection is Straight-going vehicles i The crossing time at the third intersection is Then, vehicles going straight i The travel time in the second segment, i.e., for vehicles traveling straight. i The travel time between the target intersection and the downstream intersection is For any vehicle making a left turn at the R2 entrance of the second intersection. j Left-turning vehicles j The crossing time at the second intersection is Left-turning vehicles j The crossing time at the third intersection is Then the vehicle turning left j The travel time in the third section, i.e., for vehicles turning left. j The travel time between the target intersection and the downstream intersection is The duration of the current time period can be customized based on the actual application, such as 5 minutes, 10 minutes, or 15 minutes, serving as the data statistical update interval to collect a dataset of travel times for vehicles passing through the current time period. , Furthermore, based on statistical methods, the collected vehicle travel time dataset was further filtered. According to the 3σ principle of normal distribution, discrete outliers were detected and removed. Abnormal data regarding the travel time of a single vehicle in the second or third road segment within the current time period were filtered out in real time, resulting in a new travel time dataset. , .
[0027] Based on the filtered travel time dataset , It can determine any driving direction p The average travel time of all vehicles between the target intersection and the downstream intersection is the travel time in the direction of travel. p The travel time. Driving directions include straight ahead and left turns; the travel time for straight ahead... Travel time for left turn .
[0028] For any straight-going vehicle at the R2 entrance of the second intersection i Straight-going vehicles i The speed at the second intersection is For any vehicle making a left turn at the R2 entrance of the second intersection. j Left-turning vehicles j The speed at the second intersection is Collect a dataset of vehicle speeds during the current time period. , Similarly, based on statistical methods, the collected speed dataset is filtered. According to the 3σ principle of normal distribution, discrete outliers are detected and removed. Abnormal vehicle speed data for the second or third road segment within the current time period are filtered out in real time, resulting in a new dataset of passing vehicle speeds. , .
[0029] Based on the filtered vehicle speed dataset , It can be determined that the average speed of all vehicles traveling in any direction p from the target entrance towards the downstream intersection within the current time period is the traffic flow speed in direction p; the traffic flow speed in the straight-ahead direction... Speed of traffic turning left M is the total number of vehicles going straight, and N is the total number of vehicles turning left.
[0030] Step 3: Based on the traffic flow speed at the target intersection and the travel time for each direction of traffic from the target entrance to the downstream intersection, determine the congestion level for each direction of traffic from the target entrance to the downstream intersection.
[0031] Congestion levels are categorized as no congestion, mild to severe congestion, moderate congestion, and heavy congestion. Specifically, this involves determining any direction of traffic traveling from the target entrance towards the downstream intersection. p The level of congestion includes: When driving direction p The travel time exceeds n1 times the target travel time but does not exceed n2 times the target travel time, and the direction of travel... p When the traffic flow speed is lower than the first speed threshold, determine the driving direction. p The congestion level is mild. When driving direction p The travel time exceeds n² times the target travel time but does not exceed n³ times the target travel time, and the direction of travel... p When the traffic flow speed is below the first speed threshold but above the second speed threshold, determine the driving direction. p The congestion level is moderate. When driving direction p The travel time exceeds n3 times the target travel time, and the direction of travel... p When the traffic flow speed is lower than the second speed threshold, determine the driving direction. p The level of congestion is classified as severe or mild. When driving direction p The travel time does not exceed n1 times the target travel time and the direction of travel is p When the traffic flow speed is higher than the first speed threshold, determine the driving direction. p The level of congestion is not congested.
[0032] In this system, n1 < n2 < n3, the first speed threshold is greater than the second speed threshold, and the target travel time is the travel time under smooth traffic conditions, which can be predetermined based on historical traffic enforcement data. The specific values of the multiples n1, n2, and n3 are set based on actual application conditions and historical experience, for example, n1=0.5, n2=0.8, and n3=1.1. Similarly, the first and second speed thresholds are also set based on actual application conditions and historical experience, for example, the first speed threshold is set to 30 km / h and the second speed threshold is set to 10 km / h.
[0033] Step 4: The signal controller at the target intersection switches the lane attributes of the reversible lane according to the congestion level of each direction of traffic. The lane attribute indicates whether the reversible lane is a straight lane or a left-turn lane.
[0034] When moderate or higher levels of congestion occur in a driving direction, it indicates that the downstream road segment corresponding to that driving direction has shown signs of overflow. The number of lanes corresponding to the driving direction at the target entrance of the target intersection should be increased to suppress the flow impact of the target intersection on the downstream intersection, so as to facilitate the dissipation of vehicles accumulated in the expected overflow section and prevent the intersection from overflowing and causing a deadlock.
[0035] In one embodiment, switching the lane attributes of a reversible lane includes: When the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is higher than the congestion level of the left-turn direction, the lane attribute of the reversible lane is switched to a left-turn lane; when the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is lower than the congestion level of the left-turn direction, the lane attribute of the reversible lane is switched to a straight-ahead lane. When the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is equal to the congestion level of the left-turn direction, and both the straight-ahead and left-turn directions are congested, the lane attributes of the reversible lane remain unchanged. When the congestion level for both the straight-ahead and left-turn directions from the target entrance towards the downstream intersection is not congested, the switching status of the reversible lane is determined based on traffic data from the target entrance. Specifically, determining the switching status of the reversible lane based on traffic data from the target entrance includes: (1) Based on the license plate information, determine the passage time of all vehicles flowing into the target intersection from the target entrance direction in the current time period at the upstream intersection of the target entrance direction and the target intersection, and calculate the travel time of each vehicle from the upstream intersection of the target entrance direction to the target intersection.
[0036] (2) Filter the travel time of each vehicle, and determine the average travel time of all straight-going vehicles from the target entrance direction to the downstream intersection from the upstream intersection to the target intersection based on the filtered travel time of all vehicles. And the average travel time of all left-turning vehicles traveling from the target entrance direction to the downstream intersection from the upstream intersection to the target intersection in the target entrance direction. Filtering is used to remove data with abnormal travel times to improve the accuracy of calculations. Specific data filtering methods can adopt existing technologies, such as the statistical methods in step 2.
[0037] like Figure 2 As shown, the road segment between the first and second intersections is designated as the first segment. For any straight-going vehicle entering the R2 entrance at the second intersection... i Straight-going vehicles i The crossing time at the first intersection is Straight-going vehicles i The crossing time at the second intersection is Then, vehicles going straight i The travel time for the first segment, i.e., for vehicles traveling straight. i The travel time between the upstream intersection and the target intersection in the direction of the target entrance is: For any vehicle making a left turn at the R2 entrance of the second intersection. j Left-turning vehicles j The crossing time at the first intersection is Left-turning vehicles j The crossing time at the second intersection is Then the vehicle turning left j The travel time for the first segment, i.e., left-turning vehicles j The travel time between the upstream intersection and the target intersection in the direction of the target entrance is: The duration of the current time period can be customized based on the actual application, such as 5 minutes, 10 minutes, or 15 minutes, serving as the data statistical update interval to collect a dataset of travel times for vehicles passing through the current time period. , The collected vehicle travel time dataset is filtered to obtain a new travel time dataset. , .
[0038] Based on the filtered travel time dataset , The average travel time for all straight-going vehicles between the upstream intersection and the target intersection in the direction of the target entrance can be determined. Average travel time for all vehicles turning left .
[0039] (3) Based on the average travel time of all straight-going vehicles and the average travel time of all left-turning vehicles Determine the switching status of the reversible lane.
[0040] When the current variable lane attribute for the target approach direction is a left-turn lane, determine the average travel time for all straight-through vehicles. and the average travel time of all left-turning vehicles The travel time is longer than And when the travel time is longer than TTR 1. When the switching threshold Th1 is exceeded, the lane attribute of the variable lane is switched to a straight lane; When the current variable lane attribute for the target approach direction is a straight-ahead lane, determine the average travel time of all straight-ahead vehicles. and the average travel time of all left-turning vehicles The travel time is longer than And when the travel time is longer than TTR 2. When the switching threshold Th2 is exceeded, the lane attribute of the variable lane will be switched to the left turn lane.
[0041] The variable lane switching threshold is determined by information such as the current signal timing scheme of the target intersection, the proportion of straight and left-turn traffic, lane saturation, and traffic volume. The specific method is as follows: Determine the current time period based on traffic data from the target import direction. k The number of vehicles traveling in each direction from the inner target entrance to the downstream intersection; based on the current time period. kThe green light execution time and traffic volume of each driving direction corresponding to the phase of the inner target entrance direction to the downstream intersection are determined to establish the traffic saturation flow reference value of each driving direction corresponding to the phase. The traffic saturation flow reference value of each driving direction represents the lane carrying capacity of that driving direction. According to the current time period k The number of vehicles traveling from the inner target entrance direction to the downstream intersection in each driving direction is determined, and the lane inflow coefficient for each driving direction is determined. The lane inflow coefficient for each driving direction represents the traffic demand intensity in that driving direction. When the current variable lane attribute of the target entrance direction is a left-turn lane, the variable lane switching threshold Th1 is determined to be the ratio of the lane inflow coefficient of the corresponding phase of the straight direction to the reference value of the traffic saturation flow of the straight direction; when the current variable lane attribute of the target entrance direction is a straight lane, the variable lane switching threshold Th2 is determined to be the ratio of the lane inflow coefficient of the corresponding phase of the left-turn direction to the reference value of the traffic saturation flow of the left-turn direction.
[0042] The direction of the reversible lane is dynamically adjusted by detecting the traffic flow in the corresponding driving direction of the target entrance during the current time period and combining it with the current signal timing scheme to adapt to real-time changes in traffic demand. When the current reversible lane attribute of the target entrance is a left-turn lane, it is necessary to monitor the traffic status in the straight-ahead direction to determine whether the reversible lane needs to be adjusted to a straight-ahead lane; when the current reversible lane attribute of the target entrance is a straight-ahead lane, it is necessary to monitor the traffic status in the left-turn direction to determine whether the reversible lane needs to be adjusted to a left-turn lane.
[0043] Considering that lane inflow coefficients reflect the intensity of traffic demand in different driving directions—for example, the inflow coefficient for straight-ahead lanes reflects the proportion of straight-ahead traffic to the total traffic flow at that entrance, directly representing the level of vehicle traffic demand in that direction—and the traffic saturation flow reference value reflects the current lane capacity of that phase, indicating whether the lane has reached saturation. The ratio of the lane inflow coefficient to the traffic saturation flow reference value quantifies the degree to which "demand exceeds capacity." When the ratio exceeds a threshold, it indicates that the current lane allocation can no longer match the high demand or saturation state in that direction, and lane attributes need to be switched to increase the capacity in that direction. Combining both to calculate the threshold ensures that lane switching and signal timing adjustments are synchronized, maximizing intersection efficiency. The specific calculation methods for the lane inflow coefficient and the traffic saturation flow reference value are as follows: For the current time period k Any direction of traffic from the target entrance to the downstream intersection p According to the direction of travel p Green light execution time for the corresponding phase and driving direction p Based on the traffic volume in each lane, the driving direction is determined through smoothing.p Traffic saturation flow reference value for the corresponding phase , It is a time period k -1 Inner driving direction p Traffic saturation flow reference value for the corresponding phase, It is the direction of travel. p The i Traffic volume in each lane m It is the direction of travel. p Total number of lanes. Driving direction. p The total number of lanes is determined based on the attributes of the reversible lanes and the total number of lanes corresponding to the target entrance direction. Please refer to [reference needed]. Figure 3 As can be seen from the location of the reversible lane deployment, the current reversible lane is a straight-ahead lane, so the total number of lanes corresponding to the straight-ahead direction is 2, and the total number of lanes corresponding to the left-turn direction is 1. The smoothing process avoids misjudgments caused by short-term fluctuations, making the switching decisions more stable and realistic. The smoothing method is to smooth the current traffic saturation flow reference value with the result of the previous time period. Therefore, the current traffic saturation flow reference value needs to be determined based on the traffic saturation flow reference value of the previous time period, hence the integer parameters... k ≥2; while for the initial time period of k=1, the traffic saturation flow reference value .
[0044] According to the direction of travel p The corresponding number of vehicles determines the direction of travel. p Corresponding lane inflow coefficient , Vol This refers to the number of vehicles traveling from the target entrance direction to the downstream intersection in all directions, including the number of vehicles turning left, going straight, and turning right. , It represents the number of vehicles turning left. It represents the number of vehicles traveling in the straight direction. This refers to the number of vehicles turning right. The number of vehicles is calculated based on the actual traffic flow recorded by the traffic police. When calculating the traffic flow, large vehicles are converted to the equivalent of 2 small cars, and medium-sized vehicles are converted to the equivalent of 1.5 small cars, based on the vehicle type data in the traffic police data.
[0045] After the variable lane attribute is switched, each phase can be executed according to a fixed timing, which is a common practice at intersections. However, this approach is not flexible enough and does not meet the actual traffic flow requirements of the intersection. To improve the intersection's adaptability to real-time traffic flow, this application uses traffic monitoring data as support to monitor traffic flow trends and lane channelization in real time. It dynamically adjusts the green light execution time of each phase to construct a signal control strategy adapted to the variable lane switching strategy, thereby achieving synchronization between lane switching and signal timing adjustment and maximizing intersection throughput.
[0046] Specifically, the variable lane automatic control method of this application also includes: For any direction of travel from the target entrance to the downstream intersection p When driving direction p When the congestion level is classified as severe congestion, the traffic signal controller at the target intersection will be immediately notified to implement phase-change control, which means controlling the traffic signal controller at the target intersection to change the direction of travel. p The green light duration for the corresponding phase is reduced to 0 to alleviate traffic congestion at downstream intersections; When driving direction p When the congestion level is moderate, the signal controller at the target intersection will adjust the traffic direction. p The green light execution time for the corresponding phase is adjusted to the minimum green light time for the overflow phase. The minimum green light time for the overflow phase refers to the minimum green light time when the phase overflows, and this value can be directly extracted from the signal controller. In addition, during the congestion period, the variable lane switching function needs to be locked throughout the entire signal adjustment process so that the traffic at the intersection is implemented in the direction most conducive to eliminating the overflow problem. Once the vehicles in the overflow section have dissipated and the average travel time or average speed has returned to a reasonable range, the variable lane switching function is unlocked.
[0047] When the driving direction p When the congestion level is light or no congestion, it depends on the direction of travel. p The corresponding phase's current green light execution time, green light requirement time, and direction of travel. p The corresponding number of vehicles determines the direction of travel. p The corresponding phase-adjusted green light execution time is then used to control the signal controller at the target intersection. Since the signal controller stores the current signal timing scheme, the green light execution time and green light requirement time for each phase can be directly extracted from the signal controller.
[0048] In one embodiment, the driving direction is determined. p The green light execution time after phase adjustment includes: According to the direction of travel p The current green light execution time for the corresponding phase Green light requirement time and driving direction p Determine the driving direction based on the traffic volume in each lane. p Traffic saturation flow reference value for the corresponding phase and green light time compensation value ; According to the direction of travel p Traffic saturation flow reference value for the corresponding phase and green light time compensation value Determine the driving direction p Green light execution time correction value , This is the compensation correction factor, which can be customized according to the actual application. The default value is 1. when Determine driving direction in time p The green light execution time after phase adjustment is ,when Determine driving direction in time p The green light execution time after phase adjustment is ,when Determine driving direction in time p The green light execution time after phase adjustment is , This is the maximum green light execution time. It is the minimum green light execution time. The maximum and minimum green light execution times are defined in the signal controller.
[0049] By obtaining the green light execution time and green light demand time for each phase of the target intersection within the current time period, and smoothing the difference between the two, the green light time compensation value can be calculated. Specific traffic saturation flow reference values are also available. and green light time compensation value The calculation method is as follows: According to the direction of travel p Green light execution time for the corresponding phase and driving direction p Determine the driving direction based on the traffic volume in each lane. p Traffic saturation flow reference value for the corresponding phase , It is a time period k -1 Inner driving direction p Traffic saturation flow reference value for the corresponding phase, It is the direction of travel. p The i Traffic volume in each lane m It is the direction of travel. p The total number of lanes; According to the direction of travel p Green light execution time for the corresponding phase and green light demand time Determine the driving direction p Green light time compensation value for the corresponding phase , It is a time period k -1 Inner driving direction p Green light time compensation value for the corresponding phase, integer parameter k ≥2, the green light time compensation value for the initial period k=1. .
[0050] The method proposed in this application can effectively improve the accuracy, flexibility and universality of variable lane control, maximize the efficiency of intersection traffic, reduce vehicle delays, and provide a more effective technical means for urban traffic congestion management.
[0051] The above descriptions are merely preferred embodiments of this application, and this application is not limited to the above embodiments. It is understood that other improvements and variations that can be directly derived or conceived by those skilled in the art without departing from the spirit and concept of this application should be considered to be included within the protection scope of this application.
Claims
1. A variable lane automatic control method based on vehicle alarm data, characterized in that, The automatic control method for variable lanes includes: Based on the traffic data of the target intersection and its upstream and downstream intersections during the current time period, determine the traffic data of the target entrance direction of the target intersection and the traffic data of the downstream intersection from the target entrance direction. Variable lanes are deployed in the target entrance direction. The speed of traffic flowing into the target intersection from the target entrance direction is determined based on the traffic data from the target entrance direction; the travel time for each direction of traffic from the target entrance direction to the downstream intersection is determined based on the traffic data from the target entrance direction and the traffic data from the downstream intersection from the target entrance direction. Based on the traffic flow speed at the target intersection and the travel time of each direction of traffic from the target entrance to the downstream intersection, determine the degree of congestion for each direction of traffic from the target entrance to the downstream intersection. The signal controller at the target intersection switches the lane attributes of the reversible lanes according to the congestion level in each direction of traffic. The lane attribute indicates whether the reversible lane is a straight-ahead lane or a left-turn lane.
2. The automatic control method for variable lanes according to claim 1, characterized in that, The congestion level includes no congestion, light to heavy congestion, moderate congestion, and heavy congestion; the driving direction includes straight-ahead direction and left-turn direction; and the lane attributes for switching reversible lanes include: When the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is higher than the congestion level of the left-turn direction, the lane attribute of the reversible lane is switched to a left-turn lane; when the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is lower than the congestion level of the left-turn direction, the lane attribute of the reversible lane is switched to a straight-ahead lane. When the congestion level of the straight-ahead direction from the target entrance to the downstream intersection is equal to the congestion level of the left-turn direction, and both the straight-ahead and left-turn directions are congested, the lane attributes of the reversible lane remain unchanged. When the congestion level of both the straight-ahead and left-turn directions from the target entrance to the downstream intersection is not congested, the switching status of the reversible lane is determined based on the traffic data of the target entrance.
3. The automatic control method for variable lanes according to claim 2, characterized in that, The traffic data includes license plate information and vehicle passage time. Determining the switching status of the reversible lane based on the traffic data for the target entrance direction includes: Based on license plate information, determine the passage time of all vehicles entering the target intersection from the target entrance direction in the current time period at the upstream intersection of the target entrance direction and the target intersection, and calculate the travel time of each vehicle from the upstream intersection of the target entrance direction to the target intersection. The travel times of each vehicle are filtered, and based on the filtered travel times of all vehicles, the average travel time of all straight-going vehicles traveling from the target entrance to the downstream intersection is determined from the upstream intersection to the target intersection in the target entrance direction. And the average travel time of all left-turning vehicles traveling from the target entrance direction to the downstream intersection from the upstream intersection to the target intersection in the target entrance direction. ; Based on the average travel time of all straight-going vehicles and the average travel time of all left-turning vehicles Determine the switching status of the reversible lane.
4. The automatic control method for variable lanes according to claim 3, characterized in that, Determining the switching status of reversible lanes includes: When the current variable lane attribute for the target approach direction is a left-turn lane, determine the average travel time for all straight-through vehicles. and the average travel time of all left-turning vehicles The travel time is longer than And when the travel time is longer than TTR 1. When the switching threshold Th1 is exceeded, the lane attribute of the variable lane is switched to a straight lane; When the current variable lane attribute for the target approach direction is a straight-ahead lane, determine the average travel time of all straight-ahead vehicles. and the average travel time of all left-turning vehicles The travel time is longer than And when the travel time is longer than TTR 2. When the switching threshold Th2 is exceeded, the lane attribute of the variable lane will be switched to the left turn lane.
5. The automatic control method for variable lanes according to claim 4, characterized in that, Determine the current time period based on traffic data from the target import direction. k The number of vehicles traveling in each direction from the inner target entrance to the downstream intersection; based on the current time period. k The green light execution time and traffic volume of each driving direction corresponding to the phase of the inner target entrance direction to the downstream intersection are determined, and the traffic saturation flow reference value of each driving direction corresponding to the phase is determined. The traffic saturation flow reference value of each driving direction represents the lane carrying capacity of the driving direction. According to the current time period k The number of vehicles traveling from the inner target entrance direction to the downstream intersection in each driving direction is determined, and the lane inflow coefficient for each driving direction is determined. The lane inflow coefficient for each driving direction represents the traffic demand intensity of that driving direction. When the current variable lane attribute of the target entrance direction is a left-turn lane, the variable lane switching threshold Th1 is determined to be the ratio of the lane inflow coefficient of the corresponding phase in the straight direction to the traffic saturation flow reference value in the straight direction. When the current variable lane attribute of the target entrance direction is a straight lane, the variable lane switching threshold Th2 is determined to be the ratio of the lane inflow coefficient of the corresponding phase of the left turn direction to the reference value of the traffic saturation flow of the left turn direction.
6. The automatic control method for variable lanes according to claim 5, characterized in that, For the current time period k Any direction of traffic from the target entrance to the downstream intersection p , According to the driving direction p Green light execution time for the corresponding phase and the driving direction p The driving direction is determined based on the number of vehicles in each lane. p Traffic saturation flow reference value for the corresponding phase , It is a time period k The driving direction described in -1 p Traffic saturation flow reference value for the corresponding phase, The driving direction is p The i Traffic volume in each lane m The driving direction is p Total number of lanes, integer parameter k ≥2; According to the driving direction p The corresponding number of vehicles determines the driving direction. p Corresponding lane inflow coefficient , Vol It represents the number of vehicles traveling in all directions from the target entrance direction to the downstream intersection.
7. The automatic control method for variable lanes according to claim 1, characterized in that, The automatic control method for variable lanes also includes: For any direction of travel from the target entrance to the downstream intersection p When the driving direction p When the congestion level is severe, the signal controller at the target intersection will adjust the direction of travel. p The green light execution time for the corresponding phase is reduced to 0; When the driving direction p When the congestion level is moderate, the signal controller at the target intersection will adjust the direction of travel. p The green light execution time for the corresponding phase is adjusted to the minimum green light time for the overflow phase; When the driving direction p When the congestion level is light or no congestion, it depends on the direction of travel. p The corresponding phase's current green light execution time, green light requirement time, and driving direction. p The corresponding number of vehicles determines the driving direction. p The corresponding phase-adjusted green light execution time is used to control the signal controller at the target intersection.
8. The automatic control method for variable lanes according to claim 7, characterized in that, Determine the driving direction p The green light execution time after phase adjustment includes: According to the driving direction p The current green light execution time for the corresponding phase Green light requirement time and the driving direction p The driving direction is determined based on the number of vehicles in each lane. p Traffic saturation flow reference value for the corresponding phase and green light time compensation value ; According to the driving direction p Traffic saturation flow reference value for the corresponding phase and green light time compensation value Determine the driving direction p Green light execution time correction value , It is a compensation correction factor; when Determine the driving direction at the time p The green light execution time after phase adjustment is ,when Determine the driving direction at the time p The green light execution time after phase adjustment is ,when Determine the driving direction at the time p The green light execution time after phase adjustment is , This is the maximum green light execution time. It is the minimum green light execution time.
9. The automatic control method for variable lanes according to claim 8, characterized in that, According to the driving direction p Green light execution time for the corresponding phase and the driving direction p The driving direction is determined based on the number of vehicles in each lane. p Traffic saturation flow reference value for the corresponding phase , It is a time period k The driving direction described in -1 p Traffic saturation flow reference value for the corresponding phase, The driving direction is p The i Traffic volume in each lane m The driving direction is p The total number of lanes; According to the driving direction p Green light execution time for the corresponding phase and green light demand time Determine the driving direction p Green light time compensation value for the corresponding phase , It is a time period k The driving direction described in -1 p Green light time compensation value for the corresponding phase, integer parameter k ≥2.
10. The automatic control method for variable lanes according to claim 1, characterized in that, Determine any driving direction from the target entrance to the downstream intersection. p The level of congestion includes: Determine any direction of travel from the target entrance to the downstream intersection within the current time period. p The average speed of all vehicles at the target intersection is the speed in the direction of travel. p Traffic flow speed; determine the driving direction p The average travel time of all vehicles between the target intersection and the downstream intersection is the travel time in the direction of travel. p Travel time; When the driving direction p The travel time exceeds n1 times the target travel time but does not exceed n2 times the target travel time, and the travel direction p When the traffic flow speed is lower than a first speed threshold, the driving direction is determined. p The congestion level is mild. When the driving direction p The travel time exceeds n² times the target travel time but does not exceed n³ times the target travel time, and the travel direction... p When the traffic flow speed is lower than a first speed threshold but higher than a second speed threshold, the driving direction is determined. p The congestion level is moderate. When the driving direction p The travel time exceeds n3 times the target travel time value, and the travel direction p When the traffic flow speed is lower than the second speed threshold, the driving direction is determined. p The congestion level is classified as severe or mild; where n1 < n2 < n3, the first speed threshold is greater than the second speed threshold, and the target travel time is the travel time when the traffic is smooth.