A traffic signal lamp duration dynamic control method

Abstract

This invention relates to the technical field of dynamic control methods for traffic signal duration, and discloses a method for dynamic control of traffic signal duration. It utilizes a calculated congestion clearing time limit to restrict the number of vehicles flowing into congested road sections, allowing vehicles to alleviate congestion within the congestion clearing time limit, provided they are aware of the need to leave. After the congestion clearing time expires, the number of vehicles in the queue is recalculated, and the red light duration is redistributed to the corresponding first upstream node, increasing the duration. This allows the congestion clearing capacity of the core congestion node to be adjusted dynamically according to time changes. By comparing the number of vehicles in the queue before and after the congestion clearing time, if the number of vehicles in the queue is not less than the previous number, traffic police are notified via communication software to direct traffic. This allows for timely resolution of congestion caused by human factors, incorporating human factors into the method and improving its practicality.

Description

Technical Field

[0001] This invention relates to the technical field of dynamic control methods for traffic signal duration, specifically a dynamic control method for traffic signal duration. Background Technology

[0002] The dynamic control method for traffic signal duration is based on the real-time traffic flow status at the intersection (vehicle flow, queue length, pedestrian flow, etc.) to dynamically adjust the duration of each phase of the traffic lights, thereby achieving "on-demand allocation of green light resources" to improve intersection efficiency, reduce vehicle delays and queue lengths, and at the same time ensure the right-of-way for pedestrians and non-motorized vehicles and traffic safety. This research was supported by the Dazhou Municipal Architectural Environment Engineering Technology Research Center Project: "Research on the Framework and Planning of Intelligent Transportation Systems in Small and Medium-Sized Cities in my country" (Project No.: SDJ2022ZB-01).

[0003] Chinese patent application CN114842654B discloses a method for dynamic control of traffic signal duration. This scheme receives video image data of vehicular roads and / or pedestrian roads via a 5G network, determines the next round of vehicular road passage duration based on the video image data of the vehicular road within the signal light switching interval, and determines the pedestrian road passage duration by combining the concurrent video image data of the pedestrian road. Finally, the corresponding signal light display is controlled based on the above durations. This scheme can quickly integrate traffic flow and pedestrian information and optimize the signal light switching logic, but it has obvious limitations: The core assumption of this scheme is that "vehicles and pedestrians will travel according to established rules," completely excluding the influence of subjective human factors. However, in actual traffic congestion, human factors often dominate. For example, after a traffic accident at an intersection, the dispute between the parties involved may lead to road obstruction; or due to a sudden interesting event on the road, vehicles and pedestrians may gather around and be unwilling to pass through the intersection quickly. In this case, the scheme will continuously extend the green light duration in the congested direction because it detects "continuous congestion." However, in reality, the congestion of pedestrians and vehicles is not alleviated, but instead leads to traffic jams in the intersecting directions.

[0004] Therefore, when adjusting traffic lights at congested intersections, it cannot be assumed that traffic participants will completely follow the established rules; the relief of congestion needs to be limited, and the system cannot unilaterally extend the green light duration. To this end, this application proposes a dynamic control method for traffic light duration, aiming to solve the above problems. Summary of the Invention

[0005] (0) Technical problems to be solved The main objective of this invention is to provide a method for dynamic control of traffic light duration to solve the problems mentioned in the background.

[0006] (II) Technical Solution To achieve the above objectives, the present invention provides the following technical solution: a method for dynamic control of traffic light duration, comprising the following steps: Step 1: Establish a city-wide road traffic network, using the location of traffic lights on each road as the core node. Based on historical big data, set speed thresholds for vehicle speeds on each road and establish red light duration levels for the entire city's road traffic network. Step 2: Establish the first upstream node and the second upstream node for each core node. For each core node, define the traffic light at its directly upstream intersection as the first upstream node, and define the traffic light at the directly upstream intersection of the first upstream node as the second upstream node. Step 3: Monitor each road in real time through the video surveillance system. When the queue length of vehicles on a certain road exceeds the length of two or more core nodes, it is determined that the road is congested, and the core node at the downstream end of the congested section is identified as the congestion core node. Step 4: Determine the congestion clearing time of the core congestion node, and calculate the red light extension duration of the first upstream node based on the single-cycle traffic capacity of vehicles. Call the red light duration level according to the red light extension duration, monitor the average speed of vehicles on the road where the first upstream node is located, and adjust the red light extension duration of the second upstream node when the normal speed of vehicles at the first upstream node is lower than the speed threshold, and monitor the average speed of vehicles on the road where the second upstream node is located. Step 5: Monitor congested roads in real time. Within the congestion clearing time limit, monitor the length of congested road sections. Based on the principle that the vehicle queue length is reduced to within the length range of the two corresponding core nodes, determine traffic congestion and give corresponding responses.

[0007] Preferably, in establishing the city's road traffic network, the average vehicle speed on roads between adjacent core nodes is calculated using big data from normal urban traffic operation. The average vehicle speed on each road is then calculated by doubling the average vehicle speed during congestion in the big data and using this average as the normal vehicle speed threshold.

[0008] Preferably, when the first upstream node and the second upstream node to which the core node belongs intersect, the intersecting node is positioned as the first upstream node based on the principle that the first upstream node is greater than the second upstream node.

[0009] Preferably, the video surveillance system is based on computer vision algorithms to collect real-time data on the overall queue length of vehicles in congested road sections. With the number of vehicles in the queue .

[0010] Preferably, the road lengths of two or more adjacent core nodes are fixed, and traffic monitoring equipment is installed on all roads in the city. The traffic monitoring backend uses real-time data to collect the queue lengths of vehicles on each road. ,when When the road length exceeds that of two or more adjacent core nodes, it is identified as a congested road segment, and information on the congested core nodes at the downstream end of the congested road segment is collected.

[0011] Preferably, the city's road traffic network establishes red light switching duration levels, with 1 to 6 duration levels based on 30 seconds, 45 seconds, 60 seconds, 75 seconds, 90 seconds, and 120 seconds.

[0012] Preferably, the cycle for clearing queued vehicles at the congestion core node is determined by the real-time number of queued vehicles. The single-cycle throughput capacity of the core congestion node is the maximum number of vehicles that can be allowed to pass through in that direction within one signal cycle. The number of signal cycles that need to be alleviated is obtained by multiplying the number of signal cycles by the time required for one signal cycle to obtain the congestion clearing time for congestion relief.

[0013] Preferably, the single-cycle traffic capacity, red light switching duration, and green light switching duration of all first upstream nodes are obtained. The single-cycle traffic capacity is divided by the green light switching duration to obtain the number of vehicles exiting each first upstream node per second. The number of vehicles exiting each first upstream node per second is summed and then divided by the vehicle queue number. Divide by the sum to obtain the number of red light seconds that each first upstream node needs to add. Add the number of red light seconds to the existing red light switching duration of each first upstream node, determine the level of the red light switching duration after addition, and adjust the red light switching duration of each first upstream node one by one.

[0014] Preferably, the congestion clearing time The mitigation time for the first upstream node and the second upstream node is limited to a certain amount of congestion clearing time. Within the system, the first upstream node maximizes the red light switching time to prevent vehicles from merging into congested sections and exacerbating congestion. The second upstream node gradually increases the existing red light switching time levels and monitors the average vehicle speed on the adjusted road using speed thresholds, providing feedback to the second upstream node.

[0015] Preferably, the congestion clearing time After the expiration date, the overall queue length of vehicles on congested road sections will be retrieved again. With the number of vehicles in the queue The length of the vehicle compared to the previous one Number of vehicles in queue For comparison, based on vehicle length Congestion is determined by the number of vehicles in the queue. Not less than the number of vehicles in the previous queue If necessary, the traffic police will be notified in a timely manner via communication software to direct traffic offline.

[0016] Compared with the prior art, the present invention provides a method and system for dynamic control of traffic light duration, which has the following beneficial effects: 1. This invention limits the inflow of vehicles into congested road sections by setting a first upstream node. Within the congestion clearing time limit, the number of vehicles flowing into the congested road section is limited, so that vehicles in the congested road section can alleviate congestion within the congestion clearing time limit under the premise of having the awareness to leave on their own. Moreover, by sharing the vehicle number limit with multiple first upstream nodes, the red light duration limit of the first upstream node can be reduced, avoiding the occurrence of excessively long red light durations.

[0017] 2. This invention, by setting a congestion clearing time limit, recalculates the number of queued vehicles at the core congestion nodes of the congested road segment after the congestion clearing time expires, and redistributes the red light duration to the corresponding first upstream node, so that the congestion clearing capacity of the core congestion nodes can be adjusted according to time changes, maintaining dynamic adjustment.

[0018] 3. This invention compares the number of vehicles in the queue before and after the congestion clearing time. When the number of vehicles in the queue is not less than the number of vehicles in the previous queue, the traffic police are notified through communication software to conduct offline traffic control. For congestion that may be caused by human factors, the traffic police can be used to resolve it in a timely manner. Human factors are taken into account in the method, which improves its practicality. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating the overall steps of the present invention; Figure 2 This is a schematic diagram of the urban road traffic network structure of this invention; Figure 3 This is a schematic diagram of the architecture of the congestion core node of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Example 1, please refer to Figures 1 to 3 As shown: A method for dynamic control of traffic light duration, comprising the following steps: Step 1: Establish a city-wide road traffic network, using the location of traffic lights on each road as the core node. Based on historical big data, set speed thresholds for vehicle speeds on each road and establish red light duration levels for the entire city's road traffic network. Step 2: Establish the first upstream node and the second upstream node for each core node. For each core node, define the traffic light at its directly upstream intersection as the first upstream node, and define the traffic light at the directly upstream intersection of the first upstream node as the second upstream node. Step 3: Monitor each road in real time through the video surveillance system. When the queue length of vehicles on a certain road exceeds the length of two or more core nodes, it is determined that the road is congested, and the core node at the downstream end of the congested section is identified as the congestion core node. Step 4: Determine the congestion clearing time of the core congestion node, and calculate the red light extension duration of the first upstream node based on the single-cycle traffic capacity of vehicles. Call the red light duration level according to the red light extension duration, monitor the average speed of vehicles on the road where the first upstream node is located, and adjust the red light extension duration of the second upstream node when the normal speed of vehicles at the first upstream node is lower than the speed threshold, and monitor the average speed of vehicles on the road where the second upstream node is located. Step 5: Monitor congested roads in real time. Within the congestion clearing time limit, monitor the length of congested road sections. Based on the principle that the vehicle queue length is reduced to within the length range of the two corresponding core nodes, judge traffic congestion and give corresponding responses. For example, if the length of the vehicle queue is within the distance between the core congestion node and the previous upstream core node, it is judged that the congestion has been relieved. At this time, the red light duration of all first upstream nodes and second upstream nodes is restored to the original state. For example, if the length of the vehicle queue exceeds the distance between the core congestion node and the previous upstream core node, it is determined that the congestion has not been alleviated. At this time, based on the comparison between the re-detected number of vehicles in the queue and the previous number of vehicles in the queue, if the number of vehicles in the queue is less than the previous number of vehicles in the queue, the congestion has been effectively alleviated. Based on the latest number of vehicles in the queue and other data of the core congestion node, the red light duration level of the first upstream node is adjusted again. If the length of the vehicle queue exceeds the distance between the core congestion node and the previous upstream core node, but the number of vehicles in the queue is not less than the number of vehicles in the previous queue, it proves that the congestion relief operation is ineffective. At this time, the method continues to adjust the red light duration level of the first upstream node again based on the latest number of vehicles in the queue and other data, and at the same time notifies the traffic police through communication software to carry out offline traffic control, with manual assistance to improve the practicality of the method.

[0022] In establishing the city's road traffic network, using big data from normal urban traffic operation, the vehicle speed on roads between adjacent core nodes is calculated to obtain the average vehicle speed on each road. The average vehicle speed during congestion on each road in the big data is doubled and then multiplied by the average vehicle speed as the normal vehicle speed threshold. The normal vehicle speed threshold is a dynamic threshold that is adaptively adjusted based on at least one of the real-time or predicted weather and road conditions. For example, corresponding normal vehicle speed thresholds are established based on the weather conditions of sunny, rainy, foggy, and snowy days, and the corresponding vehicle speed threshold is called according to the real-time weather on the road.

[0023] The system assesses the road conditions after adjusting the red light duration at the first upstream node based on the normal vehicle speed threshold for each road. Then, it calls the second upstream node to control the average vehicle speed on the road at the second upstream node within the speed threshold range. The system monitors the effect of increasing the red light duration level and controls the number of vehicles flowing into congested road sections through the first upstream node. This increases the red light duration and reduces the number of vehicles flowing into the congested road sections, thus easing congestion.

[0024] When the first and second upstream nodes to which a core node belongs intersect, the intersecting node is designated as the first upstream node, based on the principle that the first upstream node is greater than the second upstream node. Congested road sections may contain a large number of core nodes, and each core node corresponds to a large number of first and second upstream nodes. When the first and second upstream nodes to which multiple core nodes belong intersect, the corresponding node is changed to the first upstream node, based on the principle that the first upstream node is greater than the second upstream node.

[0025] The video surveillance system uses computer vision algorithms to collect real-time data on the overall length of queued vehicles in congested road sections. With the number of vehicles in the queue queuing length To determine congestion, the number of vehicles in the queue. Determine whether this method is effective in alleviating congestion.

[0026] The city's road traffic network has established red light switching duration levels, with 1 to 6 levels based on standards of 30 seconds, 45 seconds, 60 seconds, 75 seconds, 90 seconds, and 120 seconds. Based on drivers' driving habits, the red light switching durations have been further categorized into six levels, from level 1 to level 6, with switching times of 30 seconds, 45 seconds, 60 seconds, 75 seconds, 90 seconds, and 120 seconds respectively. For example, if the red light switching duration of a certain first upstream node is 35 seconds, and it is between 30 seconds and 45 seconds (inclusive of 45 seconds, exclusive of 30 seconds), then the 45-second level 2 red light switching duration will be invoked. Similarly, if the time is between 45 and 60 seconds (inclusive of 60 seconds, exclusive of 45 seconds), then the 60-second Level 3 red light switching duration will be used. If the time is between 60 and 75 seconds (inclusive of 75 seconds, exclusive of 60 seconds), then the 75-second Level 4 red light switching duration will be used. If the time is between 75 and 90 seconds (inclusive of 90 seconds, exclusive of 75 seconds), then the 90-second Level 5 red light switching duration will be used. If the time is between 90 and 120 seconds (inclusive of 120 seconds, exclusive of 90 seconds), then the 120-second Level 6 red light switching duration will be invoked. If the red light switching duration is no more than 30 seconds, the Level 1 red light switching duration of 30 seconds will be used. If the red light switching duration is more than 120 seconds, the Level 6 red light switching duration of 120 seconds will still be used.

[0027] The time required to clear queued vehicles at key congestion nodes is determined by the real-time number of vehicles in the queue. The single-cycle throughput capacity of the core congestion node is used to determine the maximum number of vehicles that can pass through in that direction within one signal cycle. This yields the number of signal cycles required to alleviate congestion. Multiplying the number of signal cycles by the time required for one signal cycle gives the congestion clearing time. The specific steps are as follows: Step 1: Obtain the number of vehicles in the queue in real time Single-cycle traffic capacity of congestion core nodes Divide to obtain the number of signal cycles ; ; Number of vehicles in queue This represents the number of vehicles queuing between the congestion core node and the upstream core node, expressed in vehicles, and represents the single-cycle throughput capacity. This represents the maximum number of vehicles that can be allowed to pass through in that direction within one signal cycle, expressed in vehicles per cycle. The number of cycles is expressed in units of 1; Calculate the number of signal cycles required to clear congested road sections; Step 2: Obtain one signal cycle time of the core congestion node. ; = ; The congestion clearing time for this congested road segment is expressed in seconds. The time of one signal cycle for a congestion-prone core node, in seconds; By calculating the congestion clearing time, the red light time is increased using the first upstream node to reduce the number of vehicles entering congested road sections.

[0028] Example 2, please refer to Figures 1 to 3 As shown: Based on Example 1, the single-cycle traffic capacity, red light switching duration, and green light switching duration of all first upstream nodes are obtained. The single-cycle traffic capacity is divided by the green light switching duration to obtain the number of vehicles exiting each first upstream node per second. The number of vehicles exiting each first upstream node per second is summed, and the result is calculated using the vehicle queue number. Divide by the total to obtain the number of red light seconds that each first upstream node needs to add. Add the number of red light seconds to the existing red light switching duration of each first upstream node, determine the level of the added red light switching duration, and adjust the red light switching duration of each first upstream node one by one. The specific steps are as follows: Step 1: Obtain the single-cycle throughput of all first upstream nodes. Red light switching time Green light switching time ; Step 2: Obtain the total number of vehicles queued into the core node from the first upstream node per second: ; The single-cycle throughput of the first upstream node is divided by the corresponding green light switching duration to obtain the vehicle discharge volume per second of the first upstream node under ideal conditions. In actual use, the first upstream node is a multi-passage road. Under the red light restriction of the first upstream node, the first upstream node may still discharge vehicles by turning right. Therefore, the calculation formula calculates the total number of first upstream nodes per second under ideal conditions. Step 3: Obtain the additional red light duration required for all first upstream nodes: ; The red light switching time that needs to be added for each first upstream node; Step 4: Increase the red light duration for each of the existing red light switching durations at the first upstream node. The system then judges the results, determines the red light switching duration level, and calls the corresponding level of red light duration. By adjusting the red light switching duration of all first upstream nodes, the number of vehicles entering the congested section is reduced. Then, the video surveillance system monitors the average vehicle speed on the road where each first upstream node is located and the vehicle queue length on the congested section. The original state of the first upstream node may cause congestion due to the adjustment of the red light switching time. Therefore, when the corresponding first upstream node uses the speed threshold to determine congestion, it should restore the original state in time. Step 5: Once the average speed of vehicles on the road where the first upstream node is located is within the driving speed threshold range, the length of vehicle queues on the congested road section will be continuously monitored until the congestion is resolved. When the average vehicle speed on the road where the first upstream node is located is lower than the speed threshold, the red light switching duration of the corresponding road where the first upstream node is located will be restored to its original state, and the red light switching duration level of each second upstream node corresponding to the first upstream node will be increased by one level. The vehicle speed on the road where each second upstream node is located will be continuously monitored through monitoring equipment. When some roads are congested, the red light switching duration of the corresponding second upstream node will be restored to its original state. For each of the second upstream nodes to which the first upstream node that has already experienced congestion belongs, the red light switching duration level will be increased by one level from the existing level, and the average vehicle speed on the road where the adjusted second upstream node is located will be monitored. If the speed is within the speed threshold, the changed red light switching duration level will be maintained. If the average speed of the vehicle corresponding to the second upstream node is lower than the minimum value of the speed threshold, the red light switching duration of the corresponding second upstream node will be restored immediately. Step Six: The adjustment time for the first upstream node and the second upstream node is limited to... Within the time frame, when time T expires, the congested road segment is reassessed. If the congestion has eased, the red light switching duration of the first and second upstream nodes is restored to its original state. If the congestion has not eased, the length of the queued vehicles is recalculated, and the above steps are repeated. If the number of queued vehicles decreases, the cycle continues. If the number of queued vehicles increases or remains the same, it proves that the method of congestion relief is ineffective and manual intervention is required. Therefore, the traffic police are contacted through communication software. The single-cycle traffic capacity is calculated based on a preset standard vehicle equivalent. After counting the number of vehicles on the corresponding road, the video surveillance system converts this into the number of vehicles in queue based on the standard vehicle equivalent. ; The standard vehicle equivalent is a preset definition, such as setting a car as 1 equivalent, a regular bus or large passenger bus as 2 equivalent, and a large truck or large bus as 3 equivalent, etc. After the video surveillance system detects the corresponding vehicle, it converts it into a corresponding equivalent, and finally obtains a comprehensive number, which is the number of vehicles in the queue based on the standard vehicle equivalent. ; Obtain the single-cycle traffic capacity, red light switching duration, and green light switching duration of all first upstream nodes. Divide the single-cycle traffic capacity by the green light switching duration to obtain the number of vehicles exiting each first upstream node per second. Sum the number of vehicles exiting each first upstream node per second and use the vehicle queue number as the sum. Divide by the total to obtain the number of additional red light seconds required for each first upstream node. Add the red light seconds to the existing red light switching duration of each first upstream node, determine the level of the added red light switching duration, and adjust the red light switching duration of each first upstream node one by one. When congestion has eased, restore the red light switching duration of the first and second upstream nodes to their original state. If congestion has not eased, recalculate the queue length and predict the duration of congestion impact based on weather conditions. The specific steps are as follows: Step 1: Under the influence of current weather conditions, predict the congestion duration of queuing vehicles. The calculation formula is as follows: ; in, This indicates the predicted duration of congestion for vehicles in a queue. This represents the base duration, i.e., the normal travel time under undisturbed conditions. This represents the amplification factor of weather (or other factors) on travel time, set according to actual needs. This represents the influencing factor, set according to actual needs, i.e., the weather impact level; for example: the basic travel time for a certain road section under clear weather conditions. The time is set at 30 minutes. Based on historical data analysis, heavy rain can increase travel time on this road section by an average of 45%, therefore an impact coefficient is set. The value is 0.45. Today's weather forecast is for heavy rain. Assigning a value of 2, and substituting it into the formula, we get: T = 30 × (1 + 0.45 × 2) = 30 × (1 + 0.9) = 30 × 1.9 = 57 minutes. The prediction is that under the current weather conditions, the travel time on this section of the road will be extended to approximately 57 minutes. Step 2: Under the influence of current weather conditions, estimate the total travel time required for vehicles on the current road segment. The calculation formula is as follows: ; in, This indicates the estimated total time required to complete a certain section of road or task under specific conditions (such as current weather and road conditions). Indicates the length of the queue of vehicles. This represents the average speed of a vehicle traveling along a path under ideal, undisturbed conditions. For example, consider a queue of vehicles at an intersection with a length L = 2 kilometers. The average speed of the queue when the traffic is flowing smoothly is... =30 km / h. Historical data shows that heavy rain reduces the traffic efficiency of this intersection by 40%, therefore an impact coefficient is set. =0.4, the current weather warning is for heavy rain, therefore the weather impact factor is... =2, the base time is 2 divided by 30 = 0.0667 hours = 4 minutes, predicting the congestion duration: =4×(1+0.4×2)=4×1.8=7.2 minutes. Conclusion: After considering the impact of heavy rain, the predicted queue dissipation time at this intersection will be extended from 4 minutes to approximately 7.2 minutes. Step 3: Adjust the traffic light switching time according to the estimated total time, and contact the traffic police via communication software. Specifically, this is based on the calculated time. The traffic lights are adjusted by a timer countdown, and the red light turns on when the countdown ends.

[0029] Single-cycle capacity is the maximum number of vehicles that can be allowed to pass through the congestion core node in that direction within one signal cycle. This number of vehicles is calculated based on the standard vehicle equivalent, which improves the accuracy of congestion relief.

[0030] Congestion clearing time The mitigation time for the first and second upstream nodes is limited to a congestion clearing time. Within the system, the first upstream node maximizes the red light switching time to prevent vehicles from merging into congested sections and exacerbating congestion. The second upstream node gradually increases the existing red light switching time levels and monitors the average vehicle speed on the adjusted road using speed thresholds, providing feedback to the second upstream node.

[0031] Example 3, please refer to Figures 1 to 3 As shown: Based on Example 2, congestion clearing time After the expiration date, the overall queue length of vehicles on congested road sections will be retrieved again. With the number of vehicles in the queue The length of the vehicle compared to the previous one Number of vehicles in queue For comparison, based on vehicle length The number of vehicles used to determine congestion is determined by their length. It is the standard for judging traffic congestion, and the number of vehicles queuing on each road is calculated in real time using a video surveillance system. The length of the queue of vehicles When the length exceeds that of two or more adjacent core nodes, road congestion is determined, and the number of vehicles in the queue is [indicated]. The traffic light duration dynamic control method is used to assess the congestion level. If the number of vehicles on the congested road decreases, it indicates the method is effective. The system then recalculates the core congestion points and adjusts the timing for the next congestion clearing period. Within, continue to adjust the first upstream node and the second upstream node; if the number of queued vehicles... If the situation remains unchanged or increases, it proves that the control method is ineffective. In this case, the traffic police should be notified in a timely manner through communication software to conduct offline traffic control and manually clear the congestion. The change in the number of vehicles queuing on the actual congested road will determine whether the control method has a traffic clearing effect. Based on historical data, frequently congested road locations can be marked as high-incidence road sections, and the effective congestion clearing time can be verified by calling these high-incidence road sections. The adjustment schemes for the first upstream node and the second upstream node are based on the congestion occurrence time in historical data, and the congested road sections are adjusted in advance. Based on historical data, roads that frequently experience congestion can be marked as high-incidence sections. Successful congestion-alleviating solutions from this method are selected and recorded, along with their corresponding congestion clearing times. The adjustment schemes for the first and second upstream nodes are marked accordingly. Based on historical data, the time periods when congestion occurs frequently are prevented in advance. When the time approaches the start time of the time period again, the corresponding adjustment scheme is retrieved and the congested road is adjusted to prevent and alleviate congestion in advance.

[0032] In this invention, a city-wide road traffic network is established, with the location of traffic lights on each road as the core node. Based on historical big data, speed thresholds are set for each road, and red light duration levels of 1 to 6 are established for all traffic lights. The red light duration levels are based on the red light switching durations that drivers are familiar with, which enhances drivers' familiarity and improves their adaptability, avoiding unfamiliar and uncertain red light switching durations that increase drivers' aversion. For each core node, a first upstream node and a second upstream node are established. A video surveillance system is used to monitor roads in real time, identify congested roads, and calculate the queue length of vehicles on congested roads based on computer vision algorithms. With the number of vehicles in the queue When the length of the queue of vehicles on congested roads When the length of the congestion core node on the corresponding road exceeds the distance between the congestion core node and its direct upstream adjacent core node, it is judged as congestion. Since some congestion on roads is caused by human factors, the length of such congestion is within the distance between the congestion core node and its direct upstream core node. This kind of congestion is not caused by the vehicle discharge capacity of the congestion core node or the vehicle entry capacity of the upstream core node being unable to adapt to the large number of vehicles entering in a short period of time. Therefore, this situation needs to be excluded. By the length of the queued vehicles If the length of a vehicle exceeds the length of the congestion core node and its direct upstream adjacent core node, it indicates that there are too many vehicles on the current road segment and the poor traffic flow has caused the vehicle to exceed the length of two adjacent core nodes. Therefore, it is necessary to control the red light switching time so that the congested road can clear the vehicles as quickly as possible. Utilize the single-cycle traffic capacity of core congestion nodes and the number of vehicles queuing on congested roads. Data such as the time required for a single signal cycle at the core congestion node are used to calculate the congestion clearing time. The congestion clearing time is used to test the method's ability to alleviate congested road sections. Data such as congestion clearing time, single-cycle traffic capacity of each first upstream node, red light switching time, and green light switching time are used. This allows for the calculation of the additional red light duration required for each first upstream node, and the corresponding red light duration levels from 1 to 6 are then applied. By controlling the red light switching duration of the first upstream node, the number of vehicles flowing into congested roads from the first upstream node is reduced during the congestion clearing time. This allows congested roads to expel vehicles and alleviate congestion during the congestion clearing time by reducing the inflow of vehicles. After the first upstream node switches the red light switching duration, the average speed of vehicles on each road is monitored. The speed threshold of each road is used to determine whether the road is congested. If no congestion occurs, the red light switching duration of each road at the first upstream node is maintained. If the corresponding road is congested, the red light switching duration of the corresponding first upstream node is restored to its original state, and the level of the red light switching duration of each corresponding second upstream node is increased by one level. The average speed of vehicles on the adjusted road is judged using the speed threshold. If the vehicle speed is lower than the speed threshold, it proves that the adjustment of the red light duration level has caused road congestion, and the traffic lights on the corresponding road are restored to their original state. Once the congestion clearing period is over, the video surveillance system will reassess the congested sections, using the length of the queued vehicles. Make another judgment, if If the congestion is located within the length of the congestion core node and its directly upstream adjacent core node, then the surface congestion will be relieved, and the first upstream node and the second upstream node will be restored to their original state. if The length exceeds the length range between the congested core node and its directly adjacent upstream core nodes, affecting the number of queued vehicles. Make a judgment if the number of vehicles in the queue If the congestion is reduced, it proves that the method is effective. The congestion clearing time of the core congestion node and the red light increase duration of the corresponding first upstream node are recalculated. During the next new congestion clearing time, the congested road is cleared. If the number of vehicles in the queue If the time remains unchanged or increases, it proves that the method of clearing congestion is ineffective. The new congestion clearing time should still be used, the red light switching duration of each first upstream node should be adjusted, and at the same time, the traffic police should be notified in a timely manner through communication software to enter the congested road, find out the cause, clear the congestion, and determine whether to interrupt the control method.

[0033] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A traffic signal lamp duration dynamic control method, characterized in that, Includes the following steps: Step 1: Establish a city-wide road traffic network, using the location of traffic lights on each road as the core node. Based on historical big data, set speed thresholds for vehicle speeds on each road and establish red light duration levels for the entire city's road traffic network. Step 2: Establish the first upstream node and the second upstream node for each core node. For each core node, define the traffic light at its directly upstream intersection as the first upstream node, and define the traffic light at the directly upstream intersection of the first upstream node as the second upstream node. Step 3: Monitor each road in real time through the video surveillance system. When the queue length of vehicles on a certain road exceeds the length of two or more core nodes, it is determined that the road is congested, and the core node at the downstream end of the congested section is identified as the congestion core node. Step 4: Determine the congestion clearing time of the core congestion node, and calculate the red light extension duration of the first upstream node based on the single-cycle traffic capacity of vehicles. Call the red light duration level according to the red light extension duration, monitor the average speed of vehicles on the road where the first upstream node is located, and adjust the red light extension duration of the second upstream node when the normal speed of vehicles at the first upstream node is lower than the speed threshold, and monitor the average speed of vehicles on the road where the second upstream node is located. Step 5: Monitor congested roads in real time. Within the congestion clearing time limit, monitor the length of congested road sections. Based on the principle that the vehicle queue length is reduced to within the length range of the two corresponding core nodes, determine traffic congestion and give corresponding responses.

2. The traffic signal lamp duration dynamic control method of claim 1, wherein: In establishing the city's road traffic network, the average vehicle speed on roads between adjacent core nodes is calculated using big data from normal urban traffic operation. The average vehicle speed on each road is then calculated by doubling the average vehicle speed during congestion in the big data and using that average as the normal vehicle speed threshold. The normal vehicle speed threshold is a dynamic threshold that is adaptively adjusted based on at least one of the real-time or predicted weather and road conditions.

3. The traffic signal lamp duration dynamic control method of claim 2, wherein: When the first upstream node and the second upstream node to which the core node belongs intersect, the intersecting node is positioned as the first upstream node, based on the principle that the first upstream node is greater than the second upstream node.

4. The method for dynamic control of traffic signal duration according to claim 3, characterized in that: The video monitoring system is based on computer vision algorithm, and the whole queuing vehicle length of the congestion section is collected in real time The number of queuing vehicles .

5. The method for dynamic control of traffic signal duration according to claim 3, characterized in that: The road lengths of two or more adjacent core nodes are fixed. Traffic monitoring equipment is installed on all roads in the city, and the traffic monitoring backend uses real-time data to collect the queue lengths of vehicles on each road. ,when When the road length exceeds that of two or more adjacent core nodes, it is identified as a congested road segment, and information on the congested core nodes at the downstream end of the congested road segment is collected.

6. The method for dynamic control of traffic signal duration according to claim 4, characterized in that: The city's road traffic network will establish red light switching duration levels, with 1 to 6 duration levels based on 30 seconds, 45 seconds, 60 seconds, 75 seconds, 90 seconds, and 120 seconds.

7. The method for dynamic control of traffic signal duration according to claim 5, characterized in that: The cycle for clearing queued vehicles at the core congestion node is determined by the real-time number of queued vehicles. The single-cycle throughput capacity of the core congestion node is the maximum number of vehicles that can be allowed to pass through in that direction within one signal cycle. The number of signal cycles that need to be alleviated is obtained by multiplying the number of signal cycles by the time required for one signal cycle to obtain the congestion clearing time for congestion relief.

8. The method for dynamic control of traffic signal duration according to claim 7, characterized in that: Obtain the single-cycle traffic capacity, red light switching duration, and green light switching duration of all first upstream nodes. Divide the single-cycle traffic capacity by the green light switching duration to obtain the number of vehicles exiting each first upstream node per second. Sum the number of vehicles exiting each first upstream node per second and use the vehicle queue number as the sum. Divide by the total to obtain the number of additional red light seconds required for each first upstream node. Add the red light seconds to the existing red light switching duration of each first upstream node, determine the level of the added red light switching duration, and adjust the red light switching duration of each first upstream node one by one. When congestion has eased, restore the red light switching duration of the first and second upstream nodes to their original state. If congestion has not eased, recalculate the queue length and predict the duration of congestion impact based on weather conditions. The specific steps are as follows: Step 1: Predict the congestion duration of queuing vehicles under the influence of current weather conditions; Step 2: Under the influence of current weather conditions, estimate the total travel time required for vehicles on the current road segment; Step 3: Adjust the traffic light switching time according to the estimated total time, and contact the traffic police via communication software; The single-cycle traffic capacity is calculated based on a preset standard vehicle equivalent. After counting the number of vehicles on the corresponding road, the video surveillance system converts this into the number of vehicles in queue based on the standard vehicle equivalent. .

9. The method for dynamic control of traffic signal duration according to claim 8, characterized in that: The congestion clearing time The mitigation time for the first upstream node and the second upstream node is limited to a certain amount of congestion clearing time. Within the system, the first upstream node maximizes the red light switching time to prevent vehicles from merging into congested sections and exacerbating congestion. The second upstream node gradually increases the existing red light switching time levels and monitors the average vehicle speed on the adjusted road using speed thresholds, providing feedback to the second upstream node.

10. The method for dynamic control of traffic signal duration according to claim 9, characterized in that: The congestion clearing time After the expiration date, the overall queue length of vehicles on congested road sections will be retrieved again. With the number of vehicles in the queue The length of the vehicle compared to the previous one Number of vehicles in queue For comparison, based on vehicle length Congestion is determined by the number of vehicles in the queue. Not less than the number of vehicles in the previous queue If so, the traffic police will be notified in a timely manner via communication software to direct traffic offline; Based on historical data, frequently congested road locations can be marked as high-incidence road sections, and the effective congestion clearing time can be verified by calling these high-incidence road sections. The adjustment schemes for the first and second upstream nodes are based on the congestion occurrence times in historical data, and adjustments are made to congested road sections in advance.

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