Signal management and control evaluation method based on traffic capacity

Abstract

The invention discloses a traffic capacity-based signal management and control evaluation method, which comprises the following steps of: determining a lane saturation flow of each lane, and determining a corresponding lane traffic capacity according to the lane saturation flow; obtaining flow direction information of each lane, determining a flow direction passing flow allowable value in combination with the traffic capacity of the lane, and determining different path passing flow allowable values of the intersection based on the flow direction passing capacity; and evaluating a signal control scheme at the bottleneck point of the path according to the path traffic allowable value, determining a flow direction congestion state of a coordinated flow direction at the bottleneck point, and judging whether the signal control scheme has an optimization space or not through a threshold value. According to the method, the saturation flow and traffic capacity analysis of each lane and flow direction is refined, so that highly refined evaluation of traffic conditions is realized, traffic bottlenecks and potential problem areas are identified more accurately, and accurate data support is provided for subsequent signal optimization; by acquiring the lane flow direction information in real time or regularly, the effect of the signal control scheme can be dynamically evaluated.

Description

Technical Field

[0001] The present invention relates to the technical field of capacity assessment, and in particular to a signal control assessment method based on capacity. Background Art

[0002] A mixed lane is a road width for various vehicles to travel together within the same road width, collectively referred to as a carriageway. Its width is called the carriageway width, and also called the single-lane road width. In the absence of any control measures, right turns are greatly affected by straight driving. During the period when straight-moving vehicles stop and wait for the green light, right-turning vehicles can only queue up with other vehicles. At the same time, right-turning vehicles are interspersed in the straight-moving traffic flow. Affected by non-motor vehicles traveling in the same direction, they travel at a slower speed, forming a barrier to the straight-moving traffic flow and reducing traffic efficiency. However, the evaluation of lane capacity and the corresponding signal control scheme in the existing technology often lack an accurate assessment of the actual congestion bottleneck position in the path, resulting in a gap between the signal control scheme and the actual traffic situation.

[0003] For example, a "traffic control method for alleviating traffic congestion at oversaturated intersections in cities" disclosed in Chinese patent literature, with publication number: CN113863074B, discloses that the flow data of the intersection is used to analyze the flow characteristics and congestion characteristics of the intersection; based on the vehicle queue length data at the intersection, the congestion period of the intersection, as well as the entrance and flow direction with the most serious queue length are analyzed; based on the flow characteristics of the intersection, the congestion characteristics of the intersection, the congestion period of the intersection, the entrance with the most serious queue length at the intersection, and the flow direction with the most serious queue length at the intersection, a comprehensive waiting area for the intersection is constructed by arranging pre-stop lines and pre-signal lights; by setting the cycle of the pre-signal lights and main signal lights corresponding to each lane, vehicles at the intersection are diverted, but this solution is difficult to evaluate the actual congestion location. Summary of the invention

[0004] In order to solve the problem in the prior art that it is impossible to accurately evaluate according to the actual congestion location, the present invention provides a signal control evaluation method based on capacity, which can determine the allowable value of path traffic flow according to the actual congestion location in the path, and then accurately evaluate the signal scheme at the intersection.

[0005] In order to achieve the above object, the present invention provides the following technical solutions: A signal scheme evaluation method based on traffic capacity includes: determining a lane saturation flow rate of each lane, and determining the corresponding lane traffic capacity according to the lane saturation flow rate; Obtain the flow direction information of each lane, determine the allowable flow rate of the flow direction in combination with the lane capacity, and determine the allowable flow rates of different paths at the intersection based on the allowable flow rate of the flow direction; According to the path traffic flow allowable value, the signal control scheme at the bottleneck point of the path is evaluated, the flow congestion state of the coordinated flow at the bottleneck point is determined, and the signal control scheme is judged by the threshold whether there is room for optimization. By refining the saturated flow and capacity analysis of each lane and flow direction, a highly refined assessment of traffic conditions is achieved, traffic bottlenecks and potential problem areas are more accurately identified, and precise data support is provided for subsequent signal optimization; by obtaining lane flow information in real time or regularly, the effect of the signal control scheme can be dynamically evaluated, which helps to adjust the signal timing in time to cope with changes in traffic flow; the evaluation scope is expanded to different paths of the entire intersection, which helps to find bottlenecks and conflict points in the overall traffic flow, so as to formulate a more comprehensive optimization strategy.

[0006] As a preferred method, when determining the lane saturation flow, a time interval is constructed, and the intersection signal cycle data at the intersection corresponding to the time interval is obtained; and the green signal ratio of the lane in the signal cycle data is determined. It is possible to accurately collect and analyze traffic data within a specific time period and avoid the influence of noise and uncertainty.

[0007] Preferably, when determining the lane saturation flow, it also includes determining the initial saturation flow, counting the initial saturation flow of each lane at each intersection, and filtering out unreasonable data in the initial saturation flow through threshold judgment. The ability to obtain accurate and comprehensive saturation flows of different lanes helps to accurately reflect actual traffic conditions and reduce analysis deviations caused by insufficient data or excessive errors.

[0008] Preferably, when determining lane capacity, signal schemes of multiple intersections are obtained, the green-signal ratio of each lane is determined respectively, and the lane capacity is obtained in combination with the lane saturation flow of the corresponding lane. This can accurately reflect the actual lane capacity under different signal control conditions, avoid the error caused by rough estimation based only on lane saturation flow, and discover the commonalities and differences between different intersections.

[0009] Preferably, when determining the flow direction flow allowance, the lanes in the same direction are clustered and summed to determine the flow direction of each lane; the lane capacity corresponding to several lanes with the same flow direction information is summed. By identifying the traffic bottlenecks and congestion points through the flow direction flow allowance, the actual path capacity can be accurately reflected.

[0010] As a preferred method, when determining the allowed value of the path traffic flow, all the intersection information and positions in the path are obtained, and a traffic ID is formed based on the intersection information and positions; an intersection model is established to determine the coordinated traffic capacity of each traffic ID. This helps to fully understand the traffic conditions of each link on the path and can more accurately reflect the mutual influence and restriction relationship between the intersections on the path. Through the established intersection model, the coordinated traffic capacity of the traffic ID can be dynamically evaluated.

[0011] Preferably, when determining the path traffic flow allowable value, the method further includes sorting each intersection according to the coordinated traffic capacity, and sorting the intersections according to the green signal ratio benchmark value to select bottleneck intersections. This can more accurately identify bottleneck intersections caused by improper signal control or unreasonable traffic organization.

[0012] Preferably, when determining the flow congestion state, it includes determining the flow speed of each flow direction at each entrance of the intersection, and determining the travel time and average speed according to the flow speed at different intersections. It can capture subtle traffic changes and more accurately identify which flow directions or time periods are congested, thereby improving the accuracy of congestion state determination.

[0013] Preferably, when evaluating the signal control scheme, the method includes obtaining the flow flow allowable value and the flow congestion state of the corresponding flow direction, and judging the flow saturation according to the ratio thereof. The flow saturation can be quantitatively evaluated, and the signal control scheme can be comprehensively evaluated in multiple dimensions.

[0014] Preferably, when judging the signal control scheme by threshold, it includes obtaining historical data of bottleneck points, determining the flow saturation in the historical data, and judging whether there is room for optimization according to the percentage of oversaturation in the flow saturation. Potential problems and optimization space in the signal control scheme can be accurately identified, which is not only applicable to busy traffic areas such as urban main roads, but also allows more frequent data updates and threshold adjustments to better deal with traffic congestion problems.

[0015] The present invention has the following advantages: By analyzing the saturated flow and capacity of each lane and direction, a highly refined assessment of traffic conditions is achieved, traffic bottlenecks and potential problem areas are identified more accurately, and precise data support is provided for subsequent signal optimization. By acquiring lane flow information in real time or periodically, the effectiveness of signal control schemes can be dynamically evaluated, which helps to adjust signal timing in a timely manner to cope with changes in traffic flow. Expanding the scope of evaluation to different paths throughout the intersection helps to identify bottlenecks and conflict points in the overall traffic flow, thereby formulating a more comprehensive optimization strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The drawings described below are merely exemplary. A person skilled in the art can derive other implementation drawings based on the provided drawings without inventive effort.

[0017] Figure 1 Schematic diagram of the method steps in the embodiment.

[0018] Figure 2 It is a schematic diagram of the logical steps in the embodiment. DETAILED DESCRIPTION

[0019] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in the field without making any creative work shall fall within the scope of protection of the present invention.

[0020] like Figure 1-Figure 2 As shown, in a preferred embodiment, the present invention discloses a signal scheme evaluation method based on capacity, including: determining the lane saturation flow of each lane, and determining the corresponding lane capacity according to the lane saturation flow; by refining the saturation flow and capacity analysis of each lane and flow direction, a highly refined evaluation of traffic conditions is achieved, which helps to more accurately identify traffic bottlenecks and potential problem areas, and provide accurate data support for subsequent signal optimization.

[0021] Obtain the flow information of each lane. Since traffic flow and patterns change over time (such as morning and evening rush hours, holidays, etc.), this method can dynamically evaluate the effectiveness of the signal control scheme by obtaining lane flow information in real time or regularly. Determining the allowable value of the flow flow in combination with the lane capacity helps to find bottlenecks and conflict points in the overall traffic flow, thereby formulating a more comprehensive optimization strategy. Determine the allowable value of the flow flow on different paths of the intersection based on the allowable value of the flow flow; not only pay attention to the capacity of a single lane, but also expand the evaluation scope to different paths of the entire intersection through the analysis of the allowable value of the flow flow and the allowable value of the path flow.

[0022] The signal control scheme at the bottleneck point of the path is evaluated according to the path traffic flow allowable value, so as to evaluate the signal scheme at the key position of the path. The flow congestion state of the coordinated flow at the bottleneck point is determined. At this time, not only the key congestion node is determined, but also the congestion state of the actual flow direction is determined by the state of the node. The threshold is used to determine whether there is room for optimization of the signal control scheme. By refining the saturated flow and capacity analysis of each lane and flow direction, a highly refined evaluation of the traffic conditions is achieved, and traffic bottlenecks and potential problem areas are more accurately identified, providing accurate data support for subsequent signal optimization; by obtaining lane flow information in real time or regularly, the effect of the signal control scheme can be dynamically evaluated, which helps to adjust the signal timing in time to cope with changes in traffic flow; the evaluation scope is expanded to different paths of the entire intersection, which helps to find bottlenecks and conflict points in the overall traffic flow, so as to formulate a more comprehensive optimization strategy.

[0023] In other embodiments, when determining the lane saturation flow in this solution, it includes constructing a time interval. By constructing a specific time interval, the traffic data within the time period can be accurately collected and analyzed. Traffic flow and signal control strategies often change with various factors such as time, weather, special events, etc. The noise and uncertainty that may be caused by long-term span data are avoided. The intersection signal cycle data at the intersection corresponding to the time interval is obtained; the green-to-signal ratio of the lane in the signal cycle data is determined. By accurately calculating the green-to-signal ratio, the effectiveness of the current signal timing plan can be evaluated, and necessary adjustments can be made accordingly to maximize the effective use of green light time, reduce vehicle waiting time, and alleviate traffic congestion.

[0024] In other embodiments, the present solution also includes determining the initial saturated flow, and counting the initial saturated flow of each lane at each intersection, so that more detailed and comprehensive data can be obtained. This refined data collection method helps to more accurately reflect the actual traffic conditions and reduce analysis deviations caused by insufficient data or excessive errors. Unreasonable data in the initial saturated flow is filtered out by threshold judgment. Outliers caused by equipment failure, human error or extreme traffic conditions can be removed, thereby improving the overall quality and consistency of the data set. Taking into account that the traffic conditions at different intersections and lanes may be significantly different, this solution makes the analysis results more targeted and applicable by separately counting and filtering the initial saturated flow of each lane at each intersection.

[0025] In other embodiments, when determining the lane capacity in this solution, signal schemes for multiple intersections are obtained, and signal control strategies under different traffic environments and conditions are taken into account. This comprehensive analysis helps to discover the commonalities and differences between different intersections. The green-to-signal ratio of each lane is determined separately, and the impact of signal control on lane capacity is taken into account. By accurately calculating the green-to-signal ratio of each lane, the actual lane capacity under different signal control conditions can be more accurately reflected. This helps to avoid errors that may occur when making rough estimates based only on lane saturation flow. The lane capacity is obtained in combination with the lane saturation flow of the corresponding lane. Only two key parameters, signal control scheme and lane saturation flow, need to be obtained to calculate the lane capacity.

[0026] In other embodiments, when determining the allowable value of flow direction traffic in this solution, the lanes in the same direction are clustered and summed. By clustering the lanes in the same direction, the complexity of analyzing the capacity of each lane individually is reduced. The analysis objects after clustering are more concentrated. Determine the flow direction of each lane; the overall capacity of the flow direction can be more accurately reflected. This targeted analysis method reduces the error caused by the difference in flow direction between lanes and improves the accuracy of capacity assessment. Sum the lane capacities corresponding to several lanes with the same flow direction information. By identifying traffic bottlenecks and congestion points through the allowable value of flow direction traffic, the capacity of the actual path can be accurately reflected.

[0027] In other embodiments, when determining the path traffic flow allowable value in this solution, obtaining the information and location of all intersections in the path helps to fully understand the traffic conditions of each link on the path and provide comprehensive data support for optimizing the path traffic flow allowable value. A traffic ID is formed based on the intersection information and location; the refined analysis method can more accurately reflect the mutual influence and constraint relationship between the intersections on the path, thereby improving the accuracy of the traffic capacity assessment. An intersection model is established to determine the coordinated traffic capacity of each traffic ID. The traffic conditions at the intersection are dynamically changing, and the solution can update the intersection information and location data in real time or periodically to reflect these changes. Through the established intersection model, the coordinated traffic capacity of the traffic ID can be dynamically evaluated.

[0028] In other embodiments, the present solution also includes sorting each intersection according to the coordinated capacity, so that it can be intuitively seen which intersections have relatively low capacity and are potential bottlenecks on the path. Furthermore, by sorting and screening in combination with the green-to-signal ratio benchmark value, bottleneck intersections caused by improper signal control or unreasonable traffic organization can be more accurately identified. This precise positioning helps traffic managers concentrate resources to solve key problems and improve the overall capacity of the path. Intersections are sorted and filtered according to the green-to-signal ratio benchmark value. It is convenient to allocate limited traffic management resources more reasonably. The identification and resolution of bottleneck intersections not only helps to improve the capacity of the path, but also enhances the resilience of the entire transportation system. In the event of an emergency or a surge in traffic flow, bottleneck intersections are often the source of traffic congestion. By identifying and resolving these bottlenecks in advance, the occurrence and spread of traffic congestion can be reduced, and the stability and reliability of the transportation system can be improved.

[0029] In other embodiments, the present solution includes determining the flow speed of each flow direction at each entrance of the intersection. By accurately measuring the speed of different flow directions at each entrance, the solution can capture subtle traffic changes. This meticulous data collection method helps to more accurately identify which flow directions or time periods are congested, thereby improving the accuracy of congestion status determination. The travel time and average speed are determined based on the flow speed at different intersections. Real-time monitoring of flow speed means that the system can respond quickly to changes in traffic conditions. Once the speed of a certain flow direction drops significantly, the system can immediately identify and issue an early warning. By analyzing the flow speed at different intersections, traffic bottlenecks can be identified. For travelers, understanding real-time traffic congestion can help them plan more reasonable travel routes and avoid being stuck in congested sections.

[0030] In other embodiments, the present solution includes obtaining the flow flow allowance and flow congestion status of the corresponding flow direction, and can obtain traffic flow and congestion status data in real time, thereby realizing instant evaluation of the signal control scheme. The flow saturation is judged according to its ratio. Not only the static indicator of the flow flow allowance is considered, but also the dynamic factor of the flow congestion status is combined to comprehensively evaluate the signal control scheme from multiple dimensions. This multi-dimensional evaluation method helps to more comprehensively understand the effects and problems of the signal control scheme.

[0031] In other embodiments, the scheme includes obtaining historical data of bottleneck points, and analyzing the flow saturation through historical data to ensure the accuracy and reliability of the evaluation results. The flow saturation in the historical data is determined, and by calculating the percentage of oversaturation, the scheme quantifies the flow saturation, making the evaluation results more intuitive and easy to understand. This quantitative analysis helps traffic managers to more accurately identify problem areas and optimization needs. It is determined whether there is room for optimization based on the percentage of oversaturation in the flow saturation. It is not only suitable for busy traffic areas such as urban main roads, but also can update data more frequently and adjust thresholds to better deal with traffic congestion problems.

[0032] The solution pays special attention to the historical data of bottleneck points, which are key areas in the traffic network that are prone to congestion. By analyzing the historical data of these areas, potential problems and optimization space in the signal control solution can be accurately identified. The oversaturation percentage is an intuitive indicator that can clearly reflect the degree of congestion in a flow direction during a specific time period. When the percentage exceeds a certain threshold, it indicates that there is room for optimization and corresponding measures need to be taken to improve traffic conditions.

[0033] In another embodiment, the present invention discloses a multi-dimensional capacity calculation and signal scheme evaluation method based on vehicle passing data, comprising the following steps: First, the capacity calculation is performed. Determining the allowable value of the path traffic flow includes the following steps: first, calculating the saturated flow of each lane at all intersections in the path. Second, calculating the capacity of each lane at all intersections in the path. Third, calculating the capacity of the flow direction of all intersections in the path. Fourth, calculating the capacity of the path.

[0034] When calculating the saturated flow of each lane at all intersections in the path, first obtain the flow of each lane at each intersection and establish a time interval. Obtain the intersection signal cycle data of the intersection to which the lane belongs according to the time interval. When there are intersection signal cycle data with different start times within the time range, only the intersection signal cycle data with the earliest start time is retained.

[0035] Then determine the green-to-light ratio of the lane in the signal cycle data, and determine the ratio of the green light duration in the lane.

[0036] Determine the saturated flow of each lane at each intersection. Count all saturated flow sets, sort the elements of the set from small to large, take the 99th percentile value of the set to determine whether it is abnormal, and finally output the saturated flow of each lane.

[0037] Determine lane capacity. First, obtain the saturated flow of each lane, including selecting a signal scheme, and selecting the signal scheme with the largest number of individuals and the latest time in the signal scheme cycle.

[0038] The green-to-signal ratio of the lane is calculated based on the matching relationship among phase, flow direction and lane. The lane capacity is generated by combining the saturated flow and green-to-signal ratio of the lane.

[0039] Determine the allowable value of the flow flow. First, obtain the capacity of each lane and determine the flow direction information of each lane. Determine the import direction, cluster and sum the data of each lane based on the import direction, and determine which flow direction each lane belongs to. Sum the capacity of each lane in the same flow direction as the capacity of the flow direction. When the same lane has at least two flow directions, split the flow directions of the lane according to a certain ratio. Finally, determine the capacity of each flow direction separately.

[0040] Determine the allowed value of the path traffic flow. First, obtain the path information and establish the intersection model. According to the location and direction of the intersection, form a traffic ID, and judge the traffic capacity of each direction of the intersection according to the traffic ID. Determine the coordinated traffic capacity of each intersection. Sort the intersections according to the number of lanes corresponding to each direction, and determine the coordinated traffic capacity of each direction at each intersection. Establish the traffic capacity sequence of each intersection flow direction, and filter the traffic capacity sequence according to the standard value.

[0041] This scheme also includes evaluating the signal control scheme, including determining the flow congestion status, determining the flow directions to which the lanes in each direction of the actual intersection belong, and determining the flow speed of each flow direction respectively, and determining the congestion status of each flow direction based on the flow speed of each flow direction.

[0042] Then, the bottleneck point of the path is determined, and the signal control scheme of the bottleneck point of the path is evaluated. This includes obtaining the bottleneck intersection of the actual path and determining the coordinated flow direction corresponding to the bottleneck intersection. Then, the flow saturation of the coordinated flow direction is obtained, and the congestion state of the coordinated flow direction is judged according to the flow saturation.

[0043] Including evaluating the flow saturation. Obtain the flow saturation of several coordinated flow directions, and judge whether the flow saturation of several coordinated flow directions meets expectations according to the threshold. When the number of flow saturation of several coordinated flow directions that reaches the threshold meets the requirements, it is judged that the flow saturation of the bottleneck intersection meets expectations.

[0044] In another specific embodiment, the scheme includes the following steps to determine the path traffic flow allowance. The path traffic flow allowance calculation follows the following steps: 1. Calculate the saturated flow of each lane at all intersections; 2. Calculate the capacity of each lane at all intersections; 3. Calculate the capacity of the flow direction of each intersection; 4. Calculate the capacity of a certain path.

[0045] Calculate lane saturation flow. This step is calculated every 7 days. Because lane saturation flow is essentially a long-term fixed attribute, it is mainly affected by factors such as the road's own carrying capacity, intersection signal control scheme, and local actual traffic flow, so it does not need to be updated frequently.

[0046] Step 1: Obtain the 5-minute traffic flow of n lanes at each lane j of each intersection i for 7 days

[0047] Step 2: Lane-level 5-minute traffic flow of each lane j at each intersection i According to its start-time and end-time, a time interval [start-time, end-time) is constructed, and m batches of intersection signal cycle data of the intersection i belonging to the lane within the corresponding range are obtained according to the time interval. Furthermore, if it is found that there are intersection signal cycle data with different start times within the time range, only the intersection signal cycle data with the earliest start time is retained.

[0048] Step 3: Calculate the signal cycle data of lane j Green letter ratio in: green j，mRepresents the green light duration of lane j in the m batches of intersection signal cycle data, cycletime i，m Represents the cycle length of intersection i in m batches of intersection signal cycle data.

[0049] Step 4: Calculate the n-hour initial saturated flow of lane j at intersection i:

[0050] Step 5: For each lane j of each intersection i, count all Collection Arrange the elements of the set from small to large and take the 99th percentile value of the set:

[0051] Step 6: Judgement Is it abnormal? If The result is considered unreasonable and corrected to flow. Flow is the default value of flow. If lane i is a straight or right turn lane, flow is 1440, and if it is a left turn, it is 1200.

[0052] Step 7: Output the saturated flow of each lane.

[0053] Calculate lane capacity. Calculate every 5 minutes and determine start-time and end-time. end-time is the current time, and start-time is end-time minus 10 minutes.

[0054] Step 1: Get the saturated flow of each lane.

[0055] Step 2: Get the signal scheme (start-time and end-time range) of each intersection i within a 10-minute range. You will get multiple signal schemes. Group them according to the size of the signal scheme cycle, determine the number of individuals in each group, retain the group with the largest number, and select the signal scheme with the latest time in the group as the signal scheme for calculation.

[0056] Step 3: Calculate the green light ratio of the lane based on the phase-flow direction-lane matching relationship. If the lane exists in multiple phases, add up the green light times. If it is a right-turn lane, the green light ratio is directly 1.

[0057] Step 4: Lane 5-minute traffic capacity = lane saturation flow * green-to-signal ratio.

[0058] Step 8: Output the capacity of each lane.

[0059] Calculate the allowable flow rate in the flow direction every 5 minutes.

[0060] Step 1: Obtain the capacity of each lane and the flow information of each lane.

[0061] Step 2: Cluster and sum the lane data based on the import direction. Determine which direction the lanes in each class belong to (left, straight, right), and take the sum of the capacity values ​​of the lanes in the same direction as the 5-minute capacity of the direction.

[0062] Note: The left direct current direction should be split into left turn and straight ahead, with a ratio of 1 left turn and 3 straight ahead. The right direct current direction should be split into right turn and straight ahead, with a ratio of 3 right turns and 1 straight ahead.

[0063] Step 3: Output the 5-minute flow rate allowed.

[0064] Calculate the allowed flow rate of the path every 5 minutes.

[0065] Step 1: Get the path information and distinguish the two directions of the path according to upEntranceDirections and downEntranceDirections. The intersections contains the intersection information of the path, and the intersection position corresponds to the direction position in upEntranceDirections or downEntranceDirections. The two together form an intersection-id+entrance-id entity.

[0066] Step 2: Further, based on the intersection model in redis, obtain intersection-id+direction-id based on intersection-id+entrance-id.

[0067] Step 3: Take the upEntranceDirections direction as an example. Each pair of adjacent individuals forms a group, and determine whether the direction-id of the two individuals in each group has changed: 1) For the group that has not changed, the through-flow capacity of the first intersection is the coordinated direction capacity of the intersection; 2) For the groups that have changed, if it is 1 to 4, 2 to 1, 3 to 2, 4 to 3, then the capacity of the left-turn flow at the first intersection is the capacity of the coordinated direction of the intersection; if it is 1 to 2, 2 to 3, 3 to 4, 4 to 1, then the capacity of the right-turn flow at the first intersection is the capacity of the coordinated direction of the intersection.

[0068] Step 4: Following the steps in step 3, the allowed values ​​of coordinated flow rate for all intersections except the last one can be obtained.

[0069] Step 5: Sort each intersection according to the number of lanes corresponding to the flow direction of each intersection. If there are multiple intersections with the same lanes, further sort them according to the allowed value of the flow direction traffic flow. The intersection with fewer lanes and smaller traffic capacity will be ranked first.

[0070] Step 6: Find the first intersection in the sequence, and compare its coordinated flow direction traffic allowable value with the benchmark values ​​of 1200*green signal ratio for left turn, 1440*green signal ratio for straight line, and 1200 for right turn. If the difference with the benchmark value is greater than 25%, select the next intersection for comparison until an intersection with a difference less than 25% is found.

[0071] It includes the evaluation of signal control scheme, in which the flow congestion status is evaluated first, once every 5 minutes.

[0072] Step 1: Determine the flow direction of lanes in each direction at each intersection. Each lane at an entrance will be classified into one of the three flow directions: left, straight, and right. If it is a variable lane, such as left straight, it will be assigned to the left flow direction or the straight flow direction.

[0073] Step 2: Calculate the flow speed of each flow direction at a certain entrance of a certain intersection. Taking the straight flow direction as an example, obtain the current 5-minute vehicle passing data S1 belonging to the straight flow lane, the vehicle passing data S1 includes the license plate number and the passing time, obtain the current 30-minute vehicle passing data S2 of the upstream intersection of the intersection, and obtain the length of the section between the two intersections. Take the intersection of S1 and S2 with the same license plate number, calculate the time difference of the same license plate number to obtain the travel time of each vehicle, the section length and travel time to obtain the travel speed of each vehicle, and average the speed of each vehicle to obtain the average speed of the flow direction.

[0074] Step 3: Determine the congestion status of each flow direction. If the speed of a certain flow direction is less than 10 kilometers per hour, it is considered to be in a congested state, otherwise it is unobstructed.

[0075] Evaluate the signal control scheme at the bottleneck point of the path. The capacity of the bottleneck intersection in the entire path has been calculated as the capacity of the path. In other words, the overall capacity of the path is limited by the capacity of the bottleneck intersection, and the capacity is strongly related to the setting of the signal control scheme. Then we can compare the real-time 5-minute flow with the capacity to evaluate, but because of extreme congestion, vehicles travel slower, which will lead to a smaller overall flow, and thus cause misjudgment of the evaluation. Therefore, it is necessary to introduce the flow congestion state to assist the evaluation.

[0076] The flow congestion status is evaluated every 5 minutes.

[0077] Step 1: Obtain the bottleneck intersection of the path and its coordinated flow direction. Further, obtain the 5-minute traffic capacity, 5-minute flow of the coordinated flow direction, and the congestion status of the flow direction, where the 5-minute flow of the coordinated flow direction is the sum of the 5-minute flow of each lane in the flow direction.

[0078] Step 2: Determine the saturation of the flow direction. If the coordinated flow direction (5-minute flow rate*12) / traffic capacity>1, the flow direction is considered to be oversaturated; if the coordinated flow direction is in a congested state, the flow direction is also considered to be oversaturated.

[0079] The path bottleneck signal control scheme is evaluated once every day.

[0080] Step 1: Get the 14-day historical data of the bottleneck intersection.

[0081] Step 2: If more than 50% of the 84 data in a 30-minute time period from 8:00 to 8:30 show that the traffic flow is oversaturated, it is considered that there is room for optimization of the signal control scheme for this intersection during this time period, and the green-signal ratio of the phase in which the traffic flow is located should be appropriately increased. Otherwise, it is considered that the traffic flow saturation of the bottleneck intersection meets the demand expectations.

[0082] These modifications or improvements made on the basis of the present invention without departing from the spirit of the present invention all fall within the scope of protection required by the present invention.

Claims

1. A signal control evaluation method based on traffic capacity, characterized in that: include: Determine the lane saturation flow of each lane, and determine the corresponding lane capacity according to the lane saturation flow; Obtain the flow direction information of each lane, determine the allowable flow rate of the flow direction in combination with the lane capacity, and determine the allowable flow rates of different paths at the intersection based on the allowable flow rate of the flow direction; The signal control scheme at the bottleneck point of the path is evaluated according to the allowable value of the path traffic flow, the flow congestion status of the coordinated flow at the bottleneck point is determined, and the threshold is used to determine whether there is room for optimization of the signal control scheme.

2. The signal control evaluation method based on traffic capacity according to claim 1 is characterized in that: When determining the lane saturation flow, construct a time interval and obtain the intersection signal cycle data at the intersection corresponding to the time interval; determine the green-to-signal ratio of the lane in the signal cycle data.

3. The signal control evaluation method based on traffic capacity according to claim 2 is characterized in that: When determining the lane saturation flow, it also includes determining the initial saturation flow, counting the initial saturation flow of each lane at each intersection, and filtering out unreasonable data in the initial saturation flow through threshold judgment.

4. A signal control evaluation method based on traffic capacity according to claim 1, 2 or 3, characterized in that: When determining lane capacity, obtain signal schemes for multiple intersections, determine the green-to-signal ratio of each lane respectively, and obtain lane capacity in combination with the lane saturation flow of the corresponding lane.

5. The signal control evaluation method based on traffic capacity according to claim 4 is characterized in that: When determining the allowable value of flow rate, lanes in the same direction are clustered and summed to determine the flow direction of each lane; the lane capacities corresponding to several lanes with the same flow direction information are summed.

6. A signal control evaluation method based on traffic capacity according to claim 5, characterized in that: When determining the allowed value of the path traffic flow, obtain all the intersection information and positions in the path, form a traffic ID based on the intersection information and positions; establish an intersection model to determine the coordinated traffic capacity of each traffic ID.

7. A signal control evaluation method based on traffic capacity according to claim 4, characterized in that: Determining the allowable value of the path traffic flow also includes sorting the intersections according to the coordinated traffic capacity, and sorting the intersections according to the green-to-signal ratio benchmark value to select the intersections with bottleneck points.

8. A signal control evaluation method based on traffic capacity according to claim 1, 2 or 3, characterized in that: Determining the flow congestion state includes determining the flow speed of each flow direction at each entrance of the intersection, and determining the travel time and average speed based on the flow speeds at different intersections.

9. The signal control evaluation method based on traffic capacity according to claim 8, characterized in that: When evaluating the signal control scheme, it includes obtaining the allowed value of the flow flow and the flow congestion status of the corresponding flow direction, and judging the flow saturation status according to the ratio thereof.

10. A signal control evaluation method based on traffic capacity according to claim 7, characterized in that: When judging the signal control scheme through the threshold, it includes obtaining the historical data of the bottleneck point, determining the flow saturation situation in the historical data, and judging whether there is room for optimization according to the percentage of oversaturation in the flow saturation situation.

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