Signal control time period division method considering frequent time period of extreme scene

Abstract

The invention discloses a signal control period division method considering an extreme scene frequent period, and relates to the technical field of signal control period division, and the method comprises the steps: S1, collecting the historical traffic flow data of an intersection; s2, adopting a fisher optimal segmentation method; s3, correcting the basic signal control time period by using the total flow of the intersection, and solving the problem that the morning and evening peak division time period is too long in the division result of the fisher optimal division method; s4, on the basis of historical traffic flow data, frequent time periods of typical problems of exit lane overflow, queuing imbalance and green light empty-discharge extreme scenes in the three date states are identified; and S5, fusing the extreme scene typical problem frequent occurrence time period and the correction signal control time period. By analyzing time-varying features of historical traffic flow data and frequent features of typical problems, a signal control time period division method considering frequent time periods of extreme scenes is innovatively provided, and a plurality of signal control time periods are divided for three date states of workdays, non-workdays and holidays.

Description

Technical Field

[0001] The present invention relates to the technical field of signal control period division, and in particular to a signal control period division method taking into account periods where extreme scenarios often occur. Background Art

[0002] The rapid growth of the number of motor vehicles has made urban traffic congestion, especially traffic congestion at intersections, increasingly serious. With the development of communication technology and signal control technology in recent years, time-based signal control is expected to become an effective traffic control method to improve intersection efficiency and alleviate traffic congestion. The quality of the time division results is particularly important for the effect of time-based signal control.

[0003] At present, the signal control time division methods mostly use the intersection entrance level flow as a feature, and use the Fisher optimal segmentation method or other machine learning methods to divide the time periods. Some methods consider indicators such as the gathering wave speed and queue length at the entrance. These methods are applied to non-saturated intersections with reasonable phase sequence and green time scheme settings, and can obtain high-quality time division results. However, for intersections prone to extreme scenarios such as exit overflow, unbalanced queues, and empty entrances, the division features cannot identify these problems, resulting in the time division results being unable to reflect the frequent occurrence periods of typical problems in extreme scenarios. Therefore, this scheme proposes a signal control time division method that takes into account the frequent occurrence periods of extreme scenarios. Summary of the invention

[0004] The present invention provides a method for dividing signal control time periods taking into account the time periods during which extreme scenarios often occur, thereby facilitating solving the problems mentioned in the above-mentioned background technology.

[0005] The present application provides a method for dividing a signal control period considering a period during which extreme scenes often occur, and adopts the following technical scheme: A method for dividing a signal control period considering a period during which extreme scenes often occur, comprising the following steps: S1. Collect historical traffic flow data at intersections; Among them, historical traffic flow data covers three date states: working days, non-working days and holidays; S2. Fisher optimal segmentation method is used to divide the basic time periods of the three date states based on historical traffic flow data, and multiple basic signal control periods are defined for each date state; S3. Use the total flow of the intersection to correct the basic signal control period to solve the problem that the morning and evening peak division periods are too long in the division results of the Fisher optimal division method; S4. Based on historical traffic flow data, identify the frequent occurrence periods of typical problems such as exit overflow, queue imbalance, and green light empty under three date conditions; S5. Integrate the periods of frequent occurrence of typical problems in extreme scenarios and the corrected signal control periods as signal control periods that consider the identification of periods of frequent occurrence of extreme scenarios.

[0006] By adopting the above technical solution, the typical problem-prone periods at a deeper level within the basic time periods with similar traffic characteristics are identified, and the basic time period division results based on traffic are corrected, effectively improving the similarity of traffic flow characteristics within each time period.

[0007] Furthermore, the Fisher optimal segmentation method in S2 is specifically: Among them, the phase-level flow with a granularity of 5 minutes is used as the time period division feature; Features Samples are arranged in order , for the Group Sample , the sample differences within the group are expressed using variance as: ; ; In the formula, For the The within-group variance of the group sample, For the The feature vector of the samples, For the The mean of the group sample; use Indicates that The ordered samples are divided into A method of group; The loss function is defined as: , The classification method that minimizes the loss function is the optimal segmentation, denoted as .

[0008] Furthermore, for the optimal segmentation , the category on the far right The diameter is , the loss function of the optimal segmentation is: , in Indicates the front The samples are divided into The optimal segmentation of the group is determined by recursively applying this formula to determine the optimal segmentation of each category. Then The samples are divided into a group. The loss function is: ; In getting different number of samples Divide into different groups After the loss function, from the number of groups Start increasing. If the loss function decreases too little when adding a group number, the number of groups will no longer increase, and the grouping result corresponding to the current number of groups will be output as the final time period division result.

[0009] By adopting the above technical solution and the Fisher optimal segmentation method, the three date states are divided into basic time periods according to historical traffic flow data, and multiple basic signal control time periods are defined for each date state.

[0010] Furthermore, the use of the total flow of the intersection to correct the basic signal control period in S3 specifically includes the following steps: a. Use traffic flow data to calculate the total flow of intersections in each time unit ; b. For a certain basic signal control period , extract the total flow of the intersection at the start time unit of its time period , the maximum flow in the period and its corresponding time unit ; c. From time unit Start traversing backward through the basic signal control period Each time unit Traffic ,like Decrease to the start time unit flow , then the time unit As the basic signal control period Early break time unit; d. If it is until the basic signal control period The early break time unit is still not found at the end , then the period will not be cut off early; e. Query the early-break time unit of each basic signal control period, and correct each basic signal control period based on the early-break time unit; f. If the revised basic signal control period is less than 15 minutes, it will be merged into the adjacent period.

[0011] Furthermore, the total intersection flow of each time unit is a phase-level flow with a granularity of 5 minutes.

[0012] By adopting the above technical solution, the basic time period division results based on traffic flow are corrected, which effectively improves the similarity of traffic flow characteristics in each time period.

[0013] Furthermore, when identifying the frequent occurrence periods of typical problems of the three date conditions, such as exit overflow, queue imbalance, and green light empty release, the following are the most common problems: If the time occupancy rate of the exit lane is higher than 60% and the average vehicle speed is lower than 8 km / h, it is identified as exit lane overflow; The maximum and minimum queue lengths of each entrance are and ,like and , identified as queue imbalance; If the green light utilization rate of the entrance lane is less than 10%, it is identified as low green light utilization rate of the entrance lane; Count typical problems in each extreme scenario In each time unit Number of occurrences ; like , considered a typical problem In time unit Internal hair, remember ,otherwise ; Iterate through time units ,like and , then the time unit sequence Record as a typical problem A common period of , count the time periods when each typical problem frequently occurs; If the frequent occurrence periods of multiple typical problems overlap, only the overlapping frequent occurrence period of the most important problem will be retained according to the importance of the problem, and the overlapping frequent occurrence periods of other problems will be deleted. At this time, the importance of the problem is: exit overflow > queue imbalance > green light empty; Count the time unit sequences and corresponding problem types of each typical problem-frequently occurring period.

[0014] Furthermore, in S5, integrating the typical problem frequent occurrence period and the correction signal control period specifically includes the following steps: The starting time unit of each period in the correction signal control period is ; The start and end time units of each period in the period of typical problem occurrence are ; Jordi Correction signal control period start time unit lie in During the period when typical problems often occur, that is, , then delete ; Arrange all the correction signal control period start time units in sequence and the start and end time units of each period in the period when typical problems often occur , and merge forwards into periods shorter than 15 minutes; Jordi Correction signal control period start time unit Both sides are typical problem-prone periods, that is, there are Make and , and If the performance of the typical problems during the period of frequent occurrence is the same, it is considered For invalid partition points, delete ; Control the start time unit of the period according to the remaining correction signal and the start and end time units of each period in the period when typical problems often occur , output the time period division result.

[0015] The present invention has the following beneficial effects: 1. By analyzing the time-varying characteristics of historical traffic flow data and the recurring characteristics of typical problems, the present invention innovatively proposes a signal control period division method that takes into account the periods during which extreme scenarios frequently occur, and divides the three date states of working days, non-working days and holidays into multiple signal control periods.

[0016] 2. This method of dividing signal control periods into periods where extreme scenarios frequently occur combines traffic flow indicators such as green light utilization rate, time occupancy rate, queue length, and vehicle speed when dividing signal control periods, identifies periods where deeper typical problems frequently occur within basic periods with similar traffic characteristics, and corrects the results of basic period division based on traffic flow, effectively improving the similarity of traffic flow characteristics within each period, which is more conducive to designing a background plan for signal control based on the results of period division. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the process of the present invention; Figure 2 This is the channelization diagram of the intersection of G106 National Highway and Fanghua Road; Figure 3 This is a schematic diagram of the basic signal control period division result of Fisher's optimal segmentation method. Different broken lines represent the total lane flow at different phases of the intersection, and the dotted line represents the time period dividing point. Figure 4 This is a schematic diagram of the signal control time period division result using the total flow of the intersection. Different broken lines represent the total flow of lanes at different phases of the intersection, and the dotted line represents the time period demarcation point. Figure 5This is a schematic diagram of the signal control period division results considering the period when extreme scenarios often occur. Different broken lines represent the total lane flow at different phases of the intersection, and the dotted lines represent the time period dividing points. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] Example 1 Reference Figure 1 , a signal control period division method considering the period during which extreme scenes often occur, comprising the following steps: S1. Collect historical traffic flow data at intersections; Among them, historical traffic flow data covers three date states: working days, non-working days and holidays; S2. Fisher optimal segmentation method is used to divide the basic time periods of the three date states based on historical traffic flow data, and multiple basic signal control periods are defined for each date state; S3. Use the total flow of the intersection to correct the basic signal control period to solve the problem that the morning and evening peak division periods are too long in the division results of the Fisher optimal division method; S4. Based on historical traffic flow data, identify the frequent occurrence periods of typical problems such as exit overflow, queue imbalance, and green light empty under three date conditions; S5. Integrate the periods of frequent occurrence of typical problems in extreme scenarios and the corrected signal control periods as signal control periods that consider the identification of periods of frequent occurrence of extreme scenarios.

[0020] The typical time periods with deeper problems within the basic time periods with similar traffic characteristics were identified, and the results of the basic time period division based on traffic were revised, effectively improving the similarity of traffic flow characteristics within each time period.

[0021] The specific Fisher optimal segmentation method in S2 is: Among them, the phase-level flow with a granularity of 5 minutes is used as the time period division feature; Features Samples are arranged in order , for the Group Sample , the sample differences within the group are expressed using variance as: ; ; In the formula, For the The within-group variance of the group sample, For the The feature vector of the samples, For the The mean of the group sample; use Indicates that The ordered samples are divided into A method of group; The loss function is defined as: , The classification method that minimizes the loss function is the optimal segmentation, denoted as .

[0022] For the optimal segmentation , the category on the far right The diameter is , the loss function of the optimal segmentation is: , in Indicates the front The samples are divided into The optimal segmentation of the group is determined by recursively applying this formula to determine the optimal segmentation of each category. Then The samples are divided into a group. The loss function is: ; In getting different number of samples Divide into different groups After the loss function, from the number of groups Start increasing. If the loss function decreases too little when adding a group number, the number of groups will no longer increase, and the grouping result corresponding to the current number of groups will be output as the final time period division result.

[0023] The Fisher optimal segmentation method is used to divide the three date states into basic time periods based on historical traffic flow data, and multiple basic signal control time periods are defined for each date state.

[0024] The use of total intersection flow in S3 to modify the basic signal control period specifically includes the following steps: a. Use traffic flow data to calculate the total flow of intersections in each time unit ; b. For a certain basic signal control period , extract the total flow of the intersection at the start time unit of its time period , the maximum flow in the period and its corresponding time unit ; c. From time unit Start traversing backward through the basic signal control period Each time unit Traffic ,like Decrease to the start time unit flow , then the time unit As the basic signal control period Early break time unit; d. If it is until the basic signal control period The early break time unit is still not found at the end , then the period will not be cut off early; e. Query the early-break time unit of each basic signal control period, and correct each basic signal control period based on the early-break time unit; f. If the revised basic signal control period is less than 15 minutes, it will be merged into the adjacent period.

[0025] The total intersection flow of each time unit is the phase-level flow with a granularity of 5 minutes.

[0026] The correction is made based on the basic time period division results of traffic flow, which effectively improves the similarity of traffic flow characteristics within each time period.

[0027] When identifying the frequent occurrence periods of typical problems of exit overflow, queue imbalance, and green light empty release under three date conditions: If the time occupancy rate of the exit lane is higher than 60% and the average vehicle speed is lower than 8 km / h, it is identified as exit lane overflow; The maximum and minimum queue lengths of each entrance are and ,like and , identified as queue imbalance; If the green light utilization rate of the entrance lane is less than 10%, it is identified as low green light utilization rate of the entrance lane; Count typical problems in each extreme scenario In each time unit Number of occurrences ; like , considered a typical problem In time unit Internal hair, remember ,otherwise ; Iterate through time units ,like and , then the time unit sequence Record as a typical problem A common period of , count the time periods when each typical problem frequently occurs; If the frequent occurrence periods of multiple typical problems overlap, only the overlapping frequent occurrence period of the most important problem will be retained according to the importance of the problem, and the overlapping frequent occurrence periods of other problems will be deleted. At this time, the importance of the problem is: exit overflow > queue imbalance > green light empty; Count the time unit sequences and corresponding problem types of each typical problem-frequently occurring period.

[0028] In S5, integrating the typical problem frequent occurrence period and the correction signal control period specifically includes the following steps: The starting time unit of each period in the correction signal control period is ; The start and end time units of each period in the period of typical problem occurrence are ; Jordi Correction signal control period start time unit lie in During the period when typical problems often occur, that is, , then delete ; Arrange all the correction signal control period start time units in sequence and the start and end time units of each period in the period when typical problems often occur , and merge forwards into periods shorter than 15 minutes; Jordi Correction signal control period start time unit Both sides are typical problem-prone periods, that is, there are Make and , and If the performance of the typical problems during the period of frequent occurrence is the same, it is considered For invalid partition points, delete ; Control the start time unit of the period according to the remaining correction signal and the start and end time units of each period in the period when typical problems often occur , output the time period division result.

[0029] Example 2 Reference Figure 1-Figure 5 , a signal control period division method considering the period during which extreme scenes often occur, comprising the following steps: S1. Collect historical traffic flow data at intersections, covering multiple days of data on three date states: working days, non-working days, and holidays; In this example, the G106 National Highway-Fanghua Road in Baiyun District, Guangzhou is taken as an example, and the historical traffic flow data with a time granularity of 5 minutes is collected through the radar perception equipment.

[0030] The intersection channelization of G106 National Highway and Fanghua Road, and the phase signal of each lane signal Figure 2 shown.

[0031] S2. Fisher optimal segmentation method is used to divide the basic time periods of the three date states based on historical traffic flow data, and multiple basic signal control periods are defined for each date state; In this example, Fisher optimal segmentation method is used to delineate six application periods for weekdays based on the historical traffic flow data collected in S1; They are: 07:20-11:10, 11:10-12:20, 12:20-17:35, 17:35-20:35, 20:35-22:15 and 22:15-07:20. Figure 3 As shown, different broken lines represent the total lane flow at different phases of the intersection, and the dotted lines represent the time period dividing points.

[0032] Among them, 07:20-11:10 and 17:35-20:35 are the morning peak and evening peak respectively, but the end time of these two periods is too late.

[0033] S3. Use the total flow of the intersection to correct the basic signal control period to solve the problem that the morning and evening peak division periods are too long in the division results of the Fisher optimal division method; For the period of 07:20-11:10, the maximum flow rate occurs in the 08:55 time unit. From the 08:55 time unit, 10:20 is the time unit that decreases to the flow rate at 07:20, which is regarded as the early disconnection time unit; For the period from 10:20 to 12:20, the maximum flow occurs at the 10:20 time unit. No early disconnection time unit is found from the 10:20 time unit backward. For the period from 12:20 to 17:35, the maximum flow occurs in the 17:35 time unit. No early disconnection time unit is found from the 17:35 time unit backward. For the period from 17:35 to 20:35, the maximum flow rate occurs at the 18:50 time unit. From the 18:50 time unit, 19:20 is the time unit that decreases to the 17:35 flow rate, which is regarded as the early disconnection time unit. For the period from 19:20 to 22:15, the maximum flow occurs at the 19:20 time unit. No early disconnection time unit is found from the 19:20 time unit backward. For the period from 22:15 to 07:20, the maximum flow occurs at the 07:20 time unit. No early disconnection time unit is found from the 07:20 time unit backward. The revised six application periods on working days are: 07:20-10:20, 10:20-12:20, 12:20-17:35, 17:35-19:20, 19:20-22:15 and 22:15-07:20. Figure 4 As shown, different broken lines represent the total lane flow at different phases of the intersection, and the dotted lines represent the time period dividing points.

[0034] Among them, 07:20-10:20 and 17:35-18:50 are the morning peak and evening peak respectively. Compared with the morning and evening peak obtained by S2, the time period lengths are shortened by 50 minutes and 75 minutes respectively.

[0035] S4. Based on historical traffic flow data, identify the time periods when typical problems such as exit overflow, queue imbalance, and green light vacancy often occur under three date conditions; The queue imbalance and empty inlet channel problems were not identified in each time unit. The number of occurrences of outlet channel overflow in each time unit is shown in the following table: Time unit 08:00 08:05 08:20 08:25 08:55 09:00 09:05 09:10 17:40 Occurrence 1 3 11 16 12 15 12 13 5 Time unit 17:50 18:10 18:15 18:20 18:25 18:30 18:35 18:40 18:45 Occurrence 16 12 11 16 12 15 12 13 9 According to the statistics in the table above, the occurrence frequencies of the time units 08:00, 08:05, 17:40, and 18:45 are too low, and they are the time units where the exit channel overflow is not frequent. The rest are the time units where the exit channel overflow is frequent. The time periods of 08:20-08:25 and 17:50 are too short, while 08:55-09:10 and 18:10-18:40 are the time periods when exit channel overflow often occurs; S5. Integrate the period during which typical problems in extreme scenarios often occur and the period during which the signal is corrected, as the signal control period during which the extreme scenario often occurs; The start time units of each time period in the correction signal control period are {07:20, 10:20, 12:20, 17:35,19:20, 22:15}, and the start and end time units of each time period in the typical problem frequent period are {08:55, 09:10, 18:10, 18:40}; 07:20, 10:20, 12:20, 17:35, 19:20, 22:15 are not in the typical problem-prone time periods and will not be deleted; The start time units of each time period in the correction signal control period and the start and end time units of each time period in the typical problem frequent period are arranged in sequence to obtain: {07:20, 08:55, 09:10, 10:20, 12:20, 17:35, 18:10,18:40, 19:20, 22:15}. There is no too short time period and no merging is performed. The fusion results include 10 time periods, namely 07:20-08:55, 08:55-09:10 (exit channel overflow), 09:10-10:20, 10:20-12:20, 12:20-17:35, 17:35-18:10, 18:10-18:40 (exit channel overflow), 18:40-19:20, 19:20-22:15, 22:15-07:20, e.g. Figure 5 As shown, different broken lines represent the total lane flow at different phases of the intersection, and the dotted lines represent the time period dividing points.

[0036] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0037] The above are only preferred embodiments of the present invention. It should be pointed out that, for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as within the scope of protection of the present invention.

Claims

1. A signal control period division method considering the period during which extreme scenes often occur, characterized in that: The following steps are involved: S1. Collect historical traffic flow data at intersections; Among them, historical traffic flow data covers three date states: working days, non-working days and holidays; S2. Fisher optimal segmentation method is used to divide the basic time periods of the three date states based on historical traffic flow data, and multiple basic signal control periods are defined for each date state; S3. Use the total flow of the intersection to correct the basic signal control period to solve the problem that the morning and evening peak division periods are too long in the division results of the Fisher optimal division method; S4. Based on historical traffic flow data, identify the frequent occurrence periods of typical problems such as exit overflow, queue imbalance, and green light empty under three date conditions; S5. Integrate the periods of frequent occurrence of typical problems in extreme scenarios and the corrected signal control periods as signal control periods that consider the identification of periods of frequent occurrence of extreme scenarios.

2. The signal control period division method considering the period during which extreme scenes often occur according to claim 1 is characterized in that: The Fisher optimal segmentation method in S2 is specifically: Among them, the phase-level flow with a granularity of 5 minutes is used as the time period division feature; Features Samples are arranged in order , for the Group Sample , the sample differences within the group are expressed using variance as: ； ； In the formula, For the The within-group variance of the group sample, For the The feature vector of the samples, For the The mean of the group sample; use Indicates that The ordered samples are divided into A method of group; The loss function is defined as: ， The classification method that minimizes the loss function is the optimal segmentation, denoted as .

3. The signal control period division method considering the period during which extreme scenes often occur according to claim 2 is characterized in that: For the optimal segmentation , the category on the far right The diameter is , the loss function of the optimal segmentation is: ， in Indicates the front The samples are divided into The optimal segmentation of the group is determined by recursively applying this formula to determine the optimal segmentation of each category. Then The samples are divided into a group. The loss function is: ; In getting different number of samples Divide into different groups After the loss function, from the number of groups Start increasing. If the loss function decreases too little when adding a group number, the number of groups will no longer increase, and the grouping result corresponding to the current number of groups will be output as the final time period division result.

4. The signal control period division method considering the period during which extreme scenes often occur according to claim 3 is characterized in that: The use of the total flow of the intersection to correct the basic signal control period in S3 specifically includes the following steps: a. Use traffic flow data to calculate the total flow of intersections in each time unit ; b. For a certain basic signal control period , extract the total flow of the intersection at the start time unit of its time period , the maximum flow in the period and its corresponding time unit ; c. From time unit Start traversing backward through the basic signal control period Each time unit Traffic ,like Decrease to the start time unit flow , then the time unit As the basic signal control period Early break time unit; d. If it is until the basic signal control period The early break time unit is still not found at the end , then the period will not be cut off early; e. Query the early-break time unit of each basic signal control period, and correct each basic signal control period based on the early-break time unit; f. If the revised basic signal control period is less than 15 minutes, it will be merged into the adjacent period.

5. The signal control period division method considering the period during which extreme scenes often occur according to claim 4 is characterized in that: The total intersection flow of each time unit is the phase-level flow with a granularity of 5 minutes.

6. The signal control period division method considering the frequent occurrence period of extreme scenes according to claim 5 is characterized in that: In S4, when identifying the frequent occurrence periods of typical problems of the three date conditions, such as the exit channel overflow, the queue imbalance, and the green light empty release extreme scenario: If the time occupancy rate of the exit lane is higher than 60% and the average vehicle speed is lower than 8 km / h, it is identified as exit lane overflow; The maximum and minimum queue lengths of each entrance are and ,like and , identified as queue imbalance; If the green light utilization rate of the entrance lane is less than 10%, it is identified as low green light utilization rate of the entrance lane; Count typical problems in each extreme scenario In each time unit Number of occurrences ; like , considered a typical problem In time unit Internal hair, remember ,otherwise ; Iterate through time units ,like and , then the time unit sequence Record as a typical problem A common period of , count the time periods when each typical problem frequently occurs; If the frequent occurrence periods of multiple typical problems overlap, only the overlapping frequent occurrence period of the most important problem will be retained according to the importance of the problem, and the overlapping frequent occurrence periods of other problems will be deleted. At this time, the importance of the problem is: exit overflow > queue imbalance > green light empty; Count the time unit sequences and corresponding problem types of each typical problem-frequently occurring period.

7. The signal control period division method considering the frequent occurrence period of extreme scenes according to claim 6 is characterized in that: In S5, integrating the typical problem frequent occurrence period and the correction signal control period specifically includes the following steps: The starting time unit of each period in the correction signal control period is ; The start and end time units of each period in the period of typical problem occurrence are ; Jordi Correction signal control period start time unit lie in During the period when typical problems often occur, that is, , then delete ; Arrange all the correction signal control period start time units in sequence and the start and end time units of each period in the period when typical problems often occur , and merge forwards into periods shorter than 15 minutes; Jordi Correction signal control period start time unit Both sides are typical problem-prone periods, that is, there are Make and , and If the performance of the typical problems during the period of frequent occurrence is the same, it is considered For invalid partition points, delete ; Control the start time unit of the period according to the remaining correction signal and the start and end time units of each period in the period when typical problems often occur , output the time period division result.

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