A traffic scene recognition and analysis method based on a large traffic model

Abstract

The present application discloses a traffic scene recognition and analysis method based on a large traffic model, which relates to the field of traffic control technology. The method obtains the operating parameters and traffic signal control parameters of a traffic intersection within a first time period; the first time period includes at least one time period; based on the vehicle flow in the operating parameters, the time period is divided into a first time period and a second time period; based on the operating parameters of multiple entrance sections and multiple exit sections included in the traffic intersection within the first time period, the congestion type and congestion period of the traffic intersection within the first time period are determined; the second time period is divided into multiple sub-time periods, and based on the operating parameters and traffic signal control parameters of at least one target turn of the traffic intersection in each sub-time period, the problem type and problem period of the traffic intersection within the second time period are determined, thereby solving the problem in the prior art that the corresponding problem intersection type under various scenarios cannot be given, thereby reducing the workload of manual analysis.

Description

Technical Field

[0001] The present application relates to the field of traffic control technology, and in particular to a traffic scene recognition and analysis method based on a large traffic model. Background Art

[0002] With the rapid development of urbanization, cities are growing in size, and the number of signal-controlled intersections is also increasing year by year. When optimizing urban traffic signal control, a large number of professional traffic engineers are needed to analyze and evaluate the operating status of various urban intersections, identify problems in the operation of intersections, and conduct optimization work to alleviate urban traffic problems and ensure smooth traffic operation. In addition, investment in intelligent transportation has increased year by year, and various detection equipment on the road has become increasingly abundant, generating a large amount of traffic data that is not effectively utilized. How to effectively utilize massive traffic data, establish a scientific and reasonable intersection problem identification method for urban intersections, automatically discover problems at intersections, and reduce the workload of traffic engineers is a key issue facing urban traffic management.

[0003] Existing traffic scene recognition and analysis methods based on large-scale traffic models use data from electronic police vehicles and intersection detectors to calculate indicators such as queue length, saturation, green light loss time, single-lane flow, travel time, travel time ratio, and delays. These indicators are then used to identify congestion, imbalance, and empty traffic at intersections, and determine the corresponding cause of the problem intersection, providing a scientific basis for the work of relevant traffic management departments. However, this traffic scene recognition and analysis method based on large-scale traffic models cannot determine the corresponding problem intersection type in various scenarios.

[0004] Therefore, there is an urgent need for a traffic scene recognition and analysis method based on a large traffic model to solve the problem in the existing technology that the corresponding problem intersection types in various scenarios cannot be given, thereby reducing the workload of manual analysis and improving work efficiency. Summary of the Invention

[0005] In an exemplary embodiment of the present application, a traffic scene recognition and analysis method based on a large traffic model is provided to solve the problem in the prior art that the corresponding problem intersection types in various scenarios cannot be given, thereby reducing the workload of manual analysis and improving work efficiency.

[0006] According to a first aspect of an exemplary embodiment, a traffic scene recognition and analysis method based on a large traffic model is provided, comprising:

[0007] Acquiring operating parameters and traffic signal control parameters of a traffic intersection within a first time period, wherein the operating parameters of the traffic intersection are determined based on traffic data of the traffic intersection; the first time period includes at least one time period;

[0008] Based on the traffic volume in the operating parameter, the time period is divided into a first time period and a second time period, wherein the traffic volume in the first time period is greater than the traffic volume in the second time period;

[0009] Determining a congestion type and a congestion period of the traffic intersection within the first time period based on operating parameters of a plurality of entrance road sections and a plurality of exit road sections included in the traffic intersection within the first time period;

[0010] The second time period is divided into a plurality of sub-time periods, and based on the operating parameters and traffic signal control parameters of at least one target turn at the traffic intersection in each sub-time period, the problem type and problem period of the traffic intersection in the second time period are determined.

[0011] In an embodiment of the present application, by obtaining the operating parameters and traffic signal control parameters of a traffic intersection within a first time period including at least one time period, and dividing the time period into a first time period and a second time period based on the traffic volume in the operating parameters, the division of peak scenarios and non-peak scenarios is achieved. The present application can determine the congestion type and congestion period of the traffic intersection within the first time period based on the operating parameters of multiple entrance sections and multiple exit sections included in the traffic intersection within the first time period; and by determining the problem type and problem period of the traffic intersection within the second time period based on the operating parameters and traffic signal control parameters of at least one target turn of the traffic intersection, thereby solving the problem in the prior art of being unable to provide corresponding problem intersection types under various scenarios, thereby reducing the workload of manual analysis and improving work efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0013] Figure 1 The following is a schematic diagram of an application scenario provided by an embodiment of the present application;

[0014] Figure 2 The following is a flowchart illustrating a method for identifying and analyzing traffic scenes based on a large traffic model provided in an embodiment of the present application.

[0015] Figure 3 The following is a flow chart showing a method for identifying and analyzing traffic scenes based on a large traffic model according to an embodiment of the present application.

[0016] Figure 4 A flowchart of a method for determining a congestion type and congestion period at a traffic intersection within a first time period provided in an embodiment of the present application;

[0017] Figure 5 A schematic diagram of a congested period of an import congested road section in a first time period provided in an embodiment of the present application;

[0018] Figure 6 A schematic diagram of a congested period after merging an import congested road section within a first time period provided in an embodiment of the present application;

[0019] Figure 7 A schematic diagram of a congested period after merging another import congested road section within a first time period provided in an embodiment of the present application;

[0020] Figure 8 A schematic diagram of the intersection of the driving directions of two congested entrance sections provided in an embodiment of the present application;

[0021] Figure 9 A schematic diagram of two congested entrance sections with opposite driving directions provided in an embodiment of the present application;

[0022] Figure 10 A flow chart of a method for determining whether a turning and multiple stopping type problem occurs at a traffic intersection within a second time period and the problem period provided in an embodiment of the present application;

[0023] Figure 11 A flowchart of another method for determining whether a turning and multiple stopping type problem occurs at a traffic intersection within a second time period and the problem period provided by an embodiment of the present application;

[0024] Figure 12 A flowchart of a method for determining the type of imbalance problem and the problem period occurring at a traffic intersection within a second time period provided by an embodiment of the present application;

[0025] Figure 13 A flowchart of another method for determining the type of imbalance problem and the problem period occurring at a traffic intersection within a second time period provided by an embodiment of the present application;

[0026] Figure 14 A flow chart of a method for determining the type of vacant parking problem and the problem period at a traffic intersection within a second time period provided in an embodiment of the present application;

[0027] Figure 15 A flowchart of another method for determining whether a vacant parking type problem and the problem period occur at a traffic intersection within a second time period provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0029] Existing traffic scene recognition and analysis methods based on large-scale traffic models use data from electronic police vehicles and intersection detectors to calculate indicators such as queue length, saturation, green light loss time, single-lane flow, travel time, travel time ratio, and delays. These indicators are then used to identify congestion, imbalance, and empty traffic at intersections, and determine the corresponding cause of the problem intersection, providing a scientific basis for the work of relevant traffic management departments. However, this traffic scene recognition and analysis method based on large-scale traffic models cannot determine the corresponding problem intersection type in various scenarios.

[0030] Therefore, there is an urgent need for a traffic scene recognition and analysis method based on a large traffic model to solve the problem in the existing technology that the corresponding problem intersection types in various scenarios cannot be given, thereby reducing the workload of manual analysis and improving work efficiency.

[0031] To this end, an embodiment of the present application provides a traffic scene recognition and analysis method based on a large traffic model to solve the problem in the existing technology that it is impossible to provide corresponding problem intersection types in various scenarios, thereby reducing the workload of manual analysis and improving work efficiency.

[0032] To further illustrate the technical solutions provided by the embodiments of the present application, the following is a detailed description of the technical solutions in conjunction with the accompanying drawings and specific implementation methods. Although the embodiments of the present application provide the method operation steps as shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative work. In steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided in the embodiments of the present application.

[0033] First reference Figure 1 , which is a schematic diagram of an application scenario of an embodiment of the present application, including a collector 10, a server 11, and a display 12. The collector can be any type of traffic detection equipment. The collector 10 is used to collect operating parameters and traffic signal control parameters at a traffic intersection within a first time period. The server 11 is used to determine the congestion type, congestion duration, problem type, and problem period at the traffic intersection based on the operating parameters and traffic signal control parameters at the traffic intersection within the first time period. The display 12 is used to display the congestion type, congestion duration, problem type, and problem period at the traffic intersection.

[0034] In an embodiment of the present application, one implementation method of the embodiment of the present application is that the server 11 obtains the operating parameters and traffic signal control parameters of the traffic intersection collected by the collector 10 within a first time period, wherein the operating parameters of the traffic intersection are determined based on the traffic data of the traffic intersection; the first time period includes at least one time period; based on the traffic volume in the operating parameters, the time period is divided into a first time period and a second time period, wherein the traffic volume in the first time period is greater than the traffic volume in the second time period; based on the operating parameters of the multiple entrance sections and multiple exit sections included in the traffic intersection in the first time period, the congestion type and congestion period of the traffic intersection in the first time period are determined, and displayed on the display 12; the second time period is divided into multiple sub-time periods, and based on the operating parameters and traffic signal control parameters of at least one target turn of the traffic intersection in each sub-time period, the problem type and problem period of the traffic intersection in the second time period are determined, and displayed on the display 12.

[0035] refer to Figure 2 A flow chart of a traffic scene recognition and analysis method based on a large traffic model is shown to illustrate the technical solution provided in the embodiment of the present application.

[0036] Step 201, obtaining operation parameters and traffic signal control parameters of a traffic intersection within a first time period;

[0037] The operating parameters of the traffic intersection are determined based on traffic data at the traffic intersection; the first duration includes at least one time period. For example, the first duration may be 9 days, including 5 working days and 4 non-working days, with a time period of 1 day. The operating parameters of the traffic intersection are determined by collecting and calculating traffic data from the traffic intersection using coils, geomagnetic field data, and electronic police data.

[0038] Step 202: dividing the time period into a first time period and a second time period based on the vehicle flow rate in the operating parameter;

[0039] The traffic volume in the first time period is greater than the traffic volume in the second time period. Specifically, based on the traffic volume at the intersection or other operating parameters, the time period is divided into peak period, off-peak period, and low-peak period, with the peak period serving as the first time period and the off-peak period and low-peak period serving as the second time period. This application also supports manual division of the first time period and the second time period.

[0040] Step 203: determining a congestion type and a congestion period of the traffic intersection within the first time period based on operating parameters of a plurality of entrance sections and a plurality of exit sections included in the traffic intersection within the first time period;

[0041] The above congestion types include congestion overflow type, one-way congestion imbalance, intersection congestion imbalance, opposite congestion imbalance and bottleneck congestion imbalance.

[0042] Step 204 : Divide the second time period into multiple sub-time periods, and determine the problem type and problem period of the traffic intersection in the second time period based on the operating parameters and traffic signal control parameters of at least one target turn at the traffic intersection in each sub-time period.

[0043] The above problem types are multiple parking types, imbalance types, and empty types. The present application can evenly divide the second time period into multiple sub-time periods, or can also unevenly divide the second time period into multiple sub-time periods. For example, the second time period can be evenly divided into 15-minute sub-time periods.

[0044] Turns at intersections include single turns and compound turns. Single turns include straight ahead, left turn, right turn, and U-turn at the intersection entrance, while compound turns are formed by combining any two single turns. To improve intersection traffic efficiency, the target turns must meet at least one of the following conditions:

[0045] There is no conflict between the target turn and the turns other than the target turn included in the traffic intersection when they are performed simultaneously under the instructions of the traffic signal control parameters; for example, taking a T-shaped traffic intersection as an example, going straight and turning left are performed simultaneously under the instructions of the traffic signal control parameters, and the left turn is the target turn; or the turn controlled by the traffic signal is the target turn.

[0046] Alternatively, the green light release time for the target turn indicated by the traffic signal control parameter is longer than the set pedestrian passing time.

[0047] The above-set pedestrian crossing time may be the sum of the minimum pedestrian crossing time and the set time, wherein the set time may be 7 seconds or other values.

[0048] The present application can determine that the green light release time of the target turn indicated by the traffic signal control parameter is longer than the set pedestrian passing time by the following traffic model formula:

[0049] ;

[0050] in, is the green light release duration of the target turn indicated by the traffic signal control parameter, The length that pedestrians need to pass through when turning. is the average walking speed of pedestrians, which can be 1m / s (meter / second) or other values. a is the set time length. and The ratio is the minimum time for pedestrians to cross the street.

[0051] The present application obtains the operating parameters and traffic signal control parameters of a traffic intersection within a first time period including at least one time period, and divides the time period into a first time period and a second time period based on the vehicle volume in the operating parameters, thereby achieving the division of peak scenarios and non-peak scenarios. The present application can determine the congestion type and congestion period of the traffic intersection within the first time period based on the operating parameters of multiple entrance sections and multiple exit sections included in the traffic intersection within the first time period; and can determine the problem type and problem period of the traffic intersection within the second time period based on the operating parameters and traffic signal control parameters of at least one target turn of the traffic intersection, thereby solving the problem in the prior art of being unable to provide the corresponding problem intersection type in various scenarios, thereby reducing the workload of manual analysis and improving work efficiency.

[0052] The following is a detailed description of the intersection problem identification method provided above. Figure 3 Shown, including:

[0053] Step 301, obtaining operation parameters and traffic signal control parameters of a traffic intersection within a first time period;

[0054] The first duration includes at least one time period.

[0055] Step 302: dividing the time period into a first time period and a second time period based on the vehicle flow rate in the operating parameter;

[0056] Specifically, the time period when the traffic volume exceeds the first threshold is used as the first time period, and the time period when the traffic volume does not exceed the first threshold is used as the second time period. If there may be multiple peak hours, multiple low-peak hours, and multiple off-peak hours in a time period, the multiple peak hours are used as the first time period, and the multiple off-peak hours and multiple low-peak hours are used as the second time period.

[0057] This application divides scenarios into specific and detailed categories based on operating parameters. During peak hours, the focus is on identifying congestion overflow and imbalance types at intersections; during off-peak and low-peak hours, the focus is on identifying inefficiencies at the intersection turn level. The scenarios are further refined to include identification of multiple stop types, imbalance types, and empty parking types. Therefore, the time period is divided into a first time period, namely peak hours, and a second time period, namely off-peak and low-peak hours.

[0058] Step 303: determining a congestion type and a congestion period of the traffic intersection in the first time period based on operating parameters of the plurality of entrance sections and the plurality of exit sections included in the traffic intersection in the first time period;

[0059] This application mainly divides the traffic congestion types at the traffic intersection in the first time period into the following three types:

[0060] Congestion overflow type: This type of traffic intersection has overflow sections in the exit direction during the first time period, blocking traffic flow from other entrance sections. Frequent overflows lead to large-scale congestion.

[0061] Congestion imbalance type: This type of traffic intersection has one or two congested sections during the first time period, while other entrance sections are unobstructed. This means that there is room for optimization in the traffic signal control scheme, and this type of congestion can be resolved through scheme optimization. Congestion imbalance types include one-way congestion imbalance, intersecting congestion imbalance, and opposing congestion imbalance.

[0062] Bottleneck congestion imbalance: This type of traffic intersection has at least three entrance congested sections within the first time period, that is, the intersection is oversaturated and the congestion cannot be solved through optimization solutions.

[0063] Figure 4 A flow chart of a method for determining the congestion type and congestion period of a traffic intersection within a first time period provided in an embodiment of the present application is shown as follows: Figure 4 As shown, the above step 303 specifically includes:

[0064] Step 401: determining at least one congested entrance section from the plurality of entrance sections based on operating parameters of the plurality of entrance sections at the traffic intersection within the first time period;

[0065] The duration of vehicle stays at the congested entrance section is greater than a first time threshold, which may be 10 minutes or another value. This application uses the direction of the congested entrance section as the congestion direction. This application can use a congested section identification method to determine at least one congested entrance section from the multiple entrance sections based on operating parameters of the multiple entrance sections at the traffic intersection during the first time period. The specific process is prior art and will not be further described here.

[0066] Step 402: determining at least one congested period of each of the at least one congested import sections according to the operating parameters of each of the at least one congested import sections during the first time period;

[0067] Specifically, each congested import section may include multiple congested periods within the first time period. The present application may combine the first congested period with the second congested period if the time interval between the end time of the first congested period and the start time of the second congested period is less than a set duration. The set duration may be 15 minutes or other values. Figure 5A schematic diagram of a congested section of an import road in a first time period provided in an embodiment of the present application is shown as follows: Figure 5 As shown in the figure, the first time period is (7:00-8:00), and the congested import section includes the first congestion period (7:00-7:14), the second congestion period (7:16-7:30), and the third congestion period (7:48-8:00). Taking 15 minutes as an example, since the time interval between the first and second congestion periods is 2 minutes, and the time interval between the second and third congestion periods is 18 minutes, the first and second congestion periods are merged, and the third congestion period is retained. Figure 6 A schematic diagram of a congested period after an import congested road section is merged within a first time period is provided in an embodiment of the present application, as shown in FIG. Figure 6 As shown, the import congested road section includes a first congested period (7:00-7:30) and a second congested period (7:48-8:00) within the first time period.

[0068] Step 403: Merge at least one congestion period corresponding to the at least one entrance congested road section to obtain a congestion period of the traffic intersection within the first time period;

[0069] Specifically, a traffic intersection may include multiple entrance congested sections within the first time period. Figure 7 A schematic diagram of another congested import section in a first time period after merging is provided in an embodiment of the present application, as shown in FIG. Figure 7 As shown, the first time period is (7:00-8:00), and the import congested section includes the third congested period (7:05-7:35) and the fourth congested period (7:50-8:00) within the first time period.

[0070] For example, Figure 6 The two congestion periods corresponding to the congested sections of the middle and entrance roads and Figure 7The two congestion periods corresponding to the middle import congested section are merged to obtain the congestion period of the traffic intersection within the first time period. Since the time interval between the start time of the first congestion period and the start time of the third congestion period is 5 minutes, and the time interval between the end time of the first congestion period and the end time of the third congestion period is 5 minutes, the two time intervals are less than the set duration. The set duration can be set according to actual conditions. Here, 15 minutes is taken as an example. Therefore, the first congestion period is merged with the third congestion period. The time interval between the start time of the second congestion period and the start time of the fourth congestion period is 2 minutes, and the time interval between the end time of the second congestion period and the end time of the fourth congestion period is 0 minutes. The two time intervals are less than the set duration. Therefore, the second congestion period is merged with the fourth congestion period. After merging the two congested time periods corresponding to the two import congested sections, we obtain the fifth congested time period (7:00-7:35) and the sixth congested time period (7:50-8:00) of the traffic intersection in the first time period. Since this application deletes the congested time period that is shorter than the set congestion duration, where the set congestion duration can be set according to actual conditions, 30 minutes is taken as an example here. Therefore, the congested time period (7:00-7:35) of the traffic intersection in the first time period is determined.

[0071] Step 404 : Determine the congestion type of the traffic intersection in the first time period based on the operating parameters of the multiple exit sections of the traffic intersection in the first time period and the at least one entrance congested section.

[0072] The above congestion types include congestion overflow type, one-way congestion imbalance, intersection congestion imbalance, opposite congestion imbalance and bottleneck congestion imbalance.

[0073] Regarding the congestion overflow type, the present application may determine that the congestion type of the traffic intersection during the first time period is the congestion overflow type based on the operating parameters of the multiple exit sections of the traffic intersection during the first time period and the at least one entrance congested section through the following two methods:

[0074] The first method is that if, based on the operating parameters of multiple exit sections of the traffic intersection within the first time period, it is determined that there is at least one exit section of the traffic intersection that is an overflow section within M time periods, and there is at least one import congested section, then the congestion type of the traffic intersection within the first time period is determined to be a congestion overflow type.

[0075] The first duration includes N time periods, where N is an integer greater than 1, and M is a positive integer less than or equal to N, and M is greater than a first quantity threshold. The first quantity threshold can be set based on actual needs. For example, if N is 10, the first quantity threshold can be 2, and M can be 3 or another value greater than the first quantity threshold.

[0076] The present application can determine the congestion direction corresponding to the at least one congested entrance section and the overflow direction corresponding to the at least one overflow section. The congestion direction is the entrance direction of the congested entrance section, and the overflow direction is the exit direction of the overflow section. The present application can determine at least one overflow section from the multiple exit sections using an overflow section identification method based on the operating parameters of the multiple exit sections of the traffic intersection during the first time period. The specific process is prior art and will not be further described here.

[0077] The second method is to determine that the congestion type of the traffic intersection during the first time period is a congestion overflow type if it is determined that the traffic intersection has at least one entrance congested section and at least one exit congested section.

[0078] The duration of the vehicle's stay in the exit congested road section is greater than a third time threshold. The third time threshold can be set according to actual conditions, for example, the third time threshold can be 10 minutes.

[0079] The present application can determine a first congestion direction corresponding to the at least one entrance congested road section and a second congestion direction corresponding to the at least one exit congested road section, wherein the first congestion direction is the entrance direction of the entrance congested road section; and the second congestion direction is the exit direction of the exit congested road section.

[0080] For one-way congestion imbalance, the congestion type of the traffic intersection in the first time period is determined to be one-way congestion imbalance by the following method:

[0081] Based on the operating parameters of multiple entrance sections of the traffic intersection in the first time period, it is determined that there is only one entrance congested section at the traffic intersection, and then the congestion type of the traffic intersection in the first time period is determined to be one-way congestion imbalance.

[0082] For intersection congestion imbalance, the congestion type of the traffic intersection in the first time period is determined to be intersection congestion imbalance by the following method:

[0083] Based on the operating parameters of multiple entrance sections of the traffic intersection within the first time period, it is determined that there are two entrance congested sections at the traffic intersection, and the driving directions of the two entrance congested sections intersect, then the congestion type of the traffic intersection within the first time period is determined to be intersection congestion imbalance.

[0084] For example, Figure 8 The schematic diagram of the intersection of the driving directions of two congested import sections provided in the embodiment of the present application is as follows: Figure 8 As shown, the driving direction at the first entrance congested section is south, and the driving direction at the second entrance congested section is east, and it is determined that the two driving directions intersect.

[0085] For the opposite congestion imbalance, the congestion type of the traffic intersection in the first time period is determined to be the opposite congestion imbalance by the following method:

[0086] Based on the operating parameters of multiple entrance sections of the traffic intersection within the first time period, it is determined that there are two entrance congested sections at the traffic intersection, and the driving directions of the two entrance congested sections are opposite, then the congestion type of the traffic intersection within the first time period is determined to be opposite congestion imbalance.

[0087] For example, Figure 9 The schematic diagram of two congested road sections with opposite driving directions provided in the embodiment of the present application is as follows: Figure 9 As shown, the driving direction at the first entrance congested section is south, and the driving direction at the second entrance congested section is north, and it is determined that the two driving directions are opposite.

[0088] For bottleneck congestion imbalance, the congestion type of the traffic intersection during the first time period is determined to be bottleneck congestion imbalance by the following method:

[0089] Based on the operating parameters of multiple entrance sections of the traffic intersection in the first time period, it is determined that there are at least three entrance congested sections at the traffic intersection, and then the congestion type of the traffic intersection in the first time period is determined to be bottleneck congestion imbalance.

[0090] Step 304: Divide the second time period into a plurality of sub-time periods;

[0091] Step 305 : Determine the problem type and problem period of the traffic intersection in the second time period based on the operating parameters and traffic signal control parameters of at least one target turn at the traffic intersection in each sub-time period.

[0092] The aforementioned problem types include multiple-stop, imbalance, and empty. The multiple-stop problem indicates that at least one turn at the intersection has multiple stops. The imbalance problem indicates that some target turns at the intersection have long queues or dense traffic flow, while others have short queues or dispersed traffic flow. The empty problem indicates that traffic flow at each target turn at the intersection is dispersed, resulting in low traffic signal control cycle release efficiency.

[0093] The following is a detailed description of the method for determining the problem type and problem period of the traffic intersection in the second time period based on the operating parameters and traffic signal control parameters of at least one target turn at the traffic intersection in each sub-time period:

[0094] For the turning multiple stop type, the above operating parameters include the multiple stop ratio or the average number of vehicle stops. Therefore, the following describes in detail a method for determining whether the turning multiple stop type problem occurs at the traffic intersection in the second time period and the problem period based on the operating parameters:

[0095] Figure 10 A flowchart of a method for determining the occurrence of a turning and multiple stopping type problem and the problem period at a traffic intersection within a second time period is provided in an embodiment of the present application, such as Figure 10 As shown, specifically including:

[0096] Step 101: If it is determined that the proportion of multiple stops of at least one target turn at the traffic intersection in the i-th sub-time period corresponding to each of K time periods is greater than or equal to a proportion threshold, then it is determined that the traffic intersection has a turn multiple stop type problem in the i-th sub-time period;

[0097] The first duration includes N time periods, where N is an integer greater than 1, and K is a positive integer less than or equal to N, and K is greater than a second threshold value. For example, if N is 9 days, the second threshold value may be 1, and K may be 2 days or another value greater than the second threshold value.

[0098] The multiple stop percentage for the i-th sub-period is the ratio of the number of vehicles that stopped more than twice during the i-th sub-period to the total number of vehicles during the i-th sub-period, where i is less than or equal to the number of sub-periods. For example, if the i-th sub-period is 15 minutes, and there are 10 vehicles using a target turn during the i-th sub-period, of which 5 vehicles do not stop, 3 vehicles each stop once, and 2 vehicles each stop twice, then the multiple stop percentage for the i-th sub-period is 2 / 10 = 20%.

[0099] The percentage of multiple stops in the i-th sub-time period being greater than or equal to the percentage threshold can be determined by the following traffic model formula:

[0100] ;

[0101] in, represents the proportion of multiple stops during the target turn in the i-th sub-time period, The percentage threshold can be set to 10% or other values.

[0102] Step 102 : determining a problem period during which the multiple-turn and multiple-stop problem occurs at the traffic intersection within the second time period based on at least one sub-time period during which the multiple-turn and multiple-stop problem occurs.

[0103] This application regards at least one target turn in the above step 101 that satisfies the multiple parking ratio in the i-th sub-time period corresponding to K time periods as a problem turn.

[0104] For at least one sub-period of each problematic turn in which a multiple-stop type problem occurs, the present application may combine the first and second sub-periods if the time interval between the end time of the first sub-period and the start time of the second sub-period in each of two adjacent sub-periods is less than a set duration, thereby obtaining the problematic period for each problematic turn. The set duration can be set based on actual conditions and may be 15 minutes.

[0105] For the traffic intersection, the problem time periods of each problematic turn are merged to obtain the problem time period of the traffic intersection with the problem of multiple turns and stops in the second time period. If there are two problematic turns at a traffic intersection, the problem time period of the traffic intersection with the problem of multiple turns and stops in the second time period is determined by the following traffic model formula: :

[0106] ;

[0107] in, The question period for the first question is turned to This is the question period for question 2.

[0108] Figure 11 A flowchart of another method for determining whether a traffic intersection has a turning and multiple stopping type problem and a problem period within a second time period is provided in an embodiment of the present application, such as Figure 11 As shown, specifically including:

[0109] Step 111: If it is determined that the average number of vehicle stops for at least one target turn at the traffic intersection in the i-th sub-time period corresponding to W time periods is greater than or equal to a number threshold, then it is determined that the traffic intersection has a turn multiple stop type problem in the i-th sub-time period;

[0110] The first duration includes N time periods, where N is an integer greater than 1, and W is a positive integer less than or equal to N, and W is greater than a third threshold value. For example, if N is 9 days, the third threshold value may be 1, and W may be 2 days or another value greater than the third threshold value.

[0111] The average number of vehicle stops during the i-th sub-period is the ratio of the sum of the number of stops made by multiple vehicles during the i-th sub-period to the total number of vehicles during the i-th sub-period; i is less than or equal to the number of sub-periods. For example, if the i-th sub-period is 15 minutes, and there are 10 vehicles passing through a target turn during the i-th sub-period, of which 5 vehicles do not stop, 3 vehicles each stop once, and 2 vehicles each stop twice, then the sum of the number of stops made by multiple vehicles during the i-th sub-period is 5*0+3*1+2*2=7, and the average number of vehicle stops during the i-th sub-period is determined to be 7 / 10=0.7.

[0112] The average number of vehicle stops in the i-th sub-time period is greater than or equal to the number threshold value and can be determined by the following traffic model formula:

[0113] ;

[0114] in, represents the average number of vehicle stops during the i-th sub-time period when the target turns, is the number threshold, which can be 1 or other values.

[0115] Step 112 , determining a problem period during which the multiple-turn-and-stop problem occurs at the traffic intersection within the second time period based on at least one sub-time period during which the multiple-turn-and-stop problem occurs.

[0116] This application regards at least one target turn in the above step 111 that satisfies the condition that the average number of vehicle stops in the i-th sub-time period corresponding to W time periods is greater than or equal to the number threshold as a problem turn.

[0117] For at least one sub-time period within each problematic turn in which a multiple-stop type problem occurs, the present application may combine the first sub-time period with the second sub-time period when the time interval between the end time of the first sub-time period and the start time of the second sub-time period in each of two adjacent sub-time periods is less than a set duration, thereby obtaining a problematic time period for each problematic turn. The set duration can be set based on actual conditions and may be 15 minutes. For the traffic intersection, the problem time periods of each problematic turn are combined to obtain a problematic time period within the second time period in which the multiple-stop type problem occurs at the traffic intersection.

[0118] After determining that the traffic intersection has a problem period of multiple turns and stops within the second time period, two methods for determining the type of imbalance problem and the problem period within the second time period are described in detail below:

[0119] Figure 12 A flowchart of a method for determining the type of imbalance problem and the problem period at a traffic intersection within a second time period is provided in an embodiment of the present application, such as Figure 12 As shown, specifically including:

[0120] Step 121: If there is a first target turn and the maximum queue length among the average queue lengths at multiple moments in the j-th sub-time period is greater than or equal to a first length threshold, and if there is a second target turn and the minimum queue length among the average queue lengths at multiple moments in the j-th sub-time period is less than or equal to a second length threshold, then it is determined that the traffic intersection has an imbalance type problem in the j-th sub-time period.

[0121] The first duration includes N time periods, where N is an integer greater than 1. The operating parameter includes the average queue lengths at N moments, and the average queue length at the first moment is the average of the queue lengths at the first moment across the N time periods. For example, if the first duration includes two time periods, the operating parameter includes the average queue lengths at N moments, and the average queue length at each moment is the average of the queue lengths at that moment across the two time periods.

[0122] The first length threshold is greater than the second length threshold. j is less than or equal to the number of sub-time periods included in the second time period, excluding the sub-time period with the multiple-stop-turn-type issue. For example, if the second time period includes three sub-time periods and the second sub-time period is a sub-time period with the multiple-stop-turn-type issue, the imbalance type is determined for the first and second sub-time periods.

[0123] The first target turning point that the maximum queue length among the average queue lengths at multiple moments in the j-th sub-time period is greater than or equal to the first length threshold can be determined by the following traffic model formula:

[0124] ;

[0125] in, For the first target, the maximum queue length among the average queue lengths at multiple moments in the jth sub-time period is obtained. is the first length threshold, which can be 70 meters, about the length of 10 cars, or other values.

[0126] The second target turning point in which the minimum queue length among the average queue lengths at multiple moments included in the j-th sub-time period is less than or equal to the second length threshold can be determined by the following traffic model formula:

[0127] ;

[0128] in, For the second goal, turn to the minimum queue length of b among the average queue lengths at multiple moments in the jth sub-time period. The second length threshold may be 20 meters, which is about the length of three cars, or other values.

[0129] Step 122 : determining a problem period during which the imbalance problem occurs at the traffic intersection within the second time period according to at least one sub-time period during which the imbalance problem occurs.

[0130] This application regards the first target redirection in the above step 121 as question redirection, and the first target redirection can be one or more.

[0131] For at least one sub-time period in which an imbalance-type problem occurs at each problematic turn, the present application may combine the first sub-time period with the second sub-time period when the time interval between the end time of the first sub-time period and the start time of the second sub-time period in each of two adjacent sub-time periods is less than a set duration, thereby obtaining a problem period for each problematic turn. The set duration can be set based on actual conditions and may be 15 minutes. For the traffic intersection, the problem periods of each problematic turn are combined to obtain a problem period in which the imbalance-type problem occurred at the traffic intersection within the second time period.

[0132] Figure 13 A flowchart of another method for determining the type of imbalance problem and the problem period at a traffic intersection within a second time period provided by an embodiment of the present application, such as Figure 13 As shown, specifically including:

[0133] Step 131: If there is a third target turn whose maximum steering saturation among the average steering saturations at multiple moments in the j-th sub-time period is greater than or equal to a first saturation threshold, and if there is a fourth target turn whose minimum steering saturation among the average steering saturations at multiple moments in the j-th sub-time period is less than or equal to a second saturation threshold, then it is determined that the traffic intersection has an imbalance type problem in the j-th sub-time period.

[0134] Among them, the above-mentioned turning saturation is the degree of discreteness of the traffic flow in the turn. The higher the degree of discreteness of the traffic flow in the turn, the lower the corresponding turning saturation. The present application can determine the turning saturation based on the traffic flow, green light release time and saturated headway time corresponding to each moment. Specifically, for any target turn, the first ratio between the green light direction time and the saturated headway time at the f-th moment is calculated, and the ratio between the traffic flow at the f-th moment and the first ratio is used as the turning saturation of the target turn at the f-th moment. The first time length includes N time periods, N is an integer greater than 1, and the operating parameters include the average turning saturation of N moments, and the average turning saturation of the first moment is the average value of the turning saturation of the N time periods at the first moment. For example, if the first time length includes 3 time periods, the operating parameters include the average turning saturation of N moments, and the average turning saturation of each moment is the average value of the turning saturation of the 3 time periods at that moment.

[0135] The first saturation threshold is greater than the second saturation threshold. j is less than or equal to the number of sub-time periods included in the second time period excluding the sub-time period with the turn-and-stop problem.

[0136] The third target turn, in which the maximum turn saturation among the average turn saturations at multiple moments included in the jth sub-time period is greater than or equal to the first saturation threshold, can be determined by the following traffic model formula:

[0137] ;

[0138] in, is the maximum steering saturation among the average steering saturations at multiple moments included in the jth sub-time period for the third target steering c, is the first saturation threshold, which can be 0.7 or other values.

[0139] The fourth target turn, in which the minimum turn saturation among the average turn saturations at multiple moments included in the jth sub-time period is less than or equal to the second saturation threshold, can be determined by the following traffic model formula:

[0140] ;

[0141] in, is the minimum steering saturation among the average steering saturations at multiple moments included in the jth sub-time period for the fourth target steering d, is the second saturation threshold, which can be 0.5 or other values.

[0142] Step 132 : determining a problem period during which the imbalance problem occurs at the traffic intersection within the second time period according to at least one sub-time period during which the imbalance problem occurs.

[0143] This application regards the third target redirection in the above step 131 as question redirection, and the third target redirection can be one or more.

[0144] For at least one sub-time period in each problematic turn in which an imbalance-type problem occurs, the present application may combine the first sub-time period with the second sub-time period when the time interval between the end time of the first sub-time period and the start time of the second sub-time period in each of two adjacent sub-time periods is less than a set duration, thereby obtaining a problematic time period for each problematic turn. The set duration can be set based on actual conditions and may be 15 minutes. For the traffic intersection, the problem time periods of each problematic turn are combined to obtain a problematic time period in which the imbalance-type problem occurred at the traffic intersection within the second time period.

[0145] After determining the problem period of the multiple-stop-turn type problem and the problem period of the imbalance type problem at the traffic intersection within the second time period, two methods for determining the problem period of the vacant type problem and the problem period at the traffic intersection within the second time period are described in detail below:

[0146] Figure 14 A flowchart of a method for determining the type of vacant parking problem and the problem period at a traffic intersection within a second time period is provided in an embodiment of the present application, such as Figure 14 As shown, specifically including:

[0147] Step 141: If it is determined that the intersection saturation in the k-th sub-time period corresponding to each of the L time periods is greater than or equal to a third saturation threshold, and the green light loss duration in the k-th sub-time period is greater than or equal to the green light loss threshold, then it is determined that the traffic intersection has a vacant traffic problem in the k-th sub-time period;

[0148] The first duration includes N time periods, where N is an integer greater than 1, and L is a positive integer less than or equal to N, and L is greater than a fourth threshold value. k is less than or equal to the number of sub-periods included in the second time period, excluding the sub-period with the multiple-stop-turn issue and the sub-period with the imbalance issue. For example, if N is 9 days, the fourth threshold value can be 1, and L can be 2 days or another value greater than the fourth threshold value.

[0149] The intersection saturation within the kth sub-time period is the average of the turn saturations for multiple target turns within the kth sub-time period. The green light loss duration within the kth sub-time period is the minimum sum of the green light loss durations for multiple target turns that are simultaneously executed under at least one traffic signal control parameter within the kth sub-time period. The green light loss duration for each target turn is the duration during which no vehicles pass when the corresponding target turn has a green light.

[0150] For example, a traffic intersection includes four target turns: East Straight, East Left, West Straight, and West Left. If, during the kth sub-period, the traffic signal controls the East Straight and East Left turns to be released simultaneously, and the West Straight and West Left turns to be released simultaneously, the green light loss duration for each target turn is determined. If the green light loss duration for the East Straight is 8 seconds, the green light loss duration for the East Left is 10 seconds, the green light loss duration for the West Straight is 10 seconds, and the green light loss duration for the West Left is 12 seconds, then the first minimum green light loss duration between the green light loss durations for the East Straight and the East Left is determined to be 8 seconds, and the second minimum green light loss duration between the green light loss durations for the West Straight and the West Left is determined to be 10 seconds. Therefore, the green light loss duration during the kth sub-period is the sum of the first and second minimum green light loss durations, which is 18 seconds.

[0151] Whether the intersection saturation in the kth sub-time period is greater than or equal to the third saturation threshold can be determined by the following traffic model formula:

[0152] ;

[0153] in, is the intersection saturation of the traffic intersection in the kth sub-time period, is the third saturation threshold, which can be 0.4 or other values.

[0154] The green light loss duration in the k-th sub-time period is greater than or equal to the green light loss threshold and can be determined by the following traffic model formula:

[0155] ;

[0156] in, is the green light loss duration of the traffic intersection in the kth sub-time period, and Ta is the green light loss threshold.

[0157] The green light loss threshold Ta can be determined by the following traffic model formula:

[0158] ;

[0159] Among them, C is the traffic signal control cycle in the traffic signal control parameters, and N% is the green loss ratio threshold.

[0160] The green loss ratio threshold N% can be set based on whether the traffic signal controls at the current traffic intersection and its adjacent traffic intersections are coordinated.

[0161] Specifically, if the traffic signal control period of the traffic intersection in the kth sub-time period is an integer multiple or a semi-integer multiple of the traffic signal control periods of its adjacent traffic intersections, indicating that vehicles do not need to stop due to traffic signal changes when traveling from the traffic intersection to the adjacent traffic intersections, then N% is set as the first parameter, that is, the traffic signal control coordination between the current traffic intersection and the adjacent traffic intersections in the kth sub-time period can be expressed by the following traffic model formula:

[0162] ;

[0163] in, is the traffic signal control period of the traffic intersection in the kth sub-time period, is the traffic signal control period of the hth adjacent traffic intersection in the kth sub-time period, the value range of D is 1 or 2, the value range of k is [1, n], and n is the number of adjacent traffic intersections.

[0164] If the traffic signal control period at the intersection during the kth sub-time period is not an integer multiple or a half-integer multiple of the traffic signal control period at at least one adjacent intersection, indicating that a vehicle needs to stop due to a traffic signal change when traveling from the intersection to the adjacent intersection, then N% is set as the second parameter, i.e., there is a lack of coordination in traffic signal control at the current intersection and its upstream and downstream intersections during the kth sub-time period. The first parameter is greater than the second parameter, and the first parameter can be 20% or another value, and the second parameter can be 10% or another value.

[0165] Step 142 , determining a problem period during which the vacant type problem occurs at the traffic intersection within the second time period based on at least one sub-time period during which the vacant type problem occurs.

[0166] This application takes the target turn corresponding to the maximum green light loss time as the problem turn based on the green light loss time of at least one target turn, and can use the following traffic model formula to determine the problem turn: :

[0167] ;

[0168] in, is the green light loss time for the c-th target turn, where the value of c is greater than or equal to 1 and less than or equal to the number of target turns.

[0169] For at least one sub-time period in which an idle traffic type problem occurs, the present application can merge the first sub-time period with the second sub-time period when the time interval between the end time of the first sub-time period and the start time of the second sub-time period in each adjacent sub-time period is less than the set duration, to obtain the problem period in which the idle traffic type problem occurs at the traffic intersection within the second time period.

[0170] Figure 15 A flowchart of another method for determining the type of vacant parking problem and the problem period at a traffic intersection in a second time period provided by an embodiment of the present application, such as Figure 15 As shown, specifically including:

[0171] Step 151: If it is determined that the intersection saturation in the k-th sub-time period corresponding to each of the M time periods is less than a third saturation threshold, and the maximum queue length of at least one target turn at the intersection at multiple times included in the k-th sub-time period is greater than or equal to a third length threshold, then it is determined that the intersection has a vacant traffic problem in the k-th sub-time period;

[0172] The first duration includes N time periods, where N is an integer greater than 1, M is a positive integer less than or equal to N, and L is greater than a fifth threshold value. k is less than or equal to the number of sub-periods included in the second time period, excluding the sub-period with the multiple-stop-turn issue and the sub-period with the imbalance issue. For example, if N is 9 days, the fourth threshold value can be 1, and L can be 2 days or another value greater than the fifth threshold value.

[0173] The intersection saturation in the kth sub-time period is less than the third saturation threshold value, which can be determined by the following traffic model formula:

[0174] ;

[0175] in, is the intersection saturation of the traffic intersection in the kth sub-time period, is the third saturation threshold, which can be 0.4 or other values.

[0176] The maximum queue length of the queue at the multiple moments of the at least one target turn at the traffic intersection in the kth sub-time period is greater than or equal to the third length threshold, which can be determined by the following traffic model formula:

[0177] ;

[0178] in, For a target, turn to the maximum queue length among the queue lengths at multiple moments in the kth sub-time period. is the third length threshold, which can be 20m (about the length of 3 cars) or other values.

[0179] Step 152: Determine the problem period during which the vacant type problem occurs at the traffic intersection within the second time period according to at least one sub-time period during which the vacant type problem occurs.

[0180] This application regards at least one target diversion in the above step 151 as a problem diversion, which satisfies the condition that the maximum queue length among the queue lengths at multiple moments included in the i-th sub-time period corresponding to the W time periods is greater than or equal to the third length threshold.

[0181] For at least one sub-time period for each problem turn in which an empty vehicle problem occurs, the present application may combine the first sub-time period with the second sub-time period when the time interval between the end time of the first sub-time period and the start time of the second sub-time period in each of two adjacent sub-time periods is less than a set duration, thereby obtaining a problem period for each problem turn. The set duration can be set based on actual conditions and may be 15 minutes. For the traffic intersection, the problem periods for each problem turn are combined to obtain a problem period in which an empty vehicle problem occurs at the traffic intersection within the second time period.

[0182] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0183] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0184] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0185] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0186] Obviously, those skilled in the art may make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include these modifications and variations.

Claims

1. A traffic scene recognition and analysis method based on a large traffic model, characterized in that: include: Acquiring operating parameters and traffic signal control parameters of a traffic intersection within a first time period, wherein the operating parameters of the traffic intersection are determined based on traffic data of the traffic intersection; the first time period includes at least one time period; Based on the traffic volume in the operating parameter, the time period is divided into a first time period and a second time period, wherein the traffic volume in the first time period is greater than the traffic volume in the second time period; Determining a congestion type and a congestion period of the traffic intersection within the first time period based on operating parameters of a plurality of entrance road sections and a plurality of exit road sections included in the traffic intersection within the first time period; Dividing the second time period into a plurality of sub-time periods, and determining a problem type and a problem period at the traffic intersection in the second time period based on operating parameters and traffic signal control parameters of at least one target turn at the traffic intersection in each sub-time period; The target steering satisfies at least one of the following conditions: There is no conflict between the target turn and the turns other than the target turn included in the traffic intersection when they are simultaneously performed under the instructions of the traffic signal control parameters; or, the green light release time of the target turn indicated by the traffic signal control parameters is less than the set pedestrian passage time.

2. The method according to claim 1, characterized in that The determining, based on the operating parameters of the plurality of entrance sections and the plurality of exit sections of the traffic intersection within the first time period, the congestion type and congestion period of the traffic intersection within the first time period includes: Determining at least one congested entrance section from the plurality of entrance sections based on operating parameters of the plurality of entrance sections at the traffic intersection within the first time period, wherein a duration for which vehicles stay in the congested entrance section is greater than a first time threshold; determining at least one congested period of each of the at least one import congested road section according to an operating parameter of each import congested road section in the first time period; Merging at least one congestion period corresponding to the at least one entrance congested road section to obtain a congestion period of the traffic intersection within the first time period; The congestion type of the traffic intersection in the first time period is determined based on the operating parameters of the plurality of exit sections of the traffic intersection in the first time period and the at least one entrance congested section.

3. The method according to claim 2, characterized in that The first time period includes N time periods, where N is an integer greater than 1. The determining of the congestion type of the traffic intersection within the first time period based on the operating parameters of the plurality of exit sections and the at least one entrance congested section of the traffic intersection within the first time period includes: If, based on the operating parameters of multiple exit sections of the traffic intersection during the first time period, it is determined that at least one exit section of the traffic intersection is an overflow section for M time periods and at least one entrance congested section exists, then the congestion type of the traffic intersection during the first time period is determined to be a congestion overflow type; wherein M is a positive integer less than or equal to N and M is greater than a first quantity threshold, and the duration for which vehicles on the overflow section occupy at least one entrance section of the traffic intersection is greater than a second time threshold; Alternatively, if it is determined that there is at least one entrance congested section and at least one exit congested section at the traffic intersection, the congestion type of the traffic intersection during the first time period is determined to be a congestion overflow type; wherein the duration of vehicle stay in the exit congested section is greater than a third time threshold.

4. The method according to claim 2, characterized in that The determining of the congestion type of the traffic intersection within the first time period based on the operating parameters of the plurality of exit sections of the traffic intersection within the first time period and the at least one entrance congested section includes: If, based on the operating parameters of the multiple entrance sections of the traffic intersection during the first time period, it is determined that the traffic intersection has only one entrance congested section, then the congestion type of the traffic intersection during the first time period is determined to be one-way congestion imbalance; or, if, based on the operating parameters of the multiple entrance sections of the traffic intersection during the first time period, it is determined that the traffic intersection has two entrance congested sections, and the driving directions of the two entrance congested sections intersect, then the congestion type of the traffic intersection during the first time period is determined to be intersecting congestion imbalance; or, if, based on the operating parameters of the multiple entrance sections of the traffic intersection during the first time period, it is determined that the traffic intersection has two entrance congested sections, and the driving directions of the two entrance congested sections are opposite, then the congestion type of the traffic intersection during the first time period is determined to be opposing congestion imbalance; or, if, based on the operating parameters of the multiple entrance sections of the traffic intersection during the first time period, it is determined that the traffic intersection has at least three entrance congested sections, then the congestion type of the traffic intersection during the first time period is determined to be bottleneck congestion imbalance.

5. The method according to claim 1, wherein The first time period includes N time periods, where N is an integer greater than 1; the operating parameters include a ratio of multiple stops or an average number of vehicle stops; and determining a problem type and a problem period at the traffic intersection in the second time period based on the operating parameters and traffic signal control parameters of at least one target turn at the traffic intersection in each sub-time period includes: If it is determined that the proportion of multiple stops for at least one target turn at the traffic intersection in the i-th sub-time period corresponding to K time periods is greater than or equal to a proportion threshold, then it is determined that the traffic intersection has a turn-multiple-stop type problem in the i-th sub-time period; wherein K is a positive integer less than or equal to N and K is greater than a second number threshold; and based on at least one sub-time period in which the turn-multiple-stop type problem occurs, the problem period of the turn-multiple-stop type problem at the traffic intersection in the second time period is determined; wherein the multiple-stop proportion in the i-th sub-time period is the ratio of the number of vehicles that stopped more than twice in the i-th sub-time period to the total number of vehicles in the i-th sub-time period; i is less than or equal to the number of sub-time periods; Alternatively, if it is determined that the average number of vehicle stops for at least one target turn at the traffic intersection in the i-th sub-time period corresponding to W time periods is greater than or equal to a number threshold, then it is determined that the traffic intersection has a turn multiple stop type problem in the i-th sub-time period; where W is a positive integer less than or equal to N and W is greater than a third number threshold; And based on at least one sub-time period in which the problem of turning and stopping occurs, determine the problem period of the traffic intersection in the second time period in which the problem of turning and stopping occurs; wherein the average number of vehicle stops in the i-th sub-time period is the ratio of the sum of the number of stops of multiple vehicles in the i-th sub-time period to the total number of vehicles in the i-th sub-time period; i is less than or equal to the number of sub-time periods.

6. The method according to claim 5, characterized in that The operating parameter includes an average queue length at N moments, the average queue length at a first moment being an average of queue lengths at the first moment over N time periods, and the method further includes: If there is a first target turn and the maximum queue length among the average queue lengths at multiple moments included in the j-th sub-time period is greater than or equal to a first length threshold, and there is a second target turn and the minimum queue length among the average queue lengths at multiple moments included in the j-th sub-time period is less than or equal to a second length threshold, then it is determined that the traffic intersection has an imbalance type problem in the j-th sub-time period; wherein j is less than or equal to the number of sub-time periods included in the second time period excluding the sub-time period with the turn and multiple stop type problem; According to at least one sub-time period in which the imbalance type problem occurs, determining a problem period in which the imbalance type problem occurs at the traffic intersection within the second time period; wherein the first length threshold is greater than the second length threshold.

7. The method according to claim 5, characterized in that The operating parameter includes an average steering saturation at N moments, the average steering saturation at a first moment being an average of steering saturations at the first moment in N time periods, and the method further includes: If there is a third target turn and the maximum turning saturation among the average turning saturations at multiple moments included in the j-th sub-time period is greater than or equal to the first saturation threshold, and if there is a fourth target turn and the minimum turning saturation among the average turning saturations at multiple moments included in the j-th sub-time period is less than or equal to the second saturation threshold, it is determined that the traffic intersection has an imbalance type problem in the j-th sub-time period; wherein j is less than or equal to the number of sub-time periods included in the second time period excluding the sub-time period with the turning multiple stop type problem; According to at least one sub-time period in which the imbalance type problem occurs, determining a problem period in which the imbalance type problem occurs at the traffic intersection within the second time period; wherein the first saturation threshold is greater than the second saturation threshold.

8. The method according to claim 6 or 7, characterized in that The operating parameters include intersection saturation, the traffic signal control parameters include green light loss time, and the method further includes: If it is determined that the intersection saturation in the kth sub-time period corresponding to L time periods is greater than or equal to the third saturation threshold, and the green light loss duration in the kth sub-time period is greater than or equal to the green light loss threshold, then it is determined that the traffic intersection has a vacant type problem in the kth sub-time period; wherein L is a positive integer less than or equal to N and L is greater than the fourth quantity threshold; wherein k is less than or equal to the number of sub-time periods included in the second time period excluding the sub-time period with the turn multiple stop type problem and the sub-time period with the imbalance type problem; the green light loss duration in the kth sub-time period is the sum of the minimum values ​​of the green light loss durations of multiple target turns that are simultaneously turned under the instruction of the traffic signal control parameter in the kth sub-time period; According to at least one sub-time period in which the vacant type problem occurs, a problem period in which the vacant type problem occurs at the traffic intersection within the second time period is determined.

9. The method according to claim 6 or 7, characterized in that The operating parameters include intersection saturation and queue length corresponding to each moment in each sub-time period, and the method further includes: If it is determined that the intersection saturation in the kth sub-time period corresponding to each of M time periods is less than a third saturation threshold, and the maximum queue length of at least one target turn at the traffic intersection at multiple moments in the kth sub-time period is greater than or equal to a third length threshold, then it is determined that the traffic intersection has a vacant parking type problem in the kth sub-time period; wherein M is a positive integer less than or equal to N and L is greater than a fifth quantity threshold; and wherein k is less than or equal to the number of sub-time periods included in the second time period, excluding the sub-time period with the turn multiple parking type problem and the sub-time period with the imbalance type problem; According to at least one sub-time period in which the vacant type problem occurs, a problem period in which the vacant type problem occurs at the traffic intersection within the second time period is determined.

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