Method and equipment for determining parking times on arterial traffic

Abstract

The invention discloses a method and equipment for determining the number of parking times on an arterial traffic. The method comprises the steps that vehicle passing data of all intersections included in the coordination direction of a target arterial traffic are acquired; for each road section, screening the vehicle passing data of the road section at the first moment of the driving-in intersection by using the vehicle passing data set of the driving-out intersection of the road section at the second moment, and determining a first vehicle passing data set of the driving-in intersection and the driving-out intersection; the second moment is determined according to the first moment, a signal period of the road section in the coordination direction and a zero-time parking time threshold value; determining at least one driving track included in the target trunk line according to the vehicle passing data set of the driving intersection corresponding to each road section and the first vehicle passing data set; passing vehicles or passing intersections in each driving track are different; and determining the number of parking times on each driving track included in the target trunk line. The determined parking frequency is highly matched with the trunk line, and the green wave effect for evaluating the trunk line is more accurate.

Description

Technical Field

[0001] The present application relates to the field of intelligent transportation technology, and in particular to a method and device for determining the number of stops on a traffic artery. Background Art

[0002] In the field of traffic control, the number of stops on main roads is an important indicator for evaluating the green wave effect of main roads. Therefore, accurately determining the number of stops on main roads can improve the accuracy of evaluating the green wave effect of main roads.

[0003] In the related technology, tuning engineers or traffic police usually drive on-site for inspection and record the number of stops. This method is relatively accurate, but it consumes manpower and material resources, and the inspection track is limited. In addition, if the number of stops of vehicles on the road section between two intersections is added up, the number of stops obtained is only a simple combination of the number of stops on the road section. Different vehicles on different sections may also belong to different traffic arteries. In this case, the matching degree between the obtained number of stops and the arteries is low, and it is not very accurate to evaluate the green wave effect of the arteries. Summary of the invention

[0004] In an exemplary embodiment of the present application, a method and device for determining the number of stops on a traffic trunk line are provided. The determined number of stops has a high degree of matching with the trunk line, and is used to evaluate the green wave effect of the trunk line more accurately and comprehensively.

[0005] According to a first aspect of an exemplary embodiment, a method for determining the number of stops on a traffic artery is provided, the method comprising at least the following steps:

[0006] Obtaining vehicle passing data of each intersection included in the coordinated direction of the target trunk line; wherein two adjacent intersections constitute a road section;

[0007] For each road section, the vehicle passing data set at the second moment of the road section's exit intersection is applied to filter the vehicle passing data at the first moment of the road section's entry intersection, and determine the first vehicle passing data set that passes through the entry intersection and the exit intersection; wherein the second moment is determined based on the first moment, the signal cycle of the road section in the coordinated direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of a vehicle without stopping when passing through the road section;

[0008] Determine at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or passing intersections in each driving trajectory are different;

[0009] The number of stops on each driving trajectory included in the target trunk line is determined.

[0010] According to a second aspect of an exemplary embodiment, there is provided a device for determining the number of stops on a traffic artery, the device comprising a data transmission unit and a processor;

[0011] The data transmission unit is configured to perform:

[0012] Obtaining vehicle passing data of each intersection included in the coordinated direction of the target trunk line; wherein two adjacent intersections constitute a road section;

[0013] The processor is configured to execute:

[0014] For each road section, the vehicle passing data set at the second moment of the road section's exit intersection is applied to filter the vehicle passing data at the first moment of the road section's entry intersection, and determine the first vehicle passing data set that passes through the entry intersection and the exit intersection; wherein the second moment is determined based on the first moment, the signal cycle of the road section in the coordinated direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of a vehicle without stopping when passing through the road section;

[0015] Determine at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or passing intersections in each driving trajectory are different;

[0016] The number of stops on each driving trajectory included in the target trunk line is determined.

[0017] According to a third aspect of an exemplary embodiment, there is provided a device for determining the number of stops on a traffic artery, the device comprising:

[0018] The intersection determination unit is used to: obtain the vehicle passing data of each intersection included in the coordination direction of the target trunk line; wherein two adjacent intersections constitute a road section;

[0019] The data processing unit is used to: for each road section, apply the vehicle passing data set at the second moment of the road section's exit intersection to filter the vehicle passing data at the first moment of the road section's entry intersection, and determine the first vehicle passing data set that passes through the entry intersection and the exit intersection; wherein the second moment is determined based on the first moment, the signal cycle of the road section in the coordination direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of the vehicle when passing through the road section without stopping;

[0020] The trajectory determination unit is used to determine at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entry intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or passing intersections in each driving trajectory are different;

[0021] The stop number determination unit is used to determine the stop number on each driving track included in the target trunk line.

[0022] According to a fourth aspect of the exemplary implementation, a computer storage medium is provided, in which computer program instructions are stored. When the instructions are executed on a computer, the computer executes the method for determining the number of stops on a traffic artery as described in the first aspect.

[0023] In the embodiment of the present application, the coordination direction of the target trunk line is taken into consideration. The vehicle passing data of each intersection included in the coordination direction of the target trunk line is first obtained. For each road section, the vehicle passing data set at the second moment of the exit intersection of the road section is applied to filter the vehicle passing data at the first moment of the entry intersection of the road section to determine the first vehicle passing data set that passes through the entry intersection and the exit intersection; according to the vehicle passing data set and the first vehicle passing data set corresponding to each road section, at least one driving track included in the target trunk line is determined. Such a design can determine different driving tracks, and the driving tracks are closer to the actual driving conditions, and then the number of stops on each driving track included in the target trunk line is determined with the driving track as the granularity. Not only the number of stops on the road section is considered, but also the vehicles that may be included in different tracks may be different. Therefore, the number of stops is determined for each driving track in the coordination direction of the target trunk line, which has a higher matching degree with the target trunk line, and is used to evaluate the green wave effect of the trunk line more accurately and comprehensively. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. 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 creative labor.

[0025] Figure 1 A schematic diagram of a traffic artery provided by an embodiment of the present application is exemplarily shown;

[0026] Figure 2 A flowchart of a method for determining the number of stops on a traffic artery provided by an embodiment of the present application is exemplarily shown;

[0027] Figure 3 A schematic diagram showing vehicle passing data of a road section A provided in an embodiment of the present application is exemplified;

[0028] Figure 4 A flowchart of a method for determining a target associated vehicle provided by an embodiment of the present application is exemplarily shown;

[0029] Figure 5A schematic diagram showing vehicle passing data of a road section A and a road section B provided in an embodiment of the present application is exemplified;

[0030] Figure 6 A schematic diagram of a driving trajectory provided by an embodiment of the present application is exemplarily shown;

[0031] Figure 7 A flowchart of a method for determining the number of stops of a driving trajectory provided by an embodiment of the present application is exemplarily shown;

[0032] Figure 8 A signaling flow chart of a method for determining the number of stops on a traffic artery provided in an embodiment of the present application is exemplarily shown;

[0033] Fig. 9 The schematic diagram of the structure of a device for determining the number of stops on a traffic artery provided in an embodiment of the present application is exemplarily shown;

[0034] Fig.10 A schematic diagram of the structure of a device for determining the number of stops on a traffic artery provided in an embodiment of the present application is exemplified. DETAILED DESCRIPTION

[0035] 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.

[0036] For ease of understanding, the terms involved in the embodiments of the present application are explained below:

[0037] (1) Signal cycle: For an intersection, the signal cycle refers to the total time required for the signal lights of each phase of the intersection to be displayed in turn, or the time required from the start of a green light of a main phase to the next start of the green light. In the embodiment of the present application, the signal cycle of a road section refers to the maximum value of the signal cycle of the upstream intersection (entry intersection) and the signal cycle of the downstream intersection (exit intersection).

[0038] (2) Zero stop time: the time a vehicle travels through a road section without stopping. The zero stop time threshold is used to indicate the minimum value of the travel time.

[0039] (3) Coordination direction: For an intersection, vehicles can go straight, turn left, turn right, or make a U-turn. For a fixed trunk line, the coordination direction at an intersection is fixed. For example, if the coordination direction is from east to west, the downstream intersection of intersection A is intersection B on its west side, not intersection C on its northwest side (which may be the intersection reached by turning right at intersection A).

[0040] In the field of traffic control, the number of stops on main roads is an important indicator for evaluating the green wave effect of main roads. Therefore, accurately determining the number of stops on main roads can improve the accuracy of evaluating the green wave effect of main roads.

[0041] In the related technology, tuning engineers or traffic police usually drive on-site for inspection and record the number of stops. This method is relatively accurate, but it consumes manpower and material resources, and the inspection track is limited. In addition, if the number of stops of vehicles on the road section between two intersections is added up, the number of stops obtained is only a simple combination of the number of stops on the road section. Different vehicles on different sections may also belong to different traffic arteries. In this case, the matching degree between the obtained number of stops and the arteries is low, and it is not very accurate to evaluate the green wave effect of the arteries.

[0042] To this end, the embodiment of the present application provides a method for determining the number of stops on a traffic artery, in which the coordinated direction of the artery is taken into account, and for each road section in the coordinated direction, the vehicle passing data set at the second moment of exiting the intersection is applied, and the vehicle passing data at the first moment of entering the intersection is screened to determine the first vehicle passing data set that passes through the entrance and exit intersections, and then the at least one driving trajectory included in the target artery is determined based on the vehicle passing data set at the entrance corresponding to each road section and the first vehicle passing data set, and then the number of stops on each driving trajectory included in the target artery is determined with the trajectory as the granularity. In this process, the driving trajectory of the vehicle is taken into account, and compared with the related art that simply adds up the number of stops of different vehicles in different sections, the driving trajectory of different vehicles in a time period is taken into account, so the number of stops determined in this way is more consistent with the artery and more meaningful for reference.

[0043] After introducing the design ideas of the embodiments of the present application, the following briefly introduces the application scenarios to which the technical solutions of the embodiments of the present application can be applied. It should be noted that the application scenarios introduced below are only used to illustrate the embodiments of the present application and are not limited. In specific implementation, the technical solutions provided by the embodiments of the present application can be flexibly applied according to actual needs.

[0044] refer to Figure 1 , shows a schematic diagram of a traffic trunk line, where, assuming that the coordination direction of the trunk line is from west to east, the trunk line shows 4 sections including 5 intersections, and the intersections 6 and 7 in the south and north directions do not belong to the trunk line, and there is no need to count the number of stops on sections E and F.

[0045] To further illustrate the technical solution provided by the embodiment of the present application, this is described in detail below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiment of the present application provides the method operation steps shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative labor. In the 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 embodiment of the present application.

[0046] Combine the following Figure 1 The application scenario shown is shown in Figure 2 A flow chart of determining the number of stops on a traffic artery is shown. The method can be executed by a device for determining the number of stops on a traffic artery. The device can be an electronic device or a server with data processing capabilities. The electronic device or server can transmit data with an electronic intelligent traffic violation monitoring management system to obtain vehicle passing data, and then execute the method in the embodiment of the present application based on the vehicle passing data. Figure 1 , the technical solution provided in the embodiments of the present application is described.

[0047] S201: The device obtains the vehicle passing data of each intersection included in the coordinated direction of the target trunk line.

[0048] Among them, two adjacent intersections constitute a road section.

[0049] S202: For each road section, the device applies the vehicle passing data set at the second moment of the exit intersection of the road section to filter the vehicle passing data at the first moment of the entrance intersection of the road section, and determines the first vehicle passing data set that passes through the entrance intersection and the exit intersection.

[0050] Among them, the time difference between the second moment and the first moment is determined according to the signal cycle of the road section in the coordinated direction and the zero stop time threshold; the zero stop time threshold is used to represent the minimum driving time of the vehicle when passing through the road section without stopping.

[0051] S203: The device determines at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set.

[0052] The vehicles or intersections passed through in each driving trajectory are different.

[0053] S204: The device determines the number of stops on each driving track included in the target trunk line.

[0054] In the embodiment of the present application, the coordination direction of the target trunk line is taken into consideration. The vehicle passing data of each intersection included in the coordination direction of the target trunk line is first obtained. For each road section, the vehicle passing data set at the second moment of the exit intersection of the road section is applied to filter the vehicle passing data at the first moment of the entry intersection of the road section to determine the first vehicle passing data set that passes through the entry intersection and the exit intersection; according to the vehicle passing data set and the first vehicle passing data set corresponding to each road section, at least one driving track included in the target trunk line is determined. Such a design can determine different driving tracks, and the driving tracks are closer to the actual driving conditions, and then the number of stops on each driving track included in the target trunk line is determined with the driving track as the granularity. Not only the number of stops on the road section is considered, but also the vehicles that may be included in different tracks may be different. Therefore, the number of stops is determined for each driving track in the coordination direction of the target trunk line, which has a higher matching degree with the target trunk line, and is used to evaluate the green wave effect of the trunk line more accurately and comprehensively.

[0055] In S201, the target trunk line may be a road section of key concern, for example, a road section where a large number of tickets are generated or a road section including a school. In the embodiment of the present application, the target trunk line is any pre-set trunk line. The device obtains road network data from the electronic intelligent traffic violation monitoring management system or other data storage device, and obtains each intersection included in the coordination direction of the target trunk line according to the road network data.

[0056] See also Figure 1 In the example of , the target trunk line includes 4 sections including 5 intersections.

[0057] In relation to S202, the following takes any section of the target trunk line as an example to explain the process of determining the vehicles that enter and exit the intersection of the section:

[0058] The vehicle passing data can be called a vehicle passing record, which may include a license plate number, a driving direction, etc. Vehicles whose license plates are not recognized or are not accurately recognized are not included in the vehicle passing data. Taking section A as an example, the entrance to section A is intersection 1, and the exit from section A is intersection 2. In this example, section A is the initial section of the target trunk line. The vehicle passing data set of intersection 1 at the first moment T1 is recorded as J1, and the vehicle passing data set of intersection 2 at the second moment T2 is recorded as J2. By applying set J1 to filter set J2, the vehicle passing data set that passes through intersection 1 and intersection 2 can be determined, which is recorded as the first vehicle passing data set J1-2. For example, there are 10 vehicles in the vehicle passing data of intersection 1, represented by V1-V10 respectively. They are compared one by one in the vehicle passing data set J2 of intersection 2 to find those vehicles that have passed both intersection 1 and intersection 2, such as vehicles V1-V8. The vehicle passing data set corresponding to vehicles V1-V8 here is the filtered vehicle passing data set. In the filtered vehicle passing data set, there may still be vehicle passing data that does not meet the expiration requirements. Therefore, these vehicle passing data that do not meet the timeliness requirements are filtered to obtain the first vehicle passing data set.

[0059] Optionally, the reason for the generation of the vehicle passing data that does not meet the invalidation requirements may be data errors caused by a failure of the electronic intelligent traffic violation monitoring management system. The vehicle passing data that does not meet the invalidation requirements meets at least one of the following conditions:

[0060] Condition 1: The exit time of a road section is less than the entry time.

[0061] For example, T2-T1≤0.

[0062] Condition 2: The average speed of a road section is greater than the speed limit v of a road section lim The average speed is the ratio of the length of a road section to the difference between the exit time and the entry time of a road section.

[0063] For example, l / (T2-T1)>v lim ,v lim It can reach 120km / h.

[0064] Therefore, the screened vehicle passing data set may be filtered according to the timeliness requirement to obtain the first vehicle passing data set.

[0065] Figure 3A schematic diagram of vehicle passing data of a road section A provided in an embodiment of the present application, wherein there are 10 vehicles passing through intersection 1, namely V1-V10, and 8 vehicles passing through intersection 2, namely V1-V8, that is, vehicles V9 and V10 did not pass through intersection 2, and may have entered a destination such as a residential area in road section A. Vehicle V8 that does not meet the timeliness requirement is further filtered out, and the first vehicle passing data set is obtained, which is the vehicle passing data of vehicles V1-V7.

[0066] In the above embodiment, the second moment T2 is determined according to the first moment T1, the signal cycle C of the road section in the coordination direction, and the zero stop time threshold t. Exemplarily, T2=T1+C+t, the signal cycle C can be adjusted. In the embodiment of the present application, the signal cycle C can take the maximum value of the signal cycle of intersection 1 and the signal cycle of intersection 2. In a specific example, the signal cycle C can be 120s. Optionally, the zero stop time can represent the driving time of the vehicle without stopping when passing through the road section, and the zero stop time threshold can represent the minimum value of the driving time, such as 30s.

[0067] Optionally, the zero parking time threshold is calculated as follows:

[0068]

[0069] Among them, t is the zero-stop time threshold, which can be 30s; l is the length of the section, which can be the distance between the two intersections included in the section; a is the set vehicle acceleration, including the starting acceleration and braking acceleration. In actual application, the two can take the same acceleration value or different acceleration data. Here, 6m / s 2 v1 is the configured speed of the vehicles on the road section when the green wave is passing (for example, 45 km / h) or the speed obtained by the actual speed statistics of the vehicles on the road section (for example, the average speed of the vehicles V1-V10 is calculated), v2 is the static speed of the vehicle, which can be 0 km / h, and t0 is the static time after the vehicle stops, which can be 3 seconds. The values ​​here are all examples and do not form a specific limitation.

[0070] In the above example, the initial section A is used as an example for explanation. If the section is a non-initial section of the target trunk line, there is also a situation where vehicles that pass through intersection 2 and do not enter intersection 3 may enter the residential area or other destinations on section B, and such vehicles are not counted as passing vehicles on section B; in addition, there may be vehicles that enter from the middle of section A, and such vehicles do not pass through intersection 1. Therefore, in order to improve the accuracy of determining the number of stops in the embodiment of the present application, when the section is a non-initial section of the target trunk line, after performing the above screening and filtering operations, a "relay" design is added, that is, finding new vehicles that come out from the middle of the trunk line.

[0071] For road section B, after screening and filtering operations, it is found that the vehicles that pass through intersection 2 and intersection 3 are V1-V5, and vehicles V6 and V7 pass through intersection 2 but not intersection 3. At this time, refer to Figure 4 , these relay vehicles (called associated vehicles) are found through steps S401-S403, and the finally determined target associated vehicles are added to the first passing vehicle data set.

[0072] S401: The device determines a second set of vehicle passing data that has passed the entrance intersection but not the exit intersection based on the vehicle passing data set of the entrance intersection of the road section and the first set of vehicle passing data.

[0073] Continuing with the above example, it is determined that the vehicles that passed through intersection 2 but did not pass through intersection 3 are V6 and V7. Therefore, the second vehicle passing data set in this example is recorded as the vehicle passing data set of vehicle V6 and vehicle V7.

[0074] S402: For each vehicle in the second vehicle passing data set, the device searches for at least one associated vehicle in the vehicle passing data set entering the intersection, the vehicle having a time difference with the vehicle passing the exit intersection that is less than a first set time length.

[0075] Taking vehicle V6 as an example, we search the vehicle data set at intersection 2 and find that the time difference between the time when vehicle V11 passes intersection 2 and the time when vehicle V6 passes intersection 2 is 2 seconds, which is less than the first set time length of 3 seconds. In the same way, we find all vehicles that meet this logic and call these vehicles associated vehicles.

[0076] S403: The device selects a target associated vehicle from at least one associated vehicle, and adds the vehicle passing data of the target associated vehicle to the first vehicle passing data set.

[0077] Optionally, a related vehicle with the smallest time difference is selected as the target related vehicle of the vehicle. In this example, if vehicle V11 is the related vehicle with the smallest time difference, the target related vehicle of vehicle V6 is determined to be V11. Using the same method, the target related vehicle of vehicle V7 can be determined to be vehicle V12.

[0078] Figure 5 A schematic diagram of vehicle passing data of road section A and road section B provided in an embodiment of the present application.

[0079] In S203, the vehicle passing data set of the next road section entering the intersection is the first vehicle passing data set of the previous road section, that is, the vehicle passing data of the previous road section exiting the intersection is used as a reference each time to execute the processing of the vehicle passing data of the next road section.

[0080] In order to make the determined number of stops better match the main line, after obtaining the vehicle passing data set of the entrance intersection and the vehicle passing data set of the exit intersection of each section, the vehicle passing data set of the entrance intersection corresponding to each section is processed in chronological order to obtain at least one driving trajectory included in the target main line.

[0081] Still taking the above example, Figure 6 A schematic diagram of a driving trajectory provided for an embodiment of the present application, in which it can be seen that the driving trajectories are divided into two categories, the first category of trajectories is the driving trajectory formed by the same vehicle, and the second category of trajectories is the driving trajectory formed by different vehicles. In this example, the first category of trajectories includes five cases, where the same vehicle is vehicles V1-V5; the second category of trajectories includes two cases, namely the driving trajectory formed by vehicles V6 and V11, and the driving trajectory formed by vehicles V7 and V12. In order to distinguish, a label can also be set for different driving trajectories. The label can be the number of vehicles included in the driving trajectory. For example, the label of each driving trajectory in the case of the first category of trajectories is 1, and the label of each driving trajectory in the case of the second category of trajectories is 2. In this way, the parking situation of the trunk line can be more targeted.

[0082] In S204, for different driving trajectories under different categories, the number of stops on each driving trajectory is determined. For one of the driving trajectories, refer to Figure 7 , the number of parking times can be determined through steps S701 to S702:

[0083] S701: For each road section on each trajectory, if the time difference between the exit time and the entry time of the vehicle on the road section is greater than a second set time length, the device determines that the vehicle is parked on the road section.

[0084] For the driving trajectory formed by the above-mentioned vehicles V6 and V11, the road section traveled by vehicle V6 is road section A, and the road section traveled by vehicle V11 is road section B. The number of stops a of vehicle V6 on road section A and the number of stops b of vehicle V11 on road section B are counted respectively. The process of determining the number of stops a is used as an example for explanation:

[0085] If the time difference between the time when the vehicle V6 passes the intersection 2 and the time when it passes the intersection 1 is greater than the second set time length, for example, 30 seconds, it can be determined that the vehicle V6 stops on the road section A.

[0086] S702: The device adds up the number of stops on each road section included in each driving trajectory as the number of stops on the driving trajectory.

[0087] Among them, the number of stops a is 1, the number of stops b is 1, and the number of stops of the driving trajectory in this example is 2.

[0088] Using the same method, different driving trajectories under different categories can be obtained, and the number of stops on each driving trajectory can be determined respectively.

[0089] In order to better assist manual work in making other arrangements, the number of stops in different tracks may also be added together to obtain a total number of stops.

[0090] In the embodiment of the present application, different driving trajectories can be determined, and the driving trajectories are closer to the actual driving conditions. For example, some driving trajectories only include the driving conditions of one vehicle, and some driving trajectories include the driving conditions of at least two vehicles. Therefore, the number of stops on each driving trajectory included in the target trunk line can be determined with the driving trajectory as the granularity, which can better describe the parking conditions of the vehicles. The number of stops is determined for each driving trajectory in the coordinated direction of the target trunk line, which has a higher matching degree with the target trunk line. Compared with the single data caused by simply determining the number of stops on any section in the prior art, the green wave effect used to evaluate the trunk line is more accurate and comprehensive.

[0091] In order to make the counting scheme of this application more perfect, refer to Figure 8 , is a signaling flow chart of a method for determining the number of stops on a traffic artery provided in an embodiment of the present application, and the device is described by taking an electronic device having a data processing function as an example, Figure 8 At least the following steps are included:

[0092] S801: The electronic intelligent traffic violation monitoring management system sends the vehicle passing data of each intersection included in the target trunk line to the electronic device.

[0093] S802: The electronic device determines at least one driving track included in the target trunk line and the number of stops on each driving track according to the vehicle passing data at each intersection.

[0094] S803: The electronic device sends the number of parking times to the control terminal.

[0095] S804: The control terminal displays the number of parking times.

[0096] Optionally, the control terminal can display not only the number of parking times, but also which vehicles have stopped on which road section and how many times.

[0097] The control terminal may be a handheld terminal of a tuning engineer or traffic policeman or a display terminal in an office area.

[0098] In the embodiment of the present application, the tuning engineer or traffic police can better manage the parking situation of each section of the target trunk line by determining the number of stops through electronic equipment.

[0099] like Fig. 9 As shown, based on the same inventive concept, an embodiment of the present application provides a device for determining the number of stops on a traffic artery, including an intersection determination unit 91, a data processing unit 92, a trajectory determination unit 93 and a number of stops determination unit 94.

[0100] The intersection determination unit 91 is used to: determine each intersection included in the coordination direction of the target trunk line; wherein two adjacent intersections constitute a road section;

[0101] The data processing unit 92 is used to: for each road section, apply the vehicle passing data set at the second moment of the exit intersection of the road section to filter the vehicle passing data at the first moment of the entrance intersection of the road section, and determine the first vehicle passing data set that passes through the entrance intersection and the exit intersection; wherein the second moment is determined according to the first moment, the signal cycle of the road section in the coordination direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of the vehicle when passing through the road section without stopping;

[0102] The track determination unit 93 is used to determine at least one driving track included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or the passing intersections in each driving track are different;

[0103] The stop number determination unit 94 is used to determine the stop number on each driving track included in the target trunk line.

[0104] In a possible implementation manner, if the road section is a non-initial road section of the target trunk line, the device further includes an updating unit, which is used to:

[0105] Determine a second vehicle passing data set that passes through the entrance intersection and does not pass through the exit intersection based on the vehicle passing data set of the road section and the first vehicle passing data set;

[0106] For each vehicle in the second vehicle passing data set, searching in the vehicle passing data set entering the intersection for at least one associated vehicle whose time difference with the vehicle passing the entering intersection is less than a first set time length;

[0107] A target associated vehicle is selected from the at least one associated vehicle, and the vehicle passing data of the target associated vehicle is added to the first vehicle passing data set.

[0108] In a possible implementation manner, the updating unit is specifically configured to:

[0109] Select an associated vehicle with the smallest time difference as the target associated vehicle of the vehicle.

[0110] In a possible implementation manner, the vehicle passing data set of the entrance to the next road section is the first vehicle passing data set of the vehicle passing data of the previous road section;

[0111] The trajectory determination unit 93 is specifically used for:

[0112] According to the time sequence, the vehicle passing data sets of the entrance intersections corresponding to the respective road sections are processed to obtain at least one driving track included in the target trunk line.

[0113] In a possible implementation manner, the parking number determination unit 94 is specifically configured to:

[0114] For each road section on each trajectory, if the time difference between the exit time and the entry time of the vehicle on the road section is greater than a second set time length, it is determined that the vehicle is parked on the road section;

[0115] The number of stops on each road section included in each driving trajectory is added up to obtain the number of stops on the driving trajectory.

[0116] In a possible implementation manner, the data processing unit 92 is specifically configured to:

[0117] For each road section, the vehicle passing data set of the road section exiting the intersection at the second moment is used to filter the vehicle passing data of the road section entering the intersection at the first moment, so as to obtain the filtered vehicle passing data set that passes through the intersection and the exiting intersection;

[0118] In the filtered vehicle passing data set, the vehicle passing data that does not meet the timeliness requirement is filtered out to obtain the first vehicle passing data set.

[0119] In a possible implementation manner, the vehicle passing data that does not meet the timeliness requirement meets at least one of the following conditions:

[0120] The exit time on a road section is less than the entry time; or

[0121] The average speed of driving on a road section is greater than the speed limit of the road section; wherein the average speed is the ratio of the length of a road section to the difference between the exit time and the entry time of a road section.

[0122] In a possible implementation manner, the second moment is the sum of the first moment, the signal period of the road section, and the zero stop time threshold, and the data processing unit 92 is specifically configured to determine the zero stop time threshold in the following manner:

[0123]

[0124] Among them, t is the zero stop time threshold, l is the length of the road section, a is the set vehicle acceleration, v1 is the configured speed of the vehicle on the road section when passing through the green wave or the speed obtained according to the actual speed statistics of the vehicles running on the road section, v2 is the vehicle static speed, and t0 is the static time after the vehicle stops.

[0125] Since the device is the device in the method in the embodiment of the present application, and the principle of solving the problem by the device is similar to that of the method, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0126] like Fig.10 As shown, based on the same inventive concept, an embodiment of the present application provides a device for determining the number of stops on a traffic artery, the device comprising: a data transmission unit 1001 and a processor 1002;

[0127] The data transmission unit 1001 is configured to execute:

[0128] Obtaining vehicle passing data of each intersection included in the coordinated direction of the target trunk line; wherein two adjacent intersections constitute a road section;

[0129] The processor 1002 is configured to execute:

[0130] For each road section, the vehicle passing data set at the second moment of the road section's exit intersection is applied to filter the vehicle passing data at the first moment of the road section's entry intersection, and determine the first vehicle passing data set that passes through the entry intersection and the exit intersection; wherein the second moment is determined based on the first moment, the signal cycle of the road section in the coordinated direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of a vehicle without stopping when passing through the road section;

[0131] Determine at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or passing intersections in each driving trajectory are different;

[0132] The number of stops on each driving trajectory included in the target trunk line is determined.

[0133] In a possible implementation manner, if the road segment is a non-initial road segment of the target trunk line, the processor 1002 is further configured to execute:

[0134] Determine a second vehicle passing data set that passes through the entrance intersection and does not pass through the exit intersection based on the vehicle passing data set of the road section and the first vehicle passing data set;

[0135] For each vehicle in the second vehicle passing data set, searching in the vehicle passing data set entering the intersection for at least one associated vehicle whose time difference with the vehicle passing the entering intersection is less than a first set time length;

[0136] A target associated vehicle is selected from the at least one associated vehicle, and the vehicle passing data of the target associated vehicle is added to the first vehicle passing data set.

[0137] In a possible implementation, the processor 1002 is specifically configured to execute:

[0138] Select an associated vehicle with the smallest time difference as the target associated vehicle of the vehicle.

[0139] In a possible implementation manner, the vehicle passing data set of the entrance to the next road section is the first vehicle passing data set of the vehicle passing data of the previous road section;

[0140] The processor 1002 is specifically configured to execute:

[0141] According to the time sequence, the vehicle passing data sets of the entrance intersections corresponding to the respective road sections are processed to obtain at least one driving track included in the target trunk line.

[0142] In a possible implementation, the processor 1002 is specifically configured to execute:

[0143] For each road section on each trajectory, if the time difference between the exit time and the entry time of the vehicle on the road section is greater than a second set time length, it is determined that the vehicle is parked on the road section;

[0144] The number of stops on each road section included in each driving trajectory is added up to obtain the number of stops on the driving trajectory.

[0145] In a possible implementation, the processor 1002 is specifically configured to execute:

[0146] For each road section, the vehicle passing data set of the road section exiting the intersection at the second moment is used to filter the vehicle passing data of the road section entering the intersection at the first moment, so as to obtain the filtered vehicle passing data set that passes through the intersection and the exiting intersection;

[0147] In the filtered vehicle passing data set, the vehicle passing data that does not meet the timeliness requirement is filtered out to obtain the first vehicle passing data set.

[0148] In a possible implementation manner, the vehicle passing data that does not meet the timeliness requirement meets at least one of the following conditions:

[0149] The exit time on a road section is less than the entry time; or

[0150] The average speed of driving on a road section is greater than the speed limit of the road section; wherein the average speed is the ratio of the length of a road section to the difference between the exit time and the entry time of a road section.

[0151] In a possible implementation manner, the second moment is the sum of the first moment, the signal period of the road section, and the zero stop time threshold, and the processor 1002 is specifically configured to execute: determining the zero stop time threshold in the following manner:

[0152]

[0153] Among them, t is the zero stop time threshold, l is the length of the road section, a is the set vehicle acceleration, v1 is the configured speed of the vehicle on the road section when passing through the green wave or the speed obtained according to the actual speed statistics of the vehicles running on the road section, v2 is the vehicle static speed, and t0 is the static time after the vehicle stops.

[0154] An embodiment of the present application also provides a computer storage medium, in which computer program instructions are stored. When the instructions are executed on a computer, the computer executes the steps of the above-mentioned method for determining the number of stops on a traffic artery.

[0155] 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 adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0156] 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 box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes 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 1A device that provides the functions specified in a block or multiple blocks.

[0157] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate 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 A function specified in one or more boxes.

[0158] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0159] Obviously, those skilled in the art can 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 also intended to include these modifications and variations.

Claims

1. A method for determining the number of stops on a traffic artery, characterized in that: include: Obtaining vehicle passing data of each intersection included in the coordinated direction of the target trunk line; wherein two adjacent intersections constitute a road section; For each road section, the vehicle passing data set at the second moment of the exit intersection of the road section is applied to filter the vehicle passing data at the first moment of the entrance intersection of the road section to determine the first vehicle passing data set that passes the entrance intersection and the exit intersection; wherein the second moment is determined according to the first moment, the signal cycle of the road section in the coordinated direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of the vehicle when passing the road section without stopping; Determine at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or passing intersections in each driving trajectory are different; The number of stops on each driving trajectory included in the target trunk line is determined.

2. The method according to claim 1, characterized in that If the road section is a non-initial road section of the target trunk line, the method further includes: Determine a second vehicle passing data set that passes through the entrance intersection and does not pass through the exit intersection based on the vehicle passing data set of the entrance intersection of the road section and the first vehicle passing data set; For each vehicle in the second vehicle passing data set, searching in the vehicle passing data set of the entry intersection for at least one associated vehicle whose time difference with the vehicle passing the entry intersection is less than a first set time length; A target associated vehicle of the vehicle is selected from the at least one associated vehicle, and the vehicle passing data of the target associated vehicle is added to the first vehicle passing data set.

3. The method according to claim 2, characterized in that The selecting a target associated vehicle of the vehicle from the at least one associated vehicle comprises: An associated vehicle with the smallest time difference is selected as the target associated vehicle of the vehicle.

4. The method according to claim 1 or 2, characterized in that: The vehicle passing data set of the entrance to the next road section is the first vehicle passing data set of the vehicle passing data of the previous road section; The determining of at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set comprises: The vehicle passing data sets of the entrance intersections corresponding to the respective road sections are processed in chronological order to obtain at least one driving track included in the target trunk line.

5. The method according to claim 1, characterized in that: The determining the number of stops on each driving track included in the target trunk line comprises: For each road section on each trajectory, if the time difference between the exit time and the entry time of the vehicle on the road section is greater than a second set time length, it is determined that the vehicle is parked on the road section; The number of stops on each road section included in each driving trajectory is added up to obtain the number of stops on the driving trajectory.

6. The method according to claim 1, characterized in that The method of filtering the vehicle passing data at the first moment of entering the intersection of the road section by using the vehicle passing data set at the second moment of the exit intersection of the road section for each road section, and determining the first vehicle passing data set that passes the entrance intersection and the exit intersection, comprises: For each road section, the vehicle passing data set of the exit intersection of the road section at the second moment is used to filter the vehicle passing data of the entrance intersection of the road section at the first moment, so as to obtain the filtered vehicle passing data set that passes through the entrance intersection and the exit intersection; In the filtered vehicle passing data set, the vehicle passing data that does not meet the timeliness requirement is filtered out to obtain the first vehicle passing data set.

7. The method according to claim 6, characterized in that The vehicle passing data that does not meet the timeliness requirement meets at least one of the following conditions: The exit time on a road section is less than the entry time; or The average speed of traveling on the road section is greater than the speed limit of the road section; wherein the average speed is the ratio of the length of the road section to the difference between the exit time and the entry time of the road section.

8. The method according to any one of claims 1 to 3 and 5 to 6, characterized in that: The second moment is the sum of the first moment, the signal period of the road section, and a zero-stop time threshold. The method further includes: determining the zero-stop time threshold in the following manner: Among them, t is the zero-stop time threshold, l is the length of the road section, a is the set vehicle acceleration, v1 is the configured speed of the vehicle on the road section under the green wave condition or the speed obtained based on the actual speed statistics of the vehicles running on the road section, v2 is the vehicle static speed, and t0 is the static time after the vehicle stops.

9. A device for determining the number of stops on a traffic artery, characterized in that: including a data transmission unit and a processor; Wherein, the data transmission unit is configured to execute: Obtaining vehicle passing data of each intersection included in the coordinated direction of the target trunk line; wherein two adjacent intersections constitute a road section; The processor is configured to perform: For each road section, the vehicle passing data set at the second moment of the exit intersection of the road section is applied to filter the vehicle passing data at the first moment of the entrance intersection of the road section to determine the first vehicle passing data set that passes the entrance intersection and the exit intersection; wherein the second moment is determined according to the first moment, the signal cycle of the road section in the coordinated direction, and the zero stop time threshold; the zero stop time threshold is used to represent the minimum value of the driving time of the vehicle when passing the road section without stopping; Determine at least one driving trajectory included in the target trunk line according to the vehicle passing data set of the entrance intersection corresponding to each road section and the first vehicle passing data set; wherein the passing vehicles or passing intersections in each driving trajectory are different; The number of stops on each driving trajectory included in the target trunk line is determined.

10. The device according to claim 9, characterized in that If the road section is a non-initial road section of the target trunk line, the processor is further configured to execute: Determine a second vehicle passing data set that passes through the entrance intersection and does not pass through the exit intersection based on the vehicle passing data set of the entrance intersection of the road section and the first vehicle passing data set; For each vehicle in the second vehicle passing data set, searching in the vehicle passing data set at the entrance intersection for at least one associated vehicle whose time difference with the vehicle passing the exit intersection is less than a first set time length; A target associated vehicle of the vehicle is selected from the at least one associated vehicle, and the vehicle passing data of the target associated vehicle is added to the first vehicle passing data set.

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