Traffic service deployment method, device, equipment and medium
By determining clustering event points and areas of interest in the road network map, calculating service scores, and dynamically adjusting the deployment of traffic management personnel, the problem of inefficient traffic management in the existing technology is solved and more efficient traffic service deployment is achieved.
Patent Information
- Application Number
- CN202310854923.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-07-12
- Publication Date
- 2025-01-17
AI Technical Summary
The existing transportation service deployment plan relies on human experience or fixed deployment rules, and cannot effectively respond to changes in traffic scenarios, resulting in inefficient traffic management.
By determining clustered event points in the road network map, dividing the areas of interest according to the event type and occurrence location, calculating the service scores and allocating duty areas and time to dynamically adjust the deployment of traffic management personnel.
It improves traffic management efficiency, can allocate limited human resources more reasonably, adapt to changes in traffic scenarios, and improves the efficiency of traffic order maintenance and accident handling.
Smart Images
Figure CN119323311A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of rail transit technology, and in particular to a method, device, equipment and medium for deploying transportation services. Background Art
[0002] With the construction of smart cities, the scale of traffic network is constantly expanding. In order to ensure road traffic safety, a large number of traffic control personnel need to be deployed on duty. By assigning corresponding duty areas and duty times to traffic control personnel, they can perform tasks such as maintaining order, handling accidents, and directing traffic to maintain traffic safety.
[0003] The current duty deployment scheme is mainly formulated based on human experience or fixed deployment rules. However, the traffic scenarios in actual applications are not fixed and will change due to external factors such as events and road maintenance. How to reasonably allocate duty areas and duty times for limited manpower to maximize traffic control efficiency is a pain point in current duty deployment. Summary of the invention
[0004] The embodiment of the present application provides a traffic service deployment method, device, equipment and medium, which are used to reasonably allocate duty areas and duty times for duty objects to improve traffic management efficiency.
[0005] To achieve the above purpose, the technical solution of the embodiment of the present application is implemented as follows:
[0006] In a first aspect, an embodiment of the present application provides a method for deploying traffic services, the method comprising:
[0007] In response to the deployment instruction, determine the clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in a road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents the location where the corresponding event occurs in the road network map;
[0008] For any preset time period, a high-incidence sub-period of each preset type of event in the preset time period is determined according to the number of clustered event points in each sub-period of the preset time period, and the service score of the sub-period is determined according to the duty time of the service object in the area of interest of any sub-period; wherein the area of interest is determined according to the location of the clustered event points in the sub-period;
[0009] For any preset time period, the total service score of each sub-time period is determined according to the high-incidence sub-time period within the preset time period and the service score of each sub-time period, and the duty area and duty time within the sub-time period corresponding to the total service score are allocated to the service object according to the total service score.
[0010] In some possible embodiments, determining the clustered event points of the road network map in each preset time period includes:
[0011] Acquire event data of multiple preset types generated in a historical period; wherein any event data includes the occurrence time and location of the event of the preset type;
[0012] For any sub-period under any preset time period, select target event data whose occurrence time is within the sub-period from each of the event data;
[0013] For any target event data, determining a location area of the target event data in the road network map according to the occurrence location of the target event data;
[0014] All target event data in the positioning area are clustered to obtain cluster event points determined by the occurrence locations of the target event data.
[0015] In some possible embodiments, before clustering all target event data in the positioning area to obtain clustered event points determined by the occurrence locations of the target event data, the method further includes:
[0016] If the positioning area is not within the designated road section of the road network map, the target event data is discarded.
[0017] In some possible embodiments, determining the high-incidence sub-period of each preset type of event within the preset period according to the number of clustered event points in each sub-period includes:
[0018] For any preset type in any sub-period, determine the number of target event points in the sub-period; wherein the target event point is a clustered event point within the sub-period and the corresponding event includes an event of the preset type;
[0019] A high-incidence sub-period of the event of the preset type is selected from each sub-period of the preset period according to the number of the target points.
[0020] In some possible embodiments, determining the service score in any sub-period according to the service object's duty time in the area of interest in any sub-period includes:
[0021] For any preset type in any sub-period, determine the area of interest corresponding to each target event point according to the position of each target event point in the road network map in the sub-period;
[0022] For any target event point, determine the event score corresponding to the target event point according to the total duration of duty of the service object in the area of interest during the sub-period;
[0023] The service score of the preset type in the sub-period is determined according to the event score average of each target event point in the sub-period.
[0024] In some possible embodiments, determining the total service score of each sub-period according to the high-incidence sub-period within the preset time period and the service score in each sub-period includes:
[0025] For any sub-period under the preset period, a first type corresponding to the sub-period is selected from various preset types; wherein the sub-period is a high-incidence sub-period under the first type;
[0026] After adding the first weight to the service score of the first type in the sub-period, the total service score in the sub-period is determined according to the service score of each preset type in the sub-period.
[0027] In some possible embodiments, before determining the total service score in the sub-period according to the service score of each preset type in the sub-period, the method further includes:
[0028] In response to the duty focus indication, a second type representing the duty focus in the sub-period is selected from various preset types; and a second weight is added to the duty score of the second type in the sub-period.
[0029] In some possible embodiments, the multiple preset types include part or all of a first preset type representing traffic violations, a second preset type representing traffic accidents, a third preset type representing congestion, a fourth preset type representing vehicles of a specified type, and a fifth preset type representing a specified area of a road network.
[0030] In some possible embodiments, each preset time period includes Monday to Sunday, and each hour in any preset time period is a sub-time period in the preset time period.
[0031] In a second aspect, an embodiment of the present application provides a traffic service deployment device, the device comprising:
[0032] An event acquisition unit is configured to execute, in response to the deployment instruction, determining the clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in a road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents the location where the corresponding event occurs in the road network map;
[0033] The high-incidence time period unit is configured to determine, for any preset time period, a high-incidence sub-period of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of the preset time period, and determine the service score of the sub-period according to the duty time of the service object in the interest area of any sub-period; wherein the interest area is determined according to the location of the clustered event points in the sub-period;
[0034] The duty deployment unit is configured to execute, for any preset time period, determining the total duty score of each sub-time period according to the high-incidence sub-time period within the preset time period and the duty score of each sub-time period, and allocating the duty area and duty time within the sub-time period corresponding to the total duty score to the service object according to the total duty score.
[0035] In some possible embodiments, the determining of clustered event points of the road network map in each preset time period is performed, and the event acquisition unit is configured to:
[0036] Acquire event data of multiple preset types generated in a historical period; wherein any event data includes the occurrence time and location of the event of the preset type;
[0037] For any sub-period under any preset time period, select target event data whose occurrence time is within the sub-period from each of the event data;
[0038] For any target event data, determining a location area of the target event data in the road network map according to the occurrence location of the target event data;
[0039] All target event data in the positioning area are clustered to obtain cluster event points determined by the occurrence locations of the target event data.
[0040] In some possible embodiments, before clustering all target event data in the positioning area to obtain clustered event points determined by the occurrence locations of the target event data, the event acquisition unit is further configured to:
[0041] If the positioning area is not within the designated road section of the road network map, the target event data is discarded.
[0042] In some possible embodiments, the process of determining the high-incidence sub-period for each preset type of event within the preset time period according to the number of clustered event points in each sub-period is performed, and the time period confirmation unit is configured as follows:
[0043] For any preset type in any sub-period, determine the number of target event points in the sub-period; wherein the target event point is a clustered event point within the sub-period and the corresponding event includes an event of the preset type;
[0044] A high-incidence sub-period of the event of the preset type is selected from each sub-period of the preset period according to the number of the target points.
[0045] In some possible embodiments, to determine the service score in any sub-period according to the service object's duty time in the region of interest in any sub-period, the service deployment unit is configured as follows:
[0046] For any preset type in any sub-period, determine the area of interest corresponding to each target event point according to the position of each target event point in the road network map in the sub-period;
[0047] For any target event point, determine the event score corresponding to the target event point according to the total duration of duty of the service object in the area of interest during the sub-period;
[0048] The service score of the preset type in the sub-period is determined according to the event score average of each target event point in the sub-period.
[0049] In some possible embodiments, to determine the total service score of each sub-period according to the high-incidence sub-period within the preset time period and the service score in each sub-period, the service deployment unit is configured as follows:
[0050] For any sub-period under the preset period, a first type corresponding to the sub-period is selected from various preset types; wherein the sub-period is a high-incidence sub-period under the first type;
[0051] After adding the first weight to the service score of the first type in the sub-period, the total service score in the sub-period is determined according to the service score of each preset type in the sub-period.
[0052] In some possible embodiments, before determining the total service score in the sub-period according to the service score of each preset type in the sub-period, the service deployment unit is further configured to:
[0053] In response to the duty focus indication, a second type representing the duty focus in the sub-period is selected from various preset types; and a second weight is added to the duty score of the second type in the sub-period.
[0054] In some possible embodiments, the multiple preset types include part or all of a first preset type representing traffic violations, a second preset type representing traffic accidents, a third preset type representing congestion, a fourth preset type representing vehicles of a specified type, and a fifth preset type representing a specified area of a road network.
[0055] In some possible embodiments, each preset time period includes Monday to Sunday, and each hour in any preset time period is a sub-time period in the preset time period.
[0056] In a third aspect, an embodiment of the present application provides an electronic device, including a data transmission unit and a processor:
[0057] The data transmission unit is configured to: determine, in response to the deployment instruction, clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in a road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents a location where the corresponding event occurs in the road network map;
[0058] The processor is configured to: for any preset time period, determine a high-incidence sub-period of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of the preset time period, and determine the service score of the sub-period according to the duty time of the service object in the interest area of any sub-period; wherein the interest area is determined according to the location of the clustered event points in the sub-period;
[0059] For any preset time period, the total service score of each sub-time period is determined according to the high-incidence sub-time period within the preset time period and the service score of each sub-time period, and the duty area and duty time within the sub-time period corresponding to the total service score are allocated to the service object according to the total service score.
[0060] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, wherein the computer program includes program instructions, and when the program instructions are executed by a computer, the computer executes any one of the methods described in the first aspect.
[0061] In the embodiment of the present application, the clustered event points corresponding to the target area in each preset time period are determined, and the high-incidence sub-periods of each preset type of event in any preset time period are determined based on the number of clustered event points in each sub-period of any preset time period. The service score of the sub-period is determined based on the duty time of the service object in the area of interest in any sub-period. Finally, the total service score of each sub-period in the preset time period is determined based on the high-incidence sub-periods in the preset time period and the service scores of each sub-period, and the service object is allocated the duty area and duty time in the sub-period corresponding to the total score based on the service total score.
[0062] The above process scores the clustered event points generated in the target area in each preset time period, and allocates duty areas and duty events to the duty objects in each sub-time period of each preset time period according to the scoring results, so as to improve traffic management efficiency.
[0063] Other features and advantages of the present application will be described in the subsequent description, and partly become apparent from the description, or be understood by practicing the present disclosure. The purpose and other advantages of the present application can be realized and obtained by the structures specifically pointed out in the written description, claims, and drawings. BRIEF DESCRIPTION OF THE DRAWINGS
[0064] Figure 1 An overall flow chart of a traffic service deployment method provided in an embodiment of the present application;
[0065] Figure 2 A schematic diagram of a clustering event point acquisition process provided in an embodiment of the present application;
[0066] Figure 3 Schematic diagram of 5 preset types provided for the embodiment of the present application;
[0067] Figure 4 A schematic diagram of event data of various preset types provided in an embodiment of the present application;
[0068] Figure 5 A schematic diagram of obtaining event data in each sub-period provided in an embodiment of the present application;
[0069] Figure 6 A schematic diagram of the positioning area provided in the embodiment of the present application;
[0070] Figure 7 A schematic diagram of generating clustered event points provided in an embodiment of the present application;
[0071] Figure 8 A schematic diagram of removing some event data provided in an embodiment of the present application;
[0072] Fig. 9 A schematic diagram of clustered event points in each sub-period provided in an embodiment of the present application;
[0073] Fig.10 Another schematic diagram of clustered event points in each sub-time period provided in an embodiment of the present application;
[0074] Fig.11 A schematic diagram of the clustering event points corresponding to the preset types provided in the embodiment of the present application;
[0075] Fig.12 A schematic diagram of the number of clustering event points of each preset type provided in an embodiment of the present application;
[0076] Fig.13 A schematic diagram of the service score confirmation process provided in the embodiment of the present application;
[0077] Fig.14A schematic diagram of a region of interest provided in an embodiment of the present application;
[0078] Fig.15 A schematic diagram of the service score of each preset type in each sub-period provided in the embodiment of the present application;
[0079] Fig.16 A schematic diagram of adding a first weight to a service score provided in an embodiment of the present application;
[0080] Fig.17 A schematic diagram of the focus of traffic control at different time periods provided in the embodiment of the present application;
[0081] Fig.18 A schematic diagram of adding a second weight to a service score provided in an embodiment of the present application;
[0082] Fig.19 A schematic diagram of obtaining a total service score provided in an embodiment of the present application;
[0083] Fig. 20 A structural diagram of a traffic service deployment device provided in an embodiment of the present application;
[0084] Fig.21 A schematic diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0085] In order to make the purpose, technical scheme and advantages of the present application clearer, the technical scheme in the embodiment of the present application will be clearly and completely described below in conjunction with the drawings in the embodiment of the present application. Obviously, the described embodiment is only a part of the embodiment of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of the present application. In the absence of conflict, the embodiments in the present application and the features in the embodiments can be arbitrarily combined with each other. In addition, although the logical order is shown in the flow chart, in some cases, the steps shown or described can be performed in an order different from that here.
[0086] The terms "first" and "second" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the term "comprising" and any of their variations are intended to cover non-exclusive protection. For example, a process, method, system, product or device comprising a series of steps or units is not limited to the listed steps or units, but optionally also includes steps or units that are not listed, or optionally also includes other steps or units inherent to these processes, methods, products or devices. "Multiple" in the present application can mean at least two, for example, two, three or more, and the embodiments of the present application are not limited.
[0087] As mentioned above, the current duty deployment plan is mainly formulated based on human experience or fixed deployment rules. Usually, the duty personnel are evenly distributed according to the distribution of the road network, and additional duty personnel are dispatched to key areas such as schools, hospitals, and accident-prone sections. However, the traffic scene in actual application is not fixed, and it will change due to external factors such as holding events and road maintenance. This also indirectly reflects that the places where traffic incidents are prone to occur will also change. Therefore, how to reasonably allocate duty areas and duty times for limited manpower to maximize traffic control efficiency is the pain point of current duty deployment.
[0088] To solve the above problems, the invention concept of the present application is as follows: determine the clustered event points corresponding to the target area in each preset time period, and determine the high-incidence sub-periods of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of any preset time period. And determine the service score of the sub-period according to the duty time of the service object in the area of interest in any sub-period. Finally, determine the total service score of each sub-period in the preset time period according to the high-incidence sub-periods in the preset time period and the service scores of each sub-period, and allocate the service area and duty time in the sub-period corresponding to the total score to the service object according to the total service score.
[0089] The above process scores the clustered event points generated in the target area in each preset time period, and allocates duty areas and duty events to the duty objects in each sub-time period of each preset time period according to the scoring results, so as to improve traffic management efficiency.
[0090] Specific as Figure 1 As shown, Figure 1 The overall process of a traffic service deployment method provided by an embodiment of the present application is shown, including:
[0091] Step 101: In response to a deployment instruction, determine clustered event points corresponding to a target area in each preset time period; wherein the clustered event points are located in a road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents a location where the corresponding event occurs in the road network map;
[0092] The target area is divided according to the needs of service deployment and is used to allocate the area of the service object. In the embodiment of the present application, the target area is a certain city. The clustering event points corresponding to the target area in each preset time period are as follows: Figure 2 The process shown in FIG. 1 includes the following steps:
[0093] Step 201: Acquire event data of multiple preset types generated in a historical period; wherein any event data includes the occurrence time and location of an event of the preset type;
[0094] In the embodiment of the present application, traffic events are divided according to event types, and the following are set: Figure 3 The five preset types shown specifically include a first preset type representing traffic violations, a second preset type representing traffic accidents, a third preset type representing congestion, a fourth preset type representing designated types of vehicles, and a fifth preset type representing designated areas of the road network.
[0095] During implementation, all event records of the above-mentioned preset types of events generated in the target area within a historical period (eg, the most recent month) are obtained in advance, and corresponding event data are extracted from the event records. Next, each preset type of event data is explained.
[0096] Any preset type of event data is used to indicate the time and location of the corresponding event. Figure 4 As shown, for the first preset type of event data, the time and place of occurrence are the time and place of the traffic violation. For the second preset type of event data, the time and place of occurrence are the time and place of the accident. For the third preset type of event data, the time and place of occurrence are the location of the road section where the congestion occurs and the duration of the congestion. For the fourth preset type of event data, the time of occurrence is the time when the designated type of vehicle (such as "two violations and one dangerous vehicle", i.e., vehicles transporting contraband, illegal goods and hazardous chemicals) is captured by the bayonet camera. The place of occurrence is the place where the designated type of vehicle is captured by the bayonet camera. For the fifth preset type of event data, the place of occurrence is the area specified by the road network, and the time of occurrence is the time when the event of concern in the traffic control task occurs in the key focus area, which can be specifically, for example, the time when the designated area (such as schools, hospitals, etc.) produces key focus events such as congestion and traffic accidents.
[0097] Step 202: for any sub-period of any preset period, select target event data whose occurrence time is within the sub-period from each event data;
[0098] The preset time periods in the embodiment of the present application are set according to the week, specifically including 7 preset time periods from Monday to Sunday. In addition, each preset time period is divided into 24 sub-time periods per hour.
[0099] After obtaining the event data of five preset types generated in the target area within the latest month in the aforementioned step 201, the target event data generated in each sub-period of each preset time period is counted in step 202.
[0100] To facilitate understanding of the process of obtaining target event data, the following takes the preset period "Monday" as an example. Figure 5 From the calendar shown, we can see that there are 4 Mondays in the most recent month (month A), namely the 3rd, 10th, 17th and 24th.
[0101] Assume that there are 100 events of each preset type in month A, that is, there are 100 sets of event data of the five preset types in month A. Next, count the events of the preset types that occur every hour on every Monday. Taking the sub-period "0:00-1:00" as an example, the event data corresponding to the preset type events that occurred between 0:00 and 1:00 on the aforementioned four days, namely, the 3rd, 10th, 17th and 24th, can be used as the target event data of the sub-period "0:00-1:00" under the preset period (Monday).
[0102] Step 203: for any target event data, determine the location area of the target event data in the road network map according to the occurrence location of the target event data;
[0103] Step 204: Cluster all target event data in the positioning area to obtain clustered event points determined by the occurrence locations of the target event data.
[0104] After obtaining the target event data generated in each sub-period of each preset period in the historical period through the aforementioned steps 201 to 202, clustering is performed using the DBSCAN clustering algorithm according to the location of the event. Specifically, assuming that in the sub-period "0:00-1:00" of the preset period "Monday", a total of 7 preset type events occurred in the target area, that is, there are 7 copies of the target event data corresponding to this sub-period. Next, through step 203, the location area of each target event data in the road network map is determined according to the location of occurrence, thereby obtaining Figure 6 There are 7 positioning areas X1 to X7 shown in the figure, which correspond to the 7 target event data. Then, the other target event data contained in the positioning area corresponding to each target event data is determined in sequence according to the preset order, and the other target event data and the target event data are clustered to the same point. The clustered point is the location where the target event data occurs.
[0105] To facilitate understanding of the above process, Figure 6 The 7 target event data shown are used as an example for explanation. Figure 7 When implemented, the sequence from west to east (i.e., the direction from X1 to X7) can be adopted. First, determine whether the positioning area X1 corresponding to the target event data 1 contains other target event data. Figure 7It can be seen that the positioning area X1 contains the target event data 2. It should be noted here that although the positioning area X1 intersects with the positioning areas X2 and X3 at the same time, the positioning area X1 only contains the occurrence location of the target event data 2 (i.e., the triangle mark in the positioning area 2), so the target event data 3 is not counted as a point in the positioning area X1. At this time, the target event data X1 and the target event data X2 can be aggregated into a cluster event point, and the occurrence location of the positioning area X1 or the target event data 1 (i.e., the triangle mark in the positioning area X1) can be selected as the location of the cluster event point in the map.
[0106] Next, determine whether the location area X3 corresponding to the target event data 3 contains other target event data. Since there is no target event data in X3, the target event data 3 is taken as a cluster event point. The same rule is used to cluster the remaining target event data in turn, thus obtaining Figure 7 The clustering results are shown.
[0107] In addition, before executing step 204, target event data whose positioning area is not within the specified road section of the road network map may be removed. Specifically, in actual applications, some events may not occur in the traffic road network, such as Figure 8 The location area of a certain event data shown in FIG is located in a certain community, which is not within the scope of traffic service deployment. Therefore, such event data can be regarded as invalid data and removed, and does not participate in the construction of clustered event points in the subsequent step 204.
[0108] In this way, by processing each sub-period under each preset period in the aforementioned month A through the above steps 201 to 204, the following can be obtained: Fig. 9 As shown in FIG. 1 , clustered event points in each sub-period under each preset time period. Any clustered event point represents each preset type of event occurring in the sub-period under its corresponding preset time period. Fig.10 As shown, by calling any sub-period (eg 0:00-1:00) of any preset period (eg Monday), all clustered event points occurring in the sub-period in the historical period A can be found in the road network map.
[0109] Step 102: for any preset time period, determine the high-incidence sub-period of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of the preset time period, and determine the service score of the sub-period according to the duty time of the service object in the interest area of any sub-period; wherein the interest area is determined according to the location of the clustered event points in the sub-period;
[0110] During implementation, for any preset type in any sub-period, the number of target event points in the sub-period is determined, wherein the target event point is a clustered event point in the sub-period and the corresponding event includes an event of the preset type.
[0111] The following is an example of the preset period "Monday". When implementing, the number of events of each preset type occurring in each hour on each Monday of the historical period "Month A" is predetermined. For example, when the preset type is "first preset type", the following can be used: Fig.11 As shown in FIG. 1 , there are 3 clustered event points in the sub-period “0:00-1:00” of the preset period “Monday”. Among these 3 clustered event points, the number of target event points containing event data of the “first preset type” is 2, that is, Fig.11 Clustered event points 1 and 4 are shown.
[0112] Therefore, through the above process, the number of target event points corresponding to each preset type in each sub-period of the preset period "Monday" can be obtained. Fig.11 In the sub-period "0:00-1:00" of the preset time period "Monday" shown in , the number of cluster event points under the first preset type is 2, which are cluster event points 1 and 2 respectively; the number of cluster event points under the second preset type is 1, which is cluster event point 2; the number of cluster event points under the third preset type is 1, which is cluster event point 4; the number of cluster event points under the fourth preset type is 1, which is cluster event point 4; the number of cluster event points under the fifth preset type is 1, which is cluster event point 3.
[0113] Next, based on the number of target points obtained as described above, a high-incidence sub-period for events of the preset type is selected from each sub-period of the preset time period. As mentioned above, in the embodiment of the present application, each hour in the preset time period is taken as a sub-period, so that each preset time period is divided into 24 sub-periods. Therefore, after obtaining the number of target event points corresponding to each preset type in each hour in the preset time period "Monday", for each preset type, determine the first 1 / 4 with the highest number of target event points within 24 hours, that is, 6 hours as the high-incidence sub-period for accidents corresponding to each preset type of event in the preset time period "Monday". Thus, the following can be obtained: Fig.12 As shown in , each preset time period corresponds to a high-incidence sub-period of accidents for each preset type of event.
[0114] Furthermore, under the premise of obtaining the permission of the traffic control department, the embodiment of the present application determines the duty score in any sub-period by obtaining the duty time of the duty object in the area of interest in any sub-period in the historical period. Fig.13 As shown, the following steps are included:
[0115] Step 1301: for any preset type in any sub-period, determine the area of interest corresponding to each target event point according to the position of the target event point in the road network map in the sub-period;
[0116] The following still takes the preset period "Monday" as an example to explain that for each preset type, the target event point containing event data of the preset type in every hour of "Monday" is determined, and the area of interest corresponding to the target event point is determined according to the position of the target event point in the road network map. Fig.11 For example, Fig.14 As shown in the figure, since the target event points 1 and 3 of the "first preset type" are included in the sub-period "0:00-1:00" of "Monday", the circular area formed by the positions of the target event points 1 and 3 in the road network map as the center and the specified distance as the radius (for example, 100 meters) is the area of interest corresponding to the target event point, thus obtaining Fig.14 The target event point 1 shown in the figure corresponds to the region of interest 1, and the target event point 3 corresponds to the region of interest 3.
[0117] Step 1302: For any target event point, determine the event score corresponding to the target event point according to the total duration of the service object's duty in its area of interest during the sub-period.
[0118] Still with the above Fig.14 For example, if the target event point 1 shown in the figure is on duty for 48 minutes in the 60 minutes from 0:00 to 1:00, the event score of the target event point 1 under the "first preset type" is 48 / 60×100 (percentage system) = 80. By performing the same process on the remaining target event point 3, the event score of the target event point 3 under the "first preset type" can be obtained.
[0119] Step 1303: Determine the service score of the preset type in the sub-period according to the event score average of each target event point in the sub-period;
[0120] Still taking the above target event points 1 and 3 as an example, after obtaining the event scores of target event points 1 and 3 under the "first preset type" in the sub-period "0:00-1:00" of the preset period "Monday" through step 1302, the average of the event scores of 1 and 3 is obtained, and the average of the event scores is used as the duty score of the "first preset type" on Monday from 0:00 to 1:00. Thus, the following can be obtained through the above steps 1301 to 1203: Fig.15 As shown in , the service score of each preset type in each sub-period of each preset time period.
[0121] Step 103: For any preset time period, the total service score of each sub-time period is determined according to the high-incidence sub-time period within the preset time period and the service score of each sub-time period, and the duty area and duty time within the sub-time period corresponding to the total service score are allocated to the service object according to the total service score.
[0122] After obtaining the service scores of each preset type in each sub-period of each preset period through the aforementioned steps 1301 to 1303, the total service scores of each sub-period of each preset period are obtained through the following process:
[0123] During implementation, for any sub-period under any preset period, the first type corresponding to the sub-period is selected from each preset type. After adding a first weight to the service score of the first type under the sub-period, the total service score under the sub-period is determined according to the service score of each preset type under the sub-period; wherein the sub-period is a high-incidence sub-period under the first type.
[0124] To facilitate understanding of the above process, the following is an example of the sub-period "0:00-1:00" of the preset period "Monday". Fig.16 As shown, assuming that the above Fig.12 From the content shown, it can be seen that the sub-period "0:00-1:00" of the preset period "Monday" is only a high-incidence sub-period of the first preset type and the third preset type. Fig.15 It can be seen from the displayed content that the service scores of the five preset types in the sub-period “0:00-1:00” of the preset period “Monday” are 80, 76, 78, 72, and 80 respectively.
[0125] Since the sub-period "0:00-1:00" of "Monday" is a high-incidence sub-period representing a high incidence of accidents under the first preset type and the third preset type, the first weight (1.5) can be added to the service scores of the "first preset type" and the "third preset type". And the total service score of the sub-period "0:00-1:00" of the preset period "Monday" is determined according to each service score after adding the first weight.
[0126] Specifically, considering that the traffic control department usually has different duty focuses in different time periods, the embodiment of the present application can select the second type representing the duty focus in the sub-time period from each preset type in response to the duty focus indication. Fig.17 The traffic control department's focus on duty at different time periods is shown as an example. Fig.16 For example, since the sub-period "0:00-1:00" is in the night time period, the focus of duty is to catch the second, third and fourth preset types of events. Therefore, the second weight (1.2) can be added to the duty scores of the second, third and fourth preset types.
[0127] Therefore, through the aforementioned Fig.16 and Fig.18 After adding the first weight and the second weight to the service score of each preset type, the following can be done: Fig.19 As shown, the average of the sum of the service scores is used as the total service score of the sub-period "0:00-1:00" of the preset period "Monday". Further, the average of the scores is used as the total service score of the sub-period "0:00-1:00" of the preset period "Monday". By performing the same process on each sub-period of each preset period, the total service score corresponding to each sub-period can be obtained.
[0128] When the total duty score of a sub-period under any preset period is lower than the preset score threshold of 80, it means that there is a problem with the current shift deployment for Monday. Taking the sub-period "0:00-1:00" of the preset period "Monday" as an example, assuming that its total duty score is lower than 80, we can trace back to each duty score that constitutes the total duty score. Fig.15 It can be seen that the service scores of the second, third and fourth preset types in this sub-period are relatively low, all below 80 points. At this time, in the shift deployment for "Monday", additional service objects can be dispatched near the cluster event points of the second, third and fourth preset types, or the duty time of service objects near the cluster event points of each preset type can be adaptively adjusted.
[0129] Therefore, the traffic management efficiency can be improved by scoring the clustered event points generated in the target area in each preset time period, and then subdividing the duty areas and duty events into duty objects in each sub-time period of each preset time period according to the scoring results, so as to improve the traffic management efficiency.
[0130] Based on the same inventive concept, the embodiment of the present application provides a traffic service deployment device, specifically as follows Fig. 20 As shown, including:
[0131] The event acquisition unit A11 is configured to execute, in response to the deployment instruction, determining the clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in the road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents the location where the corresponding event occurs in the road network map;
[0132] The high-incidence time period unit A12 is configured to perform, for any preset time period, determining the high-incidence sub-period of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of the preset time period, and determining the service score of the sub-period according to the duty time of the service object in the interest area of any sub-period; wherein the interest area is determined according to the location of the clustered event points under the sub-period;
[0133] The duty deployment unit A13 is configured to execute, for any preset time period, determining the total duty score of each sub-time period according to the high-incidence sub-time period within the preset time period and the duty score of each sub-time period, and allocating the duty area and duty time within the sub-time period corresponding to the total duty score to the service object according to the total duty score.
[0134] In some possible embodiments, the determining of clustered event points of the road network map in each preset time period is performed, and the event acquisition unit is configured to:
[0135] Acquire event data of multiple preset types generated in a historical period; wherein any event data includes the occurrence time and location of the event of the preset type;
[0136] For any sub-period under any preset time period, select target event data whose occurrence time is within the sub-period from each of the event data;
[0137] For any target event data, determining a location area of the target event data in the road network map according to the occurrence location of the target event data;
[0138] All target event data in the positioning area are clustered to obtain cluster event points determined by the occurrence locations of the target event data.
[0139] In some possible embodiments, before clustering all target event data in the positioning area to obtain clustered event points determined by the occurrence locations of the target event data, the event acquisition unit is further configured to:
[0140] If the positioning area is not within the designated road section of the road network map, the target event data is discarded.
[0141] In some possible embodiments, the process of determining the high-incidence sub-period for each preset type of event within the preset time period according to the number of clustered event points in each sub-period is performed, and the time period confirmation unit is configured as follows:
[0142] For any preset type in any sub-period, determine the number of target event points in the sub-period; wherein the target event point is a clustered event point within the sub-period and the corresponding event includes an event of the preset type;
[0143] A high-incidence sub-period of the event of the preset type is selected from each sub-period of the preset period according to the number of the target points.
[0144] In some possible embodiments, to determine the service score in any sub-period according to the service object's duty time in the region of interest in any sub-period, the service deployment unit is configured as follows:
[0145] For any preset type in any sub-period, determine the area of interest corresponding to each target event point according to the position of each target event point in the road network map in the sub-period;
[0146] For any target event point, determine the event score corresponding to the target event point according to the total duration of duty of the service object in the area of interest during the sub-period;
[0147] The service score of the preset type in the sub-period is determined according to the event score average of each target event point in the sub-period.
[0148] In some possible embodiments, to determine the total service score of each sub-period according to the high-incidence sub-period within the preset time period and the service score in each sub-period, the service deployment unit is configured as follows:
[0149] For any sub-period under the preset period, a first type corresponding to the sub-period is selected from various preset types; wherein the sub-period is a high-incidence sub-period under the first type;
[0150] After adding the first weight to the service score of the first type in the sub-period, the total service score in the sub-period is determined according to the service score of each preset type in the sub-period.
[0151] In some possible embodiments, before determining the total service score in the sub-period according to the service score of each preset type in the sub-period, the service deployment unit is further configured to:
[0152] In response to the duty focus indication, a second type representing the duty focus in the sub-period is selected from various preset types; and a second weight is added to the duty score of the second type in the sub-period.
[0153] In some possible embodiments, the multiple preset types include part or all of a first preset type representing traffic violations, a second preset type representing traffic accidents, a third preset type representing congestion, a fourth preset type representing vehicles of a specified type, and a fifth preset type representing a specified area of a road network.
[0154] In some possible embodiments, each preset time period includes Monday to Sunday, and each hour in any preset time period is a sub-time period in the preset time period.
[0155] Specific as Fig.21 As shown, based on the same inventive concept, an embodiment of the present application further provides an electronic device, including a data transmission unit 211 and a processor 212;
[0156] The data transmission unit 211 is configured to: determine, in response to the deployment instruction, the clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in the road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents the location where the corresponding event occurs in the road network map;
[0157] The processor 212 is configured to: for any preset time period, determine a high-incidence sub-period of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of the preset time period, and determine the service score of the sub-period according to the duty time of the service object in the interest area of any sub-period; wherein the interest area is determined according to the location of the clustered event points in the sub-period;
[0158] For any preset time period, the total service score of each sub-time period is determined according to the high-incidence sub-time period within the preset time period and the service score of each sub-time period, and the duty area and duty time within the sub-time period corresponding to the total service score are allocated to the service object according to the total service score.
[0159] In some possible embodiments, to perform the step of determining the clustered event points of the road network map in each preset time period, the processor 212 is configured to:
[0160] Acquire event data of multiple preset types generated in a historical period; wherein any event data includes the occurrence time and location of the event of the preset type;
[0161] For any sub-period under any preset time period, select target event data whose occurrence time is within the sub-period from each of the event data;
[0162] For any target event data, determining a location area of the target event data in the road network map according to the occurrence location of the target event data;
[0163] All target event data in the positioning area are clustered to obtain cluster event points determined by the occurrence locations of the target event data.
[0164] In some possible embodiments, before clustering all target event data in the positioning area to obtain clustered event points determined by the occurrence locations of the target event data, the processor 212 is further configured to:
[0165] If the positioning area is not within the designated road section of the road network map, the target event data is discarded.
[0166] In some possible embodiments, to determine the high-incidence sub-period of each preset type of event within the preset period according to the number of clustered event points in each sub-period, the processor 212 is configured to:
[0167] For any preset type in any sub-period, determine the number of target event points in the sub-period; wherein the target event point is a clustered event point within the sub-period and the corresponding event includes an event of the preset type;
[0168] A high-incidence sub-period of the event of the preset type is selected from each sub-period of the preset period according to the number of the target points.
[0169] In some possible embodiments, to determine the service score in any sub-period according to the service object's service time in the region of interest in the sub-period, the processor 212 is configured to:
[0170] For any preset type in any sub-period, determine the area of interest corresponding to each target event point according to the position of each target event point in the road network map in the sub-period;
[0171] For any target event point, determine the event score corresponding to the target event point according to the total duration of duty of the service object in the area of interest during the sub-period;
[0172] The service score of the preset type in the sub-period is determined according to the event score average of each target event point in the sub-period.
[0173] In some possible embodiments, to determine the total service score of each sub-period according to the high-incidence sub-period within the preset time period and the service score in each sub-period, the processor 212 is configured to:
[0174] For any sub-period under the preset period, a first type corresponding to the sub-period is selected from various preset types; wherein the sub-period is a high-incidence sub-period under the first type;
[0175] After adding the first weight to the service score of the first type in the sub-period, the total service score in the sub-period is determined according to the service score of each preset type in the sub-period.
[0176] In some possible embodiments, before determining the total service score in the sub-period according to the service score of each preset type in the sub-period, the processor 212 is further configured to:
[0177] In response to the duty focus indication, a second type representing the duty focus in the sub-period is selected from various preset types; and a second weight is added to the duty score of the second type in the sub-period.
[0178] In some possible embodiments, the multiple preset types include part or all of a first preset type representing traffic violations, a second preset type representing traffic accidents, a third preset type representing congestion, a fourth preset type representing vehicles of a specified type, and a fifth preset type representing a specified area of a road network.
[0179] In some possible embodiments, each preset time period includes Monday to Sunday, and each hour in any preset time period is a sub-time period in the preset time period.
[0180] The embodiment of the present application further 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 traffic signal control method.
[0181] 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.
[0182] 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 212 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 212 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.
[0183] 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 1A function specified in one or more boxes.
[0184] 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.
[0185] 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 traffic service deployment method, characterized in that: The method comprises: In response to the deployment instruction, determine the clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in a road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents the location where the corresponding event occurs in the road network map; For any preset time period, a high-incidence sub-period of each preset type of event in the preset time period is determined according to the number of clustered event points in each sub-period of the preset time period, and the service score of the sub-period is determined according to the duty time of the service object in the area of interest of any sub-period; wherein the area of interest is determined according to the location of the clustered event points in the sub-period; For any preset time period, the total service score of each sub-time period is determined according to the high-incidence sub-time period within the preset time period and the service score of each sub-time period, and the duty area and duty time within the sub-time period corresponding to the total service score are allocated to the service object according to the total service score.
2. The method according to claim 1, characterized in that: The step of determining clustered event points of the road network map in each preset time period includes: Acquire event data of multiple preset types generated in a historical period; wherein any event data includes the occurrence time and location of the event of the preset type; For any sub-period under any preset time period, select target event data whose occurrence time is within the sub-period from each of the event data; For any target event data, determining a location area of the target event data in the road network map according to the occurrence location of the target event data; All target event data in the positioning area are clustered to obtain cluster event points determined by the occurrence locations of the target event data.
3. The method according to claim 2, characterized in that Before clustering all target event data in the positioning area to obtain clustered event points determined by the locations where the target event data occur, the method further includes: If the positioning area is not within the designated road section of the road network map, the target event data is discarded.
4. The method according to claim 1, characterized in that: The step of determining the high-incidence sub-period of each preset type of event within the preset period according to the number of clustered event points in each sub-period includes: For any preset type in any sub-period, determine the number of target event points in the sub-period; wherein the target event point is a clustered event point within the sub-period and the corresponding event includes an event of the preset type; A high-incidence sub-period of the event of the preset type is selected from each sub-period of the preset period according to the number of the target points.
5. The method according to claim 4, characterized in that Determining the service score in any sub-period according to the service object's service time in the area of interest in any sub-period includes: For any preset type in any sub-period, determine the area of interest corresponding to each target event point according to the position of each target event point in the road network map in the sub-period; For any target event point, determine the event score corresponding to the target event point according to the total duration of duty of the service object in the area of interest during the sub-period; The service score of the preset type in the sub-period is determined according to the event score average of each target event point in the sub-period.
6. The method according to claim 5, characterized in that Determining the total service score of each sub-period according to the high-incidence sub-period within the preset time period and the service score in each sub-period includes: For any sub-period under the preset period, a first type corresponding to the sub-period is selected from various preset types; wherein the sub-period is a high-incidence sub-period under the first type; After adding the first weight to the service score of the first type in the sub-period, the total service score in the sub-period is determined according to the service score of each preset type in the sub-period.
7. The method according to claim 6, characterized in that Before determining the total service score in the sub-period according to the service score in the sub-period for each preset type, the method further comprises: In response to the duty focus indication, a second type representing the duty focus in the sub-period is selected from various preset types; and a second weight is added to the duty score of the second type in the sub-period.
8. The method according to any one of claims 1 to 7, characterized in that: The multiple preset types include part or all of a first preset type representing traffic violations, a second preset type representing traffic accidents, a third preset type representing congestion, a fourth preset type representing vehicles of a specified type, and a fifth preset type representing a specified area of a road network.
9. The method according to any one of claims 1 to 7, characterized in that: Each preset time period includes Monday to Sunday, and each hour in any preset time period is a sub-time period in the preset time period.
10. An electronic device, characterized in that: Including data transmission unit and processor: The data transmission unit is configured to: determine, in response to the deployment instruction, clustered event points corresponding to the target area in each preset time period; wherein the clustered event points are located in a road network map of the target area, any clustered event point corresponds to at least one event of a preset type, and any clustered event point represents a location where the corresponding event occurs in the road network map; The processor is configured to: for any preset time period, determine a high-incidence sub-period of each preset type of event in the preset time period according to the number of clustered event points in each sub-period of the preset time period, and determine the service score of the sub-period according to the duty time of the service object in the interest area of any sub-period; wherein the interest area is determined according to the location of the clustered event points in the sub-period; For any preset time period, the total service score of each sub-time period is determined according to the high-incidence sub-time period within the preset time period and the service score of each sub-time period, and the duty area and duty time within the sub-time period corresponding to the total service score are allocated to the service object according to the total service score.