Method and system for judging cross-border state of slag transporting vehicle based on trajectory data

Abstract

The invention provides a slag transport vehicle cross-border state judgment method and system based on trajectory data, and relates to the technical field of slag transport vehicle trajectories, and the method specifically comprises the following steps: S1, obtaining a current trajectory point location of a current slag transport vehicle, a corresponding current administrative region, and a pollution source point location in the administrative region in real time; s2, sequentially judging whether a track point location in the track data is only located in the current administrative region, if so, judging that the current slag transporting vehicle is an intra-region vehicle, and if not, turning to the step S3; s3, judging whether a parking point group obtained by screening track point positions in the current track data exists in the current administrative region or not, if not, judging that the current slag transporting vehicle is a transit vehicle, and if yes, turning to step S4; and S4, traversing the parking point group obtained by screening to obtain a corresponding parking center point, and performing distance matching according to the parking center point and the pollution source point position so as to judge the current cross-border state of the slag transporting vehicle.

Description

Technical Field

[0001] The present invention relates to the technical field of slag truck trajectories, and in particular to a method and system for determining a cross-border status of a slag truck based on trajectory data. Background Art

[0002] In modern urban construction and industrial development, slag trucks are an important tool for transporting construction waste and industrial waste. The standardization of their operations is directly related to the cleanliness and safety of the urban environment. However, due to the high mobility and wide range of cross-domain operations of slag trucks, as well as the differences in regulatory policies and enforcement strength between different administrative regions, the accountability work for illegal slag trucks faces many challenges.

[0003] At present, the supervision of slag trucks mainly relies on two traditional methods: one is manual fixed-point inspection, that is, setting up checkpoints at key intersections or areas, and law enforcement officers conduct on-site inspections of passing slag trucks; the other is video surveillance, that is, installing cameras on important roads and tracking violations through video playback. However, both methods have obvious limitations. Manual fixed-point inspections are limited by manpower and geographical conditions, have limited coverage, and are easy to circumvent; although video surveillance can provide evidence of violations, it is time-consuming and labor-intensive to find specific events in massive data, and it is difficult to cover all potential violation areas, especially in cross-domain operations, the allocation and coordination of monitoring resources is more complicated. Summary of the invention

[0004] The purpose of the present invention is to provide a method and system for determining the cross-border status of a slag truck based on trajectory data. The method mainly reflects the cross-border status of the slag truck based on trajectory data, and can monitor and analyze the cross-domain transportation process of the slag truck in real time, thereby effectively dividing and clarifying the responsibility for violations, and fundamentally solving the environmental problems caused by the cross-domain transportation of slag trucks.

[0005] In order to solve the above technical problems, the present invention adopts the following solutions: A method for determining the cross-border status of a slag truck based on trajectory data, the method specifically comprising the following steps: S1: obtain the current track point of the current slag truck in real time, add the current track point to the corresponding track data in chronological order and update the track data, map the current track point on the regional map to obtain the corresponding current administrative area, and obtain the pollution source point in the administrative area; S2: determine in turn whether the track points in the track data are only located in the current administrative area. If so, determine that the current slag truck is an intra-regional vehicle. If not, go to step S3; S3: Determine whether there is a stop point group obtained by screening the track points in the current track data in the current administrative area. If not, determine that the current slag truck is a transit vehicle. If so, go to step S4; S4: Traverse the filtered stop point group to obtain the corresponding stop center point, and match the distance between the stop center point and the pollution source point to determine the current cross-border status of the slag truck.

[0006] Furthermore, the stop point group is composed of a plurality of track points arranged in chronological order, and the track points are collected in real time by a GPS device carried by the slag truck itself, and one track point corresponds to one administrative area; In S3, the screening process is specifically as follows: a plurality of continuous trajectory points are screened out from the trajectory data as the stop point group according to the time threshold and the distance threshold. Further, S4 specifically includes the following steps: S41: all the stop point groups obtained by screening are traversed in sequence. In each traversal process, a group of trajectory segments are formed according to the trajectory points in the stop point group, and the corresponding stop center point is obtained according to the point cluster attributes of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; S42: Perform distance matching based on the latitude and longitude information of the stop center point and the latitude and longitude information of the pollution source point, find out whether there is a pollution source point near the stop center point with a preset distance threshold, and determine the current operation status of the slag truck through the distance matching result of the current stop center point and the stay time of the current stop center point.

[0007] Furthermore, the S41 specifically includes the following steps: S411: Obtaining a preset time threshold and a preset minimum distance threshold; S412: obtaining the track points in the current stop point group arranged in time order, in the initial state, taking the first track point as the other track points, and the second track point as the current track point, calculating the distance difference between the other track points and the current track point, judging whether the distance difference is greater than a preset minimum distance threshold, if so, forming a group of track segments with the other track points and the current track point as the head and tail, obtaining the corresponding stop center point according to the point cluster attribute of the track segment, and obtaining the latitude and longitude information of the stop center point and the corresponding stay duration; if not, going to step S413; S413: Move the current trajectory point downward a little, and determine whether the length of a group of trajectory segments formed by the current trajectory point and other trajectory points as the head and tail exceeds the total length of the current stop point group. If so, end the traversal; if not, enter the next traversal, that is, go to step S412.

[0008] Furthermore, the trajectory segment includes at least two trajectory points. The total consumed time of the trajectory segment can be obtained according to the time of the trajectory points located at the beginning and the end of the trajectory segment. The total consumed time is compared with a preset time threshold, and the point cluster attribute of the trajectory segment is determined according to the comparison result.

[0009] Furthermore, the point cluster attributes include dense clustering or sparse clustering; When the total consumption time of a track segment is greater than the preset time threshold, it means that the point cluster attribute of the track segment is densely clustered, and a stop center point can be generated through all the track points in the track segment. The longitude and latitude information of the stop center point is the average of the longitude and latitude information of all the track points in the track segment, and the stay time of the stop center point is the time difference between the two track points at the beginning and the end of the track segment; When the total consumption time of a trajectory segment is less than the preset time threshold, it means that the point cluster attribute of the trajectory segment is sparse. Then all the trajectory points in the trajectory segment are used as their respective stop center points. Starting from the trajectory point at the first position of the trajectory segment, its starting time is set as the i-point time, and the ending time is set as the i+1-point time, and so on.

[0010] Furthermore, the distance matching result includes a first matching result and a second matching result; The first matching result indicates that there is a pollution source point near the parking center point. When the distance matching result is the first matching result, it is determined that the current operation status of the slag truck is an in-domain vehicle; The second matching result indicates that there is no pollution source near the stop center point and the stay time at the stop center point exceeds the threshold. When the distance matching result is the second matching result, it is determined that the current operating status of the slag truck is an in-domain vehicle.

[0011] Furthermore, the target area may be a pre-processed grid area. When the real-time driving trajectory data of the current slag truck is obtained, the real-time driving trajectory data may be distributed on the grid, and the current driving trajectory route of the current slag truck may be visualized through the grid.

[0012] A cross-border status determination system for a slag truck based on trajectory data, comprising: Track data acquisition module: obtain the current track point of the current slag truck in real time, add the current track point to the corresponding track data in chronological order and update the track data, map the current track point on the regional map to obtain the corresponding current administrative area, and obtain the pollution source point in the administrative area; Track point judgment module: judges whether the track points in the track data are only located in the current administrative area, and determines the cross-border status of the current slag truck based on the judgment results; Stop point group judgment module: judge whether there is a stop point group obtained by screening the trajectory points in the current trajectory data in the current administrative area, and determine the cross-border status of the current slag truck based on the judgment result; Stop center point judgment module: traverse the filtered stop point group to obtain the corresponding stop center point, and match the distance between the stop center point and the pollution source point to determine the current cross-border status of the slag truck.

[0013] Furthermore, the stopping center point determination module includes the following modules: Stop center point acquisition module: traverse all the stop point groups obtained by screening in sequence. In each traversal process, a group of trajectory segments are formed according to the trajectory points in the stop point group, and the corresponding stop center point is obtained according to the point cluster attributes of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; Slag truck operation status determination module: perform distance matching based on the longitude and latitude information of the parking center point and the longitude and latitude information of the pollution source point, use the preset distance threshold to find out whether there is a pollution source point near the parking center point, and determine the current operation status of the slag truck based on the distance matching result.

[0014] Beneficial effects of the present invention: The present invention provides a method and system for determining the cross-border status of a slag truck based on trajectory data. The method mainly reflects the cross-border status of the slag truck based on the trajectory data, and performs different processing on different trajectory data. The cross-border status of the slag truck is determined by the current administrative area in the target area, the stop point group formed in the trajectory data, and the stop center point. Thus, the cross-domain transportation process of the slag truck is monitored and analyzed in real time, thereby effectively dividing and clarifying the responsibility for violations, and fundamentally solving the environmental problems caused by the cross-domain transportation of slag trucks. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the process of determining the cross-border status of a slag truck in Embodiment 1 of the present invention; Figure 2 This is a schematic diagram of the composition of the current trajectory data in Example 1 of the present invention; Figure 3 This is a schematic diagram of the first traversal of the stop point group 1 in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the second traversal of the stop point group 1 in Embodiment 1 of the present invention; Figure 5 In Example 1 of the present invention, based on Figure 2 Schematic diagram of the first traversal of stop point group 1. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments. The following description of at least one exemplary embodiment is actually only illustrative and is by no means intended to limit the present invention and its application or use. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] The relative arrangement of components and steps, the numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

[0018] At the same time, it should be understood that for the convenience of description, the sizes of the various parts shown in the drawings are not drawn according to the actual proportional relationship.

[0019] Additionally, descriptions of well-known structures, functions, and configurations may be omitted for clarity and conciseness.One of ordinary skill in the art will recognize that various changes and modifications may be made to the examples described herein without departing from the spirit and scope of the present disclosure.

[0020] Technologies, methods, and apparatus known to ordinary technicians in the relevant field may not be discussed in detail, but where appropriate, such technologies, methods, and apparatus should be considered part of the authorization specification.

[0021] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0022] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments: Example 1 A method for determining the cross-border status of a slag truck based on trajectory data, the method specifically comprising the following steps: S1: obtain the current track point of the current slag truck in real time, add the current track point to the corresponding track data in chronological order and update the track data, map the current track point on the regional map to obtain the corresponding current administrative area, and obtain the pollution source point in the administrative area; S2: determine in turn whether the track points in the track data are only located in the current administrative area. If so, determine that the current slag truck is an intra-regional vehicle. If not, go to step S3; S3: Determine whether there is a stop point group obtained by screening the track points in the current track data in the current administrative area. If not, determine that the current slag truck is a transit vehicle. If so, go to step S4; S4: Traverse the filtered stop point group to obtain the corresponding stop center point, and match the distance between the stop center point and the pollution source point to determine the current cross-border status of the slag truck.

[0023] Preferably, the stop point group is composed of a plurality of track points arranged in chronological order, the track points are collected in real time by a GPS device carried by the slag truck itself, and one track point corresponds to one administrative area; In S3, the screening process is specifically as follows: a plurality of continuous trajectory points are screened out from the trajectory data as the stop point group according to the time threshold and the distance threshold. Further, S4 specifically includes the following steps: Preferably, the S4 specifically includes the following steps: S41: all the stop point groups obtained by screening are traversed in sequence. In each traversal process, a group of trajectory segments are formed according to the trajectory points in the stop point group, and the corresponding stop center point is obtained according to the point cluster attributes of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; S42: Perform distance matching based on the latitude and longitude information of the stop center point and the latitude and longitude information of the pollution source point, find out whether there is a pollution source point near the stop center point with a preset distance threshold, and determine the current operation status of the slag truck through the distance matching result of the current stop center point and the stay time of the current stop center point.

[0024] Preferably, the S41 specifically includes the following steps: S411: Obtaining a preset time threshold and a preset minimum distance threshold; S412: obtaining the track points in the current stop point group arranged in time order, in the initial state, taking the first track point as the other track points, and the second track point as the current track point, calculating the distance difference between the other track points and the current track point, judging whether the distance difference is greater than a preset minimum distance threshold, if so, forming a group of track segments with the other track points and the current track point as the head and tail, obtaining the corresponding stop center point according to the point cluster attribute of the track segment, and obtaining the latitude and longitude information of the stop center point and the corresponding stay duration; if not, going to step S413; S413: Move the current trajectory point downward a little, and determine whether the length of a group of trajectory segments formed by the current trajectory point and other trajectory points as the head and tail exceeds the total length of the current stop point group. If so, end the traversal; if not, enter the next traversal, that is, go to step S412.

[0025] Preferably, the trajectory segment includes at least two trajectory points. The total consumed time of the trajectory segment can be obtained according to the time of the trajectory points located at the beginning and the end of the trajectory segment. The total consumed time is compared with a preset time threshold, and the point cluster attribute of the trajectory segment is determined according to the comparison result.

[0026] Preferably, the point cluster attributes include dense clustering or sparse clustering; When the total consumption time of a track segment is greater than the preset time threshold, it means that the point cluster attribute of the track segment is densely clustered, and a stop center point can be generated through all the track points in the track segment. The longitude and latitude information of the stop center point is the average of the longitude and latitude information of all the track points in the track segment, and the stay time of the stop center point is the time difference between the two track points at the beginning and the end of the track segment; When the total consumption time of a trajectory segment is less than the preset time threshold, it means that the point cluster attribute of the trajectory segment is sparse. Then all the trajectory points in the trajectory segment are used as their respective stop center points. Starting from the trajectory point at the first position of the trajectory segment, its starting time is set as the i-point time, and the ending time is set as the i+1-point time, and so on.

[0027] Preferably, the distance matching result includes a first matching result and a second matching result; The first matching result indicates that there is a pollution source point near the parking center point. When the distance matching result is the first matching result, it is determined that the current operation status of the slag truck is an in-domain vehicle; The second matching result indicates that there is no pollution source near the stop center point and the stay time at the stop center point exceeds the threshold. When the distance matching result is the second matching result, it is determined that the current operating status of the slag truck is an in-domain vehicle.

[0028] Preferably, the target area can also be preprocessed to form a grid area. When the real-time driving trajectory data of the slag truck is obtained, the real-time driving trajectory data can be distributed on the grid, and the current driving trajectory route of the slag truck can be visualized through the grid.

[0029] Based on the above principles, the present invention is further described: In order to achieve real-time monitoring and intelligent analysis of the cross-domain transportation process of slag trucks, the present invention provides a method for determining the cross-border status of slag trucks based on trajectory data. The operating status of the slag truck is mainly divided into entering other areas or staying in the current area. The slag truck entering other areas is called a transit vehicle, and the slag truck staying in the current area is called an in-domain vehicle. By determining the operating status of the slag truck, it is possible to automatically identify whether the vehicle has entered an unauthorized area or violated the regulations of a specific area. When a violation occurs, the system can quickly locate the location of the violation and accurately determine the specific administrative area to which the violation belongs based on the vehicle's driving trajectory and administrative division information, thereby providing a scientific basis for the division of responsibilities. This effective strategy for dealing with the problem of accountability for cross-domain violations of slag trucks not only greatly improves supervision efficiency and reduces labor costs, but also effectively overcomes the blind spots of traditional supervision methods and ensures the transparency and compliance of cross-domain operations.

[0030] In this embodiment, administrative regions can be divided based on a map in advance to obtain a number of administrative regions and pollution source locations within the administrative regions, wherein the administrative region data includes the name of the administrative region, the geographical boundaries, etc., in the form of (area i , geometry i ), area i Indicates the name of the administrative area, geometry i It represents the geographical boundary of the administrative region; the pollution source points mainly refer to construction sites, dumping sites, heavy parking lots, sand and gravel plants, commercial concrete mixing stations and the like. The administrative region data also includes the name, longitude and latitude information of the pollution source points, and the correlation between the pollution source points and the administrative region can be obtained, indicating the pollution source points in the administrative region.

[0031] Specifically, according to the GPS device carried by the slag truck itself, the current track point of the current slag truck can be collected in real time. The current track point indicates the position of the slag truck on the map. In addition, when the track point of the slag truck is collected in real time by the GPS device, the time of marking the current track point can also be collected, and the current track point is added to the corresponding track data in chronological order and the track data is updated. The track point is data with license plate number, longitude and latitude, time and other information, so that the track data can store the track points of the current slag truck in sequence, and the track data is composed of several track points sorted in chronological order. Therefore, the cross-border status of the slag truck can be reflected according to the track data, and the cross-domain transportation process of the slag truck can be monitored and analyzed in real time, so as to effectively divide and clarify the responsibility for violations and fundamentally solve the environmental problems caused by the cross-domain transportation of slag trucks.

[0032] Then, based on the trajectory points, the first cross-border status of the current slag truck is determined. The first cross-border status determination of the slag truck is mainly determined by judging whether the trajectory points in the trajectory data are only located in the current administrative area to determine the cross-border status of the current slag truck, specifically: Based on the current trajectory points, we can get the administrative area where the current slag truck is located. Then, we can judge whether the trajectory points in the trajectory data are only located in the current administrative area. At this time, the current administrative area refers to the administrative area corresponding to the current trajectory points, which is equivalent to judging in real time through the trajectory points whether the current slag truck has left a certain administrative area. If the current slag truck has always been located in a certain administrative area, it means that the current slag truck has not crossed the border, and the current slag truck is determined to be an intra-domain vehicle.

[0033] Furthermore, if it is determined that the track point in the track data is not located only in the current administrative region, it means that when the administrative region corresponding to the track point in the track data is not one administrative region, the current slag truck can be subjected to a second cross-border status determination based on the stop point group. The second cross-border status determination of the slag truck is mainly determined by determining whether there is a stop point group obtained by screening the track point in the current track data in the current administrative region to determine the cross-border status of the current slag truck, specifically: The stop point group is obtained by screening the trajectory points in the current trajectory data, and a plurality of continuous trajectory points are screened out in the current trajectory data according to the time threshold and the distance threshold as the stop point group, such as Figure 2 As shown, for example, a segment is composed of multiple trajectory points. According to the trajectory points in the segment, the total time for the slag truck to travel through the trajectory points in sequence is 10 minutes, and the maximum distance of the trajectory points in the segment does not exceed 200m, which means that the slag truck may run very slowly, linger, or stop during this period. All the trajectory points in this segment are taken as a group, and this group of trajectory points is called a stop point group. Then, it can be determined whether there is a stop point group in the current administrative area, that is, whether the current slag truck has similar phenomena such as lingering in the current administrative area. If not, the current slag truck is determined to be a transit vehicle.

[0034] Furthermore, if it is determined that there is a parking point group in the current administrative area, the third cross-border status of the current slag truck can be determined based on the parking center point. The third cross-border status determination of the slag truck is mainly determined by traversing the screened parking points to obtain the corresponding parking center point, and matching the distance between the parking center point and the pollution source point to determine the cross-border status of the current slag truck, specifically: If it is determined that there is Figure 2When the stop point group 1 shown in , the stop point group 1 is traversed to obtain the corresponding stop center point. The current stop point group 1 is formed by four stop point groups connected in sequence, which can be expressed as n2-n3-n4-n5. In the initial state, it starts with the starting point n2 of the stop point group 1, such as Figure 3 As shown, the first track point n2 is used as the other track point, and the second track point n3 is used as the current track point. The distance difference between track point n2 and track point n3 is calculated to determine whether the distance difference is greater than the preset minimum distance threshold. If the distance difference is not greater than the preset minimum distance threshold, the current track point is updated, as shown in FIG. Figure 4 As shown, the current track point is moved downward a little, that is, the current track point is n4. At the same time, it is determined whether the length of a group of track segments formed by the current track point and other track points as the head and tail exceeds the total length of the current stop point group, that is, whether the length of a group of track segments formed by track point n2 and track point n4 exceeds the total length of the current stop point group, that is, it is determined whether the current track point can be moved downward a little. If so, the traversal is terminated. If not, a second traversal is performed. During the second traversal, the distance difference between track point n2 and track point n4 is calculated, and so on. Moreover, during the first traversal, if the distance difference is greater than the preset minimum distance threshold, a set of trajectory segments (n2-n3) is formed with trajectory points n2 and n3 as the head and tail, and the corresponding stop center point is obtained according to the point cluster attribute of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; then, the other trajectory points are moved down by one point. At this time, n3 is used as the current trajectory point, and no trajectory segment will be formed. Then, the other trajectory points are moved down by one point to make n4 the current trajectory point, as shown in FIG. Figure 5 As shown, the corresponding trajectory segment (n3-n4) will be formed, and so on.

[0035] It can be seen that in the present invention, all trajectory points in the stop point group are obtained by cyclic traversal, and corresponding trajectory segments are formed according to the trajectory points, and corresponding point clusters are formed according to the trajectory segments. In addition, the point clusters are mainly divided into two clustering attributes: dense clustering or sparse clustering. Different clustering attributes represent different stop point group distributions in the point clusters. Different stop point group distributions will form different stop center points, thereby improving the accuracy of the judgment on the operating status of the slag truck in the present invention.

[0036] Then, after obtaining the data of the parking center point through loop traversal, the pollution source point data can be substituted, and the distance matching is performed based on the latitude and longitude information of the parking center point and the latitude and longitude information of the pollution source point. The preset distance threshold is used to find out whether there is a pollution source point near the parking center point. The current operating status of the slag truck is determined based on the distance matching result, which can be divided into the following two situations: The first matching result indicates that there is a pollution source point near the parking center point. When the distance matching result is the first matching result, the current operation status of the slag truck is determined to be an intra-domain vehicle. Specifically, it indicates that the vehicle is active near the pollution source, and the administrative area where the pollution source point is located represents the administrative area where the parking center point of the point is located (generally, the two are consistent, and the boundary position may be different). Considering the administrative information of the pollution source, it is considered that the vehicle is a normal intra-domain vehicle in this administrative area, that is, an intra-domain operating vehicle, rather than a transit vehicle.

[0037] The second matching result indicates that there is no pollution source near the stop center point and the stay time at the stop center point exceeds the threshold. When the distance matching result is the second matching result, the current operating status of the slag truck is determined to be an in-domain vehicle. Specifically, whether it is an in-domain vehicle can be determined based on the set stay time threshold. For example, if the total stay time of the vehicle in a certain area exceeds 30 minutes, it means that the vehicle has a temporary stop behavior in the area that is obviously different from waiting for traffic lights. The vehicle can be considered to be an in-domain operating vehicle in this area.

[0038] In summary, the present invention can also perform grid visualization of the trajectory distribution of all transit or intra-domain vehicles in the region based on the administrative region information to which the original trajectory of the vehicle belongs. The result can clearly show the traffic flow changes of slag trucks on each section of the road network, and give the distribution of vehicles in different states on the road; at the same time, based on the vehicle stop point center data results carrying administrative region information, the system can quickly locate the illegal locations, which greatly facilitates the relevant departments to implement environmental protection supervision measures.

[0039] Example 2 A cross-border status determination system for a slag truck based on trajectory data, comprising: Track data acquisition module: obtain the current track point of the current slag truck in real time, add the current track point to the corresponding track data in chronological order and update the track data, map the current track point on the regional map to obtain the corresponding current administrative area, and obtain the pollution source point in the administrative area; Track point judgment module: judges whether the track points in the track data are only located in the current administrative area, and determines the cross-border status of the current slag truck based on the judgment results; Stop point group judgment module: judge whether there is a stop point group obtained by screening the trajectory points in the current trajectory data in the current administrative area, and determine the cross-border status of the current slag truck based on the judgment result; Stop center point judgment module: traverse the filtered stop point group to obtain the corresponding stop center point, and match the distance between the stop center point and the pollution source point to determine the current cross-border status of the slag truck.

[0040] Preferably, the stopping center point judgment module includes the following modules: Stop center point acquisition module: traverse all the stop point groups obtained by screening in sequence. In each traversal process, a group of trajectory segments are formed according to the trajectory points in the stop point group, and the corresponding stop center point is obtained according to the point cluster attributes of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; Slag truck operation status determination module: perform distance matching based on the longitude and latitude information of the parking center point and the longitude and latitude information of the pollution source point, use the preset distance threshold to find out whether there is a pollution source point near the parking center point, and determine the current operation status of the slag truck based on the distance matching result.

[0041] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. According to the technical essence of the present invention, within the spirit and principles of the present invention, any simple modification, equivalent replacement and improvement made to the above embodiment still falls within the protection scope of the technical solution of the present invention.

Claims

1. A method for determining the cross-border status of a slag truck based on trajectory data. It is characterized in that The method specifically comprises the following steps: S1: obtain the current track point of the current slag truck in real time, add the current track point to the corresponding track data in chronological order and update the track data, map the current track point on the regional map to obtain the corresponding current administrative area, and obtain the pollution source point in the administrative area; S2: determine in turn whether the track points in the track data are only located in the current administrative area. If so, determine that the current slag truck is an intra-regional vehicle. If not, go to step S3; S3: Determine whether there is a stop point group obtained by screening the track points in the current track data in the current administrative area. If not, determine that the current slag truck is a transit vehicle. If so, go to step S4; S4: Traverse the filtered stop point group to obtain the corresponding stop center point, and match the distance between the stop center point and the pollution source point to determine the current cross-border status of the slag truck.

2. According to claim 1, a method for determining the cross-border status of a slag truck based on trajectory data, It is characterized in that The stop point group is composed of a plurality of track points arranged in chronological order, and the track points are collected in real time by the GPS device carried by the slag truck itself, and one track point corresponds to one administrative area; In S3, the screening process is specifically as follows: a plurality of continuous trajectory points are screened out from the trajectory data as the stop point group according to the time threshold and the distance threshold.

3. According to claim 2, a method for determining the cross-border status of a slag truck based on trajectory data, It is characterized in that The S4 specifically includes the following steps: S41: all the stop point groups obtained by screening are traversed in sequence. In each traversal process, a group of trajectory segments are formed according to the trajectory points in the stop point group, and the corresponding stop center point is obtained according to the point cluster attributes of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; S42: Perform distance matching based on the latitude and longitude information of the stop center point and the latitude and longitude information of the pollution source point, find out whether there is a pollution source point near the stop center point with a preset distance threshold, and determine the current operation status of the slag truck through the distance matching result of the current stop center point and the stay time of the current stop center point.

4. According to claim 3, a method for determining the cross-border status of a slag truck based on trajectory data, It is characterized in that The S41 specifically includes the following steps: S411: Obtaining a preset time threshold and a preset minimum distance threshold; S412: obtaining the track points in the current stop point group arranged in time order, in the initial state, taking the first track point as the other track points, and the second track point as the current track point, calculating the distance difference between the other track points and the current track point, judging whether the distance difference is greater than a preset minimum distance threshold, if so, forming a group of track segments with the other track points and the current track point as the head and tail, obtaining the corresponding stop center point according to the point cluster attribute of the track segment, and obtaining the latitude and longitude information of the stop center point and the corresponding stay duration; if not, going to step S413; S413: Move the current trajectory point downward a little, and determine whether the length of a group of trajectory segments formed by the current trajectory point and other trajectory points as the head and tail exceeds the total length of the current stop point group. If so, end the traversal; if not, enter the next traversal, that is, go to step S412.

5. According to claim 4, a method for determining the cross-border status of a slag truck based on trajectory data, It is characterized in that The trajectory segment includes at least two trajectory points. The total consumption time of the trajectory segment can be obtained according to the time of the trajectory points located at the beginning and the end of the trajectory segment. The total consumption time is compared with a preset time threshold, and the point cluster attribute of the trajectory segment is determined according to the comparison result.

6. According to claim 4, a method for determining the cross-border status of a slag truck based on trajectory data, It is characterized in that The point cluster attributes include dense clustering or sparse clustering; When the total consumption time of a track segment is greater than the preset time threshold, it means that the point cluster attribute of the track segment is densely clustered, and a stop center point can be generated through all the track points in the track segment. The longitude and latitude information of the stop center point is the average of the longitude and latitude information of all the track points in the track segment, and the stay time of the stop center point is the time difference between the two track points at the beginning and the end of the track segment; When the total consumption time of a trajectory segment is less than the preset time threshold, it means that the point cluster attribute of the trajectory segment is sparse. Then all the trajectory points in the trajectory segment are used as their respective stop center points. Starting from the trajectory point at the first position of the trajectory segment, its starting time is set as the i-point time, and the ending time is set as the i+1-point time, and so on.

7. A method for determining the cross-border status of a slag truck based on trajectory data according to claim 6, It is characterized in that The distance matching results include a first matching result and a second matching result; The first matching result indicates that there is a pollution source point near the parking center point. When the distance matching result is the first matching result, it is determined that the current operation status of the slag truck is an in-domain vehicle; The second matching result indicates that there is no pollution source near the stop center point and the stay time at the stop center point exceeds the threshold. When the distance matching result is the second matching result, it is determined that the current operating status of the slag truck is an in-domain vehicle.

8. A cross-border status determination system for slag trucks based on trajectory data. It is characterized in that include: Track data acquisition module: obtain the current track point of the current slag truck in real time, add the current track point to the corresponding track data in chronological order and update the track data, map the current track point on the regional map to obtain the corresponding current administrative area, and obtain the pollution source point in the administrative area; Track point judgment module: judges whether the track points in the track data are only located in the current administrative area, and determines the cross-border status of the current slag truck based on the judgment results; Stop point group judgment module: judge whether there is a stop point group obtained by screening the trajectory points in the current trajectory data in the current administrative area, and determine the cross-border status of the current slag truck based on the judgment result; Stop center point judgment module: traverse the filtered stop point group to obtain the corresponding stop center point, and match the distance between the stop center point and the pollution source point to determine the current cross-border status of the slag truck.

9. A cross-border status determination system for slag trucks based on trajectory data according to claim 8, It is characterized in that The stopping center point judgment module includes the following modules: Stop center point acquisition module: traverse all the stop point groups obtained by screening in sequence. In each traversal process, a group of trajectory segments are formed according to the trajectory points in the stop point group, and the corresponding stop center point is obtained according to the point cluster attributes of the trajectory segment, and the latitude and longitude information of the stop center point and the corresponding stay duration are obtained; Slag truck operation status determination module: perform distance matching based on the longitude and latitude information of the parking center point and the longitude and latitude information of the pollution source point, use the preset distance threshold to find out whether there is a pollution source point near the parking center point, and determine the current operation status of the slag truck based on the distance matching result.

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