CN111488417A - Information processing method, system, device, equipment and computer storage medium - Google Patents
Information processing method, system, device, equipment and computer storage medium Download PDFInfo
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Abstract
The invention discloses an information processing method, system, device, equipment and computer storage medium. The information processing method comprises the following steps: acquiring position information of a plurality of vehicles; clustering the position information of the vehicles to obtain at least one hot spot region; and determining a construction area according to the at least one hot spot area. According to the embodiment of the invention, the construction area can be accurately and efficiently determined according to the position information of a plurality of vehicles.
Description
Technical Field
The present invention relates to the field of information processing technologies, and in particular, to an information processing method, system, apparatus, device, and computer storage medium.
Background
In urban traffic management, because the management difficulty of key vehicles such as engineering vehicles is high, the method is always a field of key attention, and because the engineering vehicles have the characteristics of large volume, large load, right-turn blind area and the like, once an accident occurs, serious consequences of casualties are easily caused. Therefore, urban traffic management for engineering vehicles is particularly important.
In general, a construction area in a city is a place where construction vehicles frequently enter and exit, and therefore, in urban traffic management, road safety near the construction area is an object that requires significant attention. However, not all construction areas are registered in the traffic police department, so that the engineering vehicles are more difficult to manage, and further the potential safety hazards of roads around the construction areas are increased.
The existing management method for the engineering vehicle is to install a GPS positioning device on the engineering vehicle to realize the tracking and management of the engineering vehicle installed with the GPS positioning device. However, this management method can only track and manage the construction vehicles equipped with GPS positioning devices, and cannot comprehensively manage all the construction vehicles. In addition, since the corresponding engineering vehicles can only be tracked and managed by using the GPS information, the construction area where the engineering vehicles reside cannot be determined, and thus the road safety near the construction area cannot be managed.
Disclosure of Invention
Embodiments of the present invention provide an information processing method, system, apparatus, device, and computer storage medium, which can accurately and efficiently determine a construction area from position information of a plurality of vehicles.
In one aspect, an embodiment of the present invention provides an information processing method, including:
acquiring position information of a plurality of vehicles;
clustering the position information of the vehicles to obtain at least one hot spot region;
and determining a construction area according to the at least one hot spot area.
Further, the method further comprises:
and carrying out correlation analysis on the position information belonging to at least one hotspot area.
Further, the correlation analysis includes:
and carrying out correlation analysis on the running time information corresponding to the position information belonging to the same hot spot area, and removing the position information of the vehicle with isolated running time.
Further, the correlation analysis further comprises:
and carrying out correlation analysis on the driving direction information corresponding to the position information belonging to the same hot spot area, and removing the position information of the vehicle with a single driving direction.
Further, according to at least one hot spot area, determining a construction area, further comprising:
the method comprises the steps that vehicle parking characteristics of all vehicles are obtained for a plurality of vehicles belonging to the same hot spot area;
determining whether the current hot spot area is an active parking position or not based on a preset mapping relation between the vehicle parking characteristics and the parking position characteristics;
determining the movable parking position as a construction area; wherein,
the vehicle parking feature comprises at least one of: the vehicle running distance and the vehicle parking duration;
the parking position features include: an active parking position and an inactive parking position.
Further, the method further comprises:
and carrying out Geohash coding on the construction area.
Further, the method further comprises:
screening unregistered regions in the construction region based on the encoding result;
and selecting a target area in the unregistered area according to the staying time and the number of the vehicles in the unregistered area, and sending safety prompt information to the target terminals in a preset range corresponding to the target area.
Further, the method further comprises:
acquiring respective global positioning system GPS information of a plurality of vehicles in a preset time period;
GPS information of a plurality of vehicles is corrected by using a hidden Markov model, and the corrected GPS information is used as position information of the plurality of vehicles.
In another aspect, an embodiment of the present invention provides an information processing system, including:
the GPS positioning equipment is used for acquiring the position information of the vehicle;
the information processing device is used for acquiring the position information of the vehicles, clustering the position information of the vehicles to acquire at least one hot spot region, and determining the construction region according to the at least one hot spot region.
In another aspect, an embodiment of the present invention provides an information processing apparatus, including:
an information acquisition unit configured to acquire position information of a plurality of vehicles;
the area determining unit is configured to perform clustering processing on the position information of the plurality of vehicles to obtain at least one hot spot area;
and the analysis processing unit is configured to determine a construction area according to the at least one hot spot area.
In another aspect, an embodiment of the present invention provides an information processing apparatus, where the apparatus includes: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements the information processing method described above.
In still another aspect, an embodiment of the present invention provides a computer storage medium, where computer program instructions are stored, and when the computer program instructions are executed by a processor, the information processing method described above is implemented.
The information processing method, the system, the device, the equipment and the computer storage medium of the embodiment of the invention can perform clustering processing on the acquired position information of a plurality of vehicles, determine at least one hot spot area where the vehicles frequently come in and go out, and then determine the construction area in the at least one hot spot area, thereby directly using the position information of the plurality of vehicles to perform accurate and efficient analysis and mining processing on the construction area.
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In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required to be used in the embodiments of the present invention will be briefly described below, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of an information processing method according to an embodiment of the invention;
FIG. 2 is a flow chart illustrating a method of obtaining location information according to one embodiment of the present invention;
FIG. 3 is a flowchart illustrating a method for determining a construction area according to a hot spot area according to an embodiment of the present invention;
FIG. 4 is a flow chart of an information processing method according to another embodiment of the invention;
FIG. 5 is a flow chart of an information processing method according to another embodiment of the invention;
fig. 6 is a schematic structural diagram of an information processing apparatus provided in an embodiment of the present invention;
fig. 7 is a schematic structural diagram of an information processing apparatus according to another embodiment of the present invention;
fig. 8 is a schematic structural diagram of an information processing apparatus according to still another embodiment of the present invention;
fig. 9 is a schematic diagram of a hardware configuration of an information processing apparatus according to an embodiment of the present invention.
Detailed Description
Features and exemplary embodiments of various aspects of the present invention will be described in detail below, and in order to make objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not to be construed as limiting the invention. It will be apparent to one skilled in the art that the present invention may be practiced without some of these specific details. The following description of the embodiments is merely intended to provide a better understanding of the present invention by illustrating examples of the present invention.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
In order to solve the problem of the prior art, embodiments of the present invention provide a construction area identification method, apparatus, device, and computer storage medium. First, a construction area identification method provided by an embodiment of the present invention will be described below.
Fig. 1 is a flowchart illustrating an information processing method according to an embodiment of the present invention. As shown in fig. 1, the information processing method includes:
s110, acquiring position information of a plurality of vehicles;
s120, clustering the position information of the vehicles to obtain at least one hot spot region;
s130, determining a construction area according to the at least one hot spot area.
Therefore, the embodiment of the invention can perform clustering processing on the acquired position information of the plurality of vehicles, determine at least one hot spot area where the vehicles frequently come in and go out, and then determine the construction area in the at least one hot spot area, thereby directly utilizing the position information of the plurality of vehicles to perform accurate and efficient analysis and mining processing on the construction area.
The vehicle in step S110 of the embodiment of the present invention may be an engineering vehicle that frequently enters and exits a construction area, where the construction area may include a construction site, a removal site, a maintenance site, and the like, and the engineering vehicle may include an excavator, a transport vehicle, a muck truck, a crane, a mixer truck, a bulldozer, a breakdown van, and the like. Therefore, the acquisition of the position information of the plurality of vehicles can be specifically the acquisition of the position information of the plurality of engineering vehicles, the analysis processing of the construction area is performed by directly utilizing the position information of the engineering vehicles, the interference of other vehicles such as private cars, buses and the like on the analysis processing can be reduced, the information processing amount in the analysis processing is reduced, and the analysis processing efficiency and the analysis processing accuracy are improved. Fig. 2 is a flowchart illustrating a method of acquiring location information according to an embodiment of the present invention. As shown in fig. 2, in step S110 according to the embodiment of the present invention, a specific method for acquiring location information of a plurality of vehicles includes:
s111, acquiring respective Global Positioning System (GPS) information of a plurality of vehicles in a preset time period;
and S112, correcting the GPS information of the plurality of vehicles by using the hidden Markov model, and using the corrected GPS information as the position information of the plurality of vehicles.
In step S111 of the embodiment of the present invention, GPS information of each of vehicles (e.g., engineering vehicles) requiring position information acquisition may be acquired within a predetermined period of time by installing a GPS positioning device on the vehicle. After the respective GPS information of the vehicles is obtained, the GPS information can be preprocessed, information such as invalid information, repeated information and null value information in the GPS information is removed, and the preprocessed GPS information is utilized for subsequent processing.
The predetermined time period in step S111 of the embodiment of the present invention may be 1 month, a quarter, or even shorter or longer, and may be set as needed. In order to ensure that there is a sufficient amount of position information to accurately determine the construction area while ensuring timeliness of determining the construction area, in the embodiment of the present invention, the predetermined period of time is preferably set to 1 month.
In step S112 of the embodiment of the present invention, the drift information in the GPS information preprocessed in step S111 may be processed to correct the GPS information, so that the corrected GPS information is used as the position information of the vehicle.
In the embodiment of the invention, a map matching algorithm using a Hidden Markov Model (HMM) is adopted, which is different from a traditional method for directly removing drift information when the drift information is processed, the map matching algorithm can match longitude and latitude coordinates corresponding to GPS information of a vehicle with city road network geographic information, the longitude and latitude coordinates corresponding to a plurality of pieces of GPS information forming a complete track of the vehicle are used as input, and the real position of a drift position is presumed according to the longitude and latitude coordinates of the GPS information before and after the drift information and the shape of the city road network, so that the drift position information is corrected. Therefore, compared with the traditional method for processing the drift information, the embodiment of the invention can improve the data integrity and the accuracy of the corrected GPS information.
The principle of the hidden markov model according to the embodiment of the present invention is based on a markov chain. The principle of the Markov chain is to predict the future state, state X, using only the current state given the current knowledge or informationn+1Only with state XnRelated, state Xn+1And state XnAll the previous states are irrelevant, and the mathematical expression is as follows:
Pr(Xn+1＝x|X1＝x1,X2＝x2,…,Xn＝xn)＝Pr(Xn+1＝x|Xn＝xn)
wherein, X represents the state at the time of 1, 2, … …, n, and X represents the information data at the time of 1, 2, … …, n.
Thus, the principle of the hidden markov model is that the above-mentioned markov states are not visible, while some variables affected by the markov states are visible.
For the map matching algorithm, the GPS information (visible variable) is used to estimate the true position (hidden state) of the vehicle. Among them, the most important elements for estimating the true position using GPS information are the emission probability (observation probability) and the state transition probability.
In the embodiment of the invention, the transmission probability is the probability of the GPS information on the road section calculated by the distance of the GPS information from the adjacent road section. The smaller the distance between the GPS information and the road section is, the greater the probability of the GPS information on the road section is. Specifically, the calculation formula of the emission probability is:
wherein, p (z)t|ri) To the emission probability, ztIs GPS information, riIs a road section, xt,iIs the closest position on the road segment to the GPS information, σzIs the standard deviation of the GPS information.
The state transition probability is determined according to the proximity degree of the distance between the front position and the rear position on the road section and the distance between the front GPS information and the rear GPS information. The closer the proximity, the greater the probability of state transition. Specifically, the calculation formula of the state transition probability is:
dt＝|‖zt-zt+1‖great circle-‖xt,i-xt+1,j‖route|
wherein z ist+1Is the next GPS information, xt+1,iThe parameters sigma and β are two basic adjustable parameters in a map matching algorithm, the larger sigma represents the higher noise in the expected GPS information, the larger β represents the higher inclusion of the indirectly connected road section, and the proper adjustment of sigma and β can enlarge the inclusion of the map matching algorithm on the noise of the GPS information, so that the drift information can be matched to the road section closest to the last GPS information and the next GPS information, and the purpose of restoring the real position of the drift information as much as possible is achieved.
After the transmission probability and the state transition probability of the drift information are determined, the position on the road section can be matched according to the transmission probability and the state matching probability, and the drift information is corrected by utilizing longitude and latitude coordinates corresponding to the matched position, so that the corrected GPS information is obtained.
In step S120 of the embodiment of the present invention, it is preferable to perform clustering processing on the position information of the plurality of vehicles by using a Density-based clustering algorithm (DBSCAN). The DBSCAN algorithm may separate the location information filtering into parking location and mobile location. Specifically, when a hot spot area where the vehicle may frequently stop is determined, the position information in and around the hot spot area is dense, and the position information generated when the vehicle moves belongs to an isolated point from a global perspective and will not be regarded as the hot spot area.
Specifically, in the embodiment of the present invention, the DBSCAN algorithm may be used to divide the location information belonging to the area with dense location information into a cluster (class), where the central point of the cluster (class) is most likely the parking location where vehicles are densely parked, such as a crossing, a gas station, a garage or a construction site where engineering vehicles are heavily trafficked and are often congested. The position information belonging to the area with sparse position information may be position information generated when the vehicle moves, and the position information does not belong to any cluster (class) because the spatial distribution of the position information in the area is sparse, and can be eliminated as noise. After the noise point is eliminated, a plurality of clusters (classes) formed by the remaining position information can form a plurality of hot spot regions according to the present invention.
In the embodiment of the present invention, whether an area corresponding to a cluster (class) is an area with dense location information may be determined according to whether the number of location information corresponding to the cluster (class) reaches the set minimum number of locations, and when the number of location information reaches the set minimum number of locations, the area may be determined to be an area with dense location information, that is, a hot spot area.
It should be noted that, in the embodiment of the present invention, the method for clustering the position information of the plurality of vehicles may also use a kernel-based clustering algorithm such as Kmeans, a vehicle speed-based clustering algorithm, a residence time-based clustering algorithm, or a hybrid clustering algorithm, in addition to the DBSCAN algorithm.
However, compared with other clustering algorithms, the DBSCAN algorithm adopted in the embodiment of the present invention has the following advantages:
the DBSCAN algorithm does not need to determine the total number of clusters (classes) to be clustered in advance, and only needs to set a density numerical range (eps) and a minimum position number (p), so that all hot spot areas can be analyzed in a self-adaptive manner, and high-precision clustering processing is realized; meanwhile, the DBSCAN algorithm has low complexity and can cluster the position information of hundreds of billions of levels; in addition, the DBSCAN algorithm can also be used for directly clustering multi-dimensional data, such as longitude and latitude data (belonging to two-dimensional data), the multi-dimensional data does not need to be clustered after being converted into one-dimensional data, and the use is convenient.
However, in the hot spot area obtained by directly clustering with the DBSCAN algorithm in the embodiment of the present invention, since only the spatial relationship between the position information is considered, and the time sequence relationship between the position information is not considered, the position information of some vehicles passing through the areas right in time is included, so that the hot spot area is erroneously determined. In addition, the DBSCAN algorithm does not consider the driving direction of the vehicle, for example, the engineering vehicle may often perform operations such as steering and backing in a construction area, that is, the movement track of the engineering vehicle in the construction area should be cluttered, and when the engineering vehicle slowly travels at a congested intersection and waits for passing, the driving direction of the vehicle usually does not change in a large range, but the DBSCAN algorithm does not distinguish the two, and may also cause an erroneous determination of a hot spot area.
Therefore, in step S130 of the embodiment of the present invention, correlation analysis needs to be performed on the position information belonging to at least one hot spot region, so as to filter at least one clustered hot spot region, and remove a hot spot region that is erroneously determined, so as to determine a construction region.
The correlation analysis refers to analyzing two or more variable elements with correlation, so as to measure the degree of closeness of correlation of the two variable elements. Correlation analysis can be performed only by the existence of a certain relation or probability between variable elements of correlation.
In the embodiment of the present invention, correlation analysis may be performed on the driving time information and the driving direction information in the position information, respectively, so as to solve the above-mentioned problem that the timing relationship between the position information and the driving direction of the vehicle cannot be analyzed by using the DBSCAN algorithm, which may cause an erroneous determination of the hot spot area.
In the embodiment of the present invention, the driving time information may be information acquisition time corresponding to the position information, and the driving direction information may be an included angle between the position information and a reference direction moving along a predetermined direction. Specifically, taking the reference direction as the south-facing direction and the predetermined direction as the clockwise direction as an example, the driving direction information may be an included angle between the position information and the south-facing direction moving in the clockwise direction.
Specifically, correlation analysis may be performed on the travel time information corresponding to the position information belonging to the same hot spot region, and the position information of the vehicle with an isolated travel time is removed, so that a time sequence relationship meeting requirements is ensured between the position information. And then, carrying out correlation analysis on the driving direction information corresponding to the position information belonging to the same hot spot area, and removing the position information of the vehicle with a single driving direction, thereby ensuring that the driving direction of the vehicle meets the requirement. And when the position information which does not meet the requirements is removed according to the correlation analysis, judging the quantity of the position information left in the hot spot area, and when the quantity still can reach the preset minimum position quantity, continuously determining the position information as the hot spot area, otherwise, not determining the position information as the hot spot area.
Wherein, the specific method for carrying out correlation analysis on the running time information corresponding to the position information belonging to the same hot spot area and removing the position information of the vehicle with isolated running time comprises the steps of acquiring the running time information corresponding to the position information belonging to the same hot spot area respectively, if the quantity of the position information with continuous running time information reaches the preset minimum continuous quantity, it is determined that the position information is not the position information of the vehicle whose travel time is isolated, and if the number of the position information whose travel time information is continuous does not reach the preset minimum continuous number, it can be determined that the position information is the position information of the vehicle whose travel time is isolated, the position information needs to be rejected, therefore, the calculation amount of the correlation analysis of the driving direction information is reduced, and the accuracy of the correlation analysis of the driving direction information is improved.
The method comprises the steps of calculating the included angle deviation between two pieces of position information according to the running direction information corresponding to the two pieces of position information at each adjacent moment, calculating the vehicle running included angle deviation of each vehicle in the hot spot area and the average included angle deviation of all the pieces of position information in the whole hot spot area by using the included angle deviations after calculating the included angle deviation between the two pieces of position information at all the adjacent moments, judging whether the average included angle deviation meets a preset deviation threshold value or not, if so, not, eliminating any piece of position information, if not, eliminating all the pieces of position information corresponding to the vehicle with the minimum vehicle running included angle deviation, then recalculating the average included angle deviation of all the pieces of remaining position information in the whole hot spot area, and comparing with the preset deviation threshold value again until the deviation threshold value is met.
For example, the angle corresponding to the travel direction information of the position information at the previous time is a1, the angle corresponding to the travel direction information of the position information at the subsequent time is a2, and the angle deviation b is cosine (a1-a2) calculated from a1 and a 2. And after the included angle deviation between two pieces of position information at all adjacent moments is calculated, calculating the vehicle running included angle deviation of each vehicle in the hot spot area and the average included angle deviation of all pieces of position information in the whole hot spot area by using the included angle deviations. Since the smaller b is, the closer a1 and a2 are, and when b is close to 0, the closer a1 and a2 are, and the traveling direction of the vehicle is basically unchanged, if the average included angle deviation does not meet the deviation threshold, it is indicated that the position information corresponding to the vehicle with basically unchanged traveling direction or the minimum traveling direction, that is, all the position information corresponding to the vehicle with the minimum vehicle traveling included angle deviation, needs to be removed, so that the average included angle deviation can be increased to meet the deviation threshold.
Fig. 3 is a flowchart illustrating a method for determining a construction area according to a hot spot area according to an embodiment of the present invention. As shown in fig. 3, in step S130 of the embodiment of the present invention, determining a construction area according to at least one hot spot area specifically includes:
s210, obtaining vehicle parking characteristics of each vehicle for a plurality of vehicles belonging to the same hot spot area;
s220, determining whether the current hot spot area is an active parking position or not based on a preset mapping relation between the vehicle parking characteristics and the parking position characteristics;
and S230, determining the movable parking position as a construction area.
Wherein the vehicle parking feature comprises at least one of: the vehicle driving distance, the vehicle parking duration, the parking position characteristics include: an active parking position and an inactive parking position.
In the embodiment of the invention, the movable parking position is mainly a parking position where vehicles gather due to activities such as unloading and loading at a construction site, repairing automobiles and the like. The inactive parking positions are mainly parking positions of vehicle aggregation caused by intersections with large vehicle flow and road sections with frequent congestion. It can be seen that only when the parking position is characterized by an active parking position, the corresponding hot spot area is the construction area.
In the embodiment of the invention, the vehicle driving distance and the vehicle parking time are specific to the total driving distance and the total parking time of a plurality of vehicles in the same hot spot area.
Therefore, in the embodiment of the present invention, data such as a vehicle traveling distance and a vehicle parking duration need to be acquired, a parking position is divided into an active parking position and an inactive parking position according to a diversity of the parking position, different special vehicle position characteristics corresponding to different data are used as training data, and then a preset mapping relationship between the vehicle parking characteristics and the parking position characteristics obtained by training through a supervised learning method is used to determine whether a hot spot region is an active parking position, and if the hot spot region is an active parking position, the hot spot region is determined to be a construction region.
In the embodiment of the present invention, the supervised learning method may be a machine learning method, such as logistic regression, support vector machine, and decision tree model, and may also be a deep learning-based method.
Fig. 4 is a flowchart illustrating an information processing method according to another embodiment of the present invention. As shown in fig. 4, after the construction area is determined, the information processing method further includes:
and S140, performing Geohash coding on the construction area.
Specifically, the Geohash coding may be performed by using the position information of the central point of the construction area, so as to convert the construction area into a standard grid area, where the geographic position corresponding to the grid area is the geographic position corresponding to the construction area. The Geohash code may be a 6-bit code, and in this case, the grid region may represent a square region of about 600 meters by 600 meters.
Fig. 5 is a flowchart illustrating an information processing method according to another embodiment of the present invention. As shown in fig. 5, after the construction area is coded, the information processing method further includes:
s150, screening unregistered areas in the construction areas based on the coding results;
and S160, selecting a target area in the unregistered area according to the staying time and the number of the vehicles in the unregistered area, and sending safety prompt information to the target terminal in a preset range corresponding to the target area.
Specifically, the unregistered area may be selected by comparing the Geohash code corresponding to the construction area with the Geohash code corresponding to the construction area that has been registered in the traffic police department. Then, the stay time and the number of vehicles in each unregistered area may be counted, and the unregistered areas may be sorted by integrating the stay time and the number of vehicles, with a plurality of unregistered areas sorted in the front as target areas. The target areas can be used for sending safety prompt information to target terminals (such as mobile terminals, vehicle-mounted equipment and the like) in a predetermined range corresponding to the target areas to remind passing vehicles and pedestrians using the target terminals of paying attention to road safety, and can also be reported to a traffic police department for on-site patrol and investigation. Wherein the number of target areas can be adjusted as required. The passing vehicle includes not only the working vehicle but also other vehicles other than the working vehicle.
The predetermined range corresponding to the target area refers to an area range with a preset radius centered on a center point of the target area. For example, an area range within 500 meters centered on the center point of the target area. For vehicles in the target area, the safety prompt information can be sent to the navigation device of the vehicle, so that the driver can be promoted to drive carefully and pay attention to road safety.
In summary, the information processing method of the embodiment of the invention can determine the construction area by using the displacement information of the vehicle, can automatically analyze the displacement information of a large number of vehicles in the past one month or more, the whole analysis process only needs several hours, and improves the efficiency and accuracy of determining the construction area, thereby improving the efficiency of finding and patrolling the construction area by a traffic police department, and improving the supervision and enforcement efficiency of the construction area by the traffic police department.
The embodiment of the invention also provides an information processing system which comprises at least one GPS positioning device and an information processing device. The GPS positioning equipment is used for acquiring the position information of the vehicles, the information processing device is used for acquiring the position information of the vehicles, clustering the position information of the vehicles to acquire at least one hot spot region, and determining the construction region according to the at least one hot spot region.
Therefore, the embodiment of the invention can perform clustering processing on the acquired position information of the plurality of vehicles, determine at least one hot spot area where the vehicles frequently come in and go out, and then determine the construction area in the at least one hot spot area, thereby directly utilizing the position information of the plurality of vehicles to perform accurate and efficient analysis and mining processing on the construction area.
In the embodiment of the present invention, the information processing apparatus may be an apparatus installed in a monitoring device in a monitoring management center, or may be an apparatus installed in a GPS positioning device, which is not limited herein.
Fig. 6 is a schematic structural diagram of an information processing apparatus according to an embodiment of the present invention. As shown in fig. 6, the information processing apparatus includes:
an information acquisition unit 310 configured to acquire position information of a plurality of vehicles;
the area determining unit 320 is configured to perform clustering processing on the position information of the plurality of vehicles to obtain at least one hot spot area;
an analysis processing unit 330 configured to determine a construction area according to the at least one hot spot area.
Therefore, the embodiment of the invention can perform clustering processing on the acquired position information of the plurality of vehicles, determine at least one hot spot area where the vehicles frequently come in and go out, and then determine the construction area in the at least one hot spot area, thereby directly utilizing the position information of the plurality of vehicles to perform accurate and efficient analysis and mining processing on the construction area.
In the embodiment of the present invention, the information acquiring unit 310 may be further configured to acquire respective GPS information of the plurality of vehicles within a predetermined time period, correct the GPS information of the plurality of vehicles using a hidden markov model, and use the corrected GPS information as the position information of the plurality of vehicles. Therefore, the embodiment of the invention can improve the data integrity and the accuracy of the corrected position information.
In an embodiment of the present invention, the area determination unit 320 may be further configured to perform clustering processing on the position information of the plurality of vehicles by using a density-based clustering algorithm.
In this embodiment of the present invention, the analysis processing unit 330 may be further configured to perform correlation analysis on the position information belonging to at least one hot spot region, so as to filter at least one clustered hot spot region, and remove a hot spot region that is determined incorrectly, so as to determine a construction region.
Specifically, the correlation analysis can be performed on the driving time information corresponding to the position information belonging to the same hot spot area, and the position information of the vehicle with isolated driving time is removed, so that a time sequence relation meeting requirements is ensured between the position information, the calculation amount of the correlation analysis performed on the driving direction information is reduced, and the accuracy of the correlation analysis performed on the driving direction information is improved. And then, carrying out correlation analysis on the driving direction information corresponding to the position information belonging to the same hot spot area, and removing the position information of the vehicle with a single driving direction, thereby ensuring that the driving direction of the vehicle meets the requirement.
In this embodiment of the present invention, the analysis processing unit 330 may be further configured to obtain vehicle parking characteristics of each vehicle for a plurality of vehicles belonging to the same hot spot area; determining whether the current hot spot area is an active parking position or not based on a preset mapping relation between the vehicle parking characteristics and the parking position characteristics; and determining the movable parking position as a construction area. Wherein the vehicle parking feature comprises at least one of: the vehicle driving distance, the vehicle parking duration, the parking position characteristics include: an active parking position and an inactive parking position. Therefore, the method and the device can further improve the accuracy of determining the construction area.
Fig. 7 is a schematic structural diagram of an information processing apparatus according to another embodiment of the present invention. As shown in fig. 7, the information processing apparatus further includes:
and the region coding unit 340 is configured to perform Geohash coding on the construction region.
Fig. 8 is a schematic structural diagram of an information processing apparatus according to still another embodiment of the present invention. As shown in fig. 8, the information processing apparatus further includes:
a region screening unit 350 configured to screen an unregistered region among the construction regions based on an encoding result;
and the area pushing unit 360 is configured to select a target area in the unregistered area according to the staying time and the number of vehicles in the unregistered area, and is used for sending the safety prompting information to the target terminal in the preset range corresponding to the target area.
Therefore, the embodiment of the invention can select the unregistered area which is not registered in the traffic police department, sort the unregistered area by integrating the stay time and the number of vehicles in the construction area, and finally select the target area.
Fig. 9 is a schematic diagram showing a hardware configuration of an information processing apparatus according to an embodiment of the present invention. The information processing apparatus may include a processor 401 and a memory 402 storing computer program instructions.
Specifically, the processor 401 may include a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or may be configured as one or more Integrated circuits implementing embodiments of the present invention.
The processor 401 realizes any one of the information processing methods in the above-described embodiments by reading and executing computer program instructions stored in the memory 402.
In one example, the information processing apparatus may also include a communication interface 403 and a bus 410. As shown in fig. 9, the processor 401, the memory 402, and the communication interface 403 are connected via a bus 410 to complete communication therebetween.
The communication interface 403 is mainly used for implementing communication between modules, apparatuses, units and/or devices in the embodiments of the present invention.
By way of example, and not limitation, buses may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a front-side bus (FSB), a HyperTransport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an InfiniBand interconnect, a Low pin count (L PC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a video electronics standards Association local (V L B) bus, or other suitable bus or combinations of two or more of these.
The information processing device can execute the information processing method in the embodiment of the invention, thereby realizing the information processing method and device described in conjunction with the figures.
In addition, in combination with the information processing method in the above embodiments, the embodiments of the present invention may be implemented by providing a computer storage medium. The computer storage medium having computer program instructions stored thereon; the computer program instructions, when executed by a processor, implement any of the information processing methods in the above embodiments.
It is to be understood that the invention is not limited to the specific arrangements and instrumentality described above and shown in the drawings. A detailed description of known methods is omitted herein for the sake of brevity. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present invention are not limited to the specific steps described and illustrated, and those skilled in the art can make various changes, modifications and additions or change the order between the steps after comprehending the spirit of the present invention.
The functional blocks shown in the above-described structural block diagrams may be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, it may be, for example, an electronic circuit, an Application Specific Integrated Circuit (ASIC), suitable firmware, plug-in, function card, or the like. When implemented in software, the elements of the invention are the programs or code segments used to perform the required tasks. The program or code segments may be stored in a machine-readable medium or transmitted by a data signal carried in a carrier wave over a transmission medium or a communication link. A "machine-readable medium" may include any medium that can store or transfer information. Examples of a machine-readable medium include electronic circuits, semiconductor memory devices, ROM, flash memory, Erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, Radio Frequency (RF) links, and so forth. The code segments may be downloaded via computer networks such as the internet, intranet, etc.
It should also be noted that the exemplary embodiments mentioned in this patent describe some methods or systems based on a series of steps or devices. However, the present invention is not limited to the order of the above-described steps, that is, the steps may be performed in the order mentioned in the embodiments, may be performed in an order different from the order in the embodiments, or may be performed simultaneously.
As described above, only the specific embodiments of the present invention are provided, and it can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the system, the module and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again. It should be understood that the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive various equivalent modifications or substitutions within the technical scope of the present invention, and these modifications or substitutions should be covered within the scope of the present invention.
Claims (12)
1. An information processing method comprising:
acquiring position information of a plurality of vehicles;
clustering the position information of the vehicles to obtain at least one hot spot region;
and determining a construction area according to the at least one hot spot area.
2. The information processing method according to claim 1, wherein the method further comprises:
and carrying out correlation analysis on the position information belonging to the at least one hotspot region.
3. The information processing method according to claim 2, wherein the correlation analysis includes:
and carrying out correlation analysis on the running time information corresponding to the position information belonging to the same hot spot area, and removing the position information of the vehicle with isolated running time.
4. The information processing method according to claim 2, wherein the correlation analysis includes:
and carrying out correlation analysis on the driving direction information corresponding to the position information belonging to the same hot spot area, and removing the position information of the vehicle with a single driving direction.
5. The information processing method of claim 1, wherein the determining a construction area from the at least one hot spot area comprises:
the method comprises the steps that vehicle parking characteristics of all vehicles are obtained for a plurality of vehicles belonging to the same hot spot area;
determining whether the current hot spot area is an active parking position or not based on a preset mapping relation between the vehicle parking characteristics and the parking position characteristics;
determining the movable parking position as a construction area; wherein,
the vehicle parking feature comprises at least one of: the vehicle running distance and the vehicle parking duration;
the parking position features include: an active parking position and an inactive parking position.
6. The information processing method according to claim 1, wherein the method further comprises:
and carrying out Geohash coding on the construction area.
7. The information processing method of claim 6, wherein the method further comprises:
screening unregistered regions in the construction region based on an encoding result;
and selecting a target area in the unregistered area according to the staying time and the number of the vehicles in the unregistered area, and sending safety prompt information to a target terminal in a preset range corresponding to the target area.
8. The information processing method according to claim 1, wherein the method further comprises:
acquiring respective Global Positioning System (GPS) information of the vehicles in a preset time period;
and correcting the GPS information of the plurality of vehicles by using a hidden Markov model, and using the corrected GPS information as the position information of the plurality of vehicles.
9. An information processing system comprising:
the GPS positioning equipment is used for acquiring the position information of the vehicle;
the information processing device is used for acquiring the position information of a plurality of vehicles, clustering the position information of the plurality of vehicles to obtain at least one hot spot area, and determining a construction area according to the at least one hot spot area.
10. An information processing apparatus comprising:
an information acquisition unit configured to acquire position information of a plurality of vehicles;
the area determining unit is configured to perform clustering processing on the position information of the vehicles to obtain at least one hot spot area;
and the analysis processing unit is configured to determine a construction area according to the at least one hot spot area.
11. An information processing apparatus characterized by comprising: a processor and a memory storing computer program instructions;
the processor, when executing the computer program instructions, implements an information processing method as claimed in any one of claims 1 to 8.
12. A computer storage medium, characterized in that the computer storage medium has stored thereon computer program instructions which, when executed by a processor, implement the information processing method according to any one of claims 1 to 8.
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