Vehicle passing data processing method and electronic equipment

Abstract

The invention discloses a vehicle passing data processing method and electronic equipment, and the method comprises the steps: obtaining the vehicle passing data of a current set time period, and obtaining a track line segment set according to the vehicle passing data; determining at least one abnormal track line segment according to the vehicle passing time corresponding to each track line segment and the directed road network; each snapshot device of the directed road network is composed of nodes, and the directed road network matrix is used for representing the directed road network; for each abnormal track line segment, according to the identifier of the abnormal start snapshot device and the identifier of the abnormal termination snapshot device of the abnormal track line segment, searching in a directed road network matrix, and determining a target snapshot device and a missed shooting data record of the target snapshot device; according to the missed shooting data records corresponding to all the abnormal track line segments, determining the number of target missed shooting data of the target snapshot device; and determining a snapshot rate according to the number of the target missed shooting data and the number of the vehicle passing data of the target snapshot device. And the accuracy and the efficiency of calculating the snapshot rate of the snapshot equipment are improved.

Description

Technical Field

[0001] The present application relates to the technical field of traffic data processing, and in particular to a method and electronic device for processing vehicle passing data. Background Art

[0002] In the intelligent transportation industry, by building intelligent business platforms such as traffic cloud brain and intelligent optimization, we can greatly provide attention and control for intelligent transportation. However, the accuracy of the business data sent back by the front-end equipment has a great impact on the execution effect of these platforms. For example, if the efficiency of a large number of front-end devices cannot be discovered and handled in time, this will cause a decrease in the capture rate of passing vehicles, which will directly affect the judgment of the platform's intelligent algorithm.

[0003] In the related art, a threshold of vehicle passing data is usually set, and when a certain threshold is reached, it is judged as a reduction in efficiency. However, the accuracy of this method is extremely low. In addition, the capture rate can also be calculated by counting vehicles through manual video inspection, which is extremely inefficient. Summary of the invention

[0004] In an exemplary embodiment of the present application, a method for processing vehicle passing data and an electronic device are provided to improve the accuracy and efficiency of calculating the capture rate of a capture device.

[0005] According to a first aspect of an exemplary embodiment, a method for processing vehicle passing data is provided, the method comprising:

[0006] Obtain the vehicle passing data in the current set time period, and obtain a trajectory segment set based on the vehicle passing data; wherein each trajectory segment in the trajectory segment set is composed of points of two capture devices;

[0007] According to the vehicle passing time corresponding to each trajectory segment and the directed road network, at least one abnormal trajectory segment is determined; wherein each capture device of the directed road network is composed of nodes, the directed road network matrix is ​​used to represent the directed road network, the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment;

[0008] For each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, the target capture device and the missed capture data record of the target capture device are searched in the directed road network matrix;

[0009] According to the missed data records corresponding to all abnormal trajectory segments, the number of target missed data of the target capture device is determined;

[0010] The capture rate of the target capture device is determined according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0011] According to a second aspect of the exemplary implementation, there is provided an electronic device, including a processor and a data transmission unit:

[0012] The data transfer unit is configured to perform:

[0013] Get the vehicle passing data in the current set time period;

[0014] The processor is configured to execute:

[0015] According to the vehicle passing time corresponding to each trajectory segment and the directed road network, at least one abnormal trajectory segment is determined; wherein each capture device of the directed road network is composed of nodes, the directed road network matrix is ​​used to represent the directed road network, the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment;

[0016] For each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, the target capture device and the missed capture data record of the target capture device are searched in the directed road network matrix;

[0017] According to the missed data records corresponding to all abnormal trajectory segments, the number of target missed data of the target capture device is determined;

[0018] The capture rate of the target capture device is determined according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0019] According to a third aspect of an exemplary embodiment, a device for processing vehicle passing data is provided, the device comprising:

[0020] The data acquisition unit is used to: acquire the vehicle passing data in the current set time period, and obtain a trajectory segment set according to the vehicle passing data; wherein each trajectory segment in the trajectory segment set is composed of points of two capture devices;

[0021] A determination unit is used to: determine at least one abnormal trajectory segment according to the vehicle passing time corresponding to each trajectory segment and the directed road network; wherein each capture device of the directed road network is composed of nodes, the directed road network matrix is ​​used to represent the directed road network, the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment;

[0022] A search unit is used to: for each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, search in the directed road network matrix to determine the target capture device and the missed capture data record of the target capture device;

[0023] A calculation unit is used to determine the number of target missed data of the target capture device according to the missed data records corresponding to all abnormal trajectory segments;

[0024] The processing unit is used to determine the capture rate of the target capture device according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0025] According to a fourth aspect of an exemplary implementation, a computer storage medium is provided, in which computer program instructions are stored. When the instructions are executed on a computer, the computer executes the method for processing vehicle passing data as in the first aspect.

[0026] In the embodiment of the present application, firstly, a directed road network with capture devices as nodes is constructed through historical vehicle passing data. The directed road network can be represented by a directed road network matrix. The value of each element in the matrix represents the vehicle passing time of a historical trajectory segment. The row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of the historical trajectory segment; secondly, the vehicle passing data of the current set time period is obtained, and then a trajectory segment set is obtained according to the vehicle passing data, and at least one abnormal trajectory segment is determined according to the matching of the vehicle passing time corresponding to each trajectory segment with the directed road network matrix; for For each abnormal trajectory segment, identify the abnormal start capture device identifier and abnormal end capture device identifier of the abnormal trajectory segment; and according to the abnormal start capture device identifier and abnormal end capture device identifier, search in the directed road network matrix to determine the target capture device and the missed data record of the target capture device; according to the missed data records corresponding to all abnormal trajectory segments, determine the number of target missed data of the target capture device; according to the number of target missed data of the target capture device and the number of passing vehicle data of the target capture device, determine the capture rate of the target capture device. Such a design can determine whether there is a missed capture in the current set time period, and determine which capture device is the missed capture, and then determine the capture rate of the capture device with missed capture, thereby improving the accuracy and efficiency of calculating the capture rate of the capture device. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0028] Figure 1 An application scenario diagram of a method for processing vehicle passing data provided by an embodiment of the present application is exemplarily shown;

[0029] Figure 2 A flowchart of a method for processing vehicle passing data provided by an embodiment of the present application is exemplarily shown;

[0030] Figure 3 A schematic diagram exemplarily shows a processing process of obtaining a set of trajectory segments provided by an embodiment of the present application;

[0031] Figure 4 A flowchart of a method for establishing a directed road network matrix provided in an embodiment of the present application is exemplarily shown;

[0032] Figure 5 A flowchart of a method for determining an abnormal trajectory segment provided by an embodiment of the present application is exemplarily shown;

[0033] Figure 6 A flowchart of a method for calculating missed shot data records provided by an embodiment of the present application is exemplarily shown;

[0034] Figure 7 A flowchart of a complete method for processing vehicle passing data provided by an embodiment of the present application is exemplified;

[0035] Figure 8 The following is an exemplary diagram showing a system architecture diagram for processing vehicle passing data provided by an embodiment of the present application;

[0036] Fig. 9 The following is a schematic diagram showing the structure of a device for processing vehicle passing data provided by an embodiment of the present application;

[0037] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application is exemplarily shown. DETAILED DESCRIPTION

[0038] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0039] The intelligent transportation industry has built intelligent business platforms such as traffic cloud brain and intelligent optimization. However, the accuracy of the business data sent back by the front-end equipment has a great impact on the execution effect of these platforms. For example, the decline in efficiency of a large number of front-end equipment cannot be discovered and handled in time, which will cause a decrease in the capture rate of passing vehicles, which will directly affect the judgment of the platform's intelligent algorithm.

[0040] In the related art, a threshold of vehicle passing data is usually set, and when a certain threshold is reached, it is judged as a reduction in efficiency. However, the accuracy of this method is extremely low. In addition, the capture rate can also be calculated by counting vehicles through manual video inspection, which is extremely inefficient.

[0041] To this end, an embodiment of the present application provides a method for processing vehicle passing data, in which directed road network information is determined based on vehicle passing data in a historical time period. Since the value of each element in the directed road network matrix used to represent the directed road network information represents the vehicle passing time of a trajectory segment, the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a trajectory segment. Therefore, the vehicle passing data of the current time period can be processed to obtain a trajectory segment set, and then at least one abnormal trajectory segment is found based on the vehicle passing time and directed road network information corresponding to each trajectory segment. In this way, for each abnormal trajectory segment, the capture device (called the target capture device) of the missed data and the corresponding missed data record can be found. Finally, the capture rate of the target capture device is determined based on the number of target missed data of the target capture device and the number of vehicle passing data of the target capture device. The efficiency of calculating the capture rate and the accuracy of the calculated capture rate are improved.

[0042] After introducing the design ideas of the embodiments of the present application, the following briefly introduces the application scenarios to which the technical solutions of the embodiments of the present application can be applied. It should be noted that the application scenarios introduced below are only used to illustrate the embodiments of the present application and are not limited. In specific implementation, the technical solutions provided by the embodiments of the present application can be flexibly applied according to actual needs.

[0043] refer to Figure 1 , shows an application scenario diagram of a method for processing vehicle passing data, wherein the capture device can be an electronic eye camera, etc.

[0044] To further illustrate the technical solution provided by the embodiment of the present application, this is described in detail below in conjunction with the accompanying drawings and specific implementation methods. Although the embodiment of the present application provides the method operation steps shown in the following embodiments or drawings, more or fewer operation steps may be included in the method based on routine or no creative labor. In the steps where there is no necessary causal relationship logically, the execution order of these steps is not limited to the execution order provided in the embodiment of the present application.

[0045] Combine the following Figure 1 The application scenario shown is shown in Figure 2 A flowchart of a method for processing vehicle passing data is shown to illustrate the technical solution provided in an embodiment of the present application.

[0046] S201: Obtain the vehicle passing data in the current set time period, and obtain a trajectory segment set based on the vehicle passing data.

[0047] Each trajectory segment in the trajectory segment set is composed of points of two capture devices.

[0048] S202: Determine at least one abnormal trajectory segment according to the vehicle passing time and the directed road network corresponding to each trajectory segment.

[0049] Among them, each capture device of the directed road network is composed of nodes, and the directed road network matrix is ​​used to represent the directed road network. The value of each element in the directed road network matrix represents the passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment.

[0050] S203: For each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, search in the directed road network matrix to determine the target capture device and the missed data record of the target capture device.

[0051] S204: Determine the number of target missed data of the target capture device according to the missed data records corresponding to all abnormal trajectory segments.

[0052] S205: Determine the capture rate of the target capture device according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0053] In the embodiment of the present application, firstly, a directed road network with capture devices as nodes is constructed through historical vehicle passing data. The directed road network can be represented by a directed road network matrix. The value of each element in the matrix represents the vehicle passing time of a historical trajectory segment. The row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of the historical trajectory segment; secondly, the vehicle passing data of the current set time period is obtained, and then a trajectory segment set is obtained according to the vehicle passing data, and at least one abnormal trajectory segment is determined according to the matching of the vehicle passing time corresponding to each trajectory segment with the directed road network matrix; for For each abnormal trajectory segment, identify the abnormal start capture device identifier and abnormal end capture device identifier of the abnormal trajectory segment; and according to the abnormal start capture device identifier and abnormal end capture device identifier, search in the directed road network matrix to determine the target capture device and the missed data record of the target capture device; according to the missed data records corresponding to all abnormal trajectory segments, determine the number of target missed data of the target capture device; according to the number of target missed data of the target capture device and the number of passing vehicle data of the target capture device, determine the capture rate of the target capture device. Such a design can determine whether there is a missed capture in the current set time period, and determine which capture device is the missed capture, and then determine the capture rate of the capture device with missed capture, thereby improving the accuracy and efficiency of calculating the capture rate of the capture device.

[0054] Regarding S201, the currently set time period may be the most recent 24 hours. For each vehicle, the vehicle passing data refers to the time taken for the vehicle to pass any two adjacent capture devices.

[0055] Optional, reference Figure 3 , the trajectory segment set can be obtained through steps S201-1 to S201-2:

[0056] S201-1: For each vehicle passing data corresponding to the vehicle, based on the passing time between any two adjacent capture devices, the driving trajectory formed by the vehicle passing data is divided into different trajectory segments.

[0057] In order to improve the accuracy, the vehicle passing data whose passing time between two adjacent capture devices is greater than the time threshold (for example, 5 minutes) is eliminated. For example, if there are n capture devices, represented by P1, ..., Pn respectively, the vehicle passing data can be represented by R, R = (P1→P2, P2→P3, ... Pn-1→Pn), where Pn-1→Pn represents the time it takes for the vehicle to pass from the n-1th capture device to the nth capture device. If there is a vehicle passing time of Px-1→Px that is greater than 5 minutes, R is split with Px as the node, R1 = (P1→P2, P2→P3, ... Px-1→Px), R2 = (Px→Px+1, ... Pn-1→Pn), in this process, invalid data with less than 3 nodes can be discarded to further improve the accuracy.

[0058] The above is a process of processing the passing data of a vehicle. After the passing data of each vehicle is processed in this way, a plurality of processed passing data of each vehicle are obtained.

[0059] Each trajectory data is split into two one-way trajectory segments, so that the passing time between adjacent capture devices in each trajectory segment is less than the time threshold. When the same trajectory segment includes multiple vehicles, the average passing time of each vehicle can be calculated as the average time of the trajectory segment.

[0060] S201 - 2: Determine a set of trajectory segments corresponding to each vehicle as a trajectory segment set.

[0061] As described above, a corresponding trajectory segment can be obtained for each vehicle, so the set of trajectory segments corresponding to each vehicle can be determined as a trajectory segment set.

[0062] In S202, when a track segment has multiple vehicles passing through, the passing time corresponding to the track segment is the average of the passing times of the multiple vehicles. For each track segment, the passing time of the track segment can be compared with the directed road network matrix to determine which track segments are abnormal.

[0063] Each capture device of a directed road network is composed of nodes. The directed road network matrix is ​​used to represent the directed road network. The value of each element in the directed road network matrix represents the passing time of a historical trajectory segment. The row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment.

[0064] First, refer to Figure 4 , the process of establishing a directed road network matrix is ​​explained.

[0065] S401: Acquire historical vehicle passing data of a historical time period, and obtain a historical trajectory segment set according to the historical vehicle passing data.

[0066] For the implementation method of this step, refer to the process of obtaining the set of trajectory line segments in the current time period in step S201, which will not be elaborated here.

[0067] In addition, in order to improve the accuracy of establishing the directed road network matrix, after obtaining the set of historical trajectory line segments, each historical trajectory line segment in this set can be traversed, and some historical trajectory line segments that do not meet the requirements can be discarded.

[0068] For example, for the historical trajectory line segment Li, which represents the trajectory line segment between the capture device Pi and Pj, with a time consumption of Ti, check whether there exists Px (meeting the condition: there exist Lx(Pi→Px) and Ly(Px→Pj)). If it exists, for the time consumptions Tx and Ty of Lx and Ly, calculate the total time consumption Txy = Tx + Ty. If |Txy - Ti| < Ti×0.1, discard Li. Such a design can avoid the problem that the obtained set of historical trajectory line segments is inaccurate due to inaccurate splitting during the splitting of one-way line segments between two points.

[0069] S402: Determine the passing vehicle time between each historical trajectory line segment in the set of historical trajectory line segments.

[0070] Among them, the passing vehicle time between each historical trajectory line segment can be obtained according to the passing vehicle data.

[0071] S403: Use the identifier of the starting capture device of each historical trajectory line segment as the row number of the element, the identifier of the ending capture device as the column number of the element, and the passing vehicle time as the value of the element to obtain the directed road network matrix.

[0072] For example, the value of the element in the 3rd row and 4th column of the matrix is the passing vehicle time of the trajectory line segment whose starting capture device identifier is P3 and ending capture device identifier is P4.

[0073] In the actual process, there is also such a situation: if there is an element that does not correspond to any historical trajectory line segment, determine the value of the element to be 0. In this case, it means that the two capture devices represented by the element are not connected.

[0074] In a specific example, if there are n capture devices, the directed road network matrix can be represented by M n×n ; T 23 represents the passing vehicle time of the historical trajectory line segment between capture device P2 and capture device P3.

[0075]

[0076] Secondly, refer to Figure 5The process of comparing the passing time of the trajectory segment with the directed road network information and then determining the abnormal trajectory segment is described through steps S202-1 to S202-3:

[0077] S202-1: For any trajectory segment, determine a first identifier of a starting capture device and a second identifier of an ending capture device of the trajectory segment.

[0078] According to the driving direction of the vehicle of the trajectory segment, the starting capture device and the ending capture device of the two capture devices can be distinguished. In addition, the first identifier of the starting capture device and the second identifier of the ending capture device can be determined.

[0079] S202-2: Use the first identifier and the second identifier as the row and column of the element respectively, search in the directed road network matrix, and determine the element value corresponding to the trajectory segment in the directed road network matrix.

[0080] Since the process of establishing the directed road network matrix is ​​the process of assigning the passing time between the track segments, the first identifier and the second identifier are respectively used as the row and column of the element to search in the directed road network matrix to find the corresponding element value.

[0081] S202-3: If the element value satisfies the set condition, the trajectory segment is determined to be an abnormal trajectory segment.

[0082] Among them, the setting condition is the same as the setting condition when constructing the directed road network matrix. For example, the setting condition is to take a value of 0. Therefore, in the search process for any trajectory segment, if the corresponding element value is found to be 0, it can be determined that the trajectory segment is an abnormal trajectory segment.

[0083] In S203, for each abnormal trajectory segment, an abnormal start capture device identifier and an abnormal end capture device identifier of the abnormal trajectory segment are identified.

[0084] Then, according to the abnormal start capture device identifier and the abnormal end capture device identifier, the target capture device and the missed capture data records of the target capture device are determined by searching in the directed road network matrix.

[0085] Exemplary, reference Figure 6 , the calculation process of missed shot data record can be realized through steps S203-1 to S203-5:

[0086] S203-1: Determine the abnormal start capture device identifier as the initial row identifier, and determine the abnormal end capture device identifier as the initial column identifier.

[0087] For example, the abnormal start capture device identifier is 1, and the abnormal end capture device identifier is 3, then the initial row identifier is 1, and the initial column identifier is 3.

[0088] S203-2: In the directed road network matrix, search for multiple elements corresponding to the initial row identifier, and find the target element among the multiple elements.

[0089] Among them, in the directed road network matrix, multiple elements in the first row are searched, and the elements in the first row are screened according to the set conditions, and the elements that meet the set conditions are found, which are called target elements, and the column identifier of the column where the target element is located is not equal to the initial row identifier and the initial column identifier. Optionally, the set condition can be set to 0.

[0090] For example, the directed road network matrix is ​​a 10*10 matrix with 10 elements in the first row. Remove the element in the first row and first column (this element represents the trajectory segment from capture device 1 to capture device 1, which is unreasonable) and the element in the third column (this element represents the trajectory segment of this time). There are a total of 8 elements left. Among these 8 elements, find the elements with values ​​greater than 0. For example, the elements greater than 0 found are element A in the first row and sixth column and element B in the first row and ninth column.

[0091] S203-3: Using the column identifier of the target element as a new row identifier, find the element corresponding to the new row identifier and the initial column identifier.

[0092] For the target element A, the new row identifier is 6, and the element A1 at the 6th row and 3rd column is found; for the target element B, the new row identifier is 9, and the element B1 at the 9th row and 3rd column is found.

[0093] S203-4: If the found element meets the set condition, it is determined that the capture device corresponding to the new row identifier is the target capture device.

[0094] If the value of element A1 is 0, the target capture device is the capture device identified as 9, or, if the value of element B1 is 0, the target capture device is the capture device identified as 9.

[0095] S203-5: Generate a missing vehicle data record of the target capture device.

[0096] In the above example, if the values ​​of elements A1 and B1 are both 0, it is determined that the number of missed vehicle data records of the target capture device 9 is 2.

[0097] In S204, the number of target missed data of the target capture device is determined according to the missed data records corresponding to all abnormal trajectory segments.

[0098] The above example shows a missed vehicle data record for an abnormal trajectory segment. In actual applications, the number of missed vehicle data records corresponding to all abnormal trajectory segments is added together to obtain the number of target missed vehicle data of the target capture device.

[0099] In S205, the capture rate of the target capture device is determined according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0100] Taking the target capture device 9 as an example, the number of target missed data is C1, and the number of passing vehicle data is C2, then its capture rate Rate=C2 / (C1+C2)*100% is determined.

[0101] In the actual application process, after obtaining the capture rate of each capture device, for any target device, if the capture rate of the target capture device is less than the set capture rate threshold, an alarm message is generated, and the alarm message includes the target capture device identifier and / or the capture rate of the target capture device. With this design, relevant personnel can take responsive measures according to the alarm message.

[0102] In order to make the technical solution of this application more perfect, refer to Figure 7 , using a complete process of processing vehicle passing data to illustrate.

[0103] S701: Obtain vehicle passing data in the current set time period.

[0104] S702: For each vehicle passing data corresponding to the vehicle, based on the passing time between any two adjacent capture devices, the driving trajectory formed by the vehicle passing data is divided into different trajectory segments.

[0105] S703: Determine a set of trajectory segments corresponding to each vehicle as a trajectory segment set.

[0106] S704: For any trajectory segment, determine a first identifier of a starting capture device and a second identifier of an ending capture device of the trajectory segment.

[0107] S705: Using the first identifier and the second identifier as the row and column of the element respectively, searching in a directed road network matrix used to represent the directed road network, and determining the element value corresponding to the trajectory segment in the directed road network matrix.

[0108] S706: If the element value satisfies the set condition, the trajectory segment is determined to be an abnormal trajectory segment.

[0109] S707: For each abnormal trajectory segment, determine the identifier of the abnormal starting capture device as the initial row identifier, and determine the identifier of the abnormal ending capture device as the initial column identifier.

[0110] S708: In the directed road network matrix, search for multiple elements corresponding to the initial row identifier, and find the target element among the multiple elements.

[0111] S709: Using the column identifier of the target element as a new row identifier, searching for an element corresponding to the new row identifier and the initial column identifier.

[0112] S710: If the found element meets the set condition, the capture device corresponding to the new row identifier is determined as the target capture device.

[0113] S711: Generate a missing vehicle data record of the target capture device.

[0114] S712: Determine the number of target missed data of the target capture device according to the missed data records corresponding to all abnormal trajectory segments.

[0115] S713: Determine the capture rate of the target capture device according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0116] S714: If the capture rate of the target capture device is less than the set capture rate threshold, an alarm message is generated.

[0117] The specific implementation method of each step in this embodiment can refer to the aforementioned related steps and will not be repeated here.

[0118] In the embodiment of the present application, a directed road network with capture devices as nodes is first constructed through historical vehicle passing data as the basic data for detection, and is continuously updated. A statistical analysis is performed on the upstream and downstream vehicle passing data of the capture device to be detected, and the vehicle passing data that has passed the upstream and downstream nodes but has not been captured by the capture device to be detected is counted to obtain the number of missed vehicle passing data. The number of vehicle passing data captured by the capture device to be detected on that day is counted, and the capture rate of that day is calculated. Such a design automatically analyzes and produces directed road network data based on business data, and counts the capture rate of the waypoints based on the directed road network data, so as to analyze whether there is a capture efficiency reduction in the equipment. Compared with the traditional solution for configuring vehicle passing data thresholds, it saves implementation and maintenance costs, has a higher level of intelligence, and reduces subjective experience interference.

[0119] Figure 8A system architecture diagram for processing vehicle passing data provided in an embodiment of the present application, the system includes a data collection module, a data processing module, a data application module and an alarm module. Among them, the data collection module configures the basic data of the capture device points and collects the vehicle passing business data; the data processing module generates directed road network information in conjunction with the capture device points and vehicle passing data, and then analyzes and calculates the capture devices with missed capture and the number of missed data; the data application module uses the number of missed data and the number of captured vehicle passing data to calculate the capture rate, and compares it with the capture rate threshold, and then determines whether the corresponding capture device has degraded, and notifies the result to the user's terminal device.

[0120] like Fig. 9 As shown, based on the same inventive concept, an embodiment of the present application provides a device for processing vehicle passing data, which includes a data acquisition unit 91, a determination unit 92, a search unit 93, a calculation unit 94 and a processing unit 95.

[0121] The data acquisition unit 91 is used to: acquire the vehicle passing data in the current set time period, and obtain a trajectory segment set according to the vehicle passing data; wherein each trajectory segment in the trajectory segment set is composed of points of two capture devices;

[0122] The determination unit 92 is used to determine at least one abnormal trajectory segment according to the vehicle passing time corresponding to each trajectory segment and the directed road network; wherein each capture device of the directed road network is composed of nodes, the directed road network matrix is ​​used to represent the directed road network, the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment;

[0123] The search unit 93 is used to: for each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, search in the directed road network matrix to determine the target capture device and the missed capture data record of the target capture device;

[0124] The calculation unit 94 is used to determine the number of target missed data of the target capture device according to the missed data records corresponding to all abnormal trajectory segments;

[0125] The processing unit 95 is used to determine the capture rate of the target capture device according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0126] In an optional implementation, the data acquisition unit 91 is specifically used to:

[0127] For each vehicle passing data corresponding to the vehicle, based on the passing time between any two adjacent capture devices, the driving trajectory formed by the passing data is divided into different trajectory segments; wherein the passing time between adjacent capture devices in each trajectory segment is less than the time threshold;

[0128] A set of trajectory segments corresponding to each vehicle is determined as a trajectory segment set.

[0129] In an optional implementation, the determination unit 92 is specifically configured to: determine, for any trajectory segment, a first identifier of a starting capture device and a second identifier of an ending capture device of the trajectory segment;

[0130] Using the first identifier and the second identifier as the row and column of the element respectively, searching in the directed road network matrix used to represent the directed road network information, and determining the element value corresponding to the trajectory segment in the directed road network matrix;

[0131] If the element value meets the set conditions, the trajectory segment is determined to be an abnormal trajectory segment.

[0132] In an optional implementation manner, the searching unit 93 is specifically configured to:

[0133] Determine the abnormal start capture device identifier as the initial row identifier, and determine the abnormal end capture device identifier as the initial column identifier;

[0134] In a directed road network matrix, multiple elements corresponding to an initial row identifier are searched, and a target element is found among the multiple elements; wherein the value of the target element satisfies a set condition, and the column identifier of the column where the target element is located is not equal to both the initial row identifier and the initial column identifier;

[0135] Use the column identifier of the target element as the new row identifier and find the element corresponding to the new row identifier and the initial column identifier;

[0136] If the found element meets the set condition, the capture device corresponding to the new row identifier is determined to be the target capture device;

[0137] Generates the missed vehicle data record of the target capture device.

[0138] In an optional implementation, the method further includes a calculation unit, which is used to determine the directed road network matrix in the following manner:

[0139] Obtain historical vehicle passing data for a historical time period, and obtain a set of historical trajectory segments based on the historical vehicle passing data;

[0140] Determine the vehicle passing time between each historical trajectory segment in the historical trajectory segment set;

[0141] The identifier of the starting capture device of each historical trajectory segment is used as the row number of the element, the identifier of the ending capture device is used as the column number of the element, and the passing time is used as the value of the element to obtain a directed road network matrix.

[0142] In an optional implementation, the computing unit is further configured to:

[0143] If there is an element that does not correspond to any historical trajectory segment, the element is determined to take the value according to the set value.

[0144] In an optional embodiment, it also includes an alarm unit, which is used to generate an alarm message after determining the capture rate of the target capture device, if the capture rate of the target capture device is less than a set capture rate threshold; wherein the alarm information includes the identification of the target capture device and / or the capture rate of the target capture device.

[0145] Since the device is the device in the method in the embodiment of the present application, and the principle of solving the problem by the device is similar to that of the method, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0146] like Fig.10 As shown, based on the same inventive concept, an embodiment of the present application provides an electronic device, including a processor 101 and a data transmission unit 102:

[0147] The data transmission unit 102 is configured to perform:

[0148] Get the vehicle passing data in the current set time period;

[0149] The processor 101 is configured to execute:

[0150] A trajectory segment set is obtained according to the vehicle passing data; wherein each trajectory segment in the trajectory segment set is composed of points of two capture devices;

[0151] According to the vehicle passing time corresponding to each trajectory segment and the directed road network, at least one abnormal trajectory segment is determined; wherein each capture device of the directed road network is composed of nodes, the directed road network matrix is ​​used to represent the directed road network, the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of a historical trajectory segment;

[0152] For each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, the target capture device and the missed capture data record of the target capture device are searched in the directed road network matrix;

[0153] According to the missed data records corresponding to all abnormal trajectory segments, the number of target missed data of the target capture device is determined;

[0154] The capture rate of the target capture device is determined according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

[0155] In an optional implementation, the processor 101 is specifically configured to execute:

[0156] For each vehicle passing data corresponding to the vehicle, based on the passing time between any two adjacent capture devices, the driving trajectory formed by the passing data is divided into different trajectory segments; wherein the passing time between adjacent capture devices in each trajectory segment is less than the time threshold;

[0157] A set of trajectory segments corresponding to each vehicle is determined as a trajectory segment set.

[0158] In an optional implementation, the processor 101 is specifically configured to execute:

[0159] For any trajectory segment, determine a first identifier of a starting capture device and a second identifier of an ending capture device of the trajectory segment;

[0160] Using the first identifier and the second identifier as the row and column of the element respectively, searching in the directed road network matrix used to represent the directed road network information, and determining the element value corresponding to the trajectory segment in the directed road network matrix;

[0161] If the element value meets the set conditions, the trajectory segment is determined to be an abnormal trajectory segment.

[0162] In an optional implementation, the processor 101 is specifically configured to execute:

[0163] Determine the abnormal start capture device identifier as the initial row identifier, and determine the abnormal end capture device identifier as the initial column identifier;

[0164] In a directed road network matrix, multiple elements corresponding to an initial row identifier are searched, and a target element is found among the multiple elements; wherein the value of the target element satisfies a set condition, and the column identifier of the column where the target element is located is not equal to both the initial row identifier and the initial column identifier;

[0165] Use the column identifier of the target element as the new row identifier and find the element corresponding to the new row identifier and the initial column identifier;

[0166] If the found element meets the set condition, the capture device corresponding to the new row identifier is determined to be the target capture device;

[0167] Generates the missed vehicle data record of the target capture device.

[0168] In an optional implementation, the processor 101 is specifically configured to execute and obtain the directed road network matrix in the following manner:

[0169] Obtain historical vehicle passing data for a historical time period, and obtain a set of historical trajectory segments based on the historical vehicle passing data;

[0170] Determine the vehicle passing time between each historical trajectory segment in the historical trajectory segment set;

[0171] The identifier of the starting capture device of each historical trajectory segment is used as the row number of the element, the identifier of the ending capture device is used as the column number of the element, and the passing time is used as the value of the element to obtain a directed road network matrix.

[0172] In an optional implementation, the processor 101 is further configured to execute:

[0173] If there is an element that does not correspond to any historical trajectory segment, the element is determined to take the value according to the set value.

[0174] In an optional implementation, after determining the capture rate of the target capture device, the processor 101 is specifically configured to execute:

[0175] If the capture rate of the target capture device is less than the set capture rate threshold, an alarm message is generated; wherein the alarm message includes the identifier of the target capture device and / or the capture rate of the target capture device.

[0176] An embodiment of the present application also provides a computer storage medium, in which computer program instructions are stored. When the instructions are executed on a computer, the computer executes the steps of the above-mentioned method for processing vehicle passing data.

[0177] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0178] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0179] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0180] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0181] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for processing vehicle passing data, characterized in that: include: Obtaining vehicle passing data in a currently set time period, and obtaining a trajectory segment set according to the vehicle passing data; wherein each trajectory segment in the trajectory segment set is composed of points of two capture devices; According to the vehicle passing time corresponding to each trajectory segment and the directed road network, at least one abnormal trajectory segment is determined; wherein the directed road network is composed of various capture devices as nodes, and the directed road network matrix is ​​used to represent the directed road network, and the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of the historical trajectory segment; For each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, search in the directed road network matrix to determine the target capture device and the missed data record of the target capture device; Determine the number of target missed data of the target capture device according to the missed data records corresponding to all abnormal trajectory segments; The capture rate of the target capture device is determined according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

2. The method according to claim 1, characterized in that The step of obtaining a set of trajectory segments according to the vehicle passing data includes: For each vehicle passing data corresponding to the vehicle, based on the passing time between any two adjacent capture devices, the driving trajectory formed by the passing data is divided into different trajectory segments; wherein the passing time between the two capture devices of each trajectory segment is less than the time threshold; A set of trajectory segments corresponding to each vehicle is determined as a trajectory segment set.

3. The method according to claim 1, characterized in that The step of determining at least one abnormal trajectory segment according to the vehicle passing time and the directed road network corresponding to each trajectory segment includes: For any trajectory segment, determine a first identifier of a starting capture device and a second identifier of an ending capture device of the trajectory segment; Using the first identifier and the second identifier as the row and column of an element respectively, searching in a directed road network matrix used to represent the directed road network, and determining the value of the element corresponding to the trajectory segment in the directed road network matrix; If the value of the element meets the set condition, the trajectory segment is determined to be an abnormal trajectory segment.

4. The method according to claim 1, characterized in that: The method of searching in the directed road network matrix according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment to determine the target capture device and the missed data record of the target capture device includes: Determine the identifier of the abnormal start capture device as an initial row identifier, and determine the identifier of the abnormal end capture device as an initial column identifier; In the directed road network matrix, multiple elements corresponding to the initial row identifier are searched, and a target element is found among the multiple elements; wherein the value of the target element satisfies a set condition, and the column identifier of the column where the target element is located is not equal to both the initial row identifier and the initial column identifier; Using the column identifier of the target element as a new row identifier, searching for an element corresponding to the new row identifier and the initial column identifier; If the found element meets the set condition, determining the capture device corresponding to the new row identifier as the target capture device; Generate a missing vehicle data record of the target capture device.

5. The method according to claim 1, characterized in that The directed road network matrix is ​​obtained in the following manner: Acquire historical vehicle passing data of a historical time period, and obtain a historical trajectory segment set according to the historical vehicle passing data; Determine the vehicle passing time between each historical trajectory segment in the historical trajectory segment set; The identifier of the starting capture device of each historical trajectory segment is used as the row number of the element, the identifier of the ending capture device is used as the column number of the element, and the passing time is used as the value of the element to construct a directed road network matrix.

6. The method according to claim 5, characterized in that The method further comprises: If there is an element that does not correspond to any historical trajectory segment, it is determined that the element takes a value according to the set value.

7. The method according to any one of claims 1 to 6, characterized in that: After determining the capture rate of the target capture device, the method further includes: If the capture rate of the target capture device is less than the set capture rate threshold, an alarm message is generated; wherein the alarm message includes the identifier of the target capture device and / or the capture rate of the target capture device.

8. An electronic device, characterized in that: Including processor and data transmission unit: The data transmission unit is configured to perform: Get the vehicle passing data in the current set time period; The processor is configured to perform: A trajectory segment set is obtained according to the vehicle passing data; wherein each trajectory segment in the trajectory segment set is composed of points of two capture devices; According to the vehicle passing time corresponding to each trajectory segment and the directed road network, at least one abnormal trajectory segment is determined; wherein each capture device of the directed road network is composed of nodes, and a directed road network matrix is ​​used to represent the directed road network, and the value of each element in the directed road network matrix represents the vehicle passing time of a historical trajectory segment, and the row number and column number of the element respectively represent the identifier of the starting capture device and the identifier of the ending capture device of the historical trajectory segment; For each abnormal trajectory segment, according to the identifier of the abnormal starting capture device and the identifier of the abnormal ending capture device of the abnormal trajectory segment, search in the directed road network matrix to determine the target capture device and the missed data record of the target capture device; Determine the number of target missed data of the target capture device according to the missed data records corresponding to all abnormal trajectory segments; The capture rate of the target capture device is determined according to the number of target missed capture data of the target capture device and the number of vehicle passing data of the target capture device.

9. The electronic device according to claim 8, characterized in that: The processor is specifically configured to execute: For each vehicle passing data corresponding to the vehicle, based on the passing time between any two adjacent capture devices, the driving trajectory formed by the passing data is divided into different trajectory segments; wherein the passing time between the two capture devices of each trajectory segment is less than the time threshold; A set of trajectory segments corresponding to each vehicle is determined as a trajectory segment set.

10. The electronic device according to claim 8, characterized in that: The processor is specifically configured to execute: For any trajectory segment, determine a first identifier of a starting capture device and a second identifier of an ending capture device of the trajectory segment; Using the first identifier and the second identifier as the row and column of an element respectively, searching in a directed road network matrix used to represent the directed road network, and determining the value of the element corresponding to the trajectory segment in the directed road network matrix; If the value of the element meets the set condition, the trajectory segment is determined to be an abnormal trajectory segment.

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