A method, device and electronic device for identifying abnormal positioning

Abstract

The embodiment of the present invention discloses a positioning anomaly identification method, device and electronic device. Among them, the embodiment of the present invention determines the identification of the target task through the received abnormal judgment request, obtains the attribute information such as the positioning position, recommended position and actual position of the target task according to the identification of the target task, identifies the attribute information such as the positioning position, recommended position and actual position based on the predetermined normal position parameters, and obtains the positioning anomaly identification result of the target task. Therefore, this embodiment can determine the positioning anomaly identification result by setting the normal position parameters between the positioning position, the recommended position and the actual position, and based on the normal position parameters, according to the mutual confirmation of multiple positions, thereby improving the efficiency and accuracy of positioning anomaly identification.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and more specifically, to a positioning anomaly recognition method, device and electronic equipment. Background Art

[0002] User-side positioning will be affected by uncontrollable factors such as the number of satellites, satellite quality and the surrounding environment, such as high-rise buildings, elevated roads, tunnels, etc. If the positioning is inaccurate, it may lead to problems such as inappropriate boarding and alighting point recommendations and difficulty in meeting drivers and passengers. Therefore, how to effectively identify positioning anomalies is an issue that needs to be solved urgently. Summary of the invention

[0003] In view of this, an embodiment of the present invention provides a positioning anomaly identification method, device and electronic device, which improves the efficiency and accuracy of positioning anomaly identification by setting normal position parameters between the positioning position, recommended position and actual position, and determining the positioning anomaly identification result based on the normal position parameters by verifying multiple positions.

[0004] In a first aspect, an embodiment of the present invention provides a method for identifying positioning anomalies, the method comprising:

[0005] receiving an exception determination request, wherein the exception determination request includes an identifier of a target task;

[0006] Acquire attribute information of the target task according to the identifier of the target task, wherein the attribute information of the target task includes a positioning position, a recommended position, and an actual position;

[0007] The attribute information is identified based on predetermined normal position parameters to obtain a positioning anomaly identification result of the target task.

[0008] In a second aspect, an embodiment of the present invention provides a positioning abnormality identification device, the device comprising:

[0009] A request receiving unit, configured to receive an abnormality determination request, wherein the abnormality determination request includes an identifier of a target task;

[0010] an information acquisition unit, configured to acquire attribute information of the target task according to the identifier of the target task, wherein the attribute information of the target task includes a positioning position, a recommended position, and an actual position;

[0011] The identification unit is configured to identify the attribute information based on a predetermined normal position parameter to obtain a positioning abnormality identification result of the target task.

[0012] In a third aspect, an embodiment of the present invention provides an electronic device, comprising a memory and a processor, wherein the memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method as described above.

[0013] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described above is implemented.

[0014] In a fifth aspect, an embodiment of the present invention provides a computer program product, which, when executed on a computer, enables the computer to execute the method described above.

[0015] The embodiment of the present invention determines the identification of the target task through the received abnormal determination request, obtains the attribute information such as the positioning position, recommended position and actual position of the target task according to the identification of the target task, identifies the attribute information such as the positioning position, recommended position and actual position based on the predetermined normal position parameters, and obtains the positioning abnormality identification result of the target task. Therefore, this embodiment can determine the positioning abnormality identification result by setting the normal position parameters between the positioning position, the recommended position and the actual position, and based on the normal position parameters, according to the mutual verification of multiple positions, thereby improving the efficiency and accuracy of positioning abnormality identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other objects, features and advantages of the present invention will become more apparent through the following description of the embodiments of the present invention with reference to the accompanying drawings, in which:

[0017] Figure 1 is a flow chart of a method for identifying positioning anomalies according to an embodiment of the present invention;

[0018] Figure 2-5 is a schematic diagram of a positioning anomaly identification method according to an embodiment of the present invention;

[0019] Figure 6 is a flow chart of another positioning anomaly identification method according to an embodiment of the present invention;

[0020] Figure 7 is a process diagram of a positioning anomaly identification method according to an embodiment of the present invention;

[0021] Figure 8 is a schematic diagram of a positioning abnormality identification device according to an embodiment of the present invention;

[0022] Fig. 9 is a schematic diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] The present invention is described below based on embodiments, but the present invention is not limited to these embodiments. In the detailed description of the present invention below, some specific details are described in detail. It is possible for a person skilled in the art to fully understand the present invention without the description of these details. In order to avoid confusing the essence of the present invention, known methods, processes, flows, components and circuits are not described in detail.

[0024] In addition, persons of ordinary skill in the art will appreciate that the drawings provided herein are for illustration purposes and are not necessarily drawn to scale.

[0025] Unless the context clearly requires otherwise, words such as “include”, “including” and the like in the specification should be interpreted as including rather than being exclusive or exhaustive; that is, as meaning “including but not limited to”.

[0026] In the description of the present invention, it should be understood that the terms "first", "second", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance. In addition, in the description of the present invention, unless otherwise specified, "plurality" means two or more.

[0027] The solutions described in this specification and in the examples, if they involve the processing of personal information, will be processed on the premise of having a legal basis (such as obtaining the consent of the subject of personal information, or being necessary for the performance of a contract, etc.), and will only be processed within the scope of regulations or agreements. If a user refuses to process personal information other than the necessary information for basic functions, it will not affect the user's use of basic functions.

[0028] In the existing related technologies, when receiving a positioning anomaly determination request for a periodic query target task, or a positioning anomaly determination request issued by a driver, passenger, etc., the customer service usually manually checks the task information and makes a scene judgment, which is time-consuming and has a low accuracy rate. Therefore, the embodiments of the present invention provide a positioning anomaly identification method, device, and electronic device, which can improve the efficiency and accuracy of positioning anomaly identification by setting normal position parameters between the positioning position, the recommended position, and the actual position, and determining the positioning anomaly identification result based on the normal position parameters according to the mutual verification of multiple positions.

[0029] Figure 1 : is a flow chart of a method for identifying positioning anomalies according to an embodiment of the present invention. Figure 1 As shown, the trajectory abnormality identification method of the embodiment of the present invention includes the following steps:

[0030] Step S110: receiving an abnormality determination request, wherein the abnormality determination request includes an identifier of a target task.

[0031] In this embodiment, the abnormality determination request of this embodiment can be a request that is periodically automatically triggered (for example, batch abnormality determination is performed on target tasks within a predetermined time period to summarize abnormal causes, etc.), or a request that is triggered in real time by a driver, passenger, or staff member (for example, when it is difficult for the driver and passenger to meet, or when the recommended boarding point is too far away, the driver, passenger, or staff member initiates a request, etc.), and this embodiment does not limit this. It should be understood that the abnormality determination request of this embodiment can be triggered based on the control in the corresponding terminal application, or can be triggered based on information such as voice, text, and pictures, and this embodiment does not limit this.

[0032] Further optionally, in the present embodiment, the identifier of the target task may be a task number (such as an online car-hailing order number, etc.), etc., which can uniquely identify a certain driving behavior, and the present embodiment does not limit this.

[0033] In an optional implementation, this embodiment can set a queryable time, such as within 2 months, etc. This embodiment does not limit the specific time. Further optionally, the queryable time can be determined based on the cache time of the attribute information of the target task, or it can be determined based on the task complaint time. Taking online car-hailing as an example, assuming that the driver or passenger believes that the positioning abnormality has caused difficulty in meeting the driver and passenger, the recommended boarding point is too far away, etc., resulting in loss of time and other resources, the driver or passenger has a certain complaint time range, and can trigger an abnormality determination request within the complaint time range.

[0034] Step S120, acquiring attribute information of the target task according to the identifier of the target task, wherein the attribute information of the target task includes a positioning position, a recommended position and an actual position.

[0035] Taking online car-hailing as an example, when creating a target task, the recommended boarding point can be determined by the positioning position corresponding to the user-side system positioning, or by dragging a positioning pin or entering text position information and other custom positions. In these target task creation methods, only when the target task is created by the user-side system positioning, problems such as difficulty in meeting the driver and the passenger due to abnormal positioning or inappropriate recommended boarding point may occur. Therefore, after determining that the target task is a task based on user-side positioning, this embodiment obtains the attribute information of the target task.

[0036] Further optionally, in this embodiment, the positioning position is used to represent the user's position determined by the user-side system positioning when creating the target task. The recommended position is used to represent the recommended boarding point location based on the positioning position. The actual position is used to represent the user's actual boarding position, which can be represented by the starting charging position determined by the driver side, etc. This embodiment is not limited to this, and it can also be represented according to the position when the driver side confirms that the passenger has been picked up.

[0037] In an optional implementation, the attribute information of the target task of this embodiment may also include the positioning accuracy of the positioning position and the speed information of the user-side trajectory point. Optionally, the attribute information of the positioning position determined by satellite positioning includes the positioning accuracy of the position and the corresponding number of satellites. The user end can periodically collect trajectory points to form the trajectory of the user end. Among them, the speed information of the trajectory point can be determined according to the distance between adjacent trajectory points and the time interval between adjacent trajectory points. It should be understood that passengers usually walk before taking a vehicle, so their speed generally does not exceed the speed threshold, such as 10m / s. If it is determined by calculation that the speed information of the trajectory point after the user creates the task exceeds the speed threshold, then its positioning attribute may be abnormal, such as positioning drift causing the distance between adjacent trajectory points to be too far. Optionally, the speed limit can be determined based on testing, and this embodiment does not limit the specific value. Further optionally, the speed information of the trajectory point can also be directly characterized by the distance between adjacent trajectory points, and this embodiment does not limit this.

[0038] Furthermore, the positioning accuracy is used to characterize that the positioning position is accurate within the error range of the positioning accuracy. It is easy to understand that the smaller the positioning accuracy, the higher the accuracy of the positioning, but the greater the possibility that the positioning position does not meet the positioning accuracy. If the positioning accuracy is too large, the corresponding positioning position will have too low accuracy, and there may be a positioning drift. Therefore, in this embodiment, the positioning accuracy of the positioning position can be used to determine whether there is a possibility of abnormal positioning attributes of the trajectory point.

[0039] Furthermore, the number of satellites at the positioning position represents the number of satellites that generate the positioning position. If the number of satellites is small, the positioning position may be inaccurate and cause positioning drift. Therefore, in this embodiment, the number of satellites corresponding to the positioning position can also be used as a reference for determining whether the positioning position has abnormal positioning attributes.

[0040] In an optional implementation, the attribute information of the target task may also include the time of the target task. Further optionally, the time of the target task may be the start time of the target task (e.g., the order issuance time of the online car-hailing service, or the billing start time, etc.), the end time of the target task, or the execution time period of the target task, etc. Furthermore, this embodiment may determine whether the target task is within the queryable time based on the time of the target task, and if it is not within the queryable time, feedback a prompt message indicating that the task has exceeded the deadline.

[0041] For example, assuming that the driver or passenger sends an abnormality determination request to the customer service terminal in the corresponding terminal application, the customer service terminal queries the attribute information of the target task based on the identifier of the target task corresponding to the request. If the target task has exceeded the queryable time, the customer service terminal feeds back a prompt message to the driver or passenger's terminal indicating that the task has exceeded the query period. It should be understood that the feedback prompt information can be pre-set speech information or real-time generated speech information, etc., and this embodiment does not limit this.

[0042] Step S130, identifying the target task attribute information based on the predetermined normal position parameters, and obtaining the positioning abnormality identification result of the target task.

[0043] Since there are many negative scenarios for various types of positioning anomalies, it is difficult to enumerate them exhaustively and the enumeration is relatively complex, and the accuracy and efficiency of anomaly determination are low. Based on this, this embodiment predefines the relevant parameters of the normal position, and refers to the normal position parameters, and determines the positioning anomaly identification result by mutual verification of multiple positions such as the positioning position, the recommended position and the actual position, so as to determine the part of the attribute information of the target task that does not meet the normal position parameters, thereby determining the positioning anomaly identification result of the target task, thereby improving the accuracy and efficiency of positioning anomaly determination.

[0044] In an optional implementation, the normal position parameters include: the distance between the recommended position and the actual position is not greater than a first threshold, and the distance between the positioning position and the recommended position is not greater than a second threshold. If the positioning is in a normal state, the positioning position will not be too far from the recommended position (for example, the recommended boarding point position), and the recommended position will not be too far from the actual position (that is, the actual boarding position). Further optionally, in this embodiment, the first threshold can be determined according to the actual application scenario, and this embodiment is not limited to this. It should be understood that the first thresholds corresponding to different target tasks may be the same or different. For example, if the passenger is located in a community and the vehicle cannot enter the community, the setting of the first threshold can be determined based on the diameter of the community, etc., and its value may be relatively large.

[0045] In an optional implementation, since the positioning accuracy of the positioning position, the corresponding number of satellites, and the speed information of the trajectory points after the user terminal sends an order can all reflect whether the positioning attributes are abnormal, the normal position parameters of this embodiment may also include the positioning accuracy being within a predetermined accuracy range, and / or the speed information being within a predetermined speed range, and / or the number of satellites corresponding to the positioning position reaching a predetermined value, etc.

[0046] In an optional implementation, the positioning anomaly is reflected in positioning attribute anomaly, positioning drift, and / or recommended position anomaly (for example, the recommended position is too far from the positioning position, or too far from the actual position, etc.). Among them, the positioning attribute anomaly is also the positioning attribute value of the positioning position (for example, positioning accuracy, corresponding number of satellites, user terminal speed, etc.) is abnormal.

[0047] In an optional implementation, this embodiment identifies the attribute information of the target task by calling the trajectory anomaly identification tool to determine the positioning anomaly identification result of the target task. Among them, the positioning anomaly identification tool is set with a normal position parameter. In this embodiment, the method of positioning anomaly determination is packaged as a positioning anomaly identification toolkit, and is connected to related devices through a predetermined interface. For example, the customer service terminal accesses the positioning anomaly identification toolkit through a related application interface. After receiving the anomaly determination request, the customer service terminal can call the positioning anomaly identification tool through the related application interface, and identify the attribute information of the target task based on the positioning anomaly identification tool, obtain the positioning anomaly identification result, and feed back the positioning anomaly identification result to the customer service terminal.

[0048] In other optional implementations, this embodiment may also embed the method of positioning anomaly identification into a related application (such as an online car-hailing platform software) for direct call and execution. This embodiment does not limit the specific calling and execution method of this positioning anomaly identification method.

[0049] In an optional implementation, this embodiment determines whether there is a positioning abnormality problem through the distance between the positioning position, the recommended position and the actual position.

[0050] In an optional implementation, this embodiment determines that the positioning is abnormal in response to the distance between the recommended position and the actual position being greater than a first threshold, and / or the distance between the positioned position and the recommended position being greater than a second threshold.

[0051] Under normal circumstances, passengers usually get on the bus near the recommended location, so the distance between the recommended location and the actual location is small. Therefore, if the distance between the actual location and the recommended location is large (for example, greater than the first threshold), it indicates that the passenger did not get on the bus at the recommended location, and positioning drift may have occurred, making the recommended location too far away.

[0052] Under normal circumstances, when a passenger creates a task by locating their location, the recommended location is often near them. Therefore, if the passenger's location is normal, the distance between the location and the recommended location is also small. Therefore, if the distance between the passenger's location and the recommended location is too large (for example, larger than the second location), it may be due to positioning drift, causing the nearby boarding points to be far away from the location, or it may be that the recommended location is abnormal.

[0053] Therefore, this embodiment can determine whether there is a positioning abnormality by judging the distance between the recommended position and the actual position, or the distance between the positioned position and the recommended position, so as to improve the accuracy and efficiency of the positioning abnormality judgment.

[0054] Figure 2-5 Schematic diagram of a positioning anomaly identification method according to an embodiment of the present invention. Figure 2 As shown, in the target task x1 of this embodiment, after receiving the abnormality determination request, the attribute information such as the actual position p1, the recommended position p2 and the positioning position p3 of the corresponding target task x1 is obtained according to the identifier of the target task.

[0055] Among them, the distance D12 between the actual position p1 and the recommended position p2 is greater than the first threshold Dt1, and the distance D23 between the recommended position p2 and the positioning position p3 is less than the second threshold Dt2. In other words, when the passenger creates a task through system positioning, he / she does not get on the bus near the recommended position p2. When the passenger chooses to create a task through system positioning, he / she generally does not move to a far place to get on the bus. Therefore, the recommended position p2 determined based on the positioning position p3 is likely to be far away from the actual position of the passenger, which in turn causes the passenger to get on the bus at the actual position p1 far away from the recommended position p2. It can be seen from this that Figure 2 The positioning position p3 in the target task shown can be determined as a positioning abnormality such as positioning drift.

[0056] like Figure 3 As shown, in the target task x2 of this embodiment, after receiving the abnormality determination request, the corresponding attribute information such as the actual position p1', the recommended position p2' and the positioning position p3' of the target task x2 is obtained according to the identifier of the target task.

[0057] Among them, the distance D12' between the actual position p1' and the recommended position p2' is greater than the first threshold Dt1, and the distance D23' between the recommended position p2' and the positioning position p3' is greater than the second threshold Dt2. That is to say, when the passenger creates a task through system positioning, the recommended position p2' is far away from the positioning position p3', and the passenger does not get on the bus near the recommended position p2'. This situation may be due to the positioning drift of the positioning position p3' to a nearby position where it is impossible to get on the bus, resulting in the recommended position p2' that can be recommended within its predetermined range being too far away from the positioning position p3'. This situation may also be due to the positioning position p3' not being wrong, but because the recommended position refers to too many factors, the recommended position p2' is abnormal (for example, the recommended position p2' is too far away, etc.), and the abnormal recommended position is also likely to be caused by positioning drift. Therefore, in this case, it can be determined that the positioning is abnormal.

[0058] Further optionally, the present embodiment can further determine whether it is due to positioning anomalies such as positioning drift by judging the distance between the actual position p1' and the positioning position p3'. Since the passenger side selects the system positioning to create a task, it generally does not move to a distant place to get on the bus, so the distance between the real position of the passenger when creating the task and the actual position p1' will not be too far. Therefore, if the distance between the actual position p1' and the positioning position p3' is greater than the predetermined distance (for example, 200m, etc.), it can be determined that the above situation is caused by anomalies such as positioning drift, and if the distance between the actual position p1' and the positioning position p3' is not greater than the predetermined distance, it can be determined that the positioning has not drifted, and the above situation is an abnormality caused by the recommended position being too far away.

[0059] like Figure 4 As shown, in the target task x3 of this embodiment, after receiving the abnormality determination request, the attribute information such as the actual position p1", the recommended position p2" and the positioning position p3" of the corresponding target task x3 is obtained according to the identifier of the target task.

[0060] Among them, the distance D12” between the actual position p1” and the recommended position p2” is less than the first threshold Dt1, and the distance D23” between the recommended position p2” and the positioning position p3” is greater than the second threshold Dt2. That is to say, when the passenger creates a task through system positioning, the positioning position p3” is too far from the recommended position p2”, and the passenger gets on the bus near the recommended position p2”. It can be seen that the above situation may be caused by the positioning being normal but the recommended position being too far, or the positioning being abnormal but the recommended position being consistent with the passenger’s actual location.

[0061] Further optionally, the present embodiment can also determine whether it is a positioning abnormality based on the environmental information around the positioning position p3". Since the high-precision map basically marks relatively detailed environmental information, the present embodiment can also determine its environmental information based on the longitude and latitude of the positioning position p3". If the environmental information near the positioning position p3" indicates that pedestrians within the range cannot be reached, it can be determined that the above situation is caused by the positioning abnormality. If the environmental information near the positioning position p3" indicates that pedestrians within the range can be reached, it can be determined that the above situation is an abnormal situation in which the recommended position is too far away.

[0062] like Figure 5 As shown, in the target task x4 of this embodiment, after receiving the abnormality determination request, the corresponding attribute information such as the actual position p1"', the recommended position p2"' and the positioning position p3"' of the target task x4 is obtained according to the identifier of the target task.

[0063] Among them, the distance D12"' between the actual position p1"' and the recommended position p2"' is less than the first threshold Dt1, and the distance D23"' between the recommended position p2"' and the positioning position p3"' is less than the second threshold Dt2. That is to say, when the passenger creates a task through system positioning, the positioning position p3"' is closer to the recommended position p2", and the passenger gets on the bus near the recommended position p2". It can be seen that the above situation meets the normal position parameters, and there is no abnormal problem such as abnormal positioning or the recommended position is too far.

[0064] In an optional implementation, when this embodiment makes a cross-determination based on the distance between the positioning position, the recommended position and the actual position, if it cannot be determined whether the abnormal situation is caused by positioning anomalies such as positioning drift or the abnormal situation is caused by the recommended position being too far away, it can also be further determined through the positioning attribute value of the positioning position, for example, further determining whether the positioning accuracy value of the positioning attribute value of the positioning position is too large (the accuracy value is too large, that is, it can only be determined as accurate positioning within a large range), and / or whether the number of satellites corresponding to the positioning position is too small (too small a number of satellites is likely to be inaccurate positioning), and / or whether the speed of the moving trajectory point after the passenger creates the task exceeds the speed threshold (the calculated excessive speed may be caused by positioning drift), so as to further determine whether the abnormal situation is caused by positioning anomalies such as positioning drift.

[0065] In an optional implementation, the present embodiment can also determine whether the positioning is abnormal by judging the positioning attribute value of the positioning position. Further optionally, the present embodiment determines that the positioning attribute is abnormal in response to the positioning accuracy of the positioning position not being within a predetermined accuracy range, the number of satellites corresponding to the positioning position not reaching a predetermined value, and / or the speed of the trajectory point corresponding to the user terminal not being within a predetermined speed range. In this embodiment, if the positioning accuracy of the positioning position is not within a predetermined range, for example, the positioning accuracy is too large (the positioning accuracy is greater than 85, etc.), the number of satellites corresponding to the positioning position does not reach a predetermined value (for example, less than 5, etc.), and the speed of the trajectory point corresponding to the user terminal is not within a predetermined speed range, for example, the speed is too large (the speed is greater than 10m / s, etc.), it can be determined that the positioning of the positioning position is inaccurate, that is, the positioning attribute is abnormal.

[0066] Further optionally, after determining that the positioning attribute of the positioning position in the target task meets the predetermined conditions, whether the positioning is abnormal is determined by the positioning position of the target task, the distance between the recommended position and the actual position. It should be understood that the method of determining whether the positioning is abnormal by the positioning position of the target task, the distance between the recommended position and the actual position in this embodiment is similar to the above embodiment, and will not be repeated here. Therefore, this embodiment can first filter the target task by the positioning attribute of the positioning position, further improving the efficiency of abnormality determination.

[0067] In an optional implementation, the positioning attribute satisfies the predetermined condition specifically for: the positioning accuracy of the positioning position is within a predetermined range, the number of satellites corresponding to the positioning position reaches a predetermined value, and the speed of the trajectory point corresponding to the user terminal is within a predetermined speed range. It should be understood that in other optional implementations, if two or more of the positioning accuracy of the positioning position, the number of satellites corresponding to the positioning position, and the speed of the trajectory point corresponding to the user terminal are within the predetermined speed range, it can also be determined that the positioning attribute satisfies the predetermined condition, and this embodiment does not limit this.

[0068] In an optional implementation, the embodiment responds to the positioning abnormality identification result characterizing the positioning abnormality, and records the system information corresponding to the user end to optimize the system information. That is, after determining that the user end has a positioning abnormality, the embodiment can determine which type of application under the system needs to be further optimized by determining the system information of the user end (that is, the user end is an Android end, an IOS end, or a webapp end, etc.) to solve the positioning abnormality problem under the system.

[0069] The embodiment of the present invention determines the identification of the target task through the received abnormal determination request, obtains the attribute information such as the positioning position, recommended position and actual position of the target task according to the identification of the target task, identifies the attribute information such as the positioning position, recommended position and actual position based on the predetermined normal position parameters, and obtains the positioning abnormality identification result of the target task. Therefore, this embodiment can determine the positioning abnormality identification result by setting the normal position parameters between the positioning position, the recommended position and the actual position, and based on the normal position parameters, according to the mutual verification of multiple positions, thereby improving the efficiency and accuracy of positioning abnormality identification.

[0070] Figure 6 FIG. 1 is a flow chart of another method for identifying positioning anomalies according to an embodiment of the present invention. Figure 6 As shown, the trajectory abnormality identification method of this embodiment includes the following steps:

[0071] Step S1, receiving an abnormality determination request, wherein the abnormality determination request includes an identifier of a target task.

[0072] In this embodiment, the abnormality determination request of this embodiment can be a request that is periodically automatically triggered (for example, batch abnormality determination for target tasks within a predetermined time period to summarize the causes of abnormalities, etc.), or it can be a request triggered in real time by the driver, passenger or staff (for example, when it is difficult for the driver and passenger to meet, or when the recommended boarding point is too far away, the driver, passenger or staff initiates a request, etc.), and this embodiment does not limit this.

[0073] Step S2, whether the target task is found according to the identifier of the target task. If the target task can be found, step S4 is executed, and if the target task is not found, step S3 is executed.

[0074] Step S3, feedback the first prompt information, wherein the first prompt information is used to prompt that the corresponding target task has not been found, and select other questions for consultation.

[0075] Step S4, obtaining the attribute information of the target task. The attribute information of the target task includes the time information of the target task.

[0076] Step S5, determining whether the target task is within the queryable time, if it is within the queryable time, executing step S7, if the time of the target task exceeds the queryable time, executing step S6.

[0077] Step S6, feeding back the second prompt information, wherein the second prompt information is used to prompt that the task time is too long and exceeds the queryable time.

[0078] Step S7, if the time of the target task is within the queryable time, determine whether the starting point of the target task has been modified. The starting point is the location of the user terminal when the task is created. If the starting point is modified, execute step S8, if the starting point is not modified, execute step S9.

[0079] Step S8, after the modification starting point is determined, the task type of the target task includes the task type of determining the creation of the task by the location corresponding to the location of the user end system, determining the creation of the task by dragging a location pin or inputting text location information and other custom locations.

[0080] Step S9, determining whether the task type of the target task is to create a task by using the location corresponding to the location of the user-side system. If yes, then executing step S11, if no, then executing step S10.

[0081] Step S10: Feedback the third prompt information. The third prompt information is used to prompt that the task is not created through system positioning - non-positioning problem.

[0082] Step S11, when the target task is a task created by locating the location corresponding to the user-side system, determine whether the location attribute of the location of the target task is abnormal. If the location attribute is abnormal, execute step S12, if the location attribute is normal, execute step S13.

[0083] In an optional implementation, this embodiment can determine whether the positioning is abnormal by judging the positioning attribute value of the positioning position. Further optionally, this embodiment determines that the positioning attribute is abnormal in response to the positioning accuracy of the positioning position not being within a predetermined accuracy range, the number of satellites corresponding to the positioning position not reaching a predetermined value, and / or the speed of the trajectory point corresponding to the user end not being within a predetermined speed range. In this embodiment, if the positioning accuracy of the positioning position is not within a predetermined range, for example, the positioning accuracy is too large (the positioning accuracy is greater than 85, etc.), the number of satellites corresponding to the positioning position does not reach a predetermined value (for example, less than 5, etc.), and the speed of the trajectory point corresponding to the user end is not within a predetermined speed range, for example, the speed is too large (the speed is greater than 10m / s, etc.), it can be determined that the positioning of the positioning position is inaccurate, that is, the positioning attribute is abnormal.

[0084] Step S12, feeding back first identification information, wherein the first identification information, that is, the positioning attribute of the positioning location is abnormal.

[0085] Step S13, after determining that the positioning attribute of the positioning position in the target task meets the predetermined condition, determine whether the positioning position of the target task, the distance between the recommended position and the actual position meet the normal position parameters, if not, execute step S14, if meet the normal position parameters, execute step S15. It should be understood that the determination method of whether the positioning position of the target task, the distance between the recommended position and the actual position meet the normal position parameters in this embodiment is similar to that in the above embodiment, and will not be repeated here.

[0086] In an optional implementation, the positioning attribute satisfies the predetermined condition specifically for: the positioning accuracy of the positioning position is within a predetermined range, the number of satellites corresponding to the positioning position reaches a predetermined value, and the speed of the trajectory point corresponding to the user terminal is within a predetermined speed range. It should be understood that in other optional implementations, if two or more of the positioning accuracy of the positioning position, the number of satellites corresponding to the positioning position, and the speed of the trajectory point corresponding to the user terminal are within the predetermined speed range, it can also be determined that the positioning attribute satisfies the predetermined condition, and this embodiment does not limit this.

[0087] Step S14: If the distance between the positioning position, the recommended position and the actual position of the target task does not meet the normal position parameter, the second identification information is fed back, wherein the second identification information is positioning drift or abnormal recommended position.

[0088] Step S15: If the distance between the positioning position of the target task, the recommended position and the actual position meets the normal position parameters, the third identification information is fed back, wherein the third identification information is that there is no abnormality in the positioning.

[0089] Step S16, after determining that the target task has a positioning anomaly, determine whether the user end is known, if the user end is known, execute step S18, if the user end is unknown, execute step S17.

[0090] Step S17, determine the system information of the user terminal, that is, determine which type of system the user terminal is, such as Android terminal, IOS terminal, webapp terminal, etc. Further optionally, in this embodiment, the client can query the user terminal to determine the system information of the user terminal. It should be understood that this embodiment does not limit the method of obtaining the system information of the user terminal.

[0091] Step S18, after determining the system of the user terminal, optimize according to the system of the user terminal. That is, after determining that the positioning of the user terminal is abnormal, this embodiment can determine which type of application under the system needs further optimization by determining the system information of the user terminal (that is, the user terminal is an Android terminal, an IOS terminal, or a webapp terminal, etc.) to solve the positioning abnormality problem under the system.

[0092] The embodiment of the present invention determines the identification of the target task through the received abnormal determination request, obtains the attribute information such as the positioning position, recommended position and actual position of the target task according to the identification of the target task, identifies the attribute information such as the positioning position, recommended position and actual position based on the predetermined normal position parameters, and obtains the positioning abnormality identification result of the target task. Therefore, this embodiment can determine the positioning abnormality identification result by setting the normal position parameters between the positioning position, the recommended position and the actual position, and based on the normal position parameters, according to the mutual verification of multiple positions, thereby improving the efficiency and accuracy of positioning abnormality identification.

[0093] Figure 7 Schematic diagram of the process of the positioning anomaly identification method according to an embodiment of the present invention. Figure 7 As shown, this embodiment is explained by taking an example in which a passenger requests the customer service end to query whether the positioning of the target task is abnormal through the passenger end. It should be understood that this embodiment does not limit the form of request triggering.

[0094] like Figure 7As shown, the passenger terminal sends an abnormality determination request to the client terminal 71, such as "Does the task xxxxx have any positioning abnormality?" The client terminal 71 calls the positioning abnormality identification tool 72 through a predetermined interface to obtain the corresponding attribute information through the task identifier "xxxxx", and based on the predetermined normal position parameters, cross-identify according to the positioning position, recommended position, actual position and positioning attributes of the target task, obtain the positioning abnormality identification result of the task and feed it back to the client terminal 71, and the client terminal 71 generates corresponding feedback information and feeds it back to the passenger terminal. For example, "Task xxxxx has an abnormal situation of positioning drift", etc. It should be understood that the abnormality determination method of the trajectory abnormality identification tool 72 is similar to the above-mentioned embodiment, and will not be repeated here.

[0095] Further optionally, if the passenger end is unknown, then while feeding back the abnormal identification result, the passenger end system information used when placing the order can also be inquired. For example, the feedback information of the customer service end 71 can be "Task xxxxx has an abnormal positioning drift. What type of system did you use when placing the order?" After the passenger end responds, further feedback can be provided based on a pre-set feedback statement or a real-time generated feedback statement.

[0096] The embodiment of the present invention determines the identification of the target task through the received abnormal determination request, obtains the attribute information such as the positioning position, recommended position and actual position of the target task according to the identification of the target task, identifies the attribute information such as the positioning position, recommended position and actual position based on the predetermined normal position parameters, and obtains the positioning abnormality identification result of the target task. Therefore, this embodiment can determine the positioning abnormality identification result by setting the normal position parameters between the positioning position, the recommended position and the actual position, and based on the normal position parameters, according to the mutual verification of multiple positions, thereby improving the efficiency and accuracy of positioning abnormality identification.

[0097] Figure 8 Schematic diagram of a positioning anomaly identification device according to an embodiment of the present invention. Figure 8 As shown, the positioning abnormality identification device 8 of this embodiment includes a request receiving unit 81, an information acquiring unit 82 and an identification unit 83.

[0098] The request receiving unit 81 is configured to receive an abnormality determination request, wherein the abnormality determination request includes an identifier of a target task. The information acquiring unit 82 is configured to acquire attribute information of the target task according to the identifier of the target task, wherein the attribute information of the target task includes a positioning position, a recommended position, and an actual position. The identifying unit 83 is configured to identify the attribute information based on a predetermined normal position parameter, and acquire a positioning abnormality identification result of the target task.

[0099] In an optional implementation, the identification unit 83 is further configured to call a positioning anomaly identification tool to identify the attribute information of the target task and determine a positioning anomaly identification result of the target task, and the trajectory anomaly identification tool is provided with the normal position parameter.

[0100] In an optional implementation, the normal position parameter includes: the distance between the recommended position and the actual position is not greater than a first threshold, and the distance between the positioning position and the recommended position is not greater than a second threshold.

[0101] In an optional implementation, the attribute information further includes the positioning accuracy of the positioning position, the corresponding number of satellites, and / or the speed information of the user terminal trajectory point;

[0102] The normal position parameters also include that the positioning accuracy is within a predetermined accuracy range, the number of satellites reaches a predetermined value, and / or the speed information is within a predetermined speed range.

[0103] In an optional implementation, the identification unit 83 is further configured to determine that the positioning is abnormal in response to the distance between the recommended position and the actual position being greater than a first threshold, and / or the distance between the positioned position and the recommended position being greater than a second threshold.

[0104] In an optional implementation, the identification unit 83 is further configured to determine that the positioning attribute is abnormal in response to the positioning accuracy of the positioning position being not within the predetermined accuracy range, the number of satellites corresponding to the positioning position not reaching a predetermined value, and / or the speed of the trajectory point corresponding to the user terminal being not within a predetermined speed range.

[0105] In an optional implementation, the identification unit 83 is further configured to determine whether the positioning is abnormal according to the distance between the positioning position, the recommended position and the actual position in response to the positioning attribute of the positioning position satisfying a predetermined condition;

[0106] Whether the positioning attribute meets the predetermined condition is determined based on the positioning accuracy of the positioning position, the number of satellites corresponding to the positioning position, and the speed of the trajectory point corresponding to the user terminal.

[0107] In an optional implementation, the information acquisition unit 82 is further configured to acquire attribute information of the target task in response to the target task being a task based on user terminal positioning.

[0108] In an optional implementation, the positioning anomaly identification device 8 includes a system determination unit configured to record system information corresponding to the user terminal in response to the positioning anomaly identification result characterizing the positioning anomaly, so as to optimize the system information.

[0109] The embodiment of the present invention determines the identification of the target task through the received abnormal determination request, obtains the attribute information such as the positioning position, recommended position and actual position of the target task according to the identification of the target task, identifies the attribute information such as the positioning position, recommended position and actual position based on the predetermined normal position parameters, and obtains the positioning abnormality identification result of the target task. Therefore, this embodiment can determine the positioning abnormality identification result by setting the normal position parameters between the positioning position, the recommended position and the actual position, and based on the normal position parameters, according to the mutual verification of multiple positions, thereby improving the efficiency and accuracy of positioning abnormality identification.

[0110] Fig. 9 Schematic diagram of an electronic device according to an embodiment of the present invention. Fig. 9 As shown, the electronic device 9 is a general data processing device, which includes a general computer hardware structure, which at least includes a processor 91 and a memory 92. The processor 91 and the memory 92 are connected via a bus 93. The memory 92 is suitable for storing instructions or programs executable by the processor 91. The processor 91 can be an independent microprocessor or a collection of one or more microprocessors. Thus, the processor 91 executes the instructions stored in the memory 92, thereby executing the method flow of the embodiment of the present invention as described above to realize the processing of data and the control of other devices. The bus 93 connects the above-mentioned multiple components together, and at the same time connects the above-mentioned components to the display controller 94 and the display device and the input / output (I / O) device 95. The input / output (I / O) device 95 can be a mouse, a keyboard, a modem, a network interface, a touch input device, a somatosensory input device, a printer, and other devices known in the art. Typically, the input / output device 95 is connected to the system through an input / output (I / O) controller 96.

[0111] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, devices (equipment) or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application may adopt a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0112] The present application is described with reference to flowcharts of methods, apparatuses (devices) and computer program products according to embodiments of the present application. It should be understood that each process in the flowchart can be implemented by computer program instructions.

[0113] These computer program instructions may 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 including an instruction device that implements the process Figure 1 A function specified in a process or multiple processes.

[0114] These computer program instructions may also 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 produce the instructions for implementing the process Figure 1 A device that specifies functions in a process or multiple processes.

[0115] Another embodiment of the present invention relates to a non-volatile storage medium for storing a computer-readable program, wherein the computer-readable program is used for a computer to execute part or all of the above method embodiments.

[0116] That is, those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by specifying relevant hardware through a program, and the program is stored in a storage medium, including several instructions for a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0117] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A positioning anomaly identification method, characterized in that: The method comprises: receiving an exception determination request, wherein the exception determination request includes an identifier of a target task; Acquire attribute information of the target task according to the identifier of the target task, wherein the attribute information of the target task includes a positioning position, a recommended position, and an actual position; Identifying the attribute information based on a predetermined normal position parameter to obtain a positioning anomaly identification result of the target task; The normal position parameters include: the distance between the recommended position and the actual position is not greater than a first threshold, and the distance between the positioning position and the recommended position is not greater than a second threshold; Among them, the target task is an online car-hailing task, the positioning position is the position determined by user-side positioning when creating the target task, the recommended position is the boarding point position recommended based on the positioning position, and the actual position is the actual boarding location of the user.

2. The method according to claim 1, characterized in that The identifying the attribute information based on the predetermined normal position parameter to obtain the positioning abnormality identification result of the target task includes: A positioning anomaly identification tool is called to identify the attribute information of the target task to determine a positioning anomaly identification result of the target task, and the positioning anomaly identification tool is provided with the normal position parameter.

3. The method according to claim 1, characterized in that The attribute information also includes the positioning accuracy of the positioning position, the corresponding number of satellites, and / or the speed information of the user terminal trajectory point; The normal position parameters also include that the positioning accuracy is within a predetermined accuracy range, the number of satellites reaches a predetermined value, and / or the speed information is within a predetermined speed range.

4. The method according to claim 2, characterized in that: The identifying the attribute information based on the predetermined normal position parameter to obtain the positioning abnormality identification result of the target task includes: In response to the distance between the recommended position and the actual position being greater than a first threshold, and / or the distance between the positioning position and the recommended position being greater than a second threshold, it is determined that the positioning is abnormal.

5. The method according to claim 3, characterized in that: The identifying the attribute information based on the predetermined normal position parameter to obtain the positioning abnormality identification result of the target task includes: In response to the positioning accuracy of the positioning position not being within the predetermined accuracy range, the number of satellites corresponding to the positioning position not reaching a predetermined value, and / or the speed of the trajectory point corresponding to the user terminal not being within a predetermined speed range, it is determined that the positioning attribute is abnormal.

6. The method according to claim 3, characterized in that The identifying the attribute information based on the predetermined normal position parameter to obtain the positioning abnormality identification result of the target task includes: In response to the positioning attribute of the positioning position satisfying a predetermined condition, determining whether the positioning is abnormal according to the distance between the positioning position, the recommended position and the actual position; Whether the positioning attribute meets the predetermined condition is determined based on the positioning accuracy of the positioning position, the number of satellites corresponding to the positioning position, and the speed of the trajectory point corresponding to the user terminal.

7. The method according to claim 1, characterized in that The acquiring the attribute information of the target task according to the identifier of the target task includes: In response to the target task being a task based on user terminal positioning, attribute information of the target task is acquired.

8. The method according to any one of claims 1 to 7, characterized in that The method further comprises: In response to the positioning anomaly identification result indicating a positioning anomaly, system information corresponding to the user terminal is recorded to optimize the system information.

9. A positioning abnormality identification device, characterized in that: The device comprises: A request receiving unit, configured to receive an abnormality determination request, wherein the abnormality determination request includes an identifier of a target task; an information acquisition unit, configured to acquire attribute information of the target task according to the identifier of the target task, wherein the attribute information of the target task includes a positioning position, a recommended position, and an actual position; an identification unit configured to identify the attribute information based on a predetermined normal position parameter and obtain a positioning anomaly identification result of the target task; The normal position parameters include: the distance between the recommended position and the actual position is not greater than a first threshold, and the distance between the positioning position and the recommended position is not greater than a second threshold; Among them, the target task is an online car-hailing task, the positioning position is the position determined by user-side positioning when creating the target task, the recommended position is the boarding point position recommended based on the positioning position, and the actual position is the actual boarding location of the user.

10. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store one or more computer program instructions, wherein the one or more computer program instructions are executed by the processor to implement the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

12. A computer program product, characterized in that When the computer program product is run on a computer, the computer is caused to execute the method according to any one of claims 1 to 8.

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