High-speed rail travel identification method based on day-degree signaling data and computer equipment

Abstract

The invention provides a day-degree signaling data-based high-speed rail travel identification method and computer equipment. The day-degree signaling data-based high-speed rail travel identification method comprises the following steps of: obtaining an ordered signaling point sequence of a target user within one day; dividing a plurality of signaling segments from the ordered signaling point sequence according to the time interval of adjacent signaling points in the ordered signaling point sequence and the attribute of the area to which the signaling points belong; integrating the plurality of signaling segments according to a preset high-speed rail segment duration threshold value and a high-speed rail region separation duration threshold value to obtain a plurality of to-be-evaluated high-speed rail segments, and determining the to-be-evaluated high-speed rail segments meeting preset high-speed rail segment feature conditions as target high-speed rail segments; integrating the target high-speed rail segments based on the travel states of the target high-speed rail segments and the gap segment features between the target high-speed rail segments to obtain a to-be-evaluated high-speed rail travel; and judging whether the to-be-evaluated high-speed rail travel is reasonable or not according to the travel characteristics of the to-be-evaluated high According to the method, identification does not depend on monthly data, the influence of sparse signaling or inaccurate base station position can be avoided, and day-degree accurate high-speed rail travel identification is realized.

Description

Technical Field

[0001] The present application relates to the field of big data technology, and more specifically, to a high-speed rail itinerary identification method and computer equipment based on daily signaling data. Background Art

[0002] In daily life, people often travel by high-speed rail. Accurate identification of high-speed rail travel patterns can be used to analyze user travel patterns and facilitate intercity transportation analysis and planning. However, how to accurately identify a person's high-speed rail itinerary and obtain detailed travel information (such as starting and ending locations, time, speed, etc.) has always been a challenge. Existing analysis methods have some problems, such as relying on monthly data recognition results, or being easily affected by sparse signaling or inaccurate base station locations, resulting in low accuracy in high-speed rail itinerary recognition. Summary of the invention

[0003] The purpose of the embodiments of the present invention is to provide a high-speed rail itinerary identification method and computer equipment based on daily signaling data, so as to accurately identify continuous and complete high-speed rail itineraries based on daily signaling data.

[0004] In a first aspect, the present invention provides a high-speed rail itinerary identification method based on daily signaling data, the method comprising: obtaining an ordered sequence of signaling points of a target user within a day; wherein the signaling points in the ordered sequence of signaling points are divided into high-speed rail area signaling points and non-high-speed rail area signaling points; dividing a plurality of signaling segments from the ordered sequence of signaling points according to the time intervals and area attributes of adjacent signaling points in the ordered sequence of signaling points; wherein the signaling segments are divided into high-speed rail area signaling segments and non-high-speed rail area signaling segments; integrating a plurality of the signaling segments according to a preset high-speed rail segment duration threshold and a high-speed rail area separation duration threshold to obtain a plurality of high-speed rail segments to be evaluated, and determining the high-speed rail segments to be evaluated that meet the preset high-speed rail segment characteristic conditions as target high-speed rail segments; integrating the target high-speed rail segments based on the travel status of the target high-speed rail segments and the gap segment characteristics between the target high-speed rail segments to obtain the high-speed rail itinerary to be evaluated; and determining whether the high-speed rail itinerary to be evaluated is reasonable according to the travel characteristics of the high-speed rail itinerary to be evaluated.

[0005] In a second aspect, the present invention provides a computer device, comprising: a memory and one or more processors; the memory is used to store one or more computer programs; when the one or more computer programs are executed by the one or more processors, the one or more processors implement the high-speed rail itinerary identification method based on daily signaling data as described in the aforementioned embodiment.

[0006] The high-speed rail trip identification method and computer device based on daily signaling data provided by the present invention obtain the ordered signaling point sequence of the target user within one day and divide it into high-speed rail area signaling points and non-high-speed rail area signaling points, which lays the foundation for the subsequent accurate division of high-speed rail sections. Then, according to the time interval and regional attributes of adjacent signaling points, the signaling point sequence is divided into high-speed rail area signaling segments and non-high-speed rail area signaling segments. This step can accurately distinguish the user's high-speed rail travel from non-high-speed rail travel to avoid misjudgment. Further, by setting the high-speed rail segment duration threshold and the high-speed rail area separation duration threshold, the signaling segments are integrated to screen out the target high-speed rail segments that meet the characteristics of high-speed rail travel. This process can effectively handle the influence of different situations of sparse or dense signaling on the recognition results, and then further integrate based on the travel state and gap segment characteristics of the target high-speed rail segment to obtain the high-speed rail trip to be evaluated, and further optimize the coherence and rationality of the high-speed rail trip. Finally, by evaluating the travel characteristics of the high-speed rail trip to be evaluated, its rationality is judged to ensure that the high-speed rail trip finally output is accurate and reliable. Through this series of steps, the embodiment of the present invention can divide reasonable high-speed rail sections in combination with accurate signaling data, thereby forming a continuous high-speed rail itinerary and supporting daily output. At the same time, the embodiment of the present invention does not rely on high-speed rail station information, nor is it affected by information such as whether the time to reach the high-speed rail station is delayed, and can effectively avoid travel time conflicts caused by processing in cities of various provinces, thereby achieving efficient and accurate high-speed rail itinerary identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0008] Figure 1 A schematic flow chart of a high-speed rail itinerary identification method based on daily signaling data provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of segmenting a high-speed railway area signaling segment and a non-high-speed railway area signaling segment provided by an embodiment of the present invention; Figure 3 The signaling point interaction during the operation of the high-speed train provided by the embodiment of the present invention; Figure 4 It is a schematic diagram of orderly arrangement of high-speed railway sections and stationary points provided by an embodiment of the present invention; Figure 5 A schematic diagram of the recognition result provided by an embodiment of the present invention; Figure 6A structural block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0009] The following will be combined with the accompanying drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0010] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0011] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprises" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0012] At present, the inventors have found in the research process that the existing high-speed rail travel analysis method has the problem of low recognition rate of high-speed rail itineraries, which is mainly manifested in the following aspects: First, there are obvious deficiencies in relying solely on the geographic information of high-speed rail stations to determine whether a trip is a high-speed rail trip. For example, the signaling may appear at a non-actual stop, or the user signaling may not be within the range of the high-speed rail station, which will lead to recognition errors or even failure to recognize. If the signaling only appears in areas other than high-speed rail stations, the high-speed rail journey that the signaling has passed through will not be recognized.

[0013] Secondly, simply identifying high-speed rail journeys by "the number of high-speed rail stations passed" requires that users must pass through high-speed rail stations and must have signaling records. At the same time, they also need to pass through a large number of high-speed rail stations. This undoubtedly places too high demands on the integrity and quantity of the signaling, resulting in it only being able to identify a few cases and being unable to meet actual needs.

[0014] In addition, the way of processing data by province and city will also lead to discontinuous travel records. For example, a high-speed rail trip from Beijing to Anhui will be interrupted every time it reaches the provincial or city boundary, and it cannot be well integrated into a continuous travel record. For another example, a high-speed rail trip passes through the same province multiple times, which will cause the travel time merged in a single province to conflict with the travel time in another province, thus affecting the accuracy of the itinerary.

[0015] Taking into account the many problems existing in the above-mentioned high-speed rail itinerary identification method, an embodiment of the present invention provides a high-speed rail itinerary identification method based on daily signaling data, which can identify a reasonable high-speed rail itinerary without relying on high-speed rail station information and is not affected by factors such as whether the arrival time at the high-speed rail station is delayed. During implementation, this method can effectively handle different situations of sparse or dense signaling, and can effectively avoid travel time conflicts caused by processing in cities in various provinces, thereby improving the recognition accuracy of high-speed rail travel itineraries.

[0016] Before introducing the high-speed rail travel itinerary recognition process of the embodiment of the present invention, the data preparation stage of the embodiment of the present invention is first introduced. The description is as follows: First, the embodiment of the present invention can obtain high-speed rail route information across the country and base station data of all base stations within a preset distance range of the high-speed rail route, including but not limited to the ID and location corresponding to the base station.

[0017] The embodiment of the present invention refers to the area included in the preset distance range as the "high-speed rail area", and the area outside the distance range as the "non-high-speed rail area". To facilitate the description of subsequent embodiments, the embodiment of the present invention also refers to the signaling points located in the high-speed rail area as "high-speed rail area signaling points", and the signaling points located in the non-high-speed rail area as "non-high-speed rail area signaling points". The signaling segment composed entirely of high-speed rail area signaling points is called a "high-speed rail area signaling segment", and the signaling segment composed entirely of non-high-speed rail area signaling points is called a "non-high-speed rail area signaling segment".

[0018] In an optional implementation, data analysts can flexibly set the distance range based on actual experience, such as within 1 kilometer of a high-speed rail line.

[0019] In an optional embodiment, high-speed rail route information can be obtained through but not limited to the official data interface of the railway management department, a geographic information system (GIS) database or a professional transportation information service platform, and base station data can be obtained through but not limited to the operator's base station management system, base station location database or a geographic information data platform related to the base station.

[0020] Furthermore, the embodiments of the present invention can also obtain travel signaling data for each province in the country every day. These data cover the user's behavior trajectory, mainly including a dwelling point (dwell) and a journey via point (jvp for short), where a dwelling point (dwell) refers to a point where a user stays at a certain location for a long time. For example, when a user stays in one place for a period of time, the stay location and its time range will be recorded as a dwelling point (dwell). A journey via point (jvp) refers to a trajectory point formed when a user moves between two dwelling points (dwell). Each journey via point (jvp) contains at least the following information: user identification, timestamp (recording the time of the location point), associated base station ID (unique identification of the base station, used to determine the source of the signal) and corresponding location, etc.

[0021] In an embodiment of the present invention, it is allowed that the dwell time corresponding to the dwell point (dwell) in the cross-provincial signaling data overlaps in time, which does not affect the recognition accuracy of the embodiment of the present invention. When processing provincial data, it may happen that the user crosses the provincial boundary, for example, the user crosses different provinces on the high-speed rail, which will cause the data to overlap or be discontinuous at the provincial boundary. For example, on the provincial boundary, the dwell start and end time corresponding to a dwell point (dwell) of the user in Anhui Province is 12:57~13:02 (a point is recorded in Anhui at 13:02, and the requirement for forming a dwell point is to stay continuously in a province with a relatively close distance), and the dwell start and end time corresponding to a dwell point (dwell) in Hubei Province is 12:58~13:00. At this time, the user may be recorded as a dwell point in Anhui and Hubei at the same time during the time period of 12:58~13:00, although his actual location may have crossed the provincial boundary.

[0022] Based on the various data obtained in the above stages, the present invention can implement the identification process provided by the embodiment of the present invention for each user's daily signaling data, thereby accurately identifying each user's high-speed rail itinerary. Figure 1 , Figure 1 A schematic flow chart of a high-speed rail itinerary identification method based on daily signaling data provided by an embodiment of the present invention includes steps S101 to S105. The execution subject of the method may be a computer device with data processing capabilities, as described below: S101: Obtain an ordered sequence of signaling points of a target user within one day; Among them, the signaling points in the ordered signaling point sequence are divided into high-speed rail area signaling points and non-high-speed rail area signaling points; S102: dividing a plurality of signaling segments from the ordered signaling point sequence according to the time intervals between adjacent signaling points in the ordered signaling point sequence and the attributes of the regions to which they belong; Among them, the signaling segment is divided into the high-speed rail area signaling segment and the non-high-speed rail area signaling segment; S103: Integrate multiple signaling segments according to a preset high-speed rail segment duration threshold and a high-speed rail area separation duration threshold to obtain multiple high-speed rail segments to be evaluated, and determine the high-speed rail segment to be evaluated that meets the preset high-speed rail segment characteristic conditions as the target high-speed rail segment; S104: Integrate the target high-speed rail sections based on the travel status of the target high-speed rail sections and the gap section characteristics between the target high-speed rail sections to obtain the high-speed rail travel to be evaluated; S105: Determine whether the high-speed rail itinerary to be evaluated is reasonable based on the itinerary characteristics of the high-speed rail itinerary to be evaluated.

[0023] The above scheme provided by the embodiment of the present invention obtains the ordered sequence of signaling points of the target user within one day and divides it into high-speed rail area signaling points and non-high-speed rail area signaling points, which lays the foundation for the subsequent accurate division of high-speed rail sections. Then, according to the time interval of adjacent signaling points and the attributes of the area to which they belong, the signaling point sequence is divided into high-speed rail area signaling segments and non-high-speed rail area signaling segments. This step can accurately distinguish the user's high-speed rail travel from non-high-speed rail travel to avoid misjudgment. Further, by setting the high-speed rail section duration threshold and the high-speed rail area separation duration threshold, the signaling segments are integrated to screen out the target high-speed rail sections that meet the characteristics of high-speed rail travel. This process can effectively handle the impact of different situations of sparse or dense signaling on the recognition results, and then further integrate based on the travel state and gap segment characteristics of the target high-speed rail section to obtain the high-speed rail itinerary to be evaluated, further optimizing the coherence and rationality of the high-speed rail itinerary. Finally, by evaluating the travel characteristics of the high-speed rail itinerary to be evaluated, its rationality is judged to ensure that the high-speed rail itinerary output in the end is accurate and reliable. Through this series of steps, the embodiment of the present invention can divide reasonable high-speed rail sections in combination with accurate signaling data, thereby forming a continuous high-speed rail itinerary and supporting daily output. At the same time, the embodiment of the present invention does not rely on high-speed rail station information, nor is it affected by information such as whether the time to reach the high-speed rail station is delayed, and can effectively avoid travel time conflicts caused by processing in cities of various provinces, thereby achieving efficient and accurate high-speed rail itinerary identification.

[0024] Next, each of the above steps will be described in detail with reference to the relevant drawings.

[0025] In one embodiment of the present invention, the signaling point in the ordered signaling point sequence in step S101 is the jvp point in the aforementioned content, which is divided into a high-speed rail area signaling point and a non-high-speed rail area signaling point. Among them, the high-speed rail area signaling point refers to the jvp point located in the high-speed rail area defined in the embodiment of the present invention, and the non-high-speed rail area signaling point is the jvp point located in the non-high-speed rail area.

[0026] In the embodiment of the present invention, the target user refers to a user whose base station corresponding to the jvp is in the high-speed rail area. This indicates that the user's communication device has interacted with the base station in the high-speed rail area, thereby suggesting that the user may have high-speed rail travel behavior. In other words, users who do not have a jvp point in the high-speed rail area are not within the scope of the present invention.

[0027] It is understandable that during the data preparation phase, the device has already acquired signaling data from all provinces across the country. For the target user, the user information can be used to extract the user's daily JPVP data across the country from the signaling data, and arrange them in chronological order to obtain an ordered sequence of signaling points. Next, the signaling points are segmented as follows: Step a1: if the time interval between adjacent signaling points exceeds the preset signaling interval duration threshold or the adjacent signaling points are located in different areas, the adjacent signaling points are divided; Step a2: Segment and integrate the divided signaling points to obtain multiple signaling segments.

[0028] In the embodiment of the present invention, the signaling interval time threshold can be flexibly set by the data analyst according to the sparseness of the signaling points, for example, 5 minutes. If the time interval between adjacent signaling points exceeds the threshold, it indicates that the signaling points are relatively sparse, and the user may have interrupted the trip by getting off the bus midway, and segmentation is required at this time.

[0029] Obviously, there are three types of areas where adjacent signaling points belong: both are in the high-speed rail area, both are in the non-high-speed rail area, and one is in the high-speed rail area and the other is in the non-high-speed rail area. If adjacent signaling points are located in different areas, it means that the signaling point has undergone area switching, that is, the base station where the user performs signaling interaction has switched from the high-speed rail area to the non-high-speed rail area, or vice versa. At this time, a split is also required.

[0030] The above implementation shows that the embodiment of the present invention only performs signaling point segmentation when encountering sparse signaling points or regional switching. This segmentation is the initial division with the finest segmentation granularity in the entire identification process, which can effectively identify the dividing point between the user's high-speed rail travel behavior and non-high-speed rail travel behavior, and provides a basis for subsequent high-speed rail itinerary identification. This segmentation method can not only accurately capture the user's travel mode, but also effectively handle different situations of sparse or dense signaling, thereby providing accurate data support for subsequent high-speed rail itinerary analysis.

[0031] For ease of understanding, let's take an example: Assume that the ordered signaling point sequence is j1, j2, j3, ..., j i ,...,j N , where i=1,2,...,N. The basic duration of the high-speed rail section is set to 5 minutes, and the judgment is made according to the following conditions: Condition 1: j i and j i-1 The corresponding base stations are located in different areas, i.e., one is located in a high-speed rail area and the other is located in a non-high-speed rail area; Condition 2: j i and j i-1 The time interval exceeds 5 minutes; If two adjacent signaling points meet any one of conditions 1 and 2, the two signaling points need to be split into different signaling segments.

[0032] For an intuitive understanding, see Figure 2 , Figure 2 It is a schematic diagram of the segmentation of a high-speed rail area signaling segment and a non-high-speed rail area signaling segment provided by an embodiment of the present invention. 6 Section 1: 1st to 3rd points; Section 2: 4th to 7th points; Section 3: 8th to 9th points; Section 4: 10th to 11th points; Section 5: 12th to 13th points; Section 6: 14th point. Among them, Section 1, Section 3, and Section 4 only contain high-speed rail area signaling points, so they are high-speed rail area signaling segments, and Section 2, Section 5, and Section 6 only contain non-high-speed rail area signaling points, so they are non-high-speed rail area signaling segments.

[0033] It should be noted that it is allowed that a signaling segment contains only one signaling point. Figure 2 , the 14th point is a separate signaling segment. This design is crucial because it can effectively avoid the problem of inaccurate final recognition results due to the loss of key signaling points. For example, suppose the time interval between signaling segment A and signaling segment B is long, and there is only one signaling point in signaling segment A and it is the starting point. If this single signaling point is filtered out during the processing, the starting point will be mistakenly identified as starting from signaling segment B. This is obviously inconsistent with the user's actual travel situation, which seriously affects the final recognition results. Therefore, the embodiment of the present invention ensures the accurate capture and restoration of user travel behaviors by retaining these key single-point signaling segments, thereby improving the accuracy and reliability of the entire recognition system.

[0034] Based on the segmentation in step S102, the embodiment of the present invention can quickly and accurately integrate a complete high-speed railway segment through S103. The implementation of step S103 includes the following steps b1 to b3, which are described as follows: Step b1: if the time interval between adjacent signaling segments exceeds the high-speed rail segment duration threshold, the adjacent signaling segments are segmented to obtain a signaling segment group; Step b2: Determine whether the duration of the non-high-speed rail area signaling segment in the signaling segment group is less than the high-speed rail area departure duration threshold; Step b3: If so, take the signaling segment group as the high-speed rail segment to be evaluated; otherwise, split it from the last signaling point of the signaling segment in the non-high-speed rail area to obtain the high-speed rail segment to be evaluated.

[0035] In an embodiment of the present invention, the high-speed rail segment duration threshold and the high-speed rail area departure duration threshold are both empirical values ​​obtained based on a large amount of data analysis, wherein the high-speed rail area departure duration threshold is used to evaluate the degree to which the signaling segment departs from the high-speed rail area, for example, it is set to 8 minutes.

[0036] The duration of a signaling segment can be expressed as the time difference between the first signaling point and the last signaling point in the signaling segment. If the duration of a signaling segment leaving the high-speed rail area exceeds the high-speed rail area departure duration threshold, this may mean that the journey is interrupted or ended, so the signaling segment needs to be split here. This split can effectively avoid misjudgments caused by signaling segments that are too long or discontinuous; on the contrary, if the duration of a signaling segment leaving the high-speed rail area does not exceed the high-speed rail area departure duration threshold, it indicates that the departure of the signaling segment can be tolerated. This design can effectively prevent signaling segments that briefly leave the high-speed rail area due to signaling accuracy issues from being misjudged as journey interruptions, thereby ensuring the integrity of the high-speed rail journey.

[0037] To facilitate understanding of the above implementation, see Figure 2 . Assuming that the high-speed rail area separation time threshold is 8 minutes, if the duration of the non-high-speed rail area signaling segment represented by the second segment is less than or equal to 8 minutes, the first segment, the second segment and the third segment are merged into one segment, and the final merged result is: the 1st to 9th points, the 10th to 13th points, and the 14th point. Otherwise, the first segment and the second segment are merged into one segment of signaling segment to be evaluated, corresponding to the 1st to 7th points. The final merged results are: the 1st to 7th points, the 8th to 9th points, the 10th to 13th points, and the 14th point. Similarly, the non-high-speed rail area signaling segment represented by the fifth segment can also be processed in the same way. Similarly, the non-high-speed rail area signaling segment represented by the fifth segment can also be processed in the same way, which will not be repeated here.

[0038] In one embodiment of the present invention, after obtaining multiple high-speed rail sections to be evaluated, these high-speed rail sections can be further optimized. Specifically, the non-high-speed rail area signaling points that may exist continuously at both ends of each high-speed rail section to be evaluated can be filtered out, that is, the situation where both ends of the high-speed rail section are not in the high-speed rail area is excluded, so as to obtain a more accurate high-speed rail section to be evaluated, ensuring that both ends of the entire high-speed rail section are high-speed rail area signaling points. This optimization step can further improve the accuracy and reliability of high-speed rail trip identification.

[0039] On the basis of the above steps b1 to b3, the present invention also provides a further implementation method, which selects a more reasonable high-speed rail section from the high-speed rail sections to be evaluated to improve the accuracy of subsequent trip identification. The details are as follows: Step c1: Correct the real starting point and end point of the high-speed railway section to be evaluated, and take the signaling segment between the real starting point and end point as the valid high-speed railway section.

[0040] In the embodiment of the present invention, the purpose of correcting the real starting point and end point of the high-speed railway section to be evaluated is to improve the accuracy of segmentation and avoid the influence of factors such as long stay at the starting point (such as long waiting for the train) and long stay at the end point (such as living near the station, staying in the shopping mall near the station for a long time) on the recognition result. For example, see Figure 3 , Figure 3 The signaling point interaction during the operation of the high-speed train provided in the embodiment of the present invention. There are a large number of signaling points gathered at the departure position of the train. These signaling points may represent the activities of users near the station before the train departs, including the signaling point closest to the actual departure time and the first signaling point that actually leaves the high-speed train station in time.

[0041] In order to more accurately determine the starting point of the high-speed railway section to be evaluated, the correction method adopted in the embodiment of the present invention may be: Starting from the first signaling point of the high-speed rail section to be evaluated, search in the direction of the last signaling point. If there is a high-speed rail area signaling point whose straight-line distance with the first signaling point is less than the preset distance threshold, the time difference exceeds the high-speed rail section duration threshold, and the speed calculated based on the straight-line distance is less than the preset first speed threshold, then the high-speed rail area signaling point will be taken as the actual starting signaling point.

[0042] In an embodiment of the present invention, the high-speed rail section duration threshold is the same as the high-speed rail area separation duration threshold and the signaling point interval duration threshold, for example, 5 minutes. The purpose of this setting is to ensure the continuity and coherence of the high-speed rail journey and avoid misjudgment caused by short signaling interruptions or base station switching. The distance threshold and the first speed threshold are both empirical values ​​based on a large amount of data analysis. They can be set based on a distance value that may be traveled in a short time (such as the high-speed rail section duration threshold set above) after the high-speed rail train has just started, in combination with the signaling accuracy. For example, assuming that the high-speed rail train is restricted to not go out 1 kilometer within 5 minutes, the distance threshold can be set to 2 kilometers, and the first speed threshold can be set to 12 kilometers / hour according to the condition of 5 minutes to travel 1 kilometer. In this way, it is possible to effectively avoid missing the real starting point.

[0043] For example, if a high-speed rail area signaling point is less than 2 kilometers away from the first signaling point, and the time difference from the first signaling point to the high-speed rail area signaling point exceeds 5 minutes, and the speed corresponding to the straight-line distance from the high-speed rail area signaling point to the first signaling point is calculated to be less than 12 kilometers per hour, then the high-speed rail area signaling point is updated to the true starting point.

[0044] In the embodiment of the present invention, the selection of searching for "high-speed rail area signaling points" is to prevent misjudgment caused by abnormal signaling points. For example, due to an error in the base station location mark, the signaling point may jump to a very far location, even beyond the range of 2 kilometers, thereby reducing the probability of finding the true starting point. At the same time, due to the low signaling accuracy (approximately within 150 meters), it is reasonable to calculate the speed after more than 5 minutes. Otherwise, unreasonable situations such as moving 100 meters in 1 second may occur, that is, when it is less than 5 minutes, the speed calculation is greatly affected by the signaling accuracy, thereby affecting the accuracy of the high-speed rail section.

[0045] It should be noted that even if the signaling data is sparse, the above implementation can accurately identify the real starting point. For example, suppose the high-speed train departs at 10:00, and the similar signaling records are at 9:55 and 10:02. If the speed is slow when just setting off and the distance is within 2 kilometers, then the signaling point corresponding to 10:02 will be identified as the starting point through the above implementation, which is closer to the actual departure time and can be accepted. Through this method, the embodiment of the present invention can improve the accuracy of high-speed rail trip starting point identification while reducing errors caused by abnormal or sparse signaling data.

[0046] Similarly, in order to accurately find the true end point of the high-speed rail section to be evaluated, you can start searching from the last signaling point of the high-speed rail section to be evaluated in the direction of the first signaling point. If there is a time difference between a high-speed rail area signaling point and the last signaling point that exceeds the high-speed rail section duration threshold and the speed calculated based on the straight-line distance is less than the preset second speed threshold, then the high-speed rail area signaling point will be taken as the true termination signaling point.

[0047] Similarly, the second speed threshold can also be set based on a distance that the high-speed train may travel in a shorter time (such as the time threshold set above). The first speed threshold is less than the second speed threshold, for example, the second speed threshold is 3.33 kilometers per hour.

[0048] It can be seen that in the implementation method of identifying the actual end point, the embodiment of the present invention does not limit the straight-line distance between the high-speed rail area signaling point and the last signaling point to be within the distance threshold range. The reason is that considering that the user's home address may be near the station and there is enough signaling data, the high-speed rail journey may include many signaling points at home, which makes the end point exceed the preset distance range of the actual high-speed rail travel end point. Therefore, in the process of identifying the end point, a distance judgment condition is not set as for identifying the actual starting point.

[0049] After completing step c1 and determining the real starting point and end point of each high-speed railway segment to be identified, in order to facilitate the subsequent rapid acquisition of signaling point feature information, the embodiment of the present invention defines the signaling segment between the real starting point and the end point as a valid high-speed railway segment. Based on the signaling point data contained in the valid high-speed railway segment, step c2 can be executed to extract the signaling point feature information of the valid high-speed railway segment: Step c2: obtaining signaling point characteristic information of the effective high-speed railway section; In the embodiment of the present invention, the signaling point characteristic information includes not only the speed, duration, and ratio of signaling points in the non-high-speed rail area of ​​the effective high-speed rail section, but also distance information, specifically the sum of the signaling point distances of the effective high-speed rail section (denoted as D1) and the straight-line distance (denoted as D2). The process of obtaining these signaling point characteristic information is as follows: The first step is to obtain the signaling points within the effective high-speed railway section and the location and time of each signaling point; The second step is to determine the speed, duration and distance information of the effective high-speed rail section based on the time and location of each signaling point, and determine the proportion of signaling points in the non-high-speed rail area within the section based on the number of signaling points and the number of signaling points in the non-high-speed rail area; In the third step, the speed, duration, distance information and the proportion of signaling points in non-high-speed rail areas within the section are used as signaling point feature information.

[0050] Specifically, the duration can be determined based on the time difference between the start point and the end point, and the sum of the signaling point distances can be calculated based on the positions of each signaling point; the speed is determined by the straight-line distance and the duration.

[0051] It is worth noting that in practical applications, the calculation of the straight-line distance D2 may be affected by the recording frequency of the signaling point. Since the signaling point may interact with multiple base stations in a short period of time (e.g., 1 second), a signaling point may be recorded multiple times, which makes the calculated distance inaccurate. In order to solve this problem, the embodiment of the present invention adopts a sampling signaling point method to obtain a more accurate straight-line distance D2 through reasonable sampling.

[0052] As an optional implementation, the sampling rule may be, but is not limited to, a method of sampling every one or more signaling points. For example, if sampling is performed at intervals of one signaling point, the positions of the 1st, 3rd, 5th ... Nth signaling points are selected for straight-line distance calculation. If N is an odd number, the sum of the distances between these sampling points is directly calculated. If N is an even number, the sum of the distances between the 1st, 3rd, 5th ... N-1th points is first calculated, and then the distances between the N-1th to Nth points are added. By sampling, the deviation in straight-line distance calculation caused by the signaling point interacting with multiple base stations in a short period of time is avoided, thereby improving the accuracy of the straight-line distance calculation.

[0053] After completing steps c1 and c2, the embodiment of the present invention further performs step c3 to determine whether the high-speed railway section to be evaluated is the target high-speed railway section through the signaling point feature information. This process is based on the high-speed railway section feature conditions to ensure the accuracy and reliability of the recognition result.

[0054] Step c3: If the signaling point characteristic information meets the high-speed railway section characteristic conditions, the high-speed railway section to be evaluated is determined as the target high-speed railway section.

[0055] In the embodiment of the present invention, the characteristic conditions of the high-speed railway section are: Condition 1: The ratio of signaling points in the non-high-speed rail area within the section is less than the preset ratio threshold of signaling points in the non-high-speed rail area within the section and the duration is less than or equal to the high-speed rail section duration threshold; Condition 2: The proportion of signaling points in non-high-speed rail areas within the section is less than the threshold of the proportion of signaling points in non-high-speed rail areas within the section; the duration exceeds the threshold of the high-speed rail section duration; the speed exceeds the preset high-speed rail section speed assessment threshold; the straight-line distance is less than or equal to the preset multiple of the sum of the signaling point distances.

[0056] Based on the above conditions, the process of identifying whether the high-speed railway section to be evaluated is the target high-speed railway section is as follows: Step 1: Determine whether the duration of the effective high-speed rail section is less than or equal to the high-speed rail section duration threshold; If yes, go to step 2; otherwise, go to step 3; Step 2: If the ratio of signaling points in the non-high-speed rail area within the effective high-speed rail section is less than the ratio threshold of signaling points in the non-high-speed rail area within the section, the high-speed rail section to be evaluated is the target high-speed rail section; Step 3: If the proportion of signaling points in non-high-speed rail areas within the effective high-speed rail section is less than the threshold of the proportion of signaling points in non-high-speed rail areas within the section and the speed exceeds the high-speed rail section speed assessment threshold and the straight-line distance is less than or equal to the preset multiple of the sum of the signaling point distances, then whether the high-speed rail section to be evaluated is the target high-speed rail section.

[0057] In an embodiment of the present invention, the threshold value and preset multiple of the proportion of signaling points in the non-high-speed rail area within the section can be flexibly set according to actual needs. For example, the threshold value of the proportion of signaling points in the non-high-speed rail area within the section can be set to 0.3, and the preset multiple can be set to 3. The high-speed rail section speed evaluation threshold is flexibly set in combination with the actual speed of the high-speed rail operation (for example, 200 kilometers per hour), for example, it is set to 90 kilometers per hour. The high-speed rail section basic duration and the high-speed rail area separation duration threshold are the same as the high-speed rail section duration threshold used in step S102, for example, 5 minutes. This means that if the duration of a high-speed rail section exceeds 5 minutes and the speed exceeds 90 kilometers per hour, it means that the section has a higher speed, which meets the operating characteristics of the high-speed rail.

[0058] It can be seen from the above implementation that the embodiment of the present invention follows the principle of "limiting the speed if it exceeds the basic duration of the high-speed railway section, and limiting the proportion of signaling points in the non-high-speed railway area if it is lower than the basic duration of the high-speed railway section" in the process of identifying the target high-speed railway section. For high-speed railway sections with shorter duration (for example, no more than 5 minutes), due to the short time, the calculation of speed may be affected by the sparseness or error of signaling points, so it is judged whether it is a real high-speed railway section by limiting the proportion of signaling points in the non-high-speed railway area. For high-speed railway sections with longer duration (for example, more than 5 minutes), the calculation of speed is more reliable, so the speed threshold is used to judge whether it is a valid high-speed railway section.

[0059] In addition, the embodiment of the present invention also sets a sub-condition that the straight-line distance is less than or equal to a preset multiple of the sum of the signaling point distances. This condition is set to ensure that the travel direction of the high-speed rail section is relatively consistent and avoid atypical high-speed rail sections caused by signaling point errors or complex user movement paths. Through this condition, atypical high-speed rail sections caused by signaling point errors or complex user movement paths can be effectively excluded.

[0060] Through the above implementation, the embodiment of the present invention can combine the actual characteristics of the high-speed rail journey to ensure that the filtered high-speed rail segments have high accuracy and reliability. The setting of specific values ​​comprehensively considers the speed, duration and distribution characteristics of the high-speed rail, and can effectively distinguish the target high-speed rail segment from other non-high-speed rail segments, and can handle it well even when the number of signaling points is small.

[0061] Next, the embodiment of the present invention further integrates the target high-speed rail sections to obtain the high-speed rail itinerary to be evaluated, see step S104.

[0062] In step S104, the target high-speed rail sections are integrated based on the travel status of the target high-speed rail sections and the gap segment characteristics between the target high-speed rail sections to obtain the high-speed rail travel to be evaluated.

[0063] In the embodiment of the present invention, the "trip status" refers to whether the high-speed rail segment belongs to the previous trip or the next trip. Specifically, if the previous trip of the high-speed rail segment has ended, the high-speed rail segment belongs to the next trip; conversely, if the previous trip has not ended, the high-speed rail segment is a continuation of the previous trip.

[0064] In an optional implementation, an embodiment of the present invention can indicate in advance whether the journey before a high-speed rail section has ended by configuring a journey end flag (denoted as endFlag). In other words, if the high-speed rail section does not have this journey end flag, it indicates that the journey is still continuing. If it does, it indicates that the journey is still continuing.

[0065] In the embodiment of the present invention, the method of configuring the trip end mark is shown in steps d1 to d2. The description is as follows: Step d1: obtaining the number of inter-segment signaling points and the ratio of inter-segment high-speed rail area signaling points between adjacent target high-speed rail segments; Step d2: If the number of signaling points between sections exceeds the preset number and the ratio of signaling points in the high-speed rail area between sections is less than the preset threshold of signaling points ratio between sections in the non-high-speed rail area, a trip end mark is configured for the next target high-speed rail section in the adjacent target high-speed rail sections.

[0066] In an embodiment of the present invention, the threshold value of the ratio of signaling points in the non-high-speed rail area between segments is an empirical value, which can be flexibly set according to the actual application scenario. For example, assuming that the total number of signaling is large, the ratio of signaling points in the high-speed rail area is meaningful; if the total number of signaling is too small, there may be sporadic signaling situations, such as still driving in the high-speed rail area but interacting with a base station far away from the high-speed rail line, which may affect the final recognition result. Therefore, the threshold value of the number of signaling points between segments can be set in combination with the threshold value of the ratio of signaling points in the non-high-speed rail area between segments, for example, 10 signaling points.

[0067] For ease of understanding, assume that the adjacent target high-speed rail sections are S1 and S2. By counting the number of inter-segment signaling points between the last signaling point of S1 and the first signaling point of S2 and the number of signaling points in the inter-segment high-speed rail area, the ratio of signaling points in the inter-segment high-speed rail area between S1 and S2 can be calculated. If the number of inter-segment signaling points between S1 and S2 exceeds 10, and the ratio of signaling points in the inter-segment high-speed rail area is less than 0.3, it is considered that the high-speed rail journey before S2 has ended, and a trip end flag (endFlag=true) is configured for S2. Otherwise, it is considered to be still in the process of travel. By analogy, the same processing method is continued for subsequent adjacent target high-speed rail sections.

[0068] In step S104, in addition to the judgment of the travel status, the characteristics of the vacancy section also need to be considered. The vacancy section refers to a blank area formed between adjacent target high-speed rail sections, and its characteristics include interval duration, interval speed, number of interval signaling points and interval straight-line distance. Among them, the number of interval signaling points can be directly counted; the interval duration refers to the time difference between the first signaling point and the last signaling point in the vacancy section; the interval straight-line distance and interval duration can be calculated by the corresponding position and time of the first signaling point and the last signaling point in the vacancy section; the interval speed is the ratio of the interval distance to the interval duration.

[0069] By comprehensively considering the travel status and gap segment characteristics, the embodiment of the present invention can more accurately identify and integrate the target high-speed rail segment, thereby forming a complete high-speed rail itinerary, as described below: Step d1: judging whether each target high-speed railway section meets a preset first characteristic evaluation condition according to the travel status and the gap section characteristic condition; If so, proceed to step d2, otherwise, proceed to step d3; Step d2: Integrate the target high-speed rail sections before the target high-speed rail section into one journey section; Step d3: Determine whether the target high-speed railway section meets the preset second characteristic evaluation condition; If satisfied, return to step d2; if not satisfied, continue to determine the next target high-speed rail section.

[0070] The first characteristic evaluation condition is: there is a dwelling point of the target user in the gap segment and the gap segment duration exceeds the preset first gap segment duration threshold and the dwelling duration threshold at the same time; the second evaluation condition is: the gap segment duration is less than the first gap segment duration threshold; or the gap segment duration is less than the second gap segment duration threshold and the gap segment speed is within the preset speed range; the first gap segment duration is less than the second gap segment duration; Step d4: All the travel segments are combined into a high-speed rail travel to be evaluated.

[0071] In the embodiment of the present invention, the dwelling point of the target user has been obtained in the data preparation stage. In order to quickly and conveniently determine whether there is a dwelling point of the target user in the gap segment, before executing step d1, the dwelling point and the target high-speed rail segment can be preprocessed in the following manner, and the interval characteristics of the gap segment can be pre-calculated: The first step is to obtain the target user's residence point data within a day; wherein the residence point data includes the residence start time and residence duration of each residence point; The second step is to arrange the target high-speed rail sections and the dwelling points in order according to the start time of each target high-speed rail section and the start time of each dwelling. After the arrangement is completed, the dwelling points whose dwelling time exceeds the preset dwelling time threshold are removed; The third step is to calculate the gap duration and gap speed between each target high-speed rail section.

[0072] After the start time of the target high-speed railway section and the start time of the dwell point are uniformly sorted according to the above implementation mode, for ease of understanding, the sorting result can be as follows: Figure 4 shown. Figure 4 It is a schematic diagram of the orderly arrangement of high-speed railway sections and stay points provided by an embodiment of the present invention.

[0073] During the sorting process, you need to pay attention to the situation where the residence time conflicts with the high-speed rail section time due to cross-province. For example, if the end time of the residence point is later than the start time of the next high-speed rail section after sorting by start time, the end time of the residence point is set to the start timestamp of the next high-speed rail section minus 1 millisecond. This ensures the accuracy of the sorting results.

[0074] After the above sorting operation, the dwell points corresponding to the dwell time in the ordered sequence that exceed the preset dwell time are removed. At the same time, various interval features can be calculated based on the signaling points of the gap sections between the target high-speed rail sections.

[0075] For ease of understanding, for the above steps d1 and d2: each target high-speed rail section can be determined to be a target high-speed rail section according to the following conditions. If the following conditions are met, it can be understood that the target user has gotten off the train or is waiting for a transfer, and can be regarded as a reasonable high-speed rail section: Condition 1: There is a trip end mark; Condition 2: There is a dwelling point of the target user in the gap segment and the gap segment duration exceeds both the preset first gap segment duration threshold and the dwelling duration threshold.

[0076] If the target high-speed rail section meets condition 1 or condition 2, the sections before the target high-speed rail section can be merged into one high-speed rail journey. If neither condition 1 nor condition 2 is met, continue to judge according to the following conditions: Condition 3: The gap duration is less than the first gap duration threshold; the first gap duration is less than the second gap duration; Condition 4: The gap duration is less than a preset second gap duration threshold and the gap speed is within a preset speed range.

[0077] If the current target high-speed rail section meets condition 3 or condition 4, the sections before the target high-speed rail section can be merged into a high-speed rail journey. If neither condition 3 nor condition 4 is met, no merging is performed, and the next target high-speed rail section is judged until all target high-speed rail sections are judged.

[0078] In the embodiment of the present invention, the first gap segment duration threshold and the second gap segment duration threshold are both empirical values ​​and can be flexibly set according to the actual application scenario. For example, the first gap segment duration threshold can be set to 20 minutes, and the second gap segment duration threshold can be set to 1.5 hours. The dwell time threshold is determined based on the total duration of the dwell points in the gap segment, for example, it can be set to 80% of the total duration of the dwell points. This setting can be considered that the target user has stayed in the gap segment for an excessively long time.

[0079] In addition, the second gap duration threshold in condition 4 is greater than the first gap duration threshold, for example, set to 1.5 hours. The speed range is set to exceed the maximum speed of the high-speed rail to avoid identifying the situation of airplane travel, for example, set to greater than 75 km / h and less than 400 km / h.

[0080] Through the above conditions 3 and 4, the embodiment of the present invention can adapt to the situation where the signaling between two high-speed rail sections is sparse. Even if there is no signaling point within the first gap segment duration threshold, it can still be connected to the previous high-speed rail section to avoid trip identification errors. Figure 4 If the gap segment between AB and CD meets the merging condition, and the gap segment between CD and EF does not meet the merging condition, the high-speed rail journey can be divided into: ABCD, EF.

[0081] In one embodiment of the present invention, after obtaining each travel segment, the travel segments with a travel time of more than 5 minutes and a travel speed of more than 35 kilometers per hour can be further filtered out. If there is no travel segment with a travel time of more than 5 minutes, the travel speed can be directly used for filtering. On this basis, step S105 is performed to determine whether the identified high-speed rail itinerary is reasonable.

[0082] In step S105, the embodiment of the present invention performs a final rationality evaluation on the integrated high-speed rail itinerary to be evaluated. First, the total number of signaling points, the total non-high-speed rail area signaling point ratio, the trip duration, and the trip speed in the high-speed rail itinerary to be evaluated are obtained as trip characteristics; if the trip characteristics meet at least one preset high-speed rail itinerary characteristic condition, the high-speed rail itinerary to be evaluated is determined to be a reasonable high-speed rail itinerary.

[0083] In the embodiment of the present invention, each signaling point included in the high-speed rail itinerary to be evaluated and its corresponding time and position can be obtained to determine the itinerary characteristics. The travel speed can be obtained as follows: First, the cumulative distance of each travel segment and the sum of the distance between segments are calculated, denoted as travelD. Then, the cumulative duration of each travel segment and the sum of the duration between segments are determined, denoted as travelT. The travel speed is obtained by dividing travelD by travelT, denoted as travelSpeed. This calculation method can effectively eliminate the influence of the start of the starting segment and the stop of the ending segment, so that the calculated travel speed is consistent with the actual travel speed of the high-speed rail.

[0084] It should be understood that the distances and durations involved above can be determined using the positions and times corresponding to the signaling points within each journey segment and between the journey segments, and will not be elaborated here.

[0085] Through the above implementation, it can be considered that the situation of starting at the starting section and gradually stopping at the ending section can be discarded, and the calculated travel speed is consistent with the actual travel speed of the high-speed rail.

[0086] Similarly, the number of signaling points within the itinerary and the proportion of signaling points in the non-high-speed rail area within the itinerary can be obtained based on the statistical results of the number of signaling points contained in each itinerary segment and between itinerary segments and the number of signaling segments in the non-high-speed rail area.

[0087] Based on the above travel characteristics, the embodiment of the present invention sets the following high-speed rail travel characteristic conditions to determine whether the high-speed rail travel to be evaluated is reasonable: Condition a: The travel speed exceeds the first high-speed rail travel speed threshold and the proportion of signaling points in the non-high-speed rail area within the journey is less than the preset threshold of signaling points in the non-high-speed rail area within the journey. For example, the travel speed exceeds 108 kilometers per hour and the proportion of signaling points in the non-high-speed rail area within the journey is less than 0.4.

[0088] Condition b: The travel duration exceeds the travel duration threshold, the travel speed exceeds the second high-speed rail travel speed threshold, and the number of signaling points within the trip exceeds the number of signaling points within the trip threshold. For example, the travel duration exceeds 1 hour, the travel speed exceeds 90 kilometers per hour, and the number of signaling points within the trip exceeds 200.

[0089] If the high-speed rail trip to be evaluated meets at least one of conditions a and b, the trip is considered to be a reasonable high-speed rail trip. This evaluation method comprehensively considers the speed, duration and signaling point distribution characteristics of the high-speed rail trip, and can effectively distinguish the real high-speed rail trip.

[0090] Finally, through the above implementation, the embodiment of the present invention can obtain a real high-speed rail itinerary, such as Figure 5 As shown, Figure 5 A schematic diagram of the recognition result provided by an embodiment of the present invention.

[0091] It should be noted that in the high-speed rail travel itinerary identification results of the embodiment of the present invention, the travel itinerary may cover part of the waiting time period (the continuous waiting time period in the high-speed rail area before departure) and the situation of staying in the high-speed rail area after getting off the train (such as waiting for transfers, shopping in the mall near the station, etc.). In addition, the boarding and alighting dwelling points (dwell points) in the high-speed rail travel itinerary are defined as the last dwelling point for more than 20 minutes before getting on the train and the first dwelling point for more than 20 minutes after getting off the train. These points serve as possible boarding and alighting locations. If the high-speed rail is on the same line as the conventional rail or road travel, and the speed can reach a certain level, this part of the itinerary may also be identified as a high-speed rail section. This design enables the present invention to more comprehensively capture the user's high-speed rail travel behavior, and maintain a high level of recognition accuracy and reliability even in complex travel scenarios.

[0092] The embodiment of the present invention further provides a computer device 60, see Figure 6 , Figure 6 The computer device 60 provided in the embodiment of the present invention includes a memory 601, a processor 602 and a communication interface 603. The memory 601, the processor 602 and the communication interface 603 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines.

[0093] Optionally, the bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 6 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0094] In the embodiment of the present invention, the processor 602 may be a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, or a discrete hardware component, and may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiment of the present invention. A general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiment of the present invention may be directly embodied as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor. The software module may be located in the memory 601, and the processor 602 reads the program instructions in the memory 601 and completes the steps of the above method in combination with its hardware.

[0095] In the embodiment of the present invention, the memory 601 may be a non-volatile memory, such as a hard disk (HDD) or a solid-state drive (SSD), etc., or a volatile memory (Volatile Memory), such as RAM. The memory may also be any other medium that can be used to carry or store the desired program executable code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory in the embodiment of the present invention may also be a circuit or any other device that can realize a storage function, for storing instructions and / or data.

[0096] The memory 601 can be used to store software programs and modules, which can be stored in the memory 601 in the form of software or firmware or in the operating system (OS) of the computer device 600. The processor 602 executes various functional applications and data processing by executing the software programs and modules stored in the memory 601. The communication interface 603 can be used to communicate signaling or data with other node devices.

[0097] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0098] Understandably, Figure 6 The structure shown is for illustration only. The computer device 60 may also include Figure 6 More or fewer components as shown, or with Figure 6 Different configurations are shown. Figure 6 The components shown may be implemented in hardware, software or a combination thereof.

[0099] The computer device 60 may also be, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud consisting of a large number of hosts or network servers based on cloud computing.

[0100] Based on the above embodiments, an embodiment of the present invention further provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a computer, the computer executes the method provided by the above embodiments.

[0101] Based on the above embodiments, an embodiment of the present invention further provides a computer program. When the computer program is run on a computer, the computer executes the method provided by the above embodiments.

[0102] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0103] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0104] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0105] It should be noted that if the function is implemented in the form of a software function module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially or partly contribute to the prior art or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) 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), random access memory (RAM), disk or optical disk, and other media that can store program code.

[0106] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0107] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A high-speed rail itinerary identification method based on daily signaling data, characterized in that: The method comprises: Obtain an ordered sequence of signaling points of a target user within one day; wherein the signaling points in the ordered sequence of signaling points are divided into high-speed rail area signaling points and non-high-speed rail area signaling points; According to the time interval and area attributes of adjacent signaling points in the ordered signaling point sequence, a plurality of signaling segments are divided from the ordered signaling point sequence; wherein the signaling segments are divided into high-speed rail area signaling segments and non-high-speed rail area signaling segments; Integrate the plurality of signaling segments according to a preset high-speed rail segment duration threshold and a high-speed rail area separation duration threshold to obtain a plurality of high-speed rail segments to be evaluated, and determine the high-speed rail segment to be evaluated that meets the preset high-speed rail segment characteristic conditions as the target high-speed rail segment; Integrate the target high-speed rail sections based on the travel status of the target high-speed rail sections and the gap section characteristics between the target high-speed rail sections to obtain a high-speed rail travel to be evaluated; Whether the high-speed rail itinerary to be evaluated is reasonable is determined according to the itinerary characteristics of the high-speed rail itinerary to be evaluated.

2. The high-speed rail itinerary identification method based on daily signaling data according to claim 1 is characterized in that: According to the time intervals and area attributes of adjacent signaling points in the ordered signaling point sequence, a plurality of signaling segments are divided from the ordered signaling point sequence, including: If the time interval between the adjacent signaling points exceeds a preset signaling interval duration threshold or the adjacent signaling points are located in different areas, segmentation is performed between the adjacent signaling points; The divided signaling points are segmented and integrated to obtain a plurality of the signaling segments.

3. The high-speed rail itinerary identification method based on daily signaling data according to claim 1 is characterized in that: According to the preset high-speed rail section duration threshold and the high-speed rail area departure duration threshold, the plurality of signaling segments are integrated to obtain a plurality of high-speed rail sections to be evaluated, including: If the time interval between adjacent signaling segments exceeds the high-speed rail segment duration threshold, the adjacent signaling segments are segmented to obtain a signaling segment group; Determine whether the duration of the non-high-speed rail area signaling segment in the signaling segment group is less than the high-speed rail area departure duration threshold; If so, the signaling segment group is used as the high-speed railway segment to be evaluated; otherwise, the signaling segment in the non-high-speed railway area is split from the last signaling point to obtain the high-speed railway segment to be evaluated.

4. The high-speed rail itinerary identification method based on daily signaling data according to claim 1 is characterized in that: The high-speed railway sections to be evaluated that meet the preset high-speed railway section characteristic conditions are determined as target high-speed railway sections, including: Correcting the real starting point and end point of the high-speed railway section to be evaluated, and taking the real signaling segment between the starting point and the end point as a valid high-speed railway section; Obtaining signaling point characteristic information of the effective high-speed railway section; If the signaling point characteristic information meets the high-speed railway section characteristic condition, the high-speed railway section to be evaluated is determined as the target high-speed railway section.

5. The high-speed rail itinerary identification method based on daily signaling data according to claim 4 is characterized in that: The high-speed railway section to be evaluated that meets the preset high-speed railway section characteristic conditions is determined as the target high-speed railway section, and also includes: Obtaining the signaling points within the effective high-speed railway section and the positions and times of the signaling points; Based on the time and position of each signaling point, determine the speed, duration and distance information of the effective high-speed rail section, and determine the proportion of signaling points in the non-high-speed rail area in the section according to the number of signaling points and the number of signaling points in the non-high-speed rail area in the section; The speed, duration, distance information and the proportion of signaling points in non-high-speed rail areas within the section are used as the signaling point characteristic information.

6. The high-speed rail itinerary identification method based on daily signaling data according to claim 1 is characterized in that: The target high-speed rail sections are integrated based on the travel status of the target high-speed rail sections and the gap section characteristics between the target high-speed rail sections to obtain the high-speed rail travel to be evaluated, including: Determine whether the travel status and gap segment characteristics of each target high-speed railway section meet a preset first characteristic evaluation condition; If yes, then integrate the target high-speed rail sections before the target high-speed rail section into one travel section; if no, determine whether the target high-speed rail section meets the preset second characteristic evaluation condition; If the conditions are met, the target high-speed rail sections before the target high-speed rail section are integrated into one travel section; The first characteristic evaluation condition is: there is a trip end mark, or there is a target user's residence point in the gap segment and the gap segment duration exceeds the preset first gap segment duration threshold and residence duration threshold at the same time; the second characteristic evaluation condition is: the gap segment duration is less than the first gap segment duration threshold; or the gap segment duration is less than the second gap segment duration threshold and the gap segment speed is within the preset speed range; the first gap segment duration threshold is less than the second gap segment duration threshold; All of the trip segments are combined into the high-speed rail trip to be evaluated.

7. The high-speed rail itinerary identification method based on daily signaling data according to claim 6 is characterized in that: The target high-speed rail sections are integrated based on the travel status of the target high-speed rail sections and the gap section characteristics between the target high-speed rail sections to obtain the high-speed rail travel to be evaluated, further comprising: Obtain the number of inter-section signaling points and the ratio of inter-section high-speed rail area signaling points between adjacent target high-speed rail sections; If the number of inter-segment signaling points exceeds the preset inter-segment signaling point number threshold and the ratio of inter-segment high-speed rail area signaling points is less than the preset inter-segment non-high-speed rail area signaling point ratio threshold, the trip end marker is configured for the latter target high-speed rail segment in the adjacent target high-speed rail segments.

8. The high-speed rail itinerary identification method based on daily signaling data according to claim 6 is characterized in that: The target high-speed rail sections are integrated based on the travel status of the target high-speed rail sections and the gap section characteristics between the target high-speed rail sections to obtain the high-speed rail travel to be evaluated, further comprising: Obtaining the dwelling point data of the target user in one day; wherein the dwelling point data includes the dwelling start time and dwelling duration of each dwelling point; According to the start time of each target high-speed railway section and each dwelling point, the target high-speed railway section and the dwelling point are arranged in order, and the dwelling points whose dwelling time exceeds the preset dwelling time threshold are eliminated; Calculate the gap duration and gap speed between each of the target high-speed rail sections.

9. The high-speed rail itinerary identification method based on daily signaling data according to claim 1 is characterized in that: Determining whether the high-speed rail itinerary to be evaluated is reasonable according to the itinerary characteristics of the high-speed rail itinerary to be evaluated includes: Obtaining the total number of signaling points, the total non-high-speed rail area signaling point ratio, the trip duration, and the trip speed within the high-speed rail trip to be evaluated as the trip characteristics; If the travel characteristics meet at least one preset high-speed rail travel characteristic condition, the high-speed rail travel to be evaluated is determined to be a reasonable high-speed rail travel.

10. A computer device, characterized in that: include: memory and one or more processors; The memory is used to store one or more computer programs; When the one or more computer programs are executed by the one or more processors, the one or more processors implement the high-speed rail itinerary identification method based on daily signaling data as described in any one of claims 1-9.

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