CN110826758B - Stroke type determining method and device, storage medium and terminal - Google Patents
Stroke type determining method and device, storage medium and terminal Download PDFInfo
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Abstract
A travel type determining method and device, a storage medium and a terminal, wherein the travel type determining method comprises the following steps: acquiring track data of a user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed; determining a plurality of segment points according to the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points, wherein the travel types of the track points between every two segment points are the same; and determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment refers to a track formed by track points between two adjacent segment points. The technical scheme of the invention can accurately determine the travel mode of the user.
Description
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and apparatus for determining a trip type, a storage medium, and a terminal.
Background
As technology advances, users can locate their own locations using smart devices. In addition, when the user goes out, the travel track of the user can be obtained through continuous positioning.
In the prior art, after a user goes out, the number of steps of the user going out can be automatically recorded, and the real-time position of the user can be automatically positioned and acquired.
However, how to determine the travel mode of the user is a technical problem to be solved.
Disclosure of Invention
The invention solves the technical problem of how to determine the travel mode of a user.
In order to solve the above technical problems, an embodiment of the present invention provides a travel type determining method, including: acquiring track data of a user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed; determining a plurality of segment points according to the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points, wherein the travel types of the track points between every two segment points are the same; and determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment refers to a track formed by track points between two adjacent segment points.
Optionally, the track points are acquired according to a preset time interval, and determining the plurality of segment points according to the time interval between adjacent track points includes: and if the time interval between the adjacent track points is larger than the preset time interval, determining that the later track point in the adjacent track points is a segment point.
Optionally, the determining the plurality of segment points according to the difference of the instantaneous speeds of the adjacent track points includes: calculating a difference value between the instantaneous speed of a subsequent track point in adjacent track points and the instantaneous speed of a previous track point in the adjacent track points, and calculating a ratio of the difference value to the instantaneous speed of the previous track point; and if the ratio reaches a first preset ratio, determining the latter track point as a segmentation point.
Optionally, the stroke type determining method further includes: counting the distance of each track segment; and recording the distance and the travel type of each track segment by adopting a block chain technology.
Optionally, the determining the travel type of each track segment at least according to the average speed among the plurality of segment points includes: if the average speed between two adjacent segmentation points is lower than a first preset value, determining that the travel type of the track segment corresponding to the two adjacent segmentation points is walking; and if the average speed between two adjacent segmentation points is larger than the first preset value and smaller than a second preset value, determining that the travel type of the track segment is running, wherein the second preset value is larger than the first preset value.
Optionally, the determining the travel type of each track segment at least according to the average speed among the plurality of segment points includes: if the average speed between two adjacent segmentation points reaches a first preset value, judging whether track segments corresponding to the two adjacent segmentation points are coincident with a public transportation route or not; and if the track section coincides with the public transportation route, determining the travel type of the track section as public transportation.
Optionally, the determining that the travel type of the track segment is public transportation includes: if the track section coincides with the subway line and the average speed reaches a third preset value, determining that the travel type of the track section is subway travel, wherein the third preset value is larger than the first preset value; if the track section coincides with the bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section is smaller than a first preset threshold value, determining that the travel type of the track section is bus travel, otherwise, determining that the travel type of the track section is driving travel, wherein the fourth preset value is larger than the third preset value; and if the track section coincides with the train route, determining that the travel type of the track section is train travel.
Optionally, the track segment is determined to coincide with the public transportation route by: determining a start point and an end point of the track segment, and a public transportation route between the start point and the end point; acquiring a site position in the public transportation route; determining track points and the number of the track points, wherein the distance between the track points and the site position is smaller than a second preset threshold value, in the track section, and calculating the ratio of the number to the total number of the track points included in the track section; and if the ratio reaches a second preset ratio, determining that the track section coincides with the public transportation route.
Optionally, the determining the travel type of each track segment at least according to the average speed among the plurality of segment points includes: if the average speed between two adjacent segment points reaches a second preset value, and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold value, determining the travel type of the track segment to be riding, otherwise, determining the travel type of the track segment to be driving, wherein the fifth preset value is larger than the second preset value.
In order to solve the technical problem, the embodiment of the invention also discloses a travel type determining device, which comprises: the track data acquisition module is suitable for acquiring track data of a user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed; the segment point determining module is suitable for determining a plurality of segment points according to the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points, and the travel types of the track points between every two segment points are the same; and the travel type determining module is suitable for determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment refers to a track formed by track points between two adjacent segment points.
Optionally, the track points are acquired according to a preset time interval, and the segment point determining module includes: the first segmentation point determining unit is suitable for determining that the next track point in the adjacent track points is a segmentation point when the time interval between the adjacent track points is larger than the preset time interval.
Optionally, the segmentation point determining module includes: a speed difference calculating unit adapted to calculate a difference between an instantaneous speed of a subsequent one of the adjacent track points and an instantaneous speed of a previous one of the adjacent track points, and calculate a ratio of the difference to the instantaneous speed of the previous track point; and the second segmentation point determining unit is suitable for determining the subsequent track point as a segmentation point when the ratio reaches a first preset ratio.
Optionally, the travel type determining device further includes: the distance statistics module is suitable for counting the distance of each track segment; and the block chain storage module is suitable for recording the distance and the travel type of each track segment by adopting a block chain technology.
Optionally, the trip type determining module includes: the walking determining unit is suitable for determining that the travel type of the track section corresponding to the two adjacent segmentation points is walking when the average speed between the two adjacent segmentation points is lower than a first preset value; the running determining unit is suitable for determining that the travel type of the track segment is running when the average speed between two adjacent segmentation points is larger than the first preset value and smaller than a second preset value, and the second preset value is larger than the first preset value.
Optionally, the trip type determining module includes: the route coincidence judging unit is suitable for judging whether the track segments corresponding to the two adjacent segmentation points coincide with the public transportation route or not when the average speed between the two adjacent segmentation points reaches a first preset value; and the public transportation determining unit is suitable for determining that the travel type of the track section is public transportation when the track section is coincident with the public transportation route.
Optionally, the public transportation determining unit includes: the subway determining subunit is suitable for determining that the travel type of the track section is subway travel when the track section coincides with a subway route and the average speed reaches a third preset value, and the third preset value is larger than the first preset value; the bus determining subunit is suitable for determining that the travel type of the track section is bus travel when the track section coincides with a bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section is smaller than a first preset threshold value; the driving determining subunit is suitable for determining that the travel type of the track section is driving travel when the track section coincides with a bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section reaches a first preset threshold value, wherein the fourth preset value is larger than the third preset value; and the train determining subunit is suitable for determining that the travel type of the track section is train travel when the track section is coincident with the train route.
Optionally, the route coincidence determination unit determines that the track segment coincides with a public transportation route by: determining a start point and an end point of the track segment, and a public transportation route between the start point and the end point; acquiring a site position in the public transportation route; determining track points and the number of the track points, wherein the distance between the track points and the site position is smaller than a second preset threshold value, in the track section, and calculating the ratio of the number to the total number of the track points included in the track section; and if the ratio reaches a second preset ratio, determining that the track section coincides with the public transportation route.
Optionally, the trip type determining module includes: the riding determining unit is suitable for determining that the travel type of the track section is riding when the average speed between two adjacent segmentation points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track section is smaller than a second preset threshold value; and the driving determining unit is suitable for determining that the travel type of the track segment is driving travel when the average speed between two adjacent segmentation points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold value, wherein the fifth preset value is larger than the second preset value.
The embodiment of the invention also discloses a storage medium, on which computer instructions are stored, which execute the steps of the travel type determining method when running.
The embodiment of the invention also discloses a terminal which comprises a memory and a processor, wherein the memory stores computer instructions capable of running on the processor, and the processor executes the steps of the travel type determining method when running the computer instructions.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
the technical scheme of the invention obtains the track data of the user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed; determining a plurality of segment points according to the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points, wherein the travel types of the track points between every two segment points are the same; and determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment refers to a track formed by track points between two adjacent segment points. According to the technical scheme, the track data of the user are analyzed, so that the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points is obtained, and the segmentation points for distinguishing different stroke types can be determined; the travel type of the track section can be determined at least through the average speed among the segmentation points, and the travel type can represent the travel mode of the user, so that references can be provided for the follow-up travel and other behaviors of the user.
Further, the track points are acquired according to a preset time interval, and if the time interval between the adjacent track points is larger than the preset time interval, the next track point in the adjacent track points is determined to be a segment point. In the technical scheme of the invention, when the network is interrupted or the signal is poor, the track points can not be acquired; in this case, the re-collected track point, that is, the later track point is used as a segmentation point to divide the travel of the user in the time interval, so that the accuracy of travel type judgment is improved, and the accuracy of travel mode judgment of the user is further improved.
Further, calculating a difference value between the instantaneous speed of a subsequent track point in adjacent track points and the instantaneous speed of a previous track point in the adjacent track points, and calculating a ratio of the difference value to the instantaneous speed of the previous track point; and if the ratio reaches a first preset ratio, determining the latter track point as a segmentation point. In the technical scheme of the invention, if the instantaneous speed of the latter track point exceeds the instantaneous speed of the former track point by more than a first preset ratio, for example, 50%, the invention indicates that the vehicle on which the user sits at the latter track point may be braked or started, or the user switches the vehicle at the latter track point, so that the latter track point can be used as a segmentation point and as a starting point of the next track segment, thereby ensuring the accuracy of track segment division and further improving the accuracy of determining the travel mode of the user.
Drawings
FIG. 1 is a flow chart of a method of determining a trip type according to an embodiment of the present invention;
FIG. 2 is a flow chart of one embodiment of step S102 shown in FIG. 1;
FIG. 3 is a flow chart of another embodiment of step S102 shown in FIG. 1
FIG. 4 is a flow chart of one embodiment of step S103 shown in FIG. 1;
FIG. 5 is a flow chart of another embodiment of step S103 shown in FIG. 1;
FIG. 6 is a flow chart of yet another embodiment of step S103 shown in FIG. 1;
FIG. 7 is a schematic diagram of a specific application scenario according to an embodiment of the present invention;
FIG. 8 is a schematic view of a travel type determining device according to an embodiment of the present invention;
FIG. 9 is a schematic diagram of one embodiment of the segmentation point determination module 502 shown in FIG. 8;
fig. 10 is a schematic diagram of a specific embodiment of the stroke type determining module 503 shown in fig. 8.
Detailed Description
As described in the background art, how to determine the travel mode of the user is a technical problem to be solved.
According to the technical scheme, the track data of the user are analyzed, so that the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points is obtained, and the segmentation points for distinguishing different stroke types can be determined; the travel type of the track section can be determined at least through the average speed among the segmentation points, and the travel type can represent the travel mode of the user, so that references can be provided for the follow-up travel and other behaviors of the user.
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
Fig. 1 is a flowchart of a travel type determining method according to an embodiment of the present invention.
The travel type determination method shown in fig. 1 may include the steps of:
step S101: acquiring track data of a user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed;
step S102: determining a plurality of segment points according to the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points, wherein the travel types of the track points between every two segment points are the same;
step S103: and determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment refers to a track formed by track points between two adjacent segment points.
In implementations, the user's trajectory data may be user's positioning data. The trajectory data may be obtained using any available positioning technique, such as GPS positioning, beidou satellite positioning, base station positioning, etc. The trajectory data includes a plurality of trajectory points, which may have coordinates, time, and instantaneous speed. In particular, the coordinates of the track point may represent the location of the user, the time of the track point represents the time the user is at the location, and the instantaneous speed of the track point represents the instantaneous speed of the user at the location.
Further, the trajectory data of the user over a period of time may form a trajectory of the user over the period of time. The trace points may be acquired periodically.
Specifically, the trajectory data of the user may be acquired in real time. The trajectory data of the user may also be acquired periodically. For example, the trajectory data of the user during the previous day is acquired at zero daily.
In a specific application, a user carries an intelligent device when traveling, and the intelligent device can collect and record track data of the user.
After the trajectory data of the user is acquired, in a specific implementation of step S102, a plurality of segmentation points may be determined. Because the user may have a plurality of travel modes in the same track, the user track needs to be segmented, and then the travel type is determined. Here, the plurality of segment points may divide the user's track into a plurality of track segments over a period of time. The travel type of each track segment is uniform.
Specifically, since the speeds corresponding to different stroke types are different, a plurality of segment points can be determined according to the difference of the instantaneous speeds of the adjacent track points; alternatively, since the transition of the stroke type causes the time interval of the acquired trajectory points to be lengthened or shortened, a plurality of segment points may be determined according to the time interval between adjacent trajectory points.
The speeds corresponding to the different travel types are different, and in the implementation of step S103, the travel type of each track segment may be determined according to the average speed between the plurality of segment points. In particular, the average speed between two adjacent segment points may be an average of the instantaneous speeds of the track points between the two adjacent segment points. It can also be calculated by: and determining the distance between two adjacent segmentation points and the time difference between the two adjacent segmentation points, and calculating the ratio of the distance to the time difference.
Therefore, the travel type of each track section in the track of the user is determined, and each travel mode adopted by the user in the track can be determined. For example, the travel types of the user on the previous day are walking, subway, walking, bus, driving, respectively.
In a preferred embodiment of the present invention, the method for determining a travel type shown in fig. 1 may further include the steps of counting distances of each track segment; the distance and travel type of each track segment is recorded.
Further, the distance and the travel type of each track segment are recorded by adopting a block chain technology.
In specific implementation, the distance and the travel type of the track segment belong to personal behaviors of a user, and have higher safety requirements. The existing user track is directly stored in the APP of the intelligent equipment, and an APP operator has permission to change the user track, so that the security is low.
In the embodiment of the invention, the block chain technology adopts a decentralised storage mode, so that the safety of recorded data, namely the distance of each track section and the travel type can be ensured, and the recorded data is prevented from being tampered.
In a specific embodiment of the present invention, the track points are acquired at preset time intervals. Referring to fig. 2, step S102 shown in fig. 1 may include the following steps: step S201: and if the time interval between the adjacent track points is larger than the preset time interval, determining that the later track point in the adjacent track points is a segment point.
In this embodiment, since the track points are collected at preset time intervals, the time intervals between adjacent track points are preset time intervals. If the time interval between the adjacent track points is larger than the preset time interval, the abnormal condition occurs when the adjacent track points are acquired. An abnormal situation may be a network signal failure or a poor signal, in which case a change in the type of trip may be indicated. The latter one of the adjacent track points may be a segment point. The travel type of the segment point can be determined and confirmed in a subsequent step.
That is, when the network is interrupted or the signal is poor, the track point cannot be acquired; in this case, the re-collected track point, that is, the later track point is used as a segmentation point to divide the travel of the user in the time interval, so that the accuracy of travel type judgment is improved, and the accuracy of travel mode judgment of the user is further improved.
In a specific embodiment of the present invention, the track points are acquired at preset time intervals. Referring to fig. 3, step S102 shown in fig. 1 may include the following steps:
step S202: calculating a difference value between the instantaneous speed of a subsequent track point in adjacent track points and the instantaneous speed of a previous track point in the adjacent track points, and calculating a ratio of the difference value to the instantaneous speed of the previous track point;
step S203: and if the ratio reaches a first preset ratio, determining the latter track point as a segmentation point.
In a specific implementation, the difference between the instantaneous speed of the next track point in the adjacent track points and the instantaneous speed of the previous track point in the adjacent track points is an absolute difference, and the instantaneous speed change of the next track point relative to the previous track point cannot be accurately measured. The ratio of the difference to the instantaneous speed of the previous trace point can thus be calculated to measure the instantaneous speed change of the latter trace point relative to the previous trace point.
In the embodiment of the invention, if the instantaneous speed of the latter track point exceeds the instantaneous speed of the former track point by more than a first preset ratio, for example, 50%, the present invention indicates that the vehicle on which the user sits at the latter track point may be braked or started, or the user switches the vehicle at the latter track point, so that the latter track point can be used as a segmentation point and as a starting point of the next track segment, thereby ensuring the accuracy of track segment division and further improving the accuracy of determining the travel mode of the user.
Further, the track data of the user further comprises a step number corresponding to each track point. Specifically, the number of steps corresponding to the track point may refer to the number of steps walked by the user in a time from a preset start time to the track point, for example, the preset start time is zero daily; or the number of steps taken by the user from the time of the last track point to the time of the current track point.
The number of steps may be obtained using a sensor in a mobile terminal carried by the user.
After determining the plurality of segment points, if the differences between the step numbers of the segment points in the adjacent track segments are less than the preset average step number, the adjacent track segments are of the same travel type, and the adjacent track segments can be combined into one track segment. Wherein the preset average number of steps may be preset, for example 1600 steps/kilometer (Km).
In a specific embodiment of the present invention, the track points are acquired at preset time intervals. Referring to fig. 4, step S103 shown in fig. 1 may include the following steps:
step S301: if the average speed between two adjacent segmentation points is lower than a first preset value, determining that the travel type of the track segment corresponding to the two adjacent segmentation points is walking;
step S302: and if the average speed between two adjacent segmentation points is larger than the first preset value and smaller than a second preset value, determining that the travel type of the track segment is running, wherein the second preset value is larger than the first preset value.
In practice, the instantaneous speed of the user while walking is low and the average speed throughout the walking trip is low. If the average speed between two adjacent segmentation points is lower than a first preset value, determining that the travel type of the track section corresponding to the two adjacent segmentation points is walking, namely the travel mode of the user in the track section is walking.
The instantaneous speed of the user while running is higher and greater than the instantaneous speed of the user while walking, the average speed over the running stroke having an upper limit, a second preset value. If the average speed between two adjacent segment points is larger than the first preset value and smaller than the second preset value, determining that the travel type of the track segment is running, namely the travel mode of the user in the track segment is running.
It may be understood that the first preset value may be selected from 4 kilometers/hour (km/h) -8km/h, and the second preset value may be selected from 8km/h-12km/h, or may be adaptively configured according to a specific application scenario, which is not limited in the embodiment of the present invention. Preferably, the first preset value is 6km/h and the second preset value is 10km/h.
In another embodiment of the present invention, the track points are acquired at preset time intervals. Referring to fig. 5, step S103 shown in fig. 1 may include the following steps:
step S303: if the average speed between two adjacent segmentation points reaches a first preset value, judging whether track segments corresponding to the two adjacent segmentation points are coincident with a public transportation route or not;
step S304: and if the track section coincides with the public transportation route, determining the travel type of the track section as public transportation.
In a specific embodiment, since the public transportation means needs to stop at a plurality of stations while traveling, the average speed of the user is lower throughout the journey but higher than the average speed of the user while walking while riding the public transportation. In addition, public vehicles have a fixed travel route. Thus, when determining that the journey type is public transportation, two conditions of average speed between two adjacent segmentation points and whether the track segment coincides with the public transportation route need to be considered. And determining the travel type of the track section as public transportation under the condition that both conditions are met.
Further, the step S304 may specifically include the following steps: if the track section coincides with the subway line and the average speed reaches a third preset value, determining that the travel type of the track section is subway travel, wherein the third preset value is larger than the first preset value; if the track section coincides with the bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section is smaller than a first preset threshold value, determining that the travel type of the track section is bus travel, otherwise, determining that the travel type of the track section is driving travel, wherein the fourth preset value is larger than the third preset value; and if the track section coincides with the train route, determining that the travel type of the track section is train travel.
In specific implementation, the average running speed of the subway is higher than the average running speed of the user when running, so that when the track section coincides with the subway line and the average running speed reaches a third preset value, the travel type of the track section is determined to be subway travel.
The bus has large instantaneous speed difference when running, for example, the instantaneous speed is smaller when starting, and the highest speed can reach 100km/h when running. When the travel type is determined to be the intersection, on the basis that the average speed reaches the first preset value, the time when the average speed reaches the fourth preset value in the track section, namely the ratio of the time when the average speed reaches the fourth preset value to the total duration of the track section, needs to be considered. In particular, the first preset threshold may be selected from 8% -12%, preferably the first preset threshold may be 10%.
The user does not need to stop the station when driving, the instant speed in the whole journey is faster and longer, so on the basis that the average speed reaches a first preset value, when the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section reaches a first preset threshold value, the journey type can be determined to be driving journey.
Compared with other public transport routes, the train route is special, the train track is specially designed for a train, and other transport means cannot be used. Therefore, when the journey type is determined to be train departure, on the basis that the average speed reaches the first preset value, whether the track section coincides with the train route or not is only required to be compared.
In particular, the third preset value may be selected from 28km/h to 32km/h, preferably said third preset value is 30km/h. The fourth preset value may be selected from 38km/h to 42km/h, preferably said fourth preset value is 40km/h.
If the average speed between two adjacent segment points reaches a second preset value, and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold value, determining the travel type of the track segment to be riding, otherwise, determining the travel type of the track segment to be driving, wherein the fifth preset value is larger than the second preset value.
Further, the trajectory segment may be determined to coincide with a public transportation route by: determining a start point and an end point of the track segment, and a public transportation route between the start point and the end point; acquiring a site position in the public transportation route; determining track points and the number of the track points, wherein the distance between the track points and the site position is smaller than a second preset threshold value, in the track section, and calculating the ratio of the number to the total number of the track points included in the track section; and if the ratio reaches a second preset ratio, determining that the track section coincides with the public transportation route.
In particular, the public transportation route includes a plurality of site locations, and the track segment includes a plurality of track points. If the distance between the track point and the site position is short, that is, smaller than the second preset threshold value, it may be determined that the track point coincides with the site position. If more track points exist in the track segment and the positions of the stations coincide, the track segment is considered to coincide with the public transportation route.
According to the embodiment, the track data is split into the track points, the public transportation route is split into the station positions, and the station positions are compared respectively, so that the accuracy of judging whether the track data and the station positions are overlapped or not can be improved, and the accuracy of judging the travel mode of a user is improved.
The second preset threshold may have a value ranging from 30 to 70 meters (m), preferably the second preset threshold may be 50m. The value of the second preset ratio may be in the range of 80% -95%, and preferably the second preset ratio may be 90%.
In another embodiment of the present invention, the track points are acquired at preset time intervals. Referring to fig. 6, step S103 shown in fig. 1 may include the following steps:
step S305: if the average speed between two adjacent segment points reaches a second preset value, and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold value, determining the travel type of the track segment to be riding, otherwise, determining the travel type of the track segment to be driving, wherein the fifth preset value is larger than the second preset value.
Specifically, the average speed of the user during riding is higher than the average speed of the user during walking, and the difference of the instantaneous speeds of the user during riding is large, for example, the instantaneous speed during starting is 4km/h, and the highest speed can reach 80km/h, so that when the travel type is determined to be riding, the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track section also needs to be considered. In particular, the second preset threshold may be selected from 8% -12%, preferably the second preset threshold may be 10%.
And if the average speed between two adjacent segmentation points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment reaches a second preset threshold value, determining that the travel type of the track segment is driving travel.
In particular, the third preset value may be selected from 23km/h to 27km/h, preferably said third preset value is 25km/h.
In a specific application scenario of the present invention, please refer to fig. 7, and the steps shown in fig. 7 are performed after step S102 shown in fig. 1. That is, step S401 is performed after step S101 and step S102.
The numerical values used in the present embodiment are only exemplary and do not limit the embodiments of the present invention.
In step S401, it is determined whether the average speed between two adjacent segment points is less than 6km/h, if so, step S402 is entered, otherwise step S403 and/or step S405 is entered.
In step S402, it is determined that the travel type of the track segment corresponding to the two adjacent segmentation points is walking.
In step S403, it is determined whether the average speed between two adjacent segment points is less than 10km/h, if so, step S404 is entered, otherwise step S414 is entered.
In step S404, it is determined that the travel type of the track segment corresponding to the two adjacent segmentation points is running.
In step S405, it is determined whether the track segment coincides with the subway line, if so, step S406 is entered, otherwise step S408 is entered.
In step S406, it is judged whether or not the average speed is 30km/h or more, and if so, the process proceeds to step S407. In step S407, it is determined that the travel type of the track section is subway travel.
In step S408, it is determined whether the track segment coincides with the bus route, if so, step S409 is entered, otherwise step S412 is entered.
In step S409, it is determined whether the ratio of the time when the average speed reaches 40km/h to the total length of the track segment is less than 10%, if so, step S410 is entered, otherwise step S411 is entered.
In step S410, it is determined that the travel type of the track segment is bus travel. In step S411, the travel type of the track segment is determined as driving travel.
In step S412, it is determined whether the track segment coincides with the train route, if so, step S413 is entered, otherwise step S414 is entered. In step S413, the trip type of the track section is determined as train trip.
In step S414, it is determined whether the average speed is equal to or greater than 10km/h and the ratio of the time when the average speed reaches 25km/h to the total length of the track segment is less than 10%, if yes, step S415 is entered, otherwise step S411 is entered. In step S415, the travel type of the track segment is determined to be riding.
Therefore, at least one travel type corresponding to the track section of the user can be determined, so that the travel mode of the user in the time of the track section is determined, and references are provided for the user or other managers.
Referring to fig. 8, the trip type determining device 50 may include a trajectory data acquisition module 501, a segmentation point determining module 502, and a trip type determining module 503.
The track data obtaining module 501 is adapted to obtain track data of a user, where the track data includes a plurality of track points, and each track point has coordinates, time and instantaneous speed; the segment point determining module 502 is adapted to determine a plurality of segment points according to a time interval between adjacent track points or a difference of instantaneous speeds of the adjacent track points, wherein the travel types of the track points between every two segment points are the same; the travel type determination module 503 is adapted to determine the travel type of each track segment based at least on the average speed between the plurality of segment points, the track segment being a track formed by track points between two adjacent segment points.
According to the embodiment of the invention, the track data of the user is analyzed, namely, the time interval between adjacent track points or the difference of the instantaneous speeds of the adjacent track points is obtained, so that the segmentation points for distinguishing different stroke types can be determined; the travel type of the track section can be determined at least through the average speed among the segmentation points, and the travel type can represent the travel mode of the user, so that references can be provided for the follow-up travel and other behaviors of the user.
In an embodiment of the present invention, referring to fig. 9, the track points are acquired according to a preset time interval, and the segmentation point determining module 502 may include a first segmentation point determining unit 5021 adapted to determine that a subsequent track point in the adjacent track points is a segmentation point when the time interval between the adjacent track points is greater than the preset time interval.
In another embodiment of the present invention, referring to fig. 9, the segmentation point determination module 502 may include: a speed difference calculating unit 5022 adapted to calculate a difference between an instantaneous speed of a subsequent one of the adjacent track points and an instantaneous speed of a previous one of the adjacent track points, and calculate a ratio of the difference to the instantaneous speed of the previous track point; the second segmentation point determining unit 5023 is adapted to determine the subsequent track point as a segmentation point when the ratio reaches a first preset ratio.
In a preferred embodiment of the present invention, the trip type determining device 50 shown in fig. 8 may further include a distance statistics module (not shown) adapted to count the distance of each track segment; a blockchain storage module (not shown) adapted to record distances and travel types for each track segment using blockchain technology.
In one embodiment of the present invention, referring to fig. 10, the stroke type determining module 503 shown in fig. 8 may include: the walking determination unit 5031 is adapted to determine that the travel type of the track segment corresponding to the two adjacent segmentation points is walking when the average speed between the two adjacent segmentation points is lower than a first preset value; the running determination unit 5032 is adapted to determine that the travel type of the track segment is running when the average speed between two adjacent segmentation points is larger than the first preset value and smaller than a second preset value, and the second preset value is larger than the first preset value.
In one embodiment of the present invention, referring to fig. 10, the stroke type determining module 503 shown in fig. 8 may include: the route coincidence judging unit 5033 is adapted to judge whether the track segments corresponding to the two adjacent segment points coincide with the public transportation route when the average speed between the two adjacent segment points reaches a first preset value; the public transportation determination unit 5034 is adapted to determine that the travel type of the track segment is public transportation when the track segment coincides with a public transportation route.
Further, the public transportation determining unit 5034 may include a subway determining subunit adapted to determine that the travel type of the track segment is subway travel when the track segment coincides with a subway line and the average speed reaches a third preset value, where the third preset value is greater than the first preset value; the bus determining subunit is suitable for determining that the travel type of the track section is bus travel when the track section coincides with a bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section is smaller than a first preset threshold value; the driving determining subunit is suitable for determining that the travel type of the track section is driving travel when the track section coincides with a bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section reaches a first preset threshold value, wherein the fourth preset value is larger than the third preset value; and the train determining subunit is suitable for determining that the travel type of the track section is train travel when the track section is coincident with the train route.
The route coincidence determination unit determines that the track segment coincides with a public transportation route by: determining a start point and an end point of the track segment, and a public transportation route between the start point and the end point; acquiring a site position in the public transportation route; determining track points and the number of the track points, wherein the distance between the track points and the site position is smaller than a second preset threshold value, in the track section, and calculating the ratio of the number to the total number of the track points included in the track section; and if the ratio reaches a second preset ratio, determining that the track section coincides with the public transportation route.
In still another embodiment of the present invention, referring to fig. 10, the stroke type determining module 503 shown in fig. 8 may include:
the riding determining unit 5035 is adapted to determine that the travel type of the track segment is riding when the average speed between two adjacent segment points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold;
the driving determining unit 5036 is adapted to determine that the travel type of the track segment is driving travel when the average speed between two adjacent segment points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold, wherein the fifth preset value is larger than the second preset value.
For more details on the working principle and the working manner of the travel type determining device 50, reference may be made to the related descriptions in fig. 1 to 7, and the description thereof will not be repeated here.
The embodiment of the invention also discloses a storage medium, on which computer instructions are stored, which when run can execute the steps of the travel type determining method shown in fig. 1 to 7. The storage medium may include ROM, RAM, magnetic or optical disks, and the like. The storage medium may also include a non-volatile memory (non-volatile) or a non-transitory memory (non-transitory) or the like.
The embodiment of the invention also discloses a terminal, which can comprise a memory and a processor, wherein the memory stores computer instructions capable of running on the processor. The processor, when executing the computer instructions, may perform the steps of the trip type determination method shown in fig. 1-7. The terminal comprises, but is not limited to, a mobile phone, a computer, a tablet personal computer and other terminal equipment.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the invention, and the scope of the invention should be assessed accordingly to that of the appended claims.
Claims (16)
1. A travel type determining method, comprising:
acquiring track data of a user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed;
determining a plurality of segment points according to the difference of the instantaneous speeds of the adjacent track points, wherein the travel types of the track points between every two segment points are the same;
determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment refers to a track formed by track points between two adjacent segment points;
Wherein the determining a plurality of segment points according to the difference of the instantaneous speeds of the adjacent track points comprises: calculating a difference value between the instantaneous speed of a subsequent track point in adjacent track points and the instantaneous speed of a previous track point in the adjacent track points, and calculating a ratio of the difference value to the instantaneous speed of the previous track point;
and if the ratio reaches a first preset ratio, determining the latter track point as a segmentation point.
2. The stroke type determination method according to claim 1, further comprising:
counting the distance of each track segment;
and recording the distance and the travel type of each track segment by adopting a block chain technology.
3. The trip type determination method of claim 1, wherein said determining the trip type of each track segment based at least on the average speed between the plurality of segment points comprises:
if the average speed between two adjacent segmentation points is lower than a first preset value, determining that the travel type of the track segment corresponding to the two adjacent segmentation points is walking;
and if the average speed between two adjacent segmentation points is larger than the first preset value and smaller than a second preset value, determining that the travel type of the track segment is running, wherein the second preset value is larger than the first preset value.
4. The trip type determination method of claim 1, wherein said determining the trip type of each track segment based at least on the average speed between the plurality of segment points comprises:
if the average speed between two adjacent segmentation points reaches a first preset value, judging whether track segments corresponding to the two adjacent segmentation points are coincident with a public transportation route or not;
and if the track section coincides with the public transportation route, determining the travel type of the track section as public transportation.
5. The travel type determining method according to claim 4, wherein the determining that the travel type of the track segment is public transportation includes:
if the track section coincides with the subway line and the average speed reaches a third preset value, determining that the travel type of the track section is subway travel, wherein the third preset value is larger than the first preset value;
if the track section coincides with the bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section is smaller than a first preset threshold value, determining that the travel type of the track section is bus travel, otherwise, determining that the travel type of the track section is driving travel, wherein the fourth preset value is larger than the third preset value;
And if the track section coincides with the train route, determining that the travel type of the track section is train travel.
6. The travel type determining method according to claim 4, wherein the trajectory section is judged to coincide with a public transportation route by:
determining a start point and an end point of the track segment, and a public transportation route between the start point and the end point;
acquiring a site position in the public transportation route;
determining track points and the number of the track points, wherein the distance between the track points and the site position is smaller than a second preset threshold value, in the track section, and calculating the ratio of the number to the total number of the track points included in the track section;
and if the ratio reaches a second preset ratio, determining that the track section coincides with the public transportation route.
7. The trip type determination method of claim 1, wherein said determining the trip type of each track segment based at least on the average speed between the plurality of segment points comprises:
if the average speed between two adjacent segment points reaches a second preset value, and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold value, determining the travel type of the track segment to be riding, otherwise, determining the travel type of the track segment to be driving, wherein the fifth preset value is larger than the second preset value.
8. A stroke type determining device, characterized by comprising:
the track data acquisition module is suitable for acquiring track data of a user, wherein the track data comprises a plurality of track points, and each track point is provided with coordinates, time and instantaneous speed;
the segment point determining module is suitable for determining a plurality of segment points according to the difference of the instantaneous speeds of the adjacent track points, and the travel types of the track points between every two segment points are the same;
the travel type determining module is suitable for determining the travel type of each track segment at least according to the average speed among the plurality of segment points, wherein the track segment is a track formed by track points between two adjacent segment points;
wherein the segmentation point determination module comprises:
a speed difference calculating unit adapted to calculate a difference between an instantaneous speed of a subsequent one of the adjacent track points and an instantaneous speed of a previous one of the adjacent track points, and calculate a ratio of the difference to the instantaneous speed of the previous track point;
and the second segmentation point determining unit is suitable for determining the subsequent track point as a segmentation point when the ratio reaches a first preset ratio.
9. The stroke type determination device as recited in claim 8, further comprising:
The distance statistics module is suitable for counting the distance of each track segment;
and the block chain storage module is suitable for recording the distance and the travel type of each track segment by adopting a block chain technology.
10. The trip type determination device of claim 8, wherein the trip type determination module comprises:
the walking determining unit is suitable for determining that the travel type of the track section corresponding to the two adjacent segmentation points is walking when the average speed between the two adjacent segmentation points is lower than a first preset value;
the running determining unit is suitable for determining that the travel type of the track segment is running when the average speed between two adjacent segmentation points is larger than the first preset value and smaller than a second preset value, and the second preset value is larger than the first preset value.
11. The trip type determination device of claim 8, wherein the trip type determination module comprises:
the route coincidence judging unit is suitable for judging whether the track segments corresponding to the two adjacent segmentation points coincide with the public transportation route or not when the average speed between the two adjacent segmentation points reaches a first preset value; and the public transportation determining unit is suitable for determining that the travel type of the track section is public transportation when the track section is coincident with the public transportation route.
12. The travel type determining apparatus according to claim 11, wherein the public transportation determining unit includes:
the subway determining subunit is suitable for determining that the travel type of the track section is subway travel when the track section coincides with a subway route and the average speed reaches a third preset value, and the third preset value is larger than the first preset value;
the bus determining subunit is suitable for determining that the travel type of the track section is bus travel when the track section coincides with a bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section is smaller than a first preset threshold value;
the driving determining subunit is suitable for determining that the travel type of the track section is driving travel when the track section coincides with a bus route and the ratio of the time when the average speed reaches a fourth preset value to the total duration of the track section reaches a first preset threshold value, wherein the fourth preset value is larger than the third preset value;
and the train determining subunit is suitable for determining that the travel type of the track section is train travel when the track section is coincident with the train route.
13. The travel type determining apparatus according to claim 11, wherein the route coincidence determination unit determines that the track segment coincides with a public transportation route by:
determining a start point and an end point of the track segment, and a public transportation route between the start point and the end point;
acquiring a site position in the public transportation route;
determining track points and the number of the track points, wherein the distance between the track points and the site position is smaller than a second preset threshold value, in the track section, and calculating the ratio of the number to the total number of the track points included in the track section;
and if the ratio reaches a second preset ratio, determining that the track section coincides with the public transportation route.
14. The trip type determination device of claim 8, wherein the trip type determination module comprises:
the riding determining unit is suitable for determining that the travel type of the track section is riding when the average speed between two adjacent segmentation points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track section is smaller than a second preset threshold value;
and the driving determining unit is suitable for determining that the travel type of the track segment is driving travel when the average speed between two adjacent segmentation points reaches a second preset value and the ratio of the time when the average speed reaches a fifth preset value to the total duration of the track segment is smaller than a second preset threshold value, wherein the fifth preset value is larger than the second preset value.
15. A storage medium having stored thereon computer instructions which, when run, perform the steps of the trip type determining method of any one of claims 1 to 7.
16. A terminal comprising a memory and a processor, the memory having stored thereon computer instructions executable on the processor, wherein the processor, when executing the computer instructions, performs the steps of the trip type determination method of any one of claims 1 to 7.
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|---|---|---|---|---|
| CN113539050B (en) * | 2020-04-20 | 2022-09-23 | 华为技术有限公司 | Data processing method, device and equipment |
| CN112053566B (en) * | 2020-08-24 | 2022-01-11 | 青岛海信网络科技股份有限公司 | Electronic equipment and travel type identification method of vehicle |
| CN112268562B (en) * | 2020-10-23 | 2022-05-03 | 重庆越致科技有限公司 | Fusion data processing system based on automatic pedestrian trajectory navigation |
| CN113160273A (en) * | 2021-03-25 | 2021-07-23 | 常州工学院 | Intelligent monitoring video segmentation method based on multi-target tracking |
| CN113256830B (en) * | 2021-05-07 | 2022-02-22 | 广州红海云计算股份有限公司 | Intelligent real-time attendance checking method and device of attendance checking management device |
| CN114708729A (en) * | 2022-03-31 | 2022-07-05 | 北京交通发展研究院 | Method and device for analyzing ground bus shortcut index and electronic equipment |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102607553A (en) * | 2012-03-06 | 2012-07-25 | 北京建筑工程学院 | Travel track data-based stroke identification method |
| CN102799897A (en) * | 2012-07-02 | 2012-11-28 | 杨飞 | Computer recognition method of GPS (Global Positioning System) positioning-based transportation mode combined travelling |
| CN104318767A (en) * | 2014-10-22 | 2015-01-28 | 北京建筑大学 | Road condition information generating method based on bus global position system (GPS) tracking data |
| CN104504099A (en) * | 2014-12-29 | 2015-04-08 | 北京交通大学 | Position-trajectory-based travel state splitting method |
| CN104596507A (en) * | 2015-02-09 | 2015-05-06 | 成都小步创想畅联科技有限公司 | Method for determining travel track of mobile terminal |
| CN105183893A (en) * | 2015-09-29 | 2015-12-23 | 百度在线网络技术（北京）有限公司 | Positioning track classification method and device |
| CN106323296A (en) * | 2015-06-24 | 2017-01-11 | 骑记(厦门)科技有限公司 | Method and apparatus for recognizing travel model |
| CN106446208A (en) * | 2016-09-30 | 2017-02-22 | 东南大学 | Method for identifying traveling mode of smart phone by considering integrating degree of road network |
| CN107330469A (en) * | 2017-07-04 | 2017-11-07 | 上海交通大学 | A kind of trip mode recognition methods based on GPS track data |
| CN107330088A (en) * | 2017-07-04 | 2017-11-07 | 上海交通大学 | A kind of trip section recognition methods based on GPS track data |
-
2018
- 2018-08-14 CN CN201810923949.7A patent/CN110826758B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102607553A (en) * | 2012-03-06 | 2012-07-25 | 北京建筑工程学院 | Travel track data-based stroke identification method |
| CN102799897A (en) * | 2012-07-02 | 2012-11-28 | 杨飞 | Computer recognition method of GPS (Global Positioning System) positioning-based transportation mode combined travelling |
| CN104318767A (en) * | 2014-10-22 | 2015-01-28 | 北京建筑大学 | Road condition information generating method based on bus global position system (GPS) tracking data |
| CN104504099A (en) * | 2014-12-29 | 2015-04-08 | 北京交通大学 | Position-trajectory-based travel state splitting method |
| CN104596507A (en) * | 2015-02-09 | 2015-05-06 | 成都小步创想畅联科技有限公司 | Method for determining travel track of mobile terminal |
| CN106323296A (en) * | 2015-06-24 | 2017-01-11 | 骑记(厦门)科技有限公司 | Method and apparatus for recognizing travel model |
| CN105183893A (en) * | 2015-09-29 | 2015-12-23 | 百度在线网络技术（北京）有限公司 | Positioning track classification method and device |
| CN106446208A (en) * | 2016-09-30 | 2017-02-22 | 东南大学 | Method for identifying traveling mode of smart phone by considering integrating degree of road network |
| CN107330469A (en) * | 2017-07-04 | 2017-11-07 | 上海交通大学 | A kind of trip mode recognition methods based on GPS track data |
| CN107330088A (en) * | 2017-07-04 | 2017-11-07 | 上海交通大学 | A kind of trip section recognition methods based on GPS track data |
Non-Patent Citations (1)
| Title |
|---|
| 基于改进随机森林算法的出行方式识别系统研究与设计;易立;;信息通信(第05期);51-54 * |
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