CN112085268A - Method, device, device and readable storage medium for measuring and calculating resident travel information - Google Patents

Abstract

The embodiment of the application discloses a method, a device, equipment and a readable storage medium for measuring and calculating resident travel information, and relates to the big data technology, in particular to the technical field of intelligent transportation and electronic maps. The specific implementation scheme is as follows: acquiring a plurality of positioning data generated by the trip accompanying equipment; determining a staying area of a resident to which the travel accompanying equipment belongs in a traveling process according to the space-time information of the positioning data and whether the positioning data meet the staying requirement; and calculating the travel information of the residents based on the staying area. The method and the device for measuring the travel information of the residents can improve the measuring and calculating precision of the travel information of the residents.

Description

Method, device, device and readable storage medium for measuring and calculating resident travel information

technical field

The present application relates to the technical field of intelligent transportation and electronic maps, and in particular, to a method, device, device and readable storage medium for measuring and calculating resident travel information.

Background technique

In recent years, the use of big data to quantitatively explore the laws of residents' activities has become a research hotspot, especially in the case of major events (such as the outbreak of the new coronavirus in 2020), mastering the laws of residents' activities is of great significance for responding to emergencies. and effect.

At present, residents' travel data are generally obtained through traffic surveys such as bus and subway card swiping, and highway entrances and exits. However, the method of traffic survey has the defects of small sample coverage, biased distribution and non-sustainability, resulting in low accuracy of the measurement of residents' travel situation.

SUMMARY OF THE INVENTION

Embodiments of the present application provide a method, device, device, and readable storage medium for measuring and calculating resident travel information.

In a first aspect, the embodiments of the present application provide a method for measuring and calculating resident travel information, including:

Obtain multiple positioning data generated by travel companion devices;

According to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement, determine the stay area of the resident to which the travel companion device belongs during the travel process;

The resident travel information is calculated based on the staying area.

In a second aspect, the embodiments of the present application also provide a device for measuring and calculating resident travel information, including:

The acquisition module is used to acquire multiple positioning data generated by the travel companion device;

A determination module, configured to determine the stay area of the resident to which the travel accompanying device belongs during the travel process according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement;

an estimation module, configured to measure the travel information of the residents based on the stay area.

In a third aspect, an embodiment of the present application provides an electronic device, including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute a resident travel provided by any of the embodiments Information measurement method.

In a fourth aspect, an embodiment of the present application provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to make the computer execute the measurement and calculation of resident travel information provided by any of the embodiments method.

The embodiments of the present application can improve the measurement accuracy of resident travel information.

It should be understood that what is described in this section is not intended to identify key or critical features of embodiments of the disclosure, nor is it intended to limit the scope of the disclosure. Other features of the present disclosure will become readily understood from the following description.

Description of drawings

The accompanying drawings are used for better understanding of the present solution, and do not constitute a limitation to the present application. in:

1 is a flowchart of a first method for measuring and calculating resident travel information in an embodiment of the present application;

2a is a flowchart of a second method for measuring and calculating resident travel information in the embodiment of the present application;

2b is a schematic diagram of multiple regions obtained by clustering of trajectory points in multiple positioning data in an embodiment of the present application;

3 is a flowchart of a third method for measuring and calculating resident travel information in an embodiment of the present application;

4a is a flowchart of a fourth method for measuring and calculating resident travel information in the embodiment of the present application;

4b is a schematic diagram of an area formed by a plurality of trajectory points and a travel segment between the stay areas in the embodiment of the present application;

5 is a structural diagram of a device for measuring and calculating resident travel information in an embodiment of the present application;

FIG. 6 is a schematic structural diagram of an electronic device in an embodiment of the present application.

Detailed ways

Exemplary embodiments of the present application are described below with reference to the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted from the following description for clarity and conciseness.

According to an embodiment of the present application, FIG. 1 is a flowchart of a first method for measuring and calculating resident travel information in the embodiment of the present application. The embodiment of the present application is applicable to the case of calculating the travel information of residents based on the positioning data of the device. The method is implemented by a device for measuring and calculating the travel information of residents, the device is implemented by software and/or hardware, and is specifically configured in an electronic device with a certain data computing capability.

As shown in Figure 1, the calculation method of resident travel information includes:

S110. Acquire a plurality of positioning data generated by the travel companion device.

In this embodiment, the travel accompanying device is a device that accompanies the resident when the resident travels, such as a mobile phone, a smart bracelet, and a vehicle. The travel companion device is equipped with an electronic map and has a positioning function, and can obtain multiple positioning data generated by the device according to a set frequency when the positioning function is turned on. Exemplarily, the positioning data includes time information, spatial information (such as location latitude and longitude) of the track point, and other positioning attributes. Further, the positioning data also includes the unique identifier of the resident to which the travel companion device belongs, such as the resident's nickname.

Optionally, the number of travel companion devices is multiple, and each travel companion device generates a plurality of positioning data.

S120: Determine the stay area of the resident to which the travel companion device belongs during the travel process according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement.

The spatiotemporal information includes time information and spatial information. The spatiotemporal information of the positioning data represents the travel trajectory and time of the residents. If the time interval between some trajectory points is long and the distance is short, it reflects that the residents stay between the trajectory points. Then, the area where these trajectory points are located can be regarded as a stop area during the travel process, which is called a stop area.

Because the acquisition of positioning data depends on whether the fixed energy function is turned on or not, sometimes there is no continuity and density in time, which makes it more difficult to capture the user's staying behavior. This shortcoming,

The positioning data meeting the stay requirement refers to the fact that the trajectory points in the positioning data can meet the needs of the residents to stay here, for example, the positioning data collected indoors. It can be seen that the positioning data that meets the stay requirement can reflect that the residents stay at the track point, and the area where the track point is located can be used as the stay area during the travel process, which is called the stay area.

S130. Measure the travel information of the residents based on the stay area.

Optionally, the number of stay areas is at least one, and the stay area indicates that residents travel to this area instead of just passing through this area. Based on this, at least one stay area reflects the travel situation of residents, so as to measure the information related to residents' travel. , that is, the travel information of residents. Optionally, the resident travel information includes, but is not limited to, the travel route and the resident travel intensity.

In this embodiment, based on the fact that most residents will carry travel companion devices, the sample coverage of multiple positioning data generated by the devices is large and evenly distributed, and since the positioning data is generated when the positioning function of the travel companion device is turned on, it has a long time. and spatial continuity. Based on this, multiple positioning data can accurately reflect when and where residents are. In this embodiment, according to the spatiotemporal information of multiple positioning data and whether the multiple positioning data meet the stay requirement, these two factors complement each other, and comprehensively determine the stopping area of the residents to which the travel companion device belongs during the travel process, thereby further improving the travel information. of accuracy.

According to an embodiment of the present application, FIG. 2a is a flowchart of a second method for measuring and calculating resident travel information in the embodiment of the present application. The embodiment of the present application determines a method for determining a stay area based on the technical solutions of the above-mentioned embodiments. optimize.

The calculation method of resident travel information shown in Figure 2a specifically includes the following operations:

S210: Acquire a plurality of positioning data generated by the travel companion device.

S220. Preliminarily determine the staying area and the moving area of the resident during the travel process according to the spatiotemporal information of the multiple positioning data.

Compared with the staying area, the moving area is the area that residents only pass by without staying during the travel process.

Optionally, the first step is to cluster the multiple positioning data according to the spatial information of the multiple positioning data to obtain multiple regions.

Among them, the multiple positioning data that need to be clustered are generated by a travel companion device within a set time period, that is, the multiple positioning data reflect the travel trajectory of a resident within the set time period. The set period can be one day or one week, which is the measurement cycle of resident travel information. First, a plurality of positioning data are sorted in chronological order to obtain a time series of positioning data. A clustering algorithm based on spatial density is used to cluster multiple positioning data to obtain multiple clusters, and the positioning data (specifically, the trajectory points in the positioning data) included in each cluster constitute the area through which residents travel. Fig. 2b is a schematic diagram of multiple regions obtained by clustering of track points in multiple positioning data in an embodiment of the present application. Fig. 2b shows track points in 14 positioning data, which are represented by numbers 1-14. is 6 regions, and each region includes at least one trajectory point. Some of these areas are stay areas and some are moving areas.

Step 2: Calculate the stay duration and activity range between positioning data in each area, and determine the area where the stay duration exceeds the duration threshold and the activity range does not exceed the range threshold as the stay area, otherwise, the stay duration does not exceed the duration threshold. , or the area where the active range exceeds the range threshold is determined as the active area. Among them, obtain at least one group of positioning data adjacent in time in each area, and calculate the difference between the time information of each group of positioning data as the stay time of each group of positioning data, and superimpose the stay time of at least one group of positioning data to obtain Duration of dwell time between positioning data within the area. Calculate the maximum value of the difference between the spatial information of any two positioning data in each area as the activity range. Duration thresholds and range thresholds can be set according to the characteristics of residents' stay and movement.

S230: Screen target positioning data that meets the stay requirement from multiple positioning data, and re-determine the initially determined moving area as the stay area.

Because the positioning data sometimes does not have continuity and density in time, some areas are initially identified as moving areas, but they are actually areas where residents stay. Based on this, the positioning data that meets the stay requirement is screened from multiple positioning data, which is called target positioning data. The moving area where the target positioning data is located is filtered and re-determined as the staying area. It can be seen that if the target positioning data in an area meets the stay requirement, even if the stay duration between the positioning data in the area does not exceed the duration threshold, or the activity range exceeds the range threshold, it can also be used as a stay area for the user to stay.

Optionally, when screening the target positioning data in S230, at least one of the following optional implementations is included.

The first optional implementation manner: from a plurality of positioning data, the target positioning data located in the set resident activity scene is screened.

The resident activity scene is set as a scene that can provide resident activity. Specifically, from a plurality of positioning data, the target positioning data corresponding to the access or detection of the private network by the travel companion device is screened; and/or, from the plurality of positioning data, the target positioning corresponding to the area covered with the private network is screened. data. By filtering the target positioning data located in the set resident activity scene, the target positioning data that meets the stay needs can be accurately identified.

Access to or detection of a private network can be access to or detection of a private mobile hotspot (wifi), and the area covered by a private hotspot is generally indoors, which can provide resident activity scenarios, and then filter out the accompanying devices to access or detect a private network. corresponding target positioning data. In some cases, the network detection or connection function of the travel companion device is not enabled, and it is difficult to determine that the travel companion device is connected to or detects the private network. In the data, the target positioning data corresponding to the area covered with the private network is filtered.

The second optional implementation manner: from a plurality of positioning data, the target positioning data located at the permanent residence of the residents is screened.

In daily life, most of the departure or destination of residents' trips are frequently visited places, that is, permanent residences. If the permanent location of the residents can be obtained, it will also help to identify the staying area.

Specifically, using the positioning data of the residents in the historical period as input, the areas visited by the residents in the historical period are obtained through a clustering algorithm based on spatial density. Calculate the sum of the access times or the sum of access frequencies of each positioning data in each area. The area where the number of visits or the frequency of visits exceeds the set threshold is selected as the resident point of the user. If the resident locates at the resident point, it means that the resident stays and moves here, and the target positioning data located at the resident point of the resident is filtered. In this embodiment, the effects of temporal sparsity and discontinuity can also be alleviated by using a resident point.

S240. Measure resident travel information based on the stay area.

In this embodiment, if the target positioning data in an area meets the stay requirement, even if the area is identified as a moving area, it can be used as a stay area for residents to stay, improving the coverage and accuracy of the stay area identification.

According to an embodiment of the present application, FIG. 3 is a flowchart of a third method for measuring and calculating resident travel information in the embodiment of the present application. The embodiment of the present application determines a method for determining a stay area based on the technical solutions of the above embodiments. optimize.

As shown in Figure 3, the calculation method of resident travel information includes:

S310: Acquire a plurality of positioning data generated by the travel companion device.

S320: Clustering the multiple positioning data according to the spatial information of the multiple positioning data to obtain multiple regions.

For details of this operation, please refer to the description of the above-mentioned embodiment, and details are not repeated here.

S330. Screening target positioning data that meets the stay requirement from multiple positioning data, shortening the duration threshold corresponding to the area where the target positioning data is located, and/or expanding the range threshold corresponding to the area where the target positioning data is located.

When screening the target positioning data that meets the stay requirements, the target positioning data located in the set resident activity scene may be screened from multiple positioning data; and/or, the target located at the resident point of residence may be screened from the multiple positioning data location data. For details, please refer to the records of the foregoing embodiments, which will not be repeated here.

With reference to the above-mentioned embodiment, the area where the stay duration exceeds the duration threshold and the activity range does not exceed the range threshold is determined as the stay area, otherwise, the stay duration does not exceed the duration threshold, or the activity range exceeds the range threshold The area is determined as the activity area. In this embodiment, multiple areas are also identified as staying areas or moving areas, but the duration threshold corresponding to the area where the target positioning data is located is shortened, and/or the range threshold corresponding to the area where the target positioning data is located is expanded.

Specifically, the degree of shortening the duration threshold and the degree of expanding the range threshold can be set independently. For example, shorten the duration threshold by half and expand the range threshold by a factor of 1.5.

S340: Calculate the stay duration and the activity range between the positioning data in each area, and determine the area where the stay duration exceeds the duration threshold and the activity range does not exceed the range threshold as the stay area.

In this embodiment, the shortened duration threshold and the expanded range threshold are used, and the identified area is a stay area or a moving area.

S350. Measure the travel information of the residents based on the staying area.

In this embodiment, by shortening the duration threshold corresponding to the area where the target positioning data is located, and/or expanding the range threshold corresponding to the area where the target positioning data is located, even if the staying time is short or the activity range is large, it is possible to Identify the staying area for residents' stay activities to improve the coverage and accuracy of the identification of the staying area

According to an embodiment of the present application, FIG. 4a is a flowchart of a fourth method for measuring and calculating resident travel information in the embodiment of the present application. This embodiment optimizes the measuring and calculating process of residents' travel information on the basis of the above embodiments.

As shown in Figure 4a, the calculation method of resident travel information includes:

S410: Acquire multiple positioning data generated by the travel companion device.

In this embodiment, the number of travel accompanying devices is multiple, and correspondingly, the number of residents to which the travel accompanying devices belong is multiple.

S420: Determine the stay area of the resident to which the travel companion device belongs during the travel process according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement. Perform S430 and/or S440. FIG. 4a is a schematic diagram of executing S430 and S440.

S430. Measure the travel path of the resident according to the stay area.

For the multiple positioning data generated by the travel companion device of each resident, the stay area is determined respectively, and the travel path of each resident is calculated.

The travel segments representing a trip between two stay areas constitute a travel route. Optionally, sorting the positioning data in all the staying areas in chronological order to obtain the time series of the positioning data; constructing the time series of the staying area according to the time series of the positioning data and the staying area where the positioning data is located; according to the staying area time series to determine the travel paths of residents.

FIG. 4b is a schematic diagram of an area formed by a plurality of trajectory points and a travel segment between the stay areas in the embodiment of the present application. The track point numbers in Fig. 4b represent the time sequence, and the dashed arrows between the track points represent the paths between the track points. As shown in Figure 4b, the positioning data in all the stay areas are sorted in time order to obtain the time series (represented by the track point number): 1, 2, 6, 7, 8, 9, 10, 11, 13, 14 . According to the time series, the stay area where each positioning data is located constitutes the time series of the stay area: the first stay area, the second stay area, the third stay area, the second stay area, and the first stay area. Travel segments 1-4 are formed between two adjacent time series in the time series of the stay area, which are indicated by solid arrows in Fig. 4b. Travel segments 1-4 constitute a travel path.

Further, based on the fact that residents do not stay in two areas that are close to each other in real life, the travel segments that exceed the set length (for example, 500 meters) can be removed from each travel segment, and the remaining travel segments can be used to form a travel path.

The travel route calculation method provided in this embodiment fully considers the time sequence of the positioning data, and further guides the ordering of the stay areas, thereby restoring the real travel route of residents and improving the accuracy of travel route calculation.

S440. Count the number of target residents corresponding to the travel paths covered by the designated area, and calculate the travel information of residents based on the target number of residents.

Optionally, the resident travel information in this embodiment is the resident travel intensity, which is used to represent the strength of the resident travel activity.

In this embodiment, after the travel route of each resident is calculated, the number of target residents corresponding to the travel route covered by the designated area is counted. Among them, the designated area is the area where the travel intensity of residents needs to be measured, such as a city. If the stop areas at both ends of the travel segment are covered by the designated area, it is considered that the travel path where the travel segment is located is covered by the designated area, indicating that residents travel in the designated area and contribute a number of residents. It should be noted that if the designated area covers multiple travel routes of the same resident, it is calculated based on the number of residents.

Optionally, the number of target residents is directly used as the travel intensity of residents, so that the travel intensity of residents is quantitatively described by the number of target residents who travel in the target designated area.

Preferably, the ratio of the number of target residents to the number of active residents is used as the resident travel information. Among them, the number of active residents is the number of residents in the designated area to which the travel companion device from which the positioning data is generated belongs, that is, the number of residents in the designated area where positioning occurs. Optionally, the number of active residents can be the number of residents belonging to the travel companion device from which the positioning data in the designated area is generated during the set period; correspondingly, the number of target residents can also be determined according to the positioning data obtained within the set period, so that it can be Measure the travel information of residents in any area at any time.

Taking the named travel intensity as an example, the resident travel intensity reflects the ratio of the number of residents who travel in the number of active residents in the designated area. The greater the travel intensity, the more residents in the designated area travel. Few residents travel, so as to accurately and quantitatively describe the travel intensity of residents.

This embodiment quantitatively describes the travel information of residents from the perspectives of travel path and travel intensity, and enriches the representation of travel information of residents.

According to an embodiment of the present application, FIG. 5 is a structural diagram of a device for measuring and calculating the travel information of residents in the embodiment of the present application. The embodiment of the present application is applicable to the situation of calculating the travel information of residents based on the positioning data of the device. The device adopts software and/or Or hardware implementation, and is specifically configured in an electronic device with a certain data computing capability.

As shown in FIG. 5 , an apparatus 500 for measuring and calculating resident travel information includes: an acquisition module 501 , a determination module 502 and a calculation module 503 ; wherein,

An acquisition module 501 is used to acquire a plurality of positioning data generated by the travel companion device;

A determination module 502, configured to determine the stay area of the resident to which the travel accompanying device belongs during the travel process according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement;

The calculation module 503 is used to calculate the travel information of the residents based on the stay area.

In this embodiment, based on the fact that most residents will carry travel companion devices, the sample coverage of multiple positioning data generated by the devices is large and evenly distributed, and since the positioning data is generated when the positioning function of the travel companion device is turned on, it has a long time. and spatial continuity. Based on this, multiple positioning data can accurately reflect when and where residents are. In this embodiment, according to the spatiotemporal information of multiple positioning data and whether the multiple positioning data meet the stay requirement, these two factors complement each other, and comprehensively determine the stopping area of the residents to which the travel companion device belongs during the travel process, thereby further improving the travel information. of accuracy.

Optionally, the determining module 502 includes: a first determining unit, configured to preliminarily determine the staying area and the moving area of the resident during the travel process according to the spatiotemporal information of multiple positioning data; The target positioning data that meets the stay requirements are screened from the data, and the initially determined moving area is re-determined as the stay area.

Optionally, the determining module 502 includes: a clustering unit for clustering a plurality of positioning data according to the spatial information of the plurality of positioning data to obtain a plurality of regions; a shortening and expanding unit for obtaining a plurality of regions from the plurality of positioning data; Screening the target positioning data that meets the stay requirements, and shortening the duration threshold corresponding to the area where the target positioning data is located, and/or expanding the range threshold corresponding to the area where the target positioning data is located; a computing unit for calculating the area within each area. The stay duration and activity range between data are located, and the area where the stay duration exceeds the duration threshold and the activity range does not exceed the range threshold is determined as the stay area.

Optionally, the second determination unit is specifically configured to screen the target positioning data located in the set resident activity scene from the plurality of positioning data when screening the target positioning data that meets the stay requirement from the plurality of positioning data; and/or , from multiple positioning data, to filter the target positioning data located at the resident point of residents; when the shortening and expanding unit selects the target positioning data that meets the stay needs from the multiple positioning data, it is specifically used to select the target positioning data from the multiple positioning data. Screening the target positioning data located in the set resident activity scene; and/or, screening the target positioning data located at the resident location from a plurality of positioning data.

Optionally, when screening the target positioning data located in the set resident activity scene from the plurality of positioning data, the second determining unit is specifically configured to screen the travel companion device from the plurality of positioning data to access or detect the private network. and/or, from a plurality of positioning data, screening the target positioning data corresponding to the area covered with the private network; shortening and enlarging the unit from the plurality of positioning data, screening the setting of the resident activity scene When the target positioning data is obtained, it is specifically used to filter the target positioning data corresponding to the access of the travel companion device or the detection of the private network from the multiple positioning data; and/or, from the multiple positioning data, filter the coverage of the private network. The target positioning data corresponding to the area.

Optionally, the measurement and calculation module 503 includes: a path measurement module, used to calculate the travel path of residents according to the staying area; and/or, an information measurement module, used to count the number of target residents corresponding to the travel path covered by the designated area, and Resident travel information is calculated based on the number of target residents.

Optionally, when the information calculation module calculates the travel information of residents based on the number of target residents, it is specifically used to: take the ratio of the number of target residents to the number of active residents as the travel information of the residents; the number of active residents is the travel information generated by the positioning data in the designated area. The number of residents to which the accompanying device belongs.

Optionally, a path estimation module, which is specifically used for: sorting the positioning data in all the stay areas in chronological order to obtain the time series of the positioning data; constructing the stay area according to the time series of the positioning data and the stay area where the positioning data is located. The time series of the area; according to the time series of the stay area, the travel path of the residents is determined.

The above-mentioned resident travel information measuring device can execute the resident travel information measuring method provided in any embodiment of the present application, and has functional modules and beneficial effects corresponding to executing the resident travel information measuring method.

According to the embodiments of the present application, the present application further provides an electronic device and a readable storage medium.

As shown in FIG. 6 , it is a block diagram of an electronic device implementing the method for measuring and calculating the travel information of a resident according to the embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are by way of example only, and are not intended to limit implementations of the application described and/or claimed herein.

As shown in FIG. 6, the electronic device includes: one or more processors 601, a memory 602, and interfaces for connecting various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or otherwise as desired. The processor may process instructions executed within the electronic device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used with multiple memories and multiple memories, if desired. Likewise, multiple electronic devices may be connected, with each terminal providing some of the necessary operations (eg, as a server array, a group of blade servers, or a multiprocessor system). A processor 601 is taken as an example in FIG. 6 .

The memory 602 is the non-transitory computer-readable storage medium provided by the present application. Wherein, the memory stores instructions executable by at least one processor, so that the at least one processor executes the method for measuring and calculating the travel information of residents provided by the present application. The non-transitory computer-readable storage medium of the present application stores computer instructions, and the computer instructions are used to cause the computer to execute the method for measuring and calculating the travel information of residents provided by the present application.

As a non-transitory computer-readable storage medium, the memory 602 can be used to store non-transitory software programs, non-transitory computer-executable programs and modules, such as program instructions/modules ( For example, as shown in FIG. 5, it includes an acquisition module 501, a determination module 502 and an estimation module 503). The processor 601 executes various functional applications and data processing of the server by running the non-transitory software programs, instructions and modules stored in the memory 602 , that is, implementing the method for measuring and calculating the travel information of residents in the above method embodiments.

The memory 602 can include a stored program area and a stored data area, wherein the stored program area can store an operating system and an application program required by at least one function; the stored data area can store the data created by the use of an electronic device that implements a method for measuring and calculating resident travel information. data etc. Additionally, memory 602 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory 602 may optionally include a memory disposed remotely with respect to the processor 601, and the remote memory may be connected to an electronic device for executing the method for calculating the travel information of the resident through a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

The electronic device for executing the method for measuring and calculating the travel information of a resident may further include: an input device 603 and an output device 604 . The processor 601 , the memory 602 , the input device 603 and the output device 604 may be connected by a bus or in other ways, and the connection by a bus is taken as an example in FIG. 6 .

The input device 603 can receive input numerical or character information, and generate key signal input related to user settings and function control of the electronic equipment that executes the calculation method of resident travel information, such as a touch screen, a keypad, a mouse, a trackpad, and a touchpad , pointing stick, one or more mouse buttons, trackball, joystick and other input devices. Output devices 604 may include display devices, auxiliary lighting devices (eg, LEDs), haptic feedback devices (eg, vibration motors), and the like. The display device may include, but is not limited to, a liquid crystal display (LCD), a light emitting diode (LED) display, and a plasma display. In some implementations, the display device may be a touch screen.

Various implementations of the systems and techniques described herein can be implemented in digital electronic circuitry, integrated circuit systems, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpretable on a programmable system including at least one programmable processor that The processor, which may be a special purpose or general-purpose programmable processor, may receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device an output device.

These computational programs (also referred to as programs, software, software applications, or codes) include machine instructions for programmable processors, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages calculation program. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or apparatus for providing machine instructions and/or data to a programmable processor ( For example, magnetic disks, optical disks, memories, programmable logic devices (PLDs), including machine-readable media that receive machine instructions as machine-readable signals. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.

To provide interaction with a user, the systems and techniques described herein may be implemented on a computer having a display device (eg, a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user ); and a keyboard and pointing device (eg, a mouse or trackball) through which a user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (eg, visual feedback, auditory feedback, or tactile feedback); and can be in any form (including acoustic input, voice input, or tactile input) to receive input from the user.

The systems and techniques described herein may be implemented on a computing system that includes back-end components (eg, as a data server), or a computing system that includes middleware components (eg, an application server), or a computing system that includes front-end components (eg, a user's computer having a graphical user interface or web browser through which a user may interact with implementations of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system may be interconnected by any form or medium of digital data communication (eg, a communication network). Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), the Internet, and blockchain networks.

A computer system can include clients and servers. Clients and servers are generally remote from each other and usually interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also known as a cloud computing server or a cloud host. It is a host product in the cloud computing service system to solve the traditional physical host and VPS services, which are difficult to manage and weak in business scalability. defect.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, the steps described in the present application can be performed in parallel, sequentially or in different orders, and as long as the desired results of the technical solutions disclosed in the present application can be achieved, no limitation is imposed herein.

The above-mentioned specific embodiments do not constitute a limitation on the protection scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims (18)

1. A method for measuring resident travel information, comprising: Obtain multiple positioning data generated by travel companion devices; According to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement, determine the stay area of the resident to which the travel companion device belongs during the travel process; The resident travel information is calculated based on the staying area. 2 . The method according to claim 1 , wherein, according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement, determine the travel time of the resident to which the travel accompanying device belongs during the travel process. 3 . Stay area, including: According to the spatiotemporal information of the plurality of positioning data, preliminarily determining the staying area and the moving area of the resident during the travel process; The target positioning data that meets the stay requirement is screened from the plurality of positioning data, and the preliminarily determined moving area is re-determined as the stay area. 3 . The method according to claim 1 , wherein, according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement, determine the travel time of the resident to which the travel accompanying device belongs during the travel process. 4 . Stay area, including: Clustering the plurality of positioning data according to the spatial information of the plurality of positioning data to obtain a plurality of regions; Screening target positioning data that meets the stay requirement from the plurality of positioning data, shortening the duration threshold corresponding to the area where the target positioning data is located, and/or reducing the range threshold corresponding to the area where the target positioning data is located expand; The stay duration and activity range between the positioning data in each area are calculated, and an area where the stay duration exceeds the duration threshold and the activity range does not exceed the range threshold is determined as a stay area. 4. The method according to claim 2 or 3, wherein the screening of the target positioning data that satisfies the stay requirement from the plurality of positioning data comprises: From the plurality of positioning data, filter the target positioning data located in the set resident activity scene; and/or, From the plurality of positioning data, target positioning data located at the resident point of residence is filtered. 5. The method according to claim 4, wherein the screening of the target positioning data located in the set resident activity scene from the plurality of positioning data comprises: From the plurality of positioning data, filter the target positioning data corresponding to the private network when the travel companion device is connected or detected; and/or, From the plurality of positioning data, the target positioning data corresponding to the area covered with the private network is screened. 6. The method according to claim 1, wherein the calculating the resident travel information based on the staying area comprises: Calculate the travel path of the resident according to the stay area; and/or, The number of target residents corresponding to the travel path covered by the designated area is counted, and the travel information of residents is calculated based on the target number of residents. 7. The method according to claim 6, wherein said calculating resident travel information based on the target number of residents comprises: Taking the ratio of the number of target residents to the number of active residents as the travel information of residents; The number of active residents is the number of residents who belong to the travel companion device from which the positioning data is generated in the designated area. 8. The method according to claim 6, wherein the calculating the travel path of the resident according to the staying area comprises: Sort the positioning data in all the staying areas in time order to obtain the time series of the positioning data; According to the time series of the positioning data and the stay area where the positioning data is located, construct the time series of the stay area; According to the time series of the staying area, the travel path of the resident is determined. 9. A device for measuring and calculating resident travel information, comprising: The acquisition module is used to acquire multiple positioning data generated by the travel companion device; A determination module, configured to determine the stay area of the resident to which the travel accompanying device belongs during the travel process according to the spatiotemporal information of the plurality of positioning data and whether the plurality of positioning data meet the stay requirement; an estimation module, configured to measure the travel information of the residents based on the stay area. 10. The apparatus of claim 9, wherein the determining module comprises: a first determining unit, configured to preliminarily determine the staying area and the moving area of the resident during travel according to the spatiotemporal information of the plurality of positioning data; The second determining unit is configured to filter target positioning data that meets the stay requirement from the plurality of positioning data, and re-determine the preliminarily determined moving area as the stay area. 11. The apparatus of claim 9, wherein the determining module comprises: a clustering unit, configured to cluster the multiple positioning data according to the spatial information of the multiple positioning data to obtain multiple regions; A shortening and enlarging unit, used for screening the target positioning data that meets the stay requirement from the plurality of positioning data, and shortening the time length threshold corresponding to the area where the target positioning data is located, and/or, the target positioning data The range threshold corresponding to the area is expanded; The calculation unit is configured to calculate the stay duration and the activity range between the positioning data in each area, and determine the area where the stay duration exceeds the duration threshold and the activity range does not exceed the range threshold as the stay area. 12. The apparatus of claim 10 or 11, wherein, The second determining unit is specifically configured to filter the target positioning data located in the set resident activity scene from the plurality of positioning data when screening the target positioning data that meets the stay requirement from the plurality of positioning data; and /or, from the plurality of positioning data, screening target positioning data located at the resident point of residence; The shortening and enlarging unit is specifically configured to filter the target positioning data located in the set resident activity scene from the plurality of positioning data when screening the target positioning data that meets the stay requirement from the plurality of positioning data; and /or, from the plurality of positioning data, screening target positioning data located at the resident point of residence. 13. The apparatus of claim 12, wherein, When screening the target positioning data located in the set resident activity scene from the plurality of positioning data, the second determining unit is specifically configured to screen the travel companion device access or access from the plurality of positioning data. Detecting the target positioning data corresponding to the private network; and/or, from the plurality of positioning data, screening the target positioning data corresponding to the area covered with the private network; The shortening and enlarging unit is specifically configured to, when screening the target positioning data located in the set resident activity scene from the plurality of positioning data, is specifically configured to screen the travel accompanying device access or The target positioning data corresponding to the private network is detected; and/or, from the plurality of positioning data, the target positioning data corresponding to the area covered with the private network is screened. 14. The device according to claim 9, wherein the measurement module comprises: a path calculation module, used for calculating the travel path of the resident according to the stay area; and/or, The intensity measurement module is used to count the number of target residents corresponding to the travel path covered by the designated area, and calculate the travel information of residents based on the target number of residents. 15. The device according to claim 14, wherein, when the intensity measurement module measures the travel information of residents based on the target number of residents, it is specifically used for: Taking the ratio of the number of target residents to the number of active residents as the travel information of residents; The number of active residents is the number of residents who belong to the travel companion device from which the positioning data is generated in the designated area. 16. The device according to claim 14, wherein the path measurement module is specifically used for: Sort the positioning data in all the staying areas in time order to obtain the time series of the positioning data; According to the time series of the positioning data and the stay area where the positioning data is located, construct the time series of the stay area; According to the time series of the staying area, the travel path of the resident is determined. 17. An electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the execution of any of claims 1-8 A method for measuring the travel information of residents. 18. A non-transitory computer-readable storage medium storing computer instructions, the computer instructions being used to make the computer execute the method for measuring and calculating the travel information of a resident according to any one of claims 1-8.

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