Traffic capacity information determination method and device, equipment and storage medium

Abstract

The disclosure provides a traffic capacity information determination method and device, equipment and a storage medium, and relates to the technical field of communication. In some embodiments of the disclosure, the communication parameters of a calling terminal and the traffic line information required by a user uploaded by the calling terminal are obtained; the current position of the user is automatically determined according to the communication parameters; the target station corresponding to the user is determined according to the traffic line information and the current position; the target train is automatically determined according to the traffic line information and the target station; and the train capacity information corresponding to the target train with more abundant content is automatically determined according to the current passenger number of the target train and the traffic correlation factor, so that the user can view the train capacity information, the target train and the train capacity information are automatically obtained, the information acquisition efficiency is improved, and the user experience is improved.

Description

Technical Field

[0001] This disclosure relates to the field of communication technology, and in particular to a method, apparatus, device and storage medium for determining traffic capacity information. Background Technology

[0002] Against the backdrop of accelerated modern urbanization and deep integration with intelligent transportation systems, public transportation, as the lifeblood of urban operation, directly affects residents' travel experience and the city's operational efficiency through its service efficiency and quality.

[0003] Currently, users can check the estimated arrival time of public transportation through a public transport app. However, this requires users to download the app in advance, open it manually, and operate the app, which is a cumbersome process and not user-friendly for the elderly.

[0004] Currently, public transportation information is limited in content, resulting in low information retrieval efficiency and a poor user experience. Summary of the Invention

[0005] This disclosure provides a method, apparatus, device, and storage medium for determining transportation capacity information, in order to at least solve the problems of existing train information being limited in content, having low information acquisition efficiency, and providing a poor user experience.

[0006] The technical solution disclosed herein is as follows: This disclosure provides a method for determining traffic capacity information, including: Obtain the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; The user's current location is determined based on the communication parameters; Based on the traffic route information and the current location, the target station corresponding to the user is determined; Based on the traffic route information and the target station, determine the target train number; Based on the current passenger load of the target train and traffic correlation factors, determine the train capacity information corresponding to the target train.

[0007] Optionally, the communication parameters include: base station location, signal strength information, wireless access device address, and historical signaling trajectory. Determining the user's current location based on the communication parameters includes: The user's current location is calculated based on the location and signal strength information of multiple communication base stations accessed by the calling terminal; Alternatively, the user's current location can be identified based on the wireless access device address uploaded by the calling terminal; Alternatively, the user's current location can be calculated based on the historical signaling trajectory of the calling terminal.

[0008] Optionally, the traffic route information includes: the route and direction of travel of the vehicle; determining the target station corresponding to the user based on the traffic route information and the current location includes: Based on the vehicle route and the direction of travel, determine multiple candidate stations corresponding to the current location; Based on the current location and the locations of the multiple candidate sites, calculate the spatial distance between the current location and each of the candidate sites; Select the target site that is spatially closest from the plurality of candidate sites.

[0009] Optionally, the traffic route information includes: the route and direction of travel of the transportation vehicle, and determining the target train number based on the traffic route information and the target station includes: Based on the vehicle route and the direction of travel, candidate vehicles that match the vehicle route and the direction of travel are selected. Calculate the station order difference between each candidate vehicle and the target station; The target train is selected from the candidate vehicles based on the station order difference.

[0010] Optionally, the train capacity information includes: the number of passengers at the downstream stations and the carriage crowding level. Determining the train capacity information corresponding to the target train based on the current passenger number and traffic correlation factors includes: Based on traffic correlation factors, predict the number of passengers alighting at the downstream station of the target train and the number of passengers boarding at the downstream station. The passenger capacity of the down-bound station is calculated based on the number of passengers alighting at the down-bound station, the number of passengers boarding at the down-bound station, and the current passenger capacity. The carriage crowding level is calculated based on the current passenger capacity and the set passenger capacity corresponding to the target train.

[0011] This disclosure also provides a method for determining traffic capacity information, including: In response to the caller's operation on the traffic communication access identifier, a video ringback tone is displayed on the calling terminal; In response to the interactive operation with the video ringback tone, the system obtains the traffic route information required by the user. The traffic route information is uploaded to the server so that the server can generate the corresponding train capacity information based on the traffic route information and send out the train capacity information. The capacity information is displayed on the calling terminal.

[0012] This disclosure also provides a traffic capacity information determination device, including: The acquisition module is used to acquire the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; The first determining module is used to determine the user's current location based on the communication parameters; The second determining module is used to determine the target station corresponding to the user based on the traffic route information and the current location; The third determining module is used to determine the target train number based on the traffic route information and the target station; The fourth determining module is used to determine the train capacity information corresponding to the target train based on the current passenger number of the target train and traffic correlation factors.

[0013] This disclosure also provides an electronic device, including: processor; Memory used to store processor-executable instructions; The processor is configured to execute instructions to implement the steps in the above method.

[0014] This disclosure also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0015] This disclosure also provides a computer program product, including a computer program / instructions, which, when executed by a processor, implement the steps of the method described above.

[0016] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects: In some embodiments of this disclosure, the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal are obtained; the user's current location is automatically determined based on the communication parameters; the target station corresponding to the user is determined based on the traffic route information and the current location; the target train is automatically determined based on the traffic route information and the target station; and more comprehensive train capacity information corresponding to the target train is automatically determined for the user to view based on the current passenger capacity of the target train and traffic correlation factors. This automatic acquisition of the target train and its capacity information improves information acquisition efficiency and enhances the user experience.

[0017] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0019] Figure 1 A flowchart illustrating a method for determining traffic capacity information provided as an exemplary embodiment of this disclosure; Figure 2 A flowchart illustrating another method for determining traffic capacity information provided as an exemplary embodiment of this disclosure; Figure 3 A schematic diagram of the structure of a traffic capacity information determination device provided for an exemplary embodiment of this disclosure; Figure 4 A schematic diagram of another traffic capacity information determination device provided as an exemplary embodiment of this disclosure; Figure 5 A schematic diagram of the structure of an electronic device provided for an exemplary embodiment of this disclosure; Figure 6 A schematic diagram of the structure of another electronic device provided as an exemplary embodiment of this disclosure. Detailed Implementation

[0020] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0021] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure.

[0022] It should be noted that the user information involved in this disclosure includes, but is not limited to, user device information and user personal information; the collection, storage, use, processing, transmission, provision and disclosure of user information in this disclosure all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0023] To address the aforementioned technical issues, some embodiments of this disclosure involve obtaining the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; automatically determining the user's current location based on the communication parameters; determining the user's target station based on the traffic route information and current location; automatically determining the target train number based on the traffic route information and target station; and automatically determining more comprehensive train capacity information for the user to view based on the current passenger capacity and traffic correlation factors of the target train number. This automatic acquisition of target train numbers and train capacity information improves information acquisition efficiency and enhances user experience.

[0024] The technical solutions provided by the embodiments of this disclosure are described in detail below with reference to the accompanying drawings.

[0025] From the perspective of the calling terminal Figure 1 This is a flowchart illustrating a method for determining traffic capacity information, provided as an exemplary embodiment of this disclosure. Figure 1 As shown, the method includes: S101: In response to the calling operation of the traffic communication access identifier, display a video ringback tone on the calling terminal; S102: In response to the interaction with the video ringback tone, obtain the traffic route information required by the user; S103: Upload the traffic route information to the server so that the server can generate the corresponding train capacity information based on the traffic route information and issue the train capacity information. S104: Display capacity information on the calling terminal.

[0026] From the server's perspective, Figure 2 A flowchart illustrating another method for determining traffic capacity information provided as an exemplary embodiment of this disclosure. Figure 2 As shown, the method includes: S201: Obtain the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; S202: Determine the user's current location based on communication parameters; S203: Determine the user's target station based on traffic route information and current location; S204: Determine the target train number based on traffic route information and target station; S205: Determine the train capacity information corresponding to the target train based on the current passenger load and traffic correlation factors.

[0027] In this embodiment, the calling terminal includes, but is not limited to, mobile stations (MS), mobile terminals, mobile phones, handsets, and portable equipment. This terminal device can communicate with one or more core networks via a radio access network (RAN). For example, the terminal device can be a mobile phone (or "cellular" phone), a computer with wireless communication capabilities, a computer with wireless transceiver capabilities, a virtual reality (VR) terminal device, an AR terminal device, a wireless terminal in industrial control, a wireless terminal in self-driving, a wireless terminal in remote medical care, a wireless terminal in a smart grid, a wireless terminal in transportation safety, a wireless terminal in a smart city, a wireless terminal in a smart home, etc. The operating system installed on the terminal device includes, but is not limited to, iOS, Android, Windows, Linux, and Mac OS. In different networks, terminals may be called by different names, such as: user equipment, mobile station, user unit, station, cellular phone, personal digital assistant, wireless modem, wireless communication device, handheld device, laptop, cordless phone, wireless local loop station, television, etc. For ease of description, this embodiment will simply refer to it as terminal device.

[0028] In this embodiment, the implementation form of the server is not limited. For example, the server can be a conventional server, a cloud server, a cloud host, a virtual center, or other server devices. The server mainly consists of a processor, hard disk, memory, system bus, and other common computer architecture types.

[0029] In this embodiment, the calling terminal responds to the calling operation of the traffic communication access identifier by displaying a video ringback tone on the calling terminal; the calling terminal responds to the interaction operation with the video ringback tone to obtain the traffic route information required by the user; the calling terminal uploads the traffic route information to the server, and the server obtains the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; the server determines the user's current location based on the communication parameters; the server determines the target station corresponding to the user based on the traffic route information and the current location; the server determines the target train number based on the traffic route information and the target station; the server automatically determines more comprehensive train capacity information corresponding to the target train for the user to view based on the current passenger capacity and traffic correlation factors of the target train, automatically obtains the target train number and train capacity information, improves information acquisition efficiency, enhances user experience, and distributes the train capacity information; the capacity information is displayed on the calling terminal.

[0030] In one exemplary embodiment, this disclosure eliminates the need for users to actively operate the app, passively triggering services through call behavior. This adapts to the elderly and scenarios with weak network coverage, improving service accessibility. The integration of multi-source positioning technology significantly improves station matching accuracy, reducing location judgment errors. A multi-factor prediction model accurately calculates carriage crowding, providing users with decision-making information such as "whether there is a seat" and "whether they can board," optimizing the travel experience. The visual presentation of video ringback tones is intuitive and easy to understand, allowing users to quickly obtain comprehensive information such as train schedules, crowding levels, and waiting suggestions, improving the intelligence level of public transportation services, reducing users' ineffective waiting time, and improving overall travel efficiency.

[0031] It should be noted that the transportation communication access identifier is the public transportation hotline, such as the bus service hotline or subway service hotline. Transportation route information includes, but is not limited to, the vehicle route and direction of travel.

[0032] In some embodiments of this disclosure, the calling terminal, in response to a calling operation on a traffic communication access identifier, displays a video ringback tone on its screen; and in response to interaction with the video ringback tone, obtains the traffic route information required by the user. Specifically, after a user dials the public transportation hotline, a video ringback tone is played on the display screen of the calling terminal. A digital human in the video greets the user and guides them to obtain the required traffic route information. The user initiates a traffic information inquiry request by dialing the public transportation hotline.

[0033] In some embodiments of this disclosure, after dialing a public transportation hotline, the calling terminal collects its communication parameters and uploads these parameters, along with the required transportation route information, to the server. The server then obtains the calling terminal's communication parameters and the uploaded transportation route information.

[0034] It should be noted that the communication parameters include: base station location, signal strength information, wireless access device address, and historical signaling trajectory.

[0035] In some embodiments of this disclosure, the user's current location is determined based on communication parameters. This includes, but is not limited to, the following determination methods: Method 1 involves calculating the user's current location based on the base station locations and signal strength information of multiple communication base stations accessed by the calling terminal. To accurately determine the user's location, this disclosure obtains the cell IDs and signal strength information of multiple currently accessed communication base stations after receiving a call from the user to the service hotline. By constructing a spatial distance model between the user's current location and known transportation station locations, a nearest neighbor algorithm or a weighted minimum distance algorithm is introduced for comparison to determine the relative proximity of the user to each candidate station. For example, the multi-base station triangulation method uses at least three base stations, combined with data such as signal strength, time difference of arrival, and angle, to calculate the user's current location.

[0036] in, Let be the location coordinates of the i-th base station. For the corresponding signal strength, Estimate the user's location.

[0037] Method two involves identifying the user's current location based on the wireless access device address uploaded by the calling terminal. Specifically, the wireless access device can be a Wi-Fi hotspot or a Bluetooth probe. When a user dials and triggers a location request, the calling terminal passively scans for nearby hotspots and Bluetooth beacons using its built-in Wi-Fi and Bluetooth probes, accurately capturing the MAC addresses and signal strengths of each hotspot. The system uploads this data to the location server in real time, performs feature matching using a pre-built MAC coordinate fingerprint database, and combines this with a multi-source fusion algorithm to reduce the coarse range provided by the base station to meter-level accuracy, thereby precisely identifying the user's specific physical location.

[0038] Method three involves calculating the user's current location based on the historical signaling trajectory of the calling terminal. After obtaining user authorization, the operator's core network signaling data is accessed to extract the user's base station interaction records (such as location updates and call setup signaling) within the past hour, obtaining the base station cell ID and signal characteristics with timestamps. This discrete base station information is mapped to preliminary geographic coordinates, and combined with the current time, trajectory reconstruction algorithms (such as Kalman filtering or graph neural network models based on road network constraints) are used to smooth the historical trajectory and extrapolate movement trends, thereby accurately deducing the user's current specific location.

[0039] In some embodiments of this disclosure, a target station corresponding to the user is determined based on traffic route information and the current location. One possible approach is to determine multiple candidate stations corresponding to the current location based on the vehicle route and direction of travel; calculate the spatial distance between the current location and each candidate station based on the current location and the locations of the multiple candidate stations; and select the target station with the closest spatial distance from the multiple candidate stations.

[0040] Specifically, based on a pre-set database containing GPS coordinates of all transportation stops, all candidate stops are calculated. Based on the distance to the user's current location, select the target site with the smallest distance to determine whether the user is likely at or about to enter the target site.

[0041]

[0042] in, It is the spatial distance from the user's current location to the j-th candidate site; , () represents the estimated latitude and longitude coordinates of the user's current location; , ) represents the latitude and longitude coordinates of the j-th candidate station, and the final selection is... The smallest station location.

[0043] In some embodiments of this disclosure, a target train is determined based on traffic route information and a target station. One possible approach is to filter candidate vehicles that match the traffic route and direction of travel; calculate the station order difference between each candidate vehicle and the target station; and select the target train from the candidate vehicles based on the station order difference. The forward vehicle identification and sorting stage of this disclosure is initiated after determining the user's nearest target station and receiving the user's selected traffic route and direction of travel, with the aim of determining the target train that is expected to arrive at the target station first.

[0044] Specifically, first, candidate vehicles on the same route and traveling in the same direction are selected. This involves obtaining the set {V1, V2, ..., Vn} of all currently operating candidate vehicles whose routes and directions match the user's selection from the real-time dispatch platform. Then, the distance between the current location of each candidate vehicle and the target station is calculated. For each candidate vehicle Vi, extract its current location. Based on the route map sequence number, calculate the distance from the current station to the target station for this train. Site order difference :

[0045] like <0: The vehicle has passed this station and is removed; like =0: The vehicle is currently parked or about to enter the station; like >0: The vehicle is still ahead of the user station and can be considered as a candidate; Select from candidate vehicles The i-th car closest to 0 is selected as the target car.

[0046] It should be noted that the train capacity information includes, but is not limited to: the number of passengers at the downstream stations and the crowding level in the carriages.

[0047] In some embodiments of this disclosure, the capacity information of the target train is determined based on the current passenger count and traffic correlation factors. One possible approach is to predict the number of passengers alighting and boarding at the downstream station of the target train based on the traffic correlation factors; calculate the passenger count at the downstream station based on the number of passengers alighting and boarding at the downstream station and the current passenger count; and calculate the carriage crowding based on the current passenger count and the set passenger count corresponding to the target train. To improve prediction accuracy, this disclosure employs a multi-dimensional prediction algorithm that integrates multiple real-time and historical traffic-related factors. These factors include, but are not limited to: weather factors, such as rainfall and high temperatures, which significantly affect public transportation travel density; road condition factors, which utilize traffic monitoring platforms or third-party navigation services to obtain current major road congestion indices and determine user preferences for buses or subways; holiday and commuting peak rules, with a built-in calendar for holidays, peak hours, and specific events; boarding and alighting distribution data at intermediate stations, combined with historical passenger flow models and real-time boarding and alighting counts to predict boarding and alighting trends at subsequent stations and dynamically adjust the current carriage crowding estimate; and comparison of adjacent trains with waiting passengers, analyzing data from front-end cameras and counting devices at waiting stations to calculate the probability of passenger diversion between trains.

[0048] Mathematical modeling and prediction algorithm structure, constructing a multi-factor passenger flow prediction model: ; in, This refers to the current number of passengers (the number of passengers who left the previous station). This refers to the predicted number of passengers getting off at the next stop. This refers to the predicted number of passengers boarding at the next stop. It is the number of passengers in the carriage at the next station; f(Wt,Tt,Dt,Ht, historical average vehicle value); g(Wt, Tt, Dt, Ht, historical average number of passengers disembarking); Among them, Wt refers to weather indicators; Tt refers to road conditions; Dt refers to whether it is a holiday; Ht refers to peak hour indicators; f and g can be offline models, and the final predicted values ​​are achieved by superposition. The back-end system calculates the passenger flow density of each carriage of the train in real time.

[0049] Formula for calculating the crowding level of a train carriage: ; in, This refers to the predicted number of passengers in the carriage; K refers to the maximum approved passenger capacity of the carriage (i.e., the set passenger capacity). when A value >0.8 is considered crowded, and Ct>1 indicates severe overloading. The crowding level of the carriage is expressed in numerical or graded form and matched with the carriage structure information.

[0050] In some embodiments of this disclosure, a video clip reflecting the train's capacity information is generated based on the target train number and the carriage crowding level, and the video clip is sent to the calling terminal; the user views the video clip through the calling terminal.

[0051] This embodiment of the disclosure breaks through the traditional mode of requiring users to actively operate an App or view bus stop signs to query traffic information by using a passive information acquisition trigger mechanism. Instead, it uses the familiar and low-threshold behavior of "calling the service hotline" as the trigger point and automatically pushes information through video ringback tones. Users don't need to download apps, learn how to operate them, or rely on network coverage; they can passively receive real-time traffic data simply through their daily call behavior. This particularly addresses the pain points of users unfamiliar with smart devices, such as the elderly, achieving "zero-learning-cost" information delivery. Through a multi-dimensional integrated precise positioning and prediction system, at the positioning level, it integrates multi-base station triangulation, Wi-Fi or Bluetooth probe assistance, and signaling trajectory back-inference technologies, combined with spatial distance algorithms to accurately match the user's nearest station, overcoming the errors of single positioning methods. At the prediction level, it integrates intelligent models of multiple factors such as weather, road conditions, holidays, and passenger flow history, dynamically calculating carriage congestion through mathematical modeling, predicting vehicle arrival times, and outputting in-depth information such as carriage heat maps. By combining communication networks with traffic data, it breaks down data barriers between communication operator networks and traffic dispatch systems, deeply integrating user call behavior data (base station information, call signals) with real-time traffic data (vehicle location, passenger flow counts). Through the digital human video ringback tone, it constructs a cross-border collaborative model between communication services and traffic information services, upgrading traditional communication functions (ringback tones) into a smart travel information terminal.

[0052] Figure 3 This is a schematic diagram of the structure of a traffic capacity information determination device 30 provided for an exemplary embodiment of this disclosure. Figure 3As shown, the traffic capacity information determination device 30 includes: an acquisition module 31, a first determination module 32, a second determination module 33, a third determination module 34, and a fourth determination module 35.

[0053] The acquisition module 31 is used to acquire the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal. The first determining module 32 is used to determine the user's current location based on communication parameters; The second determining module 33 is used to determine the target station corresponding to the user based on the traffic route information and the current location; The third determining module 34 is used to determine the target train number based on traffic route information and target station; The fourth determining module 35 is used to determine the train capacity information corresponding to the target train based on the current passenger number of the target train and traffic correlation factors.

[0054] Optionally, the communication parameters include: base station location, signal strength information, wireless access device address, and historical signaling trajectory. When determining the user's current location based on the communication parameters, the first determining module 32 is used to: The user's current location is calculated based on the location and signal strength information of multiple communication base stations accessed by the calling terminal; Alternatively, the user's current location can be identified based on the wireless access device address uploaded by the calling terminal; Alternatively, the user's current location can be calculated based on the historical signaling trajectory of the calling terminal.

[0055] Optionally, the traffic route information includes: the route and direction of travel of the vehicle. When determining the user's target station based on the traffic route information and the current location, the second determining module 33 is used for: Based on the transportation route and direction of travel, multiple candidate stations are determined for the current location; Calculate the spatial distance between the current location and each candidate site based on the current location and the locations of multiple candidate sites; Select the target site that is spatially closest from multiple candidate sites.

[0056] Optionally, the traffic route information includes: the route and direction of travel of the transportation vehicle. The third determining module 34, when determining the target train number based on the traffic route information and the target station, is used for: Based on the transportation route and direction of travel, candidate vehicles that match the transportation route and direction of travel are selected. Calculate the station order difference between each candidate vehicle and the target station; The target train is selected from the candidate trains based on the station order difference.

[0057] Optionally, the train capacity information includes: the number of passengers at the downstream stations and the congestion level of the carriages. When the fourth determining module 35 determines the train capacity information corresponding to the target train based on the current passenger number and traffic correlation factors, it is used for: Based on traffic correlation factors, predict the number of passengers alighting at the downstream station and the number of passengers boarding at the downstream station for the target train. Calculate the passenger capacity of the downstream station based on the number of passengers alighting at the downstream station, the number of passengers boarding at the downstream station, and the current passenger capacity. The congestion level of the carriage is calculated based on the current passenger capacity and the set passenger capacity corresponding to the target train.

[0058] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0059] Figure 4 A schematic diagram of another traffic capacity information determination device 40 provided for an exemplary embodiment of this disclosure. (See diagram below.) Figure 4 As shown, the traffic capacity information determination device 40 includes: a first display module 41, an acquisition module 42, an upload module 43, and a second display module 44.

[0060] The first display module 41 is used to display a video ringback tone on the calling terminal in response to the calling operation of the traffic communication access identifier. The acquisition module 42 is used to obtain the traffic route information required by the user in response to the interactive operation with the video ringback tone; Upload module 43 is used to upload traffic route information to the server, so that the server can generate the corresponding train capacity information for the target train based on the traffic route information and issue the train capacity information. The second display module 44 is used to display capacity information on the calling terminal.

[0061] Figure 5 This is a schematic diagram of the structure of an electronic device provided as an exemplary embodiment of the present disclosure. For example... Figure 5 As shown, the electronic device includes a memory 51 and a processor 52. Additionally, the electronic device also includes a power supply component 53 and a communication component 54.

[0062] Memory 51 is used to store computer programs and can be configured to store various other data to support operation on the electronic device. Examples of this data include instructions for any application or method used to operate on the electronic device.

[0063] The memory 51 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0064] Communication component 54 is used for data transmission with other devices.

[0065] The processor 52 is capable of executing computer instructions stored in the memory 51 to: display a video ringback tone on the calling terminal in response to a calling operation on a traffic communication access identifier; obtain traffic route information required by the user in response to an interactive operation with the video ringback tone; upload the traffic route information to the server so that the server can generate the corresponding train capacity information based on the traffic route information and issue the train capacity information; and display the capacity information on the calling terminal.

[0066] Accordingly, embodiments of this disclosure also provide a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores a computer program, and the computer program is executed by one or more processors, it causes one or more processors to perform... Figure 1 Each step in the method embodiment.

[0067] Accordingly, embodiments of this disclosure also provide a computer program product, which includes a computer program / instructions that are executed by a processor. Figure 1 Each step in the method embodiment.

[0068] Figure 6 A schematic diagram of the structure of another electronic device provided as an exemplary embodiment of this disclosure. For example... Figure 6 As shown, the electronic device includes a memory 61 and a processor 62. Additionally, the electronic device also includes a power supply component 63 and a communication component 64.

[0069] Memory 61 is used to store computer programs and can be configured to store various other data to support operation on the electronic device. Examples of this data include instructions for any application or method used to operate on the electronic device.

[0070] The memory 61 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0071] Communication component 64 is used for data transmission with other devices.

[0072] The processor 62 can execute computer instructions stored in the memory 61 to: obtain communication parameters of the calling terminal and traffic route information required by the user uploaded by the calling terminal; determine the user's current location based on the communication parameters; determine the target station corresponding to the user based on the traffic route information and the current location; determine the target train based on the traffic route information and the target station; and determine the train capacity information corresponding to the target train based on the current passenger capacity of the target train and traffic correlation factors.

[0073] Accordingly, embodiments of this disclosure also provide a computer-readable storage medium storing a computer program. When the computer-readable storage medium stores a computer program, and the computer program is executed by one or more processors, it causes one or more processors to perform... Figure 2 Each step in the method embodiment.

[0074] Accordingly, embodiments of this disclosure also provide a computer program product, which includes a computer program / instructions that are executed by a processor. Figure 2 Each step in the method embodiment.

[0075] The above Figure 5 and Figure 6 The communication component is configured to facilitate wired or wireless communication between the device containing the communication component and other devices. The device containing the communication component can access wireless networks based on communication standards, such as WiFi, 2G, 3G, 4G / LTE, 5G, or combinations thereof. In one exemplary embodiment, the communication component receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component also includes a Near Field Communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID), Infrared Data Association (IrDA) technology, Ultra-Wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0076] The above Figure 5 and Figure 6 The power supply component provides power to the various components of the device in which it resides. The power supply component may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device in which it resides.

[0077] The aforementioned electronic devices also include a display screen and audio components.

[0078] The display includes a screen, which may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors can sense not only the boundaries of touch or swipe actions, but also the duration and pressure associated with the touch or swipe operation.

[0079] An audio component may be configured to output and / or input audio signals. For example, the audio component includes a microphone (MIC) configured to receive external audio signals when the device containing the audio component is in an operating mode, such as call mode, recording mode, or voice recognition mode. The received audio signals may be further stored in memory or transmitted via a communication component. In some embodiments, the audio component also includes a speaker for outputting audio signals.

[0080] Those skilled in the art will understand that embodiments of this disclosure can be provided as methods, systems, or computer program products. Therefore, this disclosure can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this disclosure can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] This disclosure is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0082] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0084] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0085] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0086] Computer-readable media include both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0087] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0088] The above are merely specific embodiments of this disclosure, enabling those skilled in the art to understand or implement this disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to these embodiments, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for determining traffic capacity information, characterized in that, include: Obtain the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; The user's current location is determined based on the communication parameters; Based on the traffic route information and the current location, the target station corresponding to the user is determined; Based on the traffic route information and the target station, determine the target train number; Based on the current passenger load of the target train and traffic correlation factors, determine the train capacity information corresponding to the target train.

2. The method according to claim 1, characterized in that, The communication parameters include: base station location, signal strength information, wireless access device address, and historical signaling trajectory. Determining the user's current location based on the communication parameters includes: The user's current location is calculated based on the location and signal strength information of multiple communication base stations accessed by the calling terminal; Alternatively, the user's current location can be identified based on the wireless access device address uploaded by the calling terminal; Alternatively, the user's current location can be calculated based on the historical signaling trajectory of the calling terminal.

3. The method according to claim 1, characterized in that, The traffic route information includes: the route of the vehicle and its direction of travel. Determining the user's target station based on the traffic route information and the current location includes: Based on the vehicle route and the direction of travel, determine multiple candidate stations corresponding to the current location; Based on the current location and the locations of the multiple candidate sites, calculate the spatial distance between the current location and each of the candidate sites; Select the target site that is spatially closest from the plurality of candidate sites.

4. The method according to claim 1, characterized in that, The traffic route information includes: the route and direction of travel of the transportation vehicle. Determining the target train number based on the traffic route information and the target station includes: Based on the vehicle route and the direction of travel, candidate vehicles that match the vehicle route and the direction of travel are selected. Calculate the station order difference between each candidate vehicle and the target station; The target train is selected from the candidate vehicles based on the station order difference.

5. The method according to claim 1, characterized in that, The train capacity information includes: the number of passengers at the downlink stations and the congestion level of the carriages. Determining the train capacity information corresponding to the target train based on the current passenger number and traffic correlation factors includes: Based on traffic correlation factors, predict the number of passengers alighting at the downstream station of the target train and the number of passengers boarding at the downstream station. The passenger capacity of the down-bound station is calculated based on the number of passengers alighting at the down-bound station, the number of passengers boarding at the down-bound station, and the current passenger capacity. The carriage crowding level is calculated based on the current passenger capacity and the set passenger capacity corresponding to the target train.

6. A method for determining traffic capacity information, characterized in that, include: In response to the caller's operation on the traffic communication access identifier, a video ringback tone is displayed on the calling terminal; In response to the interactive operation with the video ringback tone, the system obtains the traffic route information required by the user. The traffic route information is uploaded to the server so that the server can generate the corresponding train capacity information based on the traffic route information and send out the train capacity information. The capacity information is displayed on the calling terminal.

7. A device for determining traffic capacity information, characterized in that, include: The acquisition module is used to acquire the communication parameters of the calling terminal and the traffic route information required by the user uploaded by the calling terminal; The first determining module is used to determine the user's current location based on the communication parameters; The second determining module is used to determine the target station corresponding to the user based on the traffic route information and the current location; The third determining module is used to determine the target train number based on the traffic route information and the target station; The fourth determining module is used to determine the train capacity information corresponding to the target train based on the current passenger number of the target train and traffic correlation factors.

8. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to execute instructions to implement the steps of the method as described in any one of claims 1-5 or 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1-5 or 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1-5 or 6.

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