Passenger positioning method and device, storage medium and equipment
By obtaining signaling data of passengers and drivers, and using clustering algorithms to calculate actual vehicle points and correct them, the problem of inappropriate vehicle points in taxi-hailing applications is solved, and the efficiency and convenience of vehicle rides are improved.
Patent Information
- Application Number
- CN202510292313.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-12
- Publication Date
- 2025-08-01
AI Technical Summary
The ride-hailing application provides inappropriate ride-hailing locations, and passengers need to communicate with the driver to new ride-hailing locations, which affects the ride-hailing efficiency.
By obtaining signaling data of passengers and drivers, a continuous set of positions is generated, and the actual vehicle point is calculated using clustering algorithms to determine the nearest core point for correction.
Improve ride efficiency, ensure convenient locations that are easy for passengers to reach and drivers to park easily, and reduce traffic congestion.
Smart Images
Figure CN120407957A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of data processing, and particularly relates to a passenger positioning method, device, storage medium, and equipment. Background Art
[0002] When a passenger uses a ride-hailing application to hail a taxi, the pick-up points provided by the ride-hailing application for the passenger to choose are mostly obvious points set according to the terrain, such as the entrance of a Point of Interest (POI), an intersection, a bus stop, etc. However, these pick-up points may be far from the passenger, making it inconvenient for the passenger to reach; or they may be inconvenient for parking and easily cause traffic congestion. At this time, the passenger needs to communicate with the driver about a new pick-up point, resulting in the driver being unable to pick up the passenger quickly and affecting the riding efficiency. Summary of the Invention
[0003] This application provides a passenger positioning method, device, storage medium, and equipment for solving the problem that the pick-up points provided by the ride-hailing application are inappropriate and the passenger needs to communicate with the driver about a new pick-up point, which affects the riding efficiency. The technical solution is as follows:
[0004] According to a first aspect of this application, a passenger positioning method is provided. The method includes:
[0005] When a passenger uses a ride-hailing application to hail a taxi near a POI, obtain the signaling data of the passenger and the driver who accepts the order, generate a continuous position set of the passenger and the driver according to the signaling data, and determine the actual pick-up point of the passenger near the POI according to the continuous position set;
[0006] Use a clustering algorithm to calculate the actual pick-up points of multiple passengers near the POI to obtain the actual pick-up area corresponding to the POI;
[0007] When a passenger to travel uses the ride-hailing application to hail a taxi near the POI, obtain the expected pick-up point selected by the passenger from the set of pick-up points provided by the ride-hailing application, and the set of pick-up points is set based on the terrain of the POI;
[0008] Determine the core point of the actual pick-up area closest to the expected pick-up point;
[0009] Correct the passenger's expected pick-up point according to the core point.
[0010] In a possible implementation manner, the correcting the passenger's expected pick-up point according to the core point includes:
[0011] Calculate a first distance between the core point and the passenger's expected pick-up point;
[0012] If the first distance is greater than the first distance threshold, determine the core point as the predicted boarding point.
[0013] In a possible implementation, generating the continuous position sets of the passenger and the driver according to the signaling data, and determining the actual boarding point of the passenger near the POI according to the continuous position sets includes:
[0014] Determine the continuous positions of the passenger according to the signaling data of the passenger to obtain the first continuous position set of the passenger;
[0015] Determine the continuous positions of the driver according to the signaling data of the driver to obtain the second continuous position set of the driver;
[0016] Determine the possible boarding points of the passenger near the POI according to the first continuous position set and the second continuous position set;
[0017] Determine the actual boarding point of the passenger near the POI according to the first continuous position set, the second continuous position set, and the possible boarding points.
[0018] In a possible implementation, determining the possible boarding points of the passenger near the POI according to the first continuous position set and the second continuous position set includes:
[0019] Detect whether the first continuous position set and the second continuous position set meet a preset condition, where the preset condition is that two identical first positions first appear in the first continuous position set, two identical second positions first appear in the second continuous position set, and the moments corresponding to the first position and the second position are the same;
[0020] If the first continuous position set and the second continuous position set meet the preset condition, calculate the second distance between the first position and the second position;
[0021] If the second distance is less than the second distance threshold, determine the second position as the possible boarding point of the passenger near the POI.
[0022] In a possible implementation, the method further includes:
[0023] If the second distance is greater than the second distance threshold, continue to detect whether the first continuous position set and the second continuous position set meet the preset condition.
[0024] In a possible implementation, determining the actual boarding location of the passenger near the POI according to the first set of consecutive positions, the second set of consecutive positions, and the possible boarding locations includes:
[0025] After generating the possible boarding locations, continue to calculate the third distance between two positions at the same moment in the first set of consecutive positions and the second set of consecutive positions;
[0026] If each third distance is less than the third distance threshold, determine the possible boarding location as the actual boarding location of the passenger near the POI.
[0027] In a possible implementation, the method further includes:
[0028] If at least one third distance is greater than the third distance threshold, continue to detect whether the first set of consecutive positions and the second set of consecutive positions meet the preset conditions.
[0029] According to a second aspect of the present application, there is provided a passenger positioning device, the device includes:
[0030] A generation module, configured to obtain signaling data of the passenger and the driver who picks up the order when the passenger uses a taxi-hailing application near a POI, generate a set of consecutive positions of the passenger and the driver according to the signaling data, and determine the actual boarding location of the passenger near the POI according to the set of consecutive positions;
[0031] A clustering module, configured to calculate the actual boarding locations of multiple passengers near the POI by using a clustering algorithm to obtain the actual boarding area corresponding to the POI;
[0032] An acquisition module, configured to obtain the expected boarding location selected by the passenger from the set of boarding locations provided by the taxi-hailing application when the passenger to travel uses the taxi-hailing application near the POI, and the set of boarding locations is set based on the terrain of the POI;
[0033] A determination module, configured to determine the core point of the actual boarding area closest to the expected boarding location;
[0034] A correction module, configured to correct the expected boarding location of the passenger according to the core point.
[0035] According to a third aspect of the present application, there is provided a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement the passenger positioning method as described above.
[0036] According to a fourth aspect of the present application, a computer device is provided, and the computer device includes the above-mentioned passenger positioning device.
[0037] The beneficial effects of the technical solution provided by the present application at least include:
[0038] For each POI, compared with the boarding points set by the ride-hailing application according to the terrain, the actual boarding points of most passengers near the POI should be convenient points where passengers can easily reach, drivers can park well, and congestion will not be caused. Therefore, we can perform clustering operations on the actual boarding points of multiple passengers near the POI to obtain the actual boarding area corresponding to the POI; then, when a passenger to travel uses a ride-hailing application to hail a taxi near the POI, the expected boarding point selected by the passenger from the set of boarding points provided by the ride-hailing application can be obtained, the core point of the actual boarding area closest to the expected boarding point can be determined, and the expected boarding point of the passenger can be corrected according to the core point, which can adaptively adjust the boarding point considering the passenger's riding habits and road conditions, and improve the riding efficiency. Description of the Drawings
[0039] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application, and those of ordinary skill in the art can obtain other drawings based on these drawings without creative efforts.
[0040] Figure 1 is a simple flowchart of a passenger positioning method provided by an embodiment of the present application;
[0041] Figure 2 is a detailed flowchart of a passenger positioning method provided by another embodiment of the present application;
[0042] Figure 3 is a structural block diagram of a passenger positioning device provided by an embodiment of the present application. Detailed Embodiments
[0043] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the embodiments of the present application will be further described in detail below with reference to the drawings.
[0044] As Figure 1 shown, it shows a method flowchart of a passenger positioning method provided by an embodiment of the present application, and this passenger positioning method can be applied to a computer device. The passenger positioning method may include:
[0045] Step 101, when a passenger uses a ride-hailing app to hail a taxi near a POI, obtain the signaling data of the passenger and the driver who accepts the order. Generate a set of continuous positions of the passenger and the driver based on the signaling data, and determine the actual boarding point of the passenger near the POI according to the set of continuous positions.
[0046] In a geographic information system, a POI can be a house, a store, a mailbox, a bus stop, etc. Passengers usually use a ride-hailing app to hail a taxi at locations with obvious signs such as POIs.
[0047] When a passenger uses a ride-hailing app to hail a taxi, the generated order information will include the passenger's mobile phone number, POI name, POI coordinates, the expected boarding point selected by the passenger, etc. The driver can determine whether to accept the order based on the order information. After the driver accepts the order, the computer device can obtain the signaling data of the passenger and the driver respectively. The signaling data includes at least the mobile phone number, location information, etc.
[0048] The computer device can monitor the positions of the passenger and the driver according to the location information in the signaling data. When it is determined that the distance between the driver and the POI is less than a predetermined threshold, a set of continuous positions of the passenger and the driver is generated for the passenger and the driver. The predetermined threshold can be set to different values according to actual needs, such as set to 50 meters. Among them, the set of continuous positions is obtained by sampling the positions of the passenger and the driver respectively at the same sampling time. Here, the position can be represented by coordinates.
[0049] In this embodiment, the set of continuous positions of the passenger is denoted as {C1, C2, C3,..., C n}, and the set of continuous positions of the driver is denoted as {D1, D2, D3,..., D n}, where n represents the sampling time.
[0050] The computer device can identify the actual boarding point of the passenger according to the set of continuous positions of the passenger and the driver. The actual boarding point may be the same as the expected boarding point or different from the expected boarding point.
[0051] Step 102, use a clustering algorithm to calculate the actual boarding points of multiple passengers near the POI to obtain the actual boarding area corresponding to the POI.
[0052] For each POI, the computer device can collect the actual boarding points of multiple passengers near the POI, and use a clustering algorithm to calculate all or part of the actual boarding points near each POI after screening to obtain the actual boarding area corresponding to each POI. Among them, there are many kinds of clustering algorithms, which are not limited in this embodiment.
[0053] The computer device executes steps 101 - 102 to process the ride data at historical moments to obtain the actual boarding areas corresponding to each POI. Then, when a passenger hails a taxi near this POI, the computer device can correct the estimated boarding point selected by the passenger according to the actual boarding area, that is, execute steps 103 - 105.
[0054] Step 103, when a passenger to travel hails a taxi using a taxi-hailing app near this POI, obtain the estimated boarding point selected by the passenger from the set of boarding points provided by the taxi-hailing app, and this set of boarding points is set based on the terrain of this POI.
[0055] In the taxi-hailing app, there is a preset set of boarding points for each POI. The boarding points in this set of boarding points are set based on the terrain and can be the main entrance of this POI, intersections or bus stops near this POI, etc.
[0056] When a passenger hails a taxi using a taxi-hailing app, the taxi-hailing app will display each boarding point in the set of boarding points to the passenger, and the passenger needs to select one boarding point from them. In this embodiment, the selected boarding point is called the estimated boarding point.
[0057] Step 104, determine the core point of the actual boarding area closest to the estimated boarding point.
[0058] The computer device can determine the POI where the passenger is located according to the order information, calculate the core points of at least one actual boarding area corresponding to this POI, and select the core point closest to the estimated boarding point from the at least one core point.
[0059] Step 105, correct the passenger's estimated boarding point according to the core point.
[0060] The computer device can compare the core point and the estimated boarding point, and correct the estimated boarding point according to the comparison result, so as to be able to adaptively adjust the boarding point by taking into account the passenger's riding habits and road conditions, and improve the riding efficiency.
[0061] In summary, for the passenger positioning method provided in the embodiments of the present application, for each POI, compared with the boarding points set by the ride-hailing application according to the terrain, the actual boarding points of most passengers near the POI should be convenient points where passengers can easily reach, drivers can park well, and congestion will not be caused. Therefore, we can perform clustering operations on the actual boarding points of multiple passengers near the POI to obtain the actual boarding area corresponding to the POI; then, when a passenger to travel uses a ride-hailing application to hail a taxi near the POI, the expected boarding point selected by the passenger from the set of boarding points provided by the ride-hailing application can be obtained, the core point of the actual boarding area closest to the expected boarding point can be determined, and the expected boarding point of the passenger can be corrected according to the core point, so as to adaptively adjust the boarding point considering the passenger's riding habits and road conditions, and improve the riding efficiency.
[0062] As Figure 2 shown, it shows a flowchart of a passenger positioning method provided by an embodiment of the present application. The passenger positioning method can be applied to a computer device. The passenger positioning method may include:
[0063] Step 201, when a passenger uses a ride-hailing application to hail a taxi near a POI, obtain the signaling data of the passenger and the driver who accepts the order, generate a continuous position set of the passenger and the driver according to the signaling data, and determine the actual boarding point of the passenger near the POI according to the continuous position set.
[0064] In a geographic information system, a POI can be a house, a store, a mailbox, a bus stop, etc. Passengers usually use a ride-hailing application to hail a taxi at locations with obvious signs such as POIs.
[0065] When a passenger uses a ride-hailing application to hail a taxi, the generated order information will include information such as the passenger's mobile phone number, POI name, POI coordinates, and the expected boarding point selected by the passenger. The driver can determine whether to accept the order according to the order information. When the driver accepts the order, the computer device can respectively obtain the signaling data of the passenger and the driver. The signaling data at least includes information such as the mobile phone number and location information.
[0066] The computer device can monitor the positions of the passenger and the driver according to the location information in the signaling data. When it is determined that the distance between the driver and the POI is less than a predetermined threshold, a continuous position set of the passenger and the driver is generated for the passenger and the driver. The predetermined threshold can be set to different values according to actual needs, such as set to 50 meters. Among them, the continuous position set is obtained by sampling the positions of the passenger and the driver respectively at the same sampling time, and the positions here can be represented by coordinates.
[0067] The computer device can identify the actual boarding location of the passenger based on the set of consecutive positions of the passenger and the driver. The actual boarding location may be the same as the expected driving location or different from the expected boarding location.
[0068] Specifically, generating a set of consecutive positions of the passenger and the driver according to signaling data, and determining the actual boarding location of the passenger near the POI based on the set of consecutive positions may include:
[0069] (1) Determine the consecutive positions of the passenger according to the signaling data of the passenger to obtain the first set of consecutive positions of the passenger.
[0070] In this embodiment, the set of consecutive positions of the passenger is denoted as {C1, C2, C3,..., C n}}, where n represents the sampling time.
[0071] (2) Determine the consecutive positions of the driver according to the signaling data of the driver to obtain the second set of consecutive positions of the driver.
[0072] In this embodiment, the set of consecutive positions of the driver is denoted as {D1, D2, D3,..., D n}}, where n represents the sampling time.
[0073] (3) Determine the possible boarding locations of the passenger near the POI according to the first set of consecutive positions and the second set of consecutive positions.
[0074] Among them, determining the possible boarding locations of the passenger near the POI according to the first set of consecutive positions and the second set of consecutive positions may include: detecting whether the first set of consecutive positions and the second set of consecutive positions meet a preset condition. The preset condition is that two identical first positions first appear in the first set of consecutive positions, two identical second positions first appear in the second set of consecutive positions, and the moments corresponding to the first position and the second position are the same; if the first set of consecutive positions and the second set of consecutive positions meet the preset condition, calculate the second distance between the first position and the second position; if the second distance is less than the second distance threshold, determine the second position as the possible boarding location of the passenger near the POI; if the second distance is greater than the second distance threshold, continue to detect whether the first set of consecutive positions and the second set of consecutive positions meet the preset condition.
[0075] In this embodiment, the distance calculated by the computer device may be the Euclidean distance, and its calculation formula is the specific formula: x i,j and y i,j are the coordinates of the two positions to be calculated.
[0076] For example, when C t and C t+1 are the same for the first time, and D tand D t+1 When they are also the same, the computer device calculates C t and D t The second distance d between them t ; When d t < a (a is the second distance threshold; here it means that both the driver and the passenger are no longer moving and are very close to each other, perhaps the passenger has already gotten on the vehicle), mark D t as the possible boarding point; when d t > a (here it means that the passenger and the driver happen to not be moving but are not close, indicating that the passenger has not gotten on the vehicle), continue to detect whether the first continuous position set and the second continuous position set meet the preset conditions.
[0077] (4) Determine the actual boarding point of the passenger near the POI according to the first continuous position set, the second continuous position set, and the possible boarding point.
[0078] Among them, determining the actual boarding point of the passenger near the POI according to the first continuous position set, the second continuous position set, and the possible boarding point may include: after generating the possible boarding point, continue to calculate the third distance between two positions at the same moment in the first continuous position set and the second continuous position set; if each third distance is less than the third distance threshold, then determine the possible boarding point as the actual boarding point of the passenger near the POI; if at least one third distance is greater than the third distance threshold, then continue to detect whether the first continuous position set and the second continuous position set meet the preset conditions.
[0079] For example, the computer device continues to calculate according to the above method and obtains multiple third distances d t2 , d t3 ,..., d n , if all the third distances are < b (b is the third distance threshold), it means that the passenger and the driver continue to maintain a very close distance, and it can be determined that the passenger has gotten on the vehicle. Change D t to the actual boarding point (here), and end the continuous position monitoring of the driver and the passenger in a short period of time. If at least one third distance > b, it means that the passenger and the driver are very close, but are separated by the terrain and need to detour to the passenger's location, and the passenger has not gotten on the vehicle. Continue to detect whether the first continuous position set and the second continuous position set meet the preset conditions.
[0080] Step 202, use the clustering algorithm to calculate the actual boarding points of multiple passengers near the POI to obtain the actual boarding area corresponding to the POI.
[0081] For each POI, the computer device can collect the actual boarding points of multiple passengers near the POI, and use a clustering algorithm to calculate all or a selected part of the actual boarding points near each POI to obtain the actual boarding area corresponding to each POI. Among them, there are many kinds of clustering algorithms, which are not limited in this embodiment.
[0082] The computer device executes steps 201-202 to process the riding data at a historical moment to obtain the actual boarding area corresponding to each POI. Then, when a passenger hails a taxi near the POI, the computer device can correct the estimated boarding point selected by the passenger according to the actual boarding area, that is, execute steps 203-206.
[0083] Step 203, when a passenger to travel hails a taxi near the POI using a taxi-hailing application, obtain the estimated boarding point selected by the passenger from the set of boarding points provided by the taxi-hailing application, and the set of boarding points is set based on the terrain of the POI.
[0084] In the taxi-hailing application, a set of boarding points is preset for each POI. The boarding points in the set of boarding points are set based on the terrain and can be the gate of the POI, an intersection or a bus stop near the POI, etc.
[0085] When a passenger hails a taxi using the taxi-hailing application, the taxi-hailing application will display each boarding point in the set of boarding points to the passenger, and the passenger needs to select one boarding point from them. In this embodiment, the selected boarding point is called the estimated boarding point.
[0086] Step 204, determine the core point of the actual boarding area closest to the estimated boarding point.
[0087] The computer device can determine the POI where the passenger is located according to the order information, calculate the core points of at least one actual boarding area corresponding to the POI, and select the core point closest to the estimated boarding point from the at least one core point.
[0088] Step 205, calculate the first distance between the core point and the passenger's estimated boarding point.
[0089] The computer device can compare the core point and the estimated boarding point, and correct the estimated boarding point according to the comparison result, so as to adaptively adjust the boarding point taking into account the passenger's riding habits and road conditions, and improve the riding efficiency.
[0090] When comparing, the computer device calculates the first distance between the core point and the estimated boarding point, and the first distance can be the Euclidean distance.
[0091] Step 206: If the first distance is greater than the first distance threshold, determine the core point as the expected boarding point.
[0092] The computer device compares the first distance with the first distance threshold. If the first distance is greater than the first distance threshold, it determines that the expected boarding point needs to be corrected and determines the core point as the expected boarding point; if the first distance is less than the first distance threshold, it determines that the expected boarding point does not need to be corrected.
[0093] In summary, for the passenger positioning method provided in the embodiments of the present application, for each POI, compared with the boarding points set by the taxi-hailing application according to the terrain, the actual boarding points of most passengers near the POI should be convenient points where passengers can easily reach, drivers can park well, and congestion will not be caused. Therefore, we can perform clustering operations on the actual boarding points of multiple passengers near the POI to obtain the actual boarding area corresponding to the POI; then, when a passenger to travel uses a taxi-hailing application near the POI, we can obtain the expected boarding point selected by the passenger from the set of boarding points provided by the taxi-hailing application, determine the core point of the actual boarding area closest to the expected boarding point, and correct the passenger's expected boarding point according to the core point, which can adaptively adjust the boarding point taking into account the passenger's riding habits and road conditions, and improve the riding efficiency.
[0094] As Figure 3 shown, it shows a structural block diagram of a passenger positioning device provided in an embodiment of the present application. The passenger positioning device can be applied to a computer device. The passenger positioning device may include:
[0095] A generating module 310, configured to, when a passenger uses a taxi-hailing application to hail a taxi near a POI, obtain the signaling data of the passenger and the driver who accepts the order, generate a continuous position set of the passenger and the driver according to the signaling data, and determine the actual boarding point of the passenger near the POI according to the continuous position set;
[0096] A clustering module 320, configured to calculate the actual boarding points of multiple passengers near the POI by using a clustering algorithm to obtain the actual boarding area corresponding to the POI;
[0097] An obtaining module 330, configured to, when a passenger to travel uses a taxi-hailing application to hail a taxi near the POI, obtain the expected boarding point selected by the passenger from the set of boarding points provided by the taxi-hailing application, and the set of boarding points is set based on the terrain of the POI;
[0098] A determining module 340, configured to determine the core point of the actual boarding area closest to the expected boarding point;
[0099] A correcting module 350, configured to correct the passenger's expected boarding point according to the core point.
[0100] In an alternative embodiment, the correction module 350 is further configured to:
[0101] Calculate a first distance between the core point and the predicted boarding point of the passenger;
[0102] If the first distance is greater than the first distance threshold, determine the core point as the predicted boarding point.
[0103] In an alternative embodiment, the generation module 310 is further configured to:
[0104] Determine the continuous positions of the passenger according to the signaling data of the passenger to obtain the first set of continuous positions of the passenger;
[0105] Determine the continuous positions of the driver according to the signaling data of the driver to obtain the second set of continuous positions of the driver;
[0106] Determine the possible boarding points of the passenger near the POI according to the first set of continuous positions and the second set of continuous positions;
[0107] Determine the actual boarding point of the passenger near the POI according to the first set of continuous positions, the second set of continuous positions, and the possible boarding points.
[0108] In an alternative embodiment, the generation module 310 is further configured to:
[0109] Detect whether the first set of continuous positions and the second set of continuous positions meet a preset condition, where the preset condition is that: two identical first positions first appear in the first set of continuous positions, two identical second positions first appear in the second set of continuous positions, and the moments corresponding to the first position and the second position are the same;
[0110] If the first set of continuous positions and the second set of continuous positions meet the preset condition, calculate a second distance between the first position and the second position;
[0111] If the second distance is less than the second distance threshold, determine the second position as the possible boarding point of the passenger near the POI.
[0112] In an alternative embodiment, the generation module 310 is further configured to:
[0113] If the second distance is greater than the second distance threshold, continue to detect whether the first set of continuous positions and the second set of continuous positions meet the preset condition.
[0114] In an alternative embodiment, the generation module 310 is further configured to:
[0115] After generating the possible boarding points, continue to calculate the third distance between two positions at the same moment in the first continuous position set and the second continuous position set;
[0116] If each third distance is less than the third distance threshold, determine the possible boarding point as the actual boarding point of the passenger near the POI.
[0117] In an optional embodiment, the generating module 310 is further configured to:
[0118] If at least one third distance is greater than the third distance threshold, continue to detect whether the first continuous position set and the second continuous position set meet the preset conditions.
[0119] In summary, for each POI, the passenger positioning device provided by the embodiments of the present application. Compared with the boarding points set by the taxi-hailing application according to the terrain, the actual boarding points of most passengers near the POI should be convenient points where passengers can easily reach, drivers can park well, and congestion will not be caused. Therefore, we can perform clustering operations on the actual boarding points of multiple passengers near the POI to obtain the actual boarding area corresponding to the POI; then, when a passenger to travel uses a taxi-hailing application near the POI, the expected boarding point selected by the passenger from the boarding point set provided by the taxi-hailing application can be obtained, the core point of the actual boarding area closest to the expected boarding point can be determined, and the expected boarding point of the passenger can be corrected according to the core point, so as to adaptively adjust the boarding point considering the passenger's riding habits and road conditions, and improve the riding efficiency.
[0120] An embodiment of the present application provides a computer-readable storage medium, in which at least one instruction is stored, and the at least one instruction is loaded and executed by a processor to implement the passenger positioning method as described above.
[0121] An embodiment of the present application provides a computer device, and the computer device includes any of the above passenger positioning devices.
[0122] It should be noted that when the passenger positioning device provided in the above embodiment performs passenger positioning, only the above division of each functional module is used for illustration. In actual applications, the above functions can be allocated to different functional modules according to needs, that is, the internal structure of the passenger positioning device is divided into different functional modules to complete all or part of the functions described above. In addition, the passenger positioning device provided in the above embodiment and the embodiment of the passenger positioning method belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.
[0123] Those of ordinary skill in the art can understand that all or part of the steps for implementing the above embodiments can be completed by hardware, or can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium, and the above-mentioned storage medium can be a read-only memory, a magnetic disk, an optical disc, etc.
[0124] The above description is not intended to limit the embodiments of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the embodiments of the present application shall be included in the protection scope of the embodiments of the present application.
Claims
1. A passenger positioning method, characterized in that, The method includes: When a passenger uses a ride-hailing app to hail a taxi near a point of interest (POI), obtaining the signaling data of the passenger and the driver who accepts the order, generating a set of continuous positions of the passenger and the driver based on the signaling data, and determining the actual boarding point of the passenger near the POI according to the set of continuous positions; Calculating the actual boarding points of multiple passengers near the POI using a clustering algorithm to obtain the actual boarding area corresponding to the POI; When a passenger to travel uses the ride-hailing app to hail a taxi near the POI, obtaining the estimated boarding point selected by the passenger from the set of boarding points provided by the ride-hailing app, where the set of boarding points is set based on the terrain of the POI; Determining the core point of the actual boarding area closest to the estimated boarding point; Correcting the passenger's estimated boarding point according to the core point.
2. The passenger positioning method according to claim 1, wherein, The correcting the passenger's estimated boarding point according to the core point includes: Calculating a first distance between the core point and the passenger's estimated boarding point; If the first distance is greater than a first distance threshold, determining the core point as the estimated boarding point.
3. The passenger positioning method according to claim 1 or 2, characterized in that The generating a set of continuous positions of the passenger and the driver based on the signaling data and determining the actual boarding point of the passenger near the POI according to the set of continuous positions includes: Determining the continuous positions of the passenger according to the passenger's signaling data to obtain a first set of continuous positions of the passenger; Determining the continuous positions of the driver according to the driver's signaling data to obtain a second set of continuous positions of the driver; Determining the possible boarding points of the passenger near the POI according to the first set of continuous positions and the second set of continuous positions; Determining the actual boarding point of the passenger near the POI according to the first set of continuous positions, the second set of continuous positions, and the possible boarding points.
4. The passenger positioning method according to claim 3, wherein The determining the possible boarding points of the passenger near the POI according to the first set of continuous positions and the second set of continuous positions includes: Detecting whether the first set of continuous positions and the second set of continuous positions meet a preset condition, where the preset condition is that two identical first positions first appear in the first set of continuous positions, two identical second positions first appear in the second set of continuous positions, and the moments corresponding to the first position and the second position are the same; If the first set of continuous positions and the second set of continuous positions meet the preset condition, calculating a second distance between the first position and the second position; If the second distance is less than a second distance threshold, determining the second position as the possible boarding point of the passenger near the POI.
5. The passenger positioning method according to claim 4, wherein The method further includes: If the second distance is greater than the second distance threshold, continuing to detect whether the first set of continuous positions and the second set of continuous positions meet the preset condition.
6. The passenger positioning method according to claim 4, characterized in that Determining the actual boarding location of the passenger near the POI according to the first set of consecutive positions, the second set of consecutive positions, and the possible boarding locations includes: After generating the possible boarding locations, continue to calculate the third distance between two positions at the same moment in the first set of consecutive positions and the second set of consecutive positions; If each third distance is less than the third distance threshold, determine the possible boarding location as the actual boarding location of the passenger near the POI.
7. The passenger positioning method according to claim 6, wherein The method further includes: If at least one third distance is greater than the third distance threshold, continue to detect whether the first set of consecutive positions and the second set of consecutive positions meet a preset condition.
8. A passenger positioning device, characterized in that, The device includes: A generation module, configured to, when a passenger uses a taxi-hailing application near a point of interest (POI), obtain signaling data of the passenger and the driver who accepts the order, generate sets of consecutive positions of the passenger and the driver according to the signaling data, and determine the actual boarding location of the passenger near the POI according to the sets of consecutive positions; A clustering module, configured to calculate actual boarding locations of multiple passengers near the POI by using a clustering algorithm to obtain an actual boarding area corresponding to the POI; An acquisition module, configured to, when a passenger to travel uses the taxi-hailing application near the POI, obtain a predicted boarding location selected by the passenger from a set of boarding locations provided by the taxi-hailing application, where the set of boarding locations is set based on the terrain of the POI; A determination module, configured to determine a core point of the actual boarding area closest to the predicted boarding location; A correction module, configured to correct the predicted boarding location of the passenger according to the core point.
9. A computer-readable storage medium, characterized in that, At least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the passenger positioning method according to any one of claims 1 to 7.
10. A computer device, characterized in that, The computer device includes: the passenger positioning device according to claim 8.