Method and apparatus for processing ride information, electronic device, and storage medium

Abstract

The application discloses a kind of ride information processing method, device, electronic equipment and storage medium, it is related to Internet of Vehicles technical field, the method comprises: the ride reservation information of user is collected and first human feature;The first human feature is uploaded to server, so that the server returns the permission analysis code obtained by the feature coding processing to the first human feature;Vehicle matching processing is carried out using the ride reservation information, and the vehicle matched with the ride demand of the user is obtained;The permission analysis code is transmitted to the vehicle, so that the vehicle collects second human feature when the user rides, and the permission of the user is obtained by local analysis of the permission analysis code.The application improves ride information processing efficiency and stability, improves user ride efficiency.

Description

Technical Field

[0001] This application relates to the field of vehicle networking technology, specifically to a method, device, electronic device, and storage medium for processing passenger information. Background Technology

[0002] With the development trend of smart cities, intelligent ride-hailing, as an important manifestation of smart cities, urgently needs mature solutions. Intelligent ride-hailing is usually achieved by intelligently processing relevant ride information such as user and vehicle information.

[0003] Currently, there are few applications of intelligent ride-hailing services in the industry. Existing solutions rely on cloud-based intelligent processing of ride information, such as user identification or vehicle matching. However, this cloud-based processing suffers from network instability, leading to low user ride efficiency. Therefore, existing technologies suffer from low and unstable ride information processing efficiency, resulting in low user ride efficiency. Summary of the Invention

[0004] This application provides a method and related apparatus for processing passenger information, aiming to improve the efficiency and stability of passenger information processing and enhance user passenger efficiency.

[0005] To address the aforementioned technical problems, this application provides the following technical solutions:

[0006] According to one embodiment of this application, a method for processing passenger information is applied to a station terminal. The method includes: collecting a user's passenger reservation information and a first human feature; uploading the first human feature to a server so that the server returns an access permission code obtained by feature encoding the first human feature; using the passenger reservation information to perform vehicle matching processing to obtain a vehicle matched to the user's passenger request; and transmitting the access permission code to the vehicle so that when the user boards the vehicle, the vehicle collects a second human feature to locally parse the access permission code to obtain the user's passenger access permission.

[0007] According to one embodiment of this application, a passenger information processing device is applied to a station terminal. The device includes: a collection module for collecting a user's passenger reservation information and a first human body feature; an upload module for uploading the first human body feature to a server, so that the server returns an access permission code obtained by feature encoding processing of the first human body feature; a matching module for using the passenger reservation information to perform vehicle matching processing to obtain a vehicle matched to the user's passenger request; and a parsing module for transmitting the access permission code to the vehicle, so that when the user boards the vehicle, the vehicle collects a second human body feature to perform local access permission parsing processing on the access permission code to obtain the user's passenger access permission.

[0008] In some embodiments of this application, the matching module includes: a search unit for searching for parked vehicles within a specific distance range of the platform terminal; a matching unit for determining a target vehicle from the parked vehicles that matches the ride reservation information; and a determination unit for matching the target vehicle as the vehicle matched to the user's ride request.

[0009] In some embodiments of this application, the matching module includes: a table acquisition unit, used to acquire a vehicle information table, wherein the vehicle information table stores the driving information of vehicles associated with the platform terminal; and a table query unit, used to determine, from the vehicle information table, the vehicle corresponding to the driving information that matches the ride reservation information, as the vehicle matched to the user's ride request.

[0010] In some embodiments of this application, the acquisition module includes: a first acquisition unit, configured to acquire the target human features of the user when a user is detected making a ride reservation on the platform terminal; a second acquisition unit, configured to obtain target vehicle information from the reservation result generated by the ride reservation operation when the reservation result is received; and a third acquisition unit, configured to use the target human features as the first human features and the target vehicle information as the ride reservation information when the target vehicle information is obtained.

[0011] In some embodiments of this application, the ride reservation information includes pre-purchased ticket information, and the device further includes: a deduction module, used to upload the pre-purchased ticket information to the server, so as to associate and store the permission parsing code with the pre-purchased ticket information in the server, and to perform a deduction operation according to the pre-purchased ticket information when the server receives a deduction instruction corresponding to the permission parsing code, wherein the deduction instruction is generated and sent to the server by the vehicle when it parses and obtains the user's ride permission.

[0012] In some embodiments of this application, the device further includes: a first post-processing module, configured to mark the permission resolution code corresponding to the user as sent when receiving a first message sent by the vehicle, wherein the first message is generated and sent by the vehicle when it determines that the user's ride permission resolution is successful; and a second post-processing module, configured to continue vehicle matching processing to determine other vehicles matched to the user's ride request when receiving a second message sent by the vehicle, and send the permission resolution code to the other vehicles, wherein the second message is generated and sent by the vehicle when it determines that the user meets the ride failure conditions.

[0013] According to one embodiment of this application, a method for processing ride information is applied to a server. The method includes: receiving a user's first human body feature uploaded by a station terminal; performing feature encoding processing on the first human body feature to obtain an access permission code; sending the access permission code to the station terminal so that the station terminal transmits the access permission code to a target vehicle, wherein the target vehicle is obtained by the station terminal through vehicle matching processing using the user's ride reservation information; and, when the user rides the vehicle, the target vehicle collects the user's second human body feature to perform local parsing processing on the access permission code to obtain the user's ride permissions.

[0014] According to one embodiment of this application, a ride information processing device is applied to a server. The device includes: a receiving module for receiving a user's first human body feature uploaded by a station terminal; an encoding processing module for performing feature encoding processing on the first human body feature to obtain an authorization parsing code; and a parsing code transmission module for sending the authorization parsing code to the station terminal, so that the station terminal transmits the authorization parsing code to a target vehicle, wherein the target vehicle is obtained by the station terminal through vehicle matching processing using the user's collected ride reservation information, and the user's second human body feature is collected by the target vehicle when the user rides the vehicle to perform local parsing processing on the authorization parsing code to obtain the user's ride authorization.

[0015] In some embodiments of this application, the encoding processing module includes: a feature type determination unit, used to determine the feature type of the first human feature; a strategy matching unit, used to obtain the feature extraction strategy corresponding to the feature type; and a feature extraction unit, used to perform feature extraction processing on the first human feature according to the feature extraction strategy to obtain first feature information as the permission parsing code.

[0016] In some embodiments of this application, the encoding processing module includes: a feature extraction unit, used to perform feature extraction processing on the first human body feature to obtain first feature information; an authorization acquisition unit, used to acquire ride authorization information matched by the first feature information; and an encryption encoding unit, used to encrypt the ride authorization information using the first feature information to obtain an encrypted encoding sequence as the authorization parsing code.

[0017] According to one embodiment of this application, a method for processing passenger information is applied to a vehicle. The method includes: receiving a user's permission parsing code transmitted by a station terminal, wherein the permission parsing code is obtained by a server performing feature encoding processing on a first human feature of the user collected by the station terminal, and the vehicle is obtained by the station terminal performing vehicle matching processing using the collected passenger reservation information of the user; collecting a second human feature of the user when the user boards the vehicle; performing feature extraction processing on the second human feature to obtain second feature information; and performing local parsing processing on the permission parsing code using the second feature information to obtain the user's passenger permissions.

[0018] According to one embodiment of this application, a ride information processing device is applied to a vehicle. The device includes: a parsing code acquisition module, used to receive a user's permission parsing code transmitted by a station terminal, wherein the permission parsing code is obtained by a server performing feature encoding processing on a first human feature of the user collected by the station terminal, and the vehicle is obtained by the station terminal performing vehicle matching processing using the collected ride reservation information of the user; a second feature acquisition module, used to acquire a second human feature of the user when the user rides the vehicle; a second feature extraction module, used to perform feature extraction processing on the second human feature to obtain second feature information; and a local parsing module, used to perform local parsing processing on the permission parsing code using the second feature information to obtain the user's ride permissions.

[0019] In some embodiments of this application, the permission parsing code is a first feature information obtained by feature extraction processing of the first human body feature; the local parsing module includes: a calculation parsing unit, used to calculate the similarity between the second feature information and the permission parsing code, so as to perform local parsing processing on the permission parsing code to obtain a similarity value; and a permission acquisition unit, used to acquire the ride permission information matched by the similarity value as the user's ride permission.

[0020] In some embodiments of this application, the permission parsing code is an encrypted encoding sequence obtained by encrypting the ride permission information using first feature information, wherein the first feature information is extracted from the first human body feature; the local parsing module includes: a decryption parsing unit, used to decrypt the permission parsing code using the second feature information, so as to perform local parsing processing on the permission parsing code to obtain the decrypted ride permission information; and a permission determination unit, used to use the decrypted ride permission information as the user's ride permission.

[0021] According to another embodiment of this application, an electronic device may include: a memory storing computer-readable instructions; and a processor reading the computer-readable instructions stored in the memory to execute the methods described in the embodiments of this application.

[0022] According to another embodiment of this application, a storage medium stores computer-readable instructions thereon, which, when executed by a computer's processor, cause the computer to perform the methods described in the embodiments of this application.

[0023] According to another embodiment of this application, a computer program product or computer program includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations described in the embodiments of this application.

[0024] In this embodiment, the user's ride reservation information and first human feature are collected through the station terminal; the first human feature is uploaded to the server so that the server returns an authorization parsing code obtained by feature encoding of the first human feature; the ride reservation information is used to perform vehicle matching processing to obtain the vehicle matched with the user's ride request; the authorization parsing code is transmitted to the vehicle so that when the user rides, the vehicle collects a second human feature to locally parse the authorization parsing code to obtain the user's ride authorization.

[0025] In this way, the platform terminal collects first-person facial features in advance, transmits them to the server to obtain a permission parsing code obtained through feature encoding processing, and authorizes the user's corresponding travel permissions based on the feature code before boarding. Then, the platform terminal forwards the permission parsing code to the vehicle, so that when the user boards, the vehicle can efficiently parse the permission parsing code based on the collected second-person facial features to obtain the user's travel permissions locally. Moreover, the vehicles are selected by the platform terminal in advance through vehicle matching processing based on travel information, and the vehicle only receives the permission parsing code of the matched user, which further ensures the efficiency of local retrieval and parsing on the vehicle. Thus, through the transmission and processing of travel information between the server and the vehicle by the platform terminal, the efficiency and stability of travel information processing are effectively improved, and the vehicle can efficiently and reliably obtain the user's travel permissions locally, improving the user's travel efficiency. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 A schematic diagram of a system to which embodiments of this application can be applied is shown.

[0028] Figure 2 A schematic diagram of another system to which embodiments of this application can be applied is shown.

[0029] Figure 3 A flowchart of a passenger information processing method according to an embodiment of this application is shown.

[0030] Figure 4 A flowchart of a passenger information processing method according to another embodiment of this application is shown.

[0031] Figure 5 A flowchart of a passenger information processing method according to yet another embodiment of this application is shown.

[0032] Figure 6 A schematic diagram of a passenger information processing system in a scenario applying an embodiment of this application is shown.

[0033] Figure 7 A block diagram of a passenger information processing apparatus according to an embodiment of this application is shown.

[0034] Figure 8 A block diagram of a passenger information processing apparatus according to another embodiment of this application is shown.

[0035] Figure 9 A block diagram of a passenger information processing apparatus according to yet another embodiment of this application is shown.

[0036] Figure 10 A block diagram of an electronic device according to an embodiment of this application is shown. Detailed Implementation

[0037] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0038] In the following description, specific embodiments of this application will be illustrated with reference to steps and symbols performed by one or more computers, unless otherwise stated. Therefore, these steps and operations will be referred to several times as being performed by a computer, and computer execution as referred to herein includes operations by a computer processing unit representing electronic signals of data in a structured format. This operation transforms the data or maintains it at a location in the computer's memory system, which can be reconfigured or otherwise alter the operation of the computer in a manner well known to those skilled in the art. The data structure maintained by the data is the physical location of the memory, which has specific characteristics defined by the data format. However, the principles of this application are described in the foregoing text, which is not intended to be limiting, and those skilled in the art will understand that many of the steps and operations described below can also be implemented in hardware.

[0039] Figure 1 A schematic diagram of a system 100 to which embodiments of this application can be applied is shown. For example... Figure 1 As shown, system 100 may include server 101, platform terminal 102 and vehicle 103, wherein server 101, platform terminal 102 and vehicle 103 can be connected wirelessly.

[0040] Data can be transmitted between server 101, station terminal 102, and vehicle 103 via a target protocol link. This target protocol link may include a transport layer protocol-based link, such as a Transmission Control Protocol (TCP) link or a User Datagram Protocol (UDP) link, as well as other transport layer protocols. In one embodiment, station terminal 102 and vehicle 103 can transmit data via Bluetooth.

[0041] Server 101 can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms.

[0042] In one implementation, server 101 can provide artificial intelligence cloud services, such as AI cloud services for massively multiplayer online role-playing games (MMORPGs). AI cloud services are generally also referred to as AIaaS (AI as a Service). This is a mainstream service model for AI platforms. Specifically, AIaaS platforms break down several common AI services and provide them as independent or packaged services in the cloud. This service model is similar to opening an AI-themed marketplace: all developers can access and use one or more AI services provided by the platform through API interfaces. Some experienced developers can also use the AI ​​framework and AI infrastructure provided by the platform to deploy and maintain their own dedicated cloud AI services.

[0043] The platform terminal 102 can be an edge device. The platform terminal can be a platform-specific device set on the platform, such as an electronic bus stop sign or an electronic ticketing machine, or it can be a smartphone, computer, VR / AR device, computer, etc. that is specific to a certain platform.

[0044] In one embodiment of this example, the platform terminal 102 can collect the user's ride reservation information and a first human feature; upload the first human feature to the server 101 so that the server 101 returns an authorization parsing code obtained by feature encoding processing of the first human feature; use the ride reservation information to perform vehicle matching processing to obtain the vehicle 103 matched with the user's ride request; transmit the authorization parsing code to the vehicle 103 so that when the user rides, the vehicle 103 collects a second human feature to locally parse the authorization parsing code to obtain the user's ride authorization.

[0045] It is understood that, in the specific embodiments of this application, data related to human characteristics are involved. When the following embodiments of this application are applied to specific products or technologies, permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0046] Figure 2 A schematic diagram of another system 200 to which embodiments of this application can be applied is shown. For example... Figure 2As shown, system 200 can be composed of client 201 (client 201 can be as follows) Figure 1 The platform terminal 102 carries the client, and multiple nodes 202 (each node 202 can be as follows). Figure 1 The distributed system is formed by connecting servers 101 in the network through network communication.

[0047] Taking a distributed system as an example, see blockchain system. Figure 2 , Figure 2 This is an optional structural diagram of the distributed system 200 provided in this application embodiment applied to a blockchain system. It consists of multiple nodes 202 and clients 201, forming a peer-to-peer (P2P) network. The P2P protocol is an application layer protocol running on top of the Transmission Control Protocol (TCP). In the distributed system, any machine, such as a server or terminal, can join and become a node 202 (each node 202 can be, for example, a server or client). Figure 1 The server 101 in the system consists of a hardware layer, a middleware layer, an operating system layer, and an application layer.

[0048] See Figure 2 The functions of each node in the blockchain system shown include:

[0049] 1) Routing: A basic function of nodes used to support communication between nodes.

[0050] In addition to routing capabilities, nodes can also have the following functions:

[0051] 2) Applications are deployed in the blockchain to implement specific business needs. They record data related to the implementation of functions to form record data, carry digital signatures in the record data to indicate the source of the task data, and send the record data to other nodes in the blockchain system. When other nodes successfully verify the source and integrity of the record data, they add the record data to a temporary block.

[0052] For example, the business logic implemented by the application includes:

[0053] 2.1) A wallet is used to provide the function of conducting electronic currency transactions, including initiating transactions (i.e., sending the transaction record of the current transaction to other nodes in the blockchain system; after other nodes successfully verify the transaction, they store the transaction record data in the temporary block of the blockchain as a response to acknowledge the validity of the transaction; of course, the wallet also supports querying the remaining electronic currency in the electronic currency address.

[0054] 2.2) Shared ledger, used to provide functions such as storage, query and modification of ledger data. It sends the record data of the operation on the ledger data to other nodes in the blockchain system. After the other nodes verify the validity, as a response to acknowledge the validity of the ledger data, they store the record data in a temporary block. They can also send confirmation to the node that initiated the operation.

[0055] 2.3) Smart contracts are computerized protocols that can execute the terms of a contract. They are implemented through code deployed on a shared ledger that executes when certain conditions are met. Based on actual business needs, the code is used to complete automated transactions, such as querying the logistics status of goods purchased by a buyer and transferring the buyer's electronic money to the merchant's address after the buyer signs for the goods. Of course, smart contracts are not limited to executing contracts for transactions; they can also execute contracts for processing received information.

[0056] 3) A blockchain consists of a series of blocks that are sequentially generated. Once a new block is added to the blockchain, it will not be removed. The blocks contain the data submitted by the nodes in the blockchain system.

[0057] In one embodiment of this example, the client 201 on the platform terminal can collect the user's ride reservation information and a first human feature; upload the first human feature to the server corresponding to node 202, so that the server corresponding to node 202 returns an authorization parsing code obtained by feature encoding processing of the first human feature; use the ride reservation information to perform vehicle matching processing to obtain the vehicle matched to the user's ride request; transmit the authorization parsing code to the vehicle, so that when the user rides, the vehicle collects a second human feature to locally parse the authorization parsing code to obtain the user's ride authorization.

[0058] Figure 3 A flowchart illustrating a passenger information processing method according to an embodiment of this application is shown schematically. The entity executing this passenger information processing method may be a station terminal, for example... Figure 1 The platform terminal 102 shown is shown.

[0059] like Figure 3 As shown, the ride information processing method may include steps S310 to S340.

[0060] Step S310: Collect the user's ride reservation information and first human body characteristics;

[0061] Step S320: Upload the first human body feature to the server so that the server returns the permission parsing code obtained by feature encoding processing of the first human body feature;

[0062] Step S330: Use the ride reservation information to perform vehicle matching processing to obtain the vehicle matched to the user's ride request.

[0063] Step S340: The permission resolution code is transmitted to the vehicle so that when the user rides in the vehicle, the vehicle collects the second human feature to locally parse the permission resolution code and obtain the user's ride permission.

[0064] The following describes the specific steps involved in processing passenger information at the platform terminal.

[0065] In step S310, the user's ride reservation information and first human body characteristics are collected.

[0066] In this example implementation, the platform terminal is a terminal that can collect travel information in advance before the user boards the vehicle. In one embodiment, the platform terminal can be a travel information collection terminal set up on a specific platform, where the specific platform is the platform where the user boards the vehicle, such as a bus stop or a high-speed rail station. In this case, the platform terminal may be, for example, a self-service ticket machine or an electronic bus stop sign. In another embodiment, the platform terminal can be a mobile terminal, such as the user's personal mobile phone.

[0067] Ride information refers to information used to accurately link users, vehicles, and vehicle ride permissions. Ride information can include ride reservation information and user information. Ride reservation information can include the reserved vehicle identifier, target ride time, target route, and pre-purchased ticket information. User information can be primary biometric features, which are the features required for biometric identification. Biometric identification includes fingerprint recognition, facial recognition, iris recognition, palm / fingerprint vein recognition, etc. Primary biometric features include facial images, eye images, fingerprint images, and voice.

[0068] The platform terminal can carry a client for collecting travel information, such as ticketing applications or vehicle reservation software. The platform terminal can collect users' travel reservation information and first-person facial features through the client. For example, users can actively submit travel reservation information through the client. At the same time, the platform terminal can collect users' first-person facial features by activating a camera or fingerprint scanner.

[0069] In one embodiment, the first human feature is the user's first facial image captured by the 3D camera of the platform terminal when the user makes a ride reservation. This can efficiently collect the first human feature and ensure user experience. Meanwhile, the ride reservation information is the information submitted by the user through the submit button after the ride reservation operation is completed.

[0070] In one embodiment, step S310, collecting the user's ride reservation information and first human body feature, includes: when it is detected that the user is making a ride reservation operation on the platform terminal, collecting the user's target human body feature; when the reservation result generated by the ride reservation operation is received, obtaining the target vehicle information from the reservation result; when the target vehicle information is obtained, using the target human body feature as the first human body feature, and using the target vehicle information as the ride reservation information.

[0071] Users can make reservations through the client application. Based on the reservation, they can select the vehicle identifier, target departure time, target route, and other travel target information, and submit the corresponding pre-purchased ticket information (i.e., ticket information that has been purchased in advance but is yet to be paid for).

[0072] When a user is detected opening the client or triggering a specific operation control, it can be determined that the user is making a ride reservation on the platform terminal. When a user is detected making a ride reservation on the platform terminal, the system can automatically collect the target's human features by turning on the camera, such as capturing a facial image; or, a prompt for target human feature extraction can be displayed, reminding the user that their human features need to be collected through a specific human feature extraction device, such as prompting the user to place their finger on a fingerprint scanner to collect a fingerprint, or prompting the user to say a sentence to record their voice, etc.

[0073] When a user completes a ride reservation, they can submit the reservation result by triggering the submit button. The station terminal then receives the reservation result and can obtain the target vehicle information from the reservation result. The target vehicle information may include at least one of the following: the reserved vehicle identifier, the target boarding time, and the target boarding route.

[0074] Finally, when the platform terminal obtains the target vehicle information, it uses the target human body characteristics as the first human body characteristics and the target vehicle information as the ride reservation information. In this way, the ride reservation information and the first human body characteristics can be efficiently processed while ensuring the validity of the collected ride reservation information and the first human body characteristics. This avoids invalid information due to users temporarily browsing or interrupting operations, and ensures the effectiveness and reliability of ride information processing in subsequent steps.

[0075] The platform terminal also collects and stores the user's corresponding travel reservation information and first human characteristics in the database of the platform terminal.

[0076] In step S320, the first human body feature is uploaded to the server so that the server returns the permission parsing code obtained by feature encoding processing of the first human body feature.

[0077] In this example implementation, the first human feature is uploaded to the server, for example, the collected facial image, eye image, fingerprint image and sound are uploaded to the server. The server performs feature encoding processing on the first human feature, obtains the permission parsing code, and returns it to the station terminal.

[0078] The permission resolution code is an information code that grants a user the right to ride. The server can perform feature encoding processing on the first human feature in the following ways: In one embodiment, the server performs feature extraction processing on the first human feature according to a feature extraction strategy to obtain first feature information as the permission resolution code. For example, facial feature information (i.e., first feature information) is extracted from a face image (i.e., the first human feature) based on a facial feature extraction strategy (i.e., feature extraction strategy), or voiceprint information (i.e., first feature information) is extracted from a voice (i.e., the first human feature) based on a voiceprint extraction strategy (i.e., feature extraction strategy). In another embodiment, the first human feature is subjected to feature extraction processing to obtain first feature information; ride permission information matching the first feature information is obtained (the ride permission information may include special permission information, such as seat information and temperature information); the ride permission information is encrypted using the first feature information to obtain an encrypted encoding sequence as the permission resolution code.

[0079] By obtaining the permission parsing code, the passenger information (i.e., the first human feature) of the human body feature dimension can be preprocessed into a permission parsing code in advance. At the same time, the preprocessed code can be used to parse the user's passenger permission locally in the vehicle, which can speed up the passenger information processing efficiency and can be used to quickly authorize the user's passenger permission locally in the vehicle.

[0080] In step S330, the ride reservation information is used to perform vehicle matching processing to obtain the vehicle matched to the user's ride request.

[0081] In this example implementation, the ride reservation information may include information corresponding to the user's ride needs, such as the user's reserved vehicle identifier, target ride time, and target ride route. Then, vehicle matching processing can be performed based on the ride reservation information to obtain the vehicle matched to the user's ride needs.

[0082] By matching vehicles to a user's travel needs, the system can accurately send the access control code to the matched vehicle in subsequent steps. This avoids the vehicle storing access control codes for users whose travel information is incompatible with its own operational status. Taking a bus as an example, by using ride-hailing information for vehicle matching, the system can send the access control code of each user at the bus stop to the matched bus in subsequent steps, avoiding sending the access control codes of all users at the bus stop to all buses.

[0083] In this way, on the one hand, the storage pressure on the vehicle is not overloaded, and on the other hand, the corresponding permission resolution code can be quickly retrieved when the user takes the ride based on the small number of stored permission resolution codes, further ensuring the efficiency of subsequent ride information processing.

[0084] In one embodiment, step S330, using the ride reservation information to perform vehicle matching processing to obtain the vehicle matched to the user's ride request, includes: searching for vehicles parked within a specific distance range of the platform terminal; identifying the target vehicle that matches the ride reservation information from the parked vehicles; and using the target vehicle as the vehicle matched to the user's ride request.

[0085] The parked vehicles are predetermined vehicles that can receive information from the platform terminal and carry users. In one embodiment, parked vehicles within a specific distance range of the platform terminal can be searched using satellite positioning. In another embodiment, a connection (e.g., Bluetooth connection) can be automatically established with the platform terminal when a parked vehicle is within a specific distance range of the platform terminal. Thus, parked vehicles that have established a connection with the platform terminal can be identified as those within the specific distance range of the platform terminal.

[0086] Identifying target vehicles matching the reservation information from the parked vehicles can be done by matching the vehicle's travel information (including vehicle identification, arrival time, and route) with the reservation information. This identifies target vehicles among the parked vehicles that match the user's reserved vehicle identification, target arrival time, and target route. The vehicle's travel information can be obtained from a cloud server (e.g., when the vehicle is within a specific distance of the platform terminal). Figure 1 The server (101) sends the data to the station terminal in real time. This allows for matching the target vehicle among parked vehicles within a specific distance range, effectively ensuring the user's travel efficiency.

[0087] In one embodiment, the platform terminal can obtain the ride reservation information of all users within its planning range. Determining the target vehicle matching the ride reservation information from the parked vehicles can include: identifying the target vehicle matching the ride reservation information of each user from the parked vehicles, thus obtaining the target vehicle corresponding to each user (at least one target vehicle). The planning range of the platform terminal can be the area within a specific platform where the platform terminal is located (e.g., the platform area of ​​a bus stop). In this case, the platform terminal can consist of at least one sub-terminal. For example, three sub-terminals can be set up within the platform area to work collaboratively, sharing the ride reservation information of all users collected by all sub-terminals included in the platform terminal. One of the master and sub-terminals can perform vehicle matching. Similarly, the master and sub-terminals can send the collected first human feature to the server and receive the permission parsing code returned by the server.

[0088] In one embodiment, step S330, using the ride reservation information to perform vehicle matching processing to obtain the vehicle matched to the user's ride request, includes: obtaining a parking vehicle information table, which stores the driving information of parking vehicles associated with the platform terminal; and determining, from the parking vehicle information table, the parking vehicle corresponding to the driving information that matches the ride reservation information as the vehicle matched to the user's ride request.

[0089] The vehicle information table stores the driving information (including vehicle identification, arrival time, and route) of vehicles associated with the platform terminal. This vehicle information table can be stored on a cloud server (e.g., [missing information]). Figure 1 The information is sent in real time from server 101 to the station terminal. Based on the vehicle information table, the system can quickly determine the vehicle corresponding to the travel information that matches the passenger reservation information, further ensuring the efficiency of the passenger's journey.

[0090] In step S340, the permission resolution code is transmitted to the vehicle so that when the user boards the vehicle, the vehicle collects the second human body feature to locally parse the permission resolution code and obtain the user's boarding permission.

[0091] In this example implementation, the permission resolution code is transmitted to the vehicle. When a user boards the vehicle, the vehicle can directly collect the second human feature to locally parse the permission resolution code, quickly obtaining the user's boarding permission. During the short boarding period, there is no need to upload the user's second human feature to the cloud for user identity resolution, etc. The boarding information processing efficiency is high and stable, allowing users to board quickly and effectively improving the user's boarding efficiency.

[0092] Among them, user ride permissions refer to the processing permissions a user has when riding in the vehicle. In one example, the predetermined ride permission information (i.e., after the user's permission is successfully resolved, the user enjoys the predetermined ride permissions, such as the permission to automatically allow the user to ride by opening the gate). In another example, the ride permission is a dynamic indication of the user's ride permission information by the permission resolution code, i.e., after the user's permission is successfully resolved, the user enjoys the predetermined ride permissions as well as the ride permissions indicated by the ride permission information (such as the user's suitable seating position and the temperature inside the vehicle when riding).

[0093] In one embodiment, the ride reservation information includes pre-purchased ticket information, and the ride information processing method further includes:

[0094] The pre-purchased ticket information is uploaded to the server so that the permission resolution code is associated with and stored on the server. When the server receives the deduction instruction corresponding to the permission resolution code, it performs the deduction operation according to the pre-purchased ticket information. The deduction instruction is generated and sent to the server when the vehicle obtains the user's travel permission.

[0095] Pre-purchased ticket information refers to tickets purchased in advance but awaiting payment; that is, booking information in a pending payment state. This pre-purchased ticket information is uploaded to the server. When the vehicle verifies and obtains the user's travel authorization, it indicates that the user has successfully boarded the vehicle. Then, it generates and sends a "deduction instruction corresponding to the authorization parsing code" to the server. Upon receiving the deduction instruction, the server executes the deduction operation based on the pre-purchased ticket information. This allows for deduction only upon successful boarding, effectively improving the user experience.

[0096] In one embodiment, the deduction instruction includes the user's payment account information (such as WeChat account information or WeChat payment code), and the server can perform the deduction operation based on the payment account information. The payment account information can be obtained by the station terminal uploading the user's first human feature to the server, the server extracting the feature information of the first human feature (such as facial feature information), and then matching the feature information of the first human feature with preset feature information to obtain the payment account information corresponding to the matched preset feature information. This payment account information is then sent to the station terminal, which, along with the authorization parsing code, sends it to the vehicle. This further enables a closed-loop and reasonable process for automatic user boarding through the station terminal, server, and vehicle, effectively improving the efficiency of passenger information processing and enhancing user boarding efficiency and convenience.

[0097] In one embodiment, the passenger information processing method further includes:

[0098] When the first message sent by the vehicle is received, the user's corresponding permission resolution code is marked as sent. The first message is generated and sent by the vehicle when it confirms that the user's ride permission has been successfully resolved.

[0099] Upon receiving the second message from the vehicle, the vehicle matching process continues to determine other vehicles that match the user's ride request, and the permission resolution code is sent to the other vehicles. The second message is generated and sent by the vehicle when it determines that the user meets the conditions for ride failure.

[0100] When the vehicle confirms that the user's boarding permission has been successfully resolved, it indicates that the user has successfully boarded the vehicle. Then, it sends a first message to the station terminal, which marks the user's corresponding permission resolution code as sent, thus stopping the process of sending the user's permission resolution code to the vehicle. The first message can carry "the user's corresponding permission resolution code and a successful boarding permission resolution flag," ensuring that the station terminal accurately marks the user's corresponding permission resolution code as sent. Marking it as sent can be achieved by deleting the user's corresponding permission resolution code from the station terminal.

[0101] When a vehicle determines that a user meets the conditions for a failed ride, it indicates that the user's ride has failed. Then, by sending a second message to the station terminal, the station terminal can mark the user's corresponding permission resolution code as unsuccessfully sent. The station terminal can then continue vehicle matching to determine other vehicles matching the user's ride request and send permission resolution codes to these other vehicles until it receives the first message from another vehicle, at which point it marks the user's corresponding permission resolution code as sent. The conditions for a failed ride can be that the vehicle fails to resolve the user's ride permissions within a predetermined time period after receiving the permission resolution code from the station terminal; or that the vehicle fails to resolve the user's ride permissions when leaving the station where the station terminal is located.

[0102] In this manner, based on steps S310 to S340, the station terminal collects the first human body feature in advance and transmits it to the server to obtain the permission parsing code obtained through feature encoding processing. This allows for pre-authorization of the user's corresponding travel permissions based on the feature encoding before boarding. Then, the station terminal forwards the permission parsing code to the vehicle, enabling the vehicle to efficiently parse the permission parsing code locally based on the collected second human body feature, thus obtaining the user's travel permissions. Furthermore, since the vehicle is selected by the station terminal through pre-processing of travel information and reasonable ride planning, the vehicle only receives the permission parsing code of the matched user, further ensuring the efficiency of local retrieval and parsing. Therefore, through the station terminal's transmission and processing of travel information between the server and the vehicle, the efficiency and stability of travel information processing are effectively improved, and the vehicle can efficiently and reliably obtain the user's travel permissions locally, thereby improving the user's travel efficiency.

[0103] Figure 4 A flowchart illustrating a passenger information processing method according to an embodiment of this application is shown schematically. The entity executing this passenger information processing method may be a server, for example... Figure 1 The server shown is 101.

[0104] like Figure 4 As shown, the ride information processing method may include steps S410 to S440.

[0105] Step S410: Receive the user's first human body feature uploaded by the station terminal;

[0106] Step S420: Perform feature encoding processing on the first human body feature to obtain the permission parsing code;

[0107] Step S430: Send the permission resolution code to the station terminal so that the station terminal can transmit the permission resolution code to the target vehicle. The target vehicle is obtained by the station terminal through vehicle matching processing using the collected user's ride reservation information.

[0108] Step S440: When a user rides in the target vehicle, the user's second human feature is collected and the permission parsing code is parsed locally to obtain the user's ride permissions.

[0109] The following describes the specific steps performed by the server when processing passenger information.

[0110] In step S410, the first human body feature of the user uploaded by the station terminal is received.

[0111] In this example implementation, the first human feature is the feature required for biometric identification. Biometric identification includes fingerprint recognition, face recognition, iris recognition, palm / fingerprint vein recognition, etc. The first human feature includes, for example, a face image, an eye image, a fingerprint image, and a voice. In one embodiment, the first human feature is the user's face image captured by a 3D camera at the platform terminal when the user makes a ride reservation at the platform terminal.

[0112] In step S420, the first human body feature is subjected to feature encoding processing to obtain the permission parsing code.

[0113] In this example implementation, the feature encoding processing method may include: performing feature extraction processing on the first human body feature according to the feature extraction strategy to extract feature information, or performing feature extraction processing on the first human body feature to extract feature information and then encrypting and encoding the ride permission information.

[0114] Obtaining the permission parsing code can preprocess the passenger information (i.e., the first human feature) into a permission parsing code in advance. At the same time, the preprocessed code can be used to parse the user's passenger permissions locally in the vehicle. This can speed up the passenger information processing efficiency and can also be used to quickly authorize the user's passenger permissions locally in the vehicle.

[0115] In one embodiment, step S420, which involves performing feature encoding processing on the first human body feature to obtain an access control code, includes: determining the feature type of the first human body feature; obtaining the feature extraction strategy corresponding to the feature type; and performing feature extraction processing on the first human body feature according to the feature extraction strategy to obtain first feature information as the access control code.

[0116] Feature types include face type, eye type, fingerprint type, and voice type. The corresponding feature extraction strategy is then obtained; for example, the feature extraction strategy for face type is the face feature extraction strategy, the feature extraction strategy for eye type is the iris pattern extraction strategy, and the feature extraction strategy for voice type is the voiceprint extraction strategy.

[0117] In this embodiment, the first human feature is processed by feature extraction according to the feature extraction strategy to obtain the first feature information as the permission parsing code. The first feature information can be extracted in advance on the server as the permission parsing code. Then, the permission parsing code indicates the predetermined ride permission information (that is, after the user successfully parses the permission when riding the vehicle, the user enjoys the predetermined ride permission, such as the permission to automatically allow the user to ride the vehicle by opening the gate).

[0118] In one embodiment, step S420, which involves performing feature encoding processing on the first human body feature to obtain an access control code, includes: performing feature extraction processing on the first human body feature to obtain first feature information; obtaining ride access control information matching the first feature information; and encrypting the ride access control information using the first feature information to obtain an encrypted encoding sequence as the access control code.

[0119] In this example, the server performs feature extraction processing on the first human body feature to obtain the first feature information. Then, it obtains the ride permission information matched by the first feature information (the ride permission information may include special permission information, such as seat information and temperature information). The server uses the first feature information to encrypt the ride permission information and obtains an encrypted encoding sequence as the permission parsing code. Then, the permission parsing code dynamically indicates the user's ride permission information (that is, after the user successfully parses the permission when taking the ride, the user enjoys the predetermined ride permission and the ride permission indicated by the ride permission information).

[0120] The method for obtaining the ride permission information matching the first feature information can be that the server queries a preset ride permission information table (which stores the correspondence between weather information and ride permission information) based on the weather information of the station terminal's location; or the server matches the user's preferred permission information, such as seat information and temperature information, from historical ride records based on the first feature information.

[0121] In step S430, the permission resolution code is sent to the station terminal, so that the station terminal can transmit the permission resolution code to the target vehicle. The target vehicle is obtained by the station terminal through vehicle matching processing using the collected user's ride reservation information.

[0122] In this example implementation, vehicle matching is used to determine the vehicle matching the user's travel request. The permission resolution code is then accurately sent to the matched vehicle, avoiding the vehicle storing permission resolution codes for users whose travel conditions are incompatible with its own. Taking a bus as an example, vehicle matching is performed using travel reservation information to determine the bus matching the user's travel request. In subsequent steps, the permission resolution code for each user at the bus stop can be sent to the matched bus, avoiding sending the permission resolution codes of all users at the bus stop to all buses. In this way, the server sends the permission resolution code to the matched vehicle through the station terminal. This avoids overloading the vehicle's storage capacity and allows for quick retrieval of the corresponding permission resolution code when a user boards the bus, further ensuring the efficiency of subsequent travel information processing.

[0123] In step S440, the user's second human body feature is collected when the user rides in the target vehicle, and the permission parsing code is parsed locally to obtain the user's ride permission.

[0124] In this example implementation, the server transmits the permission resolution code to the vehicle. When a user boards the vehicle, the vehicle can directly collect a second human feature to locally parse the permission resolution code, quickly obtaining the user's boarding permission. During the short boarding period, there is no need to upload the user's second human feature to the cloud for user identity resolution, etc. The boarding information processing efficiency is high and stable, allowing users to board quickly and effectively improving the user's boarding efficiency.

[0125] Among them, user ride permissions refer to the processing permissions a user has when riding in the vehicle. In one example, the predetermined ride permission information (i.e., after the user's permission is successfully resolved, the user enjoys the predetermined ride permissions, such as the permission to automatically allow the user to ride by opening the gate). In another example, the ride permission is a dynamic indication of the user's ride permission information by the permission resolution code, i.e., after the user's permission is successfully resolved, the user enjoys the predetermined ride permissions as well as the ride permissions indicated by the ride permission information (such as the user's suitable seating position and the temperature inside the vehicle when riding).

[0126] In this manner, based on steps S410 to S440, the server receives the permission parsing code obtained by the station terminal through pre-collected first human features and feature encoding processing. This allows the server to pre-authorize the user's corresponding travel permissions based on the feature encoding before boarding. Then, the server forwards the permission parsing code to the vehicle through the station terminal. When the user boards, the vehicle can efficiently parse the permission parsing code locally based on the collected second human features to obtain the user's travel permissions. Furthermore, since the vehicle is selected by the station terminal through pre-processing vehicle matching based on travel information, and the vehicle only receives the permission parsing code of the matched user, the efficiency of local retrieval and parsing is further guaranteed. This effectively improves the efficiency and stability of travel information processing, allowing the vehicle to efficiently and reliably obtain the user's travel permissions, thus enhancing the user's travel efficiency.

[0127] Figure 5 A flowchart illustrating a passenger information processing method according to an embodiment of this application is shown schematically. The subject executing this passenger information processing method may be a vehicle, for example... Figure 1 The vehicle shown is 103.

[0128] like Figure 5 As shown, the ride information processing method may include steps S510 to S540.

[0129] Step 510: Receive the user's permission parsing code transmitted by the platform terminal. The permission parsing code is obtained by the server through feature encoding processing of the user's first human feature collected by the platform terminal. The vehicle is obtained by the platform terminal through vehicle matching processing using the collected user's ride reservation information.

[0130] Step 520: Collect the user's second human body features while the user is riding in the vehicle;

[0131] Step 530: Perform feature extraction processing on the second human body feature to obtain the second feature information;

[0132] Step 540: The permission parsing code is parsed locally using the second feature information to obtain the user's travel permissions.

[0133] The following describes the specific steps involved in processing passenger information in a vehicle.

[0134] In step 510, the system receives the user's permission resolution code transmitted from the platform terminal. This permission resolution code is obtained by the server through feature encoding processing of the user's first human body feature collected by the platform terminal. The vehicle is obtained by the platform terminal through vehicle matching processing using the collected user's ride reservation information.

[0135] In this example implementation, the station terminal uploads the user's first human characteristics, such as facial images, eye images, fingerprint images, and voice, to the server. The server performs feature encoding processing on the first human characteristics, obtains the permission resolution code, and returns it to the station terminal. The station terminal uses the collected user's ride reservation information to perform vehicle matching processing, obtaining a vehicle matching the user's ride request. Then, the vehicle receives the user's permission resolution code transmitted by the station terminal. The vehicle has a lightweight storage capacity, resulting in low storage pressure. Furthermore, it can quickly retrieve the corresponding permission resolution code when the user boards the vehicle based on the small amount of stored permission resolution code, further ensuring the efficiency of subsequent vehicle ride information processing.

[0136] In step 520, the user's second human body features are collected while the user is riding in the vehicle.

[0137] In this example implementation, the second human feature is a human feature of the same feature type as the first human feature. For example, both the second and first human features are facial images. In this way, when a user boards a vehicle, the user's second human feature is collected, and in subsequent steps, the permission parsing code obtained based on the first human feature is used to accurately parse the user's vehicle boarding permissions.

[0138] In step 530, feature extraction processing is performed on the second human body feature to obtain the second feature information.

[0139] In this example implementation, the feature type of the second human body feature can be determined; the feature extraction strategy corresponding to the feature type can be obtained; the second human body feature can be processed by feature extraction according to the feature extraction strategy to obtain the second feature information as the permission parsing code.

[0140] Feature types include face type, eye type, fingerprint type, and voice type. The corresponding feature extraction strategy is then obtained; for example, the feature extraction strategy for face type is the face feature extraction strategy, the feature extraction strategy for eye type is the iris pattern extraction strategy, and the feature extraction strategy for voice type is the voiceprint extraction strategy.

[0141] In step 540, the permission parsing code is parsed locally using the second feature information to obtain the user's travel permissions.

[0142] In this example implementation, the second feature information corresponding to the same user has a similarity to the first feature information that is higher than a predetermined threshold. Therefore, the second feature information can be used to perform similarity analysis on the first feature information corresponding to the permission parsing code, and the permission parsing code can be parsed locally to quickly obtain the user's travel permission. During the short travel time, there is no need to upload the user's second human features to the cloud for user identity parsing, etc. The travel information processing efficiency is high and stable, allowing users to travel quickly and effectively improving the user's travel efficiency.

[0143] Among them, user ride permissions refer to the processing permissions a user has when riding in the vehicle. In one example, the predetermined ride permission information (i.e., after the user's permission is successfully resolved, the user enjoys the predetermined ride permissions, such as the permission to automatically allow the user to ride by opening the gate). In another example, the ride permission is a dynamic indication of the user's ride permission information by the permission resolution code, i.e., after the user's permission is successfully resolved, the user enjoys the predetermined ride permissions as well as the ride permissions indicated by the ride permission information (such as the user's suitable seating position and the temperature inside the vehicle when riding).

[0144] In one embodiment, the permission parsing code is the first feature information obtained by feature extraction processing of the first human body feature; step 540, the permission parsing code is performed locally through the second feature information to obtain the user's ride permission, including: calculating the similarity between the second feature information and the permission parsing code, performing local parsing processing on the permission parsing code to obtain a similarity value; obtaining the ride permission information matched by the similarity value as the user's ride permission.

[0145] The permission resolution code is the first feature information obtained by feature extraction processing of the first human body feature. Then, the similarity between the second feature information and the permission resolution code is calculated to obtain a similarity value. When the similarity value is higher than a predetermined threshold, it indicates that the user has booked a ride on the vehicle, and the ride permission information matched by the similarity value is the booked ride permission information (i.e., the user enjoys the booked ride permission after successful permission resolution, such as the permission to automatically allow the user to board the vehicle by opening a gate). In other words, the permission resolution code indicates the booked ride permission information. Conversely, when the similarity value for a user is lower than the predetermined threshold, it indicates that the user has not booked a ride on the vehicle, and the user is prompted to manually pay for the ride.

[0146] In one embodiment, the permission parsing code is an encrypted encoding sequence obtained by encrypting the ride permission information using the first feature information, and the first feature information is extracted from the first human body feature; step 540, performing local permission parsing processing on the permission parsing code using the second feature information to obtain the user's ride permission, includes: decrypting the permission parsing code using the second feature information to perform local parsing processing on the permission parsing code to obtain the decrypted ride permission information; and using the decrypted ride permission information as the user's ride permission.

[0147] The first feature information is used to encrypt the ride permission information, and the resulting encrypted encoding sequence is used as the permission parsing code. The ride permission information may contain special permission information, such as seat information and temperature information. Then, the permission parsing code dynamically indicates the user's ride permission information (that is, after the user successfully parses the permission when boarding the vehicle, the user enjoys the predetermined ride permission and the ride permission indicated by the ride permission information).

[0148] By using the second feature information to decrypt the permission parsing code and performing local parsing processing on the permission parsing code, if the similarity between the second feature information and the first feature information is higher than a predetermined threshold, the decrypted ride permission information can be obtained. This indicates that the user has reserved a ride on the vehicle. The decrypted ride permission information (which may include specific permission information, such as seat information and temperature information) is used as the user's ride permission, which can effectively improve user experience while improving ride efficiency. At this time, the permission parsing code dynamically indicates the user's ride permission information (i.e., after successful permission parsing, the user enjoys the reserved ride permission and the ride permission information indicated by the ride permission information).

[0149] In this manner, based on steps S510 to S540, the vehicle receives an access permission code. This access permission code is obtained by the server receiving the first human feature collected in advance by the station terminal and processing it through feature encoding. Before boarding, the server can authorize the user's corresponding boarding permissions based on the feature encoding. Then, the server forwards the access permission code to the vehicle through the station terminal. When the user boards, the vehicle can efficiently parse the access permission code locally based on the collected second human feature to obtain the user's boarding permissions. Furthermore, since the vehicle is selected by the station terminal through pre-processing vehicle matching based on boarding information, and the vehicle only receives the access permission code of the matched user, the efficiency of local retrieval and parsing is further guaranteed. Therefore, the efficiency and stability of boarding information processing are effectively improved, and the vehicle can efficiently and reliably obtain the user's boarding permissions locally, thus improving the user's boarding efficiency.

[0150] Based on the methods described in the above embodiments, the following examples will provide further detailed explanations.

[0151] Figure 6A flowchart illustrating passenger information processing in one scenario using an embodiment of this application is shown. In this scenario, users board the bus via facial recognition. The platform terminal is a passenger information collection terminal installed on a specific platform. The first human feature is the user's first facial image, and the second human feature is the user's second facial image.

[0152] See Figure 6 In this scenario, the vehicle is equipped with a vehicle-mounted facial recognition terminal device 601 and a 3D camera. The vehicle-mounted facial recognition terminal device carries an onboard client, which may include a facial recognition service module, an asynchronous deduction module, a facial feature database, and a Bluetooth synchronization service module. The platform terminal 602 carries a platform client and a 3D camera. The platform client may include a facial recognition service module, a ticketing service module, a facial feature database, a database update receiving service module, and a Bluetooth synchronization service module. The server 603 may include a cloud-based facial recognition service module, a deduction service module, a payment account service module, a backend facial database, and a database push service module.

[0153] The passenger information processing process in this scenario includes steps (1) to (5).

[0154] (1) The platform terminal 602 collects the user's ride reservation information and the first face image, and uploads the first face image to the server 603 so that the server 603 can return the permission parsing code obtained by feature encoding of the first human body feature.

[0155] The platform client can "collect the target face image of the user as the first face image when it detects that the user is making a reservation on the platform terminal".

[0156] Specifically, the ride reservation operation can be a user triggering the "ticket purchase service module" to purchase tickets.

[0157] The platform client can use the "face recognition service module" to call the 3D camera to collect the user's current face streaming media data. Then, it filters the current face streaming media data, and selects the target face image as the first face image of the user by comprehensively evaluating all face images in the current face streaming media data based on coefficient indicators such as face size, face angle, image contrast, image brightness and clarity. Then, the first face image is uploaded to the face recognition service module in server 602 through the face recognition service module.

[0158] The selection of the target face image is based on a comprehensive evaluation of factors such as face size, face angle, image contrast, image brightness, and clarity. This can be achieved by acquiring the face size, face angle, image contrast, image brightness, and clarity data corresponding to each face image in the current face streaming media data, then calculating a weighted sum of these data, and identifying the face image with the largest weighted sum as the target face image.

[0159] The platform client can "obtain the target vehicle information from the reservation result generated by the ride reservation operation when it receives the reservation result; when the target vehicle information is obtained, the target human body characteristics are used as the first human body characteristics, and the target vehicle information is used as the ride reservation information".

[0160] Users can make reservations through the "Ticketing Service Module." The reservation results can include the vehicle identification, target departure time, target route, and other travel target information, as well as the pre-purchased ticket information (i.e., pre-purchased tickets awaiting payment). Users can also make pre-purchases using facial recognition payment through the "Ticketing Service Module" and upload the pre-purchased ticket information to the "Payment Account Service Module (e.g., WeChat Account Service Module)" on server 603. The Payment Account Service Module automatically associates the "Payment Account Information" with the "Target Facial Feature Information (i.e., Preset Feature Information) extracted during the facial recognition payment operation."

[0161] (2) Server 603 receives the first face image of the user uploaded by the station terminal, performs feature encoding processing on the first face image to obtain the permission parsing code. The specific method of performing feature encoding processing on the first face image to obtain the permission parsing code is as follows: the first face image is processed for feature extraction according to the face feature extraction strategy to obtain the first face feature information as the permission parsing code.

[0162] Specifically, after receiving the first face image uploaded from the station terminal 602, the "cloud face recognition service module" in server 603 performs feature extraction on the first face image according to the face feature extraction strategy to obtain the first face feature information, and then encodes the first face image into a feature string information that uniquely identifies the user.

[0163] Facial feature extraction strategies can include existing knowledge-based representation methods and algebraic or statistical representation methods. Taking knowledge-based representation methods as an example, the shape description of facial organs and the distance characteristics between them are used as feature data for face classification. Distance characteristics can include Euclidean distance, curvature, and angle between feature points corresponding to facial organs. That is, a face is composed of facial organs such as eyes, nose, mouth, and chin. The geometric description of these facial organs and the structural relationships between them (Euclidean distance, curvature, and angle between feature points, etc.) can be used as the geometric features for recognizing faces (i.e., the extracted first facial feature information).

[0164] Furthermore, server 603 can compare the extracted first facial feature information with the "preset feature information" in the "backend facial database" to find the preset feature information with the highest similarity score, which is then used as the matching preset feature information (i.e., the target facial feature information extracted during facial recognition payment operations). Then, it obtains the "payment account information (e.g., WeChat account or WeChat Pay payment code related information)" corresponding to the matching preset feature information from the "payment account service module (e.g., WeChat account service module)," and sends the payment account information corresponding to the matching preset feature information along with the permission parsing code to the "database update receiving service module" in station terminal 602.

[0165] (3) The “Library Update Receiving Service Module” in the platform terminal 602 associates the received payment account information, permission parsing code and ride reservation information and stores them in the “Face Feature Library” in the platform terminal 602. The platform client also uses the ride reservation information to perform vehicle matching processing to obtain the vehicle matched with the user’s ride request. By setting the vehicle to automatically connect with the platform terminal via Bluetooth when it is within a specific distance range of the platform terminal (in this scenario, the connection is based on Bluetooth, and the data transmission efficiency is effectively guaranteed), the vehicle that has established a connection with the platform terminal can be identified as the vehicle within a specific distance range of the platform terminal. The target vehicle that matches the ride reservation information is identified from the vehicles and used as the vehicle matched with the user’s ride request.

[0166] Then, the platform client transmits the user's payment account information and permission parsing code to the vehicle-mounted client's Bluetooth synchronization service module carried in the vehicle-mounted facial recognition terminal device 601 on the vehicle, through the Bluetooth synchronization service module that matches the user's travel needs. The vehicle-mounted client then saves the received payment account information and permission parsing code in its facial feature database.

[0167] (4) When a user rides in the vehicle, the vehicle uses a 3D camera to capture a second face image and performs local parsing of the permission parsing code to obtain the user's ride permission.

[0168] In this scenario, the permission parsing code is the first facial feature information obtained by feature extraction processing of the first facial image. The facial recognition service module in the vehicle client can obtain the second facial feature information by performing feature extraction processing on the second facial image locally in the vehicle. The permission parsing code is then performed locally using the second facial feature information to obtain the user's ride permissions. Specifically, the similarity between the second facial feature information and the permission parsing code can be calculated to perform local parsing processing on the permission parsing code and obtain a similarity value. The ride permission information matched by the similarity value is then obtained as the user's ride permissions.

[0169] The similarity value matches the pre-defined ride-hailing permission information (i.e., the user enjoys pre-defined ride-hailing permissions after successful permission resolution, such as the permission to automatically allow the user to board by opening a gate). In other words, the permission resolution code indicates the pre-defined ride-hailing permission information. Conversely, if the similarity value for a user is lower than a pre-defined threshold, it indicates that the user did not book the ride, and the user will be prompted to manually pay for the ride.

[0170] (5) When the vehicle client parses and obtains the user's travel permission, the vehicle generates and sends a deduction instruction to the asynchronous deduction module in the server through the asynchronous deduction module in the vehicle client. When the asynchronous deduction module in the server receives the deduction instruction corresponding to the permission parsing code, it performs the deduction operation based on the pre-purchased ticket information. The deduction instruction contains the user's payment account information (such as WeChat account information or WeChat payment code, etc.), and the server can perform the deduction operation based on the payment account information. In one embodiment, when the asynchronous deduction module in the server receives the user's payment account information, it can obtain the user's relevant credit data from historical payment records. If the relevant credit data shows that the user's credit value is higher than the predetermined credit value, the deduction operation is performed.

[0171] In this scenario, based on the embodiments of this application, the passenger information in the vehicle and the station terminal is combined, and information is synchronized after a Bluetooth connection is established between the two. On the one hand, the advantage of offline recognition without network dependence is maintained when the vehicle performs permission resolution locally. On the other hand, the vehicle-side face device only stores the user face data of a single station, which is transmitted and erased through Bluetooth connection, reducing the dependence on the storage of devices in the vehicle. While ensuring the user's face recognition boarding experience, the storage cost of devices in the vehicle is reduced.

[0172] To facilitate better implementation of the passenger information processing method provided in this application, this application also provides a passenger information processing device based on the above-described passenger information processing method. The meanings of the terms used are the same as in the above-described passenger information processing method, and specific implementation details can be found in the descriptions in the method embodiments. Figure 7A block diagram of a passenger information processing device in a platform terminal according to an embodiment of this application is shown.

[0173] like Figure 7 As shown, the passenger information processing device 700 is applied to the station terminal. The device 700 may include a data acquisition module 710, an upload module 720, a matching module 730, and a parsing module 740.

[0174] The data acquisition module 710 can be used to collect the user's ride reservation information and first human body feature; the upload module 720 can be used to upload the first human body feature to the server, so that the server returns the permission parsing code obtained by feature encoding processing of the first human body feature; the matching module 730 can be used to perform vehicle matching processing using the ride reservation information to obtain the vehicle matched to the user's ride request; the parsing module 740 can be used to transmit the permission parsing code to the vehicle, so that when the user rides, the vehicle collects a second human body feature to perform local permission parsing processing on the permission parsing code to obtain the user's ride permission.

[0175] In some embodiments of this application, the matching module 730 includes: a search unit for searching for parked vehicles within a specific distance range of the platform terminal; a matching unit for determining a target vehicle from the parked vehicles that matches the ride reservation information; and a determination unit for matching the target vehicle as the vehicle matched to the user's ride request.

[0176] In some embodiments of this application, the matching module 730 includes: a table acquisition unit, used to acquire a vehicle information table, wherein the vehicle information table stores the driving information of vehicles associated with the platform terminal; and a table query unit, used to determine, from the vehicle information table, the vehicle corresponding to the driving information that matches the ride reservation information, as the vehicle matched to the user's ride request.

[0177] In some embodiments of this application, the acquisition module 710 includes: a first acquisition unit, used to acquire the target human features of the user when a user is detected to be making a ride reservation on the platform terminal; a second acquisition unit, used to obtain target vehicle information from the reservation result generated by the ride reservation operation when the reservation result is received; and a third acquisition unit, used to take the target human features as the first human features and the target vehicle information as the ride reservation information when the target vehicle information is obtained.

[0178] In some embodiments of this application, the ride reservation information includes pre-purchased ticket information, and the device 700 further includes: a deduction module, used to upload the pre-purchased ticket information to the server, so as to associate and store the permission parsing code with the pre-purchased ticket information in the server, and to perform a deduction operation according to the pre-purchased ticket information when the server receives a deduction instruction corresponding to the permission parsing code, wherein the deduction instruction is generated and sent to the server by the vehicle when it parses and obtains the user's ride permission.

[0179] In some embodiments of this application, the device 700 further includes: a first post-processing module, configured to mark the permission resolution code corresponding to the user as sent when receiving a first message sent by the vehicle, wherein the first message is generated and sent by the vehicle when it determines that the user's ride permission resolution is successful; and a second post-processing module, configured to continue vehicle matching processing to determine other vehicles matched to the user's ride request when receiving a second message sent by the vehicle, and send the permission resolution code to the other vehicles, wherein the second message is generated and sent by the vehicle when it determines that the user meets the ride failure conditions.

[0180] In this way, based on the passenger information processing device 700, the platform terminal collects the first human feature in advance, transmits it to the server to obtain the permission parsing code obtained by feature encoding processing, and can authorize the user's corresponding passenger permissions in advance based on the feature code before boarding. Then, the platform terminal forwards the permission parsing code to the vehicle, so that when the user boards the vehicle, the vehicle can efficiently parse the permission parsing code based on the collected second human feature to obtain the user's passenger permissions locally. Moreover, the vehicle is obtained by the platform terminal through pre-processing of passenger information and reasonable ride planning. The vehicle only receives the permission parsing code of the matched user, which can further ensure the efficiency of local retrieval and parsing on the vehicle. Thus, through the transmission and processing of passenger information between the server and the vehicle by the platform terminal, the efficiency and stability of passenger information processing are effectively improved, and the vehicle can efficiently and reliably obtain the user's passenger permissions locally, thereby improving the user's passenger efficiency.

[0181] Figure 8 A block diagram of a passenger information processing apparatus in a server according to an embodiment of this application is shown. Figure 8 As shown, the ride information processing device 800 is applied to a server. The device 800 may include a receiving module 810, an encoding processing module 820, and a parsing code transmission module 830.

[0182] The receiving module 810 can be used to receive the user's first human body feature uploaded by the station terminal; the encoding processing module 820 can be used to perform feature encoding processing on the first human body feature to obtain the permission parsing code; the parsing code transmission module 830 can be used to send the permission parsing code to the station terminal, so that the station terminal can transmit the permission parsing code to the target vehicle, wherein the target vehicle is obtained by the station terminal through vehicle matching processing using the collected user's ride reservation information, and the second human body feature of the user is collected by the target vehicle when the user rides the vehicle to perform local parsing processing on the permission parsing code to obtain the user's ride permission.

[0183] In some embodiments of this application, the encoding processing module 820 includes: a feature type determination unit, used to determine the feature type of the first human feature; a strategy matching unit, used to obtain the feature extraction strategy corresponding to the feature type; and a feature extraction unit, used to perform feature extraction processing on the first human feature according to the feature extraction strategy to obtain first feature information as the permission parsing code.

[0184] In some embodiments of this application, the encoding processing module 820 includes: a feature extraction unit, used to perform feature extraction processing on the first human body feature to obtain first feature information; an authorization acquisition unit, used to acquire ride authorization information matched by the first feature information; and an encryption encoding unit, used to encrypt the ride authorization information using the first feature information to obtain an encrypted encoding sequence as the authorization parsing code.

[0185] In this way, based on the passenger information processing device 800, the server can receive the permission parsing code obtained by pre-collecting the first human feature from the station terminal and processing the feature encoding. This allows the server to pre-authorize the user's corresponding passenger permissions based on the feature encoding before boarding. Then, the server forwards the permission parsing code to the vehicle through the station terminal. When a user boards, the vehicle can efficiently parse the permission parsing code locally based on the collected second human feature to obtain the user's passenger permissions. Furthermore, since the vehicle is selected by the station terminal through pre-processing passenger information and reasonable ride planning, the vehicle only receives the permission parsing code of the matched user, further ensuring the efficiency of local retrieval and parsing. Therefore, this effectively improves the efficiency and stability of passenger information processing, allowing the vehicle to efficiently and reliably obtain the user's passenger permissions, thus improving passenger travel efficiency.

[0186] Figure 9 A block diagram of a vehicle passenger information processing apparatus according to an embodiment of this application is shown.

[0187] like Figure 9As shown, the vehicle information processing device 900 is applied to a vehicle. The device 900 may include a code acquisition module 910, a second feature acquisition module 920, a second feature extraction module 930, and a local parsing module 940.

[0188] The parsing code acquisition module 910 can be used to receive the user's permission parsing code transmitted by the station terminal. The permission parsing code is obtained by the server performing feature encoding processing on the user's first human body feature collected by the station terminal. The vehicle is obtained by the station terminal using the collected user's ride reservation information for vehicle matching processing. The second feature acquisition module 920 can be used to collect the user's second human body feature when the user rides the vehicle. The second feature extraction module 930 can be used to perform feature extraction processing on the second human body feature to obtain second feature information. The local parsing module 940 can be used to perform local parsing processing on the permission parsing code using the second feature information to obtain the user's ride permission.

[0189] In some embodiments of this application, the permission parsing code is the first feature information obtained by feature extraction processing of the first human feature; the local parsing module 940 includes: a calculation parsing unit, used to calculate the similarity between the second feature information and the permission parsing code, so as to perform local parsing processing on the permission parsing code to obtain a similarity value; and a permission acquisition unit, used to acquire the ride permission information matched by the similarity value as the user's ride permission.

[0190] In some embodiments of this application, the permission parsing code is an encrypted encoding sequence obtained by encrypting the ride permission information using first feature information, wherein the first feature information is extracted from the first human body feature; the local parsing module 940 includes: a decryption parsing unit, used to decrypt the permission parsing code using the second feature information, so as to perform local parsing processing on the permission parsing code to obtain the decrypted ride permission information; and a permission determination unit, used to use the decrypted ride permission information as the user's ride permission.

[0191] In this way, based on the passenger information processing device 900, the vehicle can receive an access permission code. This access permission code is obtained by the server receiving the first human feature collected in advance by the station terminal and processing the feature encoding. Before boarding, the user's corresponding boarding permissions can be authorized based on the feature encoding. Then, the server forwards the access permission code to the vehicle through the station terminal. When the user boards, the vehicle can efficiently parse the access permission code locally based on the collected second human feature to obtain the user's boarding permissions. Furthermore, since the vehicle is selected by the station terminal through pre-processing passenger information and reasonable ride planning, the vehicle only receives the access permission code of the matched user, further ensuring the efficiency of local retrieval and parsing. Therefore, the efficiency and stability of passenger information processing are effectively improved, and the vehicle can efficiently and reliably obtain the user's boarding permissions locally, thus improving the user's boarding efficiency.

[0192] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0193] Furthermore, embodiments of this application also provide an electronic device, which can be a terminal or a server, such as... Figure 10 As shown, it illustrates a structural schematic diagram of the electronic device involved in the embodiments of this application, specifically:

[0194] The electronic device may include components such as a processor 1001 with one or more processing cores, a memory 1002 with one or more computer-readable storage media, a power supply 1003, and an input unit 1004. Those skilled in the art will understand that... Figure 10 The electronic device structure shown does not constitute a limitation on the electronic device and may include more or fewer components than shown, or combine certain components, or have different component arrangements. Wherein:

[0195] The processor 1001 is the control center of the electronic device. It connects to various parts of the computer device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 1002, and by calling data stored in the memory 1002, it performs various functions of the computer device and processes data, thereby providing overall monitoring of the electronic device. Optionally, the processor 1001 may include one or more processing cores; preferably, the processor 1001 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user page, and application programs, and the modem processor mainly handles wireless communication. It is understood that the aforementioned modem processor may not be integrated into the processor 1001.

[0196] The memory 1002 can be used to store software programs and modules. The processor 1001 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002. The memory 1002 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, application programs required for at least one function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device. Accordingly, the memory 1002 may also include a memory controller to provide the processor 1001 with access to the memory 1002.

[0197] The electronic device also includes a power supply 1003 that supplies power to various components. Preferably, the power supply 1003 can be logically connected to the processor 1001 through a power management system, thereby enabling functions such as charging, discharging, and power consumption management through the power management system. The power supply 1003 may also include one or more DC or AC power supplies, recharging systems, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components.

[0198] The electronic device may also include an input unit 1004, which can be used to receive input digital or character information, and generate keyboard, mouse, joystick, optical or trackball signal inputs related to user settings and function control.

[0199] Although not shown, the electronic device may also include a display unit, etc., which will not be described in detail here. Specifically, in this embodiment, the processor 1001 in the electronic device will load the executable files corresponding to the processes of one or more applications into the memory 1002 according to the following instructions, and the processor 1001 will run the applications stored in the memory 1002 to realize various functions, such as the processor 1001 can perform: collecting the user's ride reservation information and a first human feature; uploading the first human feature to the server so that the server returns the permission resolution code obtained by feature encoding processing of the first human feature; using the ride reservation information to perform vehicle matching processing to obtain the vehicle matched with the user's ride request; transmitting the permission resolution code to the vehicle so that when the user rides, the vehicle collects a second human feature to locally parse the permission resolution code to obtain the user's ride permission.

[0200] In one embodiment, the processor 1001 can perform the following actions: receiving a user's first human body feature uploaded by a station terminal; performing feature encoding processing on the first human body feature to obtain an access permission code; sending the access permission code to the station terminal so that the station terminal transmits the access permission code to a target vehicle, wherein the target vehicle is obtained by the station terminal through vehicle matching processing using the user's collected ride reservation information; and, when the user rides the vehicle, the target vehicle collects the user's second human body feature to perform local parsing processing on the access permission code to obtain the user's ride permission.

[0201] In one embodiment, the processor 1001 may execute: receiving a user's permission resolution code transmitted by a station terminal, wherein the permission resolution code is obtained by the server performing feature encoding processing on the user's first human body feature collected by the station terminal, and the vehicle is obtained by the station terminal performing vehicle matching processing using the collected user's ride reservation information; collecting the user's second human body feature when the user boards the vehicle; performing feature extraction processing on the second human body feature to obtain second feature information; and performing local parsing processing on the permission resolution code using the second feature information to obtain the user's ride permission.

[0202] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be performed by a computer program, or by a computer program controlling related hardware. The computer program can be stored in a computer-readable storage medium and loaded and executed by a processor.

[0203] Therefore, embodiments of this application also provide a storage medium storing a computer program that can be loaded by a processor to execute the steps in any of the methods provided in embodiments of this application.

[0204] The storage medium may include: read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0205] Since the computer program stored in the storage medium can execute the steps of any of the methods provided in the embodiments of this application, the beneficial effects that the methods provided in the embodiments of this application can achieve can be realized. For details, please refer to the previous embodiments, which will not be repeated here.

[0206] According to one aspect of this application, a computer program product or computer program is provided, comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in the various optional implementations of the above embodiments of this application.

[0207] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0208] It should be understood that this application is not limited to the embodiments described above and shown in the accompanying drawings, but various modifications and changes can be made without departing from its scope.

Claims

1. A method for processing passenger information, characterized in that, Applied to a station terminal, the method includes: Collect users' ride-hailing reservation information and first-person facial features; The first human body feature is uploaded to the server so that the server returns an access control code obtained by feature encoding the first human body feature. The access control code is a first feature information extracted from the first human body feature, or the access control code is obtained by encrypting the ride access information using the first feature information. The ride access information matches the first feature information. The vehicle matching process is performed using the ride reservation information to obtain the vehicle that matches the user's ride request. The permission parsing code is transmitted to the vehicle so that when the user boards the vehicle, the vehicle collects a second human feature to locally parse the permission parsing code and obtain the user's boarding permissions. The boarding permissions include predetermined boarding permissions and boarding permissions indicated by the boarding permission information. The predetermined permissions include the permission to automatically allow the user to board the vehicle by opening the gate. The boarding permissions indicated by the boarding permission information include the user's suitable boarding location and the vehicle interior temperature during boarding.

2. The method according to claim 1, characterized in that, The process of matching vehicles using the ride reservation information to obtain the vehicle matching the user's ride request includes: Search for parked vehicles located within a specific distance range of the platform terminal; From the parked vehicles, identify the target vehicle that matches the ride reservation information; The target vehicle is selected as the vehicle that matches the user's travel needs.

3. The method according to claim 1, characterized in that, The process of matching vehicles using the ride reservation information to obtain the vehicle matching the user's ride request includes: Obtain the vehicle information table, which stores the driving information of the vehicles associated with the platform terminal; From the parking vehicle information table, determine the parking vehicle corresponding to the driving information that matches the ride reservation information, and use it as the vehicle matched to the user's ride request.

4. The method according to claim 1, characterized in that, The collection of users' ride reservation information and first human body characteristics includes: When a user is detected making a reservation for a ride at the platform terminal, the user's target human characteristics are collected. When the reservation result generated by the ride reservation operation is received, the target vehicle information is obtained from the reservation result; When the target vehicle information is obtained, the target human body feature is used as the first human body feature, and the target vehicle information is used as the ride reservation information.

5. The method according to any one of claims 1-4, characterized in that, The travel reservation information includes pre-purchased ticket information, and the method further includes: The pre-purchased ticket information is uploaded to the server so that the permission parsing code is associated with and stored on the server. When the server receives the deduction instruction corresponding to the permission parsing code, it performs a deduction operation based on the pre-purchased ticket information. The deduction instruction is generated and sent to the server by the vehicle when it parses and obtains the user's travel permission.

6. The method according to any one of claims 1-4, characterized in that, The method further includes: When the first message sent by the vehicle is received, the permission resolution code corresponding to the user is marked as sent. The first message is generated and sent by the vehicle when it determines that the user's ride permission has been successfully resolved. Upon receiving the second message from the vehicle, the vehicle matching process continues to determine other vehicles that match the user's travel needs, and the permission resolution code is sent to the other vehicles. The second message is generated and sent by the vehicle when it determines that the user meets the conditions for travel failure.

7. A method for processing passenger information, characterized in that, Applied to a server, the method includes: The first human body feature of the user uploaded by the receiving station terminal; The first human body feature is subjected to feature encoding processing to obtain an authorization parsing code, wherein the authorization parsing code is a first feature information extracted from the first human body feature, or the authorization parsing code is obtained by encrypting the ride authorization information using the first feature information, and the ride authorization information matches the first feature information; The permission resolution code is sent to the platform terminal so that the platform terminal can transmit the permission resolution code to the target vehicle, which is obtained by the platform terminal through vehicle matching processing using the collected user's ride reservation information. When the user boards the vehicle, the target vehicle collects the user's second human feature and performs local parsing processing on the permission parsing code to obtain the user's boarding permissions. The boarding permissions include predetermined boarding permissions and boarding permissions indicated by the boarding permission information. The predetermined permissions include the permission to automatically allow the user to board the vehicle by opening the gate. The boarding permissions indicated by the boarding permission information include the user's suitable boarding location and the vehicle interior temperature during boarding.

8. The method according to claim 7, wherein performing feature encoding processing on the first human body feature to obtain the permission parsing code includes: Determine the feature type of the first human body feature; Obtain the feature extraction strategy corresponding to the feature type; The first human body feature is processed according to the feature extraction strategy to obtain the first feature information as the permission parsing code.

9. The method according to claim 7, wherein performing feature encoding processing on the first human body feature to obtain the permission parsing code includes: The first human body feature is subjected to feature extraction processing to obtain the first feature information; Obtain the ride permission information matched by the first feature information; The ride permission information is encrypted using the first feature information to obtain an encrypted encoding sequence as the permission parsing code.

10. A method for processing passenger information, characterized in that, Applied to vehicles, the method includes: The system receives a user's permission resolution code transmitted from the platform terminal. The permission resolution code is obtained by the server through feature encoding processing of the user's first human feature collected by the platform terminal. The vehicle is obtained by the platform terminal through vehicle matching processing using the collected user's ride reservation information. The permission resolution code is either first feature information extracted from the first human feature or the permission resolution code is obtained by encrypting ride permission information using the first feature information. The ride permission information matches the first feature information. When the user is riding in the vehicle, the user's second human body characteristics are collected; The second human body feature is subjected to feature extraction processing to obtain the second feature information; The user's travel permissions are obtained by performing local parsing processing on the permission parsing code using the second feature information. The travel permissions include predetermined travel permissions and travel permissions indicated by the travel permission information. The predetermined permissions include the permission to automatically allow the user to board the vehicle by opening the gate. The travel permissions indicated by the travel permission information include the user's suitable boarding location and the vehicle interior temperature during the ride.

11. The method according to claim 10, wherein the permission parsing code is the first feature information obtained by feature extraction processing of the first human body feature; The step of locally parsing the permission parsing code using the second feature information to obtain the user's travel permissions includes: Calculate the similarity between the second feature information and the permission parsing code, and perform local parsing processing on the permission parsing code to obtain a similarity value; Obtain the ride permission information matched by the similarity value, and use it as the user's ride permission.

12. The method according to claim 10, wherein the permission parsing code is an encrypted encoding sequence obtained by encrypting the ride permission information using first feature information, wherein the first feature information is extracted from the first human body feature; The step of performing local permission parsing processing on the permission parsing code using the second feature information to obtain the user's travel permissions includes: The permission parsing code is decrypted using the second feature information, and the permission parsing code is parsed locally to obtain the decrypted travel permission information; The decrypted ride permission information will be used as the user's ride permissions.

13. A passenger information processing device, characterized in that, The device, applied to a station terminal, includes: The data collection module is used to collect users' ride reservation information and first human characteristics; An upload module is used to upload the first human body feature to a server so that the server returns a permission resolution code obtained by feature encoding the first human body feature. The permission resolution code is first feature information extracted from the first human body feature, or the permission resolution code is obtained by encrypting the ride permission information using the first feature information, and the ride permission information matches the first feature information. The matching module is used to perform vehicle matching processing using the ride reservation information to obtain the vehicle matched to the user's ride request. The parsing module is used to transmit the permission parsing code to the vehicle, so that when the user boards the vehicle, the vehicle collects a second human feature to perform local permission parsing processing on the permission parsing code to obtain the user's boarding permissions. The boarding permissions include predetermined boarding permissions and boarding permissions indicated by the boarding permission information. The predetermined permissions include the permission to automatically allow the user to board the vehicle by opening the gate. The boarding permissions indicated by the boarding permission information include the user's suitable boarding location and the vehicle interior temperature during boarding.

14. An electronic device, characterized in that, include: Memory, which stores computer-readable instructions; A processor reads computer-readable instructions stored in memory to execute the method according to any one of claims 1 to 12.

15. A storage medium, characterized in that, It stores computer-readable instructions that, when executed by the processor of a computer, cause the computer to perform the method described in any one of claims 1 to 12.

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