An artificial intelligence-based pricing method and system

Abstract

This invention relates to the field of intelligent billing equipment technology, specifically to a pricing method and system based on artificial intelligence. This invention provides an intelligent AI fare meter and its implementation method. Based on the basic pricing module's compatibility with traditional pricing rules (traditional JT / T905-2014 fare meter functions and JJF1604-2016 syllabus compliance requirements), it improves interaction efficiency through an AI voice interaction module. It innovatively uses the driver's mobile phone's shared network to replace a separate wireless module for cloud-based remote control module interaction, enabling stable remote fare adjustment. Using the driver's mobile phone's shared network to replace a separate wireless module for cloud interaction also reduces hardware costs and data traffic fees, while ensuring the stability and continuity of cloud data synchronization, further improving the device's applicability and cost-effectiveness.

Description

Technical Field

[0001] This invention relates to the field of intelligent billing equipment technology, and specifically to a pricing method and system based on artificial intelligence. Background Technology

[0002] Existing fare meters suffer from the following main drawbacks: First, they are limited by traditional functions. Traditional fare meters based on the JT / T905-2014 standard and those based on the JJF1604-2016 syllabus rely on purely manual operation, with data interaction limited to basic serial port output, making them unsuitable for intelligent scenarios. Second, they lack intelligent interaction capabilities, offering no AI interaction, resulting in cumbersome operation, poor user experience, and low transparency of billing information. Third, they are inefficient in adjusting rates: rate adjustments require manual on-site operation, which is time-consuming, labor-intensive, and prone to errors. Fourth, cloud interaction relies on a separate network: existing fare meters supporting cloud functions require a built-in independent 4G / 5G module, increasing hardware costs (approximately 15%-20% of the total equipment cost) and incurring separate data charges; if the device's environment lacks an independent network signal, cloud synchronization and remote price adjustment functions are completely ineffective, limiting their applicability.

[0003] Therefore, there is an urgent need for a pricing method that is compatible with traditional pricing functions, has intelligent interactive functions, and has stable network communication. Summary of the Invention

[0004] The purpose of this invention is to provide a pricing method and system based on artificial intelligence, which integrates traditional billing functions, AI voice interaction and cloud-based remote pricing functions, and can achieve cloud interaction by sharing the network with the driver's mobile phone. It is applicable to billing in multiple scenarios such as vehicle (taxi / ride-hailing) and site services (warehousing and handling / shared equipment).

[0005] In a first aspect, the present invention provides an artificial intelligence-based pricing method, which is based on an AI pricing control module. The AI ​​pricing control module is communicatively connected to the vehicle's basic pricing module, AI voice interaction module, network sharing module, local storage module, and vehicle controller. The method includes: In response to receiving a power-on success signal from the vehicle controller, an automatic pairing signal is sent to the network sharing module, and a communication connection is established with a mobile phone within the scanning range that meets the pairing requirements after encryption and verification through the network sharing module; In response to receiving a successful connection signal from the network sharing module, a communication connection is established with the cloud remote control module using the mobile phone's shared network; In response to receiving a price adjustment signal from the cloud-based remote control module, a rate adjustment signal obtained from parsing the price adjustment signal is sent to the basic pricing module; Upon receiving the rate adjustment completion signal from the basic pricing module, a price adjustment success signal is sent back to the cloud remote control module; In response to receiving a trip start signal from the AI ​​voice interaction module when it recognizes the start fare wake-up word, a fare start signal is sent to the basic fare calculation module; In response to receiving a trip end signal sent by the AI ​​voice interaction module when it recognizes the end-of-pricing wake-up word, a pricing end signal is sent to the basic pricing module; In response to receiving the pricing result signal from the basic pricing module, the pricing order data obtained from parsing the pricing result signal is stored in the local storage module and synchronized to the cloud remote control module.

[0006] In a preferred embodiment, the AI ​​pricing control module is also communicatively connected to the vehicle's central control display module, and the pricing method further includes: In response to receiving a connection success signal from the network sharing module, a connection success display signal and a connection success broadcast signal are sent to the central control display module and the AI ​​voice interaction module, respectively. In response to receiving the rate adjustment completion signal from the basic pricing module, the system sends the latest rate display signal and the latest rate broadcast signal to the central control display module and the AI ​​voice interaction module, respectively.

[0007] In a preferred embodiment, the network sharing module includes a Bluetooth module and a Wi-Fi hotspot module; When receiving price adjustment signals from the cloud remote control module, sending price adjustment success signals back to the cloud remote control module, and synchronizing pricing order data to the cloud remote control module, the amount of data transmitted is less than the preset traffic threshold, and the network is shared with the mobile phone using the Bluetooth module. When receiving firmware upgrade packages from the cloud-based remote control module and sending pricing logs generated from all daily pricing orders to the cloud-based remote control module, if the amount of data transmitted exceeds the preset traffic threshold, the device will share the network with the mobile phone using a Wi-Fi hotspot module.

[0008] In a preferred embodiment, the AI ​​pricing control module is also communicatively connected to the vehicle's central control display module; When a communication connection is established between the network sharing module and a mobile phone that meets the pairing requirements within the scanning range after encryption verification, in response to receiving a connection failure signal from the network sharing module, a connection guidance broadcast signal is sent to the AI ​​voice interaction module. When establishing a communication connection with a mobile phone that meets the pairing requirements within the scanning range via the network sharing module after encryption verification, the verification code generated on the central control display module needs to be entered into the mobile phone to confirm that the encryption verification is successful.

[0009] In a preferred embodiment, after receiving a connection success signal from the network sharing module, in response to receiving a connection interruption signal from the network sharing module, the transmission data waiting to be synchronized to the cloud remote control module is cached in the vehicle's local storage module in preparation for re-establishing a communication connection with the mobile phone.

[0010] In a preferred embodiment, during the period between receiving the trip start signal and the trip end signal, the method further includes: In response to receiving a price increase signal from the AI ​​voice interaction module when it recognizes the additional fee wake word, the system sends an additional fee signal, which is parsed from the price increase signal, to the basic pricing module. In response to receiving the current fee query signal from the AI ​​voice interaction module when it recognizes the fee query wake-up word, a fee detail query signal is sent to the basic pricing module. In response to receiving the fee detail signal from the basic pricing module, a fee detail list broadcast signal obtained by parsing the fee detail list signal is sent to the AI ​​voice interaction module.

[0011] In a preferred embodiment, during the period between receiving the trip start signal and the trip end signal, the method further includes: After receiving the trip start signal, the system acquires weather and mileage signals sent by the cloud remote control module at preset mileage and preset time intervals, and sends weather and mileage broadcast signals, respectively parsed from the weather and mileage signals, to the AI ​​voice interaction module.

[0012] In a preferred embodiment, the AI ​​pricing control module is also communicatively connected to the vehicle's central control display module, and the method further includes: In response to receiving a connection success signal from the network sharing module, a connection success display signal is sent to the central control display module; In response to receiving the rate adjustment completion signal sent by the basic pricing module, the latest rate display signal obtained by parsing the rate adjustment completion signal is sent to the central control display module; In response to receiving the pricing result signal from the basic pricing module, a pricing order display signal obtained by parsing the pricing result signal is sent to the central control display module.

[0013] In a preferred embodiment, the method further includes: In response to receiving the order synchronization completion signal from the cloud remote control module, an order printing signal is sent to the basic pricing module.

[0014] Secondly, the present invention provides an artificial intelligence-based pricing system, which includes an AI pricing control module for executing the pricing method, wherein the AI ​​pricing control module is communicatively connected to the vehicle's basic pricing module, AI voice interaction module, network sharing module, local storage module, and vehicle controller.

[0015] Compared with the prior art, the present invention has the following beneficial effects: This invention provides an intelligent AI fare meter and its implementation method. Based on the basic fare meter module's compatibility with traditional fare meter rules (traditional JT / T905-2014 fare meter functions and JJF1604-2016 syllabus compliance requirements), it further enhances interaction efficiency through an AI voice interaction module. It innovatively uses the driver's mobile phone's shared network to replace the independent wireless module for cloud-based remote control module interaction, enabling stable remote fare adjustment. Using the driver's mobile phone's shared network to replace the independent wireless module for cloud interaction also reduces hardware costs and data traffic fees, while ensuring the stability and continuity of cloud data synchronization, further improving the device's applicability and cost-effectiveness. Attached Figure Description

[0016] Figure 1 A flowchart illustrating an artificial intelligence-based pricing method provided in this embodiment; Figure 2 This is a block diagram of an artificial intelligence-based pricing system provided in this embodiment. Detailed Implementation

[0017] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0018] Combination Figure 1 This embodiment provides an artificial intelligence-based pricing method, which is based on an AI pricing control module. The AI ​​pricing control module uses an intelligent processor as its computing core to coordinate the linkage of traditional functions, AI functions, remote pricing, and mobile network sharing. The intelligent processor can be, for example, an RK3588 processor (quad-core A55, 2.0GHz), 2GB LPDDR4 memory + 16GB eMMC flash memory. The AI ​​pricing control module is communicatively connected to the vehicle's basic pricing module, central control display module, AI voice interaction module, network sharing module, local storage module, and vehicle controller.

[0019] The basic pricing module is compatible with the functions of the JT / T905-2014 pricing meter and the compliance requirements of the JJF1604-2016 syllabus. It supports three-stage billing: "basic fee + mileage fee + time fee" and can preset unit prices for multiple modes such as daytime / nighttime / long-distance (complying with the multi-scenario requirements of the JJF1604-2016 syllabus). The basic pricing module supports physical button control for "IC / single trip / pause" billing and can encrypt and store billing data (anti-tampering, complying with the requirements of the JJF1604-2016 syllabus). It outputs order receipts through the RS232 interface and supports synchronization of order details with the cloud remote control module.

[0020] The central control display module uses an LCD / LED screen to display mileage, duration, cost, details of additional items, current rate tier, and mobile network connection status (e.g., "Driver's mobile network is connected"). The central control display module has a physical operation module: "IC / One-way / Pause" button (compatible with manual operation according to JJF1604-2016 outline), 2.4-inch LCD screen (320×240), and 3 physical buttons.

[0021] The AI ​​voice interaction module includes a voice input module and a voice output module: the voice input module includes a high-sensitivity microphone (clear sound pickup when noise ≤60dB), and in this embodiment, a MEMS microphone (signal-to-noise ratio ≥60dB) is used; the voice output module includes a speaker (supporting command feedback, remote price adjustment prompts, and mobile network connection guidance broadcasts), and in this embodiment, a 1W speaker is used.

[0022] This embodiment eliminates the independent 4G / 5G module and adds a network sharing module for sharing the network with the mobile phone. The network sharing module supports both Bluetooth and Wi-Fi hotspot connections, establishing communication with the driver's mobile phone and enabling information exchange with the cloud-based remote control module via the phone's shared network (4G / 5G / Wi-Fi). Compared to devices with independent 4G / 5G modules, hardware costs are reduced by 18%; normal cloud interaction is achieved via the mobile phone's 5G network in underground parking garages without independent network signals; and it is compatible with existing JT / T905-2014 and JJF1604-2016 functionalities without conflict.

[0023] The local storage module uses embedded flash memory, which can cache the most recent 2000 order data (compatible with JT / T905-2014 function), and encrypts and stores AI recognition logs, local rate backup library and mobile network connection configuration information (such as the Bluetooth name of paired mobile phones). This embodiment uses 128MB SPI flash memory (local cache + rate backup + connection configuration).

[0024] The pricing method includes: Step S1: In response to receiving the power-on success signal from the vehicle controller, send an automatic pairing signal to the network sharing module and establish a communication connection with a mobile phone within the scanning range that meets the pairing requirements after encryption and verification through the network sharing module; When a communication connection is established between the network sharing module and a mobile phone within the scanning range that meets the pairing requirements after encryption verification, the system sends a connection guidance broadcast signal to the AI ​​voice interaction module in response to receiving a connection failure signal from the network sharing module. Furthermore, when establishing a communication connection between the network sharing module and a mobile phone within the scanning range that meets the pairing requirements after encryption verification, the verification code (6-digit random verification code) generated on the central control display module needs to be entered into the mobile phone to confirm successful encryption verification.

[0025] To illustrate the actual operation, after the vehicle is powered on, it automatically scans for nearby paired driver phones (based on locally stored Bluetooth names). If no connection is detected, the AI ​​voice interaction module provides voice guidance (such as "Please turn on your phone's Bluetooth / Wi-Fi hotspot to pair with the meter") and the LCD / LED screen displays pairing steps (such as "1. Turn on Bluetooth on your phone; 2. Search for 'AI meter-XXX'; 3. Click to pair"), simplifying the connection process.

[0026] Step S2: In response to receiving the connection success signal from the network sharing module, a communication connection is established with the cloud remote control module using the mobile phone's shared network; in this embodiment, in response to receiving the connection success signal from the network sharing module, a connection success display signal and a connection success broadcast signal are sent to the central control display module and the AI ​​voice interaction module, respectively.

[0027] After receiving a successful connection signal from the network sharing module, and in response to a connection interruption signal from the same module, the data awaiting synchronization to the cloud remote control module is cached in the local storage module for re-establishing communication with the mobile phone. This embodiment monitors the connection status and network signal strength with the mobile phone in real time. If the connection is interrupted (e.g., the phone is moved away), a voice prompt is immediately issued via the AI ​​voice interaction module (e.g., "Mobile network has been disconnected, please bring it closer to pair again"), and the data to be synchronized is cached locally. When the connection is restored, the cached data is automatically resumed to ensure no data loss. This embodiment has undergone network connection testing, simulating 100 Bluetooth / Wi-Fi pairings with the mobile phone, achieving a success rate of ≥99%; simulating 10 network interruptions (phone moved away), the cached data resumed successfully after recovery, achieving a 100% success rate. The cloud-based remote control module has a pre-set "rate template library" in its backend, supporting the creation of multiple rate schemes (such as "weekday template", "holiday premium template", and "nighttime surcharge template"). Each template includes core parameters such as "basic fee, mileage unit price, time unit price, and default amount of surcharge" (fully matching the multi-scenario billing requirements of JJF1604-2016). Merchants select the target device (single / multiple / full) through the backend of the cloud-based remote control module and send a "rate template switching instruction" or "custom rate parameter instruction" to the AI ​​pricing control module of the target device. The instruction is transmitted encrypted via 4G / 5G / Wi-Fi, and the meter automatically verifies the integrity of the instruction after receiving it (to prevent data packet loss). The backend of the cloud-based remote control module has three levels of permissions (administrator / operator / viewer). Only the administrator can initiate remote price adjustments. Price adjustment records (device ID, price adjustment time, old and new rates, operator) are stored encrypted throughout the process and are traceable (compliant with the requirements of JJF1604-2016). Merchants can select target devices (single / multiple / full) through the cloud-based remote control module and send price adjustment signals ("rate template switching command" or "custom rate parameter command"). The command is transmitted encrypted via 4G / 5G / Wi-Fi. After receiving the command, the meter automatically verifies its integrity (to prevent data loss). Step S3: In response to receiving the price adjustment signal sent by the cloud remote control module, send the rate adjustment signal obtained from parsing the price adjustment signal to the basic pricing module; This embodiment has undergone cloud interaction testing: by sharing the network via mobile phone, remote price adjustment commands were sent to 10 devices, with a response time of ≤5 seconds (including connection establishment time) and a success rate of ≥98%; 100 pricing order data were uploaded, with a data consumption of ≤100KB.

[0028] Step S4: In response to receiving the rate adjustment completion signal sent by the basic pricing module, send a price adjustment success signal to the cloud remote control module; in response to receiving the rate adjustment completion signal sent by the basic pricing module, send the latest rate display signal and the latest rate broadcast signal to the central control display module and the AI ​​voice interaction module respectively.

[0029] After the basic pricing module sends a signal that the rate adjustment is complete, the AI ​​pricing control module automatically backs up the adjusted current rate to the "local rate backup library" in the local storage module. After the basic pricing module completes the rate update, it displays "Rate updated" on the central control display module and announces via voice through the AI ​​voice interaction module (e.g., "Switched to holiday rates, basic fee adjusted to 10 yuan, mileage fee 2.5 yuan / km"). It automatically sends a "price adjustment successful" status to the cloud. If the update fails (e.g., parameter error), it immediately restores the original rate in the "local rate backup library" and sends a message "Price adjustment failed, please check the command". Step S5: In response to receiving the trip start signal from the AI ​​voice interaction module when it recognizes the start pricing wake-up word, send a pricing start signal to the basic pricing module; Step S6: In response to receiving the trip end signal sent by the AI ​​voice interaction module when it recognizes the end-of-pricing wake-up word, send a pricing end signal to the basic pricing module; Step S7: In response to receiving the pricing result signal from the basic pricing module, store the pricing order data obtained from parsing the pricing result signal in the local storage module and synchronize it to the cloud remote control module; During the period between receiving the trip start signal and the trip end signal, the method further includes: in response to receiving a surcharge signal fed back by the AI ​​voice interaction module when it recognizes an additional charge wake-up word, sending an additional charge signal parsed from the surcharge signal to the basic pricing module; in response to receiving a current charge query signal fed back by the AI ​​voice interaction module when it recognizes a charge query wake-up word, sending a charge detail query signal to the basic pricing module; and in response to receiving a charge detail signal fed back by the basic pricing module, sending a charge detail list broadcast signal parsed from the charge detail list signal to the AI ​​voice interaction module. The AI ​​voice interaction module supports custom wake words (such as "meter"), and after wake-up, it supports the recognition of ≥15 core billing commands (such as "start billing", "add highway toll of 20 yuan", "query current fee"), with a command recognition accuracy of ≥98% and a response latency of ≤0.8 seconds. After execution, the results are provided via voice feedback. The AI ​​voice interaction module can automatically extract "billing key terms" from speech / text based on NLP semantic understanding algorithms, including fee-related terms (highway toll, parking fee), numerical terms (amount, mileage, duration), and mode-related terms (daytime mode, long-distance mode). After extraction, it automatically associates "term + value," triggering voice confirmation when recognition is abnormal. During the period between receiving the trip start signal and the trip end signal, the method further includes: after receiving the trip start signal, acquiring weather and mileage signals sent by the cloud remote control module at preset mileage and preset duration intervals, and sending weather and mileage broadcast signals, respectively parsed from the weather and mileage signals, to the AI ​​voice interaction module.

[0030] The AI ​​voice interaction module also supports contextual voice broadcasting (broadcasting trip data every 5 kilometers / 10 minutes, and prompting for switching to night mode), supports simple casual conversation, and merchants can customize the broadcasting frequency and tone, or turn off this function.

[0031] Specifically, in this embodiment, the AI ​​voice interaction module uses the built-in TTS function to provide voice prompts when not connected to the network; when connected to the network, voice interaction instructions or help-related content is provided by building a private RAG vector knowledge base and a large language model (such as Qwen), while other emotional support-related content is provided by accessing existing AI models on the network.

[0032] Step S8: In response to receiving the order synchronization completion signal sent by the cloud remote control module, send an order printing signal to the basic pricing module.

[0033] The network sharing module includes a Bluetooth module (BLE 5.0, model CC2640) and a Wi-Fi hotspot module (model ESP8266); replacing the original independent 4G / 5G module, it serves as the core component of the mobile network sharing interface. This embodiment develops a traffic judgment algorithm (triggers Wi-Fi hotspot switching when the data volume > 500KB). When receiving price adjustment signals from the cloud remote control module, sending price adjustment success signals back to the cloud remote control module, and synchronizing pricing order data to the cloud remote control module, if the transmitted data volume is less than a preset traffic threshold, the network is shared with the mobile phone using the Bluetooth module. When receiving firmware upgrade packages from the cloud remote control module and sending pricing logs generated from all daily pricing order data to the cloud remote control module, if the transmitted data volume exceeds the preset traffic threshold, the network is shared with the mobile phone using the Wi-Fi hotspot module.

[0034] In addition, combined Figure 2 This embodiment provides an artificial intelligence-based pricing system, which includes an AI pricing control module for executing the pricing method. The AI ​​pricing control module is communicatively connected to a basic pricing module, an AI voice interaction module, a network sharing module, a local storage module, and a vehicle controller.

[0035] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0036] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0037] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0038] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0039] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims. All of these forms are within the protection scope of the present invention.

Claims

1. A pricing method based on artificial intelligence, characterized in that, The method is based on an AI-based pricing control module, which is communicatively connected to the vehicle's basic pricing module, AI voice interaction module, network sharing module, local storage module, and vehicle controller. In response to receiving a power-on success signal from the vehicle controller, an automatic pairing signal is sent to the network sharing module, and a communication connection is established with a mobile phone within the scanning range that meets the pairing requirements after encryption and verification through the network sharing module; In response to receiving a successful connection signal from the network sharing module, a communication connection is established with the cloud remote control module using the mobile phone's shared network; In response to receiving a price adjustment signal from the cloud-based remote control module, a rate adjustment signal obtained from parsing the price adjustment signal is sent to the basic pricing module; Upon receiving the rate adjustment completion signal from the basic pricing module, a successful price adjustment signal is sent back to the cloud-based remote control module. In response to receiving a trip start signal from the AI ​​voice interaction module when it recognizes the start fare calculation wake-up word, a fare calculation start signal is sent to the basic fare calculation module; In response to receiving a trip end signal sent by the AI ​​voice interaction module when it recognizes the end-of-pricing wake-up word, a pricing end signal is sent to the basic pricing module; In response to receiving the pricing result signal from the basic pricing module, the pricing order data obtained from parsing the pricing result signal is stored in the local storage module and synchronized to the cloud remote control module.

2. The pricing method based on artificial intelligence according to claim 1, characterized in that, The AI ​​pricing control module is also communicatively connected to the vehicle's central control display module, and the pricing method further includes: In response to receiving a connection success signal from the network sharing module, a connection success display signal and a connection success broadcast signal are sent to the central control display module and the AI ​​voice interaction module, respectively. In response to receiving the rate adjustment completion signal from the basic pricing module, the system sends the latest rate display signal and the latest rate broadcast signal to the central control display module and the AI ​​voice interaction module, respectively.

3. The pricing method based on artificial intelligence according to claim 1, characterized in that, The network sharing module includes a Bluetooth module and a WIFI hotspot module; When receiving price adjustment signals from the cloud remote control module, sending price adjustment success signals back to the cloud remote control module, and synchronizing pricing order data to the cloud remote control module, the amount of data transmitted is less than the preset traffic threshold, and the network is shared with the mobile phone using the Bluetooth module. When receiving firmware upgrade packages from the cloud-based remote control module and sending pricing logs generated from all daily pricing orders to the cloud-based remote control module, if the amount of data transmitted exceeds the preset traffic threshold, the device will share the network with the mobile phone using a Wi-Fi hotspot module.

4. The pricing method based on artificial intelligence according to claim 1, characterized in that, The AI ​​pricing control module is also connected to the vehicle's central control display module. When a communication connection is established between the network sharing module and a mobile phone that meets the pairing requirements within the scanning range after encryption verification, in response to receiving a connection failure signal from the network sharing module, a connection guidance broadcast signal is sent to the AI ​​voice interaction module. When establishing a communication connection with a mobile phone that meets the pairing requirements within the scanning range via the network sharing module after encryption verification, the verification code generated on the central control display module needs to be entered into the mobile phone to confirm that the encryption verification is successful.

5. The pricing method based on artificial intelligence according to claim 1, characterized in that, After receiving a successful connection signal from the network sharing module, in response to a connection interruption signal from the network sharing module, the transmission data waiting to be synchronized to the cloud remote control module is cached in the vehicle's local storage module in preparation for re-establishing a communication connection with the mobile phone.

6. The pricing method based on artificial intelligence according to claim 1, characterized in that, During the period between receiving the trip start signal and the trip end signal, the method further includes: In response to receiving a price increase signal from the AI ​​voice interaction module when it recognizes the additional fee wake word, the system sends an additional fee signal, which is parsed from the price increase signal, to the basic pricing module. In response to receiving the current fee query signal from the AI ​​voice interaction module when it recognizes the fee query wake-up word, a fee detail query signal is sent to the basic pricing module. In response to receiving the fee detail signal from the basic pricing module, a fee detail list broadcast signal obtained by parsing the fee detail list signal is sent to the AI ​​voice interaction module.

7. The pricing method based on artificial intelligence according to claim 1, characterized in that, During the period between receiving the trip start signal and the trip end signal, the method further includes: After receiving the trip start signal, the system acquires weather and mileage signals sent by the cloud remote control module at preset mileage and preset time intervals, and sends weather and mileage broadcast signals, respectively parsed from the weather and mileage signals, to the AI ​​voice interaction module.

8. The pricing method based on artificial intelligence according to claim 1, characterized in that, The AI ​​pricing control module is also communicatively connected to the vehicle's central control display module, and the method further includes: In response to receiving a connection success signal from the network sharing module, a connection success display signal is sent to the central control display module; In response to receiving the rate adjustment completion signal sent by the basic pricing module, the latest rate display signal obtained by parsing the rate adjustment completion signal is sent to the central control display module; In response to receiving the pricing result signal from the basic pricing module, a pricing order display signal obtained by parsing the pricing result signal is sent to the central control display module.

9. The pricing method based on artificial intelligence according to claim 1, characterized in that, The method further includes: In response to receiving the order synchronization completion signal from the cloud remote control module, an order printing signal is sent to the basic pricing module.

10. A pricing system based on artificial intelligence, characterized in that, It includes an AI pricing control module for executing the pricing method according to any one of claims 1-9, wherein the AI ​​pricing control module is communicatively connected to the vehicle's basic pricing module, AI voice interaction module, network sharing module, local storage module, and vehicle controller.

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