An online taxi hailing system based on a fixed-point area

Abstract

This invention relates to the field of taxi technology, specifically to an online taxi hailing system based on fixed-point areas. The system includes a passenger interaction module, a driver response module, an intelligent sensing module, a data management module, and an application support module. By constructing an intelligent taxi hailing service system, this system establishes a new model of physical space sharing and virtual dispatch empowerment, opening up passenger pick-up channels for taxis at fixed locations in designated areas, maximizing the utilization of taxi resources, and significantly improving the overall traffic management level and service quality of the city.

Description

Technical Field

[0001] This invention relates to the field of taxi technology, and more specifically, to an online taxi hailing system based on a fixed area. Background Technology

[0002] In the current urban public transportation system, traditional taxis and ride-hailing services coexist. Traditional taxis mainly rely on drivers visually scanning the streets to find passengers, which is inefficient. Ride-hailing services, on the other hand, generally adopt a "mobile APP + BD / GPS positioning" model. Passengers can take out their mobile phones to place orders from any location, and the platform pushes them to nearby drivers based on their location coordinates. Both methods are still feasible in open road scenarios, but they have exposed systemic defects in fixed areas (airports, high-speed rail stations, hospitals, schools, scenic spots, shopping districts, etc.).

[0003] First, BD / GPS positioning has a large error. Ride-hailing platforms rely on mobile phone BD / GPS or in-vehicle terminals to obtain passenger locations. However, signal attenuation occurs indoors, on elevated roads, and in densely built-up environments, resulting in errors of 50 to 200 meters. As a result, passengers may hail a ride at the entrance of a scenic spot, but the driver's navigation may direct them to stop on the road. Both parties need to walk back and forth to find the driver, which takes an average of more than 8 minutes. Furthermore, during peak hours, road congestion prevents taxis from stopping for long periods, and drivers are often forced to cancel orders because they cannot find passengers, with a cancellation rate as high as 30%.

[0004] The second issue is the queuing chaos caused by overlapping coordinates. In areas like airports and high-speed rail stations, the length of taxi waiting lanes is less than 200 meters, and the BD / GPS coordinates almost completely overlap. The platform cannot distinguish which lane a passenger is in. As a result, the platform often assigns orders based on the "shortest pick-up distance." As a result, a taxi in lane A that gets an order has to cross traffic to pick up a passenger in lane B, causing congestion at the lane intersections.

[0005] Thirdly, there is a lack of a real-name traceability mechanism. Ride-hailing services allow passengers to register anonymously and cancel orders at will, and drivers can also refuse orders without liability. As a result, if passengers use the method of calling multiple platforms at the same time with one click, they will cancel the other orders after the first car arrives, which will increase the empty driving costs of the other drivers many times over. After the cancellation of the ride, the complaint rate remains high.

[0006] Fourthly, the digital divide excludes vulnerable groups. The current way of working relies entirely on smartphones, 4G networks, and electronic payments. The drawback is that it is not friendly enough to vulnerable groups such as the elderly. The elderly do not know how to operate the app, and it can take up to 40 minutes to hail a taxi at the hospital. Tourists from other places can only look on with envy when their phones are out of power or they do not have a local data card. After evening self-study at school, students' mobile phones are centrally managed, and they are also unable to call a taxi home.

[0007] Fifthly, the low cost of breaking a promise leads to a lack of integrity. Passengers only incur a small cancellation fee when canceling an order, and drivers receive no real punishment for falsely clicking "arrived." As a result, passengers cancel at will, drivers' average empty mileage increases by 20%, fuel consumption and time costs rise, and drivers click "arrived" in advance to meet platform performance targets, resulting in passengers being charged by the system before boarding, and a surge in complaints. Summary of the Invention

[0008] To address the aforementioned problems in existing technologies, the present invention aims to provide an online taxi hailing system based on fixed-point areas. By constructing an intelligent taxi hailing service system, a new model of physical space sharing and virtual dispatch empowerment is established, opening up passenger pick-up channels for taxis at fixed points in designated areas, maximizing the utilization of taxi resources, and significantly improving the overall traffic management level and service quality of the city.

[0009] To solve the above problems, the technical solution adopted by the present invention is as follows:

[0010] An online taxi hailing system based on a fixed area, the system includes a passenger interaction module, a driver response module, an intelligent sensing module, a data management module, and an application support module; The passenger interaction module is configured to allow passengers to make a ride-hailing request in a designated area via touch screen or QR code, and generate a ride-hailing order. The driver response module is configured to provide the driver with the ability to receive and respond to the ride-hailing order generated by the passenger; The intelligent sensing module includes an active status reporting and location acquisition unit, a passenger pick-up point geofence and virtual capacity zone management unit, and a data credibility and behavior verification unit. The active status reporting and location acquisition unit includes an APP positioning and status interface device located on the taxi driver's end. The device acquires the real-time latitude and longitude coordinates of the taxi through the positioning module built into the device, and at the same time, the device acquires and uploads the current operating status of the taxi. The passenger pick-up point geofence and virtual capacity zone management unit includes a virtual electronic fence generator deployed at the pick-up point. The generator generates a pick-up point for each ride-hailing order generated by a passenger through the passenger interaction module and generates a corresponding dynamic virtual capacity matching zone. The virtual capacity matching zone is an irregular polygon geofence generated based on real-time road conditions, traffic rules, and pedestrian accessible paths. The passenger pick-up point geofence and virtual capacity zone management unit continuously reports the vehicle locations of taxis with an "empty" operating status to the data management module. The data management module includes a capacity pool management unit, an order matching and dispatch unit, and a credit management unit; The capacity pool management unit is used to dynamically manage a virtual capacity pool consisting of taxis currently located in the designated area and in an empty state, based on the data collected by the intelligent sensing module, and to establish capacity records for the taxis in the virtual capacity pool, including their location, entry time, and credit status. The order matching and dispatch unit is used to perform order matching and push the order information to the corresponding driver module after receiving a hailing order generated from the passenger interaction module, based on the geofence of the specific pick-up point associated with the hailing order and in combination with the real-time location and credit status of the taxis in the capacity pool. The credit management unit is used to record and evaluate the behavior of passengers and drivers, establish a credit score system, and implement credit penalties for breach of contract.

[0011] Furthermore, the passenger interaction module includes a core interaction unit, an auxiliary interaction unit, an intelligent guidance and feedback unit, and an accessibility unit; The core interactive unit includes the integrated screen display and the taxi hailing QR code. The auxiliary interaction unit includes a simple physical call button and a voice interaction interface. The simple physical call button is located next to the screen display all-in-one machine or installed independently. It is used to provide passengers who are not familiar with touch screen operation with a one-click ride request trigger, generate a ride order, and call the default passenger pick-up point settings associated with the screen display all-in-one machine after triggering. The voice interaction interface is integrated into the screen display all-in-one machine or implemented through a separate device, supporting passengers to issue a ride-hailing request and generate a ride-hailing order through voice commands. The intelligent guidance and feedback unit includes a dynamic information display subunit and a multi-channel notification subunit. The dynamic information display subunit is integrated into the screen display all-in-one machine and is used to display the current area's transportation capacity status, estimated waiting time, recommended pick-up points, and taxi hailing operation instructions in real time. The recommended pick-up points are dynamically calculated based on pedestrian and vehicle flow density. The multi-channel notification subunit is used to generate a dynamic QR code containing taxi hailing order details and navigation information through the screen display all-in-one machine and SMS push after a passenger successfully initiates a taxi hailing request and generates a taxi hailing order. This confirms the order status to the passenger and provides pick-up guidance. The accessible access unit includes a lightweight H5 taxi-hailing page and a privacy-protected input page. The lightweight H5 taxi-hailing page is compatible with the taxi-hailing QR code, and the privacy-protected input page is integrated into the screen display or the lightweight H5 taxi-hailing page to partially desensitize and encrypt the sensitive information entered by the passenger.

[0012] Furthermore, the intelligent sensing module also includes a data behavior credibility verification unit and an interaction confirmation verification unit; The data behavior credibility verification unit uses a third-party trusted location data source to judge the credibility of the location information reported by the positioning module of the taxi. For taxis that stay in the same location for a long time but are in the empty status, the data management module sends a silent detection request to the driver response module to verify whether the driver terminal is operating normally. The interactive confirmation verification unit continuously monitors the movement trajectory of the taxi based on the location information of the taxi obtained by the active status reporting and location acquisition unit, and determines whether the taxi has entered the preset "precise stopping area" and has behavior that meets the "stopping" characteristics. If so, the data management module sends a "confirm arrival" mandatory interactive command to the driver response module.

[0013] Furthermore, the intelligent sensing module also includes a data fusion and verification unit. The data fusion and verification unit is configured to associate and deduplicate taxi identification events from different sensing sources and different time points based on timestamps and logical locations to form a complete event chain for a single vehicle from entry, internal movement, to departure. The data fusion and verification unit is also configured to compare and resolve conflicts between multiple state signals of the same taxi, and determine the final credible state based on preset confidence rules.

[0014] Furthermore, the intelligent sensing module also includes a real-time analysis and intent judgment unit, which includes a behavior pattern analysis subunit and a departure tendency prediction subunit. The behavior pattern analysis subunit determines the current behavior of the taxi based on historical data and real-time trajectory. The departure tendency prediction subunit combines the taxi's dwell time in the designated area, movement trajectory trend, and driver operation signals to predict the probability and time of its departure from the capacity pool, providing advance signals for dynamic capacity management.

[0015] Furthermore, the application support module includes a flexible and scalable computing and storage unit, an edge computing and local processing unit, a data platform and intelligent analysis unit, and a security, privacy and compliance protection unit; The scalable computing and storage unit is configured to encapsulate core functions, including order matching, credit calculation, and real-time communication, into independent microservices and deploy them on a containerized management platform to establish a time-series database and an in-memory database for storing real-time capacity status and order flow. The edge computing and local processing unit is configured as a fixed-point edge server deployed locally in the fixed area. It is used to run latency-sensitive lightweight services, and is also responsible for accessing and managing various heterogeneous sensing devices, and completing protocol conversion, preliminary data cleaning and aggregation. The data center and intelligent analysis unit are configured to perform standardized cleaning and labeling of the raw data from each module to form a unified data model including "cruising taxis", "ride-hailing orders", "fixed pick-up points" and "passengers". At the same time, it is responsible for encapsulating and providing callable algorithm services, including time series models for capacity prediction, route planning algorithms for pick-up points for intelligent recommendation, and fraud detection models for identifying abnormal orders. The security, privacy, and compliance protection unit is configured to cover the entire lifecycle of data collection, transmission, storage, processing, and destruction, and supports the system in completing joint modeling without the data leaving the domain.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows: The design employed in this invention breaks the spatial advantage of ride-hailing services in multiple areas, providing traditional taxis with an equal passenger pick-up channel, satisfying the fairness demands of drivers, avoiding the spatial limitations of fixed pick-up points, and eliminating the need to replicate the traditional queuing model. A virtual dispatch mechanism ensures equal operational rights for traditional taxis in designated areas. Furthermore, by constructing a dynamic matching model of "vehicles entering the pool upon arrival and passengers responding to demand upon arrival," the average ride-hailing response time is controlled within 2 minutes, reducing passenger waiting time and driver idle time losses. Dynamic management of the capacity pool (with a 5-minute timeout exit mechanism) avoids the accumulation of ineffective capacity, improves traffic conversion efficiency at fixed pick-up points, and reduces localized congestion.

[0017] Secondly, it can optimize the interactive experience for drivers and passengers, enabling passengers to hail a ride without registration and with simple operation. It supports both large-screen touchscreens and mobile phone scanning, adhering to the "three-click completion" interaction principle, and is suitable for elderly people and non-smartphone users, ensuring barrier-free use for all groups. Drivers can also accept orders through a unified platform, enabling accurate push notifications and instant communication of passenger information, reducing communication costs and improving the convenience of order acceptance.

[0018] Finally, relying on intelligent sensing equipment and transportation capacity scheduling data, this invention provides real-time data support for passenger flow prediction at designated pick-up points and dynamic allocation of transportation capacity, enabling scientific management. Furthermore, through cross-validation of point data, it ensures that the accuracy rate of vehicle status judgment is ≥99%, providing regulatory authorities with a transparent and traceable operational data foundation. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the module structure of this system; Figure 2 A schematic diagram of the on-site layout of the passenger interaction module; Figure 3 This is a schematic diagram of the touch-sensitive display interface on an all-in-one display device. Detailed Implementation

[0020] The present invention will be further described below with reference to specific embodiments.

[0021] The online taxi hailing system based on fixed-point areas described in this invention constructs an intelligent taxi hailing service system, establishes a new model of physical space sharing and virtual dispatch empowerment, opens up passenger pick-up channels for taxis at fixed points in fixed areas, maximizes the utilization of taxi resources, and can significantly improve the overall traffic management level and service quality of the city.

[0022] Specifically, such as Figure 1 As shown, this system includes a passenger interaction module, a driver response module, an intelligent sensing module, a data management module, and an application support module.

[0023] The passenger interaction module is configured to allow passengers to submit ride-hailing requests via touchscreen or QR code within designated areas, generating ride-hailing orders. It provides a convenient entry point for ride-hailing, supports large-screen operation and mobile phone scanning, and enables fast ride-hailing services without registration. This passenger interaction module includes a core interaction unit, an auxiliary interaction unit, an intelligent guidance and feedback unit, and an accessibility unit. Figure 2 and Figure 3 As shown, the core interaction unit includes at least one touchscreen display unit deployed in a pre-defined designated area. This display unit has a unique screen number and is linked to one or more specific pick-up point geofences within the designated area. The core interaction unit also includes a ride-hailing QR code generated on the display unit's screen and associated with the display unit or the pick-up point geofence. Passengers can scan the QR code to submit a ride-hailing request online and generate a ride order.

[0024] The auxiliary interaction unit includes a simple physical call button and a voice interaction interface. The simple physical call button is located next to the screen display all-in-one machine or installed independently. It is used to provide passengers who are not familiar with touch screen operation with a one-click ride request trigger, generate a ride order, and call the default passenger pick-up point settings of the associated screen display all-in-one machine after triggering.

[0025] The voice interaction interface is integrated into the all-in-one display or implemented through a separate device, allowing passengers to issue ride-hailing requests and generate ride-hailing orders via voice commands. The intelligent guidance and feedback unit includes a dynamic information display subunit and a multi-channel notification subunit. The dynamic information display subunit is integrated into the screen display all-in-one machine and is used to display the current area's transportation capacity status, estimated waiting time, recommended pick-up points, and taxi hailing operation instructions in real time. The recommended pick-up points are dynamically calculated based on the density of people and vehicles. The multi-channel notification subunit is used to generate a dynamic QR code containing taxi hailing order details and navigation information through the screen display all-in-one machine and SMS push after a passenger successfully initiates a taxi hailing request and generates a taxi hailing order. This confirms the order status to the passenger and provides pick-up guidance. The accessible access unit includes a lightweight H5 taxi-hailing page and a privacy-protected input page. The lightweight H5 taxi-hailing page is compatible with the taxi-hailing QR code, while the privacy-protected input page is integrated into the screen display all-in-one machine or the lightweight H5 taxi-hailing page, and performs partial desensitization and encrypted transmission of sensitive information entered by passengers.

[0026] The driver response module is configured to enable drivers to receive and respond to ride-hailing orders generated by passengers, and to realize functions such as driver order acceptance, order confirmation, and driver-passenger communication.

[0027] The intelligent sensing module includes an active status reporting and location acquisition unit, a passenger pick-up point geofence and virtual capacity area management unit, and a data credibility and behavior verification unit.

[0028] The active status reporting and location acquisition unit includes an APP positioning and status interface device located on the taxi driver's end. The device obtains the real-time latitude and longitude coordinates of the taxi through the built-in positioning module, and at the same time, the device obtains and uploads the current operating status of the taxi.

[0029] The passenger pick-up point geofence and virtual capacity zone management unit includes a virtual electronic fence generator deployed at the pick-up point. The generator generates a pick-up point for each ride-hailing order generated by a passenger through the passenger interaction module and generates a corresponding dynamic virtual capacity matching zone. The virtual capacity matching zone is an irregular polygon geofence generated based on real-time road conditions, traffic rules, and pedestrian accessible paths. The passenger pick-up point geofence and virtual capacity zone management unit continuously reports the vehicle location of taxis with an "empty" operating status to the data management module.

[0030] The intelligent sensing module also includes a data behavior credibility verification unit and an interaction confirmation verification unit. The data behavior credibility verification unit uses a third-party trusted location data source to judge the credibility of the location information reported by the positioning module of the taxi. For taxis that stay in the same location for a long time but are in an empty status, the data management module sends a silent detection request to the driver response module to verify whether the driver terminal is operating normally. The interaction confirmation verification unit continuously monitors the movement trajectory of the taxi based on the location information of the taxi obtained by the active status reporting and location acquisition unit, and determines whether the taxi has entered the preset "precise stopping area" and has behavior that meets the "stopping" characteristics. If so, the data management module sends a "confirm arrival" mandatory interaction command to the driver response module.

[0031] The intelligent sensing module also includes a data fusion and verification unit. The data fusion and verification unit is configured to associate and deduplicate taxi identification events from different sensing sources and different time points based on timestamps and logical locations, forming a complete event chain for a single vehicle from entry, internal movement, to departure. The data fusion and verification unit is also configured to compare and resolve conflicts of multiple state signals of the same taxi, and determine the final credible state according to preset confidence rules.

[0032] The intelligent sensing module also includes a real-time analysis and intent judgment unit, which includes a behavior pattern analysis subunit and a departure tendency prediction subunit. The behavior pattern analysis subunit determines the current behavior of the taxi based on historical data and real-time trajectory. The departure tendency prediction subunit combines the taxi's dwell time in the designated area, movement trajectory trend, and driver operation signals to predict the probability and time of its departure from the capacity pool, providing advance signals for dynamic capacity management.

[0033] The data management module communicates with the passenger interaction module, driver response module, and intelligent sensing module, and is configured to handle ride-hailing business logic and capacity scheduling. It includes a capacity pool management unit, an order matching and dispatch unit, and a credit management unit. The capacity pool management unit is used to dynamically manage a virtual capacity pool consisting of taxis that are currently located in a fixed area and are in an empty state, based on the data collected by the intelligent sensing module, and to establish capacity records for taxis in the virtual capacity pool, including their location, entry time and credit status. The order matching and dispatch unit is used to perform order matching and push the order information to the corresponding driver module after receiving a hailing order generated from the passenger interaction module, based on the geofence of the specific pick-up point associated with the hailing order, and in combination with the real-time location and credit status of the taxis in the capacity pool. The credit management unit is used to record and evaluate the behavior of passengers and drivers, establish a credit score system, and implement credit penalties for breaches of contract.

[0034] The application support module is configured to provide underlying computing, storage, and communication support for the system. It includes a server cluster, a database system, and open API interfaces for data exchange with external taxi management platforms. Specifically, it includes elastic and scalable computing and storage units, edge computing and local processing units, a data platform and intelligent analysis unit, and a security, privacy, and compliance protection unit. The scalable computing and storage units are configured to encapsulate core functions, including order matching, credit calculation, and real-time communication, into independent microservices and deploy them on a containerized management platform to establish a real-time capacity status, a time-series database of order flows, and an in-memory database. The edge computing and local processing unit is configured as a fixed-point edge server deployed in a fixed area to run latency-sensitive lightweight services, while also being responsible for accessing and managing various heterogeneous sensing devices, and completing protocol conversion, preliminary data cleaning and aggregation. The data center and intelligent analysis unit are configured to standardize, clean, and label the raw data from each module to form a unified data model including "cruising taxis", "ride-hailing orders", "fixed pick-up points", and "passengers". They are also responsible for encapsulating and providing callable algorithm services, including time series models for capacity forecasting, route planning algorithms for pick-up points for intelligent recommendation, and fraud detection models for identifying abnormal orders. The security, privacy, and compliance protection unit is configured to cover the entire lifecycle of data collection, transmission, storage, processing, and destruction, and supports the system in completing joint modeling without the data leaving the domain.

[0035] The current pace of informatization development in the taxi industry still has significant room for improvement overall. The operating model of most vehicles has not yet completely broken free from the traditional framework of "people finding taxis, taxis finding people." In areas with high passenger flow, such as train stations, airports, core business districts, top-tier hospitals, and key schools, passengers often need to visually search for empty taxis in traffic or wait in designated waiting areas. Drivers, on the other hand, mostly rely on years of accumulated operating experience, "street sweeping" to find passengers or waiting in fixed locations. The supply and demand information between the two sides is not effectively exchanged, resulting in a significant information asymmetry problem.

[0036] The core of traditional taxi operation lies in its "cruising and soliciting passengers" characteristic, which is fundamentally different from the "order-taking and response" model of ride-hailing services. Ride-hailing services can receive passenger order information in real time through the platform and accurately match demand, while traditional taxis rely more on mobile solicitation on the road or waiting at fixed locations, lacking a natural information transmission channel. This difference in models makes it difficult for key operational information such as real-time vehicle location and current passenger status to be synchronized between passengers and drivers. During peak travel periods, holidays, or in severe weather conditions such as heavy rain or snow, long queues of passengers often form in popular areas, making it difficult to find a taxi. Meanwhile, many empty taxis in the surrounding area, unaware of the specific demand distribution, can only continue to blindly cruise the streets looking for passengers. This information disconnect between supply and demand not only diminishes the passenger travel experience and wastes waiting time, but also increases the driver's time costs and operational losses such as fuel and energy consumption, reducing actual income. At the same time, unnecessary empty mileage also contributes to traffic congestion on some roads, resulting in a waste of public transportation resources.

[0037] The industry as a whole is in a state of "random matching and inefficient operation," unable to reduce uncertainty through reservation services or achieve precise supply and demand scheduling through big data analysis, becoming the biggest weakness in the competition between traditional taxis and ride-hailing services. At the same time, drivers' income and service quality lack data-driven assessment, and passengers cannot know the arrival time of the vehicle and driver information in advance, resulting in a continuous decline in the experience. Regulatory authorities also have difficulty obtaining real-time operational data, making it impossible to scientifically allocate transportation capacity and dynamically supervise the industry in key areas and during key periods, creating a situation where "enterprises lack data, governments lack effective measures, and passengers lack a good experience."

[0038] The design employed in this invention breaks the spatial advantage of ride-hailing services in multiple areas, providing traditional taxis with an equal passenger pick-up channel, satisfying the fairness demands of drivers, avoiding the spatial limitations of fixed pick-up points, and eliminating the need to replicate the traditional queuing model. A virtual dispatch mechanism ensures equal operational rights for traditional taxis in designated areas. Furthermore, by constructing a dynamic matching model of "vehicles entering the pool upon arrival and passengers responding to demand upon arrival," the average ride-hailing response time is controlled within 2 minutes, reducing passenger waiting time and driver idle time losses. Dynamic management of the capacity pool (with a 5-minute timeout exit mechanism) avoids the accumulation of ineffective capacity, improves traffic conversion efficiency at fixed pick-up points, and reduces localized congestion.

[0039] Secondly, it can optimize the interactive experience for drivers and passengers, enabling passengers to hail a ride without registration and with simple operation. It supports both large-screen touchscreens and mobile phone scanning, adhering to the "three-click completion" interaction principle, and is suitable for elderly people and non-smartphone users, ensuring barrier-free use for all groups. Drivers can also accept orders through a unified platform, enabling accurate push notifications and instant communication of passenger information, reducing communication costs and improving the convenience of order acceptance.

[0040] Finally, relying on intelligent sensing equipment and transportation capacity scheduling data, this invention provides real-time data support for passenger flow prediction at designated pick-up points and dynamic allocation of transportation capacity, enabling scientific management. Furthermore, through cross-validation of point data, it ensures that the accuracy rate of vehicle status judgment is ≥99%, providing regulatory authorities with a transparent and traceable operational data foundation.

Claims

1. An online taxi hailing system based on a fixed area, characterized in that, The system includes a passenger interaction module, a driver response module, an intelligent sensing module, a data management module, and an application support module. The passenger interaction module is configured to allow passengers to make a ride-hailing request in a designated area via touch screen or QR code, and generate a ride-hailing order. The driver response module is configured to provide the driver with the ability to receive and respond to the ride-hailing order generated by the passenger; The intelligent sensing module is configured as a cloud-based distributed dynamic sensing network, used to capture and verify the location, status and availability of taxis connected to the system in real time and continuously. The data management module is communicatively connected to the passenger interaction module, the driver response module and the intelligent perception module, and is configured to handle the ride-hailing business logic and capacity scheduling. The application support module is configured to provide underlying computing, storage and communication support for the system. The application support module includes a server cluster, a database system and an open API interface for exchanging data with an external taxi management platform. The passenger interaction module is deployed in a pre-defined fixed area and includes at least one touch screen display all-in-one machine. The display all-in-one machine has a unique screen number and is bound to one or more specific boarding point geofences within the fixed area. The passenger interaction module also includes a taxi-hailing QR code generated on the screen of the integrated display device and associated with the integrated display device or the geographical fence of the pick-up point. Passengers can scan the taxi-hailing QR code to make a taxi-hailing request online and generate the taxi-hailing order. The intelligent sensing module includes an active status reporting and location acquisition unit, a passenger pick-up point geofence and virtual capacity zone management unit, and a data credibility and behavior verification unit. The active status reporting and location acquisition unit includes an APP positioning and status interface device located on the taxi driver's end. The device acquires the real-time latitude and longitude coordinates of the taxi through the positioning module built into the device, and at the same time, the device acquires and uploads the current operating status of the taxi. The passenger pick-up point geofence and virtual capacity zone management unit includes a virtual electronic fence generator deployed at the pick-up point. The generator generates a pick-up point for each ride-hailing order generated by a passenger through the passenger interaction module and generates a corresponding dynamic virtual capacity matching zone. The virtual capacity matching zone is an irregular polygon geofence generated based on real-time road conditions, traffic rules, and pedestrian accessible paths. The passenger pick-up point geofence and virtual capacity zone management unit continuously reports the vehicle locations of taxis with an "empty" operating status to the data management module. The data management module includes a capacity pool management unit, an order matching and dispatch unit, and a credit management unit; The capacity pool management unit is used to dynamically manage a virtual capacity pool consisting of taxis currently located in the designated area and in an empty state, based on the data collected by the intelligent sensing module, and to establish capacity records for the taxis in the virtual capacity pool, including their location, entry time, and credit status. The order matching and dispatch unit is used to perform order matching and push the order information to the corresponding driver module after receiving a hailing order generated from the passenger interaction module, based on the geofence of the specific pick-up point associated with the hailing order and in combination with the real-time location and credit status of the taxis in the capacity pool. The credit management unit is used to record and evaluate the behavior of passengers and drivers, establish a credit score system, and implement credit penalties for breach of contract.

2. The online taxi hailing system based on a fixed area according to claim 1, characterized in that, The passenger interaction module includes a core interaction unit, an auxiliary interaction unit, an intelligent guidance and feedback unit, and an accessibility unit. The core interactive unit includes the integrated screen display and the taxi hailing QR code. The auxiliary interaction unit includes a simple physical call button and a voice interaction interface. The simple physical call button is located next to the screen display all-in-one machine or installed independently. It is used to provide passengers who are not familiar with touch screen operation with a one-click ride request trigger, generate a ride order, and call the default passenger pick-up point settings associated with the screen display all-in-one machine after triggering. The voice interaction interface is integrated into the screen display all-in-one machine or implemented through a separate device, supporting passengers to issue a ride-hailing request and generate a ride-hailing order through voice commands. The intelligent guidance and feedback unit includes a dynamic information display subunit and a multi-channel notification subunit. The dynamic information display subunit is integrated into the screen display all-in-one machine and is used to display the current area's transportation capacity status, estimated waiting time, recommended pick-up points, and taxi hailing operation instructions in real time. The recommended pick-up points are dynamically calculated based on pedestrian and vehicle flow density. The multi-channel notification subunit is used to generate a dynamic QR code containing taxi hailing order details and navigation information through the screen display all-in-one machine and SMS push after a passenger successfully initiates a taxi hailing request and generates a taxi hailing order. This confirms the order status to the passenger and provides pick-up guidance. The accessible access unit includes a lightweight H5 taxi-hailing page and a privacy-protected input page. The lightweight H5 taxi-hailing page is compatible with the taxi-hailing QR code, and the privacy-protected input page is integrated into the screen display or the lightweight H5 taxi-hailing page to partially desensitize and encrypt the sensitive information entered by the passenger.

3. The online taxi hailing system based on a fixed area according to claim 1, characterized in that, The intelligent sensing module also includes a data behavior credibility verification unit and an interaction confirmation verification unit; The data behavior credibility verification unit uses a third-party trusted location data source to judge the credibility of the location information reported by the positioning module of the taxi. For taxis that stay in the same location for a long time but are in the empty status, the data management module sends a silent detection request to the driver response module to verify whether the driver terminal is operating normally. The interactive confirmation verification unit continuously monitors the movement trajectory of the taxi based on the location information of the taxi obtained by the active status reporting and location acquisition unit, and determines whether the taxi has entered the preset "precise stopping area" and has behavior that meets the "stopping" characteristics. If so, the data management module sends a "confirm arrival" mandatory interactive command to the driver response module.

4. The online taxi hailing system based on a fixed area according to claim 3, characterized in that, The intelligent sensing module also includes a data fusion and verification unit. The data fusion and verification unit is configured to associate and deduplicate taxi identification events from different sensing sources and different time points based on timestamps and logical locations to form a complete event chain for a single vehicle from entry, internal movement, to departure. The data fusion and verification unit is also configured to compare and resolve conflicts between multiple state signals of the same taxi, and determine the final credible state based on preset confidence rules.

5. The online taxi hailing system based on a fixed area according to claim 4, characterized in that, The intelligent sensing module also includes a real-time analysis and intent judgment unit, which includes a behavior pattern analysis subunit and a departure tendency prediction subunit. The behavior pattern analysis subunit determines the current behavior of the taxi based on historical data and real-time trajectory. The departure tendency prediction subunit combines the taxi's dwell time in the designated area, movement trajectory trend, and driver operation signals to predict the probability and time of its departure from the capacity pool, providing advance signals for dynamic capacity management.

6. The online taxi hailing system based on a fixed area according to claim 1, characterized in that, The application support module includes a flexible and scalable computing and storage unit, an edge computing and local processing unit, a data platform and intelligent analysis unit, and a security, privacy and compliance protection unit. The scalable computing and storage unit is configured to encapsulate core functions, including order matching, credit calculation, and real-time communication, into independent microservices and deploy them on a containerized management platform to establish a time-series database and an in-memory database for storing real-time capacity status and order flow. The edge computing and local processing unit is configured as a fixed-point edge server deployed locally in the fixed area. It is used to run latency-sensitive lightweight services, and is also responsible for accessing and managing various heterogeneous sensing devices, and completing protocol conversion, preliminary data cleaning and aggregation. The data center and intelligent analysis unit are configured to perform standardized cleaning and labeling of the raw data from each module to form a unified data model including "cruising taxis", "ride-hailing orders", "fixed pick-up points" and "passengers". At the same time, it is responsible for encapsulating and providing callable algorithm services, including a time series model for capacity prediction, a route planning algorithm for pick-up points for intelligent recommendation, and a fraud detection model for identifying abnormal orders. The security, privacy, and compliance protection unit is configured to cover the entire lifecycle of data collection, transmission, storage, processing, and destruction, and supports the system in completing joint modeling without the data leaving the domain.

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