Intelligent diagnosis and active intervention system based on driver's intention to find goods reporting

Abstract

The application discloses an intelligent diagnosis and active touch intervention system based on driver's intention report of finding goods, comprising: a time sequence diagnosis touch module, a multi-dimensional intention failure judgment module and a scenario-based intelligent touch and closed loop module; the time sequence diagnosis touch module is used for constructing an event trigger mechanism based on time sequence, and different types of diagnosis tasks are automatically triggered at different time nodes after the driver reports the intention of finding goods; the multi-dimensional intention failure judgment module is used for judging whether the original intention of the driver has failed in the process of triggering the diagnosis task; the scenario-based intelligent touch and closed loop module is used for selecting a touch strategy and guiding the user to complete intention update according to the diagnosis result generated by the time sequence diagnosis touch module, and forming an operation closed loop. The application continuously diagnoses the real-time position of the driver, dynamically optimizes the recommended strategy, ensures that the pushed goods information is highly consistent with the intention of the driver, and thus significantly improves the accuracy and effectiveness of the push.

Description

Technical Field

[0001] This invention relates to the field of freight platform improvement technology, and more specifically, to an intelligent diagnosis and proactive intervention system based on drivers' reported freight-seeking intentions. Background Technology

[0002] In existing freight platforms, drivers typically receive freight recommendations by actively setting their freight-finding intentions (such as frequently used routes, preferred freight types, and expected freight rates). However, this model has a significant drawback: the freight-finding intentions set by drivers are static and one-off. This is mainly due to: 1. Mismatched recommendations: The recommended freight may be far from the driver's current location or completely unrelated to their actual needs, requiring drivers to spend a significant amount of time sifting through invalid information; wasted resources: The platform's computing and push resources are heavily consumed on pushing invalid recommendations, resulting in low push open rates and conversion rates. 2. Poor user experience: Drivers feel the platform is "not intelligent" and cannot meet their real-time freight-finding needs, reducing their stickiness and trust in the platform. 3. Inefficient platform: A large number of mismatched recommendations lead to low overall vehicle-freight matching efficiency, affecting order completion speed and fulfillment rates. It is evident that existing technology, unable to perceive dynamic changes in driver status, results in inaccurate freight information being pushed, causing overall low vehicle-freight matching efficiency on the platform. Summary of the Invention

[0003] To address the aforementioned issues, the present invention aims to provide an intelligent diagnostic and proactive intervention system based on drivers' reported cargo-seeking intentions. By introducing continuous diagnostics of drivers' real-time locations and dynamically optimizing recommendation strategies, the system ensures that the cargo information pushed by the system is highly compatible with the drivers, thereby significantly improving the accuracy and effectiveness of the push notifications.

[0004] To achieve the aforementioned technical objectives, this application provides an intelligent diagnosis and proactive intervention system based on driver's reported intent to find freight, including:

[0005] The time-series diagnostic trigger module is used to build a time-series-based event triggering mechanism that automatically triggers different types of diagnostic tasks at different time points after the driver reports his intention to find cargo.

[0006] The multi-dimensional intent invalidation judgment module is used to determine whether the driver's original intent has become invalid during the process of triggering diagnostic tasks;

[0007] The scenario-based intelligent outreach and closed-loop module is used to select an outreach strategy and guide the user to complete the intent update based on the diagnostic results generated by the time-series diagnostic outreach module, thus forming an operation closed loop.

[0008] Preferably, the time-series diagnostic touch module is also used to check the exposure and feedback of the first batch of recommended cargo sources based on the initial intent after the intent is reported. If the click-through rate is lower than the threshold, it is preliminarily judged that the intent may deviate from the driver's immediate needs, and a diagnostic result is generated.

[0009] Preferably, the time-series diagnostic touch module is also used to call the driver's GPS positioning after the intention is reported, determine whether the current location has significantly deviated from the frequently traveled area set in the original intention, and generate a diagnostic result.

[0010] Preferably, the time-series diagnostic touch module is also used to collect and analyze the driver's operational behavior sequence within the time window after the intent is reported, calculate its new potential preferences, and generate diagnostic results.

[0011] Preferably, the multi-dimensional intent failure judgment module is also used to define the geofence of the original intent's frequently traveled area; when the real-time location falls into the original intent's frequently traveled area, the intent is determined to be valid; when the location deviates from the original intent's frequently traveled area and the distance is greater than the distance threshold, it is determined to be "location intent failure", and the judgment result is fed back to the time-series diagnostic touch module.

[0012] Preferably, the multi-dimensional intent failure judgment module is also used to calculate the driver's preference score for different routes based on the driver's real-time behavior data using a preference recognition model. If the preference score for one or more routes is significantly higher than the score of the original intended route, it is judged as "preference intent failure", and the judgment result is fed back to the time-series diagnostic touch module.

[0013] Preferably, the scenario-based intelligent outreach and closed-loop module is used to push different types of intent update information to driver users through different channel ports via a multi-channel outreach strategy, including: important but not urgent intent update suggestions, urgent location change reminders, and behavioral preference change suggestions when the driver actively uses the system app.

[0014] Preferably, the scenario-based intelligent outreach and closed-loop module has a daily frequency limit and a weekly frequency limit.

[0015] Preferably, the scenario-based intelligent outreach and closed-loop module is also used to set a "one-click update departure point" button in the location change reminder. After clicking, it will directly jump to the goods search settings page and pre-fill the real-time location with the new departure point.

[0016] Preferably, the scenario-based intelligent outreach and closed-loop module is also used to set a "Go to modify route" button in the preference change suggestion, and after clicking, a new route with a high score is pre-selected in the route preference page.

[0017] The present invention discloses the following technical effects:

[0018] This invention solves the problem in the prior art that the driver's intention to find goods is fixed after being set and cannot adapt to changes in their real-time location and demand, thereby reducing the driver screening cost and the waste of platform push resources caused by information mismatch.

[0019] This invention constructs an intelligent system that can automatically and continuously diagnose the real-time status of drivers (especially their location and behavioral preferences), dynamically update their cargo-finding intentions, and ensure the high accuracy and relevance of the cargo source information pushed by the platform, thereby improving the efficiency of vehicle-cargo matching and the driver's user experience. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is a schematic diagram of the logic involved in the timing-based diagnostic triggering module described in this invention;

[0022] Figure 2 This is a schematic diagram of the scenario-based intelligent reach and closed-loop operation described in this invention;

[0023] Figure 3 This is a schematic diagram of the system structure described in this invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, 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. The components of the embodiments of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0025] like Figures 1-3 As shown, this invention discloses an intelligent diagnosis and proactive intervention system based on drivers' reported intent to find goods, comprising:

[0026] The time-series diagnostic trigger module is used to build a time-series-based event triggering mechanism that automatically triggers different types of diagnostic tasks at different time points after the driver reports his intention to find cargo.

[0027] The multi-dimensional intent invalidation judgment module is used to determine whether the driver's original intent has become invalid during the process of triggering diagnostic tasks;

[0028] The scenario-based intelligent outreach and closed-loop module is used to select an outreach strategy and guide the user to complete the intent update based on the diagnostic results generated by the time-series diagnostic outreach module, thus forming an operation closed loop.

[0029] Further preferably, the time-series diagnostic module of the intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting disclosed in this invention is also used to check the exposure and feedback of the first batch of recommended cargo sources based on the initial intention after the intention is reported. If the click-through rate is lower than the threshold, it is preliminarily judged that the intention may deviate from the driver's immediate needs, and a diagnostic result is generated.

[0030] Further preferably, the time-series diagnostic module of the intelligent diagnosis and proactive intervention system based on driver's intention to find goods disclosed in this invention is also used to call the driver's GPS positioning after the intention is reported, determine whether the current position deviates significantly from the frequently traveled area set in the original intention, and generate a diagnostic result.

[0031] Further preferably, the time-series diagnostic module of the intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting disclosed in this invention is also used to collect and analyze the driver's operational behavior sequence within a time window after the intention is reported, calculate its new potential preferences, and generate diagnostic results.

[0032] Further preferably, the multi-dimensional intent failure judgment module of the intelligent diagnosis and proactive intervention system based on driver's cargo-finding intent reporting disclosed in this invention is also used to define the geofence of the original intent's frequently traveled area; when the real-time location falls into the original intent's frequently traveled area, the intent is determined to be valid; when the location deviates from the original intent's frequently traveled area and the distance is greater than a distance threshold, it is determined to be "location intent failure," and the judgment result is fed back to the time-series diagnostic intervention module. Furthermore, this module is also used to calculate the driver's preference score for different routes based on the driver's real-time behavior data using a preference recognition model; if the preference score for one or more routes is significantly higher than the score of the original intent route, it is determined to be "preference intent failure," and the judgment result is fed back to the time-series diagnostic intervention module.

[0033] More preferably, the scenario-based intelligent outreach and closed-loop module of the intelligent diagnosis and proactive outreach intervention system based on driver's cargo-finding intent reporting disclosed in this invention is used to push different types of intent update information to driver users through different channel ports via a multi-channel outreach strategy, including: important but not urgent intent update suggestions, urgent location change reminders, and when the driver actively uses the system app, push behavioral preference change suggestions.

[0034] Further preferably, the scenario-based intelligent outreach and closed-loop module of the intelligent diagnosis and proactive outreach intervention system based on the driver's intention to find goods disclosed in the invention also has a daily frequency limit and a weekly frequency limit to ensure the user's comfort.

[0035] Further preferably, the scenario-based intelligent outreach and closed-loop module of the intelligent diagnosis and proactive outreach intervention system based on driver's cargo-finding intention reporting disclosed in the invention is also used to set a "one-click update departure point" button in the location change reminder, which, when clicked, directly jumps to the cargo-finding settings page and pre-fills the real-time location with the new departure point; and to set a "go to modify route" button in the preference change suggestion, which, when clicked, pre-selects a new route with a high score in the route preference page.

[0036] Example: This invention provides an intelligent diagnosis and proactive intervention system based on drivers' reported freight-seeking intentions, including the following:

[0037] 1. Development of the timing-based diagnostic trigger module:

[0038] The system has built a time-series-based event triggering mechanism that automatically triggers different types of diagnostic tasks at different time points after the driver reports his intention to find cargo, ensuring the timeliness and effectiveness of the diagnosis.

[0039] T0 (30 minutes after the intention is reported) indicates that the "existing recommendation review and diagnosis" is triggered: check the exposure and feedback of the first batch of recommended cargo sources based on the initial intention. If the click-through rate is lower than the threshold θ_low, it is preliminarily judged that the intention may deviate from the driver's immediate needs.

[0040] T1 (2 hours after intention is reported) indicates that "location change strong verification diagnosis" is triggered: the driver's GPS location is called to determine whether the current location P_now is significantly deviated from the original intention's set frequent running area R_original.

[0041] T2 (5 hours after intention reporting) indicates that "deep analysis and diagnosis of behavioral preferences" is triggered: collect and analyze the driver's browsing, searching, clicking and other behavioral sequences {A1,A2,...,A_n} within the time window T_window, and calculate its new potential preferences through the model.

[0042] 2. Design of a multi-dimensional intent failure judgment module. This module is the core logic unit for diagnosis and is used to accurately determine whether the driver's original intent has failed.

[0043] Specifically, the design of the geofence verification unit includes defining the geofence of the area R_original where the original intent frequently travels. When the real-time location P_now falls within R_original, the intent is valid; when P_now deviates from R_original and the distance D > D_threshold (e.g., 50 kilometers), it is determined that the "location intent is invalid".

[0044] The design of the behavioral preference analysis unit includes calculating the preference score S_i for different routes L_i using a preference recognition model based on the driver's real-time behavioral data. If the preference score S_new for one or more routes is significantly higher (>S_threshold) than the score S_original for the original route, it is determined that "preference intention has failed".

[0045] 3. Design of scenario-based intelligent outreach and closed-loop modules.

[0046] Based on the diagnostic results, the system intelligently selects a reach strategy and guides the user to complete the intent update, forming an operational loop.

[0047] Specifically, the design of multi-channel outreach strategies includes, for example, WeChat Work: providing suggestions for updating important but not urgent intents.

[0048] APPPush notifications: Used for emergency location change alerts, such as "You have been detected to have arrived in XX city. Do you want to switch your pickup area?"; In-app pop-ups / banners: Used to push suggestions on changing behavioral preferences when drivers actively use the app, such as "You have recently been frequently viewing the A→B route. Do you want to set it as your preference?".

[0049] Frequency control: Each reach channel has a strict daily frequency limit N_max and a weekly frequency limit N_week_max to avoid harassing drivers.

[0050] Integrated operation loop: All reachable information is embedded with direct operation entry points. For example, location change alerts include a "One-click update departure point" button, which, when clicked, directly jumps to the cargo search settings page and pre-populates P_now with the new departure point. Preference change suggestions include a "Go to modify route" button, which, when clicked, pre-selects a new route L_new with high scores on the route preferences page.

[0051] This invention features an innovative design for a time-series-based proactive diagnostic triggering mechanism. It departs from the traditional passive reception of driver commands by designing a proactive diagnostic trigger based on fixed time intervals (T0, T1, T2), enabling the system to periodically check the validity of driver intentions like a "smart assistant." This invention transforms static intention management into a dynamic, lifecycle-based continuous optimization process.

[0052] This invention presents an innovative design for a quantitative judgment model of intent failure that integrates geofencing and behavioral analysis. It comprehensively utilizes geographic information technology (geofencing) and behavioral data analysis technology to establish quantifiable judgment criteria (D_threshold, S_threshold), providing an objective and accurate basis for determining whether an intent has failed. This invention transforms the vague concept of "change in demand" into a calculable and executable technical judgment logic. It also includes a scenario-adaptive intelligent multi-channel outreach and frequency control strategy.

[0053] This invention features an innovative design for an intelligent multi-channel outreach and frequency control strategy that adapts to different scenarios: Based on the nature of the diagnostic results (urgency, amount of information) and the driver's status, this invention dynamically selects the most suitable outreach channel and content template, coupled with strict frequency control, to balance notification effectiveness and user experience; this invention achieves refined and personalized outreach strategies, avoiding user aversion caused by "one-size-fits-all" push notifications.

[0054] This invention features an innovative integrated closed-loop design that seamlessly connects diagnosis and operation: It embeds a direct operation entry point at the initial contact stage, minimizing the path from "problem discovery - problem alert - problem resolution." Users only need a single click to update their intent, resulting in an extremely simplified operation path. This invention breaks down the barriers between the diagnostic system and the user interface, forming a highly fluid interactive closed loop, significantly improving the practicality and user adoption of the technical solution.

[0055] This invention uses time-series diagnostics and multi-dimensional models to ensure that the driver's intent as understood by the platform is always consistent with their actual state, greatly improving the matching accuracy of cargo recommendations.

[0056] This invention enables the system to proactively adapt to the driver, reducing the tedious manual modification of settings by the driver and improving the efficiency of finding goods.

[0057] 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.

[0058] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An intelligent diagnosis and proactive intervention system based on drivers' reported freight-seeking intentions, characterized in that: include: The time-series diagnostic trigger module is used to build a time-series-based event triggering mechanism that automatically triggers different types of diagnostic tasks at different time points after the driver reports his intention to find cargo. The multi-dimensional intent invalidation judgment module is used to determine whether the driver's original intent has become invalid during the process of triggering diagnostic tasks; The scenario-based intelligent outreach and closed-loop module is used to select an outreach strategy and guide the user to complete the intent update based on the diagnostic results generated by the time-sequential diagnostic outreach module, thus forming an operation closed loop. The multi-dimensional intent failure judgment module is used to define the geofence of the area where the original intent frequently runs; When the real-time location falls within the area frequently visited by the original intent, the intent is deemed valid. When the location deviates from the intended frequently traveled area and the distance exceeds the distance threshold, it is determined that "location intention has failed" and the determination result is fed back to the time-series diagnostic touch module. The multi-dimensional intent failure judgment module is used to calculate the driver's preference score for different routes based on the driver's real-time behavior data and the preference recognition model. If the preference score of one or more routes is significantly higher than the score of the original intended route, it is judged as "preference intent failure" and the judgment result is fed back to the time-series diagnostic touch module.

2. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 1, characterized in that: The time-series diagnostic touch module is also used to check the exposure and feedback of the first batch of recommended cargo sources based on the initial intent after the intent is reported. If the click rate is lower than the threshold, it is preliminarily judged that the intent may deviate from the driver's immediate needs, and the diagnostic result is generated.

3. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 2, characterized in that: The time-series diagnostic touch module is also used to call the driver's GPS positioning after the intention is reported, determine whether the current position deviates significantly from the original intention's frequently traveled area, and generate the diagnostic result.

4. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 3, characterized in that: The time-series diagnostic module is also used to collect and analyze the driver's operational behavior sequence within the time window after the intent is reported, calculate its new potential preferences, and generate the diagnostic results.

5. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 1, characterized in that: The scenario-based intelligent outreach and closed-loop module is used to push different types of intent update information to driver users through different channel ports using a multi-channel outreach strategy. This includes: important but not urgent intent update suggestions, urgent location change reminders, and suggestions for changes in behavior preferences when the driver actively uses the system app.

6. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 5, characterized in that: The scenario-based intelligent outreach and closed-loop module has a daily frequency limit and a weekly frequency limit.

7. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 6, characterized in that: The scenario-based intelligent outreach and closed-loop module is also used to set a "one-click update departure point" button in the location change reminder. After clicking, it will directly jump to the goods search settings page and pre-fill the real-time location with the new departure point.

8. The intelligent diagnosis and proactive intervention system based on driver's cargo-finding intention reporting as described in claim 7, characterized in that: The scenario-based intelligent outreach and closed-loop module is also used to set a "Go to modify route" button in the preference change suggestion. After clicking, a new route with a high score will be pre-selected in the route preference page.

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