Silver age e key-to-communication multi-source collaborative scheduling method and system for community microcirculation

Abstract

The invention discloses a community microcirculation-oriented silver age e key-to-communication multi-source collaborative scheduling method and system. The method relates to the technical field of multi-source cooperative scheduling, and comprises the following steps: mistaken touch prevention demand acquisition, demand priority determination, intelligent matching and path planning, state synchronization and service closed loop, and manual scheduling intervention and degradation service. According to the invention, the old-friendly terminal acquires the demand, and judges whether the pressing time delay reaches the standard so as to output the calling signal; marking a scheduling priority according to the age of the user, matching a vehicle in combination with a preset time delay and a real-time road condition, and planning a blockage avoiding path; the predicted arrival time is synchronously pushed, and a feedback state is broadcasted through a terminal indicating lamp and a dialect; and if the vehicle matching fails, manual scheduling is triggered, so that a service closed loop is ensured, the adaptation effectiveness of the bank age e-key multi-source cooperative scheduling is improved, and the problem of low adaptation effectiveness of the bank age e-key multi-source cooperative scheduling in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of multi-source collaborative scheduling technology, and in particular to a multi-source collaborative scheduling method and system for elderly e-key communication oriented towards community micro-circulation. Background Technology

[0002] In community-based elderly care transportation services for senior citizens, physical terminals suffer from insufficient adaptability, high accidental touch rates, and low acceptance, resulting in low penetration of smart devices among the elderly. Traditional physical terminals are designed without considering the cognitive and physiological characteristics of seniors, making it difficult for them to judge device status (e.g., whether a call has been successfully made or if a vehicle is about to arrive), leading to low success rates. Furthermore, the lack of specific anti-accidental touch designs makes it easy for seniors to accidentally trigger calls due to unintentional touches. Additionally, existing smart device products fail to focus on the core needs of seniors for "simple operation and direct feedback," instead overemphasizing complex functions such as touchscreen controls and multi-step setups, leading to user rejection due to complexity and further reducing device acceptance.

[0003] Secondly, the existing traffic vehicle route planning model is not adapted to the resource capabilities of implementing entities such as ordinary university teachers and street offices. The model is designed to achieve "global optimality" in large-scale city-level traffic scheduling, which requires consideration of complex modules such as multi-objective optimization and reinforcement learning. It has serious computational redundancy and is difficult to support such complex algorithms.

[0004] Finally, the difficulties in cross-departmental coordination and insufficient coverage density are prominent issues, resulting in low dispatch efficiency and incomplete service coverage. On the one hand, the lack of a complementary design of "intelligent + manual" means that the special characteristics of elderly care service scenarios, such as the inability of the elderly to clearly express their needs and the frequent occurrence of emergencies, are not taken into account. Traditional traffic dispatch rules such as "shortest path priority" are still used, resulting in dispatch results that do not meet the goals of public service. When encountering special circumstances such as temporary vehicle breakdowns or urgent changes in the needs of the elderly, intelligent dispatch is prone to failure and there is no rapid response channel. On the other hand, the lack of technical coordination mechanisms in cross-departmental collaboration makes communication efficiency low among multiple departments involved in elderly care transportation services, such as street management, bus operation, and community services. It is difficult to quickly integrate resources such as street micro-circulation buses and community stations to form a service loop. Moreover, the traditional bus station layout model is based on "covering population density" and does not take into account the high-frequency travel destinations and residential distribution characteristics of the elderly. As a result, some elderly people have no service terminals near their residences or the terminals are too far away, which cannot meet their daily travel needs. There is a problem of low effectiveness of multi-source collaborative dispatching of the Silver Age e-Key. Summary of the Invention

[0005] To address the technical problem of low adaptability of multi-source collaborative scheduling in existing technologies for the Silver Age e-Key System, this invention provides a multi-source collaborative scheduling method and system for the Silver Age e-Key System oriented towards community micro-circulation. The technical solution is as follows:

[0006] On the one hand, a multi-source collaborative scheduling method for the "Silver Age e-Key" system oriented towards community micro-circulation is provided. This method includes: S100, collecting demand from elderly-friendly terminals; deploying elderly-friendly terminals at target community bus stops; determining whether the delay of the target elderly user pressing the anti-accidental touch button exceeds a preset delay benchmark value; if so, outputting a call request signal; otherwise, not outputting; S101, upon receiving the call request signal from the elderly-friendly terminal, extracting the terminal identifier and preset high-frequency destination information from the call request signal; combining this with the target elderly user's profile to identify the user's age; determining whether the target elderly user's age is higher than a preset elderly age benchmark value; if so, marking it as a priority scheduling demand; otherwise, marking it as a regular scheduling demand; S102, matching vehicles according to the preset shortest waiting delay benchmark value and the scheduling demand; and based on real-time traffic information, matching vehicles... The target micro-circulation vehicle plans a route to avoid congested sections and pushes the planned route to the vehicle terminal; S103, a dynamically optimal route is planned for the matched target micro-circulation vehicle, and the estimated arrival time is transmitted to the elderly-friendly terminal. The estimated arrival time is announced via dialect voice broadcast, and the red, yellow, and green status indicator lights are switched to green; when the target micro-circulation vehicle arrives at the corresponding target community bus stop, the red, yellow, and green status indicator lights are switched to red, and the vehicle is announced via dialect voice broadcast; S104, if vehicle matching fails in step S102, an SMS notification is automatically triggered to send a dispatch assistance SMS to the preset administrator to rematch the target elderly user with a micro-circulation vehicle, and the coordination result is fed back to the elderly-friendly terminal to inform the target elderly user via dialect voice broadcast.

[0007] On the other hand, a multi-source collaborative scheduling system for the elderly, oriented towards community micro-circulation, is provided. This system includes: an anti-accidental touch demand collection module, a demand priority determination module, an intelligent matching and path planning module, a state synchronization and service closed-loop module, and a manual scheduling intervention and service degradation module. Specifically, the anti-accidental touch demand collection module is used to collect demands from elderly-friendly terminals deployed at target community bus stops. It determines whether the delay when the target elderly user presses the anti-accidental touch button exceeds a preset delay benchmark value. If so, it outputs a call request signal; otherwise, it does not. The demand priority determination module, upon receiving a call request signal from an elderly-friendly terminal, extracts the terminal identifier and preset high-frequency destination information from the call request signal. It then identifies the user's age based on the target elderly user's profile and determines whether the target elderly user's age is higher than a preset elderly age benchmark value. If so, it marks it as a priority scheduling demand; otherwise, it marks it as a regular scheduling demand. The intelligent matching and path planning module is used to determine the optimal route based on a preset shortest path. The system matches vehicles based on the waiting latency baseline and scheduling requirements. Based on real-time traffic information, it plans a route to avoid congested sections for the matched target micro-circulation vehicle and pushes the planned route to the vehicle. The status synchronization and service loop module plans the dynamically optimal route for the matched target micro-circulation vehicle, transmits the estimated arrival time to the elderly-friendly terminal, and initiates a dialect voice broadcast of the estimated arrival time, while simultaneously switching the red, yellow, and green status indicator lights to green. When the target micro-circulation vehicle arrives at the corresponding target community bus stop, the red, yellow, and green status indicator lights switch to red, and a dialect voice broadcast announces the vehicle's arrival. The manual dispatch intervention and degraded service module automatically triggers an SMS notification if vehicle matching fails in step S102, sending a dispatch assistance SMS to a preset administrator to rematch the target elderly user with a micro-circulation vehicle and feeding back the coordination result to the elderly-friendly terminal, informing the target elderly user via dialect voice broadcast.

[0008] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0009] 1. By employing age-friendly terminal interaction logic and a demand priority determination mechanism, the acceptance and success rate of elderly transportation services have been improved. An anti-accidental touch design, coupled with a three-color status indicator (yellow light for calling, green light for en route, red light for arrival) and a dialect voice broadcast, provides a composite feedback mode. This addresses the issue of accidental touches caused by trembling hands in the elderly, and eliminates the digital divide and language barriers through traffic signal-style interaction tailored to their cognitive habits and dialect adaptation, ensuring a high success rate. Simultaneously, a waiting delay adjustment mechanism based on user age priority and dynamic adaptation to concurrent demands achieves precise scheduling: "ensuring baseline response speed during low demand, reducing waiting time during medium demand, and ensuring service coverage during high demand." This satisfies the urgent travel needs of the elderly while balancing service efficiency under different demand intensities, reducing average waiting time for seniors and significantly improving the accessibility and relevance of age-friendly services.

[0010] 2. By innovatively integrating a lightweight intelligent scheduling algorithm with a dynamic path planning mechanism, dual guarantees of scheduling efficiency and driving safety are achieved in community micro-circulation scenarios. On the one hand, the traditional complex VRP model is broken down into a three-step decision chain of "demand collection - vehicle matching - path push," eliminating redundant calculation modules. Combined with a lightweight deployment scheme, ordinary servers or even terminals can handle scheduling calculations, solving the implementation problem of limited resources for community-level implementers. On the other hand, during path planning, feature road segments such as high-frequency crossings and intersections without traffic lights are extracted and priority avoidance tags are added. The speed of high-frequency crossings is reduced, and the safety and efficiency weights of path selection are dynamically adjusted based on the load rate (prioritizing safety under low load and balancing safety and efficiency under medium load). This ensures that the planned path avoids congested road segments, shortens travel time, and minimizes crossings of high-risk road segments, meeting the core safety needs of elderly travelers. In addition, the dual-mode scheduling mechanism of intelligent matching and manual intervention (automatically notifying the administrator and shrinking the service scope to high-frequency sites after intelligent matching failure) improves the scheduling success rate, avoids service request loss, and ensures the stability and reliability of the scheduling system.

[0011] 3. By implementing a full-process status synchronization and cross-departmental resource integration mechanism, a closed-loop service chain of "terminal-platform-vehicle-administrator" has been constructed, significantly improving the collaborative efficiency and coverage quality of community elderly transportation services. At the service loop level, from call triggering, vehicle matching, and route planning to real-time updates of estimated arrival time, vehicle arrival notifications, and automatic reset of status indicator lights after service completion, each link achieves information synchronization between the terminal and the platform. Through dual feedback of dialect voice broadcasts and indicator light status switching, the elderly can clearly understand the service progress and eliminate travel uncertainty. At the resource collaboration level, a connection mechanism among multiple departments such as street management, bus operation, and community services has been established through technical means. Existing micro-circulation bus resources in the street have been integrated to form a service network. At the same time, station layout has been optimized based on the high-frequency travel destinations of the elderly (hospitals, markets, community centers), and the service scope shrinkage and dedicated vehicle pool matching mechanism when manual dispatching intervenes have further improved cross-departmental coordination efficiency, forming a rapidly replicable "street-bus-elderly" collaborative social model, providing a feasible path for the large-scale promotion of community elderly transportation services. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 A flowchart of a multi-source collaborative scheduling method for elderly people using the "e-key" feature, oriented towards community microcirculation, is provided in an embodiment of this application.

[0014] Figure 2 This is a schematic diagram of the structure of the Silver Age e-Key Multi-Source Collaborative Scheduling System for Community Micro-Circulation provided in an embodiment of this application. Detailed Implementation

[0015] The technical solution provided in this application will now be described with reference to the accompanying drawings.

[0016] To facilitate understanding of the embodiments of this application, the following points will be explained first:

[0017] First, in this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates an "or" relationship between the preceding and following related objects, but it does not exclude the possibility of indicating an "and" relationship; the specific meaning can be understood in context. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c; a and b; a and c; b and c; or a and b and c. Here, a, b, and c can be single or multiple.

[0018] Second, the use of prefixes such as "first" and "second" in this application is solely for the purpose of distinguishing and describing different things belonging to the same category, and does not constrain the order, size, or quantity of things. For example, "first message" and "second message" are simply different messages, and there is no chronological, size, or priority relationship between them.

[0019] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0020] like Figure 1 The diagram shown is a flowchart of a multi-source collaborative scheduling method for the elderly e-key communication system oriented towards community micro-circulation, provided in an embodiment of this application. The method includes the following steps:

[0021] S100 collects requirements for elderly-friendly terminals. The elderly-friendly terminals are deployed at bus stops in the target community. It determines whether the delay when the target elderly user presses the anti-accidental touch button exceeds the preset delay benchmark value. If so, it outputs a call request signal; otherwise, it does not output a signal.

[0022] It should be noted that the elderly-friendly terminal includes an anti-accidental touch button, red, yellow, and green status indicator lights, and dialect voice broadcast. If the target elderly user presses the anti-accidental touch button for a delay greater than or equal to a preset delay benchmark value, a call request signal is output, the red, yellow, and green status indicator lights switch to yellow, and dialect voice broadcast is activated to indicate that a call is in progress. The call request signal includes the terminal identifier and preset high-frequency destination information, which is at least one of hospitals, farmers' markets, and community centers. If the target elderly user presses the anti-accidental touch button for a delay less than the preset delay benchmark value, no call request signal is output, the red, yellow, and green status indicator lights remain in the initial standby green state, and dialect voice broadcast is not activated.

[0023] It should be understood that, firstly, in the initial state of the terminal, the red, yellow, and green status indicator lights remain in green standby mode. This design aligns with the elderly's inherent understanding of traffic lights, allowing them to quickly determine the device's status through color without additional learning, thus reducing the cognitive cost of operation from the outset. When the target elderly user needs to travel, they need to press the terminal's anti-accidental touch button. The terminal's built-in delay detection unit monitors the pressing duration in real time. If the detected pressing delay is greater than or equal to a preset delay benchmark value (e.g., 3 seconds), a call request signal is immediately triggered, and the red, yellow, and green status indicator lights simultaneously switch to yellow. Furthermore, the dialect voice broadcast module automatically starts and announces "Calling in progress." This dual feedback mechanism, on the one hand, simultaneously informs the user through visual (yellow light) and auditory (dialect voice) feedback that the call has been successfully initiated, solving the problem of delayed information reception caused by visual or hearing impairment in the elderly. On the other hand, the dialect broadcast adapts to the Mandarin communication barriers faced by some elderly individuals, ensuring accurate and effective information transmission. The included terminal identifier helps the dispatch platform quickly locate the site from which the request was initiated. Preset high-frequency destinations (at least one of hospitals, farmers' markets, and community centers) simplify the process of expressing needs for the elderly, allowing them to clearly identify their core travel direction without additional operations, thus significantly improving the efficiency of demand collection. If the terminal detects that the delay of the user pressing the anti-accidental touch button is less than the preset delay benchmark value, it is determined to be an accidental touch operation. At this time, no call request signal is output, and the red, yellow, and green status indicator lights remain in the initial standby green state, and dialect voice broadcast is not activated. This design specifically addresses the physiological defects of elderly people, such as trembling hands and slow reaction, which easily lead to accidental touches. It effectively avoids the waste of dispatch resources and social complaints caused by accidental triggering, significantly improving the reliability of terminal use. Finally, through the end-to-end adaptation design of press detection-status feedback-demand transmission, the success rate of operation for the elderly is improved, effectively solving the digital divide problem that the elderly refuse to use smart devices due to complex operation and easy accidental touch.

[0024] S101: After receiving the call request signal output by the elderly-friendly terminal, extract the terminal identifier and preset high-frequency destination information from the call request signal, identify the user's age by combining it with the target elderly user profile, and determine whether the target elderly user's age is higher than the preset elderly age benchmark value. If so, mark it as a priority scheduling request; otherwise, mark it as a regular scheduling request.

[0025] S102: Based on the preset minimum waiting time benchmark and scheduling requirements, vehicles are matched. According to real-time traffic information, a route avoiding congested sections is planned for the matched micro-circulation vehicles, and the planned route is pushed to the vehicle. This involves using a lightweight vehicle route planning algorithm, which is broken down into a three-step decision chain: demand collection, vehicle matching, and route push, removing multi-objective optimization and reinforcement learning modules. The scheduling platform, based on the integrated real-time location data, idle status data, and road congestion information of micro-circulation buses within the community, matches target micro-circulation buses according to the "shortest waiting time + age priority" rule for priority scheduling needs, and according to the "shortest waiting time" rule for regular scheduling needs. Real-time location data of micro-circulation buses is obtained through the vehicle positioning module, and road congestion information is obtained through the Gaode open API. If intelligent matching fails, the platform automatically triggers an SMS notification to the street administrator for manual scheduling, ensuring that service requests are not lost.

[0026] Furthermore, the specific process for matching vehicles based on the preset minimum waiting time baseline and scheduling requirements is as follows:

[0027] The vehicle matching process includes demand collection, matching of available vehicles, and route recommendation;

[0028] Real-time traffic information includes the vehicle's real-time location, current speed, number of remaining seats, and current passenger status, which includes empty, half-loaded, and fully loaded.

[0029] At the current moment, the total number of all unanswered call requests in the reservation pool is recorded as the concurrent demand number. A mapping relationship between the demand number and the waiting delay is established. If the concurrent demand number is less than or equal to the lower limit of the demand number, the current waiting delay is set to the preset baseline waiting delay.

[0030] If the number of concurrent demands is within the demand base range, the current number of concurrent demands is input into the demand-waiting delay mapping relationship, and the delay reduction coefficient is output. The preset base waiting delay and the delay reduction coefficient are combined to obtain the target waiting delay, so as to reduce the waiting time and match nearby vehicles. The demand base range represents the open interval formed by the lower limit of the demand base and the upper limit of the demand base.

[0031] If the number of concurrent requests is greater than or equal to the upper limit of the request base, the current number of concurrent requests is input into the request-waiting delay mapping relationship, and the delay extension coefficient is output. The preset base waiting delay and the delay extension coefficient are combined to obtain the target waiting delay, so as to relax the waiting time constraint and match the target vehicle at a long distance.

[0032] In this embodiment, the vehicle matching process follows a three-stage core logic of demand collection, available vehicle matching, and route push, with multi-dimensional real-time traffic information serving as the decision support throughout. The specific steps and technical effects are as follows: First, demand collection is performed. The dispatching platform aggregates all unanswered call requests in the reservation pool in real time, defining their total number as the concurrent demand count. Simultaneously, complete real-time traffic information is collected, including the real-time location, current speed, remaining seats, and passenger status (empty / half-loaded / fully loaded) of all micro-circulation buses within the community. This accurate dynamic data provides a comprehensive basis for subsequent vehicle matching decisions, avoiding delays due to information limitations. The platform addresses the issue of mismatched demand due to information lag. Next, it enters the idle vehicle matching phase. The platform pre-establishes a demand-waiting-latency mapping relationship and dynamically adjusts the waiting-latency constraint based on real-time changes in concurrent demand: if the concurrent demand is less than or equal to the lower limit of the demand baseline, it indicates that the current service demand is at a low point, and the platform sets the current waiting-latency to the preset baseline waiting-latency to ensure the stability of service response speed and avoid fluctuations in the waiting experience for elderly users due to excessive adjustments; if the concurrent demand is within the open interval formed by the lower and upper limits of the demand baseline (i.e., a medium demand state), then the concurrent demand is input into the preset demand-latency... In the waiting delay mapping relationship, the corresponding delay reduction coefficient is automatically output. This design can specifically shorten the waiting time constraint, guiding the platform to prioritize matching idle vehicles closer to the requesting station, significantly improving service response efficiency under medium demand conditions and reducing unnecessary waiting for the elderly. If the number of concurrent requests is greater than or equal to the baseline upper limit of the number of requests, it indicates that the service demand has entered a peak state. At this time, the number of concurrent requests is input into the mapping relationship to output the delay extension coefficient, resulting in a relaxed target waiting delay. This adjustment allows the platform to match idle vehicles that are relatively far away, effectively avoiding scheduling failures caused by overly strict waiting time constraints and ensuring the integrity of service coverage during peak periods. Finally, the route is pushed. Based on the matching results and real-time traffic information, the platform plans the optimal driving route for the target vehicle and pushes it to the vehicle terminal. The entire vehicle matching process, through the dynamic adaptation of the number of concurrent requests and the waiting delay, balances the service efficiency and scheduling success rate under different demand intensities. With the accurate support of real-time traffic information, it ensures that the matched vehicles can arrive efficiently within the target waiting delay, effectively improving the scheduling accuracy and user satisfaction of community micro-circulation elderly transportation services.

[0033] Furthermore, the specific steps for planning driving routes to avoid congested sections for the target micro-circulation vehicles are as follows:

[0034] Two types of characteristic road segments within the target community are extracted and labeled. The characteristic road segments include high-frequency through road segments and intersections without traffic lights. Priority avoidance geographical labels are added to the two types of characteristic road segments and linked to the road network database of the predefined dispatch platform.

[0035] For high-frequency through traffic segments, the path speed threshold is reduced. Specifically, a mapping relationship is established between the feature segments and the predefined path speed threshold. The high-frequency through traffic segments are input into the mapping relationship, and the speed reduction coefficient is output. The current path speed threshold and the speed reduction coefficient are combined to obtain the target path speed threshold.

[0036] For intersections without traffic lights, the current path speed threshold is maintained.

[0037] Based on the adjusted path speed threshold, the path travel time is obtained, and the path with the shortest travel time and the fewest priority avoidance sections is selected as the final planned path and pushed to the target micro-circulation vehicle.

[0038] In this embodiment, firstly, the dispatching platform comprehensively filters and labels roads within the target community, accurately extracting two types of key characteristic road segments: high-frequency crossing segments frequented by elderly people and pedestrians, and intersections without traffic lights where vehicles must slow down and yield to pedestrians. Then, "priority avoidance" geographic tags are added to these two types of road segments. These tags contain key information such as the road segment's start and end coordinates and attribute type, and are linked to a predefined road network database of the dispatching platform. This design enables rapid retrieval and accurate identification of characteristic road segments, providing a clear basis for safe avoidance in subsequent route planning and mitigating high-risk road segments for elderly travelers from the outset. Next, differentiated speed threshold adjustments are made for different types of characteristic road segments: for high-frequency crossing segments, the platform pre-establishes a mapping relationship between characteristic road segments and predefined route speed thresholds. After inputting the identified high-frequency crossing segments into this mapping relationship, the platform automatically outputs the appropriate speed threshold. The platform employs a corresponding speed reduction factor, and the reduced speed threshold simulates actual deceleration and avoidance scenarios for vehicles in pedestrian-dense areas, effectively reducing driving risks and ensuring the safety of elderly travelers. For intersections without traffic lights, considering that while avoidance is necessary, continuous deceleration is not required, the platform maintains the current path speed threshold, balancing safety needs with avoiding excessive deceleration that could reduce traffic efficiency. Finally, based on the adjusted path speed threshold and the length of each road segment, the platform calculates the accurate travel time for each candidate path and counts the number of priority avoidance segments along each path. Ultimately, the platform selects the optimal path with the shortest travel time and the fewest priority avoidance segments and pushes it to the target micro-circulation vehicle. This decision-making logic ensures that vehicles can avoid congestion and travel efficiently, reducing the travel time for the elderly, while minimizing the probability of passing through high-risk road segments. This achieves a dual optimization of safety and efficiency for elderly-friendly travel, truly meeting the core needs of elderly travelers.

[0039] As a further specific explanation, planning driving routes to avoid congested sections for the target micro-circulation vehicles also includes:

[0040] Establish a dynamic mapping relationship between weight coefficients and scheduling demand intensity. The ratio of concurrent demand to available micro-circulation vehicles in the current scheduling cycle is recorded as the load rate. If the load rate is less than or equal to the lower limit of the load rate benchmark, the current priority avoidance segment number weight is set as the critical upper limit of the target priority avoidance segment number weight, and the path travel time weight is set as the difference between 1 and the critical upper limit of the target priority avoidance segment number weight. Path selection prioritizes minimizing this value.

[0041] If the load rate is within the load rate benchmark range, the current priority avoidance segment number weight is set to the critical lower limit of the target priority avoidance segment number weight, and the path travel time weight is set to the difference between 1 and the critical lower limit of the target priority avoidance segment number weight, in order to balance safety and efficiency. The load rate benchmark range represents the open interval formed by the load rate benchmark lower limit and the load rate benchmark upper limit.

[0042] If the load rate is greater than or equal to the upper limit of the load rate benchmark, an alert will be sent to the relevant operations and maintenance personnel.

[0043] In this embodiment, firstly, the scheduling platform pre-establishes a dynamic mapping relationship between weight coefficients and scheduling demand intensity, clarifying the safety and efficiency priority adaptation rules for path selection under different demand intensities. Simultaneously, the ratio of concurrent demand (total number of unanswered call requests in the reservation pool) to the number of available micro-circulation vehicles within the current scheduling cycle is defined as the load rate. The load rate intuitively quantifies the current busyness of the scheduling system, providing an objective and quantifiable basis for weight adjustment, avoiding subjectivity and blindness in weight setting. Next, differentiated weight allocation is performed based on the real-time calculation results of the load rate: if the load rate is less than or equal to the lower limit of the load rate benchmark, it indicates that the current scheduling demand is in a low-peak state, and the system has sufficient scheduling margin. In this case, the weight of the number of priority avoidance road segments is set to the critical upper limit of the target priority avoidance road segment number weight, while the path travel time weight is set to 1. The difference from this critical upper limit (i.e., the travel time weight is at a low level) prioritizes minimizing the number of priority avoidance road segments. This design maximizes the safety of elderly travelers in low-demand scenarios by prioritizing the avoidance of high-frequency crossings and intersections without traffic lights, aligning with the core demand of "safety first" for elderly travelers. If the load rate is in the open interval formed by the lower and upper limits of the load rate benchmark (i.e., medium demand state), the weight of the number of priority avoidance road segments is set to the critical lower limit of the target priority avoidance road segment weight, and the path travel time weight is set to 1. The difference between the threshold and the lower limit ensures a reasonable balance between safety and efficiency weights, achieving a dynamic equilibrium between safety and traffic efficiency in route selection. This avoids both excessive pursuit of safety leading to traffic delays and prioritizing efficiency at the expense of elderly travel safety. If the load rate is greater than or equal to the upper limit of the load rate benchmark, it indicates that the current scheduling demand has exceeded the system's capacity. At this time, the platform immediately sends an early warning message to relevant maintenance personnel. The warning message includes key data such as the current load rate, the number of concurrent requests, and the number of available vehicles, enabling maintenance personnel to quickly grasp the system overload situation and take timely countermeasures such as dispatching more vehicles and adjusting the scheduling range. This effectively avoids scheduling failures and service quality degradation caused by system overload, ensuring the stability and sustainability of elderly-friendly transportation services.

[0044] S103 will plan the dynamic optimal driving route for the matched target micro-circulation vehicle, transmit the estimated arrival time to the elderly-friendly terminal, and start the dialect voice broadcast of the estimated arrival time. At the same time, the red, yellow and green status indicator lights will be switched to green. When the target micro-circulation vehicle arrives at the corresponding target community bus stop, the red, yellow and green status indicator lights will be switched to red, and the dialect voice broadcast of the vehicle's arrival will be started.

[0045] Furthermore, step S103 includes: after completing vehicle matching and route planning, pushing the dynamically optimal driving route to the target micro-circulation vehicle, and sending the estimated arrival time information and vehicle status command to the elderly-friendly terminal, triggering the elderly-friendly terminal's composite status feedback, specifically:

[0046] Switch the red, yellow, and green status indicator light from the current yellow light to the green light. The yellow light indicates that the call is in progress, and the green light indicates that the vehicle has been matched and is on its way. The estimated arrival time will also be announced in the local dialect.

[0047] If route replanning is triggered based on real-time traffic information, resulting in a change in the estimated arrival time and the difference in the change exceeds the preset difference threshold, the new estimated arrival time will be sent to the elderly-friendly terminal again. While maintaining the green light status, the elderly-friendly terminal will start a new round of dialect voice broadcast to notify the time change.

[0048] In this embodiment, firstly, the platform accurately pushes the calculated dynamic optimal driving route to the target micro-circulation vehicle, ensuring that the driver receives real-time driving guidance to avoid congestion and achieve efficient passage, thus guaranteeing timely arrival at the station. Simultaneously, the platform sends the estimated arrival time information and the status command "vehicle matched, en route" to the elderly-friendly terminal that initiated the call, triggering the terminal's composite status feedback mechanism. The terminal automatically switches the yellow light currently indicating "calling" to a green light representing "vehicle en route," and clearly announces the estimated arrival time (e.g., "vehicle is en route") through a dialect voice broadcast module. The system features a dual feedback mechanism: "The vehicle will arrive in 10 minutes." This design aligns with the elderly's existing understanding of traffic lights, allowing them to quickly learn about service progress without additional learning. It also addresses the Mandarin communication barriers faced by some elderly individuals through dialect adaptation, ensuring accurate delivery of estimated arrival time information and effectively eliminating uncertainty and anxiety during the waiting process. Furthermore, during the vehicle's journey, the platform continuously monitors real-time traffic conditions. If sudden congestion, temporary traffic control, or other circumstances trigger route replanning, and the new route causes a change in estimated arrival time exceeding a preset threshold (e.g., 3 minutes), the system will detect any issues. (Minutes later), the platform will immediately calculate the new estimated arrival time and resend it to the age-friendly terminal. At this time, the terminal will remain in a green light state to maintain the elderly's stable perception that "the vehicle is on its way." At the same time, a new round of dialect voice broadcast will be initiated to inform the elderly of the time change (such as "Road congestion, the vehicle is expected to arrive in 15 minutes"). This real-time dynamic adjustment and feedback mechanism avoids the problem of the elderly waiting for the wrong vehicle or missing the ride due to the failure to notify them of the time change in a timely manner, ensuring the timeliness and accuracy of service information. The entire process, through the closed-loop design of "route push - status feedback - dynamic update", not only ensures the efficiency of vehicle operation, but also allows the elderly to clearly and accurately grasp the progress of the entire service process through the age-friendly composite feedback mode, significantly improving the transparency of age-friendly services and the user experience.

[0049] As a further specific explanation, step S103 also includes: when the target micro-circulation vehicle arrives at the target community bus stop and stops, it automatically determines that it has entered the electronic fence range of the station and automatically triggers the sending of a vehicle arrival confirmation signal to the dispatch platform.

[0050] After receiving the vehicle arrival confirmation signal, the dispatch platform immediately sends an arrival instruction packet, which specifically involves switching the red, yellow, and green status indicator lights from green to red to indicate that the vehicle has arrived, and broadcasting a report to the target elderly user in a local dialect.

[0051] If the red light status and dialect voice broadcast continue within the first threshold of the preset broadcast duration, the status indicator light will switch back to yellow (waiting for new calls). If no new long press operation is triggered, the indicator light will automatically turn off and return to the initial standby state (green light) after the second threshold of the preset broadcast duration, thus completing a single service loop.

[0052] In this embodiment, when the target micro-circulation vehicle arrives at the target community bus stop and stops, the positioning module on the vehicle will automatically detect whether it has entered the preset electronic fence range of the station. Once it is determined that it has entered the range, the arrival detection mechanism is immediately triggered, and a vehicle arrival confirmation signal containing the vehicle number, station identifier, and actual arrival timestamp is sent to the dispatch platform. This electronic fence detection method ensures the accuracy of vehicle arrival judgment and avoids information synchronization deviations caused by delays or false reports due to manual reporting. After receiving the vehicle arrival confirmation signal in real time, the dispatch platform immediately generates and sends an arrival instruction packet to the corresponding age-friendly terminal without manual intervention. The instruction packet triggers the terminal to perform a dual state feedback operation: on the one hand, the green light currently indicating "vehicle on the way" is switched to a red light indicating "vehicle has arrived". Using the traffic light logic familiar to the elderly, they can visually know that the vehicle has arrived without having to understand complex signs; on the other hand, the dialect voice broadcast function is activated to clearly announce in the dialect that "vehicle has arrived" in a way that is easy for the elderly to understand. The "Arrival" feature addresses the issue of delayed information reception for some elderly users due to hearing loss or Mandarin communication difficulties. The dual feedback mechanism significantly improves the effectiveness of information delivery. After receiving the arrival notification, the terminal maintains a red light and dialect voice broadcast until the preset broadcast duration reaches the first threshold (e.g., 30 seconds), ensuring the elderly have sufficient time to perceive the vehicle's arrival and preventing omissions due to insufficient broadcast duration. The terminal then automatically switches the status indicator back to yellow, entering a ready state to await new calls. If no new user triggers a call request by long-pressing the anti-accidental touch button within the preset second threshold (e.g., 5 minutes), the indicator automatically turns off and returns to the initial standby green light state. This achieves a complete closed loop for a single service, from call initiation, vehicle matching, on-the-way feedback to arrival notification. Furthermore, the automatic reset design ensures the terminal is always available, eliminating the need for manual operation and maintenance. This enhances the ease of use and service continuity, allowing elderly users to clearly understand the service progress throughout the process, further improving the experience and reliability of age-friendly services.

[0053] S104. If vehicle matching fails in step S102, an SMS notification is automatically triggered, sending a dispatch assistance SMS to the preset administrator. At the same time, the service area is narrowed to three preset high-frequency stations, which correspond to a hospital, a vegetable market, and a community center, respectively. After receiving the dispatch assistance SMS, the preset administrator re-matches a micro-circulation vehicle for the target elderly user and feeds back the coordination result to the elderly-friendly terminal, broadcasting the report to the target elderly user in a local dialect.

[0054] Furthermore, if vehicle matching fails in step S102, the specific steps for automatically triggering an SMS notification are as follows:

[0055] If the dispatch platform fails to find an available micro-circulation vehicle within the preset matching time limit based on the preset matching rules (shortest waiting time and age above the preset benchmark value take priority), it will determine that the intelligent matching has failed and immediately extract and encapsulate the following information of the current request, including: the unique identifier of the requester, the preset high-frequency destination, the timestamp of the matching failure, and the user's age.

[0056] The encapsulated information is filled into a preset SMS template and automatically sent to one or more preset administrators. While sending the assistance SMS, the dispatch platform automatically narrows the dispatchable range of this call request from the entire community road network to the service area covered by the predefined high-frequency stations. The predefined high-frequency stations correspond to hospitals, vegetable markets, and community centers, and the platform will only retry matching from the micro-circulation vehicle pool currently serving the high-frequency stations.

[0057] After receiving a dispatch assistance SMS, the default administrator will reassign a vehicle for the call request. After successful assignment, the default administrator will submit the assignment result to the dispatch platform through the management terminal. The assignment result includes the assigned vehicle number and the latest estimated arrival time.

[0058] After receiving the submitted assignment result, the dispatch platform immediately sends a notification instruction to the corresponding elderly-friendly terminal and starts dialect voice broadcasting. The red, yellow, and green status indicator lights remain yellow (calling) until a vehicle arrival confirmation signal is received, at which point the red, yellow, and green status indicator lights switch.

[0059] In this embodiment, during vehicle matching, the dispatch platform strictly adheres to the preset matching rule of "priority given to vehicles with the shortest waiting time and those exceeding a preset age threshold." A preset matching time limit is also set to control response efficiency. If no suitable available micro-circulation vehicle is found within this time limit, the system automatically determines that intelligent matching has failed. This combination of rule and time limit ensures the priority travel rights of elderly users while avoiding a decline in service experience due to unlimited waiting. After a matching failure, the platform immediately initiates an information extraction and encapsulation process to quickly capture the core information of the current call request, including the unique identifier of the request (used to accurately locate the request source terminal), the preset high-frequency destination (clearly defining the core travel needs of the elderly), and the matching details. The system includes a failure timestamp (for tracing scheduling anomalies) and user age (to provide priority reference for manual dispatching), ensuring administrators can quickly grasp complete request information and improve coordination efficiency when manual intervention occurs. Subsequently, the platform automatically populates the standardized information into a preset SMS template and sends it instantly to one or more preset administrators, achieving rapid synchronization of fault information. Simultaneously, the dispatch platform automatically activates a service range contraction mechanism, precisely narrowing the dispatchable range of this call request from the entire community road network to the service area covered by predefined high-frequency stations (hospitals, markets, community centers), and retrying matching only from the micro-circulation vehicle pool currently serving these high-frequency stations. This contraction strategy focuses on core service areas. Domain-specific and dedicated vehicle resources significantly reduce the search scope and difficulty of secondary matching, improving the success rate of manual dispatch. Upon receiving a dispatch assistance SMS, the administrator, based on the complete request information in the SMS and combined with the current vehicle distribution and operational status, quickly reassigns a suitable micro-circulation vehicle to the call request. After successful assignment, the administrator submits the assignment result, including the assigned vehicle number and the latest estimated arrival time, to the dispatch platform via the management terminal, ensuring accurate feedback of dispatch information. Upon receiving the assignment result in real time, the dispatch platform immediately sends a notification command to the corresponding age-friendly terminal. The terminal then activates a dialect voice broadcast, clearly informing the elderly that the vehicle has been reassigned and the latest estimated arrival time, while the red, yellow, and green status indicator lights remain on. The yellow light indicating "calling" remains active until a vehicle arrival confirmation signal is received, at which point the status changes. This status is maintained in conjunction with voice notifications, ensuring that seniors are aware that service is uninterrupted, alleviating anxiety, while dialect-based announcements ensure accurate and timely information delivery. The entire process employs a closed-loop design of "intelligent matching failure trigger - rapid information packaging and push - precise service scope narrowing - manual assignment - terminal status feedback," constructing a dual safety net mechanism of "intelligent and manual" support. This effectively prevents service request loss due to intelligent matching failures, ensuring effective response to the travel needs of elderly individuals. Furthermore, standardized information transmission and service scope narrowing significantly improve the efficiency of cross-departmental collaborative scheduling, ensuring the stability and continuity of age-friendly transportation services.

[0060] like Figure 2 The diagram shows the structure of the multi-source collaborative scheduling system for elderly users (e-key) in a community micro-circulation, as provided in this application embodiment. It includes: an anti-accidental touch demand collection module, a demand priority determination module, an intelligent matching and path planning module, a state synchronization and service closed-loop module, and a manual scheduling intervention and degraded service module. The anti-accidental touch demand collection module is used to collect demands from elderly-friendly terminals deployed at target community bus stops. It determines whether the delay when the target elderly user presses the anti-accidental touch button exceeds a preset delay benchmark value. If so, it outputs a call request signal; otherwise, it does not. The demand priority determination module, upon receiving a call request signal from an elderly-friendly terminal, extracts the terminal identifier and preset high-frequency destination information from the call request signal, identifies the user's age based on the target elderly user's profile, and determines whether the target elderly user's age is higher than a preset elderly age benchmark value. If so, it marks it as a priority scheduling demand; otherwise, it marks it as a regular scheduling demand. The intelligent matching and path planning module is used to determine the priority of the scheduling system based on a preset high-frequency destination information. The system matches vehicles with short waiting time baseline values ​​and scheduling requirements. Based on real-time traffic information, it plans a route to avoid congested sections for the matched target micro-circulation vehicles and pushes the planned route to the vehicle. The status synchronization and service closed-loop module plans the dynamically optimal route for the matched target micro-circulation vehicles, transmits the estimated arrival time to the elderly-friendly terminal, and starts a dialect voice broadcast of the estimated arrival time, while switching the red, yellow, and green status indicator lights to green. When the target micro-circulation vehicle arrives at the corresponding target community bus stop, the red, yellow, and green status indicator lights switch to red, and a dialect voice broadcast announces the vehicle's arrival. The manual dispatch intervention and degraded service module automatically triggers an SMS notification if vehicle matching fails in step S102, sends a dispatch assistance SMS to a preset administrator, rematches a micro-circulation vehicle for the target elderly user, and feeds back the coordination result to the elderly-friendly terminal, notifying the target elderly user via dialect voice broadcast.

[0061] In this embodiment, through the collaborative linkage of the anti-accidental touch demand collection module, the demand priority determination module, the intelligent matching and route planning module, the state synchronization and service closed-loop module, and the manual dispatch intervention and service degradation module, a full-process elderly-friendly traffic dispatch system adapted to community micro-circulation scenarios is constructed, achieving multiple core technical effects: The anti-accidental touch demand collection module relies on the long-press delay determination mechanism of elderly-friendly terminals to accurately filter accidental touch operations, solving the problem of elderly people's trembling hands easily triggering accidental events, and lowering the operation threshold through zero-screen interaction design, ensuring that elderly users with different cognitive levels can easily initiate travel requests, greatly improving the accuracy and universality of demand collection; The demand priority determination module extracts the terminal identifier from the call request, preset high-frequency destination information, and associates it with the user's age profile to realize age-based demand classification, marking elderly users as priority dispatching needs, protecting the emergency travel rights of vulnerable elderly groups, tilting dispatching resources towards core needs, and improving the targeting of services; The intelligent matching and route planning module combines the preset shortest waiting delay benchmark value with real-time traffic information, and dynamically adjusts, etc. The system achieves efficient vehicle matching by controlling latency, while simultaneously planning optimal routes to avoid congested areas. This balances service efficiency under varying demand intensities and ensures timely vehicle delivery, keeping the average waiting time for seniors within a reasonable range. The status synchronization and service loop module provides dual feedback through dynamic switching of red, yellow, and green status indicator lights and dialect voice broadcasts, allowing elderly users to clearly understand the entire process status, including vehicle matching, en route, and arrival. This eliminates uncertainty during waiting, adapts to the cognitive habits and language communication needs of the elderly, and significantly improves the user experience. The manual dispatch intervention and degraded service module automatically triggers a manual assistance mechanism when intelligent matching fails. It notifies the administrator via SMS and narrows the service scope to high-frequency stations, quickly completing a second vehicle matching and providing feedback on the results. This avoids lost service requests and ensures the stability and continuity of the dispatch system. Ultimately, this forms a complete service loop from demand initiation, hierarchical dispatch, route planning to status feedback and backup guarantees, effectively addressing pain points such as the digital divide for the elderly, inefficient travel dispatch, and incomplete service coverage, providing efficient technical support for community-based elderly transportation services.

[0062] The various features and processes described above can be used independently of each other or can be combined in various ways. All possible combinations and sub-combinations are intended to fall within the scope of this disclosure. Furthermore, certain method or process blocks may be omitted in some embodiments. The methods and processes described herein are not limited to any particular order, and the blocks or states associated with them may be performed in other suitable orders. For example, the described blocks or states may be performed in an order different from the order specifically disclosed, or multiple blocks or states may be combined in a single block or state. Example blocks or states may be performed serially, in parallel, or in some other manner. Blocks or states may be added to or removed from the disclosed example embodiments. The exemplary systems and components described herein may be configured differently from those described. For example, elements may be added to, removed from, or rearranged compared to the disclosed example embodiments.

[0063] The various operations of the example methods described herein can be performed at least in part by an algorithm. This algorithm can be contained in program code or instructions stored in memory (e.g., the aforementioned non-transitory computer-readable storage medium). Such an algorithm may include a machine learning algorithm. In some embodiments, the machine learning algorithm may not be explicitly programmed into the computer to perform the function, but can learn from training data to create a predictive model that performs the function.

[0064] The various operations of the example methods described herein can be performed, at least in part, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors can constitute the engine of a processor implementation that operates to perform one or more of the operations or functions described herein.

[0065] Similarly, the methods described herein can be implemented at least in part by a processor, where one or more specific processors are examples of hardware. For example, at least some operations of a method can be performed by one or more processors or an engine implemented by a processor. Furthermore, one or more processors can also be operated to support the performance of related operations in a “cloud computing” environment or as “Software as a Service” (SaaS). For example, at least some operations can be performed by a set of computers (as an example of a machine including processors), where these operations are accessible via a network (e.g., the Internet) and via one or more suitable interfaces (e.g., application programming interfaces (APIs)).

[0066] The performance of certain operations can be distributed across processors, residing not only within a single machine but also deployed across multiple machines. In some example embodiments, the processor or processor-implemented engine may reside in a single geographic location (e.g., within a home environment, office environment, or server cluster). In other example embodiments, the processor or processor-implemented engine may be distributed across multiple geographic locations.

[0067] In this specification, multiple instances may implement components, operations, or structures described as single instances. Although individual operations of one or more methods are shown and described as separate operations, one or more of the separate operations may be performed simultaneously and do not need to be performed in the order shown. Structures and functions presented as separate components in the example configuration may be implemented as composite structures or components. Similarly, structures and functions presented as single components may be implemented as separate components. These and other variations, modifications, additions, and improvements fall within the scope of this document.

[0068] While an overview of the subject matter has been described with reference to specific example embodiments, various modifications and changes can be made to these embodiments without departing from the broader scope of embodiments of this disclosure. Such embodiments of the subject matter are referred to herein, individually or collectively, by the term "invention," and are used for convenience only and are not intended to limit the scope of this application to any single disclosure or concept, should more than one disclosure or concept be disclosed in fact.

[0069] The embodiments described herein have been described in sufficient detail to enable those skilled in the art to practice the disclosed teachings. Other embodiments may be used and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. Therefore, the detailed description should not be construed as limiting, and the scope of the various embodiments is defined only by the appended claims and the full scope of their equivalents.

Claims

1. A multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation, characterized in that, Includes the following steps: S100, collecting requirements for elderly-friendly terminals, wherein the elderly-friendly terminals are deployed at the target community bus stops, and determining whether the delay of the target elderly user pressing the anti-accidental touch button exceeds a preset delay benchmark value. If yes, a call request signal is output; otherwise, no signal is output. S101. After receiving the call request signal output by the elderly-friendly terminal, extract the terminal identifier and preset high-frequency destination information from the call request signal, identify the user's age by combining the target elderly user profile, and determine whether the target elderly user's age is higher than the preset elderly age benchmark value. If yes, mark it as a priority scheduling request; otherwise, mark it as a regular scheduling request. S102, matching vehicles according to the preset minimum waiting time baseline value and scheduling requirements, and planning a driving route to avoid congested sections for the matched target micro-circulation vehicles based on real-time traffic information, and pushing the planned route to the vehicle end. S103 will plan the dynamic optimal driving route for the matched target micro-circulation vehicle, transmit the estimated arrival time to the elderly-friendly terminal, and start the dialect voice broadcast of the estimated arrival time. At the same time, the red, yellow and green status indicator lights will be switched to green. When the target micro-circulation vehicle arrives at the corresponding target community bus stop, the red, yellow and green status indicator lights will be switched to red, and the dialect voice broadcast of the vehicle's arrival will be started. S104. If vehicle matching fails in step S102, an SMS notification is automatically triggered to send a dispatch assistance SMS to the preset administrator, re-match the target elderly user with a micro-circulation vehicle, and feed back the coordination result to the elderly-friendly terminal to inform the target elderly user in dialect voice.

2. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, The age-friendly terminal includes anti-accidental touch buttons, red, yellow and green status indicator lights, and dialect voice broadcast; If the delay when the target elderly user presses the anti-accidental touch button is greater than or equal to the preset delay benchmark value, a call request signal is output, the red, yellow and green status indicator lights switch to yellow and the dialect voice broadcast is started to announce that the call is in progress. The call request signal includes the terminal identifier and preset high-frequency destination information. The preset high-frequency destination is at least one of the following: hospital, vegetable market and community center. If the delay when the target elderly user presses the anti-accidental touch button is less than the preset delay benchmark value, no call request signal will be output, the red, yellow and green status indicator lights will remain in the initial standby green light state, and dialect voice broadcast will not be activated.

3. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, The specific process for matching vehicles based on a preset minimum waiting time baseline value and scheduling requirements is as follows: The vehicle matching process includes demand collection, idle vehicle matching, and route push. The real-time traffic information includes the vehicle's real-time location, current speed, number of remaining seats, and current passenger status, which includes empty, half-loaded, and fully loaded. At the current moment, the total number of all unanswered call requests in the reservation pool is recorded as the concurrent demand number. A mapping relationship between the demand number and the waiting delay is established. If the concurrent demand number is less than or equal to the lower limit of the demand number, the current waiting delay is set to the preset baseline waiting delay. If the number of concurrent demands is within the demand base range, the current number of concurrent demands is input into the demand-waiting delay mapping relationship, and the delay reduction coefficient is output. The preset base waiting delay and the delay reduction coefficient are combined to obtain the target waiting delay, so as to reduce the waiting time and match nearby vehicles. The demand base range represents the open interval formed by the lower limit of the demand base and the upper limit of the demand base. If the number of concurrent requests is greater than or equal to the upper limit of the request base, the current number of concurrent requests is input into the request-waiting delay mapping relationship, and the delay extension coefficient is output. The preset base waiting delay and the delay extension coefficient are combined to obtain the target waiting delay, so as to relax the waiting time constraint and match the target vehicle at a long distance.

4. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, The specific steps for planning a driving route to avoid congested road sections for the target micro-circulation vehicle are as follows: Two types of characteristic road segments within the target community are extracted and labeled. The characteristic road segments include high-frequency through road segments and intersections without traffic lights. Priority avoidance geographical labels are added to the two types of characteristic road segments and associated with the road network database of the predefined dispatch platform. For the high-frequency through road segments, the path speed threshold is reduced. Specifically, a mapping relationship is established between the feature road segments and the predefined path speed threshold. The high-frequency through road segments are input into the mapping relationship, and the speed reduction coefficient is output. The current path speed threshold and the speed reduction coefficient are combined to obtain the target path speed threshold. For intersections without traffic lights, the current path speed threshold is maintained. Based on the adjusted path speed threshold, the path travel time is obtained, and the path with the shortest travel time and the fewest priority avoidance sections is selected as the final planned path and pushed to the target micro-circulation vehicle.

5. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 4, characterized in that, The method of planning driving routes to avoid congested road sections for the target micro-circulation vehicles also includes: A dynamic mapping relationship between weight coefficients and scheduling demand intensity is established. The ratio of concurrent demand to available micro-circulation vehicles in the current scheduling cycle is recorded as the load rate. If the load rate is less than or equal to the lower limit of the load rate benchmark, the current priority avoidance segment number weight is set as the critical upper limit of the target priority avoidance segment number weight. The path travel time weight is set as the difference between 1 and the critical upper limit of the target priority avoidance segment number weight. Path selection prioritizes minimizing this difference. If the load rate is within the load rate benchmark range, the current priority avoidance segment quantity weight is set to the critical lower limit of the target priority avoidance segment quantity weight, and the path travel time weight is set to the difference between 1 and the critical lower limit of the target priority avoidance segment quantity weight, in order to balance safety and efficiency. The load rate benchmark range represents the open interval formed by the load rate benchmark lower limit and the load rate benchmark upper limit. If the load rate is greater than or equal to the upper limit of the load rate benchmark, an alert will be sent to the relevant operations and maintenance personnel.

6. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, Step S103 includes: after completing vehicle matching and route planning, pushing the dynamic optimal driving route to the target micro-circulation vehicle, and sending the estimated arrival time information and vehicle status command to the elderly-friendly terminal to trigger the composite status feedback of the elderly-friendly terminal, specifically: The red, yellow, and green status indicator lights will be switched from the current yellow light to the green light. The yellow light indicates that the call is in progress, and the green light indicates that the vehicle has been matched and is en route. The estimated arrival time will also be announced in the local dialect. If route replanning is triggered based on real-time traffic information, resulting in a change in the estimated arrival time and the change difference exceeding a preset change difference threshold, the new estimated arrival time will be sent to the elderly-friendly terminal again. While maintaining the green light status, the elderly-friendly terminal will start a new round of dialect voice broadcast to notify of the time change.

7. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, Step S103 further includes: when the target micro-circulation vehicle arrives at the target community bus stop and stops, it automatically determines that it has entered the electronic fence range of the station and automatically triggers the sending of a vehicle arrival confirmation signal to the dispatch platform. After receiving the vehicle arrival confirmation signal, the dispatch platform immediately sends an arrival instruction packet, which specifically involves switching the red, yellow, and green status indicator lights from green to red to indicate that the vehicle has arrived, and broadcasting a report to the target elderly user in a local dialect. If the red light status is maintained and the dialect voice broadcast continues within the first threshold of the preset broadcast duration, the status indicator light will switch back to yellow. If no new long press operation is triggered, the indicator light will automatically turn off and return to the initial standby state after the second threshold of the preset broadcast duration, thus completing a single service loop.

8. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, The specific steps for automatically triggering an SMS notification if vehicle matching fails in step S102 are as follows: If the dispatch platform fails to find an available micro-circulation vehicle within the preset matching time limit based on the preset matching rules, it will determine that the intelligent matching has failed and immediately extract and encapsulate the following information of the current request, including: the unique identifier of the requester, the preset high-frequency destination, the timestamp of the matching failure, and the user's age; The encapsulated information is filled into a preset SMS template and automatically sent to one or more preset administrators. While sending the assistance SMS, the dispatching platform automatically narrows the dispatchable range of this call request from the entire community road network to the service area covered by predefined high-frequency stations. The predefined high-frequency stations correspond to hospitals, vegetable markets, and community centers, and the platform only tries to match from the micro-circulation vehicle pool currently serving the high-frequency stations.

9. The multi-source collaborative scheduling method for elderly e-key communication oriented towards community micro-circulation as described in claim 1, characterized in that, After receiving the dispatch assistance SMS, the preset administrator reassigns a vehicle for the call request. After successful assignment, the preset administrator submits the assignment result to the dispatch platform through the management terminal. The assignment result includes the assigned vehicle number and the latest estimated arrival time. After receiving the submitted assignment result, the dispatch platform immediately sends a notification instruction to the corresponding elderly-friendly terminal and starts dialect voice broadcasting. The red, yellow and green status indicator lights remain yellow until a vehicle arrival confirmation signal is received, after which the red, yellow and green status indicator lights switch.

10. A system applying the multi-source collaborative scheduling method for elderly people's communication based on community micro-circulation as described in any one of claims 1-9, characterized in that, include: The module includes a module for preventing accidental touches, a module for prioritizing requirements, a module for intelligent matching and path planning, a module for state synchronization and service closed-loop, and a module for manual scheduling intervention and service degradation. The anti-accidental touch requirement collection module is used to collect the requirements of elderly-friendly terminals. The elderly-friendly terminals are deployed at the target community bus stops. The module determines whether the delay when the target elderly user presses the anti-accidental touch button exceeds a preset delay benchmark value. If so, a call request signal is output; otherwise, no signal is output. The demand priority determination module is used to extract the terminal identifier and preset high-frequency destination information from the call request signal after receiving the call request signal output by the elderly-friendly terminal, identify the user's age in combination with the target elderly user profile, and determine whether the target elderly user's age is higher than the preset elderly age benchmark value. If so, it is marked as a priority scheduling demand; otherwise, it is marked as a regular scheduling demand. The intelligent matching and route planning module is used to match vehicles based on a preset minimum waiting time benchmark value and scheduling requirements, and to plan a driving route to avoid congested road sections for the matched target micro-circulation vehicles based on real-time traffic information, and push the planned route to the vehicle end. The state synchronization and service closed-loop module is used to plan the dynamic optimal driving route for the matched target micro-circulation vehicle, transmit the estimated arrival time to the elderly-friendly terminal, and start the dialect voice broadcast of the estimated arrival time, while switching the red, yellow and green status indicator lights to green; when the target micro-circulation vehicle arrives at the corresponding target community bus stop, the red, yellow and green status indicator lights are switched to red, and the dialect voice broadcast of the vehicle's arrival is started. The manual dispatching intervention and downgrade service module is used to automatically trigger an SMS notification if vehicle matching fails in step S102, send a dispatching assistance SMS to a preset administrator, re-match the target elderly user with a micro-circulation vehicle, and feed back the coordination result to the elderly-friendly terminal to inform the target elderly user in dialect voice.

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