Dynamic scheduling interrupt system based on adaptive priority resident arc

Abstract

A dynamic scheduling interrupt system based on an adaptive priority resident arc comprises an adaptive priority resident arc generation module, a resident interrupt logic control module, a resident state keeping module and a priority guarantee target optimization module, the self-adaptive priority resident arc generation module, the resident interrupt logic control module and the resident state keeping module are respectively connected with the self-adaptive priority resident arc generation module; and adjusting the adaptive priority resident arc, the linkage constraint mechanism and the logic judgment constraint. According to the method, immediate response and resident interruption of high-priority tasks are realized by defining resident arc generation rules with priorities and introducing constraints.

Description

Technical Field

[0001] This invention relates to the field of dynamic response technology for airport water truck scheduling, and in particular to a dynamic scheduling interruption system based on adaptive priority dwell arc. Background Technology

[0002] In the current era of rapid development in the civil aviation industry, flight turnaround efficiency has become a core indicator for measuring airport operational capabilities, and the airport ground support system is a key infrastructure supporting efficient flight turnaround. Among these, water truck dispatching, as a core business module of aircraft ground support, is primarily responsible for providing clean water to arriving flights. Its response speed and dispatching accuracy directly affect the progress of aircraft cleaning operations, thereby impacting flight punctuality, passenger travel experience, and the overall reputation of airport support. With the continuous increase in flight density, especially the surge in flight takeoffs and landings during peak hours at hub airports, the complexity and timeliness requirements of water truck dispatching are constantly increasing, making traditional dispatching models inadequate for adapting to dynamically changing support needs.

[0003] In the mathematical modeling of water truck scheduling, the dwell arc is a core element depicting the waiting behavior of vehicles between two consecutive tasks. Its design rationality directly determines the adaptability and flexibility of the scheduling model. Traditional scheduling schemes, to simplify modeling logic, generally define the dwell arc as a static, fixed-duration time-filling unit, only fulfilling the basic function of "connecting preceding and following tasks and avoiding scheduling path breaks." Under this design approach, the dwell arc's duration parameter is not adjusted once set, failing to consider the resource scarcity of waiting points in different areas of the airport, and lacking a correlation mechanism with the attributes of subsequent tasks. This results in the generation and adjustment of the dwell arc being completely detached from the actual task requirements.

[0004] The core flaws of the aforementioned static dwell arc design become particularly apparent in high-priority task emergencies, specifically manifested in a lack of awareness of task urgency and delayed response. In actual airport operations, high-priority water replenishment requests are frequent, such as emergency water replenishment after flight delays, priority support for government / international flights, and emergency water replenishment after sudden mechanical failures. Failure to respond promptly to these tasks can easily trigger further flight delays and a chain reaction of resource congestion. In traditional solutions, water trucks in a dwell state are constrained by fixed durations and cannot proactively interrupt their waiting period to enter operational mode, leading to delayed responses to high-priority tasks. This problem has become a key bottleneck restricting the improvement of airport ground support efficiency, necessitating the development of a dwell arc scheduling system with priority awareness and dynamic interruption capabilities to address it. Summary of the Invention

[0005] The purpose of this invention is to provide a dynamic scheduling interrupt system based on adaptive priority dwell arc, which has the advantages of enabling immediate response and dwell interrupt for high-priority tasks.

[0006] To achieve the above objectives, this invention provides a dynamic scheduling interruption system based on adaptive priority dwell arcs. By defining priority-based dwell arc generation rules and introducing constraints, it achieves immediate response and dwell interruption for high-priority tasks. The system includes: an adaptive priority dwell arc generation module, which generates adaptive priority dwell arcs and dynamically adjusts the upper limit of allowed dwell time according to the priority level of subsequent tasks, achieving flexible adaptation of dwell time; a dwell interruption logic control module, which establishes a linkage constraint mechanism between high-priority task trigger signals and low-priority dwell arc termination actions to ensure the timeliness and accuracy of interruption response; a dwell state maintenance module, which generates logical judgment constraints and ensures the logical consistency and physical rationality of core state parameters during dwell through multiple balancing constraints; and a priority guarantee target optimization module, which adjusts the adaptive priority dwell arcs, linkage constraint mechanism, and logical judgment constraints in the adaptive priority dwell arc generation module, dwell interruption logic control module, and dwell state maintenance module, respectively.

[0007] Preferably, in the adaptive priority dwell arc generation module, the adaptive priority dwell arc is triggered by the linkage of three elements: task priority E1, vehicle status E2, and geographical location E3. E1 constraint and quantification calculation uses a weighted summation formula to quantify task priority. The core formula is: E1 = α × A + β × B + γ × C; α, β, and γ are all indicator weights, satisfying α + β + γ = 1; A is the flight support level score; B is the flight delay urgency score; C is the water replenishment urgency score. Priority is determined by E1 ≥ 8 (high priority), 5 ≤ E1 < 8 (medium priority), and E1 < 5 (low priority). The results serve as the core basis for adjusting the dwell time, forming a logical linkage with subsequent dwell interruption and priority optimization modules; and the dynamic adjustment constraint and calculation of the dwell time upper limit T, with E1 as the core trigger condition, linking E2 and E3 to dynamically calculate the dwell time upper limit through correction coefficients, the core formula: T=T0×K, where K=K1×K2×K3, where T0 is the baseline dwell time upper limit; K1 is the E1 correction coefficient, realizing the negative correlation between priority and dwell time; K2 is the E2 correction coefficient, avoiding dwell invalidity due to insufficient water; K3 is the E3 correction coefficient, optimizing the adaptability of vehicle driving time.

[0008] Preferably, in the dwell interruption logic control module, the module collects high-priority task trigger signals in real time through the task acquisition unit. The signal trigger condition is E1≥8. It synchronously captures the dwell arc priority corresponding to the water truck that is currently in the dwell state, filters out low-priority dwell arcs that can be interrupted, and avoids high-priority dwell arcs being mistakenly interrupted.

[0009] Preferably, in the resident interrupt logic control module, the maximum allowable interrupt response delay t is calculated. delay The core calculation formula is t delay =t task -t now -t travel ; where t task t represents the latest completion time for high-priority tasks. now t represents the current system time. travel The travel time from the stationed vehicle to the mission point is calculated using the E3 geolocation parameters, t. travel =d / v, where d is the straight-line distance between the stationary point and the mission point, and v is the standard speed of the water truck; compared to t delay With the remaining duration t of the current dwell arc remain In the formula t remain Let t be the remaining duration of the current dwell arc. delay <t remain If t is interruptible, the pause interruption action is executed immediately, instructing the vehicle to terminate waiting and proceed to the mission point; if t delay ≥t remain If the interruption is not required, the vehicle will proceed to the mission point after completing its current stop, ensuring a balance between the rationality and timeliness of the interruption action.

[0010] Preferably, the resident interruption logic control module further includes: executing interruption compensation logic to balance the rights and interests of low-priority resident tasks, with the compensation formula being t. comp =t set -t actual ; where t set The initial duration of this dwell arc is set to t. actual The actual length of stay, plus compensation time t. comp This will be included in the vehicle's next dwell time arc duration to avoid scheduling imbalances caused by long-term interruptions of low-priority dwell tasks, and to ensure the rationality and systematic nature of the interruption response.

[0011] Preferably, the dwell state maintenance module includes: a vehicle water volume dynamic calculation and maintenance module, which collects the real-time water volume W of the vehicle water tank in real time through the vehicle status monitoring unit. real Combined with the length of stay t stay Calculate natural water loss W loss The calculation formula is W loss =k loss ×t stay； Where, k loss The water loss coefficient per unit time; simultaneously predicting the water consumption W for traveling to the next mission point after the stay ends. travel If W real -Wloss -W travel <W min Among them, W min To ensure the minimum safe water level threshold, an immediate water replenishment reminder or adjustment of the dwell time is triggered to ensure that the vehicle has the water required to perform subsequent tasks, thus guaranteeing the physical rationality of the scheduling logic.

[0012] Preferably, the dwell state maintenance module includes: a geographic location accuracy calibration module, which acquires real-time GPS positioning data (X) through a location positioning unit. real Y real ), and the preset dwell point coordinates (X real Y real Calculate the positional deviation Δd using the following formula: If Δd > Δd max , where Δd max The maximum permissible deviation is 50m by default; immediately instruct the vehicle to adjust its position to ensure the accuracy of the stopping point.

[0013] Preferably, the dwell state maintenance module includes: the priority guarantee target optimization module includes: an objective function optimization module and a hard time constraint module; the core objective of the objective function optimization module is to minimize the overall penalty cost, while taking into account high-priority task guarantee, interruption compensation balance and dwell time adaptation, and the objective function is as follows: Where ω1, ω2, and ω3 are the target weights, satisfying... (Can be dynamically adjusted according to airport support priorities); Where Z4 represents the penalty for high-priority tasks not being assigned in a timely manner; n represents the total number of high-priority tasks; k i Let be the unit penalty coefficient for the i-th task; Xi∈{0,1} is the flag for untimely assignment, where 1 = untimely, 0 = timely; E 1i Quantify the priority score for the i-th task to achieve the differentiated constraint that "the higher the priority, the heavier the penalty"; Where Z5 is the dwell interrupt compensation deviation penalty term; m is the number of interrupts; The penalty coefficient is used to compensate for deviations. For the first The compensation duration for each interruption constrains scheduling imbalances caused by excessive compensation deviations. Among them, the penalty for deviation in the dwell time of Z6; The penalty coefficient per unit for deviation in dwell time; For the first The dynamic duration limit of each dwell arc; The actual length of stay is determined to ensure that the length of stay aligns with the dynamically adjusted target.

[0014] Preferably, the dwell state maintenance module includes: a hard time constraint module, which constructs a full-process hard constraint of "completion time - response latency - arrival time" to ensure that high-priority tasks are completed on time. The constraint includes: core completion time constraint: t Fi ≤LFTi−Δti, ∀i∈High-priority task set; where t Fi Let t be the actual completion time of the i-th high-priority task, LFTi be its latest completion time, and Δti be the reserved buffer time to avoid cascading delays caused by task timeouts. The dwell arc interrupt mechanism is the core guarantee of this constraint; interrupt response delay constraint: t delay,i ≤t threshold , ∀i∈High-priority task set; where t delay,i =t task,i -t now -t travel,i , t threshold To constrain the interrupt response speed to the maximum allowable response delay threshold, ensuring timely triggering of resident interrupts; here, 'i' is merely a symbol, representing the same parameter as described above; vehicle arrival time constraint: t arrive,i =t now +t travel,i +t delay,i ≤LSTi; where t arrive,i Let LSTi be the time when the vehicle arrives at the i-th task point, and t be the earliest start time of the task. travel,i With t delay,i， Further strengthen the timeliness guarantee for high-priority tasks.

[0015] In summary, compared with the prior art, the dynamic scheduling interrupt system based on adaptive priority dwell arc provided by the present invention has the following beneficial effects:

[0016] First, the present invention proposes a dynamic scheduling interruption system based on adaptive priority dwell arc, which optimizes resource utilization. It adopts a dwell time adaptive strategy, dynamically shrinking or widening the dwell window according to the urgency of subsequent tasks. In high-priority task scenarios, the dwell time is shortened to reserve response space, and in regular task scenarios, the dwell time is reasonably set to reduce the ineffective driving of vehicles, which effectively improves the utilization efficiency of water truck resources.

[0017] Secondly, the dynamic scheduling interruption system based on adaptive priority dwell arc proposed in this invention effectively solves the problems of inflexible dwell behavior and delayed emergency task response in traditional static scheduling, and ensures the timeliness of airport emergency support needs.

[0018] Third, the dynamic scheduling interruption system based on adaptive priority dwell arc proposed in this invention achieves consistency between the scheduling model at the physical level (vehicle water volume) and the logical level (scheduling path), avoids logical loopholes that occur during dynamic adjustment, and improves the reliability and executability of the scheduling scheme. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of a dynamic scheduling interrupt system based on adaptive priority dwell arc proposed in this invention. Detailed Implementation

[0020] The following will be combined with the appendix in the embodiments of the present invention. Figure 1 The technical solutions, structural features, objectives and effects achieved in the embodiments of the present invention will be described in detail.

[0021] It should be noted that the accompanying drawings are in a very simplified form and use non-precise proportions. They are only used to facilitate and clarify the purpose of illustrating the embodiments of the present invention, and are not intended to limit the implementation conditions of the present invention. Therefore, they have no substantial technical significance. Any modifications to the structure, changes in the proportional relationship, or adjustments to the size should still fall within the scope of the technical content disclosed in the present invention, provided that they do not affect the effects and objectives that the present invention can produce.

[0022] It should be noted that, in this invention, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only the expressly listed elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0023] like Figure 1 As shown, this invention proposes a dynamic scheduling interruption system based on adaptive priority dwell arcs. By defining priority-based dwell arc generation rules and introducing constraints, it achieves immediate response and dwell interruption for high-priority tasks.

[0024] The system includes:

[0025] The adaptive priority dwell arc generation module generates adaptive priority dwell arcs, which dynamically adjust the upper limit of the allowed dwell time according to the priority level of subsequent tasks, so as to achieve flexible adaptation of dwell time.

[0026] The interrupt-residence logic control module establishes a linkage constraint mechanism between high-priority task trigger signals and low-priority dwell arc termination actions to ensure the timeliness and accuracy of interrupt response.

[0027] The stationary status maintenance module generates logical judgment constraints and ensures the logical consistency and physical rationality of core status parameters such as vehicle water volume and geographical location during the stationary process through multiple balance constraints.

[0028] The priority guarantee target optimization module, which is composed of the adaptive priority dwell arc generation module, the dwell interrupt logic control module, and the dwell state maintenance module, adjusts the adaptive priority dwell arc, the linkage constraint mechanism, and the logical judgment constraint.

[0029] Specifically, in the adaptive priority dwell arc generation module, the adaptive priority dwell arc is triggered by the linkage of three factors: E1 (task priority), E2 (vehicle status), and E3 (geographical location).

[0030] Among them, the task priority (E1) constraint and quantification calculation adopts the weighted summation formula to quantify the task priority. The core formula is: E1=α×A+β×B+γ×C.

[0031] α, β, and γ are all indicator weights, satisfying α+β+γ=1 (default values: α=0.5, β=0.3, γ=0.2, which can be dynamically calibrated according to the actual operation scenario of the airport); A is the flight support level score (government / international flights=10, domestic direct flights=8, stopovers=6); B is the flight delay urgency score (delay>30min=10, 10≤delay≤30min=7, no delay=4); C is the water replenishment urgency score (emergency=10, routine=5, backup=3).

[0032] The priority determination is based on E1≥8 (high priority), 5≤E1<8 (medium priority), and E1<5 (low priority). The determination result serves as the core basis for adjusting the dwell time and forms a logical linkage with the subsequent dwell interruption and priority optimization modules.

[0033] In a preferred embodiment, the adaptive priority dwell arc generation module further includes dynamic adjustment constraints and calculations for the upper limit of dwell time (T), with the aim of dynamically controlling the dwell arc density according to parameters such as task density.

[0034] In this step, E1 is used as the core trigger condition, and E2 and E3 are linked to dynamically calculate the upper limit of the dwell time through correction coefficients. The core formula is: T=T0×K, where K=K1×K2×K3

[0035] Among them, T0 is the upper limit of the baseline dwell time (default 30min, which can be calibrated according to the airport flight density); K1 is the E1 correction coefficient (high priority = 0.3, medium priority = 0.7, low priority = 1.0), realizing the negative correlation between priority and dwell time; K2 is the E2 (e.g., vehicle water volume) correction coefficient (water volume ≥ 80% = 1.1, 30% ≤ water volume < 80% = 1.0, water volume < 30% = 0.8), to avoid insufficient water volume leading to invalid dwell time; K3 is the E3 (e.g., distance) correction coefficient (distance ≤ 1km = 1.0, 1 < distance ≤ 3km = 0.9, distance > 3km = 0.7), to optimize the adaptability of vehicle travel time.

[0036] Meanwhile, E2 uses the vehicle's remaining water volume as the core indicator and adjusts the upper limit of the dwell time T through K2 to prevent the vehicle from being unable to perform subsequent tasks due to insufficient water volume, thus ensuring the effectiveness of the dwelling behavior; E3 uses the straight-line distance between the dwelling point and the task point as the core indicator and adjusts the upper limit of the dwell time T through K3 to optimize vehicle driving efficiency and reduce the time wasted on ineffective round trips.

[0037] The above three constraints, through E1 quantization and K coefficient linkage, constitute the complete generation logic of the dwell arc, ensuring that the generation of the dwell arc not only meets the task priority requirements, but also takes into account the actual state of the vehicle and the rationality of the geographical location, fully matching the original design intention of this module, and providing core parameter support for the subsequent dwell interruption and state maintenance modules.

[0038] Specifically, in the dwell interruption logic control module, the module collects high-priority task trigger signals in real time through the task acquisition unit. The signal trigger condition is E1≥8, which is consistent with the task priority quantification standard mentioned above. It also captures the dwell arc priority (denoted as E1') corresponding to the water truck that is currently in the dwell state, and filters out low-priority dwell arcs that can be interrupted (E1'<8) to avoid high-priority dwell arcs being mistakenly interrupted.

[0039] Calculate the maximum allowable delay t for interrupt response. delay The core calculation formula is t delay =t task -t now -t travel ; where t task The latest completion time for high-priority tasks (corresponding to the hard time constraint t mentioned later). Fi ≤LFT), t now t represents the current system time. travel The travel time for the stationed vehicle to reach the mission point (calculated from the E3 geographical location parameters mentioned above, t) travel =d / v, where d is the straight-line distance between the stationary point and the mission point, and v is the standard speed of the water truck. Then, an interruption feasibility assessment is performed, comparing t... delay With the remaining duration t of the current dwell arcremain In the formula t remain Let t be the remaining duration of the current dwell arc. delay <t remain If t is interruptible, the pause interruption action is executed immediately, instructing the vehicle to terminate waiting and proceed to the mission point; if t delay ≥t remain If the interruption is not required, the vehicle will proceed to the mission point after completing its current stop, ensuring a balance between the rationality and timeliness of the interruption action.

[0040] Finally, the interruption compensation logic is executed to balance the interests of low-priority resident tasks. The compensation formula is t. comp =t set -t actual ; where t set The initial duration of this dwell arc is set to t. actual The actual length of stay, plus compensation time t. comp The duration of the vehicle's next dwell arc will be included (cumulatively added to T0) to avoid scheduling imbalance caused by long-term interruption of low-priority dwell tasks, ensure the rationality and systematic nature of interruption response, and form a closed-loop management of "interruption-compensation".

[0041] In a specific embodiment, the dwell state maintenance module includes:

[0042] The vehicle water volume dynamic calculation and maintenance module collects the real-time water volume W of the vehicle's water tank through the vehicle status monitoring unit. real Combined with the length of stay t stay Calculate natural water loss W loss The calculation formula is W loss =k loss ×t stay； Where, k loss This is the water loss coefficient per unit time (default value 0.5L / min, dynamically calibrated according to ambient temperature); it also simultaneously predicts the water consumption W required to travel to the next task point after the stay ends. travel If W real -W loss -W travel <W min (W) min (At the minimum safe water threshold), immediately trigger a water replenishment reminder or adjust the dwell time to ensure that the vehicle has the water conditions to perform subsequent tasks and ensure the physical rationality of the scheduling logic;

[0043] The geolocation accuracy calibration module acquires real-time GPS positioning data (X) through the positioning unit. real Y real ), and the preset dwell point coordinates (X real Y realCalculate the positional deviation Δd using the following formula: If Δd > Δd max (Δd) max To ensure the maximum permissible deviation (default 50m), the vehicle is immediately instructed to adjust its position to ensure the accuracy of the dwell point, laying the foundation for subsequent task response and guaranteeing the spatial rationality of the scheduling logic.

[0044] The scheduling logic consistency verification module correlates the T (upper limit of dwell time) of the adaptive dwell arc generation module with the interrupt signal of the dwell interruption module in real time to build a logic verification mechanism. If the dwell time exceeds T or an interruption signal is received, the vehicle status is immediately adjusted to ensure that the dwell process and scheduling model logic are closed-loop and without loopholes, thus ensuring the executability of the scheduling scheme.

[0045] In a specific embodiment, the priority guarantee target optimization module includes: an objective function optimization module and a hard time constraint module;

[0046] The objective function optimization module aims to minimize the overall penalty cost while balancing high-priority task protection, interrupt compensation, and dwell time adaptation. The objective function is as follows: ;

[0047] Where ω1, ω2, and ω3 are the target weights, satisfying (Can be dynamically adjusted according to airport support priorities);

[0048] Where Z4 represents the penalty for high-priority tasks not being assigned in a timely manner; n represents the total number of high-priority tasks; k i Let E be the unit penalty coefficient for the i-th task; Xi∈{0,1} is the flag indicating untimely assignment (1=untimely, 0=timely); 1i Quantify the priority score for the i-th task to achieve the differentiated constraint that "the higher the priority, the heavier the penalty";

[0049] Where Z5 is the dwell interruption compensation deviation penalty term; m is the number of interruptions; To compensate for deviation, a unit penalty coefficient is applied (default 0.3). For the first The compensation duration for each interruption constrains scheduling imbalances caused by excessive compensation deviations.

[0050] Z6 is the penalty for deviation in dwell time; Penalty coefficient per unit for deviation in dwell time (default 0.1); For the first The dynamic duration limit of each dwell arc; To ensure the actual duration of stay aligns with dynamically adjusted targets;

[0051] The objective function is minimized using gradient descent, and the task allocation sequence and dwell time adjustment parameters are iteratively updated. During each iteration, the interruption response delay t from the previous context is synchronously verified. delay This ensures a closed loop between the optimization process and the interruption response and dwell adjustment logic. Unlike traditional single scheduling algorithms, this algorithm uses gradient descent and subsequent greedy constraint verification algorithms in conjunction to prioritize high-priority tasks while also ensuring scheduling stability, thus improving the practicality and reliability of the algorithm.

[0052] The hard time constraint module, to ensure high-priority tasks are completed on time, constructs a full-process hard constraint of "completion time - response latency - arrival time," which includes:

[0053] Core completion time constraint: t Fi ≤LFTi−Δti, ∀i∈High-priority task set; where t Fi Let LFTi be the actual completion time of the i-th high-priority task, LFTi be its latest completion time, and Δti be the reserved buffer time (compared to E). 1i Negative correlation, Δti=5×10−E1i / 10, unit min), to avoid cascading delays caused by task timeouts, the dwell arc interruption mechanism is the core guarantee of this constraint;

[0054] Interrupt response delay constraint: t delay,i ≤t threshold , ∀i∈High-priority task set; where t delay,i =t task,i -t now -t travel,i (Related to the interrupt response delay calculation mentioned earlier), t threshold The maximum allowable response latency threshold (default 5 minutes, calibrable) constrains the interrupt response speed to ensure timely triggering of resident interrupts; here, 'i' is only used as a symbol, which is the same as the aforementioned content and belongs to the same parameter.

[0055] Vehicle arrival time constraint: t arrive,i =t now +t travel,i +t delay,i ≤LSTi; where t arrive,i Let LSTi be the time when the vehicle arrives at the i-th task point, and t be the earliest start time of the task. travel,i (Calculation of E3 geographic location parameters mentioned above) and t delay,i This creates a full-process time constraint of "response-driving-arrival," further strengthening the timeliness guarantee for high-priority tasks;

[0056] A greedy algorithm is used to verify all constraints in real time. If any constraint is not met, scheduling adjustments are immediately triggered (prioritizing the adjustment of the interruption order of low-priority dwell arcs and optimizing vehicle travel paths) to ensure the rigidity and executability of the constraint system. This works in conjunction with the gradient descent optimization algorithm mentioned earlier to improve the rigor of the overall scheduling algorithm.

[0057] Although the present invention has been described in detail through the preferred embodiments above, it should be understood that the above description should not be considered as a limitation of the present invention. Various modifications and substitutions to the present invention will be apparent to those skilled in the art after reading the above description. Therefore, the scope of protection of the present invention should be defined by the appended claims.

Claims

1. A dynamic scheduling interrupt system based on adaptive priority dwell arcs, characterized in that, By defining priority-based rules for generating dwell arcs and introducing constraints, we can achieve immediate response and dwell interruption for high-priority tasks. The system includes: The adaptive priority dwell arc generation module generates adaptive priority dwell arcs, which dynamically adjust the upper limit of the allowed dwell time according to the priority level of subsequent tasks, so as to achieve flexible adaptation of dwell time. The interrupt-residence logic control module establishes a linkage constraint mechanism between high-priority task trigger signals and low-priority dwell arc termination actions to ensure the timeliness and accuracy of interrupt response. The dwell state maintenance module generates logical judgment constraints and ensures the logical consistency and physical rationality of core state parameters during dwell through multiple balancing constraints. The priority guarantee target optimization module adjusts the adaptive priority dwell arc generation module, dwell interrupt logic control module, and dwell state maintenance module; and adjusts the adaptive priority dwell arc, linkage constraint mechanism, and logical judgment constraint.

2. The dynamic scheduling interrupt system based on adaptive priority dwell arc according to claim 1, characterized in that, In the adaptive priority dwell arc generation module, the adaptive priority dwell arc is triggered by the linkage of three elements: task priority E1, vehicle status E2, and geographical location E3. Among them, the E1 constraint and quantification calculation adopts the weighted summation formula to quantify the task priority. The core formula is: E1=α×A+β×B+γ×C. α, β, and γ are all indicator weights, satisfying α+β+γ=1; A is the flight support level score; B is the flight delay urgency score; C is the water replenishment urgency score. Priority determination is used to determine the following: E1≥8 indicates high priority, 5≤E1<8 indicates medium priority, and E1<5 indicates low priority. The determination result serves as the core basis for adjusting the dwell time and forms a logical linkage with the subsequent dwell interruption and priority optimization modules. The system includes dynamic adjustment constraints and calculations for the maximum dwell time T. Using E1 as the core trigger condition, and linking E2 and E3, the maximum dwell time is dynamically calculated through correction coefficients. The core formula is: T = T0 × K, where K = K1 × K2 × K3. Among them, T0 is the upper limit of the baseline dwell time; K1 is the E1 correction coefficient, which realizes the negative correlation between priority and dwell time; K2 is the E2 correction coefficient, which avoids the dwell time being invalid due to insufficient water; K3 is the E3 correction coefficient, which optimizes the adaptability of vehicle driving time.

3. The dynamic scheduling interrupt system based on adaptive priority dwell arc according to claim 2, characterized in that, In the dwell interruption logic control module, the module collects high-priority task trigger signals in real time through the task acquisition unit. The signal trigger condition is E1≥8. It synchronously captures the dwell arc priority corresponding to the water truck that is currently in the dwell state, filters out low-priority dwell arcs that can be interrupted, and avoids high-priority dwell arcs being interrupted by mistake.

4. The dynamic scheduling interrupt system based on adaptive priority dwell arc according to claim 3, characterized in that, In the resident interrupt logic control module, the maximum allowable interrupt response delay t is calculated. delay The core calculation formula is t delay =t task -t now -t travel ; Among them, t task t represents the latest completion time for high-priority tasks. now t represents the current system time. travel The travel time for parked vehicles to reach the mission point is calculated from the E3 geolocation parameters, t travel =d / v, where d is the straight-line distance between the stationary point and the mission point, and v is the standard driving speed of the water truck; Comparison t delay With the remaining duration t of the current dwell arc remain In the formula t remain Let t be the remaining duration of the current dwell arc. delay <t remain If t is interruptible, the pause interruption action is executed immediately, instructing the vehicle to terminate waiting and proceed to the mission point; if t delay ≥t remain If the vehicle completes its current stop, it is determined that no interruption is required. The vehicle will then proceed to the mission point after completing its current stop, ensuring a balance between the rationality and timeliness of the interruption action.

5. A dynamic scheduling interrupt system based on adaptive priority dwell arcs according to claim 4, characterized in that, The resident interruption logic control module also includes: executing interruption compensation logic to balance the rights and interests of low-priority resident tasks, with the compensation formula being t. comp =t set -t actual ; where t set The initial duration of this dwell arc is set to t. actual The actual length of stay, plus compensation time t. comp This will be included in the vehicle's next dwell time arc duration to avoid scheduling imbalances caused by prolonged interruptions of low-priority dwell tasks, and to ensure the rationality and systematic nature of the interruption response.

6. A dynamic scheduling interrupt system based on adaptive priority dwell arcs according to claim 5, characterized in that, The dwell state maintenance module includes: The vehicle water volume dynamic calculation and maintenance module collects the real-time water volume W of the vehicle's water tank through the vehicle status monitoring unit. real Combined with the length of stay t stay Calculate natural water loss W loss The calculation formula is W loss =k loss ×t stay； Where, k loss The water loss coefficient per unit time; simultaneously predicting the water consumption W for traveling to the next mission point after the stay ends. travel If W real -W loss -W travel <W min Among them, W min To ensure the minimum safe water level threshold, an immediate water replenishment reminder or adjustment of the dwell time is triggered to ensure that the vehicle has the water required to perform subsequent tasks, thus guaranteeing the physical rationality of the scheduling logic.

7. A dynamic scheduling interrupt system based on adaptive priority dwell arcs according to claim 6, characterized in that, The dwell state maintenance module includes: The geolocation accuracy calibration module acquires real-time GPS positioning data (X) through the positioning unit. real Y real ), and the preset dwell point coordinates (X real Y real Calculate the positional deviation Δd using the following formula: If Δd > Δd max , where Δd max The maximum permissible deviation is 50m by default; immediately instruct the vehicle to adjust its position to ensure the accuracy of the stopping point.

8. A dynamic scheduling interrupt system based on adaptive priority dwell arcs according to claim 7, characterized in that, The dwell state maintenance module includes: The priority guarantee target optimization module includes: an objective function optimization module and a hard time constraint module; The objective function optimization module aims to minimize the overall penalty cost while balancing high-priority task protection, interrupt compensation, and dwell time adaptation. The objective function is as follows: ; Where ω1, ω2, and ω3 are the target weights, satisfying (Can be dynamically adjusted according to airport support priorities); Where Z4 represents the penalty for high-priority tasks not being assigned in a timely manner; n represents the total number of high-priority tasks; k i Let be the unit penalty coefficient for the i-th task; Xi∈{0,1} is the flag for untimely assignment, where 1 = untimely, 0 = timely; E 1i Quantify the priority score for the i-th task to achieve the differentiated constraint that "the higher the priority, the heavier the penalty"; Where Z5 is the dwell interruption compensation deviation penalty term; m is the number of interruptions; The penalty coefficient is used to compensate for the deviation. For the first The compensation duration for each interruption constrains scheduling imbalances caused by excessive compensation deviations. Z6 is the penalty for deviation in dwell time; The penalty coefficient per unit for deviation in dwell time; For the first The dynamic duration limit of each dwell arc; The actual length of stay is determined to ensure that the length of stay aligns with the dynamically adjusted target.

9. A dynamic scheduling interrupt system based on adaptive priority dwell arcs according to claim 8, characterized in that, The dwell state maintenance module includes: The hard time constraint module, to ensure high-priority tasks are completed on time, constructs a full-process hard constraint of "completion time - response latency - arrival time," which includes: Core completion time constraint: t Fi ≤LFTi−Δti, ∀i∈High-priority task set; where t Fi Let be the actual completion time of the i-th high-priority task, LFTi be its latest completion time, and Δti be the reserved buffer time to avoid chain delays caused by task timeouts. The dwell arc interrupt mechanism is the core guarantee of this constraint. Interrupt response delay constraint: t delay,i ≤t threshold , ∀i∈High-priority task set; where t delay,i =t task,i -t now -t travel,i , t threshold The maximum allowable response latency threshold is used to constrain the interrupt response speed and ensure timely triggering of resident interrupts; here, 'i' is only used as a symbol, which is the same as the aforementioned content and belongs to the same parameter. Vehicle arrival time constraint: t arrive,i =t now +t travel,i +t delay,i ≤LSTi; where t arrive,i Let LSTi be the time when the vehicle arrives at the i-th task point, and t be the earliest start time of the task. travel,i With t delay,i， Further strengthen the timeliness guarantee for high-priority tasks.

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