Inspection route planning method and system
By quantifying the priority of inspection sites and dynamically inserting weights using intelligent factors, and combining this with real-time traffic conditions to generate inspection routes, the inefficiency caused by the reliance on human experience in traditional inspection modes has been solved, enabling efficient and orderly execution of inspection tasks.
Patent Information
- Application Number
- CN202511932043.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-19
- Publication Date
- 2026-03-03
AI Technical Summary
Traditional inspection methods rely heavily on human experience, resulting in low inspection efficiency, increased time and personnel costs, and an inability to adapt to changes in dynamic factors.
The system uses intelligent factor quantification to prioritize inspection sites, divides them into multi-level classification sets and dynamically inserts weights, generates inspection routes in conjunction with real-time traffic conditions, prioritizes high-priority tasks, and optimizes routes through conflict elimination strategies.
This improved inspection efficiency, reduced route backtracking and redundant planning, lowered costs, and ensured the timely execution of high-priority tasks and the orderly progress of the overall mission.
Smart Images
Figure CN121594886A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of inspection technology, and in particular to an inspection route planning method and system. Background Technology
[0002] As the company's stores continue to expand, inspections are a core and fundamental task to ensure the stability of daily operations and maintain the normal functioning of stores. Traditional inspection methods rely heavily on manual experience, leading to a significant increase in time and personnel costs during the inspection process. Summary of the Invention
[0003] This application provides a method and system for planning inspection routes to solve the problem of low inspection efficiency caused by reliance on manual experience during inspections in related technologies.
[0004] Firstly, a method for planning inspection routes is provided, which includes the following steps: Obtain the intelligence factor reflecting the inspection priority of each inspection site; Based on the magnitude of the aforementioned intelligent balance factor, each inspection site is divided into multiple classification sets with different inspection priorities; Based on the location information and real-time traffic conditions of each inspection site in the highest priority category, an initial inspection route covering the inspection sites included in that category is generated. According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraints of the inspection location, to obtain the final inspection route.
[0005] In some embodiments, the method further includes, before obtaining the final inspection route: According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraint of the inspection location, to obtain the temporary inspection route. If there is a conflict between the temporary inspection route and the real-time inspection situation, the temporary inspection route is optimized according to the conflict elimination strategy to obtain the final inspection route.
[0006] In some embodiments, based on the magnitude of the intelligent balance factor, each inspection site is divided into multiple classification sets with different inspection priorities, including: Multiple consecutive numerical intervals are set, each corresponding to a classification set, and the intervals do not overlap with each other, together covering the entire range of values of the Zhiheng factor. Based on the value range of the Wisdom Factor at each inspection location, it is divided into the corresponding classification set.
[0007] In some embodiments, according to the inspection priority order of the classification set, the remaining inspection locations contained in the classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraints of the inspection location, to obtain a temporary inspection route, specifically including: For the remaining classification set with the highest inspection priority, calculate the dynamic insertion weight of the inspection sites it contains; Based on the dynamic insertion weight and the insertion constraints corresponding to the current classification set, the inspection locations within the classification set are inserted into the current inspection route to form an updated temporary inspection route. Repeat the above steps until all remaining inspection locations in the classification set have been processed. The resulting route is the temporary inspection route.
[0008] In some embodiments, the calculation of the dynamic insertion weight of the inspection site includes: calculating based on a preset first threshold and in combination with the abnormal warning correction value of the inspection site and the congestion correction value of real-time traffic conditions; The step of inserting the inspection site into the current inspection route includes: dynamically inserting the inspection site into any adjacent inspection site in the current inspection route in descending order of the insertion weight, and calculating the time increment caused by each insertion. The insertion constraint is: the sum of the total duration of the current inspection route and the duration increment caused by the insertion does not exceed the remaining working time of the day; If the insertion of the current inspection location satisfies the insertion constraint, then the current inspection location is inserted into the current inspection route; otherwise, the inspection location is adjusted to a lower priority category set and is not inserted for the time being.
[0009] In some embodiments, the calculation of the dynamic insertion weight of the inspection site includes: calculating based on a preset second threshold and in combination with a time surplus coefficient, wherein the time surplus coefficient is obtained by dividing the remaining working hours of the day by the product of the historical average inspection time of the current inspection site and a predetermined coefficient; If the time surplus coefficient is less than or equal to 1, then the dynamic insertion weight of the current inspection site is 0; The insertion constraint is: the dynamic insertion weight of the current inspection site is greater than 0; If the insertion of the current inspection location satisfies the insertion constraint, then the current inspection location will be inserted into the current inspection route.
[0010] In some embodiments, the condition for determining whether the temporary inspection route conflicts with the real-time inspection situation is: Obtain the ratio of real-time travel time to estimated travel time for each segment of the temporary inspection route, and take the maximum value of the ratio for all segments as the spatial conflict coefficient. The ratio of the total estimated time for temporary inspection routes to the total working hours of the day is used as the time conflict coefficient. Based on the spatial conflict coefficient, the temporal conflict coefficient, and their respective weights, a comprehensive conflict coefficient is obtained. If the overall conflict coefficient is greater than or equal to the preset value, it is determined that there is a conflict between the temporary inspection route and the real-time inspection situation.
[0011] In some embodiments, the conflict resolution strategy is as follows: Obtain the two inspection points corresponding to the road segment with the maximum spatial conflict coefficient; Based on the real-time road conditions between the two inspection points, an alternative route between the two inspection points is obtained, and the comprehensive conflict coefficient is recalculated. If the new overall conflict coefficient is less than the preset value, then a new inspection path including the alternative path is adopted; If the new overall conflict coefficient is still greater than or equal to the preset value, then the lowest priority inspection site is removed from the inspection site sequence, and a new inspection path is generated. Recalculate the overall conflict coefficient under the new inspection path; Repeat the removal and calculation steps until the overall conflict coefficient under the new inspection path is less than the preset value; The new inspection route will be used as the final inspection route.
[0012] In some embodiments, the intelligent balance factor includes at least the task weight, the inspection site value weight, the remaining working time factor, and the historical efficiency factor.
[0013] Secondly, an inspection route planning system is provided, which includes: Data processing module: used to obtain the intelligence factor reflecting the inspection priority of each inspection site, and divide each inspection site into multiple classification sets with different inspection priorities according to the size of the intelligence factor. Path planning module: Based on the location information and real-time traffic conditions of each inspection point in the highest priority category, generate an initial inspection route covering the inspection points included in that category. According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraints of the inspection location, to obtain the final inspection route.
[0014] This application provides a method and system for patrol route planning. By introducing a smart factor to quantify the patrol priority of patrol sites, the importance of different patrol sites can be distinguished. By dividing and classifying the sites according to priority, the patrol needs of high-priority patrol sites can be prioritized, ensuring that core patrol tasks are executed first. By combining the location information of patrol sites in the high-priority classification set with real-time traffic conditions to generate an initial route, traffic interference can be effectively avoided, improving the rationality and traffic efficiency of the initial route. Subsequently, according to the priority order, the remaining patrol sites are inserted into the initial route in sequence based on dynamic insertion weights and insertion constraints. Under the premise of ensuring patrol priority, the route integration of all patrol sites can be achieved, reducing route backtracking and redundant planning, improving the overall coordination and execution efficiency of patrols, and reducing patrol costs and time consumption. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of this application, 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 this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 A flowchart of the inspection route planning method provided in the embodiments of this application; Figure 2 A block diagram of an inspection route planning method provided in an embodiment of this application; Figure 3 A diagram of the inspection route planning system provided in this application embodiment. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0018] Current mainstream inspection route planning methods are mostly based on preset fixed routes or simple shortest path algorithms, and the influencing factors are also fixed. However, in actual inspection scenarios, there are often multiple dynamic factors such as the urgency of the task, the importance of the inspection site, abnormal event warnings, handling urgent needs, and road conditions. Fixed routes or simple algorithms are difficult to flexibly adapt to these real-time changes, which can easily lead to low inspection efficiency and untimely problem handling, and fail to meet the actual needs of enterprises for efficient inspection.
[0019] This application provides a method for planning inspection routes, which can solve the problem of low inspection efficiency caused by reliance on manual experience during inspections in related technologies.
[0020] When a user logs into the system, the system automatically acquires static data, including the latitude and longitude coordinates / value weight of the inspection site, the average inspection time for each inspection site over the past 30 days, and anomaly warnings; it also acquires dynamic data, including real-time location, real-time traffic conditions (congestion index 0-1), and remaining working time, and automatically initiates planning. Users can also manually select inspection time periods and batch select inspection sites through the interface to initiate planning.
[0021] like Figure 1 and Figure 2 As shown, an inspection route planning method specifically includes the following steps: S100: Obtain the intelligence factor reflecting the inspection priority of each inspection site.
[0022] Furthermore, the intelligent balance factor includes at least task weights. Inspection site value weight Remaining working hours factor and historical efficiency factor .
[0023] Calculate the Zhiheng factor using the following formula. : ; The definitions of each factor and its weight coefficient are as follows: The normalized task weights are based on the urgency of the task, and are assigned values from highest to lowest priority: Emergency Event Handling 0.5, Abnormal Event Warning 0.3, Special Inspection 0.2, and Basic Inspection 0.
[0024] To normalize the value weight of inspection sites based on the business importance of inspection sites, fixed values are set for different types of inspection sites such as red-label stores and fresh food stores. The higher the business importance of the inspection site, the larger the weight value. The urgency normalization factor is based on the remaining working hours of the day, and its calculation method is as follows: = 1 - (Remaining working hours for the day ÷ Maximum working hours for the day). For example, if the working hours are from 7:30 to 22:30, and the maximum working hours for the day are 900 minutes, the less remaining working hours... The larger the value, the higher the priority it should be. This is an efficiency normalization factor based on the historical average inspection time of the inspection site. The value is based on the average inspection time of each inspection site over the past 30 days, or it can be based on the average inspection time of a single store over the past 15 days. The calculation method is as follows: =1 - (average time per store ÷ maximum average time of all locations to be inspected). The shorter the execution time, the easier it is to complete.
[0025] , , , These are the weight coefficients of the corresponding factors, which must satisfy... + + + =1, and follows > > > The priority sorting, in this embodiment, is specifically set to a value of =0.4、 =0.3、 =0.2、 =0.1.
[0026] The aforementioned intelligent factor acquisition scheme enables multi-dimensional quantification of inspection priorities. An evaluation system is constructed using four key dimensions: task urgency, core value of the inspection site, time urgency, and historical execution efficiency. This effectively avoids misjudgments caused by single-dimensional assessments. Furthermore, by normalizing each factor and assigning weights, the scheme highlights the core guiding role of task urgency and the business importance of the inspection site while also considering the actual impact of time constraints and execution efficiency, making the inspection priority ranking more aligned with actual work needs. In addition, clear factor calculation rules and fixed weight values ensure the standardization and repeatability of priority assessment, reducing interference from subjective human judgment. This helps to rationally allocate inspection resources, optimize inspection route planning, improve the overall execution efficiency and resource utilization efficiency of inspection work, ensure priority coverage of urgent tasks and important inspection sites, and reduce the risk of inspection delays.
[0027] S200: Based on the magnitude of the intelligent balance factor, each inspection site is divided into multiple classification sets with different inspection priorities.
[0028] Specifically, multiple consecutive numerical intervals are set, each corresponding to a classification set, and the intervals do not overlap with each other, together covering the entire value range of the Zhiheng factor. Based on the value range of the Wisdom Factor at each inspection location, it is divided into the corresponding classification set.
[0029] For example, the value range of the intelligence factor corresponding to the highest priority classification set can be set to >0.6, the value range of the lowest priority classification set to <0.3, and the value range of the middle priority classification set to 0.3-0.6. Based on the intelligence factor values of each inspection site obtained in step S100, different inspection sites can be classified into the above-mentioned priority classification sets respectively. In some optional embodiments, more levels of numerical ranges can be set according to actual inspection management needs, so as to divide a more refined inspection priority classification set to adapt to diverse inspection resource allocation and task arrangement needs.
[0030] S300: Based on the location information and real-time traffic conditions of each inspection site in the highest priority category, generate an initial inspection route covering the inspection sites included in that category.
[0031] In specific implementation, taking the high, medium, and low priority levels set in step S200 as an example, first find all inspection locations corresponding to the highest priority classification set. Using the user's location as the starting point, call the map API to obtain real-time intersection data (where intersection data is quantified by the congestion index, with a value range of 0-1, where a larger value indicates higher congestion, and 1 represents the most congested state). Use the large model to call MPC to obtain the initial inspection route. The specific steps include the following: S301: Using the real-time location of the inspector as the starting point of the route, and obtaining the location information and real-time traffic data of all inspection sites corresponding to the highest priority classification set, calculate the estimated travel time from the current route endpoint to each inspection site that has not yet been included in the route.
[0032] The estimated travel time is calculated by dividing the straight-line distance d by the adjusted travel speed v based on real-time congestion conditions. (x and y are latitude and longitude), 、 ) represents the location information corresponding to the current path's endpoint. 、 ) represents the location information of the inspection sites not included in the inspection route; the adjusted driving speed v = base speed (km / h) × (1 - real-time congestion index), and the final estimated travel time t = d / v.
[0033] S302: Select the inspection point with the shortest estimated travel time, add it to the end of the path, and update the path endpoint to the location of the newly added inspection point.
[0034] S303: Repeat steps S301 and S302 above until all inspection sites corresponding to the highest priority classification set are included in the path or the termination condition is triggered.
[0035] The termination condition is: the total duration of the initial inspection route is less than or equal to the remaining working time of the day multiplied by the reservation coefficient. In this embodiment, the reservation coefficient is 0.7, that is, 30% of the remaining working time of the day is reserved for the execution of other priority classification inspection tasks. The calculation standard for the total duration of the initial inspection route is: the sum of the single-store inspection time of all inspection locations in the initial inspection route, plus the sum of the travel time between all adjacent inspection locations.
[0036] By following the steps above, an orderly route for the highest priority inspection sites is planned. While ensuring priority processing, the overall travel time is shortened as much as possible, and this route serves as the basic framework for inserting lower priority inspection sites later.
[0037] S400: According to the inspection priority order of the classification set, the remaining inspection locations contained in the classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraint of the inspection location, to obtain the final inspection route.
[0038] Furthermore, according to the inspection priority order of the classification sets, the remaining inspection locations contained in the classification sets are sequentially inserted into the initial inspection route, taking into account the dynamic insertion weights and insertion constraints of the inspection locations. Specifically, this includes: For the remaining classification set with the highest inspection priority, calculate the dynamic insertion weight of the inspection sites it contains; Based on the dynamic insertion weight and the insertion constraints corresponding to the current classification set, the inspection locations within the classification set are inserted into the current inspection route to form an updated temporary inspection route. Repeat the above steps until all remaining inspection locations in the classification set have been processed. The resulting route is the temporary inspection route.
[0039] Because this scheme sets multiple classification sets with different inspection priorities, the insertion process uses the initial inspection route formed by the inspection locations of the highest priority classification set as the core framework. When inserting other classification sets, the priority order of the remaining classification sets is followed step by step to ensure that the execution logic of high-priority inspection tasks is not disturbed. Taking the high, medium, and low priority levels in step S200 as an example, after the high-priority classification set inspection locations are planned to form the initial inspection route, the medium-priority inspection locations are first inserted one by one into the current route to form an updated temporary inspection route based on the dynamic insertion weights and corresponding insertion constraints of the medium-priority classification sets. Then, based on the dynamic insertion weights and corresponding insertion constraints of the low-priority classification sets, the low-priority inspection locations are inserted one by one into the updated temporary inspection route, finally obtaining the temporary inspection route. In some optional embodiments, if there are more levels of classification sets, the route generation principle remains the same, and the insertion of inspection locations and route updates are completed step by step according to the order of priority from high to low and the corresponding constraints.
[0040] Furthermore, taking the high, medium, and low priority levels in step S200 as an example, after completing the planning of the inspection sites for the high-priority classification set to form the initial inspection route, when inserting the inspection sites contained in the medium-priority classification set, the dynamic insertion weight and insertion constraints are calculated as follows: S401: Calculate the dynamic insertion weight of the inspection site, including: based on a preset first threshold, and combined with the abnormal warning correction value of the inspection site and the congestion correction value of the real-time traffic conditions.
[0041] The first threshold is the separation value between the upper-level classification set and the lower-level classification set. Taking step S200 as an example, the first threshold is the separation value between the high-level classification set and the intermediate-level classification set, and its value is 0.6. If there is an unprocessed warning at the inspection site, the abnormal warning correction value is 0.2; otherwise, it is 0. If the congestion index of the road segment through which the inspection site passes is >0.7, the congestion correction value is 0.1; otherwise, it is 0. Therefore, the calculation method of the dynamic insertion weight W is as follows: W = 0.6 + abnormal warning correction value + congestion correction value.
[0042] The range of dynamically inserted weight W is 0.5 ≤ W ≤ 0.8 to ensure priority differentiation.
[0043] S402: Insert the inspection site into the current inspection route, including: dynamically inserting the inspection site in descending order of weight, and sequentially inserting the inspection site between any adjacent inspection sites in the current inspection route, and calculating the time increment caused by each insertion.
[0044] Sort W from high to low, and try to insert paths in turn. Evaluate the insertion position. For each pair of adjacent inspection points in the initial inspection route, such as (A, B), calculate the change in time after inserting the new intermediate inspection point C. ΔT = inspection time of C + [t(A→C) + t(C→B) - t(A→B)].
[0045] S403: If the insertion of the current inspection location satisfies the insertion constraint, then the current inspection location is inserted into the current inspection route; otherwise, the inspection location is adjusted to a lower priority category set and is not inserted for the time being.
[0046] The insertion constraint is: the sum of the current total inspection route duration and the duration increment caused by the insertion does not exceed the remaining working time for the day.
[0047] If the total duration of the current inspection route + ΔT ≤ the remaining working hours for the day, then insert; otherwise, skip the inspection location, pause insertion in this round, and downgrade it to a lower-level classification set.
[0048] Furthermore, taking the high, medium, and low priority levels in step S200 as an example, after completing the planning of inspection routes for the high and medium priority classification sets, when inserting inspection locations included in the low priority classification sets, the dynamic insertion weight and insertion constraints are calculated as follows: S404: Calculate the dynamic insertion weight of the inspection site, including: based on a preset second threshold and combined with a time surplus coefficient, the time surplus coefficient is obtained by dividing the remaining working hours of the day by the product of the historical average inspection time of the current inspection site and a predetermined coefficient.
[0049] The second threshold is the separation value between the upper-level classification set and the lower-level classification set. Taking step S200 as an example, the second threshold is the separation value between the intermediate-level classification set and the low-level classification set, and its value is 0.3. The time surplus coefficient = the remaining working hours of the day ÷ (the average inspection time of a single inspection site × 1.2), and the predetermined coefficient is 1.2.
[0050] The dynamic insertion weight W = 0.3 × time surplus coefficient.
[0051] If the time surplus coefficient is greater than 1, it means that there is sufficient time surplus. If the time surplus coefficient is less than or equal to 1, it means that there is insufficient time. In this case, the dynamic insertion weight of the current inspection site is 0.
[0052] S405: If the insertion of the current inspection location satisfies the insertion constraint condition, then insert the current inspection location into the current inspection route.
[0053] The insertion constraint is: the dynamic insertion weight of the current inspection site is greater than 0.
[0054] Only inspection sites with sufficient time surplus are processed, i.e., inspection sites with dynamic insertion weight > 0. They are inserted into the current inspection route according to the proximity principle, i.e., into the planned path in step S403. The proximity principle is to calculate the straight-line distance between the inspection site and all two adjacent inspection sites in the path, and select the shortest interval (A, B) for insertion to obtain the final inspection route.
[0055] This final inspection route generation scheme has significant benefits in multiple dimensions: First, it adopts a hierarchical logic of using high-priority routes as the framework and inserting low-priority inspection sites step by step, coupled with differentiated dynamic insertion weight calculation rules, to achieve the transmission of inspection priority. When inserting mid-priority routes, the weight is quantified by combining anomaly warnings and real-time congestion status to ensure that inspection sites with anomalies or tight traffic are inserted first. When inserting low-priority routes, the selection is based on the time surplus coefficient to avoid occupying core task time, so that route planning focuses on core needs while also taking into account resource redundancy. Second, the setting of insertion constraints forms a rigid control boundary. When inserting mid-priority routes, the constraint of "total time not exceeding the remaining working time" is used, and low-priority routes are subject to the premise of "sufficient time surplus". This effectively avoids the problem of uncontrolled total route time. At the same time, through the flexible handling mechanism of "degradation if constraints are not met", it avoids low-priority inspection sites from excessively crowding out high-priority task resources, ensuring the orderly progress of the overall inspection task. Third, the combination of the nearest insertion principle and the large-scale model optimization process significantly improves the practicality of the route planning—nearest insertion reduces unnecessary detours and time consumption, thus improving overall inspection efficiency. Fourth, the entire process replaces subjective experience-based judgment with quantified weight calculations, constraints, and hierarchical insertion logic, improving the standardization and accuracy of route planning. This achieves maximum coverage of all inspection sites while ensuring the core position of high-priority tasks, effectively balancing inspection efficiency and task integrity. Simultaneously, it reduces waste of inspection resources and improves the overall management level and execution effectiveness of the inspection work.
[0056] In the above methods, if only two classification sets are divided—one high-priority and one low-priority—either method S401 or S403 can be used for insertion. If more than one classification set is divided, other dynamic insertion weights and corresponding insertion constraints can be inserted in S401 and S403. Dividing the classification set into three is preferred.
[0057] In the above steps, the generated final inspection route is calculated based on static data during planning and instantaneous dynamic data (such as current location and real-time traffic conditions). However, there are many uncertain factors that change in real time during the inspection process, such as changes in traffic conditions and inspection duration, which can cause the initial path to become disconnected from the actual execution scenario. Therefore, before obtaining the final inspection route, the method further includes: S500: According to the inspection priority order of the classification set, the remaining inspection locations contained in the classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraint of the inspection location, to obtain the temporary inspection route.
[0058] For example, the temporary inspection route is starting point O, point B (0.8), point A (0.9), point E (0.2), point F (0.5), and point C (0.7). The numbers in parentheses represent the intelligent balance factor for each inspection point. The inspection durations corresponding to the BAEFC inspection points are 20, 25, 15, 20, and 25 minutes, respectively. The estimated travel times for road segments OB, BA, AE, EF, and FC are 15, 10, 20, 12, and 18 minutes, respectively, and the real-time travel times are 18, 25, 22, 10, and 15 minutes, respectively. All times are in minutes.
[0059] Furthermore, the criteria for determining a conflict between the temporary inspection route and the real-time inspection situation are as follows: S501: Obtain the ratio of real-time travel time to estimated travel time for each segment in the temporary inspection route, and take the maximum value of the ratio for all segments as the spatial conflict coefficient.
[0060] The spatial conflict coefficient S is taken as the ratio of the most congested road segments, S = max(real-time travel time of each road segment ÷ estimated travel time). The ratio of each road segment is calculated as follows: S OB =18÷15=1.2; S BA =25÷10=2.5; S AE =22÷20=1.1; S EF =10÷12≈0.83; S FC =15÷18≈0.83.
[0061] Take the maximum value as S for the entire route, S=max(1.2,2.5,1.1,0.83,0.83)=2.5. Compare the spatial conflict coefficient S with the preset value, which is 1.5. S=2.5>1.5, so a spatial conflict is determined.
[0062] S502: Obtain the ratio of the total estimated time for temporary inspection routes to the total working hours of the day, as the time conflict coefficient.
[0063] Time conflict coefficient T = Total estimated time for the entire route ÷ Maximum total working hours for the day. Substitute the data to calculate: The total estimated travel time for the entire route is calculated as follows: Total estimated travel time for all road segments + Total inspection time for all inspection points. In this formula, the total estimated travel time is 15 + 10 + 20 + 12 + 18 = 75 minutes, the total inspection time is 20 + 25 + 15 + 20 + 25 = 105 minutes, and the total estimated travel time is 75 + 105 = 180 minutes. Substituting these values into the formula, we can calculate T. T = 180 ÷ 240 = 0.75, T = 0.75 < 1, so there is enough time and no time conflict.
[0064] S503: Based on the spatial conflict coefficient, the temporal conflict coefficient and their respective weights, the comprehensive conflict coefficient is obtained.
[0065] Assign a weight of 0.6 to the spatial conflict coefficient and a weight of 0.4 to the temporal conflict coefficient. Calculate the comprehensive conflict coefficient C = S × 0.6 + T × 0.4 = 2.5 × 0.6 + 0.75 × 0.4 = 1.5 + 0.3 = 1.8.
[0066] S504: If the overall conflict coefficient is greater than or equal to the preset value, it is determined that there is a conflict between the temporary inspection route and the real-time inspection situation.
[0067] In this embodiment, the preset value is 1.2. The comprehensive conflict coefficient of 1.8 is greater than 1.2, indicating that there is a conflict and the conflict elimination strategy needs to be activated.
[0068] Furthermore, the conflict resolution strategy is as follows: Obtain the two inspection points corresponding to the road segment with the maximum spatial conflict coefficient; Based on the real-time road conditions between the two inspection points, an alternative route between the two inspection points is obtained, and the comprehensive conflict coefficient is recalculated. If the new overall conflict coefficient is less than the preset value, then a new inspection path including the alternative path is adopted; If the new overall conflict coefficient is still greater than or equal to the preset value, then the lowest priority inspection site is removed from the inspection site sequence, and a new inspection path is generated. Recalculate the overall conflict coefficient under the new inspection path; Repeat the removal and calculation steps until the overall conflict coefficient under the new inspection path is less than the preset value; The new inspection route will be used as the final inspection route.
[0069] Based on the above calculations, since the B→A section is the most congested, the congestion levels are ranked by the following factors: A (0.9) > B (0.8) > C (0.7) > F (0.5) > E (0.2). An alternative route is sought to replace the congested B→A path, reducing the spatial conflict coefficient S. Real-time navigation is invoked to find an alternative route to B→A. Assuming that after the replacement, the real-time travel time for the new B→A section is 12 minutes (estimated at 10 minutes), the ratio for this section after the replacement is 12 ÷ 10 = 1.2 < 1.5, indicating no spatial conflict.
[0070] Recalculate the spatial conflict coefficient: S = max(starting point O→B: 1.2, B→A: 1.2, A→E: 1.1, E→F: 0.83, F→C: 0.83) = 1.2.
[0071] The time conflict coefficient T remains unchanged at 0.75 (the total time is still 180 minutes, which does not exceed the 240-minute limit).
[0072] The new comprehensive conflict coefficient C = 1.2 × 0.6 + 0.75 × 0.4 = 0.72 + 0.3 = 1.02 < 1.2, indicating that the conflict has been successfully eliminated. The new detour route can then be followed, and all planned inspection points can be inspected normally.
[0073] If the new overall conflict coefficient C>1.2, and it is found that detour is not feasible, first ensure that the high priority is maintained and the low priority is postponed. The lowest priority is postponed, such as E(0.2), and then removed. After that, the total time is recalculated.
[0074] Total estimated time = original 180 minutes - inspection time at inspection point E (15 minutes) - travel time from A to E and from E to F (20+12) = 180 - 47 = 133 minutes. Therefore, the new route sequence is: O → B → A → F → C (skipping E, directly A → F, with an estimated 15 minutes for A → F, and a real-time 15 minutes).
[0075] Recalculate the global coefficients: new road segment ratios: starting point O→B (1.2), B→A (2.5), A→F (15÷15=1.0), F→C (0.83); The new spatial conflict coefficient S = 2.5 (B→A is still congested, but the total time is reduced). The new time conflict coefficient T = 133 ÷ 240 ≈ 0.55; The new comprehensive conflict coefficient C = 2.5 × 0.6 + 0.55 × 0.4 = 1.5 + 0.22 = 1.72 (still ≥ 1.2, requiring secondary resolution). If it is found that further elimination is needed, then remove F. Following the same logic as above, the final path is obtained.
[0076] By quantitatively calculating spatial conflict coefficient, temporal conflict coefficient, and comprehensive conflict coefficient, accurate determination of inspection route conflicts is achieved, avoiding the problem of misjudgment or omission of conflicts caused by insufficient consideration of dynamic factors such as real-time road conditions and time allocation in traditional route planning. The conflict elimination strategy prioritizes detour alternatives, ensuring the integrity of inspection coverage without reducing the number of inspection sites. When detours are not feasible, low-priority inspection sites are gradually removed according to the priority of the intelligent balance factor, ensuring that high-priority inspection tasks (such as high-priority inspection sites such as points A and B) are completed first. The entire process achieves adaptive optimization of inspection routes by dynamically iterating the comprehensive conflict coefficient through real-time data. This ensures the scientific nature of route adjustments, minimizes unnecessary backtracking and time waste, significantly improves inspection efficiency, and retains complete adjustment logic and calculation basis for easy follow-up optimization. Combined with the accurate quantification of inspection site priority by the intelligent balance factor, the route planning is more in line with actual inspection needs, reducing manpower and transportation energy costs and improving the flexibility and reliability of inspection work.
[0077] like Figure 3 As shown, the present invention also provides an inspection route planning system, which includes: Data processing module: used to obtain the intelligence factor reflecting the inspection priority of each inspection site, and divide each inspection site into multiple classification sets with different inspection priorities according to the size of the intelligence factor. Path planning module: Based on the location information and real-time traffic conditions of each inspection point in the highest priority category, generate an initial inspection route covering the inspection points included in that category. According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraints of the inspection location, to obtain the final inspection route.
[0078] In the description of this application, it should be noted that the terms "upper," "lower," etc., indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication between two elements. For those skilled in the art, the specific meaning of the above terms in this application can be understood according to the specific circumstances.
[0079] It should be noted that in this application, 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 those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.
[0080] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.
Claims
1. A method for planning inspection routes, characterized in that, It includes the following steps: Obtain the intelligence factor reflecting the inspection priority of each inspection site; Based on the magnitude of the aforementioned intelligent balance factor, each inspection site is divided into multiple classification sets with different inspection priorities; Based on the location information and real-time traffic conditions of each inspection site in the highest priority category, an initial inspection route covering the inspection sites included in that category is generated. According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraints of the inspection location, to obtain the final inspection route.
2. The inspection route planning method as described in claim 1, characterized in that, Before obtaining the final inspection route, the method also includes: According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraint of the inspection location, to obtain the temporary inspection route. If there is a conflict between the temporary inspection route and the real-time inspection situation, the temporary inspection route is optimized according to the conflict elimination strategy to obtain the final inspection route.
3. The inspection route planning method as described in claim 1, characterized in that, Based on the magnitude of the aforementioned intelligence factor, each inspection site is divided into multiple classification sets with different inspection priorities, including: Multiple consecutive numerical intervals are set, each corresponding to a classification set, and the intervals do not overlap with each other, together covering the entire range of values of the Zhiheng factor. Based on the value range of the Wisdom Factor at each inspection location, it is divided into the corresponding classification set.
4. The inspection route planning method as described in claim 3, characterized in that, According to the inspection priority order of the classification set, the remaining inspection locations contained in the classification set are sequentially inserted into the initial inspection route, taking into account the dynamic insertion weight and insertion constraints of the inspection location, to obtain the temporary inspection route, specifically including: For the remaining classification set with the highest inspection priority, calculate the dynamic insertion weight of the inspection sites it contains; Based on the dynamic insertion weight and the insertion constraints corresponding to the current classification set, the inspection locations within the classification set are inserted into the current inspection route to form an updated temporary inspection route. Repeat the above steps until all remaining inspection locations in the classification set have been processed. The resulting route is the temporary inspection route.
5. The inspection route planning method as described in claim 4, characterized in that, The calculation of the dynamic insertion weight of the inspection site includes: based on a preset first threshold, and combined with the abnormal warning correction value of the inspection site and the congestion correction value of the real-time traffic conditions. The step of inserting the inspection site into the current inspection route includes: dynamically inserting the inspection site into any adjacent inspection site in the current inspection route in descending order of the insertion weight, and calculating the time increment caused by each insertion. The insertion constraint is: the sum of the total duration of the current inspection route and the duration increment caused by the insertion does not exceed the remaining working time of the day; If the insertion of the current inspection location satisfies the insertion constraint, then the current inspection location is inserted into the current inspection route; otherwise, the inspection location is adjusted to a lower priority category set and is not inserted for the time being.
6. The inspection route planning method as described in claim 4, characterized in that: The calculation of the dynamic insertion weight of the inspection site includes: calculation based on a preset second threshold and combined with a time surplus coefficient, wherein the time surplus coefficient is obtained by dividing the remaining working hours of the day by the product of the historical average inspection time of the current inspection site and a predetermined coefficient. If the time surplus coefficient is less than or equal to 1, then the dynamic insertion weight of the current inspection site is 0; The insertion constraint is: the dynamic insertion weight of the current inspection site is greater than 0; If the insertion of the current inspection location satisfies the insertion constraint, then the current inspection location will be inserted into the current inspection route.
7. The inspection route planning method as described in claim 2, characterized in that, The criteria for determining if there is a conflict between the temporary inspection route and the real-time inspection situation are as follows: Obtain the ratio of real-time travel time to estimated travel time for each segment of the temporary inspection route, and take the maximum value of the ratio for all segments as the spatial conflict coefficient. The ratio of the total estimated time for temporary inspection routes to the total working hours of the day is used as the time conflict coefficient. Based on the spatial conflict coefficient, the temporal conflict coefficient, and their respective weights, a comprehensive conflict coefficient is obtained. If the overall conflict coefficient is greater than or equal to the preset value, it is determined that there is a conflict between the temporary inspection route and the real-time inspection situation.
8. The inspection route planning method as described in claim 7, characterized in that, The conflict resolution strategy is as follows: Obtain the two inspection points corresponding to the road segment with the maximum spatial conflict coefficient; Based on the real-time road conditions between the two inspection points, an alternative route between the two inspection points is obtained, and the comprehensive conflict coefficient is recalculated. If the new overall conflict coefficient is less than the preset value, then a new inspection path including the alternative path is adopted; If the new overall conflict coefficient is still greater than or equal to the preset value, then the lowest priority inspection site is removed from the inspection site sequence, and a new inspection path is generated. Recalculate the overall conflict coefficient under the new inspection path; Repeat the removal and calculation steps until the overall conflict coefficient under the new inspection path is less than the preset value; The new inspection route will be used as the final inspection route.
9. The inspection route planning method as described in claim 1, characterized in that: The intelligent balance factor includes at least the task weight, the inspection site value weight, the remaining working time factor, and the historical efficiency factor.
10. An inspection route planning system, characterized in that, It includes: Data processing module: used to obtain the intelligence factor reflecting the inspection priority of each inspection site, and divide each inspection site into multiple classification sets with different inspection priorities according to the size of the intelligence factor. Path planning module: Based on the location information and real-time traffic conditions of each inspection point in the highest priority category, generate an initial inspection route covering the inspection points included in that category. According to the inspection priority order of the classification set, the inspection locations contained in the remaining classification set are sequentially inserted into the initial inspection route, combined with the dynamic insertion weight and insertion constraints of the inspection location, to obtain the final inspection route.