School intelligent quick-receiving and quick-sending method and system

Abstract

The invention discloses an intelligent quick receiving and sending method and system for a school. The method comprises the steps of information registration and reminding, intelligent scheduling, dynamic strategy optimization, student safety confirmation and receiving and sending feedback. The invention belongs to the technical field of intelligent pick-up and sending of students, and particularly relates to a school intelligent quick pick-up and flash-sending method and system.According to the scheme, the search space is limited, a one-way special channel is delimited, grading peak shifting parking of vehicles is achieved, dynamic shunting is carried out, and the green light time of intersections is dynamically distributed according to the pheromone concentration; the state transition probability is calculated, global pheromone updating is carried out, and traffic flow self-adaptive equilibrium distribution is guided; a dynamic fitness function is designed to balance traffic efficiency and path diversity, adaptive diversity parameters based on an iteration stage are calculated, a solution space is explored in an initial stage, fine development is carried out in a later stage, vehicles in the same area are guided to stop in a concentrated manner by utilizing similarity clustering, a slow passage and a dynamic insertion strategy are set, emergencies are solved, and traffic efficiency is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent student pick-up and drop-off, and specifically relates to a school intelligent quick pick-up and flash delivery method and system. Background Art

[0002] The school intelligent quick pick-up and flash delivery system is a system for parents of students in the campus to quickly pick up and drop off students to and from school based on the intelligent parking system platform technology. Through identity recognition technology, communication technology and positioning technology, it realizes the quick pick-up and drop-off of students, optimizes the traffic flow of the school, reduces the waiting time of parents, and improves the use experience of parents and school administrators. However, the existing intelligent optimization methods for student pick-up and drop-off have technical problems such as a large number of vehicles gathering at the school gate within a short time during peak pick-up and drop-off hours, resulting in queuing overflow, and the fixed allocation of parking lot and road resources, which cannot meet the dynamic demand; there are also technical problems such as the traditional scheme recommended by the navigation during the way home often pursues the shortest path, resulting in concentrated congestion of vehicles, chaotic vehicle parking, congestion in the parking lot, and potential safety hazards due to the mixed traffic of slow traffic and motor vehicles, and system crashes caused by sudden demands. Summary of the Invention

[0003] In view of the above situation, in order to overcome the defects of the prior art, the present invention provides a school intelligent quick pick-up and flash delivery method and system. For the technical problems of a large number of vehicles gathering at the school gate within a short time during peak pick-up and drop-off hours, resulting in queuing overflow, and the fixed allocation of parking lot and road resources, which cannot meet the dynamic demand, intelligent scheduling is adopted to limit the search space, demarcate one-way dedicated channels, set up grade diversion gates to achieve hierarchical staggered docking of vehicles, conduct dynamic diversion, dynamically distribute the green light time at intersections according to the pheromone concentration, calculate the state transition probability, dynamically recommend the optimal and dispersed routes, and conduct global pheromone update to guide the vehicle flow to adaptively and evenly distribute; for the technical problems of the traditional scheme recommended by the navigation during the way home often pursuing the shortest path, resulting in concentrated congestion of vehicles, chaotic vehicle parking, congestion in the parking lot, and potential safety hazards due to the mixed traffic of slow traffic and motor vehicles, and system crashes caused by sudden demands, a dynamic fitness function is designed to balance traffic efficiency and path diversity, an adaptive diversity parameter based on the iterative stage is calculated, the solution space is explored in the initial stage and finely developed in the later stage, similarity clustering is used to guide vehicles in the same area to concentrate on docking, reduce the moving distance of vehicles in the parking lot, shorten the average time for parents to find parking spaces, set up slow traffic channels and dynamic insertion strategies to solve emergencies and improve traffic efficiency.

[0004] The technical solution adopted by the present invention is as follows: A school intelligent quick pick-up and flash delivery method provided by the present invention includes the following steps:

[0005] Step S1: Information registration and reminder. Through the cooperation of the management terminal, parent terminal, teacher terminal and tablet terminal, the whole process is digitally managed;

[0006] Step S2: Intelligent scheduling. Limit the search space, delimit one-way dedicated channels, set up grade diversion gates to achieve hierarchical and staggered parking of vehicles, conduct dynamic diversion, dynamically distribute the green light time at intersections according to the pheromone concentration, calculate the state transition probability, dynamically recommend the optimal and dispersed routes, and perform global pheromone update to guide the adaptive and balanced distribution of vehicle flows;

[0007] Step S3: Dynamic optimization strategy. Design a dynamic fitness function to balance traffic efficiency and path diversity, calculate the adaptive diversity parameter based on the iterative stage, explore the solution space in the initial stage and conduct fine-grained development in the later stage. Use similarity clustering to guide vehicles in the same area to park centrally, reduce the moving distance of vehicles in the parking lot, shorten the average time for parents to find parking spaces, set up slow lanes and dynamic insertion strategies to solve emergencies and improve traffic efficiency;

[0008] Step S4: Student safety confirmation. Through GPS positioning technology, verify the student's identity and pick-up / drop-off address, and generate pick-up / drop-off records;

[0009] Step S5: Pick-up / drop-off feedback. After the pick-up / drop-off task is completed, the system records the task details, and parents can evaluate through the application.

[0010] Furthermore, in Step S1, the information registration and reminder include the following steps:

[0011] Step S11: Use the management terminal to register student parent information, manage classes, push pick-up / drop-off messages, configure pick-up / drop-off areas, schedule teachers, and conduct pick-up / drop-off statistics;

[0012] The registration of student parent information includes registering the student's name, number, school, school stage, grade, class, parent's name, contact information, and license plate number; after the parent's mobile phone number is entered, the small program can be used, and it can be selected whether to pick up / drop off the child on the same day;

[0013] The class management includes listing each grade, configuring the pick-up time period for going to school and the pick-up time period for leaving school for the corresponding school stage, and setting the cut-off time for modifying the pick-up / drop-off method for going to school and the cut-off time for modifying the pick-up / drop-off method for leaving school. After the cut-off time, parents are not allowed to modify the student's pick-up / drop-off method;

[0014] The push of pick-up / drop-off messages includes reminding parents before picking up / dropping off students, sending text messages to parents to remind them of the pick-up / drop-off time and the waiting area number;

[0015] Step S12: Use the parent terminal to manage pick-up / drop-off vehicles and modify pick-up / drop-off methods;

[0016] The pick-up and drop-off vehicle management includes adding vehicles and modifying vehicles;

[0017] The modification of the pick-up and drop-off method is to select the way to go to school and the way to leave school today, whether to drive or not;

[0018] Step S13: Use the teacher's terminal to conduct pick-up and drop-off statistics and view scheduling information;

[0019] Step S14: Use the tablet terminal to display pick-up and drop-off data in real time.

[0020] Further, in step S2, the intelligent scheduling includes the following steps:

[0021] Step S21: Limit the visual search space for the dynamic planning of the pick-up and drop-off route. In the search space, increasing the number of grids will lead to a large amount of computational load. To reduce the complexity of the search, set the maximum horizontal, vertical, and vertical direction limits according to the road grids of the city, and make full use of the underground garage resources of the Experimental Primary School to demarcate a one-way pick-up and drop-off dedicated channel. Set 10 gates according to grades and classes. When students go to school and leave school, parents can find the corresponding pick-up and drop-off ports in the first time, realizing stop-and-go;

[0022] Step S22: Calculate the state transition probability. In the path exploration process of the ant colony algorithm, the state transition probability is mainly calculated according to the pheromone level and heuristic information related to each node, and dynamically recommend the optimal and dispersed routes. The formula used is as follows:

[0023] ;

[0024] In the formula, represents the state transition probability, represents the pheromone concentration from node i to node j at time t, represents the heuristic information of the path from node i to node j at time t, represents the pheromone factor, represents the heuristic information factor, represents the set of nodes that ant m can choose. Each ant does not have access to all nodes when choosing a path, but selects nodes within the range according to the constraints of the problem for transfer;

[0025] Calculate the heuristic information to avoid blindness in path selection. The formula used is as follows:

[0026] ;

[0027] In the formula, represents whether the grid cell is safe and feasible. If the grid cell is an obstacle, its value is 0; otherwise, the value is 1; represents the Euclidean distance between the current grid cell and the target grid cell, represents the signal-to-noise ratio factor of the current grid cell;

[0028] Step S23: Local pheromone update. Set the Zhongxin Youhao Garden Parking Lot more than 400 meters away as the flexible waiting area, relieve congestion through the off-peak sharing of 400 parking spaces, and monitor the traffic flow of each path in real time. When congestion occurs on one of the pick-up and drop-off routes, the local pheromone update mechanism is automatically triggered, and the guiding weight of this path is gradually reduced to prompt some vehicles to explore new paths. The formula used is as follows:

[0029] ;

[0030] In the formula, represents the attenuation coefficient of the pheromone, represents the pheromone concentration from node i to node j at time t - 1, represents the initial concentration of the pheromone;

[0031] When dynamically guiding the microcirculation from Zhongxin Avenue to Xin'er Street, the system attenuates the pheromone concentration of each intersection node according to the real-time road conditions. When the waiting time at a node exceeds the threshold, the pheromone concentration is reduced to prompt the vehicle flow to distribute evenly spontaneously, improve the overall traffic efficiency, and maintain the redundancy of path exploration to cope with emergencies;

[0032] Step S24: Global pheromone update. Calculate the updated pheromone and pheromone increment. At the end of each traffic scheduling cycle, the system performs a Pareto front analysis on all current feasible path schemes. The formula used is as follows:

[0033] ;

[0034] ;

[0035] In the formula, represents the pheromone at time t + 1, represents the pheromone update coefficient. For example, it takes 0.7 during the peak period and 0.3 during the off-peak period, represents the pheromone increment, which is used to adjust the path weight. The less congested the path is, the higher the pheromone increment it gets. Q represents the pheromone intensity constant, represents the congestion cost of the solution, including the average travel time, the queue length at intersections, etc.;

[0036] Step S25: Measure the evenness of the solution distribution. An evenly distributed solution set ensures that the solution space is widely explored, which helps to find the global optimal solution in multi-objective problems. The formula used is as follows:

[0037] ;

[0038] In the formula, S represents the Spacing index, which measures the degree of uniform distribution among the solutions in the solution set. The smaller the value of S, the more evenly distributed the solutions in the solution set. For example, when S exceeds the threshold of 1.2, it indicates that the path recommendations are too concentrated. At this time, the pheromone update coefficient is reduced and the random exploration probability is increased to prompt the vehicle to try sub-optimal paths, such as detouring through Zhongxin Avenue or using different parking lot entrances; when S continues to be low, below 0.5, the pheromone intensity constant is increased to strengthen the attraction of high-performance paths and balance exploration and exploitation. represents the number of solutions in the solution set SolSet. represents the distance between the i-th solution and its nearest neighbor solution. represents the average value of the distances between all pairs of solutions in the solution set SolSet.

[0039] Furthermore, in step S3, the dynamic optimization strategy includes the following steps:

[0040] Step S31: Design a dynamic fitness function. When evaluating the quality of a path plan, both traffic efficiency and path diversity are considered simultaneously. The formula used is as follows:

[0041] ;

[0042] In the formula, fit represents the fitness value, TOC represents traffic efficiency, represents the maximum value of traffic efficiency, NV represents path diversity, represents the maximum value of path diversity;

[0043] Step S32: Update the population diversity parameter according to the iteration situation. In the initial stage of iteration, the parameter value is large, and the algorithm pays more attention to exploring new solution regions to maintain the diversity of the population and prevent early convergence to local optimal solutions; in the later stage of iteration, the parameter value is small, and the optimization process gradually turns to exploitation, more finely optimizing the existing solutions to find the optimal solution. The formula for calculating the population diversity parameter is as follows:

[0044] ;

[0045] In the formula, mp represents the parameter of population diversity, gen represents the current iteration number, represents the maximum iteration number;

[0046] Step S33: Optimize the pick-up and drop-off path arrangement according to the similarity value. According to the similarity value calculated in real time, the vehicles of student parents with similar residences are grouped and guided to the same area of the Zhongxin Friendship Garden Parking Lot to reduce the moving distance of vehicles within the parking lot. The formula used is as follows:

[0047] ;

[0048] In the formula, Represents the similarity value between student a and student b, which is used to evaluate the relationship between the two students in the pick-up and drop-off routes. A high similarity means that the pick-up and drop-off relationship between the two students is relatively close, and it is suitable to be arranged on the same route; a low similarity means that they are far apart in the pick-up and drop-off route, and the route arrangement needs to be adjusted; Indicates whether student a and student b are on the same pick-up route v, represents the distance between student a and student b, represents the maximum distance between all pairs of students, V represents the set of pick-up and drop-off routes, and C represents the set of students involved in the pick-up and drop-off.

[0049] Step S34: Restoring the slow-moving road. In view of the fact that there are many students riding bicycles and parents riding electric bikes to pick up their children in the surrounding area, about 1,500 non-motor vehicles are parked on the slow-moving trail of Zhongtian Avenue on weekdays, affecting traffic. The Eco-City Urban Management Bureau transformed the road near the school wall into a non-motor vehicle parking lot, restored the function of the slow-moving road, alleviated the potential safety hazard of mixed traffic of motor vehicles and non-motor vehicles, and transformed the hedges on the roads around the campus into pedestrian pavements, so that the entrances and exits of students to the school are changed from points to lines, further improving traffic efficiency;

[0050] Step S35: dynamic demand insertion strategy, including the following steps:

[0051] When special vehicles enter the control area, such as ambulances and fire trucks, they need to clear the optimal path pheromones and monopolize the right of way;

[0052] When a road suddenly becomes congested, local updates are triggered, pheromones are reduced, and detours are activated;

[0053] When the parking lot is full, the heuristic information is dynamically adjusted to guide vehicles to the suboptimal parking lot.

[0054] Furthermore, in step S4, the student safety confirmation is specifically real-time GPS location verification. The GPS positioning of the pick-up vehicle is verified in combination with the student's pick-up location. When the pick-up vehicle approaches the predetermined pick-up point, the system can automatically verify whether the location matches the registered pick-up address. Once the verification is passed, the system will automatically record the student's pick-up information and generate a pick-up confirmation record. The pick-up personnel and parents will also receive a confirmation notification of the pick-up status.

[0055] Furthermore, in step S5, the pick-up feedback includes the following steps:

[0056] Step S51: After arriving at the destination, confirm that the pick-up task is completed, and the system records the detailed information of the pick-up task as a basis for feedback;

[0057] Step S52: Parent evaluation and feedback. After the pick-up and drop-off task is completed, the parent evaluates the pick-up and drop-off process through the application.

[0058] A school intelligent quick pick-up and flash delivery system provided by the present invention includes an information registration and reminder module, an intelligent scheduling module, a dynamic optimization strategy module, a student safety confirmation module, and a pick-up and drop-off feedback module;

[0059] The information registration and reminder module realizes full-process digital management through the cooperation of four terminals: the management terminal, the parent terminal, the teacher terminal, and the tablet terminal;

[0060] The intelligent scheduling module restricts the search space, delimits one-way dedicated channels, sets grade diversion gates to achieve hierarchical and staggered parking of vehicles, conducts dynamic diversion, dynamically distributes the green light time at intersections according to the pheromone concentration, calculates the state transition probability, dynamically recommends the optimal and dispersed routes, and conducts global pheromone update to guide the vehicle flow to adaptively and evenly distribute;

[0061] The dynamic optimization strategy module designs a dynamic fitness function to balance traffic efficiency and path diversity, calculates the adaptive diversity parameter based on the iterative stage, explores the solution space in the initial stage and conducts fine development in the later stage, uses similarity clustering to guide vehicles in the same area to concentrate on parking, reduces the vehicle movement distance in the parking lot, shortens the average time for parents to find parking spaces, sets slow-moving channels and dynamic insertion strategies to solve emergencies and improve traffic efficiency;

[0062] The student safety confirmation module verifies the student's identity and pick-up and drop-off address through GPS positioning technology and generates pick-up and drop-off records;

[0063] The pick-up and drop-off feedback module records the task details after the pick-up and drop-off task is completed, and the parent evaluates through the application.

[0064] The beneficial effects achieved by the present invention using the above solution are as follows:

[0065] (1) Aiming at the technical problems that during the peak hours of going to and from school, a large number of vehicles gather at the school gate in a short time, resulting in road paralysis at intersections, queue overflow, and the fixed allocation of parking lot and road resources, which cannot adapt to dynamic demands. Intelligent scheduling is adopted to restrict the search space, delimit one-way dedicated channels, set grade diversion gates to achieve hierarchical and staggered parking of vehicles, conduct dynamic diversion, dynamically distribute the green light time at intersections according to the pheromone concentration, calculate the state transition probability, dynamically recommend the optimal and dispersed routes, and conduct global pheromone update to guide the vehicle flow to adaptively and evenly distribute;

[0066] (2)In view of the technical problems that in the traditional solution recommended by the navigation on the way home, the shortest path is often pursued, resulting in concentrated vehicle congestion, chaotic vehicle parking, congestion in the parking lot, potential safety hazards due to the mixed operation of slow traffic and motor vehicles, and system collapse caused by sudden demands, a dynamic fitness function is designed to balance traffic efficiency and path diversity, an adaptive diversity parameter based on the iterative stage is calculated, the solution space is explored in the initial stage and finely developed in the later stage, similarity clustering is used to guide vehicles in the same area to park concentratedly, the moving distance of vehicles in the parking lot is reduced, the average time for parents to find a parking space is shortened, a slow traffic channel and a dynamic insertion strategy are set up to solve emergencies and improve traffic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 FIG. is a schematic flowchart of a school intelligent quick pick-up and flash delivery method provided by the present invention;

[0068] Figure 2 FIG. is a schematic diagram of a school intelligent quick pick-up and flash delivery system provided by the present invention;

[0069] Figure 3 FIG. is a schematic flowchart of step S2;

[0070] Figure 4 FIG. is a schematic flowchart of step S3.

[0071] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0072] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments; based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present invention.

[0073] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc. indicating the orientation or position relationship are based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation to the present invention.

[0074] Embodiment 1, referring to Figure 1 , a school intelligent quick pick-up and flash delivery method provided by the present invention, the method includes the following steps:

[0075] Step S1: Information registration and reminder, through the collaboration of the management terminal, parent terminal, teacher terminal and tablet terminal, the whole process of digital management is realized;

[0076] Step S2: Intelligent scheduling, limiting the search space, demarcating one-way dedicated channels, setting grade diversion gates to achieve graded staggered parking for vehicles, dynamic diversion, dynamically distributing the green light time at intersections according to pheromone concentration, calculating the state transition probability, dynamically recommending the optimal and dispersed routes, performing global pheromone updates, and guiding the adaptive balanced distribution of traffic flow;

[0077] Step S3: Dynamic optimization strategy, design dynamic fitness function to balance traffic efficiency and path diversity, calculate adaptive diversity parameters based on the iteration stage, explore the solution space in the early stage, and develop it in detail in the later stage, use similarity clustering to guide vehicles in the same area to park in a concentrated manner, reduce the moving distance of vehicles in the parking lot, shorten the average time for parents to find parking spaces, set slow lanes and dynamic insertion strategies, solve emergencies and improve traffic efficiency;

[0078] Step S4: Student safety confirmation: verify the student identity and pick-up address through GPS positioning technology, and generate a pick-up record;

[0079] Step S5: Pick-up and drop-off feedback. After the pick-up and drop-off task is completed, the system records the task details and parents evaluate it through the application.

[0080] Example 2, see Figure 1 This embodiment is based on the above embodiment. In step S1, the information registration and reminder includes the following steps:

[0081] Step S11: Use the management terminal to register student parent information, class management, push pick-up and drop-off messages, configure pick-up and drop-off areas, schedule teachers, and perform pick-up and drop-off statistics;

[0082] The registered student parent information includes the student's name, ID, school, grade, class, parent's name, contact information and license plate number. Parents can use the mini program only after entering their mobile phone number and choose whether to pick up their children on that day.

[0083] The class management includes listing each grade, configuring the time periods for school drop-off and pick-up for the corresponding school period, and setting the cut-off time for modifying the school drop-off and pick-up method and the cut-off time for modifying the school drop-off and pick-up method. Parents are not allowed to modify the student drop-off and pick-up method after the cut-off time.

[0084] The push pick-up message includes reminding parents before picking up students, sending text message reminders to parents, reminding parents of the pick-up time and waiting area number;

[0085] Step S12: Use the parent terminal to manage pick-up and drop-off vehicles and modify the pick-up and drop-off methods;

[0086] The pick-up and drop-off vehicle management includes adding vehicles and modifying vehicles;

[0087] The modification of the pick-up and drop-off method is to select whether to drive or not drive for the way to school and the way home today;

[0088] Step S13: Use the teacher terminal to conduct pick-up and drop-off statistics and view scheduling information;

[0089] Step S14: Use the tablet terminal to display pick-up and drop-off data in real time.

[0090] Example 3, refer to Figure 1 and Figure 3 , based on the above example, in step S2, the intelligent scheduling includes the following steps:

[0091] Step S21: Limit the visual search space for dynamic planning of pick-up and drop-off routes. In the search space, increasing the number of grids will lead to a large amount of computational load. To reduce the complexity of the search, set the maximum horizontal, vertical, and vertical direction limits according to the road grids of the city, and make full use of the resources of the underground garage of the Experimental Primary School to demarcate a one-way pick-up and drop-off dedicated channel. Set 10 gates according to grades and classes. When students go to school and leave school, parents can find the corresponding pick-up and drop-off ports in the first time and achieve immediate stop and go;

[0092] Step S22: Calculate the state transition probability. In the path exploration process of the ant colony algorithm, the state transition probability is mainly calculated based on the pheromone level and heuristic information related to each node, and dynamically recommend the optimal and dispersed routes. The formula used is as follows:

[0093] ;

[0094] In the formula, represents the state transition probability, represents the pheromone concentration from node i to node j at time t, represents the heuristic information of the path from node i to node j at time t, represents the pheromone factor, represents the heuristic information factor, represents the set of nodes that ant m can choose. Each ant does not have access to all nodes when choosing a path, but selects the nodes within the range according to the constraints of the problem for transfer;

[0095] Calculate the heuristic information to avoid blindness in path selection. The formula used is as follows:

[0096] ;

[0097] In the formula, indicates whether the indicated grid cell is safe and feasible. If the grid cell is an obstacle, its value is 0; otherwise, the value is 1; represents the Euclidean distance between the current grid cell and the target grid cell, represents the signal-to-noise ratio factor of the current grid cell;

[0098] Step S23: Local pheromone update. Set the Zhongxin Youhao Garden Parking Lot more than 400 meters away as the flexible waiting area. Alleviate congestion through the off-peak sharing of 400 parking spaces. Real-time monitor the traffic flow of each path. When congestion occurs on one of the pick-up and drop-off routes, automatically trigger the local pheromone update mechanism, gradually reduce the guiding weight of this path, and prompt some vehicles to explore new paths. The formula used is as follows:

[0099] ;

[0100] In the formula, represents the attenuation coefficient of the pheromone, represents the pheromone concentration from node i to node j at time t - 1, represents the initial concentration of the pheromone;

[0101] When dynamically guiding the microcirculation from Zhongxin Avenue to Xin'er Street, the system attenuates the pheromone concentration of each intersection node according to the real-time road conditions. When the waiting time at a node exceeds the threshold, the pheromone concentration is reduced to prompt the vehicle flow to distribute evenly spontaneously, improve the overall traffic efficiency, and maintain the redundancy of path exploration to cope with emergencies;

[0102] Step S24: Global pheromone update. Calculate the updated pheromone and pheromone increment. At the end of each traffic scheduling cycle, the system performs a Pareto front analysis on all current feasible path schemes. The formula used is as follows:

[0103] ;

[0104] ;

[0105] In the formula, represents the pheromone at time t + 1, represents the pheromone update coefficient. For example, it takes 0.7 during peak hours and 0.3 during off-peak hours, represents the pheromone increment, which is used to adjust the path weight. The less congested the path is, the higher the pheromone increment it gets. Q represents the pheromone intensity constant, represents the congestion cost of the solution, including the average travel time, the queue length at intersections, etc.;

[0106] Step S25: Measure the distribution uniformity of the solutions. A uniformly distributed solution set ensures that the solution space is widely explored, which is helpful for the global optimal solution in multi-objective problems. The formula used is as follows:

[0107] ;

[0108] In the formula, S represents the Spacing index, which measures the uniform distribution degree among the solutions in the solution set. The smaller the value of S, the more uniformly the solutions in the solution set are distributed. For example, when S exceeds the threshold of 1.2, it indicates that the path recommendation is too concentrated. At this time, reduce the pheromone update coefficient and increase the random exploration probability to encourage the vehicle to try sub-optimal paths, such as detouring through Zhongxin Avenue or using different parking lot entrances; when S continues to be low, lower than 0.5, then increase the pheromone intensity constant to strengthen the attraction of high-performance paths and balance exploration and exploitation. represents the number of solutions in the solution set SolSet. represents the distance between the i-th solution and its nearest neighbor solution. represents the average value of the distances between all pairs of solutions in the solution set SolSet.

[0109] An actual application example is for parking lot diversion. When the around the Zhongxin Youhao Garden Parking Lot suddenly increases, the system reduces the pheromone increment of the associated path and adopts the direct access channel to the basement; for dynamic road right allocation, the signal cycle at the intersection of Xin'er Street and Zhongxin Avenue is adjusted in real time according to the pheromone at time t + 1, giving priority to releasing the flow with a higher pheromone concentration, but forcibly reserving 10% of the green light time for the low-concentration path.

[0110] By performing the above operations, intelligent scheduling is adopted, the search space is restricted, one-way dedicated channels are delimited, grade diversion gates are set to achieve hierarchical and staggered parking of vehicles, dynamic diversion is carried out, the green light time at intersections is dynamically distributed according to the pheromone concentration, the state transition probability is calculated, the optimal and dispersed routes are dynamically recommended, global pheromone update is performed, and the vehicle flow is guided to adaptively and evenly distribute, solving the technical problems that during the peak school arrival and departure times, a large number of vehicles gather at the school gate within a short time, resulting in the paralysis of the intersection, queuing overflow, and the fixed allocation of parking lot and road resources, which cannot adapt to dynamic demands.

[0111] Example 4, refer to Figure 1 and Figure 4 , based on the above example, in step S3, the dynamic optimization strategy includes the following steps:

[0112] Step S31: Design a dynamic fitness function. When evaluating the quality of a path plan, both traffic efficiency and path diversity are considered simultaneously. The formula used is as follows:

[0113] ;

[0114] In the formula, fit represents the fitness value, and TOC represents the traffic efficiency. represents the maximum value of the traffic efficiency, and NV represents the path diversity. represents the maximum value of the path diversity;

[0115] Step S32: Update the population diversity parameter according to the iteration situation. In the initial stage of iteration, the parameter value is large, and the algorithm pays more attention to exploring new solution regions, maintaining the diversity of the population, and preventing early convergence to local optimal solutions; in the later stage of iteration, the parameter value is small, and the optimization process gradually turns to exploitation, more finely optimizing the existing solutions to find the optimal solution. The formula for calculating the population diversity parameter is as follows:

[0116] ;

[0117] In the formula, mp represents the parameter of the population diversity, gen represents the current iteration number, represents the maximum iteration number;

[0118] Step S33: Optimize the pick-up and drop-off route arrangement according to the similarity value. According to the similarity value calculated in real time, group the vehicles of the parents of students with similar residences and guide them to the same area of the Zhongxin Friendship Garden Parking Lot, reducing the moving distance of vehicles in the parking lot. The formula used is as follows:

[0119] ;

[0120] In the formula, represents the similarity value between student a and student b, which is used to evaluate the relationship between the pick-up and drop-off routes of the two students. A high similarity means that the pick-up and drop-off relationships of these two students are relatively close and are suitable to be arranged on the same route; a low similarity means that their relationships on the pick-up and drop-off routes are far, and the route arrangement needs to be adjusted; represents whether student a and student b are on the same pick-up and drop-off route v, represents the distance between student a and student b, represents the maximum distance value between all pairs of students, V represents the set of pick-up and drop-off routes, and C represents the set of students participating in pick-up and drop-off;

[0121] Step S34: Restore the slow-moving road. Considering that there are many students riding bicycles and parents picking up and dropping off children by electric vehicles in the surrounding area, and about 1500 non-motor vehicles are parked on the slow-moving path of Zhongtian Avenue during weekdays, affecting traffic, the Urban Management Bureau of the Eco-city has transformed the road on one side of the school close to the wall into a non-motor vehicle parking lot, restored the function of the slow-moving road, alleviated the safety hazard problem of the mixed traffic of motor vehicles and non-motor vehicles, and transformed the green hedges on the roads around the campus into pedestrian pavements, changing the entrance and exit of students entering the school from a point to a line, further improving the traffic efficiency;

[0122] Step S35: Insertion strategy for dynamic demand, including the following steps:

[0123] When special vehicles enter the control area, such as ambulances, fire trucks, etc., it is necessary to forcibly clear the pheromone of the optimal path and monopolize the right of way;

[0124] When the road suddenly becomes congested, trigger local update, reduce pheromone and activate the detour path;

[0125] When the parking lot is at full capacity, dynamically adjust the heuristic information to guide the vehicle to the sub-optimal parking lot.

[0126] By performing the above operations, adopt a designed dynamic fitness function to balance traffic efficiency and path diversity, calculate the adaptive diversity parameter based on the iterative stage, explore the solution space in the initial stage, and refine and develop in the later stage. Use similarity clustering to guide vehicles in the same area to park concentratedly, reduce the moving distance of vehicles in the parking lot, shorten the average time for parents to find parking spaces, set up slow lanes and dynamic insertion strategies to solve emergencies and improve traffic efficiency. It solves the technical problems that the traditional scheme recommended by the navigation during the way home often pursues the shortest path, resulting in concentrated vehicle congestion, chaotic vehicle parking, congestion in the parking lot, potential safety hazards in the mixed traffic of slow traffic and motor vehicles, and system crashes caused by sudden demands.

[0127] Example 5, refer to Figure 1 , based on the above embodiment, in step S4, the student safety confirmation is specifically real-time GPS position verification. The GPS positioning of the pick-up and drop-off vehicle is combined with the pick-up and drop-off location of the student for verification. When the pick-up and drop-off vehicle approaches the predetermined pick-up and drop-off point, the system can automatically verify whether the location matches the registered pick-up and drop-off address. Once the verification is passed, the system will automatically record the pick-up and drop-off information of the student and generate a pick-up and drop-off confirmation record.

[0128] Example 6, refer to Figure 1 , based on the above embodiment, in step S5, the pick-up and drop-off feedback includes the following steps:

[0129] Step S51: After arriving at the destination, confirm that the pick-up and drop-off task is completed, and the system records the detailed information of this pick-up and drop-off task as the feedback basis;

[0130] Step S52: Parent evaluation feedback. After the pick-up and drop-off task is completed, the parent evaluates the pick-up and drop-off process through the application.

[0131] Example 7, refer to Figure 2 , based on the above embodiment, a school intelligent quick pick-up and flash delivery system provided by the present invention includes an information registration and reminder module, an intelligent scheduling module, a dynamic optimization strategy module, a student safety confirmation module, and a pick-up and drop-off feedback module;

[0132] The information registration and reminder module realizes full-process digital management through the cooperation of four terminals: the management terminal, the parent terminal, the teacher terminal, and the tablet terminal;

[0133] The intelligent scheduling module restricts the search space, demarcates one-way dedicated channels, sets up grade diversion gates to achieve hierarchical and staggered docking of vehicles, conducts dynamic diversion, dynamically distributes the green light time at intersections according to the concentration of pheromones, calculates the state transition probability, dynamically recommends the optimal and dispersed routes, and conducts global pheromone update to guide the vehicle flow to adaptively and evenly distribute;

[0134] The dynamic optimization strategy module designs a dynamic fitness function to balance traffic efficiency and path diversity, calculates the adaptive diversity parameter based on the iterative stage, explores the solution space in the initial stage and conducts fine development in the later stage, uses similarity clustering to guide vehicles in the same area to dock centrally, reduces the moving distance of vehicles in the parking lot, shortens the average time for parents to find parking spaces, and sets up slow lanes and dynamic insertion strategies to solve emergencies and improve traffic efficiency;

[0135] The student safety confirmation module verifies the student's identity and pick-up and drop-off address through GPS positioning technology and generates pick-up and drop-off records;

[0136] The pick-up and drop-off feedback module records the task details after the pick-up and drop-off task is completed, and parents can evaluate through the application.

[0137] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0138] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

[0139] The above describes the present invention and its implementation manners. This description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Generally speaking, if those of ordinary skill in the art are inspired by it and design similar structural manners and embodiments without creative efforts without departing from the purpose of the present invention, they shall fall within the protection scope of the present invention.

Claims

1. A school smart fast connection and transmission method, characterized by: The method comprises the following steps: Step S1: information registration and reminder; Step S2: Intelligent scheduling, limiting the search space, demarcating one-way dedicated channels, setting grade diversion gates, dynamically distributing the green light time at intersections according to pheromone concentration, calculating the state transition probability, dynamically recommending the optimal and dispersed routes, performing global pheromone updates, and guiding the adaptive balanced distribution of traffic flow; Step S3: Dynamic optimization strategy, design dynamic fitness function, calculate adaptive diversity parameters based on the iteration stage, use similarity clustering to guide vehicles in the same area to stop together, set slow lanes and dynamic insertion strategies to solve emergencies; Step S4: Student safety confirmation; Step S5: receiving and delivering feedback.

2. According to claim 1, a school intelligent fast connection and transmission method is characterized by: In step S2, the intelligent scheduling includes the following steps: Step S21: restricting the visual search space, setting the maximum horizontal, longitudinal and vertical limits according to the road grid of the city; Step S22: Calculate state transition probabilities, dynamically recommend optimal and decentralized routes, and calculate heuristic information; Step S23: local update of pheromones, setting a flexible waiting area, and real-time monitoring of the traffic volume of each route. When one of the pick-up routes is congested, the local update mechanism of pheromones is automatically triggered to reduce the guidance weight of the route and encourage vehicles to explore new routes; Step S24: Global update of pheromones, calculation of updated pheromones and pheromone increments. At the end of each traffic scheduling cycle, the system performs a Pareto frontier analysis on all currently feasible path solutions. Step S25: measure the uniformity of solution distribution, and a uniformly distributed solution set ensures that the solution space is widely explored.

3. According to claim 1, a school intelligent fast connection and transmission method is characterized by: In step S3, the dynamic optimization strategy includes the following steps: Step S31: design a dynamic fitness function to consider both traffic efficiency and path diversity when evaluating the quality of path solutions; Step S32: updating population diversity parameters according to iteration conditions; Step S33: optimizing the pick-up and drop-off route arrangement according to the similarity value, and guiding the vehicles of parents of students who live close to each other to the same area of ​​the parking lot according to the similarity value calculated in real time, so as to reduce the moving distance of the vehicles in the parking lot; Step S34: Restoring the slow-moving road. For students riding bicycles and parents picking up their children on electric bikes, the Eco-City Urban Management Bureau transformed the road near the school wall into a non-motor vehicle parking lot, restoring the function of the slow-moving road, and transformed the hedges on the roads around the campus into pedestrian pavement, so that the entrances and exits for students to enter the school are changed from points to lines; Step S35: Insertion strategy for dynamic requirements.

4. According to claim 1, a school intelligent fast connection and delivery method is characterized by: In step S1, the information registration and reminder includes the following steps: Step S11: Use the management terminal to register student parent information, class management, push pick-up and drop-off messages, configure pick-up and drop-off areas, schedule teachers, and perform pick-up and drop-off statistics; Step S12: Use the parent terminal to manage the pick-up vehicle and modify the pick-up method; Step S13: Use the teacher terminal to check pick-up statistics and shift scheduling information; Step S14: Use the tablet terminal to display the pick-up and drop-off data in real time.

5. According to claim 1, a school intelligent fast connection and transmission method is characterized by: In step S4, the student safety confirmation is specifically real-time GPS location verification. The GPS positioning of the pick-up vehicle is verified in combination with the student's pick-up location. When the pick-up vehicle approaches the predetermined pick-up point, the system automatically verifies whether it matches the registered pick-up address. Once the verification is passed, the system automatically records the student's pick-up information and generates a pick-up confirmation record. The pick-up personnel and parents will also receive a confirmation notification of the pick-up status.

6. A school smart quick connection and delivery method according to claim 1, characterized in that: In step S5, the pick-up feedback includes the following steps: Step S51: After arriving at the destination, confirm that the pick-up task is completed, and the system records the detailed information of the pick-up task as a basis for feedback; Step S52: Parent evaluation feedback: After the pick-up task is completed, the parent evaluates the pick-up process through the application.

7. A school smart fast connection and flash transmission system, used to implement a school smart fast connection and flash transmission method as described in any one of claims 1 to 6, characterized in that: It includes information registration and reminder module, intelligent scheduling module, dynamic optimization strategy module, student safety confirmation module and pick-up and drop-off feedback module.

8. The school intelligent fast connection and delivery system according to claim 7 is characterized by: The information registration and reminder module realizes full-process digital management through the collaboration of the management terminal, parent terminal, teacher terminal and tablet terminal; The intelligent scheduling module limits the search space, demarcates one-way dedicated channels, sets grade diversion gates, dynamically distributes the green light time at intersections according to pheromone concentration, calculates the state transition probability, recommends the optimal and dispersed routes, performs global pheromone updates, and guides the adaptive and balanced distribution of traffic flow; The dynamic optimization strategy module designs a dynamic fitness function, calculates adaptive diversity parameters based on the iteration phase, explores the solution space in the early stage, and develops it in detail in the later stage, uses similarity clustering to guide vehicles in the same area to stop in a centralized manner, and sets slow-moving channels and dynamic insertion strategies; The student safety confirmation module verifies the student identity and pick-up address through GPS positioning technology and generates a pick-up record; In the pick-up and drop-off feedback module, after the pick-up and drop-off task is completed, the system records the task details and the parents evaluate it through the application.

Images