Light and small unmanned aerial vehicle urban logistics route structure design and optimization method

Abstract

The invention discloses a light and small unmanned aerial vehicle urban logistics route structure design and optimization method. The method comprises the following steps: designing an urban logistics route concept; based on an urban logistics route concept, constructing an initial route configuration; constructing a parameterized model representing a route structure and a link mode between route segments; according to a pre-constructed feasible rule base, screening a change range of variable structure parameters in each initial airline configuration parameterized model to form a feasible search space; constructing a route structure evaluation model based on the parameterized model; and based on the feasible search space, solving the route structure evaluation model, determining an optimal variable structure parameter, and obtaining an optimized route structure. According to the method, the problem of connection between the approach and departure routes and the air route is solved, parameterized representation of the routes is constructed, a universal route structure evaluation and optimization method is constructed, high-density approach safety of the unmanned aerial vehicle is realized, and the total delay time and the total delay cost are reduced.

Description

Technical Field

[0001] The present invention belongs to the technical field of unmanned aerial vehicle (UAV) route structure design and optimization, and specifically relates to a light and small UAV urban logistics route structure design and optimization method. Background Art

[0002] Lightweight and small multi-rotor logistics drones take off and land near tall buildings and residential buildings. They are not only subject to restrictions such as noise and public privacy, but are also easily affected by complex wind fields between buildings and the random influence of unstable communication and navigation signals. In this situation, intensive takeoffs and landings undoubtedly pose a major safety risk. In order to reduce the risks brought to the city by the intensive takeoffs and landings of drones performing logistics and transportation tasks in urban environments, drone logistics and distribution service operators often set up fixed routes in low-altitude airspace and control drones to fly along certain routes to reduce the risk of collision. To support the safe and efficient operation of drones, route structure design and optimization is one of the key technologies.

[0003] In practice, different route structure designs will directly affect the flight efficiency of UAV operations. Designing a route structure with the goal of safety, efficiency, and low energy consumption requires not only considering the design of each part of the route, but also the efficient connection between the flight segments. The existing route structure design focuses more on the macro planning of the route network, the design of the approach route, and the design of the intersection of the air routes. Not only does it not consider the departure route, it also ignores the connection between the approach and departure routes and the air routes. Summary of the invention

[0004] Purpose: In view of at least one of the above technical problems, the present application provides a method for designing and optimizing the structure of light and small UAV urban logistics routes.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides a method for designing and optimizing a light and small UAV urban logistics route structure, comprising:

[0007] Step (1): designing a concept of an urban logistics route based on the functional differences of each segment of the route; wherein the urban logistics concept is a round-trip route structure, and the round-trip route includes an outbound route and a return route;

[0008] Step (2): Based on the concept of the urban logistics route, according to the design principles of the traffic flow direction, cruising altitude, and segment connection of the flight segment, construct the initial route configurations of four different round-trip route structures;

[0009] Step (3): Based on the existence of each flight segment, the shape of the flight segment, the height of the highest point of the flight segment, and the number of UAVs that can be accommodated in the flight segment, a parameterized model representing the route structure and the connection method between the flight segments is constructed, and the variable structural parameters in the parameterized model are determined;

[0010] Step (4): According to the pre-constructed feasible rule base, the change range of the variable structural parameters in each initial route configuration parameterization model is determined to form a feasible search space;

[0011] Step (5): Based on the parameterized model, the route structure evaluation model is constructed with minimizing the average delay as the objective function and the conflict-free operation of the UAV in the flight segment as the constraint condition;

[0012] Step (6): Based on the feasible search space, the route structure evaluation model is used to perform evaluation and optimization, determine the optimal variable structure parameters, and obtain the optimized drone urban logistics route structure.

[0013] In a second aspect, the present application provides a light and small UAV urban logistics route structure design and optimization device, including a processor and a storage medium;

[0014] The storage medium is used to store instructions;

[0015] The processor is configured to operate according to the instructions to execute the method according to the first aspect.

[0016] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the method described in the first aspect when executed by a processor.

[0017] In a fourth aspect, the present application provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the method of the first aspect when executing the computer program.

[0018] In a fifth aspect, the present application provides a computer program product, comprising a computer program, which implements the method described in the first aspect when executed by a processor.

[0019] Beneficial effects: The present invention provides a light UAV urban logistics route structure design and optimization method to solve the connection problem between approach, departure and air routes, construct a parametric representation of the route, and construct a general route structure evaluation and optimization method to achieve high-density UAV approach safety and reduce total delay time and total delay cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a schematic diagram of a design and optimization process for a light and small UAV urban logistics route according to an embodiment of the present invention;

[0021] Figure 2 This is a schematic diagram of the conceptual design of the urban logistics route according to an embodiment of the present invention;

[0022] Figure 3 Schematic diagram of four initial route configurations according to an embodiment of the present invention;

[0023] Figure 4 This is a schematic diagram comparing average delays of four initial route configurations according to an embodiment of the present invention;

[0024] Figure 5 Schematic diagram of comparison of average delay optimization results of different initial route configurations according to an embodiment of the present invention;

[0025] Figure 6 This is a schematic diagram comparing the average delay of the route configuration before and after optimization according to the embodiment of the present invention;

[0026] Figure 7 Schematic diagram showing the comparison of the route structure before and after optimization according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] The present application is further described below in conjunction with the accompanying drawings and embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present application, and cannot be used to limit the protection scope of the present application.

[0028] In the description of this application, "several" means more than one, "more" means more than two, "greater than", "less than", "exceed", etc. are understood to exclude the number itself, and "above", "below", "within", etc. are understood to include the number itself. If there is a description of "first" or "second", it is only used for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0029] In the description of the present application, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples" or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0030] The term "and / or" is only a description of the association relationship between related objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " generally indicates that the related objects are in an "or" relationship.

[0031] Example 1: This example provides a method for designing and optimizing a light and small UAV urban logistics route. Figure 1 As shown, including:

[0032] Step (1): Design the concept of urban logistics routes based on the functional differences of each segment in the route;

[0033] The urban logistics concept is a round-trip route structure, which includes an outbound route and a return route. Figure 2 This is a schematic diagram of the concept design of the urban logistics route in the embodiment of the present invention. Figure 2 The outbound route structure includes a vertical takeoff segment r t , Departure holding segment wd , departure segment d , Cruise segment c , Arrival segment a , Arrival holding segment wa , vertical landing segment l ; The return route structure is the same, and the return route structure segment r' includes the vertical takeoff segment r t ', departure waiting segment r wd ', departure segment d ', Cruise segment r c ', Arrival segment r a ', Arrival waiting segment r wa ', vertical landing segment r l '.

[0034] See also Figure 2 The flight segments in the round-trip route structure should be directed line segments with a starting point and an end point. The outbound route connection method includes: vertical takeoff segment r t From the take-off and landing point p t Align to the take-off and landing point lt , departure holding segment r wd For p lt To the departure waiting point wd , departure segment r d For p lt or p wd To the exit point p d , cruise segment r c For p d To the entry point a , approach segment r a For p a Go to the entry waiting point wa Or landing take-off point is aligned with the landing point ll , Arrival holding segment r wa From the entry waiting point p wa Align to the landing point ll , flight segment r l For p ll To the landing point p lThe return route connection includes a vertical take-off segment. t ' is the take-off and landing point p t 'Align to the take-off and landing point lt ', departure waiting segment r wd 'For from p lt 'Go to the departure waiting point wd ', departure segment r d 'For from p lt 'or p wd 'To the exit point p d ', cruise segment r c 'For from p d 'To the entry point p a ', approach segment r a 'For from p a 'Go to the entry waiting point wa 'Or landing take-off point is aligned with the landing point p ll ', approach segment r wa 'For from p wa 'To p ll ', vertical landing segment r l 'For from p ll 'To the landing point p l '.

[0035] In some embodiments, in the outbound route structure, the vertical takeoff segment r t The function is to quickly climb from the ground; the departure waiting segment r wd The function is to wait before the departing drone enters the departure segment; the departure segment r d The function is to increase altitude and enter the air route; the cruising segment r c The function is to fly between take-off and landing points; the approach segment r a The function is to descend the altitude and fly above the landing point; the approach waiting segment r wa The function is to wait before the approaching drone lands; the vertical landing segment r l The function is to land the drone at the take-off and landing point; the functions of each section in the return route are the same.

[0036] Step (2): Based on the concept of the urban logistics route, according to the design principles of the traffic flow direction, cruising altitude, and segment connection of the flight segment, construct the initial route configurations of four different round-trip route structures;

[0037] In this embodiment, the idea of ​​designing the initial route configuration is to combine the arrival and departure route configurations with the air route configurations and remove several types of situations that are impossible to occur. The design method is as follows.

[0038] Design the arrival and departure route configuration: outbound departure segment r d and return arrival segmenta 'Same route, same altitude, r d and r a 'Different routes, same altitude, r d and r a 'Different routes with the same cruising altitude, r d and r a 'Different cruising altitudes for different routes;

[0039] Design air route configuration: outbound cruise segment c and return cruise segment c 'The round trip route coincides with the cruising altitude, r c and r c 'Round trips at the same cruising altitude do not overlap, r c and r c 'Round trips at different cruising altitudes do not overlap;

[0040] The designed arrival and departure route configurations and air route configurations are combined with each other to remove the impossible situations (such as the combination of cruising altitude and different arrival and departure altitudes, etc.), and the initial route configurations of four different round-trip route structures are obtained: Configuration 1, Configuration 2, Configuration 3, and Configuration 4. Figure 3 .

[0041] Step (3): Based on the existence of each segment, the segment shape, the highest point height of the segment, and the number of UAVs that can be accommodated by the segment, a parameterized model representing the route structure and the connection mode between segments is constructed, and variable structural parameters in the parameterized model are determined; the parameterized model includes a parameterized model of the outbound route Route d and the parameterized model Route for the return route a ;

[0042] Define a parametric model to represent the route structure and the connection between flight segments. The route structure is represented in matrix form. The parametric model of the outbound route is Route d The expression is as follows:

[0043]

[0044] Among them, C d is the outbound route control matrix, S d is the outbound route state matrix, and C in the control matrix t , C wd , C d , C c , C a , C wa , C l Respectively represent the flight segment r t 、r wd 、r d 、rc 、r a 、r wa 、r l Does it exist, S in the state matrix t , S wd , S d , S c , S a , S wa , S l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l Horizontal, inclined, vertical shapes, H t , H wd , H d , H c , H a , H wa , H l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l Height of the highest point, N t 、N wd 、N d 、N c 、N a 、N wa 、N l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l The number of drones that can be operated;

[0045] Parameterized model of return route Route a The expression is as follows:

[0046]

[0047] Among them, C a is the return route control matrix, S a is the state matrix, C in the control matrix t '、C wd '、C d '、C c '、C a '、Cwa '、C l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'Does it exist, S in the state matrix t '、S wd '、S d '、S c '、S a '、S wa '、S l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'Horizontal, inclined, vertical shape, H t '、H wd '、H d '、H c '、H a '、H wa '、H l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'The highest point height, N t '、N wd '、N d '、N c '、N a '、N wa '、N l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'The number of drones that can be operated.

[0048] In this embodiment, the idea of ​​setting variable structural parameters in the parameterized model is that only structural parameters that exist in the actual operation scenario can be changed. The design method is as follows.

[0049] In actual operation, the flight segment r d、r d '、r a 、r a There are three shapes: horizontal, inclined, and vertical. The parameters S corresponding to each segment d , S d '、S a , S a ' as a variable structured parameter;

[0050] In actual operation, some routes at the operation site have flight segments r wa , and check whether there is a corresponding parameter C for each waiting segment wd , C wd '、C wa , C wa ' as a variable structured parameter;

[0051] Therefore, the variable structural parameter is designed as S d , S' d , S a , S' a , C wd , C' wd , C wa , C' wa .

[0052] Step (4): According to the pre-constructed feasible rule base, the change range of the variable structural parameters in each initial route configuration parameterization model is determined to form a feasible search space;

[0053] Changing the variable structural parameter S in the parameterized model d , S' d , S a , S' a , C wd , C' wd , C wa , C' wa , determine whether the changed parameterized model satisfies the pre-built feasible rule base; the parameterized model that satisfies the pre-built feasible rule base is added to the feasible search space.

[0054] In this embodiment, the idea of ​​constructing a feasible rule base is to determine the conditions that the feasible variable structural parameters should satisfy by combining the variable structural parameters with each other. The design method is as follows.

[0055] Based on the status and existence of the flight segment above the take-off and landing points, the situations where the flight segment is not feasible are discussed in different situations:

[0056] Infeasible situation 1: Flight segment r d Level and segment a 'The variable structural parameter combination of multiple take-off and landing points on point due to tilt and the absence of waiting segments;

[0057] Unfeasible situation 2: Flight segment r d Vertical and segment a 'Vertical and without any variable structural parameter combination that causes the round-trip routes to overlap;

[0058] The final feasible rule base can be obtained by combining the variable structure parameters.

[0059] A feasible rule base is constructed. Under the route structure configuration with the same cruising altitude, its rules include shape constraints of the approach and departure segments. In order to ensure that the designed segment structure is consistent with the route concept, the shape change values ​​of the approach and departure segments should be restricted to achieve the approach and departure segments in the route structure connected at one point, as follows:

[0060] S d =1→S' a =1

[0061] S' a =1→S d =1

[0062] S d =2→S' a ≠1

[0063] S' a =2→S d ≠1

[0064] Furthermore, while limiting the shape change values ​​of the arrival and departure segments, the existence of the waiting segment should also be considered, as follows:

[0065] C wd +C' wa =0→(S d =3→S' a =2)

[0066] C wd +C' wa =0→(S' a =3→S d =2)

[0067] C wd +C' wa ≥1→(S d =3→S' a ≠1)

[0068] C wd +C' wa ≥1→(S' a =3→S d ≠1)

[0069] A feasible rule base is constructed. Under the route structure configurations at different cruising altitudes, the rules include shape constraints for the approach and departure segments. To ensure that the designed segment structure is consistent with the route concept, the shape change values ​​of the approach and departure segments should be restricted to achieve the approach and departure segments in the route structure connected at one point, as follows:

[0070] S' a =1→S d ≠1

[0071] S' a =2→S d ≠1

[0072] Furthermore, while limiting the shape change values ​​of the arrival and departure segments, the existence of the waiting segment should also be considered, as follows:

[0073] C wd +C' wa =0→S' a ≠3

[0074] C wd +C' wa ≥1→(S d =3→S' a ≠1)

[0075] According to the parameterized representation of the initial route configuration, whether the outbound route and the return route are at the same cruising altitude, the corresponding feasible rule base is selected.

[0076] In this embodiment, 4 of the variable structural parameters are the shape of the flight segment, and the parameter variation range is 3, and the other 4 are whether the flight segment exists, and the parameter variation range is 2. After permutation and combination, the total search space should be 1296 configuration schemes. After screening through the feasible rule base, there are 361 feasible configurations at the same cruising altitude, and 484 feasible configurations at different cruising altitudes. The feasible configurations together constitute the feasible search space.

[0077] Step (5): Based on the parameterized model, the route structure evaluation model is constructed with minimizing the average delay as the objective function and the conflict-free operation of the UAV in the flight segment as the constraint condition;

[0078] The objective function of the route structure evaluation model is to minimize the average delay, which is expressed as:

[0079]

[0080] Among them, U is the set of drones carrying the corresponding task; Delay i represents the delay of the i-th UAV; n represents the number of tasks; Delay 1 Indicates the takeoff delay of the drone at the takeoff and landing point; Delay2 Indicates the arrival delay of the drone at the landing point. For the i-th UAV from p t Time of departure, ETD i is the estimated take-off time of the i-th UAV; Indicates that the i-th UAV arrives at the landing point p l time; represents the flight time of the i-th UAV from the take-off point to the landing point without any delay;

[0081] The constraints of the route structure evaluation model include departure time constraints, same UAV operation constraints, landing and take-off point stop time constraints, conflict-free take-off and landing constraints above take-off and landing points, conflict-free take-off and landing constraints above landing and take-off points, different UAV operation constraints, and cruise segment capacity constraints;

[0082] Furthermore, a route structure evaluation model is constructed, whose constraints include departure time constraints, which should limit the take-off time of the UAV from the take-off and landing points to ensure that it is greater than the expected take-off time, as follows:

[0083]

[0084] in, For the i-th UAV from p t Time of departure, ETD i is the estimated take-off time of the i-th UAV, and U is the set of UAVs carrying the corresponding mission;

[0085] Construct a route structure evaluation model, whose constraints include the time interval constraints for the same drone to leave the starting point of adjacent segments in the outbound route. The time constraints for the drone to leave the adjacent segments should be imposed to ensure that the drone can leave each segment according to the planned time, as follows:

[0086]

[0087] in, is the time when the i-th UAV leaves the starting point of segment r, r+1 represents the next segment connected to segment r, and t r is the time required for the drone to fly from the starting point of segment r to the end point, and R is the set of segments in the outbound route;

[0088] Construct a route structure evaluation model, whose constraints include the time interval constraints for the same drone to leave the starting point of adjacent segments in the return route. The time constraints for the drone to leave the adjacent segments should be imposed to ensure that the drone can leave each segment according to the planned time, as follows:

[0089]

[0090] in, is the time when the i-th UAV leaves the starting point of segment r', r'+1 represents the next segment connected to segment r', t r' is the time required for the drone to fly from the starting point of segment r' to the end point, and R' is the set of segments in the return route;

[0091] Construct a route structure evaluation model, whose constraints include the time interval constraint of the drone staying at the landing point. The time the drone stays at the landing point should be constrained to ensure that the drone can complete the order delivery process, as follows:

[0092]

[0093] Among them, t T The minimum time interval for the drone to stay at the landing point;

[0094] The route structure evaluation model is constructed, and its constraints include the conflict-free take-off and landing constraints above the take-off and landing points. The take-off and landing time of the drone above the take-off and landing points should be constrained to ensure that the drone is within the flight segment r. t There will be no head-to-head conflict, as follows:

[0095]

[0096] in, is the maximum value of the time when drone i leaves from the starting point of segment r and the time when drone j leaves from the starting point of segment r', is the minimum value between the time when drone i leaves from the starting point of segment r and the time when drone j leaves from the starting point of segment r';

[0097] The route structure evaluation model is constructed, and its constraints include the take-off and landing conflict-free constraints above the landing and take-off points. The time constraints for landing and taking-off drones above the landing and take-off points should be imposed to ensure that the drones are within the flight segment r. l There will be no head-to-head conflict, as follows:

[0098]

[0099] Where M is a sufficiently large positive integer, λ i,j is a 0-1 variable, which is 1 when the departure time of UAV i from the take-off and landing point of the outbound route is less than or equal to that of UAV j, otherwise it is 0;

[0100] Construct a route structure evaluation model. Its constraints include the time interval constraints for different drones to leave the starting points of adjacent segments in the outbound route. The time constraints for different drones to pass through points should be imposed to ensure that drones at the same time will not conflict in the same segment, as follows:

[0101]

[0102] in, is the time when the jth UAV leaves from the starting point of segment r;

[0103] Construct a route structure evaluation model. Its constraints include the time interval constraints for different drones to leave the starting points of adjacent segments in the return route. The time constraints for different drones to pass through points should be imposed to ensure that drones at the same time will not conflict in the same segment, as follows:

[0104]

[0105] in, is the time when the jth UAV leaves from the starting point of segment r';

[0106] A route structure evaluation model is constructed, and its constraints include that the drone should meet the capacity constraints of the cruising segment in the outbound route, as follows:

[0107]

[0108] in, is the number of drones in flight segment r at time t;

[0109] The route structure evaluation model is constructed, and its constraints include that the UAV should meet the capacity constraints of the cruising segment in the return route, as follows:

[0110]

[0111] in, is the number of drones in the flight segment r' at time t;

[0112] In this embodiment, the idea of ​​constructing a route structure evaluation model is to construct an integer programming model that characterizes the conflict-free operation of the drone by constructing time constraints for the drone to pass through each waypoint and occupy a flight segment. This model is used for route structure evaluation, that is, under the same transportation task, the configuration with the smallest delay is optimal.

[0113] In this embodiment, the GUROBI solver is used to solve the global exact solution of the evaluation model. The final value of the optimization target in the evaluation model is not affected by the number of experiments and the algorithm performance, but is only related to the route structure. The solution result of the evaluation model can be used as an evaluation indicator of the route structure.

[0114] Step (6): Based on the feasible search space, the route structure evaluation model is used for optimization to determine the optimal variable structure parameters and obtain the optimized UAV urban logistics route structure.

[0115] In step (6): the route structure evaluation model is input into the solver for optimization and solution, all feasible search spaces are traversed, and the optimal variable structural parameters are determined from the feasible search space, so as to obtain the optimized route structure of each configuration.

[0116] In this embodiment, during the process of solving the problem using the GUROBI optimization solver, a heuristic branch and bound algorithm is used in the optimization solver to optimize and solve the route structure evaluation model. The convergence condition of the optimization is:

[0117] max|Delay g -Delay g-1 |≤E D

[0118] Among them, Delay g is the value of the optimization target of the route structure evaluation model in the iterative solution process, Delay g-1 is the value of the optimization target m of the route structure evaluation model in the previous iterative solution process, E D To solve for tolerance;

[0119] After the optimization requirements are met, the parameterized representation of the optimized route structure is returned, and the existence, shape, highest point height and capacity of each segment are output.

[0120] In order to verify the effectiveness of the light and small UAV urban logistics route structure design and optimization method provided by the embodiment of the present invention, the present invention selects the Xinghe Central Business District in Longgang, Shenzhen, Guangdong Province, and designs four initial route configurations. Since all the flight segments of configuration one overlap, parameterization cannot be used. The parameterization representation of the outbound route of configurations two to four is shown in Table 1. The parameterization representation of the return route is shown in Table 1. Figure 3 And parameterized representation content.

[0121] Table 1 Outbound routes with different configurations

[0122]

[0123] Table 1 shows the specific assignment of variables in the parametric representation of the UAV route. Variable C is a 0-1 variable. When it is 1, it means that the segment exists. The value range of variable S is an integer from 0 to 3, 1 means that the segment shape is horizontal, 2 means that the segment shape is inclined (the inclination angle is related to the connection needs of the segment), and 3 means that the segment shape is vertical. The value range of variable H is an integer from 0 to 2, 1 means that the highest point of the segment is below 70m, and 2 means that the highest point of the segment is below 90m. Variable N represents the maximum number of UAVs that the segment can accommodate at the same time. When the parameterized variable is 0, it means that the parameter does not exist.

[0124] In order to demonstrate the effect of the method for designing the route structure configuration provided by the embodiment of the present invention, the embodiment of the present invention uses uniform distribution to generate tasks within 30 minutes, generates random task sequences with task numbers ranging from 10 to 100, and each random task sequence is a task scenario. In each task scenario, the route structure evaluation model is used to evaluate the four initial route configurations, such as Figure 4 As shown. Taking the average delay as the evaluation index, the design configurations are ranked from best to worst: configuration 4, configuration 3, configuration 2, configuration 1. Taking the average delay of configuration 1 as the benchmark, when the number of tasks is 10, the percentage of decrease of configurations 2, 3, and 4 compared with configuration 1 is the largest, which are 88.9%, 89.2%, and 93.3% respectively; when the number of tasks is 100, the absolute value of the average delay compared with configuration 1 is the largest, which are: 12195.6s, 13274.6s, and 16301.0s respectively.

[0125] In order to demonstrate the effect of the route structure optimization method provided by the embodiment of the present invention, the average delay performance of the route structure optimization before and after the optimization at the same cruising altitude and at different cruising altitudes is compared. Figure 5 As shown. Figure 5 As shown in (a), after searching the feasible search space at the same cruising altitude, with the minimum average delay as the goal, the optimal configuration optimization solution appears at the 198th place in the feasible search space, configuration two appears at the 1st place, and configuration three appears at the 93rd place. When the number of tasks is 60, the average delay of the optimized configurations of configurations two and three decreased by -12.5% ​​compared with configuration two, and decreased by -13.8% compared with configuration three. After searching the feasible search space at different cruising altitudes, with the minimum average delay as the goal, the optimal configuration optimization solution appears at the 203rd place in the feasible search space, and configuration four appears at the 379th place, as shown in Figure 5 When the number of tasks is 60, the average delay of the optimized configuration is -3.2% lower than that of the configuration 4.

[0126] In order to demonstrate the optimization results of the route structure optimization method provided by the embodiment of the present invention under different task numbers, the average delay performance of the route structure optimization before and after the optimization under different task numbers at the same cruising altitude and at different cruising altitudes is compared. Figure 6 As shown. Figure 6 As shown in (a), compared with configuration 2, the maximum difference in average delay reduction of the optimized configuration is 15.6%; compared with configuration 3, the maximum difference in average delay reduction of the optimized configuration is 26.3%. The optimization of configurations 2 and 3 has achieved relatively obvious results under different task numbers. As the number of tasks increases, the optimization effect becomes more obvious. Figure 6 As shown in (b), since configuration 4 is in a better position in the feasible search space before optimization, the optimization performance of the average delay is not obvious, but the average delay performance is slightly improved.

[0127] The optimization results for the initial route configuration in the present invention are as follows: Figure 7 As shown. Figure 7 As shown in (a), the optimized configuration adds three waiting segments, especially the segment r in the outbound route. wd and flight segment r wa , which makes the drones queue up in the air as much as possible to reduce the waiting time of the drones. d ' and flight segment r a 'The tilted shape of the drone will help the drone maintain a safe distance while ensuring efficiency, as the drone runs at the slowest speed in the tilted section. Figure 7 As shown in (b), the optimization results of configuration 4 are almost the same as those of configurations 2 and 3.

[0128] In summary, the light and small UAV urban logistics route structure design and optimization method proposed in the present invention: a more complete definition of urban logistics UAV routes is proposed, a parametric representation of the definition is constructed, and four round-trip route configurations are sorted out. A route structure evaluation and optimization method is constructed. This method takes the minimum average delay as the goal and evaluates the performance parameters of various configurations under different numbers of tasks. Combined with the route parameterization model, the variable structural parameters are adjusted to obtain the optimal route configuration. Based on the above method, and through example analysis, it is shown that a reasonable route structure configuration design can significantly reduce the average delay change. The configuration currently widely used in practice is only suitable for small-batch transportation. When the transportation volume increases, it will bring about a linear increase in delays. A more complex configuration must be adopted to significantly reduce the level of delays. In addition, this study also shows that the various approach route design schemes proposed in the previous study can be completely optimized by a more complete route structure.

[0129] Embodiment 2: Based on Embodiment 1, this embodiment provides a light and small UAV urban logistics route structure design and optimization device, including a processor and a storage medium;

[0130] The storage medium is used to store instructions;

[0131] The processor is used to operate according to the instruction to execute the method according to embodiment 1.

[0132] Embodiment 3: Based on Embodiment 1, this embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method described in Embodiment 1 is implemented.

[0133] Embodiment 4: Based on Embodiment 1, this embodiment provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the method described in Embodiment 1 when executing the computer program.

[0134] Embodiment 5: Based on Embodiment 1, this embodiment provides a computer program product, including a computer program, which implements the method described in Embodiment 1 when executed by a processor.

[0135] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0136] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram and the combination of the processes and / or blocks in the flowchart and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0137] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0138] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0139] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A light and small UAV urban logistics route structure design and optimization method, characterized in that: The following steps are involved: Step (1): designing a concept of an urban logistics route based on the functional differences of each segment of the route; wherein the urban logistics concept is a round-trip route structure, and the round-trip route includes an outbound route and a return route; Step (2): Based on the concept of the urban logistics route, according to the design principles of the traffic flow direction, cruising altitude, and segment connection of the flight segment, construct the initial route configurations of four different round-trip route structures; Step (3): Based on the existence of each flight segment, the shape of the flight segment, the height of the highest point of the flight segment, and the number of UAVs that can be accommodated in the flight segment, a parameterized model representing the route structure and the connection method between the flight segments is constructed, and the variable structural parameters in the parameterized model are determined; Step (4): According to the pre-constructed feasible rule base, the change range of the variable structural parameters in each initial route configuration parameterization model is determined to form a feasible search space; Step (5): Based on the parameterized model, the route structure evaluation model is constructed with minimizing the average delay as the objective function and the conflict-free operation of the UAV in the flight segment as the constraint condition; Step (6): Based on the feasible search space, the route structure evaluation model is used to perform evaluation and optimization, determine the optimal variable structure parameters, and obtain the optimized drone urban logistics route structure.

2. The method for designing and optimizing the structure of light and small UAV urban logistics routes according to claim 1 is characterized in that: The step (1) designs the concept of the urban logistics route according to the functional differences of each segment in the route, including: Step (101): Perform a functional analysis on the round-trip route and design each segment in the urban logistics route structure. The segment r of the outbound route structure includes the vertical take-off segment r t , Departure holding segment wd , departure segment d , Cruise segment c , Arrival segment a , Arrival holding segment wa , vertical landing segment l , the return route structure segment r' includes the vertical take-off segment r t ', departure waiting segment r wd ', departure segment d ', Cruise segment r c ', Arrival segment r a ', Arrival waiting segment r wa ', vertical landing segment r l '; Step (102): Design the connection method of each flight segment. The flight segment in the route structure is a directed line segment with a start point and an end point. Outbound route connection methods include: vertical take-off segment r t From the take-off and landing point p t Align to the take-off and landing point lt , departure holding segment r wd For p lt To the departure waiting point wd , departure segment r d For p lt or p wd To the exit point p d , cruise segment r c For p d To the entry point a , approach segment r a For p a Go to the entry waiting point wa Or landing take-off point is aligned with the landing point ll , approach segment r wa For p wa to p ll , vertical landing segment r l For p ll To the landing point p l ; Return route connection includes vertical take-off segment t ' is the take-off and landing point p t 'Align to the take-off and landing point lt ', departure waiting segment r wd 'For from p lt 'Go to the departure waiting point wd ', departure segment r d 'For from p lt 'or p wd 'To the exit point p d ', cruise segment r c 'For from p d 'To the entry point p a ', approach segment r a 'For from p a 'Go to the entry waiting point wa 'Or landing take-off point is aligned with the landing point p ll ', approach segment r wa 'For from p wa 'To p ll ', vertical landing segment r l 'For from p ll 'To the landing point p l '.

3. The method for designing and optimizing the structure of urban logistics routes for light and small UAVs according to claim 2 is characterized in that: In step (2), four initial route configurations with different round-trip route structures are constructed, including: Step (201): Design four types of arrival and departure route configurations: outbound departure segment r d and return arrival segment a 'Same route, same altitude, r d and r a 'Different routes, same altitude, r d and r a 'Different routes with the same cruising altitude, r d and r a 'Different cruising altitudes for different routes; Step (202): Design three air route configurations: outbound cruise segment r c and return cruise segment c 'The round trip route coincides with the cruising altitude, r c and r c 'Round trips at the same cruising altitude do not overlap, r c and r c 'Round trips at different cruising altitudes do not overlap; Step (203): The designed arrival and departure route configurations and air route configurations are combined with each other to remove impossible situations, thereby obtaining initial route configurations of four different round-trip route structures, namely, configuration one, configuration two, configuration three, and configuration four.

4. The method for designing and optimizing the structure of light and small UAV urban logistics routes according to claim 2 is characterized in that: The step (3) constructs a parameterized model representing the route structure and the connection mode between flight segments, including: Step (301): define a parameterized model representing the route structure and the connection mode between flight segments, and represent the route structure in matrix form. The parameterized model includes a parameterized model of the outbound route Route d and the parameterized model Route for the return route a ; Parameterized model of outbound route Route d The expression is as follows: Among them, C d is the outbound route control matrix, S d is the outbound route state matrix, and C in the control matrix t , C wd , C d , C c , C a , C wa , C l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l Does it exist, S in the state matrix t , S wd , S d , S c , S a , S wa , S l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l Horizontal, inclined, vertical shapes, H t , H wd , H d , H c , H a , H wa , H l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l Height of the highest point, N t 、N wd 、N d 、N c 、N a 、N wa 、N l Respectively represent the flight segment r t 、r wd 、r d 、r c 、r a 、r wa 、r l The number of drones that can be operated; Parameterized model of return route Route a The expression is as follows: Among them, C a is the return route control matrix, S a is the state matrix, C in the control matrix t '、C wd '、C d '、C c '、C a '、C wa '、C l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'Does it exist, S in the state matrix t '、S wd '、S d '、S c '、S a '、S wa '、S l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'Horizontal, inclined, vertical shape, H t '、H wd '、H d '、H c '、H a '、H wa '、H l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'The highest point height, N t '、N wd '、N d '、N c '、N a '、N wa '、N l 'represents flight segment r t '、r wd '、r d '、r c '、r a '、r wa '、r l 'The number of drones that can be operated; Step (302): Referring to the actual operation scenario, the outbound departure segment r d , return departure segment d ', outbound arrival segment r a , Return arrival segment a There are three shapes: horizontal, inclined and vertical. Some routes at the operation site have approach waiting segments. wa , the variable structural parameter is designed as S d , S d '、S a , S a '、C wd , C wd '、C wa , C wa '.

5. The method for designing and optimizing the structure of urban logistics routes for light and small UAVs according to claim 4 is characterized in that: In step (4), the feasible rule base includes a feasible rule base under the route structure configuration of the same cruising altitude and a feasible rule base under the route structure configuration of different cruising altitudes; The feasible rule base under the route structure configuration at the same cruising altitude is expressed as: S d =1→S' a =1 S' a =1→S d =1 S d =2→S' a ≠1 S' a =2→S d ≠1 C wd +C' wa =0→(S d =3→S' a =2) C wd +C' wa =0→(S' a =3→S d =2) C wd +C' wa ≥1→(S d =3→S' a ≠1) C wd +C' wa ≥1→(S' a =3→S d ≠1) "→" indicates that the proposition on the left can lead to the proposition on the right; The feasible rule base under the route structure configuration at different cruising altitudes is expressed as: S' a =1→S d ≠1 S' a =2→S d ≠1 C wd +C' wa =0→S' a ≠3 C wd +C' wa ≥1→(S d =3→S' a ≠1)。 6. The method for designing and optimizing the structure of a light and small UAV urban logistics route according to claim 1 is characterized in that: In step (4), the feasible rule base includes a feasible rule base under the route structure configuration with the same cruising altitude and a feasible rule base under the route structure configuration with different cruising altitudes. According to whether the outbound route and the return route are at the same cruising altitude in the parameterized representation of the initial route configuration, the corresponding feasible rule base is selected to form a feasible search space by satisfying all changed parameterized models of the feasible rule base.

7. The method for designing and optimizing the structure of a light and small UAV urban logistics route according to claim 1 is characterized in that: In step (5), the objective function of the route structure evaluation model is: Among them, U is the set of drones carrying the corresponding task; Delay i represents the delay of the i-th drone; n represents the number of missions; Delay1 represents the take-off delay of the drone at the take-off and landing point; Delay2 represents the arrival delay of the drone at the landing and landing point, The i-th UAV takes off from the take-off and landing point p t Time of departure; ETD i is the estimated take-off time of the i-th UAV; Indicates that the i-th UAV arrives at the landing point p l time; It represents the flight time of the i-th UAV from the take-off point to the landing point without any delay.

8. The method for designing and optimizing the structure of a light and small UAV urban logistics route according to claim 7 is characterized in that: The constraints of the route structure evaluation model include: Departure time constraints limit the takeoff time of the drone from the takeoff and landing point to ensure that it is greater than the estimated takeoff time, as follows: in, The i-th UAV takes off from the take-off and landing point p t Time of departure, ETD i is the estimated take-off time of the i-th UAV, and U is the set of UAVs carrying the corresponding mission; The time interval constraint for the same drone to leave the starting point of adjacent segments in the outbound route should be constrained to ensure that the drone can leave each segment according to the planned time, as follows: in, is the time when the i-th UAV leaves the starting point of segment r, r+1 represents the next segment connected to segment r, and t r is the time required for the drone to fly from the starting point of segment r to the end point, and R is the set of segments in the outbound route; The same drone leaves the starting point of the adjacent flight segment during the return flight. The time interval constraint should be set to ensure that the drone can leave each flight segment according to the planned time, as follows: in, is the time when the i-th UAV leaves the starting point of segment r', r'+1 represents the next segment connected to segment r', t r' is the time required for the drone to fly from the starting point of segment r' to the end point, and R' is the set of segments in the return route; The time interval constraint for the drone to stay at the landing point should be constrained to ensure that the drone can complete the order delivery process, as follows: Among them, t T The minimum time interval for the drone to stay at the landing point; The take-off and landing time of the drone above the take-off and landing points are restricted to ensure that the drone is within the flight segment r. t There will be no head-to-head conflict, as follows: in, is the maximum value of the time when drone i leaves from the starting point of segment r and the time when drone j leaves from the starting point of segment r', is the minimum value between the time when drone i leaves from the starting point of segment r and the time when drone j leaves from the starting point of segment r'; There is no conflict constraint on take-off and landing above the landing point. The time of landing and taking-off of the UAV above the landing point should be constrained to ensure that the UAV is within the flight segment r. l There will be no head-to-head conflict, as follows: Where M is a sufficiently large positive integer, λ i,j is a 0-1 variable, which is 1 when the departure time of UAV i from the take-off and landing point of the outbound route is less than or equal to that of UAV j, otherwise it is 0; The time interval constraints for different drones to leave the starting points of adjacent segments in the outbound route should be constrained to ensure that drones at the same time will not conflict in the same segment, as follows: in, is the time when the jth UAV leaves from the starting point of segment r; The time interval constraints for different drones to leave the starting points of adjacent segments on the return route should be constrained to ensure that drones at the same time will not conflict in the same segment, as follows: in, is the time when the jth UAV leaves from the starting point of segment r'; The drone should meet the capacity constraints of the cruise segment in the outbound route: in, is the number of drones in the flight segment r at time t; The drone should meet the capacity constraints of the cruise segment in the return route, as follows: in, is the number of drones in the flight segment r' at time t.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 8 is implemented.

10. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 8 is implemented.

Images