47 results about "Urban logistics" patented technology

The invention relates to the technical field of logistics distribution, and discloses a big data analysis method and system based on traffic transportation logistics, and the method comprises the steps: constructing a space-time diagram convolution network model, and predicting the traffic congestion propagation trend of an urban region; based on the congestion propagation trend, the order density and the distribution resource state, executing a space-time dynamic partitioning algorithm, and dividing the urban distribution region into a plurality of dynamic micro-regions; constructing a double-layer intelligent decision-making system, and generating a logistics fleet separation and combination decision and path planning; heterogeneous distribution resource dynamic marshalling is executed, and different types of distribution tools are combined into a miniature formation; using a multi-agent reinforcement learning algorithm to optimize the cooperation process in the micro formation; according to the invention, through fusion of congestion propagation prediction, dynamic micro-area division, double-layer intelligent decision and heterogeneous resource collaboration, key problems of traffic congestion, resource scheduling and'last kilometer 'distribution in urban logistics distribution are effectively solved.

The invention discloses an unmanned aerial vehicle take-off and landing site selection method for urban end logistics, and relates to the technical field of facility site selection, and the method comprises the following steps: S1, obtaining a building contour of a region to be subjected to site selection, and constructing a customer buffer region according to the building contour; s2, based on the customer buffer area, performing noise analysis and safety analysis on the unmanned aerial vehicle, and constructing an overall restricted area; and S3, based on the overall restricted area, constructing a target function taking the lowest cost as an optimization target, a target function taking the highest satisfaction as an optimization target and a plurality of constraint conditions, and obtaining a site selection layout result. According to the method, the applicability of the grid map method in the complex urban environment is verified, and a new thought is provided for the layout of the urban logistics unmanned aerial vehicle take-off and landing points.

The invention relates to the technical field of logistics collaborative optimization, in particular to an urban logistics distribution range collaborative optimization method and system, and the method comprises the following steps: obtaining a path network node and order coordinate time sequence, constructing a path mapping number, extracting a direction vector and an included angle difference value, and recognizing a path sudden change node and a density change node. Dividing boundaries, calculating density ratio differences, screening unbalanced sections, extracting direction and distance abrupt change nodes, reconstructing a path structure and outputting a boundary graph. According to the method, the corresponding relation between the order and the path node is enhanced by constructing the path mapping number sequence, the adaptive capacity of the boundary to the path trend is improved, the density ratio analysis is combined with the spatial distribution difference to identify the non-uniform region, the responsiveness of the boundary to the order aggregation situation is enhanced, and the boundary node is jointly judged through the included angle and the centroid distance. And target judgment and structural stability control of boundary adjustment are realized, connection coherence is kept in path structure reconstruction, and a boundary path shape with dynamic adaptation capability is output.

Aiming at the problem of time-dependent multi-target green vehicle path optimization, the invention designs a space-time attenuation factor-driven urban logistics low-carbon robust optimization method, takes the total vehicle distribution time and carbon emission as optimization targets, and adopts double-layer ant colony pheromones to guide ant colony search, so that the optimal path optimization is realized. The adaptive capacity of ants in a high-disturbance uncertain environment is improved, the convergence of solutions is enhanced, more solution sets balancing robustness and optimality are excavated through solution robustness evaluation and a feedback mechanism thereof, the diversity of optimal solutions is improved, an optimal vehicle path robust optimization scheme is obtained, the carbon emission of urban road network distribution is reduced, and the urban road network distribution efficiency is improved. And the distribution efficiency of logistics is improved.

The invention discloses a multi-access-considered vehicle-unmanned aerial vehicle distribution path optimization method, relates to the technical field of vehicle and unmanned aerial vehicle collaborative distribution optimization, and aims to solve a path planning problem caused by complex constraints and multi-target optimization in urban logistics distribution. According to the method, firstly, multiple constraint conditions of vehicle-unmanned aerial vehicle cooperative distribution are analyzed, energy consumption cost and carbon emission factors are fused into a target function, an integer programming model with the minimum time and transportation cost as double targets is constructed, and carbon emission cost is considered in the transportation cost; secondly, solving a vehicle path and an initial solution by adopting an ant colony algorithm; and finally, a large-field search algorithm is used to solve the problem of vehicle-machine cooperation path optimization. According to the method, the vehicle and unmanned aerial vehicle cooperative distribution logistics efficiency is effectively improved, the total cost is reduced, and powerful support is provided for development of green logistics.

The invention belongs to the technical field of urban logistics and resource management, and provides a logistics resource scheduling method based on rule guidance and hierarchical greedy, which comprises the following steps: S1, customer demand structured analysis; s2, carrying out multi-dimensional logistics resource attribute modeling; s3, realizing resource filtering through rule guidance; s4, defining a combined path template; s5, obtaining an optimal solution through a hierarchical greedy resource matching algorithm for resource scheduling; comprising the following specific steps: S5.1, carrying out resource level dependence modeling; s5.2, setting a comprehensive matching degree algorithm and a matching priority rule; and S5.3, optimizing a resource combination path based on a hierarchical sequence and a greedy strategy. The method can adapt to different customer requirements to realize the reasonability of resource combination, and can also guarantee better resource matching efficiency.

The invention discloses an urban low-altitude multi-unmanned aerial vehicle autonomous route planning system and method, and belongs to the technical field of low-altitude airspace intelligent route planning. Comprising a gridding airspace construction module for constructing a digital urban low-altitude airspace model, an air route planning module for generating respective initial air routes for a plurality of unmanned aerial vehicles on the basis of the gridding airspace model, and a conflict detection and resolution module for ensuring that all finally output air routes are globally conflict-free, the invention further discloses an urban low-altitude multi-unmanned-aerial-vehicle autonomous route planning method based on the system. Through airspace grid division, an improved three-dimensional jump point search algorithm and a conflict resolution mechanism based on conflict search, efficient generation and global conflict-free collaboration of an unmanned aerial vehicle route are realized, and the method is suitable for multiple scenes such as urban logistics distribution, routing inspection and emergency response.

The invention discloses an urban logistics unmanned aerial vehicle take-off and landing point layout optimization method and system, and belongs to the technical field of path planning, and the method comprises the steps: taking all existing express cabinets in an urban region as a candidate take-off and landing point set, and obtaining the express cabinet transformation cost of each candidate take-off and landing point; obtaining the distribution cost from each candidate take-off and landing point to the demand point; determining customer coverage of all existing express cabinets in the urban area; obtaining all paths from each candidate take-off and landing point to the demand point without passing through the no-fly zone, and determining a plurality of take-off and landing point layout schemes corresponding to the selected take-off and landing points and the delivery paths based on all the paths as to-be-optimized individuals; a multi-objective optimization model is constructed by taking minimization of the sum of the transformation cost and the distribution cost of the express cabinet and maximization of the customer coverage degree as objectives, optimization is carried out on individuals to be optimized, and the optimal take-off and landing point layout and the planning result of the demand point range of the service of the take-off and landing point layout are determined. According to the method, reasonable and efficient operation of urban unmanned aerial vehicle logistics can be realized.

The invention discloses a vehicle and unmanned aerial vehicle cooperative distribution path planning method based on a temporary waiting mode, and the method comprises the steps: carrying out the preprocessing of a customer set, carrying out the clustering of the customer set served by a vehicle-mounted unmanned aerial vehicle based on the capacity of a truck, obtaining a clustering center and affiliated to-be-served customers, and obtaining an initial network; modifying the initial network, constructing a spatial expansion network, splitting each clustering center into an unmanned aerial vehicle virtual outflow node and a virtual inflow node, and introducing a corresponding virtual arc; establishing a mixed integer nonlinear programming model; performing objective function and soft time window constraint linearization processing on the mixed integer nonlinear programming model, and establishing an arc-based mixed integer linear programming model; and solving to obtain an optimal distribution scheme. According to the invention, complex constraints of multi-vehicle multi-unmanned aerial vehicle cooperative distribution can be systematically considered, distribution cost minimization and time window constraint satisfaction are realized, and a scientific and efficient scheduling planning scheme is provided for urban logistics and intelligent distribution.

The invention discloses a graded unmanned aerial vehicle take-off and landing site selection method for urban low-altitude logistics demands, relates to infrastructure site selection, and aims to improve the distribution efficiency of urban logistics unmanned aerial vehicles and promote low-altitude economic development. Firstly, urban low-altitude logistics demands are evaluated, and key factors influencing the low-altitude logistics demands are captured; secondly, determining unmanned aerial vehicle take-off and landing point candidate points by applying a multi-stage facility polygon intersection point set method; thirdly, establishing a multi-target grading unmanned aerial vehicle take-off and landing point maximum coverage site selection model by maximizing the demand coverage rate, minimizing the construction cost and the demand repeated coverage rate; and finally, a QGPS-NSGA-III algorithm with improved design is adopted to solve the site selection model. According to the method, key factors influencing site selection can be accurately identified, multiple optimization targets are met to the maximum extent, the rationality and feasibility of unmanned aerial vehicle take-off and landing site selection are remarkably improved, and scientific decision support is provided for planning and implementation of an urban low-altitude logistics system.

The present invention belongs to the field of urban smart logistics technology and relates to an urban logistics distribution method that collaborates with buses and drones. The present invention is a new bus-drone collaborative distribution model suitable for non-peak traffic scenarios, and designs and constructs a two-layer decision-making framework. The upper-layer decision-making adopts the Dueling DQN algorithm that integrates a multi-head attention mechanism to reasonably match the package with the bus it should take. After the package is transported to a specific drone station by bus according to the upper-layer decision-making result, the lower-layer decision-making uses a heuristic algorithm to plan the paths of each drone. The present invention forms an efficient network of "trunk transportation + flexible terminals" by coordinating the idle transportation capacity of buses during non-peak periods with drone terminal distribution, which not only activates bus resources but also improves distribution efficiency, reducing traffic and pollution problems caused by additional vehicles in traditional solutions.

The invention discloses an unmanned aerial vehicle and unmanned vehicle collaborative operation automatic goods changing base station, and belongs to the technical field of intelligent logistics, the unmanned aerial vehicle and unmanned vehicle collaborative operation automatic goods changing base station comprises an outer frame, a roadway goods changing device is arranged in the middle of the outer frame, base station storage systems are arranged on the two sides of the roadway goods changing device respectively, and the roadway goods changing device comprises a vertical transmission mechanism, a horizontal transmission mechanism and a goods fork; the base station warehousing system comprises an unmanned aerial vehicle / unmanned vehicle goods exchange area and a base station warehouse; through the cooperation mechanism of the unmanned vehicles and the unmanned aerial vehicles, full-automatic goods changing operation between the unmanned aerial vehicles can be achieved, and the operation efficiency of the logistics system is remarkably improved; the roadway goods changing device is matched with a self-developed low-cost horizontal bidirectional pallet fork, so that high efficiency and engineering feasibility are achieved; autonomous charging of unmanned transportation equipment in the parking process is achieved in the base station goods changing area, and continuity of energy supply is guaranteed; the whole set of base station structure supports transverse cascade expansion, the scale can be flexibly adjusted according to actual application scenes, and large-scale popularization and application in urban logistics networks are facilitated.

The invention relates to the technical field of logistics optimization management, and provides a multi-party collaborative optimization method and system for urban logistics distribution, and the method comprises the steps: obtaining the vehicle information of various types of vehicles in an urban logistics distribution fleet and the order information of a plurality of logistics orders; the method comprises the following steps: extracting a plurality of distribution centers, network points and distribution destinations of urban logistics distribution, constructing a distribution graph structure, and obtaining a shortest distribution path for each logistics order; obtaining a plurality of order categories and the total cargo weight of each order category; obtaining a preferred transportation factor; quantizing time transportation cost; constructing a transportation objective function in combination with the optimized transportation factors; and obtaining an optimal transport vehicle type for each section of road in the shortest distribution path of each order type, thereby carrying out logistics vehicle distribution on each logistics order, and realizing multi-party collaborative optimization distribution of urban logistics. The objective of the invention is to solve the problem that a logistics distribution fleet is complex in vehicle type and cannot accurately distribute tasks.

This invention discloses an autonomous route planning system and method for multiple unmanned aerial vehicles (UAVs) in urban low-altitude airspace, belonging to the field of intelligent route planning technology for low-altitude airspace. It includes a gridded airspace construction module for building a digital urban low-altitude airspace model, a route planning module for generating initial routes for multiple UAVs based on the gridded airspace model, and a conflict detection and resolution module to ensure global conflict-free operation of all output routes. It also includes an autonomous route planning method for multiple UAVs in urban low-altitude airspace based on the above system. Through airspace grid division, an improved three-dimensional jump point search algorithm, and a conflict resolution mechanism based on conflict search, it achieves efficient generation of UAV routes and globally conflict-free coordination, applicable to various scenarios such as urban logistics distribution, inspection, and emergency response.

This invention discloses a traffic flow allocation method for urban logistics drones, with the following specific steps: Calculating the safety impedance of each segment of the airway network based on the safety impact of the logistics drone's flight on ground personnel; calculating the efficiency impedance of each segment of the airway network considering the maximum capacity of the airways and flight energy consumption; calculating the comprehensive impedance of the urban low-altitude public airway network segments by integrating safety and efficiency impedances; establishing a dynamic traffic flow allocation model for the urban low-altitude airway network and determining the constraints for traffic flow allocation; and finally, using a staged allocation method to complete the traffic flow allocation for the public airway network. This invention employs the above-mentioned traffic flow allocation method for urban logistics drones, which can ensure efficient and safe flight of low-altitude aircraft and improve the operational efficiency of low-altitude airspace traffic flow.

The invention relates to the technical field of unmanned aerial vehicle navigation, and discloses an unmanned aerial vehicle logistics distribution method and device, computer equipment and a storage medium, and the method comprises the steps: building a feature attention fusion network based on a YOLOv8 model, enhancing the foggy day image feature extraction capability through a channel and pixel attention module, and improving the target recognition precision; resolving three-dimensional coordinates of a target and dynamically correcting a flight path by combining a frequency-modulated continuous wave radar and array antenna phase difference technology; the unmanned aerial vehicle is controlled to move through an ROS framework, hovers when approaching a target and performs secondary visual verification, and safe landing is ensured. According to the method, the improved model and the multi-sensor technology are fused, the detection reliability, the positioning precision and the distribution efficiency of the unmanned aerial vehicle in foggy days, rainy days and other scenes are remarkably improved through a low-cost scheme, and the method is suitable for urban logistics and remote region transportation.

This application provides an adaptive path planning method and system for urban distribution networks based on spatiotemporal correlation prediction, relating to the field of urban logistics and distribution technology. First, it obtains a set of constraint parameters for delivery tasks and a set of basic traffic parameters for the urban road network structure. Then, it constructs an initial solution space set for delivery paths based on these parameters. Next, it analyzes the travel time dependency relationship of road segment allocation sequences, generating travel time correlation parameters and travel time impact propagation parameters. Finally, it performs structural redundancy identification and dynamic response integration processing based on these parameters to generate a path decision set responding to real-time traffic events. This invention can perceive traffic conditions in real time and dynamically optimize delivery paths, improving delivery efficiency, accuracy, and reliability, reducing delivery costs, and enhancing customer satisfaction.

The utility model discloses a three-axis tilt rotor vertical take-off and landing aircraft, and belongs to the technical field of aviation. A side canard type triangular distribution structure is adopted, the flight gravity center is arranged in a connecting line of three propellers, and the vertical lifting stability is remarkably enhanced. The unmanned aerial vehicle is provided with a unique rotor wing system, a horizontal wing system and a switching mechanism, and efficient switching between vertical flight and horizontal flight can be achieved. During flight, the rotors vertically provide lift force in the take-off stage, the inclination angles and the pitch angles of the rotors are adjusted in the conversion stage, and the horizontal wings bear main lift force during horizontal flight. A flexible engine management strategy, an efficient fixed wing take-off mode and the like are further arranged. In mountainous area rescue, urban logistics and other implementation cases, the unmanned aerial vehicle has the advantages of flexible take-off and landing, efficient flight, accurate control and the like. The aircraft can save energy consumption by 20%-40%, the takeoff taxiing distance is shortened by 30%-60%, the flight speed is increased by 15%-30%, the voyage is increased by 20%-35%, and the aircraft can be widely applied to multiple fields such as emergency rescue and cargo transportation.

The invention discloses an unmanned aerial vehicle adaptive anti-interference precise landing control system for urban logistics, and the system comprises the following modules: a fractal intention tensor body construction module which is used for constructing a fractal intention tensor body; the asymmetric self-evolution intention generation network module is used for generating an intention section sequence; an anti-causal state projector module for generating a plurality of virtual future state nodes; the back projection function construction module is used for performing inverse mapping on each virtual future state node to generate a back-stepping control path set; the disturbance guide path search module is used for sampling and variation by adopting a disturbance guide Monte Carlo path search algorithm to generate an optimal control path; the anti-interference control instruction generation module is used for outputting an anti-interference control instruction; and the flight feedback updating module is used for collecting execution feedback information of the unmanned aerial vehicle and updating state evolution distribution of the fractal intention tensor body. According to the method, tensor modeling and disturbance optimization path backstepping are fused, and anti-interference accurate landing of the unmanned aerial vehicle is achieved.

The application discloses a kind of unmanned aerial vehicle cluster cooperative path planning methods for city logistics distribution, comprising: loading environment 3D model;According to the environment 3D model and task information, initialize path planning model;Path planning model is the problem model with the minimum comprehensive cost as the solving target when unmanned aerial vehicle cluster cooperative path is solved;Comprehensive cost comprehensively height cost, angle cost, avoid obstacle cost, collision cost, communication cost and path length cost;By improving wolf swarm algorithm, the path planning model is solved, and the optimal unmanned aerial vehicle cluster cooperative path is obtained;Improved search strategy is based on population vitality value and problem dimension selection search strategy to search.The application can realize accurate and efficient logistics distribution for dense building city.

The application provides a planning method and system for a simultaneous pickup and delivery vehicle routing problem with multiple time windows under uncertain pickup demand, comprising the following steps: obtaining distribution information of customer points to be served; constructing a fuzzy chance-constrained programming model for the simultaneous pickup and delivery vehicle routing problem with multiple time windows based on credibility measure theory; solving the model by using a genetic and harmony search algorithm to obtain a pre-optimized distribution scheme; scheduling a vehicle to travel according to the pre-optimized distribution scheme to determine the pickup demand of each customer; judging whether there is a failure point with a vehicle residual loading capacity less than the actual pickup demand of the customer, if there is a failure point, adopting a failure point service strategy to re-optimize the path planning for the failure point within the remaining serviceable time window; if there is no failure point, storing the determined distribution information of the customer points and outputting an optimal distribution scheme. The application makes full use of the loading capacity of the vehicle and maximizes the economicization, efficiency and greenization of urban logistics distribution.

The invention relates to the technical field of aircrafts, in particular to a ducted fan combined propulsion vertical take-off and landing aircraft and a control method thereof. According to the aircraft, six ducted fans serve as power sources, four ducted fans are located in the vertical direction and symmetrically arranged in a rectangular shape, and the other two ducted fans are symmetrically distributed along the axis of the aircraft in the horizontal direction. Due to the fact that the ducted fan is used, the aircraft of the structure is low in flight noise, the risk that blades are exposed is avoided through the ducted shell protection design, the loading capacity under the same size is higher than that of a traditional multi-rotor unmanned aerial vehicle, higher maneuverability is provided through a redundant power propelling structure, and the aircraft is more suitable for executing tasks on complex terrains. The invention further provides a control method based on cascade PID for the designed ducted fan combined propulsion vertical take-off and landing aircraft, and stable position and attitude cooperative control is achieved based on real-time feedback of an aircraft sensor system. The scheme is suitable for urban logistics, disaster rescue and other scenes needing vertical take-off and landing and omni-directional maneuvering.

The invention discloses a logistics end distribution post site selection method and system based on deep learning, and relates to the field of artificial intelligence, and the method comprises the steps: firstly constructing a regional topology network comprising service demand points and resource alternative points, obtaining the description parameters of all position points, and obtaining the description parameters of all the position points; wherein the service demand points comprise dense demand points which have topological links with the resource alternative points; extracting a sample position point and determining a corresponding association link; training an initial site selection decision feature extraction model and an initial feature conversion module by using description parameters on the associated link to obtain a target model and module; and finally, based on the target model and module, determining a target site selection point with the highest adaptation score by calculating the deviation degree between the site selection decision feature and the conversion feature of the dense demand point and the resource matching feature space association degree with the candidate courier site selection points. According to the method, the complex association between the location points is excavated through deep learning, the accuracy of site selection of the courier station is improved, and the method is suitable for a complex urban logistics network scene.

The invention discloses an unmanned aerial vehicle cluster collaborative path planning method for urban logistics distribution. The method comprises the following steps: loading an environment 3D model; initializing a path planning model according to the environment 3D model and the task information; the path planning model is a problem model taking an unmanned aerial vehicle cluster collaborative path as a solving target when the comprehensive cost is minimized; the comprehensive cost integrates the height cost, the angle cost, the obstacle avoidance cost, the collision cost, the communication cost and the path length cost; solving the path planning model through an improved wolf pack algorithm to obtain an optimal unmanned aerial vehicle cluster cooperation path; and the improved search strategy is used for searching based on the population vitality value and the problem dimension selection search strategy. According to the invention, accurate and efficient logistics distribution can be realized for dense building cities.

The present invention discloses an intelligent planning method, device, medium and equipment for urban logistics. The method includes: dividing a target city into a target number of logistics areas; generating an ecological cluster category and distribution method corresponding to each logistics area, such as drone distribution, etc.; predicting the logistics demand change trend of the corresponding logistics area in a target period according to the ecological cluster category; and adjusting the current logistics distribution point layout status of the target city according to the distribution method and logistics demand change trend. The present invention divides the urban area into multiple logistics areas with more significant ecological clusters. Each logistics area has a corresponding distribution system and distribution method based on the ecological cluster category, traffic conditions and geographical environment. Not only can the overall layout of the logistics distribution points be targeted at a higher level, but also future changes in logistics demand and distribution methods are considered during the layout process, thereby increasing the foresight, flexibility and practicality of urban logistics planning.

The invention discloses an urban logistics distribution method and system considering road traffic operation state changes, and a medium. The system comprises a decision center and a plurality of distribution centers. Each distribution center is provided with a plurality of distribution vehicles; the method comprises the steps of 1) resolving a logistics distribution decision model based on an order of a customer point and traffic operation conditions in each time section so as to generate a distribution center receiving scheme and a distribution scheme; 2) issuing a corresponding customer point order and a distribution scheme to a distribution center in the distribution center receiving scheme; 3) the delivery center delivers the goods according to the received customer order and selects a corresponding number of delivery vehicles; and 4) the distribution vehicle goes to the customer point according to the distribution scheme to wait for service or directly serves, and after logistics distribution is completed, the distribution vehicle returns to any distribution center. According to the method, the actual characteristic of road traffic operation state change is fully considered, the vehicle driving cost and the waiting time cost are considered at the same time, the total transportation time cost is minimized, and the total transportation cost is reduced for logistics enterprises.

The invention relates to the technical field of logistics, in particular to an urban logistics unmanned aerial vehicle three-dimensional obstacle avoidance and path optimization method, which constructs an unmanned aerial vehicle flight path planning model fusing safety height constraint and obstacle space distribution characteristics, improves an A * algorithm, introduces a direction heuristic optimization strategy, and optimizes the three-dimensional obstacle avoidance and path optimization of an urban logistics unmanned aerial vehicle. The optimal path area can be locked more quickly by the algorithm, so that the calculation overhead is greatly reduced and the search efficiency is improved while the optimality of the solution is ensured. Experiments show that the trajectory planned by the method provided by the invention can effectively avoid static obstacles, a safe distance is kept in the whole process, the path search efficiency and the algorithm robustness are remarkably improved, and the method has excellent performance in the aspects of path length, smoothness, calculation performance and the like, and is suitable for large-scale popularization and application. And a reliable technical support is provided for three-dimensional flight path planning of the logistics unmanned aerial vehicle in an urban complex scene.

The invention relates to an intra-city express distribution transfer center site selection optimization method based on multi-index evaluation, and belongs to the technical field of urban logistics distribution. The method comprises the steps that rail transit station information is acquired, importance evaluation is carried out on rail transit stations, and alternative transfer centers are screened according to the importance of the stations; determining constraint conditions for establishing a transfer center site selection optimization model; the optimization problem of a transfer center site selection optimization model is established by taking the minimization of the total cost as the target in consideration of the express transportation cost, the express loading and unloading and carrying cost and the transportation fixed cost; and solving an optimization problem by adopting a genetic algorithm, and generating an optimal site selection scheme through encoding, crossover and mutation operations. According to the method, by means of multi-index evaluation of the importance degree of the rail transit stations, alternative transfer centers with more advantages can be accurately screened out, the express transportation cost, the loading, unloading and carrying cost and the transportation fixed cost are comprehensively considered, and optimization solution is carried out with the purpose of minimizing the total cost.

The invention discloses an urban logistics unmanned aerial vehicle navigation station network optimization method and device, and relates to the technical field of civil engineering computer algorithms. The method comprises the following steps: establishing an unmanned aerial vehicle route topology based on Delaunay triangulation; performing sample expansion calculation based on the urban travel data to obtain an outdoor exposed population model; performing unmanned aerial vehicle failure probability and head injury criterion-simple injury grading coupling operation on the outdoor exposed population model, and constructing a risk cost spatial distribution map; executing space weighted Gini coefficient operation to obtain the equality of service population distribution; constructing an energy consumption model; and constructing a Boolean mask matrix based on a gridding outdoor exposed population model, and executing a non-dominated sorting genetic algorithm under the constraint of a Boolean mask by taking a risk cost spatial distribution map, the equality of service population distribution and an energy consumption model as three targets to obtain an optimal navigation station spatial layout with a minimum mean square error. According to the invention, the performance of the urban logistics unmanned aerial vehicle navigation station network can be effectively optimized.

The invention discloses an urban low-altitude cableway logistics distribution system built based on urban street lamp poles, and relates to the technical field of urban logistics. According to the system, urban street lamp poles conforming to national technical standards are used as supports, and safe distribution of goods (including 2.5 kg of transportation bins) within 12.5 kg is achieved through a cableway system, a power transmission mechanism, a beautifying type goods carrying device and an intelligent dispatching module which are optimally designed. The system ensures that the street lamp pole has no potential safety hazard through mechanical optimization design, adopts landscape design to be integrated into the urban environment, and has a cross-intersection safe passing mechanism. The method does not relate to a cableway erection engineering technology, only protects the structural combination, safety control and landscape adaptation scheme of the system, has the advantages of high safety, good environment fusion degree, high adaptability and the like, and can be widely applied to scenes such as urban communities and commercial streets.