101 results about "Bicycle sharing" patented technology

The invention provides an implementation method of a shared bicycle real-time tracking and positioning system. The system comprises a controller, a plurality of tracking devices, a plurality of shared bicycles and a plurality of operation devices. And the operation equipment monitors and positions the shared bicycles in real time through the controller and the tracking equipment. Through the system, an operator can obtain accurate position information of the monitored shared bicycle in real time, and all-weather and high-precision bicycle tracking and positioning are realized. The system remarkably improves the operation and maintenance management efficiency of the shared bicycles, reduces the operation cost, and has a wide application prospect in the fields of smart transportation, urban shared travel and the like.

The invention relates to a shared bicycle brake pad abrasion monitoring system and a monitoring method thereof, and aims to solve the problems that in the prior art, shared bicycle brake pad abrasion monitoring is high in cost and low in precision, and abnormal abrasion cannot be detected, and accurate monitoring is achieved through a multi-parameter correction model of brake frequency statistics and pressure distribution perception. A microswitch is arranged on a brake pedal, three film pressure sensors are arranged on a brake pad steel backing, a brake pressure value, an average effective pressure Pavg and a pressure distribution difference delta P are synchronously collected, a wear estimation model is built by combining working condition data such as temperature and vehicle speed, and a material coefficient k, a vehicle speed correction coefficient f (v) and a temperature correction coefficient g (T) are adopted for multi-dimensional correction, so that the wear estimation precision is improved. And calculating the accumulated abrasion loss and predicting the residual thickness. Accurate recognition of abnormal wear such as eccentric wear and block falling is achieved by analyzing a delta P threshold value and Pavg mutation characteristics, parameter customization of brake pads made of different materials is supported, and a graded early warning function is achieved.

The invention relates to the technical field of shared bicycle scheduling methods, in particular to a shared bicycle multi-target dynamic scheduling method based on double-matrix variable neighborhood search. The system comprises four core components, namely a scheduling problem modeling module, a double-matrix coding module, an improved genetic algorithm module and a dynamic scheduling decision module. Constructing a multi-objective optimization model containing site topological data, operation constraint parameters and demand prediction data through a scheduling problem modeling module; the dual-matrix coding module adopts a dual coding structure of a path matrix and a scheduling quantity matrix, and respectively represents vehicle path planning and station loading and unloading quantity distribution; the improved genetic algorithm module implements a collaborative optimization strategy of hybrid crossover operation and variable neighborhood search; and the dynamic scheduling decision module finally outputs an optimal scheduling scheme meeting multi-target balance. According to the invention, through a double-matrix decoupling optimization architecture and an intelligent search mechanism, the problems of complex constraint and multi-target optimization in dynamic scheduling of shared bicycles are effectively solved.

The utility model discloses a full-automatic shared bicycle fixed-point returning electronic lock which comprises a base, two positioning frames are fixedly connected to the top of the base, limiting grooves are formed in the tops of the two positioning frames, recognition modules are fixedly connected to the bottoms in the limiting grooves in an embedded mode, a bicycle body is arranged between the two positioning frames, and the bicycle body is fixedly connected with the two positioning frames. A front wheel frame is arranged on one sides of the two positioning frames, and a bicycle locking assembly is jointly arranged on the sides, close to the front wheel frame, of the two positioning frames. The front wheel frame, the limiting groove and the electromagnetic lock are matched with one another, and the front wheel frame and the limiting groove are used for fixing the shared bicycle, so that a handlebar of the bicycle and a bicycle body including a front wheel are stably positioned and are not prone to toppling over; the electromagnetic lock at the top of the base attracts and locks the vehicle, the vehicle structure is not prone to being damaged when the vehicle is subjected to external acting force, and the service life of the vehicle is prolonged.

The invention provides a shared bicycle multi-dimensional risk data early warning management method and system, and relates to the technical field of data processing, and the method comprises the steps: 1, obtaining riding data, bicycle positioning data and environment data, carrying out the preprocessing, and generating fusion data with geographic coordinates; step 2, based on the fusion data, constructing a geographic bounding box covering all vehicle positions as a virtual reference plane, dividing the virtual reference plane into four partitions according to distribution density characteristics of vehicles on the virtual reference plane, calculating a vehicle number change rate and a space-time stability index of each partition, and obtaining a partition adjustment coefficient; according to the invention, early warning and dynamic scheduling of the deposition and shortage risk of the shared bicycle are realized, and the operation management efficiency and the user bicycle use experience are improved.

The embodiment of the invention discloses a shared bicycle management system, method and device, electronic equipment and a storage medium, and relates to the technical field of augmented reality. The system comprises AR glasses, a management platform and a shared bicycle, the AR glasses send a vehicle searching request and the first position information to the management platform; the management platform determines a candidate shared bicycle, queries the real-time state of the candidate shared bicycle, determines a target shared bicycle, and sends second position information of the target shared bicycle to the AR glasses; the AR glasses generate virtual navigation elements according to the second position information, and display the virtual navigation elements in the real world in an overlapping manner based on the virtual screen; the AR glasses collect information of the target shared bicycle based on the camera and send unlocking information to the management platform; after the management platform verifies the user identity and the target shared bicycle, an unlocking instruction is sent to the target shared bicycle to unlock the target shared bicycle. According to the scheme, a user can be guided to quickly find and unlock the shared bicycle in a good state.

This invention discloses a method and system for optimizing community bus service zones and sub-zone routes based on connection resistance, comprising the following steps: S1, constructing a main model for community shuttle bus service zones based on finite center-subordination rules to obtain the service sub-zone allocation scheme for community shuttle bus stops; S2, for each service sub-zone, constructing a sub-model for optimizing community shuttle bus service routes based on bus service impedance index to obtain shuttle bus service route schemes for each sub-zone connecting to public transportation hubs, determining whether the minimum service standard for shuttle buses is met by checking the connection resistance; for all sub-zones that fail the connection resistance test, adding the corresponding sub-zone partitioning constraint set to the main problem, and returning to S1 to resolve the main model until all shuttle bus route schemes for each sub-zone pass the test. This invention, through connection resistance testing, makes the designed community shuttle bus connection routes more competitive in service compared to shared bicycle travel.

The invention discloses an electric bicycle battery changing cabinet locating and sizing method and system based on bilevel programming. The method comprises the following steps: firstly, acquiring required parameters, constructing each individual of an initial population in an upper-layer optimization model based on the required parameters, and coding candidate site selection schemes and capacity configuration of the power conversion cabinet; then, the initial population is transmitted to a lower-layer solving module, the lower-layer solving module generates a plurality of feasible scheduling paths of a scheduling vehicle in a random scene through the randomization requirement of an electric bicycle station, Monte Carlo sampling and a variable neighborhood search algorithm, and the comprehensive index of the individual is calculated according to the feasible scheduling paths. And then, feeding back the comprehensive index to an upper layer optimization model for correcting the initial population, and obtaining a convergent optimal solution through an iterative evolution process of the upper layer model. Through the double-layer interaction mechanism, collaborative optimization of battery changing cabinet site selection, capacity configuration and scheduling vehicle path planning is realized, and the operation efficiency and robustness of the whole system are improved.

The invention discloses a shared bicycle supervision and identification method, system and device and a storage medium, and the method comprises the steps: obtaining a Bluetooth broadcast signal in a scanning coverage area through a shared bicycle supervision client, carrying out the anti-cheating identification, analysis verification and encryption processing of the obtained Bluetooth broadcast signal, and transmitting the Bluetooth broadcast signal to a cloud big data platform; the cloud big data platform decrypts the received data to obtain MAC addresses, then traverses a filing database based on the MAC addresses to determine associated filing two-dimensional codes, and counts the number of the MAC addresses associated with the associated filing two-dimensional codes; and when the number of the MAC addresses associated with the associated filing two-dimensional code exceeds the filing release limit, triggering a one-code multi-bicycle violation alarm, thereby effectively solving the problems of difficult shared bicycle supervision, low efficiency and high supervision cost in the prior art, and realizing automatic identification and early warning of the'one-code multi-bicycle 'violation behavior on the basis of not increasing the cost.

The invention discloses a shared bicycle travel hot spot area positioning method and system based on a travel vector field, a medium and a terminal. The method comprises the following steps: obtaining geographic space information data of a to-be-identified area, and carrying out unit grid division; based on the travel data of the shared bicycle in the target research time period, the longitude and latitude information of the starting point and the ending point is matched to the corresponding grids; counting the travel volume of the shared bicycles in each grid to generate an accumulated travel vector of each grid; carrying out clustering analysis on all grids by taking the travel volume of the normalized grids and the modulus of the cumulative travel vector as features, and dividing unit grids into different categories; according to the accumulative travel vectors of the different types of unit grids, sub-travel vector fields are constructed respectively, and corresponding potential energy is calculated; and determining a corresponding potential energy weight according to the travel volume mean value of the grids of each category, and calculating the potential energy of the global travel vector field of the city. The problems that resident travel directivity features are not comprehensively considered, and the hot spot area of the shared bicycle is not accurately positioned are solved.

The embodiment of the present specification provides a smart city shared bicycle delivery and operation area planning method and an Internet of Things system. The method is executed based on a management platform of the smart city shared bicycle delivery and operation area planning Internet of Things system. The method comprises the following steps: obtaining reference information of human flow of at least one target area, determining predicted human flow of the at least one target area at a target time based on the reference information of human flow, and determining a shared bicycle demand based on the predicted human flow; obtaining shared bicycle historical data of a plurality of reference areas, predicting a shared bicycle change amount of the at least one target area at the target time based on the shared bicycle historical data; and determining a shared bicycle delivery amount of the at least one target area at the target time based on the shared bicycle demand and the shared bicycle change amount.

The invention discloses a shared bicycle rebalancing method considering operator and user excitation. The method comprises the following steps: abstracting a shared bicycle initial distribution and multi-vehicle type rebalancing problem into a two-stage stochastic programming model and solving the two-stage stochastic programming model; describing a first-stage initial allocation optimization problem including a single vehicle total amount constraint and a budget constraint; after initial distribution is completed, in the rebalance problem of the second stage, user incentive constraints and truck dispatching related constraints are described; generating a random demand scene; an SAA algorithm is used for solving initial putting of the single vehicles, and the total expected cost is minimized; solving a user incentive task based on an upper-layer VNS algorithm; and further optimizing a shared bicycle redistribution strategy of the operator through the lower layer VNS, wherein the shared bicycle redistribution strategy comprises path planning of a scheduling motorcade and loading and unloading amount decision of each station. According to the invention, joint optimization of initial allocation and rebalance decision is realized, the resource utilization rate is improved, and the overall operation cost is effectively reduced.

The utility model relates to the technical field of shared bicycles, in particular to a shared bicycle saddle wiping structure which comprises a bicycle frame, a saddle tube is connected to the bicycle frame, a seat is connected to the saddle tube, a rotating shaft is fixedly connected to the bottom of the seat, a connecting block is connected to the top of the saddle tube, and the rotating shaft is rotationally connected to the connecting block. The bottom of the seat is slidably connected with a guide rod, the guide rod is inserted into the connecting block, and when the guide rod pulls or inserts the connecting block, the connecting block can be unlocked or locked on the rotating shaft; a storage roller is rotationally connected to the guide rod, wiping cloth is connected to the storage roller in a winding mode, and when the guide rod is pulled out of the connecting block, the wiping cloth is released from the wiping cloth; according to the structure, the seat can be overturned to be in a vertical state, so that water stains slide down, and meanwhile, the wiping cloth is arranged at the bottom of the seat, so that the wiping cloth can be conveniently used for wiping the seat stained with water.

The invention discloses a hybrid shared bicycle system environment impact assessment method and system based on digital twinning, relates to the technical field of shared bicycle system assessment, and realizes denoising and stable modeling of station occupation data by introducing a long-term baseline and a standardized data set, so that abnormal oscillation stations can be accurately identified. Through an oscillation intensity index (i.e., an accumulated variation value normalization result), normal periodic fluctuation and abnormal large fluctuation can be effectively distinguished. And a hotspot cluster set is formed by further combining density clustering, and the future short-term fluctuation direction is predicted based on a trend quantity, so that a potential abnormal region is locked in advance in double dimensions of space and time. The mechanism ensures that scheduling triggering does not depend on single-point data any more, but improves timeliness and accuracy of vehicle supplementing operation based on double judgment of stability and tendency.

The application provides a shared bicycle dispatching method based on data fusion and dynamic resource optimization, relates to the technical field of data processing, and fuses first position data of a bicycle itself and second position data collected by an environment to obtain fusion position data of each station; generates a dynamic capacity baseline of each station based on historical data, a bicycle movement line and environmental parameters; determines a redundancy value of the station according to the fusion position data of each station and the capacity baseline; and generates shared bicycle dispatching information based on the redundancy value, the position of the station and the attributes of a dispatching device, so that the supply of bicycles can be accurately and efficiently dispatched according to multi-dimensional factors corresponding to different regions, and problems such as uneven distribution of shared bicycles and low dispatching efficiency are solved.

The present application relates to the field of intelligent transportation system and big data analysis technology, and more particularly to a shared bicycle rail connection analysis method considering travel stage built environment, comprising: obtaining shared bicycle order trajectory data in a target area, identifying travel behavior, performing OD mapping of the identified connection travel starting point-destination, and generating shared bicycle travel OD samples; performing shared bicycle trajectory data corresponding to the OD samples for riding path reconstruction and path restoration; for different travel stages of shared bicycle connection travel, corresponding built environment features are extracted respectively; based on the built environment features of different travel stages, prediction models for predicting shared bicycle use probability of rail transit inbound connection and outbound connection are constructed respectively; the prediction models are explained and analyzed, and key influencing factors and their action relationships are output. The present application can more comprehensively and truly reflect the formation mechanism of shared bicycle and rail transit integrated travel.

The invention discloses a shared bicycle scheduling variable VRP search method based on deep reinforcement learning driving, and the method comprises the following steps: S1, constructing a variable VRP mathematical model considering space-time resource constraints, constraint conditions met by the variable VRP mathematical model comprise one or more of a traffic volume variable constraint, a flow conservation constraint, a vehicle load limit and a time cost coupling constraint of driving time and operation time; s2, constructing a deep reinforcement learning interaction environment based on an ALNS; s3, a Double DQN intelligent agent is built and trained; s4, executing online topology-traffic volume nested search by adopting a double-layer nested search strategy; and S5, introducing a constraint penalty term into the target function, and executing softening and processing of multiple complex constraints. The method has excellent generalization performance, can be directly expanded and applied to various logistics scenes such as express terminal distribution, material emergency dispatching and urban garbage recycling, and has wide industrial application prospects.

The utility model discloses a universal umbrella for shared bicycles, which comprises an umbrella support and an umbrella, an elastic rope is sewed on the front side of the bottom surface of an umbrella cover of the umbrella close to the edge, and the other end of the elastic rope is provided with a fastener; the rear side of the umbrella is provided with a first extension umbrella cover through a first umbrella rib to form an eccentric umbrella; a second extension umbrella cover is arranged at the other end of the first extension umbrella cover through a second umbrella rib; a bolt adjusting buckle in the umbrella support is sleeved on an umbrella handle of the umbrella; the plastic ring in the umbrella support is clamped and sleeved on an umbrella handle of the umbrella; according to the universal umbrella for the shared bicycle, through the special-shaped eccentric design, the arrangement of the elastic connecting buckle and the combination of the umbrella support, in rainy and snowy days, the umbrella can be stably installed on the shared bicycle through the buckle and the umbrella support, riding and umbrella holding at the same time are not needed, riding is facilitated, and potential safety hazards are reduced; and meanwhile, the vast majority of parts of the whole body of the user can be shielded by using the enlarged umbrella cover, so that the rain shielding effect is improved.

The present application belongs to the technical field of traffic detection, in order to solve the problem of insufficient practicability and high cost of existing illegal parking detection method, a roadside illegal parking detection method and system based on shared bicycle trajectory similarity is proposed, a trajectory similarity matrix is constructed based on historical shared bicycle trajectory data, clustering analysis is performed on the trajectory similarity matrix to obtain the normal traffic template of each cluster, the real-time trajectory is matched with each normal traffic template for detection to determine whether the current shared bicycle traffic is normal, the abnormal area is determined according to the space area where the shared bicycle is located and the corresponding trajectory abnormality degree and abnormal time duration, and then whether there is illegal parking is judged according to the abnormal area. The present application realizes the identification of illegal parking under the condition of no manual annotation and no special monitoring equipment, reduces the deployment cost and expands the detection range.

The invention belongs to the technical field of traffic geographic information analysis, and discloses an urban crowd activity and space structure dynamic deduction method and system based on single traffic flow, a terminal and a storage medium. Identifying a spatial distribution mode through a flow similarity measurement method in combination with a hierarchical clustering algorithm; carrying out quantity aggregation on the identified spatial distribution mode according to grid units, and constructing a spatial grade distribution model; combining the urban built environment features with spatial grade distribution in the spatial grade distribution model, and constructing a comprehensive data set suitable for machine learning regression modeling; and based on the comprehensive data set, in combination with a machine learning model interpretation method of a game theory, quantitatively analyzing a nonlinear influence mechanism of urban built environment characteristics on different spatial distribution modes, and deducing internal relevance between urban crowd activities and spatial structures. The dynamic evolution process of the urban space structure is comprehensively realized.

The application provides a multi-constraint-based spatial element dynamic aggregation method and system, and belongs to the technical field of spatial data processing. The method comprises the following steps: acquiring shared bicycle parking point spatial element data set and multi-dimensional constraint conditions; performing spatial profiling on a target research area based on spatial division constraints, generating a plurality of initial aggregation service range units, and mapping elements in the spatial element data set into the initial aggregation service range units, and calculating statistical indexes of the initial aggregation service range units; constructing a graph structure with the initial aggregation service range units as nodes, and the spatial adjacency relationship and semantic similarity between the units as edges; constructing a graph structure aggregation model, including a target function with the minimum variance of the statistical indexes between the initial aggregation service range units as the target, and a constraint condition based on the integrity of the spatial division constraints; and solving the graph structure aggregation model by using a heuristic search algorithm or a graph partitioning algorithm to generate a dynamic aggregation service range result satisfying the statistical balance constraint.

The application relates to the technical field of urban bus line network and timetable integration optimization, and particularly discloses a bus line network and timetable integration optimization method and device based on graph reinforcement learning. The method is used for generating a bus line network structure and a timetable in a multi-mode public transport network containing BRT, subway and shared bicycles. Firstly, a multi-mode public transport road network is constructed, and passenger flow demand data is obtained; a bus line network design and a synchronous timetable compilation process are modeled as a Markov decision process; according to a current bus line network state, the road network is reconstructed into a heterogeneous graph containing time sequence evolution arcs and spatial topology arcs, and a double attention graph neural network is used to extract candidate node features; according to the node features, an action is selected through an action network, and the bus line network state is updated; the node feature extraction, the action selection are repeated until a termination condition is met, and the bus line network structure and the line timetable are output. The application can generate a bus line network and timetable which are more coordinated with other public transport modes, and reduce the operation cost of bus enterprises and the travel and transfer time of passengers.

The application discloses a shared bicycle demand prediction method based on a geographical distance enhanced space-time graph neural network, belongs to the technical field of bicycle demand prediction, and inputs bicycle data cleaned and aggregated into a double-branch framework integrating local and global space-time information, which is composed of a local information branch and a global information branch. In the local branch, the distance information between stations is introduced, a multi-scale Gaussian kernel is designed for processing, and is added to the calculation of attention scores to solve the deficiencies of existing models in global and local information integration and real geographical distance information extraction. In the global information branch, global spatial patterns and long-term time trends are extracted through the combination of GAT and TCN, and information is further fused through shared GNN and shared MLP to comprehensively integrate global space-time information, better grasp the overall change rule of bicycle demand in time and space, and improve the prediction accuracy and stability.

The invention relates to the technical field of shared bicycles, and particularly discloses a shared bicycle positioning management method and system based on artificial intelligence, and the method comprises the steps: obtaining multi-source sensor data uploaded by a bicycle, and obtaining environment data related to positioning information; estimating data quality information of the multi-source sensor data based on the positioning information and the environmental data; obtaining a weight set about the multi-source sensor data according to the data quality information; performing weighted fusion on the multi-source sensor data based on the weight set to obtain fusion data features; on the basis of a pre-trained state analysis model, motion state information is generated according to the fused data features; performing operation management based on the motion state information and the corresponding positioning information; according to the method, the problem that sensor data in the urban environment is interfered, drifted or missing can be effectively solved, so that an operation platform can identify the real state of the vehicle more accurately, misjudgment is reduced, and operation management activities such as vehicle scheduling, maintenance and theft prevention are optimized.

The invention provides a shared bicycle automatic checkout and locking method and system, and belongs to the technical field of shared bicycle management, and the method comprises the steps that a mobile terminal receives a Bluetooth signal and an audio signal sent by a shared bicycle; the Bluetooth signal and the audio signal have the same sending period, and the Bluetooth signal and the audio signal respectively comprise corresponding packet serial numbers; the mobile terminal decodes the received Bluetooth signal and audio signal to obtain a Bluetooth data packet serial number and an audio data packet serial number; the mobile terminal determines a position relationship between the mobile terminal and the shared bicycle based on the signal time difference; the signal time difference is the receiving time difference of the Bluetooth signal and the audio signal with the same packet sequence number; and if the position relationship represents that the mobile terminal is far away from the shared bicycle, the current travel is ended, and the mobile terminal generates a travel order and locks the shared bicycle. The relative position relation between the mobile terminal and the shared bicycle is judged through the time difference between the Bluetooth signal and the audio signal, and quick response of automatic bicycle locking and checkout is achieved.

The utility model discloses a shared bicycle locking column easy to import, and relates to the technical field of shared bicycle locking. The bottoms of the stand columns are fixedly connected with the two sides of the bottom plate; the outer side of the guiding device is fixedly connected with the bottom of the outer side of the stand column, and the guiding device is used for guiding the shared bicycle to advance; the outer side of the bicycle locking device is fixedly connected with the side, close to the guiding device, of the stand column; the bottom of the fixing frame is fixedly connected with the top of the bottom plate; the guiding device comprises an arc-shaped block, and the outer side of the arc-shaped block is fixedly connected with the outer side of the stand column. According to the device, the guide device is arranged to guide the shared bicycle to enter the bicycle locking column, so that a user can smoothly find and use the bicycle locking column in a dark environment, and the problems of time waste and non-standard bicycle parking caused by difficulty in finding or inaccurate introduction are reduced.

The invention is suitable for the technical field of smart cities, and provides a shared bicycle illegal parking identification method, which comprises the following steps: acquiring image data of a target area, and determining a current time period; generating a dynamic no-parking area corresponding to the target task in the target area based on scene semantics in the image data and the current time period; and carrying out illegal parking behavior identification on the shared bicycles in the dynamic parking forbidding area, and determining target shared bicycles with illegal parking behaviors. According to the invention, through the scene semantics in the image data of the target area and the current time period, the dynamic no-parking area corresponding to the target task is generated in the target area, the illegal parking behavior of the shared bicycles in the dynamic no-parking area is identified, and the target shared bicycle with the illegal parking behavior is determined. The method solves the problems that a static electronic fence needs to preset a fixed area and cannot adapt to dynamic illegal parking scenes such as subway entrances and the like when the static electronic fence is used for carrying out illegal parking recognition on shared bicycles in an existing illegal parking recognition method, and illegal parking recognition is single.