2279 results about "Parking lot" patented technology

The invention relates to the field of new energy vehicles, and discloses a charging pile load test data analysis method and system based on intelligent sensing, and the method comprises the steps: carrying out the dynamic mapping of a charging pile group in a public parking lot through a multi-source heterogeneous sensing assembly; carrying out dislocation labeling on handshake waveforms, thermal image hot spots and harmonic pulses based on a scene semantic segmentation network; performing multi-scale sliding window cross-domain correlation tracking on the data priority sequence, and combining historical waveform fingerprints, a power factor drift trajectory and an environmental electromagnetic interference matrix; based on a multi-dimensional time sequence feature tensor, a load evolution trajectory is extracted by using a priority adaptive model, and clustering density abrupt change and entropy drift inflection points are identified; calibrating a charging entity and a coupling range corresponding to the potential safety hazard candidate event as a candidate area; and on the basis of a local load priority interference atlas, potential unstable nodes and a global risk entropy fluctuation trend in monitoring data are combined. The method has the advantage of improving the safety and accuracy of the load in a complex environment.

The invention discloses an urban traffic intelligent regulation and control system and method based on digital twinning. The method comprises the following steps: S1, collecting and fusing multi-source data in real time; s2, constructing a digital twinborn model; s3, traffic flow prediction and optimization; s4, multi-system cooperative control is carried out; the system comprises the following modules: a multi-source data real-time acquisition and fusion module which comprises a video data acquisition and processing unit, a geomagnetic sensor network construction unit and a floating car data integration unit; the digital twinborn model building module comprises a three-dimensional road network model building unit and a data fusion and calibration unit; the traffic flow prediction and optimization module comprises an intelligent prediction model unit and a real-time optimization control unit; and the multi-system cooperative control module comprises an emergency priority passing system unit, a reversible lane dynamic adjustment unit and a parking lot induction unit. The traffic efficiency can be remarkably improved, the cooperative response speed is greatly increased, and carbon emission is effectively reduced.

The invention provides an intelligent parking lot charge management and parking space resource intelligent allocation optimization method, and relates to the technical field of intelligent parking lots, and the method comprises the steps: obtaining the real-time occupation state data of parking spaces in a parking lot, carrying out the time window division and sequence similarity analysis through time sequence data mining, and calculating the real-time parking space pressure value of each region; when the pressure value of the first region exceeds a threshold value, selecting a second region for integration based on a prediction result and a region stability integration degree, and forming a dynamic management region; and calculating a real-time rate by adopting deep reinforcement learning, determining a core influence area according to the parking request, and distributing a target parking space based on neighborhood density characteristics. According to the invention, the utilization rate of parking lot resources is improved, and intelligent parking space allocation and dynamic pricing are realized.

The invention, which relates to the parking space management field, discloses a visual parking lot parking space release management system comprising a dynamic twinborn modeling module, an intelligent path planning module, a dynamic twinborn modeling module, a dynamic twinborn modeling module and a dynamic twinborn modeling module. The dynamic twin modeling module comprises a multi-source data acquisition module, a point cloud preprocessing module, a semantic enhancement modeling module, a real-time rendering and optimizing module and a dynamic updating and maintaining module; the intelligent path planning module comprises a high-precision positioning and environment sensing module and a space-time constraint path planning module. According to the visual parking lot parking space release management system, the distance between the vehicle and the parking space, the turning frequency, the energy consumption and the gradient can be comprehensively considered through the improved D * Lite algorithm, the traffic situation of the parking lot in the future is predicted in combination with the traffic situation prediction module, the path is recalculated every 5 seconds, the path of the parking space can be effectively planned, and the parking space release management efficiency is improved. And the problem of vehicle energy consumption can be effectively avoided.

The invention belongs to the technical field of parking management, and particularly relates to an intelligent parking management method based on the Internet of Things, a terminal and a storage medium, and the method comprises the steps: collecting the parking space state, vehicle information and environment data of a parking lot in real time through a multi-mode sensor; preprocessing and fusing the collected data to generate a spatio-temporal data matrix; constructing a parking space demand prediction model based on the spatio-temporal data matrix, and outputting a parking space demand thermodynamic diagram in a future preset time period; receiving a reservation request, and generating a parking space reservation distribution strategy according to the parking space demand prediction result in combination with a preset time sequence constraint condition; outputting a corresponding appointment accepting decision and a parking space locking instruction; by monitoring the parking space state in real time, a user can obtain accurate parking information in advance, the situation that a large amount of time and energy are wasted in the parking space searching process is avoided, and therefore the parking efficiency is remarkably improved. Meanwhile, due to the introduction of the parking space reservation function, the user can lock the parking space in advance, and the time for finding the parking space is further shortened.

The invention relates to the technical field of smart parking lots, in particular to a vehicle safety management method based on a smart parking lot, which comprises the following steps: S1, multi-source data acquisition: acquiring dynamic trajectory data of a target vehicle, parking lot environment parameters and adjacent parking space state data in real time, and generating a multi-source feature vector set; s2, data space-time alignment: carrying out space-time alignment processing on the multi-source feature vector set, and outputting a standardized vehicle behavior sequence; s3, abnormal behavior recognition: inputting the standardized vehicle behavior sequence into an abnormal behavior recognition model, and generating an abnormal behavior characteristic spectrum and a confidence coefficient parameter; s4, risk level assessment: constructing a risk assessment model based on the confidence coefficient parameter and the environmental parameter, and outputting the risk level of the parking lot in the current scene; and S5, security policy triggering: triggering a corresponding security policy execution instruction according to the risk level. According to the invention, potential risks can be effectively prevented, and the safety of vehicles and personnel is ensured.

The invention discloses an intelligent parking management system based on multi-dimensional data analysis, and relates to the technical field of urban parking management, and the system can dynamically monitor the real-time state of a parking lot through a parking lot information collection module, can obtain the parking demands of a driver through a to-be-parked person collection unit, and can achieve the intelligent parking management of the driver. Comprise distance preference, cost budget and parking space types, and the most suitable parking lot is accurately matched by combining static and dynamic characteristics of the parking lot, so that the parking convenience is improved. And the correction module calculates a parking cost performance index of the parking lot, and performs dynamic adjustment according to a cost performance threshold value Z, so that the recommended parking lot is ensured to meet requirements, cost, parking convenience and parking space stability are considered, and an optimal choice is provided for a user. The system can reduce disordered wandering of vehicles in high-demand time periods or hot spot areas, improves reasonable configuration of parking resources, reduces traffic congestion caused by searching parking spaces, and improves the overall efficiency of urban parking management.

The invention relates to the technical field of warehouse-in and warehouse-out management, in particular to a second-hand car warehouse-in and warehouse-out management system and method. The system comprises a vehicle RFID tag module, an intelligent electronic price tag module, a warehouse-in management module, a warehouse-out management module, an inventory monitoring and alarming module, a multi-point RFID positioning network module and an inventory map visualization module, and a unique encrypted RFID tag can be configured for each second-hand vehicle; binding an intelligent electronic price tag for each second-hand vehicle, and receiving verification to generate a verification result; collecting label information when the vehicle enters the parking lot; the label information is verified when the vehicle leaves; receiving the verification result of the intelligent electronic price tag and the vehicle in-library data of the database to lock the position of the abnormal vehicle; dense RFID reader nodes are arranged in the market to collect and output positioning data; and receiving the positioning data and the vehicle state information, generating a real-time inventory distribution map, and providing a scheduling and site planning decision basis for a manager. The scheduling and planning efficiency of managers can be improved.

The invention relates to the technical field of charging parking space guiding control, and particularly discloses a parking space charging reservation and intelligent guiding method, device, equipment and medium, and the method comprises the steps: obtaining vehicle battery state data and a user reservation time window through an Internet of Things terminal; synchronously acquiring charging pile state data, real-time traffic flow data and power grid load information in the parking lot; fusing the obtained multi-source heterogeneous data based on a federated learning framework, constructing a dynamic charging demand prediction model, and predicting charging pile occupancy rate distribution in a preset time period by using a space-time diagram convolutional network; through the combination of the dynamic charging demand prediction model and the space-time diagram convolutional network, the occupancy rate distribution of the charging piles is accurately predicted, the scheduling strategy of the charging piles is adjusted in real time, the problem of unreasonable resource allocation is avoided, and the waiting time of a user is shortened; the application of the quantum genetic algorithm optimizes the matching process of the charging pile through global optimal solution search, thereby ensuring the balance of the power grid load and the rationality of the charging strategy.

The invention discloses an intelligent parking space guiding system for a hospital parking lot, relates to the technical field of intelligent traffic, and is used for solving the problems that the hospital parking lot is seriously jammed in peak hours and special vehicles lack exclusive passing authority. The system comprises a parking space monitoring module, a vehicle identification module, an intelligent guiding module and a user interaction module. The parking space state is monitored in real time through the multi-mode sensor array; recognizing entering and exiting vehicles through a deep learning recognition algorithm based on cameras deployed at entrances and exits, and obtaining corresponding vehicle information; based on parking space state information and vehicle identification information, a route optimal value is dynamically calculated, and a whole-course navigation service from an entrance to a target parking space is provided for a driver, so that accurate detection of the parking space state, special vehicle priority distribution, high-low peak dynamic route planning and whole-process intelligent guidance are realized, the hospital parking efficiency is remarkably improved, and the hospital parking experience is improved. And the congestion condition in the peak period is relieved.

The invention discloses an intelligent parking method and device based on multi-source data fusion and a medium, and relates to the technical field of big data technologies. The method comprises the following steps: collecting multi-source parking data, and analyzing the multi-source parking data to generate a parking lot label library; generating a user tag based on historical search records and residence time preferences of the user, and constructing a user information database; when it is detected that a user triggers a parking request, performing multi-dimensional matching calculation on a user tag and a parking lot tag library to obtain a recommended parking space sequence; and optimizing the recommended parking space sequence based on the real-time traffic state and the user credit score to generate a final navigation path. According to the method, a dynamic parking recommendation mechanism is constructed by collecting and analyzing the multi-source parking data and the user preference data.

The invention provides a semantic aerial view visual relocation method and device in a non-exposed scene, electronic equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a multi-view image sequence under a non-exposed scene (such as a tunnel, an underground pipe gallery or an underground parking lot); semantic recognition is carried out based on a pre-trained semantic target detection model, and spatial consistency semantic features are extracted through a semantic-geometric dual-channel fusion mechanism combining a semantic mask and geometric constraints; the method comprises the following steps of: realizing three-dimensional reconstruction by using a voxel micro-renderable modeling method (VGGT), and generating a dense three-dimensional semantic point cloud fusing semantics and a geometric structure; two-dimensional semantics are mapped to a three-dimensional space through a projection and back projection relation, and point cloud semantics are endowed; main structure planes such as the ground, the left wall surface and the right wall surface are extracted, and a two-dimensional semantic aerial view with semantic annotation is generated; and pose estimation is carried out based on a reciprocal matching strategy guided by a semantic mask, so that visual repositioning with high precision, high robustness and semantic interpretability is realized. The method breaks through the problems of low precision, sparse features and poor semantic consistency of traditional visual repositioning in a non-exposed environment, and can be widely applied to the fields of intelligent transportation, underground inspection and unmanned system positioning.

The invention discloses a real-time reservation and scheduling system for shared parking, and relates to the technical field of intelligent traffic and smart city management, and the system comprises a demand analysis module which is used for extracting parking lot scene types, time requirements and priority information from user parking request data, generating standardized demand description through dynamic weight distribution, and sending the standardized demand description to a user; the process decomposition module is used for decomposing a parking scheduling process into demand receiving, resource matching and path planning business units according to parking lot scene types and time requirements in the user demand analysis result, and determining a business unit set; according to the real-time reservation and scheduling system for shared parking, through dynamic weight distribution and real-time response optimization, efficient resource distribution and path planning are ensured, and the parking scheduling efficiency and the user experience are remarkably improved.

The invention discloses an elastic resource allocation and barrier gate linkage control system and method for mixed traffic of parking lots, a medium and equipment, and the system comprises a vehicle type recognition module, a dynamic resource allocation module, a cooperative control decision module, an emergency channel management module and a multi-mode communication module. According to the parking lot mixed traffic management system integrating vehicle-road cooperative communication, double-layer game optimization and elastic resource pool division, an independent resource pool and a dynamic quota adjustment mechanism of automatic driving vehicles and manual driving vehicles are constructed, and a charging pile-barrier gate cooperative optimization unit and a multi-stage emergency response protocol are combined; the global optimization of parking lot resource allocation and traffic control is realized, and the problems of prominent resource competition contradiction, separation of barrier gate control and resource allocation, insufficient intelligence of an emergency response mechanism and short delay of multi-mode communication and decision cooperation in a mixed traffic scene are solved.

The invention discloses a parking space recommendation and reservation method, which comprises the steps of normalizing acquired multi-source heterogeneous data to generate parking lot static attribute data, real-time parking space state data and dynamic user request data; constructing an objective basic potential field by using fuzzy reasoning according to a fuzzy rule set capable of performing adaptive evolution based on performance feedback; modeling long and short term preferences of the user by adopting methods such as hierarchical Bayesian and an attention mechanism so as to generate a user subjective preference modulator; an objective potential field, a subjective modulator and a multi-agent rejection potential field with dynamically adjustable parameters are fused, a total potential energy function of the system is constructed, and a collaborative guidance strategy for all users and conflict avoidance is determined and output by solving the minimum value of the function. According to the invention, efficient and personalized parking guidance with macroscopic cooperation capability can be provided, and the user experience and the operation efficiency of the parking lot are significantly improved.

The invention discloses a quadruped robot inspection method based on multi-modal sensing fusion. The method comprises the following steps of: 1, initializing a global task, loading a basic navigation map, and generating the basic navigation map comprising topographic features, forbidden areas and parking positions; 2, autonomous navigation and dynamic correction of positioning deviation are realized according to laser radar SLAM data, and the positioning deviation is dynamically corrected according to real-time observation data; 3, dynamically switching or adjusting the gait strategy according to the terrain category, training the gait strategy of the quadruped robot to be matched with the terrain category, and generating a self-adaptive motion control instruction to adapt to the terrain in real time; and step 4, synchronously realizing parking area structured data acquisition and dynamic abnormal information perception through multi-sensor fusion, and realizing target state monitoring and abnormal event response in the inspection task. According to the invention, through collaborative innovation of the bionic motion platform and multi-mode intelligent detection, all-terrain coverage, total-factor perception and full-process autonomous intelligent inspection in a complex parking lot environment is realized.

The invention discloses a method for dynamically monitoring and automatically processing abnormity of an entrance and an exit of a parking lot, relates to the technical field of intelligent parking lot management, and aims to solve the problems that existing unattended parking lot entrance and exit management depends on manpower, abnormity processing is passive, and the misjudgment rate is high. The method is based on an information acquisition and execution layer-edge processing layer-cloud platform three-layer architecture, the core realizes high-precision scene understanding through a multi-algorithm fused visual perception module, multi-modal data weighted fusion is combined with a ground induction coil, a radar and the like, and the misjudgment rate is reduced; a sensing result is converted into an automatic processing action through a configurable intelligent rule engine; and meanwhile, the cloud platform stores passing data and an evidence chain, optimizes an AI model through incremental training and returns the AI model to an edge layer, so that closed-loop evolution is realized.

The invention provides a parking lot license plate detection method and system based on exclusive learning, and belongs to the technical field of computer vision and edge computing. The method comprises the following steps: deploying a lightweight detection main model at each entrance and exit edge device to carry out real-time detection and screen low-confidence difficult case samples; after the sample is uploaded, the central processing end generates a high-quality pseudo label by using a high-performance teacher model, and trains an exclusive student model by using a mixed loss function fusing detection loss, distillation loss and difficult case concentration loss; and finally, calculating a weight difference value and quantizing to generate a lightweight incremental update package, and directionally pushing the lightweight incremental update package to edge equipment to complete non-perception hot update. The system correspondingly comprises an edge processing unit and a central processing unit. According to the method, the problem that a general model cannot adapt to a multi-gateway differentiated scene is solved, unification of personalized accurate optimization and efficient lightweight updating of the model is realized, and the accuracy and reliability of license plate detection in a complex scene are remarkably improved.

The invention discloses an intelligent parking navigation system based on image recognition and the Internet of Things, and relates to the technical field of intelligent parking navigation, the system draws a three-dimensional electronic map of a parking lot, divides the parking lot into monitoring areas, deploys sensors and cameras to collect image data, and transmits the image data to a cloud through the Internet of Things. The intelligent regulation and control model module uses a convolutional neural network CNN to carry out parking space recommendation and path guidance. And the vehicle monitoring module monitors vehicles entering the parking lot in real time, calculates a geometric environment adaptation coefficient and evaluates a traffic risk. And the vehicle guiding analysis module calculates the traffic flow and the parking space idle index, and recommends a proper parking area for the vehicle. The parking space recommendation analysis module evaluates the comfort level of the parking space, ensures the safety of backing and parking, and avoids the risk of traffic jam or traffic accident through strategy adjustment. The system improves the parking efficiency and safety, and optimizes the parking experience.

The invention provides a method and a system for predicting idle parking spaces of a parking lot. The method comprises the steps that ramp curvature parameters extracted from topological structure data of the special-shaped parking lot and historical vehicle turning radius data are fused, and a spatial-temporal topological graph of the special-shaped parking lot is generated; aggregating the parking space occupancy state data of all the special-shaped parking lots and the special-shaped parking lot space-time topological graph through a federal transfer learning framework to obtain target feature extraction model parameters; combining the time change characteristics of the channel flow of the special-shaped parking lot in the spatial-temporal topological graph of all the special-shaped parking lots and the target characteristic extraction model parameters, and generating a dynamic parking space distribution strategy; and mapping the dynamic parking space distribution strategy to a real-time navigation path of the special-shaped parking lot space-time topological graph, so that the to-be-parked vehicle arrives at the idle parking space through the real-time navigation path. According to the invention, the dynamic parking space distribution strategy is generated by fusing the topological structure and historical data of the special-shaped parking lot and real-time navigation is carried out, so that the parking space utilization rate and the parking efficiency are optimized.

The invention provides a multi-mode vehicle charging and parking cooperative management method based on the Internet of Things, and relates to the technical field of intelligent parking. The application steps of the main control system are multi-modal data acquisition and dynamic parking and charging constraint initialization, multi-scale parallel parking and charging model construction and preliminary distribution, multi-scale error feedback and cross-node collaborative evaluation, and adaptive constraint adjustment and asynchronous distributed iterative optimization. Global parking and charging scheme integration, expandability verification, output optimization scheme and industrial application packaging are carried out, multi-mode data such as vehicle electric quantity, position and parking lot state are collected in real time through the Internet of Things, changes of charging and parking demands can be found in time, the problems of congestion and waiting caused by resource allocation lag are effectively avoided, and the service life of a vehicle is prolonged. The real-time performance and efficiency of management are improved, and dynamic parking and charging constraints are generated by adopting a deep reinforcement learning algorithm.

The invention provides a smart city construction system based on big data, and relates to the technical field of smart cities, and the system comprises a traffic data collection module, a transmission and preprocessing module, a flow prediction and analysis module, an intelligent signal optimization module, a parking lot scheduling and induction module, a decision support module and a user service module. The traffic flow prediction and analysis module predicts a traffic state in a set time length in the future through a space-time diagram convolutional network in combination with a seasonal autoregression model; and the intelligent traffic signal optimization module is used for dynamically adjusting signal lamp timing based on a deep reinforcement learning algorithm and realizing intersection linkage through a regional cooperative control algorithm. According to the invention, the space-time diagram convolutional network, the deep reinforcement learning intelligent algorithm, the block chain and the distributed computing technology are fused to construct a multi-source data-driven traffic whole-flow intelligent management system, so that the whole-chain intelligence from real-time sensing and dynamic optimization to cross-platform service is realized; and the collaboration, the prediction accuracy and the service ecological openness of the urban traffic system are obviously improved.

The invention relates to the technical field of parking lot digital management, and discloses a digital twin enabling parking lot digital global management system. According to the system, a global digital twin model of a parking lot is generated, and multi-source sensing data such as parking space states, vehicle identities and environmental parameters are fused; generating a parking space distribution matrix with priorities and time windows in combination with the parking request of the user and the real-time parking space state; according to the parking space two-dimensional code hardware parameters, the digital twin model and the parking space distribution matrix, outputting a vehicle guiding path set with a timestamp; a real-time obstacle avoidance and dynamic adjustment system is constructed to generate a safe driving path set so as to dispatch vehicles; outputting a power distribution control instruction set and updating the digital twinborn model by combining the electric quantity of the energy storage unit, the power distribution network data and the safe driving path set; and finally, system knowledge evolution and end-to-end closed-loop optimization are realized through scheduling execution logs. According to the system, global efficient management of the parking lot is realized, and the parking space utilization, vehicle scheduling and energy utilization levels are improved.

The invention relates to the technical field of parking lot busy degree prediction. The parking lot busy degree prediction method comprises the steps of based on historical parking space number change information, performing feature extraction on the historical parking space number change information through a convolutional neural network (CNN) to obtain local spatial features of parking space changes, performing time sequence modeling on the local spatial features through a recurrent neural network (RNN) to obtain a busy degree prediction result of the parking lot, and obtaining a busy degree prediction result of the parking lot. The method comprises the steps of obtaining long-term trend characteristics of parking space changes, carrying out time sequence mode clustering on historical change information of the number of parking spaces by adopting a hybrid clustering method according to the long-term trend characteristics to obtain a time sequence mode of parking space change rules of a parking lot, and obtaining parking space change rules of the parking lot by utilizing a BallTree multi-stage similarity matching method according to static characteristic information of the parking lot and the time sequence mode. And according to the busy degree information of the similar parking lot, predicting the number of unoccupied parking spaces and the busy degree of the parking lot with the unknown information at the target moment. The method has the effect of predicting the busy degree of the parking lot.

The invention provides a digital intelligent parking space intelligent parking guiding method, which comprises the following steps: an information acquisition step: acquiring parking space information in a parking lot and vehicle information at the entrance of the parking lot, applying for connecting a vehicle interaction module, if the vehicle allows interaction, connecting through the interaction module, and if the vehicle does not allow interaction, connecting through the interaction module; if yes, signal transmission is carried out through a guide screen in the parking lot; a parking space matching step: according to the vehicle information and the parking space information, corresponding parking information is acquired through a path planning strategy, and the parking information comprises a parking position and an optimal parking route; an interaction guiding step: when the vehicle allows interaction, the vehicle is used for receiving parking information; in the traditional guiding step, when the vehicle does not allow interaction, the position of the vehicle in the parking lot is obtained, the vehicle traveling path is judged, the nearest guiding screen on the vehicle traveling path is obtained, the vehicle traveling direction is indicated on the guiding screen, and parking space information is recommended on the guiding screen.

The present invention relates to the technical field of transportation demand management and parking pricing, and specifically to a parking reservation method in the urban central business district based on dynamic pricing, comprising the following steps, S1, traffic data acquisition, S2, key value calibration, S3, perceived utility calculation, S4, parking probability measurement, and S5, pricing strategy realization. The method of reserving parking spaces in the CBD of this city is aimed at addressing the serious imbalance between the supply and demand of parking resources. To alleviate the problem of parking difficulties in urban CBD areas and appropriately increase the revenue of parking lots by dynamically adjusting parking costs. At the same time, this method greatly reduces the cruising time of vehicles when searching for parking spaces, effectively reduces fuel waste and exhaust emissions during cruising, and largely avoids traffic congestion caused by the convergence of cruising vehicles and through traffic.

The invention discloses a parking lot dynamic charging task distribution method for a multi-robot system, and relates to the technical field of parking lot charging task distribution, and the method comprises the following steps: generating a path interference relation matrix between charging task paths based on the charging achievable degree and the path passing state of each robot, determining a task suppression coefficient for path conflict judgment; according to the determined task suppression coefficient and path interference relation matrix, target distribution and path sequence rearrangement of the charging piles are carried out, and a passing priority sequence between tasks is established; and predicting a change interval of path passing resistance based on the historical path state and the real-time passing data, and updating the effective remaining time of each robot to correct the task priority. According to the method, the problem of charging priority failure of multiple robots under the condition of path congestion is solved, collaborative optimization of task allocation and path scheduling is realized, and the system stability and the task completion rate are improved.

The invention relates to the technical field of parking resource scheduling, in particular to an intelligent parking resource scheduling system based on multi-source data analysis, which realizes full-scale digital mapping from vehicle individual behaviors and parking lot flow fields to a regional traffic network by constructing microscopic-mesoscopic-macroscopic three-level parking twin bodies and fusing dynamic and static multi-source data. Through scale conversion and data interaction among the three-level model, dynamic characteristics of parking resources in space and time dimensions are accurately captured, a high-fidelity and fine-grained digital twinborn base is provided for scheduling decision making, splitting of local optimization and global collaboration in traditional scheduling is broken through, the accuracy and foresight of resource allocation are supported, and the scheduling efficiency is improved. Based on dynamic construction of an algorithm strategy library and twinborn simulation evaluation, the scheme takes a multi-dimensional scheduling value as a core to realize closed-loop optimization of algorithm combination-effect rehearsal-strategy optimization-dynamic adjustment.

The invention discloses a parking lot virtual green wave guiding method and related equipment. The core is to construct a space-time resource map, plan a path according to the space-time resource map, reserve a time window to form a virtual green wave band, issue an instruction to a vehicle terminal and an intelligent barrier gate, monitor vehicle position deviation, and trigger local re-planning if a threshold value is exceeded. According to the scheme, the defects in the prior art are accurately overcome, global space-time resource overall planning is achieved through a space-time resource map, an exclusive time window is reserved for vehicles, multi-vehicle path conflicts are eliminated from the source, and the defects of lack of global view and active scheduling are overcome; static road network navigation is replaced by a space and time coordinated virtual green wave band, vehicles are actively guided to pass orderly, microscopic traffic congestion is effectively solved, and the in-field passing efficiency is greatly improved; through a real-time monitoring and local re-planning mechanism, emergency situations such as vehicle faults can be rapidly handled, congestion diffusion is avoided, traffic flow stability is guaranteed, and finally seamless and non-stop passing of the vehicle from an entrance to a parking space is achieved.

The invention provides an intelligent parking guidance system based on voice interaction and intelligent matching. The intelligent parking guidance system comprises a voice interaction recognition module, an intelligent video module, a path planning module and a parking space scheduling and management module. Wherein the voice interaction recognition module is deployed in an entrance area of a parking lot, interacts with a driver and recognizes a parking position demand; the intelligent video module is arranged at a key node in a parking lot, identifies a vehicle, constructs a vehicle movement track, and analyzes and obtains the overall traffic flow information of the parking lot. The path planning module receives information provided by the voice interaction recognition module and the intelligent video module, carries out path planning, and issues the path planning to the parking space scheduling and management module. And the parking space scheduling and management module is distributed in the parking lot and guides nearby vehicles according to the received route plan.