12 results about "Vehicle search" patented technology

The application belongs to the field of sea unmanned vehicle search, and particularly discloses a multi-unmanned vehicle target search algorithm based on ant colony optimization. The algorithm mainly uses the ant colony optimization method, so that the unmanned vehicle cluster can search for the lost target in the shortest possible time, and ensure the optimal search trajectory. The application updates the target probability graph composite target moving route based on the Markov prediction model, guides the unmanned vehicle cluster to move to the area with high target existence probability for target search task, which not only can guarantee the best solution, but also can accelerate the convergence speed of the algorithm and improve the efficiency of the target search task. Compared with other algorithms, the target search algorithm based on ant colony optimization can effectively avoid obstacles for the unmanned vehicle cluster, and ensure the safety of the unmanned vehicle cluster in the search process. In addition, when the multi-unmanned vehicle cooperatively searches for unknown dynamic targets, it has the advantages of information sharing and regional search division, can expand the search range and shorten the time to search for the target.

1. The name of the design product: airborne communication load and its main body. 2. The use of the design product: the whole and part of the design product are used for air relay communication of 400MHz-510MHz ground communication terminal, air data collection of ground sensor, and unmanned aerial vehicle search and rescue scene. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design. 6. Other circumstances that need to be explained: design 2 and design 3 are partial designs, and the dashed line indicates the part not claimed.

This invention provides a reverse vehicle search method, apparatus, device, and storage medium, comprising: acquiring a target person identifier and target vehicle information of a target vehicle; acquiring target image data collected by multiple cameras in a designated area; the multiple cameras are distributed along a driving lane in the designated area, and parking spaces are set around the driving lane; based on the target vehicle information and the target person identifier, performing target tracking and trajectory fitting processing on the target image data of each camera to determine a first driving trajectory corresponding to the target vehicle and a second movement trajectory corresponding to the user; performing trajectory collision analysis on the first driving trajectory and the second movement trajectory to determine the target location where the target vehicle is parked, and determining a reverse vehicle search path based on the user's current location and the target location. Using this invention can reduce the hardware cost of reverse vehicle search.

The application provides a kind of based on the cooperative search method and system of distributed unmanned aerial vehicle cluster of evolution game theory, the method comprises: first, the expected return of each unmanned aerial vehicle search strategy is initially predicted by Monte Carlo method, the relationship between strategy and expected return is initially determined, then enter the strategy optimization stage based on evolution game, that is, with the search process, each unmanned aerial vehicle constantly updates expected return according to certain rules, the strategy evaluation value of the current strategy of each unmanned aerial vehicle in subnet is calculated, and each unmanned aerial vehicle optimizes and updates strategy based on evolution game mechanism according to strategy evaluation value, wherein the principle of strategy optimization and update is that excellent strategy will be accepted by more unmanned aerial vehicles, and poor strategy will be gradually eliminated. Through this dynamic evolution process, the unmanned aerial vehicle cluster can adaptively select the optimal search strategy in the connected subnet, so as to realize efficient cooperation of the cluster under distributed architecture, and significantly improve the efficiency of cooperative search.

The disclosure provides an artificial intelligence-based vehicle search method and device and electronic equipment, relates to the technical field of artificial intelligence, in particular to the technical fields of natural language processing, intelligent transportation, computer vision, intelligent search, deep learning, image recognition and video analysis, and can be applied in smart city, city governance and public security emergency scenarios. The specific implementation scheme is as follows: determining license plate information and a feature vector of a to-be-searched vehicle picture; determining a first recall result based on the feature vector and a second recall result based on the license plate information; determining a picture recall result according to the first recall result and the second recall result; and determining a picture search result of the to-be-searched vehicle picture according to the picture recall result. In this way, the picture search result of the to-be-searched vehicle picture is determined by combining the license plate information and the feature vector of the to-be-searched vehicle picture, thereby expanding the number of pictures in the picture search result and improving the search efficiency and search accuracy.

The application discloses a kind of unmanned aerial vehicle based on boundary and heat source exploration and its search and rescue method, equipment and medium, it is related to unmanned aerial vehicle search and rescue technical field, the method comprises: based on the boundary set generated to guide unmanned aerial vehicle to carry out boundary elimination, and real-time perception whether there is heat source;If there is heat source, adjust the exploration strategy of unmanned aerial vehicle and explore heat source preferentially, and obtain the image data of heat source to determine whether heat source is search and rescue target;If so, end search and rescue task;If not, continue to guide unmanned aerial vehicle to search by boundary set, until search and rescue task ends;If there is no heat source, construct the ATSP cost matrix of unmanned aerial vehicle current viewpoint to boundary viewpoint and obtain multi-viewpoint set;Using Minimum Snap trajectory optimization algorithm, generate search and rescue path based on multi-viewpoint set, and complete search and rescue task based on the search and rescue path.The application can complete search and rescue task faster and more quickly in limited environment.

The application discloses a kind of unmanned aerial vehicle cross-layer cooperative decision method and system for disaster relief search, it is related to unmanned aerial vehicle search and rescue and communication cooperation field.The method comprises: obtaining disaster area task area information, target information to be searched, environmental constraint information and unmanned aerial vehicle cluster initial deployment information, constructs disaster relief search task model;Collect each unmanned aerial vehicle basic operating state data, generate basic search control scheme;Collect the channel state information corresponding to target position, received signal strength indication and link quality parameter, with unmanned aerial vehicle maneuvering state cross-layer fusion, generate replacement maneuvering decision;To candidate maneuvering decision carry out micro signal gain discrimination, change trend confirmation and maneuvering inhibition processing, output stable control decision;According to stable control decision, execute search flight, communication relay and target information back, and carry out cyclic update.The application can be used for target position communication coverage adjustment and cluster maneuvering control.

The application relates to the technical field of aerosol, and particularly discloses a car search blocking visual jetting agent and a preparation method thereof. In the car search blocking visual jetting agent, the preparation raw materials of the car search blocking visual jetting agent include acrylic ester copolymer, modified carbon black powder, thickening agent, solvent, first propellant and second propellant; the preparation raw materials of the acrylic ester copolymer include long-chain alkyl acrylate, acrylamide and 2-hydroxyethyl methacrylate phosphate, and the mass ratio of the long-chain alkyl acrylate, the acrylamide and the 2-hydroxyethyl methacrylate phosphate is (40-48):(3-5):(2-4). After jetting, the car search blocking visual jetting agent can form effective shielding in the area of the front windshield within 3 seconds, can improve the adhesion of the blocking visual jetting agent, and can ensure the durability of the visual suppression effect.

The application relates to the technical field of intelligent transportation and Internet of Vehicles, and discloses a guided intelligent vehicle searching method and system. The method comprises the following steps: receiving a service calling request for triggering a callable service in a first vehicle and calling an external service to remotely control the vehicle to issue a response action, the service calling request is correspondingly issued by a cloud platform when the cloud platform receives a vehicle searching request sent by a mobile terminal, the vehicle searching request is used for searching a second vehicle, the first vehicle is a vehicle parked near a path to the second vehicle and identified by the cloud platform, the first vehicle and the second vehicle register vehicle information, a parking position and a callable service in the cloud platform when parking, and authorize the cloud platform to call the callable service; and the first vehicle executes a response action in the callable service in response to the service calling request. The application dynamically schedules authorized vehicles in a parking lot as temporary guide nodes, and realizes cooperative intelligent vehicle searching based on a real-time path.

The application discloses a train hook position positioning method and device and a storage medium, relates to the technical field of train overturning, and has the technical scheme as follows: the positioning method comprises the following steps: acquiring a first detection signal and a last detection signal in the process that a positioning vehicle drags a target train to a stop position; determining the positions of the first detection signal and the last detection signal according to the first detection signal and the last detection signal; determining the middle position of the train hook according to the positions of the first detection signal and the last detection signal; determining the target position at which the positioning vehicle stops searching for the hook according to the middle position; controlling the positioning vehicle to walk according to the target position, so as to obtain the position of the positioning vehicle after walking; and judging whether the position of the positioning vehicle is in a position range in which arm operation is allowed to be performed. Through the positioning method, the efficiency of the positioning vehicle searching for the hook and the positioning accuracy of the train hook can be improved, the positioning vehicle can automatically adjust the searching position of the hook, manual intervention is reduced, automation is improved, and the operation efficiency is improved.

This utility model discloses a smart parking vehicle locator, which includes a linear track component located below the ceiling of the parking space and a vehicle locator service terminal located at the exit of the parking lot elevator. The linear track component includes a linear suspended rail fixed to the ceiling above the parking space, with an electrically controlled slide rail inside. An electrically controlled slider is slidably connected to the slide rail, and a bracket is connected to the bottom of the slider. A license plate and parking space camera is fixed to the bottom of the bracket and consists of a servo telescopic rod, a telescopic shaft, and a spherical camera. An LED supplementary light is installed on the top of the spherical camera. The linear suspended rail is arranged horizontally, and its length can span multiple parking spaces, facilitating the camera to capture license plate numbers and parking space numbers. The spherical camera can rotate 360 ​​degrees to capture license plates of vehicles that are not parked correctly. After the user inputs the parking space number or license plate number, the information captured by the camera is processed, and the terminal provides vehicle locator guidance.

The application discloses a car searching method, device, system, electronic equipment and storage medium. The car searching method is applied to a wearable device integrated with a first V2X module, and includes the following steps: when starting to search for a car, analyzing BSM information sent by a target vehicle through the first V2X module to obtain position information of the target vehicle, wherein the BSM information is sent by the target vehicle through a second V2X module integrated on the target vehicle after parking in a parking lot; obtaining real-time position information of the wearable device during the car searching process; obtaining real-time relative position information of the target vehicle relative to the wearable device based on the position information of the target vehicle and the real-time position information of the wearable device; and generating a car searching route for searching for the car based on the real-time relative position information, the real-time position information of the wearable device and a map of the parking lot that has been obtained. Through implementation of the application, intelligent car searching is realized, the user does not need to remember by himself, and the car searching efficiency is improved.