41results about How to "Improve traffic efficiency" patented technology

This invention discloses a method and terminal for intelligent coordinated control of traffic lights. The method includes: upon receiving a request for passage from an intelligent driving vehicle at a target intersection, real-time collection of pedestrian passage requests, traffic conditions in conflicting directions, and traffic conditions in the target direction; determining whether to trigger a constant green strategy based on the traffic conditions in the conflicting directions and the pedestrian passage request; if not triggered, calculating the next cycle phase sequence and duration scheme of the traffic lights using a signal control algorithm based on the intelligent vehicle passage request, the traffic conditions in the target direction, the traffic conditions in conflicting directions, the pedestrian passage request, and the default timing strategy; adjusting the traffic lights at the target intersection according to the next cycle phase sequence and duration scheme; and adjusting the traffic lights at the next preset intersection according to the driving route in the intelligent vehicle passage request and the traffic lights at the target intersection to form a green wave segment. This method can effectively improve intersection traffic efficiency and meet the passage needs of intelligent driving vehicles.

The utility model relates to a kind of offshore wind power platform anti-collision device, including foundation platform and surrounding multiple foundation columns, and there is protective ring frame outside foundation column, which is composed of large and small arc frames with buffer protection parts, large arc frame is fixed in vice foundation column, and notch is arranged at the position of main foundation column;Small arc frame is movably connected to main foundation column and located in the notch, and the notch is opened and closed by driving device;Protective ring frame is composed of large and small arc frames, under normal condition, small arc frame closes the notch, so that protective ring frame forms complete annular structure, can be all-around around foundation column, intercepts impact object from all directions;When personnel need to go up and down platform through the ladder of main foundation column, small arc frame is driven to move by driving device to open the notch, and the ladder position is directly exposed, without bypassing anti-collision structure, significantly improve traffic efficiency and safety, especially suitable for emergency repair or emergency evacuation scene.

The utility model discloses a wharf portal truck identification system, include: set up on the safety island of each wharf portal both sides low frequency activator and camera device, set up on each wharf portal top microwave active RFID read-write ware, set up in control room host computer, low frequency activator activates the microwave active label of truck license plate built -in, makes it to empty send data packet, microwave active RFID read-write ware receives data packet, camera device gathers image data, host computer receives data packet, truck's image data, carries out comprehensive analysis, identifies truck information, the portal that truck went in and truck advancing direction to, and verifies truck information, the utility model provides a wharf portal truck identification system, has combined RFID transmission technology, low frequency activation technology and image recognition technology, carries out accurate identification and check to the container truck information and the direction of passage of wharf portal, can promote the efficiency of portal traffic, ensures the effective supervision of port wharf to truck vehicle.

This invention provides a method, device, terminal, and storage medium for bus priority control at multiple intersections. The method includes: acquiring the approach lane status of each approach lane at each intersection within a target area at the current time, and the traffic light prediction model for each intersection; determining the target bus closest to its current intersection on each approach lane, and acquiring the bus status and bus prediction model for the target bus at the current time; predicting the traffic light phase status of each intersection at the next time based on the approach lane status, bus status, and traffic light prediction model; and predicting the bus acceleration corresponding to each target bus at the next time based on the approach lane status, bus status, and bus prediction model. This application can adjust the traffic light phase status and bus acceleration using traffic light prediction models and bus prediction models in a multi-intersection environment, thereby improving bus traffic efficiency.

This utility model discloses a toll station card dispensing machine, comprising: a chassis with a built-in controller and an opening on one side; an aerial imaging device installed inside the chassis, comprising a housing, an imaging lens, and a display screen, both located within the chassis, with the imaging lens facing the opening; signal light emitted from the display screen is projected onto the imaging lens, and the signal light passes through the imaging lens to form a real image in the air that is mirror-symmetrical to the display screen; and a card receiving and dispensing device installed on the side of the chassis facing the lane, communicating with the aerial imaging device, containing a card, and positioned within the chassis but adapted to carry the card out of the chassis. The toll station card dispensing machine according to this utility model has advantages such as improving vehicle traffic efficiency, alleviating traffic pressure, and increasing user safety.

This utility model discloses an elevator call device based on Time-of-Flight (ToF) technology, belonging to the field of elevator control equipment technology. It includes a housing with a sensor window extending through its front end and a projection window extending through its front end near the upper edge. This utility model, through the cooperation of a projection display module and a ToF sensor module, fundamentally eliminates direct contact between the user and the device surface using non-contact ToF technology. Compared to traditional contact-based elevator call devices, it effectively reduces the transmission routes of bacteria and viruses, significantly lowering the risk of cross-infection between patients. In places with high population mobility, it provides users with a safer and healthier elevator environment, meeting the growing demand for public health and safety.

This invention relates to the technical fields of tunnel safety control, intelligent transportation, vehicle-road cooperation, and tunnel safety early warning. Specifically, it relates to a tunnel active safety control system and method based on vehicle-road cooperation. Key technical points include: a multi-source data fusion module: integrating data from roadside equipment (including radar, cameras, and fiber optic sensors) and vehicle-mounted terminals to construct a four-dimensional perception network of people, vehicles, roads, and the environment; a dynamic risk assessment module: quantifying the probability of an accident (P) and collision energy loss (E) based on an equivalent traffic conflict number (ECN) model to achieve risk-level early warning; and a vehicle-road cooperative intervention module: triggering early warning and control strategies from both the roadside and vehicle perspectives through two-way communication between roadside smart guidance signs, information boards, and vehicle-mounted terminals. This invention improves the ability to respond to tunnel risks.

The present application relates to a kind of port unmanned truck intersection cooperative traffic method, system and medium, the method comprises: L1.unmanned truck vehicle sequence executes port operation task, through intersection, based on intersection road testing equipment, vehicle arrival intersection time series data information and the number data information of vehicle are acquired in real time, and according to vehicle number data information, the task trajectory data information of vehicle is obtained;L2.based on the vehicle arrival intersection time series data information and the number data information of vehicle, with the number data information of vehicle as the basis, time series priority algorithm is used to preliminary optimization vehicle traffic sequence.The present application not only determines the traffic priority of all trucks at the intersection to be passed in advance, lets part of the trucks wait, part of the trucks go first, but also can avoid the deadlock problem caused by multiple vehicles entering the intersection at the same time, improve the traffic efficiency, and further improve the work efficiency, save labor cost.

This utility model relates to the field of controller technology, specifically to a novel highway lane controller, comprising a housing and a main control module, an I / O control module, a data exchange and transmission module, a sub-control communication module, and a power supply module disposed within the housing. Through the quick-installation structure of the housing and the modular design of the internal components, it overcomes the shortcomings of cumbersome maintenance found in general-purpose industrial control computers, making maintenance more convenient and faster, and reducing maintenance costs. By setting up interconnected main control modules, I / O control modules, data exchange and transmission modules, and sub-control communication modules, it can effectively meet on-site requirements, enabling flexible configuration and control according to the actual conditions of the lanes, improving vehicle traffic efficiency, and providing more stable performance. With a high degree of integration, it offers better cost-effectiveness than general-purpose industrial control computers, reducing highway operating costs.

The application provides a signal timing and networked automatic driving vehicle speed hierarchical collaborative control method based on reinforcement learning, and relates to the technical field of intelligent traffic control and vehicle-road collaborative control, and comprises the following steps: obtaining the stop-and-drive vehicle state information on the import lane served by each phase at each signal cycle boundary, and generating a reference timing scheme of the next cycle by a cycle timing intelligent agent based on the stop-and-drive vehicle state information; obtaining a refined discharge window; and outputting a continuous longitudinal acceleration control instruction to a target networked automatic driving vehicle by a networked automatic driving vehicle speed intelligent agent according to the refined discharge window, so that the arrival time of the target networked automatic driving vehicle matches the discharge window, and the collaborative control of traffic signal timing and vehicle speed is realized.

The application provides a three-dimensional modeling method and system based on cooperation of a mobile phone and a UAV in shooting, comprising a data acquisition module, a data transmission module, a data processing center and a model display and analysis module; the data acquisition module adopts an acquisition strategy configuration logic based on a traffic accident type and combined with an accident scene scale, and is used for determining a combination mode of acquisition equipment under different traffic accident scenes; the data acquisition module comprises a mobile phone shooting unit used for close-range data acquisition of a small-range traffic accident scene and a UAV shooting unit used for data acquisition of a large-range traffic accident. Through the cooperative acquisition mode of the mobile phone and the UAV and combined with a three-dimensional modeling processing flow, macro scene information and micro detail information can be simultaneously acquired at an accident scene, the acquisition and modeling of key elements of the accident scene can be completed in a short time, and the application is favorable for shortening the occupation time of the accident scene and improving traffic relief efficiency.

This application relates to a navigation route planning method, apparatus, electronic device, and storage medium. The navigation route planning method first determines a preliminary target road segment, then obtains the historical road condition scores of the target vehicle when it previously traveled the target road segment. The target vehicle includes the vehicle itself and / or other vehicles traveling on the target road segment. The historical road condition score is obtained by calculating the weighted variance of the vertical acceleration of the sampling points of the target road segment, which can effectively suppress the scoring inaccuracy caused by single-point anomalies. Next, based on the vehicle type threshold corresponding to the vehicle itself and the historical road condition score, it determines whether to travel on or detour around the target road segment. This can effectively determine whether the micro road conditions of the preliminary target road segment are suitable for the vehicle to travel on, providing users with better navigation routes, reducing vehicle damage, and improving traffic efficiency.

This invention relates to an AGV task allocation and path planning system and method, specifically a multi-AGV task collaborative time-series allocation and path planning system and method. It addresses the problems of inflexible deployment, high costs, and inability to accurately trigger tasks based on map point arrivals in complex time-series task collaboration among multiple AGVs due to reliance on a central server. The invention includes a scheduling decision module, a status management module, a task distribution module, and a path planning service module. The status management module continuously collects real-time status and location information of the AGVs. The task distribution module sends task instructions or scheduling instructions generated by the scheduling decision module to the corresponding target AGVs. Through establishing a map network and task flow timeline, path planning, status monitoring, task issuance and execution, and fault tolerance handling steps, automated operation of multiple AGVs is achieved.

This invention discloses a boundary signal control method based on traffic elasticity theory, belonging to the fields of network elasticity science and urban traffic management. The method includes: acquiring the urban traffic network topology, traffic flow information, and signal control data; establishing a capacity multigraph of the traffic network based on its topology, defining a finite set of roads, and dividing it into multiple traffic sub-regions; constructing boundary signal phase models for the boundary regions of each traffic sub-region, and constructing a global signal phase matrix based on the signal phases at each node, thus establishing a control signal set; establishing elasticity state curves for each traffic sub-region and calculating the elasticity values ​​of the traffic sub-regions; constructing an incremental model of the road network traffic flow system based on traffic flow information and elasticity values, establishing an output vector prediction expression, establishing an error prediction model, and designing a model predictive controller. This invention can improve the traffic efficiency of the road network and solve the problem of existing signal control schemes being insufficiently timely and effective.

The application provides a kind of city granularity-based vehicle transfer path calculation method, system and terminal machine, belongs to the field of vehicle path planning, constructs adjacent city data network;Vehicle path data network is constructed;According to the input condition, the shortest path between nodes is calculated using Dijkstra algorithm, and the strategy of greedy algorithm is adopted, the adjacent nodes of the vertex closest to the starting point and not visited are traversed each time, until the end point is expanded, to obtain the hottest route between any two nodes or multiple nodes.The method is based on the actual vehicle operating conditions, from the perspective of city transfer, analyzes the transfer trend and heat between cities, and provides an effective method for finding popular routes, with strong practical value.

The application discloses a vehicle early warning method, device, equipment and medium. The method comprises the following steps: when a vehicle to be warned enters a specified area, acquiring vehicle position information of the vehicle to be warned, vehicle state information of surrounding vehicles, and preset area level information of the specified area; determining target vehicles satisfying early warning conditions and corresponding early warning event intensity information according to the preset area level information, the vehicle position information and the vehicle state information; and issuing the early warning event intensity information to the vehicle to be warned. The area level of the vehicle to be warned and the surrounding vehicles satisfying the early warning conditions is divided according to the preset area level information, and then the early warning event intensity information is determined according to the area level at the division position, so that the vehicle to be warned is warned with different early warning intensities. Real-time perception and prediction of abnormal driving behaviors are realized, and differentiated information prompting and early warning are realized. The safety risk near an expressway exit ramp is reduced, and the traffic efficiency is improved.

This invention proposes a method for updating lane-level dynamic information in high-precision maps based on crowdsourced data. The method includes: collecting trajectory information and road image data from multiple sources, with a high-precision map embedded within; constructing a single-stage line-anchor detection model using a convolutional neural network; performing lane line perception detection on the road image data based on the single-stage line-anchor detection model; outputting lane line perception information; using an image alignment compensation algorithm to register and fuse road image data from consecutive frames during vehicle movement, and inputting this data into a target detection model for recognition, outputting traffic cone perception information; and projecting the lane line perception information and traffic cone perception information onto the high-precision map's geographic coordinate system using camera parameters. This method effectively suppresses missed and false detections in single-vehicle perception by combining low-cost crowdsourced data with a multi-vehicle evidence fusion mechanism, improving the accuracy and real-time performance of lane-level dynamic information updates, and meeting the high-precision requirements of autonomous driving for high-precision maps.

The utility model provides a kind of intelligent epidemic prevention lock, including shell, lock tongue, unlocking drive mechanism and controller;The lock tongue is installed on shell, and can be switched between unlocking position and locking position;The unlocking drive mechanism is used to switch the lock tongue to unlocking position;Health code recognizer and temperature measurement sensor are equipped on the shell, and the health code recognizer and temperature measurement sensor are electrically connected with the controller;The intelligent epidemic prevention lock of the utility model integrates health code identification, temperature measurement, personnel registration and access control function together, effectively improves the quality and efficiency of epidemic prevention and control.

The utility model relates to a sliding and telescopic linear door with composite transmission structure, belonging to the technical field of gate. The linear door is composed of fixed vertical column frame, starting fixed door row and at least two mobile door rows arranged in sequence. The door row grid of door row is fixedly connected with the grid support frame, and the door row grid of mobile door row can pass through the hollow part of the grid support frame of the front door row. The transmission structure adopts composite mode, and the starting fixed door row and the adjacent first mobile door row are moved through the driving device matched with the meshing of rack and driving gear. The driving devices of the upper and lower half ring clamping devices are followed through the traction rope ring between each mobile door row, and the same direction equidistant synchronous movement is realized. The utility model has the advantages of saving space, stable operation, convenient maintenance, high safety and the like, effectively improves the stability and reliability of door body operation, and reduces the use cost.

The application discloses a method and device for identifying road congestion state in real time, equipment and storage medium. Including: obtaining trajectory data corresponding to an idling vehicle equipped with a front image device, filtering a target vehicle driving on a road based on the trajectory data; extracting the front view image of the target vehicle, inputting the front view image into a pre-trained traffic object recognition model, and outputting the traffic object recognition result in the image; based on the traffic object recognition result, filtering an initial congestion image and automatically labeling the traffic light category corresponding to the initial congestion image; based on the traffic light category, inputting the initial congestion image into the corresponding congestion recognition model, and outputting the congestion level determination result of the current vehicle. Through image data recognition and congestion level recognition, the application accurately determines the congestion level, improves the accuracy and real-time performance of congestion recognition, provides strong support for traffic management and optimization, and improves road traffic efficiency.

The application discloses a vehicle passing method and system, the method comprises: the vehicle responds to the guest parking starting instruction, and the vehicle self-inspects the driving state, initiates the passing request through the back cloud, and submits the verification information, receives and stores the passing token issued by the cloud. When the vehicle passes to the first distance of the gate, the pre-communication is activated, the gate is connected, the vehicle position, driving intention and token summary are transmitted, and the environment state confirmation information of the gate is received. When passing to the second distance, the target communication channel is determined by evaluating the Bluetooth communication quality, and the passing strategy is determined by comprehensively evaluating the gate and the surrounding environment. The passing request with the token is sent, the vehicle is controlled to pass at a safe speed after receiving the gate opening confirmation, and the gate and the surrounding environment are monitored throughout the passing. After the vehicle completely passes, the completion confirmation is sent to the gate and the cloud, the token is released, and the communication connection is closed. The technical scheme provided by the application can improve the passing efficiency of the vehicle in the guest parking scene.

This invention provides a method and system for dynamic control of urban traffic signals based on AI reinforcement learning. By using a pre-set learning model, this invention can generate instantaneous occupancy prediction coefficients and instantaneous dynamic threshold ranges corresponding to instantaneous detection information. It then determines the instantaneous occupancy level corresponding to the instantaneous detection information and finally selects a matching dynamic signal control strategy for signal control. This achieves adaptive adjustment of the dynamic threshold range based on real-time traffic conditions, replacing fixed threshold settings. This significantly improves the generalization ability and robustness of this method in complex traffic scenarios and avoids the dependence of static threshold methods on a single data distribution.

This application proposes a cross-traffic induction control method, electronic device, and computer-readable storage medium, including: acquiring traffic flow data of a target intersection at the current moment and the corresponding traffic light operation data; determining the comprehensive traffic demand of each light group in the target phase based on the traffic flow data; determining the comprehensive traffic demand of the target light group by combining the sensing data collected by the sensing devices deployed in the same direction as the target light group and the sensing data collected by the sensing devices deployed in the opposite direction; determining the gradient vehicle number threshold corresponding to each light group in the target phase based on the running time of the target phase and the preset correspondence between each light group in the target phase and the vehicle number threshold for different running time intervals; and generating control instructions for controlling the traffic lights at the target intersection based on the operation data, the comprehensive traffic demand of each light group in the target phase, and the gradient vehicle number threshold.

This utility model discloses an automatic temperature-measuring and disinfection pedestrian passage, including a support base, a passage door connected to the surface of the support base, a disinfection box installed on one side of the passage door, a conveying pipe installed inside the disinfection box, one end of the conveying pipe passing through the disinfection box and connecting to the support pipe, an automatic disinfection mechanism installed on one side of the support pipe, a support frame connected to one side of the passage door, and an infrared camera rotatably mounted on one side of the support frame. This utility model has the following advantages: through the cooperation of various structures within the automatic disinfection mechanism, when a pedestrian passes through the passage, the pedestrian's own weight provides power to the automatic disinfection mechanism, thereby automatically spraying disinfectant from the top of the passage door. It can automatically disinfect passing pedestrians without the need for additional sensors and actuators, and its structure is simple and low-cost.

This application belongs to the field of elevator door control technology, specifically an adaptive anti-pinch control system and method for elevator door operators, including a sensing layer, a control layer, and an execution layer. The sensing layer integrates infrared sensors, ultrasonic sensors, pressure sensors, and current sensors to collect information on obstacles near the door and the load information of the door operator motor. The control layer uses an Arduino microcontroller as its core, paired with a dedicated BLDC driver module, to receive and analyze the data from the sensing layer and issue control commands. The execution layer consists of a brushless DC motor and a door drive mechanism, controlling the opening and closing of the door according to the commands from the control layer. This solution addresses the problem that traditional systems lack real-time monitoring and fault warning functions for the door operator's operating status, making it difficult to detect potential safety hazards in a timely manner, thus increasing maintenance costs and safety risks.

The application discloses an intelligent home control system and a control method, the intelligent home control system comprises a core control unit, an intelligent central control screen, a local artificial intelligence processing module, a control signal expansion module and an Internet of Things gateway, the core control unit is integrated with a building intercom communication interface and an elevator control interface, the building intercom communication interface is used for being communicatively connected with a building video intercom system, the elevator control interface is used for being communicatively connected with an elevator control system, the elevator control interface is also used for sending an elevator dispatching instruction to the elevator control system and receiving an elevator operation state, the core control unit communicates with a plurality of intelligent home devices through a power line carrier Internet of Things communication network, and the intelligent central control screen is integrated with a building video intercom interface and an elevator control interface. The application deeply integrates the intelligent home system with the building video intercom and the elevator control system at the software and interface levels, and can display an elevator state and make a reservation for calling an elevator in real time; when a visitor opens a door through intercom, an elevator can be automatically dispatched in linkage, so that the traffic efficiency and experience are greatly improved.

The invention discloses an urban traffic flow prediction and signal optimization method based on a space-time diagram neural network. The method specifically comprises the following steps: S1, constructing an urban road network topological graph; s2, multi-source heterogeneous data fusion and feature extraction; s3, establishing a space-time diagram neural network prediction model; s4, a signal optimization algorithm based on a prediction result; s5, model training and online strategy updating; s6, integration and real-time reasoning optimization are carried out; according to the method, through constructing topological graph representation of an urban road network, fusing multi-source heterogeneous traffic data and adopting a deep learning architecture combining a graph convolutional network and a time sequence prediction model, accurate short-term prediction of traffic flows of intersections and road sections is realized, and a dynamic signal optimization algorithm is designed based on a prediction result, so that the traffic flow prediction efficiency is improved. The adaptive adjustment of traffic signal timing is realized, so that the traffic efficiency of a road network is improved, and the vehicle delay is reduced.

The present invention provides a multi-topography integrated path planning method incorporating road factors. Based on the image information of the target area, at least one terrain feature included in the target area is determined, and a grid map corresponding to the target area is constructed. In response to a path search instruction input for indicating searching for a driving path between a starting point and an ending point in the target area, at least one path is determined in the grid map. The sum of the values of the cost function corresponding to each grid passed by each path is obtained. The cost function is associated with the slope value, type of the terrain feature included in the corresponding grid, the speed of a preset vehicle passing through the terrain feature included in the corresponding grid, and the Euclidean distance between the starting point and the ending point. The path corresponding to the minimum value of the sum is determined as the target path. Determining the path corresponding to the target path as the driving path in the target area can improve the passing efficiency of the user.

The application provides a heavy-load vehicle ecological driving control method for multiple-red-green-light intersections considering the influence of preceding vehicles, comprising the following steps: S1. obtaining the start point and end point position information of the current heavy-load vehicle and the traffic information between the start point and the end point of the current heavy-load vehicle, and determining the feasible path between the start point and the end point; S2. determining the global optimal path from the feasible path, and determining the remaining paths as suboptimal passing paths; S3. establishing a control strategy, including a first control strategy, a second control strategy and a third control strategy; S4. determining the maximum passing time and the minimum passing time of the current heavy-load vehicle passing through the kth red-green-light intersection between the start point and the end point, and predicting the green light interval of the front intersection in the feasible path of the heavy-load vehicle based on the maximum passing time and the minimum passing time; S5. determining control strategy determination parameters, including the real-time distance between vehicles, the safety distance between vehicles, the distance between the vehicle and the red-light intersection in the kth road section, the distance between the end point of the kth road section and the red-light intersection, and the average speed of the heavy-load vehicle on the distance already traveled in the kth road section; and S6. determining the control strategy of the current heavy-load vehicle according to the control strategy determination parameters.