9 results about "Loop detector" patented technology

The invention discloses a deep reinforcement learning-based cooperative control method for an expressway confluence area, and the method comprises the steps: building a LiikeSim-Python joint simulation environment, and setting a coil detector in the simulation environment to obtain the traffic flow data of the upstream and downstream of the expressway confluence area; an EM algorithm based on Gaussian mixture distribution is used as a traffic state classifier, traffic flow data of the highway confluence area are used as input, and traffic states of the highway confluence area are divided; designing a state space, an action space and a reward function; taking the state space of the highway confluence area as input, taking the actions of the variable speed-limiting intelligent agent and the ramp metering intelligent agent as output, and constructing a network model of multi-agent sharing experience under time sequence characteristics; an independent experience pool is set for each of the variable speed limit agent and the ramp metering agent, and interaction experience of the agents and the traffic simulation environment is collected with the control period as the frequency; training an agent model by using the sampled samples; and realizing cooperative control of the highway confluence area by using the trained intelligent agent model. According to the invention, the traffic travel delay of the highway confluence area can be reduced.

The invention discloses an electromagnetic interference detection method and device and a nonvolatile storage medium. The method comprises the following steps: acquiring an initial voltage signal; fourier transform is carried out on the initial voltage signal, and a target spectral line corresponding to the initial voltage signal is determined; the target spectral line is input into a preset phase-locked loop detector, a target signal component is obtained based on a transmission mode in the phase-locked loop detector, and the target signal component comprises amplitude and frequency; demodulating and filtering the target signal component in sequence to obtain a target filtering signal; processing the target filtering signal by adopting a preset quasi-peak value detector to obtain a target voltage quasi-peak value; based on the target voltage quasi-peak value, an interference detection result of the initial voltage signal is determined, and the interference detection result comprises existence of electromagnetic interference or absence of electromagnetic interference. According to the invention, the technical problems of inaccurate measurement result, complex measurement process and high cost of the existing detection technology are solved.

This invention discloses a collaborative control method for highway merging zones based on deep reinforcement learning. A LiikeSim-Python co-simulation environment is established, and loop detectors are set up in the simulation environment to acquire traffic flow data upstream and downstream of the highway merging zone. An EM algorithm based on Gaussian mixture distribution is used as a traffic state classifier, taking the traffic flow data of the highway merging zone as input to classify the traffic state of the merging zone. A state space, action space, and reward function are designed. Using the state space of the highway merging zone as input and the actions of the variable speed limit agent and the ramp metering agent as output, a multi-agent shared experience network model under time-series characteristics is constructed. An independent experience pool is set up for the variable speed limit agent and the ramp metering agent, and the interaction experience between the agent and the traffic simulation environment is collected at the control cycle frequency. The agent model is trained using sampled data. The trained agent model is used to realize collaborative control of the highway merging zone. This invention can reduce travel delays in highway merging zones.

A current-mode programming (CMP) circuit of one-time programmable memory (OTP) is disclosed. The CMP circuit has a constant current source and a closed-loop detector. The constant current source provides a sufficiently high programming current of rupturing a fuse of a bit cell of OTP selected by the logic control unit. The closed-loop detector monitors the programming current and determines whether the programming current is rapidly reduced when the fuse has been ruptured. Therefore, the CMP circuit successfully ruptures the fuse of the selected bit cell against process and temperature impacts thereon. Further, the closed-loop detector monitors the resistance transition of the selected bit cell and flags a successful programming signal in real time during each fuse-rupturing process.

The invention relates to a detection system (1) for real-time detection of abnormally sized and weighted vehicles (A) travelling at high speed on motorways. The detection system (1) subject to the invention comprises the following in its most basic form: a plurality of display units; a LIDAR sensor unit (3); a license plate detection unit (4); an axle number determination unit (5); at least one loop detector (8); at least one quartz weight measuring unit (9); at least one data processing unit (11) that calculates the weight and total weight of the vehicles (A) per axle group; a control unit (12) that creates a 3D profile of the vehicles (A) and creates a class data for each vehicle (A) and transition data containing the data produced for the vehicles by matching the data produced by the units in question with the transition images of the vehicles (A); a central server system (13) that produces oversize violation information and weight violation information according to the transit data and violation limit rules, and at least one competent authority system (18) that directly imposes penal sanctions based on the violation information produced.

This invention belongs to the field of detector technology and discloses a coaxial dual-coil metal detector and its application. The coaxial dual-coil metal detector includes a transmitting module and a receiving detection module. The transmitting module consists of an RC oscillation circuit, an amplification circuit, and a transmitting coil. The receiving detection module consists of a receiving coil, a dual second-order multi-feedback bandpass circuit, a phase-locked loop detector circuit, a low-pass filter amplification circuit, a microcontroller circuit, a buzzer circuit, and a display circuit. The coaxial dual-coil metal detector of this invention consists of two main parts: a transmitting module and a receiving detection module. It achieves the detection of gel-encapsulated seeds through a complete process of transmitting a specific electromagnetic field, seed-induced signal generation, signal reception and processing, and microcontroller judgment and alarm display. Each module has a clear division of labor and works collaboratively, efficiently completing the detection task through a series of sequential processing steps such as signal amplification, filtering, and demodulation.

The present disclosure provides a visual loop detection method based on a depth image fusion technology, comprising: initializing loop detection data; extracting current picture features, comprising: using a pre-trained depth network model to extract features of a current picture with a frame number f; calculating the similarity between the current picture and a feature set, and determining a candidate frame based on the similarity; calculating the similarity between the current picture and the feature set through a similarity calculation method, and determining the candidate frame based on the similarity; grouping the candidate frame to form several candidate sets, and determining a final candidate set; and determining a loop frame through loop detection. The present disclosure also provides a visual loop detection device based on a depth image fusion technology, an electronic device, and a readable storage medium.

This invention provides a collaborative variable speed limit control method for merging areas based on deep reinforcement learning, belonging to the field of intelligent transportation systems technology. The method includes: deploying loop detectors in a ramp merging area simulation environment, acquiring traffic state information using an access interface, setting up demand scenarios, and configuring road test units and speed limit panels; defining a state space based on the traffic state information, simultaneously considering mainline and ramp actions to obtain the action space and a single-selection action, introducing ramp dwell time, constructing a reward function, and obtaining a speed limit control model; training the speed limit control model using the single-selection action, and simulating the trained speed limit control model to obtain the control strategy for the ramp merging area. This invention addresses the shortcomings of existing collaborative variable speed limit control methods for merging areas, which mainly focus on a single type of control measure, lacking sufficient coordination between mainline and ramp control, and having an imperfect linkage control mechanism between mainline and ramp.

The invention discloses an optical chip loop detector and a manufacturing method, and belongs to the field of optical communication. A core layer of the loop detector is arranged at the joint of the lower cladding and the upper cladding; the radian of the bent waveguide of each waveguide structure of the core layer is pi; the first ends of the two straight waveguides are connected with the two ends of the bent waveguide respectively, and the second ends of the two straight waveguides are connected with the input and output interfaces respectively; the at least two U-shaped optical waveguide assemblies are similar in shape and are arranged in an array from small to large and from inside to outside, and the distance between every two adjacent straight waveguides in the straight waveguides located on the same side is equal. The lower cladding, the upper cladding and the U-shaped optical waveguide assembly are all made of polymer materials, the difference between the material refractive index of the U-shaped optical waveguide assembly and the material refractive index of the lower cladding and the material refractive index of the upper cladding ranges from 7% to 17.5%, and the absorption loss of the U-shaped optical waveguide assembly ranges from 0.005 dB / mm to 0.2 dB / mm. According to the invention, low-insertion-loss and low-crosstalk self-loop detection and multichannel insertion loss equalization of the multi-channel light receiving and emitting chip can be realized.