2943results about "Arrangements for variable traffic instructions" patented technology

An intelligent traffic management device for optimizing traffic flow at one or more intersections using reinforcement learning, comprising: a central control unit housed in a weatherproof enclosure and mounted on a structural support near an intersection; a sensor interface operatively connected to a variety of multimodal sensors, including at least radar-based vehicle detectors, inductive loop sensors embedded in the road surface, infrared pedestrian detection detectors, and high-resolution optical imaging modules; a powerful embedded computing unit consisting of a multi-core processor and a GPU configured for on-device inference; a reinforcement learning engine embedded in the computing unit, comprising a deep reinforcement learning model trained to map environmental states defined by traffic-related sensor inputs to optimized action policies for traffic light control; a signal actuation module electrically connected to traffic signal controllers, with action policies outputting signal phase durations and transitions in real time; a communications module supporting wireless connectivity and configured for device-to-device communication and cloud synchronization; a policy synchronization module configured to perform federated learning-based updates of model parameters by exchanging gradient weights or distilled traffic state vectors with neighboring intelligent traffic management devices deployed in a traffic network; where the reinforcement learning engine continuously observes traffic state vectors consisting of vehicle counts, average speeds, queue lengths, and pedestrian activity, and dynamically updates the policy to maximize cumulative traffic throughput and minimize average delay.

The invention discloses an expressway emergency management and control method and system, and the method comprises the steps: building a multi-dimensional heterogeneous data fusion model through a time-space diagram neural network according to the traffic flow, meteorological data and accident reports collected by roadside sensing equipment, and carrying out the dynamic prediction of the risk level of a road segment, and obtaining a real-time risk level map of a whole road network; based on the real-time risk level map, outputting a dynamic shunting scheme containing variable lane marks and a speed limiting strategy; according to the dynamic shunting scheme, generating a vehicle trajectory optimization strategy; and outputting an anti-interference optimization control strategy based on a vehicle trajectory optimization strategy in combination with sudden obstacle data polled by the unmanned aerial vehicle in real time. According to the embodiment of the invention, rapid and accurate path adjustment and cooperative control can be carried out, and the emergency management level of the expressway is improved.

The invention discloses a road intelligent induction and dynamic early warning method and system integrated with meteorological perception, and relates to the technical field of intelligent traffic and road safety. The method comprises the following steps: acquiring real-time weather, traffic and road data, performing multi-source data fusion by adopting an improved Kalman filtering and attention mechanism, and generating unified state estimation; dynamic risk assessment is carried out in combination with Bayesian reasoning and a Markov model, and speed-limiting adaptive adjustment is realized based on safety, traffic efficiency and energy consumption multi-objective optimization; and further calculating the length and position of the dynamic early warning area, and controlling devices such as intelligent spikes to issue induction information. The system comprises a data acquisition unit, a fusion estimation unit, a risk prediction unit, a speed adjustment unit, an early warning calculation unit and an induction unit. According to the invention, real-time monitoring, risk prediction and intelligent regulation and control of the road traffic environment in complex weather are realized, and the driving safety and the traffic efficiency are improved.

The invention relates to the technical field of tunnel parking guidance, and discloses a tunnel emergency parking strip guidance emergency system and method, and the system comprises a data collection module, an analysis decision module, and an emergency indication module. Wherein the data acquisition module is used for acquiring environment data and vehicle data in a tunnel; the analysis decision module divides the tunnel into different emergency sections based on the environment data, sets an emergency indication strategy for each emergency section, and adjusts the emergency indication strategies based on the vehicle data; the emergency indication module performs emergency guidance on an emergency parking strip in the tunnel based on the emergency indication strategy; the analysis decision module also performs abnormal vehicle detection based on the vehicle data and generates an emergency guidance strategy; the emergency indication module performs emergency stop guidance on the abnormal vehicle based on the emergency guidance strategy; the indication and guidance modes of the emergency parking strip in the tunnel can be reasonably set and adjusted, and tunnel traffic safety can be guaranteed.

The embodiment of the invention provides an unmanned aerial vehicle task scheduling method and device for intelligent road network patrol, and precise planning of an unmanned aerial vehicle patrol route is realized by constructing a three-dimensional road network topology model and an obstacle distribution map. And designing an unmanned aerial vehicle scheduling strategy based on task fitness, and extracting patrol rules from the task template library to perform intelligent scheduling in combination with the real-time position, the endurance mileage and the load state. A grading early warning mechanism is introduced, and the event influence range is analyzed through target detection and scene recognition, so that differentiated early warning of the roadside equipment and the vehicle-mounted terminal is realized. According to the method, the defects of the traditional technology in the aspects of task planning, unmanned aerial vehicle scheduling, early warning linkage and the like are effectively overcome, and the intelligent level and the emergency disposal effect of road network patrol are remarkably improved.

A method and system for managing roadside information and distributing navigation information is disclosed. The embodiments provide a roadside device network configured to collect sensor data and vehicle-originated data about the local roadway. The roadside devices are spaced along the road and are connected to a central server to collect information about the impaired road condition, determine an approximate location of an impaired road condition, calculate an alternate route, and transmit an alternate route to a roadside device to transfer the information to a passing vehicle.

The invention relates to the technical field of highway traffic safety guarantee, and particularly discloses a highway early warning system and an early warning equipment layout method under ice and snow conditions. The problems that recognition lags, the early warning response has the regional splitting phenomenon and the early warning information has deviation in the common technology are solved. Comprising a data acquisition layer which is used for acquiring meteorological data, road surface data, traffic flow data and vehicle behavior data in real time and eliminating abnormal data through a cross validation mechanism; the analysis decision-making layer analyzes the fused multi-dimensional data based on a multi-factor coupling dynamic risk assessment model, and generates a blue / yellow / orange / red four-level early warning signal; and the early warning issuing layer is used for issuing early warning information according to the early warning grade matching equipment combination. Through multi-source data cross validation and feature fusion, the false report and missing report rate is remarkably reduced, and the risk identification accuracy is improved.

The invention relates to a road section risk early warning method based on thunder-vision fusion perception, and the method comprises the following steps: S1, obtaining the high-precision space-time position information of a vehicle in a tunnel through the multi-source information fusion of a millimeter-wave radar and machine vision; s2, mapping the vehicle position under the global coordinate system to a coordinate system expanded along a road center line, and representing the vehicle position as a longitudinal projection position and a transverse offset along the road direction; s3, under the coordinate system, taking anti-collision time as a core index, combining lane judgment and relative speed, constructing a dynamic longitudinal risk grading model, and performing linkage triggering with a warning system; s4, constructing a regional risk integral model; and S5, speed limiting information is issued to all driving-in vehicles in real time through the variable speed limiting screen, and the rear-end collision risk is actively prevented and controlled. According to the method, the sudden risk response time can be shortened, the speed limit control response precision can be improved, the rear-end collision rate of the diversion and convergence areas can be reduced, false alarm interference can be reduced, and the tunnel driving safety and the information guiding efficiency can be improved.

The invention relates to a mine road network scheduling method and device, equipment and a medium, and the method comprises the steps: obtaining the average loading time length of each loading region; obtaining the driving duration of the scheduled mine card reaching each loading area in the target state; acquiring the queuing duration of the dispatched mine cards in each loading area; based on the average loading time length of each loading area and the driving time length and the queuing time length of the dispatched mine cards, the loading operation estimated time length of the dispatched mine cards relative to each loading area is determined; and taking the loading area corresponding to the minimum loading operation estimation duration as a target loading area, controlling the dispatched mine card to run to the target loading area according to a path corresponding to the shortest running duration, and determining that a target electric shovel performs operation processing on the dispatched mine card according to the electric shovel use state of the target loading area. Therefore, the shortest dispatching time length of the mine cards can be quickly and accurately obtained to dispatch the mine cards, and the mine card dispatching efficiency and effect are improved.

Techniques for handling vehicle privileges while changing geographical regions are disclosed. In some embodiments, a user equipment (UE) may be configured to, based on a determination that the UE is within a first geographical region associated with a first authority, receive first privilege information from a first wireless node within the first geographical region; based on a determination that the UE is within an overlapping region, operate the UE according to the first set of behavioral rules; and receive second privilege information from the second wireless node within the second geographical region, the second privilege information configured to enable the UE to operate according to a second set of behavioral rules determined by the second authority while within the second geographical region and not within the overlapping region.

Systems and techniques are described herein for responding to queries. For instance, a method for responding to queries is provided. The method may include obtaining a plurality of vehicle to everything (V2X) messages, each V2X message of the plurality of V2X messages comprising a plurality of fields; obtaining a query from an occupant of a vehicle; determining V2X information comprising at least one field of at least one V2X message of the plurality of V2X messages; and processing the query and the determined V2X information using a machine-learning model to generate a response to the query.

A real-time traffic signal optimization system that includes: (a) a traffic data acquisition module that collects real-time traffic data from sensors, cameras, GPS and vehicle-to-infrastructure communication; b) a machine learning-based traffic prediction engine that analyses historical and real-time data to predict congestion patterns; c) an adaptive signal control unit that dynamically adjusts traffic light switching times based on real-time traffic flow and predictive insights; (d) an emergency and priority vehicle management system that overrides normal signal operation to give priority to emergency vehicles and public transport vehicles; (e) a central traffic monitoring and control dashboard for real-time monitoring, manual interventions and system configuration; and (f) a vehicle-to-infrastructure communication interface enabling data exchange between traffic signals and connected vehicles to improve driver awareness and traffic coordination.

The invention discloses a global traffic signal control method based on a regional context enhanced large language model, and the method comprises the steps: dividing a target region into K traffic signal lamp control regions according to a traffic network structure of the target region; global real-time traffic information of the target area is collected and converted into global traffic text information; and inputting the global traffic text information into the large language model after LoRA fine tuning, and outputting a global traffic signal lamp control strategy of the target area, namely a traffic signal lamp phase of each intersection. In the fine tuning process of the large language model, an optimal phase decision is generated by using a reinforcement learning agent, a decision result is converted into text data, a region-level optimal phase decision data set is constructed according to an adjacent region division strategy, fine tuning is performed on the model by using the data set, region loss is calculated, and the large language model is optimized through the loss. According to the invention, optimization of global traffic signal lamp control can be realized, the overall traffic delay is reduced, and the traffic efficiency is improved.

The invention discloses a road traffic flow management and control system based on a mobile road cone. The road traffic flow management and control system comprises a data transmission module (1), a scheme generation module (2), a field management and control module (3) and an energy storage and charging module (4), the data transmission module (1) is used for transmitting a control instruction issued by a traffic manager to the scheme generation module (2); the scheme generation module (2) is used for receiving an instruction issued by a traffic manager and generating a moving path scheme and a formation scheme; the field management and control module (3) is used for moving a mobile road cone (6) to a target position according to the mobile path scheme and the formation scheme to form a preset formation management and control traffic flow; and the storage and energy charging module (4) is used for charging the movable road cone (6). Manual on-site operation is not needed, the coverage range is far, the intelligent degree is high, and response is rapid.

The invention discloses an intelligent control system and method based on an intelligent indication board, and relates to the technical field of intelligent traffic and Internet of Things control, and the method comprises the following steps: building a unified time mark baseline, collecting an exposure sequence, a saturation threshold sequence and a track residual error, and generating an exposure-track coupling spectrum for calibrating a rain and snow triggering time window; and calculating phase residual mapping under the constraint of an exposure-trajectory coupling spectrum, identifying an exposure oscillation root cause, extracting a saturated source region and a trajectory breakpoint set, and generating a fault anchor point. According to the method, rain and snow interference is identified through a time mark base line and a coupling spectrum, a fault anchor point is constructed, an optical path is played back to assess risks, multi-source signals are fused to generate a steady track, conjugate correction and feedforward constraint are adopted to suppress oscillation, a time reversal closed-loop instruction and multi-strategy joint debugging are combined, and self-adaptive optimization of exposure and induction information is achieved. And the stability and the control precision of the intelligent indication board in extreme weather are improved.

The invention discloses a sudden accident alarm system for a highway, and belongs to the technical field of highway operation management. According to the system, a seven-in-one intelligent terminal integrated with a laser radar sensor, an emergency alarm button, an induction lamp, broadcasting equipment, a two-dimensional code label, a self-luminous plate and a reflective coating film is arranged along the line. A laser radar periodically scans a front 8-meter range, a primary event label is generated in combination with an emergency alarm button signal, and an accident is found in time; calling adjacent terminal data for transverse comparison, tracking a time sequence change trend, and comprehensively judging a risk level; the colors and flicker frequencies of the induction lamps are activated according to the grades, broadcast voice is triggered, and night identification is enhanced through a self-luminous plate and a reflective coating film. The system realizes on-site discovery, on-site response and on-site warning, the response time is remarkably shortened, the problems of lagging discovery and insufficient warning of a traditional monitoring means are solved, and the emergency efficiency and the driving safety are improved.

The invention provides an intersection accident evacuation scheduling method based on cooperation of an unmanned aerial vehicle and a large language model, and relates to the technical field of intelligent traffic management, unmanned aerial vehicle application and artificial intelligence multi-mode fusion. The method comprises the following steps: generating an optimized patrol route based on a large language model; controlling an unmanned aerial vehicle cluster to perform multi-modal data acquisition on urban road network intersection nodes; fusing multi-source heterogeneous data by using a multi-modal fusion module enhanced by a large language model; inputting a multi-modal large language model based on a traffic-dedicated Prompt template, and generating a semantic report including accident positioning, influence evaluation and resource requirements; natural language decisions output by the large model are converted into structured control instructions, and signal lamp timing and lane allocation strategies are elastically adjusted in combination with real-time loads of a road network; and synchronously issuing a multi-mode guide instruction through the variable information board, the vehicle-mounted terminal and the navigation APP.

The present disclosure is directed to a traffic signal apparatus communication system and methods of communicating traffic information to vehicles using same. The traffic signal apparatus communication system includes a traffic signal apparatus for providing a message to a vehicle. The apparatus includes at least one spatially encoded marker, and the vehicle is configured to receive returns of a radar signal from the spatially-encoded marker. At least one controller of the vehicle is configured to determine the message encoded by the spatially-encoded marker based on the returns and to control the vehicle based on the message. The message may include a value indicating a time to a transition of a new state of the traffic signal apparatus, where the new state includes emission of light from one of a first light source, a second light source, or a third light source of the traffic signal apparatus.

The utility model relates to the field of underground garage access safety, in particular to an underground garage access channel safety guidance system. The induction system comprises a controller, at least two displacement sensors and at least two indicator lights; the underground garage access channel is provided with a blind area road section which is provided with at least two entrances and exits. Each entrance is provided with a displacement sensor and an indicator lamp; the controller is connected with all the displacement sensors and all the indicating lamps and used for controlling the indicating lamps at all the entrances and exits to turn on green lights or flicker as green lights when the displacement sensor at only one entrance and exit detects that a moving target enters the blind area road section; and when the displacement sensors of at least two entrances and exits detect that the moving target enters the blind area road section, the indicator lamps of the at least two entrances and exits are controlled to be red or flicker with red lights. According to the utility model, the opposite lane condition of the blind area road section of the underground garage access passage can be well prompted, and drivers and pedestrians are induced to safely pass through the underground garage access passage.

The invention relates to the technical field of displays, and provides a traffic display screen, which comprises a main body, the lamp strip is used for emitting light with different colors; the supporting pieces are arranged on the main body, the supporting pieces are used for installing the lamp strip, the number of the supporting pieces is multiple, and the multiple sets of supporting pieces are sequentially arranged on the main body; the mounting assembly is used for mounting and separating the supporting piece and the main body; after the multiple sets of supporting pieces and the main body are installed through the installation assembly, one set of supporting pieces in every two adjacent sets of supporting pieces moves relative to the main body, and the other set of supporting pieces is fixed relative to the main body. When one group of supporting pieces moves relative to the main body, a gap is formed between two adjacent groups of supporting pieces. When the display screen is blown by strong wind, the strong wind can enable the movable supporting piece to move, the interval is generated between the movable supporting piece and the fixedly-installed supporting piece, then part of the wind passes through the display screen through the interval, the blowing force of the wind on the whole display screen is reduced, and therefore the display screen can be conveniently and rapidly installed. Therefore, the display screen is prevented from loosening due to large-amplitude shaking.

The present disclosure describes a vehicle including a first wireless interface configured to communicate with an external computational device using a first wireless communication protocol, and a second wireless interface configured to communicate with the external computational device using a second wireless communication protocol that is different from the first wireless communication protocol. The vehicle further includes a network controller having a network selector configured to select either the first wireless communication protocol or the second wireless communication protocol for communication with the external computational device. The selection is based on one or more signals received at the network controller from the external computational device. The network selector selects the first wireless communication protocol to communicate with the external computational device at a first time, and selects the second wireless communication protocol to communicate with the external computational device at a second time different from the first time.

A vehicle traveling information analysis device comprises: a reception unit that receives, from a plurality of vehicles, traveling information which includes location information and time information; a traveling information recording unit that stores, in a traveling information storage unit, the traveling information received from the reception unit together with identification information of vehicles; an analysis condition input unit that accepts, from a user, designation of an analysis condition which includes information pertaining to an analysis target road; an extraction region setting unit that sets extraction regions each having a predetermined area to a respective plurality of locations on a road map on the basis of the designated analysis condition; and a vehicle identification information extraction unit that extracts identification information of a vehicle having a record of traveling information in all the extraction regions which have been respectively set to the plurality of locations on the road map.

According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver- the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated. Insurance discounts may be provided for autonomous vehicles having this safety functionality.

The invention relates to a road traffic congestion relief technology, and discloses a highway emergency event coordination control method and device, and the method comprises the steps: collecting images of lanes in response to different road sections in a highway, carrying out the recognition of the images, and at least obtaining the driving condition information of the lanes; based on the driving condition, determining that the vehicle driving speed in a lane is lower than a first threshold value, or the vehicle density exceeds a second threshold value, or the distance between vehicles in a plurality of lanes is smaller than a third threshold value; determining that corresponding road sections of the expressway need to be subjected to traffic intervention; based on the collected image of the to-be-intervened road section, identifying a congestion reason; determining an intervention mode according to the position information of the to-be-intervened road section and the congestion reason; and according to the intervention modes of the to-be-intervened road section, each local unit is notified of each intervention mode, and each unit intervenes the traffic mode of the expressway according to the intervention modes. According to the invention, the traffic efficiency of the expressway is ensured, and the accident rate is reduced.

The invention provides a vehicle dangerous driving evaluation method based on a large model, and relates to the field of traffic control systems. The vehicle dangerous driving evaluation method based on the large model comprises the following steps: step 1, data acquisition: setting a data acquisition layer to acquire multi-source heterogeneous data, and acquiring driving state data of a vehicle in real time through cameras and sensor equipment deployed along a highway; 2, data preprocessing: setting a data preprocessing layer, and performing whole-chain data management and alignment; step 3, data extraction: setting a feature extraction layer to construct a multi-dimensional feature engineering system; step 4, identification: setting a large model identification layer: establishing a large model based on a Transform architecture; and step 5, outputting a result: outputting a result judged and identified by the large model for evaluating dangerous driving of the vehicle. According to the scheme, the dangerous driving behavior of the vehicle is accurately identified, the danger index is provided, and a reliable risk assessment result is provided.

An in-vehicle control device disclosed herein is an in-vehicle control device to be mounted in a vehicle and includes a control unit that transmits at least some of vehicle data collected by the vehicle to an external device that is provided outside of the vehicle and communicates with the in-vehicle control device via a network. When an ignition switch of the vehicle is switched off, the control unit executes calculation control for calculating a transmittable amount of the vehicle data based on a remaining battery charge of the vehicle, extraction control for extracting, from the vehicle data, first data that fits within the transmittable amount, and first transmission control for transmitting the first data to the external device and not transmitting second data that is different from the first data out of the vehicle data to the external device.

An in-vehicle terminal includes: a V2X communication control unit controlling communication with a neighboring vehicle capable of vehicle-to-vehicle communication; a neighboring vehicle information management unit managing neighboring vehicle information acquired by the vehicle-to-vehicle communication; a V2N communication control unit performing control to provide a first base station connected via direct communication with information on a second base station unable to be connected via direct communication and to request the first base station to provide connected terminal information on the neighboring vehicle connected to the second base station; a relay management unit selecting a relay station that is the neighboring vehicle relaying indirect communication with the second base station based on the neighboring vehicle information and the connected terminal information; and a redundant system management unit instructing the relay management unit to perform indirect communication with the second base station when the second base station cannot be connected via direct communication.

A vehicle control method includes obtaining road condition information ahead of a vehicle; controlling, in response to determining, based on the road condition information, that the vehicle has entered a double solid line road section, the vehicle to perform automated driving; and controlling, in response to determining, based on the road condition information, that the vehicle has exited the double solid line road section, the vehicle to exit automated driving.

A fog lamp induction warning control system comprises a data acquisition module, the data acquisition module comprises a vibration sensor, an acoustic sensor and a light sensor, and the vibration sensor is used for capturing vibration waveforms generated during vehicle collision and acquiring vibration data in real time; the signal processing module is used for processing signals of the data acquisition module, and the data processing module performs fusion by using weighted average; setting a threshold value to judge whether the fused features belong to abnormal conditions or not; the threshold value is determined through statistical analysis or experiment of historical data, and the output result exceeding the threshold value is output; the warning module comprises a fog lamp and a sound alarm arranged on the edge of the fog lamp; the invention aims to solve the problem that a secondary collision accident is easily caused because a traffic accident warning cannot be sent to a driver behind in time after a vehicle is collided.

A method and system for cloud-based V2X for providing real-time broadcast of signal phase and timing (SPaT) data. An example method includes receiving SPaT data from one or more traffic signal controllers, processing the SPaT data by converting the SPaT data from an original format into one or more different formats, where the processing includes distributing a processing load over a plurality of docker containers using a grouping or clustering algorithm that takes into account a raw data arrival sequence from the traffic signal controllers, determining one or more nearest intersections based on geolocation of a client device, and transmitting processed SPaT data related to at least one of the one or more nearest intersections to the client device.