24 results about "Highway environment" patented technology

The invention discloses highway ecological environment monitoring equipment which comprises a base, a lifting mechanism is mounted at the top of the base, a movable seat is arranged at the top of the lifting mechanism, a rotating mechanism is mounted on one side of the movable seat, the output end of the rotating mechanism is connected with a rotating cylinder, and a plurality of collecting cylinders are arranged in the rotating cylinder. A plurality of collecting barrels are arranged in the rotating barrel, a fan sucks sampled air into the collecting barrels for collection and detection, and a cleaning pipe for cleaning dust is arranged in the middle of a collecting pipe. The invention also discloses a highway ecological environment monitoring system, which only uses natural wind along the highway and follow-up wind power resources or solar energy resources of passing vehicles to generate power, stores electric power energy through the energy storage unit, and establishes wireless communication connection to monitor the ecological environment of the highway. Data collected by the highway ecological environment monitoring equipment are fed back to the control analysis platform in real time, and online monitoring of the highway environment is achieved.

The present invention belongs to the field of artificial intelligence technology. The present invention discloses an intelligent highway integrated management system based on the Internet of Things, including: collecting lane speed limit data, vehicle speed data, vehicle condition data, highway environment data and lane specified speed data; based on vehicle status data, using a multi-task DNN model to predict emission health data, engine health data and tire health data, and using an adaptive weighting method to obtain vehicle diagnostic index data; setting a health threshold to determine whether the vehicle is healthy; using an SVR model to predict a safe speed based on the vehicle diagnostic index data and highway environment data of healthy vehicles; setting safe highway range data to determine whether healthy vehicles are speeding or driving at a snail's pace, and issuing early warning reminders; improving the traffic safety and environmental protection performance of highways, and also improving emergency response capabilities through intelligent speed limit management and real-time monitoring, and effectively reducing accident risks.

The utility model discloses a noise reduction device for road traffic engineering, which relates to the technical field of road traffic engineering, and comprises a rack, a noise reduction plate is arranged above the rack, and the noise reduction plate is used for reducing the noise of the road environment; the sliding box is slidably connected to an inner cavity of the rack, a sliding block is slidably connected to an inner cavity of the sliding box, and the silencing plate is rotationally arranged at the top of the sliding block; and the horizontal driving mechanism is arranged in the rack, and the horizontal driving mechanism is used for driving the sliding block to move. When noise reduction treatment is needed, the horizontal driving mechanism is used for driving the sliding block to move, the sliding block drives the multiple noise reduction plates to unfold to form a complete noise reduction plate, and when noise reduction is not needed to be conducted on the road environment, the horizontal driving mechanism is used for driving the multiple noise reduction plates to fold, so that the noise reduction plates are not affected by wind, and the situation that wind power destroys an equipment structure is avoided; and meanwhile, the occupied space is reduced, and the view of a driver is prevented from being shielded.

The present invention discloses a formation decision-making method for connected intelligent vehicle formations based on nested graph reinforcement learning, belonging to the technical fields of vehicle networking and autonomous driving. The method includes: S1, collecting the vehicle state information within the formation and processing the state information to obtain an inter-formation nested graph and an intra-vehicle nested graph; S2, using a feature extraction network to extract features from the inter-formation nested graph and the intra-vehicle nested graph, and obtaining the actions of each intelligent vehicle based on the extracted features; the feature extraction network includes: a graph attention layer, a fully connected layer, and an activation layer, and a multi-head attention mechanism is introduced to improve the feature extraction ability; S3, optimizing the actions using a reward function to obtain an intelligent vehicle decision-making method. The present invention can achieve fully integrated formation decision-making control under high-efficiency communication in a highway environment with high dynamics, high complexity, and strong randomness.

The invention relates to an expressway vehicle-mounted network multi-target robustness dynamic communication optimization method, and belongs to the technical field of intelligent traffic. The method comprises the following steps: acquiring vehicle position, speed and channel state information in real time; constructing four objective functions of communication delay, load balance, link quality and time sequence stability; an improved NSGA-II algorithm is adopted to carry out multi-objective optimization solution, and a Pareto optimal solution set is obtained; the solution set diversity is kept through crowding distance calculation, the method is used for routing decision making, local optimum is avoided, and therefore the robustness and stability of the routing decision making are improved. According to the method, the communication reliability, the resource utilization rate and the path stability are effectively improved, the method is suitable for a dynamic expressway environment, the network topology change and uncertainty are dealt with, and the effects of high communication reliability, high resource utilization rate and more stable path in an expressway scene are achieved.

This utility model relates to the field of road guardrail technology, and in particular to an adjustable guardrail for highway traffic safety. It includes two mounting bases, each with four casters at its lower corners. The adjustable guardrail of this utility model allows for easy movement to a designated position via the casters. Turning the lever activates a screw to drive a clamping plate, fixing the abrasive block to the ground. When length adjustment is needed, pushing the support rod allows the extension frame to slide out, embedding the extension component and adjusting it using fixing bolts and pins. When a required height is needed on the highway, a motor, gears, and racks work together to slide a guide plate, moving the crossbar and extending / retracting the extension guardrail, simultaneously adjusting the position of the second extension guardrail. This allows for flexible and precise adjustment of the guardrail's length and height, effectively addressing the diverse needs of different construction areas and complex highway environments, improving adaptability and efficiency.

The invention discloses an automatic driving decision-making method based on a competition network and an attention mechanism, and the method comprises the steps: 1, carrying out the modeling of an automatic driving decision-making problem through employing an MDP, abstracting an automatic driving scene into a quintuple (S, A, P, r, gamma), and enabling the quintuple to comprise a state space, an action space, a state transition probability, a reward function, and a discount factor; 2, defining MDP-based state space, action space and action selection problems, including state space refinement, action space instantiation and action selection problems; 3, combining an attention mechanism network and a reinforcement learning network to construct a DA-DDQN for solving an automatic driving decision problem; 4, training, testing and verifying the network model DA-DDQN in an expressway environment of a Highway simulation platform; 5, the training process in the step 4 is repeated and iterated until the strategy network converges; and 6, applying the DA-DDQN with the optimal parameter to an automatic driving vehicle, and making an automatic driving decision. According to the invention, the decision-making safety and efficiency of the vehicle in a complex traffic environment can be improved.

The utility model discloses an adjustable highway sound barrier relates to sound barrier technical field, including vertical positioning frame, the inner wall movable insertion of vertical positioning frame has from below and upwards laminated first combination barrier and second combination barrier, and the contact end movable joint of first combination barrier and second combination barrier, first combination barrier includes positioning board and turnover board. The utility model discloses through the positioning board and turnover board of first combination barrier can rotate around axle rod, can arrange vertically up and down, form conventional sound barrier structure, satisfy general noise reduction demand, can also stack in front and back, form thickening structure, when facing high noise road section or special noise environment, can effectively improve the noise reduction effect. Meanwhile, first combination barrier and second combination barrier also can be adjusted through movable joint, and this kind of multi -mode adjustment function makes sound barrier can according to different highway environment, noise intensity factor, adjusts structure flexibly.

The invention provides an expressway multi-expert autonomous behavior decision-making method based on scene perception constraint, and belongs to the technical field of automatic driving. Comprising the steps that a one-way three-lane linear expressway environment is built; describing vehicle kinematics by using a bicycle model; the method comprises the following steps: modeling longitudinal car-following behaviors of surrounding vehicles by adopting an IDM model to form a traffic flow with certain randomness and uncertainty; dividing the driving scene into a plurality of sub-scenes; constructing a unified state space and action space state space; the scene constraint cost with the unified form is designed for all the sub-scenes; introducing scene perception constraint, improving a DRL algorithm used by each sub-scene, and training a corresponding expert model based on a scene perception constraint SAC algorithm; constructing a training set and a test set; and carrying out an actual operation or simulation test stage.

The utility model provides a multi-mode early warning device used in a complex highway environment, which is characterized in that a base is semi-buried and fixed underground, a main rod is fixed on the base, a camera is mounted on the side surface of the main rod in a liftable manner, a double-layer frame is arranged at the top of the main rod, a lower plate is fixed at the upper end of the main rod, an upper plate is positioned above the lower plate, and the upper plate and the lower plate are horizontally arranged; side plates are arranged at the two ends of the lower plate and the upper plate, laser radars are arranged on the outer sides of the side plates, and a control device is installed in the middle of the bottom plate and can transmit information obtained by the camera and the laser radars to a control center. The beneficial effects of the utility model are that the device achieves the comprehensive collection of the road condition and environment information of the expressway through the integration of a plurality of devices, such as the camera, the laser radar, the rain gauge and the anemograph; the lifting design of the camera improves the flexibility of information acquisition; a plurality of early warning modes such as the light-emitting indication board and the sounder are combined, so that the early warning effect is enhanced; the whole device can adapt to the complex environment of the expressway, and powerful guarantee is provided for driving safety.

The invention discloses a method for constructing an intelligent highway inspection tour controller based on a generative AI (Artificial Intelligence). Basic gait learning is realized through motion redirection and simulation reinforcement learning by utilizing motion track data of an open source robot, a basic level control network based on VQ-VAE is constructed, an expressway environment is disassembled into typical unit scenes such as rugged ground, obstacles, holes and hurdling, and various inspection skills such as crawling, jumping, climbing and obstacle avoiding are trained in each scene. A multi-expert knowledge distillation method is adopted, a plurality of skill-level controllers are fused to form a unified inspection-level controller, and the robot is driven to execute a full-coverage inspection task in a complex road environment in combination with a coverage path generation algorithm. The system has higher maneuverability, adaptability and stability, can realize high-coverage-rate and high-efficiency autonomous inspection in complex scenes such as tunnels, bridges and side slopes, and is suitable for safety monitoring and maintenance of large-scale intelligent traffic infrastructures.

The embodiment of the invention provides a steering wheel hand release time control method and a related device, which are used for adopting different hand release detection durations in different driving modes and / or driving areas so as to improve the safety in a plurality of different driving scenes on the premise of satisfying a plurality of automatic driving scenes. The method provided by the embodiment of the invention comprises the following steps: acquiring a driving mode of a vehicle, or a driving mode and a driving area; if the vehicle is in the self-adaptive cruise control mode, the hand release time of the steering wheel is controlled to be first time; if the vehicle is in the non-adaptive cruise control mode and the driving area of the vehicle is in the urban road environment, controlling the hand release time of the steering wheel to be second time; if the vehicle is in the non-adaptive cruise control mode and the driving area of the vehicle is the highway environment, the hand release time of the steering wheel is controlled to be third time, the third time is longer than the second time, and the second time is longer than the first time.

Aiming at the problem of potential safety hazards in erecting lines in a highway environment, a prefabricated and assembled anti-collision pier provided by this application relates to the technical field of high-voltage power facilities. The prefabricated and assembled anti-collision pier includes a number of anti-collision walls connected end to end in sequence, and the number of anti-collision walls forms a closed-loop structure and surrounds the outside of the facilities for line erection. The anti-collision wall includes a main body part, a first connection end and a second connection end, and the first connection end of the anti-collision wall is fixedly connected to the second connection end of the adjacent anti-collision wall through a connection component. The connection component includes two connection steel plates, and both the first connection end and the second connection end connected through the connection component are fixedly connected to the connection steel plates on both sides through a locking component. This prefabricated and assembled anti-collision pier can not only effectively protect the facilities for line erection, but also effectively shorten the construction period by adopting an assembled structure.

This application discloses a method for correcting misjudgments in high-speed multi-type event detection based on LoRA, relating to the field of intelligent transportation technology. The method includes: acquiring real-time event information on the highway, identifying it using the YOLO algorithm, and outputting the original preliminary event detection results and environmental parameters; standardizing the preliminary detection results and extracting semantic and scene features of the event targets from the preliminary detection results to obtain standard preliminary detection results; performing secondary verification and misjudgment correction using a LoRA-optimized large model based on the standard preliminary detection results to obtain the event detection results; uploading the event detection results to the road segment central monitoring platform, and retaining misjudged, missed, and new scene samples for iterative optimization. This application aims to resolve the contradiction between the low reliability of event detection in complex highway environments and the inability to deploy high-precision large models at low cost and high efficiency under existing hardware conditions.

The present invention discloses a drone inspection method and system for highway environmental improvement, relating to the field of drone communication technology. The method comprises: allocating a drone swarm to each inspection unit; predicting the drone mission load of each inspection unit, formulating a drone scheduling mechanism based on the predicted drone mission load, and establishing a communication link between the current drone cluster and the scheduling drone according to the drone scheduling mechanism; sensing the communication link signal between the current drone cluster and the scheduling drone in real time, and using a path optimization algorithm to calculate the optimal relay transmission path when the communication link signal is interrupted to achieve communication link signal reconstruction. The present invention ensures communication stability between the drone cluster and the scheduling drone through a communication resource allocation mechanism based on spatiotemporal hash codes, thereby avoiding task delays caused by communication resource conflicts.

The application relates to the technical field of environment monitoring devices, and discloses a highway environment monitoring device and a use method thereof, which comprises an air guiding component, a second linkage component, a transmission component and the like. When a motor drives a fan to rotate through an output shaft, external air enters a monitoring box for detection, and under the action of the second linkage component, the transmission component can be driven to transmit, a push rod on the transmission component can slide in the inside of a movable frame, so that the movable frame can be pushed and pulled, the movable frame can reciprocate left and right, and a brush at the bottom of the movable frame can rub and clean a filter screen located at the right side of a partition plate. The first linkage component is arranged between the conveying component and the transmission component, and in the transmission process of the transmission component, the first linkage component can also drive the conveying component to intermittently transmit, so that the filter screen can intermittently move, and the filter screen located at the lower side of the air guiding component can be intermittently used.

The invention discloses an ETC (Electronic Toll Collection) and vehicle sensing target point location matching method based on multi-mode sensing of a toll portal, and relates to the technical field of vehicle sensing matching. Comprising the steps of obtaining position information and quantity information of a highway toll gate frame, obtaining an obtained information set, installing a sensing system and an ETC system based on the obtained information set, and obtaining sensing data of a vehicle based on the sensing system. According to the invention, a multi-modal sensing system is constructed and a deep learning model is introduced for optimization, a point location matching algorithm is used for carrying out space-time alignment and fusion on standardized ETC data and sensing data, a deep learning model based on a convolutional neural network is introduced, and fused latitude and longitude, course angle, timestamp and other characteristics are input, so that the ETC sensing system is obtained. According to the method, the limitation of a single visual system is greatly overcome, and the vehicle positioning precision and the license plate recognition success rate in complex expressway environments such as illumination variation, shielding, long distance and fouling are remarkably improved.

The application relates to a highway environment-friendly structure and relates to the technical field of road environment protection. The highway environment-friendly structure comprises a plurality of channel bases connected in sequence, the channel bases are used for planting green plants, water flow holes are formed in the bottoms of the channel bases, the water flow holes of adjacent two channel bases are communicated, the water flow hole of the channel base at the head end is communicated with a water pump, the water pump is communicated with a water tank, the channel base at the tail end is communicated with the water tank through a pipeline, the water tank is used for storing water, a collecting hole for collecting rainwater is formed between the top end of the channel base and the water flow hole, the water flow hole and the channel base are internally provided with water supply holes for water supply, and the channel base is provided with an adjusting assembly for adjusting the closing or opening of the water supply holes and the water flow holes; when the channel base lacks water, the adjusting assembly makes the water supply holes open and the water flow holes close; and when the channel base stores water, the adjusting assembly makes the water supply holes close and the water flow holes open. The application has the effect of stably supplying water to the highway green vegetation layer for a long time.

This invention provides a multi-expert autonomous behavior decision-making method for highways based on scene-aware constraints, belonging to the field of autonomous driving technology. It includes: constructing a one-way three-lane straight highway environment; using a bicycle model to describe vehicle kinematics; employing an IDM model to model the longitudinal following behavior of surrounding vehicles, forming a traffic flow with a certain degree of randomness and uncertainty; dividing the driving scenario into multiple sub-scenarios; constructing a unified state space and action space; designing a unified scene constraint cost for each sub-scenarios; introducing scene-aware constraints, improving the DRL algorithm used for each sub-scenarios, and training a corresponding expert model based on the scene-aware constraint SAC algorithm; constructing training and testing sets; and conducting actual operation or simulation testing.

The highway-railway dual-purpose fire-fighting robot comprises a vehicle frame system, a fire-fighting equipment integration system, a walking system and an electrical control system, and the fire-fighting equipment integration system is arranged at the top of the vehicle frame system; the walking system comprises crawler belt mechanisms, track wheel mechanisms and jacking mechanisms, the crawler belt mechanisms are arranged on the two sides of the bottom of the frame system, the two jacking mechanisms are arranged in the advancing direction and the retreating direction of the frame system respectively, and the two track wheel mechanisms are connected with the executing ends of the two jacking mechanisms respectively; the electrical control system is electrically connected with the fire fighting equipment integration system, the crawler belt mechanism, the track wheel mechanism and the jacking mechanism. Through the rail wheel mechanism and the jacking mechanism, the robot can independently walk in the railway environment, and autonomous switching and efficient operation in the highway environment and the railway environment can be achieved.

The embodiment of the invention relates to the technical field of data processing, and discloses a low-environmental-impact construction evaluation data analysis method and device based on road environment index information, and the method comprises the steps: obtaining the original data of a plurality of evaluation indexes of an evaluation target; for each evaluation index, calculating the original data according to a preset calculation method corresponding to the evaluation index, and performing standardization processing on a calculation result to obtain standard data; respectively constructing a static evaluation model and a dynamic evaluation model for low environmental impact construction evaluation based on the standard data, and obtaining a static evaluation result and a dynamic evaluation result corresponding to the evaluation target; determining the comprehensive relative close degree of the evaluation target based on the static evaluation result and the dynamic evaluation result; and determining the environmental influence level of the evaluation target based on the comprehensive relative closeness. According to the low-environmental-influence construction evaluation based on the multi-dimensional evaluation index, the accuracy of obtaining the comprehensive relative close degree is improved, and the road construction project is effectively guided to reduce the influence of road construction on the environment.

A vehicle including a diffuser assembly that is movable between a non-deployed position and a deployed position, a deployment system configured to move the diffuser assembly between the non-deployed position and the deployed position, a controller configured to instruct the deployment system to move the diffuser assembly between the non-deployed and deployed positions, at least one device in communication with the controller that is configured to communicate signals to controller that are analyzed by the controller to determine whether the vehicle is travelling in an on-road environment or an off-road environment, wherein if the controller determines that the vehicle is travelling in an off-road environment, controller is configured to instruct the deployment system to either move the diffuser assembly from the deployed position to the non-deployed position or prevent the deployment system from moving the diffuser assembly from the non-deployed position to the deployed position.