158 results about "Urban road" patented technology

The application discloses a kind of visual enhancement methods for urban road all-weather environment perception, it is related to computer vision and intelligent transportation technical field, steps include: acquisition includes the data set of multiple typical weather and illumination condition;Build physical real cross-domain visual simulation environment, based on training set data, carry out night simulation, dynamic simulation, rain fog simulation, generate the synthetic image with target domain feature;Optimization is carried out to feature, including: the feature fusion based on CutMix and the consistent feature representation based on CORAL Loss;Model adaptation is carried out, from three levels of basic model reconstruction, backbone network light weight, feature fusion structure optimization, systematic adaptation is carried out, improve the perception ability under rain, fog, night complex weather conditions.The method of the application can provide technical support for intelligent perception of urban road under complex weather through real-time deployment and application on edge device.

This invention discloses a method for predicting traffic conditions in large-scale urban road networks based on graph neural networks. The method first acquires road network topology and traffic time-series data, extracts road hierarchy information, and constructs graph data. The core lies in building a spatiotemporal graph neural network model that integrates dedicated road hierarchy components: a road hierarchy embedding layer maps discrete levels to continuous vectors to enhance feature semantics; a hierarchical global context module aggregates the global states of similar roads with linear complexity; and a dynamic cross-level attention module models the dynamic interaction dependencies between roads of different levels. This method suppresses noise interference from low-level roads through a hierarchical differentiation strategy and uses a separate weighted loss function for training. This invention effectively solves the problems of insufficient global perception, missing interaction modeling, and significant noise interference caused by neglecting road hierarchy semantics in existing technologies, significantly improving the accuracy and robustness of traffic condition prediction for large-scale urban road networks.

The present application belongs to the intelligent traffic technical field, specifically is a kind of trajectory restoration system based on urban traffic road network.The system of the present application includes traffic trajectory data acquisition module, GPS trajectory feature extraction module, GPS trajectory restoration learning module;Wherein traffic trajectory data acquisition module collects the latitude and longitude data of the vehicle driving on urban road in driving process, GPS trajectory feature extraction module extracts space-time feature to the low sampling rate trajectory point input neural network, and GPS trajectory restoration learning module inputs the output of last stage into new neural network model to predict the latitude and longitude information of missing sampling point in input low sampling rate trajectory.The present application can greatly improve the utilization of low sampling rate trajectory data;At the same time, combined with the topological structure of urban road network, the restored GPS trajectory is more in line with the real trajectory, effectively improves the utilization efficiency of trajectory data.

The application discloses a kind of urban road drainage devices, belong to urban road drainage technical field, rainwater flows from rainwater well lid to left flow guide box and right flow guide box of initiative component, when rainwater flow is larger, that is, the pressure of rainwater to inner wall of flow guide groove is greater than the elastic force of transverse elastic member, left flow guide box and right flow guide box resist the elastic force of transverse elastic member and mutually far away, make initiative piece pass through guide groove and move to the direction of far away from drainage tank, initiative piece drives baffle strip to separate from the drainage hole of rainwater well lid, make drainage hole completely open and then avoid sundries to block the drainage hole of rainwater well lid, after that, rainwater carries sundries and flows downward to conveying mechanism, and rainwater flowing through flow guide groove impacts the driving wheel of conveying mechanism, the driving wheel drives conveying mechanism to convey from back to front, conveying mechanism conveys sundries to collection tank and collects, therefore, the cleaning efficiency of the urban road drainage device of the embodiment is higher, and additional electric equipment is not needed, realizes intelligent clearing effect.

The present invention relates to a method for performing two-phase detection on abnormal congestion on an urban road on the basis of the polar coordinate transformation of trajectory data. The method includes two phases, i.e., the identification of an abnormal trajectory segment and the detection of incident-induced congestion. In the phase involving the identification of an abnormal trajectory segment, two key features (i.e., an average speed and a time when a road section is entered) are defined so as to capture trajectory segment features within spatio-temporal windows, and the features are affected by both incident-induced congestion and signal timing at downstream intersections; and on the basis of the two key features, the abnormal trajectory segment is identified by means of clustering. In the phase involving the detection of incident-induced congestion, anomaly rates of the spatio-temporal windows are defined; and on the basis of the anomaly rates, a decision tree is used to identify spatio-temporal windows in which incident-induced congestion occurs. Compared with the prior art, the present invention is applicable to urban road networks, and by means of the present invention, the detection of incident-induced congestion at a signal-cycle level in time and a vehicle-flow-level in space is realized.

This invention relates to the field of assisted driving technology, specifically to a method for detecting pole-shaped obstacles in assisted driving, comprising the following steps: creating a self-made pole-shaped obstacle dataset; labeling the acquired images using data annotation software, and processing the labeled files to divide them into training, validation, and test sets according to proportions; using an improved loss function based on the YOLOv5s network to backfeed network parameters; introducing the MK function into the original loss function; adding a dual-channel hybrid attention mechanism (CBAM) after the residual module; introducing an improved multi-scale feature fusion network structure into the neck network; training the model; and applying the trained model to pole-shaped obstacle detection. This method not only improves the recall and precision for detecting obstacles in the complex and ever-changing traffic environment of urban roads, but also solves the problem of variations in the size and shape of pole-shaped obstacles at different scales.

The application discloses a kind of based on high-efficiency structure diagram clustering realizes the method for urban traffic network planning, first using the characteristics that core intersection node in high threshold under SCAN algorithm and collaborative traffic function area are necessarily contained in low threshold result, the traffic area division result under different intersection correlation degree threshold and traffic area scale threshold is pre-organized into a kind of urban traffic road network hierarchical index model;Second, in online query stage, by parameter analysis and index positioning processing to the intersection correlation degree threshold input by user, quickly locate to corresponding target traffic hierarchical tree;Subsequently, using the hierarchical relationship and threshold screening processing of target traffic hierarchical tree, replace traditional complex full road network traversal operation, quickly extract traffic subnet node set;Finally, based on the initial clustering member list extracted, accurately determine pivot node and outlier by label mapping and extraction processing in closed neighborhood structure, to realize the efficient clustering of large-scale urban road network data.

The utility model relates to a kind of rain season urban road low-lying road surface sewage well overflow prevention facilities, solve the problem of rainwater and sewage unable to be completely shunted when urban rainwater and sewage pipe network is reconstructed by objective condition, sewage pipe network congestion in rainy season, urban road low-lying place sewage well lid water problem of spouting.This facility includes the sewage well of being arranged in the urban low-lying road surface, the sewage well includes well shaft, well shaft upper end is provided with closed pressure well lid, pressure well lid upper side is provided with ordinary well lid;The top side of the well shaft is provided with high-level drainage pipeline, the high-level drainage pipeline is connected with regulating reservoir, the regulating reservoir is set in the high ground of urban low-lying road surface side, regulating reservoir bottom is provided with lifting pump, the lifting pump is connected to downstream non-low-lying place sewage well by pressure pipeline.The utility model avoids low-lying road surface sewage to spout, while setting regulating reservoir, shunt and regulate the sewage in sewage well, and play the role of adjustment between fine and rain, relieve the pressure of sewage pipe network.

This invention provides a collaborative control method for multiple bottleneck ramps and connecting road networks on expressways based on feedback control. This method treats the entire expressway mainline and each sub-region of the urban road network as continuous entities that can be represented by a macroscopic basic graph model, constructing a feedback control system based on real-time traffic detection data. The entire expressway mainline adopts dynamic pre-set point proportional-integral (PI) feedback control based on the macroscopic basic graph, while each urban road network unit adopts classical PI feedback control. The method includes the following steps: S1, construction of the research object and control unit; S2, traffic state parameters and model assumptions; S3, construction of the upper-level control framework; S4, feedback control decision system based on the macroscopic basic graph; S5, allocation and execution of the lower-level control total flow in individual control objects. The method proposed in this invention utilizes a simple and highly robust macroscopic basic graph to efficiently achieve collaborative control of large-scale expressways and urban road networks, thereby improving the overall traffic efficiency of the transportation system and providing a feasible new approach for urban traffic congestion management.

This invention relates to the field of geological safety risk monitoring technology, specifically a side-flipping type soil multi-parameter monitoring device and method with a fixed-depth implantation capability. It includes an outer tube, an inner tube coaxially arranged with the outer tube, a drill bit fixed to the bottom of the inner tube, and a sensor module. The outer tube has a sensor section sleeve and a sealing section sleeve sealed to its end. The outer wall of the sensor section sleeve has an installation groove, in which the sensor module is embedded. The static fixed-depth implantation method eliminates the need for drilling and excavation, minimizing disturbance to the original soil and urban road surfaces. Single-point deployment is simple and efficient, suitable for rapid large-scale deployment of monitoring points in densely populated urban areas. The outer tube employs a modular splicing structure, allowing for flexible adjustment of the implantation depth according to monitoring needs, enabling precise fixed-depth monitoring of soil layers. This solves the core problem of existing technologies being unable to simultaneously address deep monitoring and convenient deployment.

The application provides a kind of multi-target trajectory prediction method for urban road, improve the trajectory prediction precision and efficiency of automatic driving vehicle in multi-vehicle complex scene. First, the driving scene is divided into two levels of global scene and local scene by scene layering device;Then, the global scene and local scene are encoded by scene encoder, the global interaction features and local time sequence motion features are extracted respectively by adopting attention mechanism, and the fusion features with attitude invariance are generated;Finally, the adaptive anchor points are dynamically generated based on the fusion features by motion decoder, and the multi-modal future trajectory and confidence score of each target vehicle are output in parallel decoding. The application effectively solves the problems of large attitude loss and redundant calculation in existing methods through hierarchical scene representation and adaptive anchor point generation, significantly improves the accuracy and real-time performance of multi-target trajectory prediction.

A vehicle mileage estimation method based on remote sensing imagery and deep learning includes: constructing a self-labeled dataset by dividing high-resolution satellite images into grid cells; estimating vehicle density using a YOLO-based deep learning model, which achieves multi-scale feature fusion through a three-layer pyramid network for accurate vehicle detection; abstracting the urban road network as a graph structure and employing a cross-temporal graph neural network (CrossGraphNet) to build a model of the relationship between vehicle density and speed for accurate speed prediction; and training a semi-supervised graph neural network vehicle mileage estimation model using traffic count data from ground monitoring stations as ground truth. This model combines vehicle density and speed data with road topology relationships and uses a message passing algorithm to accurately estimate vehicle mileage. This invention overcomes the limitations of traditional methods, effectively improves the efficiency and accuracy of traffic monitoring, and provides strong data support for traffic management and planning.

This utility model discloses a water-retaining ecological tree pit for urban roads, comprising a circular tree pit composed of two semi-circular tree pits joined together; a rectangular planting trough vertically located at the center of the semi-circular tree pit; a fan-shaped rubber sheet disposed at the lower interior of the semi-circular tree pit; infiltration pipes evenly distributed on the fan-shaped rubber sheet; an L-shaped water collection pipe disposed within the rectangular planting trough; and a square annular water collection hopper disposed within the square annular tree pit formed by several curb stones. This utility model utilizes the square annular water collection hopper to collect rainwater and guide it into the two semi-circular tree pits, then through infiltration pipes, greatly improving the utilization rate of rainwater. The elastic deformation of the fan-shaped rubber sheet itself prevents stress from being completely transferred to the rigid tree pit, ensuring the stability and aesthetics of the tree pit during long-term use.

1. Name of this design product: Wide-edge anti-settlement manhole cover. 2. Purpose of this design: For use on urban roads to prevent manhole covers from sinking. 3. The key design features of this product are the combination of shape and pattern. 4. The image or photograph that best illustrates the design's key points: 3D view 1.

The utility model discloses a kind of urban road cleaning and powder pressure integrated sweeper, comprising: mobile car body, the cleaning component of the front side of mobile car body, the crushing compression component of the rear side of mobile car body, cleaning component can gather from both sides to middle with garbage cleaning;Crushing compression component includes: crushing assembly, compaction assembly, wherein crushing assembly has crushing box, crushing cutter group;Crushing box is equipped with the feed inlet of garbage receiving, crushing cutter group is located in crushing box, can carry out crushing treatment to garbage;Compaction assembly has compression bin, and the pressing plate that is driven to move up and down in compression bin;Wherein, cleaning component is equipped with the conveying component that can convey garbage from front to back between crushing compression component. The utility model realizes the integrated processing of garbage cleaning, crushing, compression, avoids multiple equipment step-by-step operation, effectively increases storage space, improves cleaning efficiency, reduces transportation cost.

The utility model belongs to the related technical field of guardrail, concretely relates to a novel city road and traffic engineering guardrail, including installation base, installation base is provided with two, two installation base's upper end all are fixedly connected with support column. The utility model discloses the mutual cooperation between the rotatory rod one, bevel gear no.

The application provides a kind of city road network data resource directory generation method and system combined with service atlas, it is related to city traffic data management technical field, first access city road network service association conduction source and road network basic data generate service data association conduction pool;Then, based on the service association conduction logic deduces the road network data association derivative relationship, forms data association derivative network;According to the dynamic adaptation of data association derivative network, the dynamic directory unit is constructed by combining road network data;Based on the service conduction attribute of dynamic directory unit, the association conduction link is generated;Finally, the dynamic directory unit and the association conduction link are integrated to form a closed-loop city road network data resource directory that can be dynamically updated, which effectively improves the management efficiency and utilization value of city road network data resources.

The utility model relates to the technical field of protection block, disclose an improved A -level road guardrail is with prevent blocking block, including prevent blocking block body, prevent blocking block body rear end penetrates and is fixedly connected with backplate, the backplate rear end is equipped with preset hole, prevent blocking block body top front end fixedly connected with arc plate, prevent blocking block body front end is equipped with through -hole, prevent blocking block body front end is provided with first bolt. In the utility model, through the cooperation between prevent blocking block body, backplate, preset hole, stand, arc plate, through -hole, compared with the cost of reconstruction is saved, the traffic recovery benefit brought by construction period shortening, the safety protection level is promoted, reduces the accident risk, the sustainable development, promotes the applicability of resource -conserving construction city road, expressway etc. asphalt or cement additional paving road section, the potential market demand of road reconstruction project.

The application provides a kind of urban vehicle carrying capacity scale optimization method and system based on mixed prediction, it is related to traffic transport engineering technical field, the method steps include obtaining city, traffic, running track, travel and point of interest data, and pre-processing;Supply capacity and travel demand mixed two-way prediction model is constructed, based on the upper limit of physical capacity of urban road and parking resources, combined with the reasonable sharing rate of taxicab in traffic structure to calculate the supply capacity, by fusing deep learning and traffic planning theory to simulate the space-time network distribution of origin-destination travel, obtain the initial carrying capacity scale based on travel demand;The initial carrying capacity scale is corrected based on the model of multimodal traffic development trend and estimated and adjusted based on horizontal city comparison, to obtain the recommended carrying capacity scale after optimization;Set up multi-dimensional monitoring index system, real-time monitoring and evaluation of the operation state of taxicab market, execute corresponding control response measures.

This application discloses a vehicle control method, device, vehicle, and storage medium, relating to the field of vehicle braking control technology. The method includes: acquiring navigation history data, obstacle occlusion information, and current vehicle speed for the current driving segment; determining a control strategy based on the obstacle occlusion information, the current vehicle speed, and multiple data points from the navigation history data; controlling the vehicle based on the control strategy. For complex occlusion scenarios on urban roads, the method integrates obstacle occlusion information, vehicle speed information, and navigation history distance information to determine a corresponding control strategy. This allows for early identification of occlusion risks and early braking intervention in complex urban road conditions, thereby effectively improving vehicle driving safety and reducing the probability of collisions.

This invention relates to the field of road speed bump technology, and more particularly to a retractable speed bump suitable for urban roads. It includes a triggering device, a force transmission device, a feedback device, and a recovery device pre-embedded in the road surface. The triggering device and the feedback device are spaced apart, with the force transmission device and the recovery device respectively located between them, and the recovery device positioned above the force transmission device. The triggering device includes a trigger block, trigger rods at both ends of the trigger block, and a compression spring damper located below the trigger block. The feedback device includes a retractable speed bump and fixed speed bumps on both sides of the retractable speed bump. The fixed speed bumps are fixedly connected to the asphalt surface layer by fixing pins. A tension spring damper is located below the retractable speed bump. This invention utilizes the lever principle and the cooperation of gears and rotating rods to achieve different driving experiences through speed control, reducing vehicle wear and increasing the driver's awareness of slowing down.

This invention provides a visual odometry based on a multi-scale feature aggregation network. Addressing the problem of large pose estimation errors in traditional deep learning visual odometry architectures when vehicles are turning, this invention introduces a feature aggregation module to fully utilize the details and semantic information in the multi-scale feature pyramid of the image, thus improving the accuracy of vehicle pose estimation. The feature aggregation module consists of three sub-modules: a spatiotemporally deformable convolutional fusion sub-module to enhance the extraction of detailed feature changes in the image; a gated attention ConvLSTM sub-module to handle the differences in semantic information of the vehicle in different driving states; and a cross-attention spatiotemporal feature interaction fusion module to enhance the complementary information between adjacent frames of the high-order feature map, further improving the reliability of pose prediction. Compared with traditional deep learning architectures, the method of this invention can effectively improve the accuracy of vehicle pose estimation in urban road scenes.

The utility model discloses a fine soft branch class middle and big shrub supporting device of multi -functional integration, is equipped with telescopic support rod, spiral support coil and fixing device, and the spiral support coil is based on telescopic support rod, can provide stable support to the branch and leaf of fine soft branch class middle and big shrub, prevent shrub lodging, and can utilize spiral support coil as elastic buffer to realize wind -resisting and shock -resisting, to stabilize the root system of shrub and prevent wind erosion, and, shrub can correspondingly dynamic adjustment growth form under the restraint of spiral support coil, and, with the height growth change of fine soft branch class middle and big shrub, can gradually stretch out upwards through the telescopic end of telescopic support rod, to make the spherical space surrounded by spiral support coil expand upwards the growth space of shrub, and can guide fine soft branch class middle and big shrub to grow upwards through the spherical space, avoid the branch of shrub in city road isolation band to droop and shield traffic sign.

1. Name of the design product: integrated intelligent signal lamp (small waist). 2. Use of the design product: the design product is used for indicating urban road traffic signal lamp. 3. Design points of the design product: combination of shape and pattern. 4. Picture or photo best indicating the design points: perspective view.

This application relates to a method and system for intelligent cable network mapping based on urban road networks. The method includes: determining a road network distribution map within the coverage area of ​​the cable's origin and destination equipment coordinates; performing path calculations on the road network distribution map using a multi-dimensional path algorithm to obtain the cable's routing path; generating cable channels along the cable's routing path on the urban road network; and generating working wells on the cable channels according to preset parameters to form a cable network routing map within the coverage area of ​​the origin and destination equipment coordinates. This application cleverly utilizes the relationship between cable laying and the road network, automatically mapping the cable network based on the cable's origin and destination and road network information. It effectively digitizes cables with unclear laying records, reduces the time and effort required for manual on-site data collection, and solves the problem of high costs associated with collecting existing cable routing information.

The present application belongs to the technical field of intelligent transportation, and specifically discloses a kind of urban road network traffic state and congestion propagation probability prediction method and system.The present application first introduces spatial distance, historical traffic correlation and other information on the basis of road topology, forms a weighted checkpoint road network;Secondly, a conditional denoising diffusion model based on checkpoint space-time graph is proposed, which models the conditional distribution of future multi-step graph signals by forward noise addition and reverse denoising process, with historical multi-step graph signals and road network structure as conditions.The present application obtains multiple future traffic evolution sample trajectories by multiple sampling, maps node operation indicators to discrete congestion levels, counts the occurrence frequency of each node at different congestion levels, and obtains node congestion level probability;Further, the time sequence co-occurrence relationship of congestion state between adjacent nodes is counted, the propagation conditional probability of congestion in the road network is estimated, and the key node influence degree index and high-risk propagation path are constructed.