540 results about "Carriageway" patented technology

A vehicular driving assist system includes at least one sensor disposed at a vehicle and having a field of sensing exterior of the vehicle. An ECU includes circuitry and associated software, with the circuitry including a data processor for processing sensor data captured by the sensor to detect presence of objects in the field of sensing of the sensor. The ECU, responsive to processing by the data processor at the ECU of sensor data captured by the sensor, determines traffic attributes for a plurality of traffic lanes of a road the vehicle is travelling along. The ECU, responsive to determining the traffic attributes determines a predicted traffic value based on the traffic attributes and an output from a trained prediction model. The ECU, responsive to determining the predicted value, determines a traffic jam probability for at least one traffic lane based on the predicted value and the respective traffic attributes.

The invention discloses a traffic scene risk identification method and device considering dynamic and static information fusion, and a storage medium. The method comprises the steps of 1, obtaining a traffic scene high-precision map and a time sequence track of each vehicle; track points in the time sequence tracks are converted into a high-precision map coordinate system, lane matching is carried out, and a time sequence track high-precision map of each vehicle is obtained; 2, predicting vehicle positions, and extracting dynamic and static characteristics of each vehicle time sequence track; 3, fusing the dynamic and static features of each vehicle to obtain a fused feature; inputting the fusion features of all vehicles into a risk factor prediction model to predict and obtain dynamic and static risk factor prediction results; on the basis of prediction errors between dynamic and static risk factor prediction results and corresponding real results, combined with vehicle position prediction errors, calculating a comprehensive risk value of the traffic scene; the equipment and the storage medium are used for implementing the method. The method provides a new thought for traffic risk identification.

The invention relates to the technical field of intelligent driving, and discloses a lane line detection method based on an attention mechanism, and the method comprises the steps: obtaining a lane line data set for data enhancement processing; constructing a backbone network EMAResNet, and fusing the EMA with a backbone network ResNet 18; inserting a self-attention layer SA between the backbone network and the neck network; the neck network adopts a feature pyramid network FPN to be fused with an improved PSA module; inputting the feature map generated by the neck network into a decoder, respectively generating a confidence map and an offset map by using the key nodding head and the offset head in the decoder, and constructing a lane line according to the confidence map and the offset map; and based on the lane line data set, performing model training by using four loss functions of auxiliary loss, key point head loss, offset head loss and focus loss, and performing lane line detection by using the optimized model. Compared with the prior art, the method has the advantages that the perception capability of the model for different scale features is enhanced, the complex scene can be better processed, and the lane line detection precision and robustness are improved.

The embodiment of the invention provides a traffic flow simulation parameter calibration method and device, equipment and a storage medium, and relates to the technical field of data processing. According to the method, track data and current speed data of corresponding vehicles are obtained, lane data obtained by lane area division at an intersection are obtained, multiple groups of car-following vehicle pairs are selected from the vehicles according to passing timestamps of the vehicles passing through lane stop lines, and the car-following vehicle pairs are selected according to the passing timestamps of the vehicles passing through the lane stop lines. And inputting the current radar data into the car-following model for data processing to obtain predicted speed data of a rear car, performing error statistics according to the current speed data and the predicted speed data corresponding to the rear car by using an orthogonal analysis method to obtain an error result, and calibrating simulation parameters in the car-following model based on the error result to obtain target simulation parameters. A high-precision map does not need to be introduced, multiple groups of following vehicle pairs are selected by using timestamps, adverse effects of heterogeneous data on result accuracy are effectively avoided, and the accuracy of a calibration result is improved by using an orthogonal analysis method.

A driving assistance method uses a controller to perform automated lane change to control the own vehicle in such a way that the own vehicle makes a lane change under a condition that the passenger is at least in contact with the steering wheel, the driving assistance method causing the controller to perform processing including: selecting a target lane; and when automated lane change from a current lane to the target lane includes a first automated lane change from a first lane to a second lane and a second automated lane change from the second lane to a third lane, performing lane-keeping assistance under a condition that the passenger is at least in contact with the steering wheel from an end of control of the first automated lane change until a start of control of the second automated lane change.

The invention belongs to the technical field of expressway passenger and truck lanes, and particularly relates to an expressway passenger and truck lane dynamic allocation optimization method which comprises the following specific steps: S1, data acquisition and preprocessing: integrating ETC and radar multi-source data, cleaning and fusing original data, and accurately distinguishing small passenger cars and trucks by using an advanced vehicle type recognition technology, so as to obtain a new vehicle type recognition technology; a reliable data basis is provided for subsequent analysis; s2, traffic state perception and prediction: calculating key traffic parameters of traffic flow, speed and density based on the preprocessed data; and a scientific prediction model is called. According to the method, the future short-time passenger and freight predicted flow provided by traffic state perception and prediction is received, and the lane allocation decision is made based on the dynamic data, so that the number of the passenger car special lanes can be increased in time when the flow of the passenger cars is sharply increased in the morning peak, the delay of the passenger cars on the passenger and freight mixed lanes is reduced, and the overall traffic efficiency is effectively improved.

The invention relates to the technical field of image recognition, and discloses a YOLO v9-based lane line recognition method under strong light and weak light backgrounds, and the method comprises the steps: carrying out the scene judgment of first to-be-recognized image data based on the first to-be-recognized image data and illumination intensity data at the same moment in the automatic driving process of a vehicle, and carrying out the recognition of the first to-be-recognized image data; performing strong light suppression processing on the first to-be-recognized image data belonging to the strong light scene, and performing weak light enhancement processing on the first to-be-recognized image data belonging to the weak light scene to obtain second to-be-recognized image data; according to the illumination intensity data, a pre-trained lane line identification model is adopted to carry out lane line identification on the second to-be-identified image data to obtain a lane line identification result, the lane line identification model is constructed by adopting an improved YOLO v9 model, and a neck network of the improved YOLO v9 model is integrated with a channel attention mechanism and a space attention mechanism. According to the method, the accuracy of target detection is effectively improved.

The invention relates to the technical field of lane line detection, in particular to a 3D-BEV lane line sensing method based on polar coordinates, and the method comprises the steps: carrying out the 3D lane line detection through employing the polar coordinates to replace a conventional method based on a rectangular coordinate system, employing a sliding long-strip-shaped window convolution to adapt to a polar coordinate system, and carrying out the 3D lane line detection through employing the sliding long-strip-shaped window convolution. According to the method, the lane line in the picture can be accurately identified in the polar coordinate system, accurate positioning is carried out in the 3D space, the false detection rate is greatly reduced, the radial distribution characteristic of perspective projection can be more naturally matched, and the modeling precision of the geometric structure of the lane line is remarkably improved.

The present application provides a 3D lane line detection method and device. The method includes: obtaining an image semantic feature matrix and a multidimensional depth feature matrix based on a road scene image and a detection model, converting the multidimensional depth feature matrix into depth probabilities at different depths of the camera's visual cone, and generating lane line BEV features based on the image semantic feature matrix and the depth probabilities at different depths of the camera's visual cone; then, supervising the lane line BEV features based on the road scene image and point cloud ground truth data and performing explicit depth supervision on the multidimensional depth feature matrix to update model parameters until model training is complete; in actual application, performing 3D lane line detection based on the 3D lane line detection model and real-time road scene images to obtain the lane line coordinates in the 3D coordinate system of the vehicle. The method and device can effectively identify 3D lane lines, have low computational complexity, high computational efficiency, and can adapt to complex and changing driving scenarios.

The invention discloses a lane line detection method and device and a storage medium, and the detection method comprises the steps: carrying out the lane line detection of a preprocessed road image, and obtaining each lane line instance; based on each lane line instance, processing the original road image to obtain a connected domain of each lane line; calculating the attribute of the connected domain of each lane line; counting the number of connected domains meeting attribute threshold conditions in each lane line according to the attributes of the connected domains of each lane line; determining the type of the lane line according to the number of connected domains meeting an attribute threshold condition in each lane line; centroids of connected domains meeting attribute threshold conditions in the dotted lane lines are extracted, and all the connected domains are sorted according to the coordinate sizes of the centroids of the connected domains; and screening a plurality of continuous connected domains in the space according to the centroids of two adjacent connected domains to realize positioning of each dotted line block in the dotted line lane line. According to the invention, on the basis of lane line detection, lane line type discrimination and accurate positioning of the dotted line block are realized.

The invention provides an intelligent driving scene reconstruction method and system and a storage medium, and the method comprises the steps: obtaining an OpenStretMap map file based on the real vehicle GPS data, and carrying out the lane-level road network matching based on the OpenStretMap map file; the OpenStreetMap map file obtained after matching of the lane level road network is converted into an OpenDR IVE map file; based on real vehicle GPS data, generating a main vehicle track by using a FastDTW algorithm; based on the environment vehicle information, generating a dynamic interaction object track through a Hungary matching algorithm; and fusing the OpenDRIVE map file, the main vehicle track and the dynamic interaction object track, and reconstructing a scene file in an OpenSCENARIO format in preset simulation software. According to the method, automatic reconstruction is carried out by utilizing the real vehicle data, the real vehicle data can be automatically stored as a universal OpenSCENARIO scene file, simulation testing can be carried out in different types of automatic driving simulation software, a real driving scene can be accurately simulated, and a reliable simulation environment is provided for development, testing and verification of an intelligent driving algorithm.

The invention provides a construction method for a viaduct in a narrow space. The construction method for the viaduct in the narrow space comprises the following steps that 1, a pile foundation platform is constructed; 2, constructing a cast-in-place bent cap; step 3, mounting a portal structure; step 4, component acceptance and transportation; 5, on-site assembling is conducted; step 6, mounting a temporary bracket; step 7, trial hoisting; 8, mounting the box girder; ninthly, the support is detached; the portal structure is slidably mounted on the rail distribution beam arranged on the non-motorized vehicle lane, the temporary support foundation is arranged on the traffic lane, so that the temporary support disperses load through the column bottom distribution beam, and the top is provided with the adjusting steel pipe to finely adjust the elevation of the box beam. The box girders are spliced in sections, the weight of the portal structure hoisted at a time can be reduced through sectional welding forming of the connecting cross beams, the portal structure adapts to small-space operation, and accumulative errors are reduced through sectional welding; a clearance is reserved during disassembly, collision between the box girder and the support is avoided, the disassembly process is controllable, and the integrity of a main body structure is protected.

The invention discloses a vehicle augmented reality navigation method, an augmented reality head-up display device and a vehicle. The method comprises the following steps: acquiring fork road data of a navigation route according to acquired lane-level navigation map data; at least one reverse guiding element is rendered and displayed in an augmented reality head-up display view field range of the vehicle in response to the situation that the fork road data meets a preset triggering condition, the fork road data are obtained based on positioning information of the vehicle and lane-level navigation map data, and different reverse guiding elements are mapped in different forbidden lanes; the forbidden lane is a lane on which the vehicle is forbidden and which is determined based on fork data and perception data of the vehicle. According to the invention, the technical problem of low accuracy and saliency of navigation guidance for a driver in a fork road driving scene in the prior art is solved.

The invention discloses a passable lane identification method and a vehicle, and belongs to the technical field of automatic driving. According to the technical scheme provided by the embodiment of the invention, under the condition that the target vehicle is in the automatic driving state, the target lane mask is determined by utilizing the environmental perception information, the local map information and the navigation instruction set in the driving direction of the target vehicle, namely, the position identification of the passable lane is realized by utilizing the multi-source and multi-mode data. The passable lane is determined by using the environmental perception information and the target lane mask subsequently, and the accuracy of the obtained passable lane is high.

A driving control method is performed to execute a lane-change control for controlling a host vehicle to autonomously change lanes from a first lane to an adjacent second lane using a processor of a driving control device that controls vehicle speed and steering of the host vehicle traveling in the first lane in an autonomous driving mode. The processor determines that the lane-change control can be executed upon determining that the other vehicle has been detected in a detection zone of the second lane, based on a detection result of a sensor. The processor determines that the lane-change control cannot be executed upon determining that the other has not been detected within the detection zone of the second lane. The processor outputs information regarding whether the lane-change control can be executed.

The invention discloses an automatic driving method based on an improved Astar algorithm and a hierarchical state machine, and the method consists of three parts: road topology abstract graph construction, a lane adaptive Astar algorithm and the hierarchical state machine, and forms an efficient and cooperative'planning-decision 'integrated frame. Firstly, a road topology abstract graph is constructed. Secondly, path planning is carried out by adopting an improved lane adaptive Astar algorithm, and two stages of search strategies are included: in the first stage, road section-level global planning is carried out on a road topology abstract graph, and a macroscopic feasible path is rapidly determined; in the second stage, lane-level refined path generation is carried out in the selected road section, road curvature, width and static and dynamic obstacle distribution are comprehensively considered, and a smooth and safe accurate driving track meeting vehicle dynamics constraints is generated. Finally, a hierarchical state machine is designed, and the top layer is responsible for managing a driving mode and ensuring the global consistency of decisions; and the bottom layer executes fine speed control and lane changing control according to the top layer instruction.

The roadside overhead type parking equipment with the vehicle carrying plate capable of moving forwards and lifting structurally comprises a fixed frame 1 and a forward moving frame 2, and fixed frame single stand columns with the bottoms fixed to the roadside ground are arranged below the middle portions of edge beams on the two sides of the fixed frame 1; the forward moving frame 2 is arranged between the inner sides of the left and right boundary beams of the fixing frame and can move forwards in the direction of a carriageway. And a vehicle carrying plate 3 hung by a lifting rope chain 31 is arranged in a hollow area of the forward moving frame 2. After the forward moving frame 2 moves forwards to the position above a road surface traffic lane, the vehicle carrying plate 3 can descend to the road surface to pick up the vehicle 4. Compared with an existing similar scheme, the structure is simpler, the vehicle carrying plate is prevented from falling by a constructed object, safety is higher, the overall structure is balanced and stable, and stress is more reasonable. The device can be arranged side by side along the roadside, can also be arranged independently at will, and is more flexible in application.

The invention relates to a lane selection method, electronic equipment, a vehicle and a product, and relates to the technical field of intelligent driving control. According to the method, at least one primary lane is determined according to the current position of the vehicle and the position of the next turning point in the navigation route of the vehicle; and then, according to the lane information of each primarily-selected lane, selecting a target lane which is suggested to be driven in for the vehicle from at least one primarily-selected lane. According to the invention, the accuracy and flexibility of lane selection for the vehicle can be improved, and then the safety, experience and traffic efficiency of automatic driving of the vehicle are improved.

The invention relates to the technical field of intelligent traffic, in particular to a vehicle driving area generation method and system, and the method comprises the steps: obtaining a vehicle position coordinate in a traffic image, and constructing a time-space point cloud; carrying out outlier filtering on the space-time point clouds, carrying out lane clustering based on the filtered space-time point clouds, and separating out point cloud clusters representing different lanes; calculating an alpha value based on the space density of the space-time point cloud; inputting the alpha value into an Alpha Shape algorithm to generate a road network level driving area, and independently applying the alpha value to each point cloud cluster to generate a lane level driving area; and generating a dynamic obstacle area based on the filtered static vehicle position points, integrating the generated road network level area and the lane level driving area, and outputting a vehicle multi-level driving area. According to the invention, the problems that a real dynamic driving area is difficult to accurately extract and abnormal tracks and outliers are insufficient to process in the prior art are effectively solved, and the accuracy of driving area generation and the adaptability to a complex traffic environment are improved.

The invention discloses a method for determining an initial modulus of a semi-rigid base of an in-service asphalt pavement, and relates to the technical field of road engineering, a preset monitoring point of the in-service asphalt pavement is detected through a drop weight deflectometer, and a base modulus value is obtained through back calculation based on a deflection detection result; based on the transverse distribution coefficient of the carriageway, respectively calculating the accumulated axle load action times of the preset monitoring points; establishing a basic layer modulus damage model with basic layer initial modulus parameters by utilizing the structure behavior equation; and detecting basic layer modulus values under different accumulated axle load action times by using a drop weight deflectometer, performing regression fitting to obtain model parameters, obtaining a complete basic layer modulus damage model, and obtaining a basic layer initial modulus. According to the method, the initial modulus of the base layer is determined through the drop weight deflectometer.

The invention discloses a road passage control method and system based on visual detection, and relates to the technical field of road passage control methods, and the method comprises the steps: determining a release lane passage road according to a multi-phase passage road, and determining the congestion condition of each driving road, according to the congestion condition of each driving road, the plurality of traffic routes and the real-time image of the multi-phase passing road, the traffic guidance of the traffic signal to each driving road is determined, and the accuracy of the traffic guidance of the traffic signal to each driving road is improved. Determining an overall congestion combination according to the abnormal congestion event, the daily congestion event and the traffic plan project of each driving road; according to the traffic combination content of each overall congestion combination, the sub-traffic route of each driving road and the corresponding road peak driving flow, the driving load level corresponding to each driving road is determined, the accuracy of the driving load level corresponding to each driving road is improved, and intelligent traffic regulation and control of each driving road are triggered.

The present invention discloses a lane region segmentation method, system, electronic device, and storage medium, relating to the field of intelligent transportation. The method comprises the following steps: 1) inputting a road image captured by a road monitoring probe and extracting straight lines from the road image using the Hough method; 2) clustering the extracted lines and sorting them by angle and distance to the origin, taking the first and last straight lines l1 and l2 after the sorting; 3) using l1 and l2 to segment the road image to obtain an image of the road surface area; 4) calculating the histogram of the segmented image, using grayscale features to find two grayscale thresholds, and using dual-threshold binarization to segment the lane region; 5) using morphological methods to remove interference from small image holes, and using connected domain detection to remove the median strip, thereby completing the lane region.

A method for controlling a driving mode transition of an autonomous driving vehicle may safely perform a lane change to avoid a collision accident with the other vehicle and prevent an injury to a joint, etc., while minimizing a sense of heterogeneity of a driver according to minimization of rotational steering of a steering wheel by determining whether the other vehicle in a next lane suddenly cuts in in an autonomous driving controller while the autonomous driving vehicle is driving in a manual driving mode and determining a safety distance from a rear vehicle to minimize rotational steering of the steering wheel held by the driver and at the same time perform partial braking control by autonomous driving mode transition control using an autonomous driving controller.

The utility model provides a traffic lane flow guiding device which comprises a solar power generation panel and connecting stairs, a group of bridges for pedestrians to pass through are arranged at the lower end of the solar power generation panel, the left side and the right side of each bridge are respectively provided with a group of connecting stairs for the pedestrians to get on and off the bridges, and a plurality of groups of lane guiding marks are evenly distributed on the front side and the rear side of each bridge. The number of the lane guide marks on one side is consistent with the number of the lanes, the lower end of the bridge is provided with a lane main body for vehicles to pass through, and the lane main body is internally provided with a plurality of groups of lanes for vehicles to pass through. Natural energy is utilized and stored by using a battery and a solar power generation panel, driving direction indication is performed on a single lane by using a variable indicator, and a lane position and a lane driving direction are identified by using a lane cursor.

Provided is a travel road recognition device that can accurately recognize a travel road end of a travel road on which an own vehicle travels. A travel road recognition device of the present invention is a travel road recognition device that recognizes the travel road end of the travel road on which an own vehicle 301 travels, and includes: a laser radar 101 that emits a laser bean from the own vehicle 301 toward the travel road; a road surface determination unit 203 that obtains a cross slope of the travel road based on coordinate values of a point cloud obtained by the laser radar 101; and a road end determination unit 204 that obtains a change point at which a slope angle changes in the cross slope of the travel road obtained by the road surface determination unit 203, and obtains coordinate values of at least one travel road end of both sides in a cross direction of the travel road based on the coordinate values of the change point.

Provided in the present application are a vehicle driving control method, and a device. The method comprises: determining the distance between a vehicle and an intersection; when the distance is less than a first distance threshold, acquiring camera image data and radar point cloud data; on the basis of the camera image data and the radar point cloud data, determining perception information; on the basis of the perception information, determining whether the vehicle needs to make a lane change; and when it is determined that the vehicle needs to make a lane change, generating lane change path planning information on the basis of navigation map information, navigation positioning information and the perception information, wherein the lane change path planning information is used for controlling the vehicle to complete a lane change before the intersection. The method is used for achieving the effect of using a standard map to efficiently perform lane-level lane change navigation in an energy-saving manner.