1034 results about "Carriageway" patented technology

The invention discloses a logistics park vehicle path planning method and system, and the method comprises the steps: obtaining the real-time position and task state information of a vehicle in a park, dynamically constructing a vehicle path planning network model, dividing a road into nodes and edges, and forming a directed weighted graph; according to the directed weighted graph, an improved multi-lane algorithm is adopted, the path length, the congestion degree and the vehicle characteristic factors are comprehensively considered, and the optimal path of each vehicle is calculated; for the optimal path, introducing a virtual lane and a time dimension, pre-judging occupation conditions of multiple vehicles on the virtual lane for each time slice, and constructing a conflict constraint matrix; obtaining park high-precision map data, extracting road network topology, lane lines and traffic sign marking elements, performing lane-level refinement on the optimal path, and generating a driving track; and through a multi-sensor fusion positioning technology, obtaining high-precision position and attitude information of the vehicle, matching the high-precision position and attitude information with the driving track, and calculating a track tracking error.

The invention relates to a vehicle obstacle avoidance trajectory planning method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining information of obstacles around a current vehicle; predicting driving tracks of all obstacles in a future preset time period according to the information of the obstacles around the current vehicle; under the condition that the condition that no fast approaching obstacle exists behind the current vehicle is obtained based on the driving track analysis, target obstacles needing to be subjected to in-lane obstacle avoidance are screened and recognized; calculating a lane occupation space of the target obstacle based on the driving data of the target obstacle; calculating the lane driving space of the current vehicle according to the lane occupation space of the target obstacle; and performing path planning and speed planning solution based on the lane driving space of the current vehicle, and generating an obstacle avoidance track of the current vehicle. By adopting the method, vehicles in the same direction of the adjacent lanes can be effectively avoided during driving on the expressway, and the driving safety is improved.

The invention provides a vehicle driving control method and device. The method comprises: determining a distance from a vehicle to an intersection; when the distance is smaller than a first distance threshold value, camera image data and radar point cloud data are acquired; determining perception information according to the camera image data and the radar point cloud data; judging whether the vehicle needs to change lanes or not according to the sensing information; when it is determined that the vehicle needs to change lanes, lane changing path planning information is generated according to the navigation map information, the navigation positioning information and the sensing information, and the lane changing path planning information is used for controlling the vehicle to complete lane changing in front of the intersection. The method is used for achieving the effect of efficient and energy-saving lane-level lane-changing navigation by adopting a standard map.

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 relates to a light blanket projection control method and device, computer equipment and a readable storage medium. The method comprises the steps of obtaining a road image collected by a vehicle camera at a current time step under the condition that a vehicle projects a light blanket; performing lane line detection and light blanket boundary detection on the road image, and determining deviation information between a lane line and a light blanket boundary in the road image according to a detection result; based on a perspective transformation matrix between an image coordinate system and a light blanket projection coordinate system, mapping the deviation information from the image coordinate system to the light blanket projection coordinate system to obtain mapped deviation information; adjusting light blanket projection control information corresponding to the next time step of the current time step according to the mapped deviation information; and the vehicle is controlled to perform light blanket projection at the next time step according to the light blanket projection control information, so that the light blankets projected under various road conditions are accurately matched with the lane lines, the road perception ability of a driver is improved, and the driving safety of the vehicle is ensured.

Provided is a vehicle control device that uses a target inter-vehicle distance corresponding to a vehicle in front with respect to a travel lane of an ego-vehicle to enable safe travel while securing an inter-vehicle distance that reduces the level of fear the user is made to feel. The vehicle control device 60 calculates the travel lane area (A) of the ego-vehicle mirroring the area (the preceding vehicle blocking area (B) and the viewing angle blocking area (C)) blocked by the vehicle (preceding vehicle) which is in front of the ego-vehicle and the speed of the ego-vehicle, in the area (the travel lane area (A)) of the lane on which the ego-vehicle travels detected by the sensor, and in a case where the calculated travel lane area (A) of the ego-vehicle is equal to or less than a threshold value, performs vehicle control to adjust the inter-vehicle distance between the ego-vehicle and the vehicle in front, thereby enabling vehicle control while reducing the level of fear the user is made to feel.

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 invention discloses a lane line recognition method and device based on a time sequence aerial view, a non-temporary computer readable storage medium and a vehicle, and the method comprises the steps: obtaining an image in a preset range in front of the vehicle, and carrying out the feature extraction of the image, and obtaining the features of a plurality of frames of images; storing the extracted multi-frame image features into a preset image feature storage queue according to a time sequence; respectively obtaining bird's-eye view features of a historical frame and bird's-eye view features of a current frame in the preset image feature storage queue; fusing the bird's-eye view feature of the historical frame and the bird's-eye view feature of the current frame to obtain an updated bird's-eye view feature of the historical frame; and carrying out lane line identification by adopting the updated aerial view features of the historical frames. According to the method, the aerial view features with the time sequence information are introduced to update the aerial view features of the historical frames, and powerful support is provided for improving the prediction performance under the condition that the lane lines are shielded.

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.

An apparatus for controlling an autonomous vehicle disclosure may include a processor and a memory configured to be operatively connected to the processor and to store at least one code performed in the processor, wherein the memory may store a code that, when executed by the processor, causes the processor to control the autonomous vehicle to travel on the basis of a distance from a preceding vehicle in a travel lane in which the autonomous vehicle travels or a preset speed, determine a risk level of a lane change on the basis of a speed of the autonomous vehicle, a speed of a side vehicle traveling in a target lane of a lane change, and a distance between the autonomous vehicle and the side vehicle upon occurrence of a lane change request, and perform longitudinal or lateral control for the lane change on the basis of the risk level.

A vehicle includes a windshield configured to transmit a front view of the vehicle to an interior of the vehicle, and a display device configured to display information set to overlap the front view on the windshield, and to divide the windshield into a first display area including a driving lane, both sides of the driving lane, and an upper settings area, and at least one peripheral display area located in a periphery of the first display area, display at least one of driving energy information, speed information, driving lane information, augmented reality (AR) turn by turn (TBT) information, traffic signal information, a distance to a vehicle ahead, warnings, and surrounding vehicles information on the first display area, and display at least one of destination arrival information, media content information, surrounding real image, audio video navigation (AVN) menu, speed limit information, and local geographic information on the peripheral display area.

This disclosure relates to automatic lane and and / or terrain detection and recognition under various ambient and driving conditions for robotic / vehicular control purposes / applications. In one aspect, a rule-based detection system is configured to perform lane recognition using optical images. Various edge detection thresholds are adaptively tuned from frame to frame using a feedback signal derived from a fuzzy logic inference mechanism. Such detection techniques may also be adapted for drivable region detection, which may be fused together with drivable region detection based on LiDAR cloud point. Such detection techniques may be further adapted for a preprocessing of optical images of road to generate preprocessed images that may then be processed by learning-based lane detection models. In another aspect, an intelligent terrain classification system may be configured to include a fusion of both a vision-based terrain classification convolutional neural network (CNN) and a parallel proprioception-based terrain classification CNN. These CNNs may be configured to process a small number of selected set of proprioceptive signals and to adaptively detect / classify the terrain as platform-independent as possible.

The invention discloses an intelligent traffic signal control method and system based on Agent-ARIMA, and a program product. The intelligent traffic signal control method comprises the steps of calculating the shortest green light time of each intersection direction, distributing the green light time of each direction, distributing the green light time of left-turn and straight lanes, adjusting the traffic cycle, calculating the time weight offset of multiple intersections, and predicting the traffic flow in the future by using an ARIMA model. And inputting the prediction time of the ARIMA algorithm into the LLM-Agent agent for time prediction, and the like. The method is suitable for different city scales, time distribution of the traffic lights is dynamically adjusted through accurate prediction and analysis of the traffic flow, the traffic jam condition of a large city can be optimized, and the traffic efficiency of a small city can also be improved.

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.

A vehicle system recognizes a situation of surroundings of a host vehicle, automatically controls at least steering of the host vehicle on the basis of the recognized situation of the surroundings to cause the host vehicle to perform lane change, acquires information on a route from a navigation device guiding the route along which the host vehicle travels, and suppresses control for assisting the steering on the basis of an event regarding the route when the event occurs in the navigation device.

The invention discloses a lane construction method and device, equipment, a storage medium and a product, and relates to the technical field of intelligent driving, and the method comprises the steps: carrying out the coordinate point splicing and coordinate point fitting based on a pre-obtained inter-frame lane map, and obtaining a lane fitting curve; according to the lane fitting curve, lane coordinate sequence construction is carried out to obtain a scene level lane sequence, specifically, after interframe lane maps are spliced, fitting is carried out on a spliced coordinate point sequence, then operations such as equidistant truncation and coordinate point interpolation are carried out on the fitting curve to construct the scene level lane coordinate sequence, and the scene level lane sequence is obtained. Therefore, the lane construction precision is improved, and the accuracy of vehicle lane binding and vehicle lane change and cut-in recognition is improved.

An autonomous driving lane-keeping control method, system and apparatus, and a storage medium, which can achieve a high-precision lane-keeping function in through lanes having weak GPS signals and / or in narrow through lanes. The method comprises: according to a control cycle, on the basis of the deviation of an ego vehicle with respect to a lane center line at the previous moment and the deviation observation value of the ego vehicle with respect to the lane center line at the previous moment, obtaining the deviation observation value of the ego vehicle with respect to the lane center line at the current moment; on the basis of the deviation observation value at the current moment, correcting the position of the ego vehicle at the current moment; on the basis of the corrected position of the ego vehicle, acquiring the lane center line at the current moment; and generating a current path on the basis of the lane center line, and performing lane-keeping control on the basis of the current path.

The embodiments of this specification disclose a method, device and medium for diversion induction control of a highway toll station, which relates to the field of intelligent transportation technology and is used to alleviate the congestion problem of highway toll stations. The method includes: obtaining the traffic data and scene data of the highway toll station area to be induced by pre-installing multiple types of acquisition equipment; establishing a digital twin model of the highway toll station area to be induced based on the traffic data and scene data; classifying the vehicles in the area based on the flow data of the gantry pre-transaction system to obtain the first vehicle and the second vehicle; determining the current traffic data and current scene data corresponding to the vehicle based on the digital twin model, and extracting the traffic flow feature data; clustering the neighborhood topology of the traffic flow feature data to obtain the cluster center; determining the traffic state estimation of the vehicle based on the cluster center, so as to perform lane induction diversion for the first vehicle and the second vehicle based on the traffic state estimation.

An image recognition apparatus comprises an image information acquirer that acquires image information in a given cycle by capturing an image of a traveling path along which an own vehicle travels, a road sign recognizer that recognizes a road sign based on the image information and a traffic lane recognizer that recognizes traffic lanes located in the traveling path based on the image information. A memory is provided in the image recognition apparatus to store traffic lane information about a traffic lane recognized by the traffic lane recognizer in a time series. A determiner is also provided to determine if the road sign recognized by the road sign recognizer is for an own traffic lane by choosing a most suitable traffic lane among the traffic lanes recognized for a given period based on the traffic lane information stored in the time series.

The invention discloses a lane changing recognition method, device and equipment, a storage medium and a product, and relates to the technical field of intelligent driving. Determining a current lane scene, wherein the current lane scene comprises a lane separation scene and / or a lane combination scene; according to the driving map topological relation information and the driving scene target data frame, lane separation lane change identification is carried out on the lane separation scene, and / or lane combination lane change identification is carried out on the lane combination scene. Therefore, the behavior recognition accuracy of the intelligent driving system during lane separation and lane combination of the vehicle is improved.

Techniques for segmenting and classifying a representation of aggregated sensor data from a scene are discussed herein. Sensor data may be collected during multiple traversals of a same scene, and the sensor data may be filtered to remove portions of the sensor data not relevant to road network maps. In some examples, the filtered data may be aggregated and represented in voxels of a three-dimensional voxel space, from which an image representing a top-down view of the scene may be generated, though other views are also contemplated. Operations may include segmenting and / or classifying the image e.g., by a trained machine-learned model, to associate class labels indicative of map elements (e.g., driving lane, stop line, turn lane, and the like) with segments identified in the image. Additionally, techniques may create or update road network maps based on segmented and semantically labeled image(s) of various portions of an environment.

The invention relates to a transport facility (100), having a first traction cable (11) that describes a first closed loop (10) and is configured to be driven by at least a first drive means (12) at a nominal linear velocity, and a vehicle (30) having a coupling device (31) for coupling the vehicle to the first traction cable, the transport facility comprising at least a first traffic lane (101) having at least a first segment (110) comprising at least one track (111) along the first traction cable, the first traffic lane comprising at least a second segment (120), the transport facility being configured so that the vehicle is coupled to the first traction cable and pulled by same at the nominal velocity so as to pass through the first segment and the second segment, the first traction cable fully supporting the vehicle and driving it at the nominal speed along the second segment.

The invention provides a mobile illumination detection device and system, and the device comprises the steps: setting a plurality of illumination detection points through a control module, controlling a mobile carrier to sequentially move to each illumination detection point, controlling an illumination detection module to carry out the illumination detection of each illumination detection point, and generating illumination detection data; generating illumination adjustment data through a dimming module according to the illumination detection data when the illumination conditions of the target detection area are inconsistent, so as to carry out dimming operation on each target roadside illumination device; therefore, the illumination conditions of the plurality of roadside illumination devices in the target detection area on the lane pavement can be automatically detected and adjusted, and the technical problems of high resource cost, low working efficiency, poor detection precision and obvious traffic potential safety hazards caused by an existing manual or semi-manual illumination detection method are effectively avoided. And the illumination conditions of the target detection area can be consistent, so that the illumination of road illumination is ensured, and the safety of night travel is further ensured.

The invention relates to the technical field of urban traffic management, in particular to a road section traffic capacity calculation method and system under bus station interference, and the method comprises the steps: determining a research range and a research time period; social vehicle track data and bus track data in a research range and a research time period are acquired; performing curve fitting based on the social vehicle trajectory data and the bus trajectory data to obtain a social vehicle trajectory fitting curve and a bus trajectory fitting curve; on the basis of the social vehicle track fitting curve, lane division is carried out according to a wave crest positioning-interval width fixing lane division method, and a lane sequence is determined; determining a plurality of target lanes influenced by the bus stations according to the lane sequence; and comprehensively evaluating the traffic capacity reduction coefficient of each target lane based on the overlapping area of the fitting curve of the social vehicle and the bus track and the comparative analysis of the lane driving data, and further determining the actual traffic capacity of each target lane in combination with the basic traffic capacity of the lane.

The invention discloses a pedestrian avoidance method and device for a watering cart based on visual identification area proportion detection, and the method comprises the steps: constructing a target detection model based on a Yolov5 target detection algorithm, and deploying the target detection model in the watering cart; after the watering cart is started, a camera is started through a GStreamer pipeline to obtain a video stream, an image in the video stream is preprocessed, and an optimized image is obtained; inputting the optimized image into a target detection model for target object detection, and outputting a target object rectangular frame and coordinate information of the rectangular frame; the working mode of the watering cart is selected through lane line recognition; the real-time proportion of the rectangular frame of the target object entering the EWR area is obtained through real-time calculation; and comparing the real-time proportion with a first set threshold value and a second set threshold value, and performing corresponding processing according to a comparison result. According to the method, the reliability and accuracy of visual identification can be effectively optimized, the problems of partial misjudgment, missed judgment and the like are solved, and the performance of a system in a complex scene is improved.

The invention provides a lane line completion method and device, and relates to the technical field of electronic maps, and the method comprises the steps: obtaining lane line vector data corresponding to a map region to be subjected to lane line completion; according to the lane line vector data, determining a lane line image and a mapping relation between position coordinates of an original lane line in the lane line vector data and pixel point coordinates of the original lane line in the lane line image; according to the lane line image, determining a missing lane line and complementing the missing lane line to obtain a target lane line image; and according to the target lane line image and the mapping relation, determining the position coordinates of the complemented lane line after the missing lane line is complemented, and generating target lane line vector data. Therefore, the part with the missing lane line in the lane line vector data can be automatically complemented, compared with manual drawing complementation, the processing efficiency is greatly improved, and accurate complementation of the lane line in different map road scenes can be realized.

Aspects of the disclosure relate to routing an autonomous vehicle. For instance, the vehicle may be maneuvered along a route in a first lane using map information identifying a first plurality of nodes representing locations within the first lane and a second plurality of nodes representing locations within a second lane different from the first lane. While maneuvering, when the vehicle should make a lane change may be determined by assessing a cost of connecting a first node of the first plurality of nodes with a second node of a second plurality of nodes. The assessment may be used to make the lane change from the first lane to the second lane.