414 results about "Lane detection" patented technology

Lane marker coordinate data obtained from a previous frame of a vehicle vision system is projected into the current video frame based on measured translation and rotation of the host vehicle. The projected lane marker coordinate data is consolidated with lane marker coordinate data from the current video frame for lane detection or display applications.

A method and system for video-based road departure warning for a vehicle on a road, is provided. Road departure warning involves receiving an image of a road in front of the vehicle from a video imager, and detecting one or more road markings in the image corresponding to markings on the road. Then, analyzing the characteristics of an image region beyond the detected markings to determine a rating for drivability of the road corresponding to said image region, and detecting the lateral offset of the vehicle relative to the markings on the road based on the detected road markings. A warning signal is generated as function of said lateral offset and said rating.

A lane keeping assist device for a vehicle includes a steering control device, a detection device for lane of travel for assisting travel of the vehicle in a lane of travel in accordance with detection results and steering state and traveling state of the vehicle. Road curvature in a direction the vehicle traveling in is estimated on the basis of a first road curvature calculated on the basis of calculation result of a vehicle state amount calculation device and detection result of a state detection device, and a second road curvature calculated on the basis of positional coordinates by a predetermined distance in the direction the vehicle traveling in detected by a navigation system NAV. Target state amount is set on the basis of the road curvature and the steering state and traveling state of the vehicle.

The invention discloses a lane line detection and GIS map information development-based vision navigation method. The method comprises the following steps: acquiring GIS map information, preprocessing, carrying out real-time image acquisition and lane line detection to generate a GIS local map in real-time, carrying out coupling verification on a track line detection result and the GIS local map through an ICP algorithm, and generating a high-credibility track line result according to the coupling result. The method can realize the credibility evaluation of the lane line detection through a geographic information system, corrects when false detection or missing inspection appears, expands the application range of the lane detection algorithm, and also can improve the map positioning precision through visual perception information, so the performances of a vision navigation system in a whole intelligent driving and aided driving system are improved, thereby the system can adapt to more complex environments.

The invention relates to a visual computing and prewarning method of deviation angle and distance of an automobile from a lane line. The image processing and computer vision technologies are utilized, and the deviation angle and distance of the automobile from the lane line are computed in real time according to the road surface image acquired by a vehicle-mounted camera, thereby estimating the line crossing time for safety prewarning. The method comprises the following steps: detecting the lane lines of the road surface image to obtain a linear equation of partial lane lines; establishing a three-dimensional coordinate system by using the camera as the initial point, and recording the mounting height and depression angle of the camera; calibrating the focal length according to the lane detection result under the condition of a given deflection angle; computing the deflection angle and vertical distance of the automobile relative to the lane line according to a pinhole camera model; and estimating the deviation time from the lane according to the instantaneous running speed of the automobile, thereby obtaining the safety prewarning or intelligent control information of the running automobile.

The invention discloses a lane detection method and device. The method comprises the following steps that a region to be detected is determined according to a camera image; a detection result is obtained by detecting lane marks in the region to be detected; the detection result is optimized according to radar data; the positions of center lines of lanes are calculated according to the detection result and curb information detected by a radar; and the calculated positions of the center lines of the lanes are synthesized to obtain a position result of the multiple lanes. According to the lane detection method and device, the lane marks in the two-dimensional image are recognized through a camera, filtration is conducted by the aid of the radar data, and the effect of rapidly and accurately detecting the lane marks is achieved. Moreover, the center lines of the lanes are estimated and traced, so that the capability of dynamically recognizing lane lines of a vehicle is improved, and the automatic driving safety of an automated vehicle is improved.

A method of alerting the driver of a vehicle to a lane departure condition. The method includes operating a lane detection system to detect that the vehicle is experiencing a lane departure condition, operating a sensor to detect background vibration experienced by the vehicle, determining a characteristic making a haptic signal likely to be distinguishable from the background vibration, and operating a haptic signal generator in response to the lane departure condition to deliver to a driver the haptic signal having the characteristic.

The invention relates to a vehicle auxiliary positioning method based on lane detection and object tracking, belonging to technical field of intelligent traffic. The method aims to accurately position the specific lane of a vehicle. Based on the lane line detection and multi-target vehicle tracking, the two lane lines closest to the vertical axis of an image are taken as the lane lines of the vehicle and the target vehicle is connected with the original point via a straight line by taking the midpoint of the bottom edge of the road image as the original point, and whether the straight line is intersected with the lane lines of the vehicle is determined to determine the relative position relation of the target vehicle and the lane, and through the combination of the relative position relation and the lane lines, the specific lane of the vehicle can be determined, and the lane level positioning of the vehicle can be realized through the combination of the specific lane information and the GPS information. According to the invention, the defect that a GPS system cannot accurately position the specific lane of the vehicle is made up, and more reliable and accurate data is provided for the lane level positioning and auxiliary driving.

A mobile detecting apparatus which can include the ability to transmit data to and receive instructions from a remote location, detect multiple objects (e.g. stacked or side by side containers or cargo), and provide efficient traffic flow (e.g. at cargo port).

A vehicle control apparatus capable of automatic steering control while reducing discomfort or stress on vehicle occupants. In the apparatus, a lane detection unit detects a lane in which the vehicle is traveling. An offset setting unit sets an offset within the lane suitable for making a driver feel less stressed. An occupant detection unit detects the presence of a designated occupant of a seat opposite a driver's seat. An offset adjustment unit, when the designated occupant is detected, adjusts the offset set by the offset setting unit to be decreased. A vehicle-path estimation unit estimates a vehicle path in the lane such that the vehicle can travel along the vehicle path from a current lateral position to a target lateral position of the vehicle. An automatic steering control unit automatically controls steering so that the vehicle travels along the estimated vehicle.

The invention belongs to the technical field of vehicle active safety and relates to a lane line detection method based on monocular vision. The lane line detection method comprises the following steps: acquiring an original image of a road condition in front of a vehicle; intercepting subimages of boundary regions at the two sides, wherein the subimages include the original image; removing the high-frequency noise of the subimages and carrying out grey level histogram equalization and binaryzation; intercepting left and right lane line detection region images; filtering based on the fixed width range of a lane line according to the features of low grey value pavements at the two sides of the lane line; preliminarily determining feature points of the lane line in a sampling line scanning manner and screening; and carrying out lane detection. The lane line detection method has the characteristics of good real time and high reliability.

A method and apparatus for lane detection using overhead images and positional data. A server receives positional data from a vehicle and computes a continuous trajectory. The server receives an overhead image of a road section. The server crops and processes the overhead image to remove unwanted portions. The server identifies edge features using the continuous trajectory and steerable filters. The server identifies lanes in the overhead image using a maximization algorithm, the edge filters, and the continuous trajectory.

A system and method for using triplet loss for proposal free instance-wise semantic segmentation for lane detection are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on an autonomous vehicle; performing a semantic segmentation operation or other object detection on the received image data to identify and label objects in the image data with object category labels on a per-pixel basis and producing corresponding semantic segmentation prediction data; performing a triplet loss calculation operation using the semantic segmentation prediction data to identify different instances of objects with similar object category labels found in the image data; and determining an appropriate vehicle control action for the autonomous vehicle based on the different instances of objects identified in the image data.

In apparatus and method for detecting a traffic lane mark for an automotive vehicle, a plurality of traffic lane detection windows are set in a manner for the traffic lane to be included in each traffic lane detection window from an image data photographed by a photograph device, the traffic lane mark is detected from a luminous intensity information within each traffic lane detection window of each coordinate point, a plurality of noise detection windows are set at positions which abut the respective traffic lane detection windows, an edge intensity within each noise detection window is detected; a weight value to a predetermined number of the traffic lane detection windows is modified in accordance with the edge intensity in the noise detection window; and a road contour is calculated using the traffic lane detected at the window internal traffic lane detecting and the modified weight value.

In a vehicle lane detector that detects a lane sign on a road surface, a condition for determining that the lane sign is detected is changed based on one of a frequency and a ratio of detection error of the lane sign.

The invention discloses a method for detecting a boundary of a lane where a vehicle is, which comprises the steps of: first adaptively extracting edge points for the part below a horizon of a road image according to pixel gradient amplitudes and calculating an edge direction, then searching and positioning a lane boundary by utilizing the particle swarm optimization in a parameter vector space ofa lane boundary projection model according to the extracted edge points, the edge direction and the lane boundary projection model; finally, calculating a plane geometric structure of the lane wherein the vehicle is, a position of the vehicle in the lane and an angle of deviation according to the searched lane boundary projection model parameter values and a parameter calculation method. The method can reflect an actual lane boundary curve more accurately, has better environment self-adaption capability, enhances the robustness of the lane detection, and has high reliability and strong antijamming capability.

The present invention relates to a three-lane detection method based on image morphological segmentation and region growing. The method comprises: a method for, by using a shape of a lane mark and a relative gray level of a roadway, performing segmentation on the lane mark by means of image morphology; a method for fitting a vanishing point by using a weighted least square method; and a method for forming a region of interest (ROI) of the lane mark by a region growing method and iteratively searching for a feature point of the lane mark. According to the three-lane detection method based on image morphological segmentation and region growing, aimed at the problem of perception of a vehicle-mounted visual system of an intelligent vehicle to a multi-lane road in a process of driving on the urban structural multi-lane road, a method of carrying out image morphology preprocessing and carrying out iterative solution on the lane mark is adopted to adapt to a multi-lane environment. The method is novel in algorithm, high in adaptability, relatively high in illumination robustness, small in computation amount and easy to implement by programming, so that a module of the vehicle-mounted visual system is improved, and the efficiency and environmental adaptability of an intelligent vehicle environment sensing module are further improved.

The invention relates to a universal road and lane detection system and method. The method comprises: S300, interference elimination and image artifact and irrelevant image part removing are carried out on an input image to obtain a relevant image; S302, lane edge feature or road edge feature is extracted from the relevant image; S304, according to the lane edge feature or road edge feature, fitting is carried out to obtain a synthesized path expression model; S306, the path expression model is tracked to carry out time sequence consistency integration or position consistency integration; and S308, the path expression model corresponds to a global coordinate system. On the basis of the module design, pretreatment is carried out on the image inputted by the camera, the interested relevant image is selected; lane detection or road detection is carried out by combining input information of the laser radar; model fitting is carried out to estimate a road path and the accuracy of path estimation is improved by using the time sequence integration module; and then the image corresponds to the global coordinate system in real time by using a coordinate system correspondence module to improving path estimation accuracy. Therefore, a problem that the existing road estimation model has imperfect functions can be solved.

The invention discloses a motorcade formation driving system and method and belongs to the field of automobiles. Each automobile is provided with a positioning part, a communication part, an adjacent lane detection part and an automatic driving control part, each automatic driving control part controls the corresponding automobile to automatically follow the adjacent automobile ahead to travel according to specific conditions, so that as for at least two automobiles, except that the first automobile is driven manually, the rest of automobiles can be all driven automatically by following the first automobile instead of being manually driven by drivers, the probability of traffic accidents caused by fatigue driving or incorrect operations of the drivers is reduced, the motorcade traveling safety is improved, and labor is saved.

A lane detection system includes a non-volatile memory storing machine-readable instructions and an image processor capable of receiving a road image. The image processor, when executing the machine-readable instructions, is capable of: (i) processing the road image to identify a lane candidate within a lane-existing region of the road image, the lane-existing region having (a) a near subregion including an imaged road region nearer to the vehicle and (b) a far subregion including an imaged road region farther from the vehicle, (ii) verifying the lane candidate as a true lane candidate when a minimum distance between (a) a line fit to a portion of the lane candidate in the near subregion and (b) a predetermined reference point in the road image is less than a neighborhood distance; and (iii) extending the true lane candidate into the far subregion to form a detected lane marker demarcating the lane marker.

The invention discloses a converged network lane line detection method based on an attention mechanism and terminal equipment. The method comprises the following steps: synchronously acquiring a natural image and point cloud data of a road surface; inputting the natural image and the point cloud data into a pre-established and trained fusion network, and outputting a lane detection result, whereinthe fusion network performs information fusion processing on the point cloud data and the natural image by adopting an adding time sequence frame and an attention mechanism. According to the invention, continuous frames are used to improve the performance of the detection network so as to deal with complex situations such as mark loss and vehicle occlusion; and by splicing the low-dimensional features and the high-dimensional features through Skip Connection, image detail information which is continuously lost along with the increase of the network depth is made up, and the image is reduced by using Decoder to obtain a final result. The fusion network greatly improves the detection performance of the lane lines and can perform detection in various complex environments.

The invention relates to a Beidou visual fusion accurate lane identification and positioning method and an implementation device thereof. The Beidou visual fusion accurate lane identification and positioning method comprises the following steps: (1) lane detection: detecting and identifying lane lines and dividing the lanes; identifying current, left and right lane types, and determining the current lane of the vehicle; (2) performing map matching to obtain positioning information; determining a road where the vehicle is located, and extracting information such as road lane number, lane type,lane width, bus lane opening time and the like; measuring the vehicle speed, and obtaining BTD; (3) positioning correction: correcting a Beidou positioning result; and (4) monitoring and early warning, judging whether the vehicle runs on the road, and if so, capturing, identifying and uploading. By means of the Beidou visual fusion accurate lane identification and positioning method, a common lane, a bus lane, an emergency lane and a reversible lane can be accurately identified, meanwhile, different colors of masks are used for distinguishing, so as to provide a reference for a driver, and provide more accurate positioning for an auxiliary driving and navigation system.

A lane change assist system is comprised of a host vehicle state detecting device that detects a host vehicle traveling condition, a surrounding vehicle detecting device that detects other vehicle located around the host vehicle, a lane detecting device that detects a lane around the host vehicle, and a processing unit. The processing unit is arranged to set a target lane, to determine a period of a lane change assist, to set a predicted period for an evaluation of a lane change to the target lane based on a prediction, to obtain an appropriate speed range during the predicted period for each gap, and to select a target vehicle speed from the appropriate speed range.

An expressway network running status detection method based on OBU adopts a toll station ETC lane OBU detectors and expressway side OBU detectors to obtain expressway section traffic flow speed, expressway network running indexes and expected running time between every two expressway sections and informs the information to vehicles. In the detection method, data of the toll station ETC lane OBU detectors and data of the expressway side OBU detectors are combined, the accuracy of detection results of real-time traffic circulation states of an expressway network and the estimation reliability of the running time between every two expressway sections are improved, and accordingly the supervision ability and service level of the traffic management department are improved.

In apparatus and method for detecting a traffic lane mark for an automotive vehicle, a plurality of traffic lane detection windows are set in a manner for the traffic lane to be included in each traffic lane detection window from an image data photographed by a photograph device, the traffic lane mark is detected from a luminous intensity information within each traffic lane detection window of each coordinate point, a plurality of noise detection windows are set at positions which abut the respective traffic lane detection windows, an edge intensity within each noise detection window is detected; a weight value to a predetermined number of the traffic lane detection windows is modified in accordance with the edge intensity in the noise detection window; and a road contour is calculated using the traffic lane detected at the window internal traffic lane detecting and the modified weight value.

A system for realizing support of safety driving or automatic driving, in which a vehicle-mounted stereo camera is used to detect obstacles on a road surface even in the presence of a reflected image of an obstacle under a wet road condition. The system includes two cameras, an image transforming section transforming a first camera's image by image transform T that transforms any given pixel in a road surface region in the first camera's image to a corresponding pixel in a second camera's image, a lane detecting section detecting a traffic lane on a road on the basis of characteristics of the image obtained from the second camera, a similarity calculating section sequentially establishing processing regions, each having a base formed by one of image lines in a region within a lane, for carrying out inter-image arithmetic operations on the assumption that an obstacle stands from a contact line on a road surface as an image line, and obtaining respective degrees of similarity between the first cameras s image and the second camera's image and between the second camera's image and the transformed image, and an obstacle judging section detecting the object from a difference between the two kinds of degrees of similarity on the road region sequentially obtained.

A method of alerting the driver of a vehicle to a lane departure condition. The method includes operating a lane detection system to detect that the vehicle is experiencing a lane departure condition, operating a sensor to detect background vibration experienced by the vehicle, determining a characteristic making a haptic signal likely to be distinguishable from the background vibration, and operating a haptic signal generator in response to the lane departure condition to deliver to a driver the haptic signal having the characteristic.

The invention provides an intelligent control method for a traffic light at a highway intersection, and belongs to the technical field of traffic signal light control methods. The intelligent control method comprises the steps of setting a lane and traffic flow detection meter for detecting lane sections of the lane and the traffic flow, setting the traffic light, and setting up an information processor for analyzing and processing the traffic flow and controlling the traffic light. The intelligent control method has the advantages that coexistence of lane blocking and lane idleness is eliminated, and whatever any time periods, any time frames and any reasons, all lane resources of the highway intersection are can be utilized to the maximum extent, intersection traffic efficiency is improved; due to improvement of the traffic efficiency, reactive power consumption of vehicle fuel and energy is reduced to the maximum extent, expenses and time are saved, and waste gas emission is reduced; waiting time for passing of a vehicle driver is relatively reduced in lane sections or time periods with a few traffic flow, impatient emotion of the driver can be effectively relieved, and second rushing, lane rushing and traffic accidents due to the second rushing and lane rushing are reduced.

The invention discloses a road jamming detection method and device. The method comprises steps of acquiring monitoring video data; classifying and preprocessing the monitoring video data so as to obtain processed data; carrying out iteration trainings so as to obtain a lane detection model and a vehicle detection model; obtaining vehicle information in a to-be-identified image; integrating the lane information and the vehicle information so as to obtain a target image; for each lane in the target image, calculating a lane occupation rate corresponding to the to-be-identified image; and according to the corresponding relation between the lane occupation rate corresponding to the to-be-identified image and a preset threshold vale, and the corresponding relation between the preset threshold value and the jamming grade, acquiring the jamming grade corresponding to the to-be-identified image. According to the invention, road jamming detection is quite accurate.

A diagrammatizing apparatus (20) for vehicle lane detection which detects at least two lines of boundary lines of the sign lines (5L, 5R) or the boundary lines of a vehicle lane (4) on the road surface from a picked-up image of the road surface, includes a first boundary line extracting unit that selects a longest line (L0) as a first boundary line from a first line group consisting of plurality of lines (L0), La, Lb which intersect with each other in the image, and a second boundary line extracting unit that selects a longest line (L10) as a second boundary line from a second line group consisting of a plurality of lines (L10, Lc, Ld) which intersect with each other in the image.