Abstract: A method is provided for optimizing the use of autonomous features of advanced driver assistance systems and the tracking thereof. For example, a vehicle may be equipped with several driver assistance systems in which a driver of the vehicle may be assisted. The vehicle may automatically change the number of active assistance systems or suggest to the driver one or more assistance systems to activate based on several factors, including poor driving on behalf of the driver or poor driving conditions due to weather or road quality. Statistics regarding the use of such advanced driver assistance systems may be monitored and tracked and stored on an onboard database or transmitted continuously or periodically to various entities. For example, the system may operate to allow an insurance company to track the driving performance and the use of the advanced driver assistance systems to update actuarial models to more accurately adjust rates.

Abstract: Described herein is a high confidence ground truth information service executing on a network of edge computing devices. A variety of participating devices obtain high confidence ground truth information relating to objects in a local environment. This information is communicated to the ground truth information service, where it may be verified and aggregated with similar information before being communicated as part of an acquired ground truth dataset to one or more subscribing devices. The subscribing devices use the ground truth information, as included in the ground truth dataset, to both validate and improve their supervised learning systems.

Abstract: A vehicle includes a light switch for manually operating a lighting state of a lighting device. The light switch includes a light-off position and an auto-light position for executing an auto-light process. A vehicle control system includes a first controller for executing an automated driving of the vehicle, and a second controller for controlling a lighting state of the lighting device based on a request from the first controller or operation information of the light switch. The first controller is configured to transmit an auto-light request for executing the auto-light process to the second controller during execution of the automated driving. The second controller is configured to execute the auto-light process when the auto-light request is received from the first controller in a state where the light switch is operated to the light-off position.

Abstract: Provided are lane recognition apparatuses and methods including a sensor provided at a vehicle to detect a left line and a right line of a current lane, sense a left line distance and right line distance from a middle of the vehicle to the left line and right line, respectively, and a controller configured to set a sum of the left line distance and the right line distance as a lane width, when the sensor detects both the left line and the right line, correct the left line distance or the right line distance based on a previously set lane width, when the sensor detects one of the left line or the right line, and determine a moving state of the vehicle as any one of normal, left-biased, right-biased, or lane change driving state based on the left line and the right line of the current lane.

Abstract: Aspects of the disclosure relate to providing transportation services with autonomous vehicles. For instance, a first route to a first destination may be determined. The first route may have a first cost. Weather information for the first destination may be received. A characteristic is determined based on the weather information. A second destination having the characteristic may be selected. The second destination may be different from the first destination. A second route to the second destination may be determined. The second route may have a second cost. The first cost may be compared to the second cost, and the vehicle may use the comparison to set one of the first destination or the second destination as a current destination for a vehicle to cause the vehicle to control itself in an autonomous driving mode to the current destination.

Abstract: Embodiments described herein may provide a method for using vehicle sensor data to identify where road work exists within a road network. Methods may include: receiving probe data and sensor data from a plurality of probe apparatuses traveling along a sequence of road segments; identifying, from the sensor data, one or more indicators of a beginning of a road work area; identifying, from the sensor data, binary indicators of the presence of road work or a lack of presence of road work along the sequence of road segments; and determining, based on the one or more indicators of a beginning of a road work area and the binary indicators of the presence of road work or the lack of road work along the sequence of road segments, a probability of road work occurring along one or more road segments of the sequence of road segments.

Abstract: In various examples, a deep neural network (DNN) is trained—using image data alone—to accurately predict distances to objects, obstacles, and/or a detected free-space boundary. The DNN may be trained with ground truth data that is generated using sensor data representative of motion of an ego-vehicle and/or sensor data from any number of depth predicting sensors—such as, without limitation, RADAR sensors, LIDAR sensors, and/or SONAR sensors. The DNN may be trained using two or more loss functions each corresponding to a particular portion of the environment that depth is predicted for, such that—in deployment—more accurate depth estimates for objects, obstacles, and/or the detected free-space boundary are computed by the DNN.

Abstract: An intelligent decision-making method and system for an unmanned surface vehicle are provided. The system comprises: an image acquisition module, configured to acquire an image sequence signal of an observation region; a target detection and recognition module, configured to receive the image sequence signal, recognize a preset interested target appeared in a scenario, determine and identify an image region occupied by the preset interested target; distinguish a type of the interested target, screen out the target that causes a threat to an unmanned platform itself according to the type of the target, continuously observe the target, and generate tracking trajectory information of the target; a target situation distinguishing module, configured to calculate a target threat factor; and a target threat evaluation and decision module, configured to evaluate a threat type, give a threat level, and lock the interested target with a high threat level for tracking in real time.

Abstract: A method of simultaneously estimating a movement and shape of a target vehicle using a preliminary distribution model of a tracklet may have high reliability in estimation performance even with a change in heading of the target vehicle while being implemented in real time by setting the preliminary distribution model defined by a small number of representative tracklet appearance points using a tracklet defined in an orthogonal coordinate system and a linear correspondence relationship between a preliminary distribution model of the tracklet and a central position of the target vehicle and performing many-to-one data association between tracklet outputs. The method of simultaneously estimating the movement and shape of the target vehicle using the preliminary distribution model of the tracklet is performed by a signal processing device configured to process signals emitted from a plurality of radars mounted at a host vehicle and reflected from the target vehicle.

Abstract: A method of building a video surveillance system for object detection and tracking relates to the field of computer vision, and to methods and means of detecting and tracking moving objects, for example, persons. The method consists in special adjustment of each camera of a video surveillance system by means of calibration elements, linking cameras to the location plan, plotting a coordinate match of a coordinate system of a two-dimensional image of each camera with a three-dimensional system of coordinates of a location plan, for example premises; detecting and tracking objects of interest. The method makes it possible to construct motion tracks of objects of interest in the coordinate system of the location plan by means of multicamera surveillance, to analyze the nature of behavior and motion of objects, assess their interaction and individual parameters, as well as to calculate the quantity thereof in location regions of interest.

Abstract: An autonomous mobile platform is described. The autonomous mobile platform is configured for use in road monitoring, and comprising: a scanning module configured to be used for road scanning in order to enable identifying hazards associated with the road being scanned; a location finder, configured to determine locations of hazards identified at the road being scanned; and at least one transmitter comprised in a respective autonomous mobile platform, and configured to transmit data derived by the scanning module from the road scanning.

Abstract: An object is to obtain a trained model whose robustness is high in a case of learning a network in an image signal processing system. For teacher images consisting an acquired teacher image group, a distribution characteristic of at least one of three attributes of color is analyzed and based on analysis results, a teacher image group uniform in the distribution characteristic is generated. Learning of a network is performed by generating a data set including a set of a teacher image and a pupil image from a new teacher image group thus obtained.

Abstract: A method and an apparatus identifies an object. The method includes at a first time instant, acquiring raw data output by a camera installed on a vehicle, the output raw data comprises one of a continuous data output format for a continuous model or a discrete data output format for a discrete model; feeding the raw data to a discrete statistic model to form discrete statistic model format data for the first time instant, the discrete statistic model format data includes a continuous part having the continuous data output format and a discrete part having the discrete data output format; fusing the discrete statistic model format data for the first time instant with historical discrete statistic model format data to update the discrete statistic model format data for the first time instant; and identifying the object from the updated discrete statistic model format data for the first time instant, wherein the object includes a lanemarking characterized by a curve.

Abstract: A method for training a model for generating simulation data for training an autonomous driving agent, comprising: analyzing real data, collected from a driving environment, to identify a plurality of environment classes, a plurality of moving agent classes, and a plurality of movement pattern classes; generating a training environment, according to one environment class; and in at least one training iteration: generating, by a simulation generation model, a simulated driving environment according to the training environment and according to a plurality of generated training agents, each associated with one of the plurality of agent classes and one of the plurality of movement pattern classes; collecting simulated driving data from the simulated environment; and modifying at least one model parameter of the simulation generation model to minimize a difference between a simulation statistical fingerprint, computed using the simulated driving data, and a real statistical fingerprint, computed using the real dat

Abstract: A method is described and includes receiving a frame of point cloud data from at least one onboard light detection and ranging (LIDAR) sensor of a vehicle; discarding points of the received frame of point cloud data that are outside a defined geographic area around the vehicle; and, subsequent to the discarding, performing ray tracing in connection with the remaining points of the received frame of point cloud data. The method may further include characterizing an occupancy condition of each of a plurality of cells of a three-dimensional (3D) grid corresponding to the defined geographic area based on the ray tracing of the received frame of point cloud data, wherein the 3D grid corresponds to the received frame of point cloud data.

Abstract: Anti-abandonment system (99) in a vehicle (100), comprising: at least one laser sensor (1a; 1b) structured for detecting a movement in the vehicle (100) by emission of a laser beam and measurement of a respective time of flight; at least one camera sensor (2a; 2b) structured for detecting a movement in the vehicle (100); a command-and-control unit (3) operatively connected to the at least one laser sensor (1a; 1b) for receiving a first detection signal representative of the movement detected by the at least one laser sensor (1a; 1b) and to the at least one camera sensor (2a; 2b) for receiving a second detection signal representative of the movement detected by the at least one camera sensor (2a; 2b), the command-and-control unit (3) being configured and programmed for: processing the first and second detection signal for verifying an achievement of a respective alarm condition; provided the achievement of the respective alarm condition for both the first and second detection signal, sending a respective c

Abstract: Systems and apparatuses for capturing an image of a vehicle for which roadside assistance is being requested are provided. The image may be captured by a mobile device and the mobile device may geotag location information to the image. The image and associated geotag location information may then be processed to determine a location of the vehicle and a roadside assistance issue for which service is being requested. The image may be further analyzed to determine a context including, a make, model and/or year of the vehicle, whether special equipment is needed to service the vehicle, whether the vehicle is located in a particular situation (e.g., within a structure, in a ditch, or the like). The information obtained from the image may be used to determine a type of service to provide to the vehicle and to identify one or more service providers to dispatch to the vehicle.

Abstract: Methods, systems, and non-transitory computer readable media are configured to perform operations comprising determining an occurrence of a sign in an environment of a vehicle; determining that at least a portion of the sign is unrecognized by a local machine learning model of the vehicle; and providing sensor data associated with the at least one portion of the sign to an operations center remote from the vehicle.

Abstract: The measurement device acquires output data from a sensor unit for detecting road surface lines around, and determines a predetermined range based on an own position and positional information of broken-line type road surface lines. Then, the measurement device extract, from the output data, data corresponding to detection result of the predetermined range, and executes predetermined processing based on the extracted data.

Abstract: A method of generating a color image using a monochromatic image sensor. The method includes sequentially illuminating a surface in a plurality of colors, one color at a time. The monochromatic image sensor captures a plurality of image frames of the surface based on the plurality of colors. The plurality of image frames are identified, and at least one feature in the target of the plurality of image frames is highlighted. Color intensities of the plurality of image frames are normalized. A color intensity map of the target for each of the plurality of image frames is generated. A correlation score is determined by comparing each color intensity map of the plurality of image frames. The color image is generated based on the correlation score.

Abstract: This document describes techniques, apparatuses, and systems for sensor fusion for object-avoidance detection, including stationary-object height estimation. A sensor fusion system may include a two-stage pipeline. In the first stage, time-series radar data passes through a detection model to produce radar range detections. In the second stage, based on the radar range detections and camera detections, an estimation model detects an over-drivable condition associated with stationary objects in a travel path of a vehicle. By projecting radar range detections onto pixels of an image, a histogram tracker can be used to discern pixel-based dimensions of stationary objects and track them across frames. With depth information, a highly accurate pixel-based width and height estimation can be made, which after applying over-drivability thresholds to these estimations, a vehicle can quickly and safely make over-drivability decisions about objects in a road.

Abstract: A motor vehicle includes a left side view camera attached to the left lateral side of the body and having a field of view in a rearward direction. A right side view camera is attached to the right lateral side of the body and has a field of view in a rearward direction. There is a right back up camera and a left back up camera. An optics module receives resulting video signals and produces light fields such that the light fields are reflected off of windows of the motor vehicle and are then visible to a driver of the motor vehicle as virtual images.

Abstract: A method for loading a container on a landing target on a land vehicle using a container crane including a trolley and a spreader for holding and lifting the container. The method is performed in a container crane control system and includes the steps of: obtaining two-dimensional images of the landing target from a first pair of cameras arranged on the spreader; performing feature extraction based on the two-dimensional images to identify key features of the landing target; generating a point cloud based on the feature extraction, wherein each point in the point cloud contains coordinates in three dimensions; and controlling movement of the container to the landing target based on the point cloud and the identified key features of the landing target.

Abstract: Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.

Abstract: One aspect herein provides a method of analysing driving behaviour in a data processing computer system, the method comprising: receiving at the data processing computer system driving behaviour data to be analysed, wherein the driving behaviour data records vehicle movements within a monitored driving area; analysing the driving behaviour data to determine a normal driving behaviour model for the monitored driving area; using object tracking to determine driving trajectories of vehicles driving in the monitored driving area; comparing the driving trajectories with the normal driving behaviour model to identify at least one abnormal driving trajectory; and extracting a portion of the driving behaviour data corresponding to a time interval associated with the abnormal driving trajectory.

Abstract: Methods and apparatus to calibrate a multicamera system based on a human pose are disclosed. An example apparatus includes an object identifier to identify a first set of coordinates defining first locations of anatomical points of a human in a first image captured by a first camera and identify a second set of coordinates defining second locations of the anatomical points in a second image captured by a second camera. The apparatus includes a pose detector to detect, based on at least one of the first or second sets of coordinates, when the human is in a particular pose. The apparatus includes a transformation calculator to, in response to detection of the human in the particular pose, calculate a relative transformation between the first camera and the second camera based on a first subset of the first set of coordinates and a second subset of the second set of coordinates.

Abstract: Vehicle movement sensor for a vehicle travelling on a road surface. An optoelectronic sensor from a first sample area on the road surface at a first location relative to the vehicle and generating a pixel pattern image of road surface irregularities in the first sample area. A processor for sampling pixel pattern images of the first sample area and determining movement of the vehicle using digital image correlation of sequential sampled pixel pattern images of the first sample area.

Abstract: An embodiment device for detecting a boundary of a road in a 3D point cloud using a cascade classifier includes a rule-based classifier configured to determine whether a received LiDAR cluster has a likelihood of becoming a candidate for the boundary of the road using a box parameter surrounding a point cloud constituting the LiDAR cluster and a point parameter, and a learning-based classifier configured to apply a machine-learning scheme to the LiDAR cluster selected as the candidate for the boundary of the road by the rule-based classifier to determine the LiDAR cluster to be the boundary of the road or an object other than the boundary of the road.

Abstract: A method 100 assessing and mitigating risks encounterable by an autonomous vehicle includes collecting information associated with an environment of an ego vehicle and determining and assessing a set of risks encounterable by the ego vehicle. A system for assessing and mitigating risks can include and/or interface with an ego vehicle (equivalently referred to herein as an autonomous vehicle, autonomous agent, ego agent, agent, etc.) and a set of computing subsystems (equivalently referred to herein as a set of computers) and/or processing subsystems (equivalently referred to herein as a set of processors), which function to implement any or all of the processes of the method.

Abstract: An optical system includes a first optical element including a first reflective area having a convex shape toward a magnification side, a second optical element including a second reflective area having a convex shape toward the magnification side, and a light shielding member disposed between the first optical element and the second optical element. Light from the magnification side travels to a reduction side through the second reflective area, the first reflective area, and a refractive area of the second optical element in order. The light shielding member is disposed between light entering the second reflective area and light entering the first reflective area in a first cross-section including an optical axis.

Abstract: An apparatus of assisting steering of a vehicle, may include a turning direction recognizer that recognizes a turning direction of a tire, by use of a steering angle controlled through manipulation of a handle; and a tire driving controller that determines a tire, to which a first driving force for generating a steering assisting torque that assists turning of the tire to the recognized turning direction is applied, and a tire, to which a second driving force for offsetting the first driving force to maintain a forward/rearward force of the vehicle at 0 is applied, and controls driving motors provided in the tires, respectively, to generate the first driving force and the second driving force, whereby the tire may be turned with a steering torque of a limit steering torque or more which may be generated by the steering motor, and a control method thereof.

Abstract: Methods, systems, and non-transitory computer-readable media are configured to perform operations comprising determining lane detection data and object detection data associated with an environment; determining a lane template based on the lane detection data; and generating localization data that identifies a location of an object in the environment based on the lane template and the object detection data.

Abstract: The present disclosure relates to a method and apparatus for heuristically defending against a local adversarial attack through gradient optimization. The method includes: processing an original image to obtain a gradient image; selecting a noise region in the gradient image and suppressing the noise region to form a defense patch; performing gradient enhancement on the original image to form a gradient-enhanced image; and projecting the defense patch onto the gradient-enhanced image to form a defense-processed image. The present disclosure can suppress high-frequency noise and prevent a deep neural network from being attracted by the high-frequency noise to make misjudgment, to suppress an adversarial patch. In addition, a contour and texture of the original image are enhanced by performing gradient enhancement on the original image, recognition by a classifier is facilitated, and image recognition accuracy is improved.

Abstract: The technology relates to determining whether a camera is occluded. For instance, an image may be captured using a camera having red, green, and blue pixels each including a photosensor. Output values for the photosensors of each of the red pixels, green pixels, and blue pixels may be determined for the images. The output values of the green pixels may be compared to one or more of the output values of the red pixels or the output values of the blue pixels. That the camera is occluded is determined based on the comparison.

Abstract: The present disclosure provides a method of matching lane line data, which relates to a field of automatic driving, and in particular to a field of locating an autonomous vehicle. The method of matching lane line data includes: obtaining a first data indicating sensed lane lines and a second data indicating map lane lines respectively; constructing a correlation weight matrix for the first data and the second data, based on differences between the sensed lane lines and the map lane lines; and matching the first data with the second data according to the correlation weight matrix, so as to obtain a third data having an optimal match with the first data from the second data. The present disclosure further discloses an apparatus of matching lane line data, a device, a storage medium and a computer program product.

Abstract: A method of operation of a navigation system comprising: receiving multiple frames, including a first frame and a second frame, of images; detecting a traffic sign from the images between the first frame and the second frame based on a sign recognition model; extracting a first image from the first frame and a second image from the second frame; matching the traffic sign is the same in the first image and the second image based on a similarity model; generating a sign location of the traffic sign with an inertial measurement unit reading based on the first image and the second image; and generating a global coordinate for the sign location for displaying on a navigation map.

Abstract: An information processing apparatus according to an embodiment of the present technology includes an output control unit. The output control unit outputs distance information based on an actual distance between a first target object imaged by a first imaging device and a second target object imaged by a second imaging device on the basis of scale information regarding the actual distance, first position information regarding a position and an attitude of the first imaging device, and second position information regarding a position and an attitude of the second imaging device. Accordingly, a distance between two target objects can be easily and accurately measured.

Abstract: Methods for performing operations for improving driver safety across a fleet of vehicles are disclosed. A plurality of safety events pertaining to a driving of a fleet of vehicles by a plurality of drivers are detected. A subset of the events is identified. The subset corresponds to one or more safety events of the plurality of safety events involving one or more vehicles of the fleet of vehicles to which drivers have not been assigned. A user interface is generated for presentation on a client device, the user interface including an interactive user interface element for accessing the subset of the events. One or more user interface elements are provided for accepting or rejecting recommendations for assignments of one of the plurality of drivers to each of the vehicles. The recommendations are generated based on an application of a machine-learned model to images of faces captured.

Abstract: A method for guiding an emergency vehicle to an emergency site includes receiving an emergency dispatch message including a location of an emergency. Present location information is received for an emergency vehicle. A route between the received present location and the received location of the emergency is calculated using area map data. Navigation guidance is provided to the emergency vehicle based on the calculated route. The calculated route and the present location information for the emergency vehicle are transmitted to an unmanned aerial vehicle (UAV). The UAV is automatically piloted ahead of the emergency vehicle, along the calculated route, using the calculated route and present location transmitted thereto. A traffic alert is transmitted from the UAV to influence traffic flow ahead of the emergency vehicle.

Abstract: A mapping method for right-turn conflict warning lines at urban road intersections includes: obtaining the conflict data of urban intersections and the driving trajectory information of large vehicles and obtaining the outermost rear wheel trajectory curve and the innermost rear wheel trajectory curve through the driving trajectory information of large vehicles; using the regression model to construct the dynamic model of the right-turn conflict area of large vehicles and obtain the relationship between the parameters of the outermost rear wheel trajectory curve and the innermost rear wheel trajectory curve and the dynamic and static indexes; inputting the dynamic and static indexes of other road intersections into the dynamic model of the right-turn conflict area of large vehicles to obtain the corresponding outermost rear wheel trajectory curve and the innermost rear wheel trajectory curve, and drawing the urban road warning line.

Abstract: An indoor lighting device of a vehicle includes: a substrate, a plurality of light sources assembled with the substrate to be arranged in a row, and a light guide panel including: a plurality of incidence parts such that light emitted by the light sources is incident thereupon, a diffusion area part provided behind the incidence parts to diffuse and reflect the light incident upon the incidence parts, a visual field area part provided behind the diffusion area part to emit the light diffused and reflected by the diffusion area part outside, and light diffusion holes provided behind the respective incidence parts. In particular, each of the light diffusion holes is surrounded by a transmission plane, a pair of reflection planes and a diffusion plane.

Abstract: A method for detecting real lateral locations of target plants includes: recording an image of a ground area at a camera; detecting a target plant in the image; accessing a lateral pixel location of the target plant in the image; for each tool module in a set of tool modules arranged behind the camera and in contact with a plant bed: recording an extension distance of the tool module; and recording a lateral position of the tool module relative to the camera; estimating a depth profile of the plant bed proximal the target plant based on the extension distance and the lateral position of each tool module; estimating a lateral location of the target plant based on the lateral pixel location of the target plant and the depth profile of the plant bed surface proximal the target plant; and driving a tool module to a lateral position aligned with the lateral location of the target plant.

Abstract: An indirect viewing system for a vehicle has at least one image capture device (2) having an image sensor (3) for continuously taking images at a first frame rate, an image memory (4) that temporarily stores images for processing that is temporally after the images are captured, and an image processing device (6) adapted to continuously compute at least one new image from at least two successively taken images, the computed new images having a second frame rate different from the first frame rate, and an image output device (5) for outputting the continuously computed new images at the second frame rate.

Abstract: A method and system for performing indicia recognition includes obtaining, at an image sensor, an image of an object of interest and identifying at least one region of interest in the image. The region of interest contains one or more indicia indicative of the object of interest. The processor then determines positions of each region of interest and further determines a geometric shape based on the positions of each of the regions of interest. An orientation classification is identified for each region of interest is based on a respective position relative to the geometric shape for reach region of interest. The processor then identifies and performs one or more transformations for each region of interest, with each transformation determined by each regions respective orientation classification. The processor then performs indicia recognition on each of the one or more transformed regions of interest.

Abstract: Customized navigation maps of an area are generated for autonomous vehicles based on a baseline map of the area, transportation systems within the area, and attributes of the autonomous vehicles. The customized navigation maps include a plurality of paths, and two or more of the paths may form an optimal route for performing a task by an autonomous vehicle. Customized navigation maps may be generated for outdoor spaces or indoor spaces, and include specific infrastructure or features on which a specific autonomous vehicle may be configured for travel. Routes may be determined based on access points at destinations such as buildings, and the access points may be manually selected by a user or automatically selected on any basis. The autonomous vehicles may be guided by GPS systems when traveling outdoors, and by imaging devices or other systems when traveling indoors.

Abstract: A system for conducting a video conference and methods for making and utilizing the same. The system can generate a first virtual stage for a first participant in the video conference by selecting one or more items of personal information associated with the first conference participant and disposing the selected personal information items in a predetermined arrangement. The first virtual stage can be transmitted with a first visual image of the first conference participant to a computer system associated with a second conference participant for visual presentation during the video conference. The system advantageously can enable the computer system associated with each conference participate to visually present a visual image with an associated virtual stage for each of the other conference participants.

Abstract: Systems and methods for predicting a location of a target vehicle are disclosed. A processor receives trajectory information for the target vehicle and determines a trajectory feature based on the trajectory information. The processor further determines a lane feature of a lane within a threshold vicinity of the target vehicle, and determines a probability associated with the lane based on the trajectory feature and the lane feature. The lane that the vehicle may enter is identified based on the probability. The processor may also generate interactive features of interactions between the target vehicle and other vehicles. The processor predicts a location of the target vehicle in an upcoming time period based on the lane feature and the trajectory feature. In some embodiments, the interactive features are also used for the prediction.

Abstract: A driver assistance system for coupling a trailer to a towing vehicle is described, including a video camera attached to the towing vehicle and an associated display device in the driver's field of vision, in whose video image a static guide marking is displayed along which a coupling mouth arranged on the towing vehicle can be contacted with a drawbar eye held on the trailer by a drawbar. Providing a driver assistance system which helps the driver estimating the three-dimensional position of the drawbar eye in relation to the towing vehicle while rearwards approaching a trailer. The video camera is arranged at a vertical distance from the coupling and the guide marking is formed by two beam corridors arranged on both sides of the vehicle's longitudinal axis converging towards one another in the rearward direction of the towing vehicle.

Abstract: Systems and methods for predicting user interaction with vehicles. A computing device receives an image and a video segment of a road scene, the first at least one of an image and a video segment being taken from a perspective of a participant in the road scene and then generates stimulus data based on the image and the video segment. Stimulus data is transmitted to a user interface and response data is received, which includes at least one of an action and a likelihood of the action corresponding to another participant in the road scene. The computing device aggregates a subset of the plurality of response data to form statistical data and a model is created based on the statistical data. The model is applied to another image or video segment and a prediction of user behavior in the another image or video segment is generated.

Abstract: An apparatus for controlling object tracking and a method therefor are provided. The apparatus includes an object detector configured to detect an object in an image, an object tracker configured to track the object, a learning device configured to learn whether to enable the object detector based on features of the object and tracking results of the object tracker, and a controller configured to determine whether to enable the object detector by interworking with the learning device.