Abstract: The home position estimation system includes a GNSS receiver, an object detection device for detecting an object in surroundings of the hybrid vehicle, an identifying part configured to identify the object detected by the object detection device, and a position estimating part configured to estimate a position of the hybrid vehicle based on an output of the GNSS receiver. If a predetermined condition is satisfied and the object identified by the identifying part is an object indicating a boundary of a low emission zone which requires that the internal combustion engine be stopped, the position estimating part is configured to judge whether the hybrid vehicle is located within the low emission zone, regardless of the output of the GNSS receiver, based on a result of identification by the identifying part.

Abstract: When a marker on a road is detected, an automated driving apparatus mounted on a vehicle determines whether to perform automated driving based on comparison between a relative movement log from the marker as a start point according to autonomous navigation and shape point data concerning a lane acquired from the most recent map data.

Abstract: The invention relates to a method for detecting at least one object present on a motor vehicle, wherein by way of a control device, at least one camera image is captured by means of a camera, wherein a detection region of the camera is directed to an outer region of the motor vehicle, and partially or entirely to an outer surface of the motor vehicle. The invention proposes that for a clearance test in the at least one camera image, it is checked by an image analysis device of the control device, if at least one predetermined intrinsic structure of the motor vehicle is imaged, and in the event that at least one intrinsic structure cannot be found by the image analysis device, a blocking signal, which indicates that an object is present on the motor vehicle is generated.

Abstract: A vehicle operation assistance device is provided with: a visual line range determination unit that determines whether a recognition range including a visual line range of an operator of a mobile body corresponds to either an operation panel range to be operated or an external-environment checking range; a vigilance calculation unit that calculates alertness and attentiveness of the operator on the basis of at least movement of the operator's visual line; and a control unit that controls on-board devices of the mobile body on the basis of the recognition range and at least one of the alertness and attentiveness.

Abstract: To improve learning accuracy, while avoiding transferring of a dataset from an edge terminal to a cloud server. A management device accessible to a target object to be managed has a processor executing a program, a storage device storing the program, and a communication interface communicable with the target object. The processor executes a reception process for receiving first environmental information representing a first environment of the target object, a first generation process for generating relevant information representing relevancy between the first environmental information and second environmental information representing a second environment of the target object, a second generation process for generating a first learned model for inference by the target object in the first environment based on the relevant information and a second learned model for inference by the target object in the second environment, and a transmission process for transmitting the first learned model to the target object.

Abstract: A method configured to implemented on at least one map processing device for determining new roads on a map includes obtaining a first road network image of a region, the first road network image including a first plurality of roads. The method also includes determining a second road network image of the region based on a map of the region, the second road network image including a second plurality of roads that are not present in the first road network image. The method further includes determining a third road network image by concatenating the first road network image and the second road network image. The method still further includes determining a fourth road network image of the region by processing the third road network with at least one convolution layer, the fourth road network including the second plurality of roads.

Abstract: Of a plurality of learning models learned to output geometric information corresponding to a captured image, a learning model corresponding to a setting region is acquired.

Abstract: A method for evaluating images and in particular for evaluating correspondences of images. The method includes (i) providing correspondences between given first and second images, (ii) providing a quality measure or a plurality of quality measures as attributes for characterizing a particular correspondence, (iii) evaluating and conditionally selecting the correspondences, (iv) providing selected correspondences as an evaluation result, the evaluation of correspondences being based on a combination of attributes and the selection of correspondences being based on a result of the evaluation.

Abstract: An artificial neural network-based method for detecting a surface pattern of an object includes receiving a plurality of object images, dividing each object image into a plurality of image areas, designating at least one region of interest from the plurality of image areas of each of the object images, and performing deep learning with the at least one region of interest to build a predictive model for identifying a surface pattern of the object.

Abstract: A parking assistance device includes an imager that captures an image of a surrounding of a vehicle, and a display that displays a guidance image for guiding the vehicle from a parking start position to a target parking position and displays a moving area in which the vehicle can move during a parking operation. An area and dimension of the moving area displayed on the display changes based on a change in a steering angle of the vehicle.

Abstract: Vehicle-mounted camera pose estimation methods, apparatuses, and systems, and electronic devices involve performing lane line detection of a road on which a vehicle drives on the basis of a video stream of the road acquired by a vehicle-mounted camera; obtaining horizon information of the road on which the vehicle drives according to a lane line detection result; and obtaining pose information of the vehicle-mounted camera according to the horizon information.

Abstract: A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.

Abstract: Road sign recognition method and system.

Abstract: Efficient and scalable three-dimensional point cloud segmentation. In an embodiment, a three-dimensional point cloud is segmented by adding points to a spatial hash. For each unseen point, a cluster is generated, the unseen point is added to the cluster and marked as seen, and, for each point that is added to the cluster, the point is set as a reference, a reference threshold metric is computed, all unseen neighbors are identified based on the reference threshold metric, and, for each identified unseen neighbor, the unseen neighbor is marked as seen, a neighbor threshold metric is computed, and the neighbor is added or not added to the cluster based on the neighbor threshold metric. When the cluster reaches a threshold size, it may be added to a cluster list. Objects may be identified based on the cluster list and used to control autonomous system(s).

Abstract: In one example, a computing system is configured to obtain orientation data describing an orientation of the camera and geolocation data describing a location of the camera. The computing system is further configured to select, from one or more candidate images from an image database and based at least on the orientation data and the geolocation data, a best-matched image for a current image captured by the camera. The computing system is also configured to determine a location of a vehicle lane in the current image based on at least one lane marker visible in the best-matched image and output at least one indication of the location of the vehicle lane.

Abstract: A target object estimating apparatus comprises parallax information calculating means for calculating parallax information including a parallax between corresponding pixels of taken images taken at a same computation timing, road surface region detecting means for detecting a road surface region in the taken image based on the parallax information, road surface region determining means for determining whether or not each pixel in the taken image corresponds to the road surface region, transition information calculating means for calculating transition information including a change amount of a position of each pixel, using temporally sequential taken images, and estimated value calculating means for estimating a position and a speed of a target object by calculating, based on the parallax/transition information, estimated values of the position and the speed of each pixel.

Abstract: The imaging device includes: an imaging section that includes a plurality of lens units having optical axes aligned in the same direction and one or more imaging elements, the lens units and the imaging elements being combined to form imaging units, the imaging units having different focus temperatures; an image processing unit that calculates a sharpness of an image acquired by each imaging unit; a selection unit that selects an imaging unit which acquires a use image on the basis of the sharpness; and a control unit that controls the imaging section, the image processing unit, and the selection unit.

Abstract: A device provides improved obstacle identification. A first camera acquires first vehicle image data and provides it to a processing unit. A second camera acquires and provides second vehicle image data. An image overlap region has at least a portion of the first vehicle image data and at least a portion of the second vehicle image data. The first and second vehicle image data extend over a ground plane and the image overlap region extends over an overlap region of the ground plane. The processing unit extracts first image features from the first vehicle image data and extracts second image features from the second vehicle image data. The processing unit projects the first and the second image features onto the ground plane.

Abstract: An automated guided vehicle (AGV) has an image reader that scans indicia located on a floor. The image reader scan the indicium to obtain instructions for the AGV to follow. A processor in the AGV can perform geometry estimation of ellipsoidal objects in order to align the AGV as it moves or is stopped along a path.

Abstract: A method for determining the course of the road for a moving motor vehicle having a surroundings sensor system. Sensor data generated by the surroundings sensor system are evaluated to detect lane-relevant features. A lane model having at least one lane model parameter that determines the course of the lane is generated for the road, structures of at least one distance range that are parallel to the road are detected in the sensor data, the tangential direction of at least the one structure that is parallel to the road is determined, and the value of the tangential direction of the structure that is parallel to the road is adopted as the value of the direction of the tangent line at the point of contact with the structure that is parallel to the road to determine at least the one lane model parameter by predictive estimation in the lane model.

Abstract: A system and methods for reducing map search area requirements in a navigation system are disclosed. The system includes a vehicle, an imaging device onboard the vehicle configured to generate an image scan, receive at least one image responsive to the image scan, and a processing device configured to receive and store the at least one image. The system further includes a navigation system onboard the vehicle configured to store an image of a map, and a learning network associated with the navigation system and configured to divide the image of the map into a plurality of map subsections, recognize each one of a plurality of images of different landmarks on the map, generate a set of classifications for each map subsection, and associate each classification of the set of classifications with at least one landmark of the different landmarks on the map.

Abstract: A system and methods for reducing map search area requirements in a navigation system are disclosed. The system includes a vehicle, an imaging device onboard the vehicle configured to generate an image scan, receive at least one image responsive to the image scan, and a processing device configured to receive and store the at least one image. The system further includes a navigation system onboard the vehicle configured to store an image of a map, and a learning network associated with the navigation system and configured to divide the image of the map into a plurality of map subsections, recognize each one of a plurality of images of different landmarks on the map, generate a set of classifications for each map subsection, and associate each classification of the set of classifications with at least one landmark of the different landmarks on the map.

Abstract: A method for identifying an object in a surrounding region of a motor vehicle as a stationary object is disclosed. The surrounding region is captured in images using a vehicle-side capture device and the object is detected in the captured images using an image processing device. A first position of the object in the surrounding region relative to the motor vehicle is estimated on the basis of a first captured image, a movement sequence of the object in image coordinates is determined on the basis of the first image and a second captured image, a first movement sequence that characterizes a first, stationary object in the image coordinates is determined proceeding from the first estimated position in the surrounding region, and the captured object is identified as a stationary object on the basis of a comparison of the movement sequence of the captured object to the first characterizing movement sequence.

Abstract: A parking support system includes a parking path planning unit that plans a trajectory of each unit path when moving a vehicle to a target parking position by repeating a movement of the unit path including one forward movement and one backward movement in succession and calculates a vehicle control signal that causes the vehicle to move along the trajectory such that a steering angle of the vehicle is substantially 0 degrees at an arrival position of each of the forward movement and the backward movement.

Abstract: A system to use submaps to control operation of a vehicle is disclosed. A storage system may be provided with a vehicle to store a collection of submaps that represent a geographic area where the vehicle may be driven. A programmatic interface may be provided to receive submaps and submap updates independently of other submaps.

Abstract: Systems, Methods and Apparatuses are provided for detecting surface conditions, which includes: an image scene captured by a camera wherein the image scene includes: a set of a plurality of regions of interest (ROIs); and a processor configured to receive the image scene to: extract at least a first and a second ROI from the set of the plurality of ROIs of the image scene; associate the first ROI with an above-horizon region and associate the second ROI with a surface region; analyze the first ROI and the second ROI in parallel for a condition related to an ambient lighting in the first ROI and for an effect related to the ambient lighting in the second ROI; and extract from the first ROI features of the condition of the ambient lighting and extract from the second ROI features of the effect of the ambient lighting on a surface region.

Abstract: A camera module, which is mounted on an inside of a front windshield of a vehicle and configured to image an external environment of the vehicle, includes multiple lens units on which an optical image of the external environment is incident, individually, and an imaging system to generate an outside image of the external environment by imaging through each of the lens units, individually.

Abstract: An apparatus can include a processor that can receive location data from a user device, and store the location data in a user profile data structure also storing facial recognition data. The processor can also receive at least one image, and can identify a location based at least in part on a set of characteristics within the at least one image. The processor can, for each user profile data structure stored in a database, compare location data in that user profile data structure to the location. The processor can, when the location data of the user profile data structure and the location match, conduct facial recognition to determine whether the user associated with the user profile data structure can be identified in the at least one image. The processor can then associate the at least one image with the user profile data structure if the user can be identified.

Abstract: A camera module, which is mounted on an inside of a front windshield of a vehicle and configured to image an external environment of the vehicle, includes multiple lens units on which an optical image of the external environment is incident, individually, and an imaging system to generate an outside image of the external environment by imaging through each of the lens units, individually.

Abstract: A lane keeping assist method and system may include determining a driving state of a vehicle according to a state of a lane change in which an intention of a driver is reflected after a turn signal is applied, adjusting a criterion for driver override depending on an error between a driving path of the vehicle and a target path according to the driving state of the vehicle, comparing a steering torque of the driver with the adjusted criterion to determine activation or cancellation of the driver override, minimizing the driver's discomfort in the steering operation when the driver intentionally changes the lane.

Abstract: A parking assist system for a vehicle includes a rear backup camera and a control having an image processor that processes image data captured by the rear backup camera. The control, when the vehicle is driven forward into a parking slot and responsive to image processing of captured image data, determines a parking slot marker at a side boundary of the parking slot at which the vehicle is being parked. The system may include a display screen that displays images representative of the vehicle at a determined orientation relative to the determined parking slot marker so a driver of the vehicle can determine whether or not the vehicle is aligned in the parking slot. The control may determine a degree of misalignment of the vehicle relative to the parking slot and may generate an output to alert the driver that the vehicle is not aligned in the parking slot.

Abstract: A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.

Abstract: Systems and methods are provided for navigating a vehicle using a crowdsourced sparse map. In one implementation, a method of autonomously navigating a vehicle along a road segment may include receiving a sparse map model, receiving at least one image representative of an environment of the vehicle, analyzing the sparse map model and the at least one image, and determining an autonomous navigational response for the vehicle based on the analysis of the sparse map model and the at least one image. The at least one image may be received from a camera, and the sparse map model may include at least one line representation of a road surface feature extending along the road segment, each line representation representing a path along the road segment substantially corresponding with the road surface feature.

Abstract: A camera module, which is mounted on an inside of a front windshield of a vehicle and configured to image an external environment of the vehicle, includes multiple lens units on which an optical image of the external environment is incident, individually, and an imaging system to generate an outside image of the external environment by imaging through each of the lens units, individually.

Abstract: A position identifying apparatus includes a position detecting unit; an information acquiring unit; a feature extracting unit; an index value calculating unit; a feature selecting unit; a correlating unit; a weight setting unit; and a correcting unit. The position detecting unit performs a map matching to detect a vehicle position on a map. The information acquiring unit acquires road information from the map. The feature extracting unit extracts features of a ground object. The index value calculating unit calculates an index value representing a likelihood of a stationary object. The feature selecting unit selects feature candidates among the features having the index values larger than or equal to a predetermined likelihood of the stationary object. The correlating unit correlates the feature candidates with the road information. The weight setting unit sets weights of the feature candidates. The correcting unit corrects the position of the vehicle using the weights.

Abstract: A vehicle is operable in a first operating mode in which the vehicle travels autonomously inside the traffic lane based on a detection of lane markings of a traffic lane and in a second operating mode in which the vehicle autonomously follows a vehicle driving in front while ignoring lane markings, and a method of its operation includes operating the vehicle in a first of the two operating modes, detecting a vehicle environment, and switching from the first operating mode to the other of the two operating modes as a function of the detected vehicle environment. A device can execute the method and a computer program can be executed by a device for performing the method.

Abstract: The invention relates to creating and viewing stereo images, for example stereo video images, also called 3D video. At least three camera sources with overlapping fields of view are used to capture a scene so that an area of the scene is covered by at least three cameras. At the viewer, a camera pair is chosen from the multiple cameras to create a stereo camera pair that best matches the location of the eyes of the user if they were located at the place of the camera sources. That is, a camera pair is chosen so that the disparity created by the camera sources resembles the disparity that the user's eyes would have at that location. If the user tilts his head, or the view orientation is otherwise altered, a new pair can be formed, for example by switching the other camera. The viewer device then forms the images of the video frames for the left and right eyes by picking the best sources for each area of each image for realistic stereo disparity.

Abstract: A road paver for paving paving material in a paving direction (a) is provided comprising a machine frame, a driver's platform, a drive motor, a chassis with at least a left travel unit and a right travel unit, a material container arranged at the front of the road paver in the paving direction (a) for receiving paving material, the material container comprising a left container half and a right container half, which each have a container floor, a rising container sidewall and a rising container rear wall, and a longitudinal conveying device configured to transport paving material from the material container to a paving screed arranged at the rear of the road paver in the paving direction.

Abstract: A camera module, which is mounted on an inside of a front windshield of a vehicle and configured to image an external environment of the vehicle, includes multiple lens units on which an optical image of the external environment is incident, individually, and an imaging system to generate an outside image of the external environment by imaging through each of the lens units, individually.

Abstract: Example sinkhole detection systems and methods are described. In one implementation, a method receives data from multiple sensors mounted to a vehicle and analyzes the received data to identify a sinkhole in a roadway ahead of the vehicle. If a sinkhole is identified, the method adjusts vehicle operations and reports the sinkhole to a shared database and/or another vehicle.

Abstract: A domestic robotic system including a robot, which includes a movement system for moving the robot over a surface, an image obtaining device, and a processor. The processor is programmed to detect a predetermined pattern within the images, the predetermined pattern being associated with a marker provided on a base station, respond to the detection of the predetermined pattern by determining, by a first process, an estimate of the robot's position and/or orientation, this estimate of the robot's position and orientation being relative to the base station, the processor and the image obtaining device thereby forming part of a first positioning system, determine, by a second process, an alternative estimate of the robot's position and/or orientation, the processor thereby forming part of a second positioning system, and perform at least one calibration of the second positioning system using the first positioning system.

Abstract: A travel control apparatus for a vehicle includes: a frontward environment recognition unit that obtains frontward environment information by recognizing a frontward environment of the vehicle; a frontward environment information reliability calculator that calculates a reliability of the frontward environment information; a map information storage unit that stores map information relating to a travel region of the vehicle on the basis of position information indicating a position of the vehicle; a map information updating unit that updates the map information while calculating a reliability of the map information; a control information selector that compares the reliability of the frontward environment information with update information relating to the map information, and selects either one of the frontward environment information and the map information as information to be used during automatic driving control; and an automatic driving control execution unit that executes the automatic driving control ba

Abstract: A camera module, which is mounted on an inside of a front windshield of a vehicle and configured to image an external environment of the vehicle, includes multiple lens units on which an optical image of the external environment is incident, individually, and an imaging system to generate an outside image of the external environment by imaging through each of the lens units, individually.

Abstract: Various aspects of a system and method to provide driving assistance are disclosed herein. The system comprises one or more circuits in an electronic control unit used in a vehicle configured to detect one or more actions associated with the vehicle based on one or more signals generated by one or more sensors embedded in the vehicle. The electronic control unit may be further configured to control the activation of an imaging device located on the vehicle at an opposite side of a driver of the vehicle, based on the detected one or more actions. The imaging device is operable to capture one or more images in a forward-facing direction of the vehicle.

Abstract: An automatic land following control system is provided and includes an image sensor, a steering angle sensor, an inertial measurement unit, a vehicle speed sensor and a controller. The image sensor senses a vehicle lane to generate a land data. The steering angle sensor senses a steering angle to generate a steering angle data. The IMU senses an acceleration, a yaw rate and a roll angle of the vehicle to generate an acceleration data, a yaw rate data and a roll angle data. The vehicle speed sensor senses a speed of the vehicle to generate a vehicle speed data. The controller receives a digital map data, the lane data, the steering angle data, the acceleration data, the yaw rate data, the roll angle data and the vehicle speed data to calculate a compensation angle data of the wheel.

Abstract: In an example embodiment, a vehicle guidance system includes a memory including computer-readable instructions stored therein and a processor. The processor is configured to execute the computer-readable instructions to estimate a wheel angle of a vehicle based on at least a first value, the first value being a hand wheel based estimate of the wheel angle, and adjust steering commands for steering the vehicle based on the estimated wheel angle to permit the vehicle to move along a set path.

Abstract: Provided is a display device for a vehicle. The display device includes a display member and a collision predictor. The collision predictor detects one or more moving bodies on and around a course of the vehicle, and predicts collision of the vehicle with the one or more moving bodies detected, and a position of the collision. The display member displays a collision-position mark at a display position in a visual field of a driver, on a condition that the collision of the vehicle with any one of the one or more moving bodies is predictable. The display position is superimposed on the predicted position of the collision. The display member displays a delineator mark that associates the collision-position mark with the relevant one of the one or more moving bodies detected.

Abstract: Methods and apparatuses are provided for controlling an external object by an electronic device. A line of sight of a user is determined using an image sensor of the electronic device. An object located outside of the electronic device is determined based on the line of sight of the user. Object information regarding the object is determined. A user input with respect to the object is received from the user. The object or another electronic device associated with the object is controlled based on the user input and the object information.

Abstract: A vehicle can be controlled in a first autonomous mode of operation by at least navigating the vehicle based on map data. Sensor data can be obtained using one or more sensors of the vehicle. The sensor data can be indicative of an environment of the vehicle. An inadequacy in the map data can be detected by at least comparing the map data to the sensor data. In response to detecting the inadequacy in the map data, the vehicle can be controlled in a second autonomous mode of operation and a user can be prompted to switch to a manual mode of operation. The vehicle can be controlled in the second autonomous mode of operation by at least obtaining additional sensor data using the one or more sensors of the vehicle and navigating the vehicle based on the additional sensor data.

Abstract: A method for detecting a narrow road includes calculating relative heights of points from a distance measuring sensor to a ground based on distance information. A left boundary point and a right boundary point, at which a difference in relative heights from adjacent points becomes maximal, are acquired. A road boundary line of a driving road is acquired based on the left boundary point and the right boundary point depending on a movement trajectory of the vehicle when a difference in relative heights at the left boundary point and the right boundary point is more than or equal to a reference value. A road width of the driving road is calculated based on the road boundary line. It is detected whether the driving road of the vehicle is a narrow road based on the road width.