Abstract: A system and method for remapping surface areas of vehicle environment that include receiving a plurality of images of the surface areas of the vehicle environment from a computing device. The system and method also include evaluating the plurality of images to determine an optical flow value associated with at least one pixel of at least two images of the plurality of images. The system and method additionally include determining at least one surface area that includes an external environment of the vehicle. The system and method further include remapping the surface areas by filtering the at least one surface area from which the external environment is captured and rendering at least one surface area graphical augmentation on at least one remapped surface area of the vehicle environment.

Abstract: In one embodiment, a computing system accesses a number of features extracted from one or more first images. The extracted features are associated with at least one object captured in the first images. The first images are captured by a camera associated with a vehicle. The computing system identifies, in a reference map, reference features matching one or more of the features extracted from the first images. The reference features are associated with the at least one object captured in the first images. The computing system generates, for the camera, a calibration model by comparing the identified reference features in the reference map and the features that match the one or more reference features. The calibration model is used to calibrate second images captured by the camera associated with the vehicle.

Abstract: Disclosed is a method and apparatus for detecting a road line includes segmenting a driving image data into a plurality of segmentation areas, determining a candidate vanishing-point area corresponding to a segmentation area of the segmentation areas, extracting at least one straight road line from the segmentation area, detecting a partial line corresponding to the segmentation area based on whether the at least one straight road line meets the candidate vanishing-point area, detecting the road line of the driving image data by connecting partial lines corresponding to the segmentation areas, and indicating the detected road line.

Abstract: A method of enhancing positioning of a moving vehicle based on visual identification of visual objects, comprising obtaining from a location sensor a global positioning and a movement vector of a moving vehicle, capturing one or more images using one or more imaging devices mounted on the moving vehicle to depict at least partial view of a surroundings of the moving vehicle, analyzing the image(s) to identify one or more visual objects having a known geographical position obtained according to the global positioning from a visual data record associated with a navigation map, analyzing the image(s) to calculate a relative positioning of the moving vehicle with respect to the identified visual object(s), calculating an enhanced positioning of the moving vehicle based on the relative positioning and applying the enhanced positioning to a navigation system of the moving vehicle.

Abstract: A traffic light monitoring system includes a vehicle. The vehicle includes an imaging sensor configured to capture images, one or more processors, one or more memory modules, and machine readable instructions stored in the one or more memory modules that cause the vehicle to perform at least the following when executed by the one or more processors: identify a traffic light based on the images, determine a first transition time when a first light of a traffic light turns off and a second light of the traffic light turns on based on the images, determine a second transition time when the second light of the traffic light turns off and a third light of the traffic light turns on based on the images, and transmit information about the first transition time and the second transition time to an edge computing device.

Abstract: Embodiments of the present invention facilitate product defect detection. A computer-implemented method comprises: receiving, by a device operatively coupled to one or more processors, a template image of a normal product; generating, by the device, one or more geometric training parameters for transforming the template image; and transforming, by the device, the template image using the one or more geometric training parameters to generate a transformed image for training a data model, wherein the trained data model being used for aligning the template image and an image under inspection of a product.

Abstract: An image processing device includes: a road surface detecting section to detect a road surface region from an input image based on a shot image obtained by shooting with a camera; a time-series verifying section to perform time-series verification to verify a result of detection of the road surface region in the input image in a time-series manner; a detection region selecting section to set a detection region for detection of an object in the input image according to the result of detection of the road surface region by the road surface detecting section and a result of the time-series verification by the time-series verifying section; and a detecting section to detect the object in the detection region.

Abstract: A sensor system mounted on a vehicle includes: a first sensor configured to acquire information on a first area outside the vehicle; a second sensor configured to acquire information on a second area that partially overlaps with the first area outside the vehicle; and a controller configured to change an information acquisition rate of the first sensor and an information acquisition rate of the second sensor, in which when the information acquisition rate of one of the first sensor and the second sensor falls below a predetermined value, the controller increases the information acquisition rate of the other sensor to be higher than the predetermined value.

Abstract: Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Abstract: A system and a method for determining a parking space are provided. The method includes: obtaining parking space information within a range where a vehicle is located, the parking space information including parking lot map data; analyzing an object in individual parking space in the parking space information and generating object information of the object of the individual parking space; and using the object information and the parking space information to calculate a spatial relationship between the object in the individual parking space and a parking space where the object is located, and determining that the parking space is an available parking space if the spatial relationship satisfies vehicle body information of the vehicle. Therefore, the vehicle can determine an available parking space before passing it, and can further choose a better parking space.

Abstract: A lighting system of a vehicle may include light units and controllers for operating the light units. Each light unit is multifunctional in that the light unit may operate in various modes, which may be invoked at different times under varying circumstances. A light unit on the first end of a vehicle may operate as a headlight if the first end is the front end of the vehicle. On the other hand, the light unit may operate as a tail light if the first end is the rear end of the vehicle. Furthermore, the light unit may operate as a turn signal in either direction or brake light while the first end is the rear end of the vehicle. The light unit includes a lens array positioned to receive light from various light sources. The lighting system may operate in a fashion that allows for lighting redundancy on each end of the vehicle in the event of a lighting controller failure.

Abstract: Determine a current position of a camera relative to a road based on a set of imagery from the camera and a recommended position of the camera relative to the road based on the set of imagery from the camera, while the camera is maintained at a constant height relative to the road and a constant lateral distance relative to the road. The camera can be positionally adjusted from the current position to the recommended position based on a movement of the camera about a Y-axis or a Z-axis of the camera at that time relative to the road. In order to enable movement of the camera, a guide can be output to a user such that the user can follow the guide and move the camera from the current position to the recommended position.

Abstract: A vehicle control device includes a recognizer 130 which recognizes a surrounding situation of a host vehicle and a driving controller 140 and 160 which executes driving control by controlling one or both of steering and acceleration/deceleration of the host vehicle on the basis of the surrounding situation recognized by the recognizer, wherein the driving controller assigns predetermined required tasks to an occupant of the host vehicle to execute the driving control when there is a gap of a threshold value or more between first speed information determined from at least one of a traveling speed of the host vehicle and a target speed and second speed information determined from at least one of a speed limit in a lane in which the host vehicle is traveling and a speed of a neighboring vehicle traveling around the host vehicle.

Abstract: Multi-modal data representing driving events and corresponding actions related to the driving events can be obtained and used to train a neural network at least in part by using a triplet loss computed for the driving events as a regression loss to determine an embedding of driving event data. In some cases, using the trained neural network, a retrieval request for an input driving event and corresponding action can be processed by determining, from the neural network, one or more similar driving events or corresponding actions in the multi-modal data.

Abstract: In the present invention, sign information displayed on road signs installed above a road are associated with lanes more accurately. This vehicle control device 1 acquires the number of lanes, in the direction of movement of a host vehicle, on a road on which the host vehicle is traveling, and assigns a lane sequence code indicating the layout sequence to each of the lanes indicated by the number of lanes. The vehicle control device 1 acquires the position of a road sign installed above the road and sign information displayed on the road sign from a captured image of the road sign, and, if there are two or more items of sign information, assigns a sign information sequence code indicating the layout sequence to each of the items of sign information on the basis of the position of the road sign.

Abstract: A combination of target images and control images are presented to a user device for selection by the user. Based on a correct selection of images that the user either recognizes or does not recognize, the user may be authenticated. Target images have some connection to a legitimate user in a way that a legitimate user may recognize the target image. Control images have no known connection to the legitimate user, such that they would not typically be recognized by the legitimate user. The legitimacy of a user may be determined based on images selected and/or not selected, depending on accompanying instructions for selection.

Abstract: An apparatus includes a sensor, a navigation circuit and a control circuit. The sensor may be configured to generate surrounding road information of a road. The road may have a plurality of available lanes. The navigation circuit may be configured to determine a current position of the apparatus on the road. The control circuit may be configured to (i) access map data that identifies a number of the available lanes in the road proximate the position, (ii) determine a current lane among the available lanes that the apparatus is within based on all of the position, the surrounding road information and the map data and (iii) generate feedback data based on both the position and the current lane. The navigation device may be further configured to adjust the current position to a center of the current lane in response to the feedback data.

Abstract: An image processing device includes an image acquiring unit, a detection unit, and a display processing unit. The image acquiring unit is configured to acquire a captured image from an image capturing device configured to capture an image of the periphery of a vehicle. The detection unit is configured to detect a lane marker defining a traveling track of the vehicle from the captured image acquired by the image acquiring unit. The display processing unit is configured to display, on a display device, a superimposition image as the captured image on which a marker image for supporting visibility of the lane marker is superimposed such that the marker image is superimposed on the lane marker detected by the detection unit.

Abstract: A system for tracking a following vehicle by a leading vehicle. In one example, the system includes a user interface, a camera, an output device, and an electronic controller. The electronic controller is configured to receive, via the user interface, an indication of the following vehicle and recognize the following vehicle. The electronic controller tracks the following vehicle using a video feed from the camera and determines whether the following vehicle is struggling to follow the leading vehicle. The electronic controller also generates a driver notification when the following vehicle is struggling to follow the leading vehicle and outputs, via the output device, the driver notification.

Abstract: Methods of creating trained semantic segmentation network models and operating vehicles using the model. One example method includes an outside view camera configured to capture images that represent an artificial representation of the driver's view, a driver-facing camera configured to capture a driver's eye movements, and an electronic controller. The electronic controller is configured to receive images from the cameras; calibrate the image of the driver's eye movement with the artificial driver view; create a pixel weighted heat map of the calibrated images; create a trained semantic segmentation neural network model and a trained attention neural network model using the pixel weighted heat map and the artificial driver view; and operate the vehicle using the trained semantic segmentation neural network model and the trained attention neural network model.

Abstract: An information providing device and an information providing method capable of providing information according to a driving load while alleviating or eliminating a sense of discomfort of a user of a vehicle is provided. An information providing device includes an emotion determination unit that determines virtual emotion of a vehicle, and an output control unit that determines one or both of content and an output mode of the information that the output unit is caused to output according to the virtual emotion of the vehicle. The emotion determination unit determines predetermined emotion to be the virtual emotion of the vehicle when a condition that a period in which the traveling state of the vehicle detected by the traveling state detection unit is a predetermined traveling state has continued for a predetermined period or longer is satisfied.

Abstract: A method for co-registering terrain data and image data includes receiving terrain data and image data. The method also includes determining a position of a light source based upon the image data. The method also includes creating a hillshade representation of the terrain data based upon the terrain data and the position of the light source. The method also includes identifying a portion of the hillshade representation and a portion of the image data that correspond to one another. The method also includes comparing the portion of the hillshade representation and the portion of the image data. The method also includes determining a vector control between the portion of the hillshade representation and the portion of the image data based upon the comparison. The method also includes applying the vector control to the image data to produce updated image data.

Abstract: Disclosed is a method and apparatus for determining a lane, the method including extracting plural straight-line segments from a captured stereo image including a first image and a second image of a driving road, selecting a first lane from the stereo image based on line segments of the plural straight-line segments, corresponding to lanes of the driving road, predicting a second lane candidate, based on the first lane, including at least a portion of a lane area excluding the line segments in the stereo image, and determining a second lane by updating a position of the predicted second lane candidate based on a confidence value of the predicted second lane candidate.

Abstract: System, methods, and other embodiments described herein relate to dynamically determining an appropriate responsive action for a moving vehicle that encounters a roadside pedestrian and stationary vehicle. In one embodiment the disclosed system identifies a stationary vehicle in an environment of a subject vehicle based at least in part on information from a plurality of sensors disposed on the subject vehicle and determines a classification for the stationary vehicle as valid or abandoned based at least in part on the information from the plurality of sensors. A classification of valid indicates that the subject vehicle is recommended to undertake an action relative to the stationary vehicle. The disclosed generates a score based at least in part on the classification, the score indicating a recommended trajectory modification for the subject vehicle, and modifies a trajectory of the subject vehicle based on score.

Abstract: A method for detecting a screening of a sensor device of a motor vehicle by an object. The method includes receiving at least one echo signal, captured by the sensor device, that characterizes a spacing between the sensor device and the object, determining a capture region for the sensor device based on the at least one received echo signal, checking whether the capture region is being screened by the object at least in some regions, assigning the at least one echo signal to a discrete spacing value from multiple discrete spacing values, determining, for each discrete spacing value a power value based on the echo signal, and deciding, by a classifier based on the power values, whether a predetermined proportion of the capture region is being screened by the object.

Abstract: An autonomous system for generating and interpreting point clouds of a rail corridor along a survey path while moving on a railroad corridor assessment platform. The system includes two rear-facing LiDAR sensors configured to scan along scan planes that intersect but not at all points and wherein neither scan plane intersects a main body of any rail car adjoined to a rear end of the railroad corridor assessment platform. The system also includes a plurality of high-resolution cameras for gathering image data from a rail corridor. The LiDAR sensors and the high-resolution cameras are housed in autonomously controlled and temperature controlled protective enclosures.

Abstract: A method and apparatus for processing image data is provided. The method includes the steps of employing a main processing network for classifying one or more features of the image data, employing a monitor processing network for determining one or more confusing classifications of the image data, and spawning a specialist processing network to process image data associated with the one or more confusing classifications.

Abstract: The present invention relates to an image analysis method, device, system, and program, which use vehicle driving information, and a recording medium, and according to one embodiment of the present invention, an image analysis method of a device linked with a camera and a controller through an in-vehicle communication network can comprise the steps of: receiving vehicle driving information from at least one controller for controlling vehicle driving; receiving image information captured by the camera; generating a first optical flow pattern estimated on the basis of the vehicle driving information; generating a second optical flow pattern calculated on the basis of the image information; and identifying a foreground movement pattern on the basis of the first optical flow pattern and the second optical flow pattern. Therefore, the present invention can more accurately analyze, by using vehicle driving information, an image captured by a camera.

Abstract: Disclosed is a driving assistance method, comprising: periodically capturing an image in front of a vehicle; obtaining fitting points on each of edges of a road in the image; generating a virtual boundary on the basis of the obtained fitting points; and generating at least one virtual lane line between two virtual boundaries of the road. With the driving assistance method, the road without lane division can be divided into lanes to improve traffic safety. The present disclosure also provides a driving assistance device and a vehicle having the same.

Abstract: Aspects of the disclosure relate to training and using a phrase recognition model to identify phrases in images. As an example, a selected phrase list may include a plurality of phrases is received. Each phrase of the plurality of phrases includes text. An initial plurality of images may be received. A training image set may be selected from the initial plurality of images by identifying the phrase-containing images that include one or more phrases from the selected phrase list. Each given phrase-containing image of the training image set may be labeled with information identifying the one or more phrases from the selected phrase list included in the given phrase-containing images. The model may be trained based on the training image set such that the model is configured to, in response to receiving an input image, output data indicating whether a phrase of the plurality of phrases is included in the input image.

Abstract: An information processing apparatus that estimates waiting time in a waiting line with improved accuracy includes a first acquisition unit that acquires a number of objects in the waiting line, a second acquisition unit that acquires frequency of an object exiting the waiting line, and an estimation unit that estimates waiting time in the waiting line based on the acquired number of objects in the waiting line and the acquired frequency of an object exiting the waiting line.

Abstract: The invention relates to a method for classifying a traffic sign (7) in an environment region (4) of a motor vehicle (1) as a traffic sign sticker (9) located on an industrial or commercial vehicle (10) or as a stationary traffic sign (8), wherein in the method at least one first image (11, 12) of the environment region (4), captured by a camera (3) of the motor vehicle (1), is received and the traffic sign (7) is recognized in the at least one first image (11, 12), wherein a geometric dimension (D1?, D2?) of the traffic sign (7) in the first image (11, 12) is determined on the basis of said first image (11, 12), a first reference dimension (Dmin, Dmax), which is characteristic of a stationary traffic sign (8), is prescribed for the captured traffic sign (7), a first position (Pmin, Pmax) of the traffic sign (7) in the environment region (4) is estimated based on the geometric dimension (D1?, D2?) of the traffic sign (7) in the first image (11, 12) and on the basis of the first reference dimension (Dmin, Dmax

Abstract: A vehicle speed limiter system installed on a vehicle includes a detection unit to detect a speed limit value of a road while the vehicle is traveling; a setting unit to set the speed limit value; a limiter unit to limit the vehicle speed, based on the speed limit value; an obtainment unit to obtain a stepping amount on an accelerator pedal; a calculation unit to calculate a parameter depending on the stepping amount in a state where the vehicle speed is being limited by the limiter unit; and a display unit to display information based on the parameter, in a case where a speed limit value newly detected by the detection unit is greater than the speed limit value previously set by the setting unit, before the setting unit sets the speed limit value newly detected.

Abstract: In response to a first image captured by a camera of an ADV, a horizon line is determined based on the camera's hardware settings, representing a vanishing point based on an initial or default pitch angle of the camera. One or more lane lines are determined based on the first image via a perception process performed on the first image. In response to a first input signal received from an input device, a position of the horizon line is updated based on the first input signal and a position of at least one of the lane lines is updated based on the updated horizon line. The input signal may represent an incremental adjustment for adjusting the position of the horizon line. A first calibration factor or first correction value is determined for calibrating a pitch angle of the camera based on a difference between the initial horizon line and the updated horizon line.

Abstract: A method, system, and computer program product is provided, for example, for matching a geospatial message to one or more static objects on a link. The method may include identifying a location of an observation point for observing the one or more static objects from a vehicle on the link. The method may further include applying spatial filtering criteria to each of the one or more static objects based on an observable distance of each of the one or more static objects from the location of the observation point to filter the one or more static objects. The filtering of the one or more static objects may provide one or more filtered static objects. The method may further include calculating a heading of the vehicle and further using the heading of the vehicle for applying a heading filtering criteria to the one or more filtered static objects based on the heading of the vehicle and a pre-computed heading of each of the one or more filtered static objects to provide one or more candidate objects.

Abstract: A dimensional measuring device includes an overview camera and a triangulation scanner. A six-DOF tracking device tracks the dimensional measuring device as the triangulation scanner measures three-dimensional (3D) coordinates on an exterior of the object. Cardinal points identified by the overview camera are used to register in a common frame of reference 3D coordinates measured by the triangulation scanner on the interior and exterior of the object.

Abstract: An image processing apparatus includes one or more processors; and a memory, the memory storing instructions, which when executed by the one or more processors, cause the one or more processors to generate vertical direction distribution data indicating a frequency distribution of distance values with respect to a vertical direction of a range image, from the range image having distance values according to distance of a road surface in a plurality of captured images captured by a plurality of imaging parts; estimate a plurality of road surfaces, based on the vertical direction distribution data; and determine a desired road surface, based on the estimated plurality of road surfaces.

Abstract: A driving assistance device converts an image captured by an in-vehicle camera configured to image the periphery of a vehicle into an image viewed from a virtual viewpoint. The driving assistance device combines, as a higher-level layer, a vehicle image indicating the position and shape of the vehicle with a converted target image. The driving assistance device adjusts the opacity of the vehicle image such that the target image as a lower-level layer is visible at a superimposed portion of the vehicle image and the target image. At this point, the opacity of the vehicle image is variably set according to at least one of an own vehicle surrounding condition or a vehicle running condition. The driving assistance device outputs, as a driving assistance image, the target image combined with the adjusted vehicle image.

Abstract: Disclosed is an autonomous distributed system for detecting and tracking a falling object within a region being monitored by using a plurality of camera assemblies cooperating with each other, and disclosed is a camera assembly therefor. Each of the camera assembly, normally, operates in a falling object detecting mode, but, when detecting a falling object, shifts to a tracking mode. In the tracking mode, a degree of danger of the falling object is determined by referring to the size of the falling object in real space and the movement of a falling. In addition, when the falling object is further tracked and moved outside of the angle of view, a search request including information of the degree of danger as to the falling object is issued to surrounding camera assemblies, such that the multiple camera assemblies search for the falling object in cooperation.

Abstract: A road parameter calculator is provided which is equipped with an edge-point extracting unit, a road parameter calculating unit, a gradient detecting unit, and a modeling unit. The image acquiring unit. The edge-point extracting unit extracts edge points from an image of a frontal view of a vehicle. The parameter calculating unit calculates a road parameter using the edge points through a Kalman filter. The gradient detecting unit detects a change in gradient of the road in front of the vehicle. The modeling unit is responsive to a change in gradient to make a model as extending more straight than when the change in gradient is not detected. This minimizes adverse effects of the change in gradient of the road on the calculation of the road parameter.

Abstract: Methods described herein relate to using vision-based mapping to provide augmented reality of objects in the environment of the vehicle in response to objects being obscured. Methods may include: receiving sensor data from a vehicle traveling along a road segment; identifying a location of the vehicle on the road segment; retrieving map data from a map database of an environment of the road segment at the location of the vehicle on the road segment; identifying an object in the sensor data representing an obscured object in an environment of the vehicle; and providing for display of at least one object from the map data in an augmented reality of the environment, where the at least one object appears overlaid on the obscured object to a driver of the vehicle. The object in the sensor data may include a road sign having information relating to driving along the road segment.

Abstract: A method for controlling one or more lights of a light system supported by a vehicle is provided. The method includes receiving sensor system data from a sensor system supported by the vehicle and determining a current status associated with the one or more lights of the vehicle light system. The method includes determining an updated status associated with the one or more lights of the vehicle light system based on the sensor system data. The method also includes transmitting instructions to the light system. The instructions cause the one or more lights to adjust their current status based on the updated status.

Abstract: A mobile body surroundings display method is performed by a mobile body surroundings display apparatus that includes an image capturing element that acquires surroundings information on a mobile body by image capturing, a controller that creates a captured image using the surroundings information and a virtual image representing a situation around the mobile body, and a display that displays the virtual image. The method detects an attention-required range around the mobile body, creates a captured image of the attention-required range, and displays the captured image of the attention-required range on the display.

Abstract: A vehicle external recognition extracts a feature point from an image including an environment around a vehicle; measures a distance from the vehicle to the feature point based on a movement of the feature point; extracts, as a first road surface area, a local area judged as a road surface based on distance information to the feature point and a position of the feature point in the image from among a plurality of local areas in the image; calculates a multi-dimensional image feature amount including color information for each of the plurality of local areas, and similarity to the first road surface area using the image feature amount with respect to a no-road-surface-extracted area(s) from among the plurality of local areas; extracts a second road surface area from the no-road-surface-extracted area(s) based on the similarity; and recognizes a travelable area using the first and the second road surface areas.

Abstract: A method and device for determining an ego-motion of a vehicle are disclosed. Respective sequences of consecutive images are obtained from a front view camera, a left side view camera, a right side view camera and a rear view camera and merged. A virtual projection of the images to a ground plane is provided using an affine projection. An optical flow is determined from the sequence of projected images, an ego-motion of the vehicle is determined from the optical flow and the ego-motion is used to predict a kinematic state of the car.

Abstract: A head-up display device is configured to project a display image in a vehicle onto a projection member that transmits an external real image to display the display image superimposed on the external real image for virtual image display visible to an occupant in the vehicle. A projection unit is configured to project a notification image as the display image for notifying the occupant of specific information onto the projection member. A display control unit is configured to control the projection unit to adjust a virtual image display state of the display image and to cut a virtual image display of specific pixels forming an inner portion inside an outer edge portion of the notification image.

Abstract: The present subject matter refers an image-processing method comprises receiving a first-image of an object captured by a range-imaging device at a first viewing location. The transforming the first-image into a second image of the object, said second image corresponding to an image captured based on range-imaging at a second viewing location with respect to the object. The gaps in the second-image are identified based on comparison with the first image, such that the identified gaps within the second image are complemented to result in a complemented second image.

Abstract: The present disclosure discloses method and an autonomous navigation system for guiding an autonomous vehicle in forward path in real-time. The method comprises instructing the vehicle to terminate autonomous steering in a forward path, on identifying an angular difference, between a current orientation of the vehicle and orientation of a generated path, to be greater than a predefined threshold value and performing estimation of a frontal area for the vehicle based on a current speed, an orientation, and a width of the vehicle, calculation of a forward turning angle based on the angular difference and a length of the frontal area and guiding vehicle to manoeuvre steer at the forward turning angle within the frontal area, for every predefined time interval, until the angular difference is less than the predefined threshold value. Thus, the present disclosure provides an efficient method for guiding autonomous vehicle in forward path in real-time.

Abstract: An automatic calibration system for a traffic system includes at least one position determining device, at least one image capturing device, a matching and tagging module, an image analysis module, and a calibration module. The position determining device detects a vehicle in violation of traffic rules and activates the image capturing device to capture images of the vehicle. The vehicle is matched and tagged in the images according to vehicle-related information detected by the position determining device by the matching and tagging module. The image analysis module analyses a plurality of images selected from the images to obtain an analysis result. The analysis result is compared with the vehicle-related information by a processor. If the analysis result is different than the vehicle-related information, the position determining device is calibrated by the calibration module. If the analysis result is the same as the vehicle-related information, a calibration is not performed.

Abstract: An automotive vehicle includes at least one actuator configured to control vehicle steering, shifting, acceleration, or braking, at least one sensor configured to provide signals indicative of road geometry in the vicinity of the vehicle, and a controller in communication with the sensor and the actuator. The controller is configured to selectively control the actuator in an autonomous driving mode based on signals from the sensor. The controller is configured to automatically determine a first time parameter based on a distance to a merge location between a current driving lane of the vehicle and a target lane adjacent the current driving lane in response to signals from the sensor, to automatically determine a second time parameter based on a calculated merge completion time, and to automatically discontinue autonomous control of the actuator based on a difference between the first time parameter and the second time parameter.