Abstract: A vehicle includes a controller, programmed to responsive to identifying a first user via a mobile device, load a first non-person entity associated with the first user from the mobile device to configure vehicle settings, the first non-person entity including a driver setting, a first entertainment setting and a second entertainment setting; and responsive to identifying a second user entering the vehicle, switch from the first entertainment setting to a second entertainment setting.

Abstract: A system for navigating a host vehicle includes at least one electronic horizon processor to access a map representative of at least a road segment on which the host vehicle travels or is expected to travel, wherein the map includes one or more splines representative of road features associated with the road segment, localize the host vehicle relative to a drivable path for the host vehicle represented among the one or more splines, determine a set of points associated with the one or more splines based on the localization of the host vehicle relative to the drivable path for the host vehicle, and generate a navigation information packet including information associated with the one or more splines and the determined set of points relative to the one or more splines.

Abstract: An Anti-lock Braking System and control method are disclosed. The control method is performed after a control module intervenes a vehicle's braking system and comprises: receiving a wheel speed signal of a wheel and a vehicle acceleration signal; computing a tire-slip feedback value according to the wheel speed signal of the wheels and the vehicle acceleration signal; generating a feedback control voltage according to a tire-slip difference between a tire-slip target value and the tire-slip feedback value; generating a tire-slip compensation value by performing a differential compensation to the tire-slip feedback value; obtaining a feedforward voltage according to the tire-slip compensation value via a look-up table approach; generating a braking control voltage by adding the feedback control voltage to the feedforward voltage; and outputting the braking control voltage to a proportioning-valve brake, such that the proportioning-valve brake adjusts a braking pressure according to the braking control voltage.

Abstract: A travel control system for a vehicle includes a vehicle speed calculator, a mode continuation determiner, and a mode continuing unit. The vehicle speed calculator evaluates a level of worsening of a traveling environment and calculates a first vehicle speed on the basis of the level of the worsening of the traveling environment. The mode continuation determiner determines whether it is possible to continue with driving assist control in the second driving assist mode by comparing a second vehicle speed in the second driving assist mode with the first vehicle speed. When it is not possible to continue with the driving assist control in the second driving assist mode, the mode continuing unit lowers the second vehicle speed in the second driving assist mode to the first vehicle speed to allow the driving assist control in the second driving assist mode to continue.

Abstract: Systems and methods for predictively detecting vehicle failure based on diagnostic trouble codes are provided. In one example, a method is provided, comprising determining a probability of failure of a vehicle based on one or more diagnostic trouble codes (DTCs); and indicating to an operator of the vehicle that failure is likely in response to the probability exceeding a threshold.

Abstract: Aspects relate to methods and systems for parking a vehicle. An exemplary system includes a first plurality of sensors located on the vehicle and configured to detect first sensor data as a function of objects over a first height range, a second plurality of sensors located on the vehicle and configured to detect second sensor data as a function of objects over a second height range at least partially greater than the first height range, and a computing device configured to receive the first sensor data from the first plurality of sensors and the second sensor data from the second plurality of sensors, and determine the space proximal the vehicle is suitable for parking the vehicle as a function of the first sensor data, the second sensor data, and a height of the vehicle.

Abstract: Aspects of the disclosure relate to determining perceptive range of a vehicle in real time. For instance, a static object defined in pre-stored map information may be identified. Sensor data generated by a sensor of the vehicle may be received. The sensor data may be processed to determine when the static object is first detected in an environment of the vehicle. A distance between the object and a location of the vehicle when the static object was first detected may be determined. This distance may correspond to a perceptive range of the vehicle with respect to the sensor. The vehicle may be controlled in an autonomous driving mode based on the distance.

Abstract: Provided is an automated valet parking system giving an instruction to a target vehicle by specifying a node section at which the target vehicle is located, setting a node status including information on whether passing of a node is allowed, specifying a target node that is the node including a next-passing node among unpassed nodes of the target vehicle and having a predetermined number smaller than a total number of the unpassed nodes, the next-passing node being the node through which the target vehicle passes next on the target route, and transmitting node information associated with the target node to the target vehicle. When the node status at the next-passing node is re-set from a node impassable status to a node passable status, the automated valet parking system transmits the node information of the target node ahead of the next-passing node among the unpassed nodes to the target vehicle.

Abstract: A route setting device includes: a route candidate generation unit that generates multiple route candidates from a current position to a destination; an index calculation unit that calculates, for each of the multiple route candidates, a change index that indicates a probability that an automatic driving system performs a driving change request when a vehicle travels along each of the multiple route candidates by using the automatic driving system; a display unit that associates the multiple candidates with the change index calculated for each of the multiple route candidates, and display the multiple associated route candidates and the associated change index; an input unit that receives a selection among the multiple route candidates by an occupant of the vehicle; and a route setting unit that sets a route among the multiple route candidates based on the selection received by the input unit.

Abstract: A small-object perception system, for use in a vehicle, includes a stereo vision system that captures stereo images and outputs information identifying an object having a dimension in a range of ˜20 cm to about ˜100 cm in a perception range of ˜3 meters to ˜150 meters from the vehicle, and a system controller configured to receive output signals from the stereo vision system and to provide control signals to control a path of movement of the vehicle. The stereo vision system includes cameras separated by a baseline of ˜1 meter to ˜4 meters. The stereo vision system includes a stereo matching module configured to perform stereo matching on left and right initial images and to output a final disparity map based on a plurality of preliminary disparity maps generated from the left and right initial images, with the preliminary disparity maps having different resolutions from each other.

Abstract: Detecting out-of-model scenarios for an autonomous vehicle including: determining, based on first sensor data from one or more sensors, an environmental state relative to the autonomous vehicle, wherein operational commands for the autonomous vehicle are based on a selected machine learning model, wherein the selected machine learning model comprises a first machine learning model; comparing the environmental state to a predicted environmental state relative to the autonomous vehicle; and determining, based on a differential between the environmental state and the predicted environmental state, whether to select a second machine learning model as the selected machine learning model.

Abstract: A system for controlling platooning by a following vehicle includes a sensor located in or on the following vehicle configured to detect data corresponding to a shape of a leading vehicle. The system further includes an electronic control unit (ECU) located in or on the following vehicle, coupled to the sensor, and configured to determine an optimal distance from the following vehicle to the leading vehicle based on the shape of the leading vehicle, the optimal distance corresponding to a distance at which drag applied to the following vehicle is reduced based on a pressure wake from the leading vehicle.

Abstract: A lane change control unit restricts an automatic lane change in the case of predicting that a user's own vehicle after having made the automatic lane change will be adjacent to another vehicle that exists inside of a third lane or on a third lane dividing line, and executes the automatic lane change without restriction in the case of predicting that the user's own vehicle after having made the automatic lane change will be adjacent to another vehicle that exists inside a fourth lane or inside of a road shoulder.

Abstract: Embodiments of the disclosure provide a transfusion guiding robot and a guiding method for guiding a movement of a transfused person. The transfusion guiding robot comprises a controller, a moving portion and a fixing portion. The controller is configured to receive and process instruction information, and control the transfusion guiding robot according to the instruction information; the moving portion is configured to move according to a command from the controller; and the fixing portion is configured to fix a container, a height of the fixing portion being adjustable.

Abstract: Embodiments of the present disclosure are directed to lane marker prediction for occluded lane markers. Image data from one or more sensors of a vehicle is received by a processor of a control system. The image data includes a roadway from a route being navigated by the vehicle and lane marker information. If there are not enough lane markers captured in the lane marker information to produce a threshold look-ahead horizon of the roadway ahead of the vehicle, a longest lane marker ahead of the vehicle from the lane marker information is selected. A curvature tangent to the longest lane marker is computed and predictive lane markers are generated based on the curvature tangent. The vehicle is steered based on the predictive lane markers ahead of the vehicle generated from the curvature tangent.

Abstract: The described systems and methods determine a driver's fitness to safely operate a moving vehicle based at least in part upon observed impairment patterns. A smart ring, wearable on a user's finger, continuously monitors impairment levels. This impairment data, representing impairment patterns, can be utilized, in combination with driving data, to train a machine learning model, which will predict the user's level of risk exposure based at least in part upon observed impairment patterns. The user can be warned of this risk to prevent them from driving or to encourage them to delay driving. In some instances, the disclosed smart ring system may interact with the user's vehicle to prevent it from starting while the user is in a state of impairment induced by substance intoxication.

Abstract: A device for virtualizing a driving environment surrounding a first node, which includes: a data acquisition device, configured to acquire position data of the first node, position data and sensing data of at least one second node, where the at least one second node and the first node are in a first communication network; and a scene construction device, configured to construct a scene virtualizing the driving environment surrounding the first node based on the position data of the fist node and the at least one second node, and on the sensing data of the at least one second node. Accordingly, by utilizing position data and sensor data of a node, a scene for virtualizing a driving environment can be constructed in real time for a driver, which improves driving safety.

Abstract: A driving support system includes: an acquisition portion configured to acquire visual-recognition position information on a position where a driver of a vehicle visually recognizes a traffic light; an image acquisition portion configured to acquire a forward image ahead of the vehicle; a traffic-light recognition portion configured to recognize a traffic light included in a forward image; and a notification portion configured to notify the driver of warning when the traffic light is not recognized from the forward image, in a case where the vehicle is present at a position based on the visual-recognition position information.

Abstract: A system and method for providing adaptive trust calibration in driving automation that include receiving image data of a vehicle and vehicle automation data associated with automated of driving of the vehicle. The system and method also include analyzing the image data and vehicle automation data and determining an eye gaze direction of a driver of the vehicle and a driver reliance upon automation of the vehicle and processing a Markov decision process model based on the eye gaze direction and the driver reliance to model effects of human trust and workload on observable variables to determine a control policy to provide an optimal level of automation transparency. The system and method further include controlling autonomous transparency of at least one driving function of the vehicle based on the control policy.

Abstract: A road abnormality detection apparatus includes: a memory; and a processor having hardware, wherein the processor is configured to: receive, from a traveling vehicle, a road image indicating an image of a surface of a road or a periphery of the road and image capturing position information indicating a position where the road image is captured; recognize a road facility included in the road image and a position of the road facility based on the road image and the image capturing position information; determine whether or not abnormality exists in the road facility by comparing the road facility included in the road image and correctness information that is prepared in advance; and accumulate, in the memory, facility position information indicating the position of the road facility that the abnormality exists in when it is determined that the abnormality exists in the road facility.