Abstract: This document describes vehicle localization using map and vision data. For example, this document describes a localization system that obtains a map centerline point and a vision centerline point of a lane of a roadway. The localization system also obtains the position of the vehicle. The localization system can then compare the map centerline point and the vision centerline point to generate a lateral and a longitudinal correction relative to the vehicle's position. The lateral and longitudinal corrections are used to generate a corrected position. In this way, the described localization system can provide accurate vehicle localization that addresses potential drift caused by lapsed or inaccurate positioning data and allows for the operation of assisted-driving and autonomous-driving systems at higher speeds and on roadways with tighter curves.

Abstract: Provided is a risk estimation device capable of appropriately estimating a risk in a traveling direction of an own vehicle even under the condition that a relationship between a traffic participant and a road condition is inappropriate. The risk estimation device recognizes a traffic participant, a road condition, and a condition of the traffic participant in the traveling direction of the own vehicle based on a surrounding condition data, determines, by using a reference relationship model, whether the relationship between the traffic participant and the road condition is appropriate, estimates, by using a risk model, a traveling risk in a case where the relationship between the traffic participant and the road condition is determined to be appropriate, and estimates the traveling risk according to the condition of the traffic participant in a case where the relationship between the traffic participant and the road condition is determined to be inappropriate.

Abstract: An autonomous controller, a system including the same, and a method thereof include a processor that detects a target object attempting to cut in at a low speed during autonomous driving and that performs response control. The controller, system, and method include a storage storing data and an algorithm for detecting the target object and performing the response control. The processor calculates a final distance value on the basis of a point tracking a distance between a host vehicle and the target object and compares the final distance value with a predetermined threshold to determine whether the target object cuts in.

Abstract: An apparatus may receive first data, in a first data format, from one or more unmanned aircraft system service suppliers comprising first positions of one or more unmanned aircraft systems, receive second data, in a second data format, from one or more communications systems comprising second positions of one or more manned aircraft, transmit third data, in a third data format, comprising the first positions of the one or more unmanned aircraft systems and the second positions of the one or more manned aircraft, receive a first control signal comprising a control command associated with one or more of the unmanned aircraft systems or one or more of the manned aircraft, and transmit a second control signal comprising the control command to one or more of the unmanned aircraft system service suppliers or to one or more of the communications systems.

Abstract: A vehicular collision avoidance system includes a sensor disposed at a vehicle for sensing exterior and forwardly of the vehicle. A processor processes sensor data captured by the sensor to determine the presence of a pedestrian ahead of the vehicle and outside a path of travel of the vehicle. The processor determines a projected path of travel of the pedestrian based on movement of the pedestrian. The processor determines where the forward path of travel of the vehicle intersects the projected path of travel of the pedestrian. The system, responsive at least in part to prediction that the pedestrian will be in the forward path of travel of the vehicle when the vehicle time to intersection elapses, adjusts the speed of the vehicle based at least in part on attentiveness of a driver of the vehicle and a driving condition of the vehicle.

Abstract: The following relates generally to determining effectiveness of an update to a vehicle feature. In some embodiments, information indicating an update to a vehicle feature, and accident record information may be received. A first dataset from before the update was implemented in the vehicle, and a second dataset from after the update was implemented in the vehicle may then be constructed. An effectiveness score may then be calculated based upon the first and second datasets.

Abstract: The present invention obtains a controller and a control method capable of appropriately executing automatic emergency deceleration operation of a straddle-type vehicle. In the controller according to the present invention, when the automatic emergency deceleration operation of the straddle-type vehicle is executed, at a braking start time point at which a braking force starts being generated on at least one of wheels, braking force distribution between the front and rear wheels is brought into an initial state where the braking force is generated on the front wheel. In the control method according to the present invention, when the automatic emergency deceleration operation of the straddle-type vehicle is executed, at the braking start time point at which the braking force starts being generated on at least one of the wheels, the braking force distribution between the front and rear wheels is brought into the initial state where the braking force is generated on the front wheel.

Abstract: Provided are a video data acquisition unit that acquires video data; an event detection unit that detects an event; a recording function control unit that operates a parking recording function for storing video data, based on detection of the event, while the vehicle is parked; a surrounding information acquisition unit that acquires surrounding information; and a determination unit that determines whether the vehicle is in an environment where there is a high risk of an object colliding with the vehicle, based on the surrounding information.

Abstract: A vehicle management system includes a vehicle use situation recognition unit recognizing that a user of a vehicle visits a predetermined area or a predetermined facility by the vehicle based on a position of the vehicle recognized by a vehicle position recognition unit and a vehicle cleaning handling unit transmitting vehicle cleaning information about cleaning of the vehicle to at least either one of a user terminal and a maintenance management server in a case where the vehicle use situation recognition unit recognizes that the user visits the predetermined area or the predetermined facility by the vehicle, the user terminal being used by the user, the maintenance management server managing maintenance of the vehicle.

Abstract: A driving assist system assists driving of a vehicle. A deceleration target includes at least one of a preceding vehicle, a mandatory stop line, a mandatory stop sign, a traffic signal, and a stop line before the traffic signal that exist ahead of the vehicle. A risk factor includes at least one of a pedestrian, a bicycle, a motorcycle, an oncoming vehicle, and a parked vehicle that exist ahead of the vehicle. The driving assist system executes: deceleration assist control that automatically decelerates the vehicle before the deceleration target; and risk avoidance control that automatically performs at least one of steering and deceleration of the vehicle so as to avoid the risk factor. When both the deceleration assist control and the risk avoidance control operate concurrently, the driving assist system notifies a driver of the vehicle of not the deceleration target but the risk factor.

Abstract: In some embodiments, methods and systems are provided that provide for facilitating delivery, via autonomous ground vehicles, of products ordered by customers of a retailer to customer-specified restricted areas accessible by an entryway openable via an access code.

Abstract: The present disclosure may relate to a method capable of monitoring a tire pressure, and may include estimating a tire necessary air pressure based on a location and an external temperature of a vehicle, determining whether a change in a current applied to an in-wheel motor is included in a preset range, when the vehicle is driving at a uniform speed during a preset time, calculating weights according to a plurality of conditions, respectively, and calculating a tire pressure based on the weights.

Abstract: The present disclosure relates to a method for determining a user-specific configuration of a braking device of a motor vehicle, the method including detecting measurement data using a detector and providing a data record to an evaluation circuitry. Based on the measurement data and data record, a user-specific braking profile is determined. Furthermore, a selected braking profile that has the greatest degree of conformity with the user-specific braking profile is identified from a plurality of braking profiles. A corresponding configuration associated with the selected braking profile is identified as the suitable user-specific configuration. A changeover operation is triggered in order to provide the user-specific configuration in the motor vehicle.

Abstract: An unmanned vehicle including a vehicle body, propulsion system, maneuvering system, vehicle control system, rack, sensor, and a power supply. The vehicle control may be used to control the unmanned vehicle in combination with the propulsion and the maneuvering system. The rack may include a retractable mount that may move between a down position and an up position. The sensor system may include a plurality of transient object detection sensors. The plurality of transient object detection sensors may include a sensor adapted to detect an item of interest and may provide an item of interest signal to the vehicle control system. The vehicle control system may identify an item of interest classification and may provide a classification signal. The classification signal may be determined by the item of interest classification and may be utilized to avoid detection of the unmanned vehicle by the item of interest.

Abstract: Methods and systems are disclosed herein for encouraging particular behavior while occupying vehicles. For example, by granting and restricting access to media and other user comfort devices based on whether or not a user is conforming to a predetermined rule set, the media guidance application may encourage a user to adhere to the rule set.

Abstract: The present teaching relates to method and system for sensor protection. A sensor protection system includes an assembly having a first structure embedded in a second structure, wherein a sensor is firmly placed in the first structure for sensing information through the assembly and protected from negative impact of outside environment, and one or more devices mounted on the second structure for providing means to clean a slanted surface of the second structure through which the sensor senses the surrounding information, wherein the one or more devices can be individually or jointly activated as needed to clean the slanted surface in order to prevent degradation of information sensed by the sensor through the assembly.

Abstract: A sun visor actuation system including an attachment apparatus configured to attach to an automobile structure, an arm member rotatably attached to the attachment apparatus, a body member attached to the arm member, and an actuation system. The actuation system is operable to at least one of rotate the body member and prevent the rotation of the body member responsive to an indication of an imminent collision.

Abstract: A method of controlling an actuator system including a plurality of k actuators. Each of the actuators-receives a control input ui, wherein index i denotes a particular actuator, which control input ui is determined depending on a weight matrix W including a weighting factor wi for each actuator and depending on at least a physical maximum control limit uimax for each of the actuators. The weighting factors wi and/or physical maximum control limit uimax are actively changed during operation if a first comparison of the control input ui or a function f(ui) thereof with a set first threshold value yields that the control input ui or function f(ui) thereof exceeds the set first threshold value. The first comparison is repeated during operation, and a new control input ui is determined from the adjusted weighting factor wi and/or the adjusted physical maximum control limit uimax and applied to the actuators.

Abstract: A vehicle acquires position information of the obstacle, identifies a collision point that may collide with the obstacle based on the acquired position information of the obstacle, controls one of steering and braking based on the position information of the identified collision point, and when controlling the steering, acquires a collision avoidance margin distance value corresponding to the position information of the identified collision point, predicts the collision position based on the position information of the obstacle and the information detected by the velocity detector, acquires a distance value between the predicted collision position and the current position, acquires a lateral movement distance value based on the acquired distance value and a preset turning radius of the vehicle, acquires a steering angle based on the acquired lateral movement distance value and the acquired collision avoidance margin distance value and controls steering based on the acquired steering angle.

Abstract: According to the present invention there is provided a drone (1) comprising one or more propellers (2) and one or more actuators (3) for actuating said one or more propellers (2) to generating a thrust force which enables the drone (1) to fly; a controller (4) which is configured such that it can control the flight of the drone (1), wherein the controller (4) comprises a memory (6) having stored therein a plurality of predefined sets of positions which define a virtual rail which can be used to guide the flight of the drone (1) so that the drone can avoid collision with an subject; and wherein the controller further comprises a mathematical model (7) of the drone; wherein the controller (4) is configured to control the flight of the drone by performing at least the following steps, (a) approximating lag error based on the position of the drone (1) measured by a sensor (5) and the virtual rail, wherein the lag error is the distance between a point along the virtual rail which is closest to the drone (1) and an