Abstract: A regenerative braking system and method include: a regenerative braking determination unit configured to determine whether or not a vehicle satisfies an entry condition for regenerative braking based on information collected by the vehicle; a calculation unit configured to calculate a hydraulic braking torque according to a pressure of a master cylinder and a target amount of a regenerative braking torque varied according to the pressure of the master cylinder, if the vehicle satisfies the entry condition; and a controller configured to perform braking of the vehicle based on the target amount of the regenerative braking torque and the hydraulic braking torque.

Abstract: A behavior control device and a behavior control method for an autonomous vehicle are provided. The behavior control device includes a learning device configured to perform deep learning of a behavior pattern of a vehicle according to a driving environment and a controller configured to control a behavior of the autonomous vehicle based on a result of the learning of the learning device.

Abstract: An apparatus and method for controlling an autonomous vehicle are provided. The apparatus includes a user input unit that receives identification information of a driver within the vehicle during autonomous driving and an information collection unit that acquires a global route of the vehicle and surrounding environment information. A controller determines a learning section on the global route based on the surrounding environment information and outputs a driving pattern of the driver by performing repetitive learning based on operation information of the driver in the learning section. Autonomous driving of the vehicle is then executed based on the output driving pattern of the driver.

Abstract: A device for controlling travel of a vehicle includes: a sensor that acquires information on a surrounding region of the vehicle, and a controller that generates a speed profile based on the information on the surrounding region of the vehicle, calculates an average acceleration in the speed profile based on a current vehicle speed and a vehicle speed at a predetermined time point, and calculates a required acceleration at a time point at which a difference between the speed profile and the average acceleration is greatest, and performs travel control based on at least one of the average acceleration or the required acceleration. The device allows a longitudinal control to be performed based on the speed profile generated by the vehicle, thereby improving an accuracy of autonomous driving.

Abstract: An image sensor package includes: an image sensor chip that includes first and second faces that are opposite to each other and includes side walls that connect the first and second faces; a mold layer disposed on the side walls of the image sensor chip and that includes third and fourth faces that are opposite to each other; a transparent substrate disposed on the second face of the image sensor chip and spaced apart from the image sensor chip in a first direction, the transparent substrate including a first portion that overlaps the image sensor chip in the first direction and a second portion that does not overlap the image sensor chip in the first direction; and an adhesive layer disposed between the mold layer and the second portion of the transparent substrate, wherein the side walls of the image sensor chip overlap the mold layer in a second direction intersecting the first direction and the fourth face of the mold layer does not overlap the image sensor chip in the first direction.

Abstract: A vehicle and an autonomous driving control method therefore may include detecting traffic environment information around a host vehicle, determining traffic flow in a host vehicle lane and a neighboring lane adjacent to the host vehicle lane according to the traffic environment information, and generating a driving strategy based on the traffic flow to control driving of the host vehicle according to the generated driving strategy.

Abstract: A method for controlling autonomous driving for an autonomous driving vehicle, includes collecting sensing information on autonomous driving in an autonomous driving mode, calculating an initial longitudinal control value based on the sensing information on the autonomous driving, correcting the initial longitudinal control value based on the sensing information, and performing a longitudinal driving control by transmitting the corrected longitudinal control value to a lower controller.

Abstract: A vehicle running control method includes: acquiring, at least one of a first traveling state information of an autonomous vehicle and a second traveling state information of adjacent vehicles traveling in a traveling lane or in a lane adjacent to the traveling lane through a sensor unit; determining, by a determination processor, a candidate cut-in vehicle that travels behind the autonomous vehicle among the adjacent vehicles based on the first and second traveling state information; searching, by a controller, for a potential cut-in space, which is determined based on the relative velocity of a preceding vehicle that is the closest to the autonomous vehicle among the adjacent vehicles and the distance between the preceding vehicle and the autonomous vehicle; and performing, by the controller, deceleration, acceleration, or velocity maintenance of the autonomous vehicle depending on whether the potential cut-in space is present.

Abstract: An apparatus for switching driving control authority of an autonomous vehicle and a method thereof are provided to deeply learn a normal driving pattern of the autonomous vehicle corresponding to a driving situation, detect a matching degree of the driving pattern of a driver based on the deep learning result, and determine whether to retrieve the driving control authority of the driver corresponding to the detected matching degree. Accordingly, the driving control authority of the driver is retrieved to prevent an accident in advance even if there is no request to activate an autonomous driving mode of the driver.

Abstract: A method of generating a U-turn path of an autonomous vehicle is provided. The method includes generating a plurality of virtual path points on a high definition map based on driving environment information and generating a reference path corresponding to the U-turn situation When a preceding vehicle is present ahead of the vehicle, a moving trajectory of the preceding vehicle is followed and a candidate path is generated. The reference path is compared with the candidate path to generate an optimum U-turn path.

Abstract: A method for controlling braking of an autonomous vehicle includes: recognizing, by a driving situation recognizer, a vehicle stop situation based on environment information around the vehicle; generating, by a deceleration profile generator, a nth-order polynomial-based deceleration profile having a plurality of inflection points (n being a natural number equal to or greater than three) when the vehicle stop situation is recognized; correcting, by a corrector, the nth-order polynomial-based deceleration profile by setting at least one of a response time of a decelerator, a mass of the vehicle during driving or a deceleration performance of a brake to a control variable; and executing, by a controller, braking of the vehicle based on the corrected nth-order polynomial-based deceleration profile.

Abstract: An automated valet parking system, an automated valet parking method, and an automated valet parking infrastructure, and a vehicle having an automated valet parking feature are disclosed. In particular, the vehicle can autonomously move to and park in a designated parking spot by communicating with the infrastructure. In addition, the vehicle can autonomously move to a pickup area from a parking spot by communicating with the infrastructure.

Abstract: A regenerative braking system and method include: a regenerative braking determination unit configured to determine whether or not a vehicle satisfies an entry condition for regenerative braking based on information collected by the vehicle; a calculation unit configured to calculate a hydraulic braking torque according to a pressure of a master cylinder and a target amount of a regenerative braking torque varied according to the pressure of the master cylinder, if the vehicle satisfies the entry condition; and a controller configured to perform braking of the vehicle based on the target amount of the regenerative braking torque and the hydraulic braking torque.

Abstract: A behavior control device and a behavior control method for an autonomous vehicle are provided. The behavior control device includes a learning device configured to perform deep learning of a behavior pattern of a vehicle according to a driving environment and a controller configured to control a behavior of the autonomous vehicle based on a result of the learning of the learning device.

Abstract: A system and method for supporting automated valet parking are provided. The vehicle may autonomously travel to an empty parking space and perform automated parking based on communication with the infrastructure. Further, the vehicle may autonomously travel to a parking space to a pickup area based on the communication with the infrastructure.

Abstract: A lane change control device and a method for an autonomous vehicle improve safety and accuracy in changing lanes on a road. In particular, the lane change control device includes: a learning device that learns an environment in which the autonomous vehicle is able to change lanes on a road; and a controller that controls a lane change of the autonomous vehicle, based on a learned result of the learning device.

Abstract: An apparatus and method for controlling an autonomous vehicle are provided. The apparatus includes a user input unit that receives identification information of a driver within the vehicle during autonomous driving and an information collection unit that acquires a global route of the vehicle and surrounding environment information. A controller determines a learning section on the global route based on the surrounding environment information and outputs a driving pattern of the driver by performing repetitive learning based on operation information of the driver in the learning section. Autonomous driving of the vehicle is then executed based on the output driving pattern of the driver.

Abstract: A device and a method for compensating a route of an autonomous vehicle are provided in which a normal route pattern for each section and abnormal route patterns for each section are learned based on a deep neural network (DNN). A compensated route pattern is obtained by changing a weighted value of each of a plurality of sensors for the abnormal route patterns for each section is learned, and the route of the autonomous vehicle is compensated based on the learning result to detect which sensor has an error when the route of the autonomous vehicle is abnormal.

Abstract: The present disclosure provides a system and a method for correcting a friction coefficient of a brake pad for a vehicle, which can estimate a brake factor including a friction coefficient of a brake pad, and ultimately correct the brake factor through the calculation and the update of a brake factor offset based on the estimated brake factor, thereby enhancing the braking linearity of an electric brake system.

Abstract: A method for fabricating a semiconductor device is provided. The method includes the actions of: providing on a substrate comprising an etch stop layer formed on the substrate; forming a stacked structure on the etch stop layer, the stacked structure including a lower pattern and at least one upper pattern, wherein each of the lower pattern and the at least one upper pattern includes a sacrificial layer and a support layer formed on the sacrificial layer; forming a hole penetrating the stacked structure and the etch stop layer; forming a lower conductive pattern in the hole; forming an opening penetrating the at least one upper pattern and the support layer of the lower pattern by a first etch process; and removing the sacrificial layers of the lower pattern and the at least one upper pattern by a second etch process.