Abstract: The present disclosure relates to a host vehicle and control method thereof, according to one aspect of the present disclosure, the purpose is to enable quick and accurate recognition of cut-in vehicles that change lanes from adjacent lanes to travel lanes. Disclosed are a control method of a host vehicle, the method including: obtaining a front image by photographing the front of the host vehicle; identifying left and right lines of a travel lane in which the host vehicle is traveling from the front image; determining that a vehicle cutting-in from an adjacent lane to the travel lane exists when the lengths of the left line and the right line of the travel lane are different from each other in the front image.

Abstract: A smart license plate vault securely holds small objects, such as a vehicle key, while resembling a license plate mounting platform. The smart license plate vault may be operated by authorized third parties via a keypad located on the smart license plate vault to accept access codes and other information. The smart license plate vault may include a storage compartment with a removable cover for providing access to the storage compartment and an electronic locking mechanism for locking and unlocking the vault, a vault cover plate sensor for detecting when the vault cover plate has been placed into a closed position, a storage compartment sensor for recording information regarding an interior of the storage compartment when the vault cover plate sensor detects that the vault cover plate has been placed into the closed position, and a transmitter for wirelessly transmitting the recorded information to a remote location.

Abstract: An apparatus and method for controlling a vehicle speed based on information about forward vehicles that travel in the same lane may be acquired using Vehicle to Everything (V2X) communications in a cooperative adaptive cruise control (CACC) system. The CACC system includes a communication unit receiving vehicle information from neighboring vehicles using V2V communications; an information collection unit collecting vehicle information of the neighboring vehicles and the subject vehicle using sensors; and a control unit determining a forward vehicle and a far-forward vehicle using the sensors, selecting first and second target vehicles for being followed by the subject vehicle based on the vehicle information of the forward vehicle and the far-forward vehicle and the vehicle information of the neighboring vehicles, and controlling the driving speed of the subject vehicle based on speed information of the first and second target vehicles.

Abstract: A mobile robot, capable of communicating with neighboring devices in a 5G communication environment and capable of efficient cleaning via machine learning based on such communication, comprises a main body configured to move in the movement space, a driving unit mounted on the main body to move the main body, a receiving unit configured to receive moving history information of a user robot that has been moved by a user in the movement space, a memory in which a computer-readable program and map information of the movement space are stored, and a control unit configured to communicate with the receiving unit, the memory, and the driving unit to control the main body, wherein the control unit establishes a moving area of the mobile robot based on the moving history information of the user robot received by the receiving unit.

Abstract: Systems and methods for basis path generation are provided. In particular, a computing system can obtain a target nominal path. The computing system can determine a current pose for an autonomous vehicle. The computing system can determine, based at least in part on the current pose of the autonomous vehicle and the target nominal path, a lane change region. The computing system can determine one or more merge points on the target nominal path. The computing system can, for each respective merge point in the one or more merge points, generate a candidate basis path from the current pose of the autonomous vehicle to the respective merge point. The computing system can generate a suitability classification for each candidate basis path. The computing system can select one or more candidate basis paths based on the suitability classification for each respective candidate basis path in the plurality of candidate basis paths.

Abstract: Techniques for determining a vehicle action and controlling a vehicle to perform the vehicle action for navigating the vehicle in an environment can include determining a vehicle action, such as a lane change action, for a vehicle to perform in an environment. The vehicle can detect, based at least in part on sensor data, an object associated with a target lane associated with the lane change action sensor data. In some instances, the vehicle may determine attribute data associated with the object and input the attribute data to a machine-learned model that can output a yield score. Based on such a yield score, the vehicle may determine whether it is safe to perform the lane change action.

Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with object perception and prediction of object motion are provided. For example, a plurality of temporal instance representations can be generated. Each temporal instance representation can be associated with differences in the appearance and motion of objects over past time intervals. Past paths and candidate paths of a set of objects can be determined based on the temporal instance representations and current detections of objects. Predicted paths of the set of objects using a machine-learned model trained that uses the past paths and candidate paths to determine the predicted paths. Past path data that includes information associated with the predicted paths can be generated for each object of the set of objects respectively.

Abstract: An apparatus for controlling to enable an autonomous system in a vehicle is provided. The apparatus includes a sensor, an input device configured to receive an input from a driver of the vehicle, an output device configured to output a notification in the vehicle, and a control circuit configured to be electrically connected with the sensor, the input device, and the output device. The control circuit is configured to activate an autonomous control in response to an input of the driver to the input device, detect a critical situation of the vehicle using the sensor, output a notification to transfer a control authority using the output device in response to the detected critical situation, and automatically reactivate the autonomous control when the critical situation is solved after temporarily releasing the autonomous control, when the critical situation corresponds to a critical situation of a specified type.

Abstract: A vehicle control method as executed includes acquiring surrounding information of the subject vehicle by a sensor includes, specifying an entry position located on a second lane adjacent to a first lane where the subject vehicle travels in accordance with the surrounding information of the subject vehicle, specifying a front vehicle located front the entry position and a rear vehicle located rear the entry position, determining the travel state of each of the front vehicle and the rear vehicle, determining whether there is a space for the subject vehicle to enter at the entry position, predicting whether the front vehicle starts to travel when the front vehicle and the rear vehicle are determined to be stopped and no space is determined at the entry position, and starting to move the subject vehicle to the entry position when the front vehicle is predicted to start traveling.

Abstract: A method for localizing a target object may include applying, to a first image captured by an apparatus, a first machine learning model trained to determine whether the target object is visible in the first image depicting a first region of a search area. In response to the target object being absent from the first image, a second machine learning model may be applied to identify, based on the target object as being visible and/or nonvisible in one or more portions of the first image, a second region of the search area corresponding to a sub-region within the first region of the search area having a highest probability of including the target object. A command may be sent to the apparatus to navigate the apparatus to the second region of the search area in order to capture a second image of the second region of the search area.

Abstract: In response to a request to pull over an ADV at a destination point at a side of a lane, a path including a first segment, a second segment and a transition point is planned. The transition point is determined based on at least one of a distance to the destination point or a predetermined distance to a boundary of the side of the lane. The first segment from a start point to the transition point is generated by using a quadratic programming (QP) operation. The second segment from the transition point to the destination is generated based on a shape of the boundary. The ADV is controlled to pull over to the destination point according to the planned path.

Abstract: An optical assembly for a LiDAR system is described. The optical assembly includes receiver optics and transmitter optics, designed to include partially coaxial beam paths; a line light source having a line orientation, which is configured, in particular within the range of a field of view of the underlying LiDAR system; and a deflection unit in a transition region from a common coaxial region to a separate biaxial region of the beam paths of the receiver optics and of the transmitter optics for biaxially splitting off a detector-side portion of the beam path of the receiver optics. The deflection unit has a hole mirror having an elongated hole that has a greater extent in a direction of longitudinal extent and a lesser extent in a direction of transverse extent. The direction of longitudinal extent of the elongated hole is oriented orthogonally to the line orientation of the line light source.

Abstract: Embodiments of the present disclosure relate to generating velocity profiles for an autonomous vehicle (101). An ECU (107) of the autonomous vehicle (101) receives road information from one or more sensors (106) associated with the autonomous vehicle (101). One or more parameters related to smooth movement of the autonomous vehicle on the road is determined from the road information. Further, a first velocity profile is produced using an AI model and a second velocity profile is produced using a hierarchical model, based on the one or more parameters. Furthermore, one of the first and the second velocity profile is selected by comparing the first and the second velocity profiles. The selected velocity profile has a lower value of velocity value compared to the other velocity profile. The selected velocity profile is provided to the autonomous vehicle (101) for navigating on the road (102) smoothly.

Abstract: A method includes obtaining multiple data items from multiple heterogeneous data sources, where the multiple data items relate to an unmanned aerial system (UAS) flying in an area. The method also includes processing the multiple data items using a machine learning algorithm to determine a threat level of the UAS to one or more targets in the area. The method further includes outputting the threat level of the UAS for review by a user.

Abstract: A learning apparatus includes: a learning part that performs, based on charging/discharging data indicating at least one of charging and discharging of a secondary battery that supplies electric power for traveling of a vehicle, a capacity learning of the secondary battery and that performs the capacity learning in response to a change amount of a charging rate that is indicated by the charging/discharging data exceeding a threshold value; and a threshold determination part that determines the threshold value based on history information of the learning part performing the capacity learning in a predetermined period.

Abstract: A plurality of frequency orthogonal signals are transmitted into a person. At least one of the plurality of frequency orthogonal signals is received at a receiving antenna or conductor. The received signal is measured. Characteristics of the received signal are used to establish a result related to that person.

Abstract: A non-transitory computer readable storage medium has instructions executed by a processor to obtain the relative speed between a first traffic object and a second traffic object. The separation distance between the first traffic object and the second traffic object is received. The relative speed and the separation distance are combined to form a quantitative measure of hazard encountered by the first traffic object. The obtain, receive and combine operations are repeated to form cumulative measures of hazard associated with the first traffic object. The cumulative measures of hazard are analyzed to derive a first traffic object safety score for the first traffic object.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: An apparatus for controlling to enable an autonomous system in a vehicle is provided. The apparatus includes a sensor, an input device configured to receive an input from a driver of the vehicle, an output device configured to output a notification in the vehicle, and a control circuit configured to be electrically connected with the sensor, the input device, and the output device. The control circuit is configured to activate an autonomous control in response to an input of the driver to the input device, detect a critical situation of the vehicle using the sensor, output a notification to transfer a control authority using the output device in response to the detected critical situation, and automatically reactivate the autonomous control when the critical situation is solved after temporarily releasing the autonomous control, when the critical situation corresponds to a critical situation of a specified type.

Abstract: A vehicle control method for executing a lane change of a subject vehicle includes acquiring surrounding information of the subject vehicle; specifying an entry position indicating a position of an entry destination of the subject vehicle, the entry position being located on a second lane adjacent to a first lane in which the subject vehicle is traveling; when operating a blinker, decelerating the subject vehicle, and executing a lane change; determining that there is a following vehicle which follows the subject vehicle in a predetermined area located behind the subject vehicle on a first lane; setting a preparation time longer than the preparation time when determining that there is not the following vehicle, the preparation time indicating a time from operating the blinker to decelerating the subject vehicle and starting the lane change; and controlling a travel position of the subject vehicle on the first lane within the preparation time.