Abstract: Realized is a vehicle control device capable of performing automatic driving control that does not reduce turning accuracy of a host vehicle even when an object in a blind spot is different from an assumption and a vehicle speed decreases due to a rapid deceleration. A vehicle control device 10 includes a blind spot object estimation unit 24 that detects a blind spot region 320 of an external-field recognition sensor 12 that recognizes an external field and estimates a blind spot object 310 potential in the blind spot region 320, and a future trajectory generation unit 26 that generates a future trajectory of a host vehicle in consideration of a potential risk from the blind spot object 310 estimated by the blind spot object estimation unit 24 and surrounding information of a vehicle 1 that is the host vehicle.

Abstract: An example operation includes one or more of merging at least one vehicle from a first group of vehicles and at least one vehicle from a second group of vehicles, where the merged vehicles communicate with one another, and where a main vehicle in the second group is notified of the merging by the at least one vehicle in the second group after the merging.

Abstract: In a vehicle sensor attaching structure in which a first sensor and second sensors for detecting an object outside a vehicle by sensor fusion are attached to the vehicle, the first sensor and the second sensors are disposed side by side in a uniaxial direction along a surface of the vehicle, and the one first sensor is disposed to be sandwiched between the two second sensors at equal intervals.

Abstract: Systems, methods and instrumentalities for a distributed detect and avoid (DM) framework for unmanned vehicles, such as unmanned aerial vehicles (UAVs). The systems, methods and instrumentalities may include a wireless transmit/receive unit (WTRU) associated with a vehicle. The WTRU may include a memory and a processor. The processor may be configured to store a trajectory of the vehicle and to send a message indicative of a conflict between the trajectory of the vehicle and a trajectory of another vehicle. The processor may be configured to receive a message from the other vehicle that is indicative of one or more conflicts and to determine a list that includes the vehicle(s) associated with the one or more conflicts. The processor may be configured to determine a resolution that addresses the conflict(s) associated with the list.

Abstract: A remote support system is configured to determine whether a vehicle collides with an object to be avoided when the vehicle gets into a remote control request situation, stop to send a remote control request when the remote support system determines that the vehicle does not collide with the object, generate a first speed plan for the vehicle to continue autonomous driving at a predicted collision position and a second speed plan for the vehicle to stop before reaching the predicted collision position when the remote support system determines that the vehicle collides with the object, and determine to send a remote control request based on the degree of deviation between these speed plans.

Abstract: The present invention obtains a controller capable of suppressing worsening of comfort of an occupant in a vehicle when compared to the background art. The controller according to the present invention is a controller that is mounted to the vehicle and outputs a command signal corresponding to a damping coefficient of a shock absorber to an actuator that adjusts the damping coefficient of the shock absorber of a damping force adjustment type.

Abstract: A manager to be mounted on a vehicle includes a reception unit that receives a plurality of kinematic plans from a plurality of ADAS applications, an arbitration unit that performs arbitration of the kinematic plans, a calculation unit that calculates a motion request based on a result of the arbitration at the arbitration unit, and a distribution unit that distributes the motion request to at least one actuator system. The reception unit receives information related to arbitration targets of the arbitration unit from the ADAS applications.

Abstract: Methods and systems described herein can assist a user when loading a watercraft onto a trailer (e.g., at a boat ramp). For example, position data generated by sensor(s) coupled to the watercraft and/or trailer can cause one or more propulsion devices associated with the watercraft to automatically (e.g., without user intervention) position the watercraft onto the trailer, for example, by controlling the power and/or thrust direction of the propulsion device(s).

Abstract: Examples are provided for traffic pole verification systems.

Abstract: A door control device has a processor configured to determine whether or not an emergency situation has occurred in a vehicle, based on operation by a user on an operating unit that is to be operated to open a door of the vehicle, and to decide to open the door when it has been determined by the first assessment unit that the emergency situation has occurred.

Abstract: The control device according to the present disclosure executes a process of acquiring an image captured by a camera provided in a vehicle and estimating an vehicle-to-vehicle distance and a relative speed with the preceding vehicle based on an image, a process of calculating a time to collision with respect to the preceding vehicle from the vehicle-to-vehicle distance and the relative speed, a deceleration process of decelerating the vehicle based on the vehicle-to-vehicle distance, the relative speed, and the time to collision, and a process of performing a warning to the driver of the vehicle upon receiving that the amplitude of the variation of any one physical quantity of the vehicle-to-vehicle distance, the relative speed, or the time to collision has become equal to or greater than a predetermined threshold value.

Abstract: In one embodiment, a method is provided. The method includes receiving, at an input of a first machine learning model, first input data representing an environment. The method also includes determining, by the first machine learning model, a set of objects within the environment based on the first input data. The method further includes determining, by a second machine learning model, a set of behaviors for a second set of objects. An input of the second machine learning model is coupled to a set of intermediate layers of the first machine learning model. Determining the set of objects and determining the set of behaviors for the second set of objects is performed at least partially simultaneously.

Abstract: A vehicle navigation apparatus includes a storage, a second map information acquisition unit, a display, and a display control unit. The storage stores first map information. The second map information acquisition unit acquires second map information. The display displays map data on the basis of at least one of the first map information or the second map information. The display control unit controls the form of displaying the map data on the display in accordance with a predetermined condition. The display control unit causes the map data to be displayed at a greater scale in a case where the map data is displayed on the basis of the second map information than in a case where the map data is displayed on the basis of only the first map information.

Abstract: An acquisition unit acquires data regarding a travel trajectory of another vehicle from the other vehicle. A specifying unit specifies an intersection position between the travel trajectory of the other vehicle and a travel trajectory of a self-vehicle. A setting unit setts a region based on the intersection position and the travel trajectory of the other vehicle as a monitoring region when performing driving assistance. A determination unit determines whether or not to update the monitoring region based on a result of comparison between first data that is the data used to set the monitoring region and second data that is the data acquired from the other vehicle traveling in the monitoring region. The setting unit updates the monitoring region based on the second data in a case where the determination unit determines to update the monitoring region.

Abstract: Techniques for determining occupancy using unobstructed sensor emissions. For instance, a vehicle may receive sensor data from one or more sensors. The sensor data may represent at least locations to points within an environment. Using the sensor data, the vehicle may determine areas within the environment that are obstructed by objects (e.g., locations where objects are located). The vehicle may also use the sensor data to determine areas within the environment that are unobstructed by objects (e.g., locations where objects are not located). In some examples, the vehicle determines the unobstructed areas as including areas that are between the vehicle and the identified objects. This is because sensor emissions from the sensor(s) passed through these areas and then reflected off of objects located farther distances from the vehicle. The vehicle may then generate a map indicating at least the obstructed areas and the unobstructed areas within the environment.

Abstract: The invention relates to an access control method for a motor vehicle. The motor vehicle has at least a first and a second access element automatically adjustable between a closed position and an open position. The method comprises at least the following steps: detecting at least one position of a key element carried by a user relative to the motor vehicle by radio; calculating a probability of use for each access element depending on the at least one detected position of the key element; adjusting both the first access element and the second access element from the closed position to the open position if: the probability of use of each of the first and second access elements is above a predetermined first threshold value; and an absolute value of a difference in the probability of use of the first and second access elements is below a predetermined second threshold value.

Abstract: Systems and methods of controlling an active safety feature of a vehicle are provided. The systems and methods receive radar data from a radar device of the vehicle and image data from a camera of the vehicle. Object detection and tracking processes are performed on the radar data and the image data to identify and track objects in an environment of the vehicle. Conditions are assessed with respect to identified objects to ascertain whether a radar track is erroneously reported as a separate object to a camera track. When the conditions are assessed to be true, an object corresponding to the camera track is used as an input for controlling an active safety feature of the vehicle and an object corresponding to the radar track is discounted for controlling the active safety feature of the vehicle.

Abstract: An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

Abstract: Provided are techniques for automatic annotation of drivable road segments, including but not limited to: receiving sensor data, generating a map, dividing the map into disjoint sub-maps, inferring sub-map segmentation masks, constructing an inferred segmentation mask, filtering the inferred segmentation mask, smoothing the filtered segmentation mask, planning a path for a vehicle and controller the vehicle.

Abstract: A control unit for a vehicle is designed to predict a driving tube for the vehicle, which driving tube surrounds a motion path ahead of the vehicle. The control unit detects an object ahead, for example a vehicle moving in or out. The control unit determines a reference point on the object and determines overlap information regarding overlap of the reference point with the driving tube. The control unit determines, on the basis of the overlap information, whether the object is penetrating into the driving tube of the vehicle.