Autonomous vehicles need to plan at the task level to compute a sequence of symbolic actions, such as merging left and turning right, to fulfill people's service requests, where efficiency is the main concern. At the same time, the vehicles must compute continuous trajectories to perform actions at the motion level, where safety is the most important. Task-motion planning in autonomous driving faces the problem of maximizing task-level efficiency while ensuring motion-level safety. To this end, we develop algorithm Task-Motion Planning for Urban Driving (TMPUD) that, for the first time, enables the task and motion planners to communicate about the safety level of driving behaviors. TMPUD has been evaluated using a realistic urban driving simulation platform. Results suggest that TMPUD performs significantly better than competitive baselines from the literature in efficiency, while ensuring the safety of driving behaviors.

A device for setting a target vehicle that sets a target vehicle to be subjected to driving assistance control of a host vehicle includes: a detection signal acquisition device capable of acquiring a first detection signal representing an object by an image, and a second detection signal representing the object by a reflection point; and setting control unit, which determines whether to set a forward object as a target vehicle, wherein if a movement history is not associated with the forward object, and a combination history is associated with the forward object, then as a selection threshold of a first determination parameter for determining whether to set the forward object as the target vehicle, a selection threshold is used such that the forward object is less likely to be selected as the target vehicle than with the selection threshold which would be used if a movement history is associated with the forward object.

A driving warning method applied to a vehicle-mounted device is provided. The method includes detecting a moving object and a moving direction of the moving object by using at least one external sensor when a vehicle is moving. A driving behavior of a driver of the vehicle is monitored by using at least one internal sensor when the moving object and the moving direction of the moving object are detected. Once the moving direction of the moving object is not parallel to a moving direction of the vehicle and a sight direction of the driver does not cross the moving direction of the moving object, a first warning is transmitted.

A method for navigating a vehicle automatically from a current location to a destination location without a human operator is disclosed. The method includes identifying a vehicle location using global positioning system (GPS) data regarding the vehicle. Also included is identifying that the vehicle location is near or at a parking location. Then, using mapping data defined for the parking location. The mapping data at least in part is used to find a path at the parking location to avoid a collision of the vehicle with at least one physical structure when the vehicle is automatically moved at the parking location. The method includes instructing the electronics of the vehicle to proceed with controlling the vehicle to automatically move from the current location to the destination location at the parking location. The electronics use as input at least part of the mapping data and sensor data collected from around the vehicle by at least two vehicle sensors. The path is configured to be updatable dynamically based on changes in the destination location or changes along the path. The destination location is a parking spot for the vehicle at the parking location.

Systems and methods are provided for vehicle navigation. In one implementation, at least one processor may receive, from a camera, at least one captured image representative of features in an environment of the vehicle. The processor may identify an intersection and a pedestrian in a vicinity of the intersection represented in the image. The processor may determine a navigational action for the vehicle relative to the intersection based on routing information for the vehicle; and determine a predicted path for the vehicle relative to the intersection based on the determined navigational action and a predicted path for the pedestrian based on analysis of the image. The processor may further determine whether the vehicle is projected to collide with the pedestrian based on the projected paths; and, in response, cause a system associated with the vehicle to implement a collision mitigation action.

A control device detects an object that is present in a traveling direction of a road on which a mobile object is traveling, controls a behavior of the mobile object, acquires an operation state of a turn signal, causes, when a degree of proximity between the mobile object and the detected object is less than a reference, the mobile object to move in a direction intersecting the traveling direction when a predetermined time has elapsed from starting of operating the turn signal obtained from the operation state of the turn signal, and causes, when the degree of proximity is equal to or greater than the reference, the mobile object to move in the direction intersecting the traveling direction before the turn signal is operated or before a predetermined time has elapsed from starting of operating the turn signal.

Please replace the original Abstract with the following new 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.

A vehicle is provided to avoid a collision with a target object located in front of the vehicle by predicting an expected traveling path of the target object. The vehicle also predicts the possibility of a collision with the target object.

Provided is a driving assistance apparatus that assists driving of a vehicle. The driving assistance apparatus includes: a training data generator that stores a traveling route traveled by the vehicle according to a driving operation of a user in a training traveling mode, and generates training data for a target route based on the traveling route. The training data generator generates the target route by connecting, for example, between a first point and a second point on the traveling route, in a case where a difference in orientation of the vehicle at the first point and the second point during training traveling is less than a first threshold and distance between the vehicle at the first point and the vehicle at the second point during the training traveling is less than a second threshold.

A system includes a controller circuit configured to monitor, while a host vehicle is operated in a manual driving mode, a speed change response of an operator of the host vehicle based on a movement of a first vehicle traveling on a roadway, identify at least one speed parameter based on the speed change response, and apply, when the host vehicle is controlled in an autonomous driving mode, the at least one speed parameter based on the movement of a second vehicle traveling on the roadway.