Apparatuses and methods for evaluating the risk factors of a proposed vehicle maneuver using remote data are disclosed. In embodiments, a computer-assisted/autonomous driving vehicle communicates with one or more remote data sources to obtain remote sensor data, and process such remote sensor data to determine the risk of a proposed vehicle maneuver. A remote data source may be authenticated and validated, such as by correlation with other remote data sources and/or local sensor data. Correlation may include performing object recognition upon the remote data sources and local sensor data. Risk evaluation is performed on the validated data, and the results of the risk evaluation presented to a vehicle operator or to an autonomous vehicle navigation system.

A method and apparatus for controlling a vehicle are provided. A lane in which a target vehicle is driving, and an object in a vicinity of the lane are detected from an image of surroundings of the target vehicle, a degree of danger of the object is evaluated, driving information of the target vehicle is determined based on the degree of danger, and the target vehicle is controlled based on the driving information.

Systems, apparatus and methods may be configured to implement actively-controlled light emission from a robotic vehicle. A light emitter(s) of the robotic vehicle may be configurable to indicate a direction of travel of the robotic vehicle and/or display information (e.g., a greeting, a notice, a message, a graphic, passenger/customer/client content, vehicle livery, customized livery) using one or more colors of emitted light (e.g., orange for a first direction and purple for a second direction), one or more sequences of emitted light (e.g., a moving image/graphic), or positions of light emitter(s) on the robotic vehicle (e.g., symmetrically positioned light emitters). The robotic vehicle may not have a front or a back (e.g., a trunk/a hood) and may be configured to travel bi-directionally, in a first direction or a second direction (e.g., opposite the first direction), with the direction of travel being indicated by one or more of the light emitters.

Vision based guidance system and method for lawn mowing devices are disclosed. An exemplary method for operating an autonomous lawn mower includes receiving, via a receiver, a perimeter data set from a handheld computer. The perimeter data set includes a perimeter outline of at least one perimeter that is determined utilizing a GPS unit of the handheld computer. The exemplary method also includes collecting, via at least one camera, images of a set area within the perimeter outline and mowing, via a mowing blade, grass within the set area. The exemplary method also includes autonomously steering, via a controller, the autonomous lawn mower based on the perimeter outline of the at least one perimeter and the images captured by the at least one camera.

An anti-collision system includes a truck cab defining a truck cab volume and a sensor positioned with respect to the truck cab. The truck cab is rotatable with respect to the truck chassis along a rotation path to define a truck cab rotation volume. The truck cab volume is entirely within the truck cab rotation volume along the entire rotation path, i.e., the truck cab rotation volume encompasses the truck cab volume at every position of the truck cab volume along the rotation path. The sensor has a field of view (FOV) that overlaps a portion of the truck cab rotation volume to detect an obstruction in the FOV that is within the truck cab rotation volume. The sensor may also cause the system to provide an alert or control rotation of the truck cab in response to detecting the obstruction.

A behavior prediction device comprising: a moving object behavior detection unit configured to detect moving object behavior, a behavior prediction model database that stores a behavior prediction model, a behavior prediction calculation unit configured to calculate a behavior prediction of the moving object using the behavior prediction model, a prediction deviation determination unit configured to determine whether a prediction deviation occurs based on the behavior prediction and a detection result of the moving object behavior corresponding to the behavior prediction, a deviation occurrence reason estimation unit configured to estimate a deviation occurrence reason when determination is made that the prediction deviation occurs, and an update necessity determination unit configured to determine a necessity of an update of the behavior prediction model database based on the deviation occurrence reason when the determination is made that the prediction deviation occurs.

A stopping position control device according to an embodiment includes a sitting position specifying unit configured to specify a sitting position of a user who gets off a vehicle next, the vehicle being subjected to automatic driving control, and a stopping position determination unit configured to determine a stopping position of the vehicle, at which the user gets off the vehicle, corresponding to the sitting position of the user.

A method for trajectory planning of a vehicle includes storing a desired driving path of the vehicle. The method then includes observing external interference factors (2) on the vehicle. The method proceeds by using the driving path and the interference factors (2) to calculate tracking errors (3) and secondary conditions (4). The method then includes optimizing a trajectory (5) in such a way that the tracking errors (3) are reduced within the secondary conditions (4). A corresponding device, a corresponding computer program, and a corresponding storage medium also are provided.

A driving assistance device includes a travel information acquisition unit, a first information acquisition unit, a second information acquisition unit, a first determination unit, a second determination unit, a first avoidance-amount setting unit, a second avoidance-amount setting unit, and a driving control unit. The second avoidance-amount setting unit sets, when the second avoidance-amount setting unit sets a control amount of a driving control as a second avoidance amount for performing a second avoidance driving action, the control amount smaller than a control amount that is set as a first avoidance amount by the first avoidance-amount setting unit, and sets, when the second avoidance-amount setting unit sets a start timing of the driving control as the second avoidance amount for performing the second avoidance driving action, the start timing later than a start timing that is set as the first avoidance amount by the first avoidance-amount setting unit.

A driving support apparatus (12) has: a setting device (122) for setting a first target position (31) on the basis of a first sign object (21), if the first sign object requesting a vehicle (1) to stop is detected; and a supporting device (123) for performing a first deceleration control for decelerating the vehicle to a first target speed before the vehicle reaches the first target position, if a second sign object (22) representing a stop position is detected during a period when the first decelerating control is performed, the setting device sets a second target position (32) on the basis of the second sign object and the supporting device performs a second decelerating control for decelerating the vehicle to a second target speed before the vehicle reaches the second target position.