An articulatable mount for temporarily affixing a camera and illumination system to a vehicle is disclosed. The articulating drive mechanism is lightweight, vertically compact, and ruggedized for severe service such as withstanding shocks from off-road travel and abrupt maneuvering. Articulation and illumination may be controlled remotely over Wi-Fi from inside or nearby the vehicle, and encrypted video feeds may be received by authorized users of an ad-hoc network of available smart-phone users and in-vehicle computer systems authorized and authenticated to participate in the network.

A system and method for assisting drivers of vehicles are described. The systems and methods provide an extended view of the area surrounding the driver's vehicle while providing real-time object trajectory for objects and other vehicles that may enter the driver's reactionary zone. The system and methods capture images of the area surrounding the driver's vehicle and create a composite image of that area in real-time and using Augmented Reality (AR) create a 3-D overlay to warn the driver as objects or other vehicles enter the driver's reactionary zone so that a driver can make more informed driving decisions.

A method for training a machine learning algorithm for predicting an intent parameter of an object in proximity to a self-driving vehicle on a terrain are provided. The method includes generating a training dataset having assessor-less labels, based on data collected by a training vehicle. The data collected by the training vehicle include data on the state of the training vehicle, the state of a training object, and a training terrain at a target moment in time and at a time after the target moment in time. The training data is based, at least in part, on the data for the target moment in time, and the assessor-less label is based, at least in part, on the data for a time after the target moment in time. A method for operating a self-driving vehicle and a self-driving vehicle are also disclosed.

A method for training a machine learning algorithm for predicting an intent parameter of an object in proximity to a self-driving vehicle on a terrain are provided. The method includes generating a training dataset having assessor-less labels, based on data collected by a training vehicle. The data collected by the training vehicle include data on the state of the training vehicle, the state of a training object, and a training terrain at a target moment in time and at a time after the target moment in time. The training data is based, at least in part, on the data for the target moment in time, and the assessor-less label is based, at least in part, on the data for a time after the target moment in time. A method for operating a self-driving vehicle and a self-driving vehicle are also disclosed.

A vehicle external environment imaging apparatus includes imaging devices and a controller. The imaging devices are disposed on a vehicle to perform imaging of a vehicle external environment. The controller generates information regarding a distance or a direction of a vehicle-external imaging target with imaging images of the imaging devices. At least two imaging devices are disposed on the vehicle to be able to perform duplicated imaging of a common imaging region. The controller generates, on the basis of a distance and a direction in an imaging image obtained by a first one of the at least two imaging devices, correction information regarding a distance, a direction or both of the vehicle-external imaging target based on an imaging position which is to be used in a monocular process on an imaging image of at least one the at least two imaging devices that is different from the first one.

A vehicle external environment imaging apparatus includes imaging devices and a controller. The imaging devices are disposed on a vehicle to perform imaging of a vehicle external environment. The controller generates information regarding a distance or a direction of a vehicle-external imaging target with imaging images of the imaging devices. At least two imaging devices are disposed on the vehicle to be able to perform duplicated imaging of a common imaging region. The controller generates, on the basis of a distance and a direction in an imaging image obtained by a first one of the at least two imaging devices, correction information regarding a distance, a direction or both of the vehicle-external imaging target based on an imaging position which is to be used in a monocular process on an imaging image of at least one the at least two imaging devices that is different from the first one.

Automatic drive mode lighting systems and methods are disclosed herein. An example method can include determining when a drive mode of a vehicle is an off-road mode, determining when a speed of the vehicle is below a speed threshold, determining when a location of the vehicle corresponds to an off-road location, and automatically activating off-road lighting for the vehicle when the drive mode is in an off-road mode, the speed is below the speed threshold, and the location corresponds to an off-road location.

The present invention improves the accuracy of detection of a three-dimensional object. A three-dimensional object detecting device generates a mask image 90 that masks regions outside a three-dimensional object candidate region in a difference image G of a first overhead image F1 and a second overhead view image F2 for which the imaging locations O are mutually aligned, identifies a near ground contact line L1 of a three-dimensional object based on a masked difference image wherein the difference image G is masked with the mask image 90, finds an end point of the three-dimensional object based on the masked difference image Gm, identifies the width of the three-dimensional object based on a distance between a non-masking region boundary N and the end point V of the three-dimensional object in the mask image 90, identifies a far ground contact line L2 of the three-dimensional object based on the width of the three-dimensional object and the near ground contact line L1, and identifies the location of the three-dimensional object in the difference image G based on the near ground contact line L1 and the far ground contact line L2.

The present invention improves the accuracy of detection of a three-dimensional object. A three-dimensional object detecting device generates a mask image 90 that masks regions outside a three-dimensional object candidate region in a difference image G of a first overhead image F1 and a second overhead view image F2 for which the imaging locations O are mutually aligned, identifies a near ground contact line L1 of a three-dimensional object based on a masked difference image wherein the difference image G is masked with the mask image 90, finds an end point of the three-dimensional object based on the masked difference image Gm, identifies the width of the three-dimensional object based on a distance between a non-masking region boundary N and the end point V of the three-dimensional object in the mask image 90, identifies a far ground contact line L2 of the three-dimensional object based on the width of the three-dimensional object and the near ground contact line L1, and identifies the location of the three-dimensional object in the difference image G based on the near ground contact line L1 and the far ground contact line L2.

A method of processing an image using a camera of a vehicle includes: a first operation of controlling a road wheel of the vehicle according to an imaging mode selected by a user from among a plurality of imaging modes, and a second operation of generating an image according to the imaging mode selected by the user by using the camera while the road wheel of the vehicle is controlled.