Upon determining that a vehicle is operating at an off-road location, a control parameter for the vehicle can be adjusted to compensate for data from a vehicle sensor affected by operating at the off-road location. The vehicle can then be operated at the off-road location according to the adjusted control parameter.

A method for controlling a lane keep assist system comprises the combination of predicting that a driver may initiate a lane change without using a turn indicator switch and temporarily deactivating the lane keep assist system in response to such prediction.

A driving assistance apparatus measures a position and a movement direction of a target object present in the periphery of an own vehicle. The driving assistance apparatus performs a driving assistance process of the own vehicle when the measured position of the target object is within a determination area provided in the periphery of the own vehicle. The driving assistance apparatus corrects the determination area in a direction at which the target object is measured, when the target object is determined to be moving towards the determination area based on the measured movement direction of the target object.

A vehicle control system includes a central ECU configured to calculate target outputs of actuators, and relay devices each disposed in a communication path between the central ECU and a corresponding actuator among the actuators. The relay devices include a specific relay device capable of communicating with a specific actuator related to driving control, braking control, or steering control of a vehicle. The specific relay device among the relay devices includes a specific abnormality diagnosis unit configured to diagnose an abnormality in the specific relay device, and a backup calculation unit capable of calculating a control amount of the specific actuator coupled to the specific relay device. A relay device other than the specific relay device among the relay devices does not have a self-diagnosis function.

Provided are a vehicle approach detection device and a vehicle approach detection method that are capable of detecting an approach of another vehicle without installing a dedicated device on a road. At least one of a vehicle surrounding video for showing an observed area (for example, road surface) used to observe irradiation light (for example, headlight beam emitted from a headlight of another vehicle) from another vehicle and a vehicle surrounding environmental sound is detected as vehicle external information, and it is determined based on the detected vehicle external information whether or not another vehicle is approaching an own vehicle.

A motorised vehicle comprises a first wheel located laterally on a first side of the vehicle, and a second wheel located laterally on a second side of the vehicle opposite the first side. The vehicle comprises a steering system configured to modify the orientation of the wheels and to turn the vehicle. The vehicle comprises a trajectory modifier configured to vary the speed of rotation of the first wheel and to modify the trajectory of the vehicle in the event of failure of the steering system.

A vehicle control arrangement is configured to control steering and velocity of a road vehicle including a velocity control arrangement, remote sensors configured to acquire vehicle surrounding information, a steering control unit configured to control steering of the vehicle based on the vehicle surrounding information, an upcoming road geometry detecting unit configured to detect presence of an upcoming curve section, a hands-on-wheel detecting unit configured to detect if presence exists of at least one hand on a steering wheel of the vehicle. The velocity control arrangement is configured to perform a reduction of velocity of the vehicle in case presence of an upcoming curve section is detected and no presence is detected of at least one hand on the steering wheel.

An in-vehicle image processing device processes camera images to determine a parkable area and includes an overhead image generation section generating an overhead image relative to a road surface by converting the view point of an image of a nearby vehicle and the road surface taken by a vehicle-mounted camera; a tire recognition section recognizing the tires of the nearby vehicle; a three-dimensional object recognition section recognizing three-dimensional objects including the nearby vehicle; an area-under-vehicle recognition section calculating the ground contact position of the tire and the above-ground height from the ground contact position to the vehicle body and recognizing an area under the vehicle body on the road surface from the overhead image; and a parkable area recognition section for recognizing the area occupied by the vehicle body and the area under the vehicle body as a non-parking area and recognizing a parkable area on the road surface.

A vehicle control apparatus is mounted on a vehicle including an emergency stop function to detect an abnormal state of a driver and automatically stop the vehicle. The vehicle control apparatus provides control at a time of stopping the vehicle and includes process execution sections and a process stop section. The process execution sections perform predetermined emergency processes in response to the emergency stop function stopping the vehicle; the emergency processes control instruments mounted on the vehicle and use a battery of the vehicle as a driving power source. The process stop section stepwise stops at least part of the emergency processes performed by the process execution sections based on a predetermined stop sequence.

A system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions. One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions. One general aspect includes sends video data and light detecting and ranging (LIDAR) data to a recurrent neural network (rnn) that includes feedback elements to identify a roadway feature. The system also sends the data to a dynamic convolutional neural network (dcnn) to identify the feature. Output values are sent to a softmax decision network to aggregate the rnn and the dcnn output values and determine a vehicle positional location on the roadway.