A vehicular control system includes a camera disposed at a vehicle and having a field of view exterior of the vehicle. Data is wirelessly transmitted from the vehicle to a data cloud. An image processor processes image data captured by the camera to detect objects present within the field of view of the camera. Data is wirelessly received at the vehicle from the data cloud concerning a potential hazard existing exterior of the vehicle that has not yet been detected via processing by the image processor of image data captured by the camera. Responsive at least in part to the vehicular control system detecting the potential hazard via the image processor processing image data captured by the camera, the vehicular control system controls at least one vehicle function of the vehicle to mitigate collision with the potential hazard.

One embodiment describes an automation system including a sensor that determines operational parameters of the automation system; one or more actuators that perform control actions during operation of the automation system; and a control system communicatively coupled to the sensor and the one or more actuators. The control system includes memory that stores the operational parameters; determines occurrence of memory errors in data stored in the memory; determines error parameters that indicate characteristics of the memory errors; determines error-corrected data by correcting the memory errors based at least in part on the error parameters; adaptively adjusts a refresh rate used to refresh stored data in the memory based at least in part on the error parameters; and determines control commands instructing the one or more actuators to perform the control actions by processing the error-corrected data.

A vehicular personalized adaptive cruise control system includes a forward-viewing camera viewing forward through a windshield of a vehicle, and an electronic control unit disposed at the vehicle. When the vehicle is operating in an adaptive cruise control mode, the system controls driving of the vehicle. When the equipped vehicle is not operating in the adaptive cruise control mode, a driver present in the vehicle drives the vehicle. The system identifies the driver via processing of image data captured by a cabin monitoring camera. When the identified driver drives the vehicle with the vehicle not operating in the adaptive cruise control mode, the system determines and stores personalized parameters for the identified driver. With the identified driver present in the vehicle, and when the vehicle is operating in the adaptive cruise control mode, the system uses the determined personalized parameters.

A method of optimizing fuel economy and reduced noise and vibration levels in a vehicle includes one or more of the following steps: evaluating an engine speed and a speed of the vehicle, determining if the engine speed and the speed of the vehicle produces a noise level that causes a potential customer complaint, monitoring the noise level in the vehicle, calculating the engine operating condition that causes the noise level, determining if the noise level is above a threshold, adjusting an engine torque or a slip condition of a torque converter for optimal vehicle fuel economy if the noise level is at or below the threshold, and, if the noise level is above the threshold, adjusting the engine torque or the slip condition of the torque converter such that the noise level is at or below the threshold.

The present disclosure relates to systems and methods for autonomous driving. The systems may obtain driving information associated with a vehicle; determine a state of the vehicle; determine one or more candidate control signals and one or more evaluation values corresponding to the one or more candidate control signals based on the driving information and the state of the vehicle by using a trained control model; select a target control signal from the one or more candidate control signals based on the one or more evaluation values; and transmit the target control signal to a control component of the vehicle.

A system and 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.

In one embodiment, during a planning stage of autonomous driving of an autonomous driving vehicle (ADV), it is determined that the ADV needs to change lanes from a source lane to a target lane. A first trajectory is generated from a current location of the ADV in the source lane to the target lane such as a center line of the target lane. A lane shifting correction is then calculated based on the lane configuration of at least the source lane and/or target lane, as well as the current state of the ADV. Based on the lane shifting correction, at least the starting point of the first trajectory is modified, which in turn generates a second trajectory. In one embodiment, the starting point of the first trajectory is shifted laterally with respect to a heading direction of the source lane based on the lane shifting correction.

A moving amount estimating apparatus includes a position data obtaining unit, a first estimating unit, and a second estimating unit. The position data obtaining unit obtains a plurality of position data used to form a projection object image before and after movement of a mobile body. The first estimating unit calculates a moving amount of a parallel movement and/or a rotational movement of second position data as a moving amount of a mobile body when a plurality of moving position data is calculated. A second estimating unit compensates for a wheel moving amount based on a comparison between a second reference moving amount based on a rotating amount of a wheel during a predetermined period and a first reference moving amount obtained by calculating the moving amount of the mobile body in the first estimating unit during the predetermined period, and estimates the moving amount of the mobile body.

There are provided an apparatus and a method for controlling a lane change considering priority. The apparatus for controlling a lane change includes: a collision judger checking whether or not there is an object vehicle having collision possibility that attempts to change a lane from a region of interest road corresponding to an ego-road on which an ego-vehicle is being driven to a target road to which the ego-vehicle changes the lane, before or during the lane change of the ego-vehicle; and a priority determiner determining a priority vehicle that first performs the lane change among the ego-vehicle and the object vehicle considering at least one of accessibility to the target road of the ego-vehicle and the object vehicle when there is the object vehicle, and accessibility to a join point when the object vehicle or the ego-vehicle is positioned on a road to be joined.

A system according to the principles of the present disclosure includes a cruise control module, an engine control module, and a brake control module. The cruise control module determines a cruise torque request based on at least one of a following distance of a vehicle and a rate at which the vehicle is approaching an object. The engine control module determines a negative torque capacity of a powertrain. The powertrain includes an engine and an electric motor. The brake control module applies a friction brake when the cruise torque request is less than the negative torque capacity of the powertrain.