A vehicle automated driving system 100 comprises a surrounding environment information acquiring device 10, a vehicle information acquiring device 20, a driver information acquiring device 30, a package selecting part 90, a package proposing part 91, an automated driving executing part 92, and a rejection count detecting part 93. The package selecting part determines the driving assistance package based on at least one of the surrounding environment information, the vehicle information, and the driver information, selects the determined driving assistance package if the rejection count of the determined driving assistance package is less than a predetermined threshold value, and selects a driving assistance package different from the determined driving assistance package if the rejection count of the determined driving assistance package is the threshold value or more.

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.

Disclosed are an in-cabin safety sensor installed in a vehicle and capable of providing a recognition service for drowsy driving and careless driving, and a method of providing a service platform therefor. The in-cabin safety sensor may recognize a state of drowsy driving or careless driving by using an image obtained by photographing a driver. In addition, the in-cabin safety sensor may not only implement immediate response actions, but also provide information on the state information to a service server, so that driver's driving habits and the like may be recorded. In this way, at the level of the service server or a manager thereof, different response actions may be taken for the drowsy driving or careless driving of the corresponding driver of the vehicle.

A crosswalk navigation system for operating an automated vehicle in an intersection includes an intersection-detector, a pedestrian-detector, and a controller. The intersection-detector is suitable for use on a host-vehicle. The intersection-detector is used to determine when the host-vehicle is proximate to an intersection and determine when the intersection includes a cross-walk. The pedestrian-detector is suitable for use on the host-vehicle. The pedestrian-detector is used to determine a motion-vector of a pedestrian relative to the cross-walk. The controller is in communication with the intersection-detector and the pedestrian-detector. The controller is configured to determine a travel-path of the host-vehicle through the intersection, determine when the pedestrian will pass through an intersect-location where the travel-path intersects the cross-walk based on the motion-vector, and operate the host-vehicle to enter the intersection before the pedestrian passes through the intersect-location and to arrive at the intersect-location after the pedestrian passes through the intersect-location.

A lane-keeping system suitable for use on an automated vehicle includes a camera, an inertial-measurement-unit, and a controller. The camera is configured to detect a lane-marking of a roadway traveled by a vehicle. The inertial-measurement-unit is configured to determine relative-motion of the vehicle. The controller in communication with the camera and the inertial-measurement-unit. When the lane-marking is detected the controller is configured to steer the vehicle towards a centerline of the roadway based on a last-position, and determine an offset-vector indicative of motion of the vehicle relative to the centerline of the roadway. When the lane-marking is not detected the controller is configured to: determine an offset-position relative to the last-position based on information from the inertial-measurement-unit, determine a correction-vector used to steer the vehicle from the offset-position towards the centerline of the roadway based on the last-position and the offset-vector, and steer the vehicle according to the correction-vector.

A method for processing image data. The method includes a step of determining correspondence data as the result of a correspondence generation between first image data that represent data recorded by a camera at a first point in time, and preceding image data that represent data recorded by the camera at a preceding point in time. In a step of determining, depth data are determined on the basis of an ego-motion estimate carried out using the correspondence data. In a step of ascertaining, fusion data are ascertained using the depth data and the transferred fusion data, the fusion data including an item of depth information based on the image data.

An autonomous navigation system may autonomously navigate a vehicle through an environment in which one or more non-solid objects, including gaseous and/or liquid objects, are located. Sensors, including sensors which can detect chemical substances in a region of the environment, may detect non-solid objects independently of an opacity of the objects. Non-solid objects may be determined to present an obstacle or interference based on determined chemical composition, size, position, velocity, concentration, etc. of the objects. The vehicle may be autonomously navigated to avoid non-solid objects based on positions, trajectories, etc. of the non-solid objects. The vehicle may be navigated according to avoidance driving parameters to avoid non-solid objects, and a navigation system may characterize a non-solid object as a solid object having dimensions and position which encompasses the non-solid object, so that the vehicle is navigated in avoidance of non-solid objects as if the non-solid objects were solid.

A vehicle automated driving system 100 comprises a surrounding environment information acquiring device 10, a vehicle information acquiring device 20, a driver information acquiring device 30, a package selecting part 90, a package proposing part 91, an automated driving executing part 92, and a rejection count detecting part 93. The package selecting part determines the driving assistance package based on at least one of the surrounding environment information, the vehicle information, and the driver information, selects the determined driving assistance package if the rejection count of the determined driving assistance package is less than a predetermined threshold value, and selects a driving assistance package different from the determined driving assistance package if the rejection count of the determined driving assistance package is the threshold value or more.

A method of autonomously backing a vehicle (e.g., a tractor unit) to a trailer (e.g., a semi-trailer) comprising a trailer-mounted coupling device (e.g., a kingpin). The method includes determining, by an autonomous backing module of the vehicle, a target corresponding to the trailer-mounted coupling device; determining, by the autonomous backing module, a path to maneuver the vehicle to the target and align a vehicle-mounted coupling device (e.g., a fifth wheel) with the trailer-mounted coupling device, determining, by the autonomous backing module, commands to components of the vehicle to autonomously control the vehicle to maneuver along the determined path to the target, and transmitting, by the autonomous backing module, the commands to the components of the vehicle (e.g., a braking control module, a steering control module, and/or a torque request module). Suitably configured vehicles are also described.

Disclosed is an autonomous driving device in which a threshold value for switching to manual driving which is used for switching a driving state from autonomous driving to manual driving with respect to degree to which a steering operation is carried out by a driver is calculated to be a greater value by a calculation unit when the direction of the steering operation is predicted to be a direction close to an obstacle than a threshold value when the direction of the steering operation is predicted to be a direction away from the obstacle or a threshold value when no obstacle is detected.