A vehicle control device includes a pedestrian recognizer configured to recognize a pedestrian present in the periphery of a vehicle, and a driving controller configured to decelerate at least the vehicle irrespective of an occupant's operation of the vehicle in accordance with the vehicle and a pedestrian approaching each other, and delays a timing at which the vehicle is stopped in a case where a plurality of pedestrians recognized by the pedestrian recognizer are present on a traveling route of the vehicle.

With conventional automatic drive control, no consideration is given to whether the driver is in a condition to be able to drive the vehicle properly when automatic driving is cancelled. Accordingly, an automatic drive control device is switchable between a manual driving mode in which driving operation by the driver of the vehicle is required, and an automatic driving mode in which driving operation by the driver of the vehicle is not required. The device is equipped with: a surrounding conditions recognition unit for recognizing surrounding conditions of the vehicle; an information notification unit for notifying the driver of the vehicle; and an automatic drive control unit for carrying out control of the vehicle in automatic driving mode, and controlling the information notification unit in such a way as to alert the driver of the vehicle on the basis of the surrounding conditions recognized by the surrounding conditions recognition unit.

A processing unit with at least one image that relates to a scene external to a vehicle, processes the image to extract low level features. A low level feature is defined such that an object in the scene cannot be characterized on the basis of at least one low level feature in a single image of the at least one scene. The processing unit determines if at least a part of an object is present in a part of the scene, the determination comprises an analysis of the low level features. An output unit outputs information that there is something present in the scene.

A control system for a vehicle may include a forward-facing camera to capture a plurality of images of a road ahead of the vehicle and a processing device. The processing device may be configured to: provide feedback to a vehicle operator of the vehicle to change lanes to a new lane, in which the vehicle is not already traveling, based on the ending of a current lane, the ending of the current lane indicated by a first traffic cone identified in the plurality of images; and update a distance from the vehicle to a second traffic cone, based on a position of the vehicle, the second traffic cone used to constrain vehicle operation to the new lane.

A vehicle speed control device 1 includes a lane detection unit 120 configured to detect a road outside line of a lane on which a host vehicle V is traveling, a target detection unit 121 configured to detect a target that is present outside the road outside line, and a speed control unit 123 configured to control a speed of the host vehicle V such that the host vehicle V passes a lateral side of the target at a speed lower than a speed of the host vehicle V when the target has been detected. After the host vehicle V has passed the lateral side of the target, the speed control unit 123 accelerates the host vehicle V up to the speed when the target has been detected.

Techniques are discussed for controlling a vehicle, such as an autonomous vehicle, based on occluded areas in an environment. An occluded area can represent areas where sensors of the vehicle are unable to sense portions of the environment due to obstruction by another object. An occlusion grid representing the occluded area can be stored as map data or can be dynamically generated. An occlusion grid can include occlusion fields, which represent discrete two- or three-dimensional areas of driveable environment. An occlusion field can indicate an occlusion state and an occupancy state, determined using LIDAR data and/or image data captured by the vehicle. An occupancy state of an occlusion field can be determined by ray casting LIDAR data or by projecting an occlusion field into segmented image data. The vehicle can be controlled to traverse the environment when a sufficient portion of the occlusion grid is visible and unoccupied.

A driving assistance apparatus can execute deceleration assistance of decelerating a host vehicle independently of an operation by a driver. The driving assistance apparatus is provided with: an acquirer configured to obtain surrounding information associated with a surrounding situation of the host vehicle; and a controller programmed to reduce a deceleration assistance amount associated with the deceleration assistance when execution of the deceleration assistance is released. The controller is programmed to quickly reduce the deceleration assistance amount when execution of the deceleration assistance is released, if a surrounding situation indicated by the obtained surrounding information is a first situation in which the host vehicle can be required to accelerate, in comparison with a second situation in which the host vehicle cannot be required to accelerate.

An occupant support adapted for use in a vehicle includes a seat bottom, a seat back, and a sensory system. The seat bottom is coupled to a floor of the vehicle. The seat back extends upwardly away from the seat bottom. The sensor system is configured to monitor for fatigue of an occupant of the occupant support.

Systems and methods for communicating autonomous vehicle operations are provided. In one example embodiment, a computer implemented method includes obtaining data associated with the autonomous vehicle. The method includes identifying an object within the surrounding environment of the autonomous vehicle or a planned vehicle motion action of the autonomous vehicle based at least in part on the data associated with the autonomous vehicle. The method includes determining an audible vehicle indication that is associated with the identified object or the planned vehicle motion action. The audible vehicle indication is indicative of a type of the object or a type of the planned vehicle motion. The method includes outputting, via one or more output devices onboard the autonomous vehicle, the audible vehicle indication.

In response to sensor data received from sensors mounted on an autonomous vehicle, a surrounding environment is perceived based on the sensor data. The surrounding environment includes multiple sub-environments. For each of the sub-environments, one of a plurality of driving scenario handlers associated with the sub-environment is identified, each driving scenario handler corresponding to one of a plurality of driving scenarios. The identified driving scenario handler is invoked to determine an individual driving condition within the corresponding sub-environment. An overall driving condition for the surrounding environment is determined based on the individual driving conditions provided by the identified driving scenario handlers. A route segment is planned based on the overall driving condition of the surrounding environment, the route segment being one of a plurality of route segments associated with a route. The autonomous vehicle is controlled and driven based on the planned route segment.