In the present invention, it is possible to accurately predict, at an earlier timing, that a pedestrian will perform constant speed movement or a route change that is more complex than the constant speed movement. Provided is a travel control device that can accurately determine a change in the route of the pedestrian according to a change in the pedestrian's posture and, in particular, a change in the orientation of the body or a change in an inverted angle, and that can appropriately control the travel of the vehicle.

The present disclosure relates to a driving control apparatus, a driving control method, and a program that can resolve a conflict between a deliberate action and a reflex action during determination of a next action in autonomous driving.

During autonomous driving, a reflex action is determined as a simplified action on the basis of detection results detected by a variety of sensors provided in a vehicle, and a deliberate action ranked higher than a reflex action is determined through elaborate processing. A plurality of resolution modes are made available to deal with a possible conflict between the reflex action and the deliberate action, and by which of the resolution modes the conflict is resolved is specified in advance so that the conflict is resolved by the specified resolution mode. The present disclosure is applicable to motor vehicles that drive autonomously.

An apparatus for controlling virtual engine sound, which includes a sensor unit configured to detect a position of a pedestrian in front of a vehicle, a speaker unit configured to output a virtual engine sound in all directions of the vehicle or output a sound guidance message only to the position of the pedestrian, and a control unit configured to cause the speaker unit to operate in either a virtual engine sound system (VESS) mode or a pedestrian communication mode in which the sound guidance message is transmitted only to the pedestrian's position, by changing a sound focal point output through the speaker unit.

A method of transferring vehicle communication content. The apparatus includes a surrounding-environment detection unit configured to detect a surrounding-environment information of a vehicle, a communication content transfer unit provided on at least one of a front side, a rear side, and a lateral side of the vehicle and configured to output sound or light; and a controller configured to recognize an object on the basis of the surrounding-environment information of the vehicle, to rotate the communication content transfer unit in a direction toward the object, depending on whether or not communication content needs to be transferred to the recognized object, and to output the communication content containing warning information or guide information through the communication content transfer unit.

An information display device includes a surrounding environment detector, a vehicle information acquirer, a predictor, an avoidance path provider, and an information display. The surrounding environment detector detects position relevant information related to a position of at least a surrounding object in a surrounding environment of a vehicle. The vehicle information acquirer detects vehicle information including a speed and a steering direction of the vehicle. The predictor predicts a contact of the vehicle with the surrounding object, based on the position relevant information and the vehicle information. When the predictor has predicted that there is a possibility of the contact of the vehicle with the surrounding object, the avoidance path provider assumes an avoidance path for avoiding the contact, based on the position relevant information and the vehicle information. The information display displays the avoidance path.

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.

This invention provides a secure self-driving system or drive-assisting system. A drive control system of the present invention has an image recognition unit for detecting the peripheral environment of a vehicle and a drive control apparatus that controls driving of the vehicle, characterized by having a peripheral environment storage unit for storing the peripheral environment of the vehicle and by changing a mode of drive control performed by the drive control apparatus on the basis of a detection performance status of the image recognition unit obtained on the basis of information about the peripheral environment stored in the peripheral environment storage unit and information detected by the image recognition unit.

Systems, methods and apparatus may be configured to implement automatic semantic classification of a detected object(s) disposed in a region of an environment external to an autonomous vehicle. The automatic semantic classification may include analyzing over a time period, patterns in a predicted behavior of the detected object(s) to infer a semantic classification of the detected object(s). Analysis may include processing of sensor data from the autonomous vehicle to generate heat maps indicative of a location of the detected object(s) in the region during the time period. Probabilistic statistical analysis may be applied to the sensor data to determine a confidence level in the inferred semantic classification. The inferred semantic classification may be applied to the detected object(s) when the confidence level exceeds a predetermined threshold value (e.g., greater than 50%).

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.

A vehicle sensing system is for being disposed on a vehicle. The vehicle sensing system includes a calculating unit, which includes a turning calculating module and a vehicle dimension dataset. The vehicle dimension dataset includes at least one of a wheelbase, a vehicle width, a front overhang and a rear overhang of the vehicle. The calculating unit is configured to receive a turning dataset of the vehicle. Based on the turning calculating module, the calculating unit is configured to determine an inner front wheel and an inner rear wheel. The calculating unit is configured to further determine a turning alarm zone in accordance with the vehicle dimension dataset and the turning dataset. The turning alarm zone is dependent on at least one of time and the turning dataset.