Techniques are provided for operation of a vehicle in the event of an emergency. The techniques include receiving, using one or more sensors of a vehicle operating within an environment, sensor data representing an object located within the environment. The sensor data is used to identify whether the object is an emergency vehicle. Responsive to identifying that the object is an emergency vehicle, the sensor data is used to determine whether the emergency vehicle is operating in an emergency mode. Responsive to determining that the emergency vehicle is operating in the emergency mode, instructions representing an emergency operation for the vehicle are transmitted to a control module of the vehicle. The control module of the vehicle operates the vehicle in accordance with the emergency operation.

A device for controlling a vehicle at an intersection. The device variably sets a monitoring range of a vehicle sensor in accordance with a relationship between the progress paths of a host vehicle and a target vehicle at an intersection, or controls the host vehicle according to a collision avoidance control method in comparison with a predetermined scenario of a collision possibility of the host vehicle and the target vehicle at the intersection according to a scenario, thereby making it possible to prevent a collision at the intersection.

An autonomous driving control device is capable of starting an autonomous driving control without an operation of a driver and reducing a possibility that the driver can not start manual driving. An autonomous driving control is switched to manual driving when a determination section determines that the amount of operation by the driver is equal to or greater than a first threshold, before a predetermined time elapses since the autonomous driving control is automatically started. An autonomous driving control is switched to a manual driving when the determination section determines that the amount of operation by the driver is equal to or greater than a second threshold that is greater than the first threshold, after the predetermined time elapses.

A collision-avoidance system for use with an autonomous-capable vehicle can continuously receive image frames captured of the roadway to determine drivable space in a forward direction of the vehicle. The system can determine, for each image frame, whether individual regions of the image frame depict drivable space. The system can do so using machine-learned image recognition algorithms such as convolutional neural networks generated using extensive training data. Using such techniques, the system can label regions of the image frames as corresponding to drivable space or non-drivable space. By analyzing the labeled image frames, the system can determine whether the vehicle is likely to impact a region of non-drivable space. And, in response to such a determination, the system can generate control signals that override other control systems or human operator input to control the brakes, the steering, or other sub-systems of the vehicle to avoid the collision.

An automated driving system includes at least one electronic control unit configured to: recognize at least one obstacles around a vehicle, based on ambient surroundings of the vehicle; create a traveling plan of the vehicle, based on the ambient surroundings and a result of recognition of the at least one obstacles; control the vehicle using an actuator installed on the vehicle, based on the traveling plan; and perform, according to input from a user of the vehicle, overwriting operation to change the result of recognition of the at least one obstacles used for creation of the traveling plan.

A surroundings modeling device for a driver assistance system for a motor vehicle, includes a separating device configured to separate a total vehicle surroundings model into a static vehicle surroundings model based on a first look-ahead distance and a dynamic vehicle surroundings model based on a second look-ahead distance. A first real-time computing device is configured to calculate the dynamic vehicle surroundings model on the basis of the first look-ahead distance within a maximum response time. A second real-time computing device is configured to calculate the static vehicle surroundings model on the basis of the second look-ahead distance with a characteristic response time. A situation analysis device is configured to change the separation process on the basis of an analysis of the total vehicle surroundings model.

A vehicle control apparatus includes an electric control unit that performs a preceding vehicle trading control which makes an own vehicle trail a preceding vehicle as an adaptive cruise control, and performs a first brake control which automatically applies a first braking control to the own vehicle when a time-to-collision to a target object is less than a first threshold. In a case where a performing condition for the first brake control has been determined to be satisfied during a performance of the adaptive cruise control, the electric control unit continues performing the adaptive cruise control without performing the first brake control when a deceleration control by the adaptive cruise control is being performed, whereas stops performing the adaptive cruise control when the deceleration control by the adaptive cruise control is not being performed.

A passive infra-red guidance system and method for augmenting operation of an autonomous vehicle on a roadway includes at least one forward-looking infra-red imaging sensor mounted on the vehicle in operative communication with an image processor tied into the vehicle's operational system. The system determines the left and right edges of the roadway using thermal imaging, and then determines the centerline of the travel lane in which the vehicle is travelling based on the determined left and right edges of the roadway. The system then compares the determined centerline of the travel lane with the actual position of the vehicle and identifies any adjustment needed for the vehicle's position based on the comparison. The left and right edge determination may comprise identifying a difference between a thermal signature representative of the roadway and a thermal signature representative of a non-roadway portion that is located proximate to the roadway portion.

A method for generating a trigger signal for triggering at least one safety function of a motor vehicle. The method includes at least the following method steps: a) receiving respective signals from at least two pressure tube sensors, b) determining at least one collision parameter from the signals received according to step a), c) outputting the trigger signal for the at least one safety function as a function of the at least one collision parameter determined in step b).

A vehicle that operates in an autonomous driving mode and includes: an occupant sensing unit that is configured to sense an occupant inside the vehicle; and at least one processor configured to: determine, through the occupant sensing unit, whether the vehicle is occupied; and in a state in which the vehicle operates in the autonomous driving mode, control one or more in-vehicle devices based on a determination of whether the vehicle is occupied.