The invention relates to a method for adjusting fully automatic vehicle guidance functions, which are realized by means of a vehicle system of a motor vehicle, during the operation of the motor vehicles in a predefined navigation environment. A stationary infrastructure device that communicates with the motor vehicles is associated with the navigation environment. Function limits of each vehicle guidance function are defined by means of limit operation parameters of the vehicle guidance function. Current traffic situation information describing dynamic objects in the navigation environment is determined by the infrastructure device by means of environment sensors of the navigation environment. The current traffic situation information is used, together with a digital map describing stationary objects and properties of the navigation environment, to determine at least one piece of risk information for each motor vehicle.

A method for performing automatic valet parking, which includes selecting a road scenario applicable to a roadway; notifying a driver to release manual control elements of a motor vehicle and to leave the motor vehicle; checking whether the control elements have been released and the driver has left the motor vehicle and, in this case, entering an EXPLORE mode in which the motor vehicle is slowly driven autonomously and searches for a free car space or a parking space using the vehicle's own environmental sensors, before the motor vehicle is placed in a parking position; and then to change from the EXPLORE mode to a PARKING mode in which the motor vehicle is parked in the car space or in the parking space from the parking position by means of the longitudinal and lateral controllers and using the environmental data previously obtained from the environmental sensors in the EXPLORE mode.

A method of operating a vehicle, such as an autonomous vehicle, includes the steps of receiving a message from roadside infrastructure via an electronic receiver and providing, by a computer system in communication with said electronic receiver, instructions based on the message to automatically implement countermeasure behavior by a vehicle system. Additionally or alternatively, the method may include the steps of receiving a message from another vehicle via an electronic receiver and providing, by a computer system in communication with said electronic receiver, instructions based on the message to automatically implement countermeasure behavior by a vehicle system.

Systems and methods for situational behavior of an autonomous vehicle are disclosed. In one aspect, an autonomous vehicle includes at least one perception sensor configured to generate perception data indicative of at least one other vehicle on a roadway, a non-transitory computer readable medium, and a processor. The processor is configured to determine that the other vehicle is violating one or more rules of the roadway based on the perception data, tag the other vehicle as a non-compliant driver, and modify control of the autonomous vehicle in response to tagging the other vehicle as a non-compliant driver.

An automated vehicle control distributed network node, that includes at least two modems for communicating with two neighboring roadside nodes on the same side of the roadway; at least one antenna for communicating with vehicles via a wireless connection; pattern recognition processing operative to detect patterns using image data from a plurality of high speed, high resolution video cameras that include night vision; vehicle prediction processing, operatively coupled to the pattern recognition processing, operative to predict vehicle location, velocity and direction using the pattern recognition processing; and a vehicle controller, operatively coupled to the vehicle prediction processing to receive vehicle prediction data, and to the at least one antenna, operative to send acceleration, deceleration and steering control signals to a plurality of vehicles in response to vehicle prediction data received from the vehicle prediction processing.

A vehicle control device includes a recognizer that is configured to recognize a peripheral situation of a vehicle and a driving controller that is configured to execute automated driving for controlling a speed and steering of the vehicle on the basis of a recognition result of the recognizer. The recognizer is configured to recognize a real-time environment including a situation of a nearby vehicle or a situation of a nearby road on which the vehicle travels, and the driving controller is configured to shunt the vehicle to a shunt location to suspend the automated driving in a case where the real-time environment corresponds to a predetermined condition, and resume the automated driving in a case where the predetermined condition is resolved after the shunt.

An automated vehicle control distributed network node, that includes at least two modems for communicating with two neighboring roadside nodes on the same side of the roadway; at least one antenna for communicating with vehicles via a wireless connection; pattern recognition processing operative to detect patterns using image data from a plurality of high speed, high resolution video cameras that include night vision; vehicle prediction processing, operatively coupled to the pattern recognition processing, operative to predict vehicle location, velocity and direction using the pattern recognition processing; and a vehicle controller, operatively coupled to the vehicle prediction processing to receive vehicle prediction data, and to the at least one antenna, operative to send acceleration, deceleration and steering control signals to a plurality of vehicles in response to vehicle prediction data received from the vehicle prediction processing.

A method of assisting a motor vehicle driven in an at least semiautomated manner, for passing through a tunnel. The method includes: receiving surrounding-area signals that represent an area, which surrounds the motor vehicle, and of which at least a part includes a tunnel; receiving safety condition signals, which represent at least one safety condition that must be satisfied, so that the motor vehicle may be assisted from outside of the motor vehicle while passing through the tunnel; checking if the at least one safety condition is satisfied; generating data signals, which represent data suitable for assisted traversal of the tunnel by the motor vehicle, based on the surrounding-area signals, and based on a result of whether the at least one safety condition is satisfied; outputting the generated data signals. A device, a computer program, and a machine-readable storage medium are also described.

A travel control system for a vehicle includes a vehicle speed calculator, a mode continuation determiner, and a mode continuing unit. The vehicle speed calculator evaluates a level of worsening of a traveling environment and calculates a first vehicle speed on the basis of the level of the worsening of the traveling environment. The mode continuation determiner determines whether it is possible to continue with driving assist control in the second driving assist mode by comparing a second vehicle speed in the second driving assist mode with the first vehicle speed. When it is not possible to continue with the driving assist control in the second driving assist mode, the mode continuing unit lowers the second vehicle speed in the second driving assist mode to the first vehicle speed to allow the driving assist control in the second driving assist mode to continue.

A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.