An autonomous vehicle may include a processor configured to transmit vehicle data for remote control of the autonomous vehicle to a control system when the remote control of the autonomous vehicle is required, and when receiving a remote control command for the remote control from the control system, to generate and follow a path based on the received remote control command.

An autonomous vehicle, a control system for remotely controlling the same, and a method thereof may include an autonomous driving control apparatus including a processor for determining whether remote control of the autonomous vehicle is required according to at least one of occurrence of failure of the vehicle during autonomous driving thereof, occurrence of an accident, a region where the autonomous driving is not possible, reliability of positioning data of the vehicle, a stopping time of the vehicle, or a response point of a hand signal, and for requesting the remote control to a control system when the remote control of the vehicle is required.

According to one embodiment, a method, computer system, and computer program product for using mobile devices for anomaly detection in a vehicle. The present invention may include a computer receives sensor data from at least one mobile device associated with the vehicle, where the mobile device having one or more sensors. The computer analyzes data from the one or more sensors to identify an anomaly associated with the vehicle. The computer identifies a message associated with the anomaly. The computer determines an urgency value of the message based on the anomaly. The computer transfers the message with the urgency value to the vehicle and causes the vehicle to notify the message using a vehicle notification device.

A method for operating a motor vehicle having a camera device that records the area ahead of the vehicle and an associated control device for evaluating images taken by the camera device, wherein the control device evaluates the images in order to detect at least one hand gesture performed by a person shown in the images, wherein, when a hand motion describing a calling gesture that indicates a stop request is detected, in the case of a self-driving motor vehicle, the motor vehicle is controlled to stop in the vicinity of the person, or in the case of a non-self-driving motor vehicle, the driver of the motor vehicle is given a signal indicating the stop request.

Methods, devices and a computer-readable medium comprising instructions for determining applicable traffic regulations for a motor vehicle are provided. In some embodiments, the position and direction of movement of the motor vehicle are determined. The position and direction of movement of the motor vehicle are then transmitted to a back end by a transmission apparatus of the motor vehicle. In response to the information transmitted to the back end, information concerning traffic regulations applicable to the position of the motor vehicle is received by the transmission apparatus. The transmission of the position and direction of movement of the motor vehicle to the back end is carried out in a cyclical manner or in accordance with information concerning the validity of the traffic regulations, which is included in the information concerning the traffic regulations applicable at the position of the motor vehicle.

The present invention relates to a method of cooperatively coordinating future driving maneuvers of a vehicle with fellow maneuvers of at least one fellow vehicle, wherein trajectories for the vehicle are rated with an effort value each, trajectories and fellow trajectories of the fellow vehicle are combined into tuples, the trajectory and the associated effort value of a collision-free tuple are selected as reference trajectory and reference effort value, trajectories with a lower effort value than the reference effort value are classified as demand trajectories, trajectories with higher effort value than the reference effort value are classified as alternative trajectories, and a data packet having a trajectory set consisting of the reference trajectory and the associated reference effort value as well as at least one trajectory from a group comprising the demand trajectories and the alternative trajectories as well as the respective effort values is transmitted to the fellow vehicle.

An absorber device for electromagnetic sensor systems has at least one aperture. Each aperture is able to be opened and closed by an aperture closure. The absorber device is designed in such a way that when the aperture is open, electromagnetic waves incoming through the aperture do not then leave the absorber device, and when the aperture is closed, electromagnetic waves impinging on the aperture are reflected.

A traffic control system for an automatic driving vehicle includes a vehicle control system and a management and control system. The management and control system collects snow removal information by a snow removal information collector, and calculates traveling environment information of the snow-removed area by a snow-removed area traveling environment information calculator. The vehicle control system performs, by a first automatic driving controller, first automatic driving control that is made redundant by a control system based on map information and location information and by a control system based on external environment recognition information. The vehicle control system performs, by a second automatic driving controller, second automatic driving control that is made redundant by a control system based on the location information and the map information corrected using the traveling environment information of the snow-removed area and by a control system based on the external environment recognition information.

Among other things, techniques are described for predicting how an agent (e.g., a vehicle, bicycle, pedestrian, etc.) will move in an environment based on prior movement, the road network, the surrounding objects and/or other relevant environmental factors. One trajectory prediction technique involves generating a probability map for an agent's movement. Another trajectory prediction technique involves generating a trajectory lattice, for an agent's movement. In addition, a different trajectory prediction technique involves multi-modal regression where a classifier (e.g., a neural network) is trained to classify the probability of a number of (learned) modes such that each model produces a trajectory based on the current input.

Provided herein is a system of a vehicle that comprises one or more sensors, one or more processors, and memory storing instructions that, when executed by the one or more processors, causes the system to perform: selecting a trajectory along a route of the vehicle; predicting a trajectory of another object along the route; adjusting the selected trajectory based on a predicted change, in response to adjusting the selected trajectory, to the predicted trajectory of the another object, the predicted change to the predicted trajectory of the another object being stored in a model; determining an actual change, in response to adjusting the selected trajectory, to a trajectory of the another object, in response to an interaction between the vehicle and the another object; updating the model based on the determined actual change to the trajectory of the another object; and selecting a future trajectory based on the updated model.