A computer includes a processor and a memory, the memory storing instructions executable by the processor to determine a first bounding box for a road sign in an image, identify a second bounding box for a physical member, the second bounding box for the physical member extending from the first bounding box for the road sign, and upon identifying the second bounding box for the physical member, actuate one or more vehicle components.

The present invention provides a vehicle control apparatus for controlling traveling of a vehicle, the apparatus comprising: a stop control unit configured to move the vehicle in a vehicle width direction and stop the vehicle in a traveling state; a notification unit configured to make a notification of the stop of the vehicle; and a change unit configured to change a notification method by the notification unit in accordance with a stop mode of the vehicle stopped by the stop control unit.

In various examples, systems and methods are disclosed for weighting one or more optional paths based on obstacle avoidance or other safety considerations. In some embodiments, the obstacle avoidance considerations may be computed using a comparison of trajectories representative of safety procedures at present and future projected time steps of an ego-vehicle and other actors to ensure that each actor is capable of implementing their respective safety procedure while avoiding collisions at any point along the trajectory. This comparison may include filtering out a path(s) of an actor at a time step(s)—e.g., using a one-dimensional lookup—based on spatial relationships between the actor and the ego-vehicle at the time step(s). Where a particular path—or point along the path—does not satisfy a collision-free standard, the path may be penalized more negatively with respect to the obstacle avoidance considerations, or may be removed from consideration as a potential path.

A control device of a mobile object includes a control unit configured to restrict, based on information specifying a suppression area where occurrence of a communication delay is to be suppressed, the mobile object from performing an operation that induces a communication delay in the suppression area.

In the vehicle traveling control device, a host vehicle location specification unit specifies a host vehicle location on a map. A first peripheral information detector detects a location of a planimetric feature or characteristics of a road in a periphery of the host vehicle on the basis of map data and the host vehicle location on the map specified by the host vehicle location specification unit. A second peripheral information detector detects a location of a planimetric feature or characteristics of a road in the periphery of the host vehicle on the basis of information acquired by a camera, a sensor, or a road-vehicle communication device mounted on the host vehicle. When the detection result from the first peripheral information detector and the detection result from the second peripheral information detector do not coincide, an automatic driving restriction unit restricts performance of automatic driving of the host vehicle.

A safety system can include a self-driving vehicle, a temperature detection system attached to the self-driving vehicle, and a vehicle management system configured to autonomously drive the self-driving vehicle. The self-driving vehicle can include cameras, lidar, and radar to detect objects on the road. The vehicle management system can be configured to respond to the temperature detection system detecting elevated temperatures.

An autonomous driving system for vehicles includes: an autonomous driving controller for controlling autonomous driving of a host vehicle based on information of nearby vehicles and requesting warning and handover upon determining that a failure in autonomous driving of nearby vehicles has occurred; a communication controller for requesting the warning and handover; selecting an emergency target vehicle and requesting a driving mode of following the emergency target vehicle upon receiving autonomous driving failure information; a human-machine interface device for outputting warning and handover information in response to the request of the autonomous driving controller and the communication controller; and a host vehicle driving controller for controlling driving of the host vehicle in response to the request of the autonomous driving controller and the communication controller.

A method for controlling autonomous driving in an autonomous vehicle includes: determining whether a human driver is in a forward gaze state under an autonomous driving mode, setting a first steering wheel torque threshold and a first torque holding time, based on a result of determining whether the human driver is in the forward gaze state, determining whether human driver intervention has occurred, based on the first steering wheel torque threshold and the first torque holding time, and switching the autonomous driving mode to a manual driving mode when the human driver intervention has occurred.

Process scheduling based on data arrival in an autonomous vehicle, including: receiving, by a node and from one or more other nodes of a distributed automation computing system, a plurality of portions of data; generating a process schedule by scheduling, for each portion of data of the plurality of portions of data, a process for processing a corresponding portion of data within a time window, wherein an ordering of the process schedule corresponds to an order of arrival of the plurality of portions of data; and executing, during the time window, the process schedule.

A system and method for controlling one or more vehicles with one or more controlled vehicles may include one or more processors and a memory in communication with the one or more processors. The memory may include one or more modules that cause the one or more modules to obtain a state of an environment having a universe of vehicles operating therein, identify one or more anomaly vehicles from the universe of vehicles operating in the environment, select one more actions to control a plurality of controlled vehicles to control the operation of one or more anomaly vehicles and direct the plurality of controlled vehicles execute the one or more actions. The selecting of one or more actions may be performed by utilizing a reinforcement-learning trained algorithm.