An object recognition apparatus includes at least one processor and at least one memory communicably coupled to the processor. The processor sets one or more object presence regions in each of which an object is likely to be present, on the basis of observation data of a distance sensor. The processor estimates an attribute of the object that is likely to be present in each of the one or more object presence regions. The processor sets, on the basis of the attribute of the object, a level of processing load to be spent on object recognition processing to be executed for each of the one or more object presence regions by using at least image data generated by an imaging device. The processor performs, for each of the one or more object presence regions, the object recognition processing corresponding to the set level of the processing load.

A method for deactivating an automated driving mode of a vehicle involves automatically terminating the automated driving mode if, due to a manual steering torque acting on the steering wheel of the vehicle, a system steering torque generated by a control system of an assistance system for automated driving mode in terms of amount is exceeded by a predetermined first value if at least one hand of a vehicle user is detected on the steering wheel of the vehicle, is exceeded by a predetermined second value if neither of the vehicle user's hands is detected on the steering wheel, or is exceeded by a predetermined third value if it is determined that the vehicle user is distracted from the driving situation, or if it is determined that there is a lateral collision risk for the vehicle and the manual steering torque of the vehicle user is acting in the direction of the collision risk.

A method includes receiving first data from one or more vehicles in a geographic area, the first data indicating operation of an active safety system by at least one of the one or more vehicles, receiving second data indicating driving performance of the one or more vehicles, determining whether the driving performance of the one or more vehicles in the geographic area is improved or diminished by the use of the active safety system based on the first data and the second data, and transmitting a signal to a vehicle approaching the geographic area to cause the vehicle approaching the geographic area to activate or deactivate the active safety system based on the determination.

A method includes receiving first data from one or more vehicles in a geographic area, the first data indicating operation of an active safety system by at least one of the one or more vehicles, receiving second data indicating driving performance of the one or more vehicles, determining whether the driving performance of the one or more vehicles in the geographic area is improved or diminished by the use of the active safety system based on the first data and the second data, and transmitting a signal to a vehicle approaching the geographic area to cause the vehicle approaching the geographic area to activate or deactivate the active safety system based on the determination.

One or more outputs from a planning module of an ADV are received. Data of a driving environment of the ADV is received. A performance of the planning module is evaluated by determining a score of the performance of the planning module based on the data of the driving environment and the one or more outputs from the planning module. Whether the one or more outputs from the planning module violates at least one of a set of safety rules is determined. The score is determined being larger than a predetermined threshold in response to determining that the one or more outputs from the planning module violate at least one of the set of safety rules. Otherwise, the score is determined based on a machine learning model. The planning module is modified by tuning a set of parameters of the planning module based on the score.

An example operation includes one or more of determining a level of risk of a collision of a transport, wherein the level of risk is related to an occupant of the transport and an environment of the transport, accumulating an amount of data based on the level of risk, preparing the accumulated data for sending to one or more recipients when the level of risk exceeds a risk threshold, and sending the prepared data to the one or more recipients when the collision occurs.

A vehicle is provided that includes a cruise control deactivation system. The system includes a cruise control system, and a user control that, when activated, commands deactivation of the cruise control system. The system also includes a processor configured to permit or override the commanded deactivation of the cruise control system while the vehicle is moving, based on at least one criterion. Criteria may include whether or not a first sensor detects a foot of a driver of the vehicle on an accelerator pedal of the vehicle, and whether or not a first computation indicates that the deactivation of the cruise control system will cause a collision with a second vehicle located behind the vehicle.

Aspects of the disclosure provide for a method of controlling an autonomous vehicle in an autonomous driving mode. For instance, a predicted future trajectory for an object detected in a driving environment of the autonomous vehicle may be received. A routing intent for a planned trajectory for the autonomous vehicle may be received. The predicted future trajectory and the routing intent intersect with one another may be determined. When the predicted future trajectory and the routing intent are determined to intersect with one another, a time gap may be applied to a predicted future state of the object defined in the predicted future trajectory. A planned trajectory may be determined for the autonomous vehicle based on the applied time gap. The autonomous vehicle may be controlled in the autonomous driving mode based on the planned trajectory.

A vehicle may include a primary system for generating data to control the vehicle and a secondary system that validates the data and/or other data to avoid collisions. For example, the primary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and generate a trajectory for the vehicle. The secondary system may localize the vehicle, detect an object around the vehicle, predict an object trajectory, and determine a likelihood of a collision of the vehicle with the object. A simulation system may generate simulation scenarios that test aspects of the primary system and the secondary system. Simulation scenarios may include simulated vehicle control data that causes the primary system to generate a driving trajectory and simulated object data that causes the secondary system to determine a collision.

An example operation includes one or more of determining a characteristic of an occupant in a transport and a current driving environment of the transport, wherein the characteristic includes a position of the occupant, determining that the current driving environment will lead to a collision of the transport, and based on a predicted result of the collision, sending a predicted state of the occupant based on the position, to an emergency service node.