A driver assistance method and a driver assistance apparatus are provided, which may be applied to the field of autonomous driving or intelligent driving. The driver assistance method includes: determining that a driver is in an abnormal state; determining that a first operation performed by the driver on a first terminal is an abnormal operation; and performing first processing, where the first processing includes outputting indication information and/or control information, and the indication information or the control information indicates a second operation performed on the first terminal, or the first processing includes controlling the first terminal to perform the second operation.

Provided is an information processing device including: a first acquisition unit configured to acquire a task; a second acquisition unit configured to acquire a processing time of the task; a third acquisition unit configured to acquire a wirelessly communicable period with an external communication device; and a communication control unit configured to control, based on the processing time and the wirelessly communicable period, a wireless communication unit to transmit request information to the external communication device, the request information requesting to process at least a part of the task, in which the communication control unit is configured to control the wireless communication unit to perform direct communication with the external communication device.

Apparatus for estimating a grip factor of at least one wheel comprising: a control unit configured to process a current slip angle of said wheel; a storage unit, within which, in a consultation table, a plurality of grip curves correlating a plurality of values of a steering parameter comprising the rack force with a plurality of values of the slip angle are recorded; along a same curve, the value of the grip factor remains unchanged; wherein the control unit is configured to cyclically estimate at least one raw value of the grip factor of said at least one wheel based on the position of a current condition within the consultation table, as a function of the current slip angle and of the current rack force.

Apparatus for estimating a grip factor of at least one wheel comprising: a control unit configured to process a current slip angle of said wheel; a storage unit, within which, in a consultation table, a plurality of grip curves correlating a plurality of values of a steering parameter comprising the rack force with a plurality of values of the slip angle are recorded; along a same curve, the value of the grip factor remains unchanged; wherein the control unit is configured to cyclically estimate at least one raw value of the grip factor of said at least one wheel based on the position of a current condition within the consultation table, as a function of the current slip angle and of the current rack force.

In one aspect, an operating method of an intelligence vehicle driving control system is provided that comprises: a collecting step of collecting big data including a wheel torque and a speed for every vehicle type and traffic information; a torque calculating step of learning the big data using a predetermined machine learning model and inputs a specific desired speed profile to the machine learning model to calculate a motor torque of a driving vehicle; and an optimal speed profile deriving step of calculating an energy consumption required to generate the calculated motor torque using a predetermined dynamic programming method and a reverse vehicle dynamic model and deriving an optimal speed profile in which the energy consumption is minimized.

A cooling mechanism apparatus, system, and method for adaptively controlling heat of a vehicle processor, includes a processor configured to control deactivation or activation of an application driving the in-vehicle controller depending on grades of a predetermined functional safety level of the application and to determine an order of the deactivation or the activation of the application when heat is generated in the controller.

Methods and systems are provided for controlling an autonomous vehicle. In one embodiment, a method includes: identifying, by a processor, at least one constraint on a longitudinal dimension of an upcoming road; defining, by the processor, constraint activation logic based on a type of the at least one constraint; performing, by the processor, the constraint activation logic to determine a state of the constraint to be at least one of active and inactive; when the state of the constraint is active, validating, by the processor, a motion plan of the autonomous vehicle based on the constraint; and selectively controlling the autonomous vehicle based on the validating of the motion plan.

Systems and methods for image-based perception. The methods comprise: obtaining, by a computing device, images captured by a plurality of cameras with overlapping fields of view; generating, by the computing device, spatial feature maps indicating locations of features in the images; defining, by the computing device, predicted cuboids at each location of an object in the images based on the spatial feature maps; and assigning, by the computing device, at least two cuboids of said predicted cuboids to a given object when predictions from images captured by separate cameras of the plurality of cameras should be associated with a same detected object.

Systems and methods for image-based perception. The methods comprise: obtaining, by a computing device, images captured by a plurality of cameras with overlapping fields of view; generating, by the computing device, spatial feature maps indicating locations of features in the images; defining, by the computing device, predicted cuboids at each location of an object in the images based on the spatial feature maps; and assigning, by the computing device, at least two cuboids of said predicted cuboids to a given object when predictions from images captured by separate cameras of the plurality of cameras should be associated with a same detected object.

An apparatus for displaying a virtual lane may include: a processor to generate the virtual lane by converting lane information of a preceding vehicle into lane information viewed in a viewpoint of a host vehicle, in platooning, and a display to display the virtual lane.