A method of distributing driving force of a four wheel drive (4WD) eco-friendly vehicle includes determining a first allowable range of driving force for each driving force based on determination of travel stability, determining a second allowable range of driving force for each driving wheel based on system limitations of at least one of the first driving source or the second driving source, determining a range of available driving force of the first driving wheel based on the first allowable range of driving force and the second allowable range of driving force, determining first target driving force of the first driving wheel in consideration of efficiency of the first driving source within the range of available driving force, and determining second target driving force of the second driving wheel based on the first target driving force and requested torque.

The steering controller calculates a target steering angle for causing the own vehicle to travel along the target course acquired by the traveling road information acquirer. The braking/driving force controller calculates a target yaw moment for correcting the positional displacement of the own vehicle from the target course. The control ratio setter sets a control ratio of cooperative control of steering control and yaw moment control based on the deviation amount of a lateral position of the own vehicle from the target course. The control ratio is set so that when the positional displacement of the own vehicle from the target course is relatively small, the ratio at which the steering control occupies is reduced, and the yaw moment control is dominant, and when the positional displacement of the own vehicle from the target course is relatively large, the ratio at which the steering control occupies is increased.

A vehicular driving assistance system includes a camera viewing exterior of a vehicle and capturing image data. The system, via processing captured image data as the vehicle travels along a current traffic lane, determines a current lateral position of the vehicle within the current traffic lane and determines a target lateral position of the vehicle within the current traffic lane. The system determines a steering command to guide the vehicle from the current lateral position to the target lateral position and determines a steering angle offset required to maintain the target lateral position within the current traffic lane and stores the determined steering angle offset in nonvolatile memory. After storing the determined steering angle offset and when the vehicle is traveling during a subsequent trip, the system determines a second target lateral position of the vehicle within the current traffic lane and applies the stored steering angle offset.

A control method is provided for controlling a lateral position of a motor vehicle. The control method includes calculating a sighting distance of a detector means embedded in the vehicle, calculating a first component of a steering angle setpoint of a steered wheels of the vehicle, and calculating a second component of the steering angle setpoint. The first component is an open loop component of a control system, while the second component is a closed loop component of the control system. The first component is weighted by a gain that is a decreasing function of the sighting distance.

A travel controller executes a first correction process on a request value when the vehicle is traveling on an uphill road, and executes a second correction process on the request value when the vehicle is traveling on a downhill road. The first correction process corrects the request value such that the traveling speed is higher than that in a case in which the first correction process is not executed. The second correction process corrects the request value such that the traveling speed is lower than that in a case in which the second correction process is not executed. If hard braking of the vehicle is requested during execution of the first correction process, the travel controller sets a correction amount of the request value to a lower value than that in a case in which hard braking of the vehicle is not requested.

Methods and systems for controlling a hydromechanical transmission are proposed. In one example, a control method for a hydrostatic unit of a hydromechanical variable transmission (HVT) is presented, comprising controlling the hydrostatic unit via a feedforward control architecture including a non-linear, multi-coefficient model, wherein the hydrostatic unit comprises a hydrostatic pump and a hydrostatic motor. A desired differential pressure of the hydrostatic unit or a desired hydraulic pump displacement may be used as inputs for the model, where the model's output is a pressure difference for a pump control piston coupled to a swash plate of the hydrostatic unit. Use of the non-linear model permits the hydrostatic unit to be controlled based on load, speed, and/or torque, thereby increasing the adaptability of the control system.

A method for inertia drive control is provided. The method includes performing advanced inertia drive control by an inertia drive controller. The controller detects a speed reduction event during road driving of a vehicle, lane division together with road type division for a road, and performs inertia drive control guide and the inertia drive control based on drive conditions of lane change and lane maintenance.

In various examples, an end-to-end perception evaluation system for autonomous and semi-autonomous machine applications may be implemented to evaluate how the accuracy or precision of outputs of machine learning models—such as deep neural networks (DNNs)—impact downstream performance of the machine when relied upon. For example, decisions computed by the system using ground truth output types may be compared to decisions computed by the system using the perception outputs. As a result, discrepancies in downstream decision making of the system between the ground truth information and the perception information may be evaluated to either aid in updating or retraining of the machine learning model or aid in generating more accurate or precise ground truth information.

Provided are a hybrid power vehicle range extender power following control method and system. The method includes: when a vehicle satisfies range extender power closed-loop control conditions, an actual charge-discharge power of a power battery and a charge-discharge power expectation value of the power battery are taken as control errors to adjust a total range extender electric power requirement, an engine torque requirement is calculated according to the total range extender electric power requirement, and an engine is controlled to perform the engine torque requirement; and when it is detected that a drive motor electric power suddenly changes and/or a load power suddenly changes, engine quick torque control is activated, and an engine quick torque requirement is taken as a feed-forward value of a generator speed setting controller to control a generator.

An embodiment method for controlling a hybrid vehicle includes driving a motor that starts an engine of the hybrid vehicle and controlling the motor to generate an engine starting torque to prevent a vibration of the engine, wherein the engine starting torque is generated by a feedforward control method. An embodiment device for controlling a hybrid vehicle includes a motor configured to start an engine of the hybrid vehicle, and a controller configured to drive the motor and control the motor to generate an engine starting torque to prevent a vibration of the engine, wherein the engine starting torque is generated by a feedforward control method.