Disclosed is a simulation learning-based drowsy driving simulation platform system for detecting careless driving in conjunction with deep learning, the simulation learning-based drowsy driving simulation platform system comprising: a drive state warning device configured to determine a driver's careless driving from a captured image, determine a driver's careless driving determination level, and output the determined level; a smart cruise control interworking part configured to transmit the driver's careless driving determination level outputted from the drive state warning device; and a smart cruise control processing part configured to control a vehicle according to the driver's careless driving determination level transmitted by the smart cruise control interworking part, during a smart cruise control operation.

A vehicle control apparatus starts driving trouble tackling control designed to decelerate and stop an own vehicle when it is determined that a driver is in a driving trouble state where the driver has trouble driving the own vehicle, then start a deceleration process at a predetermined timing as a process of driving trouble tackling control, and then start a hazard lighting process at a predetermined timing as another process of driving trouble tackling control. The vehicle control apparatus stops driving trouble tackling control when a hazard switch is operated during the performance of the hazard lighting process, and starts the hazard lighting process without stopping the driving trouble tackling control when the hazard switch is operated between a timing when it is determined that the driver is in the driving trouble state and a timing when the hazard lighting process is started.

A system and method for monitoring a driver's operation of a vehicle and automatically providing a lesson to a driver based on the driver's operation are provided. Input data generated by an onboard vehicle computing system specifying actions taken by the driver while operating the vehicle are received. Based on the input data, a determination is made whether a driving event has occurred that requires the lesson to be output to the driver. The driving event is analyzed based on threshold data stored in the memory, and based on the results of the analysis of the driving event one or more lessons are automatically output to the driver. Additionally, the driver's completion of the lesson can be monitored, and subsequent instances of the driver's operation of the vehicle may include controlling movement of the vehicle based on the results of the analysis of the driving event.

A vehicular driving assist system includes an electronic control unit (ECU). When the equipped vehicle is driving in the autonomous mode, driving of the vehicle is controlled by the ECU without human intervention. When the vehicle is being driven in a non-autonomous mode, a particular driver at least partially drives the vehicle. The vehicular driving assist system learns a driving style of the particular driver and, when the vehicle is being driven in the non-autonomous mode by the particular driver, the system restricts learning of the driving style of the particular driver responsive to determination by the system that the particular driver is (i) driving the vehicle erratically and/or (ii) performing an illegal driving maneuver. When the vehicle is driving in the autonomous mode, and responsive to the particular driver being present in the vehicle, the vehicle drives in accordance with the learned driving style of the particular driver.

A drive mode switch control device controls switching of driving between a driver and an autonomous driving function. The drive mode switch control device includes an operation information acquisition unit, a drive state switch unit, an attitude determination unit, and an approved target setting unit. The operation information acquisition unit acquires an operation information item associated with the driving operation input to at least one of a plurality of operation targets. The drive state switch unit executes an override that switches from an autonomous driving state to another driving state. The attitude determination unit acquires a plurality of detection information items related to driving attitudes of the driver, and determine whether each of the plurality of detection information items is appropriate for the driving operation. The approved target setting unit sets an approved operation target or a disapproved operation target to each of the plurality of operation targets.

A driver assistance method for a vehicle includes the steps of establishing an energy prediction for a route on the basis of an anticipated driver behavior, determining a driving behavior which is optimized with regard to the energy prediction, and outputting an action recommendation on the basis of the optimized driving behavior.

An onboard device estimates a traveling state of a vehicle that may be influenced by the psychological state of a driver, based on an utterance of the driver without the use of various sensors, and includes: a voice collection unit for collecting a driver's voice; a traveling state collection unit for collecting traveling state information representing a traveling state of a vehicle; a database generation unit for generating a database by associating voice information corresponding to the collected voice with the collected traveling state information; a learning unit for learning an estimation model, with pairs including the voice information and the traveling state information recorded in the generated database being used as learning data; and an estimation unit for estimating the traveling state of the vehicle that may be influenced by a psychological state of the driver by using the estimation model, based on an utterance of the driver.

A processing platform may obtain sensor data associated with a vehicle and manual input data associated with the vehicle. The processing platform may determine, based on the sensor data, automated control information. The processing platform may determine, based on the sensor data and the manual input data, a parameter associated with the vehicle. The processing platform may determine, based on the automated control information, a control rating associated with the parameter. The processing platform may determine whether the control rating satisfies a threshold for a period of time. The processing platform may cause, based on determining that the control rating satisfies the threshold for the period of time, at least one action to be performed.

The present invention relates to a method for operating a driver model for controlling a vehicle. Acc.sup.Vehicle speed (kph) ntion, a vehicle .sub.Accelerator pedal [%] cle is selected and activated by the driver model from a number of vehicle statuses (301, 303, 305, 307, 309) by comparing a current status of the vehicle with at least one selection condition specified for a particular vehicle status, the number of vehicle statuses (301, 303, 305, 307, 309) comprising at least a first vehicle status (301, 303, 305, 307, 309) and a second vehicle status (301, 303, 305, 307, 309). Furthermore, the driver model, on activation of a particular vehicle status (301, 303, 305, 307, 309), enables at least one control command assigned to the vehicle status (301, 303, 305, 307, 309) for modifying a setting of the vehicle, wherein a plurality of changes are made by the driver model between a currently activated vehicle status (301, 303, 305, 307, 309) and at least one further vehicle status (301, 303, 305, 307, 309) and, for at least one change of the plurality of changes, a coasting status (303), in which the vehicle is coasting, is activated before any activation of the further vehicle status (301, 303, 305, 307, 309) by the driver model.

A control unit for a hybrid drive of a vehicle is provided. The hybrid drive includes an internal combustion engine and an electric machine. The hybrid drive is designed in such a way that the electric machine is used for providing a drive torque of the vehicle and for starting the internal combustion engine. The control unit is configured to predict a start time, at which at least a part of the total power of the electric machine is available for a starting process of the internal combustion engine. Furthermore, the control unit is configured to start the internal combustion engine at the predicted start time by way of the electric machine.