A vehicle control apparatus is capable of switching between an automatic driving control mode and a manual driving mode. The apparatus includes a driver state monitor and a vehicle controller. The driver state monitor monitors a gaze of a driver and a state of the driver. The vehicle controller controls steering and a drive system in the automatic driving control mode. In a case that the driver state monitor detects that the driver gazes at a device that is operated by the driver as a second task when the vehicle controller requests to the driver for a takeover from the automatic driving control mode to the manual driving mode, the vehicle controller stops a function of the device.

A first imaging section 201 captures an image of the vehicle exterior, and a second imaging section 202 captures an image of a driver. An image processing section 203 detects the driver's line of sight. An information acquisition section 205 acquires status information indicative of the surrounding environment. A driving parameter information generation section 206 generates driving parameter information by use of, as parameter information, the current position detected by a self-position detection section 204, travel control information generated by a travel control section, information indicative of the driver's line of sight, information indicative of the surrounding environment, and the like. A determination section 209 determines whether there is a danger on the basis of a difference between the driving parameter information indicative of the state of the vehicle or of its driver on one hand, and optimum parameter information indicative of an optimum state of the vehicle or of its driver in the current position and in the current surrounding environment on the other hand. An information presentation section 214 presents driving assistance information on the basis of a result of the determination. On the basis of the determination result, a travel control section 210 provides traveling assistance such as to reduce the difference in parameter information. The present technology enables appropriate driving assistance.

Systems and methods for assisting navigation of a vehicle are disclosed. In one embodiment, a method of assisting navigation of a vehicle includes receiving navigational data relating to an intended route of the vehicle, receiving object data relating to at least one external object detected within a vicinity of a current position of the vehicle, determining whether the at least one external object affects an ability of the vehicle to proceed along the intended route, and generating at least one instruction relating to the ability of the vehicle to proceed along the intended route.

This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

A method for controlling autonomous driving in an autonomous vehicle includes detecting a situation in which autonomous driving is impossible while the vehicle operates in an autonomous driving mode, outputting a control-right handover request warning alarm and then activating a minimal risk maneuver driving mode, determining a human driver gaze validity based on the detected situation, determining a human driver intervention validity upon determination that the human driver gaze is valid, and determining control-right handover of the autonomous vehicle based on the human driver intervention validity. Thus, the control-right may be reliably transferred from a system to a human driver.

A computer-implemented method for determining awareness data includes determining occlusion information related to a surrounding of a vehicle, determining a viewing direction of an occupant of the vehicle, and determining awareness data representing the occupant's awareness of the surrounding based on the occlusion information and the viewing direction.

A control method is performed by an information display system displaying information on one or more display units included in a vehicle. The information display system executes guidance processing for guiding a line of sight of a driver of the vehicle toward a display unit which is not in the line of sight. The control method including: obtaining vicinity information indicating a state of vicinity of the vehicle from a device outside the vehicle; determining whether or not the driver should pay more attention to the state of the vicinity indicated in the vicinity information than the information displayed on the one or more display units; and executing control for suppressing the guidance processing when it is determined that the driver should pay more attention to the state of the vicinity than the information displayed on the one or more display units.

Techniques for cognitive analysis for directed control transfer with autonomous vehicles are described. In-vehicle sensors are used to collect cognitive state data for an individual within a vehicle which has an autonomous mode of operation. The cognitive state data includes infrared, facial, audio, or biosensor data. One or more processors analyze the cognitive state data collected from the individual to produce cognitive state information. The cognitive state information includes a subset or summary of cognitive state data, or an analysis of the cognitive state data. The individual is scored based on the cognitive state information to produce a cognitive scoring metric. A state of operation is determined for the vehicle. A condition of the individual is evaluated based on the cognitive scoring metric. Control is transferred between the vehicle and the individual based on the state of operation of the vehicle and the condition of the individual.

Systems and methods are disclosed for determining a distraction level of a driver. A real-time driver analysis computer may receive sensor data from one or more driver analysis sensors. The real-time driver analysis computer may analyze the sensor data to determine a distraction level of a driver. Based on the distraction level, the real-time driver analysis computer may send one or more control signal to the vehicle and output one or more alerts to a mobile device associated with the driver.

A method for warning a driver of a motor vehicle and to a control device for a motor vehicle are disclosed. The method comprises: steps: receiving, using the vehicle, position data of a first object from a communication device external to the vehicle; detecting a vehicle environment by a detection device of the motor vehicle and detecting an own position of the motor vehicle. In addition, determining if the detection device detects a second object hiding the first object in a field of view between the motor vehicle and the first object, and determining if in a potentially critical situation for the motor vehicle results from the first object. If it is recognized that the first object is hidden and that the potentially critical situation for the motor vehicle results from the first object, a specified warning cascade is initiated.