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 vehicle control device is applied to a vehicle including at least a shift control system configured to switch a shift range. The vehicle control device is configured to control the vehicle to perform autonomous driving travel without depending on an operation of a driver in at least one driving operation. The vehicle control device includes a controller. The controller is configured to determine the propriety of travel by the autonomous driving travel according to a type of abnormality that occurs in the shift control system. The controller is configured to perform travel control of the vehicle according to the propriety of the travel by the autonomous driving travel.

Disclosed is a vehicular electronic device including a processor configured to receive information on a user gaze direction, to determine whether a user looks forward based on the information, to perform control to make a call using voice only upon determining that the user looks forward, and to perform control to make a call using voice and an image upon determining that the user does not look forward.

A system for detecting and mitigating an unsafe condition in a vehicle includes an image sensor configured to generate and output image data of one or more seats in a cabin of the vehicle and a processing system operably connected to the image sensor and including at least one processor. The processing system is configured to receive the image data from the image sensor, process the image data to determine a location of at least one passenger in the cabin, detect that the at least one passenger is located outside of the one or more seats based on the determined location of the at least one passenger in the cabin, and operate at least one component of the vehicle in a predefined manner in response to detecting that the at least one passenger is located outside of the one or more seats.

The present disclosure is directed to controlling state transitions in an autonomous vehicle. In particular, a computing system can initiate the autonomous vehicle into a no-authorization state upon startup. The computing system can receive an authorization request. The computing system determines whether the authorization request includes a request to enter the first or second mode of operations, wherein the first mode of operations is associated with the autonomous vehicle being operated without a human operator and the second mode of operations is associated with the autonomous vehicle being operable by a human operator. The computing system can transition the autonomous vehicle from the no-authorization state into a standby state in response to determining the authorization request includes a request to enter the first mode of operations or into a manual-controlled state in response to determining the authorization request is a request to enter the second mode of operations.

A method and system to facilitate monitoring of vehicles, riders, and drivers that includes receiving, using a communication device, and input related to driver energy and driver availability from one or more driver devices. Further, the method may include a step of analyzing, using a processing device, the input related to driver energy to determine energy levels of the one or more drivers. Further, the method may include matching, using the processing device, the rider with a driver based on the analyzing. Further, the method may include transmitting, using the communication device, a notification to the rider device and a matched driver device.

Systems and methods of using a common control scheme to autonomously controlling a vehicle during semi-autonomous and fully autonomous driving modes are provided. In particular, embodiments of the presently disclosed technology incorporate reference tracking for driving input and vehicle state into this common control scheme. In some embodiments, this common control scheme may be implemented using Model Predictive Control (MPC).

A driving assist device is mounted on a vehicle. The driving assist device includes a derivation unit that derives driving characteristics of a user who drives the vehicle, a determination unit that determines, based on the driving characteristics, whether a driving operation by the user corresponds to a driving operation that falls outside the driving characteristics, and an inhibition unit that performs, in a case where the determination unit determines that the driving operation by the user corresponds to a driving operation that falls outside the driving characteristics, control for inhibiting traveling based on the driving operation by the user.

During execution of lane keeping control, a vehicle driving support device sets a center line passing through a center of a travelable width of an own vehicle within a current lane as a target traveling line, and autonomously steers the own vehicle such that a reference point of the own vehicle moves along the target traveling line. The vehicle driving support device changes a position of the target traveling line such that the target traveling line is a line located between the center line and the reference point of the own vehicle, when a driver performs a steering operation for steering the own vehicle during the execution of the lane keeping control and a steering operation force of the driver becomes equal to or larger than a target change start threshold value.

A method includes receiving a video signal that comprises a time series of images of a face of a human, wherein the images in the time series of images comprise a set of landmark points in the face, applying tracking processing to the video signal to reveal variations over time of at least one image parameter at the set of landmark points in the human face, generating a set of variation signals indicative of variations revealed at respective landmark points in the set of landmark points, applying processing to the set of variation signals, the processing comprising artificial neural network processing to produce a reconstructed PhotoPletysmoGraphy (PPG) signal, and estimating a heart rate variability of a variable heart rate of the human as a function of the reconstructed PPG signal.