An auto driving control system includes: a situation determining unit which recognizes a situation around the vehicle and determines whether automatic traveling is possible; a drive control unit which performs traveling control when the automatic traveling is possible; a state determining unit which determines whether an occupant is able to drive; and an estimation drive control unit configured such that when the automatic traveling is difficult and it is difficult for the occupant to take over the driving, and when it is determined that execution of a function of the automatic traveling is difficult due to a first sensor, the estimation drive control unit executes the function by using information of a second sensor, and performs traveling control of the vehicle, wherein the automatic traveling is continued based on a control instruction of the estimation drive control unit until the occupant becomes able to take over the driving.

Provided is a wearable device including a main body that is configured to be worn on a specific portion of a user's body, a sensing unit, provided in the main body, that senses a biological signal of a user, a storage unit that collects log information relating to the biological signal, and in which an index pattern relating to a state of the user included in the collected log information is stored, and a controller that sets a reference driving index, using the stored index pattern, in which when it is sensed that the user gets in a vehicle, the controller determines a current driving index corresponding to the biological signal that is sensed before and after the user gets in the vehicle, based on the reference driving index being set, and outputs feedback that notifies the state of the user that corresponds to a result of the determination.

In an evacuation travelling assistance apparatus, a risk determining unit determines, when a driver is not in a state capable of appropriately performing driving operations, a risk involved in stopping at a location and a risk involved in passing through the location, for each of a plurality of locations that may serve as an advancing destination of the own vehicle, based on map information, own vehicle information, and peripheral environment information. The risk determining unit evaluates, for each of the plurality of locations, at least one evaluation subject among a plurality of evaluation subject including: a risk occurrence frequency at the location; a risk avoidability at the location; and a level of danger of the risk occurring at the location, based on a plurality of levels, and determines the risk involved in stopping at each location and the risk involved in passing through each location, based on evaluation results.

An autonomous driving control device capable of starting an autonomous driving control without an operation of a driver and reducing a possibility that the driver can not start manual driving. An autonomous driving control is switched to manual driving when a determination section determines that the amount of operation by the driver is equal to or greater than a first threshold, before a predetermined time elapses since the autonomous driving control is automatically started. An autonomous driving control is switched to manual driving when the determination section determines that the amount of operation by the driver is equal to or greater than a second threshold that is greater than the first threshold, after the predetermined time elapses.

An autonomous driving control system for a vehicle which is able to switch between manual driving and autonomous driving is provided with a driver condition sensor, acting part, and electronic control unit. The electronic control unit is provided with an autonomous driving control part, reliance calculating part for calculating an autonomous driving output reliance, vigilance calculating part for calculating a driver vigilance, and an action control part for controlling a strength of an action against a driver. In a region in which an operating point determined by the autonomous driving output reliance and driver vigilance can fall, a plurality of sub regions are defined by boundary lines extending so that the driver vigilance becomes higher as the autonomous driving output reliance becomes lower. The action control part controls the strength of the action against the driver to differ in accordance with the sub region in which the operating point falls.

Provided is a vehicle stop support system for supporting vehicle stop in an emergency condition. The vehicle stop support system detects a physical abnormality of a driver; sets a target time period based on the detected abnormality; detects a plurality of stop point candidates in a traveling direction of a vehicle; estimates a time period required to reach each of the candidates; a estimates a rear-end collision risk which is a risk that, when assuming that the vehicle stops at each of the candidates, the vehicle will be rear-ended by a following vehicle; and a sets a stop point, wherein the system is operable to set, as the stop point, one of the candidates which satisfies a condition that the required time period estimated with respect thereto is equal to or less than the target time period and which is lowest in terms of the rear-end collision risk.

The present disclosure provides a vehicle control device, a vehicle control method and a head-up display apparatus. The vehicle control device includes: an extraction circuit used to extract brain wave signals of a user; and a control circuit used to determine whether the user is in an unsafe driving state according to the brain wave signals, and perform at least one of operations including issuing a warning reminder and controlling vehicle deceleration when determining that the user is in the unsafe driving state.

System, methods, and other embodiments described herein relate to improving driver warnings for automated driving by a vehicle. In one embodiment, a method includes monitoring a vehicle control system for driver feedback during the automated driving. The method also includes adapting a points value at a defined rate according to whether the driver feedback is present. The method also includes, responsive to determining that the points value satisfies a threshold before the driver feedback is present, generating a warning to a driver.

In a vehicle control system (1, 101, 201) configured for autonomous driving, a control unit executes a stop process by which the vehicle is parked in a prescribed stop area when it is detected that the control unit or a driver has become incapable of properly maintaining a traveling state of the vehicle, and a stop maintaining process for keeping the vehicle parked following the vehicle coming to a stop in the stop process. The control unit keeps the brake lamp turned on while the stop maintaining process is being executed.

The systems and methods disclosed herein provide a risk prediction system that uses trained machine learning models to make predictions that a VRU will take a particular action. The system first receives, in a video stream, an image depicting a VRU operating a micro-mobility vehicle and extract the depictions from the image. The extraction process may be determined by bounding box classifiers trained to identify various VRUs and micro-mobility vehicles. The system feeds the extracted depictions to machine learning models and receives, as an output, risk profiles for the VRU and the micro-mobility vehicle. The risk profile may include data associated with the VRU/micro-mobility vehicle determined based on classifications of the VRU and the micro-mobility vehicles. The system may then generate a prediction that the VRU operating the micro-mobility vehicle will take a particular action based on the risk profile.