A computer includes a processor and a memory storing instructions executable by the processor to receive operating data including occupant data indicating one or more occupant actions to operate a vehicle and location data specifying a location of a vehicle during collection of the occupant data, assign the operating data to a respective set in a plurality of sets, each set including operating data collected during a different specified period of time from other sets, input the plurality of sets to a machine learning program trained to output an identification of a hazard at a specified location, the hazard being a roadway condition or an obstacle that changes operation of the vehicle from a default operation, output the hazard at the specified location from the machine learning program, and send a message to a vehicle including the hazard at the specified location.

An apparatus for deciding a steering intent of a driver is provided. The apparatus includes a processor configured to determine whether a driver intends to steer a vehicle based on sensing results of a stabilization state of a vehicle and whether a hand of the driver is positioned on a steering wheel of the vehicle, and a memory configured to store a preset reference value to determine the steering intent of the driver.

A vehicle collision avoidance system and method. The vehicle collision avoidance system includes an input unit configured to receive driving information of a host vehicle and driving information of a rear vehicle, a memory configured to store a program that calculates a collision risk level using the driving information of the host vehicle and the driving information of the rear vehicle, and a processor configured to execute the program, wherein the processor performs control to display visual information about the risk of collision upon a right or left lane change based on the collision risk level.

A vehicle control device includes: a first obtaining part obtaining gripping information indicating a driver of a vehicle is gripping a steering wheel; a second obtaining part obtaining operation information indicating the driver is performing a driving operation; a recognition part recognizing a road marking line of a lane traveled by the vehicle; and a support part providing a support so that the vehicle does not deviate from the road marking line when a deviation probability is greater than or equal to a predetermined degree. The support part delays an operation of the support when the gripping information is obtained and the operation information is not obtained, as compared with a case where the gripping information and the operation information are not obtained, and suppresses the operation of the support for a predetermined time when the operation information is obtained regardless of whether the gripping information is obtained.

A vehicular driving assist system includes a sensor disposed at a vehicle and sensing forward of the equipped vehicle. With the equipped vehicle traveling along a traffic lane of a road, the system, responsive to processing of sensor data captured by the sensor, determines a leading vehicle traveling along the traffic lane ahead of the equipped vehicle. The system determines position and heading information of the leading vehicle relative to the equipped vehicle. As the equipped vehicle approaches locations that correspond with the determined position and heading information of the leading vehicle, the system adapts the position and heading information of the leading vehicle to the current location and heading of the equipped vehicle and controls lateral movement of the equipped vehicle to follow the leading vehicle in and long the traffic lane of the road.

A swerve assist to assist the driver of a transportation vehicle during an avoidance maneuver so that a collision with an obstacle is avoided. An additional steering torque for amplifying a current steering torque is applied when an avoidance maneuver of the transportation vehicle is detected. A single-wheel braking of the transportation vehicle is actuated to increase a transverse offset of the transportation vehicle.

A device for estimating a friction coefficient between a road surface and an automotive tire through determination of a steering torque during a steering maneuver of a slow-rolling or stationary vehicle includes a computer configured for constructing a brush model for a description of the steering torque across a contact patch between the tire and road surface. The steering torque is a torque acting on a steering axis required to overcome resistance to tire twisting on the road surface at a wheel velocity and a steering rate. The steering torque depends on a tire brush vertical load distribution and relative motion of tire brushes and the road surface. The device further includes sensors for measuring the wheel velocity and the steering rate and mechanism for measurements or estimation of the steering torque. The friction coefficient is estimated based on the measurements or estimation of the steering torque and the brush model.

The invention relates to a method for improving hands-off recognition in a vehicle with steering torque-based recognition in that swarm data are provided from vehicles that recognize hands-off situations with hand distance sensors in the steering wheel. Both recognition results over a certain route section are compared and, in the case of deviations, the correctness of the results of the hand distance sensors is assumed. On this basis, route sections are determined in which steering torque-based recognition is unreliable. Based on this recognition, systems with steering torque evaluation can then be re-parameterized in order to be more reliable relative to the route.

A computer includes a processor and a memory storing instructions executable by the processor to input steering torque data and steering wheel angle data to a machine learning program trained to output a status of a hand of an occupant relative to a steering wheel, the status being one of (1) the hand is on the steering wheel, (2) the hand is off the steering wheel and no weight is applied to the steering wheel, or (3) the hand is off the steering wheel and a weight is applied to the steering wheel, and actuate a steering subsystem when the output of the machine learning program indicates that the hand of the occupant is off the steering wheel.

A system includes a processor and a memory in communication with the processor. The memory has a human-machine interface module having instructions that, when executed by the processor, cause the processor to identify, influenced by sensor data regarding a vehicle and an environment in which the vehicle operates, an event in which the vehicle should perform an autonomous steering maneuver determined by an autonomous driving system. The instructions further cause the processor to, in response to identifying the event, decouple control of a steering rack of the vehicle by a handwheel of the vehicle and lock the handwheel to prevent the handwheel from substantially moving. The instructions further cause the processor to determine, by the autonomous driving system, the autonomous steering maneuver to be performed by the vehicle influenced by an isometric torque input applied to the handwheel and detected by the processor when the handwheel is locked.