A method that may include receiving driving information and environmental metadata indicative of information sensed by the vehicle; detecting multiple driving events encountered during the driving over the path; determining driving events; for each driving event, determining a comfort based autonomous driving pattern information; for each driving event, determining an driving event identifier; and storing in at least one data structure a driving event identifier for each one of the multiple types of driving events, and a comfort based autonomous driving pattern information.

Provided is a vehicle braking support device. The braking support device includes: detection units for detecting a state around a host vehicle; a braking support control unit for executing braking support by a braking device according to the detected state; and a vehicle stop control unit for maintaining a stopped state of a host vehicle after the host vehicle is stopped by the braking support control unit, and for releasing the stopped state of the host vehicle after a predetermined period has elapsed. The vehicle stop control unit, in a case where by using the detected state it is determined that it is desirable to maintain the stopped state of the host vehicle beyond the predetermined period, the vehicle stop control unit does not release the stopped state of the host vehicle until an operation by a driver is detected.

A computer includes a processor and a memory, the memory storing instructions executable by the processor to predict a heading angle of a target vehicle, determine a distance between a host vehicle and a center line of the target vehicle based on the predicted heading angle, and perform a threat assessment for the target vehicle when the distance is below a threshold.

A vehicle includes: a driver assistance system; an accelerator configured to perform acceleration of the vehicle; a braking device configured to perform deceleration of the vehicle; a velocity sensor configured to detect a current velocity of the vehicle; a driver status sensor configured to acquire a driver's behavioral data; and a controller. The controller is configured to identify a carelessness status of the driver based on the driver's behavioral data and to activate a velocity control mode when the carelessness status of the driver is detected in the activation status of the driver assistance system.

A method of operating a vehicle having a driver assistance system includes detecting driving parameters pertaining to the vehicle while the vehicle is being driven on a roadway using a sensor system of the vehicle. Objects including road signs, lane indicators, and other vehicles are detected using the sensor system. The objects include at least road signs, lane indicators, and other vehicles on the roadway. A traffic rule pertaining to the roadway is identified using a traffic violation warning and prevention system of the driver assistance system. A traffic situation pertaining to the traffic rule is detected based on the detected objects and the driving parameters. An alert is generated that warns the driver of a potential traffic violation when the traffic situation is detected. Alternatively, the driver assistance system may be configured to take control of the vehicle to prevent violation of the traffic rule.

Systems and method are provided for controlling a vehicle. In one embodiment, a method includes: receiving a first surface value associated with a first road surface area in an upcoming environment of the vehicle; receiving a second surface value associated with a second road surface area in the upcoming environment of the vehicle; determining a change in surface value based on the first surface value and the second surface value; and in response to the change in surface value being greater than a threshold, adapting at least one of vehicle collision warning messages, vehicle braking control, vehicle steering control, and path planning based on the second surface value.

A braking control apparatus includes a braking force control unit, a first abnormality detecting unit, a regenerative brake stopping unit, and a braking force compensating unit. The braking force control unit is configured to perform a braking force control by causing an engine brake, a regenerative brake, and a friction brake to operate in cooperation with each other. The regenerative brake stopping unit is configured to disconnect the regenerative brake from the braking force control, when an abnormality of the regenerative brake is detected by the first abnormality detecting unit. The braking force compensating unit is configured to perform a braking force compensation that utilizes the friction brake, from the detection of the abnormality of the regenerative brake until the regenerative brake is disconnected from the braking force control, by performing a feedback control on a deceleration rate at a time when the abnormality of the regenerative brake is detected.

Systems and Methods for controlling an autonomous vehicle, may include: receiving sensor data, the sensor data comprising vehicle parameter information for the autonomous vehicle; using the sensor data to determine a vehicle state for the autonomous vehicle, wherein the vehicle state comprises information regarding a magnitude of an actual or predicted effective understeer gradient for the vehicle; computing a yaw moment required to correct the effective understeer gradient based on the magnitude of the effective understeer gradient; and determining a combination of one or more vehicle control inputs, including applying a brake torque, to correct the effective understeer gradient; applying the brake torque to a single wheel of the vehicle, wherein an amount of brake torque applied is sufficient to lock up the single wheel to create a yaw moment on the vehicle to achieve the computed yaw moment required to correct the effective understeer gradient.

A controlling and warning system based on traffic conditions feedback and a method thereof are disclosed. In the controlling and warning system, a camera disposed on a rear of a vehicle body is configured to generate and transmit a rear video to a controlling host, and the controlling host identifies a vehicle object in the rear video and calculates a separation distance between the vehicle object and the vehicle body; the vehicle object is inputted into a large-sized vehicle recognition model which is built based on artificial intelligence neural network and trained completely, to recognize whether the vehicle object is a large-sized vehicle; when the vehicle object is recognized as the large-sized vehicle and the separation distance reaches to a safe distance, a warning signal is generated. Therefore, the technical effect of improving the warning immediacy of an approaching large vehicle can be achieved.

An autonomous vehicle control system is provided. The control system may include a plurality of cameras to acquire a plurality of images of an area in a vicinity of a vehicle; and at least one processing device configured to: recognize a curve to be navigated based on map data and vehicle position information; determine an initial target velocity for the vehicle based on at least one characteristic of the curve as reflected in the map data; adjust a velocity of the vehicle to the initial target velocity; determine, based on the plurality of images, observed characteristics of the curve; determine an updated target velocity based on the observed characteristics of the curve; and adjust the velocity of the vehicle to the updated target velocity.