A first vehicle includes: steering, brakes, memory, sensors, and processor(s) configured to: determine, with the sensors: the first vehicle's acceleration, a second vehicle's acceleration; compute a theoretical collision velocity (TCV) between the first vehicle and the second vehicle based on the accelerations; apply a function or generate a command based on the TCV and a selected coefficient of kinetic friction (COF).

A traveling assistance apparatus recognizes a travel road on which a vehicle is traveling, acquires a traveling state of the vehicle, and determines whether or not the vehicle will deviate from the travel road based on the recognition result of the travel road and the traveling state of the vehicle. The apparatus determines whether to perform, as a prevention method for preventing from the travel road, a method in which either of steering control and brake control of the vehicle is performed, or a method in which a period over which either of the steering control and the brake control is performed and a period over which both of the steering control and the brake control are performed are set. The apparatus sets a steering amount for the steering control and a brake amount for the brake control when the deviation prevention control is performed based on the prevention method.

This disclosure relates to a system and method for transitioning vehicle control between autonomous operation and manual operation. The system includes sensors configured to generate output signals conveying information related to the vehicle and its operation. During autonomous vehicle operation, the system gauges the level of responsiveness of a vehicle operator through challenges and corresponding responses. The system determines when to present a challenge to the vehicle operator based on internal and external factors. If necessary, the system will transition from an autonomous operation mode to a manual operation mode.

A steering control system for a vehicle that considers the limitations of at least one of the vehicle and the environment is contemplated. The steering control system can receive a vehicle characteristic, an environmental condition, a desired amount of turning, and a desired velocity of the vehicle. Based on some, or all of these parameters, the steering control system can determine at least one of a wheel torque, a wheel angle, a wheel camber, and a wheel suspension for a desired vehicle path to enhance vehicle performance.

Provided are methods for motion planner constraint generation based on road surface hazards, which can include receiving information about an object, identifying the object as a particular road hazard, generating one or more motion constraints based on the road hazard, and controlling a vehicle based on the motion constraints. Systems and computer program products are also provided.

Provided is a driving support device including a storage device and a hardware processor, the hardware processor executing a program stored in the storage device to: acquire, from a mobile object, information on existence of a specific situation on a planned travel route, which is set as a route to a destination set by an occupant of the mobile object; plan a coaching item, including notification of warning information relating to traveling of the mobile object and suggestion relating to traveling of the mobile object, based at least on the information; and control a notification device so as to execute the notification and suggestion based on the planed coaching item.

Section acquisition systems, methods, and programs acquire a scheduled travel route of a vehicle driven by at least one of an internal combustion engine or a motor. The systems, methods, and programs divide the scheduled travel route that is in a range of a predetermined distance from a current location into a plurality of sections such that a difference in traffic congestion degree is distinguished, and divide the scheduled travel route that is not in the range of the predetermined distance from the current location into a plurality of sections such that a difference in travel load is distinguished.

Systems and methods for an autonomous vehicle are provided. In one aspect, an autonomous vehicle includes a perception sensor and a processor configured to: receive detected roadway conditions data including roadway grade data from the perception sensor, retrieve mapped data having grade data, and determine that the roadway has a grade based on the detected roadway grade data and the retrieved roadway grade data. The processor can be further configured to, in response to determining that the roadway has a grade, determine that the grade of the roadway is greater than or equal to a predetermined high grade value and less than a predetermined grade limit, and in response to determining that the grade of the roadway is greater than or equal to the predetermined high grade value and less than the predetermined grade limit, operate the autonomous vehicle to change lane to a right-most lane.

A controller may indicate a low-traction mode of a vehicle when a longitudinal tracking accumulation exceeds a first threshold value and a lateral response accumulation exceeds a second threshold value. The longitudinal tracking accumulation may measure a tally of activation of a traction control system over time. The lateral response accumulation may measure a comparison of the vehicle yaw-rate to a driver-desired model-based prediction of the yaw-rate. The controller may indicate the low-traction mode by providing a recommendation to switch to the low-traction mode in a human-machine interface screen of the vehicle, or by automatically adjusting the operational mode of at least one electronic control unit of the vehicle to implement the low-traction mode.

A method for controlling braking of an autonomous vehicle includes: recognizing, by a driving situation recognizer, a vehicle stop situation based on environment information around the vehicle; generating, by a deceleration profile generator, a n.sup.th-order polynomial-based deceleration profile having a plurality of inflection points (n being a natural number equal to or greater than three) when the vehicle stop situation is recognized; correcting, by a corrector, the n.sup.th-order polynomial-based deceleration profile by setting at least one of a response time of a decelerator, a mass of the vehicle during driving or a deceleration performance of a brake to a control variable; and executing, by a controller, braking of the vehicle based on the corrected n.sup.th-order polynomial-based deceleration profile.