An apparatus and method for controlling articulation of an articulated vehicle may prevent jackknifing of the articulated vehicle driven backwards. The apparatus includes a hitch angle calculator configured to calculate a desired hitch angle based on a steering angle and a speed of the articulated vehicle, an error calculator configured to calculate an error between the desired hitch angle and an actual hitch angle of the articulated vehicle, a moment generator configured to generate a moment for controlling the articulation of the articulated vehicle based on the error, and an articulation controller configured to control the articulation of the articulated vehicle based on the moment.

A method for controlling a vehicle to make an emergency stop of the vehicle providing a camera and an electronic control unit (ECU) at the vehicle. Presence of a road condition is determined at the road along which the vehicle is traveling. Responsive to determining an emergency driving condition while the vehicle is traveling along the road at the road condition, the ECU at least partially controls driving of the vehicle along the road. While the ECU is at least partially controlling driving of the vehicle along the road, and responsive to determining an end of the road condition, a target stopping location is determined ahead of the vehicle at the road along which the vehicle is traveling and after the end of the road condition. The ECU at least partially controls driving of the vehicle to the target stopping location.

A method for controlling axle load distribution of a heavy-duty vehicle during a maneuver, wherein the heavy-duty vehicle comprises a number of wheel axles and one or more motion support devices arranged to adjust a relative axle load of one or more wheel axles of the number of wheel axles, the method comprising obtaining a vehicle model and a tire model, wherein the vehicle model and the tire model are jointly configured to predict a tire scrubbing force in dependence of a vehicle state comprising a relative axle load distribution during the maneuver, determining a nominal tire scrubbing force for a current relative axle load distribution, determining an improved relative axle load distribution maneuver associated with a reduced tire scrubbing force compared to the nominal tire scrubbing force, and controlling the one or more motion support devices to provide the improved relative axle load distribution during the maneuver.

A vehicle body side system has a second data communication unit that receives road surface data transmitted from a first data communication unit, a storage unit that stores teacher data, a road surface determination unit that determines a road surface state on a traveling road surface of a vehicle based on the road surface data and the teacher data, and a tire identification unit that identifies a predetermined type as an identification target and identifies which content the tire corresponds to in the type. The tire identification unit identifies the tire based on the identification data transmitted from the tire side device, and the road surface determination unit determines the road surface state using a teacher data corresponding to the tire identification result, when the road surface determination unit determines the road surface state.

A method of controlling a vehicle having wheels provided with tires resting on a surface, the method using a model of the physical behavior of each tire as a function of a sideslip angle (β.sub.ij) for each tire relative to the surface. The model is obtained by implementing an adaptive algorithm that selectively applies an affABREGEine model (Z1), a DUGOFF model (Z2), or a constant model (Z3).

Techniques are provided which may be implemented using various methods and/or apparatuses in a vehicle to utilize vehicle external sensor data, vehicle internal sensor data, vehicle capabilities and external CV2X input to determine, send, receive and utilize data elements to determine inter-vehicle spacing, intersection priority, lane change behavior and spacing and other autonomous vehicle behavior.

The disclosed invention makes use of slip related values to calculate friction related values and tire stiffness related values and feeds back an estimated tire stiffness relates value or a calculated friction related as a basis for further calculations. In particular, the disclosure relates to methods, apparatuses and computer program products to achieve the mentioned objective.

Embodiments of this application disclose a vehicle control method and device, where the method includes: calculating a longitudinal force interference compensation torque and a lateral force interference compensation torque of a vehicle when a flat tire occurs in the vehicle; calculating a feedback control torque of the vehicle; determining an additional yaw moment based on the longitudinal force interference compensation torque, the feedback control torque, and the lateral force interference compensation torque; and controlling, based on the additional yaw moment, a wheel in which the flat tire occurs.

Environmentally friendly electrical vehicles are presented. The electrical vehicles include electrical low speed vehicles (LSVs) that may use sensed location data to obtain one or more operational profiles. The operational profiles may govern the behavior of the LSV in a specific environment, area, or zone to ensure the LSV reduces its impact on the local terrain. The LSV may leverage locally sensed data to form a local context in which the LSV is operating. The LSV's vehicular controller may refine the operational parameters of the operational profile to ensure smooth operation based on local conditions from the local context.

The technology employs a variable motion control envelope that enables an on-board computing system of a self-driving vehicle to estimate future vehicle driving behavior along an upcoming path, in order to maintain a desired amount of control during autonomous driving. Factors including intrinsic vehicle properties, extrinsic environmental influences and road friction information are evaluated. Such factors can be evaluated to derive an available acceleration model, which defines an envelope of maximum longitudinal and lateral accelerations for the vehicle. This model, which may identify dynamically varying acceleration limits that can be affected by road conditions and road configurations, may be used by the on-board control system (e.g., a planner module of the processing system) to control driving operations of the vehicle in an autonomous driving mode.