Embodiments of the present invention provide a vehicle control system comprising a speed control system, the speed control system being configured automatically to attempt to cause a vehicle to operate in accordance with a target speed value by causing a first vehicle speed value determined according to a first predetermined method to become or be maintained substantially equal to the predetermined target speed value at least in part by causing application of positive drive torque to one or more wheels by means of a powertrain, wherein the speed control system is configured to impose a constraint on the amount of driving torque that may be demanded of the powertrain in dependence on the target speed value and a second vehicle speed value determined according to a second predetermined method, said a second predetermined method being based on the mean speed of the driven wheels of the vehicle.

Control system and method which is adapted for use in a motor vehicle and intended to effect an at least semi-autonomous driving operation of the motor vehicle by means of assigned actuators on the basis of environmental data which are obtained from one or more environment sensors assigned to the motor vehicle, and wherein the control system is adapted and intended to detect a failure of a conventional steering system of the motor vehicle and attempt a change of direction of the vehicle, which corresponds to a desired steering angle, from current driving parameters by means of matched acceleration and/or deceleration interventions at individual wheel drives or wheel brakes, respectively, of the vehicle.

A method is disclosed for analyzing historical accident information to adjust driving actions of an autonomous vehicle over a travel route in order to avoid accidents which have occurred over the travel route. Historical accident information for the travel route can be analyzed to, for example, determine accident types which occurred over the travel route and determine causes and/or probable causes of the accident types. In response to determining accident types and causes/probable causes of the accident types over the travel route, adjustments can be made to the driving actions planned for the autonomous vehicle over the travel route. In addition, in an embodiment, historical accident information can be used to analyze available travel routes and select a route which presents less risk of accident than others.

A control method controls an electric four-wheel-drive vehicle to switch a drive torque distribution between a first distribution prioritizing energy efficiency and a second distribution prioritizing driving performance. The distribution is set to the second distribution where wheel slip is detected during a trip, and returned to the first distribution once the vehicle has stopped. When wheel slip is detected at least during acceleration, the distribution is switched from the first distribution to the second distribution. When wheel slip is detected during deceleration, a slip experience flag is set. The slip experience flag is maintained at least until starting off in a subsequent trip. Where the slip experience flag has been set, the distribution is maintained as the second distribution when the vehicle has stopped, and where the slip experience flag has not been set, the distribution is returned to the first distribution upon the vehicle being stopped.

Controlling an actual slip of at least one driven axle of a motor vehicle with at least one axle having at least one wheel and a one drive unit for providing a drive torque for the axle and for the wheel can be carried out by a control device for controlling the drive unit. The control device can be configured for establishing a first actual speed of the motor vehicle; establishing a second actual speed of the at least one wheel; calculating a target speed of the at least one wheel for the established first actual speed taking into account parameters; determining an actual slip of the at least one wheel with respect to a substrate on which the motor vehicle is being moved; when the actual slip exceeds a defined first limit slip, generating a limit torque by which the drive torque produced by the drive unit is adjusted.

The present disclosure provides a method and system for controlling a four-wheel-independent-drive (4WID) electric vehicle (EV) which incorporates the method steps of: acquiring driving environmental information of the vehicle, running state information of the vehicle and driving expectation information of a driver; tracking a body attitude; switching a condition of the vehicle according to information of an upper module; calculating an expected longitudinal torque, an expected lateral torque and an expected yaw torque of the vehicle that meet a driver's expectation; optimally distributing the torques of the vehicle; and generating armature voltage signals required by output torques of motors and controlling the motors. The method divides the driving process of the vehicle into multiple independent driving conditions. The method does not globally implement operation and control in multiple driving conditions with a single control strategy, but coordinately switches the conditions according to multiple control modes and multiple control strategies.

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: predict, at a trained machine learning classifier, a target slip value based on a predicted slip slope and a predicted road texture, wherein the predicted slip slope and the predicted road texture are determined using sensor data representing tire forces and modify at least one vehicle action based on the target slip value when a confidence level value corresponding to the target slip value is greater than or equal to a confidence level threshold.

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: estimate a slip condition corresponding to at least one vehicle wheel; and generate, via an explicit Nonlinear Model Predictive Control (NMPC) module, control data for operating the at least one vehicle wheel based on the estimated slip condition. The explicit Nonlinear Model Predictive Control (NMPC) module includes a feedforward control module that is configured to generate adjustment data based on the estimated slip condition, wherein the adjustment data modifies the control data.

A driving force control apparatus includes: a sensor that collects information associated with a state of a vehicle, a driving device that provides a driving force to a drive wheel of the vehicle, and a processor electrically connected with the sensor and the driving device. In particular, the processor calculates a required driving force of a driver and a limit driving force of the vehicle based on at least a portion of information collected by means of the sensor, in a situation where the vehicle is turning. The processor further controls the driving device such that the required driving force does not exceed the limit driving force.

An attachment is attached to an upper turning body. During a normal operation, a drive means drives the attachment according to an input of an operator to a manipulation device. A sensor detects a motion of an excavator. Based on an output of the sensor, the slip suppression unit detects slip of a traveling body in an extension direction of the attachment and corrects an operation of the attachment performed by the drive means.