A determining method for determining a state of a road surface includes: sequentially acquiring a rotational speed of tires mounted on the vehicle, sequentially acquiring a driving force of the vehicle, calculating a slip ratio based on the sequentially acquired rotational speed of the tires, calculating a regression equation and a confidence interval width for a relationship between the slip ratio and the driving force, based on data sets of the slip ratio and the driving force in a predetermined zone, and determining a state of the road surface on which the vehicle travels, based on the confidence interval width calculated for the predetermined zone.

A vehicle-based safety intervention system receives sensor data collected or generated by an onboard computing system of a vehicle. The sensor data is divided into a plurality of blocks, each of the blocks having a duration. A driver behavioral model is applied to one or more of the plurality of blocks to generate one or more driver behavioral parameters. A trend of the one or more driver behavioral parameters is extracted from the plurality of blocks. Based on the extracted trend, it is determined that a driver's performance when operating the vehicle is unsatisfactory or will be unsatisfactory in the future. A vehicle-based intervention is generated based on the determination that the driver's performance is unsatisfactory or will be unsatisfactory in the future.

A method of distributing driving force of a four wheel drive (4WD) eco-friendly vehicle includes determining a first allowable range of driving force for each driving force based on determination of travel stability, determining a second allowable range of driving force for each driving wheel based on system limitations of at least one of the first driving source or the second driving source, determining a range of available driving force of the first driving wheel based on the first allowable range of driving force and the second allowable range of driving force, determining first target driving force of the first driving wheel in consideration of efficiency of the first driving source within the range of available driving force, and determining second target driving force of the second driving wheel based on the first target driving force and requested torque.

An automotive electronic dynamics control system for an automated motor-vehicle. The electronic dynamics control system is designed to implement two distinct Model Predictive Control (MPC)-based Trajectory Planners comprising a Longitudinal Trajectory Planner designed to compute a planned longitudinal trajectory for the automated motor-vehicle; and a Lateral Trajectory Planner designed to compute a planned lateral trajectory for the automated motor-vehicle. The electronic dynamics control system is further designed to cause the planned longitudinal trajectory to be computed before the planned lateral trajectory.

A method for determining road surface conditions in a system with at least one vehicle and a data processing device. The vehicle exchanges data with the data processing device wirelessly. The vehicle has at least one sensor for determining measured values describing a road surface friction coefficient, and a computing unit. The data processing device includes a database, containing a road map having a plurality of route sections. The method includes determining measured values for a route section by the sensor, determining a first friction coefficient for the route section by the vehicle's computing unit, sending a data record, containing measured values and/or the first determined friction coefficient and a piece of information identifying the route section, to the data processing device, determining an average friction coefficient for the route section, sending the average friction coefficient determined for the route section to the vehicle, and determining the road surface condition.

A vehicle slip control apparatus to be installed in a vehicle including a drive source configured to output power to a driving wheel of the vehicle and a gear pair interposed between an output shaft of the drive source and the driving wheel includes a rotating speed detector, a slip determination unit, and a slip determination prohibition unit. The rotating speed detector is configured to detect a rotating speed of the output shaft. The slip determination unit is configured to determine, when an absolute value of an angular acceleration of the rotating speed detected by the rotating speed detector exceeds a set threshold, that the driving wheel is in a slip state. The slip determination prohibition unit is configured to prohibit the determination by the slip determination unit until a predetermined time elapses after a direction of torque outputted from the drive source is inverted.

A vehicle control apparatus includes a controller configured to perform creep traveling control in which a vehicle is caused to travel regardless of an accelerator operation. When one or both of front wheels or one or both of rear wheels of the vehicle are determined as having moved onto a step by the controller after the creep traveling control starts, the controller causes a target vehicle speed of the creep traveling control to be lower than a first target vehicle speed until the remaining wheels out of the front wheels and the rear wheels are determined as having moved onto the step. The first target vehicle speed is equal to the target vehicle speed having been set before a time when the one or both of the front wheels or the one or both of the rear wheels are determined as having moved onto the step.

The present disclosure relates to a method and an apparatus for controlling an electronic control suspension using a deep learning-based road surface classification model. The method for controlling an electronic control suspension in a vehicle including a camera and a GPS receiver may include collecting location information of the vehicle using the GPS receiver while driving, identifying whether there is a previously generated road surface classification model corresponding to a front obstacle when the front obstacle is detected, determining a first control value based on a first characteristic value corresponding to the road surface classification model when there is the road surface classification model as a result of the identification, controlling the electronic control suspension with the determined first control value when entering the obstacle, and collecting new sensing data through a physical sensor, and correcting the first characteristic value based on the new sensing data.

Systems and methods are provided herein for operating a vehicle in a vehicle yaw mode. In response to initiating vehicle yaw mode, the system engages an open-loop mode, that provides open-loop forward torque to the outer wheels of the vehicle and open-loop backward torque to the inner wheels of the vehicle until a sufficient number of wheels are slipping. In response to determining that a sufficient number of wheels are slipping, engaging a closed-loop mode. While operating in the closed-loop mode, one or both of the wheel rotation and vehicle yaw rate are monitored to adjust the torques provided to the wheels of the vehicle to control the vehicle yaw rate.

A vehicle includes an electric machine and a controller. The controller is programmed to responsive to a threshold difference, indicative of wheel slip, between average wheel speed and a vehicle speed that is based on a difference between wheel acceleration and measured vehicle acceleration, command a speed to the electric machine to reduce the wheel slip.