Abstract: An off-road travel assistive device includes a receiver configured to receive travel data of a vehicle, and an estimator. The estimator includes a road surface severity estimator configured to estimate road surface severity data based on the travel data of the vehicle. The device also includes a stuck probability determiner configured to determine probability of a stuck state of the vehicle occurring using the travel data and the road surface severity data. The stuck probability determiner determines stuck probability using a meta-model.

Abstract: A road surface condition estimation apparatus includes a storage unit configured to store a road surface condition estimation model, and a road surface severity estimator configured to estimate, based on travel information, severity of a condition of a road surface on which a vehicle is travelling using the road surface condition estimation model.

Abstract: An apparatus for determining whether a vehicle is in a stuck state may include: a receiving unit configured for receiving driving information of a vehicle; a score determination unit configured for determining a stuck score based on the driving information; and a stuck determining unit configured for determining whether a vehicle is in a stuck state based on accumulated stuck scores obtained by accumulating stuck scores.

Abstract: An apparatus for estimating a vehicle speed includes: a vehicle information receiving unit for receiving driving information of a vehicle, including wheel speed, motor torque, and longitudinal acceleration of the vehicle; a wheel slip determining unit for determining whether wheel slip occurs; a longitudinal acceleration correction unit correcting the longitudinal acceleration received from the vehicle information receiving unit; and a vehicle speed estimation unit for estimating a vehicle speed using the wheel speed or the corrected longitudinal acceleration according to the determination result of the wheel slip determining unit.

Abstract: The present disclosure provides a steering control method and system for rear-wheel steering that improves driving stability and yaw responsiveness of a vehicle by controlling rear wheels on the basis of a driving state of a vehicle. The method and system receives a vehicle speed and a front-wheel turning angle and calculates a rear-wheel same/inverse-phase control amount; estimates tire slip angles when the vehicle is driven such that the rear wheels are controlled with the same phase; calculates a final rear-wheel turn control value by reflecting a control weight proportioned to the tire slip angle estimation value to the rear-wheel same-phase control amount; and turns the rear wheels on the basis of the final rear-wheel turn control value.

Abstract: Provided are a system and method for recognizing a surrounding vehicle. The system for recognizing a surrounding vehicle includes a vehicle information collecting unit configured to collect location information of an own vehicle and location information of a surrounding vehicle, a surrounding vehicle recognizing unit configured to generate a lane based on the location information of the own vehicle and the location information of the surrounding vehicle collected by the vehicle information collecting unit and to recognize a location of the surrounding vehicle based on the generated lane, and a situation notifying unit configured to determine a road situation based on the surrounding vehicle recognized by the surrounding vehicle recognizing unit.

Abstract: A method of estimating a mass of a vehicle. If a yaw rate is smaller than a reference value, a straight direction model algorithm is applied to obtain an estimated mass. If a measured speed and a measured steering angle are larger than reference values, a lateral direction model algorithm is applied to obtain another estimated mass. If a measured vertical acceleration is larger than a reference value, a vertical direction model algorithm is applied to obtain yet another estimated mass. If each of the estimated masses is in an allowable range, and is constant for a given time period, the masses are applied to a recursive least square method, thereby estimating the mass of the vehicle.

Abstract: A method of estimating a mass of a vehicle. If a yaw rate is smaller than a reference value, a straight direction model algorithm is applied. If a measured speed and a measured steering angle are larger than reference values, a lateral direction model algorithm is applied. If a measured vertical acceleration is larger than a reference value, a vertical direction model algorithm is applied. If each of the estimated masses is in an allowable range, and is constant for a given time period, the masses are applied to a recursive least square method, thereby estimating the mass of the vehicle.