A slope estimation device estimates a slope of a vehicle traveling road, and includes an input section that acquires a detected value of an acceleration sensor for detecting acceleration in a front-back direction of the vehicle, a centripetal force detecting section that detects centripetal force acting on the acceleration sensor due to a turning motion of the vehicle, and a slope computing section that computes the slope of the vehicle traveling road based on the detected value of the acceleration sensor. When the vehicle is in the turning motion, the slope computing section computes the slope of the traveling road by determining a component of the centripetal force superimposed on the detected value of the acceleration sensor based on a turning center position of the vehicle, a gravity center position of the vehicle, and an installation position of acceleration sensor, and subtracting the component of the centripetal force from the detected value of the acceleration sensor.

Methods and systems implemented in a vehicle involve obtaining a single camera image from a camera arranged on the vehicle. The image indicates a heading angle ψ.sub.0 between a vehicle heading x and a tangent line that is tangential to road curvature of a road on which the vehicle is traveling and also indicates a perpendicular distance y.sub.0 from a center of the vehicle to the tangent line. An exemplary method includes obtaining two or more inputs from two or more vehicle sensors, and estimating kinematic states of the vehicle based on applying a Kalman filter to the single camera image and the two or more inputs to solve kinematic equations. The kinematic states include roll angle and pitch angle of the vehicle.

The present disclosure provides an electronic stability control method for a vehicle for performing vehicular electronic stability control simply by adjusting driving force and braking power that are generated by a driving device of the vehicle without use of a driving force distributing method between front, rear, left, or right vehicle wheels. To this end, the vehicular electronic stability control method includes determining a vehicular state value indicating a driving state of a vehicle from information collected from the vehicle, comparing the determined vehicle state value with a first reference value, and controlling an operation of a driving device for generating driving force for driving the vehicle by the controller when the vehicle state value is greater than the first reference value to adjust driving force for preventing understeer or oversteer of the vehicle.

The present disclosure relates to a method and system for integrated path planning and path tracking control of an autonomous vehicle. The method includes: obtaining five input control variables and eleven system state variables of an autonomous vehicle at current time; constructing a vehicle path planning-tracking integrated state model according to the obtained variables at the current time; enveloping external contours of two autonomous vehicles using elliptical envelope curves to determine elliptical vehicle envelope curves of the two autonomous vehicles, respectively; determining time to collision (TTC) between the vehicles according to elliptical vehicle envelope curves and vehicle driving states; establishing an objective function of a model prediction controller (MPC) according to the model; and solving the objective function based on the TTC, and determining input control variables to the MPC at the next time. Autonomous vehicle collision avoidance can be achieved according to the present disclosure.

The present invention provides an information provision system that provides information to a driver of a straddle type vehicle, the system comprising: an acquisition unit configured to acquire information on a course of the straddle type vehicle; a specification unit configured to specify an attention portion to which attention of the driver should be paid in the course acquired by the acquisition unit; and a notification unit configured to notify the driver of the attention portion specified by the specification unit, wherein the specification unit is configured to specify the attention portion based on inclination information indicating an inclination on the course of a reference vehicle that has previously traveled on the course, and specify the attention portion based on a difference in a travel route on the course between the straddle type vehicle and a four-wheeled vehicle as the reference vehicles.

According to an embodiment, provided are a method and an apparatus for monitoring an unmanned ground vehicle (UGV), for detecting a failure of a UGV actuator in consideration of terrain information. Accordingly, the accuracy of detecting a failure of the UGV is improved.

A vehicle includes a navigation device, a sensor device, and a control device configured to identify an entry of the vehicle into a predetermined section of a road through the navigation device. In particular, the control device may identify at least one of a curvature of the road, a speed of the vehicle, or an acceleration of the vehicle through the sensor device in response to the entry of the vehicle into the predetermined section, and perform a lateral control of the vehicle based on at least one of the curvature of the road, the speed of the vehicle, or the acceleration of the vehicle.

An information processing apparatus acquires vehicle state information for each of a plurality of vehicles. The information processing apparatus estimates road surface state information of a road surface on which each of the vehicles has traveled, based on the acquired vehicle state information for each of the vehicles. The information processing apparatus estimates the road surface state information by inputting the acquired vehicle state information to a trained model that outputs the road surface state information in a case where the vehicle state information is input and that has been trained in advance based on training data in which the vehicle state information and the road surface state information are associated with each other.

A driving assistance device includes a storage medium that stores computer-readable instructions, and a processor connected to the storage medium. The processor executes the computer-readable instructions to recognize an object around a moving body, perform first control for avoiding contact between the moving body and the recognized object by steering, perform second control for avoiding contact between the moving body and the recognized object by braking, derive an estimated value of a yaw rate generated in the moving body on the basis of reference information including at least a plurality of types of information different from a measured value of a yaw rate output by a yaw rate sensor mounted on the moving body, and suppress the first control if a deviation between the measured value and the estimated value is greater than a reference.

Provided are a shift position sensor detecting a shift position of a vehicle; a yaw rate sensor detecting a yaw rate of the vehicle; a turning angle calculation unit calculating, based on the yaw rate between a start time and an end time of a first time, a turning angle of the vehicle in a plan view between the start time and the end time; and a determination unit determining that the vehicle executes a specific retreat operation when the determination unit determines, based on a detection value of the shift position sensor, that the shift position is switched to an advance position, a reverse position, and the advance position within the first time, and a maximum cumulative value of the turning angle of the vehicle in one direction between the start time and the end time, calculated by the turning angle calculation unit, is a threshold value or more.