A travel control device includes: a risk level calculation unit configured to acquire a speed in a traveling direction of a vehicle, a speed of the vehicle in a horizontal direction perpendicular to the traveling direction, and an azimuth angular velocity of the vehicle and calculate a rollover risk level based on a lateral load transfer ratio (LTR) of the vehicle; a deceleration calculation unit configured to calculate deceleration indicating an extent to which to lower the speed in the traveling direction when an absolute value of the rollover risk level exceeds a threshold value; and a control unit configured to control a driving system of the vehicle using a value obtained by lowering a target speed of the vehicle on the basis of the deceleration as a new target speed.

A controller and a control method capable of appropriately assisting with a rider's operation while suppressing falling of a motorcycle, departure of the motorcycle from a lane, a difficulty of the motorcycle in adaptive cruise, and the like is disclosed. In the controller and the control method according to the present invention, in a control mode to make the motorcycle perform autonomous cruise acceleration operation, automatic acceleration that is acceleration generated to the motorcycle by the autonomous cruise acceleration operation is controlled in accordance with a lean angle of the motorcycle.

A controller and a control method capable of appropriately assisting with a rider's operation while suppressing falling of a motorcycle, departure of the motorcycle from a lane, a difficulty of the motorcycle in adaptive cruise, and the like is disclosed. In the controller and the control method according to the present invention, in a control mode to make the motorcycle perform autonomous cruise acceleration operation, automatic acceleration that is acceleration generated to the motorcycle by the autonomous cruise acceleration operation is controlled in accordance with a lean angle of the motorcycle.

A posture estimation method includes calculating a posture change amount of an object based on an output of an angular velocity sensor, predicting posture information of the object by using the posture change amount, adjusting error information in a manner of determining whether or not the output of the angular velocity sensor is within an effective range and, when it is determined that the output of the angular velocity sensor is not within the effective range, increasing a posture error component in error information and reducing a correlation component between the posture error component and an error component other than the posture error component in the error information, and correcting the predicted posture information of the object based on the error information.

A vehicle dynamics control system receives a feedback state signal including values of a roll rate and a roll angle of the motion of the vehicle and updates parameters of a model of roll dynamics of the vehicle by fitting the received values into the roll dynamics model. The roll dynamics model explains the evolution of the roll rate and the roll angle based on the parameters including a center of gravity (CoG) parameter modeling a location of a CoG of the vehicle, and a spring constant and a damping coefficient modeling suspension dynamics of the vehicle. The system determines a control command for controlling at least one actuator of the vehicle using a motion model including the updated CoG parameter and submits the control command to the vehicle controller to control the motion of the vehicle.

A vehicle dynamics control system receives a feedback state signal including values of a roll rate and a roll angle of the motion of the vehicle and updates parameters of a model of roll dynamics of the vehicle by fitting the received values into the roll dynamics model. The roll dynamics model explains the evolution of the roll rate and the roll angle based on the parameters including a center of gravity (CoG) parameter modeling a location of a CoG of the vehicle, and a spring constant and a damping coefficient modeling suspension dynamics of the vehicle. The system determines a control command for controlling at least one actuator of the vehicle using a motion model including the updated CoG parameter and submits the control command to the vehicle controller to control the motion of the vehicle.

A first distinct vehicle operational scenario is identified for an autonomous vehicle (AV). A first set of candidate vehicle control actions are received from a model that provides a first solution to the first distinct vehicle operational scenario. An action is selected from the first set of candidate vehicle control actions. The AV is controlled based on the action. The first solution is obtained offline in a first idealized situation that is decoupled from a current context of the AV.

A travel control device for a vehicle executes a self-driving control based on traveling environment information on which the vehicle travels and traveling information on the vehicle. In the device, a traveling environment information acquisition unit acquires the traveling environment information. A traveling information detection unit detects the traveling information. An unstable behavior detector detects an unstable behavior in one or both of a rolling direction and a yaw direction of the vehicle. A steering wheel holding state detector detects a state in which a driver holds a steering wheel. The first unstable behavior reducer reduces the detected unstable behavior by correcting a steering angle. A second unstable behavior reducer reduces the detected unstable behavior by selecting a predetermined wheel and applying a braking force to the wheel. A vehicle behavior controller freely operates the unstable behavior reducers according to detection results.

A method and an arrangement for optimizing load position in relation to a transportation vehicle, comprising a platform arranged to the transportation vehicle for receiving a load; an actuating device for moving the platform in relation to the transportation vehicle; a sensing device configured to generate a vehicle sensing signal and/or a non-vehicle sensing signal; a controlling device configured to receive at least one of the vehicle sensing signal and the non-vehicle sensing signal; generate controlling commands based on the received at least one of the vehicle sensing signal and the non-vehicle sensing signal; and transmit the controlling commands to the actuating device; wherein the actuating device is configured to receive the controlling commands and to move the platform in relation to the transportation vehicle based on the controlling commands.

An arrangement and method for optimizing load position in relation to a plurality of transportation vehicles comprising at least one master vehicle and at least one slave vehicle, the arrangement comprising a platform arranged to the at least one slave vehicle for receiving a load; an actuating device of the at least one slave vehicle for moving the platform in relation to the at least one slave vehicle; a sensing device configured to generate a vehicle sensing signal and/or a non-vehicle sensing signal; an a controlling device of the at least one master vehicle. The controlling device is configured to receive at least one of the vehicle sensing signal and the non-vehicle sensing signal; generate controlling commands based on the received at least one of the vehicle sensing signal and the non-vehicle sensing signal; and transmit the controlling commands to the actuating device, wherein the actuating device is configured to receive the controlling commands and to move the platform in relation to the transportation vehicle based on the controlling commands.