An approach is provided for detecting an on-boarding or off-boarding event based on mobile device sensor data. The approach, for example, involves retrieving sensor data collected from at least one sensor of a mobile device that is fixed in a stationary position relative to a vehicle. The approach also involves processing the sensor data to determine roll angle data for the vehicle over a time window. The approach further involves processing the roll angle data to determine one or more transitions of a roll angle value of the vehicle between one or more value levels. The approach further involves determining an on-boarding event, an off-boarding event, or a combination thereof based on the one or more transitions. The approach further involves providing the on-boarding event, the off-boarding event, or a combination thereof as an output.

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, limiting a bias error in a manner of limiting a bias error component of an angular velocity around a reference vector in error information, and correcting the predicted posture information of the object based on the error information, the reference vector, and an output of a reference observation sensor.

A vehicle controller for a vehicle including a drive source including an electric motor includes: a sense-of-beating producer configured to acquire a total required torque which is a required torque of the entire vehicle and configured to derive a total target torque corresponding to the total required torque as applied to a predetermined engine combustion cycle; and a target motor torque deriver configured to, based on the total target torque, derive a target motor torque for torque control of the electric motor. The vehicle controller controls the electric motor based on the target motor torque.

A vehicle controller for a vehicle including a drive source including an electric motor includes: a sense-of-beating producer configured to acquire a total required torque which is a required torque of the entire vehicle and configured to derive a total target torque corresponding to the total required torque as applied to a predetermined engine combustion cycle; and a target motor torque deriver configured to, based on the total target torque, derive a target motor torque for torque control of the electric motor. The vehicle controller controls the electric motor based on the target motor torque.

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 system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.

A system and corresponding method for autonomous driving of a vehicle are provided. The system comprises at least one neural network (NN) that generates at least one output for controlling the autonomous driving. The system further comprises a main data path that routes bulk sensor data to the at least one NN and a low-latency data path with reduced latency relative to the main data path. The low-latency data path routes limited sensor data to the at least one NN which, in turn, employs the limited sensor data to improve performance of the at least one NN's processing of the bulk sensor data for generating the at least one output. Improving performance of the at least one NN's processing of the bulk sensor data enables the system to, for example, identify a safety hazard sooner, enabling the autonomous driving to divert the vehicle and avoid contact with the safety hazard.

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 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.