The present disclosure relates to a noise control apparatus, vehicle having the same and method for controlling the vehicle to reduce indoor noise. In accordance with an aspect of disclosure, the vehicle collects sound by using a sound collector while driving the vehicle; detects vibration occurring in the vehicle by using a vibration detector; detects an occupant in the vehicle by using an occupant detector; generates a virtual reference signal based on an actual reference signal for the detected vibration; acquires location information of the occupant's ear based on the occupant information; generates a virtual error signal based on the acquired ear location information and the actual noise signal for the collected sound; generates a noise control signal based on the virtual error signal and the virtual reference signal; and outputs the generated noise control signal as sound.

The present disclosure relates to a noise control apparatus, vehicle having the same and method for controlling the vehicle to reduce indoor noise. In accordance with an aspect of disclosure, the vehicle collects sound by using a sound collector while driving the vehicle; detects vibration occurring in the vehicle by using a vibration detector; detects an occupant in the vehicle by using an occupant detector; generates a virtual reference signal based on an actual reference signal for the detected vibration; acquires location information of the occupant's ear based on the occupant information; generates a virtual error signal based on the acquired ear location information and the actual noise signal for the collected sound; generates a noise control signal based on the virtual error signal and the virtual reference signal; and outputs the generated noise control signal as sound.

Systems and methods for navigating a host vehicle are disclosed. In one implementation, a system includes a processor configured to receive from a camera onboard the host vehicle a captured image representative of an environment of the host vehicle. The captured image is provided to a trained system. The trained system is configured to infer an output from the captured image a presence of a curved road segment in the captured image, wherein the curved road segment is associated with a road on which the host vehicle is traveling. The processor is configured to receive the output provided by the training system. The output includes at least one speed value for the host vehicle. The at least one speed value output from the trained system is based on a proximity of the host vehicle to the curved road segment and based on at least one characteristic of the curved road segment represented in the captured image. The processor is configured to cause the host vehicle to take at least one navigational action based on the determined at least one speed value.

Systems and methods for navigating a host vehicle are disclosed. In one implementation, a system includes a processor configured to receive from a camera onboard the host vehicle a captured image representative of an environment of the host vehicle. The captured image is provided to a trained system. The trained system is configured to infer an output from the captured image a presence of a curved road segment in the captured image, wherein the curved road segment is associated with a road on which the host vehicle is traveling. The processor is configured to receive the output provided by the training system. The output includes at least one speed value for the host vehicle. The at least one speed value output from the trained system is based on a proximity of the host vehicle to the curved road segment and based on at least one characteristic of the curved road segment represented in the captured image. The processor is configured to cause the host vehicle to take at least one navigational action based on the determined at least one speed value.

An onboard device includes a first learning unit that obtains gravity direction information caused by gravity by learning raw sensor information sensed by a sensor while the vehicle is not accelerated, a second learning unit that obtains travel direction information of the vehicle by learning the raw sensor information sensed by the sensor while the vehicle is accelerated; and a calculating unit that calculates an orientation conversion parameter for converting the raw information into the normalized information using the gravity direction information and the travel direction information. The raw sensor information is the acceleration information actually sensed by the sensor when the onboard device is installed in an arbitrary orientation in the vehicle, and the normalized sensor information is equivalent to the acceleration information that would be sensed by the sensor when the onboard device is installed in the vehicle with a specified orientation.

An onboard device includes a first learning unit that obtains gravity direction information caused by gravity by learning raw sensor information sensed by a sensor while the vehicle is not accelerated, a second learning unit that obtains travel direction information of the vehicle by learning the raw sensor information sensed by the sensor while the vehicle is accelerated; and a calculating unit that calculates an orientation conversion parameter for converting the raw information into the normalized information using the gravity direction information and the travel direction information. The raw sensor information is the acceleration information actually sensed by the sensor when the onboard device is installed in an arbitrary orientation in the vehicle, and the normalized sensor information is equivalent to the acceleration information that would be sensed by the sensor when the onboard device is installed in the vehicle with a specified orientation.

An information processing apparatus includes a receiver configured to receive a data set including a requested acceleration as information representing movement of a vehicle in a front-rear direction and any one of a steering angle, a yaw rate, and a rotation radius as information representing movement of the vehicle in a lateral direction from each of a plurality of applications, an arbitration unit configured to perform arbitration of information representing the movement of the vehicle in the front-rear direction and arbitration of information representing the movement of the vehicle in the lateral direction based on a plurality of the data sets received by the receiver, and a first output unit configured to output instruction information for driving an actuator based on an arbitration result of the arbitration unit.

An information processing apparatus includes a receiver configured to receive a data set including a requested acceleration as information representing movement of a vehicle in a front-rear direction and any one of a steering angle, a yaw rate, and a rotation radius as information representing movement of the vehicle in a lateral direction from each of a plurality of applications, an arbitration unit configured to perform arbitration of information representing the movement of the vehicle in the front-rear direction and arbitration of information representing the movement of the vehicle in the lateral direction based on a plurality of the data sets received by the receiver, and a first output unit configured to output instruction information for driving an actuator based on an arbitration result of the arbitration unit.

A method for compensating sensor tolerances of accelerometers of a vehicle. The method includes following steps: recording of measurement signals of at least three similarly oriented accelerometers, calculation of an acceleration (a.sub.b,z) at a reference position in the spatial direction, which corresponds to the orientation of the accelerometers, low-pass filtering of the measurement signals, determination of tolerance parameters (c.sub.x, c.sub.y, c.sub.z) of each sensor via an optimization method with the aid of the calculated acceleration (a.sub.b,z) at the reference position, and calculation of the adjusted measurement signals from the recorded measurement signals and the tolerance parameters (c.sub.x, c.sub.y, c.sub.z).

A vehicle control apparatus comprising, a center of gravity six-component calculation unit for calculating a center of gravity six-component as vehicle motion targets based on a driver input, a tire three-component calculation unit for calculating a tire three-component of four wheels of a vehicle based on the center of gravity six-component, a vehicle control unit for performing vehicle control by the vehicle control, actuator group based on the tire three-component of the four wheels, and wherein the tire three-component calculation unit calculates the tire three-component of the four wheels from the center of gravity six-component by a coordinate transformation without repetition, which is normalization with the driving stiffness of each wheel and the cornering stiffness of each wheel, when the number of control requests in the vehicle control is less than degrees of freedom of the vehicle control actuator group.