Operating an autonomous machine using analysis of machine vibration while it is operational. Accelerometers are used to measure the machines vibrations while it is being operated. If the vibrations exceed a predetermined acceleration a controller adjust the velocity of the machine to prevent/reduce further vibrations.

Motorcycle riders, being more vulnerable than drivers of four-wheeled vehicles, can especially benefit from advance warnings of hazards. Hazards are detected in the predicted path of the motorcycle or are predicted to be in the path within the next few seconds of the motorcycle's travel. The outputs from the sensors that detect the hazards are corrected for the lean of the motorcycle as it corners. The predicted path or ego lane of the motorcycle is also adjusted depending on the lean of the motorcycle.

A mining machine includes: a road gradient calculator that calculates a road gradient of a travel route based on a position and a speed measured by a GNSS receiver, a vehicle body posture measured by a vehicle body posture sensor, and an acceleration measured by an acceleration sensor; a traction coefficient calculator that calculates a traction coefficient based on the speed measured by the GNSS receiver, the acceleration measured by the acceleration sensor, a wheel speed measured by a wheel speed sensor, a steering direction measured by a steering angle sensor, a vehicle weight measured by a load sensor, and a driving torque measured by a driving torque sensor; and a target torque calculator that calculates a target torque based on the road gradient calculated by the road gradient calculator and the traction coefficient calculated by the traction coefficient calculator.

A damping control system for a vehicle having a suspension located between a plurality of ground engaging members and a vehicle frame includes at least one adjustable shock absorber having an adjustable damping profile.

A road surface evaluation apparatus including a microprocessor. The microprocessor is configured to perform acquiring driving information (including information indicating a motion of a vehicle while driving and position information of the vehicle, map information including information on a road on which the vehicle is traveling, and vehicle information including unique information of the vehicle), deriving a roughness value indicating a roughness of a road surface of the road on which the vehicle is traveling based on the driving information, correcting the roughness value based on the vehicle information, and outputting the corrected roughness value in association with the road information.

An anti-kinetosis device for a motor vehicle includes a triaxial accelerometer, a display means, and a control unit. The triaxial accelerometer detects accelerations of the vehicle along three axes emits a corresponding acceleration signal. The display means includes light markers forming a first horizontal plane. The control unit includes an acceleration signal input, a processor, and a memory. The control unit receives the acceleration signals emitted by the accelerometer at the acceleration signal input. The memory stores instructions configured to cause the processor to align the first horizontal plane perpendicular to a gravitation vector by driving the means for displaying light markers and configured to cause the processor to align the first horizontal plane with a physical parameter of a first person seated in the motor vehicle. The first horizontal plane is positioned just beside the first internal surface and just in front of the second internal surface.

A system and method for avoiding unintended acceleration is provided and includes a first integrated circuit-based electronic controller configured to receive acceleration and brake requests and provide a control output via a datalink dedicated to controlling a prime mover system of the vehicle, a three-axis accelerometer configured to provide acceleration outputs indicative of acceleration of the accelerometer relative to three dimensions, and a second integrated circuit-based electronic controller operative independently of the first integrated circuit-based controller configured to receive the acceleration and braking requests, receive the acceleration outputs of the three-axis accelerometer, and operatively coupled with the datalink. The second integrated circuit-based electronic controller is configured to determine an unintended acceleration event in response to the acceleration and braking requests, and the acceleration outputs of the three-axis accelerometer.

A device for determining positional information relating to the position of a vehicle is configured to determine a measured value of an acceleration vector of the vehicle, and to determine a value of a dynamic component of the measured value of the acceleration vector caused by a movement of the vehicle. The device is further configured to determine an estimated value of the gravity vector based on the measured value of the acceleration vector and based on the value of the dynamic component, and to determine positional data relating to the position of the vehicle based on the estimated value of the gravity vector.

A computer-implemented method for motion estimation of a vehicle is disclosed. The method includes performing a first preliminary motion estimation based on radar sensor data, performing a second preliminary motion estimation based on inertial measurement unit sensor data, and determining a motion estimation for the vehicle as a weighted average of the first and second preliminary motion estimations. The weighted average is determined by application of a dynamically varying weighting. The weighting may vary dynamically based on one or more of: a speed of the vehicle, an ambient temperature of the vehicle, an ambient humidity of the vehicle, and an activity level of windscreen wipers of the vehicle.

A driving skill evaluation method according to one embodiment of the disclosure includes: generating a kernel density estimation image, based on time-series data of a first parameter corresponding to a direction change in a traveling direction of a vehicle, and time-series data of a second parameter indicating a square of a jerk in the traveling direction of the vehicle; and evaluating a driving skill of a driver of the vehicle, by comparing the kernel density estimation image with a reference image.