Methods, apparatuses, and computer-readable media are described. In one example, a method of controlling a vehicle comprises: receiving, using one or more sensors, a first set of measurements of a set of physical attributes of the vehicle in a motion; determining, based on a motion data model that defines a set of relationships among the set of physical attributes of the vehicle in the motion and based on the first set of measurements, a set of expected measurements of the set of physical attributes; determining whether to use an entirety of the first set of measurements to control an operation of the vehicle based on comparing the first set of measurements and the set of expected measurements; and responsive to determining not to use the entirety of the first set of measurements, controlling the operation of the vehicle based on a second set of measurements.

Described herein are various techniques, including systems and non-transitory instructions, that, in response to obtaining information regarding a potential collision between a vehicle and an object, obtain data describing the vehicle for a time period extending before and after a time of the potential collision. The system may determine a likelihood that the potential collision is a non-collision event based on the data describing the vehicle by performing one or more assessments. The assessments may include telematics monitor assessment, driver behavior assessment, road surface feature assessment, trip correlation assessment, and/or context assessment. In response to determining that the likelihood indicates that the potential collision is not a non-collision event, the system may trigger one or more actions responding to the potential collision.

Kalman filter based road grade estimation techniques use models of a longitudinal accelerometer, an angular pitch rate gyroscope, and a velocity sensor and their outputs, and fuses the sensor measurements to optimally estimate the road grade. The proposed Kalman filter formulation is unique in that it uses a mathematical model of the sensors where the gyroscope output is considered as the input and the combined accelerometer and velocity sensor output is considered as the output of the model whose states are to be estimated. By using this unique second-order state space model, a Kalman filter based estimation algorithm is developed to estimate road grade accurately in real-time. This estimated road grade is then being utilized by various vehicle efficiency and/or safety systems to improve vehicle efficiency and/or vehicle safety.

An acceleration sensor for a vehicle includes a micro-electro-mechanical (MEMS) high-G sensing element and low-G sensing element provided in a single MEMS housing in one embodiment. In another embodiment, the high-G sensor and the low-G sensor are integrated as a single MEMS low/high-G sensing element and in another embodiment, the high-G and low-G sensing elements are provided in separate MEMS housings disposed in the same acceleration sensor housing. An application specific integrated circuit (ASIC) processes signals from the high-G/low-G sensing element(s). A collision determination system for an autonomous vehicle processes the high-G/low-G signals to actuate airbags and/or to provide collision information to a remote system.

A vehicle includes an inertial measurement unit (IMU); and a controller electrically connected to the IMU. The controller is configured to receive an output signal including at least one of an angular velocity and an acceleration from the IMU, to identify a driving state of the vehicle according to at least one of the output signal, a steering angle of the vehicle, a steering angular velocity of the vehicle, a number of gear stages of the vehicle, a wheel speed of the vehicle, and a braking pressure of the vehicle, to identify an offset and an offset reliability of the output signal according to the driving state of the vehicle, and to transmit a signal from which the offset is removed from the output signal according to the offset and the offset reliability.

A drive and control system for a lawn tractor includes a CAN-Bus network, a plurality of controllers, a pair of electric transaxles controlled by the plurality of controllers, and one or more steering and drive input devices coupled to respective sensor(s) for sensing user steering and drive inputs. The plurality of controllers communicate with one or more vehicle sensors via the CAN-Bus network. The plurality of controllers receive the user's steering and drive inputs and posts on the CAN-Bus network and generate drive signals to obtain the desired speed and direction of motion of the lawn tractor.

Method and system that includes receiving data about (1) a driver's expected vehicle performance and (2) a difference between the driver's expected vehicle performance and an estimated actual vehicle performance, and based on the received data determining control signals for an electric drivetrain system to effect the driver's expected vehicle performance. A vehicle control system that incorporates one or machine learning functions to control a drivetrain that is decoupled from a driver.

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 method of determining a position of a mobile device in a vehicle during a drive includes measuring at least one first acceleration magnitude of the mobile device in a gravity direction with at least one sensor of the mobile device, measuring at least one second acceleration magnitude of the mobile device in the gravity direction with the at least one sensor of the mobile device, the at least one second acceleration magnitude separated in time from the at least one first acceleration magnitude, comparing the at least one first acceleration magnitude with the at least one second acceleration magnitude, and based on a result of the comparing, predicting the position of the mobile device in the vehicle.

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.