Disclosed is a system for controlling a vehicle safety device, the system including: a vehicle safety device configured to protect an occupant; a first occupant detection unit configured to detect a position of the occupant's movable body part; a second occupant detection unit configured to detect a position of the occupant's body part fixed to the safety device; a calculation unit configured to calculate information on the occupant's behavior in the event of a collision accident of a vehicle based on the position of the occupant's movable body part detected by the first occupant detection unit and the position of the occupant's body part fixed to the safety device detected by the second occupant detection unit; and a control unit configured to control an operation of the vehicle safety device for protecting the occupant based on the information on the occupant's behavior calculated by the calculation unit.

To robustly estimate three-dimensional behaviors of an occupant by fusing, through a particle filter, information obtained through vehicle indoor cameras and through vehicle internal information sensors, an occupant behavior estimation system includes: a camera configured to obtain images of the at least one occupant within the vehicle; sensors configured to obtain information on the vehicle; an image processing device configured to process images obtained from the camera and to obtain key point information of the at least one occupant and object tracking information that is provided by tracking the at least one occupant; and a vehicle safety controller configured to estimate the behaviors of the occupant by using a particle filter based on the information on the vehicle obtained through the sensors, the key point information and the object tracking information, which are obtained from the image processing device.

Detecting off-zone crashes involving a vehicle using lateral acceleration values detected at locations within the vehicle. In one example method, an electronic processor receives a first acceleration value at a centerline of the vehicle from a first acceleration sensor of at least two acceleration sensors. The electronic processor also receives a second acceleration value at the centerline of the vehicle from a second acceleration sensor of the at least two acceleration sensors. The method also includes deriving, with the electronic processor, an approximate yaw acceleration at the centerline of the vehicle based on the first acceleration value and the second acceleration value. The method also includes comparing, with the electronic processor, the approximate yaw acceleration to a threshold and initiating, with the electronic processor, one or more actions in response to the yaw acceleration exceeding the threshold.

An occupant protection device includes: a collision prediction unit configured to predict a collision state including a collision direction in a vehicle; a seat direction detection unit configured to detect a direction of a seat that is rotatable around a vertical axis of the vehicle with respect to the vehicle; a driving unit configured to adjust a degree of tension of a seatbelt; and a control unit configured to control the driving unit in accordance with the collision direction with respect to the vehicle predicted by the collision prediction unit and the direction of the seat with respect to the vehicle detected by the seat direction detection unit to change the degree of tension of the seatbelt.

A device implementing a system for estimating device location includes at least one processor configured to receive a first and second set of signals, each set corresponding to location data and being received based on a sampling interval. The at least one processor is configured to, for each sampling period defined by the sampling interval, obtain sensor data corresponding to device motion during the sampling period, determine an orientation of the device relative to that of the vehicle based on the sensor data, calculate a non-holonomic constraint based on the orientation of the device relative to that of the vehicle such that the non-holonomic constraint is iteratively updated, and estimate a device state based on the non-holonomic constraint.

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.

A method and an apparatus for monitoring a motorcycle. Based on the acceleration-relevant data, a vehicle motion and a vehicle position in three-dimensional space are estimated. The vehicle position in space is analyzed and is evaluated as a normal or a critical riding state. A detection direction of a sensor unit is predefined in such a way that in an upright normal resting position of the motorcycle the detection direction lies in a horizontal plane, and the detected acceleration-relevant data encompass a first acceleration component in a longitudinal vehicle direction and a second acceleration component in a transverse vehicle direction. A riding state evaluated as critical is plausibilized with the estimated vehicle motion in order to recognize a critical resting position after an accident. An emergency call is generated when a critical resting position after an accident is recognized.

A vehicle safety system includes an actuatable restraint for helping to protect a vehicle occupant and a controller for controlling actuation of the actuatable restraint in response to a vehicle rollover event. The controller is configured to execute a discrimination algorithm comprising at least one classification metric that utilizes at least one of vehicle pitch rate (P_RATE) and vehicle roll acceleration (D_RATE) to discriminate at least one of a ramp rollover event and a soil rollover event from an embankment rollover event. The discrimination algorithm determines a classification of the vehicle rollover event as one of a ramp rollover event, a soil rollover event, and an embankment rollover event. The controller is also configured to select a deployment threshold for deploying the actuatable restraint. The deployment threshold corresponds to the classification of the vehicle rollover event.

In a triggering system for activating a safety device, an acceleration sensor outputs a signal for a time duration in which an acceleration impulse exceeds an acceleration magnitude threshold. A first switching device receives the signal output by the acceleration sensor, and electrically connects a power supply to at least one safety response device for the time duration. A time delay device, upon completion of a delay time after receiving the signal output by the acceleration sensor, outputs a signal for the time duration. A second switching device receives the signal output by the time delay device, and electrically connects the power supply to the at least one safety response device for the time duration. When the time duration exceeds the delay time, the first switching device and the second switching device concurrently electrically connect the safety response device to the power supply, activating the safety response device.

A method detects a risk of collision between a motor vehicle and a secondary object located in traffic lanes adjacent to the main traffic lane of the vehicle, in the event of a lane change by the vehicle, which involves detecting objects in a predetermined danger zone, and estimating a time-to-collision between the vehicle and a detected object. Detecting objects in a danger zone involves: calculating the actual distance between the vehicle and each object detected by the radar, the actual distance corresponding to the length of an arc between two points; determining a danger zone as a function of lines of the main traffic lane and a width of the main traffic line; and checking, for each object detected by the radar, whether its coordinates are inside the predetermined danger zone.