A method for determining the vital functions of a vehicle occupant enables precise measurements and is easy to use without negatively affecting the vehicle occupant. The method includes determining the vital functions of the vehicle occupant using a sensor device integrated in a vehicle seat of a motor vehicle, and acquiring measurement signals of the vehicle occupant from which cardiogram signals are acquired. The method further includes using an evaluation unit to ascertain the vital functions of the vehicle occupant from the cardiogram signals. The sensor device is a magnetic field sensor device, and the cardiogram signals are magnetic cardiogram signals.

A system and method for monitoring and analyzing activities of a person operating a machine, particularly driving a vehicle, is provided. A first magnet is attached to a hand of the person and a second magnet is attached to the head of the person. A smart watch having a magnetometer is attached to the other hand of the person. The magnetometer is in magnetic communication with both the first magnet and the second magnet to generate a first magnetic signal and a second magnetic signal. Both signals can be received by a processor and applied to mathematical models by the processor to generate indicators representative of positions and motions of the hands and the head. An alarm can be generated based on the indicators.

An adaptive vehicle control system that includes processors, memory modules communicatively coupled to the processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.

A vehicle is provided. The vehicle includes a plurality of sensors. The vehicle also includes a vehicle controller. The vehicle controller is programmed to collect first sensor information from at least the first sensor during operation of a vehicle, ii) apply the first sensor information to an intersection classification model to determine a type of intersection that the vehicle is approaching, iii) collect second sensor information from the at least the second sensor during vehicle operation, and iv) apply the second sensor information to an intersection specific model to determine at least one course of action for the vehicle to execute, wherein the intersection specific model is associated with the type of intersection determined by the intersection classification model.

Systems and methods are disclosed for operating an autonomous vehicle based on real-time operating data. The operating data may be data about vehicles, drivers, passengers, as well as relevant environmental conditions and contextual data. In some cases, historical data for the preceding data types may be used. The systems and methods may obtain a set of real-time operating data indicative of one or more behaviors of an autonomous vehicle. One or more operations may be performed on the set of real-time operating data. An instruction to modify a particular vehicle operation may be generated based on output from the operations and the one or more behaviors of the autonomous vehicle, and the instruction to modify the particular vehicle operation may be provided to a particular processor that is on-board the vehicle and that controls the particular vehicle operation, to thereby automatically modify the particular vehicle operation.

When a likelihood of a collision between an object and an own vehicle is determined to be present, an vehicle control apparatus calculates an object width indicating a size of the object in a lateral direction and an overlap ratio indicating a proportion of an amount of overlap in the lateral direction between the calculated object width and a determination area that is virtually set ahead of the own vehicle. Based on the calculated overlap ratio, an operation timing for a collision avoidance control is set. The object width is changed when the overlap ratio is less than a predetermined threshold such that the object width is less than the object width when the overlap ratio is greater than the predetermined threshold. The operation timing for the collision avoidance control is set based on a new overlap ratio calculated based on the determination area and the object width after change.

A vehicle may include an engine selectively coupled to a motor and a transmission. The vehicle may include a controller configured to, in response to actuation of a brake pedal, command the transmission to downshift during a regenerative braking event based on a regenerative braking downshift torque. The regenerative braking downshift torque may be determined from a predicted brake pedal input rate. The predicted brake pedal input rate may be based on road grade, vehicle headway range and a driver history. The predicted brake pedal input rate may be classified as Low, Medium, or High. The regenerative braking downshift torque may also be determined from a predicted brake torque rate that is based on a predicted deceleration rate of the vehicle, a vehicle speed prediction and a road grade prediction within a future time interval that begins upon actuation of the brake pedal.

Vehicle drive and control systems are disclosed. A utility vehicle includes a first electric drive motor configured to drive a first traction wheel, a second electric drive motor configured to drive the a traction wheel, a steering wheel configured to receive a first user input, one or more pedals configured to receive a second user input, a steering input sensor, and a drive input sensor. The steering input sensor is configured transmit a steering input signal that corresponds with a steering input position. The drive input sensor is configured to transmit a drive input signal that corresponds with a drive input position. A plurality of controllers are configured to collectively generate, based on the steering input signal and the drive input signal, a first drive signal to drive the first electric drive motor and a second drive signal to drive the second electric drive motor.

An adaptive vehicle control system that includes processors, memory modules communicatively coupled to the processors, and machine readable instructions stored in the one or more memory modules that cause the adaptive vehicle control system to determine an autonomous operation profile of a target vehicle positioned in a vehicle operating environment, wherein the vehicle operating environment includes a roadway having one or more lanes, determine an autonomous operation profile of one of more neighboring vehicles positioned within the vehicle operating environment, compare the autonomous operation profile of at least one of the one or more neighboring vehicles with the autonomous operation profile of the target vehicle, and alter a condition of the target vehicle such that the autonomous operation profile of the target vehicle matches an autonomous operation profile of an individual neighboring vehicle of the one or more neighboring vehicles positioned in the same lane as the target vehicle.

The present disclosure discloses a system and a method for controlling a vehicle in an environment. The method uses a processor coupled to a memory storing a probabilistic map of the environment relating measurements of a magnetic field and time of the measurements of the magnetic field to a probability of locations within the environment. The processor is coupled with stored instructions when executed by the processor carry out steps of the method comprising estimating a probability of the current location in the environment based on a current measurement of a magnetometer at a current timestamp by submitting the current measurement and the current timestamp to the probabilistic map, and controlling an actuator of the vehicle based on a stochastic control employing the probability of the current location.