A vehicle includes an internal combustion engine, an electric machine, and a controller. The electric machine is rotatably coupled to the engine and is configured to deliver electrical power to electrical accessories. The controller is programmed to, in response to a control signal loss between the electric machine and the controller, limit torque output of electric machine to less than a torque threshold that corresponds to the power threshold. The controller is further programmed to, in response an accessory power demand being greater than the power threshold, control the engine to power the electric machine to increase the torque output of electric machine to greater than the torque threshold to meet the accessory power demand.

A lane-keeping system suitable for use on an automated vehicle includes a camera, an inertial-measurement-unit, and a controller. The camera is configured to detect a lane-marking of a roadway traveled by a vehicle. The inertial-measurement-unit is configured to determine relative-motion of the vehicle. The controller in communication with the camera and the inertial-measurement-unit. When the lane-marking is detected the controller is configured to steer the vehicle towards a centerline of the roadway based on a last-position, and determine an offset-vector indicative of motion of the vehicle relative to the centerline of the roadway. When the lane-marking is not detected the controller is configured to: determine an offset-position relative to the last-position based on information from the inertial-measurement-unit, determine a correction-vector used to steer the vehicle from the offset-position towards the centerline of the roadway based on the last-position and the offset-vector, and steer the vehicle according to the correction-vector.

A calibration apparatus and method suitable for calibration of an offset sensor of a subject vehicle. The calibration apparatus comprises a reference structure that is placed into, a reference locus using image data generated by a camera associated with the reference structure. An offset-target structure is then placed into position by coupling the offset-target structure to the reference structure, the coupling providing an appropriate locus for the offset-target structure during calibration of the offset sensor. The coupling restricts the linear and rotational displacement of the offset-target structure during calibration.

Provided are methods for managing vehicle sensors, which can include: determining a stopping distance for a vehicle travelling on a route, identifying one or more sensors of the vehicle that have respective detection ranges less than the stopping distance, and upon identifying the one or more sensors, deactivating at least one operation of at least one sensor of the one or more sensors. Systems and computer program products are also provided.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for real-time determination of the status of autonomous operation features of an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, the operation of the autonomous or semi-autonomous vehicle may be monitored to obtain operating data from one or more autonomous operation features. An operating status of the autonomous features may be determined based upon the operating data. After which, a change in the operating status of the autonomous features may be identified, and a report containing information regarding the change in the operating status of the autonomous features may be generated. Insurance discounts may be provided to risk averse customers that maintain their autonomous vehicles, and associated accident avoidance functionality, in good working condition.

A system and method of sensor validation utilizing a sensor-fusion network. The sensor-fusion network may comprise a number of sensors associated with one or more vehicles having autonomous or partially autonomous driving functions.

A fault diagnosis method for a bio-signal sensor for the vehicle includes measuring a first bio-signal through the bio-signal sensor in response to a seating detecting signal, measuring a second bio-signal through the bio-signal sensor in response to input through an on-board interface, and determining whether the bio-signal sensor may have malfunctioned according to whether the second bio-signal includes a signal deviating from a range set in response to the first bio-signal.

A vehicle control method is disclosed. The vehicle control method includes: while controlling the driving of a vehicle taking control of itself, determining if there is a need to hand over the control of driving to a passenger in the vehicle; if it is determined that there is a need to hand over the control of driving to a passenger in the vehicle, selecting at least one of passengers to whom the control of driving may be handed over; determining an order of priority in handing over the control of driving by taking into consideration the at least one selected passenger's occupancy state information; handing over the control of driving to a top priority passenger according to the order of priority; and controlling the driving environment by taking into consideration the top priority passenger's occupancy state information.

Method for monitoring a computer vision system (CVS), said computer vision system (CVS) being part of a vehicle control system (VCS) of a vehicle (1000) that is used to maneuver said vehicle (1000) in 3D-space (3000), said computer vision system (CVS) being configured to monitor a surrounding area of the vehicle in real time and said computer vision monitor (CVM) monitoring the behavior of the computer vision system (CVS), comprising the steps of a.) providing the computer vision monitor (CVM) with information concerning a position (LM_POS) of at least one landmark (2000) in the 3D-space (3000), wherein said information is provided by a source, said source being independent of the computer vision system (CVS), b.) providing the computer vision monitor (CVM) with information concerning a current position (CUR_POS) of the vehicle (1000), c.) selecting based on steps a.) and b.) at least one landmark which falls within the range of vision of the computer vision system (CVS), d.) classifying the computer vision system (CVS) as being faulty when the computer vision system (CVS) fails to detect a configurable number of selected landmarks (2000).

A control device executes abnormality detection processing for detecting an abnormality of a current sensor. The abnormality detection processing includes first processing which is executed in a case where, during reception of electric power from a power supply, a state of charge of a power storage device is equal to or greater than a predetermined amount and electric power is supplied to an electrically heated catalyst device. The first processing includes processing for detecting an abnormality of the current sensor by estimating a current supplied to the electrically heated catalyst device using a detection value of a charging current sensor and comparing the estimated value with a detection value of the current sensor.