Disclosed are systems and methods for determining fuel economy of a vehicle. The method may include: receiving, by a processor, travel route information for the vehicle and fuel payment information for the vehicle from a first user device through a network; determining, by the processor, an amount of fuel used by the vehicle based on the received fuel payment information; determining, by the processor, fuel economy of the vehicle based on the received travel route information and the determined amount of fuel used by the vehicle; and transmitting, by the processor, the determined fuel economy of the vehicle to a second user device through the network.

An automatic driving control apparatus for a vehicle is capable of switching a driving mode between a manual driving mode in which a driver manually performs a driving operation of the vehicle and an automatic driving mode in which a driving operation is automatically performed along a set target traveling route. The automatic driving control apparatus includes a driving mode switching unit configured to monitor a manual operation by the driver during traveling in the manual driving mode, and to control so as to switch the driving mode to the automatic driving mode after traveling a set range by manual driving.

There is provided a hybrid vehicle to suppress switching between a motor drive and a hybrid drive in a short time. The hybrid vehicle includes an engine, motor, battery, map information, and a control device programmed to set a drive route from a current location to a destination, to create a drive support plan that assigns one of drive modes including a CD mode and a CS mode to each of drive sections of the drive route, and to perform drive support control. The hybrid vehicle does not perform the drive support control until elapse of a predetermined time period since the system activation or since the termination of the drive support control. This suppresses switching between the motor drive and the hybrid drive in a short time immediately after the system activation or immediately after the termination of the drive support control.

This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle

A method of controlling vehicle inducement in response to an override request includes transmitting, by a controller, an override request to a remote computing device. The override request includes a fault condition resulting in a vehicle inducement that limits a performance parameter of the vehicle to a first value. The method additionally includes receiving, by the controller, instructions from the remote computing device in response to the override request. The instructions include an inducement calibration including a second value of the performance parameter. The method further includes controlling, by the controller, the vehicle inducement to limit the performance parameter of the vehicle to the second value.

A system and method for actuating a vehicle operation power mode that include receiving sensor data from at least one sensor of a vehicle. The system and method also include determining if at least one vehicle operation requirement is met based on analysis of the sensor data and actuating an electric powered operation mode of the vehicle based on determining that the at least one operation requirement is met. The system and method further include controlling the vehicle to be powered by electrical power supplied by an electric battery of the vehicle based on the actuation of the electric powered operation mode.

A vehicle lean inspection apparatus that determines whether a vehicle is leaning during a driving test, includes: a communication module connected to a diagnostic communication module through an OBD-II connector of the vehicle to collect state information of driving of the vehicle; an acceleration sensor to measure an acceleration signal generated by a vertical vibration during driving of the vehicle to recognize a start point and an end point of an inspection interval of a predetermined reference distance; a gyro sensor to measure a road slope during the driving of the vehicle; and a controller to collect state information of the vehicle to measure an actual driving distance passing through the inspection interval, and to determine that the vehicle leans when the remaining driven distance calculated based on a first distance increment and a second distance increment exceeds the reference distance.

This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

A hybrid vehicle includes an engine, a motor, a power storage device connected to the motor, and an electronic control unit. The electronic control unit executes power storage capacity decreasing control in a current trip and executes power storage capacity recovering control in a next trip when parking at a predetermined point is predicted. The electronic control unit limits execution of the power storage capacity decreasing control in the current trip when heavy-load traveling with a load heavier than a predetermined load is predicted to be performed within a predetermined period after the start of the next trip when the next trip is started at a predetermined point.