Methods and systems for determining risk associated with operation of autonomous vehicles using autonomous communication are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, including features associated with autonomous communication between vehicles or with infrastructure. This information may be used to determine risk levels for a plurality of features, which may be based upon test data regarding the features or actual loss data. Expected use levels and autonomous communication levels may further be determined and used with the risk levels to determine a total risk level associated with operation of the vehicle. The autonomous communication levels may indicate the types of communications, the levels of communication with other vehicles or infrastructure, or the frequency of autonomous communication. The total risk level may be used to determine or adjust aspects of an insurance policy associated with the vehicle.

A control device includes a model generation unit that generates a control model that formulates a task to be executed, and a task processing unit that causes the vehicle to execute the task by performing model prediction control using the control model. Assuming that a first state space is a state space of the control model used at an execution time of the first task, and a second state space is a state space of the control model used at an execution time of the second task, the task processing unit starts to cause the vehicle to execute the second task, after executing a transition process that is a process of making a value of a state variable that is commonly included in both the first state space and the second state space within a predetermined range that is allowed at the execution time of the second task.

A system for control of an automated device includes a control system configured to operate a device during an operating mode corresponding to a first state in which the control system automatically controls operation, the operating mode prescribing that a user monitor the device operation during automated control, and a scheduling module configured to, during the operating mode, receive a request for the user to temporarily stop monitoring in order to perform a task unrelated to the device operation, allocate a time period during which automated control is maintained and the user stops monitoring, the time period including a non-monitoring period having a duration based on a minimum amount of time for the task, and put the device into a temporary state at initiation of the allocated time period during which the user stops monitoring and automated control is maintained.

A vehicle running mode control method may include detecting, by a mode controller, a mode switching from an electric vehicle mode (EV mode) to a hybrid electric vehicle mode (HEV mode) while a vehicle runs; and performing a continuously variable transmission (CVT) cooperative mode switching control in which a drive motor is connected to an engine by engaging a clutch by operating the CVT.

A travel control device for a vehicle, includes: a lane information acquisition unit configured to acquire lane information; a steering control unit configured to control steering of the vehicle by executing lane travel control to make the vehicle travel along the lane; and a vehicle speed control unit configured to control a vehicle speed by executing constant speed travel control in which the vehicle is made to travel at a set vehicle speed and/or adaptive cruise control in which the vehicle is made to travel at a speed equal to or lower than the set vehicle speed so as to follow a preceding vehicle. The vehicle speed control unit is configured to control the vehicle speed during a turn of the vehicle by setting a vehicle speed upper limit value, which is set to different values depending on whether the lane travel control is being executed.

Methods and systems are provided for adjusting driver demand wheel torque of a vehicle. The driver demand wheel torque may be adjusted as a function of a minimum wheel torque. The minimum wheel torque may be determined according to a plurality of torques that may be evaluated in three different phases.

A driving force control system for a vehicle is provided to control a torque vectoring device is provided. A controller is configured to bring the torque vectoring device into a preparatory state in which the differential torque and the differential limit torque are equalized to each other when shifting the operating mode between the differential mode and the differential limit mode, and to shift the operating mode of the torque vectoring device by gradually reducing a difference between the differential torque and the differential limit torque.

A method for autonomous operation of a vehicle on a driving route ahead permits autonomous operation of the vehicle is only permitted if one or a group of conditions is/are fulfilled for a predetermined route length of the driving route ahead. The conditions include: there is a structural separation on at least one side of a current travel path of the vehicle; a driving lane of the vehicle has a minimum lane width; there are no humps and dips substantially limiting the range of environmental detection sensors; the number of driving lanes does not change; there are no tunnels; there are no buildings on the travel path; there are no motorway junctions; a radius of curvature of the driving lane of the vehicle is larger than a predetermined limit value; there are no traffic disruptions; there are no traffic reports about dangerous situations; and there are no traffic reports about the presence of roadworks.

An operating method for a vehicle includes driving in a manual mode, in which a longitudinal movement and a lateral movement are controlled by a human driver, and driving in an autonomous mode, in which the longitudinal movement and the lateral movement are controlled by an automated system. In the method, driving in semi-autonomous mode is activated from the autonomous mode by the human driver either resuming the longitudinal movement, such that the automated system continues to control the lateral movement, or resuming the lateral movement, such that the automated system continues to control the longitudinal movement. In the semi-autonomous mode, one or more automatic stop operations brake the vehicle when the human driver does not quickly resume control of the lateral movement and the longitudinal movement, which continues to be controlled by the automated system.

Methods and systems for evaluating the effectiveness of autonomous operation features of autonomous vehicles using an accident risk model are provided. According to certain aspects, an accident risk model may be determined using effectiveness information regarding autonomous operation features associated with a vehicle. The effectiveness information may indicate a likelihood of an accident for the vehicle and may include test data or actual loss data. Determining the likelihood of an accident may include determining risk factors for the features related to the ability of the features to make control decisions that successfully avoid accidents. The accident risk model may further include information regarding effectiveness of the features relative to location or operating conditions, as well as types and severity of accidents. The accident risk model may further be used to determine or adjust aspects of an insurance policy associated with an autonomous vehicle.