A system comprises a computer having a processor and a memory, the memory storing instructions executable by the processor to monitor a position of a vehicle while an adaptive cruise control feature of the vehicle is set to operate in a standard operation mode, identify, based on the position of the vehicle and on visibility zone information, a limited visibility zone in a route of travel of the vehicle, and cause the adaptive cruise control feature to operate in a modified operation mode while the vehicle is in the limited visibility zone, wherein during operation in the modified operation mode, the adaptive cruise control feature operates in accordance with one or more modified operating parameters.

Methods and systems for improving fuel economy and reducing emissions of a vehicle with an electric motor, an engine, an energy storage device, and a controller are disclosed. The method includes obtaining current state information including a current hybrid control surface, and determining a target hybrid control surface for the vehicle based on the current state information.

The operation of a hybrid powertrain system is optimized with respect to a desired state-of-charge trajectory, taking account of the estimated anticipated vehicle drive power. The hybrid powertrain system has an internal combustion engine and an electrically operated torque machine. The internal combustion engine and the torque machine are controlled by a control device and are connected to an output element via a hybrid transmission. Before the start of the prediction period Δt, an experience-based state-of-charge trajectory for the anticipated route, covering at least the prediction period Δt, is retrieved from an external database. The desired state-of-charge trajectory is established based on the experience-based state-of-charge trajectory by modifying it with at least one optimization constraint. The experience-based state-of-charge trajectory can be established based on operating data from hybrid powertrain systems of multiple vehicles and/or from operating data from multiple comparable journeys with the same vehicle.

Systems, methods, and other embodiments described herein relate to controlling a vehicle system when the vehicle system is under control of a user. In one embodiment, a method includes predicting a start of a user sneezing episode. The method includes identifying a plurality of phases in the user sneezing episode, and controlling the vehicle system based on which one of the plurality of phases is active.

A computer includes a processor and a memory, the memory storing instructions executable by the processor to collect (a) ambient weather data, (b) vehicle speed data including at least one of a vehicle speed or an engine speed, and (c) operation data of a climate control subsystem of a vehicle, input the collected data to a regression program trained to output a predicted pressure of refrigerant of the climate control subsystem, the regression program trained with previously determined ambient weather data, data of a previous vehicle speed or a previous engine speed, and previous operation data of the climate control subsystem, determine an actual pressure of the refrigerant in the climate control subsystem, and actuate a component upon determining that a difference between the predicted pressure and the actual pressure falls below threshold.

A vehicle for traversing an area with a minimal environmental impact is described. The vehicle includes a first component that creates a first environmental impact when the vehicle is traversing in the area. The vehicle further includes a second component configured to reduce the first environmental impact.

A safety system for a vehicle may include one or more processors configured to determine, based on a friction prediction model, one or more predictive friction coefficients between the ground and one or more tires of the ground vehicle using first ground condition data and second ground condition data. The first ground condition data represent conditions of the ground at or near the position of the ground vehicle, and the second ground condition data represent conditions of the ground in front of the ground vehicle with respect to a driving direction of the ground vehicle. The one or more processors are further configured to determine driving conditions of the ground vehicle using the determined one or more predictive friction coefficients.

An electronic device obtains location information and traveling status information of multiple vehicles in platooning, and traffic condition information of a road segment on which the multiple vehicles travel. The electronic device determines whether the multiple vehicles are suitable for continuing the platooning according to the location information and the traveling status information of the multiple vehicles, and the traffic condition information of the road segment on which the multiple vehicles travel. The electronic device transmits a platoon dismissing notification message to the multiple vehicles when it is determined that the multiple vehicles are not suitable for continuing the platooning, to inform the multiple vehicles to cancel the platooning.

Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption map that provide input to nonlinear model predictive controller.

Aspects of the disclosure provide for enabling autonomous vehicles to pull over into driveways when picking up or dropping off passengers or goods. For instance, a request for a trip identifying a first location and a second location may be received. The first location may be a location of a client computing device, and the second location may be a starting location or a destination for the trip. A user preference for the trip indicating that a pickup for the trip be in a driveway may be identified. That the first location corresponds with the second location may be identified. Based on the determination that the first location corresponds with the second location, dispatch instructions may be to an autonomous vehicle. The dispatch instructions may identify a polygon for a driveway at the second location in order to cause the autonomous vehicle to pull over into the driveway.