Methods and systems are provided for a vehicle system. In one example, a method may include ascertaining a functional relationship between the driving resistance and the velocity v.sub.veh of a motor vehicle comprising an electrical machine as a torque source for the drive and a storage device for electrical energy.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicle and/or smart homes are described herein. Autonomous operation features and related components can be assessed using direct or indirect data regarding operation. Such assessment may be performed to determine the condition of components for salvage following a collision or other loss-event. To this end, the information regarding a plurality of components may be received. A component of the plurality of components may be identified for assessment. Assessment may including causing test signals to be sent to the identified component. In response to the test signal, one or more responses may be received. The received response may be compared to an expected response to determine whether the identified component is salvageable.

A system including a processor and memory may provide for automatically activating or deactivating a feature of a fleet vehicle. For example, one or more fleet vehicles may include one or more of a global-positioning system, a speed governor, electronically-controlled brakes, an electronically-controlled accelerator, a speed limiter, or an on-board computer with a processor and memory. One or more features may be activated by a local or remote computing device or system. For example, a system may determine one or more recommended routes between two or more locations. The system may track a fleet vehicle’s progress along a route, and activate a feature of the fleet vehicle based on the fleet vehicle following or not following the recommended route. For example, the system may cause activation of a speed limiter on the fleet vehicle, disable the fleet vehicle, and/or activate or deactivate autonomous features of the fleet vehicle.

Excess fuel consumption monitor and feedback systems for vehicles include sensor arrays of two primary types including those sensors deployed as part of a vehicle manufacturer established sensor suite and sensors deployed as after-market sensors. Together, these sensor suites include sensors coupled to vehicle subsystems and operating environments associated with the vehicle. Data from these sensors may be used as parametric inputs to drive algorithmic calculations which have outputs that express excess fuel consumption. Expressions of excess fuel consumption may be made instantaneously as real-time feedback to a vehicle operator/driver and/or a fleet manager as part of a summary report.

Methods and systems for enhancing the functionality of a semi-autonomous vehicle are described herein. The semi-autonomous vehicle may receive a communication from a fully autonomous vehicle within a threshold distance of the semi-autonomous vehicle. If the vehicles are travelling on the same route or the same portion of a route, the semi-autonomous vehicle may navigate to a location behind the fully autonomous vehicle. Then the semi-autonomous vehicle may operate autonomously by replicating one or more functions performed by the fully autonomous vehicle. The functions and/or maneuvers performed by the fully autonomous vehicle may be detected via sensors in the semi-autonomous vehicle and/or may be identified by communicating with the fully autonomous vehicle to receive indications of upcoming maneuvers. In this manner, the semi-autonomous vehicle may act as a fully autonomous vehicle.

A method is used to control a fuel level gauge of a vehicle system and includes: monitoring, via an engine controller, a fuel economy of the vehicle system; comparing, via the engine controller, the fuel economy with a predetermined fuel economy threshold to determine whether the fuel economy is less than the predetermined fuel economy threshold; adjusting, via the engine controller, a sensitivity of a display filter in response to determining that the fuel economy is less than the predetermined fuel economy threshold for a predetermined amount of time in order to maximize an accuracy of the fuel level gauge, wherein the display filter smoothes an unfiltered fuel level signal received from a fuel level sensor of the vehicle system, thereby generating a filtered fuel level signal; and controlling, via an instrument panel controller, the fuel level gauge of the vehicle system.

A mileage prediction and optimization system (FIG. 1) is disclosed for optimizing the mileage of a vehicle. The mileage prediction and optimization system comprises a prediction and optimization module (300) adapted to determine variation in mileage of the vehicle at least based on the current fuel volume, current speed, current fuel density, the current tire air pressure, the current tire air temperature, current fetched values from an ECU module (700) and the pre-defined mileage data of the vehicle. Further, the prediction and optimization module (300) is adapted to optimize the mileage of the vehicle by reducing variation of fuel density, reducing variation of tire air pressure and informing optimal gear-speed combinations to a user regardless of whether the vehicle is stationary or in motion.

A fuel-empty-state recovery determination method including: when driving of the hybrid vehicle is started, performing rotation speed control of an electric power generator for a specified time, and then stopping the rotation speed control; in a case where it is detected that a state in which the rotation speed of an engine after stopping the rotation speed control is higher than a threshold continues for more than a first determination time, determining that recovery has been made from a fuel-empty state; in a case where the measured time does not exceed the first determination time, starting measurement of the time during which the rotation speed of the engine is lower than the threshold; and in a case where the measured time exceeds a second determination time, maintaining determination that the vehicle is in a fuel-empty state.

A computer includes a processor and a memory storing instructions executable by the processor to receive data indicating a lane change by a first vehicle that is towing a second vehicle, the data including data indicating a direction that first wheels of the first vehicle are turning while the first vehicle is performing the lane change; and during the lane change, instruct a steering system of the second vehicle to turn second wheels of the second vehicle in a same direction as the first wheels.

Methods and systems for communicating between autonomous vehicles are described herein. Such communication may be performed for signaling, collision avoidance, path coordination, and/or autonomous control. A computing device may receive data for the same road segment from autonomous vehicles, including (i) an indication of a location within the road segment, and (ii) an indication of a condition of the road segment. The computing device may generate, from the data for the same road segment, an overall indication of the condition of the road segment, which may include a recommendation to vehicles approaching the road segment. Additionally, the computing device may receive a request from a computing device within a vehicle approaching the road segment to display vehicle data. The overall indication for the road segment may then be displayed on a user interface of the computing device.