Energy consumption for a vehicle may be reduced based at least in part on an environment characteristic associated with the environment through which the vehicle travels or an operation characteristic associated with operation of the vehicle, thereby increasing an operational time of the vehicle. In some situations, reducing energy consumption may be associated with operation of one or more of a sensor (e.g., turning the sensor off, reducing a frequency or resolution of the sensor, etc.) and/or one or more processors associated with the vehicle (e.g., turning a processor off, reducing a rate of computation, etc.) based at least in part on one or more of the environment characteristic signal or the operation characteristic signal.

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.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles 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 robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles 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 robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. To this end, a server may retrieve one or more routines associated with autonomous operation. The server may also generate a set of test data associated with test conditions. The server may also execute an emulator that virtually simulates autonomous environment. The test data may be presented to the routines executing in the emulator to generate output data. The server may then analyze the output data to determine a quality metric.

A method includes identifying route data including a threshold arrival time for a route for an autonomous vehicle (AV) and calculating, based on the route data and a fuel-efficient speed value for each segment of the route, an estimated arrival time. Responsive to the estimated arrival time not meeting the threshold arrival time, the method includes identifying at least a subset of segments that each represent a candidate for speed increase, computing, for each segment in the subset and based on the fuel economy data, a correlation metric that indicates a correlation between a change in fuel economy and a change in speed for a corresponding segment in the subset, and increasing, for at least one segment from the subset and based on a respective correlation metric, a fuel-efficient speed value of the corresponding segment from the subset to provide a speed profile reflecting the increased fuel-efficient speed value.

Methods and systems for autonomous and semi-autonomous vehicle control relating to malfunctions are disclosed. Malfunctioning sensors or software of autonomous vehicles may be identified from operating data of the vehicle, and a component maintenance requirement status associated with such malfunctioning component may be generated. Based upon such status, usage restrictions may be enacted to limit operation of the vehicle while the component is malfunctioning. This may include disabling or restricting use of certain autonomous or semi-autonomous features of the vehicle until the component is repaired or replaced. Repair may be accomplished by automatically scheduling repair of the vehicle or installing an updated or uncorrupted version of a software program, in various embodiments.

Methods and systems for autonomous and semi-autonomous vehicle routing are disclosed. Roadway suitability for autonomous operation is scored to facilitate use in route determination. Maps of roadways suitable for various levels of autonomous operation may be generated. Such map data may be used by autonomous vehicles or other computer devices in determining routes based upon criteria for vehicle trips. Such routes may be automatically updated based upon changes in road conditions, vehicle conditions, operator conditions, or environmental conditions. Emergency routing using such map data is described, such as automatic routing and travel when a passenger is experiencing a medical emergency.

Methods and systems for autonomous and semi-autonomous vehicle control relating to malfunctions are disclosed. Malfunctioning sensors or software of autonomous vehicles may be identified from operating data of the vehicle, and a component maintenance requirement status associated with such malfunctioning component may be generated. Based upon such status, usage restrictions may be enacted to limit operation of the vehicle while the component is malfunctioning. This may include disabling or restricting use of certain autonomous or semi-autonomous features of the vehicle until the component is repaired or replaced. Repair may be accomplished by automatically scheduling repair of the vehicle or installing an updated or uncorrupted version of a software program, in various embodiments.

A method for assembling a vehicle from a set of modules for travelling a planned route, wherein the set of modules comprises at least one functional module and a plurality of drive modules. Each drive module comprises a pair of wheels, electrical motor, and an interface releasably connectable to a corresponding interface on another module, wherein each drive module is configured to operate autonomously and has an individual set of energy parameters. The method comprising obtaining route information associated with route segments of the planned route, selecting a first drive module having an individual set of energy parameters matching route information associated with a first route segment and selecting a second drive module having an individual set of energy parameters matching route information associated with a second route segment, and thereafter commanding the drive modules to connect together and with a functional module.

Methods and systems for autonomous vehicle recharging or refueling are disclosed. Autonomous electric vehicles may be automatically recharged by routing the vehicles to available charging stations when not in operation, according to methods described herein. A charge level of the battery of an autonomous electric vehicle may be monitored until it reaches a recharging threshold, at which point an on-board computer may generate a predicted use profile for the vehicle. Based upon the predicted use profile, a time and location for the vehicle to recharge may be determined. In some embodiments, the vehicle may be controlled to automatically travel to a charging station, recharge the battery, and return to its starting location in order to recharge when not in use.