Abstract: Methods and systems for repairing a malfunctioning autonomous vehicle (AV) or semi-autonomous vehicle (SAV) are described herein. The AV or SAV may determine that an autonomous feature or sensor is malfunctioning and the extent of the damage to the autonomous feature or sensor. Then the AV or SAV may compare the extent of the damage to a predetermined threshold to determine whether the AV or SAV remains serviceable or otherwise road worthy. If the AV or SAV remains serviceable, the AV or SAV may locate the nearest repair facility having the necessary electronic components in stock and technical expertise for repairing the AV or SAV. Then the AV or SAV may request the nearest repair facility to send an autonomous repair vehicle to the current location of the AV or SAV to facilitate repair.

Abstract: 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.

Abstract: Methods and systems for determining fault for an accident involving a vehicle having one or more autonomous (and/or semi-autonomous) operation features and paying claims associated with such accidents are provided. According to certain aspects, operating data from sensors within or near the vehicle may be used to determine the occurrence of a vehicle accident, such as a collision. The operating data may further be used to determine an allocation of fault for the accident between a vehicle operator, the autonomous operation features, or a third party. The allocation of fault may be used to further determine and make claims payments related to the accident. In some embodiments, claims may be rejected based upon the operating data and determined allocation of fault.

Abstract: A method includes converting a frame of pixel data to a first frame division unit. The method further includes, responsive to an X,Y coordinate, cropping and shifting the frame division unit to produce a second frame division unit. The method also includes outputting the second frame division unit.

Abstract: Methods and systems for monitoring use, determining collision risk, and recommending usage levels of one or more autonomous (and/or semi-autonomous) operation features of a vehicle are provided. According to certain aspects, operating data from sensors within the vehicle may be used to determine collision risks associated with use of the features, which may include use at particular levels or with certain settings. The operating data may further be used to determine optimal or suggested use levels for the features. When the actual and suggested use levels differ, an alert may be generated and presented to the vehicle operator indicating suggested changes. The vehicle operator may then change the use levels or select an option to change the usage to the suggested use levels.

Abstract: To generate a projected light beam, a headlamp includes: a light source to provide light; and a digital micromirror device (DMD). Illumination optics are optically coupled between the light source and the DMD to illuminate the DMD with the light from the light source. The DMD is arranged to reflect the light as pixelated light. Projection optics are optically coupled to the DMD to project the pixelated light as a mid-beam portion of the projected light beam. The mid-beam portion has a non-uniform mid-range beam profile shaped by at least the DMD and the illumination optics. A field of view and an intensity of the projected light beam are controllable by the light source and the DMD. Also, the headlamp includes a high beam module to provide a high beam portion of the projected light beam.

Abstract: 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.

Abstract: Methods and systems for monitoring use and determining risk associated with operation of autonomous vehicles are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, and operating data regarding vehicle operation may be obtained. The operating data may include information regarding use levels or settings associated with use of the autonomous operation features. Risk levels associated with the features may be determined from test data or actual loss data. The risk levels and operating data may be used to determine a total risk level associated with operation of the vehicle with expected use levels of the autonomous operation features. The total risk level may further be used to determine or adjust aspects of an insurance policy associated with the vehicle.

Abstract: 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.

Abstract: Techniques for building and managing data models are provided. According to certain aspects, systems and methods may enable a user to input parameters associated with building one or more data models, including parameters associated with sampling, binning, and other factors. The systems and methods may automatically generate program code that corresponds to the inputted parameters and display the program code for review by the user. The systems and methods may build the data models and generate charts and plots depicting aspects of the data models. Additionally, the systems and methods may combine data models and select champion data models.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. Malfunctions may be detected by receiving sensor data from a plurality of sensors. One of these sensors may be selected for assessment. An electronic device may obtain from the selected sensor a set of signals. When the set of signals includes signals that are outside of a determined range of signals associated with proper functioning for the selected sensor, it may be determined that the selected sensor is malfunctioning. In response, an action may be performed to resolve the malfunction and/or mitigate consequences of the malfunction.

Abstract: 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.

Abstract: Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Autonomous operation feature usage levels or settings may be automatically set, adjusted, or restricted based upon operating conditions and characteristics of the vehicle operator. Autonomous operation feature usage levels or settings may also be automatically adjusted to optimize performance using suitability data for road segments along a route traveled by a vehicle, such as when operating conditions change. Usage levels or settings may also be automatically adjusted based upon vehicle operator preferences or to ensure compliance with restrictions on usage by the vehicle operator, such as a new driver. Sensor data associated with the features may also be automatically collected and analyzed to determine allowable or optimal autonomous operation feature settings or usage levels.

Abstract: Methods and systems for determining fault for an accident involving a vehicle having one or more autonomous (and/or semi-autonomous) operation features are provided. According to certain aspects, operating data from sensors within or near the vehicle may be used to determine the occurrence of a vehicle accident, such as a collision. The operating data may further be used to determine an allocation of fault for the accident between a vehicle operator, the autonomous operation features, or a third party. The allocation of fault may be used to adjust risk levels or profiles associated with the vehicle operator or with the autonomous operation features.

Abstract: Methods and systems for determining fault for an accident involving a vehicle having one or more autonomous (and/or semi-autonomous) operation features are provided. According to certain aspects, operating data from sensors within or near the vehicle may be used to determine fault for a vehicle accident, such as a collision. The operating data may include information regarding use of the features at the time of the accident and may further be used to determine an allocation of fault for the accident between a vehicle operator, the autonomous operation features, or a third party. The allocation of fault may be used to determine and/or adjust coverage levels for an insurance policy associated with the vehicle. The allocation of fault may further be used to adjust risk levels or profiles associated with the vehicle operator or with the autonomous operation features.