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 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 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.

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: 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 monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Abstract: 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.

Abstract: Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

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. Vehicle collision and/or smart home incident monitoring, damage detection, and responses are also described, with particular focus on the particular challenges associated with incident response for unoccupied vehicles and/or smart homes. Operating data associated with the autonomous vehicle and/or smart home may be received. Within the operating, an unusual condition indicative of a likelihood of incident may be detected. Based on the unusual condition, it may be determined that the incident occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.

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 monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

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. Vehicle collision and/or smart home incident monitoring, damage detection, and responses are also described, with particular focus on the particular challenges associated with incident response for unoccupied vehicles and/or smart homes. Operating data associated with the autonomous vehicle and/or smart home may be received. Within the operating, an unusual condition indicative of a likelihood of incident may be detected. Based on the unusual condition, it may be determined that the incident occurred. Accordingly, a response to the incident may be determined. The response may be implemented by the autonomous vehicle and/or smart home.

Abstract: Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Sensors associated with autonomous operation features may be utilized to search an area for missing persons, stolen vehicles, or similar persons or items of interest. Sensor data associated with the features may be automatically collected and analyzed to passively search for missing persons or vehicles without vehicle operator involvement. Search criteria may be determined by a remote server and communicated to a plurality of vehicles within a search area. In response to which, sensor data may be collected and analyzed by the vehicles. When sensor data generated by a vehicle matches the search criteria, the vehicle may communicate the information to the remote server.

Abstract: Methods and systems autonomously parking and retrieving vehicles are disclosed. Available parking spaces or parking facilities may be identified, and the vehicle may be navigated to an available space from a drop-off location without passengers. Special-purpose sensors, GPS data, or wireless signal triangulation may be used to identify vehicles and available parking spots. Upon a user request or a prediction of upcoming user demand, the vehicle may be retrieved autonomously from a parking space. Other vehicles may be autonomously moved to facilitate parking or retrieval.

Abstract: Methods and systems for monitoring use and determining risks associated with operation of a vehicle having one or more autonomous operation features are provided. According to certain aspects, operating data may be recorded during operation of the vehicle. This may include information regarding the vehicle, the vehicle environment, use of the autonomous operation features, and/or control decisions made by the features. The control decisions may include actions the feature would have taken to control the vehicle, but which were not taken because a vehicle operator was controlling the relevant aspect of vehicle operation at the time. The operating data may be recorded in a log, which may then be used to determine risk levels associated with vehicle operation based upon risk levels associated with the autonomous operation features. The risk levels may further be used to adjust an insurance policy associated with the vehicle.

Abstract: Methods and systems autonomously parking and retrieving vehicles are disclosed. Available parking spaces or parking facilities may be identified, and the vehicle may be navigated to an available space from a drop-off location without passengers. Special-purpose sensors, GPS data, or wireless signal triangulation may be used to identify vehicles and available parking spots. Upon a user request or a prediction of upcoming user demand, the vehicle may be retrieved autonomously from a parking space. Other vehicles may be autonomously moved to facilitate parking or retrieval.

Abstract: Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Sensors associated with autonomous operation features may be utilized to search an area for missing persons, stolen vehicles, or similar persons or items of interest. Sensor data associated with the features may be automatically collected and analyzed to passively search for missing persons or vehicles without vehicle operator involvement. Search criteria may be determined by a remote server and communicated to a plurality of vehicles within a search area. In response to which, sensor data may be collected and analyzed by the vehicles. When sensor data generated by a vehicle matches the search criteria, the vehicle may communicate the information to the remote server.

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 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.