Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for generating or updating usage-based insurance policies for autonomous or semi-autonomous vehicles may be provided. A request to generate an insurance quote may be received via wireless communication, and with the customer's permission, risk levels associated with intended usage by the customer of an autonomous or semi-autonomous vehicle may be determined. An insurance policy may be adjusted based upon the risk levels and the intended vehicle usage. The insurance policy may then be presented on the customer's mobile device for review and approval. In some aspects, the vehicle may be rented, and the intended vehicle usage is measured in distance or duration of vehicle operation. Insurance discounts may be provided to risk averse vehicle owners based upon low risk levels.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for real-time determination of the status of autonomous operation features of an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, the operation of the autonomous or semi-autonomous vehicle may be monitored to obtain operating data from one or more autonomous operation features. An operating status of the autonomous features may be determined based upon the operating data. After which, a change in the operating status of the autonomous features may be identified, and a report containing information regarding the change in the operating status of the autonomous features may be generated.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, with the customer's permission, a vehicle operator in an autonomous or semi-autonomous vehicle may be determined by a sensor disposed within the autonomous or semi-autonomous vehicle or a mobile computing device associated with the vehicle operator. A determination may be made as to whether the vehicle operator is authorized to operate the vehicle based upon the determined identity of the vehicle operator; and if the vehicle operator is not authorized, an alert may be generated and/or the vehicle may be caused to not operate. Alternatively, autonomous operation features may be automatically engaged to automatically drive the autonomous or semi-autonomous vehicle to a safe location when the operator is not authorized. Insurance discounts may be provided based upon the anti-theft functionality.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, vehicle operation safety may be enhanced. An environmental or weather condition (e.g., hail, storm, wind) may be identified that presents a hazard to an autonomous or semi-autonomous vehicle. With the customer's permission, when it is determined that the vehicle is parked in an unprotected location, a protected or covered location to park the vehicle may be identified, a route to that location may be determined, and the vehicle may be directed to travel automatically to the protected location under the operation of autonomous operation features. Insurance discounts or cost savings may be provided to risk averse insurance customers based upon the self-parking functionality that will reduce or mitigate damage to insured vehicles caused by adverse conditions, falling trees or power lines, hail, etc.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. In certain aspects, with the customer's permission, a computer-implemented method for updating an autonomous operation feature may be provided. An indication of a software update associated with the autonomous operation feature may be received, and several autonomous or semi-autonomous vehicles having the feature may be identified. The update may be installed within the several vehicles, such as via wireless communication. Also, a change in a risk level associated with the update to the autonomous operation feature may be determined, and an insurance discount may be determined or adjusted.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Abstract: The present invention involves a system and method of providing decision support for assisting medical treatment decision-making. A patient agent software module processes information about a particular patient. A doctor agent software module processes information about a health status of a particular patient, beliefs relating to patient treatments, and the actual effects of treatment decisions. By filtering information over time from the patient agent into the doctor agent, a plurality of decision-outcome nodes are created and formed into a patient-specific outcome tree with the plurality of decision-outcome nodes. An optimal treatment is determined by evaluating the plurality of decision-outcome nodes with a cost per unit change function to output the optimal treatment.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies are provided. In one aspect, a computer-implemented method for generating or adjusting an insurance policy is provided. With an insurance customer's permission, data regarding several factors associated with the customer may be received via wireless communication from their mobile device, vehicle controller, or smart home controller. The data may be related to (i) the customer's home, (ii) an autonomous or semi-autonomous vehicle, and/or (iii) home and vehicle features, maintenance history, and/or repairs performed to each over time. Risk levels may be determined using the data received. Aspects of one or more insurance policies (auto, home, life, etc.) may be adjusted based upon the risk levels. An updated insurance discount may be transmitted to the customer's mobile device via wireless communication for their review and approval. As a result, insurance discounts may be provided to risk averse insurance customers.

Abstract: In some examples, a multi-node system may access physical storage divided into extents and further arranged into extent groups that may be allocated on demand as thin provisioned storage in response to write requests. Protection class instances are set with specified data protection capabilities. Each instance acts as a logical unit having a distinct addressable block storage space from the extent groups allocated thereto. The extents in an extent group to be allocated to a given protection class instance may vary depending on the protection class capabilities. Management information for the extents, extent groups, and protection classes may be stored in mirrored devices separate from the write data stored in the extents for providing redundant protection to the management information and for increasing the availability of write data in the event of a failure that may cause data loss at one or more locations in the system.

Abstract: The present invention involves a system and method of providing decision support for assisting medical treatment decision-making. A patient agent software module processes information about a particular patient. A doctor agent software module processes information about a health status of a particular patient, beliefs relating to patient treatments, and the actual effects of treatment decisions. By filtering information over time from the patient agent into the doctor agent, a plurality of decision-outcome nodes are created and formed into a patient-specific outcome tree with the plurality of decision-outcome nodes. An optimal treatment is determined by evaluating the plurality of decision-outcome nodes with a cost per unit change function to output the optimal treatment.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status and/or configuration of autonomous operation features of an autonomous or semi-autonomous vehicle may be determined, such as via an on-board computer system or mobile device, and/or then directly or indirectly wirelessly communicated via data transmission from the vehicle computer system or mobile device to a remote server. An adjustment to one or more risk levels associated with operation of the autonomous or semi-autonomous vehicle may also be determined, and an auto insurance policy, premium, or discount may be adjusted based upon the adjustment to the risk levels and presented to the customer for their review and approval. As a result, insurance cost savings may be passed onto risk averse customers that opt into to a rewards program.

Abstract: According to certain aspects, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, an identity of a vehicle operator may be identified and a vehicle operator profile may be retrieved. Operating data regarding autonomous operation features operating the vehicle may be received from vehicle-mounted sensors. When a request to disable an autonomous feature is received, a risk level for the autonomous feature is determined and compared with a driver behavior setting for the autonomous feature stored in the vehicle operator profile. Based upon the risk level comparison, the autonomous vehicle retains control of vehicle or the autonomous feature is disengaged depending upon which is the safer driver—the autonomous vehicle or the vehicle human occupant. As a result, unsafe disengagement of self-driving functionality for autonomous vehicles may be alleviated.

Abstract: In some examples, both object data and corresponding metadata are stored on thin provisioned block storage in which blocks for the storage of the object data and the metadata are dynamically provisioned from a shared pool. For instance, the metadata may be stored on the block storage using a tree data structure that may grow proportionally with the corresponding stored object data. The object storage may automatically adapt to the size and number of objects being stored, and storage space for metadata may be allocated dynamically on demand. Additionally, some implementations include storing data across multiple trays. For instance, a plurality of storage extents of an extent group may be allocated across a plurality of storage devices on multiple trays. The extent allocation may be tray-aware by allocating extents to maximize the probability that data remains available/recoverable in the presence of a failure in one or more trays.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Abstract: A method for detecting an event occurring during operation of a vehicle includes receiving indications of a plurality of variables from an installed device communicatively coupled to the mobile device via an internal communication link. The method further includes analyzing the received indications of the plurality of variables to detect the event occurring during the operation of the vehicle. Still further, the method includes, upon detecting the event, initiating: (i) a first communication session between the mobile device and an entity outside of the vehicle, and (ii) a second communication session between the mobile device and the installed device, wherein the mobile device forwards content communicated via the first communication session to the installed device via the second communication session such that the installed device presents the content to the vehicle operator. In one aspect, air pressure wave sensor and accelerometer data may trigger automatic crash notifications to emergency responders.

Abstract: Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, an identity of a vehicle operator may be determined and a vehicle operator profile and/or operating data regarding autonomous operation features of the vehicle may be received after the vehicle operator opts into a rewards program and agrees to share their data. Autonomous operation and vehicle operator risk levels associated with operation of the autonomous or semi-autonomous vehicle may be determined. Based upon the risk levels and/or comparison thereof, one or more autonomous operation features may be disengaged. A preparedness level of the vehicle operator to assume or reassume control of operating the vehicle is determined prior to disengagement. If satisfactory, an alert is presented to the vehicle operator prior to disengagement of the autonomous operation features.

Abstract: The present invention involves a system and method of providing decision support for assisting medical treatment decision-making. A patient agent software module processes information about a particular patient. A doctor agent software module processes information about a health status of a particular patient, beliefs relating to patient treatments, and the actual effects of treatment decisions. By filtering information over time from the patient agent into the doctor agent, a plurality of decision-outcome nodes are created and formed into a patient-specific outcome tree with the plurality of decision-outcome nodes. An optimal treatment is determined by evaluating the plurality of decision-outcome nodes with a cost per unit change function to output the optimal treatment.