Abstract: A system and method may create auto insurance quotes using data collected from a device that tracks vehicle usage data and other data. Usage data may be tracked by an On Board Diagnostic (OBD) device or other portable computing device such as a smart phone. Based on a received coverage type, the usage data and other data may be analyzed to determine auto insurance quotes. A potential customer may then purchase an auto insurance policy. Once the purchased policy has been determined to have expired, new usage data will be collected, and new quotes will be created for the customer.

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 determining risk associated with operation of fully autonomous vehicles are provided. According to certain aspects, autonomous operation features associated with a vehicle may be determined, including types and version of sensors, control systems, and software. This information may be used to determine a risk profile reflecting risk levels for a plurality of features, which may be based upon test data regarding the features or actual loss data. Expected use levels may further be determined and used with the risk profile to determine a total risk level associated with operation of the vehicle by the autonomous operation features. The expected use levels may indicate expected vehicle use, as well as traffic, weather, or other conditions in which the vehicle is likely to operate. The total risk level may be used to determine or adjust aspects of an insurance policy associated with the vehicle.

Abstract: A computer-implemented method of using telematics data at a destination device is provided. The destination device may be a mobile device associated with a driver, or a smart vehicle controller of a destination vehicle. The telematics data is generated by an originating mobile device (i) having a Telematics Application (or “App”), and (ii) associated with a second driver/vehicle, the telematics data including acceleration, braking, speed, heading, and location data associated with an originating vehicle. The telematics data may be broadcast from the originating mobile device to the destination device that (a) analyzes the telematics data received, (b) determines that an abnormal travel condition exists, and (c) automatically take corrective action that alleviates a negative impact of the abnormal travel condition on the destination vehicle to facilitate safer travel.

Abstract: A computer system configured to use train telematics data to reduce risk of accidents via a mobile device traveling within a vehicle may be provided. The mobile device may be configured to (1) receive train telematics data associated with a train that includes GPS location, speed, route, heading, acceleration, and/or track data; (2) determine when, or a time period of when, the train will pass through, be passing through, or be within a predetermined distance of a railroad crossing based upon the train telematics data; (3) determine an alternate route for the vehicle to take to avoid waiting at the railroad crossing; and (4) cause display of the alternate route on a display of the mobile device or a vehicle navigation system to allow the train to pass and to avoid train-vehicle collisions. Insurance discounts may be generated based upon the risk mitigation or prevention functionality.

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 first autonomous vehicle may receive a communication from a second autonomous vehicle travelling on the same road as the first autonomous vehicle, where the communication includes an indication of a maneuver which will be performed by the second autonomous vehicle. The first autonomous vehicle may then analyze the communication to identify a first maneuver for the first autonomous vehicle in response to the second maneuver performed by the second autonomous vehicle. Thus, the first autonomous vehicle may move in accordance with the first maneuver.

Abstract: Methods and systems for evaluating the effectiveness of autonomous operation features of autonomous vehicles using an accident risk model are provided. According to certain aspects, an accident risk model may be determined using effectiveness information regarding autonomous operation features associated with a vehicle. The effectiveness information may indicate a likelihood of an accident for the vehicle and may include test data or actual loss data. Determining the likelihood of an accident may include determining risk factors for the features related to the ability of the features to make control decisions that successfully avoid accidents. The accident risk model may further include information regarding effectiveness of the features relative to location or operating conditions, as well as types and severity of accidents. The accident risk model may further be used to determine or adjust aspects of an insurance policy associated with an autonomous vehicle.

Abstract: Techniques for obtaining and/or maintaining insurance coverage include receiving insurance policy preferences for a customer, storing the insurance policy preferences in a customer profile database, and using the insurance policy preferences to automatically obtain a first insurance policy from a first insurance provider, where the first insurance policy has (i) first policy features, and (ii) a first premium corresponding to a first policy term. Automatically obtaining the first insurance policy includes receiving, from each of a plurality of insurance provider computer systems associated with the plurality of respective insurance providers, a quote indicating one or more policy features corresponding to a policy term, selecting one of the quotes from the plurality of respective insurance providers based on the one or more policy features for the quote and the insurance policy preferences for the customer, and notifying the customer of the first insurance provider and the first premium.

Abstract: Techniques for obtaining and/or maintaining insurance coverage include receiving customer information for customers including insurance policy preferences or characteristics for each customer. These techniques further include grouping the customers into affinity groups by generating a set of preferences or characteristics for each affinity group, comparing the insurance policy preferences or characteristics for each customer to the set of preferences or characteristics for each affinity group, and assigning a customer to an affinity group in response to determining that at least a threshold number of insurance policy preferences or characteristics for the customer matches the set of preferences or characteristics for the affinity group. For at least one affinity group, an insurance provider is selected for providing an insurance policy to each of the customers in the affinity group, and each of the customers in the affinity group is notified of the selected insurance provider and the premium.

Abstract: An intermediary entity may act on behalf of consumers to find Usage-Based Insurance (UBI) that best or optimally meet the consumers' UBI preferences and/or characteristics. Based upon an analysis of individual UBI consumer characteristics and/or preferences, each individual UBI consumer may be grouped with other UBI consumers having similar characteristics and/or UBI preferences. For at least one individual assigned a first UBI policy group or segment, intermediary entity may determine that a UBI preference or characteristic of the individual has changed, divide or segment the individual into a second UBI policy group or segment based on the changed UBI preference or characteristic, and update or provide a UBI policy for the individual associated with the second UBI policy group or segment.

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: Vehicle costs may be allocated between users of a vehicle, including autonomous vehicles. A vehicle cost allocation (VCA) computing device receives trip reports and/or vehicle telematics data associated with trips performed by vehicle users using a vehicle. The VCA computing device is also configured to determine which vehicle user is a driver for a trip. Based on the determined driver, the VCA computing device is also configured to determine one or more vehicle costs associated with the trip based upon the vehicle telematics data. The vehicle costs may include usage-based or trip-based insurance. The VCA computing device is also configured to allocate a respective portion of the vehicle cost to each of the one or more vehicle users.

Abstract: Methods and systems for improving vehicular safety by notifying vehicle operators of location-based risks are provided. According to embodiments, a processing server may receive an initial location of a vehicle. Based on location data associated with the initial location, the processing server can determine the risk of an incident. The processing server can generate a notification to communicate to the vehicle operator, and the vehicle operator can assess the risk and take action to mitigate the risk, for example by relocating the vehicle. The processing server can receive updated location data for the vehicle and can determine, based on the updated location data, that the risk has been mitigated.

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 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.

Abstract: A computer implemented method for providing insurance comprises receiving a plurality of vehicle data including a start point, an end point and a frequency value. The method further comprises analyzing the plurality of vehicle data to determine a driving route associated with the vehicle. The method also comprises determining, based on the frequency value, that the driving route is a common driving route and a risk level of the common driving route. The method further comprises processing one or more insurance options, including pricing and underwriting, based at least in part on the risk level of the common driving route.

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 to determine the robustness of autonomous systems, including the use of virtual assessment of software components within a simulated environment. 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: Vehicle costs may be allocated between users of a vehicle, including autonomous vehicles. A vehicle cost allocation (VCA) computing device receives vehicle telematics data associated with trips performed by vehicle users using a vehicle. The VCA computing device is also configured to determine one or more vehicle costs associated with the trip based upon the vehicle telematics data. The vehicle costs may include usage-based or trip-based insurance. The VCA computing device is also configured to determine a respective portion of the vehicle cost to each of the one or more vehicle users, access a respective pre-paid account associated with each vehicle user, and transmit instructions to a respective financial institution associated with each pre-paid account to withdraw funds corresponding to the respective portion of the total vehicle cost.

Abstract: Methods and systems for assessing, detecting, and responding to malfunctions involving components of autonomous vehicles and/or smart homes are described herein. A risk of malfunction and/or cyber-attack may be determined by collecting operating data from a plurality of autonomous vehicles and/or smart homes. The operating data may be analyzed to identify occurrences of a component malfunctioning. For each component, a risk associated with malfunctioning and/or cyber-attack may be determined based upon the identified occurrences. Based on the risks, at least one result associated with the malfunction and/or cyber-attack may be determined. A component profile may be generated based upon the determined risk and/or the impact of the determined results.

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. Several communications from autonomous vehicles may be received at a computing device, where the autonomous vehicles are travelling within a threshold distance of each other. Each communication may include an indication of the next waypoint on a route for the respective vehicle. The computing device may analyze the communications to determine maneuvers for the autonomous vehicles so that each autonomous vehicle may navigate to the corresponding waypoint in the least amount of time or distance. The computing device also may cause each of the autonomous vehicles to move in accordance with the maneuvers for the respective vehicle.