Abstract: A computer-implemented method for operating an autonomous or semi-autonomous vehicle may include identifying a vehicle operator and retrieving an associated vehicle operator profile. Operating data regarding operation of the autonomous or semi-autonomous vehicle may be received that includes data from sensors disposed within the vehicle. When a request to enable an autonomous operation feature is received, (i) autonomous operation risk levels associated with vehicle operation by the autonomous operation feature based upon the received operating data, and (ii) operator risk levels associated with vehicle operation by the vehicle operator based upon the vehicle operator profile are determined. Autonomous operation feature enablement may be allowed based upon a comparison of (i) autonomous operation risk levels with (ii) operator 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, a computer-implemented method for operating an autonomous or semi-autonomous vehicle may be provided. With a vehicle owner's permission, a vehicle operator identity may be determined; and operating data regarding the autonomous or semi-autonomous vehicle may be received from one or more vehicle-mounted sensors. Based upon the received operating data, (i) autonomous operation risk levels associated with autonomous vehicle operation; and (ii) operator risk levels associated with autonomous vehicle operation by the vehicle operator may be determined. Based upon a comparison of the autonomous operation versus vehicle operator risk levels, the autonomous features may be engaged if it is safer for the vehicle to travel autonomously.

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 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: Systems and methods relate to, inter alia, calculating a number of expected collisions in an area over a time period. The systems and methods may further determine a number of observed collisions in the area over the time period. The systems and methods may further calculate a risk index for the area based upon a comparison between the number of expected collisions and the number of observed collisions. The systems and methods may further generate a notification of a travel route for a vehicle based on the risk index.

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: A method, implemented in an electronic processing system that includes a memory and one or more processors, includes receiving, at the electronic processing system, sensor data representing information collected by a sensor (i) located on or in a first vehicle and (ii) configured to sense an environment external to the first vehicle, and storing the received sensor data in the memory. The method also includes processing the stored sensor data to determine conditions in which the second vehicle was driven, driving habits of a driver of the second vehicle, and an identifying characteristic of the second vehicle. The method further includes identifying the driver of the second vehicle using the identifying characteristic, and determining a risk level for the driver of the second vehicle using the determined conditions and driving habits.

Abstract: Systems and methods relate to, inter alia, calculating a number of expected collisions in an area over a time period. The systems and methods may further determine a number of observed collisions in the area over the time period. The systems and methods may further calculate a risk index for the area based upon a comparison between the number of expected collisions and the number of observed collisions. The systems and methods may further determine one or more travel routes for a vehicle based upon the calculated risk index. The systems and methods may further display a notification depicting the one or more travel routes to facilitate routing of the vehicle that avoids traversing the area.

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: Systems and methods are disclosed for adjusting autonomous vehicle driving behavior. A controller of the autonomous vehicle may utilize an aggression factor to adjust control of the autonomous vehicle. The autonomous vehicle may detect one or more characteristics of proximate vehicles, analyze the one or more characteristics to estimate an aggression level of the proximate vehicles, and adjust the aggression factor based on the estimated aggression level.

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: Systems and methods relate to, inter alia, calculating a collision risk index for an area based upon historical traffic data. The systems and methods may further generate a notification to automatically engage or disengage an autonomous, or semi-autonomous, vehicle control feature in a vehicle based upon the collision risk index for the area. The systems and methods may further transmit the notification to a device of the vehicle to facilitate automatically engaging or disengaging an autonomous, or semi-autonomous, vehicle control feature in the vehicle as the vehicle approaches the area. As a result, vehicle collisions may be reduced, and vehicle safety enhanced.

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: Systems and methods relate to, inter alia, calculating a number of expected collisions in an area over a time period. The systems and methods may further determine a number of observed collisions in the area over the time period. The systems and methods may further calculate a risk index for the area based upon a comparison between the number of expected collisions and the number of observed collisions. The systems and methods may further select a travel route for a vehicle based upon the risk index.

Abstract: Systems and methods are disclosed for adjusting autonomous vehicle driving behavior. A controller of the autonomous vehicle may utilize an aggression factor to adjust control of the autonomous vehicle. The autonomous vehicle may detect one or more characteristics of proximate vehicles, analyze the one or more characteristics to estimate an aggression level of the proximate vehicles, and adjust the aggression factor based on the estimated aggression level.

Abstract: A method and computer system provides vehicle insurance underwriting and ratings to a policy holder. The method and system receives captured sensor data associated with a vehicle from the policy holder. For example, the captured sensor data may include vehicle image and sound data. The method and system may compare the received data to baseline data to determine an operating condition of the vehicle. Based at least in part on the determined operating condition of the vehicle, the method and system may identify a risk of loss for the vehicle. The method and system may then determine an insurance premium for the vehicle based at least in part on the identified risk of loss, and provide the determined insurance premium to the policy holder. In some embodiments, the sensor data is image and sound data captured by a user's mobile phone.

Abstract: A computer-implemented method for determining a risk rating of a vehicle. The method includes receiving information indicative of protections against unauthorized electronic access to one or more electronic systems of a vehicle. The method includes determining a vehicle security level based at least on the information indicative of protections against unauthorized electronic access. The method includes determining a risk rating associated with the vehicle. The method includes setting at least one parameter of an insurance policy associated with the vehicle based on at least the determined risk rating.

Abstract: Systems and methods relate to, inter alia, calculating a number of expected collisions in an area over a time period. The systems and methods may further determine a number of observed collisions in the area over the time period. The systems and methods may further calculate a risk index for the area based upon a comparison between the number of expected collisions and the number of observed collisions. The systems and methods may further select a travel route for a vehicle based upon the risk index.

Abstract: A method includes receiving vehicle sensor data from a second vehicle via one or more wireless signals. The vehicle sensor data is collected by a sensor that is located on or in the second vehicle and configured to sense an environment external to the second vehicle. The vehicle sensor data is received at an electronic processing system, and stored in a memory. A set of one or more characteristics of the environment external to the first vehicle is determined by processing the stored vehicle sensor data, and a risk indicator is determined based on the set of one or more characteristics, a risk indicator. An insurance rating for an insurance policy associated with the first vehicle is determined based on the risk indicator.

Abstract: A computer system or computer-implemented method may provide incentives to an insured customer for receiving sensor data indicating risk-reducing and risk-increasing behavior during the policy term. In-vehicle sensors or other devices may gather information about the vehicle and its use during the policy term and send the information to a back-end system for analysis. Based on this analysis, the back-end system may determine that the received information is indicative of risk-reducing or increasing behavior. Upon confirmation that the information indicates risk-reducing or increasing behavior, the back-end system may perform one or more actions defined by a set of rules to establish an incentive or disincentive for the customer corresponding to the behavior. For example, the system may modify the customer's insurance policy data, send an e-mail, letter, gift card, coupon, points, or other incentive or disincentive for the customer based on the analysis.