Abstract: Apparatuses, systems, and methods are provided for the utilization of vehicle control systems to cause a vehicle to take preventative action responsive to the detection of a near short term adverse driving scenario. A vehicle control system may receive information corresponding to vehicle operation data and ancillary data. Based on the received vehicle operation data and the received ancillary data, a multi-dimension risk score module may calculate risk scores associated with the received vehicle operation data and the received ancillary data. Subsequently, the vehicle control systems may cause the vehicle to perform at least one of a close call detection action and a close call detection alert to lessen the risk associated with the received vehicle operation data and the received ancillary data.

Abstract: Systems and methods provide for configuring and transferring multiple data files including image data files using a mobile computing device. A mobile computing device may acquire multiple data files including image files from disparate sources and transmit them to an enhanced image processing server. The enhanced image processing server may analyze the received image files using various techniques. To aid in analysis, the server may also interface with various internal and external databases storing reference images or other reference data of previously analyzed similar data. Further still, the enhanced image processing server may transmit a result of the analysis back to a mobile computing device.

Abstract: Intelligent routing systems and methods of use to match a user from a user call with a unique ID associated with the user, generate a plurality of call reason predictions for the user call with an intelligent router module of the intelligent routing system based on the unique ID, generate a confidence level and a likelihood rating with the intelligent router module for each call reason prediction of the plurality of call reason predictions, determine a call reason prediction with a highest likelihood rating and such that the confidence level for the call reason prediction exceeds an associated confidence level threshold that is machine learned and adjustable, determine a call routing service mode from a plurality of service modes based on the call reason prediction, and route the user call to the call routing service mode.

Abstract: Electronic digital display systems, including roadside display devices, vehicle-based devices, personal mobile devices, intermediary servers, advertising servers, and/or additional external data sources may operate individually or in combination to identify one or more vehicle locations, driving routes, driver and passenger characteristics, and the like. Vehicle and individual characteristics may be determined based on data received from traffic cameras, vehicle-based devices, personal mobile devices, and/or other data sources. Based on the vehicle characteristics, individual characteristics, driving data and driving patterns, and the like, digital content may be determined for electronic roadside displays to be viewable by the approaching vehicles, and/or other digital display devices to be viewable by associated individuals via other display devices and at other times.

Abstract: Systems and methods provide for an automated system for analyzing damage and processing claims associated with an insured item, such as a vehicle. An enhanced claims processing server may analyze damage associated with the insured item using photos/video transmitted to the server from a user device (e.g., a mobile device). The mobile device may receive feedback from the server regarding the acceptability of submitted photos/video, and if the server determines that any of the submitted photos/video is unacceptable, the mobile device may capture additional photos/video until all of the data are deemed acceptable. To aid in damage analysis, the server may also interface with various internal and external databases storing reference images of undamaged items and cost estimate information for repairing previously analyzed damages to similar items. Further still, the server may generate a payment for compensating a claimant for repair of the insured item.

Abstract: Systems and methods are disclosed for generating vehicle insurance rates based on driver-independent variables and/or driver-dependent variables. Vehicle insurance rates may additionally or alternatively be based on changes in the level of autonomy of vehicles. In some embodiments, a density of vehicles near a target vehicle may be tracked. Vehicle insurance rates may be determined based on the vehicle density. Furthermore, systems and methods are disclosed for analyzing a driver's use of autonomous vehicle features and/or the driver's maintenance of the autonomous vehicle. The driver may also be taught certain driving skills by enabling vehicle teaching features. The driver's response to these teaching features may be monitored, and a reward or recommendation may be generated and provided to the driver based on the driver's response.

Abstract: A central claims adjuster control unit associated with an entity may oversee the assignment of claims cases to claims adjusters. The control unit may designate that a threshold number of cases may be assigned to certain claims adjusters. When new claims cases arrive, the control unit may monitor the workload of each of the claims adjusters and the threshold value assigned to any of the claims adjusters before assigning the case to one of the adjusters. If no adjuster is available, the control unit may store the case(s) in a memory until one of the adjusters becomes available. An additional feature of the control unit includes a user interface for modifying information about claims adjusters, including whether or not a threshold value is associated with them, the value of any associated threshold, and the reassignment of cases from one adjuster to another.

Abstract: Apparatuses, systems, methods, and computer-readable media are provided for the logical configuration of vehicle control systems based on driver profiles. A vehicle control computer may identify driving behavior of a driver of a vehicle through vehicle operation data provided by one or more of vehicle sensors, a telematics device, and a mobile device. Based on the driving behavior, the vehicle control computer may develop a first driving profile for the driver of the vehicle. The vehicle control computer transmit the first driving profile to a remote server storing driving profiles of a plurality of users. The vehicle control computer may download a second driving profile associated with a different driver from the remote server. The vehicle control computer may configure vehicle operations based off of the second driving profile associated with the different driver and may actuate vehicle operation based on the configuration.

Abstract: Systems and methods are disclosed for generating vehicle insurance rates based on driver-independent variables and/or driver-dependent variables. Vehicle insurance rates may additionally or alternatively be based on changes in the level of autonomy of vehicles. In some embodiments, a density of vehicles near a target vehicle may be tracked. Vehicle insurance rates may be determined based on the vehicle density. Furthermore, systems and methods are disclosed for analyzing a driver's use of autonomous vehicle features and/or the driver's maintenance of the autonomous vehicle. The driver may also be taught certain driving skills by enabling vehicle teaching features. The driver's response to these teaching features may be monitored, and a reward or recommendation may be generated and provided to the driver based on the driver's response.

Abstract: A system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a first computing device associated with a driver of the vehicle, and a driving behaviors analysis server, comprising hardware including a processor and memory. The driving behaviors analysis server may receive, from the one or more sensors and via the telematics device, driving data of the driver of the vehicle and identify one or more driving behaviors of the driver over a predetermined period of time. The driving behaviors analysis server may then determine one or more of the driving behaviors to be indicative of unsafe driving by the driver. Further, based on the determination of unsafe driving behaviors, the driving behaviors analysis server may transmit, to the first computing device, a message on behalf of an insurance provider, recommending the driver to stop or limit driving.

Abstract: Systems, methods, computer-readable media, and apparatuses for receiving requests for roadside assistance, generating user interfaces and using machine learning to generate roadside assistance instructions are provided. In some examples, a request for roadside assistance may be received. A user and one or more partners may be identified based on the request. In some examples, a profile associated with the user, partner or the like may be identified. A user interface may be generated based on the profile and may include features unique to the profile, partner, or the like. In some arrangements, the interface may include a first portion and a second portion. Selection of an option from the first portion may cause the system to identify data for display in the second portion and cause the data to be displayed in the second portion. Machine learning may be used to determine or identify one or more roadside assistance instructions and a roadside assistance instruction may be generated and executed.

Abstract: Systems, methods, apparatuses and computer-readable media for analyzing vehicle claim information from a vehicle that is deemed a total loss to determine one or more parts that may be removed from the total loss vehicle for reuse is presented. In some arrangements, the parts identified for reuse may be identified prior to removal from the total loss vehicle and may be identified as available inventory and may include a future availability date. One or more repair shops may then request the parts available for reuse and the part may be reserved for that shop until it becomes available.

Abstract: Systems and methods are disclosed for generating a display of a navigation map. The system may comprise a historical data source device having, for example, a historical data source computer and a database storing historical data associated with one or more of vehicle accident data, traffic data, vehicle volume data, vehicle density data, road characteristic data, or weather data. The system may comprise a map data processing device having a map data processing computer and memory storing computer-executable instructions that, when executed by the map data processing computer, cause the map data processing device to, for example, determine, based on a location determining device, a location of a vehicle. The map data processing system may determine one or more historical factors based on the location of the vehicle. The map data processing system may receive, from the historical data source device and for the location, historical data associated with the one or more historical factors.

Abstract: Apparatuses and methods may provide for generating, maintaining, and using an inventory for insurance purposes. An optimized inventory analysis server may generate and maintain user profile information for determining a demographic classification of each user associated with an inventory. A demographic classification for a given user may be used along with data related to items owned by other users to determine one or more items for recommendation to the given user. Details associated with existing insurance coverage levels may also be used to recommend new insurance products to the user. In addition, the optimized inventory analysis server may determine a depreciated value of each item within an inventory. These values may be used to assess loss and settle an insurance claim for damage to one or more of the items in the inventory.

Abstract: Methods, computer-readable media, systems, and/or apparatuses for evaluating movement data to identify a user as a driver or non-driver passenger are provided. In some examples, movement data may be received from a mobile device of a user. The movement data may include sensor data including location data, such as global positioning system (GPS) data, accelerometer and/or gyroscope data, and the like. Additional data may be retrieved from one or more other sources. For instance, additional data such as usage of applications on the mobile device, public transportation schedules and routes, image data, vehicle operation data, and the like, may be received and analyzed with the movement data to determine whether the user of the mobile device was a driver or non-driver passenger of the vehicle. Based on the determination, the data may be deleted in some examples or may be further processed to generate one or more outputs.

Abstract: Systems and methods are disclosed for generating vehicle insurance rates based on driver-independent variables and/or driver-dependent variables. Vehicle insurance rates may additionally or alternatively be based on changes in the level of autonomy of vehicles. In some embodiments, a density of vehicles near a target vehicle may be tracked. Vehicle insurance rates may be determined based on the vehicle density. Furthermore, systems and methods are disclosed for analyzing a driver's use of autonomous vehicle features and/or the driver's maintenance of the autonomous vehicle. The driver may also be taught certain driving skills by enabling vehicle teaching features. The driver's response to these teaching features may be monitored, and a reward or recommendation may be generated and provided to the driver based on the driver's response.

Abstract: Systems and methods are disclosed for generating vehicle insurance rates based on driver-independent variables and/or driver-dependent variables. Vehicle insurance rates may additionally or alternatively be based on changes in the level of autonomy of vehicles. In some embodiments, a density of vehicles near a target vehicle may be tracked. Vehicle insurance rates may be determined based on the vehicle density. Furthermore, systems and methods are disclosed for analyzing a driver's use of autonomous vehicle features and/or the driver's maintenance of the autonomous vehicle. The driver may also be taught certain driving skills by enabling vehicle teaching features. The driver's response to these teaching features may be monitored, and a reward or recommendation may be generated and provided to the driver based on the driver's response.

Abstract: Systems and methods provide for an automated system for analyzing damage to process claims and pre-claim consultations associated with an insured item, such as a vehicle. An enhanced claims processing server may analyze damage associated with the insured item using photos/video transmitted to the server from a user device (e.g., a mobile device). The mobile device may receive feedback from the server regarding the acceptability of submitted photos/video, and if the server determines that any of the submitted photos/video is unacceptable, the mobile device may capture additional photos/video until all of the data are deemed acceptable. In addition, the server may interface with third party entities such as repair shops and may generate a payment for compensating a claimant for repair of the insured item.

Abstract: Methods, systems, and computer-readable media consistent with the present disclosure manage multiple telephone calls by managing a session record associated with the call, amending the session record according to a plurality of rules to reflect a plurality of instructed actions, evaluating an amended session record to derive at least one of the plurality of instructed actions, and implementing a derived instructed action on the call under the control of an automated apparatus.

Abstract: A system may be configured to detect an emergency condition at a premises; dispatch one or more autonomous drones to a location associated with the emergency condition; receive from the one or more autonomous drones, sensor data associated with the emergency condition; generate, based on the sensor data, a plan identifying an evacuation route for safely evacuating the premises; and transmit an instruction that causes the one or more autonomous drones to indicate, to one or more persons in a vicinity of the emergency condition, the evacuation route. The system may further detect, based on the sensor data, one or more safe areas in the premises, and the evacuation route may pass through at least one of the one or more safe areas.