Abstract: A computer-implemented method for using a trained generative adversarial network to improve construction and urban planning includes receiving a semantically-segmented point cloud corresponding to a construction site; determining a volumetric soil measurement; and generating a cost estimate. A computing system for using a trained generative adversarial network to improve vehicle orientation and navigation includes one or more processors, and one or more memories having stored thereon computer-executable instructions that, when executed, cause the computing system to: receive a semantically-segmented point cloud corresponding to a construction site; determine a volumetric soil measurement; and generate a cost estimate. A non-transitory computer-readable medium includes computer-executable instructions that, when executed, cause a computer to: receive a semantically-segmented point cloud corresponding to a construction site; determine a volumetric soil measurement; and generate a cost estimate.

Abstract: A catastrophe analysis computing system includes a processor; an electronic network; and a memory having stored thereon non-transitory computer-executable instructions that, when executed by the processor, cause the system to: cause a client device to receive a exposure map layer; cause a filter graphical user interface and wind speed layers to be displayed in a graphical user interface; receive an input; and update the map graphical user interface. In another aspect, a method includes causing a client device to receive an exposure map layer; causing a filter graphical user interface and wind speed layers to be displayed in a graphical user interface; receiving an input; and updating the map graphical user interface. A method includes receiving an exposure map; displaying a filter graphical user interface; receiving an input; and updating a map graphical user interface.

Abstract: Vehicle costs may be allocated between users of a vehicle, including autonomous vehicles. A vehicle cost allocation (VCA) computing device receives an anticipated trip report associated with an anticipated future trip, the anticipated trip report associated with at least one vehicle user including an anticipated driver of the vehicle and an anticipated passenger, the anticipated trip report including at least one of an anticipated destination and a distance of the anticipated future trip. The VCA computing device is also configured to determine one or more anticipated vehicle costs for the anticipated future trip. 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 the anticipated driver and passenger and transmit the anticipated vehicle costs to for review by the anticipated driver.

Abstract: A home cost analysis server is configured to train an image processing program to identify features of homes, receive user input including a prospective home, and access a first database storing metadata and images associated with homes, including the prospective home, available for purchase. The server is also configured to input images of the prospective home to the machine-learned image processing program, which outputs a feature of the prospective home, access a second database storing historical ancillary costs, and perform a lookup in the second database to retrieve comparable historical ancillary costs associated homes having a comparable feature to the outputted feature. The server is further configured to analyze the metadata associated with the prospective home, the outputted feature, and the comparable historical ancillary costs to determine ancillary home costs associated with the prospective home, and display the ancillary home costs and an overall monthly cost for the prospective home.

Abstract: Example methods, apparatus, and articles of manufacture to capture and compress telematics data are disclosed herein. An example computer-implemented method, executed by a processor, to represent telematics data includes identifying, with the processor, a physical intersection of roads, identifying, with the processor, virtual lines crossing the roads, assigning, with the processor, ordinals to the virtual lines, representing, with the processor, a physical traversal through the physical intersection captured in first telematics data by a pair of the ordinals, and storing the pair of the ordinals in second compressed telematics data.

Abstract: A system and method are provided for controlling an interior configuration of a vehicle following a collision. Sensor data that includes, or is derived from data that includes, data collected by one or more sensors is received, and a vehicle accident condition indicative of an accident having occurred is detected by processing the sensor data. After detecting the vehicle accident condition, an actuator component is caused to prevent a passenger from adjusting an interior vehicle component outside a predetermined range of physical configurations, while allowing the passenger to adjust the interior vehicle component within the predetermined range of physical configurations.

Abstract: Systems and methods for providing real-time feedback to a driver of a vehicle based on real-time datasets is disclosed. The systems and methods include obtaining one or more sets of real-time data associated with a vehicle. Performing one or more operations on the set of real-time data, wherein the one or more operations are based on the set of real-time data. Generating, a feedback alert based on results of the one or more operations and one or more detected real-time behaviors of the vehicle. Providing the feedback alert for presentation at a user interface on-board the vehicle. The real-time data may include contextual data, environmental data, operating data, data for a plurality of drivers, or combinations thereof.

Abstract: Vehicles may have autonomous capabilities that permit the vehicle to navigate according to varying levels of participation by a human operator. A human operator may be associated with a driving capability profile and the environment surrounding a vehicle may be associated with an environmental risk profile. A vehicle, or another party in communication with a vehicle, may determine whether, based on the human operator's driving capability profile and the environmental risk profile, it is likely that the vehicle will be navigated more safely if there is a change to the vehicle's autonomous capabilities and a corresponding change to the human operator's driving responsibilities. If it is determined that a change in autonomous vehicle capability is likely to increase safe navigation of the vehicle, an insurer may offer an insurance premium cost reduction if the human operator agrees to the proposed change in autonomous capabilities.

Abstract: Computer-implemented methods, servers, and tangible, non-transitory computer-readable media storing instructions for creating one or more new insurance policy quotes for a customer associated with a customer vehicle may be may be described. The computer-implemented methods, servers, and instructions may include receiving a coverage type for the customer vehicle, causing usage data corresponding to the coverage type to be tracked, receiving the usage data, generating the new insurance policy quotes corresponding to the coverage type based upon at least the usage data, and causing the new insurance policy quotes to be displayed.

Abstract: A claims processing system includes a claims assistance component to handle the flow of data through the claim process. The data may include any documents submitted for claim processing and may be generated by disparate sources. The system may train one or more machine learning (ML) models to classify the unstructured data by insurance categories and/or determine workflow. The system may assist a user through a user device to upload or capture claims data with the device. The claims assistance component may classify the data and verify the data classification before uploading it to the servers. In examples, the claims assistance component may determine that the file size of the data exceeds a cellular data transfer threshold and determine to compress the data and/or hold the transfer until a free connection is detected.

Abstract: Method and systems generate optimized and online targeted messages. Various campaign criteria are provided having different advertising or marketing goals that cause the delivery of targeted messages. Messages may be generated based upon customer data, customer preferences, life events, marketing campaigns, predictive models, and/or propensity scores. For instance, messages may be sent when a propensity threshold score is exceeded indicating a high likelihood of a milestone event, which may be indicative of customer behavior or an event that is relevant to the campaign goal, thereby sending more relevant messages to customers. A milestone propensity score may be calculated using a predictive modeling algorithm having weighted data variables, which may include data provided by the customer or accessed through various sources, such as monitoring customer online interactions with their permission.

Abstract: A system comprising one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, cause the one or more processors to perform operations including: receiving sensor data detected by one or more image sensors in a vehicle, wherein the sensor data is representative of driver movements of a driver in the vehicle; categorizing the sensor data as driver postures representative of actions of the driver in the vehicle; rotating and scaling the driver postures to be standardized for different drivers and for different locations of the one or more image sensors within different vehicles; analyzing the sensor data to determine a reference position of the driver in the vehicle; and storing, in a database, the driver postures, as rotated and scaled, and the reference position of the driver in the vehicle. Other embodiments are disclosed.

Abstract: Methods and systems for automatically mitigating risks of insurance-related events to a property are provided. According to certain aspects, a smart home controller or insurance provider remote processor may analyze data received from a plurality of smart devices disposed on, within, or proximate to a property, as well as data received from an insurance provider. If it is determined that an actual or potential risk of property damage exists, the smart home controller or insurance provider remote processor may automatically issue commands to one or more smart devices to take actions that mitigate the risk. The smart home controller may also transmit information about the actual or potential risks and any mitigative actions to an insurance provider. The insurance provider remote processor may interpret the transmitted data to perform insurance activities, such as providing a discount and/or adjusting an insurance premium or policy associated with the property.

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: A system and computer-implemented method of identifying multiple mortgage ready properties. The method includes receiving, via one or more processors, information from a customer approved for a mortgage about preferences for a real estate property and accessing, at a memory coupled to one or more processors, a memory storage location to retrieve a plurality of mortgage ready real estate properties meeting one or more of the customer preferences information. The method further includes transmitting, via the one or more processors, the plurality of real estate properties meeting one or more of the customer preferences information to the customer.

Abstract: Systems and methods for using image analysis techniques to assess unsafe driving conditions by a vehicle operator are discloses. According to aspects, a computing device may access and analyze image data depicting the vehicle operator. In analyzing the image, the computing device may measure certain visible metrics as depicted in the image data and compare the metrics to corresponding threshold values, and may accordingly determine whether the vehicle operator is exhibiting an unsafe driving condition. The computing device may generate and present alerts that indicate any determined unsafe driving condition.

Abstract: Computer-implemented methods and computer systems are disclosed herein as implemented by a controller operatively coupled to a network of electric vehicles. The methods and systems include the controller (i) receiving a notification that an electric vehicle is stranded without sufficient power to operate; (ii) receiving information regarding the stranded electric vehicle; (iii) detecting one or more other electric vehicles in a vicinity of the stranded electric vehicle; (iv) receiving information regarding the detected one or more other electric vehicles; and/or (v) determining, based upon the received information, which of the detected one or more other electric vehicles to send a power source request. Alternatively, the notification may indicate that an electric vehicle has a low state of charge (SOC), or is otherwise has a battery in need of being recharged to facilitate the electric vehicle traveling to a destination.

Abstract: A method of generating a user mobility profile includes receiving mobility data; storing the mobility data; analyzing the mobility data; generating information; transmitting the generated information; and displaying the generated information. A computing system includes a processor; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to receive mobility data; store the mobility data; analyze the mobility data; generate information; transmit the generated information; and display the generated information. A non-transitory computer readable medium contains program instructions that when executed, cause a computer to receive mobility data; store the mobility data; analyze the mobility data; generate information; transmit the generated information; and display the generated information.

Abstract: Systems and methods for modifying operation of an autonomous vehicle in an emergency situation are disclosed. According to aspects, a computing device associated with the autonomous vehicle detects, based on sensor(s), an emergency event associated with the autonomous vehicle. In response to detecting the emergency event, the computing device determines location(s) of emergency vehicle(s) and determines an assistance location for the autonomous vehicle. The computing device determines which of the emergency vehicle(s) is a nearest emergency vehicle that is nearest to the assistance location, and transmits the assistance location to the nearest emergency vehicle. The computing device then causes the autonomous vehicle to travel to the assistance location.

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.