Abstract: Systems and methods are disclosed for educating vehicle drivers. Auto insurance claim data may be analyzed to identify hazardous areas associated with an abnormally high amount or severity of vehicle collisions. A virtual navigation map of roads within the hazardous areas may be built or generated. A common cause of several vehicle collisions at a hazardous area may be identified, and a virtual reconstruction of a scenario involving the common cause and/or a road map of collisions locations of may be created. The virtual reconstruction of the scenario may be displayed on a driver education virtual simulator to enhance driver education and reduce the likelihood of vehicle collisions.

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: An automatic alarm system for a vehicle includes a sensor adapted to detect electromagnetic data, a computer system, and an automatic alarm mechanism. The computer system receives data from the sensor. A computer processor analyzes the data from the sensor to determine whether a pattern from the electromagnetic data has been detected and compares the pattern of electromagnetic data detected by the sensor with known patterns of electromagnetic data emitted by emergency vehicles that are stored in a library. The automatic alarm mechanism activates in response to the processor determining that the comparison matches a known pattern of electromagnetic data for an emergency vehicle resulting in the computer processor sending a first signal to activate an alarm of the vehicle.

Abstract: Systems and methods for providing awareness of emergency vehicles are provided. Sensors located around a vehicle may detect moving objects that pose potentially dangerous situations for the vehicle occupants and for the object. This can cause the doors to lock automatically in order to make the situation safer. Additionally, electromagnetic radiation sensors located around the vehicle may detect the lights and sounds of emergency vehicles. If the electromagnetic data from the electromagnetic radiation sensors match a known pattern of electromagnetic data emitted by emergency vehicles stored in a library an alarm may be sounded through the speakers of the vehicle in order to alert the vehicle occupants of an emergency vehicle in the vicinity.

Abstract: Systems and methods are disclosed for identifying high risk parking lots. High risk parking lots may be, for example, parking lots that pose a higher than average risk of collisions and/or theft. Auto insurance claim data may be analyzed to identify hazardous areas. A virtual navigation of roads within the hazardous area may be identified. Public parking lots within the virtual navigation map may be defined, with each public parking lot determined as either in a hazardous area or not. A vehicle may be determined to be approaching or parking in a parking lot in a hazardous area, and a nearby public parking lot not associated with the hazardous area may be selected instead. A route from a current position to the nearby public parking lot may be generated, and the vehicle may be routed to the nearby public parking lot. As a result, collisions and thefts may be reduced.

Abstract: Systems and approaches for estimating damage to property are described. In one approach, a damage estimation device is activated using a mobile computing device. This damage estimation device may then automatically capture (e.g., using an imaging sensor) a plurality of images of the damaged property. The damage estimation device may then calculate at least one characteristic of the damaged property from the plurality of captured images and further calculate at least one characteristic of the damage to the damaged property from the plurality of captured images. A repair estimate may then be calculated based at least on the at least one characteristic of the damaged property and the at least one characteristic of the damage. This repair estimate may then be transmitted.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an insured asset and the area surrounding an insured asset, such as with the policyholder or insured's permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device. The computing device may be associated with and/or utilized by an insurance provider to perform insurance-related tasks, such as processing the data to determine an amount of risk associated with the insured asset. If the amount of risk has increased, the computing device may provide a recommendation to a mobile device of the policyholder on how to reduce the risk such that corrective action may be taken. Insurance discounts may be provided based upon following recommendations that mitigate risk.

Abstract: A computer-implemented method for providing data associated with insured losses is presented. Data regarding an event that is a cause of the insured losses may be received. Respective indications of locations of properties insured by an insurance provider and sustaining the insured losses may be received. Image data from at least one image capturing device, where the image data is obtained from an aerial view of the properties and indicative of respective conditions of the properties, may be received. The image data may be processed to determine, for each property, an indication of the respective condition. The data associated with the insured losses may be provided via a user interface. The data associated with the insured losses may include (i) the respective indications of the locations of the properties, and (ii) the indications of the respective conditions of the properties.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding an insured or potentially insured asset, such as with the insurance customer's permission, and collect data related to the insured or potentially insured asset, such as size, height, roof shape, materials (siding, roofing), etc. which may form a basis of the underwriting detail used to evaluate a property. The drone data may reveal site characteristics, such as slope or grade of a parcel; the proximity to other structures (and their uses); trees; rivers; coastlines; and earthquake faults. The drone data may be used by an insurance provider remote server to assess the risk associated with an insured asset, generate or modify an insurance premium or discount, etc. The drone data may also be used to mitigate risk and prevent loss by alerting policyholders of the risk such that corrective action may be taken.

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 system and method are provided for improving vehicle awareness and safety by generating and transmitting alerts in response to detecting a hazard in the environment omnidirectional to a vehicle awareness system. Omnidirectional environment data, representing kinematic information pertaining to one or more physically detectable elements omnidirectional to the primary vehicle, is acquired by one or more sensors communicatively coupled to ta vehicle. The system analyzes the omnidirectional environment data to detect if one or more hazards in the omnidirectional environment data, representing a change in the kinetic behavior of the one or more physically detectable elements omnidirectional to the vehicle awareness system, has occurred. When the system detects one or more hazards in the omnidirectional environment data, the system generates and transmits an alert to vehicles, vehicle operators, mobile devices, or pedestrians at risk from the hazard.

Abstract: An automatic alarm system for a vehicle includes a sensor adapted to detect electromagnetic data, a computer system, and an automatic alarm mechanism. The computer system receives data from the sensor. A computer process analyzes the data from the sensor to determine whether a pattern from the electromagnetic data has been detected, accesses a library of known patterns of electromagnetic data emitted by emergency vehicles, and compares the pattern of electromagnetic data detected by the sensor with the known patterns of electromagnetic data emitted by emergency vehicles that are stored in the library. The automatic alarm mechanism activates in response to the processor determining that the comparison matches a known pattern of electromagnetic data for an emergency vehicle resulting in the computer processor sending a first signal to activate an alarm.

Abstract: The present embodiments relate to detecting fraudulent insurance claims. According to certain aspects, a central monitoring server may receive and examine data detected by at least one unmanned vehicle and generate an estimated insurance claim for a loss event. The central monitoring server may then receive an actual insurance claim relating to the loss event, and may compare the estimated insurance claim to the actual insurance claim to identify potential buildup included in the actual insurance claim. If buildup is detected, the central monitoring server may then process the actual insurance claim accordingly based upon the potential buildup. As a result, claim monies may be paid to insureds that more accurately reflect actual losses resulting from the loss event, and insurance cost savings may be ultimately passed onto typical insurance customers.

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: Systems and methods for control systems for facilitating situational awareness of a vehicle are provided. Sensors located around a stationary vehicle may detect moving objects that pose potentially dangerous situations for the vehicle occupants and for the object. This can cause the doors to lock automatically in order to make the situation safer. Additionally, electromagnetic radiation sensors located around the vehicle may detect the lights and sounds of emergency vehicles. If the electromagnetic data from the electromagnetic radiation sensors match a known pattern of electromagnetic data emitted by emergency vehicles stored in a library an alarm may be sounded through the speakers of the vehicle in order to alert the vehicle occupants of an emergency vehicle in the vicinity.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an area surrounding an insured or potentially insured asset, such as with the insurance customer's permission, and collect data related to the insured or potentially insured asset, such as size, height, roof shape, materials (siding, roofing), etc. which may form a basis of the underwriting detail used to evaluate a property. The drone data may reveal site characteristics, such as slope or grade of a parcel; the proximity to other structures (and their uses); trees; rivers; coastlines; and earthquake faults. The drone data may be used by an insurance provider remote server to assess the risk associated with an insured asset, generate or modify an insurance premium or discount, etc. The drone data may also be used to mitigate risk and prevent loss by alerting policyholders of the risk such that corrective action may be taken.

Abstract: Systems and methods are disclosed for identifying high risk parking lots. High risk parking lots may be, for example, parking lots that pose a higher than average risk of collisions and/or theft. Auto insurance claim data may be analyzed to identify hazardous areas. A virtual navigation of roads within the hazardous area may be identified. Public parking lots within the virtual navigation map may be defined, with each public parking lot determined as either in a hazardous area or not. A vehicle may be determined to be approaching or parking in a parking lot in a hazardous area, and a nearby public parking lot not associated with the hazardous area may be selected instead. A route from a current position to the nearby public parking lot may be generated, and the vehicle may be routed to the nearby public parking lot. As a result, collisions and thefts may be reduced.

Abstract: A system and method are provided for improving vehicle awareness and safety by generating and transmitting alerts in response to detecting a hazard in the environment omnidirectional to a vehicle awareness system. Omnidirectional environment data, representing kinematic information pertaining to one or more physically detectable elements omnidirectional to the primary vehicle, is acquired by one or more sensors communicatively coupled to a vehicle. The system analyzes the omnidirectional environment data to detect if one or more hazards in the omnidirectional environment data, representing a change in the kinetic behavior of the one or more physically detectable elements omnidirectional to the vehicle awareness system, has occurred. When the system detects one or more hazards in the omnidirectional environment data, the system generates and transmits an alert to vehicles, vehicle operators, mobile devices, or pedestrians at risk from the hazard.

Abstract: Unmanned aerial vehicles (UAVs) may facilitate insurance-related tasks. UAVs may actively be dispatched to an insured asset and the area surrounding an insured asset, such as with the policyholder or insured's permission and collect data related to the insured asset, such as images, video, audio, weather conditions, thermal signatures, wood and soil samples, etc., and transmit this data to a computing device. The computing device may be associated with and/or utilized by an insurance provider to perform insurance-related tasks, such as processing the data to determine an amount of risk associated with the insured asset. If the amount of risk has increased, the computing device may provide a recommendation to a mobile device of the policyholder on how to reduce the risk such that corrective action may be taken. Insurance discounts may be provided based upon following recommendations that mitigate risk.

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.