Abstract: In a computer-implemented method, alert responsiveness data indicating how responsive a driver is to one or more types of vehicle alerts is received. The method also includes generating or modifying a driver profile associated with the driver, the driver profile including alert responsiveness profile information based upon the alert responsiveness data, and identifying, based at least upon the generated or modified driver profile, a suggested vehicle type. Identifying the suggested vehicle type includes determining that the generated or modified driver profile meets a set of one or more matching criteria associated with the suggested vehicle type at least in part by determining that the alert responsiveness profile information meets one or more criteria indicative of reliability of the suggested vehicle type. The method also includes causing an indication of the suggested vehicle type to be displayed to a user.

Abstract: In a computer-implemented method, telematics data collected during one or more time periods by one or more electronic subsystems of a vehicle, and/or by a mobile electronic device of the driver or a passenger, is received. The telematics data includes operational data indicative of how a driver of the vehicle operated the vehicle. The received telematics data is analyzed to identify driving behaviors of the driver during the time period(s). Based at least upon the driving behaviors, a driver profile is generated or modified. Based at least upon the generated or modified driver profile, a suggested vehicle type is identified, at least by determining that the profile meets a set of one or more matching criteria associated with the suggested vehicle type. An indication of the suggested vehicle type is displayed to a user.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Abstract: A computer-implemented method in a mobile computing device for tracking health and usage of electric vehicle (EV) batteries using Quick Response (QR) codes (or NFC or RFID tags) is provided. The method may include (1) capturing, by a camera associated with a mobile computing device, an image of a tag affixed to an EV; (2) analyzing the image of the tag affixed to the EV; (3) identifying, by the one or more processors of the mobile computing device, the EV based upon analyzing the image of the tag affixed to the EV; (4) determining vehicle battery data associated with a rechargeable battery that powers the identified EV; (5) determining based upon the vehicle battery data associated with the rechargeable battery that powers the identified EV, a battery status indication corresponding to the identified EV; and/or (6) providing, via a user interface, the battery status indication corresponding to the identified EV.

Abstract: A computer-implemented method in a mobile computing device for tracking health and usage of electric vehicle (EV) batteries using Quick Response (QR) codes (or NFC or RFID tags) is provided. The method may include (1) capturing, by a camera associated with a mobile computing device, an image of a tag affixed to an EV; (2) analyzing the image of the tag affixed to the EV; (3) identifying, by the one or more processors of the mobile computing device, the EV based upon analyzing the image of the tag affixed to the EV; (4) determining vehicle battery data associated with a rechargeable battery that powers the identified EV; (5) determining based upon the vehicle battery data associated with the rechargeable battery that powers the identified EV, a battery status indication corresponding to the identified EV; and/or (6) providing, via a user interface, the battery status indication corresponding to the identified EV.

Abstract: A computer-implemented method of monitoring one or more batteries of an electric vehicle (EV) includes (i) detecting an indication of a battery failure event for an electric vehicle; (ii) determining a response to the battery failure event based upon the indication; (iii) determining, based upon the battery failure event, an assistance location for the electric vehicle; (iv) generating a route from a location of an autonomous vehicle to the assistance location for the electric vehicle; and (v) transmitting a command to the autonomous vehicle to drive to the assistance location for the electric vehicle, wherein the command includes the response to the battery failure event and the route from the location of the autonomous vehicle to the assistance location.

Abstract: A computer-implemented method of predicting and providing an efficient driving route for an electric vehicle (EV) based upon battery health impact includes (i) receiving geographical telematics data; (ii) generating one or more driving routes for the electric vehicle based upon at least the geographical telematics data; (iii) predicting a projected battery health impact on a battery of the electric vehicle for each driving route of the one or more driving routes, wherein the projected battery health impact for each driving route is based at least upon geographical characteristics of the driving route; (iv) determining one or more battery-efficient driving route recommendations based upon at least the projected battery health impact for each driving route; and/or (v) providing the one or more battery-efficient driving route recommendations to a user.

Abstract: A server and non-transitory computer-readable storage medium storing instructions for monitoring one or more batteries of an electric vehicle (EV) comprising computing instructions for (i) receiving, from an electronic device associated with the EV, telematics data generated by one or more sensors associated with the electronic device that is indicative of operation of the EV; (ii) determining a battery status of the one or more batteries based upon the telematics data; and (iii) mapping the battery status of the one more batteries to a digital record corresponding to the EV in a database.

Abstract: Computer-implemented methods of monitoring one or more batteries of an electric vehicle (EV) include (i) receiving, from an electronic device associated with the EV, telematics data generated by one or more sensors associated with the electronic device that is indicative of operation of the EV; (ii) determining a battery status of the one or more batteries based upon the telematics data; and (iii) mapping the battery status of the one more batteries to a digital record corresponding to the EV in a database.

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: 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: 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: In a computer-implemented method for detecting and acting upon driver behavior while driving with passengers, telematics data is collected by one or more electronic subsystems of a vehicle and/or mobile electronic device of a driver or passenger. The collected data is transmitted to a computer system, and analyzed to identify respective time periods during which the driver of the vehicle drove with and without passengers, and one or more driving behaviors of the driver during those time periods. The method also includes determining, based upon the driving behavior(s) of the driver during the time periods with and without passengers, how the driver modifies his or her driving when driving with or without passengers, and conveying to an entity at least a portion of a driver profile associated with the driver that has been adjusted based upon how the driver modifies his or her driving.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

Abstract: Systems and methods are disclosed for estimating slipperiness of a road surface. This estimate may be obtained using an image sensor mounted on a vehicle. The estimated road slipperiness may be utilized when calculating a risk index for the road, or for an area including the road. If a predetermined threshold for slipperiness is exceeded, corrective actions may be taken. For instance, warnings may be generated to human drivers that are in control of driving vehicle, and autonomous vehicles may automatically adjust vehicle speed based upon road slipperiness detected.

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: Vehicle usage-based data, including telematics data, may be utilized to generate and/or adjust one or more terms (e.g., a variable interest rate and/or variable principle amount) of a variable vehicle loan. Telematics data may include, for example, data generated via a vehicle data system and/or a mobile electronic device. The one or more terms may be additionally or alternatively be adjusted based upon transportation metrics associated with usage of the vehicle by a transportation network company (TNC) and/or TNC driver.

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: Systems and methods for control systems for facilitating situational awareness of a vehicle are provided. Sensors located around a vehicle may detect moving objects located in one or more vehicle blind spots. These moving objects pose potentially dangerous situations for the vehicle occupants and for the object. The sensors may further determine that the moving object is a cyclist approaching a vehicle blind spot, and that the vehicle is parked. Processors associated with the vehicle may then direct a corrective action, such as automatically locking the vehicle doors, to prevent a vehicle-cyclist collision. The systems and methods provided herein may thereby make these and similar situations safer.

Abstract: In a computer-implemented method for detecting and acting upon driver compliance with driver-specific limitations, it is determined that a driver of a vehicle has one or more limitations specific to a medical condition and/or a physical characteristic of the driver. Telematics data is received and analyzed to identify a plurality of driving behaviors of the driver. Based upon the driving behaviors, a level of compliance with the limitations is determined. Based upon the level of compliance, at least a portion of a driver profile is set. At least the portion of the profile is transmitted to an entity that adjusts a credit rating of the driver, adjusts an insurance rating of the driver, reviews at least the portion of the profile in connection with a job sought by the driver, or offers a permanent or temporary credit in connection with a good or service offered by the entity. As a result, benefits or cost savings may be provided to risk-averse drivers.