Abstract: Systems and methods for generating calm or quiet routes are provided. When a user requests navigation directions and indicates a preference for a calm route, a plurality of routes between the origin location and the destination location requested by the user may be identified. Historical sensor data (e.g., including heart rate data, exterior vehicle noise level data, accelerometer data) and traffic data associated with route segments of each of the routes may be analyzed to identify indications of calmness associated with each route segment. Current traffic data associated with the route segments may be analyzed to assign a traffic score representing a level of congestion along the segment and corresponding to a level of insurance risk associated with traversing the segment. Based at least in part upon the indications of calmness and the traffic score associated with each route segment, a route may be selected and presented to the user.

Abstract: Method and system for determining a status of a mobile device of a user are disclosed. For example, the method includes receiving first sensor data at a first time from an application installed on a mobile device of a user, determining a first location of the mobile device, immediately subsequent to receiving the first sensor data at the first time, receiving second sensor data at a second time from the application, the second time following the first time by a time interval, determining a second location of the mobile device, determining a distance between the first location and the second location, determining whether the distance corresponding to the time interval exceeds a predetermined threshold, and determining whether a trip log indicative of at least one trip during the time interval is received from the application.

Abstract: Telematics systems and methods are described for generating interactive animated guided user interfaces (GUIs). A telematics cloud platform is configured to receive vehicular telematics data from a telematics device onboard a vehicle. A GUI value compression component determines, based on the vehicular telematics data, a plurality of GUI position values and a plurality of corresponding GUI time values. A geospatial animation app receives the plurality of GUI position values and the plurality of corresponding GUI time values. The geospatial animation app implements an interactive animated GUI that renders a plurality of geospatial graphics or graphical routes on a geographic area map via a display device. The geospatial graphics or graphical routes are rendered to have different visual forms based on differences between respective GUI position values and corresponding GUI time values.

Abstract: The present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying images of occupants inside a vehicle by comparing current image feature data to previously classified image features.

Abstract: A telematics data marketplace (TDM) computing device including a processor in communication with a memory device is provided. The processor may be configured to: (i) receive registration data from a provider, wherein the registration data includes desired user data sets and an associated purchase price, (ii) retrieve, from the memory device, user data associated with a plurality of users, wherein the user data includes at least telematics data, (iii) match the provider to one or more users of the plurality of users based upon the user data associated with the users matching the desired user data sets of the provider, (iv) prompt the matched users to allow the provider access to the user data for the purchase price, (v) transmit the user data of the matched users to the provider, and (vi) provide the matched users with a reward corresponding to the purchase price of the desired user data set.

Abstract: Systems and methods of generating scenic routes and safe parking locations near scenic points are provided. Based at least in part upon a driver indication of a preference for a scenic route from an origin location to a destination location, a mobile device application may generate a scenic route by selecting route segments between the origin location and the destination location associated with a large number of scenic points. Scenic points may be identified based at least in part upon historical driver telemetry data and POI data. For instance, if historical telemetry data indicates that a large number of drivers stop briefly at a location not known to be near a POI, that location may be a scenic location (e.g., a location where drivers frequently leave their vehicles to take photos). Additionally, safe parking locations near each scenic point may be identified based at least in part upon historical vehicle damage data, and navigation directions to safe parking locations may be provided.

Abstract: An electronic device for displaying targeted messages on a surface of a vehicle is presented. The device includes a transceiver, one or more memories and processors, and an electronic display disposed on the surface. The electronic display displays a targeted message for a set of individuals associated with an environment of the vehicle. The one or more processors may detect environmental data associated with the environment of the vehicle, and generate demographic data from the environmental data. The generated demographic data may be indicative of at least one individual of the set of individuals. Further, the one or more processors may transmit the demographic data to an external processing server, which determines the targeted message from the demographic data. Finally, the one or more processors may receive the targeted message from the external processing server, and display the targeted message on the electronic display.

Abstract: An interaction detection and analysis (“IDA”) computing device that includes at least one processor in communication with at least one memory device is provided. The at least one processor being configured to store software ecosystem data, environmental condition data, and performance data in a plurality of data records in a database, wherein each data record i) is associated with one autonomous vehicle (AV) of a plurality of AVs and ii) includes the software ecosystem data, the environmental condition data, and the performance data of the corresponding AV; apply at least one machine learning algorithm to a set of the plurality of data records to identify an interaction between at least one software application and at least one environmental condition resulting in a particular outcome; and transmit, to at least one AV associated with the set of data records, at least one alert message advising of the particular outcome.

Abstract: Method and system for determining a status of a mobile device of a user are disclosed. For example, the method includes receiving first sensor data at a first time from an application installed on a mobile device of a user, determining a first location of the mobile device, immediately subsequent to receiving the first sensor data at the first time, receiving second sensor data at a second time from the application, the second time following the first time by a time interval, determining a second location of the mobile device, determining a distance between the first location and the second location, determining whether the distance corresponding to the time interval exceeds a predetermined threshold, and determining whether a trip log indicative of at least one trip during the time interval is received from the application.

Abstract: Systems and methods for generating calm or quiet routes are provided. When a user requests navigation directions and indicates a preference for a calm route, a plurality of routes between the origin location and the destination location requested by the user may be identified. Historical sensor data (e.g., including heart rate data, exterior vehicle noise level data, accelerometer data) and traffic data associated with route segments of each of the routes may be analyzed to identify indications of calmness associated with each route segment. Current traffic data associated with the route segments may be analyzed to assign a traffic score representing a level of congestion along the segment and corresponding to a level of insurance risk associated with traversing the segment. Based at least in part upon the indications of calmness and the traffic score associated with each route segment, a route may be selected and presented to the user.

Abstract: A system serializing and deserializing models configured to (i) store a first model, wherein the first model includes a plurality of functionalities; (ii) generate a human-readable document based on the first model, wherein the human-readable document describes the first model; (iii) generate a second model based on the human-readable document, wherein the second model includes the plurality of functionalities; and (iv) perform at least one execution of the second model.

Abstract: The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.

Abstract: The present embodiments may relate to determining an actual driver of a vehicle based upon telematics data. For instance, a driver identification (DI) computing device may be configured to: (1) receive a first plurality of measurements captured at a first user device during a trip taken by a vehicle; (2) receive a second plurality of measurements captured at a second user device during the trip; (3) determine, based upon the measurements, that the user devices are within the vehicle during the trip; (4) calculate a respective enhanced geographic location measurement for each of the measurements based upon the measurements; (5) determine, based upon the enhanced geographic location measurements, a predicted position of the second user device relative to the first user device; and (6) identify, from among the user devices, a driver user device based upon the predicted position of the second user device relative to the first user device.

Abstract: The present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle. More particularly, the present disclosure is directed to apparatuses, systems and methods for automatically classifying digital images of occupants inside a vehicle by comparing current image data to previously classified image data.

Abstract: Method and system for predicting fuel consumption efficiency. For example, the method includes collecting past user driving data for one or more past vehicle trips that have already been made by a user, analyzing the past user driving data to determine one or more past user driving features related to a past fuel consumption efficiency of the user, collecting information for one or more future vehicle trips that will be made by the user during a predetermined future period of time, and predicting a future fuel consumption efficiency of the user during the predetermined future period of time based at least in part upon the information for the one or more future vehicle trips and the determined one or more past user driving features.

Abstract: Method and system for selecting a vehicle route. For example, the method includes collecting information for a future vehicle trip that will be made by a user, generating multiple routes for the same future vehicle trip, predicting an amount of fuel consumption for each of the multiple routes based at least in part upon information for the route and user driving features of the user, and selecting a route from the multiple routes based at least in part upon the amounts of fuel consumption predicted for the user, where the selected route corresponds to a least amount among the amounts of fuel consumption predicted for the user.

Abstract: Method and system for providing carbon offsets. For example, the method includes collecting mindful driving data for one or more vehicle trips made by a user, analyzing the mindful driving data to determine a level of mindful driving of the user, determining a level of carbon offset reward based at least in part upon the level of mindful driving of the user, determining an amount of total carbon emission of the user, and providing an amount of carbon offset reward based at least in part upon the level of carbon offset reward and the amount of total carbon emission.

Abstract: Method and system for improving fuel consumption efficiency. For example, the method includes collecting user driving data for one or more vehicle trips made by a user between a particular pair of origination and destination points, analyzing the user driving data to determine one or more user driving features of a user driving behavior for the particular pair of origination and destination points, comparing the one or more user driving features with one or more desired driving features of a desired driving behavior for the particular pair of origination and destination points, determining a performance feedback based at least in part on the comparison, and providing the performance feedback to the user to improve a user fuel consumption efficiency for the particular pair of origination and destination points.

Abstract: Method and system for verifying a reliability of sensor data received from a mobile device of a user are disclosed. For example, the method includes receiving first sensor data collected and/or generated by one or more sensors of the mobile device from an application installed on a mobile device of a user at a first time, receiving second sensor data collected and/or generated by the one or more sensors of the mobile device from the application at a second time, determining whether the mobile device is in a vehicle that the user is driving during a time interval based at least upon the first sensor data and the second sensor data, and in response to the mobile device not being in the vehicle that the user is driving during the time interval, transmitting a notification to the mobile device indicating that the application does not work properly.

Abstract: A technical design solution for classifying users as potential drivers traveling in a vehicle based upon a combination of gathered data during a shared trip and historical data. Data gathered would include, at the least, overlapping time and distance of users to be classified as potential drivers. Shared trip scenarios, where a driver is identified, include (1) two or more users share a complete trip from beginning to end; (2) two or more users share the beginning of a trip, at least one user is dropped off, thereby ending their trip, and the other user continues driving; (3) two or more users share the end of a trip, where at least one user is picked up during the shared trip; and (4) one user picks up at least one other user during a trip, thereby creating a shared trip, and drops off the at least one other user to a different location, then heads to a final location.