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: Systems and methods are provided for controlling operation of a vehicle. An example system for controlling operation of a vehicle includes one or more data collection components and one or more processors. The one or more data collection components are configured to collect data representative of a physical configuration of an interior vehicle component. The one or more processors are configured to access the collected data, determine, by processing the collected data, the physical configuration of the interior vehicle component, select a manner of operation based upon the determined physical configuration of the interior vehicle component, and cause the vehicle to operate according to the manner of operation.

Abstract: Described herein are methods and systems for generating and applying vehicle maintenance models to vehicle telematics data. A vehicle telematics analytics (VTA) computing device is configured to receive vehicle telematics data associated with operation of a subject vehicle, and apply the received vehicle telematics data to a vehicle maintenance model to determine whether the operation of the subject vehicle is better or worse than standard operation of like vehicles. The VTA computing device may adjust a maintenance cost and/or determine if a user of the vehicle is eligible for a reward based upon this determination. The VTA computing device is configured to transmit an itemized report to the user including the adjusted maintenance cost and/or the reward as well as one or more other vehicle costs.

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 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 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: 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 for real-time detection and mitigation anomalous behavior of a remote vehicle are provided, e.g., vehicle behavior that is consistent with distracted or unexpectedly disabled driving. On-board and off-board sensors associated with a subject vehicle may monitor the subject vehicle's environment, and behavior characteristics of a remote vehicle operating within the subject vehicle's environment may be determined based upon collected sensor data. The remote vehicle's behavior characteristics may be utilized to detect or determine the presence of anomalous behavior, which may be anomalous for the current contextual conditions of the vehicles' environment. Mitigating actions for detected remote vehicle anomalous behaviors may be suggested and/or automatically implemented at the subject vehicle and/or at proximate vehicles to avoid or reduce the risk of accidents, injury, or death resulting from the anomalous behavior. In some situations, authorities may be notified.

Abstract: Systems and methods for determining the effectiveness of vehicle safety features are provided. Vehicle data is obtained for vehicles having various smart safety features, and a list of translated vehicle build records is generated from the obtained data applying OEM-agnostic terminology for the smart safety features. A machine learning algorithm may be trained to generate an effectiveness score associated with one or more smart safety features, at least by analyzing a plurality of translated vehicle build records, vehicle telematics data, and vehicle accident records associated with each of the plurality of vehicles.

Abstract: Systems and methods for determining a reparability of a vehicle are provided. In some embodiments, vehicle data is obtained, and a list of variables is generated from the obtained data. A machine learning algorithm may then be trained to generate a reparability metric by: (i) generating correlation metrics between the variables and costs to repair the vehicle, (ii) removing variables with correlation metrics below a threshold, and (iii) training the machine learning algorithm based upon unremoved variables.

Abstract: Systems and methods for building a vehicle data repository (VDR) are provided. In some embodiments, the VDR is constructed by adding standardized build sheets to it. The standardized build sheets may be constructed by selecting data from various data sources (e.g., original equipment manufacturer (OEM) databases, National Highway Traffic Safety Administration (NHTSA) databases, Highway Loss Data Institute (HLDI) databases, and/or Insurance Institute for Highway Safety (IIHS) databases). Furthermore, a common ontology may be created and applied to the various data sources to aide in the selection of data between the data sources to construct the standardized build sheets.

Abstract: A computer implemented method for providing insurance comprises receiving a plurality of vehicle data including a start point, an end point and a frequency value. The method further comprises analyzing the plurality of vehicle data to determine a driving route associated with the vehicle. The method also comprises determining, based on the frequency value, that the driving route is a common driving route and a risk level of the common driving route. The method further comprises processing one or more insurance options, including pricing and underwriting, based at least in part on the risk level of the common driving route.

Abstract: A system and method are provided for controlling an interior configuration of a vehicle. The system may include an interior vehicle component, an actuator component configured to adjust a physical configuration of the interior vehicle component, an external communication component configured to collect driving environment data representing an external environment of the vehicle, and one or more processors configured to receive driving environment data and detect, by processing the driving environment data, an external driving condition. When the one or more processors detect the external driving condition, the one or more processors may cause the actuator component to adjust the interior vehicle component from a first physical configuration to a second physical configuration, or may cause the actuator component to restrict movement of the interior vehicle component to a predetermined range of physical configurations.

Abstract: A computer implemented method for determining a primary movement window from a vehicle trip is presented. A client computing device may be placed in a vehicle, be free to move with respect to movement of the vehicle, and include an accelerometer. A computer network may receive a plurality of telematics data originating from the client computing device. One or more processors may select one or more data points from the telematics data, and determine that a total spectral power of the selected data points meets a threshold value. The one or more processors may identify a primary movement window including the selected data points if the total spectral power of the selected data points does not meet the threshold value.

Abstract: Systems and methods are provided for dynamically protecting transportable articles in vehicles. A system for dynamically protecting a transportable article in a vehicle may include one or more processors and non-volatile memory storing instructions. The instructions, when executed by the one or more processors, cause the system to determine at least one of a characteristic or a trait of the transportable article; detect, based on sensed data, an emergency condition; select one or more article protection components based on (i) the at least one of the characteristic or the trait of the transportable article, and (ii) the detected emergency condition; and in response to detecting the emergency condition, deploy the selected one or more article protection components to protect the transportable article.

Abstract: Systems and methods for situational modification of autonomous vehicle operation are disclosed. According to aspects, a computing device may detect the occurrence of an emergency event and may determine a current operation of an autonomous vehicle that may be associated with the emergency event. The computing device may determine a modification to operation of the autonomous vehicle, where the modification may represent a violation of a roadway regulation that may enable effective handling of the emergency event. The computing device may generate a set of instructions for the autonomous vehicle to execute to cause the autonomous vehicle to undertake the operation modification.

Abstract: Apparatuses, systems and methods are provided for generating a vehicle driver signature. More particularly, apparatuses, systems and methods are provided for generating a vehicle driver signature based on current image data, previously classified image data, and vehicle dynamics data.

Abstract: Systems and methods for real-time detection and mitigation anomalous behavior of a remote vehicle are provided, e.g., vehicle behavior that is consistent with distracted or unexpectedly disabled driving. On-board and off-board sensors associated with a subject vehicle may monitor the subject vehicle's environment, and behavior characteristics of a remote vehicle operating within the subject vehicle's environment may be determined based upon collected sensor data. The remote vehicle's behavior characteristics may be utilized to detect or determine the presence of anomalous behavior, which may be anomalous for the current contextual conditions of the vehicles' environment. Mitigating actions for detected remote vehicle anomalous behaviors may be suggested and/or automatically implemented at the subject vehicle and/or at proximate vehicles to avoid or reduce the risk of accidents, injury, or death resulting from the anomalous behavior. In some situations, authorities may be notified.

Abstract: Systems and methods for real-time detection and mitigation anomalous behavior of a remote vehicle are provided, e.g., vehicle behavior that is consistent with distracted or unexpectedly disabled driving. On-board and off-board sensors associated with a subject vehicle may monitor the subject vehicle's environment, and behavior characteristics of a remote vehicle operating within the subject vehicle's environment may be determined based upon collected sensor data. The remote vehicle's behavior characteristics may be utilized to detect or determine the presence of anomalous behavior, which may be anomalous for the current contextual conditions of the vehicles' environment. Mitigating actions for detected remote vehicle anomalous behaviors may be suggested and/or automatically implemented at the subject vehicle and/or at proximate vehicles to avoid or reduce the risk of accidents, injury, or death resulting from the anomalous behavior. In some situations, authorities may be notified.