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:
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:
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:
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:
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:
A computer implemented method for determining one or more idling time windows from a vehicle trip is presented. A data server may receive, via a computer network, a plurality of telematics data originating from a client computing device and identify primary movement data from the plurality of telematics data. The data server may also measure a total variance from the plurality of telematics data at one or more time stamps and determine an average total variance for an entire trip from the plurality of telematics data. The data server may further normalize total variance at the one or more time stamps using the generated average and determine one or more idling time windows from the normalized total variance.
Abstract:
A method for determining a yaw angle estimate or vehicle heading direction is presented. A potential range of yaw angles is generated based on a plurality of primary telematics data. One or more yaw angle estimates are generated from the potential range of yaw angles. A driving pattern is determined based on at least one of the yaw angle estimates. The primary telematics data is a plurality of telematics data originated from a client computing device. The effects of gravity have been removed from the plurality of telematics data in a first primary movement window.
Abstract:
A method for determining a yaw angle estimate or vehicle heading direction is presented. A potential range of yaw angles is generated based on a plurality of primary telematics data. One or more yaw angle estimates are generated from the potential range of yaw angles. A driving pattern is determined based on at least one of the yaw angle estimates. The primary telematics data is a plurality of telematics data originated from a client computing device. The effects of gravity have been removed from the plurality of telematics data in a first primary movement window.
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:
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.