Abstract:
A computer implemented method for determining a yaw angle estimate or vehicle heading direction is presented. A data server may receive a plurality of telematics data originating from a client computing device and determine a first primary movement window from the telematics data. The data server may also determine a potential range of yaw angles from the plurality of telematics data from the first primary movement window and generate an equality that evaluates the potential range of yaw angles. The data server may further maximize the count of acceleration events of the telematics data from the first primary movement window to further generate one or more refined yaw angle estimates. The data server stores the one or more yaw angle estimates on a memory.
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 computer implemented method for determining a yaw angle estimate or vehicle heading direction is presented. A data server may receive a plurality of telematics data originating from a client computing device and determine a first primary movement window from the telematics data. The data server may also determine a potential range of yaw angles from the plurality of telematics data from the first primary movement window and generate an equality that evaluates the potential range of yaw angles. The data server may further maximize the count of acceleration events of the telematics data from the first primary movement window to further generate one or more refined yaw angle estimates. The data server stores the one or more yaw angle estimates on a memory.
Abstract:
Methods and systems for offering and providing trip-based vehicle insurance are provided. Information is received regarding a vehicle operator and a vehicle, and trip-based insurance policies including quantities of vehicle use units are offered to the customer. Based on selected coverage types, the insurance provider may generate an insurance quote for a policy having an amount of the vehicle use units and may facilitate a purchase transaction with the customer for the insurance policy. Once a policy is selected and purchased, the system and method monitor vehicle use to determine each use of a vehicle use unit. Each vehicle use unit generally corresponds to one vehicle trip, but additional vehicle trip limitations may be added that may result in additional charges when exceeded during the course of a vehicle trip.
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:
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:
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 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:
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.