Systems, methods, and devices for enforcing do not disturb functionality on mobile devices
摘要
說明書
Increasingly, insurance companies and underwriters are basing the cost of insuring motorists on a multitude of things such as but not limited to daily mileage, time of day for drives, age of the driver, etc. A number of insurance companies are currently attempting to more accurately assign insurance costs and premiums on companies and upon individual users or families based on the driving habits of said drivers being insured. A number of data points are taken into consideration when establishing such costs and premiums, including but not limited to tracking and monitoring harsh braking events, average and top speeds, speeds compared to speed limits, hard acceleration events, hard cornering, and the like. Much of this data can be collected by the on-board computer of many vehicles, by control devices, as described herein, that are installed in vehicles, and based on data that can be collected by the mobile devices themselves. The challenge for this insurance cost model occurs when there are multiple users of this insurance in the same vehicle at the same time. Data collected for multiple users within the same vehicle will identify the same data points for all mobile devices within the vehicle—regardless of which device user is driving. For example, Driver X may be the safer and less risky of the two drivers in the eyes of the insurance company; however, if Driver Y is riding as a passenger when Driver X is driving, the data collected about Driver X's driving behavior will also be applied, incorrectly, to Driver Y. And, thus, the lower risk profile of Driver X may be incorrectly assigned to Driver Y. The inverse is also true. If Driver Y is driving and has the higher risk profile, all data collected about risky Driver Y may be incorrectly attributed to safer Driver X when Driver X is merely riding as a passenger of Driver Y.
