Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a processor. The monitoring device also includes an output interface coupled to the processor that communicates information to a driver of the vehicle. The monitoring device further includes a communication interface coupled to the processor. The processor receives, via the communication interface, sensor information relating to operating the vehicle. The processor also receives, via the communication interface, a risk factor relating to operating the vehicle based at least in part on the sensor information. The processor further outputs, via the output interface, an adjustment to an insurance premium of the driver, an adjustment to an insurance deductible of the driver, or a payment amount of the driver, based at least in part on the risk factor.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a processor. The monitoring device also includes an output interface coupled to the processor that communicates information to a driver of the vehicle. The monitoring device further includes a communication interface coupled to the processor. The processor receives, via the communication interface, sensor information relating to operating the vehicle. The processor also receives, via the communication interface, a risk factor relating to operating the vehicle based at least in part on the sensor information. The processor further outputs, via the output interface, an adjustment to an insurance premium of the driver, an adjustment to an insurance deductible of the driver, or a payment amount of the driver, based at least in part on the risk factor.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a communication interface and one or more processors coupled to the communication interface. The one or more processors receive, via the communication interface, sensor information relating to operating the vehicle. The one or more processors also receive, via the communication interface, contextual information based at least in part on the sensor information relating to operating the vehicle. The one or more processors further generate a risk factor relating to operating the vehicle based at least in part on the sensor information and the contextual information.

Abstract: A system includes a monitoring device coupled to a vehicle. The monitoring device includes a processor. The monitoring device also includes an output interface coupled to the processor that communicates information to a driver of the vehicle. The monitoring device further includes a communication interface coupled to the processor. The processor receives, via the communication interface, sensor information relating to operating the vehicle. The processor also receives, via the communication interface, a risk factor relating to operating the vehicle based at least in part on the sensor information. The processor further outputs, via the output interface, an adjustment to an insurance premium of the driver, an adjustment to an insurance deductible of the driver, or a payment amount of the driver, based at least in part on the risk factor.

Abstract: Techniques are described for adjusting policy characteristics based on a determined similarity between routes. A similarity metric may be determined indicating the similarity between a first route followed by a vehicle and/or driver and a second (e.g., previous) route followed by the vehicle and/or driver. A similarity metric may indicate the similarity in movements, and changes in movement, exhibited by the vehicle on the routes. The similarity metric may be determined through analysis of real time data collected by in-vehicle sensor(s), mobile user device(s), external sensors or other data sources. Based on the similarity metric, a premium, a deductible, a price, or other characteristic(s) of a policy may be determined. In some examples, policy characteristics may be adjusted (e.g., in real time) based on the analysis according to changing risk conditions if a driver is following routes that are dissimilar from typical routes.