Patent Application Titled “Using Contextual Information For Vehicle Trip Loss Risk Assessment Scoring” Published Online (USPTO 20230089020): Patent Application

2023 APR 12 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Washington, D.C., by NewsRx journalists, a patent application by the inventors Black, Zebediah Robert (Wylie, TX, US); Casmedes, Corey (Plano, TX, US); Dang, Hoang (Garland, TX, US); Gao, Yuncheng (Garland, TX, US); Hargreaves, Tyler (Flower Mound, TX, US); Kirtzic, John Steven (Plano, TX, US); Li, Zongzhe (Richardson, TX, US); Longva, Einar (Manhattan, NY, US); Mao, Victor (Export, PA, US); Nemmani, Krishna (McKinney, TX, US); Nguyen, Trac (Norcross, GA, US); Panguluri, Sivarama Kirshna (McKinney, TX, US); Sherer, Dalton (Richardson, TX, US); Yang, Edward (Frisco, TX, US), filed on October 31, 2022, was made available online on March 23, 2023.

No assignee for this patent application has been made.

Reporters obtained the following quote from the background information supplied by the inventors: “Organizations such as insurance companies have an interest in obtaining information from which they can determine insurance premiums that reward good driving habits. For example, for an automobile insurance company, demographic information of a driver (such as residence location, age, years of driving experience and moving violation history) has been used as input to loss risk assessment models. More individualized information about the driver and how she drives can help to reward good driving habits. For a driver whose activity indicates that she drives in a manner that is less likely to result in loss for the automobile insurance company, this may result in a lower automobile insurance premium for the driver than for other drivers with similar demographic attributes.”

In addition to obtaining background information on this patent application, NewsRx editors also obtained the inventors’ summary information for this patent application: “Driver activity information alone, even when combined with demographic information, may not be sufficient for loss risk assessment and may not properly reward good driving behavior. That is, without considering the context of the environment in which the driver activity information was generated, the driver activity information may be an inaccurate indicator of loss risk. In some cases, the actual loss risk corresponding to particular driver activity may be lower and, in other cases, the actual loss risk corresponding to a particular driver activity may be higher when considering the context of the environment in which the driver activity information was generated.

“This disclosure describes, in part, techniques to develop an indication of loss risk assessment for a driving trip of a vehicle. The techniques may include, during the vehicle driving trip, observing driver activity. Identifying driver activity may include collecting data from sensors that are attached to the vehicle or are otherwise moving with the vehicle during the driving trip. The techniques may also include, during the trip, obtaining information indicative of a context of the identified driver activity, at the time and location of the identified driver activity. Such context may include, for example, environmental conditions at the time and location of the identified driver activity.

“Obtaining information indictive of environmental conditions may include, for example, obtaining information indicative of weather, traffic, and/or road work occurring at the time and location of the identified driver activity. As another example, such environmental conditions may include laws and/or regulations in place governing driving at the time and location of the observed driver activity, which may include, for example, information about a speed limit at the time and location of the observed driver activity.

“Obtaining information indicative of a context of the identified driver activity may include observing conditions at the vehicle and/or may include interrogating one or more collections of data (e.g., datastores) indicative of conditions for multiple locations throughout a geographic territory. The collections of data may be provided, for example, by one or more services that collect and provides contextual information for locations throughout a territory. Interrogating a collection of data may include, for example, accessing the information (e.g., information indicative of the context of the identified driver activity) using one or more application programming interfaces (APIs).

“The techniques may further include, during the driving trip, generating, using a computing device, event records that include an indication of identified driver activity correlated with an indication of obtained contextual information for the identified driver activity. Generating event records during a driving trip may include, for example, receiving, with a computing device, information indicative of driver activity at times/locations during the vehicle trip, and obtaining, with the computing device, information indicative of a context of the identified driver activity, at the times/locations of the observed driver activity. The computing device may collect the event records into a data set.

“The techniques may also include, at or after the driving trip concludes, processing, with the computing device at the vehicle, or another computing device, the event records data set to determine a score for the driving trip. In some examples, a computing device generates the driving score and updates it during the driving trip, which may also include the computing device generating and updating the driving score at or after the driving trip concludes.

“In some examples, the techniques described herein may be implemented in the context of a portable electronic device such as a mobile phone. However, the techniques described herein are not limited to use with a portable electronic device. For example, the techniques described herein may be implemented in a computing device that is in or attached to an automobile or other vehicle, such as a computing device that is attached to or otherwise in communication with an on-board diagnostic (OBD) port of a vehicle. As another example, the techniques described herein may be implemented in a computing device that is part of a vehicle’s electronics, such as electronics used to control the vehicle’s engine, an on-vehicle infotainment system, and/or other systems. In some examples, the techniques implemented herein may be distributed among a plurality of computing devices.

“Some of the techniques may be performed by a back-end server or other remotely-accessible computing device, such as in the “cloud,” in communication with a computing device that is in or attached to an automobile or other vehicle continuously, intermittently, synchronously, asynchronously, real time, near real-time, and/or otherwise. The techniques are not limited by this disclosure to being performed by a computing device at any particular location.

“A loss risk assessment determined in consideration of the context of observed driver activity for a particular vehicle trip may more accurately represent a probability of loss by an automobile insurance company and, thus, may better reward good driving behavior.”

The claims supplied by the inventors are:

“1. A method, comprising: receiving, at a vehicle and by a computing device comprising one or more processors, driver activity information indicative of an operation of the vehicle by a driver; receiving, by the computing device, context information indicative of an environment at a particular time and a particular location, the context information including at least one of weather conditions, traffic conditions, or construction activity at the particular location and at the particular time; determining, by the computing device and based at least in part on the particular time and the particular location, that the driver activity information is correlated with the context information; generating, by the computing device and based at least in part on determining that the data set corresponding to the driver activity information is correlated with the context information, a data set having a type of event field associated with the driver activity information, wherein the type of event field includes a first index and a second index, the first index indicating a type of driver activity and the second index indicating a subtype of the driver activity; and sending, to one or more servers, the data set, wherein the one or more servers are configured to generate a score based at least in part on the data set.

“2. The method of claim 1, wherein: the driver activity information includes speed of the vehicle at the particular location and at the particular time.

“3. The method of claim 1, further comprising: generating, by a computing device, the score, wherein generating the score includes: adjusting a speed limit threshold for the particular location based at least upon the context information, wherein the context information is indicative of the environment at the particular location; comparing the speed of the vehicle as indicated by the driver activity information to the adjusted speed limit threshold at the first location; and generating the score at least in part based on a result of the comparing.

“4. The method of claim 1, wherein the driver activity information is received from at least one of: a sensor or a second computing device associated with the vehicle.

“5. The method of claim 1, wherein the data set comprises a plurality of data fields, individual ones of the data fields corresponding to the driver activity information, the context information, and the particular time.

“6. The method of claim 1, further comprising: requesting the context information using an application programming interface of a service provider system, wherein the context information is received from a service provider system in response to requesting the context information.

“7. The method of claim 6, wherein the service provider system is an online weather service.

“8. The method of claim 1, further comprising: generating the context information at the vehicle, based at least on a signal from a sensor used by the vehicle in operating the vehicle.

“9. The method of claim 1, further comprising: determining, by the computing device, that a particular trip has ended, wherein sending the data set is based at least in part on the determining that the particular trip has ended.

“10. The method of claim 1, wherein the first index indicates one of: (i) an acceleration/deceleration event; (ii) a speeding event; or (iii) a distracted driving event.

“11. A device, comprising: one or more processors; and memory coupled to the one or more processors, the memory storing instructions executable by the one or more processors to perform operations including: receiving driver activity information indicative of operation of the vehicle by a driver; receiving context information indicative of an environment at a particular time and a particular location, the context information including at least one of weather conditions, traffic conditions, or construction activity at the particular location and at the particular time; determining that the driver activity information is associated with the context information; generating, based at least in part on determining that the data set corresponding to the driver activity information is correlated with the context information, a data set having a type of event field associated with the driver activity information, wherein the type of event field includes a first index and a second index, the first index indicating a type of driver activity and the second index indicating a subtype of the driver activity; and sending, to one or more servers, the data set.

“12. The device of claim 11, wherein: the driver activity information includes speed of the vehicle at the particular location and at the particular time.

“13. The device of claim 11, wherein the operations further include: generating the score based at least in part on the data set; and sending the score to the one or more servers.

“14. The device of claim 11, the operations further comprising: transmitting a request for the context information from the vehicle via a network.

“15. The device of claim 11, the operations further comprising: requesting the context information using an application programming interface of a service, wherein the context information is received from a service, in response to requesting the context information.

“16. The device of claim 11, wherein the data set comprises a plurality of data fields, individual ones of the data fields corresponding to the driver activity information, the context information, and the particular time.

“17. The device of claim 11, the operations further comprising: generating the context information at the vehicle, based at least on a signal from the sensor used by the vehicle in operating the vehicle.

“18. One or more non-transitory computer-readable media storing instructions that, when executed by one or more processors of a device at a vehicle, configure the device to perform operations including: receiving driver activity information indicative of operation of the vehicle; receiving context information indicative of an environment at a particular time and a particular location, the context information including at least one of weather conditions, traffic conditions, or construction activity at the particular location and at the particular time; generating, based at least in part on determining that the data set corresponding to the driver activity information is correlated with the context information, a data set having a type of event field associated with the driver activity information, wherein the type of event field includes a first index and a second index, the first index indicating a type of driver activity and the second index indicating a subtype of the driver activity; and sending the data set to one or more servers configured to generate a score based at least in part on the data set.

“19. The one or more computer-readable media of claim 18, wherein the operations include: generating the score based at least in part on the data set; and sending the score to the one or more servers.

“20. The one or more computer-readable media of claim 18, the operations further comprising: transmitting a request for the context information from the vehicle via a network.”

For more information, see this patent application: Black, Zebediah Robert; Casmedes, Corey; Dang, Hoang; Gao, Yuncheng; Hargreaves, Tyler; Kirtzic, John Steven; Li, Zongzhe; Longva, Einar; Mao, Victor; Nemmani, Krishna; Nguyen, Trac; Panguluri, Sivarama Kirshna; Sherer, Dalton; Yang, Edward. Using Contextual Information For Vehicle Trip Loss Risk Assessment Scoring. U.S. Patent Application Number 20230089020, filed October 31, 2022 and posted March 23, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(20230089020)&db=US-PGPUB&type=ids

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