Patent Issued for Controlling autonomous vehicles to optimize traffic characteristics (USPTO 11915318): Allstate Insurance Company

2024 MAR 15 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Alexandria, Virginia, NewsRx journalists report that a patent by the inventors Chintakindi, Sunil (Menlo Park, CA, US), Kumar, Surender (Palatine, IL, US), Slusar, Mark (Chicago, IL, US), filed on March 31, 2021, was published online on February 27, 2024.

The patent’s assignee for patent number 11915318 is Allstate Insurance Company (Northbrook, Illinois, United States).

News editors obtained the following quote from the background information supplied by the inventors: “Aspects of the disclosure relate to controlling the operation of vehicle control and guidance systems for one or more autonomous vehicles. In particular, one or more aspects of the disclosure relate to providing incentives for drivers of autonomous vehicles to adjust autonomous vehicle settings in order to improve one or more traffic characteristics.

“Autonomous vehicles are becoming increasingly sophisticated as satellite navigation technologies, traffic and pedestrian sensor technologies, and guidance technologies continue to improve. Despite advances in various technologies, however, it may be difficult to coordinate or otherwise direct autonomous vehicles to drive effectively together with other autonomous vehicles and non-autonomous vehicles. For example, different autonomous vehicles may have different capabilities, and therefore different autonomous vehicles may not coordinate effectively with other vehicles, resulting in decreased traffic characteristics such as safety, traffic flow, and average speed.”

As a supplement to the background information on this patent, NewsRx correspondents also obtained the inventors’ summary information for this patent: “Aspects of the disclosure provide effective, efficient, scalable, and convenient technical solutions that address and overcome the technical problems associated with controlling one or more vehicles including autonomous vehicles, particularly in instances in which autonomous vehicles are controlled to improve traffic characteristics such as safety, traffic flow, or average speed.

“In accordance with one or more embodiments, a computing platform having at least one processor, a memory, and a communication interface may receive, via the communication interface, vehicle guidance data associated with vehicles from autonomous vehicle control systems of the vehicles. Subsequently, the computing platform may identify a number of the vehicles currently operating in an autonomous mode based on the vehicle guidance data. Thereafter, the computing platform may identify a target number of the vehicles to be operated in an autonomous mode in order to optimize one or more traffic characteristics for the vehicles. Then, the computing platform may generate one or more messages directing selected vehicles to switch into autonomous mode in order to achieve the target number and/or may generate one or more messages directing selected vehicles to present incentives to switch into autonomous mode in order to achieve the target number. Subsequently, the computing platform may send, via the communication interface, to autonomous vehicle control systems of the selected vehicles, the one or more messages directing the selected vehicles to switch into autonomous mode in order to receive incentives and/or may send the one or more messages directing the selected vehicles to present the incentives to switch into autonomous mode. Thereafter, the computing platform may award the incentives to the selected vehicles that switch into the autonomous mode as directed by the one or more messages.

“In some embodiments, the computing platform may also generate one or more messages instructing one or more vehicles to present incentives to switch out of an autonomous mode in order to optimize the traffic characteristic. The computing platform may further send the messages to the one or more vehicles, and award the incentives to the one or more vehicles that switch out of the autonomous mode as directed by the messages.

“In some embodiments, the computing platform may also generate one or more messages instructing one or more vehicles to present incentives to follow alternate routes in order to optimize the one or more traffic characteristics. The computing platform may further send the messages to the one or more vehicles, and award the incentives to the one or more vehicles that follow alternate routes as directed by the messages.

“In some embodiments, the computing platform may receive vehicle guidance data from non-autonomous vehicles having non-autonomous vehicle control systems. The computing platform may further generate one or more messages instructing one or more non-autonomous vehicles to present incentives to follow alternate routes in order to optimize the one or more traffic characteristics. The computing platform may further send the messages to the one or more non-autonomous vehicles, and award the incentives to the one or more non-autonomous vehicles that follow alternate routes as directed by the messages.”

The claims supplied by the inventors are:

“1. A method comprising: determining, by a computing device, an evaluation group of vehicles for which to optimize one or more traffic characteristics; determining vehicles, of the evaluation group, currently operating in an autonomous mode; determining a target number of vehicles, of the evaluation group, for operating in the autonomous mode to optimize the one or more traffic characteristics; based on the target number of vehicles, selecting one or more vehicles, of the vehicles currently operating in the autonomous mode, to switch from the autonomous mode to a non-autonomous mode; and causing at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode.

“2. The method of claim 1, wherein the selected one or more vehicles are associated with highest driver safety scores among the evaluation group.

“3. The method of claim 1, wherein the selecting the one or more vehicles is based on one or more of: driver information associated with the one or more vehicles; vehicle information associated with the one or more vehicles; vehicle guidance data associated with the one or more vehicles; or road conditions information associated with the one or more vehicles.

“4. The method of claim 1, wherein the causing the at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode comprises: sending a message instructing the at least one vehicle of the selected one or more vehicles to present an incentive to switch from the autonomous mode to the non-autonomous mode.

“5. The method of claim 4, wherein the message indicates a length of time or distance during which the at least one vehicle must continue operating in the non-autonomous mode in order to receive the incentive.

“6. The method of claim 4, wherein the causing the at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode is based on a selection of acceptance of the incentive.

“7. The method of claim 1, wherein the determining the evaluation group of vehicles is based on one or more of: locations associated with vehicles of the evaluation group; travelling directions associated with the vehicles of the evaluation group; travelling speeds associated with the vehicles of the evaluation group; or destinations associated with the vehicles of the evaluation group.

“8. The method of claim 1, wherein the determining the evaluation group of vehicles is based on vehicle guidance data received from vehicles of the evaluation group.

“9. The method of claim 1, wherein the one or more traffic characteristics comprise one or more of: safety; a traffic flow; a traffic average speed; or a traffic maximum speed.

“10. A non-transitory computer-readable storage medium having computer-executable program instructions stored thereon that when executed by a processor, cause the processor to perform steps comprising: determining an evaluation group of vehicles for which to optimize one or more traffic characteristics; determining vehicles, of the evaluation group, currently operating in an autonomous mode; determining a target number of vehicles, of the evaluation group, for operating in the autonomous mode to optimize the one or more traffic characteristics; based on the target number of vehicles, selecting one or more vehicles, of the vehicles currently operating in the autonomous mode, to switch from the autonomous mode to a non-autonomous mode; and causing at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode.

“11. The computer-readable storage medium of claim 10, wherein the selected one or more vehicles are associated with highest driver safety scores among the evaluation group.

“12. The computer-readable storage medium of claim 10, wherein the computer-executable program instructions, when executed by the processor, cause the processor to perform the causing the at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode by: sending a message instructing the at least one vehicle of the selected one or more vehicles to present an incentive to switch from the autonomous mode to the non-autonomous mode.

“13. The computer-readable storage medium of claim 12, wherein the causing the at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode is based on a selection of acceptance of the incentive.

“14. The computer-readable storage medium of claim 10, wherein the determining the evaluation group of vehicles is based on one or more of: locations associated with vehicles of the evaluation group; travelling directions associated with the vehicles of the evaluation group; travelling speeds associated with the vehicles of the evaluation group; or destinations associated with the vehicles of the evaluation group.

“15. The computer-readable storage medium of claim 10, wherein the determining the evaluation group of vehicles is based on vehicle guidance data received from vehicles of the evaluation group.

“16. An apparatus comprising: a processor; and a memory configured to store computer-readable instructions that, when executed by the processor, cause the apparatus to perform: determining an evaluation group of vehicles for which to optimize one or more traffic characteristics; determining vehicles, of the evaluation group, currently operating in an autonomous mode; determining a target number of vehicles, of the evaluation group, for operating in the autonomous mode to optimize the one or more traffic characteristics; based on the target number of vehicles, selecting one or more vehicles, of the vehicles currently operating in the autonomous mode, to switch from the autonomous mode to a non-autonomous mode; and causing at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode.

“17. The apparatus of claim 16, wherein the selected one or more vehicles are associated with highest driver safety scores among the evaluation group.

“18. The apparatus of claim 16, wherein the computer-readable instructions, when executed by the processor, cause the apparatus to perform the causing the at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode by: sending a message instructing the at least one vehicle of the selected one or more vehicles to present an incentive to switch from the autonomous mode to the non-autonomous mode.

“19. The apparatus of claim 18, wherein the causing the at least one vehicle of the selected one or more vehicles to switch from the autonomous mode to the non-autonomous mode is based on a selection of acceptance of the incentive.

“20. The apparatus of claim 16, wherein the determining the evaluation group of vehicles is based on one or more of: locations associated with vehicles of the evaluation group; travelling directions associated with the vehicles of the evaluation group; travelling speeds associated with the vehicles of the evaluation group; or destinations associated with the vehicles of the evaluation group.”

For additional information on this patent, see: Chintakindi, Sunil. Controlling autonomous vehicles to optimize traffic characteristics. U.S. Patent Number 11915318, filed March 31, 2021, and published online on February 27, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11915318)&db=USPAT&type=ids

(Our reports deliver fact-based news of research and discoveries from around the world.)