IP Library Granted Patent US 10,324,463
Granted Patent B1
US 10,324,463 · App. 15/409,236 · Granted Jun 18, 2019

Autonomous vehicle operation adjustment based upon route

Inventors: Blake Konrardy (Bloomington, IL); Scott T. Christensen (Salem, OR); Gregory Hayward (Bloomington, IL); Scott Farris (Bloomington, IL)
Assignee: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
G05D1/0061B60W50/082B60W50/14G01C21/3407G01C21/3691G01S19/14G01S19/39G05D1/0278B60W2050/143
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Quick Facts
Patent No.
US 10,324,463
App. No.
15/409,236
Granted
Jun 18, 2019
Kind
B1
Abstract

Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Autonomous operation feature usage levels or settings may be automatically adjusted to optimize performance using suitability data for road segments along a route traveled by a vehicle, such as when operating conditions change. Data regarding road segment suitability may be generated from prior operating data for the road segments and retrieved from a map database to aid autonomous vehicle routing, as well as to implement automatic adjustments to feature usage. In some instances, vehicle control may be returned to a vehicle operator, in which case advance warning may be given to enable the operator to prepare to resume control of the vehicle.

Claims (72)

1. A computer-implemented method for optimizing usage of autonomous operation features of a vehicle during operation, comprising:

identifying, using one or more geolocation components within the vehicle, a location of the vehicle;

accessing, by one or more processors within the vehicle, map data containing information regarding a plurality of road segments, the information including location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment;

identifying, by the one or more processors, a current road segment from the plurality of road segments based upon the identified location of the vehicle;

monitoring, by one or more sensors disposed within the vehicle, environmental conditions within a vehicle operating environment of the vehicle;

determining, by the one or more processors, one or more optimal usage levels for one or more of the autonomous operation features of the vehicle associated with the current road segment in the environmental conditions within the vehicle operating environment of the vehicle by:

determining a current risk level associated with operation of the vehicle along the current road segment using one or more current usage levels of the autonomous operation features in the environmental conditions;

determining one or more alternative risk levels associated with operation of the vehicle along the current road segment using one or more alternative usage levels of the autonomous operation features in the environmental conditions;

identifying a subset of the one or more alternative usage levels, each alternative usage level of the subset being associated with respective alternative risk levels less than the current risk level; and

selecting the one or more optimal usage levels from the subset of the one or more alternative usage levels based upon the one or more alternative risk levels associated with the one or more alternative usage levels of the subset;

determining, by the one or more processors, a usage level change associated with at least one of the autonomous operation features by comparing the optimal usage levels against the one or more current usage levels of the autonomous operation features; and

implementing, by the one or more processors, the usage level change.

2. The computer-implemented method of claim 1 , wherein implementing the usage level change includes adjusting one or more settings of the at least one of the autonomous operation features to implement the usage level change.

3. The computer-implemented method of claim 1 , wherein the one or more optimal usage levels are selected based at least in part upon one or more variances of the one or more alternative risk levels associated with the one or more alternative usage levels of the subset.

4. The computer-implemented method of claim 1 , wherein:

the indication of suitability associated with the current road segment indicates that manual operation is required; and

implementing the usage level change includes (i) providing an alert to a vehicle operator and (ii) disabling the at least one of the autonomous operation features to transfer control of the vehicle to the vehicle operator.

5. The computer-implemented method of claim 4 , wherein implementing the usage level change further includes determining that the vehicle operator is prepared to assume manual control of the vehicle.

6. The computer-implemented method of claim 1 , wherein the usage of the autonomous operation features is optimized for each of one or more road segments along a route traversed by the vehicle.

7. The computer-implemented method of claim 6 , further comprising:

identifying, by the one or more processors, an upcoming road segment along the route;

determining, by the one or more processors, an optimal usage level of autonomous operation feature usage associated with the upcoming road segment, the optimal usage level requiring at least some manual vehicle control by a vehicle operator;

determining, by the one or more processors, a change in autonomous operation feature usage based upon a difference between the current usage levels and the optimal usage level for the upcoming road segment; and

presenting, by a communication device within the vehicle, an alert to the vehicle operator in advance of the vehicle reaching the upcoming road segment.

8. The computer-implemented method of claim 1 , wherein:

the one or more geolocation components include a global positioning system (GPS) receiver; and

the current road segment is identified based upon GPS coordinates associated with the current road segment.

9. A computer system for optimizing usage of autonomous operation features of a vehicle during operation, comprising:

one or more processors;

one or more geolocation components disposed within the vehicle and communicatively connected to the one or more processors;

a map database communicatively connected to the one or more processors and storing map data containing information regarding a plurality of road segments, the information including location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment; and

a program memory coupled to the one or more processors and storing executable instructions that, when executed by the one or more processors, cause the computer system to:

identify a location of the vehicle using the one or more geolocation components;

identify a current road segment from the plurality of road segments of the map data in the map database based upon the identified location of the vehicle;

monitor environmental conditions within a vehicle operating environment of the vehicle by one or more sensors disposed within the vehicle;

determine one or more optimal usage levels for one or more of the autonomous operation features of the vehicle associated with the current road segment in the environmental conditions within the vehicle operating environment of the vehicle based upon the map data by:

determining a current risk level associated with operation of the vehicle along the current road segment using one or more current usage levels of the autonomous operation features in the environmental conditions;

determining one or more alternative risk levels associated with operation of the vehicle along the current road segment using one or more alternative usage levels of the autonomous operation features in the environmental conditions;

identifying a subset of the one or more alternative usage levels, each alternative usage level of the subset being associated with respective alternative risk levels less than the current risk level; and

selecting the one or more optimal usage levels from the subset of the one or more alternative usage levels based upon the one or more alternative risk levels associated with the one or more alternative usage levels of the subset;

determine a usage level change associated with at least one of the autonomous operation features by comparing the optimal usage levels against the one or more current usage levels of the autonomous operation features; and

implement the usage level change.

10. The computer system of claim 9 , wherein the instructions that cause the computer system to implement the usage level change cause the computer system to adjust one or more settings of the at least one of the autonomous operation features to implement the usage level change.

11. The computer system of claim 9 , wherein:

the indication of suitability associated with the current road segment indicates that manual operation is required; and

implementing the usage level change includes (i) providing an alert to a vehicle operator and (ii) disabling the at least one of the autonomous operation features to transfer control of the vehicle to the vehicle operator.

12. The computer system of claim 9 , wherein the executable instructions further cause the computer system to:

identify an upcoming road segment along the route;

determine an optimal usage level of autonomous operation feature usage associated with the upcoming road segment, the optimal usage level requiring at least some manual vehicle control by a vehicle operator;

determine a change in autonomous operation feature usage based upon a difference between the current usage levels and the optimal usage level for the upcoming road segment; and

present an alert to the vehicle operator in advance of the vehicle reaching the upcoming road segment.

13. A tangible, non-transitory computer-readable medium storing executable instructions for optimizing usage of autonomous operation features of a vehicle during operation that, when executed by at least one processor of a computer system, cause the computer system to:

identify a location of the vehicle using one or more geolocation components within the vehicle;

access map data containing information regarding a plurality of road segments, the information including location data associated with each road segment and an indication of suitability for autonomous operation feature use associated with each road segment;

identify a current road segment from the plurality of road segments based upon the identified location of the vehicle;

monitor environmental conditions within a vehicle operating environment of the vehicle by one or more sensors disposed within the vehicle;

determine one or more optimal usage levels for one or more of the autonomous operation features of the vehicle associated with the current road segment in the environmental conditions within the vehicle operating environment of the vehicle by:

determining a current risk level associated with operation of the vehicle along the current road segment using one or more current usage levels of the autonomous operation features in the environmental conditions;

determining one or more alternative risk levels associated with operation of the vehicle along the current road segment using one or more alternative usage levels of the autonomous operation features in the environmental conditions;

identifying a subset of the one or more alternative usage levels, each alternative usage level of the subset being associated with respective alternative risk levels less than the current risk level; and

selecting the one or more optimal usage levels from the subset of the one or more alternative usage levels based upon the one or more alternative risk levels associated with the one or more alternative usage levels of the subset;

determine a usage level change associated with at least one of the autonomous operation features by comparing the optimal usage levels against the one or more current usage levels of the autonomous operation features; and

implement the usage level change.

14. The tangible, non-transitory computer-readable medium of claim 13 , wherein the instructions that cause the computer system to implement the usage level change cause the computer system to adjust one or more settings of the at least one of the autonomous operation features to implement the usage level change.

15. The tangible, non-transitory computer-readable medium of claim 13 , wherein:

the indication of suitability associated with the current road segment indicates that manual operation is required; and

implementing the usage level change includes (i) providing an alert to a vehicle operator and (ii) disabling the at least one of the autonomous operation features to transfer control of the vehicle to the vehicle operator.

16. The tangible, non-transitory computer-readable medium of claim 13 , further storing executable instructions that cause the computer system to:

identify an upcoming road segment along the route;

determine an optimal usage level of autonomous operation feature usage associated with the upcoming road segment, the optimal usage level requiring at least some manual vehicle control by a vehicle operator;

determine a change in autonomous operation feature usage based upon a difference between the current usage levels and the optimal usage level for the upcoming road segment; and

present an alert to the vehicle operator in advance of the vehicle reaching the upcoming road segment.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 24, 2017
From: KONRARDY, BLAKE; CHRISTENSEN, SCOTT T.; HAYWARD, GREGORY; FARRIS, SCOTT
To: STATE FARM MUTUAL AUTOMOBILE INSURANCE COMPANY
Reel/Frame 041471/0673 →
Continuity (35)
Provisional Application 62434359 · Dec 14, 2016
Provisional Application 62434355 · Dec 14, 2016
Provisional Application 62434361 · Dec 14, 2016
Provisional Application 62434370 · Dec 14, 2016
Provisional Application 62434368 · Dec 14, 2016
Provisional Application 62434365 · Dec 14, 2016
Provisional Application 62430215 · Dec 5, 2016
Provisional Application 62438843 · Dec 1, 2016
Provisional Application 62434078 · Nov 18, 2016
Provisional Application 62424093 · Nov 18, 2016
Provisional Application 62419017 · Nov 8, 2016
Provisional Application 62418999 · Nov 8, 2016
Provisional Application 62419009 · Nov 8, 2016
Provisional Application 62418988 · Nov 8, 2016
Provisional Application 62419023 · Nov 8, 2016
Provisional Application 62419002 · Nov 8, 2016
Provisional Application 62415672 · Nov 1, 2016
Provisional Application 62415668 · Nov 1, 2016
Provisional Application 62415678 · Nov 1, 2016
Provisional Application 62415673 · Nov 1, 2016
Provisional Application 62406605 · Oct 11, 2016
Provisional Application 62406600 · Oct 11, 2016
Provisional Application 62406595 · Oct 11, 2016
Provisional Application 62406611 · Oct 11, 2016
Provisional Application 62381848 · Aug 31, 2016
Provisional Application 62380686 · Aug 29, 2016
Provisional Application 62376044 · Aug 17, 2016
Provisional Application 62373084 · Aug 10, 2016
Provisional Application 62351559 · Jun 17, 2016
Provisional Application 62349884 · Jun 14, 2016
Provisional Application 62312109 · Mar 23, 2016
Provisional Application 62303500 · Mar 4, 2016
Provisional Application 62302990 · Mar 3, 2016
Provisional Application 62287659 · Jan 27, 2016
Provisional Application 62286017 · Jan 22, 2016
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