Moving object prediction device, hypothetical movable object prediction device, program, moving object prediction method and hypothetical movable object prediction method
US-9424468-B2 · Aug 23, 2016 · US
US10156851B1 · US · B1
| Field | Value |
|---|---|
| Publication number | US-10156851-B1 |
| Application number | US-201615384782-A |
| Country | US |
| Kind code | B1 |
| Filing date | Dec 20, 2016 |
| Priority date | Aug 29, 2014 |
| Publication date | Dec 18, 2018 |
| Grant date | Dec 18, 2018 |
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Aspects of the disclosure relate to an autonomous vehicle that may detect other nearby vehicles and designate stationary vehicles as being in one of a short-term stationary state or a long-term stationary state. This determination may be made based on various indicia, including visible indicia displayed by the detected vehicle and traffic control factors relating to the detected vehicle. For example, the autonomous vehicle may identify a detected vehicle as being in a long-term stationary state based on detection of hazard lights being displayed by the detected vehicle, as well as the absence of brake lights being displayed by the detected vehicle. The autonomous vehicle may then base its control strategy on the stationary state of the detected vehicle.
Opening claim text (preview).
The invention claimed is: 1. A computer-implemented method comprising: detecting, by one or more processors, a first vehicle; identifying, by the one or more processors, that the first vehicle is stationary; detecting, by the one or more processors, one or more objects in an area surrounding the first vehicle, the one or more objects including a second vehicle or a pedestrian; determining, by the one or more processors, whether the first vehicle is in a first stationary state or a second stationary state based on one or more locations of the one or more detected objects and map data of the area surrounding the first vehicle, the first stationary state corresponding to a first length of time and the second stationary state corresponding to a second length of time, the second length of time being greater than the first length of time; and controlling, by the one or more processors, a vehicle having an autonomous driving mode in accordance with a control strategy based on whether the first vehicle is determined to be in the first stationary state or the second stationary state. 2. The method of claim 1 , wherein the first stationary state is a short-term stationary state and the second stationary state is a long-term stationary state. 3. The method of claim 2 , wherein the first vehicle is determined to be in the first stationary state when at least one of the detected objects is determined to be blocking the first vehicle from legally proceeding based on the one or more locations and the map data. 4. The method of claim 3 , further comprising: detecting, by the one or more processors, an occlusion to the surrounding area; tracking, by the one or more processors, a movement of the at least one of the detected objects; and determining, by the one or more processors, when the at least one of the detected objects is no longer detected, that the at least one of the detected objects is in a location that is blocking the first vehicle from legally proceeding. 5. The method of claim 3 , further comprising: determining, by the one or more processors, that the first vehicle is in a first lane of traffic; detecting, by the one or more processors, an occlusion to the surrounding area; determining, by the one or more processors, that more information is required before determining a stationary state of the first vehicle based on a size of the occlusion; and detecting, by the one or more processors, a third vehicle in a second lane of traffic different from the first lane of traffic; wherein whether the first vehicle is in a first stationary state or a second stationary state is also determined based on the third vehicle. 6. The method of claim 3 , wherein the first vehicle is determined to be legally blocked from proceeding when the at least one of the detected objects is a pedestrian that is walking in front of the first vehicle. 7. The method of claim 1 , further comprising detecting, by the one or more processors, one or more lights emitted from the first vehicle; wherein determining whether the first vehicle is in a first stationary state or a second stationary state is also based on the one or more lights. 8. The method of claim 1 , further comprising detecting, by the one or more processors, one or more traffic control factors in the surrounding area; wherein determining whether the first vehicle is in a first stationary state or a second stationary state is also based on the one or more traffic control factors. 9. A system comprising: one or more sensors; and one or more processors configured to: detect, using the one or more sensors, a first vehicle; identify that the first vehicle is stationary; detect, using the one or more sensors, one or more objects in an area surrounding the first vehicle, the one or more objects including a second vehicle or a pedestrian; determine whether the first vehicle is in a first stationary state or a second stationary state based on one or more locations of the one or more detected objects and map data of the area surrounding the first vehicle, the first stationary state corresponding to a first length of time and the second stationary state corresponding to a second length of time, the second length of time being greater than the first length of time; and control a vehicle having an autonomous driving mode in accordance with a control strategy based on whether the first vehicle is determined to be in the first stationary state or the second stationary state. 10. The system of claim 9 , wherein the first stationary state is a short-term stationary state and the second stationary state is a long-term stationary state. 11. The system of claim 10 , wherein the first vehicle is determined to be in the first stationary state when at least one of the detected objects is determined to be blocking the first vehicle from legally proceeding based on the one or more locations and the map data. 12. The system of claim 11 , wherein the one or more processors are further configured to: detect an occlusion to the surrounding area; track a movement of the at least one of the detected objects; and determine when the at least one of the detected objects is no longer detected, that the at least one of the detected objects is in a location that is blocking the first vehicle from legally proceeding. 13. The system of claim 11 , wherein the one or more processors are further configured to: determine that the first vehicle is in a first lane of traffic; detect an occlusion to the surrounding area; determine that more information is required before determining a stationary state of the first vehicle based on a size of the occlusion; and detect a third vehicle in a second lane of traffic different from the first lane of traffic; wherein whether the first vehicle is in a first stationary state or a second stationary state is also determined based on the third vehicle. 14. The system of claim 11 , wherein the first vehicle is determined to be legally blocked from proceeding when the at least one of the detected objects is a pedestrian that is walking in front of the first vehicle. 15. The system of claim 9 , wherein the one or more processors are further configured to: detect one or more lights emitted from the first vehicle; and determine whether the first vehicle is in a first stationary state or a second stationary state further based on the one or more lights. 16. The system of claim 9 , wherein the one or more processors are further configured to: detect one or more traffic control factors in the surrounding area; and determine whether the first vehicle is in a first stationary state or a second stationary state further based on the one or more traffic control factors. 17. The system of claim 9 , further comprising the vehicle. 18. A non-transitory, tangible computer-readable storage medium on which computer readable instructions of a program are stored, the instructions, when executed by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising: detecting, using one or more sensors, a first vehicle; identifying that the first vehicle is stationary; detecting, using the one or more sensors, one or more objects in an area surrounding the first vehicle, the one or more objects including a second vehicle or a pedestrian; determining whether the first vehicle is in a first stationary state or a second stationary state based on one or more locations of the one or more detected objects and map data of the area surrounding the first vehicle, the firs
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