Methods and systems for generating lane line and road edge data using empirical path distributions
US-12181305-B2 · Dec 31, 2024 · US
US9534910B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-9534910-B2 |
| Application number | US-201414565265-A |
| Country | US |
| Kind code | B2 |
| Filing date | Dec 9, 2014 |
| Priority date | Dec 9, 2014 |
| Publication date | Jan 3, 2017 |
| Grant date | Jan 3, 2017 |
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An automated driving system and methods are disclosed. The automated driving system includes a perception system disposed on an autonomous vehicle. The automated driving system can detect an intersection including a yield scenario and identify a check point between the autonomous vehicle and the yield scenario. Prior to the autonomous vehicle reaching the check point, the automated driving system can send a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario. After the autonomous vehicle reaches the check point, the automated driving system can detect, using the perception system, information for the intersection. If the information indicates clear passage through the intersection for the autonomous vehicle, the automated driving system can send a command to the one or more vehicle systems to drive the autonomous vehicle through the intersection.
Opening claim text (preview).
What is claimed is: 1. An automated driving system, comprising: a perception system disposed on an autonomous vehicle; and a computing device in communication with the perception system, comprising: one or more processors for controlling operations of the computing device; and a memory for storing data and program instructions used by the one or more processors, wherein the one or more processors are configured to execute instructions stored in the memory to: detect preliminary information for an intersection including a yield scenario; identify a check point location between the autonomous vehicle and the yield scenario based on the preliminary information including at least one of traffic density information, an intersection type, an intersection configuration, or a presence of one or more obstacles that could at least partially obstruct a view of the intersection by the autonomous vehicle; prior to the autonomous vehicle reaching the check point location, send a command to one or more vehicle systems to control me autonomous vehicle to stop at the yield scenario; after the autonomous vehicle reaches the check point location, detect, using the perception system, updated information for the intersection; and when the updated information indicates clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to drive the autonomous vehicle past the yield scenario and through the intersection. 2. The automated driving system of claim 1 , wherein the yield scenario includes one of a yield sign, a red traffic light, a roundabout, and a lane merge. 3. The automated driving system of claim 1 , wherein the updated information includes at least one of information regarding intersection obstacles and information regarding one or more neighboring vehicles. 4. The automated driving system of claim 3 , wherein the information regarding the one or more neighboring vehicles includes at least one of position, velocity, acceleration, and deceleration for the one or more neighboring vehicles. 5. The automated driving system of claim 1 , wherein the one or more processors are further configured to: if the updated information does not indicate clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to stop the autonomous vehicle at the yield scenario. 6. The automated driving system of claim 1 , wherein detecting the updated information for the intersection is performed regardless of the yield scenario. 7. A computer implemented method of automated driving, comprising: detecting preliminary information for an intersection including a yield scenario; identifying a check point location between an autonomous vehicle and the yield scenario based on the preliminary information including at least one of traffic density information, an intersection type, an intersection configuration, or a presence of one or more obstacles that could at least partially obstruct a view of the intersection by the autonomous vehicle; prior to the autonomous vehicle reaching the check point location, sending a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario; after the autonomous vehicle reaches the check point location, detecting, using a perception system disposed on the autonomous vehicle, updated information for the intersection; and when the updated information indicates clear passage through the intersection for the autonomous vehicle, sending a command to the one or more vehicle systems to drive the autonomous vehicle past the yield scenario and through the intersection. 8. The method of claim 7 , wherein the yield scenario includes one of a yield sign, a red traffic light, a roundabout, and a lane merge. 9. The method of claim 7 , wherein the updated information includes at least one of information regarding intersection obstacles and information regarding one or more neighboring vehicles. 10. The method of claim 9 , wherein the information regarding the one or more neighboring vehicles includes at least one of position, velocity, acceleration, and deceleration for the one or more neighboring vehicles. 11. The method of claim 7 , further comprising: if the updated information does not indicate clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to stop the autonomous vehicle at the yield scenario. 12. A computing device, comprising: one or more processors for controlling operations of the computing device; and a memory for storing data and program instructions used by the one or more processors, wherein the one or more processors are configured to execute instructions stored in the memory to: detect an intersection including a yield scenario: identify a check point location between an autonomous vehicle and the yield scenario based on at least one of traffic density information, intersection type, intersection configuration, or a presence of one or more obstacles that could at least partially obstruct a view of the intersection by the autonomous vehicle; prior to the autonomous vehicle reaching the check point location, send a command to one or more vehicle systems to control the autonomous vehicle to stop at the yield scenario; after the autonomous vehicle reaches the check point location, detect, using a perception system, information for the intersection; and when the information indicates clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to drive the autonomous vehicle through the intersection. 13. The computing device of claim 12 , wherein the yield scenario includes one of a yield sign, a red traffic light, a roundabout, and a lane merge. 14. The computing device of claim 12 , wherein the information for the intersection includes at least one of map-based information and information regarding intersection obstacles and information regarding one or more neighboring vehicles. 15. The computing device of claim 14 , wherein the map-based information includes at least one of an intersection type and an intersection configuration. 16. The computing device of claim 14 , wherein the information regarding the one or more neighboring vehicles includes at least one of position, velocity, acceleration, and deceleration for the one or more neighboring vehicles. 17. The computing device of claim 12 , wherein the one or more processors are further configured to: if the information does not indicate clear passage through the intersection for the autonomous vehicle, send a command to the one or more vehicle systems to stop the autonomous vehicle at the yield scenario.
where a selection from the received information takes place in the vehicle · CPC title
Lane change; Overtaking manoeuvres · CPC title
where the origin of the information is within the own vehicle, e.g. a local storage device, digital map · CPC title
where the origin of the information is a central station · CPC title
for passive traffic, e.g. including static obstacles, trees · CPC title
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