Lane changes for autonomous vehicles involving traffic stacks at intersection
US-2023417565-A1 · Dec 28, 2023 · US
US2025058803A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2025058803-A1 |
| Application number | US-202318235793-A |
| Country | US |
| Kind code | A1 |
| Filing date | Aug 18, 2023 |
| Priority date | Aug 18, 2023 |
| Publication date | Feb 20, 2025 |
| Grant date | — |
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Embodiments herein include systems and methods of generating lane selection cost values to control autonomous vehicles to accommodate merging vehicles in a tapering lane (or merge lane). An autonomy system can identify a tapering lane in map data and detect a merging vehicle situated in the tapering lane using perception sensor data. The autonomy system includes a lane-selection cost function that generates lane-selection cost values for the lanes available to the automated vehicle, which the autonomy system references to determine whether to continue traveling a current lane or change lanes into an adjacent lane. The lane-selection cost function may apply a courtesy weight when detecting the merging vehicle, such that the autonomy system causes the automated vehicle to change lanes as a courtesy to the merging vehicle, but without overriding other safety-related factors of the lane-selection cost function or trajectory planning functions.
Opening claim text (preview).
What is claimed is: 1 . A method for navigation planning for an automated vehicle, the method comprising: obtaining, by a processor of an automated vehicle, sensor data from a plurality of sensors onboard the automated vehicle for a roadway, the roadway including a current travel lane of the automated vehicle, an adjacent travel lane that is adjacent to the current travel lane, and a tapering travel lane that is adjacent to the current lane of travel and on an opposite side of the current travel lane from the adjacent travel lane; identifying, by the processor, a merging vehicle in the tapering lane by applying an object recognition engine on the sensor data; obtaining, by the processor, a first cost value for the current travel lane and a second cost value for the adjacent lane based upon the sensor data, each cost value representing a cost for traveling in the corresponding lane; determining, by the processor, that the first cost value is comparatively lower than the second cost value; and updating, by the processor, a control command for causing the automated vehicle to continue driving in the current travel lane. 2 . The method according to claim 1 , further comprising: determining, by the processor, a closing-distance of the automated vehicle relative to the merging vehicle; and determining, by the processor, that the closing-distance fails to satisfy a threshold closing-distance, wherein the processor determines the first cost value is comparatively lower than the second cost value in response to determining that the closing-distance fails to satisfy the threshold closing-distance. 3 . The method according to claim 1 , further comprising: identifying, by the processor, a first vehicle and a second vehicle in the adjacent lane by applying the object recognition engine on the sensor data; and determining, by the processor, a traffic gap in the adjacent travel lane, the traffic gap having an amount of distance between the first vehicle and the second vehicle in the adjacent lane. 4 . The method according to claim 3 , wherein the processor determines that the first cost value is comparatively lower than the second cost value when the processor fails to identify the traffic gap satisfying a gap distance. 5 . The method according to claim 3 , further comprising determining, by the processor, a velocity change for the automated vehicle to move into the traffic gap, wherein the processor determines that the first cost value is comparatively lower than the second cost value when the processor determines the velocity change fails to satisfy a threshold velocity change for moving into the traffic gap. 6 . The method according to claim 1 , wherein the processor updates each cost value and the control command in response to identifying the merging vehicle. 7 . The method according to claim 1 , wherein the processor continually updates each cost value and the control command at a preconfigured interval. 8 . The method according to claim 1 , wherein the processor obtains each cost value for each lane based upon detecting each traffic vehicle in the roadway. 9 . The method according to claim 1 , wherein the processor obtains each cost value for each lane based upon a courtesy weight of a lane selection cost function. 10 . The method according to claim 1 , further comprising transmitting, by the processor, the command that causes the autonomous vehicle to continue driving in the current travel lane to an operating module for driving the automated vehicle. 11 . A system for navigation planning for an automated vehicle, the system comprising: a non-transitory computer-readable memory on board an automated vehicle configured to store map data associated with a geographic location having an intersection; and a processor of the automated vehicle configured to: obtain sensor data from a plurality of sensors onboard the automated vehicle for a roadway, the roadway including a current travel lane of the automated vehicle, an adjacent travel lane that is adjacent to the current travel lane, and a tapering travel lane that is adjacent to the current lane of travel and on an opposite side of the current travel lane from the adjacent travel lane; identify a merging vehicle in the tapering lane by applying an object recognition engine on the sensor data; obtain a first cost value for the current travel lane and a second cost value for the adjacent lane based upon the sensor data, each cost value representing a cost for traveling in the corresponding lane; determine that the first cost value is comparatively lower than the second cost value; and update a control command for causing the automated vehicle to continue driving in the current travel lane. 12 . The system according to claim 11 , wherein the processor is further configured to: determine a closing-distance of the automated vehicle relative to the merging vehicle; and determine that the closing-distance fails to satisfy a threshold closing-distance, wherein the processor determines the first cost value is comparatively lower than the second cost value in response to determining that the closing-distance fails to satisfy the threshold closing-distance. 13 . The system according to claim 11 , wherein the processor is further configured to: identify a first vehicle and a second vehicle in the adjacent lane by applying the object recognition engine on the sensor data; and determine a traffic gap in the adjacent travel lane, the traffic gap having an amount of distance between the first vehicle and the second vehicle in the adjacent lane. 14 . The system according to claim 13 , wherein the processor determines that the first cost value is comparatively lower than the second cost value when the processor fails to identify the traffic gap satisfying a gap distance. 15 . The system according to claim 13 , wherein the processor is further configured to determine a velocity change for the automated vehicle to move into the traffic gap, and wherein the processor determines that the first cost value is comparatively lower than the second cost value when the processor determines the velocity change fails to satisfy a threshold velocity change for moving into the traffic gap. 16 . The system according to claim 11 , wherein the processor updates each cost value and the control command in response to identifying the merging vehicle. 17 . The system according to claim 11 , wherein the processor continually updates each cost value and the control command at a preconfigured interval. 18 . The system according to claim 11 , wherein the processor obtains each cost value for each lane based upon detecting each traffic vehicle in the roadway. 19 . The system according to claim 11 , wherein the processor obtains each cost value for each lane based upon a courtesy weight of a lane selection cost function. 20 . The system according to claim 11 , wherein the processor is further configured to transmit the control command that causes the autonomous vehicle to continue driving in the current travel lane to an operating module for driving the automated vehicle.
Road markings, e.g. lane marker or crosswalk · CPC title
for two or more other traffic participants · CPC title
Number of lanes · CPC title
Lane change; Overtaking manoeuvres · CPC title
Position · CPC title
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