DETAILED ACTION
Receipt is acknowledged of applicant’s response to election/restriction filed on 08/25/2026.
Applicant had elected, without traverse, invention of Group I directed to claims 1-8, and 16-29. Applicant indicated that Group I is directed to claims 9-15; the examiner respectfully disagreed with this statement and it is considered a typo error because (i) on the last Office Action, claims 9-15 had been identified as invention II and (ii) currently, claims 9-15 had been canceled. Applicant had added claims 21-29.
The requirement is still deemed proper and is therefore made FINAL.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-5, 16-18 and 21-26 are rejected under 35 U.S.C. 103 as being unpatentable over Wongpiromsarn (Pub No.: US 2020/0385024 A1) in view of Yoon et al. (Patent No.: 2020/0047771 A1).
Regarding claim 1, Wongpiromsarn discloses a method for path planning for operating an autonomous vehicle, the method comprising:
receiving, by one or more processors of one or more first systems of the autonomous vehicle (e.g., perception module 402 (par. 85)), a signal indicating a e.g., identifying vehicle, via sensor(s) 121 signal(s), at spatiotemporal location 1540 along motion segment 1536 as an obstacle that will slow down an autonomous vehicle (AV) 100) (par. 179, 85 and 163));
in response to the received signal (e.g., sensor’s signal to identifying vehicle), adjusting, by the one or more processors (e.g., planning module 404), costs associated with a trajectory (e.g., the planning module 404 generated an operational metric for operating the AV 100 (e.g., cost of operating) in accordance with motion segment(s)(1528 and 1536) (par. 158). If planning module 404 predicts that operating the AV 100 in the motion segment(s)(1528 and 1536) will lead to a collision / traffic congestion, the module 404 assigns a higher operational metric (cost) to the motion segment(s) (par. 158 and 61)) based on whether the Figure 15 shows the AV 100 traveling on lane 1516, wherein identified vehicle / obstacle will slow down the AV 100 (par. 179 and Figure 15) and prevent the vehicle to exiting an intersection 1504 as the vehicle approaches it due to traffic rule – no changing lane within an intersection (par. 179)).
However, Wongpiromsarn failed to specifically disclose predicted traffic stack on a lane wherein the autonomous vehicle is traveling.
However, Yoon et al. teach an apparatus and method for assisting an autonomous vehicle comprising an electronic device 100 configured to predict a congesting probability of lane and an intersection (par. 77, 67, 70) and command the vehicle to change to another lane to avoid the congestion at the intersection (par. 65 and Figures 3A-3B). Figure 3B shows a vehicle (A) driving into an intersection with lane traffic congestion (Figure 3B and par. 65).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the autonomous vehicle taught by Wongpiromsarn such that the autonomous vehicle predicts a congesting probability of an intersection and lane and changes to another lane to avoid the congestion, in view of Yoon et al., with reasonable expectation of success, since doing so would have achieved the benefit of proactively determine a congestion status of an intersection and actively drive through the congestion area (par. 5) by command the vehicle to change to another lane to avoid the congestion (par. 65 and Figures 3A-3B).
Wongpiromsarn discloses selecting, by the one or more processors (e.g., planning module 404), a trajectory to a destination based on the adjusted costs (e.g., e.g., the planning module 404 determines trajectories (1568, 1572) – having lower total cost - based on the operational metric of each motion segment to reach destination spatiotemporal (1524) (par. 189 and Figure 15) – for instance, “the AV generates a reduced cost trajectory from the initial spatiotemporal location to the destination spatiotemporal location” (par. 41)); and
providing, by the one or more processors (e.g., the control module 406), the selected trajectory to one or more second systems of the autonomous vehicle in order to control the autonomous vehicle according to the selected trajectory (e.g., the control module 406 operates the AV 100 in accordance to the determined trajectory – par. 189).
Regarding claim 2, Wongpiromsarn discloses a method for path planning for operating an autonomous vehicle wherein the predicted traffic stack is located at an intersection (e.g., Figure 15 shows the AV 100 traveling on lane 1516, wherein identified vehicle / obstacle will slow down the AV 100 at intersection 1504 (par. 179 and Figure 15)).
Regarding claim 3, Wongpiromsarn discloses a method for path planning for operating an autonomous vehicle wherein the one or more first systems is a planning system (e.g., planning module 404) of the autonomous vehicle configured to generate trajectories according to a route for the autonomous vehicle to follow (e.g., planning module 404 determines “data representing a trajectory 414” that the vehicle can travel to reach a destination (par. 84 and Figure 4)).
Regarding claim 4, Wongpiromsarn discloses a method for path planning for operating an autonomous vehicle wherein the one or more second systems (e.g., the control module 406 / planning modules 404) include a routing system of the autonomous vehicle configured to generate a route to a destination based on the adjusted costs (e.g., planning modules 404 outputs a route 902 from the start point 904 to an end point 906 (par. 96 and Figure 9) based on operational metric for operating the AV 100 (e.g., cost of operating) in accordance with motion segment(s)(1528 and 1536) (par. 158)).
Regarding claim 5, Wongpiromsarn discloses a method for path planning for operating an autonomous vehicle wherein adjusting the costs includes increasing If planning module 404 predicts that operating the AV 100 in the motion segment(s)(1528 and 1536) will lead to a collision / traffic congestion, the module 404 assigns a higher operational metric (cost) to the motion segment(s) (par. 158)).
Regarding claim 16, Wongpiromsarn discloses an apparatus for path planning for operating an autonomous vehicle, the system comprising:
one or more processors (e.g., perception module 402, planning module 404 and control module 406 (par. 83-85 and Figure 4)) configured to:
receive a signal indicating a e.g., identifying vehicle, via sensor(s) 121 signal(s), at spatiotemporal location 1540 along motion segment 1536 as an obstacle that will slow down an autonomous vehicle (AV) 100) (par. 179, 85 and 163));
in response to the received signal (e.g., sensor’s signal to identifying vehicle), adjust costs associated with a trajectory (e.g., the planning module 404 generated an operational metric for operating the AV 100 (e.g., cost of operating) in accordance with motion segment(s)(1528 and 1536) (par. 158). If planning module 404 predicts that operating the AV 100 in the motion segment(s)(1528 and 1536) will lead to a collision / traffic congestion, the module 404 assigns a higher operational metric (cost) to the motion segment(s) (par. 158 and 61)) based on whether the Figure 15 shows the AV 100 traveling on lane 1516, wherein identified vehicle / obstacle will slow down the AV 100 (par. 179 and Figure 15) and prevent the vehicle to exiting an intersection 1504 as the vehicle approaches it due to traffic rule – no changing lane within an intersection (par. 179)).
However, Wongpiromsarn failed to specifically disclose predicted traffic stack on a lane wherein the autonomous vehicle is traveling.
However, Yoon et al. teach an apparatus and method for assisting an autonomous vehicle comprising an electronic device 100 configured to predict a congesting probability of lane and an intersection (par. 77, 67, 70) and command the vehicle to change to another lane to avoid the congestion at the intersection (par. 65 and Figures 3A-3B). Figure 3B shows a vehicle (A) driving into an intersection with lane traffic congestion (Figure 3B and par. 65).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the autonomous vehicle taught by Wongpiromsarn such that the autonomous vehicle predicts a congesting probability of an intersection and lane and changes to another lane to avoid the congestion, in view of Yoon et al., with reasonable expectation of success, since doing so would have achieved the benefit of proactively determine a congestion status of an intersection and actively drive through the congestion area (par. 5) by command the vehicle to change to another lane to avoid the congestion (par. 65 and Figures 3A-3B).
Wongpiromsarn discloses select the trajectory based on the adjusted costs (e.g., e.g., the planning module 404 determines trajectories (1568, 1572) – having lower total cost - based on the operational metric of each motion segment to reach destination spatiotemporal (1524) (par. 189 and Figure 15) – for instance, “the AV generates a reduced cost trajectory from the initial spatiotemporal location to the destination spatiotemporal location” (par. 41)); and
provide the selected trajectory to one or more second systems of the autonomous vehicle in order to control the autonomous vehicle according to the selected trajectory (e.g., the control module 406 operates the AV 100 in accordance to the determined trajectory – par. 189).
Regarding claim 17, Wongpiromsarn discloses an apparatus for path planning for operating an autonomous vehicle, further comprising the one or more second systems (e.g., a control module 406 operates the AV 100 in accordance to the determined trajectory (par. 189)).
Regarding claim 18, Wongpiromsarn discloses an apparatus for path planning for operating an autonomous vehicle, the one or more second systems include a routing system of the autonomous vehicle configured to generate a route for the autonomous vehicle (e.g., a planning module 404 determines trajectories (1568, 1572) based on the operational metric of each motion segment to reach destination spatiotemporal (1524) (par. 189 and Figure 15)).
Regarding claim 21, Wongpiromsarn discloses an apparatus for path planning for operating a vehicle, further comprising the autonomous vehicle (e.g., wherein the vehicle is an autonomous vehicle (par. 41 and 44)).
Regarding claim 22, Wongpiromsarn discloses a computer-readable medium for storing code / computer software and be executed by a microprocessor / microcontroller to perform a method for path planning to operate an autonomous vehicle (par. 83 and 105), the method comprising:
one or more processors (e.g., perception module 402, planning module 404 and control module 406 (par. 83-85 and Figure 4)) configured to:
receive a signal indicating a e.g., identifying vehicle, via sensor(s) 121 signal(s), at spatiotemporal location 1540 along motion segment 1536 as an obstacle that will slow down an autonomous vehicle (AV) 100) (par. 179, 85 and 163));
in response to the received signal (e.g., sensor’s signal to identifying vehicle), adjust costs associated with a trajectory (e.g., the planning module 404 generated an operational metric for operating the AV 100 (e.g., cost of operating) in accordance with motion segment(s)(1528 and 1536) (par. 158). If planning module 404 predicts that operating the AV 100 in the motion segment(s)(1528 and 1536) will lead to a collision / traffic congestion, the module 404 assigns a higher operational metric (cost) to the motion segment(s) (par. 158 and 61)) based on whether the Figure 15 shows the AV 100 traveling on lane 1516, wherein identified vehicle / obstacle will slow down the AV 100 (par. 179 and Figure 15) and prevent the vehicle to exiting an intersection 1504 as the vehicle approaches it due to traffic rule – no changing lane within an intersection (par. 179)).
However, Wongpiromsarn failed to specifically disclose predicted traffic stack on a lane wherein the autonomous vehicle is traveling.
However, Yoon et al. teach an apparatus and method for assisting an autonomous vehicle comprising an electronic device 100 configured to predict a congesting probability of lane and an intersection (par. 77, 67, 70) and command the vehicle to change to another lane to avoid the congestion at the intersection (par. 65 and Figures 3A-3B). Figure 3B shows a vehicle (A) driving into an intersection with lane traffic congestion (Figure 3B and par. 65).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to modify the autonomous vehicle taught by Wongpiromsarn such that the autonomous vehicle predicts a congesting probability of an intersection and lane and changes to another lane to avoid the congestion, in view of Yoon et al., with reasonable expectation of success, since doing so would have achieved the benefit of proactively determine a congestion status of an intersection and actively drive through the congestion area (par. 5) by command the vehicle to change to another lane to avoid the congestion (par. 65 and Figures 3A-3B).
Wongpiromsarn discloses select the trajectory based on the adjusted costs (e.g., e.g., the planning module 404 determines trajectories (1568, 1572) – having lower total cost - based on the operational metric of each motion segment to reach destination spatiotemporal (1524) (par. 189 and Figure 15) – for instance, “the AV generates a reduced cost trajectory from the initial spatiotemporal location to the destination spatiotemporal location” (par. 41)); and
provide the selected trajectory to one or more second systems of the autonomous vehicle in order to control the autonomous vehicle according to the selected trajectory (e.g., the control module 406 operates the AV 100 in accordance to the determined trajectory – par. 189).
Regarding claim 23, Wongpiromsarn discloses a computer-readable medium for storing code / computer software, wherein the predicted traffic stack is located at an intersection (e.g., Figure 15 shows the AV 100 traveling on lane 1516, wherein identified vehicle / obstacle will slow down the AV 100 at intersection 1504 (par. 179 and Figure 15)).
Regarding claim 24, Wongpiromsarn discloses a computer-readable medium for storing code / computer software, wherein the method further comprises using a planning system (e.g., planning module 404) to generate trajectories according to a route for the autonomous vehicle to follow (e.g., planning module 404 determines “data representing a trajectory 414” that the vehicle can travel to reach a destination (par. 84 and Figure 4)).
Regarding claim 25, Wongpiromsarn discloses a computer-readable medium for storing code / computer software, wherein the one or more second systems (e.g., the control module 406 / planning modules 404) include a routing system of the autonomous vehicle configured to generate a route to a destination based on the adjusted costs (e.g., planning modules 404 outputs a route 902 from the start point 904 to an end point 906 (par. 96 and Figure 9) based on operational metric for operating the AV 100 (e.g., cost of operating) in accordance with motion segment(s)(1528 and 1536) (par. 158) ).
Regarding claim 26, Wongpiromsarn discloses a computer-readable medium for storing code / computer software, wherein adjusting the costs includes increasing or If planning module 404 predicts that operating the AV 100 in the motion segment(s)(1528 and 1536) will lead to a collision / traffic congestion, the module 404 assigns a higher operational metric (cost) to the motion segment(s) (par. 158)).
Claims 6 and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Wongpiromsarn (Pub No.: US 2020/0385024 A1) in view of Yoon et al. (Patent No.: 2020/0047771 A1) and Noh (Pub. No.: US 2014/0358420 A1).
Regarding claims 6 and 27, Wongpiromsarn discloses a method for path planning for operating an autonomous vehicle wherein the signal is a first signal (e.g., signal from sensor(s) 121), the traffic stack is a first traffic stack (e.g., identifying vehicle at spatiotemporal location 1540 along motion segment 1536 as an obstacle that will slow down an autonomous vehicle (AV) 100)), and the lane is a first lane (e.g., Figure 15 shows lane 1515 as a first lane)(par., 179, 85 and 163 and Figure 15).
However, modified Wongpiromsarn, as modified by Yoon et al., failed to specifically disclose receiving a second signal indicating a second predicted traffic stack in a second lane adjacent to the first lane.
However, Noh teaches a vehicle controller configured to predict a traffic lane where the vehicle A is traveling and on other “traffic lanes” (e.g., second predicted traffic stack)(par. 33 and 35) of adjacent / neighboring vehicles via V2V communication (limitation: second signal) (par. 28 and Figure 2), which covers predicted traffic stack in a second adjacent lane.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ) to further modify the autonomous vehicle taught by combination of Wongpiromsarn in view of Yoon et al. such that the autonomous vehicle predicts other traffic lane based on adjacent / neighboring vehicles communication information, in view of Noh., with reasonable expectation of success, since doing so would have achieved the benefit of estimating traffic lane of a vehicle while driving in a substantial middle of the road on which there are many traffic lanes (par. 6).
Wongpiromsarn discloses (i) assigning a particular operation metric (cost) to a motion segment where AV 100 travels that will lead to a collision (par. 158) or particular level of passenger comfort (par. 176) and determining trajectories (1568, 1572) based on the operational metric of each motion segment to reach a destination (par. 189 and Figure 15).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention (AIA ), as a matter of design choice, to implement the processes for assigning an operating metric (cost) to others traffic lanes, with reasonable expectation of success, because the implementation would have achieved the benefit of a determining a trajectory with lower total cost for a vehicle to travel to a destination by considering other traffic lanes and their operating metric (cost).
Allowable Subject Matter
Claims 7-8, 19-20 and 28-29 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Van Den Berg (US 11,199,841 B1) is directed to an autonomous vehicle configured to determine a routing policy based on costs associated with vertices of the lane graph and lane change action.
Abrams (US 2024/0393785 A1) is directed to real-time lane change for autonomous vehicles based on traffic condition and cost function.
This application is CON of 17/849,936 filed on 06/27/2022 now US Pat. 12372366. See MPEP §201.07. In accordance with MPEP §609.02 A. 2 and MPEP §2001.06(b) (last paragraph), the Examiner has reviewed and considered the prior art cited in the Parent Application. Also in accordance with MPEP §2001.06(b) (last paragraph), all documents cited or considered ‘of record’ in the Parent Application are now considered cited or ‘of record’ in this application. Additionally, Applicant(s) are reminded that a listing of the information cited or ‘of record’ in the Parent Application need not be resubmitted in this application unless Applicant(s) desire the information to be printed on a patent issuing from this application. See MPEP §609.02 A. 2. Finally, Applicant(s) are reminded that the prosecution history of the Parent Application is relevant in this application.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Jorge O. Peche whose telephone number is (571)270-1339. The examiner can normally be reached Monday-Friday 8:30 AM - 5:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Khoi H. Tran can be reached at 571 272 6919. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Jorge O Peche/Examiner, Art Unit 3656
Prosecution Insights