DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is in response to the amendments filed on 06/29/2026. Wherein, Claims 1, 2, 10-14, 16, 18,19, and 20, are amended, claims 8 and 17 are cancelled, claims 21-22 are new. Claims 1-7, 9-16, and 18-22 are rejected.
Information Disclosure Statement
The information Disclosure Statement filed on 05/12/2026 has been considered. An initialed copy of form 1449 is enclosed herewith.
Response to Arguments
Applicant’s arguments, see REMARKS, filed 06/29/2026, with respect to the rejection(s) of claim(s) 1-5, 7-8, 10-14, and 16-20 under 35 USC §102 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Chen et al.
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 (i.e., changing from AIA to pre-AIA ) 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, 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.
Claim(s) 1-5, 7, 10-14, 16, 18-20, and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Xia et al. (US 2021/0188317 A1, “Xia”) in view of Chen et al. (CN 115257740 A, “Chen”).
Regarding claims 1, 10, and 18, Xia discloses method and apparatus for planning autonomous vehicle, electronic device, and storage medium and teaches:
An apparatus comprising: (The present application provides a method for planning an autonomous vehicle, an apparatus for planning an autonomous vehicle, an electronic device and a storage medium – See at least ¶ [0005])
a memory configured to store instructions; and one or more processors coupled to the memory and configured to execute the instructions to cause the apparatus to: (According to another aspect of the present application, an electronic device is provided, which may include: at least one processor; and a memory in a communicational connection with the at least one processor, where the memory is stored with instructions executable by the at least one processor, the instructions are executed by the at least one processor to cause the at least one processor to execute the method for planning an autonomous vehicle according to the embodiments of the present application – See at least ¶ [0018]-[0020])
obtain a planned traveling path and a first motion parameter of a first intelligent driving device, (Step 101 : acquire first traveling information of an autonomous vehicle adc, where the first traveling information includes a traveling track and a traveling parameter of the autonomous vehicle adc – See at least ¶ [0040]) wherein the first motion parameter comprises a first velocity or a first acceleration of the first intelligent driving device; [] (The traveling parameter may include at least one of the speed and the acceleration – See at least ¶ [0041])
obtain, when the distance is less than or equal to the first distance threshold and is greater than or equal to the second distance threshold, (Herein, in order to meet the requirement of perception stability, the preparation stage is required to be an area where the autonomous vehicle adc can stably detect the moving speed of the obstacle vehicle obs. And in order to accurately reflect the driving intention of the obstacle vehicle obs in the game stage, the preparation stage needs to be as close to the vehicle-converging area as possible. In addition, the position of the preparation stage needs to meet the distance required by straight-ahead yielding or overtaking. Specifically, the preparation stage may be determined based on the speed of the obstacle vehicle obs and the distance to the vehicle-converging area. That is, the higher the current speed of the obstacle vehicle obs is, the longer the deceleration distance is required when the obstacle vehicle obs takes a deceleration action. Therefore, earlier determination of the intention of the obstacle vehicle obs is required – See at least ¶ [0096]-[0097]) a predicted motion trajectory and a second motion parameter of the first object, and wherein the second motion parameter comprises a second velocity or a second an acceleration of the first object; (Step 102: acquire second traveling information of at least one obstacle vehicle obs, where the second traveling information includes position information and a traveling parameter of the obstacle vehicle obs. Specifically, the second traveling information of the obstacle vehicle obs may include position information of the obstacle vehicle obs at more than two time points and a lane position where the obstacle vehicle obs is located. The traveling parameter may include at least one of the speed and the acceleration – See at least ¶ [0043])
determine, when the planned traveling path overlaps the predicted motion trajectory, a planned motion trajectory of the first intelligent driving device based on the first motion parameter and the second motion parameter, (Step 104: plan a vehicle-converging strategy for the autonomous vehicle adc according to the first traveling information and the driving intention of the obstacle vehicle obs upon determining that there is a possibility of vehicle converging between the autonomous vehicle adc and the obstacle vehicle obs – See at least ¶ [0046]) wherein the planned motion trajectory comprises a motion trajectory in which the first intelligent driving device grabs a way of or yields to the first object at a first preset velocity; and (Based on the predicted driving intention of the obstacle vehicle obs in any of the above-described embodiments, the planning the vehicle-converging strategy for the autonomous vehicle adc according to the first traveling information and the driving intention of the obstacle vehicle obs may include: planning the autonomous vehicle adc to yield when the predicted driving intention of the obstacle vehicle obs is overtaking; and planning the autonomous vehicle adc to overtake when the predicted driving intention of the obstacle vehicle obs is yielding – See at least ¶ [0079]-[0081])
control the first intelligent driving device to travel based on the planned motion trajectory. (Step 105: control the autonomous vehicle adc to travel according to the vehicle-converging strategy – See at least ¶ [0047])
Xia does not explicitly teach determine whether a distance between a first object and the first intelligent driving device is less than or equal to a first distance threshold and is greater than or equal to a second distance threshold; avoid performing autonomous driving decision-making and trajectory planning of the first intelligent driving device when the distance is less than the second distance threshold. However, Chen discloses control method and device for adaptive cruise control and teaches:
determine whether a distance between a first object and the first intelligent driving device is less than or equal to a first distance threshold and is greater than or equal to a second distance threshold; (In implementation, the ACC system can determine the vehicle's driving direction based on the driving direction corresponding to the current position in the vehicle's planned path, and then determine the objects whose relative position is in the vehicle's driving direction and whose first relative distance is less than a first preset distance threshold as candidate following objects – See at least ¶ [0066])
avoid performing autonomous driving decision-making and trajectory planning of the first intelligent driving device when the distance is less than the second distance threshold (In this way, the ACC system can filter out objects located outside the vehicle's driving trajectory and retain only objects within the vehicle's driving trajectory as candidate follow up objects, thus avoiding the ACC system from mistakenly triggering objects outside the vehicle's driving trajectory – See at least ¶ [0066])
In summary, Xia discloses identifying multiple thresholds in order to perform autonomous driving functions. Xia does not explicitly teach determine whether a distance between a first object and the first intelligent driving device is less than or equal to a first distance threshold and is greater than or equal to a second distance threshold; avoid performing autonomous driving decision-making and trajectory planning of the first intelligent driving device when the distance is less than the second distance threshold. However, Chen discloses control method and device for adaptive cruise control and teaches filtering objects located outside the vehicle’s driving trajectory, i.e., when the distance is less than the threshold.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to have modified the method and apparatus for planning autonomous vehicle, electronic device, and storage medium of Xia to provide for the control method and device, as taught in Chen, to avoid the automatic driving function from mistakenly triggering objects outside the vehicles driving trajectory. (At Chen ¶ [0066])
Regarding claims 2, 11, and 19, Xia further teaches:
wherein determining the planned motion trajectory comprises:
determining a first deduced trajectory of the first intelligent driving device based on a first sampling acceleration and the first motion parameter, wherein the first sampling acceleration is a third acceleration that may be reached by the first intelligent driving device in a sampling space;
determining a second deduced trajectory of the first object based on a second sampling acceleration and the second motion parameter, wherein the second sampling acceleration is a fourth an acceleration that may be reached by the first object in the sampling space; and (Referring to FIG. 1, assuming that a traveling track taken by the autonomous vehicle adc is a first track Pade that is a track of a left turn at an intersection. A traveling track taken by the obstacle vehicle obs is a second track Pobs of going straight through the intersection from an opposite lane, it may then be determined that time points, i.e., a first sampling space, at which the autonomous vehicle adc enters and leaves a vehicle-converging area (i.e. a game point) I_R, to be Tadc,i and Tade,o respectively, and time points, i.e., a second sampling space, at which the obstacle vehicle obs enters and leaves the vehicle-converging area, to be Tobs,i, and Tobs,o respectively – see at least ¶ [0035])
determining, when the first deduced trajectory and the second deduced trajectory indicate that the first intelligent driving device does not collide with the first object, or that the first object collides with a side enclosure or a tail of the first intelligent driving device in a first traveling direction of the first object at a first moment, the planned motion trajectory based on the first deduced trajectory and the second deduced trajectory, wherein the first moment is after a current moment. (Two vehicles cannot collide at the intersection, thus there may be two cases, namely the obstacle vehicle obs overtaking and passing by or yielding and passing by, which may be expressed in time as follows: if the obstacle vehicle overtakes and passes by, the obstacle vehicle must leave the game point before the autonomous vehicle enters vehicle-converging area I_R, i.e. Tobs,0 < Tadc,i; if the obstacle vehicle yields and passes by, the obstacle vehicle must enter the game point after the autonomous vehicle leaves the vehicle-converging area I_R , i.e., Tobs,o > Tade,i)
Regarding claims 3, 12, and 20,
wherein the determining the first deduced trajectory comprises:
determining a first deduced sub-trajectory based on the first sampling acceleration and at least one of the first velocity or the first acceleration, wherein a third velocity of the first intelligent driving device at an end point of the first deduced sub-trajectory is the first preset velocity; (computing, according to the acquired first traveling information of the autonomous vehicle adc, time when the autonomous vehicle adc enters a vehicle-converging area and time when the autonomous vehicle adc leaves the vehicle-converging area – See at least ¶ [0050])
determining a second deduced sub-trajectory based on the first preset velocity, wherein the end point is a start point of the second deduced sub-trajectory; and (Referring to FIG. 1, assuming that a traveling track taken by the autonomous vehicle adc is a first track Pade that is a track of a left turn at an intersection. A traveling track taken by the obstacle vehicle obs is a second track Pobs of going straight through the intersection from an opposite lane, it may then be determined that time points at which the autonomous vehicle adc enters and leaves a vehicle-converging area (i.e. a game point) I_R, to be Tadc,i and Tade,o respectively, and time points, at which the obstacle vehicle obs enters and leaves the vehicle-converging area, to be Tobs,i, and Tobs,o respectively – see at least ¶ [0035])
determining the first deduced trajectory based on the first deduced sub-trajectory and the second deduced sub-trajectory. (Two vehicles cannot collide at the intersection, thus there may be two cases, namely the obstacle vehicle obs overtaking and passing by or yielding and passing by, which may be expressed in time as follows: if the obstacle vehicle overtakes and passes by, the obstacle vehicle must leave the game point before the autonomous vehicle enters vehicle-converging area I_R, i.e. Tobs,0 < Tadc,i; if the obstacle vehicle yields and passes by, the obstacle vehicle must enter the game point after the autonomous vehicle leaves the vehicle-converging area I_R , i.e., Tobs,o > Tade,I – See at least ¶ [0035] In step 211, an overtaking track of the obstacle vehicle obs is compared with a yielding track of the autonomous vehicle adc. In step 213, whether the vehicle-converging strategy is reasonable is determined according to a comparison result. If it is reasonable, in step 215, the strategy is retained, otherwise, in step 214, pruning is performed – See at least ¶ [0099] and Fig. 4; Here, the system is determining potential trajectories, i.e., sub-trajectories, based on different strategies, e.g., overtaking or yielding. Depending on the reasonableness the system prunes or retains the potential trajectory and then implements it.)
Regarding claims 4, 13, and 21, Xia further teaches:
wherein determining the planned motion trajectory based on the first deduced trajectory and the second deduced trajectory comprises:
determining a first game strategy based on the first deduced trajectory and the second deduced trajectory, (Assuming that a traveling track, a speed, and an acceleration of an obstacle vehicle predicted from acquired information of the obstacle vehicle are correct, taking into account that a traveling track of an autonomous vehicle is also determined, traveling routes of the two vehicles is equivalent to the determination of a game (vehicle-converging) position between the autonomous vehicle and the obstacle vehicle. Thus a two-dimensional game problem is reduced to a one-dimensional time planning game problem – See at least ¶ [0033]) wherein the first game strategy (Step 104: plan a vehicle-converging strategy for the autonomous vehicle adc according to the first traveling information and the driving intention of the obstacle vehicle obs upon determining that there is a possibility of vehicle converging between the autonomous vehicle adc and the obstacle vehicle obs – See at least ¶ [0046]) indicates to the first intelligent driving device to grab the way of or yield to the first object at the first preset velocity; and (Based on the predicted driving intention of the obstacle vehicle obs in any of the above-described embodiments, the planning the vehicle-converging strategy for the autonomous vehicle adc according to the first traveling information and the driving intention of the obstacle vehicle obs may include: planning the autonomous vehicle adc to yield when the predicted driving intention of the obstacle vehicle obs is overtaking; and planning the autonomous vehicle adc to overtake when the predicted driving intention of the obstacle vehicle obs is yielding – See at least ¶ [0079]-[0081])
determining, when a duration of the first game strategy is greater than a first time threshold, the planned motion trajectory based on the first game strategy, the planned traveling path, and the second deduced trajectory. (Optionally, the planning the vehicle-converging strategy for the autonomous vehicle adc according to the first traveling information of the autonomous vehicle adc and the driving intention of the obstacle vehicle obs may include: updating, according to the driving intention of the obstacle vehicle, time when the obstacle vehicle obs enters the vehicle-converging area and/or time when the obstacle vehicle leaves the vehicle-converging area; and planning the autonomous vehicle adc to yield under a condition that the computed time Tade,i when the autonomous vehicle adc enters the vehicle-converging area I_R is later than the time Tobs,i when the obstacle vehicle obs enters the vehicle-converging area I_R; otherwise, planning the autonomous vehicle adc to overtake – See at least ¶ [0082]-[0084])
Regarding claims 5 and 14, Xia further teaches:
wherein determining the planned motion trajectory based on the first game strategy, the planned traveling path, and the second deduced trajectory comprises:
determining, based on the planned traveling path and the second deduced trajectory, a time period in which a first location space of the first object occupies a second location space of the first intelligent driving device; and (Optionally, the planning the vehicle-converging strategy for the autonomous vehicle adc according to the first traveling information of the autonomous vehicle adc and the driving intention of the obstacle vehicle obs may include: updating, according to the driving intention of the obstacle vehicle, time when the obstacle vehicle obs enters the vehicle-converging area and/or time when the obstacle vehicle leaves the vehicle-converging area; and planning the autonomous vehicle adc to yield under a condition that the computed time Tade, i when the autonomous vehicle adc enters the vehicle-converging area I_R is later than the time Tobs,i when the obstacle vehicle obs enters the vehicle-converging area I_R; otherwise, planning the autonomous vehicle adc to overtake – See at least ¶ [0082]-[0084])
determining the planned motion trajectory based on the first game strategy, the second location space, and the time period, wherein the planned motion trajectory comprises a first trajectory in which the first intelligent driving device travels at the first preset velocity in the second location space, or the planned motion trajectory comprises a second trajectory in which the first intelligent driving device travels at the first preset velocity in the time period. (In other words, the vehicles that arrive in the vehicle-converging area I_R first pass first. Thus in a case of possible vehicle-converging, the speed of the vehicles participating in the game is changed as little as possible, i.e., a preset velocity, when the vehicles pass through the vehicle-converging area)
Regarding claims 7 and 16, Xia further teaches:
wherein determining the first deduced trajectory comprises: determining the first deduced trajectory based on a lateral offset of the first intelligent driving device, the first sampling acceleration, and the first motion parameter, and wherein the lateral offset is perpendicular to a second traveling direction of the first intelligent driving device. (Optionally, the vehicle-converging strategy planning unit 504 is further configured to: plan the autonomous vehicle adc to yield when the predicted driving intention of the obstacle vehicle obs is overtaking, and plan the autonomous vehicle adc to overtake when the predicted driving intention of the obstacle vehicle obs is yielding – See at least ¶ [0119]-[0121]; As shown in Fig. 1, the autonomous vehicle is turning left, this produces a lateral offset perpendicular to the current driving direction. In the context of the application “overtaking” includes accelerating to move through the intersection before the other vehicle.)
Claim(s) 6 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Xia in view of Chen, as applied to claims 1 and 10, and in further view of Wang et al. (US 2022/0032960 A1, “Wang”).
Regarding claims 6 and 15, the combination of Xia and Chen does not explicitly teach further comprising determining, prior to determining the first game strategy, that a strategy cost of a deduced trajectory pair comprising the first deduced trajectory and the second deduced trajectory is a smallest cost. However, Wang discloses game-theoretic planning for risk-aware interactive agents and teaches:
further comprising determining, prior to determining the first game strategy, that a strategy cost of a deduced trajectory pair comprising the first deduced trajectory and the second deduced trajectory is a smallest cost. (Aspects of the present disclosure describe the inter action of risk-aware agents in a game-theoretical frame work. In particular, the present disclosure demonstrates that the game-theoretic framework leads to more time efficient behaviors and higher safety when facing underlying risks in an uncertain environment. One configuration of a disclosed trajectory planning system models each agent as a risk aware agent with entropic risk measure . This model involves an iterative algorithm for approximating the feedback Nash equilibria of a risk-sensitive dynamic game. For example, at each iteration, the trajectory planning system derives a linearized approximation of the system dynamics and a quadratic approximation of the cost function in solving a backward recursion for finding feedback Nash equilibria – See at least ¶ [0025]; the trajectory of the ego vehicle 450 is selected to minimize the risk-aware cost function associated with a planned trajectory to complete the tactical driving maneuver of transitioning into the merge gap 430 – See at least ¶ [0058])
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to have modified the method and apparatus for planning autonomous vehicle, electronic device, and storage medium of Xia and Chen to provide for the game-theoretic planning for risk-aware interactive agents, as taught in Wang, to provide a trajectory planning system that results in behaviors for the agents that are more realistic and intuitive and is more time efficient and safer than if either the game interaction or the risk sensitivity were ignored. (At Wang ¶ [0025])
Claim(s) 9 and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Xia in view of Chen, as applied to claim 1, and in further view of Russell et al. (US 2022/0204056 A1, “Russell”).
Regarding claims 9 and 22, the combination of Xia and Chen does not explicitly teach wherein the first preset velocity is greater than or equal to 3 kilometers per hour and less than or equal to 15 kilometers per hour. However, Russell discloses permeable speed constraints and teaches:
wherein the first preset velocity is greater than or equal to 3 kilometers per hour and less than or equal to 15 kilometers per hour. (By allowing the vehicle to drive through the constraint at a low speed (e.g., less than about 5-10 mph), the amount of necessary braking is reduced – See at least ¶ [0098])
In summary, Xia discloses operating the vehicle according to preset velocity and acceleration constraints. Xia does not explicitly disclose a speed range of equal to or greater than 3 km/h and less than or equal to 15 km/h. However, Russel discloses permeable speed constraints for self-driving vehicles and teaches a speed constraint of less than about 5-10 mph.
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the instant application to have modified the method and apparatus for planning autonomous vehicle, electronic device, and storage medium of Xia and Chen to provide for permeable speed constraints, as taught in Russell, to reduce the amount of necessary braking. (At Russell ¶ [0098])
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/C.L.C./Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662
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