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 .
DETAILED ACTION
This action is in response to the applicant’s filing on 11/18/2025. Claims 1-5, 7-8 are pending.
Response to Amendment and Arguments
In respond to applicant's arguments based on the filed amendment with respect to 35 U.S.C. 102 rejections of said previous office action have been fully considered; however, upon further consideration, a new ground(s) of rejection is made.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-5, 7-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Shridhar et al. US2022/0105955 (“Shridhar”) in view of Beauchamp et al. US2021/0158687 (“Beauchamp”).
Regarding claim(s) 1, 4. Shridhar discloses an information processing device using a spatiotemporal database in which information about objects on a road is continuously stored in association with time information and space information (para. 4, A vehicle trajectory is represented by a number of footprints (e.g., a plurality of cells defining a fixed area occupied by an autonomous vehicle) spaced within a spatio-temporal occupancy grid over a number of corresponding time steps in the testing time frame.), the information processing device comprising:
a search unit, comprising one or more processors, configured to search the spatiotemporal database for information about trajectories of objects in a predetermined area (para. 82, the machine-learned models can be previously trained by the one or more remote computing system(s) 290B, the operations computing system 290A, or any other device (e.g., remote servers, training computing systems, etc.) remote from or onboard the vehicle 205. For example, the one or more machine-learned models can be learned by a training computing system (e.g., the operations computing system 290A, etc.) over training data stored in a training database.);
a prediction unit comprising one or more processors, configured to predict future paths of the objects on the basis of the information about the trajectories of the objects (para. 83-90, FIG. 3A is an example scenario 300 with a testing object 335 (e.g., real-world object, simulated object, etc.) that follows a real trajectory 315 to travel to a location on the road 310 within the trajectory of the vehicle 205. In addition, the scenario 300 includes a predicted object 325 that is predicted to follow the predicted object trajectory 320 to travel to a location off of the road 310 outside of the trajectory of the vehicle 205. FIG. 3B is an example scenario 350 in which the predicted object 325 is predicted to follow the predicted object trajectory 320 to travel to the location on the road 310 within the trajectory of the vehicle 205 and the testing object 335 actually follows the real trajectory 315 to travel to the location off of the road 310 outside of the trajectory of the vehicle 205..);
a determination unit comprising one or more processors, configured to determine whether or not objects are likely to collide based on the future paths (para. 89, The risk of the prediction data 275B may be related to recall. The prediction data 275B, for example, can forecast an object's future motion (e.g., a predicted object trajectory 320) and predict spaces of an environment occupied by the object at future points in time. Recall can represent a portion (e.g., a percentage, etc.) of an actual object's actual future occupied space that is accounted for by the prediction data 275B. A low avoidance metric 455 (e.g., low recall) can suggest that the prediction data 275B does not enable an autonomous vehicle to correctly anticipate the actual future space occupied by the actual object (e.g., a simulated object or real-world object), thereby impacting roadway safety by lowering the vehicle's ability to avoid the actual object while navigating a roadway.); and
a notification unit, comprising one or more processors, configured to notify affected objects in a case where there is a possibility of collision (para. 81, A display device (e.g., screen of a tablet, laptop, or smartphone) can be viewable by a user of the vehicle 205 that is located in the front of the vehicle 205 (e.g., driver's seat, front passenger seat). Additionally, or alternatively, a display device can be viewable by a user of the vehicle 205 that is located in the rear of the vehicle 205 (e.g., a back passenger seat). The user device(s) associated with the display devices can be any type of user device such as, for example, a table, mobile phone, laptop, etc. The vehicle user device(s) 280 can be configured to function as human-machine interfaces. For example, the vehicle user device(s) 280 can be configured to obtain user input, which can then be utilized by the vehicle computing system 210 or another computing system (e.g., a remote computing system, etc.).).
Shridhar does not explicitly teach:
generate a spatiotemporal code using time information indicating a time desired to be searched and space information indicating a space desired to be searched, and search the spatiotemporal database for information about trajectories of objects in a predetermined area using the generated spatiotemporal code as a key, wherein the generated spatiotemporal code includes first bits representing the desired time, second bits representing a latitude of the space information, third bits representing a longitude of the space information.
Beauchamp teaches another vehicle navigation system and method that generate a spatiotemporal code using time information indicating a time desired to be searched and space information indicating a space desired to be searched, and search the spatiotemporal database for information about trajectories of objects in a predetermined area using the generated spatiotemporal code as a key, wherein the generated spatiotemporal code includes first bits representing the desired time, second bits representing a latitude of the space information, third bits representing a longitude of the space information (Para. 20-21, 70-72, The AI algorithms may be used to predict the likely trajectory of participants based on small spatiotemporal data sets as well as large spatiotemporal data sets. A spatiotemporal trajectory model may be defined as a set of spatiotemporal points X=(x,y,z,t) of a participant moving along a trajectory represented by its geolocation coordinates in space and time (sequential datasets of participant, time and location).).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the system and method of Shridhar by incorporating the applied teaching of using spatiotemporal code such as position and time as taught by Beauchamp to reduce the risk of collision between vehicle and obstacles and one of ordinary skill before the effective filing date of the claimed invention would have recognized that the results of the combination would have been predictable.
Regarding claim(s) 2, 5. Shridhar in view of Beauchamp further teaches wherein in a case where a future path of an object is stored in the spatiotemporal database, the prediction unit is configured to acquire the future path from the spatiotemporal database (para. 75, para. 89, The vehicle computing system 210 can be configured to predict a motion of the object(s) within the surrounding environment of the vehicle 205. For instance, the vehicle computing system 210 can generate prediction data 275B associated with such object(s). The prediction data 275B can be indicative of one or more predicted future locations of each respective object.).
Regarding claim(s) 3. Shridhar in view of Beauchamp further teaches wherein the search unit is configured to generate a spatiotemporal code using time information indicating a time desired to be searched and space information indicating a space desired to be searched, and search the spatiotemporal database using the generated spatiotemporal code as a key (para. 27-35, . The spatio-temporal occupancy grid is defined by path-relative coordinates adapted to an intended path of the autonomous vehicle. The intended path of the autonomous vehicle is based at least in part on a road geometry associated with the environment. In some implementations, receiving the data indicative of the trajectory of the autonomous vehicle includes generating the data indicative of the trajectory of the autonomous vehicle based at least in part on the intended path of the autonomous vehicle, determining a trajectory probability for the trajectory, and determining a probability that the particular footprint is reached by the autonomous vehicle based at least in part on the trajectory probability for the trajectory. ).
Regarding claim(s) 7. Shridhar in view of Beauchamp further teaches a non-transitory computer readable medium storing a program, wherein execution of the program causes a computer to operate as each unit of the information processing device according to claim 1 (para. 157, The memory 1215 can also store computer-readable instructions 1225 that can be executed by the one or more processors 1210. The instructions 1225 can be software written in any suitable programming language or can be implemented in hardware. Additionally, or alternatively, the instructions 1225 can be executed in logically or virtually separate threads on processor(s) 1210.).
Regarding claim(s) 8. Shridhar in view of Beauchamp further teaches a non-transitory computer readable medium storing a program installed in a terminal via a network, wherein execution of the program causes a computer to operate as each unit of the information processing device according to claim 1 (para. 157, The memory 1215 can also store computer-readable instructions 1225 that can be executed by the one or more processors 1210. The instructions 1225 can be software written in any suitable programming language or can be implemented in hardware. Additionally, or alternatively, the instructions 1225 can be executed in logically or virtually separate threads on processor(s) 1210.).
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 extension fee 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 date of this final action.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRUC M DO whose telephone number is (571)270-5962. The examiner can normally be reached on 9AM-6PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramón Mercado, Ph.D. can be reached on (571) 270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TRUC M DO/Primary Examiner, Art Unit 3658
Prosecution Insights