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 the Claims
This first non-final action is in response to applicant's filing on Sept. 17, 2024. Claims 1 to 20 are pending and have been considered as follows.
Drawings
The drawings are objected to under 37 CFR 1.83(a). The drawings must show every feature of the invention specified in the claims. Therefore, the different elements of the claims, including “a likelihood that one or more first vehicles parked at a predetermined pullover location for an autonomous vehicle of a fleet of autonomous vehicles will begin to unpark from the predetermined pullover location based on previous observations, by one or more autonomous vehicles of the fleet of autonomous vehicles, of how often or long one or more second vehicles have previously parked at the predetermined pullover location” etc. must be shown or the feature(s) canceled from the claim(s). The drawings seem to merely narratively repeat the subject matter of the specification but no specifics of the claim elements are shown. No new matter should be entered.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1 to 20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-2, 6-22, 24 of U.S. Patent No. 12130147 (reference patent) as in the following claim correspondence table:
Claims in U.S. Patent 12130147 (reference patent)
Claims in Present Application 18/887,589
1
1
2
2
6
3
7
3
8
4
9
5
10
6
11
7
12
8, 20
13
9
14
10
15
12
16
13,17
17
14
18
15
19
16
20
17
21
18
22
19, 20
24
11
Applicant’s arguments with respect to the claim rejections under Double Patenting have been
Claim Rejections - 35 USC § 103
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 3, 6, 11, 18-20 are rejected under 35 U.S.C. 103 as being obvious over Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1)
Regarding claim 1, Ghose teaches a method comprising: A method comprising: determining, by the one or more processors based on the likelihood, a pullover quality value for the predetermined pullover location (Ghose, Scores are calculated at 628 for the possible parking locations. a respective score is calculated by the processor 422 of Fig. 4 for each of the possible parking locations identified at 616. the scores are calculated using each of the criteria analyzed in 619-626, [0901]); and
enabling the autonomous vehicle to select a pullover location for the autonomous vehicle by providing, by the one or more processors, the pullover quality value to the autonomous vehicle (A preferred parking location is selected at 630. the processor 422 of FIG. 4 selects the possible location with the highest (or, best), [0095]).
Ghose does not explicitly teach but Lee teaches determining, by one or more processors, a likelihood that one or more first vehicles parked at a predetermined pullover location for an autonomous vehicle of a fleet of autonomous vehicles will begin to unpark from the predetermined pullover location based on previous observations, by one or more autonomous vehicles of the fleet of autonomous vehicles, of how often or long one or more second vehicles have previously parked at the predetermined pullover location ( Lee [0370] the vehicle 100 can detect a different vehicle 100B with a high probability of moving out of the parking space S5 in future and emptying the parking space S5. For example, the vehicle 100 may detect an engine sound of the different vehicle 100B and expect that the corresponding vehicle 100B will leave from the parking space S5 soon).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose, a likelihood that one or more parked vehicles will begin to move from respective parked locations, as taught by Lee, as Ghose and Lee are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using a likelihood that one or more parked vehicles will begin to move from respective parked locations ([0370], Lee) and predictably applied it to predict parking space availability for an autonomous vehicle of Ghose.
Ghose as modified by Lee does not teach but Thakur teaches the specific limitation of wherein a likelihood that one or more first vehicles parked at a predetermined pullover location for an autonomous vehicle of a fleet of autonomous vehicles will begin to unpark from the predetermined pullover location based on previous observations (Thakur, [0104]-[0116] the machine learning/training of an algorithms based on other vehicle observations/ experiences, etc. to use in another AV at a later time, [0124] prior observations that a vehicle was moving but is now stopped can indicate that the vehicle is likely to move again; [0112] maintain (e.g., predict and update) one or more hypothesis regarding the possible intentions of the real-world object. Examples of intentions (e.g., hypotheses) include stop, turn right, turn left, go straight, pass, and park. A likelihood is associated with each hypothesis. The likelihood is updated based on observations received from sensor data)
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee, the likelihood being based on previous observations, as taught by Thakur, as Ghose, Thakur and Lee are directed to vehicle control(same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using the likelihood being based on previous observations ([0112], Thakur) and predictably applied it to predict possible intentions of the real-world object.
Regarding independent claim 11, please look at the rejection to claim 1 above.
Regarding claim 3, Ghose teaches further comprising receiving, by the one or more processors, road geometry for the predetermined pullover location, wherein determining the pullover quality value is further based on the road geometry relating to whether vehicles park on one or both sides of a road at the predetermined pullover location (at least [0092] the score is also influenced by a function that shapes the pullover trajectory for the vehicle 10 based on how much space is available to pull over. the function compares how far the pullover spot is from the lane boundary edge, and how much longitudinal space there is to perform the maneuver, and intelligently adjusts the pullover or parking maneuver accordingly, [0093] curbing parking).
Regarding claim 6, Ghose teaches wherein the characteristic includes legal restrictions at the predetermined pullover location (Local laws and regulations are analyzed at 622, [0087]).
Regarding claim 18, Ghose teaches , wherein the one or more processors are further configured to: provide, to the autonomous vehicle, a different pullover quality value associated with a different predetermined pullover location for the autonomous vehicle; and enable the autonomous vehicle to select either the predetermined pullover location or the different predetermined pullover location based the pullover quality value and the different pullover quality value (Ghosh, abstract, a respective score for each of the potential parking locations using a plurality of factors; and selecting, by the processor using the data, a selected parking location of the potential parking locations based on the respective score of each of the potential parking locations).
Regarding claim 19, while Ghose teaches wherein the one or more processors are further configured to determine the different pullover quality value based on different previous observations, by the one or more autonomous vehicles, of one or more vehicles parked at the different predetermined pullover location (Ghosh, abstract, a respective score for each of the potential parking locations using a plurality of factors; and selecting, by the processor using the data, a selected parking location of the potential parking locations based on the respective score of each of the potential parking locations).
Regarding claim 20, while Ghose teaches wherein the one or more processors are further configured to: determine a different likelihood of one or more first emergency vehicles on a road at the predetermined pullover location based on previous observations, by the one or more autonomous vehicles, of one or more second emergency vehicles at the predetermined pullover location; and determine the pullover quality value further based on the different likelihood (Ghosh, abstract, a respective score for each of the potential parking locations using a plurality of factors; and selecting, by the processor using the data, a selected parking location of the potential parking locations based on the respective score of each of the potential parking locations).
Claim 2 is rejected under 35 U.S.C. 103 as being obvious over Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) and further in view of Bahgat (US 20150130638A).
Regarding claim 2, while Ghose as modified by Lee as modified by Thakur teaches the expected curb occupancy is based on the previous observations, by the one or more other autonomous vehicles of the fleet of autonomous vehicles, of the one or more second vehicles parking or unparking at the predetermined pullover location at the second point in time (Thakur, [0104]-[0128]), Ghose as modified by Lee as modified by Thakur does not teach but Bahgat teaches wherein the characteristic includes an expected curb occupancy for the predetermined pullover location for a given period of time ([0025] vehicle data 152 also includes historical data corresponding to vehicles that have utilized the parking area (e.g., number of times a vehicle has utilized the parking area, frequency that a vehicle has utilized the parking area, previous durations of time that a vehicle has remained in the parking area, [0028] Parking space prediction engine 140 utilizes statistical model 156 to determine probabilities of a departure time of a vehicle from the parking area relative to the arrival time of the vehicle to the parking area. For example, if a vehicle has been in the parking area for twenty minutes, statistical model 156 indicates that there is a 35% probability that the -------vehicle will leave the parking area after twenty minutes (based on the vehicle's previous uses of the parking area).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, including an expected curb occupancy for the predetermined pullover location for a given period of time, as taught by Bahgat, as Ghose, as Thakur, Bahgat, and Lee are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using a likelihood that one or more parked vehicles will begin to move from respective parked locations ([0001] Bahgat) and predictably applied it to predict free parking space availability for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur.
Claim 4 is rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) and further in view of Herbach (US 2017/0057510 A1)
Regarding claim 4, Ghose as modified by Lee as modified by Thakur does not explicitly teach but Herbach teaches the specific limitations of wherein determining the pullover quality value is further based on an indication of whether the predetermined pullover location is adjacent to a bicycle lane ( [0091] [0104] In FIG. 4A, the computing device of the autonomous vehicle 400 may identify three regions 402-406 ahead of the autonomous vehicle 400 and determine whether the regions 402-406 are safe or otherwise suitable for pulling over and stopping the autonomous vehicle 400, in accordance with the methods and embodiments described above. The road may comprise two main lanes 408A-B, a bicycle lane 408C, and a curb lane 408D).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, considering whether the predetermined pullover location is adjacent to a bicycle lane, as taught by Herbach, as Ghose, Thakur, Lee and Herbach are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility, considering whether the predetermined pullover location is adjacent to a bicycle lane and predictably applied it in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur to safely pull over and stop the autonomous vehicle based on lane boundaries of the road ([0004] Herbach).
Claims 5 and 9 are rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) and further in view of Mason (US 20160334236 A1)
Regarding claim 5, Ghose as modified by Lee as modified by Thakur does not teach but Mason teaches wherein determining the pullover quality value is further based on an indication of historical traffic conditions at the predetermined pullover location for a given period of time ([0011] the site location can include at least one of: a building at the destination site, a loading dock of the building, a refrigerated loading dock of the building, a particular side of the building, a trash location collection at the destination site, a parking location at the destination site, a delivery entrance of the building, a customer entrance of the building, a long-term parking location at the destination site, an overnight parking location at the destination site, a gate, an inner gate within the site, a security station, and a user-specified location at the destination site. In addition, the context information can include at least one of: preferences of the driver, a number of hours the driver has worked, a number of hours the driver is permitted to work over a period of time, a type of the vehicle, an owner of the vehicle, an entity associated with the vehicle fleet, characteristics of cargo carried by the vehicle, characteristics of a job to be performed by the driver, characteristics of the vehicle, a weight of the vehicle, a size of the vehicle, live traffic information, historical traffic information, current weather, and expected weather)
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, including historical traffic conditions at the predetermined pullover location for a given period of time, as taught by Mason, as Ghose, Thakur, Lee and Mason are directed to vehicle control (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using including historical traffic conditions at the predetermined pullover location for a given period of time ([0011], Mason) and predictably applied it to intelligently select a parking location of Ghose as modified by Lee as modified by Thakur.
Regarding claim 9, Ghose as modified by Lee as modified by Thakur does not teach but Mason teaches determining, by the one or more processors, a feasibility of a vehicle of a particular size or shape to park at the predetermined pullover location based on previous observations, by the one or more autonomous vehicles, of one or more vehicles of the particular size or shape parking at the predetermined pullover location, wherein determining the pullover quality value is further based on the feasibility ([0011] the site location can include at least one of: a building at the destination site, a loading dock of the building, a refrigerated loading dock of the building, a particular side of the building, a trash location collection at the destination site, a parking location at the destination site, a delivery entrance of the building, a customer entrance of the building, a long-term parking location at the destination site, an overnight parking location at the destination site, a gate, an inner gate within the site, a security station, and a user-specified location at the destination site. In addition, the context information can include at least one of: preferences of the driver, a number of hours the driver has worked, a number of hours the driver is permitted to work over a period of time, a type of the vehicle, an owner of the vehicle, an entity associated with the vehicle fleet, characteristics of cargo carried by the vehicle, characteristics of a job to be performed by the driver, characteristics of the vehicle, a weight of the vehicle, a size of the vehicle, live traffic information, historical traffic information, current weather, and expected weather).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, a feasibility of a vehicle of a particular size or shape parking at the predetermined pullover location, as taught by Mason, as Ghose, Thakur, Lee and Mason are directed to vehicle control (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using a feasibility of a vehicle of a particular size or shape parking at the predetermined pullover location (abstract, Manson) and predictably applied it to intelligently select a parking location of Ghose as modified by Lee as modified by Thakur.
Claim 7 is rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) and further in view of Tanaka( US 20050055139 A1)
Regarding claim 7, Ghose as modified by Lee as modified by Thakur does not explicitly teach but Tanaka teaches the specific limitations of wherein determining the pullover quality value is further based on an indication of whether attempted pullovers at the predetermined pullover location by the one or more autonomous vehicles of the fleet of autonomous vehicles include double-parking, blocking a driveway, parking close to an object, or parallel parking ([0052]the target parking position 85 can be determined by learning the past records of the back-in parking maneuver or the parallel parking maneuver of the driver).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, a history of attempted pullovers in the predetermined pullover location, as taught by Pandit, as Ghose, Lee and Tanaka are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using a history of attempted pullovers in the predetermined pullover location and predictably applied it in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur to assist a vehicle maneuver ([0022] Tanaka).
Claims 8 and 12 are rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) and further in view of Wang (US 20180357900 A1)
Regarding claim 8, Ghose as modified by Lee as modified by Thakur does not explicitly teach but Wang teaches further comprising determining, by the one or more processors, a different likelihood of one or more first emergency vehicles on a road at the predetermined pullover location based on previous observations, by the one or more autonomous vehicles, of one or more second emergency vehicles at the predetermined pullover location, wherein determining the pullover quality value is further based on the different likelihood (Wang, [0090] inventory of other data points such as meter parking, locations of bus stops, commercial vehicle parking, taxi lanes, bus lanes, bicycle lanes, emergency lanes, locations of parking garages/facilities, street parking locations, parking restrictions, locations of fire hydrants, etc., can be gathered and applied through a GIS and output to the user's computing device 132 and visualized on a base map. [0114] The computing system 100 may also inform users of temporary changes in alternate-side parking rules (e.g., when alternate parking rules are suspended to severe weather conditions, emergencies, holidays, etc.)).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, a likelihood of emergency vehicles on a road at the predetermined pullover location, as taught by Wang, as Ghose, Lee and Wang are directed to vehicle control (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using likelihood of emergency vehicles on a road at the predetermined pullover location (abstract, Wang) and predictably applied it to avoid illegal parking in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur.
Regarding claim 12, Ghose as modified by Lee as modified by Thakur does not explicitly teach but Wang teaches the specific limitations of wherein the one or more processors are further configured to: receive input from passengers of the fleet of autonomous vehicles providing feedback about attempted pullovers at the predetermined pullover location; and determine the pullover quality value further based on the input ( [0088] suggestions for a specific location or generally, dispute recommendations 428 from users who might give advice to others on effectively disputing parking tickets, and submission ratings 430 for the user engagement panel data 420, [0126] users can rate posts positively or negatively 914 (e.g., by selecting the check-mark for a positive rating and the “X” for a negative rating) within the user engagement panel 134 of user computing device 132, as well as add any comments 910;[0131] This feedback is collected along with the ratings, which may update the database 106 to reflect the new user-submitted data).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, an input from passengers of autonomous vehicles providing feedback about a pullover by a vehicle, as taught by Wang, as Ghose, Thakur, Lee and Wang are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using the input from passengers of autonomous vehicles providing feedback about a pullover by a vehicle (abstract, Wang) and predictably applied it to avoid illegal parking in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee.
Claim 10 is rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) and further in view of Tolkin (US 20170169535 A1)
Regarding claim 10, Ghose as modified by Lee as modified by Thakur does not explicitly teach but Tolkin teaches the specific limitations of further comprising running, by the one or more processors, simulations of one or more autonomous vehicles attempting to park at the predetermined pullover location, wherein determining the pullover quality value is further based on one or more results of the simulations ([0040] FIGS. 6A-6E. Alternatively, in some examples, the travel coordination system 130 does not send eligible pickup locations to the client device 100. the client application running on the client device 100 can be preprogrammed to display simulated or randomly-generated pickup locations to indicate the possibility of other eligible pickup locations to the user).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, results of running simulations of autonomous vehicles attempting to park in the predetermined pullover location, as taught by Tolkin, as Ghose, Thakur, Lee and Tolki are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using the results of running simulations of autonomous vehicles attempting to park in the predetermined pullover location ([0021] Tolki) and predictably applied it to reduce the amount of time spent in traveling, reduce the amount of time for waiting, and/or improve the overall efficiency of traveling in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee.
Claims 13-15 are rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US 20190111916A1) in view of Thakur (US20200409386A1)
and further in view of Colijn (US 20160370194A1)
Regarding claim 13, while Ghose as modified by Lee as modified by Thakur teaches wherein the one or more processors are further configured to: receive, from a client computing device, a request for a trip identifying a location; identify a suggested location for the trip based on the pullover quality value and the location; and provide the suggested location to the client computing device for display to a user ([0063] the user inputs include a request, when appropriate, for parking the vehicle 10 in proximity to a desired destination; [0069] instructions provided by one or more users (e.g., occupants) of the vehicle 10, [0091]-[0095]), Ghose as modified by Lee as modified by Thakur does not explicitly teach but Colijn teaches the specific limitations of providing the suggested location to the client computing device for display to a user (Fig. 6 and corresponding paragraphs).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, providing the suggested location to the client computing device, as taught by Colijn, as Ghose, Lee, Thakur, and Colijn are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using providing the suggested location to the client computing device ([0021] Colijn) and predictably applied it to improve accessibility or safety for a passenger pick in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur.
Regarding claim 14, Ghose as modified by Lee as modified by Thakur teaches wherein the one or more processors are further configured to provide a notification to the client computing device indicating that the autonomous vehicle will pick up or drop off a passenger at the suggested location ([0063] the user inputs include a request, when appropriate, for parking the vehicle 10 in proximity to a desired destination; [0069] instructions provided by one or more users (e.g., occupants) of the vehicle 10, [0091]-[0095] selects the possible location with the highest (or, best) score), Ghose as modified by Lee as modified by Thakur does not explicitly teach but Colijn teaches the specific limitations of providing a notification to the client computing device indicating that a vehicle will pick up or drop off a passenger at the suggested location ([0074] The set of one or more suggested locations is provided to the client computing device at block 1260. A selection of a suggested location of the set of one or more suggested locations is received at block 1270. A vehicle of the one or more autonomous vehicles is dispatched to the selected suggested location at block 1280).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee, a notification to the client computing device indicating that a vehicle will pick up or drop off a passenger at the suggested location, as taught by Colijn, as Ghose, Lee, Thakur and Colijn are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using a notification to the client computing device indicating that a vehicle will pick up or drop off a passenger at the suggested location ([0021] Colijn) and predictably applied it to improve accessibility or safety for a passenger pick in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur.
Regarding claim 15, Ghose as modified by Lee as modified by Thakur does not explicitly teach but Colijn teaches the specific limitations of wherein the notification includes context indicating why the autonomous vehicle will pick up or drop off the passenger at the suggested location, and the one or more processors are further configured to determine the context based on the pullover quality value ([0056] the one or more server computing devices 110 provide a notification to client computing device 120 suggesting the location of map marker 426 as a suggested location for a passenger pickup or destination location, depending upon the nature of the requested location [0065]each predetermined location within the set may be scored using various factors and the one or more highest (or lowest depending upon scale) scoring locations may be returned as suggested locations to the user).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur, a notification to the client computing device indicating that a vehicle will pick up or drop off a passenger at the suggested location, as taught by Colijn, as Ghose, Lee, Thakur and Colijn are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility using a notification to the client computing device indicating that a vehicle will pick up or drop off a passenger at the suggested location ([0021] Colijn) and predictably applied it to improve accessibility or safety for a passenger pick in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur.
Claims 16-17 are rejected under 35 U.S.C. 103 as being obvious over by Ghose (US 20180304926 A1) in view of Lee (US20190111916A1) in view of Thakur (US20200409386A1) in view of Colijn (US20160370194A1) and further in view of Tolkin (US 20170169535 A1)
Regarding claim 16, while Ghose as modified by Lee a as modified by Thakur as modified by Colijn teaches the specific limitations of determining an estimated walking distance to the suggested location and a walking distance threshold (Colijn, [0058], [0061]), Ghose as modified by Lee as modified by as modified by Thakur by Colijn does not explicitly teach but Tolkin teaches further comprising: determining an estimated walking time to the suggested location (Tolkin, the eligible pickup locations may be limited by a threshold distance or walking time from the specified client location. [0038] The eligible pickup locations may be limited by a threshold distance or walking time); and
comparing the estimated walking time to a threshold, and wherein providing the notification is further based on the comparison ([0046] an eligible pickup location may also be excluded if the estimated time for the client to walk to the pickup location exceeds the time for the provider's ETA, Fig. 6A-6F and corresponding paragraphs, [0026] the eligible pickup locations may be limited by a threshold distance or walking time from the specified client location).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur as modified by Colijn, determining an estimated walking time to the suggested location, as taught by Tolkin, as Ghose, Lee, Thakur Colijn and Tolki are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility determining an estimated walking time to the suggested location ([0021] Tolki) and predictably applied it to reduce the amount of time spent in traveling, reduce the amount of time for waiting, and/or improve the overall efficiency of traveling in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur as modified by Colijn.
Regarding claim 17, Ghose as modified by Lee as modified by Thakur as modified by Colijn does not explicitly teach but Tolkin teaches the specific limitations of wherein when the comparison indicates that the estimated walking time is greater than the threshold, providing the notification further includes providing the estimated walking time for display with the notification ([0046] an eligible pickup location may also be excluded if the estimated time for the client to walk to the pickup location exceeds the time for the provider's ETA; if the cost improvement relative to the current location of the client is very low (e.g., 1-2 minutes) or relative to the specified pickup location; [0015], [0026], [0053] Any reduced time or cost (or an updated time of arrival, for example) for the trip relative to the alternate pickup location may also be displayed to the client).
It would have been obvious to one of ordinary skill in the art before the effective date of the present invention to modify, selecting a parking location for an autonomous vehicle, as taught by Ghose as modified by Lee as modified by Thakur as modified by Colijn, determining an estimated walking time to the suggested location, as taught by Tolkin, as Thakur, Ghose, Lee, Colijn and Tolki are directed to vehicle parking (same field of endeavor), and one of ordinary skill in the art would have recognized the established utility determining an estimated walking time to the suggested location ([0021] Tolki) and predictably applied it to reduce the amount of time spent traveling, reduce the amount of time for waiting, and/or improve the overall efficiency of traveling in selecting a parking location for an autonomous vehicle of Ghose as modified by Lee as modified by Thakur as modified by Colijn.
Conclusion
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/J.W./Examiner, Art Unit 3666
/ANNE MARIE ANTONUCCI/Supervisory Patent Examiner, Art Unit 3666