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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed on November 29th 2024.
Drawings
The drawings were received on November 29th 2024. These drawings are accepted.
Status of the Claims
This Non-final action is in response to the applicant’s filling on November 29th 2024.
Claims 1-18 are pending and examined below.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 14-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 14 includes limitation; “computer readable storage medium” the disclosed storage medium is claimed very broadly because it appears to further include a processor. It’s not clear to examiner how they the “computer readable storage medium” is claimed in view of the specification stating that the medium may be, for example, a CDROM and the claim language reciting that the medium includes a processor.
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.
Claims 1-4, 8-11 and 14-18 are rejected under 35 U.S.C. 103 as being unpatentable over Gupta (Patent No. US20240308513A1) in view of Zahid (Patent No. US20250030505A1) and Mizutani (Patent No. US11173906B2).
Regarding claim 1 Schoning teaches a method of controlled vehicles used in a server; (See Gupta paragraph 0168; “…FIG. 3A illustrates a flow diagram of a method 300, according to example embodiments… gap distance between the transport and the lead transport in 312, and controlling, via the server, a speed of the transport via an activated cruise control function based on the recommended gap distance in 313..”); the server comprises a processor and a storage medium; the processor executes computer programs stored in the storage medium to implement following processes; (See Gupta paragraph 0091 and 0095; “FIG. 2B illustrates another transport network diagram 210, according to example embodiments. The network comprises elements including a transport 202 including a processor 204, as well as a transport 202′ including a processor 204′. The transports 202, 202′ communicate with one another via the processors 204, 204′, as well as other elements (not shown), including transceivers, transmitters, receivers, storage, sensors, and other elements capable of providing communication. The communication between the transports 202, and 202′ can occur directly, via a private and/or a public network (not shown), or via other transports and elements comprising one or more of a processor, memory, and software. The processors 204, 204′ can further communicate with one or more elements 230 including sensor 212, wired device 214, wireless device 216, database 218, mobile phone 220, transport 222, computer 224, I/O device 226, and voice application 228. The processors 204, 204′ can further communicate with elements comprising one or more of a processor, memory, and software… The transport 202 could be a transport, server or any device with a processor and memory.… “); receiving invokable information of at least one first vehicle and first vehicle information; (See Gupta paragraph 0086 and 0087; “The server (or other system) may obtain sensor data from the transport such as images of surrounding vehicles from Lidar and/or cameras, speed from the transport's computer, GPS from the transport, and the like. This information may be used by the server to detect that the transport is following another vehicle and that the transport is not following at a recommend gap distance… FIG. 1J, the recommendation engine 112 may perform a process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport 194 until the recommended gap distance is achieved. For example, the recommendation engine 112 may transmit V2X instructions which instruct the transport 194 to take certain actions such as slowing down or speeding up to a particular speed, an amount of time to perform such action, and the like. In the example of FIG. 1J, the recommendation engine 112 controls the ADAS 184 until a recommended gap distance 190b is achieved.”; the invokable information is configured to indicate the corresponding first vehicle is in an invokable state; (See Gupta paragraph 0086; “…The server (or other system) may obtain sensor data from the transport such as images of surrounding vehicles from Lidar and/or cameras, speed from the transport's computer, GPS from the transport, and the like. This information may be used by the server to detect that the transport is following another vehicle and that the transport is not following at a recommend gap distance. In response, the recommendation engine 112 may request the change via a user interface on the transport 194 or it may overtake control of the ADAS 184 on the transport 194 and move the transport to a recommended gap distance or in between a range of recommended gap distances.”); the first vehicle sets with a fully self-driving system for autonomous controlling a vehicle to drive; (See Gupta paragraph 0096; “…controlling, via the server, the transport to change speed via the activated cruise control function based on the detected change in the weather in 247D, remotely controlling one or more of a speed and a direction of an autonomous vehicle in 248D…”); receiving first requesting information of a second vehicle and second vehicle information; (See Gupta paragraph 0086 and 0096; “FIGS. 1I and 1J illustrate a process of remotely overtaking a cruise control function of a transport 194 while it is following another transport 192 in accordance with example embodiments. According to various embodiments, the host system, for example, a server, cloud platform, a blockchain network, or the like, which is remotely connected to the transport 194, may remotely send instructions (e.g., vehicle to everything (V2X) communications, etc.) to a transport which control a speed of a transport to achieve a recommended gap distance. The server (or other system) may obtain sensor data from the transport such as images of surrounding vehicles from Lidar and/or cameras, speed from the transport's computer, GPS from the transport, and the like. This information may be used by the server to detect that the transport is following another vehicle and that the transport is not following at a recommend gap distance… The processor 204 may perform remotely activating the adaptive cruise control function via transmission of a first vehicle-to-everything (V2X) communication in 244D, remotely triggering the transport to change the speed of the transport via a second vehicle-to-everything (V2X) communications until the gap distance between the transport and the lead transport is the recommended gap distance in 245D, obtaining, via the server, one or more of weather data and traffic data, wherein the determining comprises determining the recommended gap distance based on the one or more of the weather data and the traffic data in 246D, detecting a change in weather based on the obtained sensor data, and in response, controlling, via the server, the transport to change speed via the activated cruise control function based on the detected change in the weather in 247D, remotely controlling one or more of a speed and a direction of an autonomous vehicle in 248D, executing a machine learning model on the obtained sensor data to determine the recommended gap distance in 249D, and transmitting and receiving communications via a PC5 interface in 250D.”);
confirming a vehicle stop strategy according to the first vehicle information and the second vehicle information; (See Gupta paragraph 0064-0065; “FIG. 1A illustrates a computing environment 100 for iteratively updating (i.e., training and retraining) a machine learning model for recommending gap distances between a vehicle and a lead vehicle according to example embodiments. Referring to FIG. 1A, the computing environment includes a host platform 110 such as a web server, a cloud platform, database, combination of systems, and the like. In this example, the host platform include a recommendation engine 112 for recommending a gap distance and a machine learning model 114 for predicting the recommended gap distance. The host platform 110 also includes a communication interface such as a network interface, network card, or the like, which can transmit/receive data via various wireless and/or wired communication channels.
In the example of FIG. 1A, a vehicle 104 is following a lead vehicle 102. This process can be monitored and tracked by the host platform 110 in order to perform a model training or model update process. Here, the recommendation engine has two stages: modeling stage and control stage. Both stages have their corresponding tasks in the real world (deployed on the real vehicle) and the “Digital Twin” world (deployed on the cloud). The modeling stage happens when the driver operates the vehicle manually. Based on a rule-based logic, all the car-following events can be filtered out and transmitted to the host platform 110 (via the communication interface 116) together with the environment information (e.g., weather conditions, road types, etc) from external sources such as a map server 120 and a weather server 124 which may include APIs 122 and 126, respectively, for controlling access to such data. The carfollowing events, represented as sequential trajectory data, may be approximated using GMM. The GMM distribution of a trajectory is regarded as the driver's driving style.”);
and transmitting second requesting information to the target vehicle, thereby making the target vehicle to provide a resistance to the second vehicle according to the vehicle stop strategy, and making the second vehicle to stop moving; (See Gupta paragraph 0087;” For example, in FIG. 1I, the recommendation engine 112 detects that a gap distance 196 currently exists between the transport 194 and the lead transport 192 while the two transports are traveling down a road. Here, the recommendation engine 112 may use the processes described herein to determine a recommend gap distance or recommended range of gap distances and compares the gap distance 196 to the recommend gap distance(s). In this case, the recommendation engine 112 determines that the gap distance 196 is not a recommended gap distance based on the comparison. Accordingly, in FIG. 1J, the recommendation engine 112 may perform a process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport 194 until the recommended gap distance is achieved. For example, the recommendation engine 112 may transmit V2X instructions which instruct the transport 194 to take certain actions such as slowing down or speeding up to a particular speed, an amount of time to perform such action, and the like. In the example of FIG. 1J, the recommendation engine 112 controls the ADAS 184 until a recommended gap distance 190b is achieved.”- (examiners notes - process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport - a resistance to the second vehicle… making the second vehicle to stop moving)).
Gupta does not explicitly teach but Zahid teaches, when the second vehicle is in a predefined state, the first requesting information is generated, the first requesting information indicates that the second vehicle requests the server to assist itself to stop moving; (See Zahid paragraph 0163; “One or more of the node 102I and the server 114I may identify at least one vehicle that may be affected by or associated with the event. The at least one affected vehicle may be another vehicle on roads 108I, 106I, or any other proximate road to the event. The at least one affected vehicle may be determined by node 102I, node 104I, and/or server 114I. The at least one affected vehicle may include a vehicle that must slow or stop or otherwise alter a normal traffic speed… node 102I may utilize to assist in the management of the event, such as informing vehicles proximate node 104I of the event and informing vehicles of upcoming emergency vehicles heading towards the event…communicate with those nodes the predictive data pertaining to the event. Upon receiving this information, node 104I may preemptively send out warnings or notifications to other vehicles proximate its location. The purpose of these notifications may be to instruct those vehicles to maneuver based on the received predictions before the predicted time when the vehicle(s) will be close to node 104I, effectively proactively managing vehicle movements or behaviors responsive to detected events.”).
Gupta and Zahid are in the same field of endeavor of method of controlling vehicles. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Gupta method of controlled vehicles used in a server with Zahid vehicle requests to assist itself to stop moving. Gupta includes server, V2V communication and vehicle control so it would be
obvious to modify Gupta to send a control command to the assist in stopping the second vehicle. No new functionality would arise from the combination and the combination would improve usability of Gupta by adding Zahid vehicle requests to assist itself to stop moving. Further, finding that one of
ordinary skill in the art would have recognized that the results of the combination were predictable.
Gupta does not explicitly teach but Mizutani teaches, and confirming at least one first vehicle as a target vehicle according to the vehicle stop strategy and the first vehicle information; (See Mizutani column 12-13, line 59-7;” FIG. 11 is diagram (1) for explaining a process when the following is inappropriate and the own vehicle M is not traveling in a vehicle line. Here, for example, it is assumed that, although the own vehicle M is following another vehicle m1, the gate passage controller 123C determines that it is inappropriate to follow the other vehicle m1 since the other vehicle m1 has stopped. In this case, the gate passage controller 123C selects another vehicle m2 as a following target vehicle and performs control for following the other vehicle m2. The other vehicle m2 is a vehicle scheduled to pass through the same gate as that through which the own vehicle M is scheduled to pass. Thus, even when the following has become inappropriate, the gate passage controller 123C performs control for following a new following target vehicle, and therefore it is possible to smoothly control the vehicle when passing through a gate.).
Gupta and Mizutani are in the same field of endeavor of method of controlling vehicles. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Gupta method of controlled vehicles used in a server with Mizutani confirming the target vehicle based on the stopping strategy. Gupta includes server, V2V communication and vehicle control so it would be obvious to modify Gupta to define the target vehicle. No new functionality would arise from the combination and the combination would improve usability of Gupta by adding Mizutani confirming the target vehicle based on the stopping strategy. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 2 Gupta in view of Zahid and Mizutani teaches the method of claim 1, Gupta does not teach but Mizutani teaches, wherein there are several first vehicles; a number of the target vehicles is more than one; (See Mizutani Figure 5-8 “other vehicles”) ; the target vehicles are selected from the first vehicles according to the vehicle stop strategy and the first vehicle information; (See Mizutani column 13, line 21-27; “FIG. 12 is a diagram showing how virtual lines are set when the following is inappropriate and the vehicle is not traveling in a vehicle line. For example, similar to FIG. 11, it is assumed that the gate passage controller 123C determines that it is inappropriate to follow another vehicle m1 since the other vehicle m3 has stopped.”).
Gupta and Mizutani are in the same field of endeavor of method of controlling vehicles. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Gupta method of controlled vehicles used in a server with Mizutani confirming the target vehicle from number of vehicles based on the stopping strategy. Gupta includes server, V2V communication and vehicle control so it would be obvious to modify Gupta to define the target vehicle. No new functionality would arise from the combination and the combination would improve usability of Gupta by adding Mizutani confirming the target vehicle from number of vehicles based on the stopping strategy. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 3 Gupta in view of Zahid and Mizutani teaches the method of claim 1, Gupta further teaches, transmitting a third requesting information to the target vehicle, thereby making the target vehicle to transmit vehicle control permission information; (See Gupta paragraph 0051 and Figure 2D; “…sensor information may be used to identify whether the vehicle is operating safely and whether an occupant has engaged in any unexpected vehicle conditions, such as during a vehicle access and/or utilization period. Vehicle information collected before, during and/or after a vehicle's operation may be identified and stored in a transaction on a shared/distributed ledger, which may be generated and committed to the immutable ledger as determined by a permission granting consortium, and thus in a “decentralized” manner, such as via a blockchain membership group.”); receiving the vehicle control permission information transmitted by the target vehicle; (See Gupta paragraph 0087; “in FIG. 1I, the recommendation engine 112 detects that a gap distance 196 currently exists between the transport 194 and the lead transport 192 while the two transports are traveling down a road. Here, the recommendation engine 112 may use the processes described herein to determine a recommend gap distance or recommended range of gap distances and compares the gap distance 196 to the recommend gap distance(s). In this case, the recommendation engine 112 determines that the gap distance 196 is not a recommended gap distance based on the comparison. Accordingly, in FIG. 1J, the recommendation engine 112 may perform a process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport 194 until the recommended gap distance is achieved. For example, the recommendation engine 112 may transmit V2X instructions which instruct the transport 194 to take certain actions such as slowing down or speeding up to a particular speed, an amount of time to perform such action, and the like. In the example of FIG. 1J, the recommendation engine 112 controls the ADAS 184 until a recommended gap distance 190b is achieved.”); and controlling the target vehicle to provide the resistance to the second vehicle based on the vehicle control permission information thereby making the second vehicle to stop moving; (See Gupta paragraph 0087;” For example, in FIG. 1I, the recommendation engine 112 detects that a gap distance 196 currently exists between the transport 194 and the lead transport 192 while the two transports are traveling down a road. Here, the recommendation engine 112 may use the processes described herein to determine a recommend gap distance or recommended range of gap distances and compares the gap distance 196 to the recommend gap distance(s). In this case, the recommendation engine 112 determines that the gap distance 196 is not a recommended gap distance based on the comparison. Accordingly, in FIG. 1J, the recommendation engine 112 may perform a process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport 194 until the recommended gap distance is achieved. For example, the recommendation engine 112 may transmit V2X instructions which instruct the transport 194 to take certain actions such as slowing down or speeding up to a particular speed, an amount of time to perform such action, and the like. In the example of FIG. 1J, the recommendation engine 112 controls the ADAS 184 until a recommended gap distance 190b is achieved.”- (examiners notes - process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport - a resistance to the second vehicle… making the second vehicle to stop moving)).
Gupta does not teach but Mizutani teaches, wherein after confirming at least one first vehicle as a target vehicle according to the vehicle stop strategy and the first vehicle information, the method further comprises; (See Mizutani column 12-13, line 59-7;” FIG. 11 is diagram (1) for explaining a process when the following is inappropriate and the own vehicle M is not traveling in a vehicle line. Here, for example, it is assumed that, although the own vehicle M is following another vehicle m1, the gate passage controller 123C determines that it is inappropriate to follow the other vehicle m1 since the other vehicle m1 has stopped. In this case, the gate passage controller 123C selects another vehicle m2 as a following target vehicle and performs control for following the other vehicle m2. The other vehicle m2 is a vehicle scheduled to pass through the same gate as that through which the own vehicle M is scheduled to pass. Thus, even when the following has become inappropriate, the gate passage controller 123C performs control for following a new following target vehicle, and therefore it is possible to smoothly control the vehicle when passing through a gate.).
Gupta and Mizutani are in the same field of endeavor of method of controlling vehicles. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Gupta method of controlled vehicles used in a server with Mizutani confirming the target vehicle from number of vehicles based on the stopping strategy. Gupta includes server, V2V communication and vehicle control so it would be obvious to modify Gupta to define the target vehicle. No new functionality would arise from the combination and the combination would improve usability of Gupta by adding Mizutani confirming the target vehicle from number of vehicles based on the stopping strategy. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Regarding claim 4 Gupta in view of Zahid and Mizutani teaches the method of claim 1, Gupta farther teaches, wherein confirming the vehicle stop strategy according to the first vehicle information and the second vehicle information comprises; (See Gupta paragraph 0064-0065; “FIG. 1A illustrates a computing environment 100 for iteratively updating (i.e., training and retraining) a machine learning model for recommending gap distances between a vehicle and a lead vehicle according to example embodiments. Referring to FIG. 1A, the computing environment includes a host platform 110 such as a web server, a cloud platform, database, combination of systems, and the like. In this example, the host platform include a recommendation engine 112 for recommending a gap distance and a machine learning model 114 for predicting the recommended gap distance. The host platform 110 also includes a communication interface such as a network interface, network card, or the like, which can transmit/receive data via various wireless and/or wired communication channels.
In the example of FIG. 1A, a vehicle 104 is following a lead vehicle 102. This process can be monitored and tracked by the host platform 110 in order to perform a model training or model update process. Here, the recommendation engine has two stages: modeling stage and control stage. Both stages have their corresponding tasks in the real world (deployed on the real vehicle) and the “Digital Twin” world (deployed on the cloud). The modeling stage happens when the driver operates the vehicle manually. Based on a rule-based logic, all the car-following events can be filtered out and transmitted to the host platform 110 (via the communication interface 116) together with the environment information (e.g., weather conditions, road types, etc) from external sources such as a map server 120 and a weather server 124 which may include APIs 122 and 126, respectively, for controlling access to such data. The carfollowing events, represented as sequential trajectory data, may be approximated using GMM. The GMM distribution of a trajectory is regarded as the driver's driving style.”); confirming a predicated travelling track and/or a predicated speed of the vehicle stop strategy according to the first vehicle information, person information in the second vehicle and/or a degree of the second vehicle in out-of-control; (See Gupta paragraph 0088-0089; “It should also be appreciated that the recommendation engine 112 may receive a stream of traffic data and/or weather data from the map server 120 and/or the weather server 124, respectively. The recommendation engine 112 may use this information to predict the recommended gap distance using machine learning or the like. As another example, the recommendation engine 112 may analyze images sent back from the transport 194 for signs of a change in weather (e.g., rain beginning to fall, snow beginning to fall, sunlight coming out, dark clouds/skies, etc.) and automatically overtake the ADAS 184 to address or otherwise react to the change in weather. The same images can also be analyzed for changes in traffic patterns or traffic density which can also cause the recommendation engine 112 to overtake the transport 194 and change the speed thereof.
For example, the host system may estimate/determine a distance between the transport and the lead transport based on the sensor data such as speed data, measured distances, etc. The host system may compare the distance to a one or more thresholds for example a minimum allowed distance (e.g., 25 meters, etc.) and a maximum recommended distance (e.g., 50 meters, etc.). If the transport is following the lead transport by less than the minimum threshold allowed or more than the maximum threshold allowed, the server may determine that the transport's gap distance is incorrect and should be changed. In this case, the recommendation engine 112 shown in FIG. 1I, may activate the adaptive cruise control function (ADAS 184) of a transport 1945”).
Regarding claim 18 Gupta in view of Zahid and Mizutani teaches the computer readable storage medium of claim 14, Gupta does not teach but Mizutani teaches, the target vehicle is confirmed according to the vehicle stop strategy and the first vehicles with the weight ordered in ascending sequence; (See Mizutani column 10, line 26-46; “FIG. 5 is a diagram showing an example of a scenario in which a following target vehicle is selected in a main line. The information acquirer 110 acquires, from other vehicles m1 and m2 present near the own vehicle M, information on gates through which they are scheduled to pass. For example, when the gate through which the other vehicle m1 is scheduled to pass is gate (3) and the gate through which the other vehicle m2 is scheduled to pass is the gate (6), the vehicle selector 123B selects the other vehicle m1, which is scheduled to pass through the same gate as the gate (3) through which the own vehicle M is scheduled to pass, as a following target vehicle. Then, the gate passage controller 123C causes the own vehicle M to change lanes to the lane in which the other vehicle m1 is traveling and performs control for passing through the gate (3), following the other vehicle m1 as shown in FIG. 6. FIG. 6 shows an example of a scenario in which the own vehicle M which has changed lanes in an area in which there are road lane lines enters a non-lane-line area AR in which no road lane lines are drawn (which is an area between gates and the main line before the gates) and follows another vehicle m.”).
Gupta and Mizutani are in the same field of endeavor of method of controlling vehicles. It would have been obvious for one ordinary skilled in the art before the effective filing date of present invention to modify Gupta method of controlled vehicles used in a server with Mizutani confirming the target vehicle from number of vehicles based on the stopping strategy. Gupta includes server, V2V communication and vehicle control so it would be obvious to modify Gupta to define the target vehicle. No new functionality would arise from the combination and the combination would improve usability of Gupta by adding Mizutani confirming the target vehicle from number of vehicles based on the stopping strategy. Further, finding that one of ordinary skill in the art would have recognized that the results of the combination were predictable.
With respect to the independent claims 8 and 14, please see rejection above with respect to claim 1 which is commensurate in scope to claims 8 and 14, with claim 1 being drawn to method, claim 7 being drawn to an invention server and claim 14 being drawn to invention computer readable storage medium.
With respect to the independent claims 9 -11, please see rejection above with respect to claims 2-4 which is commensurate in scope to claims 9 -11, with claims 2-4 being drawn to method and claims 9-11 being drawn to an invention server.
With respect to the independent claims 15-17, please see rejection above with respect to claims 2-4 which is commensurate in scope to claims 15-17, with claims 2-4 being drawn to method and claims 15-17 being drawn to invention computer readable storage medium.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 5-7 and 12-13 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Gupta (Patent No. US20240308513A1).
Regarding claim 5 Gupta teaches a method of controlling vehicles used in a first vehicle equipped with a fully self-driving system for autonomous controlling a vehicle to drive; (See Gupta paragraph 0110; “…The transport 276/277 may be semi-autonomous or autonomous. For example, transport 276/277 may be self-maneuvering and navigate without human input. An autonomous vehicle may have and use one or more sensors and/or a navigation unit to drive autonomously.”); the first vehicle further comprises a processor and a storage medium; the processor executes computer programs stored in the storage medium to implement following processes; (See Gupta paragraph 0098; “The transport 202 may have a computing device or a server computer, or the like, and may include a processor 204, which may be a semiconductor-based microprocessor, a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), and/or another hardware device. Although a single processor 204 is depicted, it should be understood that the transport 202 may include multiple processors, multiple cores, or the like without departing from the scope of the instant application. The transport 202 could be a transport, server or any device with a processor and memory.”); determining whether the first vehicle is in an invokable state; (See Gupta paragraph 0086; “…The server (or other system) may obtain sensor data from the transport such as images of surrounding vehicles from Lidar and/or cameras, speed from the transport's computer, GPS from the transport, and the like. This information may be used by the server to detect that the transport is following another vehicle and that the transport is not following at a recommend gap distance. In response, the recommendation engine 112 may request the change via a user interface on the transport 194 or it may overtake control of the ADAS 184 on the transport 194 and move the transport to a recommended gap distance or in between a range of recommended gap distances.”); when the first vehicle is in the invokable state, transmitting invokable information to a server; (See Gupta paragraph 0086; “…The server (or other system) may obtain sensor data from the transport such as images of surrounding vehicles from Lidar and/or cameras, speed from the transport's computer, GPS from the transport, and the like. This information may be used by the server to detect that the transport is following another vehicle and that the transport is not following at a recommend gap distance. In response, the recommendation engine 112 may request the change via a user interface on the transport 194 or it may overtake control of the ADAS 184 on the transport 194 and move the transport to a recommended gap distance or in between a range of recommended gap distances.”); and receiving second requesting information of the server, the second requesting information indicates that the first vehicle provides the resistance to a second vehicle according to a vehicle stop strategy, thereby making the second vehicle to stop moving; (See Gupta paragraph 0087;” For example, in FIG. 1I, the recommendation engine 112 detects that a gap distance 196 currently exists between the transport 194 and the lead transport 192 while the two transports are traveling down a road. Here, the recommendation engine 112 may use the processes described herein to determine a recommend gap distance or recommended range of gap distances and compares the gap distance 196 to the recommend gap distance(s). In this case, the recommendation engine 112 determines that the gap distance 196 is not a recommended gap distance based on the comparison. Accordingly, in FIG. 1J, the recommendation engine 112 may perform a process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport 194 until the recommended gap distance is achieved. For example, the recommendation engine 112 may transmit V2X instructions which instruct the transport 194 to take certain actions such as slowing down or speeding up to a particular speed, an amount of time to perform such action, and the like. In the example of FIG. 1J, the recommendation engine 112 controls the ADAS 184 until a recommended gap distance 190b is achieved.”- (examiners notes - process 190b and overtake the ADAS 184 on the transport and automatically change the speed of the transport - a resistance to the second vehicle… making the second vehicle to stop moving)).
Regarding claim 6 Gupta teaches the method of claim 5, Gupta also teaches, further comprising: transmitting vehicle control permission information of the first vehicle to the server in response to the third requesting information of the server; (See Gupta paragraph 0051 and Figure 2D; “…sensor information may be used to identify whether the vehicle is operating safely and whether an occupant has engaged in any unexpected vehicle conditions, such as during a vehicle access and/or utilization period. Vehicle information collected before, during and/or after a vehicle's operation may be identified and stored in a transaction on a shared/distributed ledger, which may be generated and committed to the immutable ledger as determined by a permission granting consortium, and thus in a “decentralized” manner, such as via a blockchain membership group.”).
With respect to the independent claims 7 and 12, please see rejection above with respect to claim 5 which is commensurate in scope to claims 7 and 10, with claim 5 being drawn to method, claim 7 being drawn to an invention method and claim 12 being drawn to invention vehicle.
With respect to the dependent claim 13, please see rejection above with respect to claim 6 which is commensurate in scope to claim 13, with claim 6 being drawn to method and claim 1 being drawn to invention vehicle.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to LIDIA KWIATKOWSKA whose telephone number is (571)272-5161. The examiner can normally be reached Monday-Friday 8:00-5:00.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott A. Browne can be reached at (571) 270-0151. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/L.K./Examiner, Art Unit 3666
/SCOTT A BROWNE/Supervisory Patent Examiner, Art Unit 3666