DETAILED ACTION
This office action is in response to the Request for Continued Examination dated August 6, 2026.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on August 6, 2026 has been entered.
Claim Status
Claims 1-182 are canceled.
Claims 183 and 193 are currently amended.
Claims 184-192 and 194-202 are as previously presented.
Therefore, claims 183-202 are currently pending.
Response to Amendment
In response to the filed amendment, the rejections under 35 USC 112 to claims 183-202 are hereby withdrawn.
Claim Rejections - 35 USC § 103
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.
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 183-187, 190-197, and 200-202 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (Kim; US PG Pub #2020/0388161), further in view of Tijink et al. (Tijink; US PG Pub #2021/0056839).
As to claim 183, Kim teaches a mobile roadside intelligent unit (MRIU) comprising an intelligent computing module, an intelligent communication module, and an intelligent mobile module (Paragraphs [0035]-[0036] teach a roadside unit vehicle system as a component of a vehicle or car and comprising an on-demand RSU module, a processor, a communication module, a planner module, and a locomotion module; Paragraph [0045] teaches the planner module plans a route and controls autonomous operation of the car via the locomotion module), wherein said MRIU is configured to serve an automated driving system (ADS) by providing, supplementing, and/or enhancing autonomous driving functions for a connected automated vehicle (CAV) (Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles; Paragraphs [0046]-[0053] teaches multiple levels of autonomous vehicles),
wherein the intelligent communication module is configured to communicate with a Roadside Unit Management Control (RUMC) system (Paragraphs [0072]-[0073] teach a car operating as an RSU communicating with a server);
wherein the RUMC system is configured to deploy an MRIU to a deployment location (Paragraph [0066] teaches management issuing a deployment instruction to a car to provide guidance or instruction to operate as a backup RSU at a precise location);
wherein said RUMC system comprises an emergency service module; and
wherein the emergency service module is configured to:
generate MRIU management and control strategies in response to emergency scenarios (Paragraph [0064] teaches the server extracts data to support on-demand RSU services at an event; Paragraphs [0078] and [0083] teach the server is responsible for the type of environments detected by the car to perform the role of RSU and types of control/computation/communication).
However, Kim does not explicitly teach the RUMC system is configured to identify optimal deployment locations and deploying to said optimal location.
In the field of intelligent transportation systems, Tijink teaches deploying to said optimal location (Paragraph [0023] teaches positioning a roadside unit service station at a crucial geographical point). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Kim with the crucial location of Tijink such that the RUMC system is configured to identify optimal deployment locations and to deploy to said optimal locations because this ensures reliable service (Paragraph [0023]).
As to claim 184, depending from the MRIU of claim 183, Kim teaches wherein said MRIU is configured to provide prediction, decision-making, and/or control functions for autonomous driving for a CAV (Paragraph [0030] teaches intention prediction of the ado vehicle detected by the autonomous vehicle operating as the RSU; Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles).
As to claim 185, depending from the MRIU of claim 183, Kim teaches wherein said intelligent computing module is configured to provide data fusion, data storage, and/or data feature extraction for sensing data and/or multi-source sensing data (Paragraph [0038] teaches a computer readable medium storing data manipulated by the processor when executing the software; Paragraph [0040] teaches processing sensor data in conjunction with the computer-readable medium; Paragraph [0054] teaches merging data and extracting frames); predict a traffic flow state; and/or optimize a moving speed and/or a moving path for an MRIU.
As to claim 186, depending from the MRIU of claim 183, Kim teaches wherein said intelligent computing module is configured to generate control strategies, generate vehicle control instructions, and/or distribute vehicle control information and/or instructions for a CAV (Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles).
As to claim 187, depending from the MRIU of claim 183, Kim teaches wherein said intelligent computing module comprises an edge computing unit configured to supplement the computing capacity of the ADS (Paragraph [0038] teaches the RSU vehicle system includes a processor; Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles).
As to claim 190, depending from the MRIU of claim 183, Kim teaches wherein said intelligent mobile module is configured to move the MRIU; and/or to monitor in real-time the movement status and/or energy consumption of the MRIU (Paragraph [0045] teaches planning and controlling locomotion of the car via the locomotion module for autonomous operation of the car).
As to claim 191, depending from the MRIU of claim 183, Kim teaches wherein said intelligent mobile module is configured to be a manual vehicle, an unmanned vehicle, a mobile robot, an unmanned aerial vehicle, a drone, and/or a propeller (Paragraph [0035] teaches the RSU may be a robotic device, a non-autonomous vehicle, or an autonomous vehicle).
As to claim 192, depending from the MRIU of claim 183, Kim teaches wherein said MRIU further includes a sensing module (Paragraph [0036] teaches a sensor module), wherein said sensing module is configured to provide environment sensing to sense the environment and/or to provide mobile state sensing to sense the mobile state of the MRIU (Paragraph [0039] teaches a vision, ranging, thermal, sonar, and/or laser sensor; Paragraph [0078] teaches the type of environment detected by the car).
As to claim 193, Kim teaches an edge computing unit provided in a mobile roadside intelligent unit (MRIU) (Paragraphs [0035]-[0036] teach a roadside unit vehicle system as a component of a vehicle or car and comprising an on-demand RSU module and a processor; Paragraph [0038] teaches the RSU vehicle system includes a processor), said edge computing unit configured to provide edge computing capabilities to serve an automated driving system (ADS) by providing, supplementing, and/or enhancing autonomous driving functions for a connected automated vehicle (CAV) (Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles; Paragraphs [0046]-[0053] teaches multiple levels of autonomous vehicles),
wherein the intelligent communication module is configured to communicate with a Roadside Unit Management Control (RUMC) system (Paragraphs [0072]-[0073] teach a car operating as an RSU communicating with a server);
wherein the RUMC system is configured to deploy an MRIU to a deployment location (Paragraph [0066] teaches management issuing a deployment instruction to a car to provide guidance or instruction to operate as a backup RSU at a precise location);
wherein said RUMC system comprises an emergency service module; and
wherein the emergency service module is configured to:
generate MRIU management and control strategies in response to emergency scenarios (Paragraph [0064] teaches the server extracts data to support on-demand RSU services at an event; Paragraphs [0078] and [0083] teach the server is responsible for the type of environments detected by the car to perform the role of RSU and types of control/computation/communication).
However, Kim does not explicitly teach the RUMC system is configured to identify optimal deployment locations and deploying to said optimal location.
In the field of intelligent transportation systems, Tijink teaches deploying to said optimal location (Paragraph [0023] teaches positioning a roadside unit service station at a crucial geographical point). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Kim with the crucial location of Tijink such that the RUMC system is configured to identify optimal deployment locations and to deploy to said optimal locations because this ensures reliable service (Paragraph [0023]).
As to claim 194, depending from the edge computing unit of claim 193, Kim teaches wherein said edge computing unit is configured to supplement the computing capacity of the ADS (Paragraph [0038] teaches the RSU vehicle system includes a processor; Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles).
As to claim 195, depending from the edge computing unit of claim 193, Kim teaches wherein said edge computing unit is configured to provide edge computing technology to an intelligent computing module of the MRIU (Paragraph [0038] teaches the RSU vehicle system includes a processor).
As to claim 196, depending from the edge computing unit of claim 193, Kim teaches wherein said edge computing unit is configured to provide edge computing technology to an intelligent computing module of the MRIU to generate control strategies, generate vehicle control instructions, and/or distribute vehicle control information and/or instructions for the CAV (Paragraphs [0058]-[0059] teach the on-demand RSU module communicates information, such as warning signals, suggested speeds, or stop signals, to connected vehicles).
As to claim 197, depending from the edge computing unit of claim 193, Kim teaches wherein said edge computing unit is configured to conduct data fusion and/or data feature extraction for traffic information (Paragraph [0054] teaches merging data and extracting frames).
As to claim 200, depending from the edge computing unit of claim 193, Kim teaches wherein said edge computing unit is configured to predict lane traffic flow parameters and/or the movement state of the CAV (Paragraph [0030] teaches predicting the intention of the detected vehicle; Tables 1 and 2 show that trajectory prediction is a computation type of the RSU).
As to claim 201, depending from the edge computing unit of claim 200, Kim teaches wherein said lane traffic flow parameters and/or the movement state of the CAV are on a microscopic and/or mesoscopic time scale (Paragraph [0030] teaches predicting the intention of the detected vehicle; Tables 1 and 2 show that trajectory prediction is a computation type of the RSU).
As to claim 202, depending from the edge computing unit of claim 193, Kim teaches wherein said edge computing unit is configured to identify, analyze, and/or predict a change of the external environment and/or a moving state of the MRIU (Paragraph [0030] teaches detecting/recognizing an ado vehicle in a region of interest in a captured image and predicting an intention of the ado vehicle in response).
Claim 188 is rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (Kim; US PG Pub #2020/0388161) in view of Tijink et al. (Tijink; US PG Pub #2021/0056839), as applied to claim 183 above, further in view of Jang et al. (Jang; US PG Pub #2017/0341660).
As to claim 188, depending from the MRIU of claim 183, Kim does not explicitly teach wherein said intelligent computing module is configured to optimize the moving speed and/or the moving path for the MRIU in real time.
In the field of autonomous vehicles, Jang teaches wherein said intelligent computing module is configured to optimize the moving speed and/or the moving path for the MRIU in real time (Paragraph [0108] teaches an autonomous vehicle deciding in real-time the optimal driving speed). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the autonomous vehicle RSU of Kim with the autonomous vehicle optimal speed determination of Jang because this allows autonomous vehicles to be driven quickly and with the highest safety standards (Paragraph [0086]) so that the vehicle interacts safely with other vehicles (Paragraph [0159]).
Claim 189 is rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (Kim; US PG Pub #2020/0388161) in view of Tijink et al. (Tijink; US PG Pub #2021/0056839), as applied to claim 183 above, further in view of Park (US PG Pub #2020/0028736).
As to claim 189, depending from the MRIU of claim 183, Kim teaches wherein said intelligent communication module is configured to provide and/or support data exchange between the MRIU and a Road Intelligent Unit (RIU), a Traffic Control Unit (TCU), a Traffic Control Center (TCC), a Traffic Operations Center (TOC), and/or a Vehicle Intelligent Unit (VIU) of a CAV (Paragraphs [0058]-[0059] teach communicating signals with nearby traffic signals and connected vehicles; Paragraphs [0061]-[0062] teach communicating with a traffic signal; Paragraph [0003] teaches communication involving road signs or traffic signals).
However, Kim does not explicitly teach providing and/or supporting low-delay, high-reliability, and/or high-density communication.
In the field of automated vehicle and highway systems, Park teaches providing and/or supporting low-delay, high-reliability, and/or high-density communication (Paragraphs [0107]-[0108] teach ultra-reliable and low latency communication). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Kim with the communication of Park because high reliability and low standby time are key requirements of remote driving (Paragraph [0310]).
Claims 198-199 are rejected under 35 U.S.C. 103 as being unpatentable over Kim et al. (Kim; US PG Pub #2020/0388161) in view of Tijink et al. (Tijink; US PG Pub #2021/0056839), as applied to claim 193 above, and further in view of Jin et al. (Jin; US PG Pub #2020/0005633).
As to claim 198, depending from the edge computing unit of claim 193, Kim does not explicitly teach wherein said edge computing unit is configured to combine mesoscopic traffic information and macroscopic traffic information.
In the field of connected automated vehicle highway systems, Jin teaches wherein said edge computing unit is configured to combine mesoscopic traffic information and macroscopic traffic information (Paragraph [0035] teaches fused RSU data including mesoscopic and macroscopic levels). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Kim with the mesoscopic and macroscopic data of Jin because this helps implement redundancy and load balancing for safety and reliability (Paragraph [0035]).
As to claim 199, depending from the edge computing unit of claim 198, Kim does not explicitly teach wherein said mesoscopic traffic information and/or macroscopic traffic information is provided by a multi-level cloud platform.
In the field of connected automated vehicle highway systems, Jin teaches wherein said mesoscopic traffic information and/or macroscopic traffic information is provided by a multi-level cloud platform (Figure 1 and Paragraph [0089] teach cloud services that support different control levels; Paragraph [0134] teaches the cloud services provide data computation, integration, and/or management at various levels). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the teaching of Kim with the multi-level data of Jin because this helps implement redundancy and load balancing for safety and reliability (Paragraph [0035]).
Response to Arguments
Applicant’s arguments with respect to claims 183 and 193 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Arena (US PG Pub #2018/0308045) teaches a monitoring device secured in an optimal location with an unobstructed view of assets to be monitored (Paragraphs [0096] and [0099]).
Khoo et al. (US PG Pub #2020/0175869) teach using vehicle in the best position to detect vehicles entering and exiting a parking structure (Paragraph [0033]).
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RYAN W SHERWIN whose telephone number is (571)270-7269. The examiner can normally be reached M-F, 7:00-8:00, 9:00-3:00 and 4:00-5:00 EST.
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, Steven Lim can be reached at 571.270.1210. 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.
/RYAN W SHERWIN/Primary Examiner, Art Unit 2688
Prosecution Insights