DETAILED ACTION
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 1-19 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.
Claims 1, 10-13, 16, and 18-19 recites the limitation "the hybrid module". There is insufficient antecedent basis for this limitation in the claim. Independent claims 1 and 13 recites a hybrid model, Examiner is reading the hybrid module to be the hybrid model. Appropriate correction is required.
The remaining claims are rejected for fully incorporating the deficiencies of the base claim(s) from which they depend.
Examiner’s Note
Examiner has performed a full and complete search on the invention in the manner best interpreted by the Examiner. Claims would be allowable once the above mentioned 112 rejection is resolved.
The closest prior arts:
Liu et al. (US 2024036006 A1) teaches A system for optimizing traffic signal timing using telemetry includes: wirelessly connected devices (WCDs), traffic operations centers (TOCs) controlling one or more traffic signals, and control modules storing and continuously executing control logic in a closed loop. The control logic continuously receives real-time WCD telemetry data and performs real-time processing of the telemetry data to match the telemetry data to physical locations. Processed telemetry data is aggregated to determine WCD trajectories. The system selectively performs time-of-day (TOD), offset, and green split optimizations, and receives the WCD trajectories and outputs of the TOD, offset, and green split optimization within an API. The system generates an optimized signal plan from data from the API, and verifies the optimized signal plan. The optimized signal plan is received by the TOCs and selectively uploaded to the traffic signals. The optimized signal plan increases throughput of traffic by decreasing total delays, and quantities of stops (Abstract).
Wanxing (CN 112863179 A) teaches a reinforced learning method supported by a deep neural network is used for realizing the self-adaptive traffic signal lamp control algorithm. In order to reflect the intersection traffic conditions as truly as possible, a single vehicle delay is defined as a fundamental element of the traffic state, and the intersection is divided into cells representing the single delay. Furthermore, to capture temporal traffic dynamics, the solution employs a series of spatial observations to enhance the representation of traffic conditions, which is introduced into a non-integer network to determine control decisions for different time intervals. The decision phase is realized by two LSTM neural networks, the Critic network predicts the expected accumulated cost, and the Actor network directly determines the optimal action in the current state. By inputting the delay state and partial historical time data of the current green light passable lane, whether the signal light is switched to the next stage according to a fixed periodic sequence is judged through a neural network. Meanwhile, because the initial parameters of the neural network are randomly given, the scheme adopts an Actor-Critic algorithm framework for optimization, so that the estimation error of the Critic network is reduced, the future cost of the Actor network is reduced, and the parameters and the feedback coefficient of the neural network are calculated (Wanxing, page 3, Background, Para. 2).
Conclusion
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/SHARMIN AKHTER/
Examiner, Art Unit 2689
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