Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
This is a non-final Office Action on the merits in response to communications filed by Applicant on January 29, 2024. Claims 1-20 are currently pending and examined below.
Priority
Receipt is acknowledged of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Information Disclosure Statement
The information disclosure statement(s) (IDS) submitted on is/are being considered by the examiner.
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 and 12 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 pre-AIA the applicant regards as the invention. The claim recites “generating first sensing capability information…” The term “capability” in claim is a relative term which renders the claim indefinite and it is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention. Furthermore, the limitation as a whole appears to be unclear to what is being generating based on “the matching results”.
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5, 8-10, 12-17, 20 are rejected under 35 U.S.C. 102(a)(1) and/or 102(a)(2) as being anticipated by Avedisov et al. US2021/0347387 (“Avedisov”).
Regarding claim(s) 1. Avedisov discloses a first roadside device comprising: a memory configured to store programming instructions (abstract, A traffic reconstruction can be generated use cooperative perception messages and other data received from a plurality of different remote sources); and at least one processor coupled to the memory and configured to execute the programming instructions to cause the apparatus to:
obtain a roadside sensing result indicating a first group of location points of a traffic participant in a preset time period ([0028] According to arrangements herein, a vehicle and/or an infrastructure device can use driving environment data received from different remote sources (e.g., vehicles, infrastructure devices, etc.) at different moments in time. The driving environment data can be sent by the remote sources in any suitable manner and/or form. For instance, the driving environment data can be sent as raw data, a subset of acquired driving environment data, and/or as part of a cooperative perception message or other type of message. The vehicle and/or an infrastructure device can also use driving environment data acquired by its own sensors.);
obtain a multi-source fusion sensing result indicating a second group of location points that is a fusion of third groups of location points that are of the traffic participant and that are from sensing devices in the preset time period (para. 26, para. 38, para. 52, Referring to FIG. 6, the traffic reconstruction module(s) 130 can, in at least some arrangements, include one or more submodules, such as a sensor fusion module 131, a reconstruction module 132, and/or a visualization module 133. The sensor fusion module 131 can receive all relevant sensory and/or wireless data from one or more elements of the traffic reconstruction system 100.);
match the roadside sensing result with the multi-source fusion sensing result to obtain matching results of target location points ( para. 123, FIG. 15 shows the information that the connected billboard 1310 has acquired about traffic on the road 1302 from its own sensors as well as from the cooperative perception messages 1340, 1345. Based on the acquired information, the connected billboard 1310 can determine that, at the first moment in time t.sub.1, traffic in region 1410 around position so is in a sparse state (e.g., vehicles are traveling at or near the speed limit on the road 1302).); and
generate first sensing capability information of the first roadside device based on the matching results, wherein the first sensing capability information indicates a first sensing capability of the first roadside device (fig. 8, para. 64-para. 65, The traffic reconstruction module(s) 130 can also take into account the map data 122, traffic rules data 124, and/or driving behavior data 126. The traffic reconstruction module(s) 130 can solve dynamic equations/simulations to satisfy all constraints (coming from sensors and CPMs) as best as possible. The more constraints/information the traffic reconstruction module(s) 130 have, the more accurate the reconstruction becomes. By applying these models and additional data, the traffic reconstruction module(s) 130 can determine the behavior (speed, position, etc.) of the vehicles 730, 731, 732 between t.sub.1 and t.sub.2.).
Regarding claim(s) 2. Avedisov discloses wherein the first sensing capability information further indicates a first region and the first sensing capability in the first region (fig. 7b and FIG. 15 shows the information that the connected billboard 1310 has acquired about traffic on the road 1302 from its own sensors as well as from the cooperative perception messages 1340, 1345. Based on the acquired information, the connected billboard 1310 can determine that, at the first moment in time t.sub.1, traffic in region 1410 around position so is in a sparse state (e.g., vehicles are traveling at or near the speed limit on the road 1302).).
Regarding claim(s) 3. Avedisov discloses wherein the first sensing capability information further indicates a first scenario, a first region, and the first sensing capability of the first roadside device in the first scenario in the first region (para. 35, In the traffic reconstruction system 100, the traffic reconstruction module(s) 130 can be configured to receive driving environment data from the connected vehicle(s) 300 and/or the infrastructure device(s) 400 at different times. In one or more arrangements, the driving environment data can be sent in a cooperative perception message (CPM) 301. The cooperative perception messages 301 can allow remote connected devices to relay their sensed information to an ego vehicle or an infrastructure device at different times.)
Regarding claim(s) 4. Avedisov discloses wherein the roadside sensing result and the multi-source fusion sensing result are based on a same scenario (para. 52, Referring to FIG. 6, the traffic reconstruction module(s) 130 can, in at least some arrangements, include one or more submodules, such as a sensor fusion module 131).
Regarding claim(s) 5. Avedisov discloses wherein the roadside sensing result comprises at least one of first time information, first location information, a first motion parameter, or first attribute information of each location point in the first group, and wherein the multi-source fusion sensing result comprises at least one of second time information, second location information, a second motion parameter, or second attribute information of each location point in the second group (FIGS. 12A-12B, the traffic reconstruction module(s) 130 can overlay the speed data and the position data associated with the first and second moments in time t.sub.1, t.sub.2. As can be seen, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold). The speed data at time stamp t.sub.2 falls within the upper limit and the lower limit of the speed data extrapolated from the first moment in time t.sub.1. Further, the position data at the second moment in time t.sub.2 falls within the upper limit and the lower limit of the position data at and extrapolated from t.sub.2. As a result, the traffic reconstruction module(s) and/or the reconstruction module(s) 132 can determine that vehicle “?” and vehicle “??” are the same vehicle/object.)
Regarding claim(s) 8. Avedisov discloses wherein the at least one processor is further configured to execute the programming instructions to cause the apparatus to update the first sensing capability information when a preset condition is met, and wherein the preset condition comprises: a current value of a sensing capability indicator indicated by the first sensing capability information is abnormal relative to a statistical value of the sensing capability indicator; a fault maintenance is performed on the first roadside device; a sensor of the first roadside device is replaced; or the first roadside device is upgraded (para. 109-113).
Regarding claim(s) 9. Avedisov discloses wherein that the current value is abnormal relative to the statistical value comprises a difference between a first sensing region and a second sensing region that correspond to a target sensing capability level is greater than a first difference threshold corresponding to the target sensing capability level, wherein the target sensing capability level is a sensing capability level for the first roadside device, wherein the first sensing region corresponds to the target sensing capability level indicated by the current value, and wherein the second sensing region corresponds to the target sensing capability level indicated by the statistical value (FIGS. 11B-11C, the traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can use the information from the cooperative perception message 945 at the second moment in time t.sub.2. Using traffic rules, dynamic models, and/or other information, the traffic reconstruction module(s) 130 can extrapolate the position and speed of the object into the future. The traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can predict the future speed(s) and positions(s) of the vehicle “??” along with upper and lower probabilistic limits. FIGS. 12A-12B, the traffic reconstruction module(s) 130 can overlay the speed data and the position data associated with the first and second moments in time t.sub.1, t.sub.2. As can be seen, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold).).
Regarding claim(s) 10. Avedisov discloses wherein the at least one processor is further configured to execute the programming instructions to cause the apparatus to generate warning prompt information based on the first sensing capability information, wherein the warning prompt information prompts a driver to take over a vehicle in a region, perform fault detection on the first roadside device, update software of the first roadside device, adjust deployment of the first roadside device, reduce confidence of information that is about the region and that is sensed by the first roadside device, or bypass the region during route planning, and wherein the first sensing capability information indicates that a second sensing capability of the first roadside device in the region is lower than a sensing threshold (FIGS. 11B-11C, the traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can use the information from the cooperative perception message 945 at the second moment in time t.sub.2. Using traffic rules, dynamic models, and/or other information, the traffic reconstruction module(s) 130 can extrapolate the position and speed of the object into the future. The traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can predict the future speed(s) and positions(s) of the vehicle “??” along with upper and lower probabilistic limits. FIGS. 12A-12B, the traffic reconstruction module(s) 130 can overlay the speed data and the position data associated with the first and second moments in time t.sub.1, t.sub.2. As can be seen, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold).).
Regarding claim(s) 12. Avedisov discloses an apparatus comprising: a memory configured to store programming instructions; and at least one processor coupled to the memory and configured to execute the programming instructions to cause the apparatus to (abstract, A traffic reconstruction can be generated use cooperative perception messages and other data received from a plurality of different remote sources,):
obtain sensing capability information indicating a region and a first sensing capability of a roadside device in the region; and based on the sensing capability information (para. 123, FIG. 15 shows the information that the connected billboard 1310 has acquired about traffic on the road 1302 from its own sensors as well as from the cooperative perception messages 1340, 1345. Based on the acquired information, the connected billboard 1310 can determine that, at the first moment in time t.sub.1, traffic in region 1410 around position so is in a sparse state (e.g., vehicles are traveling at or near the speed limit on the road 1302). Further, the connected billboard 1310 can determine that traffic in region 1420 around position Si is jammed (e.g., vehicles are at a standstill, traveling at a substantially lower speed that the vehicles in region 1420, etc.). Based on the acquired information, the connected billboard 1310 can determine that, at the second moment in time t.sub.2, traffic in region 1410′ around position so is jammed. Region 1410′ can be substantially the same as region 1410. Further, the connected billboard 1310 can determine that traffic in region 1430 at position 52 is not jammed.):
generate warning prompt information; adjust a confidence of information that is about the region and that is from the roadside device; or plan a driving route bypassing the region (para. 84, The ego vehicle 200 can include one or more alert modules 285. The alert module(s) 285 can cause an alert, message, warning, and/or notification to be presented within the ego vehicle 200. The alert module(s) 285 can cause any suitable type of alert, message, warning, and/or notification to be presented, including, for example, visual, audial, and/or haptic alert, just to name a few possibilities.).
Regarding claim(s) 13. Avedisov discloses wherein the sensing capability information further indicates a scenario and the first sensing capability in the scenario in the region (para. 123, Region 1410′ can be substantially the same as region 1410. Further, the connected billboard 1310 can determine that traffic in region 1430 at position 52 is not jammed.).
Regarding claim(s) 14. Avedisov discloses wherein the apparatus is disposed in an in-vehicle device, and wherein the at least one processor is further configured to execute the programming instructions to cause the apparatus to: determine that the first sensing capability is lower than a sensing threshold; and prompt a driver to take over a vehicle in the region (FIGS. 12A-12B, the traffic reconstruction module(s) 130 can overlay the speed data and the position data associated with the first and second moments in time t.sub.1, t.sub.2. As can be seen, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold).).
Regarding claim(s) 15. Avedisov discloses wherein the apparatus is disposed in an in-vehicle device, and wherein the at least one processor is further configured to execute the programming instructions to cause the apparatus to: determine that the second sensing capability is lower than a sensing threshold; and plan the driving route (para. 108-113, Using traffic rules, dynamic models, and/or other information, the traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can extrapolate the position and speed of the object within probabilistic bounds, including at time t.sub.2 and possibly beyond. The traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can predict the future speed(s) and positions(s) of the vehicle “?” along with upper and lower probabilistic limits.).
Regarding claim(s) 16. Avedisov discloses wherein the apparatus is disposed in a mobile terminal, and wherein the at least one processor is further configured to execute the programming instructions to cause the apparatus to: determine that the second sensing capability is lower than a sensing threshold; and prompt a user of the mobile terminal to avoid a vehicle in the region (para. 110, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold). The speed data at time stamp t.sub.2 falls within the upper limit and the lower limit of the speed data extrapolated from the first moment in time t.sub.1. Further, the position data at the second moment in time t.sub.2 falls within the upper limit and the lower limit of the position data at and extrapolated from t.sub.2. As a result, the traffic reconstruction module(s) and/or the reconstruction module(s) 132 can determine that vehicle “?” and vehicle “??” are the same vehicle/object.).
Regarding claim(s) 17. Avedisov discloses wherein the apparatus is disposed in a management device of the roadside device, and wherein the at least one processor is further configured to execute the programming instructions to cause the apparatus to: determine that the second sensing capability is lower than a sensing threshold (FIGS. 12A-12B, the traffic reconstruction module(s) 130 can overlay the speed data and the position data associated with the first and second moments in time t.sub.1, t.sub.2. As can be seen, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold).); and prompt an administrator to perform a fault detection on the roadside device, update software of the roadside device, or adjust deployment of the roadside device (para. 63, Using the example of FIG. 7A, the ego vehicle 710 may receive cooperative perception messages from the connected vehicles 721 and the connected vehicle 723. In such case, the ego vehicle 710 may request information from other connected vehicles in the driving environment 700. For example, if the vehicle 722 is a connected vehicle, then the ego vehicle 710 can request information from the vehicle 722. In some arrangements, the ego vehicle 710 may ignore, filter, delete, or assign a low priority to information received that is not accurate (e.g., high error) and/or is not within a desired distance from the ego vehicle 710 or not at a desired location.).
Regarding claim(s) 20. Avedisov discloses wherein the warning prompt information prompts a driver to take over a vehicle in the region, avoid the vehicle in the region, perform fault detection on the roadside device, reduce the confidence of information, or bypass the region during route planning, and wherein the sensing capability information indicates that the first sensing capability is lower than a sensing threshold (FIGS. 11B-11C, the traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can use the information from the cooperative perception message 945 at the second moment in time t.sub.2. Using traffic rules, dynamic models, and/or other information, the traffic reconstruction module(s) 130 can extrapolate the position and speed of the object into the future. The traffic reconstruction module(s) 130 and/or the reconstruction module(s) 132 can predict the future speed(s) and positions(s) of the vehicle “??” along with upper and lower probabilistic limits. FIGS. 12A-12B, the traffic reconstruction module(s) 130 can overlay the speed data and the position data associated with the first and second moments in time t.sub.1, t.sub.2. As can be seen, there is a significant overlap between the two solutions in this instance (e.g., an amount of overlap above a predetermined threshold).)
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.
Claim(s) 6-7, 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Avedisov discloses et al. US2021/0347387 (“Avedisov”) in view of Graefe et al. US2019/0222652 (“Graefe”).
Regarding claim(s) 6, 7, 18, 19. Avedisov does not explicitly discloses wherein the second sensing capability information comprises the first sensing capability information; and generate sensing coverage hole information based on the second sensing capability information, wherein the sensing coverage hole information indicates a region out of coverage of one or more of the second roadside devices.
Graefe teaches another vehicle to infrastructure communication system and mehod that generate sensing coverage hole information based on the second sensing capability information, wherein the sensing coverage hole information indicates a region out of coverage of one or more of the second roadside devices (para. 16, para. 68, para. 78, The infrastructure equipment (or remote system) tracks objects (e.g., vehicles, pedestrians, etc.) in the coverage area. The infrastructure equipment (or remote system) determines regions in the coverage area that are not adequately covered by the sensor array (e.g., “coverage holes” or “occlusions”), for example, by identifying gaps in currently available sensor data (e.g., “perception gaps”), sensor failures, detecting events that are occurring (or not occurring) in the coverage area, or the like. When the infrastructure equipment (or remote system) identifies a perception gap, then the infrastructure equipment (or remote system) will initiate the second operation mode to reconfigure the orientation of sensing elements of the sensors to account for or eliminate the perception gap (i.e., “filling the perception gap”). In the second operation mode, the infrastructure equipment (or remote system) detects a trigger event; determines a new sensor arrangement based on a previous or current sensor arrangement, sensor data obtained from the individual sensors, and sensor parameters or capabilities of the individual sensors in the sensor array).
Thus, it would have been obvious to one of ordinary skills in the art before the effective filing date of the claimed invention to modify the system and method of Avedisov by incorporating the applied teaching of Graefe to improve vehicle to infrastructure communication and vehicle tracking.
Allowable Subject Matter
Claims11 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRUC M DO whose telephone number is (571)270-5962. The examiner can normally be reached on 9AM-6PM.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ramón Mercado, Ph.D. can be reached on (571) 270-5744. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TRUC M DO/Primary Examiner, Art Unit 3658