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 Claims
This is in response to Applicant’s case, no. 18/457,429, with an effective filing date of 8/29/2023. Claims 1-15 are currently pending.
Response to Arguments
Regarding the rejection of claims 1-14 under 35 USC § 102 as being anticipated by Sivanesan et al. (US 20230138163 A1) [hereinafter referred to as Sivanesan], and the rejection of claim 15 under 35 USC § 103 as being unpatentable over Sivanesan in view of Lee et al. (US Pat. Pub. No. 2017/0064580 A1) [hereinafter referred to as Lee], the Applicant has elected to amend claims 1, 3, 7, 8-10 and 15. However, due to the significant amendments made by the Applicant to the claims, new references Oboril et al. (US Pat. Pub. No. 2020/0092987 A1) [hereinafter referred to as Oboril], Ferreira et al. (US Pat. Pub. No. 2020/0284883 A1) [hereinafter referred to as Ferreira], and Chae et al. (US Pat. Pub. No. 2020/0351827 A1) [hereinafter referred to as Chae] have been necessitated which upon closer examination fully replaces Lee . As such, Lee is no longer required to address any limitation of the claims and new rejections of claims 1-6, 7-14 and 15, respectively, under 35 USC § 103 are made as detailed below.
Regarding claim 1, the Applicant argues, see pp. 6-8, that Sivanesan does not disclose the limitations determining whether the safety relevance value of each of the one or more sensor detected road users corresponds to safety relevant or not safety relevant; and responsive to determining that the safety relevance value of at least one of the one or more sensor detected road users corresponds not safety relevant, adjusting Dynamic Congestion Control (DCC) triggering condition parameters. However, Oboril in [0108-109] teaches a determiner which calculates a safety cost value by assessing the risk of a maneuver based on factors like distance, size, type, and behavior of surrounding road users. Further, it can aggregate these risks for multiple users, potentially normalizing them between 0 and 1, to derive an overall safety parameter (e.g., 1-R) using predefined functions, machine learning, or collision risk approaches. This safety parameter is construed as a safety relevance value for each of the detected road users. Further, in [0116] Oboril teaches the determiner determines an action of the ego-vehicle based on estimated cost values associated with safety. Therefore, this argument is moot.
Regarding claim 7, the Applicant argues that Sivanesan does not disclose the limitations of movement similarity value and the determining whether the first movement similarity value corresponds to similar moment to the self-vehicle or not similar movement to the self-vehicle; and determining whether the second movement similarity value corresponds to similar moment to the sensor detected road user or not similar movement to the sensor detected road user. However, Ferreira teaches in [0039] In some embodiments, the LIDAR Sensor System and/or LIDAR Sensor Device comprises a sensor for vehicle movement, position and orientation. Such sensor data may allow a better prediction, as to whether the vehicle steering conditions and methods are sufficient. Furthermore, in [3618] LIDAR signal feature set may include a vector including an ordered sequence of similarity score values which is construed as movement similarity values regarding other vehicles and objects of interest. Therefore, this argument is moot.
Regarding claim 15, the Applicant argues, see pp. 8-9, that Sivanesan, as modified by Lee, does not disclose the limitations of channel load metric representing a measured wireless communication channel utilization. However, Chae teaches in [0320] s. 1-4, where in V2X communication, one challenge may be to avoid collisions and guarantee a minimum communication quality even in dense UE scenarios. Wireless congestion control may represent a family of mechanisms to mitigate such collisions by adjusting one or more communication parameters to control the congestion level on the vehicular wireless channel and guarantee reliable V2X communications. In existing technologies, a wireless device may measure the channel busy and channel occupancy ratio metrics to characterize the channel state and allow the wireless device to take necessary actions. Therefore, this argument is moot.
Applicant argues the dependent claims are patentable by virtue of their dependency.
This argument is unpersuasive as each independent claim has been fully rejected for the reasons as given above.
Claim Objections
Claims 8 and 10 are objected to because of the following informalities:
8 line 2 and claim 10 line 2 contain a typographical error where first movement similarity should be corrected to first movement similarity value; and
8 line 4 and claim 10 line 5 contain a typographical error where second movement similarity should be corrected to second movement similarity value.
Appropriate correction is required.
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:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1-6 are rejected under 35 U.S.C. 103 as being unpatentable over Sivanesan et al. (US Pat. Pub. No. 2023/0138163 A1), hereinafter referred to as Sivanesan, in view of Oboril et al. (US Pat. Pub. No. 2020/0092987 A1) hereinafter referred to as Oboril.
Regarding claim 1, Sivanesan discloses:
A method, comprising: in a vehicle-to-everything (V2X) environment and by a self-vehicle:
calculating, using an onboard processor in the self-vehicle ([0156] driving control unit (DCU) comprise controller or processing device on-board the vehicle and [0002] sentence (s.) 1, computer-assisted or autonomous vehicles which are self-vehicles that carry an on-board processor), a safety relevance value of each of one or more a sensor detected road users ([0002] use and knowledge of V2X technologies as understood by one of ordinary skill in the art, [0018] a V2V (vehicle-to-vehicle) and V2I (vehicle-to-infrastructure) connectivity used to warn drivers or AV (autonomous vehicles) about dangerous situations, which is necessarily a safety relevant event, and onboard sensors provide required measurements, [0020] where safety metrics are calculated including safety distance factors and modified times to collision that are included within event type values that trigger messages, ([0064-65] each safety metric, which is calculated on variable factors and thereby adjustable, incorporates a threshold for triggering a decentralized environment notification message (DENM), [0065] where triggering these messages are adjustable based on safety metrics such as speed, distance and heading, and [0086-88] relevance criteria (e.g., values) that are calculated or set based on event type and location as perceived via the use of sensors);
but Sivanesan does not explicitly disclose:
determining whether the safety relevance value of each of the one or more sensor detected road users corresponds to safety relevant or not safety relevant; and
responsive to determining that the safety relevance value of at least one of the one or more sensor detected road users corresponds not safety relevant, adjusting Dynamic Congestion Control (DCC) triggering condition parameters.
However, Oboril in [0108-109] teaches a determiner which calculates a safety cost value by assessing the risk of a maneuver based on factors like distance, size, type, and behavior of surrounding road users. Further, it can aggregate these risks for multiple users, potentially normalizing them between 0 and 1, to derive an overall safety parameter (e.g., 1-R) using predefined functions, machine learning, or collision risk approaches. This safety parameter is construed as a safety relevance value for each of the detected road users. Further in [0116] Oboril teaches the determiner determines an action of the ego-vehicle based on estimated cost values associated with safety.
Therefore it would have been obvious to one of ordinary skill in the art of vehicle controls before the effective filing date of the current invention to modify the V2X communication system and method of Sivanesan, by incorporating the safety relevance value teachings of Oboril, such that the combination would provide for the predictable result of improving vehicle safety within a traffic environment.
Regarding claim 2, Sivanesan, as modified by Oboril, discloses:
The method of claim 1, wherein the calculating the safety relevance value of a sensor detected road user includes categorizing V2X detected road users by respective directions of arrival relative to the self-vehicle ([0020] where safety metrics are calculated including safety distance factors and modified times to collision that are included within event type values that trigger messages, [0032] direction of travel of other vehicle is accounted for, and [0086-88] relevance criteria (e.g., values) that are calculated or set based on event type and location as perceived via the use of sensors) and
checking an arrival time of each sensor detected road user in each category ([0020] modifiable collision times are accounted for as seen above and [0022] encroachment time is accounted for).
Regarding claim 3, Sivanesan, as modified by Oboril, discloses:
The method of claim 1, wherein the adjusting the DCC triggering condition parameters includes (see claim 1), by the self-vehicle, increasing from a previously transmitted value a respective value of a parameter selected from the group consisting of a minimal distance travelled, a minimal speed change, a minimal heading change, and a combination thereof ([0022-23] estimating and tracking kinematic parameters (i.e., location, distance travelled, speed, heading) and calculating safety metrics accordingly which would include necessarily increasing and decreasing a previously transmitted value).
Regarding claim 4, Sivanesan, as modified by Oboril, discloses:
The method of claim 1, further comprising using the adjusted DCC triggering condition parameters to control transmission of both V2X Day 1 and V2X Day 2 information on a single channel ([0133] where DEN services, such as messaging, can operate on an already used channel (formerly control channel), which is understood as transmitting control transmissions of connected vehicles (Day 1, as described in line33-34 of pp.1 of Applicant’s Specification,) and sensor data for unconnected vehicles (Day 2)).
Claims 5-6 recite a method having substantially the same features of claim 4 above, therefore claims 5-6 are rejected for the same reasons as claim 4.
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Claims 7-14 are rejected under 35 U.S.C. 103 as being unpatentable over Sivanesan et al. (US Pat. Pub. No. 2023/0138163 A1), hereinafter referred to as Sivanesan, in view of Oboril et al. (US Pat. Pub. No. 2020/0092987 A1) hereinafter referred to as Oboril, and Ferreira et al. (US Pat. Pub. No. 2020/0284883 A1) hereinafter referred to as Ferreira.
Regarding claim 7, Sivanesan, as modified by Oboril, discloses:
A method, comprising: in a vehicle-to-everything (V2X) environment and by a self-vehicle:
calculating a first movement similarity between the self-vehicle and a road user ahead or behind the self-vehicle ([0286-287] the local perception and trajectory/motion prediction function detects and characterize objects (static and mobile) which are likely to cross the trajectory of the considered moving objects, which is construed as objects moving to a similar point including locally associated objects and selected vehicles), and
a second movement similarity between a sensor detected road user and a road user ahead or behind the sensor detected road user ([0286-287] as discussed above),
wherein each movement similarity is computed based on one or more measured parameters including relative speed ( [0284-5] identifying and classifying objects and comparing to image data and/or existing models for the object and use of various sensor types to obtain information of objects and the environment in a data fusion technique and [0330] speed of a feature (e.g., object of interest)), relative distance (see [0284-5] as discussed above, [0330] relative distance of a feature, and [0342] comparison of lateral distance), or lane alignment obtained from vehicle sensors (See [0284-5] as discussed above, [0043] s.2, detecting designated lane markings, and [0126] indicate the corresponding lane position of the event position);
determining whether the first movement similarity corresponds to similar moment to the self-vehicle or not similar movement to the self-vehicle ([0286-287] as discussed above trajectory/motion prediction function detects and characterize objects (static and mobile) which are likely to cross the trajectory of the considered moving objects);
determining whether the second movement similarity corresponds to similar moment to the sensor detected road user or not similar movement to the sensor detected road user ([0286-287] as discussed above trajectory/motion prediction function detects and characterize objects (static and mobile) which are likely to cross the trajectory of the considered moving objects); and
responsive to determining that the first movement similarity, the second movement similarity value, or both corresponds to similar movement, adjusting Dynamic Congestion Control (DCC) triggering condition parameters (see claim 1 and [0064-65] each safety metric, which is calculated on variable factors and thereby adjustable, incorporates a threshold for triggering a decentralized environment notification message (DENM) and [0065] where triggering these messages are adjustable based on safety metrics such as speed, distance and heading), including modifying at least one numerical threshold for message transmission as a function of the computed similarity values ([0327] s. 2-4, each connection may be assigned a weight that represents its relative importance, these are adjusted as learning proceeds and increases or decreases the strength of the signal at a connection, which is construed by the Examiner as modifying a numerical threshold for message transmission based on the assessment of the safety relevance, which is necessarily a non-binary assessment as relative importance would be better represented by percentages which correlates to the necessary weight over a binary pass/fail assessment).
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However, Sivanesan, as modified by Oboril, does not explicitly disclose:
movement similarity is a movement similarity value.
However, Ferreira teaches in [0039] In some embodiments, the LIDAR Sensor System and/or LIDAR Sensor Device comprises a sensor for vehicle movement, position and orientation. Such sensor data may allow a better prediction, as to whether the vehicle steering conditions and methods are sufficient. Furthermore, in [3618] LIDAR signal feature set may include a vector including an ordered sequence of similarity score values which is construed as movement similarity values regarding other vehicles and objects of interest.
Therefore it would have been obvious to one of ordinary skill in the art of vehicle controls before the effective filing date of the current invention to modify the V2X communication system and method of Sivanesan, as already modified by the safety relevance value teachings of Oboril, by incorporating the movement similarity value teachings of Ferreira, such that the combination would provide for the predictable result of, as acknowledged by Ferreira in [0039], where such sensor data may allow a better prediction, as to whether the vehicle steering conditions and methods are sufficient.
Regarding claim 8, Sivanesan, as modified by Oboril and Ferreira, discloses:
The method of claim 7, wherein the calculating the first movement similarity includes matching a parameter selected from a group consisting of distance, speed and heading between the self-vehicle and the respective road user ahead or behind the self-vehicle (see claims 1, 3, and 7 and Fig. 4, all above), and
wherein the calculating the second movement similarity includes matching a parameter selected from a group consisting of distance, speed and heading between the sensor detected road user and the respective road user ahead or behind(see claims 1, 3, and 7 and Fig. 4, all above).
Claim 9 recites a method having substantially the same features of claim 3 above, therefore claim 9 is rejected for the same reasons as claim 3.
Regarding claim 10, Sivanesan, as modified by Oboril and Ferreira, discloses:
The method of claim 7, wherein the calculating the first movement similarity between the self- vehicle and the road user ahead or behind the self-vehicle includes checking if the self-vehicle and the road user ahead or behind the self-vehicle are distanced by more than a given time value when fast or distanced less than a given distance value when slow ([0020] where safety metrics are calculated including safety distance factors and modified times to collision that are included within event type values that trigger messages, [0022-23] estimating and tracking kinematic parameters (i.e., location, distance travelled, speed, heading) and calculating safety metrics accordingly which would include necessarily increasing and decreasing a previously transmitted value, [0032] direction of travel of other vehicle is accounted for, [0064-65] each safety metric, which is calculated on variable factors and thereby adjustable, incorporates a threshold for triggering a decentralized environment notification message (DENM) and [0065] where triggering these messages are adjustable based on safety metrics such as speed, distance and heading, [0086-88] relevance criteria (e.g., values) that are calculated or set based on event type and location as perceived via the use of sensors, and [0286-287] the local perception and trajectory/motion prediction function detects and characterize objects (static and mobile) which are likely to cross the trajectory of the considered moving objects, which is interpreted as moving to a similar point and is not limited to solely the road user ahead of the self-vehicle but all locally associated objects and selected vehicles), and
wherein the calculating the second movement similarity between the sensor detected road user and the road user ahead or behind the sensor detected road user includes checking if the sensor detected road user and the road user ahead or behind are distanced by more than a given time value when fast or distanced less than a given distance value when slow (see above).
Claims 11-14 recite a method having substantially the same features of claim 4 above, therefore claims 11-14 are rejected for the same reasons as claim 4.
___________________________________________
Claim 15 is rejected under 35 U.S.C. 103 as being unpatentable over Sivanesan et al. (US Pat. Pub. No. 2023/0138163 A1), hereinafter referred to as Sivanesan, in view of Oboril et al. (US Pat. Pub. No. 2020/0092987 A1), hereinafter referred to as Oboril, Ferreira et al. (US Pat. Pub. No. 2020/0284883 A1), hereinafter referred to as Ferreira, and Chae et al. (US Pat. Pub. No. 2020/0351827 A1), hereinafter referred to as Chae.
Regarding claim 15, Sivanesan, as modified by Oboril and Ferreira, discloses:
In a vehicle-to-everything (V2X) environment, a system installed in a self-vehicle and comprising: a V2X Day 1 communication module for transmitting and receiving Day 1 messages that include data of the self-vehicle (see claim 1, claim 4, and [0291] systems are communicably coupled in various different units and levels);
a V2X Day 2 communication module for transmitting and receiving Day 2 sensor sharing messages that include data of sensor detected road users ( see claim 1, claim 4, and [0291] as seen above);
a first database for storing data of V2X detected road users ([0291] each information level of communication has is collected, processed and stored related to its functional and data distribution scenario, which is construed by the Examiner as a database for storing data based on its functionality, (e.g., V2X data or sensory));
a second database a first database for storing data of the sensor detected road users ([0291] as seen directly above);
a safety relevance and/or movement similarity calculation module for determining road user safety relevance and/or movement similarity by comparing parameters derived from vehicle sensor inputs including at least relative distance, speed, or lane alignment (see claim 1 and claim 7 and [0287] use of modules for safety relevance or motion detecting and tracking); and
a Dynamic Congestion Control (DCC) module for modifying message transmission thresholds based on the safety relevance and/or movement similarity (see claim 1, claim 7, and [0019] decentralized environmental notification basic service which focuses on detecting and alerting road users of detected events and [0020] where safety relevant events and metrics are accounted for) and on channel load ([0057] hardware performance measurements and/or metrics, such as power consumption, processor performance, memory and/or storage utilization and/or free space, component load, battery state such as available power, and/or thermal data; OS and/or application parameters and requirements such as computational needs, input/output characteristics, and volume of exchanged data (e.g., upload or download); overload conditions experienced, which is interpreted by the Examiner as the system accounting for the amount of data passed through the channel and prioritizing),
but Sivanesan, as modified by Oboril and Ferreira, does not explicitly disclose:
channel load metric representing a measured wireless communication channel utilization.
However, Chae teaches in [0320] s. 1-4, where in V2X communication, one challenge may be to avoid collisions and guarantee a minimum communication quality even in dense UE scenarios. Wireless congestion control may represent a family of mechanisms to mitigate such collisions by adjusting one or more communication parameters to control the congestion level on the vehicular wireless channel and guarantee reliable V2X communications. In existing technologies, a wireless device may measure the following two metrics to characterize the channel state and allow the wireless device to take necessary actions. The first metric may be a channel busy radio (CBR), which may be defined as the portion (or number) of subchannels in a resource pool with measured RSSIs exceeding a pre-configured threshold. The second metric may be a channel occupancy ratio (CR). The CR may be calculated at subframe n and may be defined as the total number of subchannels used for sidelink transmissions.
Therefore it would have been obvious to one of ordinary skill in the art of vehicle controls before the effective filing date of the current invention to modify the V2X communication system and method of Sivanesan, as already modified by the safety relevance value teachings of Oboril and the movement similarity value teachings of Ferreira, by incorporating the traffic utilization teachings of Chae, such that the combination would provide for the predictable result of improving usage and control of a shared medium used in communications and mitigate communication congestion issues.
Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Please see:
Lee et al. (US Pat. Pub. No. 2017/0064580 A1) is directed towards a method and system for packet collision avoidance in a wireless communication system.
Conclusion
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to KEITH ALLEN VON VOLKENBURG whose telephone number is (703)756-5886. The Examiner can normally be reached Monday-Friday 8:30 am-5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin D. Bishop can be reached at (571) 270-3713. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Keith A von Volkenburg/Examiner, Art Unit 3665
/Erin D Bishop/Supervisory Patent Examiner, Art Unit 3665