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 the Claims
This Office Action is in response to the claims filed on November 25, 2025.
Claims 1-20 have been presented for examination.
Claims 1-20 are currently rejected.
Claims 1-6, 8, 10-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bai et al. (U.S. Patent Publication Number 2025/0033640) in view of Orendovici et al. (U.S. Patent Publication Number 2025/0198797).
Claims 7, 9, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Bai et al. (U.S. Patent Publication Number 2025/0033640) in view of Orendovici et al. (U.S. Patent Publication Number 2025/0198797), further in view of Fowe (U.S. Patent Publication Number 2020/0025584).
Response to Argument
35 U.S.C. 101
Applicant’s arguments, see Applicant Remarks, filed on November 25, 2025, with respect to 35 U.S.C. 101 have been fully considered and are persuasive. The 35 U.S.C. 101 rejection has been withdrawn.
35 U.S.C. 103
Applicant's arguments filed November 25, 2025 have been fully considered but they are not persuasive.
The Applicant argues that Bai in combination with Orendovici does not teach the limitation “update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link.” Specifically, the Applicant appears to describe the disclosure of Orendovici and concludes that Orendovici does not describe lane level traffic jam information, and that therefore, such road/map information updates disclosed by Orendovici is not reasonably equivalent to an update to the claimed lane-level traffic jam distribution among different lanes (Applicant Remarks pages 9-10).
The Examiner has considered the arguments presented and respectfully disagrees. First, the words of the claim must be given their plain meaning under the broadest reasonable interpretation (MPEP 2111.01(I)) and it is further improper to import claim limitations from the specification (MPEP 2111.01(II)). A “lane-level” traffic jam distribution, under the broadest reasonable interpretation, refers to the traffic distribution within the current driving lane of the vehicle, see “Lane-level Positioning based on 3D Tracking Path of Traffic Signs.” Orendovici expressly discloses detecting vehicles entering or leaving the vehicle’s 2100 lane (Orendovici ¶ 255), and using the information in cooperative adaptive cruise control (CACC) to receive information about the immediately preceding vehicles (e.g., vehicles immediately ahead of and in the same lane as the vehicle 2100) (Orendovici ¶ 269). Therefore, Orendovici does teach and suggest lane-level traffic jam distribution information.
Further, the Applicant argues that Orendovici does not describe “the lane-level traffic jam distribution among different lanes as in amended claims 1 and 12” (Applicant Remarks page 10). However, the claims fail to recite or describe “different lanes,” nor do the claims describe the lane-level traffic jam to be “among different lanes.” Therefore, under the broadest reasonable interpretation, the lane-level traffic jam distribution may merely refer to the distribution of traffic within a singular lane. For these reasons, Orendovici taken alone or in combination with Bai teaches and suggests “update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link.”
Second, one cannot show nonobviousness by attacking the references individually where the rejection is based on a combination of references. In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., Inc., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986). See MPEP 2145. The Applicant appears to discuss how Orendovici does not describe lane level traffic jam information. The Examiner has considered the arguments presented and respectfully disagrees. Orendovici was relied on to supplement the teachings of Bai in combining the lane-level traffic information of Bai with updating the traffic information; therefore, Orendovici is provided in combination with Bai to teach “update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link.” Bai expressly discloses “providing individualized lane guidance to road users based on detected traffic distribution of lanes on a road to maximize traffic flow through a congested area” (Bai in at least ¶ 21). Even so, Orendovici, taken alone, expressly discloses detecting vehicles entering or leaving the vehicle’s lane, and using the information in cooperative adaptive cruise control (CACC) to receive information about the immediately preceding vehicles, as discussed above. Therefore, Bai in combination with Orendovici teaches and suggests “update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link.”
Third, the Applicant appears to describe the disclosure of Orendovici and conclude that Orendovici does not teach “update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link” without explaining a connection or producing contrary evidence establishing that the reference being relied on would not enable a skilled artisan to produce the recited limitations (MPEP 2145). For example, the Applicant does not explain why the traffic occurring in the lanes of Orendovici could not be analogous to the lane level traffic distribution as claimed.
Even if further explanation was provided, Bai in combination with Orendovici expressly discloses lane-level traffic jam information (see at least Bai in ¶ 21 “providing individualized lane guidance to road users based on detected traffic distribution of lanes on a road to maximize traffic flow through a congested area”), and updating the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link (see at least Orendovici in at least ¶¶ 255 and 259). Therefore, Bai in combination with Orendovici teach and suggest the elements of amended claim 1.
Regarding claims 3-6 and 13-16, the Applicant argues that Bai does not include using a “distribution of multiple vehicles in each section to determine any vehicle distribution in any neighboring section,” and does not teach determining a traffic jam probability in one lane of these segments based on any neighbor segments (Applicant Remarks page 11).
The Examiner has considered the arguments presented and respectfully disagrees. It is improper to import claim limitations from the specification (MPEP 2111.01(II)). As written, the claims fail to recite “neighboring sections” or “neighbor segments.” The claims further fail to recite a distribution of “multiple vehicles in each section,” and using such distribution to determine a vehicle distribution in a neighboring section. Rather, the claims merely recite a “traffic jam section” and road links. Therefore, these elements argued by the Applicant are not required by the claim. Even so, dependent claims 2-11 and 13-20 are supported by the rationale provided above. Thus, the Applicant’s arguments are not persuasive.
Thus, the Examiner maintains the prior art rejection. Additional citations and explanation from within the prior art of record are provided for further clarification.
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 1-6, 8, 10-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Bai et al. (U.S. Patent Publication Number 2025/0033640) in view of Orendovici et al. (U.S. Patent Publication Number 2025/0198797).
Regarding claim 1, Bai discloses a system comprising:
one or more processors (Bai ¶ 41 “a processor”) programmed to: obtain a first road link, a second road link connected to the first road link, and a third road link connected to the first road link based on a map; (Bai ¶ 47 discloses receiving “lane-level participation” including “a first or A segment 84, a second or B segment 86, a third or C segment 88”)
identify a traffic jam section in the first road link based on driving data of vehicles; (Bai ¶ 47 discloses that “lane-level congestion status may be provided for use by the operator of host vehicle 14,” such that each lane may be divisible into segments including a “first or A segment 84”)
generate an initial lane-level traffic jam distribution in the first road link; (Bai ¶ 49 discloses “the first or a segment 84 of the first lane 76 may be presented as a lane segment 102 having a first color or line width indicating a non-congested condition [i.e., an initial lane-level traffic jam distribution]”)
Bai does not expressly disclose:
update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link;
transmit the lane-level traffic jam distribution to vehicles approaching the traffic jam section; and
autonomously drive the vehicle based on the lane-level traffic jam.
However, Orendovici discloses:
update the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link; (Orendovici ¶ 44 discloses that “when causing a portion of the map to be updated, the system(s) may further cause one or more neighboring portions (e.g., neighboring portions that surround the portion) to also be updated.” For example, “when the selection component 124 determines to update more than one portion, the selection component 124 may further store update data 128 indicating an order for performing the updates [i.e., updating an initial traffic jam distribution in a first road link].” Also see ¶ 53 disclosing “an order associated with the updates to the portions of the map” and ¶ 55 “if a road stretches from the updated portion to a related portion, then the system(s) may cause the related portion to also be updated in order,” wherein a controller provides outputs on a display 2134 which includes a “location of other vehicles (e.g., an occupancy grid) [i.e., traffic jam distribution],” see ¶ 189, and updating the occupancy grid, see ¶ 199, wherein the field-of-view includes “vehicles entering or leaving the vehicle’s 2100 lane” [i.e., lane-level traffic]. One having ordinary skill in the art would recognize that vehicles entering or leaving the lane of the vehicle is a lane-level traffic jam distribution, see “Lane-level Positioning based on 3D Tracking Path of Traffic Signs.” One having ordinary skill in the art would further recognize that a distribution “traffic jam” is merely a distribution and may constitute any amount of traffic.)
transmit the lane-level traffic jam distribution to vehicles approaching the traffic jam section; and (Orendovici ¶ 285 discloses transmitting, over the network(s) 2190, map information 2194, including traffic and road conditions and updates to the map information, to the vehicles)
autonomously drive the vehicle based on the lane-level traffic jam. (Orendovici ¶ 187 discloses “The controller(s) 2136 may include one or more onboard (e.g., integrated) computing devices (e.g., supercomputers) that process sensor signals, and output operation commands (e.g., signals representing commands) to enable autonomous driving,” also see the steering system disclosed in ¶ 185)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the lane-level traffic information of Bai with updating the initial lane-level traffic jam distribution in the first road link based on traffic jam information on the second road link and the third road link and transmitting the lane-level traffic jam distribution to vehicles approaching the traffic jam section, and autonomously driving the vehicle based on the lane-level traffic jam, with reasonable expectation of success, to ensure that a connection of the road between the portions of the map is accurate (Orendovici ¶ 55), and to improve traffic flow smoothness and reduce congestion on the road (Orendovici ¶ 269), rendering the modification to be obvious.
Regarding claim 2, Bai in combination with Orendovici discloses the system of claim 1, wherein:
the first road link includes a plurality of lanes; (Bai in at least Fig. 5 and corresponding ¶ 53)
the initial lane-level traffic jam distribution includes a probability of traffic jam in each of the plurality of lanes; and (Bai ¶ 10 discloses “assigning a different weight to different ones of the multiple lane route options based on an available traffic volume; and randomizing assignment of a probability to an individual one of the multiple vehicles and one of the multiple lane route options”)
updating the initial lane-level traffic jam distribution includes updating the probability of traffic jam in each of the plurality of lanes. (Bai ¶ 44 discloses “A first function of the evaluation and selection module 38 defines a route evaluation 40 wherein a route choice based on detected traffic is updated,” wherein the route is assigned based on “a probability,” see ¶ 61)
Regarding claim 3, Bai in combination with Orendovici discloses the system of claim 2, wherein:
the one or more processors (Bai ¶ 41 “a processor”) are further programmed to: determine that the second road link does not include a traffic jam (Bai ¶ 49 discloses “the second or B segment 86 of the first lane 76 may be presented as a lane segment 104 having a second color or line width indicating an increased congestion condition”) and the third road link includes a traffic jam; and (Bai ¶ 49 discloses “the fourth or D segment 90 of the first lane 76 may be presented as a lane segment 108 having a third color or line width indicating a congested condition,” such that one having ordinary skill in the art would recognize that the fourth segment is in sequence with a first and second segment and may be a third segment of the lane.)
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the second road link does not include a traffic jam and the third road link includes a traffic jam. (Bai ¶ 8 discloses “performing a lane level load balancing to mitigate against the non-congested lane” which includes “assigning a probability to individual [lane route options] of the multiple lane route options,” the probability thereby having been calculated. Also see the “lane selection strategy” depicted in Fig. 1 and Fig. 5., wherein Fig. 5 further depicts “lane level congestion-aware navigation” which includes “[electing] to follow the first suggested route 136 as this route selects segments of the road lanes having minimal or no identified congestion),” see ¶ 53)
Regarding claim 4, Bai in combination with Orendovici discloses the system of claim 2, wherein:
the one or more processors (Bai ¶ 41 “a processor”) are further programmed to: determine that a front of the traffic jam section is close to an end of the first road link and a beginning of third road link is congested; and (Bai ¶ 49 discloses “the first or a segment 84 of the first lane 76 may be presented as a lane segment 102 having a first color or line width indicating a non-congested condition,” and “the fourth or D segment 90 of the first lane 76 may be presented as a lane segment 108 having a third color or line width indicating a congested condition,” also see Fig. 2)
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the front of the traffic jam section is close to an end of the first road link and the beginning of third road link is congested. (Bai ¶ 8 discloses “performing a lane level load balancing to mitigate against the non-congested lane” which includes “assigning a probability to individual [lane route options] of the multiple lane route options,” the probability thereby having been calculated. Also see the “lane selection strategy” depicted in Fig. 1 and Fig. 5., wherein Fig. 5 further depicts “lane level congestion-aware navigation” which includes “[electing] to follow the first suggested route 136 as this route selects segments of the road lanes having minimal or no identified congestion),” see ¶ 53)
Regarding claim 5, Bai in combination with Orendovici discloses the system of claim 2, wherein:
the one or more processors (Bai ¶ 41 “a processor”) are further programmed to: determine that a back of the traffic jam section is close to a beginning of the first road link and an end of third road link connected to the beginning of the first road link is congested; and (Bai ¶ 49 discloses “the first or a segment 84 of the first lane 76 may be presented as a lane segment 102 having a first color or line width indicating a non-congested condition,” and “the fourth or D segment 90 of the first lane 76 may be presented as a lane segment 108 having a third color or line width indicating a congested condition,” also see Fig. 2 depicting an exemplary road segment diagram 74 identifies how an exemplary road portion in the path of travel of the host vehicle 14 may be delineated. One having ordinary skill in the art would recognize that the specific examples are not intended to limit the scope of the present disclosure, see ¶ 24. Therefore, a skilled artisan would recognize that the congested condition may be present in the first segment 84 and the non-congested condition may be present in the fourth segment, the back of the traffic jam section thereby being close to a beginning of the first road link.)
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the back of the traffic jam section is close to the beginning of the first road link and the end of third road link is congested. (Bai ¶ 8 discloses “performing a lane level load balancing to mitigate against the non-congested lane” which includes “assigning a probability to individual [lane route options] of the multiple lane route options,” the probability thereby having been calculated. Also see the “lane selection strategy” depicted in Fig. 1 and Fig. 5., wherein Fig. 5 further depicts “lane level congestion-aware navigation” which includes “[electing] to follow the first suggested route 136 as this route selects segments of the road lanes having minimal or no identified congestion),” see ¶ 53)
Regarding claim 6, Bai in combination with Orendovici discloses the system of claim 2, wherein:
the one or more processors (Bai ¶ 41 “a processor”) are further programmed to: update the initial lane-level traffic jam distribution in the first road link based on a ratio of a number of vehicles that were in a traffic jam in the first road link to a number of vehicles that exited the traffic jam and entered the third road link. (Bai ¶ 38 discloses that “an analysis is conducted of a current lane level distribution [i.e., a ratio] of multiple vehicles in front of or proximate to the host vehicle 14,” and comparing the results “to a non-congested vehicle lane profile to distinguish lane level distribution of the vehicles in front of or proximate to the host vehicle 14,” including “providing individualized lane guidance to road users based on detected traffic distribution of lanes on a road to maximize traffic flow through a congested area,” see ¶ 21. One having ordinary skill in the art would recognize that a distribution of vehicles in each individual lane includes a ratio of a number of vehicles in each lane, which includes a number of vehicles that would enter a third road link.)
Regarding claim 8, Bai in combination with Orendovici discloses the system of claim 2, wherein:
the one or more processors (Bai ¶ 41 “a processor”) are further programmed to: update the initial lane-level traffic jam distribution in the first road link based on a percentage of vehicles that enter the first road link and are trapped in a traffic jam out of vehicles that traveled in the third road link. (Bai ¶ 49 discloses “The host vehicle 14 may automatically adjust [i.e., update] a driving path ... in view of [i.e., based on] the visual indications provided by the road segment diagram 74,” wherein “the first or a segment 84 of the first lane 76 may be presented as a lane segment 102 having a first color or line width indicating a non-congested condition,” and “the fourth or D segment 90 of the first lane 76 may be presented as a lane segment 108 having a third color or line width indicating a congested condition,” see ¶ 49, the “analysis of a current distribution of multiple vehicles in front” being used to “distinguish a lane level distribution of the multiple vehicles in front,” see ¶ 14. Also see Fig. 2. One having ordinary skill in the art would recognize that a distribution of multiple vehicles includes analysis of a percentage of the vehicles. Further, one having ordinary skill in the art would recognize that a percentage includes 100% which would account for the total number of vehicles trapped in the traffic jam.)
Regarding claim 10, Bai in combination with Orendovici discloses the system of claim 1, wherein:
the one or more processors are further programmed to: obtain information on lane changes of a vehicle in the first road link; (Bai ¶ 22 discloses “identifying multiple lane changes to maximize vehicle travel through the congested area.”)
obtain information on whether the vehicle enters the second road link or the third road link after the lane changes; and (Bai ¶ 52 discloses that “lane level congestion notification may further include a lane change recommendation identifying an upcoming exit for the host vehicle 14 to take ... to visually indicate to the user or operator the recommended lane change from the third lane 80 to the fourth lane 82.” One having ordinary skill in the art would recognize that providing a visual indication to a user to change lanes from a third lane indicates first obtaining information that the vehicle is on, and thereby has entered, the third road link.)
Bai does not expressly disclose:
update the initial lane-level traffic jam distribution in the first road link further based on the information on lane changes and the information on whether the vehicle enters the second road link or the third road link.
However, Orendovici discloses:
update the initial lane-level traffic jam distribution in the first road link further based on the information on lane changes and the information on whether the vehicle enters the second road link or the third road link. (Orendovici ¶ 44 discloses that “when causing a portion of the map to be updated, the system(s) may further cause one or more neighboring portions (e.g., neighboring portions that surround the portion) to also be updated.” For example, “when the selection component 124 determines to update more than one portion, the selection component 124 may further store update data 128 indicating an order for performing the updates.” Also see ¶ 53 disclosing “an order associated with the updates to the portions of the map” and ¶ 55 “if a road stretches from the updated portion to a related portion, then the system(s) may cause the related portion to also be updated in order”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the updating of the route choice disclosed by Bai with updating the initial lane-level traffic jam distribution in the first road link further based on the information on lane changes and the information on whether the vehicle enters the second road link or the third road link, as dislocsed by Orendovici, with reasonable expectation of success, to provide one or more additional improvements associated with updating the map (Orendovici ¶ 60), rendering the modification to be obvious.
Regarding claim 11, Bai in combination with Orendovici discloses the system of claim 1, wherein:
the one or more processors are further programmed to: obtain information on lane changes of a vehicle in the first road link; (Bai ¶ 22 discloses “identifying multiple lane changes to maximize vehicle travel through the congested area.”)
obtain information on whether the vehicle was in the second road link or the third road link before driving in the first road link; and (Bai ¶ 52 discloses that “lane level congestion notification may further include a lane change recommendation identifying an upcoming exit for the host vehicle 14 to take ... to visually indicate to the user or operator the recommended lane change from the third lane 80 to the fourth lane 82.” One having ordinary skill in the art would recognize that providing a visual indication to a user to change lanes from a third lane indicates first obtaining information that the vehicle is on, and thereby has entered, the third road link, prior to entering the fourth road link.)
Bai does not expressly disclose:
update the initial lane-level traffic jam distribution in the first road link further based on the information on lane changes and the information on whether the vehicle was in the second road link or the third road link before driving in the first road link.
However, Orendovici discloses:
update the initial lane-level traffic jam distribution in the first road link further based on the information on lane changes and the information on whether the vehicle was in the second road link or the third road link before driving in the first road link. (Orendovici ¶ 44 discloses that “when causing a portion of the map to be updated, the system(s) may further cause one or more neighboring portions (e.g., neighboring portions that surround the portion) to also be updated.” For example, “when [i.e., based on] the selection component 124 determines to update more than one portion, the selection component 124 may further store update data 128 indicating an order for performing the updates.” Also see ¶ 53 disclosing “an order associated with the updates to the portions of the map” and ¶ 55 “if a road stretches from the updated portion to a related portion, then the system(s) may cause the related portion to also be updated in order”)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have combined the updating of the route choice disclosed by Bai with updating the initial lane-level traffic jam distribution in the first road link further based on the information on lane changes and the information on whether the vehicle was in the second road link or the third road link before driving in the first road link, as disclosed by Orendovici, with reasonable expectation of success, to provide one or more additional improvements associated with updating the map (Orendovici ¶ 60), rendering the modification to be obvious.
Regarding claim 12, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 1 for the reasons discussed above.
Regarding claim 13, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 2 for the reasons discussed above.
Regarding claim 14, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 3 for the reasons discussed above.
Regarding claim 15, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 4 for the reasons discussed above.
Regarding claim 16, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 5 for the reasons discussed above.
Regarding claim 17, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 6 for the reasons discussed above.
Regarding claim 19, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 10 for the reasons discussed above.
Regarding claim 20, the combination of Bai and Orendovici discloses the parallel limitations contained in parent claim 11 for the reasons discussed above.
Claims 7, 9, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Bai et al. (U.S. Patent Publication Number 2025/0033640) in view of Orendovici et al. (U.S. Patent Publication Number 2025/0198797), further in view of Fowe (U.S. Patent Publication Number 2020/0025584).
Regarding claim 7, Bai in combination with Orendovici discloses the system of claim 6, wherein:
the one or more processors (Bai ¶ 41 “a processor”) are further programmed to: determine that a front of the traffic jam section is close to an end of the first road link; (Bai ¶ 49 discloses “the first or a segment 84 of the first lane 76 may be presented as a lane segment 102 having a first color or line width indicating a non-congested condition,” and “the fourth or D segment 90 of the first lane 76 may be presented as a lane segment 108 having a third color or line width indicating a congested condition,” also see Fig. 2)
Bai in combination with Orendovici does not expressly disclose:
determine whether the ratio is greater than a threshold; and
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the ratio is greater than the threshold.
However, Fowe discloses:
determine whether the ratio is greater than a threshold; and (Fowe ¶ 46 discloses determining a “multi-modal distribution [i.e., a ratio] across the road segment, wherein the distribution is used to calculate a speed ratio, which provides “analysis of a plurality of vehicles, VID1-VID6, approaching an intersection along road link 220 and exiting along links 225, 230, and 235,” and the speed ratio exceeding the speed ratio threshold when the speed ratio threshold is set to 0.240, see ¶ 61)
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the ratio is greater than the threshold. (Fowe ¶ 31 discloses “estimating [i.e., calculating] the spatial convergence of an arterial lane-level traffic event or congestion incidence” for “if the speed ratio test was 0.240, road link 6 would fail to pass the cluster speed ratio test, and only links 4 and 5 would be aggregated and grouped together,” see ¶ 61)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have utilized the distribution of vehicles in Bai in place of the speed ratio disclosed by Fowe with reasonable expectation of success because the speed ratio of Fowe informs map service providers of “traffic volumes and congestion” because traffic congestion would “cause a significant delay in a route” thereby resulting in slower speeds (Fowe ¶ 34). Therefore, a speed ratio being below a threshold indicates that the number of cars in the traffic jam is greater than a threshold, and that the ratio of cars in the traffic jam to a number of vehicles that have exited the traffic jam would also be greater than the threshold.
Further, it would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the combination of Bai in combination with Orendovici to incorporate calculating the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the ratio is greater than the threshold, as disclosed by Fowe, with reasonable expectation of success, to accurately measure the impact on travel time for different routes and provide route guidance and navigation (Fowe ¶ 48), and to accurate measure of how far before the intersection the traffic congestion begins (Fowe ¶ 48), rendering the modification to be obvious.
Regarding claim 9, Bai in combination with Orendovici discloses the system of claim 8, wherein:
the one or more processors are further programmed to: determine that a back of the traffic jam section is close to a beginning of the first road link; (Bai ¶ 49 discloses “the first or a segment 84 of the first lane 76 may be presented as a lane segment 102 having a first color or line width indicating a non-congested condition,” and “the fourth or D segment 90 of the first lane 76 may be presented as a lane segment 108 having a third color or line width indicating a congested condition,” also see Fig. 2)
Bai in combination with Orendovici does not expressly disclose:
determine whether the ratio is greater than a threshold; and
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the ratio is greater than the threshold.
However, Fowe discloses:
determine whether the ratio is greater than a threshold; and (Fowe ¶ 46 discloses determining a “multi-modal distribution [i.e., a ratio] across the road segment, wherein the distribution is used to calculate a speed ratio, which provides “analysis of a plurality of vehicles, VID1-VID6, approaching an intersection along road link 220 and exiting along links 225, 230, and 235,” and the speed ratio exceeding the speed ratio threshold when the speed ratio threshold is set to 0.240, see ¶ 61)
calculate the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the ratio is greater than the threshold. (Fowe ¶ 31 discloses “estimating [i.e., calculating] the spatial convergence of an arterial lane-level traffic event or congestion incidence” for “if the speed ratio test was 0.240, road link 6 would fail to pass the cluster speed ratio test, and only links 4 and 5 would be aggregated and grouped together,” see ¶ 61)
It would have been obvious to a person having ordinary skill in the art before the effective filing date to have utilized the distribution of vehicles in Bai in place of the speed ratio disclosed by Fowe with reasonable expectation of success because the speed ratio of Fowe informs map service providers of “traffic volumes and congestion” because traffic congestion would “cause a significant delay in a route” thereby resulting in slower speeds (Fowe ¶ 34). Therefore, a speed ratio being below a threshold indicates that the number of cars in the traffic jam is greater than a threshold, and that the ratio of cars in the traffic jam to a number of vehicles that have exited the traffic jam would also be greater than the threshold.
Further, it would have been obvious to a person having ordinary skill in the art before the effective filing date to have modified the threshold of Bai to incorporate calculating the probability of traffic jam in a lane of the first road link that is connected to the third road link based on the determination that the ratio is greater than the threshold, as disclosed by Fowe, with reasonable expectation of success, to accurately measure the impact on travel time for different routes and provide route guidance and navigation (Fowe ¶ 48), rendering the modification to be obvious.
Regarding claim 18, the combination of Bai, Orendovici, and Fowe discloses the parallel limitations contained in parent claim 7 for the reasons discussed above.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/STEPHANIE T SU/Patent Examiner, Art Unit 3662