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 Office Action is in response to the Office Action Response dated July 21, 2026. Claims 1-20 are presently pending and are presented for examination.
Response to Arguments
With respect to the rejections under 35 USC 101, Applicant’s amendments overcome these rejections.
With respect to the rejections of independent claims 1, 8 and 15 under 35 USC 102, regarding new features of “generating safety probability scores on different routes between said starting point and said destination by utilizing a trained machine learning model based on risks evaluated using a plurality of safety-related datasets, wherein said safety-related datasets comprise historical safety-related datasets, real-time safety-related datasets, and geographical datasets and generating said safest route to travel to said destination using a trained machine learning model based on said generated safety probability score evaluated in combination,” Applicant’s arguments are moot in view of new grounds of rejection. With respect to “displaying said generated safest route on a graphical user interface on a display screen of a smartphone device during travel of a vehicle“ Konrardy teaches navigation information is displayed on a mobile computing device (e.g. see col. 16, lines 12-36).
With respect to the rejection of claims 7 and 14, Applicant argued against the use of Designer’s Choice. In response, the Office has provided specific references teaching the claim limitations.
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.
Claims 1-6, 8-13 and 15-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent No. 11,441,916, to Konrardy et al. (hereinafter Konrardy), in view of U.S. Patent No. 12,731,080, to Zahid et al. (hereinafter Zahid).
As per claim 1, and similarly with respect to claims 8 and 15, Konrardy discloses a computer-implemented method for generating a safest route for travel (e.g. see col. 4, lines 33-34, a computer-implemented method is provided for analyzing roadway suitability of an autonomous vehicle to determine safety ratings), the method comprising: receiving an input as to a starting point and a destination (e.g. see col. 9, lines 41-65, wherein a user inputs an origin and destination); obtaining road network characteristics and operational measures in connection with said starting point and said destination (e.g. see col. 38, line 50, to col. 39, line 12, wherein a user selected characteristics of the road segments; and see col. 21, line 32, to col. 22, line 20, wherein the autonomous vehicle receives traffic information)…; generating said safest route to travel to said destination using a trained machine learning model … with said obtained road network characteristics and said operational measures in connection with said starting point and said destination (e.g. see col. 4, lines 15-32, and col. 45, line 61, to col. 46, line 52, wherein route planning is performed, via machine learning, which includes selecting road segments that result in optimize risk management); displaying said generated safest route on a graphical user interface on a display screen of a smartphone device during travel of a vehicle (e.g. see col. 16, lines 12-36, wherein navigation information is displayed on a mobile computing device).
Konrardy fails to disclose generating safety probability scores on different routes between said starting point and said destination by utilizing a trained machine learning model based on risks evaluated using a plurality of safety-related datasets, wherein said safety-related datasets comprise historical safety-related datasets, real-time safety-related datasets, and geographical datasets and generating said safest route to travel to said destination using a trained machine learning model based on said generated safety probability score evaluated in combination. However, Zahid teaches using machine learning models to provide improved route suggestions (i.e. from a starting point to a destination point) based upon historical data, real-time inputs and geographic information to calculate routes scores using parameters such as safety (e.g. see col. 23, lines 9-67). It would have been obvious to a person of ordinary skill in the art at the time of Applicants’ invention to modify the safety rating system of Konrardy to include generating safety scores of different routes using relevant data for the purpose of providing a safest route for a driver.
As per claim 2, and similarly with respect to claims 9 and 16, Konrardy, as modified by Zahid, teaches the features of claims 1, 8 and 15, respectively, and further discloses wherein said machine learning model is built and trained using a training set of data containing road network characteristics and operational measures (e.g. see col. 71, lines 6-38, wherein the machine learning utilizes road data and traffic).
As per claim 3, and similarly with respect to claims 10 and 17, Konrardy, as modified by Zahid, teaches the features of claims 1, 8 and 15, respectively, and further discloses wherein said road network characteristics and said operational measures are obtained from one or more databases (e.g. see col. 72, lines 15-40, wherein the machine learning receives its data from a database).
As per claim 4, and similarly with respect to claims 11 and 18, Konrardy, as modified by Zahid, teaches the features of claims 1, 8 and 15, respectively, and further discloses wherein said road network characteristics comprise data pertaining to intersection characteristics and road characteristics (e.g. see Fig. 5, col. 36, line 59, to col. 38, line 28, steps 502 and 504, wherein operating data includes traffic information and map data including a plurality of road segments would include intersections).
As per claim 5, and similarly with respect to claims 12 and 19, Konrardy, as modified by Zahid, teaches the features of claims 1, 8 and 15, respectively, and further discloses wherein said operational measures comprise data pertaining to aggregated traffic measures, real-time traffic measures, historical crash data, road incidents, and weather conditions (e.g. see at least col. 14, lines 1-28).
As per claim 6, and similarly with respect to claims 13 and 20, Konrardy, as modified by Zahid, teaches the features of claims 1, 8 and 15, respectively, and further discloses wherein said safety probability scores correspond to a level of safety (e.g. see Fig. 5 and col. 40, line 26, to col. 41, line 12, wherein a score is generated for the travel segments based upon risk and safety of travel).
Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Konrardy, in view of Zahid, and in further view of U.S. Patent Publication Nos. 2012/0078743, to Betancourt, 2010/0332131, to Horvitz et al. (hereinafter Horvitz), 2017/0067750, to Day et al. (hereinafter Day), and U.S. Patent No. 11,674,820, to Hydo et al. (hereinafter Hydo).
As per claim 7, and similarly with respect to claim 14, Konrardy, as modified by Zahid, teaches the features of claims 6 and 13, respectively, but fails to disclose wherein said safety probability scores are generated based on pedestrian/cyclist crash risk, crime risk, vehicle crash risk, health risk, and hazardous materials transportation risk. Konrardy does disclose the safety score is based upon the risk (e.g. see Fig. 5, step 5), but not each and every risk claimed. However, Day teaches route selection score based upon driver health condition (e.g. see para 0047). Hydo teaches route section score based upon crash risk (e.g. see claim 1). Horvitz teaches route selection based upon crime risk (e.g. see para 0042). And, Betancourt teaches route selection based upon hazardous material being transported (e.g. see para 0024). It would have been obvious to a person of ordinary skill in the art at the time of Applicants’ invention to modify the safety rating system of Konrardy to include various common risk factors so as to provide a more accurate analysis system.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to James M. McPherson whose telephone number is (313) 446-6543. The examiner can normally be reached on 7:30 AM - 5PM Mon-Fri Eastern Alt Fri. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Abby Flynn can be reached on 571 272-9855. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES M MCPHERSON/Primary Examiner, Art Unit 3663B
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