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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. EP24219236.7, filed on 12/11/2024.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 11/13/2025 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is 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 3, 10, 13, and 19 are rejected under 35 U.S.C. § 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
During examination, claims are given their broadest reasonable interpretation consistent with the Specification. Where, under that interpretation, the metes and bounds of a claim are unclear because the claim language is ambiguous, vague, or susceptible to more than one reasonable interpretation, rejection under 35 U.S.C. §112(b) is appropriate. In re Packard, 751 F.3d 1307, 1311–13 (Fed. Cir. 2014); MPEP §2173.02. A claim is not indefinite merely because it is broad; indefiniteness exists where the boundary of the claimed subject matter cannot be clearly ascertained.
Claims 3, 13, and 19
Claims 3, 13, and 19 each recite, in relevant part:
“wherein the reference route is, or follows, the average vehicle trace.”
Claims 3, 13, and 19 are indefinite because each claim expressly encompasses two alternative relationships between the reference route and the average vehicle trace, and the alternative in which the reference route “follows” the average vehicle trace lacks an ascertainable boundary.
The Specification states that the reference route may be, or may follow, the average vehicle trace. See Spec.[0044]. The Specification further describes techniques for calculating the average vehicle trace. However, neither the claim nor the Specification defines what relationship is required for a reference route that is not itself the average vehicle trace nevertheless to “follow” the average vehicle trace. No maximum lateral deviation, geometric tolerance, degree of overlap, similarity criterion, correspondence criterion, or other objective standard is provided for distinguishing a reference route that “follows” the average vehicle trace from one that does not.
The ambiguity directly affects the scope of the claimed subject matter. Claims 3, 13, and 19 depend, respectively, from Claims 2, 12, and 18, which require determination of respective lateral-displacement values for geographical positions relative to a reference route. Accordingly, the location of the reference route establishes the reference from which each claimed lateral displacement is determined.
Where the reference route is the average vehicle trace, the reference from which the lateral displacement is measured is ascertainable. In contrast, under the alternative in which the reference route merely “follows” the average vehicle trace, the position and geometry of that reference route are not objectively bounded. Multiple routes displaced by different amounts or having different geometries relative to the same average vehicle trace could each arguably “follow” that trace, without any stated criterion for determining which routes satisfy the limitation.
As a result, application of Claims 3, 13, and 19 to the same underlying vehicle-trace data could yield different reference routes and therefore different lateral-displacement values and sequences, with no claim or Specification criterion for determining which result defines the claimed subject matter. The ambiguity in “follows” therefore propagates directly into the lateral-displacement calculation required by the claims and renders the scope of the claims unclear.
Although alternative claim limitations are not improper merely because they are stated in the alternative, each alternative must nevertheless permit the scope of the claim to be ascertained. See MPEP §§2173.05(b), 2173.05(h). Here, the “is” alternative has an ascertainable meaning, whereas the additional “follows” alternative does not provide a sufficiently defined boundary. The inclusion of the indefinite alternative therefore renders Claims 3, 13, and 19 indefinite as a whole.
Claim 10
Claim 10 recites:
“further comprising processing the representative vehicle paths to identify one or more sections of the sequence of road segments as potentially hazardous.”
Claim 10 is indefinite because the phrase “potentially hazardous” does not establish an objective boundary for determining which sections of the sequence of road segments fall within, and which sections fall outside, the claimed classification.
A relative or subjective term is not indefinite merely because it encompasses a range of circumstances. Rather, the relevant inquiry during examination is whether the claim, considered in light of the Specification, provides a sufficiently ascertainable standard for determining its scope. MPEP §2173.05(b); see also Interval Licensing LLC v. AOL, Inc., 766 F.3d 1364, 1370–73 (Fed. Cir. 2014); Datamize, LLC v. Plumtree Software, Inc., 417 F.3d 1342, 1350–52 (Fed. Cir. 2005). The MPEP recognizes that examples may provide an adequate standard for a term of degree, but repeating or exemplifying a relative term does not cure indefiniteness where the disclosure still fails to identify the boundary of the claimed category.
Here, Claim 10 requires processing representative vehicle paths to identify sections as “potentially hazardous,” but does not recite what property of the representative paths must be evaluated, what condition must exist, what threshold must be met, or what relationship between the processed path information and the road section causes the section to fall within that classification.
The Specification provides examples relevant to the meaning of the term. In particular, Spec.[0142] identifies potentially dangerous sections as including, for example, sections at which traffic lanes typically merge and sections exhibiting high variance in typical vehicle behavior indicative of an uncertain or complex driving situation.
Those examples provide contextual meaning, but they do not establish an objective boundary for the claimed classification. For example, the Specification does not state:
what amount of variance constitutes “high variance”;
how such variance is to be measured for purposes of the claimed classification;
whether every road section at which traffic lanes merge necessarily qualifies;
what degree or type of merging behavior is sufficient;
what representative-path geometry, speed behavior, acceleration behavior, lateral deviation, or other path characteristic separates a potentially hazardous section from a section that is not potentially hazardous.
Accordingly, the defect is not merely that Claim 10 encompasses numerous types or degrees of hazards. A broad class may satisfy §112(b) where membership in the class is objectively ascertainable. Here, however, the claim and Specification do not provide an ascertainable criterion defining the boundary of the class itself.
For example, one section may exhibit some variance in typical vehicle behavior while another exhibits a greater variance. The Specification identifies “high variance” as an example of a potentially dangerous circumstance, but provides no standard for determining when the variance becomes sufficiently “high” to place the section within the claimed “potentially hazardous” classification. Likewise, although lane merging is given as an example, the disclosure does not establish whether every merge constitutes a potentially hazardous section or identify a condition that distinguishes qualifying merge locations from nonqualifying ones.
Thus, persons applying Claim 10 to the same representative-path data could reasonably differ as to whether a particular road section satisfies “potentially hazardous,” without an objective criterion in the claim or Specification for resolving that difference. The metes and bounds of Claim 10 are therefore unclear under the examination standard of Packard and MPEP §§2173.02 and 2173.05(b).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1–20 are rejected under 35 U.S.C. § 101 because the claimed inventions are directed to a judicial exception, i.e., an abstract idea, without reciting additional elements that integrate the judicial exception into a practical application or amount to significantly more than the judicial exception.
The analysis below is made in accordance with the Alice/Mayo framework and MPEP §§ 2106 et seq. The claims are evaluated as a whole and according to what they actually recite. No unclaimed implementation detail, performance benefit, hardware configuration, storage reduction, processing-load reduction, or other feature is imported from the Specification into the claims.
The Federal Circuit has repeatedly held that collecting information, analyzing information through mathematical algorithms or evaluative processes, and producing the results of that analysis may constitute an abstract idea. Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1353–54 (Fed. Cir. 2016). The Office likewise recognizes mathematical relationships, mathematical calculations, and certain evaluations or judgments as abstract ideas. MPEP § 2106.04(a).
Step 1 — Statutory Category
Claims 1–10 recite methods and therefore fall within the statutory category of a process.
Claim 11 and Claims 12–16 depending therefrom recite a non-transitory computer-readable storage medium and therefore fall within the statutory category of a manufacture.
Claim 17 and Claims 18–20 depending therefrom recite a processing system and therefore fall within the statutory category of a machine.
Accordingly, Claims 1–20 satisfy Step 1.
Claims 1, 11, and 17
Step 2A, Prong One — The Claims Recite an Abstract Idea
Claim 1
Claim 1 recites, in substance:
obtaining vehicle-trace information comprising geographic-position information;
determining, for each road segment, a route index for each vehicle trace;
constructing a sequence of route indices for each trace;
determining a similarity-based partitioning of those index sequences;
grouping the vehicle traces according to that partitioning; and
processing position information of traces within each group to determine a representative vehicle path.
These limitations recite mathematical concepts and evaluative/data-analysis processes.
In particular, determining a segment-specific route index from a vehicle trace is an act of classifying or categorizing information according to a predetermined set of alternatives. Determining a respective sequence of such indices is organization of the resulting information.
The recited:
“determining a similarity-based partitioning of the plurality of sequences of route indices”
requires evaluating similarity among data sequences and partitioning those sequences according to that similarity. This is a mathematical relationship/calculation and data-classification operation. A mathematical concept need not be written using equations or mathematical symbols; words operating on data can perform the same function as a formula. MPEP § 2106.04(a)(2).
Likewise, processing the geographic-position information of one or more traces in a group to determine a representative vehicle path is an analytical operation performed on numeric location information to produce representative information from the group.
Considered together, the claim therefore recites the abstract idea of:
mathematically classifying, organizing, comparing, and grouping vehicle-trajectory data to derive representative route information.
This is analogous to the type of information collection and analysis addressed in Electric Power Group, where the Federal Circuit explained that collecting information, analyzing the information mathematically or through evaluative processes, and providing the results remain within the abstract-idea category.
The use of vehicle-location information does not remove the analysis from the abstract-idea grouping merely because the information concerns a physical roadway. Limiting otherwise abstract information analysis to a particular type of information or technological field does not, by itself, make the analysis non-abstract.
Accordingly, Claim 1 recites a judicial exception under Step 2A, Prong One.
Claim 11
Claim 11 recites substantially the same data-classification, similarity-partitioning, grouping, and representative-path-determination operations as Claim 1, but places those operations in instructions stored on a non-transitory computer-readable storage medium.
The underlying operations therefore recite the same abstract idea identified for Claim 1.
Claim 17
Claim 17 likewise recites substantially the same operations performed by a processing system having one or more processors and memory storing software.
The data-analysis operations recited by Claim 17 therefore recite the same abstract idea.
Accordingly, Claims 1, 11, and 17 recite an abstract idea under Step 2A, Prong One.
Step 2A, Prong Two — No Integration Into a Practical Application
The claims are next considered as a whole to determine whether additional limitations integrate the identified abstract idea into a practical application.
They do not.
Accessing vehicle traces
Claim 1 recites:
“accessing a plurality of vehicle traces”
where each trace comprises geographic positions of a vehicle.
This limitation merely supplies the information upon which the subsequent abstract analysis operates. The claim does not require a particular sensor arrangement, GPS architecture, vehicle-mounted acquisition system, measurement technique, communication architecture, or other technological mechanism by which the position information is generated.
The claim begins with already-existing vehicle-trace information and instructs that the information be accessed.
Accordingly, this limitation is data gathering ancillary to the recited analysis, rather than a meaningful technological application of the analysis. MPEP § 2106.05(g) recognizes mere data gathering as a type of insignificant extra-solution activity that ordinarily does not integrate an exception into a practical application.
Road segments and road network
Reciting that the information concerns vehicles traveling:
“along a sequence of road segments of a road network”
does not impose a particular technological mechanism upon the mathematical/data-analysis operations.
Instead, the road-network language identifies the subject matter and technological environment of the data being analyzed.
Limiting an abstract analytical process to a particular technological environment or field of use does not itself integrate the exception into a practical application. MPEP §§ 2106.04(d), 2106.05(h).
The Federal Circuit's reasoning in Electric Power Group is instructive. There, the claims dealt specifically with information concerning the operation of an electric power grid—a physical technological system—but the information-gathering and analysis remained abstract because the claimed advance resided in the information analysis rather than in an improvement to the physical grid technology.
The same reasoning applies here.
Segment-specific route indices
The recitation that each route index is:
“selected from a predetermined set of one or more route indices”
and that the indices correspond to respective sets of possible routes does not provide a technological implementation beyond the abstract analysis.
The route indices are informational classifications. The claim does not recite a specialized computer data structure, memory organization, encoding mechanism, processor architecture, or computer-storage arrangement by which the indices are generated or stored.
Rather, the claim requires determining a classification for a vehicle trace and representing that classification using an index.
Similarly, requiring the indices to form:
“a respective sequence of route indices”
defines the content and organization of information used in the subsequent similarity analysis, rather than a particular improvement to computer functionality.
The claim does not recite, for example:
reducing memory consumption;
reducing the number of processor operations;
changing memory access;
compressing data according to a specified encoding process;
improving database retrieval;
improving processor operation;
changing network transmission;
improving sensor operation; or
implementing a particular computer architecture.
Those matters therefore cannot be treated as limitations of Claim 1 merely because they might be consequences or advantages of some implementation of the claimed concept.
Similarity-based partitioning
The limitation requiring:
“determining a similarity-based partitioning of the plurality of sequences of route indices”
does not specify a particular technological mechanism for accomplishing the partitioning.
The claim does not recite:
a particular similarity metric;
a particular mathematical formula;
a particular clustering architecture;
a specialized data structure;
a particular memory organization;
specialized hardware; or
a particular computer-processing technique that changes how a computer operates.
It instead recites the desired analytical result—partition the data according to similarity.
Functional result-oriented limitations directing that information be analyzed to obtain a desired result, without a claimed technological mechanism for achieving that result, do not by themselves establish a technological improvement. Two-Way Media Ltd. v. Comcast Cable Communications, LLC, 874 F.3d 1329, 1337–39 (Fed. Cir. 2017), found claims deficient where they recited desired functional results but not a particular non-abstract technological manner for producing them.
Representative vehicle path
Claim 1 concludes by determining:
“a representative vehicle path for the group along the sequence of road segments.”
The claimed result is itself information derived from the previously analyzed information.
Importantly, Claim 1 does not require the representative vehicle path subsequently to be used to:
control a vehicle;
steer a vehicle;
actuate braking or acceleration;
operate an autonomous-driving controller;
modify an actual navigation system;
physically alter the roadway;
control a traffic-control device; or
perform some other physical or technological operation.
The claim ends with the determination of information.
Thus, the output of the abstract analysis is not applied in the claim to effect a technological result outside the informational analysis itself.
The Federal Circuit has explained that merely producing the result of abstract information analysis, without more, does not supply the practical application needed for eligibility. Electric Power Group, 830 F.3d at 1354.
No claimed computer improvement
Nor does Claim 1 itself recite an improvement to the functioning of a computer or another technological system.
Under current MPEP guidance, an asserted technological improvement is relevant only where the claim reflects that improvement. The examiner must analyze the actual claim as a whole; an improvement described elsewhere cannot simply be imported into claim language that does not recite it.
Here, Claim 1 recites what information is classified and grouped and what informational result is obtained, but it does not recite a technical modification to the computer that performs those operations.
Accordingly, Claim 1 does not integrate the abstract idea into a practical application.
Claims 11 and 17
Claim 11 adds a:
“non-transitory computer-readable storage medium storing software comprising instructions”
and Claim 17 adds:
“one or more processors”
and:
“memory storing software for execution by the one or more processors.”
These limitations require only generic computer implementation of the same abstract analytical operations.
The claims do not recite any particular processor architecture, memory architecture, storage mechanism, computer-network configuration, database structure, or other unconventional technological implementation.
Merely implementing an abstract information-analysis process using generic processor-executable instructions does not integrate the exception into a practical application. See Alice Corp. v. CLS Bank International, 573 U.S. 208, 221–26 (2014); MPEP § 2106.05(f). Current USPTO form-paragraph guidance likewise provides that generic computer implementation does not meaningfully limit an abstract idea where the computer merely performs the recited abstract processing.
Accordingly, Claims 1, 11, and 17 are directed to the judicial exception under Step 2A.
Dependent Claims 2–10, 12–16, and 18–20
The dependent claims do not add limitations sufficient to integrate the exception into a practical application.
Claims 2, 12, and 18 — lateral-displacement values
Claims 2, 12, and 18 add determining:
“a respective lateral displacement value”
for geographic positions, where the value indicates lateral displacement:
“relative to a reference route”
and thereby produces:
“a respective sequence of lateral displacement values.”
These limitations add further mathematical analysis.
Determining displacement of one geographic position relative to a reference route is a mathematical relationship between positional values. Generating a sequence of the resulting displacement values is organization of the mathematical results.
The claims do not require that the displacement values be used to physically reposition the vehicle, actuate a steering controller, alter a sensor, or otherwise effect a physical technological operation.
Thus, the added limitations remain within the mathematical/data-analysis exception and do not integrate it into a practical application.
Claims 3, 13, and 19 — average vehicle trace
Claims 3, 13, and 19 further require calculating:
“an average vehicle trace”
and using that average trace as or to define the reference route.
Calculating an average of numerical position information is a mathematical calculation.
The limitation therefore further specifies the mathematical analysis rather than adding an additional element that applies the abstract idea in a technological manner.
Claims 4, 14, and 20 — determining route index using displacement values
Claims 4, 14, and 20 require processing the lateral-displacement sequences to determine the segment-specific route index.
The claims therefore use one set of mathematically derived information as input to the classification process already recited in the parent claim.
That is additional mathematical analysis and categorization of data. It does not constitute a practical application outside the abstract analysis.
Claim 5 and Claim 15 — clustering vehicle traces and assigning indices
Claims 5 and 15 require:
“grouping the vehicle traces through the road segment into one or more road-segment clusters”
and:
“assigning a different segment-specific route index to each road-segment cluster.”
Clustering data and assigning informational labels to the resulting clusters are mathematical/data-classification operations.
The claims do not recite a particular clustering technology or technical mechanism that changes computer operation. Rather, they specify additional analytical steps for categorizing the vehicle-trace information.
Accordingly, these limitations remain part of the judicial exception.
Claims 6 and 16 — lane indices
Claims 6 and 16 specify that the route indices are:
“lane indices corresponding to lanes of the respective road segment.”
This merely limits the information being classified to lane-related information.
A lane identifier is still informational content, and restricting the abstract classification process to lanes of physical roads is a field-of-use limitation. The claim does not require any physical operation upon the lanes or upon a vehicle occupying them.
Accordingly, this limitation does not integrate the exception into a practical application.
Claim 7 — averaging vehicle traces
Claim 7 requires calculating:
“an average vehicle trace for the group.”
Averaging a plurality of position-data sequences is a mathematical calculation. The resulting average trace remains an informational output.
Claim 7 does not require the average trace subsequently to control or alter a physical system.
Therefore, the added limitation does not provide integration.
Claim 8 — sequences of driving-attribute values
Claim 8 adds determining, for each group:
“a respective sequence of driving attribute values”
where each value is associated with a point along the road segments.
This limitation concerns organizing additional information according to location.
It does not require any physical vehicle operation based on that information and therefore merely adds further data collection/organization to the abstract analytical process.
Claim 9 — vehicle-speed values
Claim 9 specifies that the driving-attribute sequence contains:
“measures of vehicle speed.”
Restricting the informational values to vehicle speed does not alter the character of the claimed operation.
The limitation merely specifies the type of data being analyzed or organized and does not require controlling vehicle speed or otherwise applying the speed information to a physical process.
Claim 10 — identifying potentially hazardous sections
Claim 10 adds:
“processing the representative vehicle paths to identify one or more sections of the sequence of road segments as potentially hazardous.”
This limitation adds another act of analyzing information and classifying the result.
Determining from information whether a road section should be characterized as “potentially hazardous” is an evaluation or judgment based on the analyzed data.
Critically, Claim 10 ends with the identification of the potentially hazardous section.
It does not recite:
issuing a warning;
transmitting an alert;
rerouting a vehicle;
controlling vehicle operation;
applying brakes;
changing steering;
changing a traffic-control device; or
otherwise acting upon the identified condition.
Thus, Claim 10 remains directed to obtaining information by analysis rather than to a technological application of the result.
This is particularly analogous to Electric Power Group, where detecting and analyzing events occurring in an actual electric-power-grid environment did not render the informational analysis eligible.
Accordingly, none of the dependent claims integrates the judicial exception into a practical application.
Step 2B — No Inventive Concept / No Significantly More
Because Claims 1–20 are directed to an abstract idea under Step 2A, the claims are evaluated under Step 2B to determine whether they recite additional elements, individually or in combination, sufficient to amount to significantly more than the judicial exception.
They do not.
Claims 1–10
For Claims 1–10, the route-index determination, mathematical displacement calculations, averaging, similarity partitioning, clustering, grouping, attribute organization, and hazard determination form part of the abstract mathematical/evaluative process itself and therefore cannot separately supply the inventive concept merely by restating or further narrowing that abstract processing.
See Recentive Analytics, Inc. v. Fox Corp., 134 F.4th 1205, 1215 (Fed. Cir. 2025) (an abstract concept cannot itself constitute the inventive concept merely because it is claimed with additional detail).
The remaining limitations—accessing vehicle-trace information and limiting the analysis to road segments, road networks, lanes, geographic positions, vehicle speed, and similar vehicle-related information—amount to data gathering and field-of-use limitations.
Those limitations do not transform the abstract analytical process into significantly more.
Nothing in Claims 1–10 recites a particular machine integral to carrying out the claimed process. Nor is there a transformation of an article into a different state or thing; the claimed operations transform or reorganize information into other information.
Claims 11–16
The non-transitory computer-readable medium of Claim 11 stores software instructions that cause a processing system to perform the same abstract analytical operations.
The claim does not recite a specific or unconventional storage device, processor architecture, or computer configuration.
A generic computer-readable medium storing instructions and a generic processing system executing those instructions are computer components/functions recited at a high level of generality.
MPEP § 2106.05(d) recognizes that generic computer components performing generic computer functions, when claimed merely at a high level of generality, may be found well-understood, routine, and conventional based on judicial recognition.
The generic computer implementation therefore does not provide an inventive concept.
Claims 17–20
Claim 17 expressly recites:
“one or more processors”
and:
“memory storing software for execution by the one or more processors.”
These are generic computer components performing their ordinary functions—storing and executing software instructions.
The claim does not recite any particular processor structure, memory organization, processing architecture, or unconventional interrelationship among those components.
The Supreme Court has made clear that the addition of a generic computer performing generic computer functions does not transform an abstract idea into patent-eligible subject matter. Alice, 573 U.S. at 223–26.
The Federal Circuit similarly explains that generalized steps performed using conventional computer activity remain insufficient where the claim does not recite a particular improvement in computer functionality. In re Killian, 45 F.4th 1373, 1381–82 (Fed. Cir. 2022).
Considering the processor, memory, software, vehicle-related information, road-network environment, and recited mathematical/data-analysis operations both individually and as an ordered combination, the claims do not recite a non-generic computer arrangement comparable to the architecture in BASCOM, nor do they recite a specific improvement in computer operation comparable to Enfish.
Instead, the computer components serve only as tools for carrying out the abstract information processing.
Accordingly, Claims 17–20 do not recite significantly more than the judicial exception.
Distinction From Claims Reciting a Technological Improvement
The claims have also been considered to determine whether the particular ordered combination reflects an improvement to the functioning of a computer or to another technology.
It does not, based on the limitations actually recited.
In particular, none of Claims 1–20 requires:
a reduction in computer memory usage;
a reduction in computational complexity;
faster processing;
improved computer storage or retrieval;
a specialized database or data structure;
a particular compression mechanism;
an improvement to GPS sensing;
an improvement to vehicle sensors;
an improvement to autonomous-vehicle control;
a new communications architecture; or
physical control of a vehicle based on the representative paths.
The mere use of a sequence of route indices as information upon which similarity partitioning is performed does not, by itself, recite a computer-functionality improvement. The claim defines what information is used in the analysis and what analytical operations are performed upon it, not a technical modification to the computer performing those operations.
This distinction is consistent with SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161 (Fed. Cir. 2018), which distinguishes improvements to mathematical/data-analysis techniques from improvements to computer technology itself, and with Recentive, which confirms that improved results from applying data-analysis techniques in a specific technological environment do not alone establish patent eligibility.
Thus, no unrecited technical advantage is relied upon in reaching the present eligibility determination.
Conclusion
For the foregoing reasons:
Claims 1–10 recite mathematical and evaluative processing of vehicle-trajectory information, with vehicle traces and the road-network environment providing data-gathering and field-of-use limitations but no practical application or inventive concept.
Claims 11–16 recite substantially the same abstract analytical process implemented through a generically recited computer-readable storage medium and processing system.
Claims 17–20 recite substantially the same abstract analytical process implemented through generically recited processors and memory.
Accordingly:
Claims 1–20 are rejected under 35 U.S.C. § 101 as being directed to an abstract idea without additional elements that integrate the abstract idea into a practical application and without additional elements, individually or in combination, sufficient to amount to significantly more than the abstract idea.
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, 5–9, 11, and 15–17 are rejected under 35 U.S.C. §103 as being unpatentable over Fridman (US 2018/0024568 A1) in view of Del Pero (US 2021/0403001 A1).
Claims 2–4, 10, 12–14, and 18–20 are rejected under 35 U.S.C. §103 as being unpatentable over Fridman in view of Del Pero, and further in view of Fowe (US 2022/0180741 A1).
Regarding Claim 1
Disclosure by Fridman
Fridman teaches:
A method of determining representative vehicle paths
"process 1900 may include clustering, by server 1230, vehicle trajectories related to multiple vehicles travelling on the road segment and determining the target trajectory based on the clustered vehicle trajectories... Generating the target trajectory may include averaging, by server 1230, the clustered trajectories." [0304]
Rationale: Express. The target trajectory is generated by averaging the trajectories belonging to a group and therefore constitutes a vehicle path that is representative of that group.
along a sequence of road segments of a road network,
"local map 1140 may include target trajectories for one or more lanes associated with road segments 1120 and/or 1130 within geographic region 1111... Target trajectory 1147 represents a preferred path an autonomous vehicle should follow when transitioning from lanes 1120... to road segment 1130." [0246]
Rationale: Express. Fridman's road model spans interconnected road segments and includes paths that carry the vehicle from one segment of the sequence to the next.
the method comprising: accessing a plurality of vehicle traces,
"vehicles 1205, 1210, 1215, 1220, and 1225 traveling along road segment 1200 may transmit a plurality of trajectories 2200 to server 1230." [0351]
Rationale: Express. The plural received trajectories are the claimed plurality of vehicle traces.
each vehicle trace comprising a respective sequence of geographical positions
"vehicles 200 may transmit data to one or more servers relating to their motion along road segment 1100 (e.g., steering angle, heading, time, position, speed, sensed road geometry, and/or sensed landmarks, among things). The server may reconstruct trajectories for vehicles 200 based on the received data." [0244]
Rationale: Fridman does not recite the phrase "sequence of geographical positions" verbatim. It does, however, expressly disclose the transmission of time-correlated position measurements acquired as the vehicle moves along the road segment, and the reconstruction of the vehicle's trajectory from those measurements. A trajectory reconstructed from successive time-stamped position measurements is, of necessity, an ordered set of geographic positions ordered by the accompanying time data. The limitation is therefore rendered obvious to a person of ordinary skill by Fridman's express disclosure, and is not asserted as a verbatim recitation.
for a respective vehicle
"The navigation information may include a trajectory associated with each of the vehicles 1205, 1210, 1215, 1220, and 1225 as each vehicle travels over road segment 1200." [0279]
Rationale: Express one-to-one association of a trace with its respective vehicle.
wherein the segment-specific route index is selected from a predetermined set of one or more route indices for the road segment,
"The lane structure may include the total number of lanes of road segment 1200, the type of lanes (e.g., one-way lane, two-way lane, driving lane, passing lane, etc.), markings on lanes, width of lanes, etc." [0281]
"the navigation information may include a lane assignment, e.g., which lane of a plurality of lanes a vehicle is traveling in. For example, the lane assignment may be associated with a numerical value '3' indicating that the vehicle is traveling in the third lane." [0281]
Rationale: Express under the construction stated above. Fridman establishes the segment-specific route index itself: a numerical value identifying which of the lanes of road segment 1200 a particular vehicle occupied. The lane structure of that segment, including its total number of lanes, defines the finite set of such indices available for the segment, and the particular vehicle's lane assignment is selected from that set.
each segment-specific route index corresponding to a different set of possible routes along the road segment,
"Server 1230 may identify routes or trajectories associated with each lane." [0350]
"each lane of a multi-lane road may be associated with its own target trajectory." [0215]
Rationale: Express. Fridman associates each lane with its own respective route or set of trajectories; different lane indices therefore correspond to different sets of possible routes along the same road segment.
for each of the groups of vehicle traces, processing the sequence of geographical positions of one or more vehicle traces of the group to determine a representative vehicle path for the group
"In each cluster 2205, 2210, 2215, 2220, 2225, and 2230, trajectories may be averaged to obtain a target trajectory associated with the specific cluster. For example, the trajectories from multiple drives associated with the same lane cluster may be averaged." [0354]
"Server 1230 may compute a mean curve or trajectory in the C0 reference frame." [0354]
Rationale: Express. Averaging the trajectories of a cluster operates on the position data defining those trajectories (see [0244] above) and yields a mean trajectory representative of the group.
along the sequence of road segments.
"To assemble lanes from the trajectories, server 1230 may select a reference frame of an arbitrary lane. Server 1230 may map partially overlapping lanes to the selected reference frame. Server 1230 may continue mapping until all lanes are in the same reference frame." [0356]
Rationale: Express. Fridman assembles the lane-level representative paths derived from the trajectories into a single common reference frame, and the resulting model spans connected road segments and the transitions between them ([0246]).
Claim Limitations Not Explicitly Taught by Fridman
Fridman does not explicitly teach the following:
as the vehicle transits the sequence of road segments;
for each of the road segments of the sequence of road segments, processing each of the vehicle traces to determine at least one respective segment-specific route index for the vehicle trace,
and thereby determining, for each of the plurality of vehicle traces, a respective sequence of route indices;
determining a similarity-based partitioning of the plurality of sequences of route indices and thereby partitioning the plurality of vehicle traces into a plurality of groups of vehicle traces;
Examiner Note: As to the second of these, it is noted for completeness that Fridman supplies the segment-specific route index itself ([0281], mapped above) and that Fridman's server does perform lane-related processing on the received trajectories — "Server 1230 may identify routes or trajectories associated with each lane from the trajectories received from vehicles through a clustering process" ([0350]). Fridman's lane assignment is, however, described principally as information transmitted by the vehicle along with its trajectory ([0281], [0350]). Fridman is therefore not relied upon as expressly teaching the determination of the index by processing the individual vehicle trace, and that limitation is addressed below.
As to the last of these, it is noted for completeness that Fridman does teach similarity-based partitioning of vehicle traces as such — "all the drives in a cluster may be similar with respect to the lane assignment (e.g., in the same lane before and after a junction) along the drive on road segment 1200" ([0353]), and clustering "based on at least one of the absolute heading of vehicles or lane assignment of the vehicles" ([0304]) — but does not teach that the partitioning operates on sequences of route indices. Because the antecedent operation and its "thereby" consequent form a single integrated limitation, that limitation is addressed below as a combined operation rather than divided between references.
Disclosure by Del Pero
Del Pero teaches:
as the vehicle transits the sequence of road segments;
"identifying a second set of vehicle trajectories that are associated with a node positioned between two or more segments of the road network, wherein each of the two or more segments has at least one lane; for each vehicle trajectory in the second set, identifying a respective combination of lanes of the two or more segments that comprises an origin lane and a destination lane associated with the vehicle trajectory." [0014]
"the example pipeline has determined that a given trajectory (shown in black) is associated with the segment lane 412 that has the lane identifier 'B' and the segment lane 415 that has the lane identifier 'E,' where the segment lane 412 is the origin lane and the segment lane 415 is the destination lane." [0177]
Rationale: Express. The individual vehicle trajectory originates in a lane of one road-network segment and terminates in a lane of a different road-network segment joined at the node. The trace therefore transits a sequence of road segments.
for each of the road segments of the sequence of road segments, processing each of the vehicle traces to determine at least one respective segment-specific route index for the vehicle trace,
"the example pipeline may next generate geospatial lane data for each segment within the road network (or at least each of a subset of the segments within the road network)." [0073]
"the example pipeline may generate geospatial lane data for each node within the road network (or at least each of a subset of the nodes within the road network)." [0074]
"the example pipeline may determine a respective sampling point for each identified trajectory that represents the intersection between the identified trajectory and the first sampling position." [0100]
"the example pipeline may infer that each identified cluster at the first sampling point is associated with a different lane of the given segment." [0113]
"based on the comparing, identifying a first segment lane that has the greatest extent of overlap with the trajectory on a first end of the trajectory and a second segment lane that has the greatest extent of overlap with the trajectory on a second end of the trajectory." [0175]
"the geospatial lane data that is stored for the given segment may include a lane identifier for each lane of the segment." [0156]
Rationale: Express. Del Pero performs its lane determination for each segment of the road network and its origin/destination determination at each node ([0073]–[0074]), so the operation is carried out for each segment of the traversed sequence rather than at one isolated location. Within that operation, Del Pero processes the individual vehicle trajectory: it determines a sampling point for that trajectory at successive positions along the segment ([0100]), infers from the resulting clusters that each corresponds to a different lane of the segment ([0113]), and compares the individual trajectory against the segment-lane geometry to identify the lane with which that trajectory is associated ([0175]), the lane being identified by its stored lane identifier ([0156]). The determination of the index is therefore made by processing the trace, not merely received with it.
and thereby determining, for each of the plurality of vehicle traces, a respective sequence of route indices;
"creating a data element that identifies the first and second segment lanes as the pairwise combination of associated segment lanes for the trajectory, which may comprise an ordered sequence of segment lane identifiers." [0175]
"each identified segment lane has been assigned a lane identifier. Specifically, segment lane 411 has been assigned a lane identifier of 'A,' segment lane 412 has been assigned a lane identifier of 'B'..." [0165]
Rationale: Express. Del Pero creates, for each individual vehicle trajectory, a data element comprising an ordered sequence of segment-lane identifiers. Each segment-lane identifier is a route index specific to its road segment, and the ordering is derived from the trajectory's own timing information ([0175]). Where a route spans more than two segments, Del Pero's disclosed per-node operation is carried out at each node of the road network ([0074]), predictably yielding a correspondingly longer ordered index sequence. This conclusion rests on Del Pero's express network-wide repetition of its own disclosed operation, not on inherency.
determining a similarity-based partitioning of the plurality of sequences of route indices and thereby partitioning the plurality of vehicle traces into a plurality of groups of vehicle traces;
"determining a count of instances of each different pairwise combination of segment lanes that has been created for the trajectories in the identified set." [0180]
"the example pipeline has counted 52 instances of trajectories that extend from the 'C' segment lane to the 'A' segment lane, 26 instances of trajectories that extend from the 'B' segment lane to the 'E' segment lane, 43 instances of trajectories that extend from the 'F' segment lane to the 'D' segment lane, and two instances of trajectories that extend from the 'B' segment lane to the 'D' segment lane." [0181]
Rationale: This limitation is met by the combined operation of the two references, and is addressed as a single unit because the "thereby" clause is the direct consequent of the antecedent operation. Del Pero expressly sorts the plurality of vehicle trajectories according to their respective ordered segment-lane identifier combinations, producing distinct populations of trajectories (52, 26, 43, and 2) each defined by a common ordered index sequence. Sorting by identity of the ordered index sequence is a similarity-based partitioning, identity being the limiting case of similarity. Fridman independently teaches that the trace-partitioning criterion may be similarity of lane assignment, expressly permitting drives to be grouped where they are "in the same lane before and after a junction" ([0353]) and clustering "based on at least one of... lane assignment of the vehicles" ([0304]). In the combined system, Fridman's similarity-based clustering engine operates on Del Pero's ordered segment-lane identifier sequences; performing the antecedent operation on those sequences necessarily produces the recited consequent, namely the partitioning of the plurality of vehicle traces into a plurality of groups.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to represent the lane assignments associated with each vehicle trajectory in Fridman's system using Del Pero's ordered segment-lane identifiers, and to perform Fridman's lane-assignment-based similarity clustering upon those ordered identifier sequences.
Fridman expressly selects lane assignment along the traveling path as the information associated with each vehicle trajectory ([0350]), expressly identifies the lane of a road segment by a numerical index ([0281]), and expressly uses lane assignment as its clustering criterion ([0304], [0353]), including where the criterion is evaluated across a junction ([0353]). Fridman does not, however, specify how that lane assignment is derived from the trajectory itself, nor a data format for the resulting lane-assignment history. Del Pero supplies both: a disclosed process for determining, from an individual trajectory, the segment lane with which it is associated ([0100], [0113], [0175]), and identifiers assigned to the segment lanes of the road network ([0156], [0165]) and, for an individual trajectory, an ordered sequence of those identifiers spanning the segments joined at a node ([0175], [0177]), evaluated across many trajectories to identify recurring combinations ([0180]–[0181]). A person of ordinary skill would have had reason to employ Del Pero's representation in Fridman's clustering process because the ordered identifier sequence is a machine-processable expression of the very lane-assignment information Fridman already uses as its clustering criterion, and because Del Pero applies its operation across every segment and node of the road network ([0073]–[0074]), which is the scale at which Fridman's crowdsourced model is built. The combination preserves the respective functions of each element — Fridman's clustering and averaging, Del Pero's identifier representation — and would predictably result in vehicle traces being grouped according to the similarity of their lane/route index sequences, followed by generation of Fridman's averaged representative path for each group ([0354]).
Regarding Claim 2
The combination of Fridman and Del Pero establishes the method of Claim 1, which is the basis for Claim 2.
Claim Limitations Not Explicitly Taught by Fridman or Del Pero
Neither Fridman nor Del Pero is relied upon for the added subject matter of Claim 2:
comprising, for each vehicle trace, determining a respective lateral displacement value for all or a subset of the geographical positions in the sequence of geographical positions, the lateral displacement value indicating a lateral displacement of the geographical position relative to a reference route along the sequence of road segments, and thereby determining, for each of the plurality of vehicle traces, a respective sequence of lateral displacement values.
Examiner Note: For clarity of the record: Fridman does disclose an offset amount relative to a target trajectory — an "amount of lane offset from a lane for which a target trajectory is stored" used in generating navigational instructions ([0215]), and "a determined amount of offset to be maintained relative to the location of the target trajectory" ([0216]). Those disclosures concern a prospective navigation offset applied when a vehicle drives relative to a stored target trajectory. They are not relied upon as teaching the claimed determination of a lateral displacement value for a geographic position of a collected vehicle trace. Del Pero, in turn, represents each trajectory as "a time-sequence of pose values" ([0092]) and samples each trajectory at successive positions along a segment ([0100]–[0104]), but does not calculate a lateral displacement of those positions relative to a reference route. The entire limitation is therefore addressed by Fowe.
Disclosure by Fowe
Fowe teaches:
comprising, for each vehicle trace, determining a respective lateral displacement value for all or a subset of the geographical positions in the sequence of geographical positions, the lateral displacement value indicating a lateral displacement of the geographical position relative to a reference route along the sequence of road segments, and thereby determining, for each of the plurality of vehicle traces, a respective sequence of lateral displacement values.
"the probe data may also include an identifier, such as a trajectory identifier, that identifies the probe that provides the probe data and enables the linking of instances of probe data into vehicle trajectories and probe traces... Thus, probe traces define the path of a probe device, such as may be carried by a vehicle during its travel along a portion of the road network." [0045]
"A plurality of probe data, or 'probes' 400 of a segment are plotted by their deviation or d-value (e.g., d1 and d2 in FIG. 4) as the lateral distance, or x-distance between the probe position and a center line vector 402." [0056]
"the absolute value of the d-value indicates how far the probe is from the center line vector 402, measured laterally, or at a direction orthogonal to, or substantially orthogonal to the flow of traffic." [0058]
Rationale: Fowe expressly links successive individual probe instances, each of which comprises a geographic position, into a vehicle trajectory or probe trace ([0045]), and expressly calculates for an individual probe position a d-value that is the lateral distance of that geographic position from a center line vector serving as the reference ([0056], [0058]). The center line vector runs parallel to the flow of traffic along the segment ([0056]), and Fowe expressly contemplates that a segment reference may span "a plurality of contiguous segments as a strand" ([0044]), satisfying "along the sequence of road segments." The only step beyond Fowe's express disclosure is the retention of the individually calculated d-values in the order of the probes forming each trace. Because Fowe already links those probes into an ordered trace and already computes the value for the individual probe, retaining the resulting values in trace order is a routine organization of data Fowe expressly generates, and would have been obvious to a person of ordinary skill. This conclusion is not premised on inherency.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to calculate Fowe's lateral positional indicator for the successive geographic positions forming each vehicle trace in the Fridman–Del Pero system and to retain those values as a respective sequence for each trace.
All three references operate on the same category of data: crowdsourced position measurements collected from vehicles traversing a road segment. Fridman collects vehicle position and GPS data from multiple vehicles over a common road segment ([0350]); Del Pero derives trajectories as time-sequences of pose values ([0092]); Fowe links probe positions into traces and provides a known, quantitative measure of how far each such position lies laterally from a reference line ([0045], [0056], [0058]). Fridman's system already turns on lateral lane occupancy — it transmits lane assignment with each trajectory and clusters on that basis ([0304], [0350]) — but does not specify how lateral position is quantified. Applying Fowe's known d-value calculation to the position data Fridman already collects supplies that quantification using a known technique on a known data type to yield a predictable result, without altering the function of Fridman's clustering and averaging or Del Pero's identifier representation.
Regarding Claim 3
The combination of Fridman, Del Pero, and Fowe establishes the method of Claim 2, which is the basis for Claim 3.
Disclosure by Fridman
Fridman teaches:
comprising determining the reference route by processing all or a subset of the plurality of vehicle traces to calculate an average vehicle trace,
"In each cluster 2205, 2210, 2215, 2220, 2225, and 2230, trajectories may be averaged to obtain a target trajectory associated with the specific cluster. For example, the trajectories from multiple drives associated with the same lane cluster may be averaged." [0354]
Rationale: Express. Fridman processes a subset of the plurality of vehicle traces — those belonging to a given lane cluster — and calculates their average.
wherein the reference route is, or follows, the average vehicle trace.
"The averaged trajectory may be a target trajectory associate[d] with a specific lane." [0354]
"navigation based on the target trajectory may include a determined amount of offset to be maintained relative to the location of the target trajectory." [0216]
Rationale: Express. The averaged trajectory itself becomes Fridman's target trajectory, and Fridman expressly uses that target trajectory as the positional reference against which an offset is determined. The reference route is therefore the average vehicle trace.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to use Fridman's averaged clustered trajectory as the reference line relative to which Fowe's lateral positional indicators are calculated.
Fowe expressly invites this substitution. Fowe states that its center line vector "may be a y-axis vector positioned in the center of a segment, such as by determining a lateral midway point of a spread of the probe data, mean, or median lateral positional indicator of the probe data," and "may additionally or alternatively be identified based on map data and/or any other means" ([0056]). Fowe further states that "the lateral positional indicators may be determined using a different basis than the center line vector 402" ([0058]) and that "other methods for determining a baseline vector and/or corresponding lateral positional indicators of probes may be contemplated" ([0061]). Fridman independently generates, from the same category of crowdsourced trajectory data, a lane-specific averaged trajectory that runs along the road segment ([0354]). Supplying that averaged trajectory as the baseline for Fowe's d-value computation is the application of a known technique to a known reference-line requirement, with the predictable result of measuring lateral deviation from the representative route actually traveled by vehicles on that segment.
Regarding Claim 4
The combination of Fridman, Del Pero, and Fowe establishes the method of Claim 2, which is the basis for Claim 4.
Disclosure by Del Pero
Del Pero teaches:
wherein the method comprises, for each of the road segments of the sequence of road segments, processing each of the sequences of lateral displacement values to determine the respective segment-specific route index for each vehicle trace.
"the example pipeline may determine a respective sampling point for each identified trajectory that represents the intersection between the identified trajectory and the first sampling position." [0100]
"the function of identifying the one or more clusters of sampling points at the first sampling position may involve applying a clustering technique (e.g., k-means clustering technique) to the set of respective sampling points along the first sampling position." [0105]
"the example pipeline may infer that each identified cluster at the first sampling point is associated with a different lane of the given segment, and may further infer that the determined reference point for each identified cluster corresponds to a position of a centerline of a respective lane." [0113]
"based on the comparing, identifying a first segment lane that has the greatest extent of overlap with the trajectory... creating a data element that identifies the first and second segment lanes as the pairwise combination of associated segment lanes for the trajectory." [0175]
"the geospatial lane data that is stored for the given segment may include a lane identifier for each lane of the segment." [0156]
Rationale: Express as to every step of the recited determination except the identity of the values processed. For each segment, Del Pero derives from each individual trajectory a respective sampling point at each of a succession of sampling positions along that segment ([0100]), each such sampling point representing where that trajectory lies across the segment at that position. Del Pero clusters those per-trajectory positional values ([0105]) and expressly infers that each resulting cluster is associated with a different lane of the segment and corresponds to that lane's centerline ([0113]) — it is Del Pero, and not Fowe, that supplies the correspondence between a positional cluster and a lane. Del Pero then associates the individual trajectory with the resulting segment lane ([0175]) and identifies that lane by its stored lane identifier ([0156]), which is the respective segment-specific route index for that trace. What Del Pero does not expressly state is that the per-trajectory positional values so processed are lateral displacement values relative to a reference route; Fowe supplies that below.
Limitation Remaining After Fridman and Del Pero
processing each of the sequences of lateral displacement values, insofar as it requires the values processed to be lateral displacement values relative to a reference route.
Disclosure by Fowe
Fowe teaches:
processing each of the sequences of lateral displacement values
"A plurality of probe data, or 'probes' 400 of a segment are plotted by their deviation or d-value... as the lateral distance, or x-distance between the probe position and a center line vector 402." [0056]
"the d-values may then be used to partition the clusters, such as by using any suitable clustering algorithm, such as k-means." [0058]
Rationale: Express. Fowe expresses the across-segment position of a probe as a d-value — a signed lateral displacement of that geographic position from a reference line running along the segment — and expressly uses those d-values as the input to a clustering operation performed for the segment. Fowe is relied upon only for the identity and form of the values processed, namely lateral displacement values relative to a reference route. It is not relied upon for any correspondence between its clusters and the lanes of the segment; Fowe states that the number of clusters "need not necessarily be the number of lanes of the segment" ([0059]), and that correspondence is supplied by Del Pero [0113].
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to express the per-trajectory positional values that Del Pero derives at each sampling position along a road segment as Fowe's lateral displacement values, such that Del Pero's disclosed clustering and lane-association process determines the trace's segment-specific route index from that trace's sequence of lateral displacement values.
The two operations are directed to the same quantity. Del Pero's sampling point is the intersection of a trajectory with a line drawn perpendicular to the segment at a given position ([0097], [0100]) — that is, a measure of where the trajectory lies across the segment at that position. Fowe's d-value is the same quantity expressed numerically: the lateral distance of a probe position from a reference line running parallel to the flow of traffic along the segment, signed to indicate side ([0056], [0058]). A person of ordinary skill would have had reason to adopt Fowe's signed scalar representation for Del Pero's sampling points because it reduces a two-dimensional geospatial position to the single across-segment coordinate that Del Pero's clustering actually turns on, which simplifies the clustering computation and makes the resulting cluster positions directly comparable between sampling positions and between segments. The substitution changes nothing about Del Pero's process: the sampling points are still clustered (Del Pero [0105]; Fowe [0058] performs the same k-means clustering on the same quantity), the clusters are still inferred to correspond to respective lanes (Del Pero [0113]), the trajectory is still associated with a lane ([0175]), and the lane is still identified by its identifier ([0156]). Fridman supplies the surrounding architecture in which a per-segment lane index is carried with each vehicle trajectory and used for downstream clustering ([0281], [0350]). Each element performs its known function and the result — determination of the trace's segment-specific route index from its sequence of lateral displacement values — is predictable.
Regarding Claim 5
The combination of Fridman and Del Pero establishes the method of Claim 1, which is the basis for Claim 5.
Disclosure by Fridman
Fridman teaches:
comprising, for each road segment of the sequence of road segments, determining the set of segment-specific route indices by grouping the vehicle traces through the road segment into one or more road-segment clusters,
"Clustering vehicle trajectories may include clustering, by server 1230, the multiple trajectories related to the vehicles travelling on the road segment into a plurality of clusters based on at least one of the absolute heading of vehicles or lane assignment of the vehicles." [0304]
"all the drives in a cluster may be similar with respect to the lane assignment... Trajectories clustered by lane assignment may be useful for identifying lanes along the roadways." [0353]
Rationale: Express. Fridman groups the vehicle traces traversing the road segment into clusters, expressly for the purpose of identifying the lanes of that road segment. Del Pero's network-wide per-segment processing ([0073]–[0074], mapped in Claim 1) supplies the recitation that this be performed for each road segment of the sequence.
and assigning a different segment-specific route index to each road-segment cluster of vehicle traces.
"The averaged trajectory may be a target trajectory associate[d] with a specific lane." [0354]
"the lane assignment may be associated with a numerical value '3' indicating that the vehicle is traveling in the third lane." [0281]
Rationale: PHOSITA-obvious rather than express. Fridman associates each cluster with a specific lane of the road segment ([0354]) and separately identifies lanes of a road segment by numerical index ([0281]). Fridman does not recite in one sentence the step of tagging each cluster with its lane index. However, once a cluster has been determined to correspond to a specific lane, and lanes are already identified numerically in the same system, applying the corresponding numerical lane index to that cluster is nothing more than labeling an already-determined result with an identifier the reference already uses for the same purpose. A person of ordinary skill would have had reason to do so in order to reference, store, and compare the clusters in the road model, and the result — one distinct index per distinct lane cluster — is entirely predictable. Del Pero's lane identifiers ([0156], [0165]), already incorporated into the Claim 1 combination, supply the identifier form in the combined system.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to label each of Fridman's lane-based trajectory clusters with the corresponding segment-lane index, in the identifier form taught by Del Pero.
Fridman already determines that each trajectory cluster corresponds to a particular lane of the road segment ([0353]–[0354]) and already expresses lane occupancy numerically ([0281]). Del Pero, incorporated into the base combination for Claim 1, assigns a respective identifier to each segment lane and stores it with the segment's lane data ([0156], [0165]). Attaching the corresponding identifier to each determined cluster is a predictable use of a known labeling technique that facilitates the storage, retrieval, and cross-trace comparison the combined system already performs.
Regarding Claim 6
The combination of Fridman and Del Pero establishes the method of Claim 1, which is the basis for Claim 6.
Disclosure by Fridman
Fridman teaches:
wherein the predetermined set of one or more route indices for each road segment is a respective set of one or more lane indices corresponding to lanes of the respective road segment.
"The lane structure may include the total number of lanes of road segment 1200, the type of lanes... In some embodiments, the navigation information may include a lane assignment, e.g., which lane of a plurality of lanes a vehicle is traveling in. For example, the lane assignment may be associated with a numerical value '3' indicating that the vehicle is traveling in the third lane." [0281]
Rationale: Express. The set of available indices for a road segment is defined by the total number of lanes of that segment, and each index is a numerical value corresponding to a particular lane of that segment.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to implement the route indices of Claim 1 as Fridman's lane indices for the respective road segment. The rationale for combining the references is as set forth for Claim 1; Del Pero's ordered segment-lane identifiers ([0165], [0175]) are themselves lane indices corresponding to lanes of the respective segment, so the combined system uses lane indices as its route indices without modification of either reference's function.
Regarding Claim 7
The combination of Fridman and Del Pero establishes the method of Claim 1, which is the basis for Claim 7.
Disclosure by Fridman
Fridman teaches:
wherein determining a respective representative vehicle driving path for each of the groups of vehicle traces comprises processing the sequences of geographical positions for each of the vehicle traces of the group to calculate an average vehicle trace for the group.
"In each cluster 2205, 2210, 2215, 2220, 2225, and 2230, trajectories may be averaged to obtain a target trajectory associated with the specific cluster. For example, the trajectories from multiple drives associated with the same lane cluster may be averaged." [0354]
"To average a cluster of trajectories, server 1230 may select a reference frame of an arbitrary trajectory C0. For all other trajectories (C1, ..., Cn), server 1230 may find a rigid transformation that maps Ci to C0... Server 1230 may compute a mean curve or trajectory in the C0 reference frame." [0354]
"Such an operation may include finding a mean or average trajectory representing the clustered vehicle trajectories in each cluster." [0347]
Rationale: Express and essentially verbatim. Fridman averages every trajectory belonging to the group to compute a mean trajectory for that group, and the averaging operates on the position data defining those trajectories ([0244]).
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to apply Fridman's expressly disclosed averaging operation to the vehicle traces of each group formed in the Claim 1 combination. The rationale for combining the references is as set forth for Claim 1. Del Pero supplies only the representation on which the groups are formed; Fridman's averaging step is then performed on each resulting group exactly as Fridman discloses, each element performing its known function.
Regarding Claim 8
The combination of Fridman and Del Pero establishes the method of Claim 1, which is the basis for Claim 8.
Disclosure by Fridman
Fridman teaches:
further comprising determining, for each of the groups of vehicle traces, a respective sequence of driving attribute values, each driving attribute value being associated with a respective point along the sequence of road segments.
"vehicles 200 may transmit data to one or more servers relating to their motion along road segment 1100 (e.g., steering angle, heading, time, position, speed, sensed road geometry, and/or sensed landmarks, among things)." [0244]
"Vehicles travelling on a road segment may collect data by various sensors. The data may include landmarks, road signature profile, vehicle motion (e.g., accelerometer data, speed data), vehicle position (e.g., GPS data)." [0350]
"sparse map 800 may also include road signature profiles. Such road signature profiles may be associated with any discernible/measurable variation in at least one parameter associated with a road... FIG. 11D shows an example of a road signature profile 1160... profile 1160 may represent a measure of road surface roughness, as obtained, for example, by monitoring one or more sensors providing outputs indicative of an amount of suspension displacement as a vehicle travels a particular road segment." [0248]
Rationale: This limitation is presented as rendered obvious, not as expressly disclosed, and the record should reflect that distinction. Fridman expressly acquires driving-attribute measurements — steering angle, heading, speed, and accelerometer data — over the course of each vehicle's traversal of the road segment, and expressly acquires those measurements together with time and position data ([0244], [0350]), so that each attribute value is already associated with the geographic point at which it was measured. Fridman further expressly constructs position-indexed profiles from crowdsourced drive data, in which a measured parameter is expressed as its variation along a particular road segment ([0248], FIG. 11D). What Fridman does not expressly disclose is the determination of such an attribute sequence for each group of vehicle traces. However, Fridman already performs group-level aggregation of the very traces in question, averaging every trajectory in a cluster to obtain a single representative result for that cluster ([0354]). A person of ordinary skill, possessing (i) position-correlated driving attributes for each trace, (ii) an express practice of expressing measured parameters as profiles along a road segment, and (iii) an express practice of aggregating the traces of a cluster into one group-level result, would have had reason to aggregate the attribute values of a group's traces into a corresponding group-level sequence indexed along the road segment. The reason to do so is Fridman's own stated purpose of characterizing road and driving conditions along a segment for autonomous navigation ([0248], [0350]), and the result — one attribute sequence per group, indexed by position — is predictable.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to organize the position-correlated driving-attribute measurements already collected by Fridman according to the trace groups formed in the Claim 1 combination, and to retain the resulting values as a sequence indexed along the road segments of the route. The rationale for combining the references is as set forth for Claim 1. Del Pero's ordered segment-lane sequences define the groups and the order of the segments traversed, providing the index along which Fridman's already-acquired attribute values are arranged.
Regarding Claim 9
The combination of Fridman and Del Pero establishes the method of Claim 8, which is the basis for Claim 9.
Disclosure by Fridman
Fridman teaches:
wherein each sequence of driving attribute values comprises a sequence of measures of vehicle speed.
"vehicles 200 may transmit data to one or more servers relating to their motion along road segment 1100 (e.g., steering angle, heading, time, position, speed...)." [0244]
"The data may include... vehicle motion (e.g., accelerometer data, speed data), vehicle position (e.g., GPS data)." [0350]
Rationale: Express as to the acquisition of successive vehicle-speed measurements correlated with time and position over the traversal. Selecting speed — one of the enumerated attributes Fridman already collects — as the driving attribute organized into the group-level sequence of Claim 8 is a predictable use of the data Fridman expressly obtains, for the reasons set out for Claim 8.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to implement the group-level driving-attribute sequence of Claim 8 using Fridman's expressly acquired vehicle-speed measurements. The rationale for combining the references is as set forth for Claim 1. Speed is among the attributes Fridman already transmits with each trajectory ([0244]), and characterizing how the vehicles of a given lane group travel along the route yields the predictable benefit of lane-level speed information for the road model Fridman is building.
Regarding Claim 10
The combination of Fridman and Del Pero establishes the method of Claim 1, which is the basis for Claim 10.
Claim Limitations Not Explicitly Taught by Fridman or Del Pero
further comprising processing the representative vehicle paths to identify one or more sections of the sequence of road segments as potentially hazardous.
Fridman teaches that the stored target trajectories "may be continuously updated (e.g., averaged) with new trajectories received from other vehicles" ([0349]) and that the server may identify from received data conditions such as "a temporary lane closure setup" or "a pedestrian in the road" and modify the stored trajectories accordingly ([0276]). Fridman does not, however, teach processing the representative paths to identify sections of the road-segment sequence as potentially hazardous. Del Pero determines segment-lane and junction geometry but adds nothing to this limitation.
Disclosure by Fowe
Fowe teaches:
further comprising processing the representative vehicle paths to identify one or more sections of the sequence of road segments as potentially hazardous.
"partitioning historical probe data into clusters based on their lateral positional indicators." [0055]
"If the absolute value of an offset (e.g., difference) between any pair of historical and subject lateral positional indicators... equals or exceeds a closure threshold, example embodiments... may determine at least one lane of the segment is closed." [0071]
"Example embodiments may determine a segment(s), or series thereof, that includes a lane closure and/or shifting, as illustrated by the graphics 800, such as illustrated by indicators of cones or other barricades... The label 810 indicates a segment for which a shifted lane is detected... Label 812 indicates a segment for which a closed lane is detected." [0091]
"the lane statuses may be used for any other means, such as making predictions regarding traffic speeds or backups... if example embodiments determine a lane closure, apparatus 20 may further predict related traffic problems or slowdowns such that drivers are re-routed, possibly prior to reaching the affected segment." [0092]
Rationale: Fowe expressly identifies particular segments, and series of contiguous segments, of a road as exhibiting a lane closure or lane shift, and expressly locates those sections along a stretch of roadway ([0091], FIG. 8; see also [0044], a "plurality of contiguous segments as a strand"). As to "potentially hazardous," Fowe does not use that term; the characterization is applied under the broadest reasonable interpretation. A section of roadway at which a travel lane is closed or laterally shifted, marked by cones or barricades, for which approaching drivers are alerted and re-routed to avoid related traffic problems ([0091]–[0092]), is a section presenting a potential hazard to a vehicle traveling it. Absent a definition or limiting description in the Specification requiring a narrower meaning, the broadest reasonable interpretation of "potentially hazardous" encompasses a road section having a detected lane closure or lane shift, associated with construction barricades, and for which approaching drivers are warned or re-routed.
Rationale as to the recited causal relationship: The claim requires that the identification be made by processing the representative vehicle paths. Fowe's identification is made by comparing current lateral positional indicators against a historical baseline defined relative to a reference line ([0055], [0071]), and Fowe expressly permits that reference line to be supplied from outside its own probe statistics: the center line vector "may additionally or alternatively be identified based on map data and/or any other means" ([0056]), "the lateral positional indicators may be determined using a different basis than the center line vector 402" ([0058]), and "other methods for determining a baseline vector and/or corresponding lateral positional indicators of probes may be contemplated" ([0061]). Fridman generates, from the same category of crowdsourced trajectory data, a lane-specific averaged representative path along the road segment ([0354]) that is continuously updated as new drives arrive ([0349]). Supplying Fridman's representative path as the baseline against which Fowe's comparison is performed means that the representative path is the operand of the detection step, and the section identified is identified by processing it.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to use the representative averaged lane paths generated in the Fridman–Del Pero system as the reference baseline in Fowe's comparison of current against historical lateral vehicle positioning, thereby identifying the road segment or contiguous road segments exhibiting a lane closure or lane shift.
Fowe expressly requires a baseline reference and expressly leaves the source of that baseline open, permitting derivation from map data or other means ([0056], [0058], [0061]). Fridman expressly produces exactly such a baseline — a lane-specific representative path averaged from historical crowdsourced drives on the same segment, maintained and updated over time ([0349], [0354]) — and expressly contemplates that its stored trajectories be revisited in light of conditions such as temporary lane closures ([0276]). A person of ordinary skill would have had reason to supply Fridman's representative path as Fowe's baseline because it is the more accurate and continuously maintained expression of normal lane travel on the segment than a baseline recomputed from the probe spread alone, and because Fridman's model is already built and updated on the same server infrastructure that would perform the comparison. The combination preserves each element's function and predictably localizes, along the sequence of road segments, those sections at which current travel departs from the representative path by more than the disclosed threshold.
Regarding Claim 11
Disclosure by Fridman
Fridman discloses:
A non-transitory computer-readable storage medium storing software comprising instructions which, when executed on a processing system, cause the processing system to carry out a method of determining representative vehicle paths along a sequence of road segments of a road network,
"Server 1230 may include at least one non-transitory storage medium 2010, such as a hard drive, a compact disc, a tape, etc." [0343]
"Memory 2015 may be a non-transitory memory, such as a flash memory, a random access memory, etc. Memory 2015 may be configured to store data, such as computer codes or instructions executable by a processor (e.g., processor 2020)." [0344]
"Server 1230 may include at least one processing device 2020 configured to execute computer codes or instructions stored in memory 2015 to perform various functions." [0345]
"Model generating module 2105 may store instructions which, when executed by processor 2020, may generate at least a portion of an autonomous vehicle road navigation model for a common road segment... processor 2020 may cluster vehicle trajectories along the common road segment 1200 into different clusters. Processor 2020 may determine a target trajectory along the common road segment 1200 based on the clustered vehicle trajectories for each of the different clusters. Such an operation may include finding a mean or average trajectory representing the clustered vehicle trajectories in each cluster." [0347]
Rationale: Express. Fridman discloses a non-transitory medium storing processor-executable instructions that, when executed, cause the system to cluster vehicle trajectories and generate a representative averaged trajectory, across the connected road segments of the model ([0246]).
accessing a plurality of vehicle traces — [0351], as mapped for Claim 1.
each vehicle trace comprising a respective sequence of geographical positions — [0244], with the rationale stated for Claim 1.
for a respective vehicle — [0279], as mapped for Claim 1.
wherein the segment-specific route index is selected from a predetermined set of one or more route indices for the road segment — [0281], as mapped for Claim 1, Fridman supplying the segment-specific lane index itself and the finite set of such indices defined by the segment's lane structure.
each segment-specific route index corresponding to a different set of possible routes along the road segment — [0350], [0215], as mapped for Claim 1.
for each of the groups of vehicle traces, processing the sequence of geographical positions of one or more vehicle traces of the group to determine a representative vehicle path for the group — [0347], [0354], as mapped for Claim 1.
along the sequence of road segments — [0246], [0356], as mapped for Claim 1.
Claim Limitations Not Explicitly Disclosed by Fridman
as the vehicle transits the sequence of road segments;
for each of the road segments of the sequence of road segments, processing each of the vehicle traces to determine at least one respective segment-specific route index for the vehicle trace,
and thereby determining, for each of the plurality of vehicle traces, a respective sequence of route indices;
determining a similarity-based partitioning of the plurality of sequences of route indices and thereby partitioning the plurality of vehicle traces into a plurality of groups of vehicle traces;
The qualifications stated for Claim 1 apply equally here: Fridman supplies the segment-specific route index itself ([0281]) but is not relied upon as disclosing its determination by processing the individual vehicle trace, and Fridman discloses similarity-based partitioning of traces by lane assignment ([0304], [0353]) but not partitioning performed upon sequences of route indices.
Disclosure by Del Pero
Del Pero discloses each of the above limitations as mapped for Claim 1 — [0014] and [0177] (origin and destination lanes on different segments of the road network); [0073]–[0074] (per-segment and per-node processing throughout the network); [0100], [0113], [0175] and [0156] (determining the segment lane associated with an individual trajectory by processing that trajectory, and identifying it by its lane identifier); [0165] and [0175] ("an ordered sequence of segment lane identifiers"); and [0180]–[0181] (sorting the trajectory population by ordered segment-lane combination) — and further discloses the medium and processor architecture in which they are carried out:
"the disclosed technology may take the form of a non-transitory computer-readable medium comprising program instructions stored thereon that are executable to cause a computing system to carry out the functions of the aforementioned method." [0016]
Rationale: Express. Del Pero's operations are themselves disclosed as instructions stored on a non-transitory medium, confirming the compatibility of the two references' implementations.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to configure the stored road-model-generation instructions of Fridman's server to represent the lane assignments of each vehicle trajectory using Del Pero's ordered segment-lane identifiers and to perform Fridman's lane-assignment similarity clustering upon those ordered sequences. The rationale is as set forth for Claim 1, with the additional observation that both references expressly implement their operations as program instructions stored on a non-transitory medium and executed by a processor (Fridman [0344]–[0345]; Del Pero [0016]), so no modification of either implementation architecture is required.
Regarding Claim 12
The combination of Fridman and Del Pero establishes the medium of Claim 11, which is the basis for Claim 12.
Claim Limitations Not Explicitly Disclosed by Fridman or Del Pero
the method comprising, for each vehicle trace, determining a respective lateral displacement value for all or a subset of the geographical positions in the sequence of geographical positions, the lateral displacement value indicating a lateral displacement of the geographical position relative to a reference route along the sequence of road segments, and thereby determining, for each of the plurality of vehicle traces, a respective sequence of lateral displacement values.
The qualification stated for Claim 2 applies: Fridman's disclosed offset amounts ([0215]–[0216]) are navigation offsets relative to a stored target trajectory and are not relied upon as a lateral displacement determined for a geographic position of a collected trace; Del Pero's time-sequences of pose values ([0092]) are not lateral displacement values.
Disclosure by Fowe
Fowe discloses the entire limitation, at [0044], [0045], [0056], and [0058], with the rationale set out for Claim 2.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to configure the stored instructions of the Fridman–Del Pero system to calculate Fowe's lateral positional indicator for the successive geographic positions of each vehicle trace and to retain those values as a respective per-trace sequence. The rationale is as set forth for Claim 2.
Regarding Claim 13
The combination of Fridman, Del Pero, and Fowe establishes the medium of Claim 12, which is the basis for Claim 13.
Disclosure by Fridman
Fridman discloses:
the method comprising determining the reference route by processing all or a subset of the plurality of vehicle traces to calculate an average vehicle trace, wherein the reference route is, or follows, the average vehicle trace.
"In each cluster... trajectories may be averaged to obtain a target trajectory associated with the specific cluster... The averaged trajectory may be a target trajectory associate[d] with a specific lane." [0354]
"navigation based on the target trajectory may include a determined amount of offset to be maintained relative to the location of the target trajectory." [0216]
Rationale: Express, as set out for Claim 3.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to configure the medium of Claim 12 such that Fridman's averaged clustered trajectory supplies the reference line relative to which Fowe's lateral positional indicators are calculated. The rationale is as set forth for Claim 3, including Fowe's express invitation at [0056], [0058], and [0061] to derive its baseline vector from map data or other means.
Regarding Claim 14
The combination of Fridman, Del Pero, and Fowe establishes the medium of Claim 12, which is the basis for Claim 14.
Disclosure by Del Pero
Del Pero discloses:
wherein the method comprises, for each of the road segments of the sequence of road segments, processing each of the sequences of lateral displacement values to determine the respective segment-specific route index for each vehicle trace. — [0073]–[0074], [0100], [0105], [0113], [0156], and [0175], with the rationale set out for Claim 4, Del Pero supplying every step of the recited determination other than the identity of the values processed.
Limitation Remaining After Fridman and Del Pero
processing each of the sequences of lateral displacement values, insofar as it requires the values processed to be lateral displacement values relative to a reference route.
Disclosure by Fowe
Fowe discloses:
processing each of the sequences of lateral displacement values — [0056] and [0058], with the rationale set out for Claim 4. Fowe is relied upon only for the identity and form of the values processed and not for any correspondence between its clusters and the lanes of the segment (see [0059]).
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to configure the stored instructions to express the per-trajectory positional values that Del Pero derives at each sampling position along a road segment as Fowe's lateral displacement values, such that Del Pero's disclosed clustering and lane-association process determines the trace's segment-specific route index from that trace's sequence of lateral displacement values. The reasoning is as set forth for Claim 4.
Regarding Claim 15
The combination of Fridman and Del Pero establishes the medium of Claim 11, which is the basis for Claim 15.
Disclosure by Fridman
Fridman discloses:
the method comprising, for each road segment of the sequence of road segments, determining the set of segment-specific route indices by grouping the vehicle traces through the road segment into one or more road-segment clusters, — [0304], [0353], with Del Pero [0073]–[0074] supplying the per-segment recitation as mapped for Claim 1.
and assigning a different segment-specific route index to each road-segment cluster of vehicle traces. — [0354], [0281], as PHOSITA-obvious for the reasons set out for Claim 5.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to configure Fridman's stored instructions to label each lane-based trajectory cluster with the corresponding segment-lane index in the identifier form taught by Del Pero ([0156], [0165]). The rationale is as set forth for Claim 5.
Regarding Claim 16
The combination of Fridman and Del Pero establishes the medium of Claim 11, which is the basis for Claim 16.
Disclosure by Fridman
Fridman discloses:
wherein the predetermined set of one or more route indices for each road segment is a respective set of one or more lane indices corresponding to lanes of the respective road segment. — [0281], with the rationale set out for Claim 6.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to implement the route indices of Claim 11 as lane indices of the respective road segment. The rationale is as set forth for Claims 1 and 6.
Regarding Claim 17
Disclosure by Fridman
Fridman discloses:
A processing system comprising: one or more processors;
"Server 1230 may include at least one processing device 2020 configured to execute computer codes or instructions stored in memory 2015 to perform various functions." [0345]
Rationale: Express. "At least one processing device" satisfies "one or more processors."
and memory storing software for execution by the one or more processors
"server 1230 may include a memory 2015... Memory 2015 may be configured to store data, such as computer codes or instructions executable by a processor (e.g., processor 2020), map data..., the autonomous vehicle road navigation model, and/or navigation information received from vehicles." [0344]
Rationale: Express.
to carry out a method of determining representative vehicle paths along a sequence of road segments of a road network,
"Model generating module 2105 may store instructions which, when executed by processor 2020, may generate at least a portion of an autonomous vehicle road navigation model for a common road segment... Processor 2020 may determine a target trajectory along the common road segment 1200 based on the clustered vehicle trajectories for each of the different clusters." [0347]
Rationale: Express, in combination with [0246] and [0356] for the road-segment sequence.
The remaining limitations of the recited method — accessing a plurality of vehicle traces ([0351]); each vehicle trace comprising a respective sequence of geographical positions ([0244]); for a respective vehicle ([0279]); wherein the segment-specific route index is selected from a predetermined set of one or more route indices for the road segment ([0281]); each segment-specific route index corresponding to a different set of possible routes along the road segment ([0350], [0215]); for each of the groups of vehicle traces, processing the sequence of geographical positions of one or more vehicle traces of the group to determine a representative vehicle path for the group ([0347], [0354]); and along the sequence of road segments ([0246], [0356]) — are disclosed as mapped for Claim 1.
Claim Limitations Not Explicitly Disclosed by Fridman
as the vehicle transits the sequence of road segments;
for each of the road segments of the sequence of road segments, processing each of the vehicle traces to determine at least one respective segment-specific route index for the vehicle trace,
and thereby determining, for each of the plurality of vehicle traces, a respective sequence of route indices;
determining a similarity-based partitioning of the plurality of sequences of route indices and thereby partitioning the plurality of vehicle traces into a plurality of groups of vehicle traces;
The qualifications stated for Claim 1 apply.
Disclosure by Del Pero
Del Pero discloses each of the above at [0014], [0177], [0073]–[0074], [0100], [0113], [0156], [0165], [0175], and [0180]–[0181], as mapped for Claim 1, and discloses the corresponding hardware architecture:
"the disclosed technology may take the form of a computing system comprising at least one processor, a non-transitory computer-readable medium, and program instructions stored on the non-transitory computer-readable medium that are executable by the at least one processor such that the computing system is configured to carry out the functions of the aforementioned method." [0015]
Rationale: Express, and confirms that Del Pero's operations are implemented in the same processor-and-memory architecture as Fridman's.
Motivation to Combine Fridman and Del Pero
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman and Del Pero before them, to configure Fridman's processor and memory to encode the successive lane assignments of each vehicle trajectory using Del Pero's ordered segment-lane identifiers and to perform Fridman's lane-assignment-based similarity clustering upon those ordered sequences. The rationale is as set forth for Claim 1, with the additional observation that both references expressly recite a processor executing instructions stored in memory (Fridman [0344]–[0345]; Del Pero [0015]), so the combination requires no change to either hardware architecture.
Regarding Claim 18
The combination of Fridman and Del Pero establishes the system of Claim 17, which is the basis for Claim 18.
Claim Limitations Not Explicitly Disclosed by Fridman or Del Pero
the method comprising, for each vehicle trace, determining a respective lateral displacement value for all or a subset of the geographical positions in the sequence of geographical positions, the lateral displacement value indicating a lateral displacement of the geographical position relative to a reference route along the sequence of road segments, and thereby determining, for each of the plurality of vehicle traces, a respective sequence of lateral displacement values.
The qualification stated for Claim 2 applies.
Disclosure by Fowe
Fowe discloses the entire limitation at [0044], [0045], [0056], and [0058], with the rationale set out for Claim 2.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to configure the processing system of Claim 17 to calculate Fowe's lateral positional indicators for the successive geographic positions of each vehicle trace and to retain those values as a respective per-trace sequence. The rationale is as set forth for Claim 2.
Regarding Claim 19
The combination of Fridman, Del Pero, and Fowe establishes the system of Claim 18, which is the basis for Claim 19.
Disclosure by Fridman
Fridman discloses:
the method comprising determining the reference route by processing all or a subset of the plurality of vehicle traces to calculate an average vehicle trace, wherein the reference route is, or follows, the average vehicle trace. — [0354] and [0216], with the rationale set out for Claim 3.
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to configure the processing system of Claim 18 such that Fridman's averaged clustered trajectory supplies the reference line against which Fowe's lateral positional indicators are calculated. The rationale is as set forth for Claim 3, including Fowe [0056], [0058], and [0061].
Regarding Claim 20
The combination of Fridman, Del Pero, and Fowe establishes the system of Claim 18, which is the basis for Claim 20.
Disclosure by Del Pero
Del Pero discloses:
wherein the method comprises, for each of the road segments of the sequence of road segments, processing each of the sequences of lateral displacement values to determine the respective segment-specific route index for each vehicle trace. — [0073]–[0074], [0100], [0105], [0113], [0156], and [0175], with the rationale set out for Claim 4, Del Pero supplying every step of the recited determination other than the identity of the values processed.
Limitation Remaining After Fridman and Del Pero
processing each of the sequences of lateral displacement values, insofar as it requires the values processed to be lateral displacement values relative to a reference route.
Disclosure by Fowe
Fowe discloses:
processing each of the sequences of lateral displacement values — [0056] and [0058], with the rationale set out for Claim 4. Fowe is relied upon only for the identity and form of the values processed and not for any correspondence between its clusters and the lanes of the segment (see [0059]).
Motivation to Combine Fridman, Del Pero, and Fowe
Therefore, given the teachings as a whole, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having Fridman, Del Pero, and Fowe before them, to configure the processing system to express the per-trajectory positional values that Del Pero derives at each sampling position along a road segment as Fowe's lateral displacement values, such that Del Pero's disclosed clustering and lane-association process determines the trace's segment-specific route index from that trace's sequence of lateral displacement values. The reasoning is as set forth for Claim 4.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OLUWABUSAYO ADEBANJO AWORUNSE whose telephone number is (571)272-4311. The examiner can normally be reached M - F (8:30AM - 5PM).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jelani Smith can be reached at (571) 270-3969. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/OLUWABUSAYO ADEBANJO AWORUNSE/Examiner, Art Unit 3662
/JELANI A SMITH/Supervisory Patent Examiner, Art Unit 3662
