Trials@uspto.gov
`571-272-7822
`
`
`Paper 28
`Date: February 12, 2018
`
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`_____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________
`
`GOOGLE LLC,
`Petitioner,
`
`v.
`
`MAKOR ISSUES & RIGHTS LTD.,
`Patent Owner.
`
`______________________
`
`Case IPR2016-01536
`Patent No. 6,615,130 B2
`__________________________________
`
`
`Before HYUN J. JUNG, BEVERLY M. BUNTING, and
`ROBERT L. KINDER, Administrative Patent Judges.
`
`BUNTING, Administrative Patent Judge.
`
`
`
`FINAL WRITTEN DECISION
`35 U.S.C. § 318(a) and 37 C.F.R. § 42.73
`
`
`
`
`
`
`
`571-272-7822
`
`
`Paper 28
`Date: February 12, 2018
`
`
`UNITED STATES PATENT AND TRADEMARK OFFICE
`_____________
`
`BEFORE THE PATENT TRIAL AND APPEAL BOARD
`
`____________
`
`GOOGLE LLC,
`Petitioner,
`
`v.
`
`MAKOR ISSUES & RIGHTS LTD.,
`Patent Owner.
`
`______________________
`
`Case IPR2016-01536
`Patent No. 6,615,130 B2
`__________________________________
`
`
`Before HYUN J. JUNG, BEVERLY M. BUNTING, and
`ROBERT L. KINDER, Administrative Patent Judges.
`
`BUNTING, Administrative Patent Judge.
`
`
`
`FINAL WRITTEN DECISION
`35 U.S.C. § 318(a) and 37 C.F.R. § 42.73
`
`
`
`
`
`
`
`
`Case IPR2016-01536
`Patent 6,615,130 B2
`
`
`I. BACKGROUND
`
`Google, LLC, (“Petitioner”),1 filed a Petition pursuant to 35 U.S.C.
`
`§§ 311–319 requesting inter partes review of claims 1–4 (the “challenged
`
`claims”) of U.S. Patent No. 6,615,130 B2 (“the ’130 patent”). Paper 2.
`
`Patent Owner, Makor Issues & Rights Ltd. (“Patent Owner”) filed a
`
`Preliminary Response. Paper 7. Upon consideration of the information
`
`presented in the Petition, we determined that there was a reasonable
`
`likelihood that Petitioner would prevail with at least one challenged claim,
`
`and instituted this trial, pursuant to 35 U.S.C. § 314(a), as to claims 1–4 of
`
`the ’130 patent. Paper 9 (“Decision on Institution” or “Dec.”).
`
`Subsequent to institution, Patent Owner filed a Patent Owner
`
`Response (Paper 14, “PO Resp.”), and Petitioner filed a Reply (Paper 16,
`
`“Reply”). We ordered (Paper 21) the parties to concurrently submit a claim
`
`construction brief addressing whether any limitation of the challenged
`
`claims is subject to § 112 ¶ 6. Papers 25, 26. A transcript of the oral
`
`hearing held on October 19, 2017 has been entered into the record as Paper
`
`27 (“Tr.”).2
`
`This Final Written Decision is entered pursuant to 35 U.S.C. § 318(a).
`
`For the reasons that follow, we conclude that Petitioner has demonstrated, by
`
`a preponderance of the evidence, that claims 1–4 of the ’130 patent are
`
`unpatentable.
`
`
`
`
`1 Petitioner submitted an updated mandatory notice indicating that Google
`Inc., changed its name to Google LLC on September 30, 2017. Paper 24.
`2 Both parties requested to present arguments collectively for IPR2016-
`01535, IPR2016-01536, and IPR2016-01537. Papers 19, 20, 22, and 27.
`
`
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`2
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`Patent 6,615,130 B2
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`A. Real Party in Interest
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`Petitioner names itself and Waze Inc. as the real parties-in-interest.
`
`Pet. 2.
`
`B. Related Proceedings
`
`The parties state that the ʼ130 patent has been asserted in Makor
`
`Issues & Rights Ltd. v. Google Inc., Case No. 1:16-cv-00100 (D. Del.). Pet.
`
`2; Paper 6, 1. Petitioner filed additional petitions challenging the
`
`patentability of both the ’130 patent and a related patent:
`
`
`
`1.
`2.
`3.
`4.
`5.
`6.
`
`
`IPR2016-01535 (U.S. Patent No. 6,480,783)
`IPR2016-01537 (U.S. Patent No. 6,615,130)
`IPR2017-00815 (U.S. Patent No. 6,480,783)
`IPR2017-00816 (U.S. Patent No. 6,480,783)
`IPR2017-00817 (U.S. Patent No. 6,480,783)
`IPR2017-00818 (U.S. Patent No. 6,615,130)
`
`C. The ʼ130 Patent (Ex. 1001)
`
`The ʼ130 patent is titled “Real Time Vehicle Guidance and Traffic
`
`Forecasting System.” Ex. 1001, (54). The ’130 patent issued on September
`
`2, 2003, from U.S. Patent Application No. 09/800,116 filed on March 6,
`
`2001, and is a continuation-in-part of application No. 09/528,134, filed on
`
`March 17, 2000. Id. at (45), (21), (22), and (63).
`
`The ’130 patent relates generally to “communication with vehicles for
`
`the purpose of supplying traffic condition information and analyzing data
`
`relating to traffic conditions.” Id. at 1:14–16. The Specification describes a
`
`vehicle guidance system, which includes the Central Traffic Unit (“CTU”)
`
`and a fleet of vehicles or Mobile Guidance Units (“MGUs”), “i.e., traveling
`
`vehicles with mobile phones connected to the communication system.” Id.
`
`at 3:27–29. Vehicle position is monitored using a wireless technology, e.g.,
`
`
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`3
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`“GSM/GPS” while the vehicle is moving, and “by concurrent measuring of
`
`their current travel times along a broad range of roads.” Id. at 3:35–36. The
`
`vehicle driver may request route guidance reflecting the fastest route to a
`
`destination, as well as an updated route based on real time traffic
`
`information as illustrated in Figure 1, reproduced below. Id. at 3:37–49.
`
`
`
`
`
`
`
`Figure 1 illustrates information exchange in the guidance system.
`
`The CTU collects traffic congestion data using the location of MGUs
`
`mounted in a fleet of vehicles traveling throughout a broad range of road
`
`systems. Id. at 6:45–49. The location data is stored “on the GSM Network
`
`Server in Multiple-GPS Locator Packet (MGLP).” Id. at 6:49–51. The CTU
`
`processes the location data, converts into travel time data, and stores the
`
`
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`4
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`Patent 6,615,130 B2
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`travel time data in the database for use as regular travel time data and current
`
`travel time data, and for use in calculating the fastest route. Id. at 6:54–57.
`
`Updating of planned routes in the CTU is accomplished using “both
`
`statistical (empirical) travel times and current travel times.” Id. at 11:6–8.
`
`The ’130 patent discloses that current travel times are utilized in the vicinity
`
`of the present vehicle location and statistical travel times elsewhere. Id. at
`
`11:20–23. The ’130 patent also discloses that geographic areas may be
`
`subdivided into subregions, referred to as zones. Id. at 11:24–31. As a
`
`vehicle enters a zone, the IMU database receives updated information
`
`pertaining to traffic load in the neighborhood. Id. at 11:33–37. Updating of
`
`relevant traffic jam information is accomplished based on local zones. Id. at
`
`11:49–50.
`
`The ’130 patent describes three techniques for determining travel time
`
`over a road segment based on factors categorized as (i) generally stable
`
`changes in road conditions, (ii) regular predictable changes in road
`
`conditions, and (iii) sudden unpredictable changes in road conditions. Ex.
`
`1001, 11:52–12:11. The stable or theoretical travel times are based on a
`
`calculation of road or section length and maximum speed allowed on the
`
`section. Id. at 11:52–67. Statistical or empirical travel times are considered
`
`better approximations to reality than theoretical travel times because factors
`
`in the second category of regular predictable changes in road conditions are
`
`taken into account. Id. at 12:28–32. The statistical or empirical travel times
`
`are averaged, transformed into empirical speed coefficients, and stored in a
`
`central database. Id. at 12:35–42. Eventually, theoretical travel times are
`
`replaced by statistical or empirical travel times. Id. To account for traffic
`
`conditions arising from sudden and unexpected circumstances, which result
`
`
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`5
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`in excessive travel times, these slowdowns “are identified and stored in the
`
`database for a limited period of time,” and utilized to provide real time
`
`capabilities. Id. at 12:51–52.
`
`Utilizing GSM/GPS or other wireless technologies, the CTU tracks
`
`the positions of MGUs and updates in real time the database of travel times
`
`for all roads. Id. at 12:57–60. The ’130 patent discloses that
`
`[i]n response to a request from a driver for a route update from
`his present position to a desired location, it calculates the desired
`fastest route by utilizing both the regular travel times along
`segments of roads and predicted current travel times found by
`using information collected from tracking routines. Thereafter,
`the route is communicated to the driver.
`
`Id. at 12:60–66.
`
`The ’130 patent discloses that rapid unpredictable changes in road
`
`conditions may be accounted for in calculating real time optimal routes. Id.
`
`at 13:36–40. As described in the ’130 patent, the guidance system
`
`maintains special data structures associated with certain road types that
`
`make it possible to store information about changed traffic conditions and
`
`use the information for predicting future traffic conditions within a short
`
`time range by using travel times of vehicles that have recently left the
`
`corresponding section in the CTU database. Id. Additionally, the ’130
`
`patent describes a method for route planning referred to as algorithm Z that
`
`“utilizes stratification of road networks into a hierarchy of layers, executes
`
`searches separately on each layer, and then combines the obtained results to
`
`produce a solution route.” Id. at 16:60–64. According to the ’130 patent,
`
`use of algorithm Z for route planning “leads to considerable reduction in
`
`search times.” Id. at 16:63–64.
`
`
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`6
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`C. Illustrative Claim
`
`Claim 1 is independent and claims 2–4 depend therefrom. Claim 1 is
`
`illustrative of the claims at issue and is reproduced below:
`
`1. A system for real time vehicle guidance and forecasting travel
`times within a predetermined travel region, the system comprising:
`central traffic unit (CTU), mobile guidance units (MGU), and
`communication system (COS)
`the COS providing wireless communications for communicating
`with client vehicles;
`the CTU operatively connected to the communications system, the
`CTU performing a computed route search based on current and
`statistical section data;
`a receiving device for collecting GPS data at predetermined time
`intervals from sample vehicles moving within the
`predetermined travel region, and operatively connected to the
`CTU;
`said CTU operatively connected to the communications system
`capable of processing in real time said GPS data and
`transforming them into appropriately structured data;
`a database suitable for storing and updating statistical data on
`traffic parameters on at least a limited number of individual
`roads as sensed by the sample vehicles;
`computational tools for automatic identification of real time traffic
`jam conditions at various locations of the individual roads by
`utilizing the sample vehicles for measuring time delays; and
`the central traffic unit further comprising:
`a map database containing digital road maps of a predetermined
`geographical region together with predetermined relevant
`data on road factors, including data on speed limits, road
`capacity, road intersections, and street directional
`designations;
`a server for processing the location data received from MGUs
`and transforming them into structured data suitable for
`storage;
`a database suitable for storing and updating statistical data on
`traffic parameters on at least a limited number of individual
`roads as sensed by the sample vehicles;
`
`
`
`7
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`a table of administrator wherein said statistical data is further
`subdivided according to time into subdivisions;
`statistical application for collecting said structured data,
`computing individual statistical travel time estimates for at
`least said limited number of individual roads, and storing the
`results in the table of administrator according to said
`subdivisions;
`statistical application for collecting structured GPS data,
`computing individual statistical travel time estimates
`(regular times) for predetermined roads, and storing the
`results, the statistical application periodically updating the
`statistical data using statistical criteria for determining
`volumes of data necessary for obtaining valid and reliable
`estimates, the estimates having a predetermined validity;
`computational tools for dividing said geographical region into a
`number of smaller geographical zones for reducing volumes
`of traffic parameter data broadcast to client vehicles;
`software for calculation of said current travel times in traffic
`congestion based on said travel time traffic updates, thereby
`minimizing reliance on vehicle speed estimates, thereby
`increasing the reliability and stability of resulting statistical
`estimates; and
`software for calculation of fastest travel routes using said
`current travel time estimates in the zones contiguous to the
`vehicle while using statistical travel times in the zones
`situated further from the vehicle.
`
`Id. at 19:31–20:34.
`
`
`
`
`
`D. Evidence Relied Upon
`
`Petitioner relies on the following references:
`
`References
`Xu
`Peterson
`Israni
`Watters
`
`
`Patents
`6,401,027 B1
`5,845,227
`5,968,109
`5,982,324
`
`Date
`June 4, 2002
`Dec. 1, 1998
`Oct. 19, 1999
`Nov. 9, 1999
`
`Exhibits
`1006
`1007
`1008
`1009
`
`8
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`Additionally, Petitioner also relies on the declaration and rebuttal
`
`declaration of Michael S. Braasch, Ph.D. (Exs. 1003, 1021) and Patent
`
`Owner relies on the declaration of Alex A. Kurzhanskiy, Ph. D (Ex. 2002).
`
`The parties rely on other exhibits as discussed below.
`
`
`
`E. Instituted Grounds of Unpatentability
`
`
`
`We instituted the instant trial based on the following grounds of
`
`unpatentability (Dec. 25):
`
`References
`
`Basis
`
`Claim(s) Challenged
`
`Xu, Peterson, Israni
`
`§ 103(a)3
`
`1, 3, and 4
`
`Xu, Peterson, Israni, and
`Watters
`
`§ 103(a)
`
`2
`
`
`
`II. ANALYSIS
`
`A. Legal Principles
`
`In inter partes reviews, petitioner bears the burden of proving
`
`unpatentability of the challenged claims, and the burden of persuasion never
`
`shifts to the patent owner. Dynamic Drinkware, LLC v. Nat’l Graphics, Inc.,
`
`800 F.3d 1375, 1378 (Fed. Cir. 2015). To prevail in this proceeding,
`
`Petitioner must support its challenge by a preponderance of the evidence. 35
`
`U.S.C. § 316(e); 37 C.F.R. § 42.1(d). Accordingly, all of our findings and
`
`conclusions are based on a preponderance of the evidence.
`
`
`3 The relevant sections of the Leahy-Smith America Invents Act (“AIA”),
`Pub. L. No. 112–29, 125 Stat. 284 (Sept. 16, 2011), took effect on March 16,
`2013. Because the application from which the ’130 patent issued was filed
`before that date, our citations to Title 35 are to its pre-AIA version.
`
`
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`A claim is unpatentable under § 103(a) if the differences between the
`
`claimed subject matter and the prior art are such that the subject matter, as a
`
`whole, would have been obvious at the time the invention was made to a
`
`person having ordinary skill in the art to which said subject matter pertains.
`
`KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). The question of
`
`obviousness is resolved on the basis of underlying factual determinations,
`
`including: (1) the scope and content of the prior art; (2) any differences
`
`between the claimed subject matter and the prior art; (3) the level of skill in
`
`the art; and (4) where in evidence, so-called secondary considerations.
`
`Graham v. John Deere Co. of Kansas City, 383 U.S. 1, 17–18 (1966).
`
`We analyze the following ground based on obviousness in accordance
`
`with the above-stated principles.
`
`
`
`B. Level of Ordinary Skill in the Art
`
`In determining the level of ordinary skill in the art, various factors
`
`may be considered, including the “type of problems encountered in the art;
`
`prior art solutions to those problems; rapidity with which innovations are
`
`made; sophistication of the technology; and educational level of active
`
`workers in the field.” In re GPAC, Inc., 57 F.3d 1573, 1579 (Fed. Cir. 1995)
`
`(citation omitted). In that regard, Petitioner’s expert, Dr. Braasch, testifies
`
`that a person of ordinary skill in the art
`
`would have had a combination of experience and education in
`electrical engineering and navigation systems. This typically
`would consist of a minimum of a bachelor degree in electrical
`engineering or a related engineering field plus 2-5 years of
`work and/or research experience in the field of electrical
`engineering and its subfield of navigation systems.
`
`
`
`
`10
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`Ex. 1003 ¶ 20. Patent Owner does not opine on the level of ordinary skill in
`
`the art. See generally PO Resp.
`
`As such, we adopt generally Petitioner’s assessment of a person of
`
`ordinary skill in the art. Namely, we find that the person of ordinary skill in
`
`the art would have (1) a bachelor of science in electrical engineering or a
`
`related engineering field, and (2) 2-5 years of experience in the field of
`
`navigation systems.
`
`
`
`C. Claim Construction
`
`The Board interprets claims of an unexpired patent using the broadest
`
`reasonable construction in light of the specification of the patent in which
`
`they appear. See 37 C.F.R. § 42.100(b); In re Cuozzo Speed Techs., LLC,
`
`793 F.3d 1268, 1278 (Fed. Cir. 2015) (“We conclude that Congress
`
`implicitly approved the broadest reasonable interpretation standard in
`
`enacting the AIA”), aff’d, Cuozzo Speed Techs., LLC v. Lee, 136 S. Ct. 2131
`
`(2016); Office Patent Trial Practice Guide, 77 Fed. Reg. 48,756, 48,766
`
`(Aug. 14, 2012). Under the broadest reasonable interpretation standard, and
`
`absent any special definitions, claim terms are given their ordinary and
`
`customary meaning, as would be understood by one of ordinary skill in the
`
`art in the context of the entire disclosure. In re Translogic Tech. Inc., 504
`
`F.3d 1249, 1257 (Fed. Cir. 2007). Any special definitions for claim terms or
`
`phrases must be set forth with reasonable clarity, deliberateness, and
`
`precision. In re Paulsen, 30 F.3d 1475, 1480 (Fed. Cir. 1994). In the
`
`absence of such a definition, limitations are not to be read from the
`
`specification into the claims. See In re Van Geuns, 988 F.2d 1181, 1184
`
`(Fed. Cir. 1993).
`
`
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`Petitioner proposes constructions for the claim terms “GPS data” (Pet.
`
`7–8); “computational tools for dividing said geographical region into a
`
`number of smaller geographical zones for reducing volumes of traffic
`
`parameter data broadcast to client vehicles” (id. at 8); and “software for
`
`calculation of said current travel times in traffic congestion based on said
`
`travel time traffic updates, thereby minimizing reliance on vehicle speed
`
`estimates; thereby increasing the reliability and stability of resulting
`
`statistical estimates” (id. at 9).
`
` In our Decision on Institution, we determined that express
`
`construction of these terms was not necessary. Dec. 10 (citing Vivid Techs.,
`
`Inc. v. Am. Sci. & Eng’g, Inc., 200 F.3d 795, 803 (Fed. Cir. 1999) (“only
`
`those terms need be construed that are in controversy, and only to the extent
`
`necessary to resolve the controversy”)).
`
`Patent Owner does not challenge Petitioner’s proposed constructions
`
`for these terms in its Patent Owner Response. PO Resp. 4–7. Instead,
`
`Patent Owner proposes a construction for “traffic jam” as “an abnormal
`
`slowdown or bottleneck – one that is worse than a statistically computed,
`
`regular travel time on a section of a route. Id. at 4. Petitioner disputes this
`
`construction, but does not proffer its own interpretation. Pet. Reply. 1–8;
`
`Tr. 10:15–17.
`
`In addition, Petitioner asserts that some claim elements “recite purely
`
`functional software untethered from any tangible medium” and may be
`
`subject to construction under 35 U.S.C. § 112, ¶ 6, but does not otherwise
`
`identify these claim terms or proffer a construction. Pet. 10. Based on this
`
`assertion, we requested that the parties submit additional claim construction
`
`briefing as to whether claim terms such as “receiving device for,”
`
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`“computational tools for automatic identification of real time traffic jam
`
`conditions,” “statistical application for collecting structured GPS data,” and
`
`“statistical application for collecting said structured data” could potentially
`
`fall within the realm of § 112 ¶ 6. Paper 21. Specifically, whether
`
`“receiving device for,” “computational tools for,” and “statistical application
`
`for” could potentially be “nonce” words––serving the same purpose of
`
`“means.” Id. at 4–6. The parties each submitted briefing (Papers 25, 26).
`
`Petitioner argues that we need not reach the § 112 ¶ 6 issue because such
`
`determination would have no effect in resolving this controversy. Paper 25,
`
`8. Patent Owner argues that none of these terms “contains the word
`
`‘means,’ and thus none of the terms carry a presumption that 35 U.S.C.
`
`§ 112 ¶ 6 may apply.” Paper 26, 2. Having reviewed the parties’ additional
`
`claim construction in light of the record developed during trial, we agree that
`
`construction of these terms is not necessary to resolve the present
`
`controversy.
`
`Having considered the entire record, our determination regarding the
`
`obviousness of the challenged claims does not turn on the interpretation of
`
`any of the terms or limitations noted above. Thus, based on the final trial
`
`record before us, we determine that express construction of these terms is
`
`not necessary for purposes of this Final Written Decision.
`
`
`
`D. Obviousness Based on Xu, Peterson, and Israni
`
`Petitioner challenges the patentability of claims 1, 3, and 4 of the ’130
`
`patent under 35 U.S.C. § 103 as obvious based on Xu, Peterson, and Israni.
`
`Pet. 10–54. Additionally, Petitioner challenges the patentability of claim 2
`
`under 35 U.S.C. § 103(a) as obvious based on Xu, Peterson, Israni, and
`
`
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`Waters. Pet. 55–60. Petitioner relies on Xu, Peterson, Israni and Waters in
`
`the same manner as the ground based on Xu, Peterson, and Israni. Petitioner
`
`identifies the disclosures in the cited references alleged to describe the
`
`subject matter in each of the challenged claims. Pet. 10–60. Petitioner also
`
`provides an articulated reasoning with rational underpinning to support its
`
`conclusion of obviousness. Id.
`
`Patent Owner disagrees, arguing that the combination of Xu, Peterson,
`
`and Israni fails to disclose certain claim limitations. For all challenged
`
`claims, Patent Owner relies on arguments it presented with respect to claim
`
`1. PO Resp. 19. Thus, our analysis and reasoning discussed infra with
`
`respect to claim 1, applies equally to the challenges to claims 2–4.
`
`We have reviewed the parties’ contentions and supporting evidence of
`
`record in this trial. For the reasons given below, we conclude that Petitioner
`
`has demonstrated by a preponderance of the evidence that claims 1, 3, and 4
`
`would have been obvious based on Xu, Peterson, and Israni, and claim 2
`
`would have been obvious based on Xu, Peterson, Israni, and Watters. We
`
`begin our analysis with a brief summary of these references, and then
`
`address the parties’ contentions in turn.
`
`1. Xu (Ex. 1006)
`
`Xu “relates to traffic data collection and intelligent routing systems
`
`for highway vehicles and, in particular, to a system and method for remotely
`
`collecting real-time traffic data and providing traffic forecasts and travel
`
`guidance for drivers of vehicles equipped to utilize the system.” Ex. 1006,
`
`1:6–11. The Specification, in particular the Background of the Invention,
`
`states that “[t]here are several known methods for collecting traffic data.”
`
`Id. at 3:23–24. Xu goes on to describe external vehicle sensing systems used
`
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`to collect traffic volume and vehicle speed, then Xu states “a method for
`
`collecting dynamic traffic data using equipment installed in vehicles is
`
`required.” Id. at 3:47–48.
`
`Xu describes a traffic data collection system where “[e]ach vehicle 20
`
`is equipped with an in-vehicle device 21 which receives global positioning
`
`information data from [GPS] satellites 42.” Id. at 6:31–34. In-vehicle
`
`device relays road positions of the vehicle to a traffic service center (TSC).
`
`Id. at 6:40–45. As depicted in Figure 1 below, “[t]he [TSC] 60 uses the road
`
`positions of all vehicles 20 and the information obtained from the external
`
`party data sources to provide real-time road traffic conditions for the
`
`roadway system 10 and broadcasts the traffic conditions via the
`
`communication station 50.” Id. at 6:49–54.
`
`Figure 1 represents a block diagram of the remote traffic
`data acquisition and intelligent vehicle highway system.
`
`
`
`The TSC uses positions of vehicles and information obtained from the
`
`external party data sources to provide real-time road traffic conditions to
`
`vehicles, which then use the information to provide real-time optimum route
`
`
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`15
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`Patent 6,615,130 B2
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`planning. Id. at 6:50–60. Xu notes that optimal travel routes may be
`
`recommended based on either real-time or forecast traffic conditions. Id.
`
`Xu also discloses providing route planning optimization along
`
`multiple links of a route. Id. at 5:18–26. Xu further describes how abnormal
`
`traffic conditions may affect travel forecasts. Id. at 12:66–13:6. Xu states
`
`that “[i]f there is congestion on a link which is not normally congested and
`
`the congestion is completely due to traffic volume, the [TSC] receives a
`
`plurality of traffic data indicating that the link is experiencing an unusual
`
`congestion, by comparing the current traffic status with the normal traffic
`
`condition.” Id. Xu then uses the traffic data related to the unusual
`
`congestion to adjust the next traffic forecast. Id.
`
`2. Peterson (Ex. 1007)
`
`Peterson “provides a method and apparatus for supplying traffic
`
`information to users and more particularly to such a method and apparatus
`
`for assisting the users in selecting shortest elapsed time routes between
`
`various origin and destination combinations.” Ex. 1007, 1:13–17. Peterson
`
`enables vehicle tracking and management, ensuring that “routing is up to the
`
`minute, dynamic, constantly keeping track of the current traffic and
`
`recalculating the user’s route considering all changes.” Id. at 1:17–22.
`
`Peterson teaches performing route-calculations at a central computer. Id.
`
`at 9:64–10:8 (“The central computer calculates the least time route based on
`
`giving weight to sensor data in the near horizon and historical in the far
`
`horizon.”). Route travel times are estimated using current travel times for
`
`the beginning portion of the route and statistical travel times for the
`
`remaining portion of the trip. Id. Peterson describes that “[g]enerally, the
`
`most accurate predictor of elapsed time now is the sensed velocities; two
`
`
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`16
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`Patent 6,615,130 B2
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`hours from now the probability based most accurate velocity is one hundred
`
`percent historical patterns.” Id.
`
`3. Israni (Ex. 1008)
`
`
`
`Israni discloses a method and system for storage of geographic data on
`
`a physical storage media for use by a navigation application. Ex. 1008, [57].
`
`The geographic data is divided into parcels. Id.
`
`4. Watters (Ex. 1009)
`
`Watters relates to combining GPS technology and cellular technology
`
`to calculate position. Ex. 1009, Abstract.
`
`5. Discussion
`
`a. Claim 1
`
`We previously instructed Patent Owner that “any arguments for
`
`patentability not raised in the [Patent Owner Response] will be deemed
`
`waived.” Paper 10, 6; see also 37 C.F.R. § 42.23(a) (“Any material fact not
`
`specifically denied may be considered admitted.). Additionally, the Board’s
`
`Patent Trial Practice Guide states that the Patent Owner Response “should
`
`identify all the involved claims that are believed to be patentable and state
`
`the basis for that belief.” Office Patent Trial Practice Guide, 77 Fed. Reg.
`
`48,756, 48,766 (Aug. 14, 2012).
`
`With the complete trial record before us, we note that we have
`
`reviewed arguments and evidence advanced by Petitioner to support its
`
`unpatentability contentions where Patent Owner chose not to address certain
`
`limitations in its Patent Owner Response. In this regard, the record now
`
`contains persuasive arguments and evidence presented by Petitioner, many
`
`of which are unrebutted, regarding the manner in which the asserted prior art
`
`teaches corresponding limitations of the claims against which that prior art is
`
`
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`17
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`asserted. Based on the preponderance of the evidence before us, we find that
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`Petitioner presents sufficient evidence to support a finding that those
`
`limitations are disclosed by the proposed combination of Xu, Peterson, and
`
`Israni, arranged as recited in the claims. See In re Nuvasive, Inc., 841 F.3d
`
`966, 974 (Fed. Cir. 2016) (“Although the Board did not make findings as to
`
`whether any of the other claim limitations . . . are disclosed in the prior art, it
`
`did not have to: NuVasive did not present arguments about those limitations
`
`to the Board.”). The limitations that Patent Owner contests in the Patent
`
`Owner Response are addressed below.
`
`i. “Automatic Identification of Real Time Traffic Jam Conditions”
`
`Claim 1 recites in pertinent part “computational tools for automatic
`
`identification of real time traffic jam conditions at various locations of the
`
`individual roads by utilizing the sample vehicles for measuring time delays.”
`
`Ex. 1001, 19:53–56 (“automatic identification of real time traffic jam
`
`limitation”). Petitioner argues that this limitation is satisfied by the
`
`disclosure in Xu of a traffic service center that uses the road position of all
`
`vehicles to provide real time road traffic conditions (Pet. 25, (citing Ex.
`
`1006, 6:50–55)) and further that received traffic data is used “to identify
`
`congestion on a road or ‘link’” (id. at 25–26 (citing Ex. 1006, 12:66–13:6)).
`
`To demonstrate that providing real time road traffic conditions was known in
`
`the prior art, Petitioner cites the disclosure in Peterson regarding collecting
`
`“changing position data” from probe vehicles, and that the central processor
`
`“then calculates the route segment or combination of route segments
`
`providing a shortest elapsed time route between each origin-destination
`
`combination and transmits that information to the respective users.” Id. at
`
`27 (citing Ex. 1007, 3:35–50; 4:35–43; 1:13–22). According to Petitioner,
`
`
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`18
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`Peterson discloses that “the ‘central computer calculates the least time route
`
`based on giving weight to sensor [real time data] in the near horizon and
`
`historical in the far horizon.’” Id. (citing Ex. 1007, 9:48–10:10).
`
`Patent Owner argues that neither Xu nor Peterson discloses the
`
`automatic identification of real time traffic jam limitation. PO Resp. 8–16.
`
`Xu, in Patent Owner’s view, collects position data in real-time, and uses the
`
`gathered position data for future forecasting and not identification of traffic
`
`jam conditions in real time. Id. at 8 (citing Ex. 2002 ¶¶ 12–13). Patent
`
`Owner directs us to the following passage from Xu, referred to as “the Xu
`
`sentence,” asserting that this is the only citation that “can even be construed
`
`to suggest that data collected from vehicles may be used for traffic
`
`forecasting”:
`
`[t]he traffic service center 60 uses the road positions of all
`vehicles 20 and the information obtained from the external party
`data sources to provide real-time road traffic conditions for the
`roadway system 10 and broadcasts the traffic conditions via the
`communication station 50.
`
`Id. (citing Ex. 1006, 6:49–54).
`
`The crux of Patent Owner’s argument is that the Xu sentence
`
`fails to disclose how it actually ‘uses’ the static positions of the
`vehicle for real-time traffic determination – if indeed the ‘road
`positions’ are intended to be part of the determination of real-
`time road traffic conditions, rather than merely a statement of the
`geographic locus to be used for each vehicle’s report.
`
`Id. at 9 (citing Ex. 2002 ¶¶ 14–15) (emphasis added).
`
`Patent Owner understands the following passage of Xu as teaching
`
`that road positions and other sources are utilized in long-term forecasts, and
`
`external data for real-time determinations:
`
`
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`19
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`An external party interface 64 is provided to connect the external
`party data sources 70 to receive real-time information about
`weather or road conditions. The real-time information is
`processed by an external party data
`integrator 65 for
`incorporation into real-time traffic forecasts. The traffic forecasts
`are computed by a traffic forecaster 68 using the collected
`vehicle position data for normal road conditions.
`
`Id. (
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