DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Responsive to communications on 02/10/2026
Claims 1, 3-4, 6-10, 12, 15-16, and 18-20 amended
Claims 11 and 17 canceled
Claims 2, 5 and 13-14 original
Claims 21-22 new
Claims 1-10, 12-16, and 18-22 pending in application
Claims 1-10, 12-16, and 18-22 rejected
Final Action
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Response to Arguments
Response to Objections
Title was objected to for not being descriptive. The title has been changed from “Map Simulation Services” to “Map Simulation Services for Testing Map Data For Navigating Autonomous Vehicle” Applicant respectfully requests reconsideration and withdrawal of the objections in light of the amendments made by way of this response and/or the following remarks. Examiner agrees that the title is now descriptive of the applicant’s invention. Examiner withdraws the objection in light of modifications.
Disclosure was objected to for informalities. Reasons for the objection was a typo in the specifications in paragraph [0051] line two. The specification references figure "1-3 and 4A-4C4." The drawings do not contain a figure 4C 4. Applicant likely meant "4A-4C.". Applicant respectfully requests reconsideration and withdrawal of the objections in light of the amendments made by way of this response and/or the following remarks. As noted by the examiner, the typo in the specifications was corrected. Examiner withdraws the objection in light of modifications.
Regarding the use of terms is not accompanied by trademarks are copyright marks. Applicant respectfully requests reconsideration and withdrawal of the objections in light of the amendments made by way of this response and/or the following remarks. Applicant respectfully notes that the terms other than WIFI®, BLUETOOTH®, and MULTEFIRE™ are not trademarked for copyrighted terms. Examiner notes that the specifications were modified and corrected the issue for copyrighted terms. Examiner withdraws the objection in light of modifications.
Claim 1 was objected to for informalities. Reason for the objected was because claim 1 referenced "A computer implemented system" twice in the claim. Once in the preamble, and a second time as a first limitation in the body of the claim. Applicant respectfully requests reconsideration and withdrawal of the objection in light of the amendments made by way of this response. Examiner notes that the second “computer implemented system” has been removed from the claims. Examiner withdraws the objection in light of modifications.
Response to Applicant Arguments 101
Examiner does not find applicant arguments towards amended claims 1, 12, and 18 or newly added claims 21, and 22 to be persuasive,
Applicant argues against 101 rejection for the amended independent claims 1, 12, and 18. The issue that Applicant argues is that The human mind cannot mentally perform the amended claim limitations of "determining a metric for the map based on an evaluation of a vehicle planning process of the AV in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases by: executing the vehicle planning process of the AV in a computer-simulated environment configured as an empty navigation scene without other traffic participants to simulate navigation of the vehicle planning process along each of the plurality of paths corresponding to the plurality of map test cases” The rule of the MPEP 2106.04(a)(2)(III) states “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. “ The examiner maintains that determining a metric is explicitly an ”evaluation” and can therefore be performed in the mind. The examiner does not find the argument that the execution of the vehicle planning process cannot be performed in the mind convincing, that is because the claim does not outline, differentiate, or explain how this “executing the vehicle planning process” is being performed. For example, one ordinary skilled in the art would recognize in their mind that a planning process of “driving straight” would not allow the vehicle to navigate routes that involve turns. Furthermore, this execution is not limited through the determination of a “navigation failure,” since that limitation is not stated in the execution step. However, as it is understood based on the structure of the claim limitation, the ”execution of a vehicle planning process” step is performed as part of the “determination .. based on an evaluation of a vehicle planning process” Meaning, the step of “executing the vehicle planning process” is the process of gathering “the vehicle planning process of the AV” which is evaluated as part of the mental process in the “determining step”. Therefore, this limitation should and will be addressed under prong 2 analysis.
Applicant argues Even if, arguendo, the human mind can mentally assess a map (which Applicant does not admit), the human mind cannot mentally simulate the vehicle planning process of an AV in a computer-simulated environment. The rule of the MPEP 2106.04(a)(2)(III) states “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. “ The examiner does not find the argument that the simulation of the vehicle planning process cannot be performed in the mind convincing, that is because the claim does not outline, differentiate, or explain how this “simulation” is being performed. For example, one ordinary skilled in the art would recognize in their mind that a mathematic simulation, such as a node edge graphs, could be performed in the mind of one ordinarily skilled in the art. However, as it is understood based on the structure of the claim limitation, the ”execution of a vehicle planning process” step is performed as part of the “determination .. based on an evaluation of a vehicle planning process” Meaning, the step of “executing the vehicle planning process” is the process of gathering “the vehicle planning process of the AV” which is evaluated as part of the mental process in the “determining step”. Therefore, this limitation should and will be addressed under prong 2 analysis.
Applicant cites MPEP 2106.04(d)(1) as well as par 15-27 of the specifications to argue that the application as originally filed describes how the claims 1, 12, and 18 improve the ability of the AV to accurately navigate using a map. The examiner does not find this argument persuasive. The MPEP 2106.05(a)(i) states “In computer-related technologies, the examiner should determine whether the claim purports to improve computer capabilities or, instead, invokes computers merely as a tool.” The original claims as filed was directed towards determining a metric for a map, using computers as a tool to perform that function. The original claims do not tie back in the metric of the map to the improvement of an autonomous vehicle. Similarly, the newly amended claim set does not tie back in the judicial exception of determining a metric for a map to the improvement of an autonomous vehicle in navigating said map. There is nothing in the claim that limits the judicial exception of computing a metric towards a map, that the metric is actually used for an autonomous vehicle to navigate an environment. Therefore the examiner finds this argument non-persuasive.
Applicant argues that claims 1, 12, and 18 go beyond the proposed abstract idea of determining a metric for the map by listing, "determining a metric for the map based on an evaluation of a vehicle planning process of the AV in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases by: executing the vehicle planning process of the AV in a computer-simulated environment configured as an empty navigation scene without other traffic participants to simulate navigation of the vehicle planning process along each of the plurality of paths corresponding to the plurality of map test cases; categorizing reasons for navigation failures; and computing, as a metric for the map, at least one of a pass rate or a fail rate for the map, wherein the pass rate comprises a first number or percentage of the plurality of paths that the vehicle planning process successfully navigated, and wherein the fail rate comprises a second number or percentage of the plurality of paths that the vehicle planning process did not successfully navigate." Applicant argues the claims go beyond the abstract idea of “determining a metric for a map by reciting a specific implementation of how the abstract idea is implemented. Examiner finds the applicant argument towards the newly amended claims to not be persuasive. The MPEP 2106.05(e) states “When evaluating whether additional elements meaningfully limit the judicial exception, it is particularly critical that examiners consider the additional elements both individually and as a combination. When an additional element is considered individually by an examiner, the additional element may be enough to qualify as "significantly more" if it meaningfully limits the judicial exception, and may also add a meaningful limitation by integrating the judicial exception into a practical application. However, even in the situation where the individually-viewed elements do not add significantly more or integrate the exception, those additional elements when viewed in combination may render the claim eligible.” In combination, the examiner believes that the newly amended limitations do not add a meaningful limitation on the determination that was determined to be an abstract idea. As outlined above, the “execution of a vehicle planning process … simulate” is a step used to gather data to make a determination. Using a simulation to gather data, when declared broadly, does not pose a meaningful limitation to the claim since it is considered well understood and routine. For example, the MPEP 2106.05(g) gives the example “Performing clinical tests on individuals to obtain input for an equation” as an example of mere data gathering. Therefore, a step of performing a test (or in this case, executing a simulation as a ‘test’ of the map) in order to obtain data to use in an abstract idea, does not tie the exception into a practical idea. Furthermore, the MPEP s2106.05(g) also gives an example of “Testing a system for a response, the response being used to determine system malfunction.” Where it is understood that “testing a system (the navigation system) to determine a system malfunction (reason for navigation failure)” does not tie the judicial exception into a practical application or significantly more. The claim regarding “categorizing reasons for navigation failures” is a mental process of categorizing. Furthermore, the limitation of “navigation failures” does not appear in the rest of the claim, and therefore does not provide more in combination to the rest of the claims. A step of “computing” is the usage of math in making a determination. Which is a further recitation of the abstract idea. Therefore, in combination these limitations pertain to gathering data (the vehicle planning process) categorizing data (reasons for failures, which as noted do not tie into the claim effectively), and determining a metric (through a computation), which do not add a meaningful limitation to the abstract idea.
Applicant argues that the claim limitation is not directed to a generic use of a computer system Applicant cites "executing the vehicle planning process of the AV in a computer-simulated environment," "categorizing reasons for navigation failures," and "computing, as a metric for the map, at least one of a pass rate or a fail rate for the map." The rule of the MPEP 2106.05(b) states that it is important to outline “The particularity or generality of the elements of the machine or apparatus,” citing an example of a claim which “recited the particular type of antenna and included details as to the shape of the antenna and the conductors, particularly the length and angle at which they were arranged.” Furthermore “as described in MPEP § 2106.05(f), additional elements that invoke computers or other machinery merely as a tool to perform an existing process will generally not amount to significantly more than a judicial exception.” The steps of executing a simulation, categorizing reasons, and computing a metric, in reference to this claim are being performed by a generic computing device, not a particularly defined machine. Therefore, the examiner does not find this argument persuasive.
Applicant argues Claims 1, 12, and 18 recite a particular system/method that integrates the alleged abstract idea into a practical application that meaningfully limits the alleged abstract ideas by determining the metric for a map in a particular manner. Therefore, Claims 1, 12, and 18 apply or perform the alleged judicial exception in a meaningful way by linking the use of the judicial exception to a particular technological solution for determining a metric for a map. Id. at§ 2106.04(d). The MPEP 2106.04(d) outlines different rules that could coincide with the argument that the alleged judicial exception in a meaningful way by linking the use of the judicial exception to a particular technological solution for determining a metric for a map. The MPEP 2106.04(d) states different considerations that are relevant to be “An improvement in the functioning of a computer, or an improvement to other technology or technical field… Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment,” An example in the MPEP of not being sufficient to show improvement includes MPEP 2106.05(a)(II) “Gathering and analyzing information using conventional techniques and displaying the result.” As this limitation simply pertains to gathering data and analyzing it through convention means (gathering data of a vehicle planning process and computing the metric), this limitation does not improve the function of a computer or the technical field of AV. It is also worth noting that this limitation is not directed to the actual improvement of maps used by autonomous vehicles. Rather this claim is directed to a “test” process which as outlined in the rejection, contains processes which are well understood and conventional for AV testing. Furthermore, the MPEP 2106.05(h) outlines examples of field of use limitations, including “Limiting the abstract idea of collecting information, analyzing it, and displaying certain results of the collection and analysis to data related to the electric power grid” Where the examiner believes the steps in the claim can be understood as “collecting information, analyzing it, and displaying certain results” are directed to AV, and do not contain a specific method of doing so beyond what it well understood and conventional in the art.
Applicant argues that the claim limitations tie the operations to the data processing hardware's ability to execute the vehicle planning process of the AV in a computer-simulated environment. The claims, when taken as a whole, do not simply describe determining a metric for a map, but combine the step of "executing the vehicle planning process of the AV in a computer-simulated environment," "categorizing reasons for navigation failures," and "computing, as a metric for the map, at least one of a pass rate or a fail rate for the map." By this, claims 1, 12, and 18 go beyond the mere concept of determining a metric for a map. The MPEP 2106.05(f) states “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. “ The examiner maintains that the recited claim steps can be performed on generic computing devices under broadest reasonable interpretation, and that the recitations of generic computer processing hardware does not provide significantly more or apply the exception, regardless if the steps are performed tied to computer hardware. Therefore the examiner does not find this argument convincing.
Applicant argues that claims 21 and 22 are also eligible under 101. Applicant argues that claims 21 and 22 are directed to a practical application of the abstract idea. Applicant argues that the limitations "when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map." individually and/or collectively with the other recitations of the claims, represents a practical application of the abstract idea. Applicant argues Claims 21 and 22 go beyond the alleged abstract idea by reciting the practical and physical navigating of the AV along a navigation path based on the map when the fail rate satisfies the criterion. Thus, Claims 21 and 22 integrate the abstract ideas into a practical application that meaningfully limits the alleged abstract idea by navigating the AV along the navigation path using the tested map. Therefore, Claims 21 and 22 apply or use the abstract idea in a meaningful way by linking the use of the abstract idea to a particular application such that the claims as a whole are more than a drafting effort designed to monopolize the abstract idea. Id. at§ 2106.04(d). The examiner does not find this argument to be persuasive. While claims 21 and 22 are directed to an application of the judicial exception. The MPEP gives an example rule of an insignificant application MPEP 2106.05(g) of “Cutting hair after first determining the hair style”. Because claims 21 and 22 recite generically that the autonomous vehicle uses the maps generated, this mimics the example given in MPEP 2106.05(g) of “
In conclusion the examiner finds applicant arguments towards the newly amended independent claims 1, 12, and 18 not persuasive. Examiner also does not find applicant arguments towards newly added claims 21, and 22 to be persuasive. Examiner maintains 101 rejection for claims 1-10, 12-16, and 18-22 pending in application. Examiner believes that in order to overcome the 101 rejection, the claims need to be modified to better illustrate a tangible improvement to the field of AV map driving utilizing the abstract idea in a way that is not well understood in the art.
Response to Arguments Regarding 102 and 103
Applicant states that the independent claims 1, 12, and 18 have been amended to overcome the current prior art rejection. Applicant cites new limitations "executing the vehicle planning process of the AV in a computer simulated environment configured as an empty navigation scene without other traffic participants to simulate navigation of the vehicle planning process along each of the plurality of paths corresponding to the plurality of map test cases," and "computing, as a metric for the map, at least one of a pass rate or a fail rate for the map, wherein the pass rate comprises a first number or percentage of the plurality of paths that the vehicle planning process successfully navigated, and wherein the fail rate comprises a second number or percentage of the plurality of paths that the vehicle planning process did not successfully navigate."
Applicant argues While Fok describes using a simulated AV to navigate a map to test the map, Fok does not describe the newly amended limitation of "a computer-simulated environment configured as an empty navigation scene without other traffic participants." The examiner finds this argument in light of the amendments to be persuasive. While the examiner notes that Fok can make obvious an empty navigation scene (see Fig 4, 5A, and 5B which could be empty navigation scenes if other cars are not present), Fok on its own does not expressly recite that the simulated environment is an empty navigation scene. Therefore, as the scope of the claim has been changed, the examiner will introduce new mappings from existing or new references from the prior art.
Applicant argues that while Fok describes determining whether a validation test passes or fails, Fok, alone or in combination with other unrelated references such as Nayhouse and Wang, does not describe "computing, as a metric for the map, at least one of a pass rate or a fail rate for the map, wherein the pass rate comprises a first number or percentage of the plurality of paths that the vehicle planning process successfully navigated, and wherein the fail rate comprises a second number or percentage of the plurality of paths that the vehicle planning process did not successfully navigate." The examiner finds this argument to be not persuasive. Examiner believes Nayhouse makes obvious to one ordinarily skilled in the art a pass rate based on a number of paths that pass. Nayhouse teaches testing multiple lanes on a map (ie: plurality of paths) , and separately determining which lanes failed or passed in a report. See paragraphs 60 – 65. To one ordinarily skilled in the art, this makes obvious a number of paths which passed or failed. See the rejection for full mapping.
End of Response to Arguments
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 1-10, 12-16, and 18-22 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, an abstract idea, which has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception.
Claim 1
Step 1: Is the claimed invention one of the four statutory categories? :
YES. The claim recites A computer-implemented system, comprising: which is a machine.
Step 2A Prong 1, inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?":
YES. Claim 1 recites: generating, based at least in part on the information associated with the ODD, a plurality of map test cases for the maps wherein each map test case of the plurality of map test cases includes one of a plurality of paths in the geographical area;
In “The cognitive map in humans: Spatial navigation and beyond” published in 2017 by Epstein et al. (Epstein_2017), Epstein_2017 indicates in page 1504 par 1: “hippocampal and entorhinal spatial codes are used in conjunction with frontal lobe mechanisms to plan routes during navigation.” Therefore, Epstein_2017 indicates that the mechanism of planning different routes in the mind (ie: route planning) is a mental process performed in the mind of humans. Generating map test cases for a map representative of a geographical area, where each map test case includes one of a plurality of paths in a geographic area is equivalent to generating multiple paths in a geographic area, which is route planning. Epstein_2017 FIG 5: also teaches that human brain activation occurs when planning around blockades (examiner note: where a blockade in the route is information associated with an ODD. See fig 5 posted below) when planning out those routes. For instance, when planning a road trip, a couple may plan out one of a plurality of different paths of driving on a map in their geographic area. The couple may intend to test those map cases out on different days by driving those routes. The couple may intend to drive a certain route, only to find that the road was closed, and generate map cases outside that path.
“If a claim recites a limitation that can practically be performed in the human mind, with or without the use of a physical aid such as pen and paper, the limitation falls within the mental processes grouping, and the claim recites an abstract idea.” MPEP 2106.04(a)(III)(B). Since the process of route planning as outlined is a limitation that can practically be performed in the human mind, the claim recites an abstract idea.
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Epstein_2017 Figure 5:
and determining a metric for the map based on an evaluation of a vehicle planning process of the AV in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases by:
this limitation can be re-written as. “determining a metric (an evaluation) for the map (an object) based on an evaluation (an evaluation) of a vehicle planning process in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases” (information about a process).
The process of determining a metric for a map involves observing the map, evaluating the map (the map does not contain enough street lanes and does not outline all the paths in which a vehicle can drive in), and giving an opinion/ passing a judgement on what they metric should be (the metric should be mileage). The metric chosen is based off of more information in the form of an evaluation of a vehicle planning process (the vehicle was able to route properly through the map and successfully avoided detours, however, the vehicle took an inefficient path). The above limitation can be described as an evaluation of an object based on an evaluation of information about a process. The MPEP 2106.04(a)(III) defines mental processes as processes that are “performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.” Because the claim pertains to mental processes including observations, evaluations, judgements, and opinions, the claim recites an abstract idea.
categorizing reasons for navigation failures;
The MPEP 2106.04(a)(2)(III) states “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions.“ The process of categorizing is a mental process performed by humans. For instance, when having a list of navigation failures, a person ordinarily skilled in the art could categorize them into different types of failures (i.e.: traffic accidents, wrong navigation, etc.). Therefore this limitation recites an abstract idea of a mental process.
and computing, as a metric for the map, at least one of a pass rate or a fail rate for the map, wherein the pass rate comprises a first number or percentage of the plurality of paths that the vehicle planning process successfully navigated, and wherein the fail rate comprises a second number or percentage of the plurality of paths that the vehicle planning process did not successfully navigate.
The MPEP 2106.04(a)(2)(I)(C) states “A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. A mathematical calculation is a mathematical operation (such as multiplication) or an act of calculating using mathematical methods to determine a variable or number, e.g., performing an arithmetic operation such as exponentiation. There is no particular word or set of words that indicates a claim recites a mathematical calculation. That is, a claim does not have to recite the word "calculating" in order to be considered a mathematical calculation. For example, a step of "determining" a variable or number using mathematical methods or "performing" a mathematical operation may also be considered mathematical calculations when the broadest reasonable interpretation of the claim in light of the specification encompasses a mathematical calculation.” This metric under broadest reasonable interpretation is determined by taking the number of tests that pass/fail and dividing it by the total number of tests. This step is simply a mathematic calculation of determining a percentage, and further recites an abstract idea of a mathematic calculation.
Step 2A Prong 2, Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO. Claim 1 additionally recites one or more processing units; and
“Claims can recite a mental process even if they are claimed as being performed on a computer” MPEP 2106.04(a)(III)(c). The MPEP 2106.05(f)(2) states the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, the presence of one or more processing units, does not recite additional elements to integrate the claim into a practical application.
one or more non-transitory computer-readable media storing instructions that, when executed by the one or more processing units, cause the one or more processing units to perform operations, the operations comprising:
“Claims can recite a mental process even if they are claimed as being performed on a computer” MPEP 2106.04(a)(III)(c). The MPEP 2106.05(f)(2) states the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, the presence of non-transitory computer readable media, does not recite additional elements to integrate the claim into a practical application.
receiving, information associated with an operational design domain (ODD) in which an autonomous vehicle (AV) is to operate;
The MPEP 2106.05(f)(2), “states the “Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) (i.e.: ODD information) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more.” Therefore, the limitation of receiving information into a general-purpose computer implemented system does not recite additional elements to integrate the claim into a practical application. Furthermore, the additional limitation of “in which an autonomous vehicle (AV) is to operate;” is simply a field of use where the information comes from. The MPEP 2106.05(h) states “limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception (examiner note: i.e.: AV) do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application.”
obtaining a map representative of a geographical area in the ODD, wherein the map is generated based on sensor data collected by one or more AVs while operating in the ODD;
The abstract idea in the claim was determined to be determining a metric for a map. This limitation pertains to gathering data to build said map in order to perform the abstract idea of determining a metric for the map. The MPEP 2106.05(g) gives examples of insignificant extra-solution activity as Mere Data Gathering, Selecting a particular data source or type of data to be manipulated:, Insignificant application. In order to determine if this limitation could be classified as insignificant extra solution activity, the MPEP 2106.05(g)(2) considers “Whether the limitation is significant (i.e. it imposes meaningful limits on the claim such that it is not nominally or tangentially related to the invention).” This limitation does not meaningfully limit the claim, because obtaining a map for AV is related to the invention of determining a metric for a map driven by AV. Also the map generated by an AV is related to the invention as well. The MPEP 2106.05(g)(3) considers “Whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output).” All uses of the judicial exception of determining a metric for a map require that the map be first obtained. Therefore this limitation is found to be insignificant. The limitation well further be address in step 2B.
executing the vehicle planning process of the AV in a computer-simulated environment configured as an empty navigation scene without other traffic participants to simulate navigation of the vehicle planning process along each of the plurality of paths corresponding to the plurality of map test cases;
The abstract idea in the claim was determined to be determining a metric for a map. Executing the vehicle planning process is a step performed under determining a metric, where the metric is determined based on this execution. As understood under broadest reasonable interpretation, this “executing” step is a step that gathers data based on how a vehicle navigates a map, which is then used to determine the metric of the map. The MPEP 2106.05(g) gives examples of insignificant extra-solution activity as Mere Data Gathering, Selecting a particular data source or type of data to be manipulated:, Insignificant application. In order to determine if this limitation could be classified as insignificant extra solution activity, the MPEP 2106.05(g)(2) considers “Whether the limitation is significant (i.e. it imposes meaningful limits on the claim such that it is not nominally or tangentially related to the invention).” Executing a vehicle planning process of an AV in a map is related to the invention of determining a metric for a map for an AV. One example given in the MPEP 2106.05(g) of mere data gathering is “Testing a system for a response [ie: testing the vehicle planning process] , the response being used to determine system malfunction [the planning process used to determine a metric].” Therefore in light of these facts this limitation was determined to be mere data gathering.
Step 2B, does the claim recites additional elements that amount to significantly more than the judicial exception.
NO. As stated in Step 2A Prong 2, obtaining a map representative of a geographical area in the ODD, wherein the map is generated based on sensor data collected by one or more AVs while operating in the ODD;
The MPEP 2106.05(g)(1) considers Whether the extra-solution limitation is well known. In “P1-021: Map creation, monitoring and maintenance for automated driving – Literature Review” Hausler_2020, Hausler_2020 states page 46 par 4 “A HD map extends upon an enhanced digital map by recording a 3D representation of the world around the vehicle. This representation can be generated using a variety of sensors including LiDAR, Radar and Cameras. … A wide variety of companies generate HD maps for automated vehicles, ranging from small self‐driving start‐ups to large international map providers.” Where one ordinarily skilled in the art understands that it is common for a map of a vehicle to be generated based on sensor data collected by an AV. Therefore this limitation does not recite additional elements that amount to significantly more than the judicial exception.
executing the vehicle planning process of the AV in a computer-simulated environment configured as an empty navigation scene without other traffic participants to simulate navigation of the vehicle planning process along each of the plurality of paths corresponding to the plurality of map test cases;
MPEP 2106.05(g)(1) considers Whether the extra-solution limitation is well known. In “Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment” (Feng_2021), Feng_2021 states page 2 par 1 “One critical step in the development and deployment of AVs is to test and evaluate their driving intelligence, which indicates whether an AV can operate safely and efficiently without human intervention.” … page 2 par 2 “As shown in Fig. 1a, the prevailing state-of-the-art approach for AV testing uses the agent-environment framework4, through a combination of software simulation, closed-track testing, and on-road testing.” Where one ordinarily skilled in the art recognizes that it is common and well known to use a simulated process to test an AV navigation process in an environment.
Based on the above facts, the office concludes that claim 1 is not eligible under 35 USC 101.
Claim 2:
“Wherein the information associated with the ODD comprises an indication of one or more avoidance
areas in the geographical area.”
In light of the specifications, an avoidance area is interpreted as an area in which routes should not cross
into. This is a principal concept in route planning as explained in claim 1 under Epstein_2017 fig 5, where
individuals who are planning routes are able to observe a blockade and are able to process that
information to change their course. For instance, an individual planning a route would know to avoid a
route if there is a road closure. Because route planning is a process which an individual can reasonably
perform in their mind, this claim recites an additional abstract idea. This claim does not apply the
exception to a practical application nor does it apply significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 3
The computer-implemented system of claim 2, wherein the generating the plurality of map test cases comprises: determining the plurality of paths in a portion of the geographical area outside of the one or more avoidance areas.
As stated above in claim 2, determining paths that fall outside avoidance areas is a mental process relating to the process of route navigation. For instance, when planning multiple routes to go to work, an individual may cross certain routes off after determining that there is a road closure, or further determine new paths that avoid the avoidance area. See Epstein_2017 figure 5. claim 3 does not recite any further additional elements so it does not integrate the judicial exception into a practical application nor does it have additional elements that amount to significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 4
The computer-implemented system of claim 1, wherein the generating the plurality of map test cases comprises: iterating through a plurality of traffic links in the geographical area to determine the plurality of paths, the iterating comprising filtering out one or more un-routable traffic links in the geographical area.
Epstein_2017 figure 5 depicts a bread-first search iterative approach for route planning in the mind. Iterating through a plurality of traffic links to determine the plurality of paths falls under the concept of route planning. When planning a route, an individual may use an iterative process of looking at the different streets, stops, and intersections to see all the possible paths he can take. This can be done with a map and pen and paper, where the individual can then cross out whichever traffic links within the paths are unrouteable. Given a small geographic area, it is reasonable for someone in their mind to imaging all the plurality of traffic links for the paths they could take (See Epstein_2017 fig 5). This process of route planning is a mental process, that humans partake in intuitively when figuring out ways they can navigate a route from point A to B.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 5:
“wherein the plurality of traffic links has a granularity of a street, a lane, a group of streets, or a group of lanes.”
As stated in claim 4, the process of iterating through traffic links to determine the plurality of paths is the mental process of route planning. It is very intuitive that a traffic link might have a granularity of a street, lane, group of streets, or group of lanes, because a route for a car to travel on can practically only be made up of streets and lanes. Furthermore, this limitation seems to just define the term traffic link, which does not take the iterative process of iterating through those traffic links outside the realm of a mental process.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 6
The computer-implemented system of claim 1, wherein the generating the plurality of map test cases is further based on a geofence in the geographical area.
As stated previously, generating map test cases is the process of route planning, which is a mental process. The process of route planning has been performed based on a geofence, as shown in Epstein_2017 page 1509 col 1 par 3 in reference to the simulated route planning done in the mind of participants in London’s Soho street network.
The examiner recommends basing test cases on something more concrete than a geofence to significantly impact this claim. The term geofence as defined is very broad and can cover mostly every map (since all maps have boundaries). Since the limitation recited an abstract idea, it does not apply the exception to a practical application nor does it apply significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 7
The computer-implemented system of claim 1, wherein the generating the plurality of map test cases comprises: generating a graph representative of a traffic link in the geographical area, wherein the graph includes a plurality of subgraphs, each representative of a segment of the traffic link;
Generating a graph representative of a traffic link in the geographical area wherein the graph includes a plurality of subgraph, each representative of a segment of the traffic link is the process of drawing out on a map, the different streets, roads, and intersections segments (a segment of a traffic link) one must cross on their route. For instance, on a road trip, one may plan out their trip by considering the traffic link they would like to cross (in this scenario, the traffic link represents a group of streets that must be traveled). They could then break up the traffic link into subgraphs, each representing a segment of the traffic link (first we will take this road, and then afterwards take a different road). This process as described is still route planning, which can reasonably be performed in the mind and is a mental process. Since the limitation recited an abstract idea, it does not apply the exception to a practical application nor does it apply significantly more.
And determining a first path of the plurality of paths by selecting one or more connected subgraphs from the plurality of subgraphs.
After generating the graph representation of a traffic link mentally as described above, the individual planning his route could then “connect the dots” to form a first path formed by connected subgraphs. This is done by first observing the subgraphs and then passing an evaluation to choose which subgraphs he would like to take, then connecting them to form a path. This is simply determining a course, which as described, is a mental process. Since the limitation recited an abstract idea, it does not apply the exception to a practical application nor does it apply significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 8
The computer-implemented system of claim 7, wherein the selecting the one or more connected subgraphs is further based on a second subgraph of the plurality of subgraphs, the second subgraph connecting to a start or an end of the one or more connected subgraphs.
As stated in claim 7, the process of selecting one or more connected subgraphs is the mental process of determining a course for navigation. The presence of a second subgraph connected to the start or end of connected subgraphs, requires the user to observe which subgraphs are connected to the start or end of his path when making the considerations of which subgraphs to take on his route. This as described is the normal method of determining a route which is a mental process. Since the limitation recited an abstract idea, it does not apply the exception to a practical application nor does it apply significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 9
The computer-implemented system of claim 1, wherein the operations further comprise :evaluating, for a first map test case of the one or more of the plurality of map test cases, the vehicle planning process in navigating through a respective one of the plurality of paths.
This claim limitation can be rewritten as, “evaluating,
This limitation pertains to an evaluation of a vehicle planning process, where the evaluation is based on the vehicle planning process ability to navigate through a path in a map test case. This limitation can be re-written as an evaluation of a process. This is an evaluation which can reasonably be done in the mind. For example, the “vehicle planning process was good.” The MPEP 2106.04(a) defines Mental processes as “concepts performed in the human mind (including an observation, evaluation, judgment, opinion).” The examiner believes that the evaluation should be substantially limited by the applicant, so that it does not pertain to something general and broad than can be performed in the mind). Since the limitation recited an abstract idea, it does not apply the exception to a practical application nor does it apply significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 10
The computer-implemented system of claim 1, wherein the evaluation of the vehicle planning process in navigating through the one or more plurality of paths used for determining the metric for the map is based on a mode of the AV, the mode associated with at least one of a vehicle capability, a traffic rule, or an expected run time.
This claim limitation can be rewritten/understood as wherein the evaluation of the
This limitation pertains to the evaluation of the vehicle planning process for determining a metric. Which was determined in claim 1 to be a mental process as evaluations are mental processes. This limitation adds an extra constraint, that the metric is now based on a mode of the vehicle, where the mode must be either vehicle capability, traffic rule, or expected run time. Basing the metric chosen by a mental process on a “mode” is a person judging which metric is best suited for their routes. For instance, a couple planning a road trip may decide that they want their trip to be shorter, so they could base their “mode” on expected run time. MPEP 2106.04(a) defines Mental processes as “concepts performed in the human mind (including an observation, evaluation, judgment, opinion).”
Because choosing a metric based on a mode is a judgement which can reasonably be performed in the human mind, claim 10 does not recite any further additional elements so it does not integrate the judicial exception into a practical application nor does it have additional elements that amount to significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 12:
Claim 12 is effectively similar to claim 1, with the differences being that claim 12 is a method rather than a computer implemented system. Furthermore, claim 12 includes limitations that involve a “geofence” such as in claim 6. As stated in claim 6 generating map test cases is the process of route planning, which is a mental process. The process of route planning has been performed based on a geofence, as shown in Epstein_2017 page 1509 col 1 par 3 in reference to the simulated route planning done in the mind of participants in London’s Soho street network. Therefore, when a part of the abstract idea, the usage of a geofence does not take the claim outside the abstract idea. Furthermore, when introduced as additional information, the presence of a geofence is insignificant as it is related to the invention of a map, is present in all maps, and is well understood and common that maps have borders. Therefore, as stated in claims 1 and 6 this limitation is directed to an abstract idea and does not contain significantly more.
Based on the above facts, the office concludes that claim 12 is not eligible under 35 USC 101.
Claim 13:
“Wherein the map test configuration for generating the plurality of map test cases further includes an indication of a number of map test cases.”
The map test configuration was determined in claim 12 to be a mental process as it pertains to the observations and judgements people make when route planning. One judgment that can be made when route planning is how many routes should be created to test when planning a trip. All route planning endeavors inherently include a number of planned routes and therefore, simply an indication of how many map test cases should be ran in a configuration, does not meaningfully limit the claim beyond a mental process as outlined above.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 14:
“Wherein the map test configuration for generating the plurality of map test cases further includes an indication of at least one of a number of streets or a number of lanes within the geofence in the geographical area to be covered by the plurality of map test cases.”
The map test configuration was determined in claim 12 to be a mental process as it pertains to the observations and judgements people make when route planning. One judgment that can be made when route planning is what street you would like to take when planning out those routes. All route planning endeavors inherently include picking particular lanes and street when navigating their routes. For instance, a couple planning a road trip may decide that they want to cover using a particular road on one of their test routes so that they can stop in a nearby restaurant. Due to the above , this limitation does not meaningfully limit the claim beyond a mental process as outlined above.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 15
The method of claim 12, wherein the generating the plurality of map test cases comprises: iterating through at least one of a plurality of streets or a plurality of lanes within the geofence in the geographical area to determine the plurality of paths.
As stated in claim 4, Iterating through a plurality of traffic links to determine the plurality of paths falls under the concept of route planning. When planning a route, an individual may use an iterative process of looking at the different streets, stops, and intersections to see all the possible paths he can take. This can be done with a map and pen and paper, where the individual can then cross out whichever traffic links within the paths are unrouteable. Given a small geographic area within a geofence (such as within a neighborhood), it is also reasonable for someone in their mind to imaging all the plurality of traffic links for the paths they could take. This process of route planning is a mental process, that humans partake in intuitively when figuring out ways they can navigate a route from point A to B.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 16:
The method of claim 15, wherein the iterating through the at least one of the plurality of streets or the plurality of lanes: comprises filtering out at least one of an un-routable street or an un-routable lane within the geofence in the geographical area.
As stated previously, The practice of filtering out at least one of an un-routable street or lanes within a geofence is a practice done in route planning. For instance, if an individual knows that a certain street is closed for construction, he will plan his routes to avoid that street. This does not take the claim outside of a mental process as drafted
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 18:
Claim 18 is effectively similar to claim 1, with the differences being that claim 18 is a method rather than a computer implemented system. Furthermore, claim 18 limitations are effectively the same except for a slight re-ordering as written, where claim 18 states “evaluating a vehicle planning process … determining a metric by … “ while claim 1 states “determining a metric for the map based on an evaluation.” Claim 18 is rejected under 35 USC 101 for the same reasons as claim 1.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 19:The method of claim 18, wherein: the information associated with the ODD comprises an indication of one or more avoidance areas in the geographical area;
As stated previously, the information associated with an ODD is interpreted as data pertaining to the domain which the AV will operate in. “The use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general-purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. 2106.05(f)(2)” Because the additional elements in claim 18 are directed towards a general computers ordinary capacity to receive and transmit data, it does not provide significantly more.
and generating the plurality of map test cases comprises: excluding the one or more avoidance areas for all of the plurality of paths.
This limitation pertains to the application of the information received for the generating the plurality of map test cases, which was found to be the mental process of route planning. As stated previously, when route planning, individuals may exclude areas that they should avoid. Determining paths that fall outside avoidance areas is a mental process. For instance, when planning multiple routes to go to work, an individual may cross certain routes off after determining that there is a road closure, or further determine new paths that avoid the avoidance area. claim 19 does not recite any further additional elements so it does not integrate the judicial exception into a practical application nor does it have additional elements that amount to significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 20:
The method of claim 18, wherein generating the plurality of map test cases comprises: iterating through a plurality of traffic links in the geographical area to determine the plurality of paths, the iterating comprising filtering out one or more un-routable traffic links in the geographical area, the plurality of traffic links including at least one of one or more streets or one or more lanes in the geographical area.
As stated previously, iterating through a plurality of traffic links to determine the plurality of paths falls under the concept of route planning. When planning a route, an individual may use an iterative process of looking at the different streets, stops, and intersections to see all the possible paths he can take. This can be done with a map and pen and paper, where the individual can then cross out whichever traffic links within the paths are unrouteable. Given a small geographic area, it is also reasonable for someone in their mind to imaging all the plurality of traffic links for the paths they could take. This process of route planning is a mental process, that humans partake in intuitively when figuring out ways they can navigate a route from point A to B.
Furthermore as stated above, when route planning, individuals may exclude areas that they should avoid. Determining paths that fall outside avoidance areas is a mental process. For instance, when planning multiple routes to go to work, an individual may cross certain routes off after determining that there is a road closure, or further determine new paths that avoid the avoidance area.
Lastly, as stated in claim 5, It is normal that a traffic link might have a granularity of a street, lane, group of streets, or group of lanes, because a route for a car to travel on can practically only be made up of streets and lanes. Furthermore, this limitation seems to just define the term traffic link, which does not take the iterative process of iterating through those traffic links outside the realm of a mental process. claim 20 does not recite any further additional elements so it does not integrate the judicial exception into a practical application nor does it have additional elements that amount to significantly more.
Due to the findings, outlined above, the Office concludes that the claim is not eligible under 35 USC 101.
Claim 21:
Step 1: Is the claimed invention one of the four statutory categories? :
YES. The claim recites The computer-implemented system of claim 1, which is a machine.
Step 2A Prong 1, inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?":
YES. Claim 21 depends on claim 1, and thus is directed to an abstract idea.
Step 2A Prong 2, Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO. Claim 21 additionally states wherein the operations further comprise, when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map.
Determining and computing a fail rate is determined to be an abstract idea under mathematical calculation. This claim limitation, pertains to an application of the calculated failure rate criterion. The MPEP 2106.05(g) gives examples of insignificant extra-solution activity as Mere Data Gathering, Selecting a particular data source or type of data to be manipulated:, Insignificant application. The examiner believes this claim limitation to be an insignificant application of the calculated fail rate criterion. This limitations mimics the example given in MPEP 2106.05(g) of an insignificant activity “i.e. it imposes meaningful limits on the claim such that it is not nominally or tangentially related to the invention).” It is understood by one ordinarily skilled In the art that deploying a map for an AV so that the AV can navigate an environment using the map is related to the invention of creating maps for AV. Therefore, this limitation is not significant.
Step 2B, does the claim recites additional elements that amount to significantly more than the judicial exception.
NO. As stated in Step 2A Prong 2, wherein the operations further comprise, when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map.
This limitation was determined to be an insignificant application of the judicial exception. In Step 2B the MPEP 2106.05(g)(1) considers Whether the extra-solution limitation is well known. In the article “Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment” (Feng_2021). Feng_2021 states abstract “The prevailing approach tests autonomous vehicles in life-like simulations of the naturalistic driving environment.” … page 2 col 1 par 1“One critical step in the development and deployment of AVs is to test and evaluate their driving intelligence, which indicates whether an AV can operate safely and efficiently without human intervention.” Therefore, it is considered understood that prior to deploy an AV that the AV is evaluated, and a common method of doing so is by utilizing simulations of a driving environment. Where one understands the environment to be a map that the AV would be deployed in. Therefore, this limitation is considered well understood in the art.
Based on the above facts, the office concludes that claim 21 is not eligible under 35 USC 101.
Claim 22:
Step 1: Is the claimed invention one of the four statutory categories? :
YES. The claim recites The method of claim 12, which is a process
Step 2A Prong 1, inquiry "Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?":
YES. Claim 21 depends on claim 1, and thus is directed to an abstract idea.
Step 2A Prong 2, Does the claim recite additional elements that integrate the judicial exception into a practical application?
NO. Claim 21 additionally states further comprising, when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map.
Determining and computing a fail rate is determined to be an abstract idea under mathematical calculation. This claim limitation, pertains to an application of the calculated failure rate criterion. The MPEP 2106.05(g) gives examples of insignificant extra-solution activity as Mere Data Gathering, Selecting a particular data source or type of data to be manipulated:, Insignificant application. The examiner believes this claim limitation to be an insignificant application of the calculated fail rate criterion. This limitations mimics the example given in MPEP 2106.05(g) of an insignificant activity “i.e. it imposes meaningful limits on the claim such that it is not nominally or tangentially related to the invention).” It is understood by one ordinarily skilled In the art that deploying a map for an AV so that the AV can navigate an environment using the map is related to the invention of creating maps for AV. Therefore, this limitation is not significant.
Step 2B, does the claim recites additional elements that amount to significantly more than the judicial exception.
NO. As stated in Step 2A Prong 2, further comprising, when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map.
This limitation was determined to be an insignificant application of the judicial exception. In Step 2B the MPEP 2106.05(g)(1) considers Whether the extra-solution limitation is well known. In the article “Intelligent driving intelligence test for autonomous vehicles with naturalistic and adversarial environment” (Feng_2021). Feng_2021 states abstract “The prevailing approach tests autonomous vehicles in life-like simulations of the naturalistic driving environment.” … page 2 col 1 par 1“One critical step in the development and deployment of AVs is to test and evaluate their driving intelligence, which indicates whether an AV can operate safely and efficiently without human intervention.” Therefore, it is considered understood that prior to deploy an AV that the AV is evaluated, and a common method of doing so is by utilizing simulations of a driving environment. Where one understands the environment to be a map that the AV would be deployed in. Therefore, this limitation is considered well understood in the art.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 6-9, 12, 14-15, 18, and 21-22 are rejected under 35 U.S.C. 103 as being unpatentable over US12241746B2 “Systems And Methods For Automatically Generating Map Validation Tests” (Fok_2020), US20220340160A1 “SYSTEMS AND METHODS FOR SIMULATION SUPPORTED MAP QUALITY ASSURANCE IN AN AUTONOMOUS VEHICLE CONTEXT” (Nayhouse_2021), US20190317505A1 “DETERMINING DRIVING PATHS FOR AUTONOMOUS DRIVING VEHICLES BASED ON MAP DATA” (Li_2019), and US11814059B1 “Simulating Autonomous Driving Using Map Data And Driving Data” (Reschka_2019)
Claim 1:
Fok_2020 makes obvious A computer-implemented system, comprising: (col 1 lines 30-33: “a system comprises one or more physical processors programmed with computer program) one or more processing units; and (par 29: “In other embodiments, autonomous map circuit 210 can be implemented independently of the ECU. Autonomous map circuit 210 in this example includes a communication circuit 201, a processing circuit 203 (including a processor 206 and memory 208 in this example) and a power supply 212. Components of autonomous map circuit 210 are illustrated as communicating with each other via a data bus, although other communication interfaces can be included. Autonomous map circuit 210 in this example communicates with autonomous map control 205 that can be operated by the user to control the autonomous map circuit 210, for example by manual controls, voice, and the like. Processor 206 can include a GPU, CPU, microprocessor, or any other suitable processing system.“ ) one or more non-transitory computer-readable media storing instructions (col 2 lines 8-11: “a non-transitory machine-readable storage medium including instructions to) that, when executed by the one or more processing units, cause the one or more processing units to perform operations, the operations comprising: (col 1 lines 30-32: a system comprises one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, configure the system to: ).
receiving, information associated with an operational design domain (ODD) in which an autonomous vehicle (AV) is to operate; (col 1 line 32-34: “configure the system to: obtain route information identifying a route in the map for an autonomous vehicle;” Examiner notes: the claims require information “associated” with an ODD, rather than ODD itself. route information pertaining to an autonomous vehicle here is interpreted as is information associated with an ODD.)
obtaining a map representative of a geographical area in the ODD, par 5: “ In accordance with one embodiment, a method comprises: upon obtaining and/or receiving a new and/or updated map, obtaining route information identifying a route in the map for an autonomous vehicle;”)
generating, based at least in part on the information associated with the ODD, a plurality of map test cases for the maps wherein each map test case of the plurality of map test cases includes one of a plurality of paths in the geographical area; (col 1 lines 30-42: accordance with one embodiment, a system comprises one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, configure the system to: obtain route information identifying a route in the map for an autonomous vehicle; segment the route information into multiple test route subsections; identify one or more road features corresponding to one or more of the multiple test route subsections; and automatically generate one or more validation tests corresponding to the one or more of the multiple test route subsections (Examiner note: a validation test corresponding to a test route subsection is interpreted as a map test that includes one of a plurality of paths). based on a simulated autonomous vehicle traversing the one or more road features:. … col 3 lines 35-37: the route may be segmented into test route subsections according to the location of the road features.” Examiner note: The segmentation of road features according to a location in the prior art is considered by the examiner to be based on a determination using a geographical area. )
and determining a metric for the map based on an evaluation of a vehicle planning process of the AV in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases by: (Fig 3: “Automatically generate one or more validation tests corresponding to one or more of the multiple test routes subsections based on simulated autonomous vehicle traversing one of more road features (312), executing “one or more validation tests over the different ones of multiple test route subsections, (314)” determining if the “validation test(s) pass (or fail)?” (316), and either ending the tests (320) or modifying software (322). Examiner Note: determining if the validation tests pass or fail is a determination of a metric.)
executing the vehicle planning process of the AV in a computer-simulated environment
(Fig 3: “Automatically generate one or more validation tests corresponding to one or more of the multiple test routes subsections based on simulated autonomous vehicle traversing one of more road features (312), executing “one or more validation tests over the different ones of multiple test route subsections, (314)” )
and computing, as a metric for the map, at least one of a pass par 42: “In some embodiments, multiple validation tests for multiple test route subsections may be executed in parallel at 314. In some embodiments, process 300 outputs one or more simulations of the simulated autonomous vehicle traversing the route, one or more test route subsections, one or more road features, and/or other aspects of the road corresponding to the map. The simulations may be presented to a user for review. The user may determine whether one or more of the multiple validation tests pass or fail. In some embodiments, process 300 may include determining whether the one or more validation tests pass or fail, and outputting the results.”) Examiner note: Where the prior art of Fok_2020 allows a user to determine which test routes of a map pass or fail.
Fok_2020 does not expressly recite wherein the map is generated based on sensor data collected by one or more AVs while operating in the ODD;
configured as an empty navigation scene without other traffic participants
categorizing reasons for navigation failures;
and computing, as a metric for the map, at least one of a pass rate or a fail rate for the map, wherein the pass rate comprises a first number or percentage of the plurality of paths that the vehicle planning process successfully navigated, and wherein the fail rate comprises a second number or percentage of the plurality of paths that the vehicle planning process did not successfully navigate
Nayhouse_2021 however makes obvious
categorizing reasons for navigation failures; (par 50: “In scenarios in which a remote computing device (e.g., a server) performs method 600, the remote computing device performs operations to validate a quality of the entire or a portion of the HD map using AV software to simulate operations of the vehicle for traversing the lanes in the HD map. If the quality of the HD map is validated, then the remote computing device can cause operations of the vehicle to be controlled using the validated HD map. Otherwise, the remote computing device can provide a notification and/or report of the validation failure and/or reasons for the validation failure. The simulation process can be performed by the remote computing device when (i) the HD map has been generated or updated, and/or (ii) the AV software has been generated or updated.”) Examiner note: See figure 6 which makes this clearer that this validation failure refers to a navigation failure.
Fok_2020 and Nayhouse_2021 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle simulation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020 and Nayhouse_2021. The rationale for doing so would have been to follow teachings proposed in the prior art. Fok_2022 par 43 states “The new segmentation may then be tested and/or validated by steps 310-314. As such, for one or more validations tests that do not pass, the autonomous software and/or map may be modified at 322 in an attempt to correct failures before be re-tested.” In order to help correct failures in validation maps or software for testing, one ordinarily skilled in the art would recognize that identifying the reason for failure would be beneficial. Therefore, it would have been obvious to combine the testing workflow of Fok_2020 with identifying the cause of failures of Nayhouse_2021 for the benefit of identifying failures to allow a user to correct failures in validation maps or software for testing to obtain the invention as specified in the claims.
Nayhouse_2021 also makes obvious and computing, as a metric for the map, at least one of a pass rate or a fail rate for the map, wherein the pass rate comprises a first number or percentage of the plurality of paths that the vehicle planning process successfully navigated, and wherein the fail rate comprises a second number or percentage of the plurality of paths that the vehicle planning process did not successfully navigate
par 60: “ A determination is made that the vehicle cannot transverse the lane(s) (Examiner note: did not successfully navigate) in the expected manner when the vehicle did not reach the end location, faults (e.g., sensor faults and/or diagnostic faults) of one or more types occurred as the vehicle was traversing the lane(s), ride comfort was at an unacceptable level, the vehicle took an evasive or emergency maneuver to avoid an obstacle, and issues experienced while the vehicle traveled along the simulation route or path of travel were major and/or critical issues.
If so [618:YES], then the quality of the tested lane(s) is(are) deemed or otherwise considered good, acceptable, satisfactory and/or validated as shown by 620. If not [618:NO], then the quality of the lane(s) is(are) deemed or otherwise considered poor, unacceptable, unsatisfactory and/or invalidated as shown by 622. A notification in a report can be made in 622 indicating the validation failure for the respective lane(s) in the map. (Examiner note: a number of lanes that pass/fail)
Subsequent to completing 620 or 622, a determination is made as to whether all of the simulation routes or paths of travel have been evaluated. If not [624:NO], then method 600 returns to 614 so that the simulation process is repeated for a next simulation route or path of travel as shown by 627.
If so [624:YES], then the overall quality of the map is determined in 626. The map may be considered to be of a good quality, an acceptable quality, a satisfactory quality and/or a validated quality when, for example, the vehicle traversed all the lane(s) that were tested without experiencing any faults of given types or a minimal number of faults of the given type (e.g., less than X minor issues occur, where X is a threshold value determined based on historical data, and zero major or critical issues occur) and/or without having to perform a dangerous and/or emergency maneuver. The map is considered to be of a bad quality, an unacceptable quality, an unsatisfactory quality and/or invalidated quality when, for example, the vehicle was unable to traverse at least one of the lane(s) that were tested, (Examiner note: Where this further makes clear that a number of lanes that fails/passes is being recorded) experienced one or more faults of given types (e.g., more than or equal to X minor issues occur, where X is a threshold value determined based on historical data, and/or if any major or critical issues occur), and/or performed one or more emergency operations (e.g., swerved, took a sharp turn into traffic, and/or performed an emergency maneuver to avoid an obstacle).
A report and/or other information may be published in 626 indicating the determined overall quality of the map and/or quality of the lane(s). If the quality of the map is poor/unacceptable/unsatisfactory/invalidated [628:NO], then the map is discarded or the map is revised to improve its overall quality as shown by 630. The map may be revised on newly acquired sensor data (e.g., data generated by sensor(s) 462, 464, 466 of the vehicle or other vehicle(s)). Thereafter, method 600 continues with optional 632 (e.g., so that the revised map can be used to control operations of the vehicle) or 634 which will be described below.“ Examiner note: see also figure 6. Where one ordinarily skilled in the art understands that this process as proposed encompasses determining a number of paths in which the vehicle passed/failed to navigate as well as a pass/fail rate for the map.
Fok_2020 and Nayhouse_2021 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle simulation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020 and Nayhouse_2021.
The rationale for doing so would have been to follow teachings proposed in the prior art. Fok_2022 abstract states “Autonomous vehicles required accurate maps. As such, new maps may be added and/or maps map be updated frequently. Verifying these maps requires testing.” In order to test these maps, Fok_2022 tests the plurality of paths and then Fig 3 “Modify autonomous software and/or map in an attempt to correct failures” (322) if the map has a failed test. While this helps validate tests, it does not express to a user how accurate the map is. Nayhouse_2021 however in par 64 “A report and/or other information may be published in 626 indicating the determined overall quality of the map and/or quality of the lane(s).”
Therefore, it would have been obvious to combine the testing workflow of Fok_2020 with the data gathering of pass/fail rates of Nayhouse_2021 for the benefit of generating reports to indicate the quality of the maps to obtain the invention as specified in the claims.
Fok_2020 and Nayhouse_2021 do not expressly recite wherein the map is generated based on sensor data collected by one or more AVs while operating in the ODD;
configured as an empty navigation scene without other traffic participants
Li_2019 however, makes obvious wherein the map is generated based on sensor data collected by one or more AVs while operating in the ODD; (par 33: “For example, if there is no preexisting map data (e.g., there is no map and route information 311 that was previously stored in the persistence storage device 352) for the environment or geographical location/area where the autonomous vehicle 300 is currently located/travelling, the autonomous vehicle 300 may generate map data for the environment or geographical location/area based on sensor data received or processed by the perception module 302, as discussed in more detail below. The map data may be generated on the fly or while the autonomous vehicle 300 is travelling through an environment or geographical area. Based on the sensor data provided by sensor system 115 and localization information obtained by localization module 301, a perception of the surrounding environment is determined by perception module 302. The perception information may represent what an ordinary driver would perceive surrounding a vehicle in which the driver is driving. The perception can include the lane configuration (e.g., straight or curve lanes), traffic light signals, a relative position of another vehicle, a pedestrian, a building, crosswalk, or other traffic related signs (e.g., stop signs, yield signs), etc., for example, in a form of an object.”)
Fok_2020, Nayhouse_2021 and Li_2019 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle navigation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021 and Li_2019. The rationale for doing so would have been to follow a teaching proposed in the prior art. Fok_2020 teaches a workflow for validating new or updated maps for autonomous vehicles abstract “Systems and methods are provided for validating a map via automatic test generation for multiple test route subsections.” Fok_2020 also teaches the use of camera and image sensors par 28 “Sensors that might be used to detect external conditions can include, for example, sonar, radar, lidar or other vehicle proximity sensors, and cameras or other image sensors.“ Nayhouse_2021 also teaches a method of map validation with sensors, but also states in par 64 that the vehicle sensors can be used to revise an invalidated map “A report and/or other information may be published in 626 indicating the determined overall quality of the map and/or quality of the lane(s). If the quality of the map is poor/unacceptable/unsatisfactory/invalidated [628:NO], then the map is discarded or the map is revised to improve its overall quality as shown by 630. The map may be revised on newly acquired sensor data (e.g., data generated by sensor(s) “
The inventors of Fok_2020 and Nayhouse_2021 recognize the need to have a map before validating said map. The inventors similarly recognize the capability of sensor data for modifying a map. If the quality of the map proposed by Nayhouse_2021 is so poor and completely invalid (ie: empty) the inventor of Nayhouse_2021 would recognize the ability to use sensor data to generate said map. Therefore, it would have been obvious to combine map validation alongside sensor data of Fok_2020 and Nayhouse_2021 with map generation based on sensor data of Li_2019 for the benefit of validating new maps when the map is not already present in the datastore to obtain the invention as specified in the claims.
Fok_2020, Nayhouse_2021, and Li_2019 do not expressly recite configured as an empty navigation scene without other traffic participants
Reschka_2019 however, makes obvious configured as an empty navigation scene without other traffic participants (par 19: “Some aspects of the road segment 110(1) can vary. In the illustrated example, an autonomous vehicle 128 may be traveling along the drivable surface 108, e.g., in the first lane 114. Also in the illustration, an additional vehicle 130 is traveling in an opposite direction, e.g., in the second lane 116. Moreover, three parked vehicles 132 are illustrated in the parking lane 118. As will be appreciated, the presence and/or position of the autonomous vehicle 128, the additional vehicle 130, and the parked vehicles 132 may vary, and these representations are provided for example only. In other examples, more or fewer additional vehicles 130 may be present, including in the first lane 114 and/or the second lane 116. Similarly, more or fewer parked cars 132 may be present. Other objects also may be present in an environment of the first road segment 110 (1), including but not limited to pedestrians, bicyclists, skateboarders, street vendors, or the like.”) Examiner note: where the presence of the vehicles may vary implies that this simulation may occur on an empty navigation scene.
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle navigation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019. The rational for doing so would be “obvious to try.” Fok_2020 and Nayhouse_2021 teach map validation through vehicle simulation. Fok_2020 par 1: “the map validation tests may be generated based on a simulated autonomous vehicle traversing one or more road features.” And Nayhouse_2021 abstract “ simulating, by the computing device, operations of the vehicle along each route of the plurality of simulation routes in the map.” Reschka_2019 par 1 teaches “ Autonomous driving, however, requires robust computing systems capable of making split-second decisions to respond to myriad events and scenarios.” One reasonably skilled in the art appreciates that “myriad events and scenarios” includes scenarios where vehicles are both present and not present on the road. One reasonably skilled in the art also understands that roads may be empty.
Therefore, it would have been obvious to combine the map testing/generation and vehicle simulation workflow of Fok_2020, Nayhouse_2021, and Li_2019 with the varying presence of other vehicles of Rescha_2019 for the benefit of simulating and testing maps of empty road conditions to obtain the invention as specified in the claims.
Claim 6:
The computer-implemented system of claim 1,
Fok_2020 does not expressly recite wherein the generating the plurality of map test cases is further based on a geofence in the geographical area.
Nayhouse_2021 however makes obvious wherein the generating the plurality of map test cases is further based on a geofence in the geographical area.
Fig. 6 shows a method of map generation, which begins by obtaining a map (604), obtain AV software to be tested (606), optionally obtain a current location of the vehicle (608), optionally selecting a portion of the map to be quality tested based on vehicle location (610), and generate simulation paths for travel of the vehicle (612).
As already stated Nayhouse_2021 and Fok_2020 are both analogous inventions as they pertain to map simulation testing for autonomous vehicles. Nayhouse_2021 uses geofences “par 53: to select a portion of the map to be quality tested.” This is useful, as the tests can become more specific, for example “par 54: Similarly, if the vehicle software has been updated to modify a particular feature or add new feature, then the simulation route or paths of travel would include lanes only in area(s) of the map that is(are) suitable for testing the updated or new feature.” Similarly, Fok_2020 tests maps to “Col 3 lines 1-5: ensure the updated and/or new maps are compatible with the autonomous vehicle, and the autonomous vehicle is able to traverse the road features on the updated and/or new map.”
Therefore, it would have been obvious for someone ordinarily skilled in the art before the effective filing date to utilizes a geofence as described by Nayhouse_2021 to analyze a specific road or feature to ensure that the autonomous vehicle is able to traverse the road features on the new map as generated by Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019.
Claim 7:
The computer-implemented system of claim 1, wherein the generating the plurality of map test cases comprises: (see claim 1)
Fok_2020 makes obvious generating a graph representative of a traffic link in the geographical area, wherein the graph includes a plurality of subgraphs, each representative of a segment of the traffic link; and determining a first path of the plurality of paths by selecting one or more connected subgraphs from the plurality of subgraphs. col 9 line 57 – col 10 lines 8: ”FIG. 4 illustrates a map comprising route information segmented into multiple test route subsections, according to one embodiment. Map 400 may comprise a new and/or updated portion of a map. Map 400 may include route information from 402 to 404. The route information may define one or more routes for an autonomous vehicle. For example, route information may include a route from 402 to 404 comprising test route subsections 1, 2, 3, 4, 5, and/or 6. In another embodiment, route information may include a route (Examiner note: ie: a first path) from 402 to 404 comprising test route subsections 10, 9, 8, 7, and/or 6. By way of another example, route information may include a route from 402 to 404 comprising test route subsections 1, 2, 13, 7, and/or 6 . The route information may be segmented into test route subsections 1-13. Test route subsections 1-13 may be segmented based on way points A-J. In one example, way points A-I may be determined based on one or more road features present at or near way points A-J.” Examiner note: the multiple test route subsections are interpreted as subgraphs. The way points are interpreted as traffic link segments. The test route subsections 1-13 segmented based on way points A-J are interpreted as a plurality of subgraphs representative of segment of a traffic link.
Claim 8:
The computer-implemented system of claim 7,
Fok_2020 makes obvious wherein the selecting the one or more connected subgraphs is further based on a second subgraph of the plurality of subgraphs, the second subgraph connecting to a start or an end of the one or more connected subgraphs. (col 9 line 57 – col 10 lines 8: ”FIG. 4 illustrates a map comprising route information segmented into multiple test route subsections, according to one embodiment. Map 400 may comprise a new and/or updated portion of a map. Map 400 may include route information from 402 to 404. The route information may define one or more routes for an autonomous vehicle. For example, route information may include a route from 402 to 404 comprising test route subsections 1, 2, 3, 4, 5, and/or 6. In another embodiment, route information may include a route from 402 to 404 comprising test route subsections 10, 9, 8, 7, and/or 6. By way of another example, route information may include a route from 402 to 404 comprising test route subsections 1, 2, 13, 7, and/or 6 . The route information may be segmented into test route subsections 1-13. Test route subsections 1-13 may be segmented based on way points A-J. In one example, way points A-I may be determined based on one or more road features present at or near way points A-J.” Examiner note: See FIG.4. which depicts the different route subgraph(s) as well as a second subgraph connected to start or end of the one or more connected subgraphs. For example, from route 402 to 404. Connected subgraph 1,2,3,4,5,6 and subgraph 10,9,8,7,6 are both connected to the same start of the connected subgraphs.)
Claim 9:
The computer-implemented system of claim 1, wherein the operations further comprise:
Fok_2020 makes obvious evaluating, for a first map test case of the one or more of the plurality of map test cases, the vehicle planning process in navigating through a respective one of the plurality of paths. (col 9: line 35-45: “In some embodiments, multiple validation tests for multiple test route subsections may be executed in parallel at 314. In some embodiments, process 300 outputs one or more simulations of the simulated autonomous vehicle traversing the route, one or more test route subsections, one or more road features, and/or other aspects of the road corresponding to the map. The simulations may be presented to a user for review. The user may determine whether one or more of the multiple validation tests pass or fail.” Examiner note: where a determination of whether one of more validation tests passes or fail based on a simulated autonomous vehicle traversing the route is considered an evaluation of the vehicle planning process.)
Claim 12:Claim 12 is effectively similar to claim 1, with the differences being that claim 12 is a method rather than a computer implemented system. Furthermore, claim 12 includes limitations that involve a “geofence” such as in claim 6. As the claims are effectively similar, the examiner will only evaluate the minor differences for brevity.
Fok_2020 makes obvious A method comprising: (abstract “Systems and methods are provided for validating a map via automatic test generation for multiple test route subsections”)
Fok_2020 does not expressly recite receiving, a map test configuration including an indication of at least a geofence in a geographical area in which an autonomous vehicle (AV) is to operate;
obtaining a map representative of the geofence in the geographical area, wherein the map is generated based on sensor data collected by one or more AVs while operating in the geofence;
Nayhouse_2021 makes obvious receiving, a map test configuration including an indication of at least a geofence in a geographical area in which an autonomous vehicle (AV) is to operate; (Fig 6 “Optionally select a portion of the map to be quality tested based on the vehicles current location” (610)).) Examiner note: A configuration with a geofence.
obtaining a map representative of the geofence in the geographical area, Fig 6 “Optionally select a portion of the map to be quality tested based on the vehicles current location (610)“Generate simulation paths of travel for the vehicle (612), Select one of the simulation paths of travel (614), Simulate operations of the vehicle traveling along the simulation path of travel (616) “).
generating, by the computer-implemented system based on the map test configuration, a plurality of map test cases for a map representative of the geographical area wherein each map test case of the plurality of map test cases includes one of a plurality of paths within the geofence in the geographical area; (Fig 6 “Optionally select a portion of the map to be quality tested based on the vehicles current location (610)“Generate simulation paths of travel for the vehicle (612), Select one of the simulation paths of travel (614), Simulate operations of the vehicle traveling along the simulation path of travel (616) “).
As already stated Nayhouse_2021 and Fok_2020 are both analogous inventions as they pertain to map simulation testing for autonomous vehicles. Nayhouse_2021 uses geofences “par 53: to select a portion of the map to be quality tested.” This is useful, as the tests can become more specific, for example “par 54: Similarly, if the vehicle software has been updated to modify a particular feature or add new feature, then the simulation route or paths of travel would include lanes only in area(s) of the map that is(are) suitable for testing the updated or new feature.” Similarly, Fok_2020 tests maps to “Col 3 lines 1-5: ensure the updated and/or new maps are compatible with the autonomous vehicle, and the autonomous vehicle is able to traverse the road features on the updated and/or new map.”
Therefore, it would have been obvious for someone ordinarily skilled in the art before the effective filing date to utilizes a geofence as described by Nayhouse_2021 to analyze a specific road or feature to ensure that the autonomous vehicle is able to traverse the road features on the new map as generated by Fok_2020.
Nayhouse_2021 does not expressly recite wherein the map is generated based on sensor data collected by one or more AVs while operating in the geofence;
Li_2019 however makes obvious wherein the map is generated based on sensor data collected by one or more AVs while operating in the geofence;
(par 33: “For example, if there is no preexisting map data (e.g., there is no map and route information 311 that was previously stored in the persistence storage device 352) for the environment or geographical location/area where the autonomous vehicle 300 is currently located/travelling, the autonomous vehicle 300 may generate map data for the environment or geographical location/area (Examiner note: a geofence)_based on sensor data received or processed by the perception module 302, as discussed in more detail below. The map data may be generated on the fly or while the autonomous vehicle 300 is travelling through an environment or geographical area. Based on the sensor data provided by sensor system 115 and localization information obtained by localization module 301, a perception of the surrounding environment is determined by perception module 302. The perception information may represent what an ordinary driver would perceive surrounding a vehicle in which the driver is driving. The perception can include the lane configuration (e.g., straight or curve lanes), traffic light signals, a relative position of another vehicle, a pedestrian, a building, crosswalk, or other traffic related signs (e.g., stop signs, yield signs), etc., for example, in a form of an object.”)
Fok_2020, Nayhouse_2021 and Li_2019 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle navigation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021 and Li_2019. The rationale for doing so would have been to follow a teaching proposed in the prior art. Fok_2020 teaches a workflow for validating new or updated maps for autonomous vehicles abstract “Systems and methods are provided for validating a map via automatic test generation for multiple test route subsections.” Fok_2020 also teaches the use of camera and image sensors par 28 “Sensors that might be used to detect external conditions can include, for example, sonar, radar, lidar or other vehicle proximity sensors, and cameras or other image sensors.“ Nayhouse_2021 also teaches a method of map validation with sensors, but also states in par 64 that the vehicle sensors can be used to revise an invalidated map “A report and/or other information may be published in 626 indicating the determined overall quality of the map and/or quality of the lane(s). If the quality of the map is poor/unacceptable/unsatisfactory/invalidated [628:NO], then the map is discarded or the map is revised to improve its overall quality as shown by 630. The map may be revised on newly acquired sensor data (e.g., data generated by sensor(s) “
The inventors of Fok_2020 and Nayhouse_2021 recognize the need to have a map before validating said map. The inventors similarly recognize the capability of sensor data for modifying a map. If the quality of the map proposed by Nayhouse_2021 is so poor and completely invalid (ie: empty) the inventor of Nayhouse_2021 would recognize the ability to use sensor data to generate said map. Therefore, it would have been obvious to combine map validation alongside sensor data of Fok_2020 and Nayhouse_2021 with map generation based on sensor data of Li_2019 for the benefit of validating new maps when the map is not already present in the datastore to obtain the invention as specified in the claims.
Claim 14:
The method of claim 12,
Fok_2020 does not expressly recite wherein the map test configuration for generating the plurality of map test cases further includes an indication of at least one of a number of streets or a number of lanes within the geofence in the geographical area to be covered by the plurality of map test cases.
Nayhouse_2021 however makes obvious wherein the map test configuration for generating the plurality of map test cases further includes an indication of at least one of a number of streets or a number of lanes within the geofence in the geographical area to be covered by the plurality of map test cases. (Fig 6 “Optionally select a portion of the map to be quality tested based on the vehicles current location (610) “Generate simulation paths of travel for the vehicle (612), Select one of the simulation paths of travel (614), Simulate operations of the vehicle traveling along the simulation path of travel (616)”,asking“ Can the vehicle traverse the particular lane(s) in an acceptable manner? (618) ).
As already stated Nayhouse_2021 and Fok_2020 are both analogous inventions as they pertain to map simulation testing for autonomous vehicles. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020 and Nayhouse_2021. The rationale for doing so would have been to follow a teaching proposed in the prior art. Fok_2020 teaches testing road features such as par 52: “The road features may correspond to one or more test route subsections. By way of example, the road features may include one or more of a lane merge (e.g., a lane ending due to a road narrowing, a lane ending and becoming a turn lane, two roads merging into one such that lanes merge, etc.), an intersection (e.g., one or more roads and/or lanes meeting, with or without a stop sign and/or light), a cross walk (e.g., located at an intersection, located separate from an intersection, etc.), and/or other road features.” When testing a road feature involving lanes as outlined in a map, the inventor of Fok_2020 would necessarily need to include at least a particular lane that contains that specific road feature.
Therefore, it would have been obvious for someone ordinarily skilled in the art before the effective filing date to utilize at least a particular lane as specified by Nayhouse_2021 to analyze a specific road or feature to ensure that the autonomous vehicle is able to traverse the road features on the new map as generated by Fok_2020.
Claim 15:
The method of claim 12, wherein the generating the plurality of map test cases comprises: (see claim 12)
Fok_2020 makes obvious iterating through at least one of a plurality of streets or a plurality of lanes Fig. 3 contains a flow chart. The flow chart teaches obtaining route information identifying a route in map for an autonomous vehicle (306). Segment the route into one or more subsections (310), generating validation tests corresponding to one or more route subsections based on a simulated vehicle traversing the one or more road features (312), executing validation tests over different ones of the rest route subsections (314), and if the tests fail (316), further obtaining route information (306) and repeating the process. Examiner note: this process as described is iterative process. … (col 2 lines 19-30: “In some aspects, the non-transitory machine-readable storage medium may include instructions to segment multiple test route subsections based on way points. Moreover, the way points may be defined by user input and/or based on one or more road features. In some embodiments, the non-transitory machine-readable storage medium may include instructions to automatically generate multiple validation tests for different ones of the multiple test route subsections. The multiple validation tests may be executed in parallel over the different ones of the multiple test route subsections. In some embodiments, the one or more road features may include an intersection, a lane merge, a cross walk, and/or other road features.”) Examiner note: where the road features of intersection and lane merge encompass lanes.
Fok_2020 does not expressly recite within the geofence
Nayhouse_2021 makes obvious iterating through at least one of a plurality of streets or a plurality of lanes within the geofence in the geographical area to determine the plurality of paths. (Fig 6 “Optionally select a portion of the map to be quality tested based on the vehicles current location (610) “Generate simulation paths of travel for the vehicle (612), Select one of the simulation paths of travel (614), Simulate operations of the vehicle traveling along the simulation path of travel (616)”, asking “Can the vehicle traverse the particular lane(s) in an acceptable manner? (618)” after traversing through there lanes, asking “Have all the simulated paths of travel been evaluated (624)?” and if no, going back to “Selecting one of the simulation paths for travel (614).” Examiner note: please see figure 6, this depicts an iterative process which repeats by selected paths for travel, testing the lanes within the path, and then selecting more paths of travel).
As already stated Nayhouse_2021 and Fok_2020 are both analogous inventions as they pertain to map simulation testing for autonomous vehicles. Nayhouse_2021 uses geofences “par 53: to select a portion of the map to be quality tested.” This is useful, as the tests can become more specific, for example “par 54: Similarly, if the vehicle software has been updated to modify a particular feature or add new feature, then the simulation route or paths of travel would include lanes only in area(s) of the map that is(are) suitable for testing the updated or new feature.” Similarly, Fok_2020 tests maps to “Col 3 lines 1-5: ensure the updated and/or new maps are compatible with the autonomous vehicle, and the autonomous vehicle is able to traverse the road features on the updated and/or new map.”
Therefore, it would have been obvious for someone ordinarily skilled in the art before the effective filing date to utilizes a geofence as described by Nayhouse_2021 to analyze a specific road or feature to ensure that the autonomous vehicle is able to traverse the road features on the new map as generated by Fok_2020.
Claim 18:
Claim 18 is effectively similar to claim 1, with the differences being that claim 18 is a method rather than a computer implemented system. Furthermore, claim 18 limitations are directed to “evaluating a vehicle planning process … determining a metric by … “ while claim 1 states “determining a metric for the map based on an evaluation” As the claims are effectively similar, the examiner will only evaluate the minor differences for brevity.
Fok_2020 makes obvious A method comprising: (abstract “Systems and methods are provided for validating a map via automatic test generation for multiple test route subsections”)
evaluating a vehicle planning process of the AV in navigating through one or more of the plurality of paths corresponding to one or more of the plurality of map test cases by executing the vehicle planning process in a computer-simulated environment
(Fig 3: “Automatically generate one or more validation tests corresponding to one or more of the multiple test routes subsections based on simulated autonomous vehicle traversing one of more road features (312), executing “one or more validation tests over the different ones of multiple test route subsections, (314)” ) Examiner note: Where this process as described is an evaluation of the “vehicle planning process”
determining a metric for the map by (par 42: “In some embodiments, multiple validation tests for multiple test route subsections may be executed in parallel at 314. In some embodiments, process 300 outputs one or more simulations of the simulated autonomous vehicle traversing the route, one or more test route subsections, one or more road features, and/or other aspects of the road corresponding to the map. The simulations may be presented to a user for review. The user may determine whether one or more of the multiple validation tests pass or fail. In some embodiments, process 300 may include determining whether the one or more validation tests pass or fail, and outputting the results.”) Examiner note: Where the prior art of Fok_2020 makes obvious the presence of a pass fail metric.
Fok_2020 does not expressly recite configured as an empty navigation scene without other traffic participants
Reschka_2019 however, makes obvious configured as an empty navigation scene without other traffic participants (par 19: “Some aspects of the road segment 110(1) can vary. In the illustrated example, an autonomous vehicle 128 may be traveling along the drivable surface 108, e.g., in the first lane 114. Also in the illustration, an additional vehicle 130 is traveling in an opposite direction, e.g., in the second lane 116. Moreover, three parked vehicles 132 are illustrated in the parking lane 118. As will be appreciated, the presence and/or position of the autonomous vehicle 128, the additional vehicle 130, and the parked vehicles 132 may vary, and these representations are provided for example only. In other examples, more or fewer additional vehicles 130 may be present, including in the first lane 114 and/or the second lane 116. Similarly, more or fewer parked cars 132 may be present. Other objects also may be present in an environment of the first road segment 110 (1), including but not limited to pedestrians, bicyclists, skateboarders, street vendors, or the like.”) Examiner note: where the presence of the vehicles may vary implies that this simulation may occur on an empty navigation scene.
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 (see claim 1 for mapping with other references) are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle navigation. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019. The rational for doing so would be “obvious to try.” Fok_2020 and Nayhouse_2021 teach map validation through vehicle simulation. Fok_2020 par 1: “the map validation tests may be generated based on a simulated autonomous vehicle traversing one or more road features.” And Nayhouse_2021 abstract “ simulating, by the computing device, operations of the vehicle along each route of the plurality of simulation routes in the map.” Reschka_2019 par 1 teaches “ Autonomous driving, however, requires robust computing systems capable of making split-second decisions to respond to myriad events and scenarios.” One reasonably skilled in the art appreciates that “myriad events and scenarios” includes scenarios where vehicles are both present and not present on the road. One reasonably skilled in the art also understands that roads may be empty.
Therefore, it would have been obvious to combine the map testing/generation and vehicle simulation workflow of Fok_2020, Nayhouse_2021, and Li_2019 with the varying presence of other vehicles of Rescha_2019 for the benefit of simulating and testing maps of empty road conditions to obtain the invention as specified in the claims.
Claim 21:
The computer-implemented system of claim 1, wherein the operations further comprise, (see claim 1)
Fok_2020 does not expressly recite when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map.
Nayhouse_2021 however, makes obvious when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map. (par 51: In scenarios in which method 600 is performed by the vehicle's on-board computing device, the on-board computing device performs operations to validate the quality of the entire HD map or only a portion of the HD map that is selected based on a current location of the vehicle. If the quality of the HD map or the portion of the HD map is validated, then the on-board computing device causes operations of the vehicle to be controlled using the HD map) Examiner note: Where the examiner maps “the fail rate satisfying a criterion” to be “if the map is validated.” As the examiner understands, the fail rate encompasses a number or percentage of tests that fail. The fail rate satisfies a criterion is equivalents to the pass rate satisfying a criterion. Where the pass rate and fail rate were also previously mapped to Nayhouse_2021 (see claim 1)
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle testing and simulation.
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019.
The rationale for doing so would have been to follow a teaching proposed in the prior art. Fok_2020 par 2 states that “Autonomous vehicles are capable of driving with little to no human input. Such vehicles utilize a combination of sensor input and map information, among other input, to safely navigate theft environment. Such vehicles depend on accurate maps. In order to verify the autonomous vehicle behaves reasonably given the new and/or updated maps as input, the maps need to be tested and validated. As autonomous vehicles become increasingly popular, and the geographic regions they are permitted to operate in expands, automatically validating new and updated maps becomes more important.” As implied, but not expressly stated, the invention of Fok_2020 tests maps so that autonomous vehicles can drive reasonably in any given map. Fok_2020 also tests to see if the validation tests pass and if so ends the process, where one reasonably skilled in the art understands that this means that the test succeeds and will guide an autonomous vehicle. Fok_2020 also states that maps “need to be validated.” Nayhouse_2021 expressly recites a validation process where after validation the map is used to guide an autonomous vehicle.
Therefore, it would have been obvious to combine the workflow and map testing of Fok_2020 with deploying a map to the AV after validation of Nayhouse_2021 for the benefit of validating mapping to ensure vehicles behave reasonably given new or updated maps to obtain the invention as specified in the claims.
Claim 22:
The method of claim 12, further comprising
Fok_2020 does not expressly recite when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map.
Nayhouse_2021 however, makes obvious when the fail rate satisfies a criterion, deploying the map to the AV, wherein deploying the map to the AV causes the AV to navigate the AV in the geographical area based on the map. (par 51: In scenarios in which method 600 is performed by the vehicle's on-board computing device, the on-board computing device performs operations to validate the quality of the entire HD map or only a portion of the HD map that is selected based on a current location of the vehicle. If the quality of the HD map or the portion of the HD map is validated, then the on-board computing device causes operations of the vehicle to be controlled using the HD map) Examiner note: Where the examiner maps “the fail rate satisfying a criterion” to be “if the map is validated.” As the examiner understands, the fail rate encompasses a number or percentage of tests that fail. The fail rate satisfies a criterion is equivalents to the pass rate satisfying a criterion. Where the pass rate and fail rate were also previously mapped to Nayhouse_2021 (see claim 1)
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicle testing and simulation.
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019.
The rationale for doing so would have been to follow a teaching proposed in the prior art. Fok_2020 par 2 states that “Autonomous vehicles are capable of driving with little to no human input. Such vehicles utilize a combination of sensor input and map information, among other input, to safely navigate theft environment. Such vehicles depend on accurate maps. In order to verify the autonomous vehicle behaves reasonably given the new and/or updated maps as input, the maps need to be tested and validated. As autonomous vehicles become increasingly popular, and the geographic regions they are permitted to operate in expands, automatically validating new and updated maps becomes more important.” As implied, but not expressly stated, the invention of Fok_2020 tests maps so that autonomous vehicles can drive reasonably in any given map. Fok_2020 also tests to see if the validation tests pass and if so ends the process, where one reasonably skilled in the art understands that this means that the test succeeds and will guide an autonomous vehicle. Fok_2020 also states that maps “need to be validated.” Nayhouse_2021 expressly recites a validation process where after validation the map is used to guide an autonomous vehicle.
Therefore, it would have been obvious to combine the workflow and map testing of Fok_2020 with deploying a map to the AV after validation of Nayhouse_2021 for the benefit of validating mapping to ensure vehicles behave reasonably given new or updated maps to obtain the invention as specified in the claims.
Claims 2-5, 16, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and US20200341467A1 “TRAILER FOR AUTONOMOUS DELIVERY” (Glendenning_2020)
Claim 2:
The computer-implemented system of claim 1, wherein the information associated with the ODD (see claim 1)
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 do not expressly recite comprises an indication of one or more avoidance areas in the geographical area.
Glendenning_2020 however, makes obvious comprises an indication of one or more avoidance areas in the geographical area. (par 22: “The AV internal computing system 110 can also include a constraint service 114 (Examiner note: information associated with the ODD) to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 114 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, etc.)
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019 and Glendinning_2020 are both analogous arts as they both deal with challenges and improvements for autonomous vehicles navigation. Glendinning_2020 circumvents avoidance areas in order to “facilitate safe propulsion of the autonomous vehicle (22).” Fok_2020 teaches that the purpose of the map information is to safely navigate the environment (col 1 lines 1-20: “Such vehicles utilize a combination of sensor input and map information, among other input, to safely navigate theft environment.”)
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the invention to take the motivation of Glendinning_2020 of including constraint information for circumventing avoidance areas to promote safe propulsion with Fok_2020 map testing information in order to ensure that the autonomous vehicles safely navigate their environment after map validation so that users after map test validation do not drive in unsafe areas.
Claim 3:
The computer-implemented system of claim 2, wherein the generating the plurality of map test cases comprises: (see claim 2)
Fok_2020 makes obvious determining the plurality of paths in a portion of the geographical area (Col 1 lines 33-35: “obtain route information identifying a route in the map for an autonomous vehicle... col 9 lines 60-62: “The route information may define one or more routes for an autonomous vehicle”.
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019 do not expressly recite
Glendinning makes obvious determining((par 22: “The AV internal computing system 110 can also include a constraint service 114 (to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 114 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, (etc.)
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the invention to take the motivation of Glendinning_2020 of including constraint information for circumventing avoidance areas to promote safe propulsion with Folk_2020 determining a plurality of paths for map route generation in order to ensure that the autonomous vehicles safely navigate their environment after map validation so that users after map test validation do not drive in unsafe areas.
Claim 4:
The computer-implemented system of claim 1, wherein the generating the plurality of map test cases comprises: (see claim 1)
Fok_2020 makes obvious iterating through a plurality of traffic links in the geographical area to determine the plurality of paths, the iterating Fig. 3 contains a flow chart. The flow chart teaches obtaining route information identifying a route in map for an autonomous vehicle (306). Segment the route into one or more subsections (310), generating validation tests corresponding to one or more route subsections based on a simulated vehicle traversing the one or more road features (312), executing validation tests over different ones of the rest route subsections (314), and if the tests fail (316), further obtaining route information (306) and repeating the process. Examiner note: this process as described is iterative process. )
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 do not expressly recite comprising filtering out one or more un-routable
Glendinning_2020 makes obvious ((par 22: “The AV internal computing system 110 can also include a constraint service 114 (to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 114 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, etc.)
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and Glendenning_2020 are analogous arts, as they all pertain to autonomous vehicle navigation. It would have been obvious for a person of ordinary skill in the art before the effective filing date of the invention to take the motivation of Glendinning_2020 of including constraint information for circumventing avoidance areas to promote safe propulsion with Folk_2020 map route generation to exclude unrouteable paths in testing in order to ensure that the autonomous vehicles safely navigate their environment after map validation so that users after map test validation do not drive in unsafe areas.
Claim 5:
The computer-implemented system of claim 4,
Fok_2020 makes obvious wherein the plurality of traffic links has a granularity of a street, a lane, a group of streets, or a group of lanes. (col 2 lines 19-30: “In some aspects, the non-transitory machine-readable storage medium may include instructions to segment multiple test route subsections based on way points. Moreover, the way points may be defined by user input and/or based on one or more road features. In some embodiments, the non-transitory machine-readable storage medium may include instructions to automatically generate multiple validation tests for different ones of the multiple test route subsections. The multiple validation tests may be executed in parallel over the different ones of the multiple test route subsections. In some embodiments, the one or more road features may include an intersection, a lane merge, a cross walk, and/or other road features.”) Examiner note: an intersection and lane merge encompass a lane. )
Claim 16:
The method of claim 15, wherein the iterating through the at least one of the plurality of streets or the plurality of lanes: (See claim 15)
Fok_2020 does not expressly recite comprises filtering out at least one of an un-routable street or an un-routable lane within the geofence in the geographical area.
Glendinning_2020 makes obvious comprises filtering out at least one of an un-routable street or an un-routable lane within the geofence in the geographical area. (par 22: “The AV internal computing system 110 can also include a constraint service 114 (to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 114 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, (etc.)
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and Glendenning_2020 are analogous arts, as they all pertain to autonomous vehicle navigation. Nayhouse_2021 motivation of map generation is because “par 3: maps assume a static representation of the world. Because of this, over time, HD maps can become outdated. Map changes can occur due to new road construction, repaving and/or repainting of roads, road maintenance, construction projects that cause temporary lane changes and/or detours, or other reasons.” Glendinning_2020 teaches constraint-based navigation to be “ par 22: restriction
upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas.”
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the invention to take the motivation of Glendinning_2020 of including constraint information for circumventing avoidance areas with Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 map generation and testing to ensure that maps are not outdated and are up do date with the necessary information for users. If there is a road construction as described by nayhouse_2021 which would cause a detour (aka closing a road), then it would be obvious to apply a constraint-based navigation as taught by Glendenning_2020 on that map to circumvent that area for vehicle navigation safety.
Claim 19:The method of claim 18, wherein:
Fok_2020 makes obvious the information associated with the ODD comprises (Col 1 lines 33-35: “obtain route information identifying a route in the map for an autonomous vehicle... col 9 lines 60-62: “The route information may define one or more routes for an autonomous vehicle”.) and generating the plurality of map test cases comprises: Fig 3: taking in a New or updated map (Examiner note: this is interpreted as a map representative of a geographical area) (304). Obtaining route information identifying route in map for autonomous vehicle (306) “Automatically generate one or more validation tests corresponding to one or more of the multiple test routes subsections based on simulated autonomous vehicle traversing one of more road features (312)”.)
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 do not expressly recite an indication of one or more avoidance areas in the geographical area; … : excluding the one or more avoidance areas
Glendenning_2020 makes obvious the information associated with the ODD comprises an indication of one or more avoidance areas in the geographical area;
(par 22: “The AV internal computing system 110 can also include a constraint service 114 (to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 114 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, (etc.)).
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the invention to take the motivation of Glendinning_2020 of including constraint information for circumventing avoidance areas to promote safe propulsion with Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 map route generation to exclude unrouteable paths in testing in order to ensure that the autonomous vehicles safely navigate their environment after map validation so that users after map test validation do not drive in unsafe routes.
Claim 20:The method of claim 18, wherein generating the plurality of map test cases comprises: (see claim 18)
Fok_2020 makes obvious iterating through a plurality of traffic links in the geographical area to determine the plurality of paths, the iterating comprising (Fig. 3 contains a flow chart. The flow chart teaches obtaining route information identifying a route in map for an autonomous vehicle (306). Segment the route into one or more subsections (310), generating validation tests corresponding to one or more route subsections based on a simulated vehicle traversing the one or more road features (312), executing validation tests over different ones of the rest route subsections (314), and if the tests fail (316), further obtaining route information (306) and repeating the process. )((col 2 lines 19-30: “In some aspects, the non-transitory machine-readable storage medium may include instructions to segment multiple test route subsections based on way points. Moreover, the way points may be defined by user input and/or based on one or more road features. In some embodiments, the non-transitory machine-readable storage medium may include instructions to automatically generate multiple validation tests for different ones of the multiple test route subsections. The multiple validation tests may be executed in parallel over the different ones of the multiple test route subsections. In some embodiments, the one or more road features may include an intersection, a lane merge, a cross walk, and/or other road features.”)).
Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 do not expressly recite filtering out one or more un-routable traffic links
Glendenning_2020 makes obvious filtering out one or more un-routable traffic links ((par 22: “The AV internal computing system 110 can also include a constraint service 114 (to facilitate safe propulsion of the autonomous vehicle 102. The constraint service 114 includes instructions for activating a constraint based on a rule-based restriction upon operation of the autonomous vehicle 102. For example, the constraint may be a restriction upon navigation that is activated in accordance with protocols configured to avoid occupying the same space as other objects, abide by traffic laws, circumvent avoidance areas, (etc.)
It would have been obvious for a person of ordinary skill in the art before the effective filing date of the invention to take the motivation of Glendinning_2020 of including constraint information for circumventing avoidance areas to promote safe propulsion with Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 map route generation to exclude unrouteable paths in testing in order to ensure that the autonomous vehicles safely navigate their environment after map validation so that users after map test validation do not drive in unsafe routes.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and US11170652B2 “Systems And Methods For Improved Vehicle Routing To Account For Real-time Passenger Pickup And Dropoff” (Gardner_2021)
Claim 10:The computer-implemented system of claim 1,
Fok_2020 makes obvious wherein the evaluation of the vehicle planning process in navigating through the one or more plurality of paths used for determining the metric for the map (see claim 1)
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019 do not expressly recite is based on a mode of the AV, the mode associated with at least one of a vehicle capability, a traffic rule, or an expected run time.
Gardner_2021 makes obvious is based on a mode of the AV, the mode associated with at least one of a vehicle capability, a traffic rule, or an expected run time.(Col 4 ; lines 33-44 .”For example, the routing parameters can include a distance cost parameter to minimize overall length for a route, a capacity enforcement parameter to ensure the capacity of a vehicle is not violated, a time overage parameter to account for commercial regulations that limit driver time/distances, a promptness parameter that penalizes arrival too early or too late to a destination, and a trip duration parameter that penalizes routes longer than a direct route).”
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019 and Gardner_2021 are analogous arts to the claimed invention as they pertain to the improvement of autonomous vehicle navigation. Where Fok_2020 focuses on map generation and Garnder_2021 discusses improving routing given maps. Fok_2020 teaches “Col 2 lines 20-24: In some aspects, the non-transitory machine-readable storage medium may include instructions to segment multiple test route subsections based on way points. Moreover, the way points may be defined by user input and/or based on one or more road features.” Garnder_2021 teaches “system performs dynamic route planning by using a unique cost function (also referred to as a fitness function) to better select a candidate vehicle to service a ride and to better order waypoints for the ride. “ It would have been obvious for one ordinarily skilled in the art before the effective filing date to combine the map generation of Fok_2020 based on selecting waypoints with Garnder_2021 teachings of using a metric in order to better order the waypoints chosen.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and CN111783230A “Simulation Test Method And Device Of Automatic Driving Algorithm” (Wang_2020)
Claim 13:
The method of claim 12, wherein the map test configuration for generating the plurality of map test cases further includes (see claim 12)
Fok_2020 does not expressly recite an indication of a number of map test cases.
Wang_2020 however makes obvious an indication of a number of map test cases. . (Wang_2020 line 71: “If a pre-set test scenario is required, determine whether the current test process is a batch test. If so, select simulation maps and test scenarios in batches according to the quantity included in the test request from the pre-set test package”).
Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and Wang_2020 are analogous art to the claimed invention because they are from the same field of endeavor called autonomous vehicles simulation and testing. Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to combine Fok_2020, Nayhouse_2021, Li_2019, Reschka_2019, and Wang_2020. The rationale for doing so would have been to apply a known technique to a known device for improvement to yield a predictable result.
The invention of Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 is a map testing simulation for autonomous vehicles. The prior art of Wang_2020 contains a technique of having a page 71 “test request” that “simulates maps and test scenarios,” that is applicable to the prior art of map simulation testing for autonomous vehicles. One ordinarily skilled in the art would recognize that simulation testing, often includes determining a number of test cases prior to testing, and that including a number of map test cases would have yielded a predictable result of allowing users the ability to set the number of map test cases for simulation to improve the system. Therefore, it would have been obvious to combine to combine the map simulation workflow of Fok_2020, Nayhouse_2021, Li_2019, and Reschka_2019 with including a number of test cases of Wang_2020 for the benefit of allowing user control in simulation to obtain the invention as specified in the claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AHMAD HUSSAM SHALABY whose telephone number is (571)272-7414. The examiner can normally be reached Mon-Fri 7:30am - 5pm.
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/A.H.S./Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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