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 .
Summary of Claims
Claims 1-30 are pending
Response to Arguments
Note: This application was brought to a pre-appeal conference and was reopened. The Pre-appeal suggested to reopen due to lack of a good explanation for the limitation "performing a plurality of simulations of outcomes for the vehicle and other vehicles resulting from stimulating the identified animal." The examiner of record has left the office, thus a new examiner has been assigned this case.
The Karol Reference
Applicant points out what is being taught in Karol but does not indicate what it does not taught by this reference.
The KIM Reference
Applicant argues that KIM does not teach the "performing a plurality of simulations of outcomes for the vehicle and other vehicles resulting from stimulating the identified animal" within claim 1. Examiner agrees that tit was not clear where this feature is taught but Examiner respectfully disagrees. Kim teaches ([0106] “The vehicle model data 256 may include data describing of one or more virtual vehicles that are included in the simulation described by the GUI data 144…[0107] The software model data 257 may be operable so that the virtual vehicle behaves in the simulation in a manner that is the same or similar to how a real world vehicle built based on the vehicle model data 256 and the software model data 257 would behave the real world under the same or similar conditions.”).
Thus teaches this limitation. See 103 below for clarification.
The Morales Reference
Applicant further argues that Morales does not teach, as indicated, "a device for avoiding collisions between a traveling vehicle and an animal." Examiner respectively disagrees. Morales clearly teaches this limitation in the paragraphs shown by the Applicant in their own arguments. The claims are being interpreted under The Broadest Reasonable Interpretation of the claims.
Note that under a broadest reasonable interpretation (BRI), words of the claim must be given their plain meaning, unless such meaning is inconsistent with the specification. The plain meaning of a term means the ordinary and customary meaning given to the term by those of ordinary skill in the art at the relevant time. The ordinary and customary meaning of a term may be evidenced by a variety of sources, including the words of the claims themselves, the specification, drawings, and prior art. However, the best source for determining the meaning of a claim term is the specification - the greatest clarity is obtained when the specification serves as a glossary for the claim terms. The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification. 2111.01 (I). See also In re Marosi, 710 F.2d 799, 802, 218 USPQ 289, 292 (Fed. Cir. 1983) ("'[C]laims are not to be read in a vacuum, and limitations therein are to be interpreted in light of the specification in giving them their ‘broadest reasonable interpretation.'"2111.01 (II)
With respect to the interpretation of claim terms, MPEP 2111 states:
The Patent and Trademark Office ("PTO") determines the scope of claims in patent applications not solely on the basis of the claim language, but upon giving claims their broadest reasonable construction "in light of the specification as it would be interpreted by one of ordinary skill in the art." In re Am. Acad. of Sci. Tech. Ctr., 367 F.3d 1359, 1364[, 70 USPQ2d 1827, 1830] (Fed. Cir. 2004). Indeed, the rules of the PTO require that application claims must "conform to the invention as set forth in the remainder of the specification and the terms and phrases used in the claims must find clear support or antecedent basis in the description so that the meaning of the terms in the claims may be ascertainable by reference to the description." 37 CFR 1.75(d)(1).
The words of the claim must be given their plain meaning unless the plain meaning is inconsistent with the specification In re Zletz, 893 F.2d 319, 13 USPQ2d 1320 (Fed. Cir. 1989).
"Though understanding the claim language may be aided by explanations contained in the written description, it is important not to import into a claim limitations that are not part of the claim. For example, a particular embodiment appearing in the written description may not be read into a claim when the claim language is broader than the embodiment." Superguide Corp. v. DirecTV Enterprises, Inc., 358 F.3d 870, 875, 69 USPQ2d 1865, 1868 (Fed. Cir. 2004).(see MPEP 2111.01).
During patent examination, the pending claims must be "given their broadest reasonable interpretation consistent with the specification." The broadest reasonable interpretation does not mean the broadest possible interpretation. Rather, the meaning given to a claim term must be consistent with the ordinary and customary meaning of the term (unless the term has been given a special definition in the specification), and must be consistent with the use of the claim term in the specification and drawings. Further, the broadest reasonable interpretation of the claims must be consistent with the interpretation that those skilled in the art would reach. In re Cortright, 165 F.3d 1353, 1359, 49 USPQ2d 1464, 1468 (Fed. Cir. 1999) (see PMEP 2111).
Accordingly, the claims herein will be interpreted in accordance with the MPEP 2111.
Claim Rejections - 35 USC§ 103
In the event the determination of the status of the application as subject to AIA 35
U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
Determining the scope and contents of the prior art.
Ascertaining the differences between the prior art and the claims at issue.
Resolving the level of ordinary skill in the pertinent art.
Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-8, 10-18, 20-27, 29, and 30 are rejected under 35 U.S.C. 103 as being unpatentable over KAROL [US20210114514] in view of KIM [US20170286570] in view of MORALES [US20160355181], further in view of RONNING [US20140261151].
Regarding claim 1: KAROL discloses:
A method performed by a processing system of a vehicle for stimulating animal behavior, comprising: performing a recognition process to identify an animal detected in proximity to the vehicle; (see at least KAROL, ¶ 0034 (describes the processing of data “associated with the object(s) 106 (e.g., car, truck, pedestrian, bicycle, motorcycle, animal, etc.).” and further uses classification to identify the type and other attributes of the obstacle); 0050 (discusses more examples of the use of classification/types examples, the probability of conflict may be determined based on a classification)].
based on the plurality of simulations of outcomes for the vehicle and the other vehicles; and (see at least KAROL, ¶ 0017; 0020 (discusses “ the determination of a substantial match between the object reaction and the expected reaction may include a match of a threshold number of actions (e.g., one matching actions, two matching actions, etc.), a threshold percentage of actions (e.g., 90%, 50%, etc.), or the like.” And more details on simulations and how they are processed)];
controlling the vehicle signal devices-based on the selected animal stimuli mode. (see at least KAROL, ¶ 0010)
EXAMINERS NOTE: While KAROL does not explicitly name a simulation, it does perform the given actions based on processing environmental factors for an anticipated "optimal signal".
EXAMINERS NOTE: While KAROL does not explicitly state it performs computations based on the result of other vehicles, it does communicate and utilize sensor data from other nearby vehicles to coordinate actions. Additionally, KAROL does anticipate the tracking of objects in relation to other vehicle paths.
KAROL does not disclose, but KIM teaches:
performing a plurality of simulations of outcomes, for the vehicle and other vehicles, resulting from_[see at least KIM, ¶ 0005 (discusses categorization of variables and how they are used in simulations and the outcome of simulations); 0026 (discusses other aspects of the “Virtualization software” that is used in the simulations); ¶ 0073 (further discusses different simulations and their display/results of the simulations)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
KAROL in view of KIM does not disclose, but MORALES teaches:
determining one or more possible animal responses by the animal based on: (see at least MORALES ¶ 0017 (discusses collision avoidance technology in Morales, “the collision avoidance assistance device for a vehicle may further include an assistance processing selection unit configured to select a mode of the assistance processing for collision avoidance based on the determined type of the animal… the behavior characteristics of an animal when the vehicle approaches the animal differ according to the type. Therefore, the assistance efficient for collision avoidance differs according to the animal type.”) ];
the identity of the animal: and [see at least MORALES ¶ 0005 (discusses animal behavior based on type of animal)];
a plurality of different animal stimuli modes of one or more vehicle signal devices of the vehicle: (see at least MORALES, ¶ 0006 (discusses " When a warning by sound and light is issued to an animal detected ahead of the vehicle, the reaction differs among animal types; some animals are highly sensitive to the warning and move away from the vehicle and some other animals do not react to the warning at all and enter the traveling road with little or no change in the behavior…Therefore, when an animal is detected as an object in the image of the traveling road in the traveling direction of the vehicle or in the image of its surroundings, it is preferable that assistance for collision avoidance be provided in a more suitable mode according to the type of the animal.")];
the one or more possible animal responses to the plurality of different animal stimuli modes; [see at least MORALES, ¶ 0006; 0017]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making with the virtual vehicle simulation abilities of KAROL in view KIM to incorporate decision making based on animal type and warning reaction efficacy within MORALES effectively yield an effective safer reaction decision system that accounts for specific animal reaction abilities.
Neither KAROL, KIM or Morales specifically disclose/teach but Ronning teaches
a plurality of different animal stimuli modes of one or more vehicle signal devices of the vehicle ; performing a plurality of simulations of outcomes, for the vehicle and other vehicles, resulting from the one or more possible animal responses to the plurality of different animal stimuli modes; selecting one of the plurality of different animal stimuli modes based on the plurality of simulations of outcomes for the vehicle and the other vehicles; and controlling the vehicle signal devices based on the selected animal stimuli mode. [see at least Ronning, Abstract (“producing an avoidance response in an animal, and more particularly, producing an avoidance response by illuminating the animal with light or sound of sufficient wavelength, “); Claim 7 (“The method for producing an avoidance response in an animal of claim 4, wherein the one or more unmanned vehicles simulate top predator behavior to produce an avoidance response in one or more animals.”); ¶ 0011-0012 (discusses avoidance response to the stimuli); 0033 (discusses avoidance response and simulating behavior); 0034 (discusses more on avoidance response and stimuli)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making with the virtual vehicle simulation abilities of KAROL in view KIM to incorporate decision making based on animal type and warning reaction efficacy within MORALES, further with the stimuli and simulations of animal behavior or Ronning, effectively yielding an effective, safer reaction decision system that accounts for specific animal reaction abilities.
Regarding claim 2:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within claim 1 and KAROL does not disclose, but KIM teaches:
the plurality of simulations of outcomes for the vehicle and other vehicles [see at least KIM, ¶ 0005 (discusses plurality of simulations using "categorization”); ¶ 0026 (discusses "Virtualization software”)];
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
KAROL in view of KIM does not disclose, but MORALES teaches:
use information regarding behaviors of the identified animal obtained from a database accessible by a processor of the vehicle. [see at least MORALES, ¶ 0030 (discusses animal behavior); 0034 (further discusses “collision avoidance assistance device” in detail)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making with the virtual vehicle simulation abilities of KAROL in view KIM to incorporate decision making based on animal type and warning reaction efficacy within MORALES effectively yield an effective safer reaction decision system that accounts for specific animal reaction abilities.
Regarding claim 3:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within claim 1 and KAROL further discloses:
use information regarding behaviors of the identified animal provided as an output by a trained artificial intelligence (Al) model executed by a processor of the vehicle. [see at least KAROL, ¶ 0115 (discusses examples of data, identification of specific animals and use in simulations); 0117 (further discussions on this topic)}].
KAROL does not disclose, but KIM teaches:
the plurality of simulations of outcomes [see at least KIM, ¶ 0005; 0026; 0073]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding claim 4:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within claim 1 and KAROL further discloses:
identifying one or more road conditions, [see at least KAROL, ¶ 0012 (discusses "The vehicle computing system may be configured to emit a first warning signal to alert one or more objects in the environment of the vehicle presence and/or operation.”); 0039 (discusses examples of " characteristics”)];
the identified one or more road conditions. (see at least KAROL, ¶ 0012; 0039].
KAROL does not disclose, but KIM teaches:
wherein the plurality of simulations of outcomes take into account [see at least KIM, ¶ 0005; 0026; 0073].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding claim 5:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within 1 and KAROL further discloses:
identifying one or more traffic conditions, [see at least KAROL, ¶ 0012, (discusses identifying characteristics of environment or other features of an obstruction/object); 0036 (discusses " characteristics may be determined dynamically” and in real time)]
take into account the identified one or more traffic conditions. [see at least KAROL, ¶ 0012; 0036].
KAROL does not disclose, but KIM teaches:
wherein the plurality of simulations of outcomes [see at least KIM, ¶ 0005; 0026; 0073].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding claim 6:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within 1 and KAROL further discloses:
identifying ambient lighting conditions, [see at least KAROL, ¶ 0112 (discusses environmental conditions and their use in simulations or warnings]); 0043 ( further discusses characteristics of an area)];
take into account the identified ambient lighting conditions. [see at least KAROL,¶ 0112; 0043].
KAROL does not disclose, but KIM teaches:
wherein the plurality of simulations of outcomes [see at least KIM, ¶ 0005; 0026; 0073].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding claim 7:
KAROL in view of KIM in further view of MORALES discloses the limitations within claim 1 and KAROL further discloses:
identifying one or more weather conditions, [see at least KAROL, ¶ 0012 (discusses environmental conditions)];
take into account the identified -one or more weather conditions. (see at least KAROL, ,i 0012; ,i 0039].
KAROL does not disclose, but KIM teaches:
wherein the plurality of simulations of outcomes [see at least KIM, ¶ 0005;
0026; 0073)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding claim 8:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within Claim 1 and KAROL further discloses:
take into account probabilities of each of a plurality of behaviors that the identified animal may perform in response to each stimulus mode. [see at least KAROL, ¶ 0048 Discusses "The probability of conflict”); 0050; 0051 (discusses relevance and other factors that help to find Probability].
KAROL does not disclose, but KIM teaches:
the plurality of simulations of outcomes [see at least KIM, ¶ 0005; 0026; 0073].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding claim 10:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within Claim 1 and KAROL further discloses:
comprises performing the plurality of simulations of outcomes in offline simulations to generate a training database, and applying the training database to a machine learning model to generate a trained artificial intelligence (Al) model that can be implemented in a vehicle processor; and [see at least KAROL, ¶ 0115 discusses "a machine learning component 434 or machine learning component 454 of the computing device(s) 442.”); 0116, (further discusses "the machine learning components” in more detail); 0117 (further examples)];
selecting one of the different stimuli modes to be performed by vehicle signal devices to elicit a behavior of the identified animal based on the plurality of simulated outcomes for the vehicle and other vehicles comprises applying at least [see at least KAROL, ¶ 0011 (discusses the “computing system may be configured to identify objects in the environment”); 0020 (discusses examples); 0116; 0194 (further discusses object reactions, etc. for data gathering.)]; v
vehicle sensor, [see at least KAROL, ¶ 0011];
map, and [see at least KAROL, ¶ 0049 (discuses use of different types of maps in use); 0057 (more on mapping and trajectory)];
traffic data [see at least KAROL, ¶ 0033 (discusses traffic data)];
into the trained Al model in the vehicle processor and receiving as an output one of the different stimuli modes to be performed by vehicle signal devices. [see at least KAROL, ¶ 0059 (discusses using models and sensors to determine stimuli); 0120 (discusses alerts and other determining factors)
KAROL does not disclose, but KIM teaches:
performing a plurality of simulations of outcomes [see at least KIM, ¶ 0005; 0026; 0073].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
Regarding Claim 11:
With regards to claim 11, this claim is the system claim to method claim 1 and is therefore rejected using the same references and rationale. The reference to the processor executable instruction can be found in KAROL ¶ 0141.
Regarding Claim 12:
With regards to claim 12, this claim is substantially similar to claim 2 and is therefore rejected using the same references and rationale.
Regarding Claim 13:
With regards to claim 13, this claim is substantially similar to claim 3 and is therefore rejected using the same references and rationale.
Regarding Claim 14:
With regards to claim 14, this claim is substantially similar to claim 4 and is therefore rejected using the same references and rationale.
Regarding Claim 15:
With regards to claim 15, this claim is substantially similar to claim 5 and is therefore rejected using the same references and rationale.
Regarding Claim 16:
With regards to claim 16, this claim is substantially similar to claim 6 and is therefore rejected using the same references and rationale.
Regarding Claim 17:
With regards to claim 17, this claim is substantially similar to claim 7 and is therefore rejected using the same references and rationale.
Regarding Claim 18:
With regards to claim 18, this claim is substantially similar to claim 8 and is therefore rejected using the same references and rationale.
Regarding Claim 20:
With regards to claim 20, this claim is the means claim to method claim 1 and is therefore rejected using the same references and rationale.
Regarding Claim 21:
With regards to claim 21, this claim is substantially similar to claim 2 and is therefore rejected using the same references and rationale.
Regarding Claim 22:
With regards to claim 22, this claim is substantially similar to claim 3 and is therefore rejected using the same references and rationale.
Regarding Claim 23:
With regards to claim 23, this claim is substantially similar to claim 4 and is therefore rejected using the same references and rationale.
Regarding Claim 24:
With regards to claim 24, this claim is substantially similar to claim 5 and is therefore rejected using the same references and rationale.
Regarding Claim 25:
With regards to claim 25, this claim is substantially similar to claim 6 and is therefore rejected using the same references and rationale.
Regarding Claim 26:
With regards to claim 26, this claim is substantially similar to claim 7 and is therefore rejected using the same references and rationale.
Regarding Claim 27:
With regards to claim 27, this claim is substantially similar to claim 8 and is therefore rejected using the same references and rationale.
Regarding Claim 29:
With regards to claim 29, this claim is the non-transitory memory claim to method claim 1 and is therefore rejected using the same references and rationale. The reference to the non-transitory memory can be found in KAROL ,I 0141.
Regarding Claim 30:
With regards to claim 30, this claim is substantially the same scope as all of the claims 2-3 combined and is therefore rejected using the same references and rationale.
Claim(s) 9, 19, 28 are rejected under 35 U.S.C. 103 as being unpatentable over KAROL [US20210114514] in view of KIM [US20170286570] in further view of MORALES [US 20160355181], in view of RONNING [US20140261151], in further view of COMMONS [US9015093].
Regarding claim 9:
KAROL in view of KIM, MORALES and RONNING discloses the limitations within Claim 1 and KAROL further discloses:
for the vehicle and other vehicles that take into account probabilities of [see at least KAROL, ¶ 0019 (discusses examples for determining data to provide probabilities); 0020 (more examples for " determination of a substantial match between the object reaction and the expected reaction may include a match of a threshold number of actions”); 0032 (more discussion on techniques and ways to be implements)];
animal behaviors, [see at least KAROL, ¶ 0020];
vehicle behaviors, and [see at least KAROL, ¶ 0012 (discusses vehicle behaviors)];
driver reactions. [see at least KAROL, ¶ 0010 (discusses driver reactions); 0110 (discusses examples)KAROL does not disclose, but KIM teaches:
performing the plurality of simulations of outcomes [see at least KIM, ¶ 0005; 0026; 0073].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the "expected reaction" decision making of KAROL to incorporate the virtual vehicle simulation abilities of KIM to effectively yield a safer reaction decision system.
KAROL in view of KIM does not disclose, but COMMONS teaches:
comprises performing Monte Carlo simulations of outcomes [see at least COMMON, Col 20 lines 16-34 (indicates " a Monte Carlo style simulation (or less comprehensive schema) may be employed to determine a sensitivity of each output to each input or combination of inputs. In similar fashion, if the neural network is implemented as an analog network, noise may be permitted or injected on each line, with the outputs analyzed for sensitivity to the inputs."); Col 25 lines 21-35 (further goes into the "Neural network” discussion)].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify, with a reasonable expectation of success, the simulation decision-based reaction generation system of KAROL in view of KIM to incorporate the machine learning training with Monte Carlo simulations of COMMONS to yield a safer decision making-processor by allowing the vehicle to more quickly determine the appropriate stimulation to warn outside individuals/animals.
EXAMINERS NOTE: While KAROL does not explicitly use Monte Carlo simulations for preparing outputs of the simulation, it does rely on probabilities of certain responses to the vehicle-generated warnings by outside objects and continuously modifies its expected "optimal signal" based on the current environment and outcome of the actuation.
EXAMINERS NOTE: While KAROL does not explicitly account for driver reactions, it does account for other vehicles as objects that need to be tracked and warned.
Regarding Claim 19:
With regards to claim 19, this claim is substantially similar to claim 9 and is therefore rejected using the same references and rationale.
Regarding Claim 28:
With regards to claim 28, this claim is substantially similar to claim 9 and is therefore rejected using the same references and rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lunn RB, Blackwell BF, DeVault TL, Fernández-Juricic E. Can we use antipredator behavior theory to predict wildlife responses to high-speed vehicles? PLoS One. 2022 May 12;17(5).
Abstract includes “Animals seem to rely on antipredator behavior to avoid vehicle collisions. There is an extensive body of antipredator behavior theory that have been used to predict the distance/time animals should escape from predators. These models have also been used to guide empirical research on escape behavior from vehicles.
J. Del Ser, E. Osaba, J. J. Sanchez-Medina, I. Fister and I. Fister, "Bioinspired Computational Intelligence and Transportation Systems: A Long Road Ahead," in IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 2, pp. 466-495, Feb. 2020.
Abstract—This paper capitalizes on the increasingly high relevance gained by data-intensive technologies in the development of intelligent transportation system, which calls for the progressive adoption of adaptive, self-learning methods for solving modeling,
simulation, and optimization problems.
Fadaie, Joshua ; “The State of Modeling, Simulation, and Data Utilization within Industry: An Autonomous Vehicles Perspective.” Computers and Society (cs.CY); Systems and Control. [v1] Mon, 7 Oct 2019 17:26:01.
Abstract: The aviation industry has a market driven need to maintain and develop enhanced simulation capabilities for a wide range of application domains. In particular, the future growth and disruptive ability of smart cities, autonomous vehicles and in general, urban mobility, hinges on the development of state of the art simulation tools and the intelligent utilization of data. (note that can be used for vehicles too)
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/JOAN T GOODBODY/
Primary Examiner, Art Unit 3664
(571) 270-7952
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