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 .
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Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
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.
Claim(s) 1-3, 12-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (CN 117854286 A), hereinafter as Li, in view of Paeng et al. (KR 102477783 B1), hereinafter as Paeng. The original and a machine translation of Li and Paeng are provided by the examiner. The paragraphs of the machine translation of Li start with both letter ‘n’ and a number.
Regarding claim 1, Li teaches A non-transitory computer-readable recording medium having stored therein a measure execution program that causes a computer to execute a process comprising (Li paragraph [n0013] “this application also proposes a non-volatile computer storage medium storing computer-executable instructions”, paragraph [n0043, 0056-0058], “As shown in Figure 2, this application also proposes an urban traffic planning device based on digital twins, including: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform a digital twin-based urban traffic planning method”):
generating a digital twin reproducing a real world in a virtual space (Li paragraph [n0024] “based on geographic information, 3D modeling techniques, such as voxel modeling and polygon modeling, are used to digitize information such as buildings, roads, and terrain in the target city and transform it into a digital 3D model in order to construct a digital twin model of the target city.”);
acquiring information regarding a person present in a predetermined area of the real world (Li teaches different types of real environments, further teaches setting attributes such as movement trajectory for virtual image or avatar based on the people living in the different types of environment, paragraph [n0028-n0030] “Based on the area type corresponding to different locations in the target city, set the attributes of the virtual image, including quantity, type, and movement logic……based on administrative divisions, different areas within the city are categorized into different types, such as residential areas, commercial areas, educational areas, tourist areas, industrial areas, and transportation hubs…… when simulating traffic in a residential area, there are generally many pedestrians, mostly elderly people, and the main types of vehicles are electric vehicles and small cars. …… When setting the movement trajectory of the elderly images, considering that the elderly generally only move between the community and supermarkets, farmers' markets, or parks, it is necessary to set the elderly images on the roads from the community to other locations and set the elderly images to move back and forth. “);
performing, in the generated digital twin, a simulation concerning movement of the person using the acquired information regarding the person (Li paragraph [n0036] “based on real-time acquired traffic data, the attributes of the virtual avatar are set, and a digital twin model is run to simulate real-time traffic. This enables real-time monitoring and prediction of traffic conditions. Furthermore, based on the attribute settings of the virtual avatar under normal and unexpected conditions, the digital twin model is run to simulate traffic in different areas under both normal and unexpected conditions.”);
generating information indicating a verification result of a measure to be applied to the predetermined area based on a result of the performed simulation (Li teaches traffic optimization as measures to be applied on the digital twin simulation, further teaches evaluating the effectiveness of the plan, paragraph [n0039-n0042] “Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area…… the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area …… a digital twin model is used to perform refined traffic optimization in areas with traffic problems, and traffic is simulated based on the optimization plan. The traffic situation in the problem area is monitored in real time to determine whether the traffic problem has been resolved”); ……
Li is not relied on for the below claim language ……and outputting the generated information indicating the verification result to a display screen. Paeng teaches ……and outputting the generated information indicating the verification result to a display screen (Paeng teaches displaying metaverse digital twin simulation results on an electronic device, further teaches an verification step, and displaying the result on a screen, paragraph [0012] “A system for providing simulation results performed in a metaverse environment according to one embodiment disclosed in this document may include an electronic device …… outputs a metaverse screen through the display of the electronic device based on the implementation information for implementing the metaverse environment, and while outputting the metaverse screen, obtains user input to perform a simulation on the metaverse server in order to verify result information satisfying a standard condition set by the user …… and the observation information to verify result information satisfying the reference condition, and based on the simulation result, transmit the result information satisfying the reference condition to the electronic device”).
Li and Paeng are in the same field of endeavor, namely digital twin based simulation. Paeng teaches displaying the verification result on the screen of electronic device to improve user interaction. Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Paeng with the method of Li to improve user interaction.
Regarding claim 2, Li in view of Paeng teach The non-transitory computer-readable recording medium according to claim 1, and further teach wherein the performing includes executing, using the digital twin, a traffic simulation employing destination data regarding a destination for the movement of the person (Li paragraph [n0030] “When setting the movement trajectory of the elderly images, considering that the elderly generally only move between the community and supermarkets, farmers' markets, or parks, it is necessary to set the elderly images on the roads from the community to other locations and set the elderly images to move back and forth.”), and the generating includes generating the information indicating the verification result of the measure to be applied to the predetermined area regarding the movement of the person based on a result of the traffic simulation (Li teaches traffic optimization as measures to be applied on the digital twin simulation, further teaches evaluating the effectiveness of the plan, paragraph [n0039-n0042] “Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area…… the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area …… a digital twin model is used to perform refined traffic optimization in areas with traffic problems, and traffic is simulated based on the optimization plan. The traffic situation in the problem area is monitored in real time to determine whether the traffic problem has been resolved”).
Regarding claim 3, Li in view of Paeng teach The non-transitory computer-readable recording medium according to claim 1, and further teach wherein the process further includes generating the destination data for the movement of the person using attribute information of the person (Li teaches setting the destination data based on person’s age attribute, paragraph [n0030] “When setting the movement trajectory of the elderly images, considering that the elderly generally only move between the community and supermarkets, farmers' markets, or parks, it is necessary to set the elderly images on the roads from the community to other locations and set the elderly images to move back and forth”), wherein the performing includes executing, using the digital twin, the simulation concerning the movement of the person employing the destination data regarding the destination for the movement of the person (Li paragraph [n0032-n0036] “when setting up random events such as traffic accidents, the number of vehicle images is increased on the road where the accident occurs and on the surrounding roads, the running speed of pedestrian images around the accident is slowed down, and the movement logic of the surrounding pedestrian and vehicle images is adjusted, such as adjusting the route to move away from the accident location or slowly approaching the accident location …… based on real-time acquired traffic data, the attributes of the virtual avatar are set, and a digital twin model is run to simulate real-time traffic. This enables real-time monitoring and prediction of traffic conditions. Furthermore, based on the attribute settings of the virtual avatar under normal and unexpected conditions, the digital twin model is run to simulate traffic in different areas under both normal and unexpected conditions.”), and the generating includes generating the information indicating the verification result of the measure to be applied to the predetermined area regarding the movement of the person based on a result of the simulation (Li teaches traffic optimization as measures to be applied on the digital twin simulation, further teaches evaluating the effectiveness of the plan, paragraph [n0039-n0042] “Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area…… the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area …… a digital twin model is used to perform refined traffic optimization in areas with traffic problems, and traffic is simulated based on the optimization plan. The traffic situation in the problem area is monitored in real time to determine whether the traffic problem has been resolved”).
Regarding claim 12, it recites similar limitations of claim 1 but in a method using a processor form. The rationale of claim 1 rejection is applied to reject claim 12. In addition, Li teaches A measure execution method comprising: …… using a processor (Li paragraph [n0043, 0056-0058], “As shown in Figure 2, this application also proposes an urban traffic planning device based on digital twins, including: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform a digital twin-based urban traffic planning method”).
Regarding claim 13, it recites similar limitations of claim 1 but in an information processing device form. The rationale of claim 1 rejection is applied to reject claim 13. In addition, Li teaches An information processing device comprising: a processor configured to (Li paragraph [n0043, 0056-0058], “As shown in Figure 2, this application also proposes an urban traffic planning device based on digital twins, including: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which enables the at least one processor to perform a digital twin-based urban traffic planning method”):
Claim(s) 4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (CN 117854286 A), hereinafter as Li, in view of Paeng et al. (KR 102477783 B1), hereinafter as Paeng, further in view of NPL Hofer et al. (“Generating Realistic Road Usage Information and Origin-Destination Data for Traffic Simulations: Augmenting Agent-Based Models with Network Techniques”), hereinafter as Hofer. The original and a machine translation of Li and Paeng are provided by the examiner. The paragraphs of the machine translation of Li start with both letter ‘n’ and a number.
Regarding claim 4, Li in view of Paeng teach The non-transitory computer-readable recording medium according to claim 3, wherein the process further includes: but are not relied on for the below claim language acquiring a movement purpose of the person; and identifying, using the movement purpose of the person, a model associated with the movement purpose of the person from among a plurality of models, wherein the generating includes generating the destination data using the identified model. Hofer teaches acquiring a movement purpose of the person; and identifying, using the movement purpose of the person, a model associated with the movement purpose of the person from among a plurality of models, wherein the generating includes generating the destination data using the identified model (Hofer teaching commuting as the movement purpose of a person, further teaches using different models for citizen and commuters, Page 5, paragraph 2-3, “we use an agent-based approach. For every citizen, an agent is generated according to the population density of each district. Within their district, their first origin point is chosen randomly. Next a random day from the pool of mobility behaviors is as signed to each agent. For each trip, the agent chooses a valid destination node (i.e. a node with the correct distance to the origin node) and all edges that lie on the shortest path update their usage accordingly…… Since these agents only cover the traffic generated by citizens, commuters from other regions must be included separately. Statistical information about their origin and therefore the entry node from which they are most likely to enter the city were obtained from [21]. If no accurate commuter data can be found for the city in question, it is also possible to distribute the commuters uniformly among all entry points, however this might lead to less realistic results. Commuters have two trips each day. The first trip connects their entry node to a random node within the network, the second trip connects this random node to the exit node associated with their entry node.”).
Li, Paeng and Hofer are in the same field of endeavor, namely virtual traffic simulation. Hofer teaches a method to generate the destination data for virtual avatar/agents based on if the agent is commuter or not, to improve efficiency and accuracy (Hofer Page 10, paragraph 1, “This contribution presents a novel way to generate origin-destination data and information on road usage in large traffic systems, using a complex network approach supported by an agent-based simulation based on empirical survey data. Even though origin-destination data is generated within the model, it is still computationally faster than micro car-following models and can therefore be used on a 1:1 scale for large traffic systems.”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Hofer with the method of Li and Paeng to improve efficiency and accuracy.
Claim(s) 7-8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (CN 117854286 A), hereinafter as Li, in view of Paeng et al. (KR 102477783 B1), hereinafter as Paeng, further in view of Takeuchi et al. (IDS US 20140149094 A1), hereinafter as Takeuchi. The original and a machine translation of Li and Paeng are provided by the examiner. The paragraphs of the machine translation of Li start with both letter ‘n’ and a number.
Regarding claim 7, Li in view of Paeng teach The non-transitory computer-readable recording medium according to claim 1, and further teach wherein the acquiring includes acquiring the destination data with a destination associated with each of the persons (Li paragraph [n0030] “When setting the movement trajectory of the elderly images, considering that the elderly generally only move between the community and supermarkets, farmers' markets, or parks, it is necessary to set the elderly images on the roads from the community to other locations and set the elderly images to move back and forth.”), the performing includes performing, using the acquired destination data, a simulation of moving an agent …… on the digital twin (Li paragraph [n0032-n0036] “when setting up random events such as traffic accidents, the number of vehicle images is increased on the road where the accident occurs and on the surrounding roads, the running speed of pedestrian images around the accident is slowed down, and the movement logic of the surrounding pedestrian and vehicle images is adjusted, such as adjusting the route to move away from the accident location or slowly approaching the accident location …… based on real-time acquired traffic data, the attributes of the virtual avatar are set, and a digital twin model is run to simulate real-time traffic. This enables real-time monitoring and prediction of traffic conditions. Furthermore, based on the attribute settings of the virtual avatar under normal and unexpected conditions, the digital twin model is run to simulate traffic in different areas under both normal and unexpected conditions.”), and the generating includes identifying a condition of the predetermined area based on a result of the simulation (Li teaches changes of indicators of traffic flow and congestion as identifying a condition, paragraph [n0039-n0042] “Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area…… the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area …… a digital twin model is used to perform refined traffic optimization in areas with traffic problems, and traffic is simulated based on the optimization plan. The traffic situation in the problem area is monitored in real time to determine whether the traffic problem has been resolved”).
Li in view of Paeng is not relied on for the below claim language ……moving an agent corresponding to each of a plurality of persons …… Takeuchi teaches ……moving an agent corresponding to each of a plurality of persons …… (Takeuchi paragraph [0077] “The behavior of a crowd influences movement of a character and a vehicle arranged in the target region in simulation. For example, the behavior of a crowd is decided by modeling behavior of a person who is positioned in the target region in the real world or is in action regarding the target region.”).
Li, Paeng and Takeuchi are in the same field of endeavor, namely virtual agent simulation. Takeuchi teaches modeling the behavior of agent based on a person in real environment to improve user interaction (Takeuchi paragraph [0145] “An example use of the technology according to one or more of embodiments of the present disclosure is an application that enables a user to experience a real atmosphere of a desired location by viewing a simulation image on a screen even if the user does not go there.”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Takeuchi with the method of Li and Paeng to improve user interaction.
Regarding claim 8, Li in view of Paeng and Takeuchi teach The non-transitory computer-readable recording medium according to claim 7, and further teach wherein the measure to be applied to the predetermined area is a measure for alleviating traffic congestion (Li paragraph [n0039] “based on the sorted traffic operation data, the location of problem areas in the target city is determined. If there are a large number of vehicles, the probability of traffic accidents on the current road will be higher, and the current road belongs to the problem area. Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area.”),
the generating includes identifying congestion status of the predetermined area based on the result of the simulation (Li paragraph [n0040] “the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area.”), and generating the information indicating the verification result of the measure to be applied to the predetermined area using the identified congestion status (Li teaches traffic optimization as measures to be applied on the digital twin simulation, further teaches evaluating the effectiveness of the plan, paragraph [n0039-n0042] “Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area…… the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area …… a digital twin model is used to perform refined traffic optimization in areas with traffic problems, and traffic is simulated based on the optimization plan. The traffic situation in the problem area is monitored in real time to determine whether the traffic problem has been resolved”).
Claim(s) 9-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (CN 117854286 A), hereinafter as Li, in view of Paeng et al. (KR 102477783 B1), hereinafter as Paeng, further in view of Tsubouchi et al. (JP 2018097726 A), hereinafter as Tsubouchi. The original and a machine translation of Li, Paeng and Tsubouchi are provided by the examiner. The paragraphs of the machine translation of Li start with both letter ‘n’ and a number.
Regarding claim 9, Li in view of Paeng teach The non-transitory computer-readable recording medium according to claim 1, but is not relied on for the below claim language wherein the performing includes: acquiring a behavior selection model for determining whether the person acts in accordance with the measure;
executing a simulation of determining whether an agent complies with a first measure in the digital twin using the acquired behavior selection model and the acquired information regarding the person; and performing a simulation concerning the movement of the person using an execution result of the simulation of determining whether the agent complies. Tsubouchi teaches wherein the performing includes: acquiring a behavior selection model for determining whether the person acts in accordance with the measure (Tsubouchi teaches choosing a behavior model based on the road construction and congestion as the measure, paragraph [0081] “In the example shown in Figure 1, the generation unit 133 generates a model to be applied to the agent in the simulation…… the generation unit 133 may generate various models, such as a behavioral model M1 for men in their 20s or a behavioral model M2 for women in their 20s, based on the behavioral history AL11. For example, the generation unit 133 may generate a model taking into account the open data OD11.”, paragraph [0054] “the open data storage unit 122 stores open data OD11, which includes open data OD11-1 related to traffic such as road information including construction and congestion, open data OD11-2 related to weather such as weather and temperature, and open data OD11-3 related to the economy such as household finances and consumption, as shown in Figure 1.”); executing a simulation of determining whether an agent complies with a first measure in the digital twin using the acquired behavior selection model and the acquired information regarding the person; and performing a simulation concerning the movement of the person using an execution result of the simulation of determining whether the agent complies (Tsubouchi teaches a behavior model of agents reacting to the congestion as the first measure, further teaches the simulation based on the model, paragraph [0024] “Model M1 may be a probabilistic model that includes information indicating that, given the presence of traffic congestion such as congestion SN1 in the virtual space CS11, there is a 55% probability that the agent will avoid congestion SN1 and a 45% probability that it will not avoid congestion when it approaches it…… when a large number of agents to whom Model M1 is applied encounter a traffic jam SN1, the actions of those agents to whom Model M1 is applied will branch out according to their respective probabilistic models. For example, if 20,000 agents to whom Model M1 is applied encounter congestion SN1, a simulation log will be generated showing that, according to the probabilistic model, approximately 11,000 agents will avoid congestion SN1,while approximately 9,000 agents will not avoid congestion SN1 and will proceed through it.”).
Li, Paeng and Tsubouchi are in the same field of endeavor, namely virtual agent simulation. Tsubouchi teaches a method to assign different behavior models for virtual agents to improve the model accuracy (Tsubouchi paragraph [0040] “The generation
device 100 may perform simulations using various models, such as probabilistic models, as appropriate.”, paragraph [0028] “the generation device 100 can generate a simulated log using actual log data (behavioral history) as input, thereby generating log information that more accurately reflects the real world.”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Tsubouchi with the method of Li and Paeng to improve the model accuracy.
Regarding claim 10, Li in view of Paeng and Tsubouchi teach The non-transitory computer-readable recording medium according to claim 9, and further teach wherein the information regarding the person is the attribute information of the person (Tsubouchi paragraph [0015] “In the example shown in Figure 1, the model to be applied to each agent is determined based on the population composition of area A, including age and gender, as attribute information. Furthermore, the attribute information used for population composition is not limited to age and gender; various types of attribute information may be used. In the example shown in Figure 1, the population composition of Area A is assumed to consist mainly of men in their 20s, and the explanation follows.”), the performing includes executing a simulation of determining whether each of a plurality of agents moves within the predetermined area by determining whether each agent complies with the first measure based on the attribute information of the agent present in the digital twin and the acquired behavior selection model (Tsubouchi teaches selecting different behavior model based on sex and age attributes, further teaches a model defining a probability of whether agent avoid a congestion area or not, the congestion area is the predetermined area, if the agent does not avoid the congestion, it indicates the agent moves within the predetermined area, paragraph [0081] “the generation unit 133 generates a model corresponding to each attribute based on the behavioral history AL 11. For example, the generation unit 133 may generate various models, such as a behavioral model M1 for men in their 20s or a behavioral model M2 for women in their 20s”, paragraph [0024] “if 20,000 agents to whom Model M1 is applied encounter congestion SN1, a simulation log will be generated showing that, according to the probabilistic model, approximately 11,000 agents will avoid congestion SN1,while approximately 9,000 agents will not avoid congestion SN1 and will proceed through it”), identifying congestion status of the predetermined area based on the result of the simulation for determining whether to move within the predetermined area, and generating information indicating a verification result of the first measure to be applied to the predetermined area using the identified congestion status (Li teaches the simulation of virtual avatar/agents in digital twin based on optimization plan to solve congestion, further teaches verification of results, paragraph [n0039-n0040] “based on the sorted traffic operation data, the location of problem areas in the target city is determined. If there are a large number of vehicles, the probability of traffic accidents on the current road will be higher, and the current road belongs to the problem area. Through optimization algorithms, such as genetic algorithms and simulated annealing algorithms, the digital twin model is adjusted according to the traffic problems corresponding to the problem area. This includes adjusting road width, lane division, traffic light timing, intersection settings, etc., to improve the traffic capacity of roads in the problem area. Furthermore, the adjusted traffic plan is simulated in a digital twin model, and changes in indicators such as traffic flow, congestion, average speed, and travel time are observed to evaluate the effectiveness of the traffic plan and see if it has effectively solved the corresponding traffic problems in the problem area.”).
Li, Paeng and Tsubouchi are in the same field of endeavor, namely virtual agent simulation. Tsubouchi teaches a method to assign different behavior models for virtual agents to improve the model accuracy (Tsubouchi paragraph [0040] “The generation
device 100 may perform simulations using various models, such as probabilistic models, as appropriate.”, paragraph [0028] “the generation device 100 can generate a simulated log using actual log data (behavioral history) as input, thereby generating log information that more accurately reflects the real world.”). Therefore, it would have been obvious for a person of ordinary skill in the art before the effective filing date of the claimed invention to combine the teaching of Tsubouchi with the method of Li and Paeng to improve the model accuracy.
Allowable Subject Matter
Claims 5-6, 11 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Regarding claim 5, the closet prior art of Hofer teaches using different models for citizen and commuters to decide on the destination data. However, Hofer fails to teach the combined limitation below as a whole “wherein the destination data is generated based on a selection probability calculated from statistical data in a case where a movement purpose of the person is commuting to work or attending school, and the destination data is generated based on a selection probability calculated from the attribute information of the person in a case where the movement purpose of the person is other than commuting to work and attending school.”. Furthermore, no prior art of record either alone or in combination teaches the above limitation as a whole. Therefore, claim 5 is considered to be allowable.
Claim 6 contain allowable subject matter because they depend on claim 5 that contains allowable subject matter.
Regarding claim 11, the closest prior art of Li teaches a digital twin simulation based on virtual agents. However, Li fails to teach the combined limitation below as a whole “acquiring terminal data, via communication, from a terminal used by the person present in the predetermined area of the real world; positioning an agent corresponding to the person on a digital twin in which the virtual space and the real world are time-synchronized, based on the acquired terminal data; and associating the attribute information of the person with the agent positioned on the digital twin, the performing includes: receiving a first measure to be applied to the predetermined area; acquiring a behavior selection model for the first measure, the behavior selection model being a machine learning model for determining whether the person acts in accordance with the measure; and executing a simulation to determine whether the agent complies with the first measure in the digital twin, based on the acquired behavior selection model for the first measure and the attribute information of the person.”. Furthermore, no prior art of record either alone or in combination teaches the above limitation as a whole. Therefore, claim 11 is considered to be allowable.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Klenk et al. (US 20200141747 A1) teaches a method of generating multiple travel plans for a user with starting point and ending point, based on user preference model and influence strategy.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to XIAOMING WEI whose telephone number is (571)272-3831. The examiner can normally be reached M-F 8:00-5:00.
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/XIAOMING WEI/Examiner, Art Unit 2611
/KEE M TUNG/Supervisory Patent Examiner, Art Unit 2611
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