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 .
This action is in response to the amendments filed on 06/03/2026, in which claims 1-20 are currently pending and addressed below.
Response to Amendment
Applicant has amended the claims to overcome the claim objections. Accordingly, the claim objections have been withdrawn.
Response to Arguments
Applicant's arguments filed 06/03/2026 have been fully considered but they are not persuasive.
With respect to the 35 U.S.C. 103 rejections:
Applicant argues on pages 11-13 of the remarks that Ferguson in view of Matthiesen fail to teach the amended limitation of claim 1 that recites “a modification to at least one user preference of the first user, the modification preserving the service start location and the service end location specified in the first transportation service request data.” Applicant argues on page 12 of the remarks that Matthiesen fails to teach modifying the transportation service. Applicant argues on page 13 of the remarks that Ferguson fails to teach data corresponding to AV operational capabilities. Applicant argues on pages 13-14 of the remarks that there is no motivation to combine Ferguson and Matthiesen, and that the combination relies on hindsight reconstruction. Applicant further argues on pages 14-15 of the remarks that Kuhara fails to teach the amended limitations of claims 4, 5, and 15. Applicant also argues on pages 15-16 of the remarks that Cooper fails to disclose user preference data associated with a user account and the generation of an AV and non-AV transportation service description.
In response to applicant’s arguments, the examiner respectfully disagrees that Matthiesen fails to teach modifying the transportation service request. Matthiesen teaches alternative ride types or locations are recommended if an autonomous ride is not available (Matthiesen [0047]). A user can then provide an autonomous ride request after receiving the recommended alternative options, and a user will only be matched to an autonomous vehicle if an autonomous ride is available between the requested locations (Matthiesen Fig. 9). Therefore, Matthiesen teaches modifying the transportation service request because an autonomous ride request can be modified using alternative ride types or locations.
In response to applicant’s arguments, the examiner respectfully disagrees that Ferguson fails to teach data describing AV operational capabilities. Ferguson teaches selecting a vehicle based on parameters related to order details, vehicle capabilities, and additional considerations (Ferguson [0091]). Ferguson gives the example of selecting a vehicle based on a determination that an item does not fit into a vehicle compartment (Ferguson [0091]). Therefore, Ferguson teaches data describing AV operational capabilities because Ferguson analyzes whether the size of an AV compartment is sufficient for a requested item.
In response to applicant’s arguments that there is no motivation to combine Ferguson and Matthiesen, the examiner respectfully disagrees. Obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). In this case, one of ordinary skill in the art would be motivated to combine Ferguson and Matthiesen to improve interactions between human users and autonomous vehicles in a mixed autonomous and human-operated environment. Specifically, Matthiesen teaches an improvement in how instructions and information can be conveyed (Matthiesen [0001]). In response to applicant's argument that the examiner's conclusion of obviousness is based upon improper hindsight reasoning, it must be recognized that any judgment on obviousness is in a sense necessarily a reconstruction based upon hindsight reasoning. But so long as it takes into account only knowledge which was within the level of ordinary skill at the time the claimed invention was made, and does not include knowledge gleaned only from the applicant's disclosure, such a reconstruction is proper. See In re McLaughlin, 443 F.2d 1392, 170 USPQ 209 (CCPA 1971).
In response to applicant’s arguments that Ferguson in view Cooper fail to teach all elements of claim 20, the examiner respectfully disagrees. Cooper teaches user preference data associated with a user account because Cooper teaches using a recipient preference database that determines whether an intended recipient has expressed a preference for autonomous delivery of items (Cooper [0087]). Cooper also teaches using information stored within a customer profile to determine whether a destination satisfies the customer’s preference criteria (Cooper [0168]). Cooper teaches generating AV and non-AV transportation service descriptions by identifying different delivery locations for an address based on whether the delivery is completed autonomously or manually (Cooper [0091]). Cooper also teaches using the delivery location information to optimize delivery activities, including determining whether to assign an item to a manual or autonomous delivery method (Cooper [0148], [0154], [0164]). Accordingly, Ferguson in view Cooper teach all elements of claim 20 as further outlined in the 35 U.S.C. 103 rejection of claim 20 below.
Applicant’s arguments have been fully considered and have been found not persuasive.
Applicant’s arguments with respect to Ferguson in view of Matthiesen teaching “a modification to at least one user preference of the first user, the modification preserving the service start location and the service end location specified in the first transportation service request data” have been considered but are moot because the new ground of rejection does not rely on Ferguson or Matthiesen for teaching the amended limitation of claim 1.
Applicant’s arguments with respect to Kuhara teaching the amended limitations of claims 4, 15, and 15 have been considered but are moot because the new ground of rejection does not rely on Kuhara for any teaching or matter specifically challenged in the argument.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-6, 9, and 12-17 are rejected under 35 U.S.C. 103 as being unpatentable over Ferguson et al., U.S. Patent Application Publication No. 2019/0050807 A1 (hereinafter Ferguson), in view of Matthiesen et al., U.S. Patent Application Publication No. 2018/0188731 A1 (hereinafter Matthiesen), and further in view of Haas et al., U.S. Patent Application Publication No. 2022/0307856 A1 (hereinafter Haas).
Regarding claim 1, Ferguson teaches a system for managing a mixed fleet of vehicles to execute transportation services (Ferguson Fig. 11), the system comprising:
at least one processor programmed to perform operations comprising (see at least Ferguson [0014]: “The system includes one or more processors”):
accessing first transportation service request data describing a first transportation service requested by a first user via a first user computing device (see at least Ferguson [0089]: “In block 1402, the fleet management module 120 receives a request for a service either directly from the customer 202 or from the customer 202 via the central server 110.”),
analyzing the first transportation service request data against AV capability data for a plurality of autonomous vehicles (AVs) of the mixed fleet of vehicles to identify a mismatch between one or more service requirements and one or more AV capabilities (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service…In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate).”),
the AV capability data describing operational capabilities of each AV of the plurality of AVs (see at least Ferguson [0091]: “In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate)…In another example, if the item that the customer ordered does not fit into an autonomous robot vehicle compartment, the system may need to dispatch a vehicle driven by a human driver.”);
determining, based on the mismatch, that the first transportation service is not suitable for execution by at least one of a plurality of AVs based on the mismatch between service requirements and AV capabilities (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service. In various embodiments, the mixed fleet includes combinations of fully-autonomous vehicles, semi-autonomous vehicles, vehicles driven by a local human driver, and vehicles driven by a remote human driver, such as combinations of two or more such vehicle types. In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate)…In a further example, if the system is making a delivery near a busy area, the system may decide that using vehicles driven by a remote human driver or using semi-autonomous vehicles are safer or easier than fully autonomy vehicles for that situation.”),
the mixed fleet of vehicles comprising a plurality of human-driven vehicles and the plurality of AVs (see at least Ferguson [0091]: “In various embodiments, the mixed fleet includes combinations of fully-autonomous vehicles, semi-autonomous vehicles, vehicles driven by a local human driver, and vehicles driven by a remote human driver, such as combinations of two or more such vehicle types.”);
and instructing the first vehicle to begin executing the first transportation service (see at least Ferguson [0092]: “In block 1408, the system transmits a message to the selected vehicle to perform a portion of the service or all of the service.”).
Ferguson fails to expressly disclose making a modification to a transportation service to make it suitable for execution by at least one AV. However, Matthiesen teaches
the first transportation service request data specifying a service start location and a service end location (see at least Matthiesen [0018]: “A user can request a ride through an autonomous ride request GUI. The requestor can provide pickup and drop-off locations.”);
prior to assigning the first transportation service to a vehicle from the mixed fleet, prompting the first user via the first user computing device to make a modification to the first transportation service to make it suitable for execution by the at least one of the plurality of AVs (see at least Matthiesen [0047]: “In some embodiments, it can be determined whether at least one autonomous route exists between the pickup location and the drop-off location. If an autonomous ride is not available between the locations, at step 906 alternative ride types or locations may be recommended. If an autonomous ride is available between the locations, at step 908 the ride request can be matched to an autonomous vehicle.”);
selecting a first vehicle of the mixed fleet of vehicles to execute the first transportation service based on the first transportation service request data and the modification to the first transportation service (see at least Matthiesen [0047]: “In some embodiments, it can be determined whether at least one autonomous route exists between the pickup location and the drop-off location. If an autonomous ride is not available between the locations, at step 906 alternative ride types or locations may be recommended. If an autonomous ride is available between the locations, at step 908 the ride request can be matched to an autonomous vehicle. In some embodiments, at step 910 a route between the pickup location and drop-off location can be mapped. The route can then be sent to the autonomous vehicle.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system taught by Ferguson with the modification taught by Matthiesen with reasonable expectation of success. Matthiesen is directed towards the related field of autonomous vehicle pickup and drop-off management. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson with the modification taught by Matthiesen to improve conveying instructions and information for a mixed autonomous and human-operated environment (see at least Matthiesen [0001]: “Traditionally, transportation and related services have been provided by a human-operated vehicle. Improvements in computer processing have led to increasing efforts to automate more of these services, using autonomous vehicles that do not require a human operator. However, integrating these autonomously-provided services into a mixed autonomous and human-operated environment has many challenges. Riders are accustomed to interacting with human drivers to provide information and instructions in addition to the information received from a ride matching service. In the absence of a human driver, these instructions may not be so easily conveyed.”).
Ferguson in view of Matthiesen fails to expressly disclose a modification to a user preference that preserves the service start location and service end location. However, Haas teaches
the modification comprising a modification to at least one user preference of the first user, the modification preserving the service start location and the service end location specified in the first transportation service request data (see at least Haas [0020]: “For example, the AV system can provide a service coverage map showing the current coverage area of an AV fleet overlayed on a road map of a particular city or region. The UI may allow a user to select a different walking distance, and the AV system provides an updated coverage map reflecting the selected walking distance.”; [0076]: “This allows a user to obtain a coverage map that reflects how far the user is willing to walk (or bike, etc.) to or from the AV 110.”; [0017]: “Whether an AV can navigate to and stop at a particular location, or within a walkable distance of the location, may not be intuitive to a user, and it can be highly dependent the current state of the road network. Furthermore, the distance users are willing to walk between the AV and their origin or destination point can vary widely between users and between different use cases.”; instant application [0036] teaches a user preference includes a walking distance)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system taught by Ferguson in view of Matthiesen with the modification taught by Haas with reasonable expectation of success. Haas is directed towards the related field of autonomous vehicle service area coverage. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson in view of Matthiesen with the modification taught by Haas to improve the perceived quality of service (see at least Haas [0002]: “The AVs may not be able to travel on certain roads, e.g., if a road is temporarily closed, or if the road is unsuitable for the AV to travel on due to low visibility, poor condition, high pedestrian activity, or other factors. Furthermore, the AVs may only be able to stop along certain roads or at certain locations, e.g., an AV can only stop along a road if there is a suitable stopping lane or parking space. These limitations may not be immediately apparent to users. For example, due to stopping restrictions, an AV may drop a passenger off 500 meters from the passenger's destination. If the user expected door-to-door service, the drop-off location reduces the user's perceived quality of service. As another example, a user may routinely order food delivery from a certain restaurant, but due to road closures, an AV cannot provide delivery service from the restaurant to the user's house, or the delivery may be significantly delayed. This also reduces the perceived quality of service.”).
Regarding claim 2, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson further teaches
wherein the first vehicle is the at least one of the plurality of AVs (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service. In various embodiments, the mixed fleet includes combinations of fully-autonomous vehicles, semi-autonomous vehicles, vehicles driven by a local human driver, and vehicles driven by a remote human driver, such as combinations of two or more such vehicle types…In yet another example, a customer, based on preferences or due to differences in price, may specifically request a fully-autonomous vehicle.”).
Regarding claim 3, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson further teaches
the determining that the first transportation service is suitable for execution by at least one of the plurality of AVs being based at least in part on first user preference data describing a first user preference of the first user (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service…In yet another example, a customer, based on preferences or due to differences in price, may specifically request a fully-autonomous vehicle.”)
Haas further teaches
the at least one user preference including at least one of a payload delivery location, a walking distance tolerance to meet a vehicle, or a service interaction requirement between the first user and the vehicle (see at least Haas [0020]: “For example, the AV system can provide a service coverage map showing the current coverage area of an AV fleet overlayed on a road map of a particular city or region. The UI may allow a user to select a different walking distance, and the AV system provides an updated coverage map reflecting the selected walking distance.”; [0076]: “This allows a user to obtain a coverage map that reflects how far the user is willing to walk (or bike, etc.) to or from the AV 110.”; [0017]: “Whether an AV can navigate to and stop at a particular location, or within a walkable distance of the location, may not be intuitive to a user, and it can be highly dependent the current state of the road network. Furthermore, the distance users are willing to walk between the AV and their origin or destination point can vary widely between users and between different use cases.”; Haas teaches at least a walking distance tolerance to meet a vehicle).
Regarding claim 4, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson further teaches
wherein the operational capabilities of each AV described by the AV capability data comprise at least one of a sensor configuration of the AV, an autonomy-software capability of the AV, or a physical or mechanical capability of the AV (see at least Ferguson [0091]: “In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate)…In another example, if the item that the customer ordered does not fit into an autonomous robot vehicle compartment, the system may need to dispatch a vehicle driven by a human driver.”; under broadest reasonable interpretation determining whether an item can fit into an autonomous robot vehicle compartment is a physical capability of the AV).
Regarding claim 5, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Matthiesen further teaches
wherein the at least one user preference is associated with a user account of the first user and is applicable to a plurality of transportation service requests submitted under the user account (see at least Matthiesen [0062]: “User data 1214 may include user account data, preferences, location history, and other user-specific data.”; [0039]: “In some embodiments, a requestor may be associated with a user profile. A user may opt in to receive autonomous rides as a type of ride option when being matched. The user profile may include an indication as to the user's opt-in status and provide autonomous ride matches based on that status.”).
Regarding claim 6, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Matthiesen further teaches
before prompting the first user to make the modification to the first transportation service, determining that the first transportation service can be modified to make it suitable for execution by the at least one AV (see at least Matthiesen [0047]: “In some embodiments, it can be determined whether at least one autonomous route exists between the pickup location and the drop-off location. If an autonomous ride is not available between the locations, at step 906 alternative ride types or locations may be recommended. If an autonomous ride is available between the locations, at step 908 the ride request can be matched to an autonomous vehicle.”),
wherein the prompting the first user to make the modification to the first transportation service comprises prompting the first user to make a modification to the first transportation service (see at least Matthiesen [0047]: “In some embodiments, it can be determined whether at least one autonomous route exists between the pickup location and the drop-off location. If an autonomous ride is not available between the locations, at step 906 alternative ride types or locations may be recommended. If an autonomous ride is available between the locations, at step 908 the ride request can be matched to an autonomous vehicle.”).
Regarding claim 9, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson further teaches
wherein instructing the first vehicle to begin executing the first transportation service comprises instructing a human or third-party system associated with the first vehicle to begin executing the first transportation service using the first vehicle (see at least Ferguson [0092]: “In block 1408, the system transmits a message to the selected vehicle to perform a portion of the service or all of the service.”; [0042]: “Provided herein is a mixed robot fleet having robot vehicles operating fully-autonomously, semi-autonomously, with a local human driver, and/or with a remote human driver, and a fleet management module for coordination of the mixed robot fleet, where each robot within the fleet is configured for retrieving, transporting, or delivering goods or services and is capable of operating in an unstructured open or closed environment.”).
Regarding claim 12, this claim recites a method for the system of claim 1. The combination of Ferguson in view of Matthiesen and Haas also teaches a method of the system of claim 1 as outlined in the rejection to claim 1 above. Therefore, claim 12 is rejected for the same rationale as claim 1.
Regarding claim 13, this claim recites a method for the system of claim 2 as explained above. Therefore, claim 13 is rejected for the same rationale as claim 2.
Regarding claim 14, this claim recites a method for the system of claim 3 as explained above. Therefore, claim 14 is rejected for the same rationale as claim 3.
Regarding claim 15, this claim recites a method for the system of claim 5 as explained above. Therefore, claim 15 is rejected for the same rationale as claim 5.
Regarding claim 16, Ferguson in combination with Matthiesen and Haas teach all elements of the method according to claim 12 as explained above. Matthiesen further teaches
the modification to the first transportation service comprising a modification to the first transportation service request data (see at least Matthiesen [0047]: “In some embodiments, it can be determined whether at least one autonomous route exists between the pickup location and the drop-off location. If an autonomous ride is not available between the locations, at step 906 alternative ride types or locations may be recommended. If an autonomous ride is available between the locations, at step 908 the ride request can be matched to an autonomous vehicle.”).
Regarding claim 17, this claim recites a method for the system of claim 6 as explained above. Therefore, claim 17 is rejected for the same rationale as claim 6.
Claims 8 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Ferguson in view of Matthiesen and Haas, and further in view of Kuhara, U.S. Patent Application Publication No. 2018/0217598 A1.
Regarding claim 8, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson in view of Matthiesen and Haas fail to expressly disclose excluding a AV from being eligible to execute the transportation service if the user does not make the modification. However, Kuhara teaches
excluding the at least one AV from being eligible to execute the first transportation service if the first user does not make the modification (see at least Kuhara [0141]: “In the example illustrated in FIG. 15, a message box 43b indicating “Delivery to the designated delivery destination by using a self-driving vehicle is not available.” is displayed in the input area 42 on the delivery-destination-information entry screen 40 as the notification information indicating that the delivery to the delivery destination by using the self-driving vehicle 50 is not possible. In this case, when the customer clicks the “drop-down arrow” button in the option entry field “Delivery method” in the input area 42 on the delivery-destination-information entry screen 40, only the delivery method using a vehicle driven by a driver is displayed as a delivery method that can be designated.”; Kuhara [0193]-[0194] teaches self-driving vehicle is not possible unless an alternative candidate area is selected).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system taught by Ferguson in view of Matthiesen and Haas with Kuhara with reasonable expectation of success. Kuhara is directed towards the related field of a management apparatus for a delivery system. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson in view of Matthiesen and Haas with Kuhara to prevent violating road traffic laws (see at least Kuhara [0008]: “In such a case, there is a possibility that when the self-driving vehicle is parked or stopped at the delivery destination, the road traffic law is violated.”).
Regarding claim 19, this claim recites a method for the system of claim 8 as explained above. Therefore, claim 19 is rejected for the same rationale as claim 8.
Claims 7, 11, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Ferguson in view of Matthiesen and Haas, and further in view of Okabe et al., U.S. Patent Application Publication No. 2023/0037532 A1 (hereinafter Okabe).
Regarding claim 7, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson in view of Matthiesen and Haas fail to expressly disclose a conditional user preference having an AV state and a non-AV state. However, Okabe teaches
the modification to the first transportation service comprises a conditional user preference for the first user, the conditional user preference having an AV state and a non-AV state (see at least Okabe [0055]: “According to the delivery management system 1 according to the present embodiment, the first vehicle V1 is assigned as a delivery vehicle to a user who requests a requested item to be performed at a delivery destination. That is, when it is necessary for a person (a driver) to perform a requested item other than delivery of a product to a user at a delivery destination, the product is delivered by the first vehicle V1. On the other hand, for a user who does not request a requested item to be performed at a delivery destination, the second vehicle V2 is assigned as a delivery vehicle. That is, when it is necessary only to hand over a product to a user at a delivery destination, the product is delivered by the second vehicle V2. Therefore, it is possible to more favorably use the first vehicle V1 driven by a driver or the second vehicle V2, which is an autonomous vehicle, as a delivery vehicle.”);
and the instructing the first vehicle to begin executing the first transportation service comprises: instructing, if the first vehicle is an AV, to begin executing the first transportation service using the AV state (see at least Okabe [0043]: “Further, when no requested item is inputted in the requested item field of the user information about the one user, the selection unit 221 selects the second vehicle V2 as the delivery vehicle to deliver the product to the one user.”; [0053]: “Next, at S204, the delivery plan generated at S203 is transmitted to the driver terminal 300 or the second vehicle V2. At this time, the delivery plan with the first vehicle V1 is transmitted to the driver terminal 300. On the other hand, the delivery plan with the second vehicle V2 is transmitted to the second vehicle V2.”; Okabe [0018] teaches the second vehicle is an autonomous vehicle);
and instructing, if the first vehicle is not an AV, to begin executing the first transportation service using the non-AV state (see at least Okabe [0043]: “Therefore, when some requested item is inputted in the requested item field of the user information about the one user, the selection unit 221 selects the first vehicle V1 as the delivery vehicle to deliver the product to the one user. As described above, a driver is in the first vehicle V1. Therefore, by delivering the product to the one user by the first vehicle V1, it becomes possible to perform the requested item by the driver of the first vehicle V1 at the delivery destination.”; [0053]: “Next, at S204, the delivery plan generated at S203 is transmitted to the driver terminal 300 or the second vehicle V2. At this time, the delivery plan with the first vehicle V1 is transmitted to the driver terminal 300. On the other hand, the delivery plan with the second vehicle V2 is transmitted to the second vehicle V2.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system taught by Ferguson in view of Matthiesen and Haas with the conditional preference taught by Okabe with reasonable expectation of success. Okabe is directed towards the related field of managing delivery of goods by a vehicle. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson in view of Matthiesen and Haas with Okabe to prevent difficulties in performing a requested service (see at least Okabe [0019]: “It is possible to hand over the goods to the user no matter which of the first vehicle and the second vehicle is the delivery vehicle. However, it may be requested to perform a predetermined event other than handing over the goods to the user at the time of delivering the goods to a delivery destination. The predetermined event is, for example, placement of the goods or collection of an article other than the goods. At this time, when the goods are delivered by the second vehicle, which is an autonomous vehicle, it may be difficult to perform the predetermined event at the delivery destination because a driver is not in the second vehicle.”).
Regarding claim 11, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson further teaches
accessing user preference data describing preferences of the first user (see at least Ferguson [0090]: “In block 1404, the parameters for the service are determined. In various embodiments, the parameters may include the customer's 202 preference for service providers”),
selecting a plurality of candidate AVs from the mixed fleet of vehicles using the AV transportation service description (see at least Ferguson [0072]-[0073]: “In some embodiments of the robot fleet, the autonomous robots within the fleet are further configured to be part of a sub-fleet of autonomous robots, and each sub-fleet is configured to operate independently or in tandem with multiple sub-fleets having two or more sub-fleets (100-a, 100-b). For example, a package delivery service is configured to offer multiple levels of service such as “immediate dedicated rush service,” “guaranteed morning/ afternoon delivery service,” or “general delivery service.” A service provider could then have a dedicated sub-fleet of delivery vehicles for each type of service within their overall fleet of vehicles.”);
selecting a plurality of candidate human-driven vehicles from the mixed fleet of vehicles (see at least Ferguson [0091]: “In a further example, if the system is making a delivery near a busy area, the system may decide that using vehicles driven by a remote human driver or using semi-autonomous vehicles are safer or easier than fully autonomy vehicles for that situation. In yet a further example, the system may decide that it may not have the capabilities yet to operate on certain roads/areas and therefore may deploy a remotely-operated vehicle or human-driven vehicle.”; [0006]: “The fleet of mixed vehicles includes at least two of: a semi-autonomous vehicle, a fully-autonomous vehicle, a vehicle remotely operated by a human, or a human-driven vehicle.”);
and selecting the first vehicle from the plurality of candidate AVs or from the plurality of human-driven vehicles, the first vehicle being an AV (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service. In various embodiments, the mixed fleet includes combinations of fully-autonomous vehicles, semi-autonomous vehicles, vehicles driven by a local human driver, and vehicles driven by a remote human driver, such as combinations of two or more such vehicle types. In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate)...In yet another example, a customer, based on preferences or due to differences in price, may specifically request a fully-autonomous vehicle.”).
Ferguson in view of Matthiesen and Haas fail to expressly disclose a conditional user preference having an AV state and a non-AV state. However, Okabe teaches
the user preference data indicating a conditional user preference having an autonomous vehicle (AV) state and a non-AV state (see at least Okabe [0055]: “According to the delivery management system 1 according to the present embodiment, the first vehicle V1 is assigned as a delivery vehicle to a user who requests a requested item to be performed at a delivery destination. That is, when it is necessary for a person (a driver) to perform a requested item other than delivery of a product to a user at a delivery destination, the product is delivered by the first vehicle V1. On the other hand, for a user who does not request a requested item to be performed at a delivery destination, the second vehicle V2 is assigned as a delivery vehicle. That is, when it is necessary only to hand over a product to a user at a delivery destination, the product is delivered by the second vehicle V2. Therefore, it is possible to more favorably use the first vehicle V1 driven by a driver or the second vehicle V2, which is an autonomous vehicle, as a delivery vehicle.”);
generating an AV transportation service description for the first transportation service using the AV state of the conditional user preference (see at least Okabe [0043]: “Further, when no requested item is inputted in the requested item field of the user information about the one user, the selection unit 221 selects the second vehicle V2 as the delivery vehicle to deliver the product to the one user.”; [0053]: “Next, at S204, the delivery plan generated at S203 is transmitted to the driver terminal 300 or the second vehicle V2. At this time, the delivery plan with the first vehicle V1 is transmitted to the driver terminal 300. On the other hand, the delivery plan with the second vehicle V2 is transmitted to the second vehicle V2.”; Okabe [0018] teaches the second vehicle is an autonomous vehicle);
generating a non-AV transportation service description for the first transportation service using the non-AV state of the conditional user preference (see at least Okabe [0043]: “Therefore, when some requested item is inputted in the requested item field of the user information about the one user, the selection unit 221 selects the first vehicle V1 as the delivery vehicle to deliver the product to the one user. As described above, a driver is in the first vehicle V1. Therefore, by delivering the product to the one user by the first vehicle V1, it becomes possible to perform the requested item by the driver of the first vehicle V1 at the delivery destination.”; [0053]: “Next, at S204, the delivery plan generated at S203 is transmitted to the driver terminal 300 or the second vehicle V2. At this time, the delivery plan with the first vehicle V1 is transmitted to the driver terminal 300. On the other hand, the delivery plan with the second vehicle V2 is transmitted to the second vehicle V2.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system taught by Ferguson in view of Matthiesen and Haas with the conditional preference taught by Okabe with reasonable expectation of success. Okabe is directed towards the related field of managing delivery of goods by a vehicle. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson in view of Matthiesen and Haas with Okabe to prevent difficulties in performing a requested service (see at least Okabe [0019]: “It is possible to hand over the goods to the user no matter which of the first vehicle and the second vehicle is the delivery vehicle. However, it may be requested to perform a predetermined event other than handing over the goods to the user at the time of delivering the goods to a delivery destination. The predetermined event is, for example, placement of the goods or collection of an article other than the goods. At this time, when the goods are delivered by the second vehicle, which is an autonomous vehicle, it may be difficult to perform the predetermined event at the delivery destination because a driver is not in the second vehicle.”).
Regarding claim 18, this claim recites a method for the system of claim 7 as explained above. Therefore, claim 18 is rejected for the same rationale as claim 7.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over Ferguson in view of Matthiesen and Haas, and further in view of Blume et al., U.S. Patent Application Publication No. 2022/0107650 A1 (hereinafter Blume).
Regarding claim 10, Ferguson in combination with Matthiesen and Haas teach all elements of the system according to claim 1 as explained above. Ferguson further teaches
accessing second transportation service request data describing a second transportation service requested by a second user via a second user computing device (see at least Ferguson [0092]: “In various embodiments, the system can determine requests for services from multiple customers located near each other, and can determine a path to deliver the services to the multiple customers using the selected vehicle.”);
determining that the second transportation service is suitable for execution by at least one of the plurality of AVs of the mixed fleet of vehicles (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service. In various embodiments, the mixed fleet includes combinations of fully-autonomous vehicles, semi-autonomous vehicles, vehicles driven by a local human driver, and vehicles driven by a remote human driver, such as combinations of two or more such vehicle types. In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate)…In yet another example, a customer, based on preferences or due to differences in price, may specifically request a fully-autonomous vehicle.”);
and instructing at least one of the plurality of AVs to execute the second transportation service (see at least Ferguson [0092]: “In block 1408, the system transmits a message to the selected vehicle to perform a portion of the service or all of the service…In various embodiments, the system can determine requests for services from multiple customers located near each other, and can determine a path to deliver the services to the multiple customers using the selected vehicle.”).
Ferguson in view of Matthiesen and Haas fail to expressly disclose a user confirming an AV for the transportation service. However, Blume teaches
prompting the second user to confirm acceptance of an AV for the second transportation service (see at least Blume [0060]: “In addition or alternatively, the operator 432 may also select a “ready” option, for example, via the application or website or a button of the autonomous vehicle (such as user input 150), to confirm that the autonomous vehicle is ready to begin a trip to the delivery location.”);
receiving, from the second user, a confirmation in response to the prompting (see at least Blume [0060]: “In addition or alternatively, the operator 432 may also select a “ready” option, for example, via the application or website or a button of the autonomous vehicle (such as user input 150), to confirm that the autonomous vehicle is ready to begin a trip to the delivery location. Selecting this option may dispatch or cause the autonomous vehicle to travel from the loading location to the delivery location. In response, if using the client computing device 430, the application or website may send a notification indicating the same to the retail computing system 440 confirming that the autonomous vehicle has been dispatched to the delivery location. Alternatively, if a button within the autonomous vehicle is used, the autonomous vehicle may send a signal to the dispatching computing system 410 indicating that the autonomous vehicle is now traveling from the loading location to the delivery location.”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the system taught by Ferguson in view of Matthiesen and Haas with the confirmation taught by Blume with reasonable expectation of success. Blume is directed towards the related field of delivery of goods by autonomous vehicles. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson in view of Matthiesen and Haas with the confirmation taught by Blume to improve efficiency (see at least Blume [0015]: “The features described herein may provide a practical and efficient way to deliver goods to a user using autonomous vehicles.”).
Claim 20 is rejected under 35 U.S.C. 103 as being unpatentable over Ferguson in view of Cooper, U.S. Patent Application Publication No. 2018/0356823 A1.
Regarding claim 20, Ferguson teaches a method of managing a mixed fleet of vehicles to execute transportation services (Ferguson Fig. 14), the method comprising:
accessing user preference data describing preferences of a user (see at least Ferguson [0090]: “In block 1404, the parameters for the service are determined. In various embodiments, the parameters may include the customer's 202 preference for service providers”),
accessing first transportation service request data describing a first transportation service requested by the user via a user computing device (see at least Ferguson [0089]: “In block 1402, the fleet management module 120 receives a request for a service either directly from the customer 202 or from the customer 202 via the central server 110.”);
analyzing the first transportation service request data against AV capability data for a plurality of AVs of the mixed fleet of vehicle (see at least Ferguson [0091]: “In block 1406, a vehicle is selected from a fleet of mixed vehicles based on the determined parameters, to perform at least a portion of the service…In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate).”),
the AV capability data describing operational capabilities of each AV of the plurality of AVs (see at least Ferguson [0091]: “In various embodiments, these parameters may be related to the order details (e.g., what the customer requires), the capabilities of the vehicles in the fleet (e.g., what types of conditions the vehicles can handle), and additional considerations by the system (e.g., some vehicles in fleet may be more cost-effective to operate)…In another example, if the item that the customer ordered does not fit into an autonomous robot vehicle compartment, the system may need to dispatch a vehicle driven by a human driver.”);
selecting a plurality of candidate AVs from the mixed fleet of vehicles using the AV transportation service description (see at least Ferguson [0072]-[0073]: “In some embodiments of the robot fleet, the autonomous robots within the fleet are further configured to be part of a sub-fleet of autonomous robots, and each sub-fleet is configured to operate independently or in tandem with multiple sub-fleets having two or more sub-fleets (100-a, 100-b). For example, a package delivery service is configured to offer multiple levels of service such as “immediate dedicated rush service,” “guaranteed morning/ afternoon delivery service,” or “general delivery service.” A service provider could then have a dedicated sub-fleet of delivery vehicles for each type of service within their overall fleet of vehicles.”);
selecting a plurality of candidate human-driven vehicles from the mixed fleet of vehicles using the non-AV transportation service description (see at least Ferguson [0091]: “In a further example, if the system is making a delivery near a busy area, the system may decide that using vehicles driven by a remote human driver or using semi-autonomous vehicles are safer or easier than fully autonomy vehicles for that situation. In yet a further example, the system may decide that it may not have the capabilities yet to operate on certain roads/areas and therefore may deploy a remotely-operated vehicle or human-driven vehicle.”; [0006]: “The fleet of mixed vehicles includes at least two of: a semi-autonomous vehicle, a fully-autonomous vehicle, a vehicle remotely operated by a human, or a human-driven vehicle.”);
and instructing the first vehicle to begin executing the first transportation service (see at least Ferguson [0092]: “In block 1408, the system transmits a message to the selected vehicle to perform a portion of the service or all of the service.”).
Ferguson fails to expressly disclose a user preference having an AV state and a non-AV state. However, Cooper teaches
the user preference data indicating a conditional user preference having an autonomous vehicle (AV) state and a non-AV state, the conditional user preference relating to at least one of payload delivery location, walking distance tolerance, or service interaction requirements that differ between the AV state and the non-AV state (see at least Cooper [0091]: “As a specific example, a serviceable point profile may identify one or more preferred delivery locations for shipments/items to be delivered to a particular delivery address (e.g., a geocode accurately identifying the location of the front porch of a particular residence). In various embodiments, the serviceable point profile may identify a first delivery location at the corresponding delivery address for manual deliveries (e.g., deliveries made by a carrier employee should be placed on a front porch of the address) and/or may identify a second delivery location at the corresponding delivery address for autonomous deliveries (e.g., deliveries made by an autonomous UAV should be deposited on a second-story balcony of the address).”; Cooper teaches at least the conditional user preference relating to a payload delivery location),
the user preference data being associated with a user account of the first user and applicable to a plurality of transportation service requests submitted under the user account (see at least Cooper [0087]: “For example, the mapping computing entity 110 may be configured to retrieve information/data from the shipment/item profile that identifies the intended recipient, and the mapping computing entity 110 may be configured to generate and transmit a query to a recipient preference database (e.g., operated by a separate computing entity and/or by the same computing entity) determine whether the recipient has expressed a preference for autonomous delivery of shipments/items.”; [0168]: “In such embodiments, the mapping computing entity 110 may retrieve information/data stored within a delivery destination profile and/or a customer profile to determine whether a particular delivery destination satisfies one or more preference criteria when reassigning shipments/items for manual delivery. Responsive to determining that a particular destination serviceable point and/or customer profile satisfies the preference criteria, the mapping computing entity 110 may reassign a different shipment/item for manual delivery such that a shipment/item destined for the delivery serviceable point determined to satisfy the preference criteria is delivered autonomously.”);
prior to selecting a vehicle to execute the first transportation service, generating an AV transportation service description for the first transportation service using the AV state of the conditional user preference (see at least Cooper [0091]: “As a specific example, a serviceable point profile may identify one or more preferred delivery locations for shipments/items to be delivered to a particular delivery address (e.g., a geocode accurately identifying the location of the front porch of a particular residence). In various embodiments, the serviceable point profile may identify a first delivery location at the corresponding delivery address for manual deliveries (e.g., deliveries made by a carrier employee should be placed on a front porch of the address) and/or may identify a second delivery location at the corresponding delivery address for autonomous deliveries (e.g., deliveries made by an autonomous UAV should be deposited on a second-story balcony of the address).”),
wherein the AV state corresponds to service parameters based on AV capabilities (see at least Cooper [0087]: “Similarly, the mapping computing entity 110 may compare the weight of the item against weight criteria for autonomous delivery to determine whether the shipment/item is within an appropriate weight range to enable autonomous delivery. For example, the weight criteria may specify a maximum and/or a minimum weight for items to be delivered via an autonomous vehicle 140. The weight criteria may be established based on a weight limit of an autonomous vehicle 140, such that items are only eligible for autonomous delivery if the propulsion mechanisms of the autonomous vehicle 140 are capable of maneuvering the combined weight of the autonomous vehicle 140 and the shipment/item. Finally, the mapping computing entity 110 may compare the contents of the shipment/item against a listing of permitted and/or excluded item contents to determine whether the contents of the shipment/item are eligible for autonomous delivery.”);
prior to selecting a vehicle to execute the first transportation service, generating a non-AV transportation service description for the first transportation service using the non-AV state of the conditional user preference (see at least Cooper [0091]: “As a specific example, a serviceable point profile may identify one or more preferred delivery locations for shipments/items to be delivered to a particular delivery address (e.g., a geocode accurately identifying the location of the front porch of a particular residence). In various embodiments, the serviceable point profile may identify a first delivery location at the corresponding delivery address for manual deliveries (e.g., deliveries made by a carrier employee should be placed on a front porch of the address) and/or may identify a second delivery location at the corresponding delivery address for autonomous deliveries (e.g., deliveries made by an autonomous UAV should be deposited on a second-story balcony of the address).”)
after generating both the AV transportation service description and the non-AV transportation service description, selecting a first vehicle from the plurality of candidate AVs or from the plurality of candidate human-driven vehicles, the first vehicle being an AV (see at least Cooper [0145]: “Accordingly, autonomous-delivery is available to all 3 autonomous-delivery eligible serviceable points ( Residences 1000 e, 1000 k, and 1000 o; indicated with the “D” indicator and shaded for emphasis)…The autonomous vehicle(s) 140 would be expected to complete all of the autonomous deliveries before the manual delivery vehicle 100 completes all of the manual deliveries within the same geofenced area 1060.”; [0168]: “Responsive to determining that a particular destination serviceable point and/or customer profile satisfies the preference criteria, the mapping computing entity 110 may reassign a different shipment/item for manual delivery such that a shipment/item destined for the delivery serviceable point determined to satisfy the preference criteria is delivered autonomously”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the instant application to modify the method taught by Ferguson with the AV and non-AV states taught by Cooper with reasonable expectation of success. Cooper is directed towards the related field of performing a delivery manually or autonomously based on the delivery location. Therefore, one of ordinary skill in the art would be motivated to combine Ferguson with the AV and non-AV states taught by Cooper to improve delivery efficiency (see at least Cooper [0002]: “For example, selecting an appropriate delivery time and delivery route may significantly impact delivery efficiency, and accordingly additional innovation is needed to enable autonomous vehicles to efficiently deliver items to various locations.”).
Conclusion
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.
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/ELIZABETH J SLOWIK/Examiner, Art Unit 3662
/ANISS CHAD/Supervisory Patent Examiner, Art Unit 3662
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