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 is a Non-Final action on the merits of this application. Claims 1-20 are rejected and currently pending, as discussed below.
Information Disclosure Statement
The information disclosure statements filed 06/27/2025 and 09/16/2025 fail to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. The statements have been placed in the application file, but the information referred to therein has not been considered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5, and 8-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
101 Analysis – Step 1
Independent claims 1, 17, and 19 are directed to a method, vehicle, and non-transitory machine-readable medium. Therefore, claims 1, 17, and 19 are within at least one of the four statutory categories.
101 Analysis – Step 2A, Prong I
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the following groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. The other analogous 17 and 19 are rejected for the same reasons as the representative claim 1 as discussed here. Claim 1 recites:
A method for optimizing a delivery of a plurality of items to a plurality of delivery destinations, the plurality of items comprising a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination, the method comprising:
determining a mass of each of the plurality of items, the mass of the items including a mass of the first item and a mass of the second item;
calculating a value of a first vehicle parameter, the first vehicle parameter being dependent on the mass of the first item and the mass of the second item, for a first delivery route, the first delivery route configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second item;
calculating the value of the first vehicle parameter for a second delivery route, the second delivery route configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first item;
determining an optimized delivery route for a vehicle that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter; and
programming, into a route guidance system of the vehicle for routing the vehicle, the optimized delivery route having the optimized value of the first vehicle parameter, thereby improving energy efficiency routing of the vehicle.
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, calculating and determining all the various data in the context of this claim encompasses a person looking at data collected (received, detected, etc.) and forming a simple judgement (determination, analysis, comparison, etc.) either mentally or using a pen and paper. Accordingly, the claim recites at least one abstract idea. The Examiner notes that under MPEP 2106.04(a)(2)(III), the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. CyberSource Corp. v. Retail Decisions, Inc., 654 F.3d 1366, 1372, 99 USPQ2d 1690, 1695 (Fed. Cir. 2011). As the Federal Circuit explained, "methods which can be performed mentally, or which are the equivalent of human mental work, are unpatentable abstract ideas the ‘basic tools of scientific and technological work’ that are open to all.’" 654 F.3d at 1371, 99 USPQ2d at 1694 (citing Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972)). See also Mayo Collaborative Servs. v. Prometheus Labs. Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 ("‘[M]ental processes[] and abstract intellectual concepts are not patentable, as they are the basic tools of scientific and technological work’" (quoting Benson, 409 U.S. at 67, 175 USPQ at 675)); Parker v. Flook, 437 U.S. 584, 589, 198 USPQ 193, 197 (1978) (same).
101 Analysis – Step 2A, Prong II
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”):
A method for optimizing a delivery of a plurality of items to a plurality of delivery destinations, the plurality of items comprising a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination, the method comprising:
determining a mass of each of the plurality of items, the mass of the items including a mass of the first item and a mass of the second item;
calculating a value of a first vehicle parameter, the first vehicle parameter being dependent on the mass of the first item and the mass of the second item, for a first delivery route, the first delivery route configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second item;
calculating the value of the first vehicle parameter for a second delivery route, the second delivery route configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first item;
determining an optimized delivery route for a vehicle that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter; and
programming, into a route guidance system of the vehicle for routing the vehicle, the optimized delivery route having the optimized value of the first vehicle parameter, thereby improving energy efficiency routing of the vehicle.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application.
Regarding the additional limitations above, the examiner submits that these limitations are insignificant extra-solution activities. In particular, the step of programming the optimized delivery route is also recited at a high level of generality and amounts to no more than mere post solution action, which is a form of insignificant extra-solution activity. Lastly, claims 1, 17, and 19 further recite a vehicle, a controller, a non-transitory machine-readable medium, and a processor. These limitations merely describes how to generally “apply” the otherwise mental judgements in a generic or general purpose vehicle control environment. See Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot transform a patent-ineligible abstract idea into a patent-eligible invention.”). The device(s) and processor(s) are recited at a high level of generality and merely automates the steps.
Thus, taken alone, the additional elements do not integrate the abstract idea into a practical application. Further, looking at the additional limitation(s) as an ordered combination or as a whole, the limitation(s) add nothing that is not already present when looking at the elements taken individually. For instance, there is no indication that the additional elements, when considered as a whole, reflect an improvement in the functioning of a computer or an improvement to another technology or technical field, apply or use the above-noted judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement/use the above-noted judicial exception with a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is not more than a drafting effort designed to monopolize the exception (MPEP § 2106.05). Accordingly, the additional limitation(s) do/does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 9 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform the steps amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. And as discussed above, the additional limitations discussed above are insignificant extra-solution activities.
The additional limitation of programming the optimized delivery route is well-understood, routine and conventional activity because the specification does not provide any indication that the route guidance system is anything other than a conventional vehicle guidance system. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner.
Dependent claims 2-5, 8-16, 18, and 20 do not recite any further limitations that cause the claims to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or additional elements that do not integrate the judicial exception into a practical application. Therefore, dependent claims 2-5, 8-16, 18, and 20 are not patent eligible under the same rationale as provided for in the rejection of claim 1.
Examiner notes that claims 6 and 7 are sufficient to integrate the abstract idea into a practical application via causing the vehicle to drive, following one of the first and second delivery routes, under autonomous control. Claims 12, 18, and 20 recite this limitation in the alternative, and therefore are insufficient to integrate the abstract idea into a practical application. Claims 12, 18, and 20, under broadest reasonable interpretation, cover embodiments where the route is only programmed into the route guidance system and the vehicle is not caused to drive.
Therefore, claims 1-5 and 8-20 are ineligible under 35 USC §101.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being anticipated by US 20210035064 A1, with an earliest priority date of 06/27/2018, hereinafter "Nishikawa", further in view of US 20190325376 A1, filed June 18th, 2019, hereinafter “Khasis”.
Regarding Claim 1, Nishikawa teaches A method for optimizing a delivery of a plurality of items to a plurality of delivery destinations. See at least [0207] and figure 8.
the plurality of items comprising a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination. See at least [0208] and figures 3-5, first item 1234-5678-90 (delivery destination GUEST0001) and second item 1234-5678-89 (delivery destination GUEST0002).
the method comprising: determining a mass of each of the plurality of items, the mass of the items including a mass of the first item and a mass of the second item. See at least [0182] and figure 3, wherein a package DB stores information on a first package and a second package, where the first package has a first mass (CC kg) and the second package has a second mass (DD kg).
calculating a value of a first vehicle parameter. See at least [0208] and figure 8, step S2, wherein an evaluation value (first vehicle parameter) is calculated for each route, TR0001 and TR002.
the first vehicle parameter being dependent on the mass of the first item and the mass of the second item, for a first delivery route. See at least [0183]-[0184], wherein the evaluation value calculator, which calculates the evaluation value (first vehicle parameter) is dependent on the weight of each package, and see at least [0322] and figure 34, wherein the first vehicle parameter E is calculated using a formula dependent on wik (weight of each package, or the mass of the first and second items).
the first delivery route configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second item. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0001, and see at least [0205] and figure 4, wherein TR0001 stops at the first delivery destination (GUEST0001) before the second delivery destination (GUEST0002). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
calculating the value of a first vehicle parameter for a second delivery route. See at least [0208] and figure 8, step S2, wherein an evaluation value (first vehicle parameter) is calculated for each route, TR0001 and TR002.
the second delivery route configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first item. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0002, and see at least [0205] and figure 4, wherein TR0002 stops at the second delivery destination (GUEST0002) before the first delivery destination (GUEST0001). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
determining an optimized delivery route for a vehicle that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter. See at least [0179] and [0209]-[0210] and figure 8, step S3, wherein an optimized delivery route is determined for a delivery vehicle that minimizes the evaluation value, or optimizes the value of the first vehicle parameter. This optimizes delivery route is selected from TR0001 and TR0002, so it comprises both the first and second delivery destinations.
and programming, into a route guidance system of the vehicle for routing the vehicle, the optimized delivery route having the optimized value of the first vehicle parameter, thereby improving energy efficiency. See at least [0210], wherein the optimized delivery route is transmitted to a delivery person terminal 2, and see at least [0206], wherein the delivery person terminal 2 is associated with the delivery vehicle, and the optimized route has a minimum cost, and see at least [0004]-[0005], wherein the optimized delivery route improves the energy efficiency of the driver as they depart the vehicle on foot to deliver each package. See at least [0179], wherein delivery person terminal 2 is a car navigation system provided on the delivery vehicle.
Nishikawa remains silent on improving efficiency routing of the vehicle. However, Nishikawa does teach the first vehicle parameter comprising an amount of energy consumed by the driver of the vehicle in taking the optimized delivery route (see at least [0183]).
Khasis teaches thereby improving efficiency routing of the vehicle. See at least [0040] and [0103], wherein the vehicle route is optimized to reduce energy consumption. Additionally, see at least [0079], wherein the vehicle route is optimized to obtain the most cost-efficient route possible, the cost including fuel costs.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of improving energy efficiency of the vehicle. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 2, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on wherein the first vehicle parameter comprises at least one of: an amount of energy remaining in an energy store of the vehicle; or an amount of energy consumed by the vehicle in taking the optimized delivery route.
Khasis teaches wherein the first vehicle parameter comprises at least one of: an amount of energy remaining in an energy store of the vehicle; or an amount of energy consumed by the vehicle in taking the optimized delivery route. See at least [0076]-[0080], and [0133], wherein the routing of the vehicle is optimized in view of the current fuel capacity of the vehicle, and the estimated fuel consumption calculated using the vehicle’s specific energy utilization per unit of time or distance.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of a vehicle routing parameter including a current energy capacity and an amount of energy needed to take a route. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 3, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on wherein the first vehicle parameter comprises an amount of pollution emitted by the vehicle in taking the optimized delivery route.
Khasis teaches wherein the first vehicle parameter comprises an amount of pollution emitted by the vehicle in taking the optimized delivery route. See at least [0040], wherein the vehicle route is optimized in view of a carbon dioxide emissions parameter, representing the vehicle’s emissions as it takes the optimized route.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of a vehicle routing parameter including an amount of pollution emitted by the vehicle in taking the optimized delivery route. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 4, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on wherein the first vehicle parameter comprises at least one of: a top speed of the vehicle; a driving range of the vehicle; or a driving time of the vehicle.
Khasis teaches wherein the first vehicle parameter comprises at least one of: a top speed of the vehicle; a driving range of the vehicle; or a driving time of the vehicle. See at least [0041], wherein the vehicle route is optimized in view of maximum speed limits along the road segments in the route. See at least [0076]-[0079], wherein the vehicle route is optimized in view of the vehicle’s reach, representing how far a vehicle can travel with its current fuel level. See at least [0066]-[0067], wherein the vehicle route is optimized in view of a travel time parameter.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of a vehicle routing parameter including a top speed of the vehicle, a driving range of the vehicle, or a driving time of the vehicle. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 5, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa additionally teaches wherein the first parameter comprises at least one of: a number of items deliverable by the vehicle; or a number of trips of the vehicle to deliver the items. See at least [0320], wherein the evaluation value is additionally dependent on a number of route segments in the delivery route, and the number of items for each route segment.
Regarding Claim 6, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on transmitting a signal which, when received by the vehicle, causes the vehicle to drive, following one of the first and second delivery routes, under autonomous control.
Khasis teaches transmitting a signal which, when received by the vehicle, causes the vehicle to drive, following one of the first and second delivery routes, under autonomous control. See at least [0120], wherein a preferred, or optimal, route is transmitted from the optimization server to the vehicle. Additionally, see at least [0073], wherein the optimization server is communicatively coupled to an autonomous vehicle.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of transmitting a signal, which causes the vehicle to drive, following an optimal delivery route under autonomous control. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 7, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on transmitting a signal which, when received by a fleet management module, causes the fleet management module to transmit instructions to at least one vehicle in a fleet of vehicles to drive, following one of the first and second delivery routes, under autonomous control.
Khasis teaches transmitting a signal which, when received by a fleet management module, causes the fleet management module to transmit instructions to at least one vehicle in a fleet of vehicles to drive, following one of the first and second delivery routes, under autonomous control. See at least [0120], wherein a preferred, or optimal, route is transmitted from the optimization server to the vehicle. Additionally, see at least [0073]-[0075], wherein the optimization server is communicatively coupled to a vehicle fleet comprising one or more autonomous vehicles. Additionally, see at least [0085], wherein a separate communication system is used to manage communications between the vehicles of the fleet.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of a fleet management module and transmitting a signal, which causes the vehicle to drive, following an optimal delivery route under autonomous control. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 8, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa additionally teaches in response to an input describing a new destination. See at least [0251] and [0254] and figure 19, step S54, wherein a new package, or item to be delivered to a new destination, is picked up and the new destination is input by a user of the vehicle to the server.
modifying the first delivery route to derive a modified first delivery route, the modified first delivery route stopping at the first delivery destination, then the new destination, then the second delivery destination. See at least [0257]-[0258], wherein the route the vehicle is on (first or second delivery route) is modified to include the new destination. [0257] points to S35, described in [0242], as having an identical process. In S35, a first route starting at M0 (current location of vehicle, so the first delivery destination if the vehicle is currently on the first delivery route) is modified to derived the route M0-M1-M2 (first delivery destination, new destination, second delivery destination) among all of the other potential route combinations calculated.
and/or modifying the second delivery route to derive a modified second delivery route, the modified second delivery route stopping at the second delivery destination, then the new destination, then the first delivery destination. See at least [0257]-[0258], wherein the route the vehicle is on (first or second delivery route) is modified to include the new destination. [0257] points to S35, described in [0242], as having an identical process. In S35, a first route starting at M0 (current location of vehicle, so the second delivery destination if the vehicle is currently on the second delivery route) is modified to derived the route M0-M1-M2 (second delivery destination, new destination, first delivery destination) among all of the other potential route combinations calculated.
and calculating the value of the first vehicle parameter for the modified first delivery route and the modified second delivery route. See at least [0258], wherein the evaluation value, or first vehicle parameter, is calculated for the extracted, or modified/derived, first/second delivery routes. Nishikawa teaches taking whatever optimized route the vehicle is currently on, so either the first or second delivery routes TR0001/TR002 as discussed above, and deriving every combination of the new destination and remaining destination(s) to modify the vehicle’s route.
Regarding Claim 9, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa additionally teaches further comprising selecting the first vehicle parameter and/or adjusting the first vehicle parameter. See at least [0349], wherein a threshold for the first vehicle parameter is set and adjusted based on the capabilities of the delivery person.
Regarding Claim 10, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on determining whether there exists a non-refueling delivery route such that a first vehicle can deliver each of the plurality of items to its respective delivery destination, without stopping to refuel, such that the value of the first vehicle parameter is optimized.
Khasis teaches determining whether there exists a non-refueling delivery route such that a first vehicle can deliver each of the plurality of items to its respective delivery destination, without stopping to refuel, such that the value of the first vehicle parameter is optimized. See at least [0076], wherein when determining a route with the lowest cost (determining a route that optimizes the first vehicle parameter), the optimal route is checked to account for any stops for fuel needed, or whether the vehicle does not need to refuel.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of checking if a need to refuel exists when determining an optimized delivery route. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 11, Nishikawa and Khasis in combination disclose all of the limitations of Claim 10 as discussed above, and Nishikawa remains silent on wherein, in response to a determination that no non- refueling delivery route exists such that the first vehicle can deliver each item to its respective delivery destination without refueling, the method further comprises: calculating the value of the first vehicle parameter for: a composite route for the first vehicle to deliver each item to its respective delivery destinations in two sub-routes, stopping to refuel in between the two sub-routes; and for a sum of a first vehicle route and a second vehicle route, the first vehicle route being a route for the first vehicle to deliver a first subset of the plurality of items to their respective delivery destinations in one trip without refueling, and the second vehicle route being a route for a second vehicle to deliver a second subset of the plurality of items, the second subset comprising the remaining items, to their respective destinations in one trip without refueling.
Khasis teaches wherein, in response to a determination that no non- refueling delivery route exists such that the first vehicle can deliver each item to its respective delivery destination without refueling. See at least [0076], wherein the optimal route is checked to see if a refueling stop is needed.
the method further comprises: calculating the value of the first vehicle parameter for: a composite route for the first vehicle to deliver each item to its respective delivery destinations in two sub-routes, stopping to refuel in between the two sub-routes. See at least [0079] and [0133], wherein the original optimal route is split into two sub-routes and a refueling stop is inserted between the sub-routes, and the potential composite routes are analyzed by calculating the cost efficiency, or the first vehicle parameter, for each route after inserting the refueling stop.
and for a sum of a first vehicle route and a second vehicle route, the first vehicle route being a route for the first vehicle to deliver a first subset of the plurality of items to their respective delivery destinations in one trip without refueling, and the second vehicle route being a route for a second vehicle to deliver a second subset of the plurality of items, the second subset comprising the remaining items, to their respective destinations in one trip without refueling. See at least [0084]-[0087], wherein a multi-vehicle route is used in optimization, wherein the multi-vehicle route comprises a first route with a first subset of destinations for a first vehicle, and a second route with a second subset of destinations for a second vehicle, and see at least [0091] wherein the multi-vehicle route is optimized in view of the fuel tank/battery capacity of the vehicles involved in the route.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of comparing the first vehicle parameter for composite and sum routes in view of a need to refuel. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 12, Nishikawa and Khasis in combination disclose all of the limitations of Claim 11 as discussed above, and Nishikawa remains silent on wherein, if the value of the first vehicle parameter is lower for the composite route then the method comprises: transmitting a signal to the first vehicle which, when received by the first vehicle causes the composite route to be programmed into a route guidance system of the first vehicle and/or causes the first vehicle to begin driving the composite route, under autonomous control; and, if the value of the first vehicle parameter is lower for a sum of the first and second vehicle routes, then the method comprises: transmitting a signal to a fleet management module to cause the fleet management module to cause the first vehicle route to be programmed into the route guidance system of the first vehicle and the second vehicle route to be programmed into a route guidance system of a second vehicle and/or cause the first and second vehicles to begin driving the first and second vehicles routes, respectively, under autonomous control.
Khasis teaches wherein, if the value of the first vehicle parameter is lower for the composite route then the method comprises. See at least [0076]-[0079], [0091], [0130], and [0133], and figure 9A, wherein all of the potential routes, including the refueling route (composite route) and the multi-vehicle route (sum route) are checked for the lowest cost value, and the lowest cost value route is the one the autonomous vehicle(s) are directed to follow.
transmitting a signal to the first vehicle which, when received by the first vehicle causes the composite route to be programmed into a route guidance system of the first vehicle and/or causes the first vehicle to begin driving the composite route, under autonomous control. See at least [0073] and [0131], wherein the server communicates through a network (transmitting a signal) to cause vehicles to follow routes under autonomous control.
and, if the value of the first vehicle parameter is lower for a sum of the first and second vehicle routes, then the method comprises. See at least [0076]-[0079], [0091], [0130], and [0133], and figure 9A, wherein all of the potential routes, including the refueling route (composite route) and the multi-vehicle route (sum route) are checked for the lowest cost value, and the lowest cost value route is the one the autonomous vehicle(s) are directed to follow.
transmitting a signal to a fleet management module to cause the fleet management module to cause the first vehicle route to be programmed into the route guidance system of the first vehicle and the second vehicle route to be programmed into a route guidance system of a second vehicle and/or cause the first and second vehicles to begin driving the first and second vehicles routes, respectively, under autonomous control. See at least [0073] and [0131], wherein the server communicates through a network (transmitting a signal) to cause vehicles to follow routes under autonomous control.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of comparing the first vehicle parameter for composite and sum routes in view of a need to refuel and controlling the vehicle(s) to follow the route with the lowest first vehicle parameter. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 13, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa additionally teaches wherein, if the vehicle delivering the plurality of items according to a given delivery route is unable to deliver one item of the plurality of items, then the method comprises. See at least [0241], wherein each item is checked to see if the driver is able to deliver it.
re-calculating the value of the first vehicle parameter for the given delivery route based on a mass of the one item of the plurality of items that the vehicle is unable to deliver. See at least [0143] and [0241]-[0245], wherein when an item is unable to be delivered, the evaluation value of all potential routes containing the rest of the destination locations (which includes the given delivery route), is re-calculated with the undeliverable package considered as extra weight that has to be carried for the rest of the route (i.e., re-calculated based on the mass of the undeliverable item).
calculating the value of the first vehicle parameter for a further delivery route being a route to stop at the respective delivery destinations of all undelivered items. See at least [0143] and [0241]-[0245], wherein when an item is unable to be delivered, the evaluation value of all potential routes containing the rest of the destination locations and all undelivered items, is re-calculated.
and determining which one of the given delivery route or the further delivery route optimizes the first vehicle parameter. See at least [0246], wherein the optimal delivery route is determined from the given delivery route and the extracted further delivery routes.
Nishikawa remains silent on determining a location of a depot at which the vehicle is able to drop off the one item it is unable to deliver.
Khasis teaches determining a location of a depot at which the vehicle is able to drop off the one item it is unable to deliver. See at least [0094], wherein when the vehicle has an undeliverable item, a further route is determined where the vehicle is directed to unload the undelivered item at a storage facility, or depot.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of directing vehicles with undeliverable items to drop off the undeliverable items at a depot. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 14, Nishikawa and Khasis in combination disclose all of the limitations of Claim 13 as discussed above, and Nishikawa additionally teaches wherein, in response to a determination that the further delivery route optimizes the first vehicle parameter, the method further comprises: causing the further delivery route to be programmed into a route guidance system of the vehicle. See at least [0210] and [0243], wherein, when the further delivery route and the original delivery route’s first vehicle parameters are calculated, the process goes back to S2-S4, described above in Claims 1/17/19, wherein the optimized delivery route is transmitted, or programmed into terminal 2, and see at least [0179], wherein terminal 2 is implemented in a car navigation system provided on the delivery vehicle.
Regarding Claim 15, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa remains silent on wherein the first vehicle parameter is also dependent on a mass of the vehicle configured to transport at least one of the items.
Khasis teaches wherein the first vehicle parameter is also dependent on a mass of the vehicle configured to transport at least one of the items. See at least [0079], wherein the current vehicle weight or the delivery vehicle is used in the calculation of the optimal route.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of the first vehicle parameter being dependent on a mass of the delivery vehicle. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 16, Nishikawa and Khasis in combination teach all of the limitations of Claim 1 as discussed above, and Nishikawa additionally teaches wherein: the first delivery route is a route to stop at the first delivery destination before the second delivery destination that optimizes the value of the first vehicle parameter. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0001, and see at least [0205] and figure 4, wherein TR0001 stops at the first delivery destination (GUEST0001) before the second delivery destination (GUEST0002). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
and/or the second delivery route is a route to stop at the second delivery destination before the first delivery destination that optimizes the value of the first vehicle parameter. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0002, and see at least [0205] and figure 4, wherein TR0002 stops at the second delivery destination (GUEST0002) before the first delivery destination (GUEST0001). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination. See at least [0179] and [0209]-[0210] and figure 8, step S3, wherein an optimized delivery route is determined for a delivery vehicle that minimizes the evaluation value, or optimizes the value of the first vehicle parameter. This optimizes delivery route is selected from TR0001 and TR0002, so it comprises both the first and second delivery destinations.
Regarding Claim 17, Nishikawa teaches A vehicle for optimizing a delivery of a plurality of items to a plurality of delivery destinations. See at least figure 1, delivery person terminal 2, and see at least [0179], wherein terminal 2 is implemented in a car navigation system provided on the delivery vehicle.
the plurality of items comprising a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination. See at least [0208] and figures 3-5, first item 1234-5678-90 (delivery destination GUEST0001) and second item 1234-5678-89 (delivery destination GUEST0002).
comprising: a controller programmed to determine a mass of each of the plurality of items, the mass of the items including a mass of the first item and a mass of the second item. See at least [0182] and figure 3, wherein a package DB stores information on a first package and a second package, where the first package has a first mass (CC kg) and the second package has a second mass (DD kg). See at least [0181] and figure 2.
calculate a value of a first vehicle parameter. See at least [0208] and figure 8, step S2, wherein an evaluation value (first vehicle parameter) is calculated for each route, TR0001 and TR002.
the first vehicle parameter being dependent on the mass of the first item and the mass of the second item, for a first delivery route. See at least [0183]-[0184], wherein the evaluation value calculator, which calculates the evaluation value (first vehicle parameter) is dependent on the weight of each package, and see at least [0322] and figure 34, wherein the first vehicle parameter E is calculated using a formula dependent on wik (weight of each package, or the mass of the first and second items).
the first delivery route configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second item. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0001, and see at least [0205] and figure 4, wherein TR0001 stops at the first delivery destination (GUEST0001) before the second delivery destination (GUEST0002). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
calculate the value of a first vehicle parameter for a second delivery route. See at least [0208] and figure 8, step S2, wherein an evaluation value (first vehicle parameter) is calculated for each route, TR0001 and TR002.
the second delivery route configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first item. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0002, and see at least [0205] and figure 4, wherein TR0002 stops at the second delivery destination (GUEST0002) before the first delivery destination (GUEST0001). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
determine an optimized delivery route for a vehicle that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter. See at least [0179] and [0209]-[0210] and figure 8, step S3, wherein an optimized delivery route is determined for a delivery vehicle that minimizes the evaluation value, or optimizes the value of the first vehicle parameter. This optimizes delivery route is selected from TR0001 and TR0002, so it comprises both the first and second delivery destinations.
and program, into a route guidance system of the vehicle for routing the vehicle, the optimized delivery route having the optimized value of the first vehicle parameter, thereby improving energy efficiency. See at least [0210], wherein the optimized delivery route is transmitted to a delivery person terminal 2, and see at least [0206], wherein the delivery person terminal 2 is associated with the delivery vehicle, and the optimized route has a minimum cost, and see at least [0004]-[0005], wherein the optimized delivery route improves the energy efficiency of the driver as they depart the vehicle on foot to deliver each package. See at least [0179], wherein delivery person terminal 2 is a car navigation system provided on the delivery vehicle.
Nishikawa remains silent on improving efficiency routing of the vehicle. However, Nishikawa does teach the first vehicle parameter comprising an amount of energy consumed by the driver of the vehicle in taking the optimized delivery route (see at least [0183]).
Khasis teaches thereby improving efficiency routing of the vehicle. See at least [0040] and [0103], wherein the vehicle route is optimized to reduce energy consumption. Additionally, see at least [0079], wherein the vehicle route is optimized to obtain the most cost-efficient route possible, the cost including fuel costs.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of improving energy efficiency of the vehicle. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 18, Nishikawa and Khasis in combination teach all of the limitations of Claim 17 as discussed above, and Nishikawa remains silent on wherein the controller is further programmed to determine whether there exists a non-refueling delivery route such that a first vehicle can deliver each item to its respective delivery destination, without stopping to refuel, such that the value of the first vehicle parameter is optimized; in response to a determination that no non-refueling delivery route exists such that the first vehicle can deliver each item to its respective delivery destination without refueling, calculating the value of the first vehicle parameter for: a composite route for the first vehicle to deliver each item to its respective delivery destinations in two sub-routes, stopping to refuel in between the two sub-routes; and for a sum of a first vehicle route and a second vehicle route, the first vehicle route being a route for the first vehicle to deliver a first subset of the plurality of items to their respective delivery destinations in one trip without refueling, and the second vehicle route being a route for a second vehicle to deliver a second subset of the plurality of items, the second subset comprising the remaining items, to their respective destinations in one trip without refueling, wherein, if the value of the first vehicle parameter is lower for the composite route, transmit a signal to the first vehicle which, when received by the first vehicle causes the composite route to be programmed into a route guidance system of the first vehicle and/or causes the first vehicle to begin driving the composite route, under autonomous control; and if the value of the first vehicle parameter is lower for a sum of the first and second vehicle routes, transmit a signal to a fleet management module to cause the fleet management module to cause the first vehicle route to be programmed into the route guidance system of the first vehicle and the second vehicle route to be programmed into a route guidance system of a second vehicle and/or cause the first and second vehicles to begin driving the first and second vehicles routes, respectively, under autonomous control.
Khasis teaches wherein the controller is further programmed to: determine whether there exists a non-refueling delivery route such that a first vehicle can deliver each item to its respective delivery destination, without stopping to refuel, such that the value of the first vehicle parameter is optimized. See at least [0076], wherein when determining a route with the lowest cost (determining a route that optimizes the first vehicle parameter), the optimal route is checked to account for any stops for fuel needed, or whether the vehicle does not need to refuel.
in response to a determination that no non-refueling delivery route exists such that the first vehicle can deliver each item to its respective delivery destination without refueling. See at least [0076], wherein the optimal route is checked to see if a refueling stop is needed.
calculating the value of the first vehicle parameter for: a composite route for the first vehicle to deliver each item to its respective delivery destinations in two sub-routes, stopping to refuel in between the two sub-routes. See at least [0079] and [0133], wherein the original optimal route is split into two sub-routes and a refueling stop is inserted between the sub-routes, and the potential composite routes are analyzed by calculating the cost efficiency, or the first vehicle parameter, for each route after inserting the refueling stop.
and for a sum of a first vehicle route and a second vehicle route, the first vehicle route being a route for the first vehicle to deliver a first subset of the plurality of items to their respective delivery destinations in one trip without refueling, and the second vehicle route being a route for a second vehicle to deliver a second subset of the plurality of items, the second subset comprising the remaining items, to their respective destinations in one trip without refueling. See at least [0084]-[0087], wherein a multi-vehicle route is used in optimization, wherein the multi-vehicle route comprises a first route with a first subset of destinations for a first vehicle, and a second route with a second subset of destinations for a second vehicle, and see at least [0091] wherein the multi-vehicle route is optimized in view of the fuel tank/battery capacity of the vehicles involved in the route.
wherein, if the value of the first vehicle parameter is lower for the composite route. See at least [0076]-[0079], [0091], [0130], and [0133], and figure 9A, wherein all of the potential routes, including the refueling route (composite route) and the multi-vehicle route (sum route) are checked for the lowest cost value, and the lowest cost value route is the one the autonomous vehicle(s) are directed to follow.
transmit a signal to the first vehicle which, when received by the first vehicle causes the composite route to be programmed into a route guidance system of the first vehicle and/or causes the first vehicle to begin driving the composite route, under autonomous control. See at least [0073] and [0131], wherein the server communicates through a network (transmitting a signal) to cause vehicles to follow routes under autonomous control.
and if the value of the first vehicle parameter is lower for a sum of the first and second vehicle routes. See at least [0076]-[0079], [0091], [0130], and [0133], and figure 9A, wherein all of the potential routes, including the refueling route (composite route) and the multi-vehicle route (sum route) are checked for the lowest cost value, and the lowest cost value route is the one the autonomous vehicle(s) are directed to follow.
transmit a signal to a fleet management module to cause the fleet management module to cause the first vehicle route to be programmed into the route guidance system of the first vehicle and the second vehicle route to be programmed into a route guidance system of a second vehicle and/or cause the first and second vehicles to begin driving the first and second vehicles routes, respectively, under autonomous control. See at least [0073] and [0131], wherein the server communicates through a network (transmitting a signal) to cause vehicles to follow routes under autonomous control.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of determining a need to refuel, determining a composite and a sum route in view of the need to refuel, and comparing the first vehicle parameter for composite and sum routes in view of a need to refuel and controlling the vehicle(s) to follow the route with the lowest first vehicle parameter. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 19, Nishikawa teaches A non-transitory machine-readable medium comprising instructions for optimizing a delivery of a plurality of items to a plurality of delivery destinations. See at least [0007].
the plurality of items comprising a first item deliverable to a first delivery destination and a second item deliverable to a second delivery destination. See at least [0208] and figures 3-5, first item 1234-5678-90 (delivery destination GUEST0001) and second item 1234-5678-89 (delivery destination GUEST0002).
which, when executed by a processor, causes the processor to: determine a mass of each of the plurality of items, the mass of the items including a mass of the first item and a mass of the second item. See at least [0182] and figure 3, wherein a package DB stores information on a first package and a second package, where the first package has a first mass (CC kg) and the second package has a second mass (DD kg). See at least [0181] and figure 2.
calculate a value of a first vehicle parameter. See at least [0208] and figure 8, step S2, wherein an evaluation value (first vehicle parameter) is calculated for each route, TR0001 and TR002.
the first vehicle parameter being dependent on the mass of the first item and the mass of the second item, for a first delivery route. See at least [0183]-[0184], wherein the evaluation value calculator, which calculates the evaluation value (first vehicle parameter) is dependent on the weight of each package, and see at least [0322] and figure 34, wherein the first vehicle parameter E is calculated using a formula dependent on wik (weight of each package, or the mass of the first and second items).
the first delivery route configured to stop at the first delivery destination before the second delivery destination to thereby deliver the first item before the second item. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0001, and see at least [0205] and figure 4, wherein TR0001 stops at the first delivery destination (GUEST0001) before the second delivery destination (GUEST0002). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
calculate the value of a first vehicle parameter for a second delivery route. See at least [0208] and figure 8, step S2, wherein an evaluation value (first vehicle parameter) is calculated for each route, TR0001 and TR002.
the second delivery route configured to stop at the second delivery destination before the first delivery destination to thereby deliver the second item before the first item. See at least [0208], wherein an evaluation value (first vehicle parameter) is calculated for route TR0002, and see at least [0205] and figure 4, wherein TR0002 stops at the second delivery destination (GUEST0002) before the first delivery destination (GUEST0001). S/SR/DR portions in TR0001 represent the connecting segments between each delivery destination.
determine an optimized delivery route for a vehicle that comprises the first and second delivery destinations that optimizes the value of the first vehicle parameter. See at least [0179] and [0209]-[0210] and figure 8, step S3, wherein an optimized delivery route is determined for a delivery vehicle that minimizes the evaluation value, or optimizes the value of the first vehicle parameter. This optimizes delivery route is selected from TR0001 and TR0002, so it comprises both the first and second delivery destinations.
and program, into a route guidance system of the vehicle for routing the vehicle, the optimized delivery route having the optimized value of the first vehicle parameter, thereby improving energy efficiency. See at least [0210], wherein the optimized delivery route is transmitted to a delivery person terminal 2, and see at least [0206], wherein the delivery person terminal 2 is associated with the delivery vehicle, and the optimized route has a minimum cost, and see at least [0004]-[0005], wherein the optimized delivery route improves the energy efficiency of the driver as they depart the vehicle on foot to deliver each package. See at least [0179], wherein delivery person terminal 2 is a car navigation system provided on the delivery vehicle.
Nishikawa remains silent on improving efficiency routing of the vehicle. However, Nishikawa does teach the first vehicle parameter comprising an amount of energy consumed by the driver of the vehicle in taking the optimized delivery route (see at least [0183]).
Khasis teaches thereby improving efficiency routing of the vehicle. See at least [0040] and [0103], wherein the vehicle route is optimized to reduce energy consumption. Additionally, see at least [0079], wherein the vehicle route is optimized to obtain the most cost-efficient route possible, the cost including fuel costs.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of improving energy efficiency of the vehicle. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Regarding Claim 20, Nishikawa and Khasis in combination teach all of the limitations of Claim 19 as discussed above, and Nishikawa remains silent on further comprising instructions which, when executed by the processor, causes the processor to: determine whether there exists a non-refueling delivery route such that a first vehicle can deliver each item to its respective delivery destination, without stopping to refuel, such that the value of the first vehicle parameter is optimized; in response to a determination that no non-refueling delivery route exists such that the first vehicle can deliver each item to its respective delivery destination without refueling, calculating the value of the first vehicle parameter for: a composite route for the first vehicle to deliver each item to its respective delivery destinations in two sub-routes, stopping to refuel in between the two sub-routes; and for a sum of a first vehicle route and a second vehicle route, the first vehicle route being a route for the first vehicle to deliver a first subset of the plurality of items to their respective delivery destinations in one trip without refueling, and the second vehicle route being a route for a second vehicle to deliver a second subset of the plurality of items, the second subset comprising the remaining items, to their respective destinations in one trip without refueling, wherein, if the value of the first vehicle parameter is lower for the composite route, transmit a signal to the first vehicle which, when received by the first vehicle causes the composite route to be programmed into a route guidance system of the first vehicle and/or causes the first vehicle to begin driving the composite route, under autonomous control; and if the value of the first vehicle parameter is lower for a sum of the first and second vehicle routes, transmit a signal to a fleet management module to cause the fleet management module to cause the first vehicle route to be programmed into the route guidance system of the first vehicle and the second vehicle route to be programmed into a route guidance system of a second vehicle and/or cause the first and second vehicles to begin driving the first and second vehicles routes, respectively, under autonomous control.
Khasis teaches wherein the controller is further programmed to: determine whether there exists a non-refueling delivery route such that a first vehicle can deliver each item to its respective delivery destination, without stopping to refuel, such that the value of the first vehicle parameter is optimized. See at least [0076], wherein when determining a route with the lowest cost (determining a route that optimizes the first vehicle parameter), the optimal route is checked to account for any stops for fuel needed, or whether the vehicle does not need to refuel.
in response to a determination that no non-refueling delivery route exists such that the first vehicle can deliver each item to its respective delivery destination without refueling. See at least [0076], wherein the optimal route is checked to see if a refueling stop is needed.
calculating the value of the first vehicle parameter for: a composite route for the first vehicle to deliver each item to its respective delivery destinations in two sub-routes, stopping to refuel in between the two sub-routes. See at least [0079] and [0133], wherein the original optimal route is split into two sub-routes and a refueling stop is inserted between the sub-routes, and the potential composite routes are analyzed by calculating the cost efficiency, or the first vehicle parameter, for each route after inserting the refueling stop.
and for a sum of a first vehicle route and a second vehicle route, the first vehicle route being a route for the first vehicle to deliver a first subset of the plurality of items to their respective delivery destinations in one trip without refueling, and the second vehicle route being a route for a second vehicle to deliver a second subset of the plurality of items, the second subset comprising the remaining items, to their respective destinations in one trip without refueling. See at least [0084]-[0087], wherein a multi-vehicle route is used in optimization, wherein the multi-vehicle route comprises a first route with a first subset of destinations for a first vehicle, and a second route with a second subset of destinations for a second vehicle, and see at least [0091] wherein the multi-vehicle route is optimized in view of the fuel tank/battery capacity of the vehicles involved in the route.
wherein, if the value of the first vehicle parameter is lower for the composite route. See at least [0076]-[0079], [0091], [0130], and [0133], and figure 9A, wherein all of the potential routes, including the refueling route (composite route) and the multi-vehicle route (sum route) are checked for the lowest cost value, and the lowest cost value route is the one the autonomous vehicle(s) are directed to follow.
transmit a signal to the first vehicle which, when received by the first vehicle causes the composite route to be programmed into a route guidance system of the first vehicle and/or causes the first vehicle to begin driving the composite route, under autonomous control. See at least [0073] and [0131], wherein the server communicates through a network (transmitting a signal) to cause vehicles to follow routes under autonomous control.
and if the value of the first vehicle parameter is lower for a sum of the first and second vehicle routes. See at least [0076]-[0079], [0091], [0130], and [0133], and figure 9A, wherein all of the potential routes, including the refueling route (composite route) and the multi-vehicle route (sum route) are checked for the lowest cost value, and the lowest cost value route is the one the autonomous vehicle(s) are directed to follow.
transmit a signal to a fleet management module to cause the fleet management module to cause the first vehicle route to be programmed into the route guidance system of the first vehicle and the second vehicle route to be programmed into a route guidance system of a second vehicle and/or cause the first and second vehicles to begin driving the first and second vehicles routes, respectively, under autonomous control. See at least [0073] and [0131], wherein the server communicates through a network (transmitting a signal) to cause vehicles to follow routes under autonomous control.
One having ordinary skill in the art, before the effective filing date of the claimed invention, would have found it obvious to modify the method of Nishikawa with Khasis’ technique of determining a need to refuel, determining a composite and a sum route in view of the need to refuel, and comparing the first vehicle parameter for composite and sum routes in view of a need to refuel and controlling the vehicle(s) to follow the route with the lowest first vehicle parameter. It would have been obvious to modify because doing so allows for optimization of multi-stop routing in view of dynamic updates, as recognized by Khasis (see at least [0005]-[0006]).
Conclusion
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/S.M.J./ Examiner, Art Unit 3667
/FARIS S ALMATRAHI/ Supervisory Patent Examiner, Art Unit 3667
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