Technical Field
The following disclosure relates to the field of package delivery and, more particularly, to a system, method, computer program embodied on a computer-readable medium, and apparatus for determining the utilization of each trailer in a plurality of trailers for the purpose of optimizing a delivery network.
Description of Related Art
In the shipping and delivery industry, many shipping carriers attempt to maximize the utilization of trailers and other shipping equipment in which packages are transported. Utilization often has a significant impact on a shipping operation's efficiency and the shipping costs of a carrier. Accordingly, carriers may measure, track, and monitor the utilization of their trailers in order to attempt to maximize utilization.
Past attempts to measure trailer utilization have involved various methods, including, for example, visual inspection of the packages loaded into trailers. Visual inspection is a less than optimal method for determining utilization of a trailer, as the utilization is merely a visual estimate of the amount of space occupied by packages.
Accordingly, it may be desirable to develop a technique for determining trailer utilization that addresses at least some of these and other issues and drawbacks.
The following summary is not an extensive overview and is not intended to identify key or critical elements of the apparatuses, methods, systems, processes, and the like, or to delineate the scope of such elements. This Summary provides a conceptual introduction in a simplified form as a prelude to the more-detailed description that follows.
Embodiments of the present invention provide an improvement by, among other things, providing a trailer utilization and optimization system that may be configured to provide one or more of the following advantages: (1) determine trailer utilization through automated processes, (2) precisely determine trailer utilization, (3) determine trailer utilization promptly after loading and/or transport, (4) provide a cost effective solution for determining trailer utilization. These and other objects and advantages are met by the present invention, which include systems, methods, apparatuses, and computer programs embodied on computer-readable media for determining trailer utilization.
In one embodiment of the present invention, a system for determining the utilization of each trailer in a plurality of trailers is provided. The system includes a dimensional scanner configured to determine one or more dimensions of at least one of the plurality of packages; a scanner configured to scan a unique identification code displayed on each of the plurality of packages in order to identify in which of a plurality of trailers each of the plurality of packages is assigned and to transmit an identified trailer assignment associated with each of the plurality of packages; and a network entity in electronic communication with the computing device, dimensional scanner, and scanner. The network entity is configured to receive from the computing device the data associated with each of the plurality of packages, the one or more dimensions of at least one of the plurality of packages from the dimensional scanner, and the identified trailer assignment associated with each of the plurality of packages from the scanner. Additionally, the network entity is configured to determine one or more dimensions of each of the plurality of packages based at least in part on some combination of the dimensional information of the data received from the computing device and the one or more dimensions of at least one of the plurality of packages received from the dimensional scanner. Furthermore, the network entity is configured to calculate, for each of the trailers in the plurality of trailers, the volume of the packages assigned to the trailer, based at least in part on the identified trailer assignments and the one or more determined dimensions of each of the packages. Moreover, the network entity is configured to determine the utilization of each of the plurality of trailers based at least in part on the calculated volume of the packages assigned to each of the plurality of trailers.
In another embodiment of the present invention, an apparatus for determining the utilization of each trailer in a plurality of trailers is provided. The apparatus includes a processor configured to receive an indication of one or more packages assigned to a trailer, determine one or more dimensions of each package assigned to the trailer, and determine the utilization of the trailer based at least in part on the one or more dimensions of each of the packages assigned to the trailer. Additionally, the processor may be further configured to determine the weight of each package assigned to the trailer and to determine the utilization of each of a plurality of trailers used in a delivery network.
In a further embodiment, a computer program embodied on a computer-readable medium for determining the utilization of each trailer in a plurality of trailers is provided. The computer program embodied on a computer-readable medium includes a first executable portion for receiving an indication of one or more packages assigned to a trailer; a second executable portion for determining one or more dimensions of each package assigned to the trailer; and a third executable portion for determining the utilization of the trailer based at least in part on the one or more dimensions of each of the packages assigned to the trailer. Furthermore, the computer program embodied on a computer-readable medium may include a fourth executable portion for determining the utilization of each of a plurality of trailers used in a delivery network.
In an additional embodiment, a method for determining the utilization of each trailer in a plurality of trailers is provided. The method includes the steps of receiving by a network entity over a wired or wireless communication network an indication of one or more packages assigned to a trailer; determining by the network entity one or more dimensions of each package assigned to the trailer; and determining by the network entity the utilization of the trailer based at least in part on the one or more dimensions of each of the packages assigned to the trailer. In addition the method may further include determining by the network entity the weight of each package assigned to the trailer and determining by the network entity the utilization of each of a plurality of trailers used in a delivery network.
Having thus described the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:
The present invention now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the inventions are shown. Indeed, these inventions may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.
Overview
The present disclosure, according to various embodiments, may enable a shipping carrier to optimize a delivery network by evaluating the utilizations of the respective trailers, trucks, and/or delivery vehicles (collectively referred to as “trailers”) operating within the delivery network and realigning the delivery trailers and the schedule accordingly. According to one embodiment, a trailer utilization server may be employed to calculate the utilization of a trailer by determining the percentage of the interior volume of the trailer that is occupied by packages that are being transported in the trailer.
The trailer utilization server may determine the interior volume of the trailer, for example, by accessing a trailer database containing “trailer data,” or data identifying, among other things, the interior volume associated with each of the trailers operating within the delivery network. The volume of packages being transported inside of the trailer may be determined by, for example, aggregating package-related data obtained from various different sources at various different times throughout the delivery cycle. In one embodiment, as discussed in more detail below, the package-related data may be stored in one or more databases accessible by the trailer utilization server and may include, for example, “billing data,” or data input by a customer at the time of placing an order to ship a package, “dimensional data,” or height, length and/or width data obtained from a dimensional scanner as the package is scanned at a hub within the delivery network, and/or the like. According to embodiments of the present invention, the billing, dimensional, and other package-related data may include information such as package dimensions and/or package weight, which may be used by the trailer utilization server to determine the total volume of the packages transported within the trailer. In particular, according to one embodiment, the trailer utilization server may divide the total volume of the packages by the interior volume of the trailer in order to determine the trailer utilization.
This process may be repeated for each trailer operating within the delivery network, until the trailer utilization server may determine the utilization for each trailer. Once the utilization for each trailer has been determined, the trailer utilization server may provide the utilization values to a network optimization server, which may analyze the utilizations and the delivery network schedule in order to determine the parameters for an delivery network, which may include, for example, adding, eliminating, and/or modifying scheduled routes. According to embodiments of the present invention, this network optimization process may be a continual, iterative process.
System Overview
Reference is now made to
According to one embodiment, the trailer utilization server 100 may be configured to receive package-related data from various sources at various different times throughout a package delivery cycle, and use this information to determine the utilization of at least one trailer operating within the delivery network. Once the trailer utilization server 100 determines the utilization for each trailer operating within the delivery network, the trailer utilization server 100 may provide the utilization information to the network optimization server 110, which may be configured to determine the parameters for an optimized delivery network, which may include, for example, eliminating, adding, and/or modifying scheduled routes, among other actions.
According to one embodiment, the package-related data may include, for example, “billing data,” “scan data,” “dimensional data,” “trailer data,” and/or the like, each of which is discussed in more detail below. As shown, this and other package-related data may be stored in one or more databases associated with or accessible by the trailer utilization server 100 including, for example, a billing database 200, a scan database 300, a dimensional database 400, and a trailer database 500, among other databases. While shown as separate databases associated with each of the different types of data, as one of ordinary skill in the art will recognize in light of this disclosure, some or all of the package-related data may be stored in the same database associated with or accessible by the trailer utilization server 100.
According to one embodiment, “billing data” may refer to information provided by a customer at the time he or she is placing a shipping order. Referring to
According to one embodiment, “scan data” may refer to information obtained when a package is scanned as the package is loaded into or unloaded from a trailer prior to or following transport. Scan data may include, for example, a tracking number associated with the package, the number of the trailer in which the package is being transported, at both the time of loading into and the time of unloading from the trailer, and/or the like. In particular, referring to
“Dimensional data” may refer to the height, width, and/or length of the package obtained, for example, when the package is scanned by a dimensional scanner at various and multiple points during the shipment of the package. In particular, as shown in
Finally, according to one embodiment, “trailer data” may refer to the physical information about each trailer operating within the delivery network, including, for example, the trailer number, type, length, and/or volume. As noted above, the volume of the trailer may be utilized by the trailer utilization server 100 in determining the percent utilization of the trailer. According to one embodiment, trailer data may be stored in the trailer database 500 located on or accessible by the trailer utilization server 100.
Referring now to
In addition, the central server 500 may include at least one storage device 515, such as a hard disk drive, a floppy disk drive, a CD Rom drive, or optical disk drive, for storing information on various computer-readable media, such as a hard disk, a removable magnetic disk, or a CD-ROM disk. As will be appreciated by one of ordinary skill in the art, each of these storage devices 515 may be connected to the system bus 545 by an appropriate interface. The storage devices 515 and their associated computer-readable media may provide nonvolatile storage for a personal computer. It is important to note that the computer-readable media described above could be replaced by any other type of computer-readable media known in the art. Such media include, for example, magnetic cassettes, flash memory cards, digital video disks, and Bernoulli cartridges.
A number of program modules may be stored by the various storage devices and within RAM 530. Such program modules may include an operating system 550, a trailer utilization module 560, and a network optimization module 570. The trailer utilization module 560 and network optimization module 570 may control certain aspects of the operation of the central server 500, with the assistance of the processor 510 and the operating system 550. For example, as discussed in more detail below with regard to
Also located within the central server 500 may be a network interface 525, for interfacing and communicating with other elements of a computer network. It will be appreciated by one of ordinary skill in the art that one or more of the central server 500 components may be located geographically remotely from other central server 500 components. Furthermore, one or more of the components may be combined, and additional components performing functions described herein may be included in the central server 500. While the foregoing describes the software of embodiments of the invention in terms of modules by way of example, as one of ordinary skill in the art will recognize in light of this disclosure, the software associated with embodiments of the invention need not be modularized and, instead, may be intermingled or written in other non-modularized formats.
Method for Determining Trailer Utilization
Reference is now made to
As depicted in
Once the package is loaded onto the trailer, the trailer utilization server 100 or, in one embodiment, the trailer utilization module 560 executed by the processor 510 on the central server 500, may, at Block 650, obtain from the scan database 300 an indication of each package that is assigned to the trailer. In addition to obtaining each indication, the trailer utilization server 100 or module 560 may, at Block 660, further obtain package-related data including, for example, billing data from the billing database 200, dimensional data from the dimensional database 400, scan data from the scan database 300, trailer data from the trailer database 500, and/or other similar information related to each package that may be used to determine trailer utilization. In order to determine utilization, the trailer utilization server 100 or module 560 of one embodiment may take into account the volume of each package transported in the trailer, wherein in order to determine volume, the trailer utilization server 100 or module 560 may use, for example, the dimensions and/or weight of each package.
In particular, as shown in
Next, the trailer utilization server 100 or module 560 may, at Block 710, determine the weight of each package assigned to the trailer. To determine the weight of the package assigned to the trailer, the trailer utilization server or module may obtain the billing weight of the package from the billing data provided by the customer. The billing weight may be either actual or estimated by the customer. Alternatively, the trailer utilization server or module may instead obtain the weight of the package from dimensional data provided by the dimensional scanner. In particular, package dimensions received by the dimensional scanner may be used to determine a dimensional weight of the package. Dimensional weight may be a calculated measurement and may be the equivalent weight of the package based upon the dimensions of the package. For example, if the customer ships an item in the package that is designed to carry items of greater weight than the item shipped, the dimensional weight of the package may be greater than the actual or estimated weight provided by the customer. In other words, if the dimensions of the package received by the dimensional scanner indicate that the package is a five pound equivalent sized box, the dimensional weight may be five pounds, even if the item shipped weighs only one pound. If the billing weight is not provided in the billing data, the trailer utilization server or module may use the dimensional weight as the weight of the package. Additionally, dimensional weight may be substituted for the billing weight as the weight of the package if the dimensional weight is calculated to be greater than the billing weight. Furthermore, if billing weight is not provided in the billing data and the package has not been scanned by a dimensional scanner in order for a dimensional weight to be calculated, the trailer utilization server or module may use as the weight of the package the average weight of the packages being shipped in the same trailer for which there is weight-related data. If there is no weight-related data for the other packages being shipped in the same trailer, then a weight/volume factor may be used to estimate the weight of the package.
According to one embodiment, the trailer utilization server 100 or module 560 may, at Block 720, determine the volume of each package assigned to the trailer. To determine the volume of each package, the trailer utilization server or module may use the dimensions of the package assigned to the trailer to calculate the volume of the package. If neither the billing data nor the dimensional data include the dimensions of the package, the volume of the package may be estimated by various methods. In some embodiments, the volume may be estimated as the historical average volume of the package, based on the weight of the package. This historical average volume may be obtained by sampling packages of various weights, measuring the volume of each sample package, and determining a relation between the weight of each sample package and its corresponding volume. An example of a system and method for estimating the volume of a package that may be utilized in this system may be found in U.S. application Ser. No. 11/457,015, filed Jul. 12, 2006, and entitled “Systems and Methods for Forecasting Container Density,” which is hereby incorporated by reference. Accordingly, if the billing data and dimensional data do not include package dimensions, the trailer utilization server 100 or module 560 may reference a lookup table (e.g., residing in the memory 505 or the memory 515) that may include a mapping of weights to historical average volumes in order to obtain the estimated volume for the package based on the weight of the package.
Once the volume of each package transported by the trailer has been determined, the trailer utilization server or module may determine the utilization of the trailer (Block 730). In particular, the trailer utilization server or module may calculate the total volume of the packages assigned to the trailer to determine the total volume occupied by the packages in the trailer. The trailer utilization server or module may then divide the total volume occupied by the packages in the trailer by the total volume of the trailer, which, as discussed above, may be obtained from the trailer data stored in the trailer database 500. The resulting percentage may be the utilization for the individual trailer. To illustrate, one example of a formula for calculating trailer utilization is as follows:
where Pt is a package assigned to trailer t, n is the number of packages assigned to trailer t, VPt is the volume of a package assigned to trailer t, Vt is the interior volume of trailer t, and Ut is the utilization of trailer t.
Referring to
In various embodiments, the optimization process may be an iterative process that may be continually performed in order to continually improve the efficiency of the delivery network. Accordingly, the trailer utilization server or module may continually determine the utilization of the trailers in the delivery network, and the parameters of an optimized delivery network may be continually determined either through the use of the network optimization server or module or through manual optimization.
In other embodiments, if trailer utilization can be determined before the scheduled route of the trailer has begun, then the delivery network may be optimized “on-the-fly.” If two trailers, for example, are scheduled to travel from the same origin to the same destination, and the utilization of each the trailers is such that the packages in both trailers could be adequately combined into one of the two trailers, then one of the routes could be eliminated. Additional types of related actions may be taken to preemptively optimize the delivery network.
The present disclosure is not limited solely to the shipping industry. Embodiments of this disclosure may be utilized in any scenario in which a logistics network may be optimized in order to increase efficiency, reduce costs, save time, or other related reasons. Examples may include the airline industry, railroad industry, and public transportation, among other related industries and businesses. In addition, while the foregoing provides an example of the process that may be performed in order to calculate trailer utilization and perform optimization, the order described above of the steps performed in relation to that process is provided for exemplary purposes only and should not be taken in any way as limiting the scope of embodiments of the present invention to the order provided. Alternatively, as one of ordinary skill in the art will recognize in light of this disclosure, the foregoing steps may be performed in multiple different orders and combinations without departing from the spirit and scope of embodiments of the present invention.
As described above and as will be appreciated by one skilled in the art, embodiments of the present invention may be configured as a method or apparatus. Accordingly, embodiments of the present invention may be comprised of various means including entirely of hardware, entirely of software, or any combination of software and hardware. Furthermore, embodiments of the present invention may take the form of a computer program product on a computer-readable storage medium having computer-readable program instructions (e.g., computer software) embodied in the storage medium. Any suitable computer-readable storage medium may be utilized including hard disks, CD-ROMs, optical storage devices, or magnetic storage devices.
Embodiments of the present invention have been described above with reference to block diagrams and flowchart illustrations of methods, apparatuses (i.e., systems) and computer program products. It will be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, respectively, can be implemented by various means including computer program instructions. These computer program instructions may be loaded onto a general purpose computer, special purpose computer, or other programmable data processing apparatus, such as processor 510 discussed above with reference to
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus (e.g., processor 510 of
Accordingly, blocks of the block diagrams and flowchart illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions or steps, or combinations of special purpose hardware and computer instructions.
Many modifications and other embodiments of the inventions set forth herein will come to mind to one skilled in the art to which these inventions pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the inventions are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
This patent application is a continuation of U.S. patent application Ser. No. 12/340,233, filed Dec. 19, 2008, which is incorporated herein by reference in its entirety.
| Number | Name | Date | Kind |
|---|---|---|---|
| 4611268 | Gotz et al. | Sep 1986 | A |
| 5430831 | Snellen | Jul 1995 | A |
| 5699258 | Thiel | Dec 1997 | A |
| 6219653 | O'Neill et al. | Apr 2001 | B1 |
| 6477503 | Mankes | Nov 2002 | B1 |
| 6606604 | Dutta | Aug 2003 | B1 |
| 6622127 | Klots et al. | Sep 2003 | B1 |
| 6701299 | Kraisser et al. | Mar 2004 | B2 |
| 6952628 | Prutu | Oct 2005 | B2 |
| 7015824 | Cleveland et al. | Mar 2006 | B2 |
| 7137556 | Bonner et al. | Nov 2006 | B1 |
| 7139721 | Borders et al. | Nov 2006 | B2 |
| 7158948 | Rodriguez et al. | Jan 2007 | B1 |
| 7177825 | Borders et al. | Feb 2007 | B1 |
| 7181426 | Dutta | Feb 2007 | B2 |
| 7233907 | Young | Jun 2007 | B2 |
| 7252227 | Chase | Aug 2007 | B2 |
| 7313460 | Prater et al. | Dec 2007 | B1 |
| 7363126 | Zhong et al. | Apr 2008 | B1 |
| 7509228 | Bielefeld et al. | Mar 2009 | B2 |
| 7624024 | Levis et al. | Nov 2009 | B2 |
| 7647233 | Kadaba et al. | Jan 2010 | B2 |
| 7831439 | Bryar et al. | Nov 2010 | B1 |
| 7925524 | Florence | Apr 2011 | B2 |
| 7962422 | Melechko et al. | Jun 2011 | B1 |
| 8068930 | Perez et al. | Nov 2011 | B2 |
| 8073723 | Bilibin et al. | Dec 2011 | B1 |
| 8108321 | Neal et al. | Jan 2012 | B2 |
| 8306875 | Schneur | Nov 2012 | B2 |
| 8311850 | Johnson et al. | Nov 2012 | B2 |
| 8386397 | Agarwal et al. | Feb 2013 | B1 |
| 8407151 | Agarwal et al. | Mar 2013 | B1 |
| 8407154 | Fallows | Mar 2013 | B1 |
| 8429019 | Yeatts et al. | Apr 2013 | B1 |
| 8433659 | Johnston et al. | Apr 2013 | B2 |
| 8473425 | Maurer et al. | Jun 2013 | B1 |
| 8554694 | Ward et al. | Oct 2013 | B1 |
| 8572002 | Kadaba | Oct 2013 | B2 |
| 8615473 | Spiegel et al. | Dec 2013 | B2 |
| RE45160 | Ferlauto et al. | Sep 2014 | E |
| 8924312 | Kadaba | Dec 2014 | B2 |
| 9020846 | Siris | Apr 2015 | B2 |
| 9047607 | Curial et al. | Jun 2015 | B1 |
| 10163119 | Bolton et al. | Dec 2018 | B1 |
| 20010029473 | Yamaoka et al. | Oct 2001 | A1 |
| 20010042024 | Rogers | Nov 2001 | A1 |
| 20010051885 | Nardulli et al. | Dec 2001 | A1 |
| 20020007299 | Florence | Jan 2002 | A1 |
| 20020007353 | Kornacki | Jan 2002 | A1 |
| 20020016726 | Ross | Feb 2002 | A1 |
| 20020103724 | Huxter | Aug 2002 | A1 |
| 20020107820 | Huxter | Aug 2002 | A1 |
| 20020111914 | Terada et al. | Aug 2002 | A1 |
| 20020147654 | Kraisser et al. | Oct 2002 | A1 |
| 20020178023 | Bjerre et al. | Nov 2002 | A1 |
| 20030009361 | Hancock et al. | Jan 2003 | A1 |
| 20030036935 | Nel | Feb 2003 | A1 |
| 20030046133 | Morley et al. | Mar 2003 | A1 |
| 20030130753 | Grant et al. | Jul 2003 | A1 |
| 20030200111 | Damji | Oct 2003 | A1 |
| 20040030572 | Campbell et al. | Feb 2004 | A1 |
| 20040151068 | Carlsruh et al. | Aug 2004 | A1 |
| 20040215480 | Kadaba | Oct 2004 | A1 |
| 20040249699 | Laurent et al. | Dec 2004 | A1 |
| 20050080638 | Maseruka | Apr 2005 | A1 |
| 20050165629 | Bruns | Jul 2005 | A1 |
| 20050171738 | Kadaba | Aug 2005 | A1 |
| 20050216319 | Reblin | Sep 2005 | A1 |
| 20050267791 | LaVoie et al. | Dec 2005 | A1 |
| 20050278063 | Hersh et al. | Dec 2005 | A1 |
| 20060041481 | Stowe | Feb 2006 | A1 |
| 20060261164 | Bochicchio | Nov 2006 | A1 |
| 20070083410 | Hanna | Apr 2007 | A1 |
| 20080091342 | Assael | Apr 2008 | A1 |
| 20080235147 | Jensen | Sep 2008 | A1 |
| 20080245873 | Dwinell | Oct 2008 | A1 |
| 20080294536 | Taylor et al. | Nov 2008 | A1 |
| 20080301009 | Plaster et al. | Dec 2008 | A1 |
| 20090106124 | Yang | Apr 2009 | A1 |
| 20090164295 | Sion | Jun 2009 | A1 |
| 20090187489 | Mallick et al. | Jul 2009 | A1 |
| 20100004960 | Frankenberg et al. | Jan 2010 | A1 |
| 20100094769 | Davidson et al. | Apr 2010 | A1 |
| 20100100507 | Davidson et al. | Apr 2010 | A1 |
| 20100121689 | Wallace et al. | May 2010 | A1 |
| 20100161170 | Siris | Jun 2010 | A1 |
| 20100169000 | Overgoor et al. | Jul 2010 | A1 |
| 20100211426 | Mcclurg | Aug 2010 | A1 |
| 20100312715 | Esque et al. | Dec 2010 | A1 |
| 20110065458 | Staton et al. | Mar 2011 | A1 |
| 20110258014 | Evangelist et al. | Oct 2011 | A1 |
| 20110288958 | Obasanjo et al. | Nov 2011 | A1 |
| 20120030133 | Rademaker | Feb 2012 | A1 |
| 20120059729 | Roa et al. | Mar 2012 | A1 |
| 20120246090 | Griffith et al. | Sep 2012 | A1 |
| 20120284083 | Wu et al. | Nov 2012 | A1 |
| 20120303540 | Marcus et al. | Nov 2012 | A1 |
| 20130006739 | Horvitz et al. | Jan 2013 | A1 |
| 20130013350 | McCullough et al. | Jan 2013 | A1 |
| 20130066844 | Bowers et al. | Mar 2013 | A1 |
| 20130144428 | Irwin et al. | Jun 2013 | A1 |
| 20130151435 | Hocquette et al. | Jun 2013 | A1 |
| 20130166359 | Kadaba | Jun 2013 | A1 |
| 20130262336 | Wan et al. | Oct 2013 | A1 |
| 20130325737 | Smalling et al. | Dec 2013 | A1 |
| 20130325741 | Smalling et al. | Dec 2013 | A1 |
| 20140025464 | Kadaba | Jan 2014 | A1 |
| 20140052661 | Shakes et al. | Feb 2014 | A1 |
| 20140095350 | Carr et al. | Apr 2014 | A1 |
| 20140148944 | Bailey et al. | May 2014 | A1 |
| 20140149244 | Abhyanker | May 2014 | A1 |
| 20140188748 | Cavoue et al. | Jul 2014 | A1 |
| 20140229338 | Borders et al. | Aug 2014 | A1 |
| 20140297554 | Armato | Oct 2014 | A1 |
| 20140330741 | Bialynicka-Birula et al. | Nov 2014 | A1 |
| 20150081587 | Gillen | Mar 2015 | A1 |
| 20150178678 | Carr et al. | Jun 2015 | A1 |
| 20150227890 | Bednarek et al. | Aug 2015 | A1 |
| 20150248795 | Davidson | Sep 2015 | A1 |
| 20150269520 | Knapp et al. | Sep 2015 | A1 |
| 20150294262 | Nelson et al. | Oct 2015 | A1 |
| 20150302347 | Fredette | Oct 2015 | A1 |
| 20150356503 | LaVoie et al. | Dec 2015 | A1 |
| 20150363843 | Loppatto et al. | Dec 2015 | A1 |
| 20160071056 | Ellison et al. | Mar 2016 | A1 |
| 20170083862 | Loubriel | Mar 2017 | A1 |
| Number | Date | Country |
|---|---|---|
| 1598850 | Mar 2005 | CN |
| 2461722 | Jan 2010 | GB |
| WO 2000068856 | Nov 2000 | WO |
| WO 2001071534 | Sep 2001 | WO |
| WO 2013134417 | Sep 2013 | WO |
| Entry |
|---|
| “How it Works—Cargo Sensors,” General Electric Company, http://web.archive.org/web/20070307032108/http://www.trailerservices.com/veriwise/cargo.html, Mar. 7, 2007 |
| Search Report dated Jun. 19, 2008, PCT/US06/27041, Filed Jul. 12, 2006 |
| United States Patent and Trademark Office, Office Action for U.S. Appl. No. 12/340,233, dated May 11, 2011, 31 pages, U.S.A. |
| United States Patent and Trademark Office, Office Action for U.S. Appl. No. 12/340,233, dated Dec. 13, 2011, 32 pages, U.S.A. |
| United States Patent and Trademark Office, Office Action for U.S. Appl. No. 12/340,233, dated Jan. 30, 2014, 31 pages, U.S.A. |
| United States Patent and Trademark Office, Office Action for U.S. Appl. No. 12/340,233, dated Jun. 25, 2014, 32 pages, U.S.A. |
| United States Patent and Trademark Office, Notice of Allowance for U.S. Appl. No. 12/340,233, dated Jan. 22, 2015, 21 pages, U.S.A. |
| “Tap Your Phone, Get Stuff (Including Funding)” [online] [retrieved May 27, 2015]. Retrieved from the Internet: <URL: http://techcrunch.com/2014/04/06/tap-your-phone-get-stuff-including-funding/> (dated Apr. 6, 2014) 8 pages. |
| American Airlines, “American Airlines Cargo—Reservations”, Aug. 5, 2013 to Sep. 19, 2015, Internet Archive <http://web.archive.org/web/20130805094248/https://www.aacargo.com/learn/reservations.html>, 4 pages. |
| Browning-Blas, Kristen, “Schwan's frozen-food truckers are driven to make customers' day”, The Denver Post, Sep. 17, 2008, retrieved from <http://www.denverpost.com/browning/ci_10472479>, on Mar. 20, 2016, 9 pages, U.S.A. |
| Evans, Kenneth R., et al., “Purchasing Motor Carrier Service: An Investigation of the Criteria Used by Small Manufacturing Firms”, Journal of Small Business Management, vol. 28.1, p. 39, 1990; retrieved from Google Scholar at <https://www.questia.com/library/journal/1G1-8854587/purchasing-motor-carrier-service-an-investigation>, on Mar. 20, 2016. |
| U.S. Appl. No. 13/828,652, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Mar. 14, 2013), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 13/964,766, “Methods, Apparatuses and Computer Program Products for Generating Logistics Zones”, Unpublished (filed Aug. 12, 2013), (Mark J. Davidson, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/046,172, “Methods, Apparatuses and Computer Program Products for Identifying Duplicate Travel”, Unpublished (filed Oct. 4, 2013), (Mark J. Davidson, inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/859,766, “Systems and Methods for Reserving Space in Carrier Vehicles to Provide on Demand Delivery Services”, Unpublished (filed Sep. 21, 2015), (Paul Loubriel, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/988,136, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Jan. 5, 2016), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/988,527, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Jan. 5, 2016), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/988,536, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Jan. 5, 2016), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/988,545, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Jan. 5, 2016), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/988,552, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Jan. 5, 2016), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| U.S. Appl. No. 14/988,561, “Systems and Methods for Synchronized Delivery”, Unpublished (filed Jan. 5, 2016), (Chris Bolton, Inventor) (United Parcel Service of America, Inc., assignee). |
| Wohlsen, Marcus, “How Robots and Military-Grade Algorithms Make Same-Day Delivery Possible”, Wired.com, Mar. 19, 2013, 8 pages, retrieved from <http://www.wired.com/category/business/?p=76398>, on Mar. 20, 2016. |
| Final Office Action received for U.S. Appl. No. 14/664,202, dated Apr. 20, 2018, 18 pages. |
| Final Office Action received for U.S. Appl. No. 14/664,223, dated Apr. 20, 2018, 18 pages. |
| Final Office Action received for U.S. Appl. No. 14/988,527, dated Feb. 26, 2018, 13 pages. |
| Non-Final Office Action received for U.S. Appl. No. 14/694,313, dated Apr. 3, 2018, 15 pages. |
| Non-Final Office Action received for U.S. Appl. No. 14/859,766, dated Nov. 13, 2018, 36 pages. |
| Non-Final Office Action received for U.S. Appl. No. 14/988,136, dated Aug. 28, 2018, 19 pages. |
| Non-Final Office Action received for U.S. Appl. No. 14/988,552, dated Oct. 4, 2018, 17 pages. |
| Non-Final Rejection dated Nov. 30, 2017 for U.S. Appl. No. 13/828,652. |
| Final Rejection dated Dec. 19, 2017 for U.S. Appl. No. 14/988,561. |
| Applicant Initiated Interview Summary (PTOL-413) dated Jan. 24, 2018 for U.S. Appl. No. 14/988,561. |
| Applicant Initiated Interview Summary (PTOL-413) dated Jan. 24, 2018 for U.S. Appl. No. 13/828,652. |
| Final Office Action received for U.S. Appl. No. 14/988,552, dated Feb. 5, 2019, 26 pages. |
| Non-Final Office Action received for U.S. Appl. No. 14/664,202, dated Jan. 24, 2019, 21 pages. |
| Non-Final Office Action received for U.S. Appl. No. 14/664,223, dated Feb. 7, 2019, 23 pages. |
| Number | Date | Country | |
|---|---|---|---|
| 20150199644 A1 | Jul 2015 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 12340233 | Dec 2008 | US |
| Child | 14667418 | US |