Patent Publication Number: US-11386362-B1

Title: System and method for optimizing waste / recycling collection and delivery routes for service vehicles

Description:
RELATED APPLICATIONS 
     This application claims the benefit, and priority benefit, of U.S. Provisional Patent Application Ser. No. 63/126,463, filed Dec. 16, 2020, the disclosure and contents of which are incorporated by reference herein in their entirety. 
    
    
     BACKGROUND 
     1. Field of Invention 
     The presently disclosed subject matter relates generally to route optimization, and more specifically, to optimization of collection/delivery routes for waste/recycling service vehicles. 
     2. Description of the Related Art 
     Traditional system and method of waste/recycling operations involve collecting and transporting waste to disposal stations and delivery of containers to customers by trucks along settled routes. These settled routes may present logistical and other challenges for service providers. Improvements in this field are therefore desired. 
     SUMMARY 
     In accordance with the presently disclosed subject matter, various illustrative embodiments of a system and method for optimizing waste or recycling routes for one or more service vehicles are described herein. 
     In certain illustrative embodiments, a method of optimizing delivery of waste or recycling services to customers using a waste or recycling service vehicle is disclosed. A sequence is developed of two or more census tracts using United States census tract data. A travel route is developed for the waste or recycling service vehicle using the sequence of two or more census tracts. Waste or recycling services are delivered to customers along the travel route with the waste or recycling service vehicle. In certain aspects, the developing of the sequence of two or more census tracts can include determining a representing stop for each census tract, wherein the representing stop comprises a customer location that is at or near the centroid of the census tract, and sequencing the census tracts using the representing stops of each census tract to determine an optimal tract sequence list. In certain aspects, the developing the travel route for the waste or recycling service vehicle can include: (i) adding all unrouted stops from each census tract into the travel route, starting from the first census tract of the optimal tract sequence list, until the travel route has met a defined primary fullness criteria; (ii) adding all unrouted stops from each census block group into the travel route, starting from the first block group of the census tract in (i) that is closest to the census tract that fulfills the primary fullness criteria, until the travel route has met a defined secondary fullness criteria; (iii) adding all unrouted stops from each census block into the travel route, starting from the first block of the census block group in (ii) that is closest to the census block group that fulfills the primary fullness criteria, until the travel route has met a defined tertiary fullness criteria; (iv) determining an optimal sequence for the travel route; and (v) repeating steps (i)-(iv) until all desired stops in each census tract are routed. The primary fullness criteria can include one or more of a daily volume capacity or a daily maximum time met for the travel route. The secondary fullness criteria can include one or more of a daily volume capacity or a daily maximum time met for the travel route. The secondary fullness criteria can vary depending on the type of waste or recycling service vehicle. The tertiary fullness criteria can include one or more of a daily volume capacity or a daily maximum time met for the travel route. The tertiary fullness criteria can vary depending on the type of waste or recycling service vehicle. The primary fullness criteria can further include real time route conditions, including but not limited to traffic conditions on the road, and the position of the vehicle on the road through a GPS device can be applied to perform a real time reroute. The primary fullness criteria can further include one or more of the number of customers already served, and the current customer being served relative to the remaining time available to complete the route can be applied to perform a real time reroute. The secondary fullness criteria further can include real time route conditions, including but not limited to traffic conditions on the road, and the position of the vehicle on the road through a GPS device can be applied to perform a real time reroute. The secondary fullness criteria can further include one or more of the number of customers already served, and the current customer being served relative to the remaining time available to complete the route can be applied to perform a real time reroute. The tertiary fullness further includes comprises real time route conditions, including but not limited to traffic conditions on the road, and the position of the vehicle on the road through a GPS device can be applied to perform a real time reroute. The tertiary fullness criteria further include one or more of the number of customers already served, and the current customer being served relative to the remaining time available to complete the route can be applied to perform a real time reroute. 
     In certain illustrative embodiments, a system for optimizing delivery of waste or recycling services to customers is disclosed. The system can include a waste or recycling service vehicle, a memory storage area, and a processor in communication with the memory storage area and configured to develop a sequence of two or more census tracts using United States census tract data, and develop a travel route for the waste or recycling service vehicle using the sequence of two or more census tracts. The processor can be further configured to determine a representing stop for each census tract, wherein the representing stop comprises a customer location that is at or near the centroid of the census tract, and sequence the census tracts using the representing stops of each census tract to determine an optimal tract sequence list. The processor can be further configured to: (i) add all unrouted stops from each census tract into the travel route, starting from the first census tract of the optimal tract sequence list, until the travel route has met a defined primary fullness criteria; (ii) add all unrouted stops from each census block group into the travel route, starting from the first block group of the census tract in (i) that is closest to the census tract that fulfills the primary fullness criteria, until the travel route has met a defined secondary fullness criteria; (iii) add all unrouted stops from each census block into the travel route, starting from the first block of the census block group in (ii) that is closest to the census block group that fulfills the primary fullness criteria, until the travel route has met a defined tertiary fullness criteria; (iv) determine an optimal sequence for the travel route; and (v) repeat steps (i)-(iv) until all desired stops in each census tract are routed. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a representative map of U.S. census block, block group, and tract regions according to embodiments of the present disclosure. 
         FIG. 2  is a diagram of an illustrative method according to embodiments of the present disclosure. 
         FIG. 3  is a flow diagram of an illustrative method according to embodiments of the present disclosure. 
         FIG. 4  is a flow diagram of an illustrative method according to embodiments of the present disclosure. 
         FIG. 5  is a flow diagram of an illustrative method according to embodiments of the present disclosure. 
         FIG. 6  is a representative example of a waste services environment to be serviced by a waste service vehicle according to embodiments of the present disclosure. 
         FIG. 7  is a system for data collection and sharing for a waste services provider during performance of a waste service activity in the environment of  FIG. 1 , according to embodiments of the present disclosure. 
         FIG. 8  an example of a communications network for a waste services vehicle according to embodiments of the present disclosure. 
         FIG. 9  is an example of a communications network for a waste services vehicle according to embodiments of the present disclosure. 
         FIG. 10  is an example of a computing system according to embodiments of the present disclosure. 
     
    
    
     While the presently disclosed subject matter will be described in connection with the preferred embodiment, it will be understood that it is not intended to limit the presently disclosed subject matter to that embodiment. On the contrary, it is intended to cover all alternatives, modifications, and equivalents, as may be included within the spirit and the scope of the presently disclosed subject matter as defined by the appended claims. 
     DETAILED DESCRIPTION 
     Various illustrative embodiments of a system and method for optimizing waste or recycling routes for one or more service vehicles are described herein. 
     Traditional vehicle routing approaches have sought to minimize the number of vehicle routes and total route time and cost for a waste/recycling services provider during performance of a service activity, but these approaches have proven to be ineffective. 
     In certain illustrative embodiments, the presently disclosed system and method can utilize unique route shapes to minimize route overlapping, as well as utilize route balancing to produce routes with more manageable daily workloads. The presently disclosed system and method enable providers to determine optimal sets of routes for a fleet of vehicles to traverse in order to service customers more quickly and efficiently. 
     In certain illustrative embodiments, the presently disclosed system and method can utilize predefined geographic areas such as government census regions as a guiding tool for vehicle routing. Vehicle routing algorithms can be developed using nested levels of census geographies such as census block identifications. For example, the algorithms can run up and down to nested levels, e.g., from census tract, to census block groups, and to census blocks, which allows a service provider to incorporate more stops into routes while preserving route boundaries. In certain illustrative embodiments, the presently disclosed system and method allow a user to estimate the number of vehicle routes for operational planning purposes, as well as create an optimal route sequence while considering natural boundaries for tactical planning. 
     The United States Census Bureau utilizes a census block as a base geographic unit or region for tabulation of data. Collections of census blocks form a block group, and collections of block groups form a tract. See  FIG. 1  herein. Census blocks can be bounded on all sides by visible geographic features, such as streets, roads, streams, and railroad tracks, and can nest within all types of geographic areas. For example, in cities, a census block may correspond to a city block, but in rural areas where there are fewer roads, census blocks may be defined by other features such as political boundaries, rivers and other natural features, parks and similar facilities, etc. Each census block/block group/tract has a unique ID (GEOID). The GEOID for a census block is a 15 digit number. A collection of census blocks under same block group have the same first 12 digits of the census block ID. Likewise, a collection of block groups sharing the same tract have the same first 11 digits of census block group ID. 
     Referring now to  FIG. 2 , an illustrative embodiment of a method of using geographic entities for vehicle route optimization is provided. In certain illustrative embodiments, the method can include an iterative two-step process. 
     In Step  1 , census tracts are sequenced. In Step  1 . 1 , a customer location is found that is closest from the centroid of each census tract and this customer stop is set as a representing stop of the census tract. In Step  1 . 2 , the census tracts are sequenced using the representing stops of each census tract. The output of Step  1 . 2  is the optimal tract sequence list (“OTSL”). 
     In Step  2 , routes are created using the OTSL. In Step  2 . 1 , all unrouted stops in the census tract are added into the route, starting from the first sequence of the OTSL. In Step  2 . 2 , the route is checked to see if it is full. As used herein, the term “full” can mean either daily volume capacity for the route or daily maximum route time met, although other possible meanings of the term “full” are also contemplated. When the route is full by adding all unrouted stops in the current census tract, it is possible that the final sequenced route time is over maximum route time. In order to increase the level of solution quality both in balance and in compactness, the next step in the process is to go down to nested levels (census block groups and census blocks) of census tract. To do so, if the route is full, first remove recently added stops of the current census tract from the route, and the next set of nested levels can be applied under Step  2 . 2 . 0 . If the route is not full, Steps  2 . 1  and  2 . 2  are repeated with the next sequence of the OTSL. In Step  2 . 2 . 0 , census block groups of the current census tract can be applied. In Step  2 . 2 . 1 , all unrouted stops in a census block group can be added into the route, starting from the closest census block group from the previous tract. In Step  2 . 2 . 2 , the route is checked to see if it is full. If the route is not full, Steps  2 . 2 . 1  and  2 . 2 . 2  are repeated with the next closest census block group. If the route is full, all stops added in the current census block group are removed, and Steps  2 . 2 . 0 ,  2 . 2 . 1 , and  2 . 2 . 2  are repeated with the census block, which is the next nested lower level of the census block group. Once the route is full and no more block groups can be added, then Step  2 . 3  can be applied. In Step  2 . 3 , an optimal sequence is determined for a given route, and Step  2  is repeated until all desired stops in the census tracts are routed. 
     Referring now to  FIG. 3 , a more detailed flow diagram of the illustrative embodiment of  FIG. 2  is provided. 
     In certain illustrative embodiments, a method of optimizing delivery of waste or recycling services to customers using a waste or recycling service vehicle is disclosed. A sequence is developed of two or more census tracts using United States census tract data. A travel route is developed for the waste or recycling service vehicle using the sequence of two or more census tracts. Waste or recycling services are delivered to customers along the travel route with the waste or recycling service vehicle. In certain aspects, the developing of the sequence of two or more census tracts can include determining a representing stop for each census tract, wherein the representing stop comprises a customer location that is at or near the centroid of the census tract, and sequencing the census tracts using the representing stops of each census tract to determine an optimal tract sequence list. In certain aspects, the developing the travel route for the waste or recycling service vehicle can include: (i) adding all unrouted stops from each census tract into the travel route, starting from the first census tract of the optimal tract sequence list, until the travel route has met a defined primary fullness criteria; (ii) adding all unrouted stops from each census block group into the travel route, starting from the first block group of the census tract in (i) that is closest to the census tract that fulfills the primary fullness criteria, until the travel route has met a defined secondary fullness criteria; (iii) adding all unrouted stops from each census block into the travel route, starting from the first block of the census block group in (ii) that is closest to the census block group that fulfills the primary fullness criteria, until the travel route has met a defined tertiary fullness criteria; (iv) determining an optimal sequence for the travel route; and (v) repeating steps (i)-(iv) until all desired stops in each census tract are routed. The primary fullness criteria can include one or more of a daily volume capacity or a daily maximum time met for the travel route. The secondary fullness criteria can include one or more of a daily volume capacity or a daily maximum time met for the travel route. The secondary fullness criteria can vary depending on the type of waste or recycling service vehicle. The tertiary fullness criteria can include one or more of a daily volume capacity or a daily maximum time met for the travel route. The tertiary fullness criteria can vary depending on the type of waste or recycling service vehicle. The primary fullness criteria can further include real time route conditions, including but not limited to traffic conditions on the road, and the position of the vehicle on the road through a GPS device can be applied to perform a real time reroute. The primary fullness criteria can further include one or more of the number of customers already served, and the current customer being served relative to the remaining time available to complete the route can be applied to perform a real time reroute. The secondary fullness criteria further can include real time route conditions, including but not limited to traffic conditions on the road, and the position of the vehicle on the road through a GPS device can be applied to perform a real time reroute. The secondary fullness criteria can further include one or more of the number of customers already served, and the current customer being served relative to the remaining time available to complete the route can be applied to perform a real time reroute. The tertiary fullness further includes comprises real time route conditions, including but not limited to traffic conditions on the road, and the position of the vehicle on the road through a GPS device can be applied to perform a real time reroute. The tertiary fullness criteria further include one or more of the number of customers already served, and the current customer being served relative to the remaining time available to complete the route can be applied to perform a real time reroute. 
     In certain illustrative embodiments, a system for optimizing delivery of waste or recycling services to customers is disclosed. The system can include a waste or recycling service vehicle, a memory storage area, and a processor in communication with the memory storage area and configured to develop a sequence of two or more census tracts using United States census tract data, and develop a travel route for the waste or recycling service vehicle using the sequence of two or more census tracts. The processor can be further configured to determine a representing stop for each census tract, wherein the representing stop comprises a customer location that is at or near the centroid of the census tract, and sequence the census tracts using the representing stops of each census tract to determine an optimal tract sequence list. The processor can be further configured to: (i) add all unrouted stops from each census tract into the travel route, starting from the first census tract of the optimal tract sequence list, until the travel route has met a defined primary fullness criteria; (ii) add all unrouted stops from each census block group into the travel route, starting from the first block group of the census tract in (i) that is closest to the census tract that fulfills the primary fullness criteria, until the travel route has met a defined secondary fullness criteria; (iii) add all unrouted stops from each census block into the travel route, starting from the first block of the census block group in (ii) that is closest to the census block group that fulfills the primary fullness criteria, until the travel route has met a defined tertiary fullness criteria; (iv) determine an optimal sequence for the travel route; and (v) repeat steps (i)-(iv) until all desired stops in each census tract are routed. 
     The presently disclosed system and method have a number of advantages over prior art technologies. Traditionally, vehicle routing has belonged to the NP-hard class of computational complexity theory, meaning it is in a class of problems at least as hard as the hardest problems in NP (non-deterministic polynomial-time). In certain illustrative embodiments, the presently disclosed system and method are effective for developing well-shaped and well-balanced vehicle routes with minimal route overlaps, while also minimizing the number of routes and total route time. Since census block IDs are based on geographic area and incorporate pre-existing geographic boundaries, the use of this data for finding routing algorithms and developing solutions and practical applications for this information is particularly effective. For example, natural geographic barriers such as rivers, mountains, and railroads can work as route boundaries and be avoided in a waste/recycling collection route. Also, customers in nearby census blocks are geographically close and thus can be inserted into the same route. 
     The presently disclosed system and method produce well-balanced, well-compacted and well-shaped routes, and also show significant route number and total route time savings as compared to existing system and method. The resulting routes are balanced with respect to meeting the planned maximum route time for the routes within an acceptable buffer time. Using the presently disclosed system and method, the number of routes whose route time is over a maximum route time plus allowable buffer is a small percentage and is a significant improvement while showing route savings compared to existing systems and methods. 
     In certain illustrative embodiments, the presently disclosed system and method can be extended to using other geographic entities besides U.S. government census regions, such as parcels. For example, the presently disclosed system and method can be extended to use parcel geographies maintained for the counties in the US, whereby information and attributes of the parcels can be utilized to create routes. 
     In addition, the presently disclosed system and method can be extended to using other vehicle routing besides waste/recycling collection vehicles, such as package delivery/pickup vehicles, food delivery services, passenger pickup services, school bus routing, and the like. The vehicle routing solutions provide an accurate estimate of the total route time and are designed to minimize the cost of the route while meeting the other required constraints and providing consistency of service to customers in various types of industries. 
     Referring now to  FIGS. 4-5 , illustrative embodiments of a system and method for using geographic entities for future route estimation are also provided. Traditional means for estimating future routes are often based on historical data regarding the number of routes used in relation to the forecasted volume of waste in a specific operational or geographic area. This typical approach has a number of disadvantages. For example, it does not accurately estimate volume increase/decrease at the customer level. Also, it cannot project the impact of volume increase to route times, especially correlations of landfill break points for a route because of volume changes to estimate the route times. 
     In certain illustrative embodiments, the presently disclosed system and method can estimate the number of future routes based on future customer footprint or anticipated demand, which can lead to more effective operational planning. This approach can be applicable to multiple use cases, including loss or gain of customers because of seasonal volume changes as well as economic conditions resulting in loss or gain of customers, to inform the anticipated number of future routes. In addition, estimating the number of future routes can also anticipate future driver and/or vehicle needs to meet operational requirements. 
     In certain illustrative embodiments, the following steps can be utilized as an alternative to, or in addition to, using historical volume vs. number of routes. As shown in  FIG. 5 , for a volume increase of “v %” and a current number of routes of “k”, the route optimization described herein can be run initially with current volume and current number of routes, to determine the current route time maximum. Next, for every customer, volume v % can be increased and the route optimization can be re-run with the route time maximum. The result of this step is the estimated number of routes. In certain illustrative embodiments, performance of route number estimation from future anticipated demand can include: (i) increase or decrease in volume (x %) to each customer (if you don&#39;t have forecasted volume locations, this is valid assumption to apply volume increase; if anticipated seasonal loss of specific customers known use); (ii) find sequence for census tract (find optimal sequence of census tracts; exclude tracts if anticipate seasonal loss of specific existing customers is known); (iii) find sequence and calculate route time for each census tract (find a sequence of stops in each tract by assuming previous tract&#39;s last stop as a starting point of the current tract; route time estimation for tract does not consider LF trips yet); and (iv) estimate number of routes based on route time and route/vehicle capacity (based on sequence of each tract, chop a long train of stops into a route, possibly heterogeneous, considering max route time, route capacity). This is based on assumption that existing customers have volume increase or loss of specific customers because of seasonal changes by DOW, of 10%, in certain illustrative embodiments. 
     The presently disclosed system and method have a number of advantages. The estimation of routes is very accurate, since it considers landfill (“LF”) break points along with volume changes because of increase or decrease of customers. Also, when volume estimation is known for certain geographic units, such as tracts, changes can be added only in this area to impact the route change. This allows for what-if analysis to model and estimate the number of routes based on the future customer demand. 
     The presently disclosed system and method can be especially effective for creation and maintenance of optimal and practical waste collection routes that meet operational realities (such as crossing highways, navigating physical boundaries, etc.) and enabling tactical planning. The number of routes in a given geographical area can be optimized to realize operational efficiencies and add new customers and/or services while still meeting existing customer commitments. Operational planning can be improved, with users having the ability to estimate the number of future routes based on future customer footprint or demand. Seasonal volume changes can be considered, and customers can be put on hold to inform future routes. Future demand from customers can be incorporated in a geographical area to enable the planning of waste collection routes. Estimating the number of future routes enables users to estimate future driver and vehicle needs to meet operational requirements. 
       FIGS. 2-3  and  FIGS. 4-5  herein illustrate exemplary methods with a plurality of sequential, non-sequential, or sequence independent “steps” as described herein. It should be noted that the methods of  FIGS. 2-3  and  FIGS. 4-5  are exemplary and may be performed in different orders and/or sequences as dictated or described herein, and any alternative embodiments thereof. Numerous arrangements of the various “steps” can be utilized. In addition, not all “steps” described herein need be utilized in all embodiments. However, it should be noted that certain particular arrangements of “steps” for the methods described herein are materially distinguishable from and provide distinct advantages over previously known technologies. 
     The presently disclosed system and method can be incorporated into the functional operations of the service vehicles, to communicate and provide routing, optimization and other operational information to vehicle drivers and workers regarding waste/recycling collection and delivery routes. This can occur prior to beginning operations and/or on an ongoing, real time basis. As a result, the disclosed subject matter has a variety of practical applications, as well as provides solutions to a number of technological and business problems of the prior art. 
     Service vehicles used in the waste collection, delivery, disposal and recycling industry often have on-board computers, location devices and interior and exterior safety and non-safety related cameras installed on the exterior and interior thereof. These devices can provide waste services providers and their field managers with information related to the service vehicle, location of the service vehicle, service confirmation, customer service issues, service routing issues, customer site information and safety issues and concerns, as well as provide vehicle drivers and workers with information relating to collection and delivery routes. 
     For example,  FIG. 6  is an example of a services environment  10  where the presently disclosed system and method can be utilized. A service vehicle  15  is configured to provide services to customers, which can include typical lines of waste industry services such as waste collection and transport and/or recycling for commercial, residential and/or industrial. Service vehicle  15  collects waste or recyclables from a plurality of containers  20  which will typically be assigned to, or associated with, specific customers registered to a waste collection company. 
       FIG. 7  illustrates a high-level overview of a system and network according to various illustrative embodiments herein. The components and general architecture of the system and network may be adapted for use in the specific services environment of  FIG. 6 . The system can include one or more data sources  30  and a central server  35 . Data sources  30  may be, for example, devices configured for capturing and communicating operational data indicative of one or more operational characteristics. Data sources  30  are configured to communicate with central server  35  by sending and receiving operational data over a network  45  (e.g., the Internet, an Intranet, or other suitable network). Central server  35  may be configured to process and evaluate operational data received from data sources  30  in accordance with user input received via a user interface provided on a local or remote computer. 
     In the illustrative embodiment shown in  FIGS. 8-10 , a system and network are provided wherein a communications device  50  can be disposed on waste service vehicle  15 . Communications device  50  and central server  35  are configured to communicate with each other via a communications network  45  (e.g., the Internet, an Intranet, a cellular network, or other suitable network). In addition, communications device  50  and central server  35  are configured for storing data to an accessible central server database  96  located on, or remotely from, central server  35 . In the description provided herein, the system may be configured for managing and evaluating the operation of a large fleet of service vehicles  15 . As such, in certain illustrative embodiments, the system may further comprise a plurality of communications devices  50 , each being associated with one of a plurality of waste service vehicles  15 . 
     In certain illustrative embodiments, the communication between communications device  50  provided on-board service vehicle  15  and central server  35  may be provided on a real time basis such that during the collection/delivery route, data is transmitted between each service vehicle  15  and central server  35 . Alternatively, communication device  50  may be configured to temporarily store or cache data during the route and transfer the data to the central server  35  on return of service vehicle  15  to the location of the collection/delivery company. 
     In certain illustrative embodiments, as illustrated in  FIG. 8 , service vehicle  15  can also include an onboard computer  60  and a location device  65 . Onboard computer  60  can be, for example, a standard desktop or laptop personal computer (“PC”), or a computing apparatus that is physically integrated with vehicle  15 , and can include and/or utilize various standard interfaces that can be used to communicate with location device  65  and optical sensor  70 . Onboard computer  60  can also communicate with central server  35  via a communications network  45  via communication device  50 . In certain illustrative embodiments, service vehicle  15  can also include one or more optical sensors  70  such as video cameras and relating processors for gathering image and other data at or near the customer site. 
     Location device  65  can be configured to determine the location of service vehicle  15  always while service vehicle  15  is inactive, in motion and operating and performing service related and nonservice related activities. For example, location device  65  can be a GPS device that can communicate with the collection/delivery company. A satellite  75  or other communications device can be utilized to facilitate communications. For example, location device  65  can transmit location information, such as digital latitude and longitude, to onboard computer  60  via satellite  75 . Thus, location device  65  can identify the location of service vehicle  15 , and therefore the location of the customer site where container  20  is located, after vehicle  15  has arrived at the customer site. 
     In the illustrative embodiment of  FIGS. 9-10 , an exemplary computer system and associated communication network is shown. In certain illustrative embodiments, central server  35  can be configured to receive and store operational data (e.g., data received from waste services vehicle  15 ) and evaluate the data to aid waste services company in improving operational efficiency. Central server  35  can include various means for performing one or more functions in accordance with embodiments of the present invention, including those more particularly shown and described herein; however, central server  35  may include alternative devices for performing one or more like functions without departing from the spirit and scope of the present invention. 
     In certain illustrative embodiments, central server  35  can include standard components such as processor  75  and user interface  80  for inputting and displaying data, such as a keyboard and mouse or a touch screen, associated with a standard laptop or desktop computer. Central server  35  also includes a communication device  85  for wireless communication with onboard computer  60 . 
     Central server  35  may include software  90  that communicates with one or more memory storage areas  95 . Memory storage areas  95  can be, for example, multiple data repositories which stores pre-recorded data pertaining to a plurality of customer accounts. Such information may include customer location, route data, items expected to be removed from the customer site, and/or billing data. For example, using the location (e.g., street address, city, state, and zip code) of a customer site, software  90  may find the corresponding customer account in memory storage areas  95 . Database  96  for data storage can be in memory storage area  95  and/or supplementary external storage devices as are well known in the art. 
     While a “central server” is described herein, a person of ordinary skill in the art will recognize that embodiments of the present invention are not limited to a client-server architecture and that the server need not be centralized or limited to a single server, or similar network entity or mainframe computer system. Rather, the server and computing system described herein may refer to any combination of devices or entities adapted to perform the computing and networking functions, operations, and/or processes described herein without departing from the spirit and scope of embodiments of the present invention. 
     In certain illustrative embodiments, a system is provided for optimizing waste/recycling collection and delivery routes for waste/recycling service vehicles. Central server  35  may utilize memory storage area  95  and processor  75  in communication with memory storage area  95 , and/or onboard computer  60  can be utilized, to perform the method steps described herein and communicate results to/from the vehicle, prior to and/or in real time during performance of the waste/recycling service activity. Also, in certain illustrative embodiments, software can execute the flow of the method steps of  FIGS. 2-3  and  FIGS. 4-5  herein while interacting with the various system elements of  FIGS. 6-10 . 
     In certain illustrative embodiments, the presently disclosed systems and methods can also be utilized in connection with a centralized platform for remote, real-time customer management of waste/recycling pick-up and collection services. In certain illustrative embodiments, a system for facilitating selection and monitoring of waste/recycling pick-up and collection services by a customer can include a memory, an electronic viewing portal with a display for viewing by a customer, and a processor coupled to the memory programmed with executable instructions. The processor and/or memory can be configured to receive identifying information from a customer via the electronic viewing portal, associate the customer with stored customer information based on the identifying information, determine (using back end functionality) one or more waste/recycling pick-up and collection service options for the customer based on the stored customer information, which can include the use of customer and/or container discovery information based on GPS drive path analysis for a waste/recycling service vehicle as described in the various embodiments herein, display the one or more waste/recycling pick-up and collection service options on the display, receive instructions from the customer regarding which of the waste/recycling pick-up and collection service options to perform, and display the status of the performance of the one or more waste/recycling pick-up and collection service options on the electronic viewing portal for viewing by the customer. The customer facing applications may be present in the form of downloadable applications installable and executable on user devices, e.g., “electronic viewing portals” such as computers, smartphones, or tablets. Additionally (or alternatively), the customer applications may be available as one or more web applications, accessible via a client device having an internet browser. The customer facing applications can utilize customer service digitalization and allow a customer to select and/or monitor waste/recycling pick-up and collection services from the provider on a real-time basis, and the customer offerings can be based, in whole or in part, upon back end functionality that includes the use of customer and/or container discovery information based on GPS drive path analysis for a waste/recycling service vehicle, as described in the various embodiments herein. The presently disclosed systems and methods can also be utilized in connection with a centralized platform for remote, real-time customer management of other services besides waste/recycling pick-up and collection services, such as, for example, package delivery, logistics, transportation, food delivery, ride hailing, couriers, freight transportation, etc. 
     Those skilled in the art will appreciate that certain portions of the subject matter disclosed herein may be embodied as a method, data processing system, or computer program product. Accordingly, these portions of the subject matter disclosed herein may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, portions of the subject matter disclosed herein may be a computer program product on a computer-usable storage medium having computer readable program code on the medium. Any suitable computer readable medium may be utilized including hard disks, CD-ROMs, optical storage devices, or other storage devices. Further, the subject matter described herein may be embodied as systems, methods, devices, or components. Accordingly, embodiments may, for example, take the form of hardware, software or any combination thereof, and/or may exist as part of an overall system architecture within which the software will exist. The present detailed description is, therefore, not intended to be taken in a limiting sense. 
     As used herein, the phrase “at least one of” preceding a series of items, with the terms “and” or “or” to separate any of the items, modifies the list as a whole, rather than each member of the list (i.e., each item). The phrase “at least one of” allows a meaning that includes at least one of any one of the items, and/or at least one of any combination of the items, and/or at least one of each of the items. By way of example, the phrases “at least one of A, B, and C” or “at least one of A, B, or C” each refer to only A, only B, or only C; any combination of A, B, and C; and/or at least one of each of A, B, and C. As used herein, the term “A and/or B” means embodiments having element A alone, element B alone, or elements A and B taken together. 
     While the disclosed subject matter has been described in detail in connection with a number of embodiments, it is not limited to such disclosed embodiments. Rather, the disclosed subject matter can be modified to incorporate any number of variations, alterations, substitutions or equivalent arrangements not heretofore described, but which are commensurate with the scope of the disclosed subject matter. 
     Additionally, while various embodiments of the disclosed subject matter have been described, it is to be understood that aspects of the disclosed subject matter may include only some of the described embodiments. Accordingly, the disclosed subject matter is not to be seen as limited by the foregoing description, but is only limited by the scope of the claims.