The present invention relates generally to traffic flow models, and more particularly, to determining real-time queue times for waypoints within venues.
The following description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
Today, position determination is commonly used with maps and navigation in outdoor environments but not indoors. This is because the accuracy of indoor position determination systems relative to the elliptical model of the earth is not representative of the wireless device's true latitude longitude. Therefore, indoor map and navigation systems require a higher measurement resolution of position determination in the horizontal plane and vertical plane commonly seen as your floor number or level number in a structure. Because the GPS and cell signals do not provide the measurement resolution needed for indoor positioning. WiFi, Near Field Communications, RFID, Bluetooth and UWB are just some of the RF systems that offer signal measurement resolutions capable of providing the necessary position determination accuracy for single and multilevel structure.
Through the use of an indoor positioning determining entity in conjunction with a mapping service a wider range of information about any indoor structure and the user(s) within can be accessed and converted into functional data. In specific, there is no system which collects and then correlates dynamic mobile user data location with a structure map which can be used to derive average queue times for waypoints (known locations where queuing is known to occur) or average dwell time for areas (known locations where people tend to dwell) within a structure. A system which could collect multiple instances of mobile user data (time stamps of location or presence) near a known location and then calculate individual dwell time for all users passing through this location would be able to not only determine the average dwell time for this location, but also determine the average dwell time for different groups of individuals.
Exemplary embodiments are illustrated in the referenced figures. It is intended that the embodiments and figures disclosed herein are to be considered illustrative rather than restrictive.
One skilled in the art will recognize many methods, systems, and materials similar or equivalent to those described herein, which could be used in the practice of the present invention. Indeed, the present invention is in no way limited to the methods, systems, and materials described.
Embodiments of the present invention are directed to determining average queue time for a given location, which may be done by collecting a plurality of mobile user locations and comparing the dynamic state of this data to a structure map which can be used to derive average queue times for waypoints within the structure, and is referred to as real-time queuing. In the first embodiment described herein with reference to FIGS. (1) and (6), determining real-time queuing, may be done by identifying an area on a map where queuing occurs and collating a plurality of mobile user time stamps while they are located within the pre-determined location (dwell time). In this embodiment, the system (100) is configured for operative communication with a plurality of positioning determining entities 105 (a.k.a. “location server”) as well as a plurality of mapping services (110) over one or more wireless and/or wired communication networks.
As shown in FIG. (1), the system (100) comprises a plurality of applications or “modules” executable on one or more computers, such as one or more servers, one or more wireless devices (120), or any combination thereof. It should be appreciated that the various modules of the system (100) maybe logically or physically implemented and/or combined in a plurality of ways, and that the invention in not limited to the particular arrangement shown in FIG. (1). Each of the various modules of the system (100) is described below.
The system (100) comprises a positioning determining system or module (105) configured for establishing the location of the wireless device within any given structure. In addition to the location of the wireless device, the positioning determining system will also provide a device identification tag to distinguish individual devices along with a time stamp for each device. The positioning determining system itself is not limited to any one positioning determining entity and thus can be serviced by a variety of providers, e.g. a wireless location server connected to a wi-fi network, or a handset capable of producing accurate indoor location.
The system (100) also comprises a mapping service module (110) configured for creating a latitude and longitude (and altitude) framework for a structure or set of structures, such as a retail store, shopping center, airport, etc. (i.e., a reference geodetic datum). The mapping service itself may refer to the indoor positioning, mapping, and navigation system of Point Inside, but is not limited to any one mapping service system.
The system (100) also comprises a dwell time determination module (115) configured to create real-time queue times for pre-identified queuing locations. The dwell time determination module itself (115) comprises an application that defines an area of a structure to be surveyed, allowing the specification of areas of interest (e.g. areas of high queuing) to be monitored while excluding areas of non-interest. In addition, the dwell time determination module (115) comprises an application that collects and aggregates the time stamps of a plurality of mobile users that have been amassed by a positioning determining entity. In conjunction with an additional application that defines the mathematical processes to be applied, average dwell times can be calculated. In this embodiment, the dwell time determination module (115) calculates the average length of time that a plurality of mobile users spend amassed within the specified area of interest. What is to be appreciated is the fact that the module (115) is also able to recognize multi-modal distributions, thereby discriminating between differing patterns of queuing, such as different lines within a single queuing location.
The system (100) also comprises a publishing service module (125) configured to organize the output of the dwell time determination module (115) and subsequently publish this output on a near real-time basis so that other services may gain access to real-time queue times. A mobile application will then subscribe to this information allowing for the communication of the real-time queue times to user of this application.
The system (100) also comprises a navigation service module (130) configured to receive queue wait times from the publishing service. The navigation service will use this information to determine the best route through the structure as a function of calculated walking times factoring in the queue time to choose the best queue based on the shortest total walking time included queue time.
An example of the operation of the system (100) is provided below. The example is provided for explanatory purposes and should not be considered limiting in any way.
In one example (see
The advantages of this embodiment include, without limitation, providing the ability utilize mobile user metadata in conjunction with mapping services to offer additional functional information; in this case, real-time queue times around areas of high traffic and congestion in locations such as airports and retail stores. Through the use of additional mobile services, this data can then be subscribed to from any number of mobile devices (mobile phones, tablets), providing the user with up to date wait times at various check points, thus enabling the user to choose the most time efficient path through any given structure. Through the use of additional mobile services, this data can then be subscribed to from any number of mobile devices or even a management console, providing insights to enable staff deployments within the location (e.g., additional staff can be deployed to an area where a lot of customers are dwelling; additional staff could be deployed to open checkout stands or security screening facilities).
FIG. (2) illustrate the operation of another embodiment of the present invention. In this embodiment, the system (200) is configured for determining real-time queuing by identifying an area on a map where queuing occurs and collating a plurality of mobile user time stamps once as they enter the specified area and again when they depart that area, creating a measurement of traffic flow through a specified queuing location. By determining the real-time queuing times according to this embodiment, the system (200) may perform similar functions including positioning determination, mapping, position and map correlation, and the like, as discussed above with reference to FIG. (1) and FIGS. (3) through (5b).
In the second embodiment of the present invention, illustrated in
The traffic flow determination module (215) is also configured to determine real-time queue times for pre-identified queuing locations. In this embodiment, it does so through comparing two separate time stamps for each individual mobile user; the first time stamp being created when the mobile user enters the pre-identified queuing location, the second time stamp being created when the mobile user exits the same queuing location. By calculating the lapse of time between each mobile user's time stamps, the traffic flow determination module (215) determines the length of time the mobile user has spent passing through the queuing location and collates this queue time with all the other mobile users also found within the pre-identified queuing location, thereby determining the average queue time for the location. As with the dwell time determination module (115), the traffic flow determination module (215) recognizes multi-modal distributions allowing for queuing times for two or more distinct categories, e.g. different queues within a single queuing area.
An example of the operation of the system (200) is provided below. The example is provided for explanatory purposes and should not be considered limiting in any way.
In this example (see
The advantages of this embodiment include, without limitation, providing the ability to utilize mobile user metadata in conjunction with mapping services to offer additional functional information; in this case, real-time queue times around areas of high traffic and congestion in locations such as airports and grocery stores. Through the use of additional mobile services, this data can then be subscribed to from any number of mobile devices (mobile phones, tablets), providing the user with up to date wait times at various check points, thus enabling the user to choose the most time efficient path through any given structure.
The computing device (800) also includes at least one processing unit (815), memory (835), and an optional display (810), all interconnected along with the network interface (805) via a bus (825). The memory (835) generally comprises a random access memory (“RAM”), a read only memory (“ROM”), and a permanent mass storage device, such as a disk drive or SDRAM (synchronous dynamic random-access memory). The memory (835) stores program code for software modules, such as, for example, the modules discussed above. In addition, the memory (835) also stores an operating system (840). These software components may be loaded from a non-transient computer readable storage medium (830) into memory (835) of the computing device (800) using a drive mechanism (not shown) associated with a non-transient computer readable storage medium (830), such as a floppy disc, tape, DVD/CD-ROM drive, memory card, or other like storage medium. In some embodiments, software components may also or instead be loaded via a mechanism other than a drive mechanism and computer readable storage medium (830) (e.g., via network interface (805)).
The computing device (800) may also comprise hardware supporting optional input modalities, Optional Input (820), such as, for example, a touchscreen, a keyboard, a mouse, a trackball, a stylus, a microphone, and a camera.
Computing device (800) also comprises or communicates via bus (825) with data store (865). In various embodiments, bus (825) may comprise a storage area network (“SAN”), a high speed serial bus, and/or via other suitable communication technology. In some embodiments, computing device (800) may communicate with data store (865) via network interface (805).
This application claims the benefit of the filing date of and incorporates by this reference the following application: 61/548,796, filed 2011 Oct. 19.
Number | Date | Country | |
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61548796 | Oct 2011 | US |