Patent Application
20230053647
The invention relates generally to vehicle ridesharing and systems and methods for ridesharing management. More particularly, the invention relates to ridesharing management systems related to transit systems.
Recent years have witnessed increasing interest and development in the field of vehicle sharing, where one or more riders may share the same vehicle for a portion of their rides. Ridesharing may save ride costs, increase vehicle utilization, and reduce air pollution. A rider may use a ridesharing service through a ridesharing service application accessed by the rider’s mobile device.
Ridesharing service can be performed with a car, van, and/or bus. Ridesharing service can include scheduling pickup-drop offs of riders, determining routes for vehicles, modifying routes for vehicles on the fly. Ridesharing services can operate as fixed route, semi -fixed route, and/or full point-to-point services, and vehicles can be commanded to operate in any of those modes and/or be switched between those service types.
One difficulty with ridesharing management platforms can be an inability to accurately predict a number of ridesharing vehicles needed for a particular zone and/or rigidity in the zone selection. For example, a ridesharing service provider may provide service for different areas at different times. For example, a ridesharing service may provide service for different events or occurrences (e.g., the Olympics, the U.S. Open, local transit becoming inoperable in a particular region, etc.) requiring that the ridesharing service provider predict vehicle supply needs for varying regions at varying times in a short period of time (e.g., real-time or near real-time). One difficulty is that current ridesharing management systems typically rely upon simulations to predict supply, they can require many user inputs, and typically take a long time (e.g., on the order of days) to produce results. Additionally, simulations typically do not produce a number of vehicles needed, instead, a number of vehicles is typically input into the simulation and one or more service characteristics can be determined. If different simulation performance is desired (e.g., service characteristics having different values), the number of vehicles input into the simulation can be increased or decreased and the simulation can be run again. Accordingly, it can be desirable to predict ridesharing vehicle supply in real-time or near real-time for any defined region.
Current ridesharing systems typically do not have the flexibility to switch between supply prediction for a fixed route, on demand or a hybrid fixed route on demand ridesharing scenario. Accordingly, it can be desirable to switch between predicting vehicle supply for a particular region for a fixed route, on demand and/or a hybrid fixed route on demand ridesharing scenario in real-time or near real-time.
Another difficulty with current ridesharing systems typically involves a time -consuming step of deciding on the boundary geography for the service. Typically, in current systems the boundary geography is based on data analysis which often includes running simulations and gathering feedback from stakeholders, which can be time consuming. In some scenarios, users can desire a modification to the boundary geography, e.g., may be interested in understanding the impact on supply if the boundary changes by a few miles. Therefore, it can be desirable to allow for predicting vehicle supply for boundary geography that can easily change such that the results can be available in real-time or near real-time.
Advantages of the invention can include an ability to predict ridesharing vehicle supply in real-time or near real-time for any defined region. Another advantage of the invention can include determining supply of vehicles needed for a region based on historical data rather than on simulation. Another advantage of the invention can include an ability to determine supply of vehicles needed for a region based on a few number of user inputs (e.g., 1, or 5) in comparison to a full set of simulation parameters (e.g., a couple of dozen up to on the order of seventy). Another advantage of the invention can include an ability to determine a value for a supply of vehicles needed for a region.
Another advantage of the invention can include switching between predicting vehicle supply for a particular region for a fixed route, on demand and/or a hybrid fixed route on demand ridesharing scenario in real-time or near real-time. Another advantage of the invention can include predicting vehicle supply for boundary geography that can easily change such that the results can be available in real-time or near real-time.
In one aspect, the invention involves a system for managing a fleet of ridesharing vehicles. The system includes a communications interface configured to receive a plurality of user input boundaries specified on a geographical map, wherein the plurality of user input boundaries define a zone. The system also includes at least one processor configured to estimate a number of riders based on a number of people that live within the zone and a number of people that work within the zone. The at least one processor can also be configured to determine n number of sample trips within the zone, where n is an integer, and wherein each trip has a start location and an end location. The at least one processor can also be configured to determine a number of ridesharing vehicles to supply for the zone over a time duration based on the estimate number of riders and the n number of sample trips within the zone. The at least one processor can also be configured to output the number of ridesharing vehicles to supply to a display.
In some embodiments, n is selected such that variance for speed for each of the n sample trips is below a predetermined value. In some embodiments, n is selected such that variance for distance for each of the n sample trips is below a predetermined value. In some embodiments, n is based on a size of the zone. In some embodiments, n is 1000.
In some embodiments, the start location and the end location of any trip of the n number of sample trips is predetermined. In some embodiments, the number of ridesharing vehicles to supply is a range.
In some embodiments, determining a number of ridesharing vehicles to supply for the zone further comprises determining a confidence value for the determination, and for a confidence value below a threshold outputting an indicator that the zone is low confidence, otherwise, outputting the number of ridesharing vehicles.
In some embodiments, the number of riders is received by a user input, and the user input is used instead of the estimated value. In some embodiments, determining a number of ridesharing vehicles to supply for the zone over a time duration is further based a distance, speed, wait time or any combination thereof.
In another aspect, the invention involves a method for managing a fleet of ridesharing vehicles. The method involves receiving, via communications interface, a plurality of user input boundaries specified on a geographical map, wherein the plurality of user input boundaries define a zone. The method also involves estimating, via a processor, a number of riders based on a number of people that live within the zone and a number of people that work within the zone. The method also involves determining, via the processor, n number of sample trips within the zone, where n is an integer, and wherein each trip has a start location and an end location. The method also involves determining a number of ridesharing vehicles to supply for the zone over a time duration based on the estimate number of riders and the n number of sample trips within the zone. The method also involves outputting the number of ridesharing vehicles to supply to a display.
In some embodiments, n is selected such that variance for speed for each of the n sample trips is below a predetermined value. In some embodiments, n is selected such that variance for distance for each of the n sample trips is below a predetermined value. In some embodiments, n is based on a size of the zone. In some embodiments, n is 1000.
In some embodiments, the start location and the end location of any trip of the n number of sample trips is predetermined. In some embodiments, the number of ridesharing vehicles to supply is a range. In some embodiments, determining a number of ridesharing vehicles to supply for the zone further comprises determining a confidence value for the determination, and for a confidence value below a threshold outputting an indicator that the zone is low confidence, otherwise, outputting the number of ridesharing vehicles.
In some embodiments, the number of riders is received by a user input, and the user input is used instead of the estimated value. In some embodiments, determining a number of ridesharing vehicles to supply for the zone over a time duration is further based a distance, speed, wait time or any combination thereof.
The foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the claims.
The subject matter regarded as the invention is particularly pointed out and distinctly claimed in the concluding portion of the specification. The invention, however, both as to organization and method of operation, together with objects, features and advantages thereof, can be understood by reference to the following detailed description when read with the accompanied drawings. Embodiments of the invention are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like reference numerals indicate corresponding, analogous or similar elements, and in which:
In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be understood by those skilled in the art that the present invention can be practiced without these specific details. In other instances, well-known methods, procedures, and components, modules, units and/or circuits have not been described in detail so as not to obscure the invention.
The users 130A-130F can be riders, drivers and/or other computing systems. In
The network 140 can be coupled to the user devices 120 to facilitate communications between the user devices 120 and the ridesharing management server 150. For example, the rider 130A can request a ride via the rider device 120A that is a smart phone. The request can be transmitted by the user device 120A to the ridesharing management server 150 through the network 140. The ridesharing management server 150 can transmit a route to the driver device 120E to instruct the driver 130E to pick-up the rider 130A. The ridesharing management server 150 can transmit a message to the rider 130A via the rider device 120A indicating that the driver 130E is on its way and the message can instruct the rider 130A to a particular pick-up location.
The network 140 can facilitate communications that include receiving ride requests and/or other ride related input from or sending confirmations to the rider devices 120A-120C and/or sending ride service assignments to the driver devices 120D-120E and driving-control device 120F.
The network 140 can be any type of network that provides communications, exchanges information, and/or facilitates the exchange of information between ridesharing management server 150 and user devices 120. For example, network 140 can be the Internet, a Local Area Network, a cellular network, a public switched telephone network (“PSTN”), and/or other suitable connection(s) that enables ridesharing management system 100 to send and/or receive information between the components of the ridesharing management system 100. The network 140 can be wired and/or wireless depending on the type of connection to the network 140. Although the network 140 is shown herein as a cloud, the network 140 can include a variety of computing components, including wired and wireless components that in various networked configurations to facilitate desired communication between components.
The network 140 can support a variety of messaging formats as is known in the art and may support a variety of services and applications for user devices 120. For example, the network 140 can support navigation services for user devices 120, such as directing users and/or ridesharing service vehicles to pick-up and/or drop-off locations.
The ridesharing management server 150 can be a system that communicates with and/or is part of a communication service provider which provides a variety of data or services, such as voice, messaging, real-time audio/video, to users, such as users 130A-130E. The ridesharing management server 150 can be a computer-based system including computer system components, desktop computers, workstations, tablets, handheld mobile communications devices, memory devices, and/or internal network(s) connecting the components.
The ridesharing management server 150 can receive information from user devices 120 over the network 140, process the information, store the information, and/or transmit information to mobile communications devices 120 over network 140. The ridesharing management server 150 can receive ride requests from user devices 120A-120C. The ridesharing management server 150 can send ride confirmation and/or ride fare information to user devices 120A-120C. The ridesharing management server 150 can send ride service assignments (e.g., including pick-up and/or drop-off location information) to driver devices 120D and 120E, and driving-control device 120F.
The ridesharing management server 150 can receive user input from user devices 120A-120C. For example, the ridesharing management server 150 can receive various ride service parameters, such as walking distance to a pick-up location, maximum delay of arrival/detour, and/or maximum number of subsequent pick-ups. The ridesharing management server 150 can receive various ride summary metrics such as actual pickup location, actual drop off location, ride duration, number of passengers for the ride. The ridesharing management server 150 can receive requests for supply planning that can include user input boundaries specified on geographical map defining a zone, as described in further detail below in
The ridesharing management server 150 can receive user input from user devices 120D, 120E and 120F. For example, the ridesharing management server 150 can receive from each of the user devices GPS locations, a time stamp the GPS location was received by the user device, and/or a speed of the vehicle (e.g., in meters/second) at the time the GPS location was received by the respective user device.
The rideshare vehicle can be a car, van, SUV, truck, bus or any kind of vehicle suitable for human transportation. In some embodiments, a vehicle is a taxi. In some embodiments, a rideshare vehicle can be an autonomous vehicle, wherein a control device integrated with the vehicle, or a management system separate from the vehicle can send operational messages.
The ridesharing management server 150 can calculate ride fares based on a solo portion of a user’s ride and a shared portion of the ride. The ride fare calculation can be based on various ride service parameters set by the user, such as the walking distance involved in the ride, and/or user selection regarding toll road usage.
The database 170 may include one or more physical and/or virtual storages coupled with the ridesharing management server 150. The database 170 can store user account information (e.g., registered rider and/or driver accounts) and/or corresponding user profiles (e.g., contact information, profile photos, and/or associated mobile communications device information). User account information for a rider can include ride history, service feedback, complaints, and/or comments. User account information for a driver can include number of ride service assignments completed, ratings, and/or ride service history information. The database 170 can store various ride requests received from user devices 120A-120C. Each ride request can include a corresponding starting point and desired destination information, user input regarding various service parameters, pick-up and drop-off locations, time of pick-up and drop-off, ride fares, and/or other user feedback (e.g., user comments).
The database 170 may include traffic data, maps, and/or toll road information, which may be used for ridesharing service management. The traffic data may include historical traffic data and/or real-time traffic data regarding a certain geographical region. The traffic data may be used to determine traffic conditions. Traffic data and traffic conditions can be used to estimate pick-up and drop-off times for riders and/or determine an optimal route for a particular ride or for all rides. The real-time traffic data may be received from a real-time traffic monitoring system, which may be integrated into or independent from ridesharing management system 100. The database 170 may include GPS locations, time stamps, and/or speed of the vehicle received from one or more user devices.
The maps may include map information (e.g., roads, streets and/or distances) typically used for navigation purposes. The map information can be used to determine potential routes and in transit routes for the rideshare vehicles and/or guiding the users to a pick-off or drop-off location. Guiding the users to a pick-up or drop off location can include displaying a map, outputting audio, displaying a list of directions or any combination thereof. The in-transit routes can be modified based on adding or reducing passengers, the driver driving off the route, speed and/or other updates. Toll road information may include an amount of toll charges regarding certain roads, and any change or updates thereof. Toll road information may be used to calculate ride fares. In some embodiments, a rider can specify that the rideshare vehicle route avoids toll roads.
The data stored in database 170 can be transmitted to the ridesharing management server 150 for accommodating ride requests. In some embodiments, the database 170 is stored in a cloud-based server (not shown) that is accessible by the ridesharing management server 150 and/or user devices 120 through the network 140. In some embodiments, the database 170 reside within the ridesharing management server 150.
During operation, the ridesharing management server 150 can communicate with the driving-control device 120F to direct the autonomous vehicle 130F to pick up and drop off riders 130A-130C. In some embodiments, autonomous vehicles capable of detecting objects on the road and navigate to designated locations may be utilized for providing ridesharing services.
In various embodiments, the ridesharing management server 150 is implemented on a single server or on multiple servers. Each server can be on a single computing device or distributed among multiple computing devices. In various embodiments, the ridesharing management system 100 includes multiple ridesharing management servers, and each ridesharing management server can serve a category of ridesharing services, ridesharing services associated with a certain category of service vehicles, and/or ridesharing services in a specific geographical region. For example, a first ridesharing management server can direct a first fleet of vehicles, a second ridesharing management server can direct a second fleet of vehicles and a third ridesharing server can direct a third fleet of vehicles. The first, second and third fleet of vehicles can be on-demand services, fixed-route services, or any combination thereof.
In some embodiments, a plurality of ridesharing management servers collectively provides a dynamic and integrated ridesharing service system.
As shown in
In some embodiments, a user may directly hail a vehicle by hand gesture or verbal communication, such as traditional street vehicle hailing. In such embodiments, once a driver accepts the request, the driver can use his respective user device to input the ride request information. Ridesharing management server 150 can receive the information, and accordingly assign one or more additional ride service assignments to the same vehicle, for example, subsequent ride requests received from other user devices 120 through network 140.
In some embodiments, driver devices 120D and 120E, and driving-control device 120F may be embodied in a vehicle control panel, as a part of the vehicle control system associated with a particular vehicle. For example, a traditional taxi company may install a drive device in all taxi vehicles managed by the taxi company. In some embodiments, driver devices 120D and 120E, and driving-control device 120F, may be further coupled with a payment device, such as a card reader installed as a part of the vehicle control panel or as a separate device associated with the vehicle. A user may then use the payment device as an alternative payment mechanism. For example, a user who hails the taxi on the street may pay through the payment device, without using a user device providing ridesharing service.
Turning back to
Sensors, devices, and subsystems can be coupled to peripherals interface 206 to facilitate multiple functionalities. For example, a motion sensor 210, a light sensor 212, and a proximity sensor 214 may be coupled to peripherals interface 206 to facilitate orientation, lighting, and/or proximity functions. One or more sensors 216 can be connected to peripherals interface 206, such as a positioning system (e.g., GPS receiver), a temperature sensor, a biometric sensor, and/or other sensing devices. A GPS receiver can be integrated with, or connected to, mobile communications device 200. For example, a GPS receiver may be included in mobile telephones, such as smartphone devices. GPS software can allow mobile telephones to use an internal and/or external GPS receiver (e.g., connecting via a serial port or Bluetooth). A camera subsystem 220 and/or an optical sensor 222, e.g., a charged coupled device (“CCD”) or a complementary metal-oxide semiconductor (“CMOS”) optical sensor, can be used to facilitate camera functions, such as recording photographs and video clips.
Communication functions can be facilitated through one or more wireless/wired communication subsystems 224, which can include an Ethernet port, radio frequency receivers and transmitters and/or optical (e.g., infrared) receivers and/or transmitters. The specific design and implementation of wireless/wired communication subsystem 224 may depend on the communication network(s) over which mobile communications device 200 is intended to operate. For example, in some embodiments, mobile communications device 200 may include wireless/wired communication subsystems 224 designed to operate over a GSM network, a GPRS network, an EDGE network, a Wi-Fi or WiMax network, and a Bluetooth® network.
An audio subsystem 226 may be coupled to a speaker 228 and a microphone 230 to facilitate voice-enabled functions, such as voice recognition, voice replication, digital recording, and/or telephony functions.
I/O subsystem 240 may include touch screen controller 242 and/or other input controller(s) 244. Touch screen controller 242 may be coupled to touch screen 246. Touch screen 246 and touch screen controller 242 may, for example, detect contact and movement or break thereof using any of a plurality of touch sensitivity technologies, including but not limited to capacitive, resistive, infrared, and surface acoustic wave technologies, as well as other proximity sensor arrays or other elements for determining one or more points of contact with touch screen 246. While touch screen 246 is shown in
Other input controller(s) 244 may be coupled to other input/control devices 248, such as one or more buttons, rocker switches, thumb-wheel, infrared port, USB port, and/or a pointer device such as a stylus. Touch screen 246 may, for example, also be used to implement virtual or soft buttons and/or a keyboard.
Memory interface 202 may be coupled to memory 250. Memory 250 includes high-speed random access memory and/or non-volatile memory, such as one or more magnetic disk storage devices, one or more optical storage devices, and/or flash memory (e.g., NAND, NOR). Memory 250 may store an operating system 252, such as DRAWIN, RTXC, LINUX, iOS, UNIX, OS X, WINDOWS, or an embedded operating system such as VXWorkS. Operating system 252 may include instructions for handling basic system services and for performing hardware dependent tasks. In some implementations, operating system 252 can be a kernel (e.g., UNIX kernel).
Memory 250 may also store communication instructions 254 to facilitate communicating with one or more additional devices, one or more computers and/or one or more servers. Memory 250 can include graphical user interface instructions 256 to facilitate graphic user interface processing; sensor processing instructions 258 to facilitate sensor-related processing and functions; phone instructions 260 to facilitate phone-related processes and functions; electronic messaging instructions 262 to facilitate electronic-messaging related processes and functions; web browsing instructions 264 to facilitate web browsing-related processes and functions; media processing instructions 266 to facilitate media processing-related processes and functions; GPS/navigation instructions 268 to facilitate GPS and navigation -related processes and instructions; camera instructions 270 to facilitate camera-related processes and functions; and/or other software instructions 272 to facilitate other processes and functions.
In some embodiments, communication instructions 254 may include software applications to facilitate connection with ridesharing management server (e.g., ridesharing management server 150 as described above in
Each of the above identified instructions and applications may correspond to a set of instructions for performing one or more functions described above. These instructions need not be implemented as separate software programs, procedures, or modules. Memory 250 may include additional instructions or fewer instructions. Furthermore, various functions of mobile communications device 200 may be implemented in hardware and/or in software, including in one or more signal processing and/or application specific integrated circuits.
As shown in
The ridesharing management server 150 can be a computer platform that provides services via a network, such as the Internet, it can use virtual machines that may not correspond to individual hardware. The computational and/or storage capabilities can be implemented by allocating appropriate portions of desirable computation/storage power from a scalable repository, such as a data center and/or a distributed computing environment.
Processor 310 may be one or more processing devices configured to perform functions of the disclosed methods, such as a microprocessor manufactured by Intel™ or manufactured by AMD™. Processor 310 can include a single core or multiple core processors executing parallel processes simultaneously. For example, processor 310 may be a single core processor with virtual processing technologies. In some embodiments, processor 310 can uses logical processors to simultaneously execute and/or control multiple processes. Processor 310 can implement virtual machine technologies, and/or other technologies to provide the ability to execute, control, run, manipulate, and/or store multiple software processes, applications, programs. In some embodiments, processor 310 includes a multiple-core processor arrangement (e.g., dual and/or quad core) to provide parallel processing functionalities to allow ridesharing management server 150 to execute multiple processes simultaneously. It is appreciated by one of ordinary skill in the art that other types of processor arrangements can be implemented that provide for the capabilities disclosed herein.
Memory 320 can be a volatile or non-volatile, magnetic, semiconductor, tape, optical, removable, non-removable, or other type of storage device or tangible or non-transitory computer-readable medium that stores one or more program(s) 330 such as server apps 332 and operating system 334, and data 340. Common forms of non-transitory media include, for example, a flash drive, a flexible disk, hard disk, solid state drive, magnetic tape, or any other magnetic data storage medium, a CD-ROM, any other optical data storage medium, any physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM or any other flash memory, NVRAM, a cache, a register, any other memory chip or cartridge, and networked versions of the same.
The ridesharing management server (e.g., ridesharing management server 150 as described above in
Database 170 or other external storage may be a volatile or non-volatile, magnetic, semiconductor, tape, optical, removable, non-removable, or other type of storage device or tangible or non-transitory computer-readable medium. Memory 320 and database 170 may include one or more memory devices that store data and instructions used to perform one or more features of the disclosed embodiments. Memory 320 and database 170 may also include any combination of one or more databases controlled by memory controller devices (e.g., server(s), etc.) or software, such as document management systems, Microsoft SQL databases, SharePoint databases, Oracle™ databases, Sybase™ databases, or other relational databases.
In some embodiments, ridesharing management server 150 may be communicatively connected to one or more remote memory devices (e.g., remote databases (not shown)) through network 140 or a different network. The remote memory devices can be configured to store information that ridesharing management server 150 can access and/or manage. By way of example, the remote memory devices may include document management systems, Microsoft SQL database, SharePoint databases, Oracle™ databases, Sybase™ databases, or other relational databases. Systems and methods consistent with disclosed embodiments, however, are not limited to separate databases or even to the use of a database.
Programs 330 may include one or more software modules causing processor 310 to perform one or more functions of the disclosed embodiments. Moreover, processor 310 may execute one or more programs located remotely from one or more components of the ridesharing management system 100. For example, ridesharing management server 150 may access one or more remote programs that, when executed, perform functions related to disclosed embodiments.
In the presently described embodiment, server app(s) 332 may cause processor 310 to perform one or more functions of the disclosed methods. For example, devices associated with users, drivers and autonomous vehicles may respectively be installed with user applications for vehicle ridesharing services, and driver applications for vehicle ridesharing services. Further, a mobile communications device may be installed with both the driver applications and the user applications, for uses in corresponding situations.
In some embodiments, other components of ridesharing management system 100 may be configured to perform one or more functions of the disclosed methods. For example, mobile communications devices 120 may be configured to calculate estimate pick-up and drop-off times based on a certain ride request, and may be configured to calculate estimate ride fares. As another example, mobile communications devices 120 may further be configured to provide navigation service, and location service, such as directing the user to a particular pick-up or drop-off location, and providing information about a current location of the respective user or vehicle to ridesharing management server 150.
In some embodiments, program(s) 330 may include operating system 334 performing operating system functions when executed by one or more processors such as processor 310. By way of example, operating system 334 may include Microsoft Windows™, Unix™, Linux™, Apple™ operating systems, Personal Digital Assistant (PDA) type operating systems, such as Apple iOS, Google Android, Blackberry OS, Microsoft CE™, or other types of operating systems. Accordingly, the disclosed embodiments may operate and function with computer systems running any type of operating system 334. Ridesharing management server 150 may also include software that, when executed by a processor, provides communications with network 140 through communications interface 360 and/or a direct connection to one or more mobile communications devices 120. Specifically, communications interface 360 may be configured to receive ride requests (e.g., from user devices 120A -120C) headed to differing destinations, and receive indications of the current locations of the ridesharing vehicles (e.g., from driver devices 120D and 120E or driving-control device 120F). In one example, communications interface 360 may be configured to continuously or periodically receive current vehicle location data for the plurality of ridesharing vehicles that are part of ridesharing management system 100. The plurality of ridesharing vehicles can be a car fleet, bus fleet or any combination thereof. The current vehicle location data may include global positioning system (GPS) data generated by at least one GPS component of a mobile communications device 120 associated with each ridesharing vehicle.
In some embodiments, data 340 may include, for example, profiles of users, such as user profiles or driver profiles. User profiles can include contact information, profile photos, user account information and/or associated mobile communications device information. Rider account information can include ride history, service feedbacks, complaints, and/or comments. Driver account information can include number of ride service assignments completed, ratings, ride service history, rider ride history, driver service record, and/or communications between a driver and a rider regarding a particular ride request. In some embodiments, data 340 may further include traffic data, toll road information, and navigation information, which may be used for handling and accommodating ride requests.
Automated ridesharing dispatch system 300 may also include one or more I/O devices 350 having one or more interfaces for receiving signals or input from devices and providing signals or output to one or more devices that allow data to be received and/or transmitted by automated ridesharing dispatch system 300. For example, automated ridesharing dispatch system 300 may include interface components for interfacing with one or more input devices, such as one or more keyboards, mouse devices, and the like, that enable automated ridesharing dispatch system 300 to receive input from an operator or administrator (not shown).
The method involves receiving (e.g., via the communications interface 360 as described above with respect to
As shown in
In some embodiments, each of the plurality of user input boundaries are based on starting latitude and longitude coordinates and ending latitude and longitude coordinates with the boundary being defined by a function between the two. The function can be linear, a curve or any function as is known in the art. The function can be a user input and/or retrieved from a file.
In some embodiments, the plurality of user input boundaries are pulled by an application programming interface or fetched from a web service hosted by a transit agency and/or another rideshare provider. For example, in the event that a transit agency has predefined boundaries. In some embodiments, the plurality of user input boundaries are saved from a GIS layer visually displayed (e.g., a visualization of a city boundary).
In some embodiments, key pick-up points and key drop-off points can be specified. For example, a user can select one or more key pick-up points and/or one or more key drop-off points. The key pick-up points and/or key drop-off points can be locations where rides are required to begin and/or end, respectively for a particular region (e.g., a transit station where the ridesharing service only provides service to and from that transit station from other points in the region). The key pick-up points and/or key drop-off points can be a common location where some percentage of rides should begin and/or end in a region, respectively, and the user can configure the percentage of trips that start and/or end at that point (e.g., a Wal-Mart in the zone that is a common destination). For example,
Turning back to
The method can also involve estimating a number of riders based on a number of people that live within the zone, a number of people that work within the zone, or both (Step 420).
The number of people that live within the zone can be determined based on government provided census data or user input data set with population, which can be at the census block or block group level. In some embodiments, when the zone determined by the user does not match the underlying geometry of the available zone for the data to be used for determining the number of people (e.g., census blocks), the number of people can be determined based on an overlap between the zone determined by the user and the available zones for the data (e.g., a geospatial intersection calculation).
In some embodiments, the number of people that live within the zone can be received from a user input.
The number of people that live and work within the zone can be determined based on government provided census data or user input data set with population and jobs, which can be at the census block or block group level. In some embodiments, when the zone determined by the user does not match the underlying geometry of the available zone for the data to be used for determining the population and jobs (e.g., census blocks), the population and jobs can be determined based on an overlap between the zone determined by the user and the available zone for the data.
In some embodiments, the number of people that work within the zone can be received from a user input.
The number of riders can be determined from the number of people that live within the zone and the number of people that work within the zone based on a machine learning model. In some embodiments, the machine learning model is a capture rate model (e.g., 0.5-1.5% of total pop and jobs) based on a blended average of capture rates for best fit services where results update regularly. In some embodiments, the machine learning model is a regression model. The regression model can be based on type of on demand service, population density, significant demographic population (e.g., seniors or students), and/or other predictive attributes.
In some embodiments, the regression model has coefficients that vary based on whether the zone is within an urban environment or a rural environment. In some embodiments, if the number of vehicles in the ridesharing management system is less than a threshold value (e.g., 10 vehicles), the regression model has a first set of coefficients, and if the number of vehicles is greater than or equal to the threshold value the regression model has a second set of coefficients, where the first set of coefficients and the second set of coefficients are not equal.
In some embodiments, a user can input the number of riders. In these embodiments, the number of riders input by the user can be used instead of the estimated number of riders. This can be desirable, for example, when the transit agency already has an idea of demand. For example, a transit agency may have an idea of demand if the transit agency has fixed route ridership data for the area of the zone, if the transit agency already has a rideshare service operating in the zone with a different rideshare operator, and/or if the transit agency has other rideshare services running in other parts of the city which can give them an idea of what percentage capture rate they might get for the service. In some embodiments, the user can input the number of riders because they have local data and/or aware of other factors that may improve prediction.
The method can also involve determining n number of sample trips within the zone, where n is an integer, and wherein each trip has a start location and an end location (Step 430). In various embodiments, the start location and/or the end location is predetermined. In various embodiments, the start location and /or the end location can be input by a user. In various embodiments, the sample trips are based on historical data for the zone. In some embodiments, the start location and/or the end location is based on historical data.
Each trip can also include an average speed of the trip, number of passengers in the trip, trip duration, routed distance, and/or shortest distance from one place to another.
In some embodiments, n is any integer value. In some embodiments, n is 1000. In some embodiments, n is a user input. In some embodiments, n is based on variance and/or speed for an initial set of trips in the zone. For example, if variance is high for an initial set of trips in the zone (e.g., 10 trips), then n can be increased.
The n number of sample trips can be used to determine speeds and/or trip distance by, for example, using map service (e.g., TomTom, Mapbox, Google Maps), wherein the start location and start time and the end location and end time of each trip can be a basis for determining speed and/or routed trip distance for each trip. A mean and/or variance for speed and/or routed trip distance can be determined for the n number of sampled trips.
In some embodiments, the mean and/or variance for speed and/or routed trip distance can be based on a Google Maps API outputs based on the input of the n number of sampled trips.
In some embodiments, the sampled trips are selected from all of the trips by first looking at points of interest (POI). For each POI, multiply the percentage of trips that are assigned to the POI by the number of samples (e.g., n = 1000), and select randomly that number of trips from the respective POI. For example, if POI has 20% of trips, and n is 1000, then 200 trips are assigned from that POI. Each POI is analyzed and the respective percentage of trips selected. If there are more POI trips then available samples, then all of the POIs can be scaled down. If there are less POI trips such that more samples need to be selected, then additional locations can be randomly sampled within the zone. In some embodiments, the POIs are the pick-up location and the service hubs are the drop-off location. The drop-off locations can be allocated according to percentages similar to the POIs for multiple service hubs. In some embodiments, if there is only one service hub, all POIs have the same drop-off location, the service hub. In some embodiments, if there are no service hubs, the drop-off locations are randomly sampled within the zone. In some embodiments, an assumption can be made that the distance is symmetrical between the POI and the service hub irrespective of the direction of travel.
In some embodiments, n is selected such that variance for the average speed of the n sample trips is below a predetermined value. The predetermined value can be based on a desired variance in the vehicle supply. For example, n can be chosen such that a range of variance in the supply leads to a vehicle supply within the range (e.g., plus or minus 3 vehicles). The predetermined value can be input by a user.
In some embodiments, n is selected such that variance for average distance for the n sample trips is below a predetermined value. The predetermined value can be based on a desired variance in the vehicle supply. For example, n can be chosen such that a range of variance in the supply leads to a vehicle supply within the range (e.g., plus or minus 3 vehicles). The predetermined value can be input by a user.
In some embodiments, n is based on a size of the zone.
The method can also involve determining a number of ridesharing vehicles to supply for the zone over a time duration based on the estimated number of riders and the n number of sample trips within the zone (Step 440). As described above in Step 430, the n number of sampled trips is used to determine distance and speed, thus the number of ridesharing vehicles is based on the n number on sample trips within the zone.
The time duration can be set by a user. The time duration can be automatically determined based on a common service window (e.g., 6am - 8pm). The time duration can be 8 hours, 16 hours, 24 hours, 2 days, 7 days, or any time duration.
Turning back to
The number of ridesharing vehicles to supply can be determined based on a machine learning model that takes as input the estimated number of riders and one or more parameters of each of the n number of sample trips within the zone. The one or more parameters can include average trip distance, average speed, and/or number of passengers over a predetermined duration for the number of sample trips within the zone. In some embodiments, the one or more parameters impact vehicles to supply via a log-linear regression model.
The number of ridesharing vehicles to supply can be a single integer value or can be a range of integer values. In some embodiments, the range is larger when the modeled variance is larger.
In some embodiments, a low confidence value results from “out of sample” results.
In some embodiments, a confidence value is determined. The confidence value can indicate a confidence for the number of ridesharing vehicles to supply. If the confidence value is greater than a predetermined threshold, then there can be sufficient confidence in the determination of the number of ridesharing vehicles to supply. If the confidence value is below a threshold, then a is insufficient confidence in the determination of the number of ridesharing vehicles to supply. In some embodiments, the confidence value can be based on quality and/or commonality of the data that the machine learning model has been trained on in the range of the inputs supplied. For example, if the zone is the size of the state of Alabama, the confidence is likely low because the training data is unlikely to contain many zones that large.
In some embodiments, a low confidence indicator is output to the user (e.g., via a display).
The method can also involve outputting the number of ridesharing vehicles to supply (Step 450). The number of ridesharing vehicles to supply can be output to a display (e.g., display of a user making the request). For example, Table 1 as shown below is an example of ridesharing supply output:
Table 1
Turning to
One skilled in the art will realize the invention can be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting of the invention described herein. Scope of the invention is thus indicated by the appended claims, rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
In the foregoing detailed description, numerous specific details are set forth in order to provide an understanding of the invention. However, it will be understood by those skilled in the art that the invention can be practiced without these specific details. In other instances, well-known methods, procedures, and components, modules, units and/or circuits have not been described in detail so as not to obscure the invention. Some features or elements described with respect to one embodiment can be combined with features or elements described with respect to other embodiments.
Although embodiments of the invention are not limited in this regard, discussions utilizing terms such as, for example, "processing," "computing," "calculating," "determining," "establishing", "analyzing", "checking", or the like, can refer to operation(s) and/or process(es) of a computer, a computing platform, a computing system, or other electronic computing device, that manipulates and/or transforms data represented as physical (e.g., electronic) quantities within the computer’s registers and/or memories into other data similarly represented as physical quantities within the computer’s registers and/or memories or other information non-transitory storage medium that can store instructions to perform operations and/or processes.
Although embodiments of the invention are not limited in this regard, the terms “plurality” and “a plurality” as used herein can include, for example, “multiple” or “two or more”. The terms “plurality” or “a plurality” can be used throughout the specification to describe two or more components, devices, elements, units, parameters, or the like. The term set when used herein can include one or more items. Unless explicitly stated, the method embodiments described herein are not constrained to a particular order or sequence. Some of the described method embodiments or elements thereof can occur or be performed simultaneously, at the same point in time, or concurrently.
A computer program can be written in any form of programming language, including compiled and/or interpreted languages, and the computer program can be deployed in any form, including as a stand-alone program or as a subroutine, element, and/or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site.
Method steps can be performed by one or more programmable processors executing a computer program to perform functions of the invention by operating on input data and generating output. Method steps can also be performed by an apparatus and can be implemented as special purpose logic circuitry. The circuitry can, for example, be a FPGA (field programmable gate array) and/or an ASIC (application-specific integrated circuit). Modules, subroutines, and software agents can refer to portions of the computer program, the processor, the special circuitry, software, and/or hardware that implement that functionality.
Processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer. Generally, a processor receives instructions and data from a read -only memory or a random access memory or both. The essential elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Generally, a computer can be operatively coupled to receive data from and/or transfer data to one or more mass storage devices for storing data (e.g., magnetic, magneto-optical disks, or optical disks).
Data transmission and instructions can also occur over a communications network. Information carriers suitable for embodying computer program instructions and data include all forms of non-volatile memory, including by way of example semiconductor memory devices. The information carriers can, for example, be EPROM, EEPROM, flash memory devices, magnetic disks, internal hard disks, removable disks, magneto-optical disks, CD-ROM, and/or DVD-ROM disks. The processor and the memory can be supplemented by, and/or incorporated in special purpose logic circuitry.
To provide for interaction with a user, the above-described techniques can be implemented on a computer having a display device, a transmitting device, and/or a computing device. The display device can be, for example, a cathode ray tube (CRT) and/or a liquid crystal display (LCD) monitor. The interaction with a user can be, for example, a display of information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer (e.g., interact with a user interface element). Other kinds of devices can be used to provide for interaction with a user. Other devices can be, for example, feedback provided to the user in any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback). Input from the user can be, for example, received in any form, including acoustic, speech, and/or tactile input.
The computing device can include, for example, a computer, a computer with a browser device, a telephone, an IP phone, a mobile device (e.g., cellular phone, personal digital assistant (PDA) device, laptop computer, electronic mail device), and/or other communication devices. The computing device can be, for example, one or more computer servers. The computer servers can be, for example, part of a server farm. The browser device includes, for example, a computer (e.g., desktop computer, laptop computer, and tablet) with a World Wide Web browser (e.g., Microsoft® Internet Explorer® available from Microsoft Corporation, Chrome available from Google, Mozilla® Firefox available from Mozilla Corporation, Safari available from Apple). The mobile computing device includes, for example, a personal digital assistant (PDA).
Website and/or web pages can be provided, for example, through a network (e.g., Internet) using a web server. The web server can be, for example, a computer with a server module (e.g., Microsoft® Internet Information Services available from Microsoft Corporation, Apache Web Server available from Apache Software Foundation, Apache Tomcat Web Server available from Apache Software Foundation).
The storage module can be, for example, a random access memory (RAM) module, a read only memory (ROM) module, a computer hard drive, a memory card (e.g., universal serial bus (USB) flash drive, a secure digital (SD) flash card), a floppy disk, and/or any other data storage device. Information stored on a storage module can be maintained, for example, in a database (e.g., relational database system, flat database system) and/or any other logical information storage mechanism.
The above-described techniques can be implemented in a distributed computing system that includes a back-end component. The back-end component can, for example, be a data server, a middleware component, and/or an application server. The above-described techniques can be implemented in a distributing computing system that includes a front-end component. The front-end component can, for example, be a client computer having a graphical user interface, a Web browser through which a user can interact with an example implementation, and/or other graphical user interfaces for a transmitting device. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), the Internet, wired networks, and/or wireless networks.
The system can include clients and servers. A client and a server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.
The above-described networks can be implemented in a packet-based network, a circuit-based network, and/or a combination of a packet-based network and a circuit-based network. Packet-based networks can include, for example, the Internet, a carrier internet protocol (IP) network (e.g., local area network (LAN), wide area network (WAN), campus area network (CAN), metropolitan area network (MAN), home area network (HAN), a private IP network, an IP private branch exchange (IPBX), a wireless network (e.g., radio access network (RAN), 802.11 network, 802.16 network, general packet radio service (GPRS) network, HiperLAN), and/or other packet-based networks. Circuit-based networks can include, for example, the public switched telephone network (PSTN), a private branch exchange (PBX), a wireless network (e.g., RAN, Bluetooth®, code-division multiple access (CDMA) network, time division multiple access (TDMA) network, global system for mobile communications (GSM) network), and/or other circuit-based networks.
Some embodiments of the present invention may be embodied in the form of a system, a method or a computer program product. Similarly, some embodiments may be embodied as hardware, software or a combination of both. Some embodiments may be embodied as a computer program product saved on one or more non-transitory computer readable medium (or media) in the form of computer readable program code embodied thereon. Such non-transitory computer readable medium may include instructions that when executed cause a processor to execute method steps in accordance with embodiments. In some embodiments the instructions stored on the computer readable medium may be in the form of an installed application and in the form of an installation package.
Such instructions may be, for example, loaded by one or more processors and get executed. For example, the computer readable medium may be a non-transitory computer readable storage medium. A non-transitory computer readable storage medium may be, for example, an electronic, optical, magnetic, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof.
Computer program code may be written in any suitable programming language. The program code may execute on a single computer system, or on a plurality of computer systems.
One skilled in the art will realize the invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The foregoing embodiments are therefore to be considered in all respects illustrative rather than limiting of the invention described herein. Scope of the invention is thus indicated by the appended claims, rather than by the foregoing description, and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
In the foregoing detailed description, numerous specific details are set forth in order to provide an understanding of the invention. However, it will be understood by those skilled in the art that the invention can be practiced without these specific details. In other instances, well-known methods, procedures, and components, modules, units and/or circuits have not been described in detail so as not to obscure the invention. Some features or elements described with respect to one embodiment can be combined with features or elements described with respect to other embodiments.
This application claims the benefit of and priority to U.S. Provisional Pat. App No. 63/235,431, filed Aug. 20, 2021, the entire contents of which are owned by the assignee of the instant application and incorporated herein by reference in their entirety.
| Number | Date | Country | |
|---|---|---|---|
| 63235431 | Aug 2021 | US |
