WO2024118050A1 - Identification de régions candidates sur la base d'une commutabilité partagée - Google Patents

Identification de régions candidates sur la base d'une commutabilité partagée Download PDF

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Publication number
WO2024118050A1
WO2024118050A1 PCT/US2022/051166 US2022051166W WO2024118050A1 WO 2024118050 A1 WO2024118050 A1 WO 2024118050A1 US 2022051166 W US2022051166 W US 2022051166W WO 2024118050 A1 WO2024118050 A1 WO 2024118050A1
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geographic region
carpools
metric
business
frequenters
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PCT/US2022/051166
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English (en)
Inventor
Bruce BAHNSEN
Yan Borisovich MAYSTER
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Google Llc
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Priority to PCT/US2022/051166 priority Critical patent/WO2024118050A1/fr
Publication of WO2024118050A1 publication Critical patent/WO2024118050A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations

Definitions

  • the technology generally relates to systems and methods for identifying a candidate geographic region for a business based on a value of one or more metrics, such as a “carpoolability” metrics.
  • the carpoolability metrics for a given geographic region may be determined based on carpools originating in, terminating in, or traveling through the geographic region.
  • the carpools may be any form of shared commuting, such as carpools, vanpools, buses, trains, etc.
  • Information related to the existing carpools may be used as one or more submetrics when determining the carpoolability metrics for a given geographic region. For example, the total number of existing carpools, the number of stops the carpools make, the number of seats available in the carpools, etc.
  • Another submetric used to determine the carpoolability metric of the geographic region is the total number of miles of specialty lanes, such as carpool lanes, high occupancy vehicle (HOV) lanes, bus lanes, etc. in the geographic region.
  • One or more values of the carpoolability metrics of geographic regions may be compared to determine which geographic region reduces the consumption of resources for frequenters of the business. The geographic region that has a greater reduction in resources consumed (an improved value of the metric(s)) may be output as the candidate geographic region for the business.
  • One aspect of the technology is directed to a method of identifying a candidate geographic region for a business, comprising identifying, by one or more processors, a first candidate geographic region for a potential physical location for the business and computing, by the one or more processors, a first metric for the first candidate geographic region.
  • the computing may comprise identifying, by the one or more processors, one or more carpools for frequenters of the business, the one or more carpools including existing carpools originating in, terminating in, or traveling through the first candidate geographic region.
  • the method may further comprise identifying, by the one or more processors, a second candidate geographic region for the potential physical location for the business and computing, by the one or more processors, a second metric for the second candidate geographic region.
  • the computing may comprise identifying, by the one or more processors, one or more carpools for the frequenters, the one or more carpools including existing carpools originating in, terminating in, or traveling through the second candidate geographic region.
  • the method may further comprise comparing, by the one or more processors, the first metric with the second metric, determining, by the one or more processors based on the comparison, which of the first and second metrics has an improved value corresponding to reduced consumption of resources for the frequenters, and providing for output, by the one or more processors, an indication of the first or second candidate geographic region corresponding to the respective first or second metric having the improved value.
  • the one of the first or second candidate geographic regions may reduce consumption of resources for a greater number of the frequenters as compared to the other of the first or second candidate geographic region.
  • Reducing the consumption of resources may comprise reducing a number of vehicles traveling to the business.
  • Reducing the number of vehicles traveling to the business may correspond to at least one of a decrease in a carbon footprint, a decrease in fossil fuel consumption, or a decrease in electricity usage.
  • Reducing the consumption of resources may comprise improving a value of a travel metric for at least a subset of the frequenters.
  • the travel metric may comprise at least one of a mileage, an amount of driving time, a carbon footprint, a driving expense, or an average travel speed.
  • the method may further comprise determining, by the one or more processors based on the existing carpools originating in, terminating in, or traveling through the first or second candidate geographic region, seat availability, wherein the seat availability indicates a number of frequenters that can be added to the existing carpools.
  • Computing the first or second metric may be further based on the determined seat availability.
  • Another aspect of the technology is directed to a system for identifying a candidate geographic region for a business, the system comprising one or more processors.
  • the one or more processors may be configured to identify a first candidate geographic region for a potential physical location for the business and compute a first metric for the first candidate geographic region.
  • the computing may comprise identifying one or more carpools for frequenters of the business, the one or more carpools including existing carpools originating in, terminating in, or traveling through the first candidate geographic region.
  • the one or more processors may be further configured to identify a second candidate geographic region for the potential physical location for the business and compute a second metric for the second candidate geographic region.
  • the computing may comprise identifying one or more carpools for the frequenters, the one or more carpools including existing carpools originating in, terminating in, or traveling through the second candidate geographic region.
  • the one or more processors may be further configured to compare the first metric with the second metric, determine, based on the comparison, which of the first and second metrics has an improved value corresponding to reduced consumption of resources for the frequenters, and provide for output an indication of the first or second candidate geographic region corresponding to the respective first or second metric having the improved value.
  • Yet another aspect of the technology is directed to a computer-readable medium storing instructions, which when executed by one or more processors, cause the one or more processors to identify a first candidate geographic region for a potential physical location for the business and compute a first metric for the first candidate geographic region.
  • the computing may comprise identifying one or more carpools for frequenters of the business, the one or more carpools including existing carpools originating in, terminating in, or traveling through the first candidate geographic region.
  • the one or more processors may be further configured to identify a second candidate geographic region for the potential physical location for the business and compute a metric for the second candidate geographic region.
  • the computing may comprise identifying one or more carpools for the frequenters, the one or more carpools including existing carpools originating in, terminating in, or traveling through the second candidate geographic region.
  • the one or more processors may be further configured to compare the first metric with the second metric, determine, based on the comparison, which of the first and second metrics has an improved value corresponding to reduced consumption of resources for the frequenters, and provide for output an indication of the first or second candidate geographic region corresponding to the respective first or second metric having the improved value.
  • Figure 1 is a pictorial diagram of example carpoolability metrics in accordance with aspects of the disclosure.
  • Figure 2 is a pictorial diagram of example possible carpools in a geographic region in accordance with aspects of the disclosure.
  • Figure 3 is a pictorial diagram of example specialty lanes in a geographic region in accordance with aspects of the disclosure.
  • Figure 4 is a pictorial diagram of an example carpoolability metric for a geographic region in accordance with aspects of the disclosure.
  • Figure 5 is a pictorial diagram of example travel metrics for possible carpools in accordance with aspects of the disclosure.
  • Figure 6A is a block diagram of an example system in accordance with aspects of the disclosure.
  • Figure 6B is a pictorial diagram of the example system of Figure 6A.
  • Figure 7 is a flow diagram for an example method of determining a candidate geographic region based on a comparison of carpoolability metrics for geographic regions in accordance with aspects of the disclosure.
  • the technology generally relates to identifying a candidate geographic region for a business based on a comparison of metrics for different geographic regions.
  • the metrics may be the above-described “carpoolability” metrics.
  • “Carpoolability” metrics may also be termed “shared travel” metrics, or indeed any other term describing a metric relating to shared travel.
  • the carpoolability metric for the candidate region may be determined based on possible carpools that originate, terminate, or travel through the region.
  • possible carpools may include carpools that have one or more stops for picking up and/or dropping off people in the region.
  • Carpools may include, for example, two or more people sharing a mode of transportation, such as a car, van, bus, train, etc.
  • the people may include, for example, frequenters of the business. Frequenters may be employees, visitors, customers, clients, etc. that regularly travel to the location of the business.
  • One or more submetrics may be used to determine a value of the carpoolability metric for the region.
  • the submetrics may include, for example, the number of carpools in the region, the number of stops made by each carpool, seat availability in the carpools, travel metrics of the carpools, presence of infrastructure in the region that facilitates the creation of additional carpools, etc.
  • the carpoolability metric for candidate geographic regions may be used to identify a geographic region that can accommodate the current and/or prospective frequenters of the business. For example, carpoolability metrics for different geographic regions may be compared to determine which candidate geographic region provides a reduced consumption of resources for the frequenters.
  • the candidate geographic region with the better value of the carpoolability metric and, therefore, a greater reduction of resources consumed by the frequenters may be suggested to the business as a location for establishing, relocating, or opening another location.
  • the positioning of the business in that location would provide an objective reduction in resources consumed by frequenters of that type of business. Since it is known that, objectively, travel to that type of business in one location consumes more resources on average than travel to that same type of business in the suggested location, it can be said that the suggested location provides an objective average reduction of consumed resources to frequenters of that type of business.
  • the value of the carpoolability metric is determined for a predetermined group of frequenters.
  • the predetermined group of frequenters may be current frequenters of the business.
  • the predetermined group of frequenters may be prospective frequenters of the business.
  • the predetermined group of frequenters may be a mix of current and prospective frequenters of the business. The comparison of the carpoolability metric for the geographic regions may, therefore, be made based on the predetermined group of frequenters.
  • the predetermined group of frequenters to the business in a first geographic region has a carpoolability metric of 87.75 while the carpoolability metrics for the same predetermined group of frequenters to the business in the second geographic region has a carpoolability metric of 84.15, establishing the business in the first geographic region would reduce the consumption of resources for the predetermine group of frequenters.
  • the resources consumed by the frequenters may be reduced as compared to each of the frequenters driving separately to the business. For example, by using carpools, fewer cars, vans, motorcycles, etc. may be traveling on the roads, which may lead to a reduction of fuel and carbon emissions. In some examples, fewer cars, vans, motorcycles, etc. may lead to a reduction in electricity usage. According to some examples, the reduction in resources consumed by the frequenters may correspond to an improved value of a travel metric for at least a subset of the frequenters.
  • the travel metrics may include, for example, distance traveled, transit time, travel cost, etc.
  • the system beneficially determines improved geographic regions for businesses that objectively provide an average reduction in vehicles traveling on the roads, fuel and/or electricity usage for the vehicles, carbon emissions, etc. According to some examples, identifying the candidate geographic region that reduces the consumption of resources for the frequenters may facilitate transportation for the frequenters to the business while minimizing the number of vehicles on the road.
  • the system beneficially determines improved geographic regions for businesses that objectively provide improved values of travel metrics for at least a subset of the frequenters.
  • Travel metrics may be a measurement, or an indication of a value, of a characteristic of what is required to travel from a user’ s location to a destination.
  • travel metrics may include distance traveled, transit time, carbon emissions, travel costs, average travel speed, average miles per gallon, etc.
  • an improved value of the travel metric may be a reduction in the financial cost for the frequenter to travel to the business.
  • an improved value of the travel metric would be a reduction in the distance traveled.
  • an improved value of the travel metric may be a reduction in the average travel time.
  • an improvement value of the travel metric may be a greater average speed traveled. If the travel metric is average miles per gallon, the value of the travel metric may be improved if the average miles per gallon increases.
  • the systems and methods discussed herein are directed to identifying a candidate geographic region for a business
  • the systems and methods may be used to identify a candidate geographic region for a residential location.
  • the carpoolability metrics may be used to identify a geographic region to which a user should relocate based on the carpoolability metric of the geographic region. Additionally or alternatively, the carpoolability metrics may be used to identify a geographic region to which a user should purchase or rent a first property or additional residential property based on the carpoolability metric of the geographic region.
  • the user may be a person, user, frequenter, etc. that may use one or more of the shared commuting options in the geographic region.
  • Figure 1 illustrates example carpoolability metrics for a first and second candidate geographic region.
  • the carpoolability metrics 104, 114 may be determined based on possible carpools that originate in, terminate in, pick up in, drop off in, or travel through the geographic region.
  • the carpools may be, for example, shared transportation such as carpools and/or vanpools 106a-g, bus routes 110a, 110b, trains 108, etc. having a substantially consistent scheduled pick up and/or drop off times.
  • Determining the schedule of pickup and/or drop off times of the carpools may be based on a user location information.
  • the user may be anyone who is traveling in or around the geographic region. In some examples, the user may be anyone who is traveling within a threshold radius of the geographic location.
  • the threshold radius may be, for example, ten miles.
  • the threshold radius may be, in some examples, more or less than ten miles, such as five miles, twenty-five miles, etc.
  • the example of the threshold radius being five miles is just one example and is not intended to be limiting.
  • the location information may be, for example, the user’s travel history.
  • the user’s travel history may be based on location information provided by a personal device, a navigational system, a mapping application, etc.
  • Location information may be, for example, data collected by a device having a location sensor, such as a global positioning system (GPS), which illustrates the locations a user has traveled to.
  • location information may include pick up or drop off location identified in e-mails, calendar appointments, etc. that the user has allowed the system to access.
  • Location information may be used after the user provides authorization for the system to access or receive location information.
  • the user may provide authorization to an application or the system to access one or more databases in the memory of the user’s device, vehicle, remote server, etc.
  • the schedule of the carpools may be determined based on carpools registered in an application that may also be used to identify a possible carpool for the user.
  • the schedule for buses and trains may be determined, for example, based on publicly accessible information. Additionally or alternatively, the schedule of carpools, buses, and trains may be stored in a database accessible by the system.
  • FIG. 1 there may be a plurality of carpools originating in, terminating in, or traveling through the first geographic region 102 and the second geographic region 112.
  • Carpool routes 106a-g may be carpools in which a vehicle of one of the users in the carpool is used to travel between the originating location “O” of the route to the terminating location “T.”
  • Train route 108 may be a carpool in which a train is used to travel between the originating location “O” and the terminating location “T.”
  • Bus routes HOa-b may carpools in which a bus is used to travel between the originating location “O” and the terminating location “T.”
  • the originating location “O” and terminating location “T” of train route 108 and bus routes 1 lOa-b may be interchangeable due to the round-trip nature of train and bus routes.
  • the terminating location “T” for one direction of the train route 108 and bus routes HOa-b may be the originating location “O” for the return train route 108 and bus routes HOa-b.
  • Values of the carpoolability metrics 104, 114 of the respective first and second geographic regions 102, 112 may be determined based on the number of possible carpools originating in, terminating in, or traveling through the respective regions.
  • the first geographic region 102 has five carpool routes 106a-e, one train route 108, and one bus route 110a for a total of seven possible carpools.
  • the second geographic region 112 has four carpool routes 106d-g, one train route 108, and one bus route 110b for a total of six possible carpools.
  • the value of the carpoolability metric may be proportional to the number of possible carpools such that a greater number of possible carpools in the geographic region corresponds to a greater or improved value of the carpoolability metric for the geographic region.
  • the value of the carpoolability metric for the region may directly correspond to the number of possible carpools such that the value of the carpoolability metric substantially equals the number of possible carpools.
  • the carpoolability metric for the geographic region may be determined based on submetrics in addition to or besides the number of possible carpools.
  • the carpoolability metric may be determined based on the number of stops in the geographic region, the number of seats available in the possible carpools, the total mileage of specialty lanes in the geographic region, etc.
  • the number of stops in the geographic region may correspond to pick up and/or drop off locations that are already part of the carpool route 106a-g, train route 108, and bus routes 1 lOa-b.
  • stops along the train route 108 may be at train stations “TS” and stops along the bus routes 1 lOa-b may be at bus stops “BS.”
  • the number of stops in the geographic region may be aggregated based on the type of stop, such as whether the stop is part of a carpool, a bus route, or a train route.
  • the number of seats available in the possible carpools may be determined based on registered carpools, average ticket sales for buses and trains, information reported by users of the carpools, etc.
  • the number of seats available may indicate the number of additional users that can be added to the possible carpools without increasing the consumption of resources.
  • the total mileage of specialty lanes may be determined based on mapping information stored in a database accessible by the system.
  • Specialty lanes may include, for example, carpool lanes, HOV lanes, bus lanes, etc.
  • the total mileage of specialty lanes may provide an indication of the infrastructure that encourages or incentivizes users to use carpools.
  • the carpoolability metric for the geographic region may be determined using one or more submetrics, such as number of possible carpools, number of stops, number of seats available, miles of specialty lanes, transportation costs, travel metrics, etc.
  • the submetrics may be weighted.
  • the weight applied to each submetric may be the same or may be different.
  • the number of bus stops and/or train stops may be weighted greater than the number of stops along a carpool route as the buses and trains may have a greater number of seats available.
  • the total number of possible carpools may be weighted greater than the miles of specialty lanes as established carpools may provide a better indication of the availability of shared transportation than the fact that there is infrastructure in place to encourage shared transportation.
  • Figure 2 illustrates example possible carpools in a geographic region.
  • Possible carpools may include carpools having routes originating in, terminating in, or traveling through geographic region 202.
  • the carpools may be any form of shared transportation, such as carpools, vanpools, buses, trains, etc. that have a substantially consistent schedule for departing an originating location “O” and arriving at a terminating location “T.”
  • the schedule may deviate due to, for example, traffic, accidents, users running late, mechanical issues, etc.
  • the originating location “O”, terminating location “T”, and stops “S” may correspond to a user’s residential location, a commuter parking lot, a designated location along the carpool route, a business, a point of interest, a train station, a bus stop, etc.
  • the total number of carpools originating in, terminating in, or traveling through a geographic region 202 may be used as a submetric to determine the carpoolability metric for the geographic region 202.
  • the possible carpools in the geographic region 202 include carpool routes 206a-e, train route 208, and bus route 210.
  • the total number of possible carpools in the geographic region 202 is seven, including five carpool routes 206a-e, one bus route 210, and one train route 208.
  • carpool routes 206a-e have at least one of an originating location “O”, terminating location “T”, or one or more stops within the geographic region 202.
  • carpool route 206a has an originating location “O” outside the geographic region 202 but includes two stops “S” within geographic region 202 before reaching terminating location “T” outside of the geographic region 202.
  • carpool route 206e has an originating location “O” within geographic region 202, includes two stops “SI” and “S2” outside of geographic region 202, and has a terminating location “T” outside of geographic region 202.
  • the originating and terminating location for train route 208 may correspond to train stations “TS” along train route 208.
  • train station “TS1” may correspond to the originating location of train route 208 while train station “TS3” may correspond to the termination location of train route 208.
  • the originating and terminating location for bus route 210 may correspond to bus stops “BS” along bus route 210.
  • bus stop “BS1” may correspond to the originating location of bus route 210 while bus stop “BS5” may correspond to the terminating location of bus route 210.
  • the number of stops of a possible carpool may be used as a submetric to determine the carpoolability metric for the geographic region.
  • a stop “S” for carpool routes 206a-e, bus stops “BS”, and train stations “TS” may be a location along the carpool route in which a user is picked up or dropped off.
  • the originating location “O” and/or terminating location “T” may be included as a stop.
  • the total number of stops for the possible carpools may be aggregated.
  • the number of stops may, in some examples, correspond to the number of stops made between the originating location “O” and the terminating location “T”, not including the originating location “O”, or terminating location “T” as a stop.
  • carpool route 206e has two stops, stops “SI” and “S2”, between an originating location “O” and terminating location “T”.
  • the total number of stops may include one or both of the originating location “O” and terminating location “T” of the possible carpools.
  • carpool route 206e may have three or four stops.
  • the system may determine whether to include the originating location “O” and/or terminating location “T” as a stop. For example, the system may include the originating location “O” and/or terminating location “T” as a stop if an additional user is picked up or dropped off at that location. For example, the originating location “O” may be included in the total number of stops in examples where users of the carpool travel to the originating location “O” to begin the carpool.
  • the total number of stops may be aggregated for the geographic region 202.
  • the total number of stops may be aggregated regardless of the type of shared transportation, such as carpool, vanpool, bus, train, etc.
  • the total number of stops for geographic region 202, not including the originating location “O” or terminating location “T” of the possible carpools is twelve stops.
  • the total number of stops may be aggregated based on the type of shared transportation.
  • the total number of stops for carpool routes 206a-3 is eight
  • the total number of stops for bus route 210 is three
  • the total number of stops for train route 208 is one.
  • the total number of stops includes at least one of the originating location “O” or the terminating location “T”
  • the total number of stops is nineteen.
  • Each possible carpool may include a predetermined number of seats corresponding to the number of seats in the vehicle used for the carpool.
  • a sedan being used for a carpool route may have five seats whereas a van or SUV used for a carpool route may have seven or more seats.
  • a bus being used for a bus route may have, on average, between thirty-six to sixty seats and a train being used for a train route may have over two hundred seats.
  • the number of seats available on a bus or train may depend on the type of bus, size of the bus, number of train cars being used, type of train cars being used, etc. Therefore, the average number of seats on a bus is just one example and is not intended to be limiting as each bus may have more or less seats.
  • the number of seats available on the train route may be more or less than two hundred as two hundred seats is just one example and is not intended to be limiting.
  • the number of seats in a carpool may be stored when the carpool is registered, provided by users of the carpool, and/or stored in a database accessible by the system.
  • the system may determine the number of available seats in each possible carpool.
  • the number of available seats in the possible carpools may be a submetric used to determine the carpoolability metric for the geographic region 202. Available seats may be seats within the possible carpool that would allow for another user to join the carpool. For example, if a vehicle of a carpool route has five seats total and there are currently only three users, including the driver, the carpool route has two available seats.
  • the system may determine an average number of tickets sold for each route. The system may compare the average number of tickets sold to the predetermined number of seats on the train or bus route. The difference between the tickets sold and the predetermined number of seats may be the number of available seats on that train or bus route.
  • Figure 3 illustrates an example map of specialty lanes in a geographic region.
  • the specialty lanes 330a-d may be, for example, carpool lanes, HOV lanes, bus lanes, etc.
  • the specialty lanes may be used by vehicles, such as cars, vans, buses, trolleys, etc. that have a threshold number of users.
  • carpool lanes may require at least two users in the vehicle in order to be eligible to use the specialty lane.
  • specialty lanes 330a-c may be carpool lanes and specialty lane 330d may be a bus lane.
  • the total mileage of specialty lane 330a-d may be a submetric used to determine the carpoolability metric for a geographic region 302.
  • the total mileage of specialty lanes 330a-d may be aggregated regardless of the type of specialty lane. For example, if specialty lane 330a is 80 miles, specialty lane 330b is 100 miles, specialty lane 330c is 125 miles, and specialty lane 330d is 137 miles, the total miles of specialty lanes is 442 miles. In some examples, the total mileage of specialty lanes may be aggregate based on types of specialty lanes. In such an example, there may be 305 miles of carpool lanes and 137 miles of bus lanes.
  • a geographic region may use specialty lanes to encourage the use of carpools.
  • a greater total mileage of specialty lanes may result in a decrease in resource consumption.
  • the more mileage of specialty lanes within a geographic region may correspond to a greater number of possible carpools and/or more users using carpools. The more users that use carpools objectively decreases resource consumption by reducing the number of vehicles on the road thereby reducing carbon emissions.
  • Figure 4 is an example carpoolability metric of a geographic region.
  • the geographic region may be, for example, predefined based on neighborhoods, towns, cities, counties, states, etc. According to some examples, the geographic region may be predefined based on square feet, meters, miles, etc. According to other examples, the geographic region may be defined by arbitrary designations on a map. Additionally or alternatively, the geographic region may be defined based on a current location of a business or user.
  • the value of the carpoolability metric of geographic region 402 may be compared to the values of carpoolability metrics of other geographic regions to determine which geographic region has an improved value, and thus corresponds to reduced consumption of resources for users. For example, a high value of the carpoolability metric may indicate a greater reduction in the consumption of resources for users as compared to a low value of the carpoolability metric. However, this may be reversed and a low value of the carpoolability metric could indicate the relatively greater reduction in the consumption of resources.
  • businesses may use carpoolability metrics to identify candidate geographic regions to establish the business, relocate the business, or establish an additional location for the business.
  • the carpoolability metrics may correspond to a reduction of resources consumed by frequenters of the business.
  • the frequenters may be, for example, employees or regular visitors of the business.
  • the business may use the carpoolability metrics to determine how easy it may be for the employees of the business to travel to the business.
  • a greater carpoolability metric for a given geographic region as compared to another may indicate that the given geographic region has a plurality of carpool options and infrastructure that can be used by the employees to travel to the business. This may encourage users to become employees of the business.
  • the carpoolability metric of the given geographic region may encourage employees to relocate to the business’ new location.
  • a greater carpoolability metric may correspond to a reduction of resources consumed by the employees of the business.
  • a greater carpoolability metric for the geographic region may result in a greater number of employees using shared transportation to reach the business, resulting in fewer cars on the road, less gas or electricity being consumed, etc.
  • the business may, therefore, use the carpoolability metric to determine how easy it would be for employees to reach the business.
  • the business may use the carpoolability metrics to determine how easy it may be for visitors of the business to reach the business. For example, a greater carpoolability metric for a given region as compared to another may indicate that a visitor of the business may be able to travel to the business using shared transportation instead of the visitor having to drive themselves.
  • the amount of shared transportation may encourage visitors to frequent the business, as it may reduce the consumption of resources of the visitor and/or improve one or more travel metrics for the visitor.
  • the use of shared transportation may decrease the travel costs for the visitor, increase travel speed, decrease their carbon emissions, etc.
  • the business may use the carpoolability metrics to determine a geographic region to establish, relocate, or establish an additional location of the business based on how its employees and visitors will reach the location. For example, the business may compare two or more geographic regions to receive an indication of the geographic region that reduces the consumption of resources for the employees and visitors, improves a value of at least on travel metric for the employees and visitors, or improves a value of one of the submetrics used to determine the carpoolability metrics for the geographic region.
  • the value of the carpoolability metric may be based on the value of one or more submetrics.
  • the value of each submetric may indicate a level of carpoolability for the geographic region 402.
  • the submetrics may include the number of possible carpools, the number of stops, the number of available seats, and the total mileage of specialty lanes, travel metrics, etc. Travel metrics may include, for example, miles traveled, driving time, carbon footprint, driving expense, etc.
  • the carpoolability metric may be output as a pop-up 440, overlay, etc.
  • the pop-up 440 nay be inputs that allow businesses, users, entities, etc. to adjust how the carpoolability metric is determined.
  • each submetric that is used to determine the carpoolability metric may be assigned a weight 442a-d.
  • the weight may correspond to a degree of reliability of the submetric, wherein the degree of reliability may be higher for publicly accessible information such as the total mileage of specialty lanes or the total number of possible carpools.
  • the number of possible carpools may have a larger weight assigned than the weight assigned to number of seats available.
  • One example for determining the carpoolability metric includes the following equation:
  • W1 corresponds to the weight 442a assigned to the number of possible carpools
  • W2 corresponds to the weight 442b assigned to the number of stops
  • W3 corresponds to the weight 442c assigned to the number of seats available
  • W4 corresponds to the weight 442d assigned to the total mileage of specialty lanes. While four submetrics are shown in the equation, any number of submetrics may be included such that the equation includes more or less than four submetrics. Additionally, or alternatively, while four weights are shown, the weights applied to any of the submetrics may be the same or different. Further, while only four submetrics are shown, additional submetrics, such as the day of the week, submetrics pertaining to partially traveled routes, etc. may be included when determining the failure score.
  • the carpoolability metric for geographic region 402 may be determined.
  • the number of possible carpools may be 7, the number of stops may be 12, the number of seats available may be 351, and the total mileage of specialty lanes may be 442 miles.
  • the weight W1 for the number of possible carpools may be 1
  • the weight W2 for the number of stops may be 0.5
  • the weight W3 for the number of available seats may be 0.15
  • the weight 442a-d assigned to each submetric may change based on the preferences of the business. For example, a business may place a greater emphasis and, therefore, may assign a larger weight to number of seats available as compared to the number of stops. As shown, the business, user, entity etc. may adjust the weight 442a-d for each submetric by providing a numerical input for weights 442a-d.
  • the pop-up 440 may include a drop-down menu, sliding scale, radio button, etc. as a way to select or set the weight 442a-d for each submetric.
  • the value of the carpoolability metric for geographic region 402 may be compared to carpoolability metrics determined for other geographic regions.
  • the value of the carpoolability metric for respective geographic regions may be compared to determine which geographic region corresponds to a greater reduction in the consumption of resources for users.
  • the system may provide for output an indication of the geographic region that has a greater reduction in the resources consumed by the users.
  • the users may be frequenters of the business.
  • the value of the carpoolability metric may be determined based on a predetermined group of frequenters.
  • the value of the carpoolability metrics may be determine for a first geographic region and a second geographic region based on the same group of frequenters traveling to the business.
  • the value of the carpoolability metric for the first and geographic regions may be compared to determine an improved value of the carpoolability metric for the group of frequenters.
  • the value of the carpoolability metrics for the predetermined group of frequenters to the business in the first geographic region may be 87.75 while the value of the carpoolability metrics or the predetermined group of frequenters to the business in the second geographic region may be 84.15.
  • the first geographic region may have an improved value for the predetermined group of frequenters as compared to the second geographic region.
  • the indicated geographic region may reduce the consumption of resources for a greater number of the frequenters as compared to the other geographic regions.
  • the indicated geographic region may have a higher value of a carpoolability metric than the other geographic regions due to the number of possible carpools, number of stops, number of seats available, miles of specialty lanes, etc.
  • the higher value of the carpoolability metric may correspond to the carpool infrastructure being able to add a greater number of frequenters to the possible carpools than the other geographic regions.
  • Being able to add frequenters to the possible carpools may reduce the consumption of resources by having fewer vehicles on the roads traveling to the business. Fewer vehicles on the road may reduce the consumption of fossil fuels or electric used to power the vehicles.
  • Reducing resources consumed by frequenters of the business may account for an increase in the number of frequenters traveling to the business. For example, if the business establishes itself, relocates, or opens a new location in the geographic region, additional frequenters may utilize the possible carpools to reach the business in the geographic region.
  • the additional frequenters may be frequenters of the business that relocate to a location relative to the geographic region.
  • the additional users may be frequenters of the business that changed employment or becomes a patron of the business.
  • the additional frequenters may utilize the possible carpools to travel to the business.
  • the reduction in resources may correspond to fewer vehicles being used to reach the business due to the frequenters participating in the possible carpools.
  • carbon emissions may be reduced.
  • additional frequenters may require additional carpools. Additional carpools may result in reduced consumption of resources by the frequenters as compared to the additional frequenters driving separately.
  • reducing the consumption of resources may include improving a value of a travel metric for at least a subset of the frequenters.
  • the travel metrics may include, for example, distance traveled, travel time, driving or travel expense, carbon footprint, etc.
  • the driving expense travel metric may improve as the driving expenses will be shared among all the frequenters in the carpool. Sharing driving expenses among a greater number of frequenters will reduce the driving expense for each frequenter in the carpool.
  • the carbon footprint for the frequenters will be improved. For example, by utilizing the possible carpools or establishing a new carpool route, fewer vehicles will be used to travel to the business which will reduce the carbon footprint for the frequenters.
  • Figure 5 illustrates example travel metrics for the possible carpools originating in, terminating in, or traveling through a geographic region 502.
  • travel metrics 550 may be determined for carpool route 506b
  • travel metrics 552 may be determined for bus route 510
  • travel metrics 554 may be determined for train route 508
  • travel metrics 556 may be determined for carpool route 506e.
  • the travel metrics 550-556 may indicate the average time of travel, average distance, average travel expense, average carbon footprint for the carpool.
  • the travel metrics may be determined on a per user, or frequenter, basis.
  • the travel metrics 550-556 may include an indication of how the value of each metric would change if another user were added to the carpool.
  • the current average time of travel of the carpool route 506b may be 35 minutes but if a user is added to carpool route 506b the average time of travel may be estimated as 40 minutes.
  • the current average travel expense for carpool route 506b may be $1.50 per day per user but if a user is added to carpool route 506 the average travel expense may be $1.15 per day per user.
  • the current average carbon footprint for carpool route 506b may be 22.22 kg CO2 per day per user but if a user is added to carpool route 506b the average carbon footprint may be 17.78 kg CO2 per day per user.
  • the average carbon footprint per user may decrease as the new user is joining an existing carpool and, therefore, is not using a separate vehicle to travel. By reducing the number of vehicles on the road, the carbon footprint of the additional user and, therefore, the users of carpool route 506b decreases.
  • bus route 510 the current average time of travel and average distance traveled along bus route 510 may not change based on the locations of the bus stops “BS.” However, the average carbon footprint may decrease as additional users take the bus. The carbon footprint per user of bus route 510 may decrease due to the vehicles of the additional users no longer being used to travel.
  • FIG. 6A illustrates an example system 600 in which the features described above may be implemented. It should not be considered limiting the scope of the disclosure or usefulness of the features described herein.
  • system 600 may include device(s) 602, vehicle(s) 612, server computing device 630, storage system 640, and network 620.
  • Each of devices 602 may include one or more processors 632, memory 642, data 662 and instructions 652. Each of devices 602 may also include an output 662, user input 682, and location sensor 692.
  • the devices 602 may be any device that includes a location sensor 692, such as a smart phone, tablet, laptop, smart watch, AR/VR headset, smart helmet, etc., as shown in Figure 6B.
  • Memory 642 of devices 602 may store information that is accessible by processor 632. Memory 642 may also include data that can be retrieved, manipulated or stored by the processor 632.
  • the memory 642 may be of any non-transitory type capable of storing information accessible by the processor 632, including a non-transitory computer-readable medium, or other medium that stores data that may be read with the aid of an electronic device, such as a hard-drive, memory card, read-only memory (“ROM”), random access memory (“RAM”), optical disks, as well as other write-capable and read-only memories.
  • Memory 642 may store information that is accessible by the processors 632, including instructions 652 that may be executed by processors 632, and data 662.
  • Data 662 may be retrieved, stored or modified by processors 632 in accordance with instructions 652.
  • the data 662 may be stored in computer registers, in a relational database as a table having a plurality of different fields and records, XML documents, or flat files.
  • the data 662 may also be formatted in a computer-readable format such as, but not limited to, binary values, ASCII or Unicode.
  • the data 662 may comprise information sufficient to identify the relevant information, such as numbers, descriptive text, proprietary codes, pointers, references to data stored in other memories (including other network locations) or information that is used by a function to calculate the relevant data.
  • the instructions 652 can be any set of instructions to be executed directly, such as machine code, or indirectly, such as scripts, by the processor 632.
  • the terms “instructions,” “application,” “steps,” and “programs” can be used interchangeably herein.
  • the instructions can be stored in object code format for direct processing by the processor, or in any other computing device language including scripts or collections of independent source code modules that are interpreted on demand or compiled in advance. Functions, methods and routines of the instructions are explained in more detail below.
  • the one or more processors 632 may include any conventional processors, such as a commercially available CPU or microprocessor. Alternatively, the processor can be a dedicated component such as an ASIC or other hardware-based processor. Although not necessary, computing devices 602 may include specialized hardware components to perform specific computing functions faster or more efficiently.
  • Figure 6A functionally illustrates the processor, memory, and other elements of devices 602 as being within the same respective blocks, it will be understood by those of ordinary skill in the art that the processor or memory may actually include multiple processors or memories that may or may not be stored within the same physical housing. Similarly, the memory may be a hard drive or other storage media located in a housing different from that of the devices 602. Accordingly, references to a processor or device will be understood to include references to a collection of processors or devices or memories that may or may not operate in parallel.
  • Output 672 may be a display, such as a monitor having a screen, a touchscreen, a projector, or a television.
  • the display processors of the one or more computing devices 602 may electronically display information to a user via a graphical user interface ("GUI") or other types of user interfaces.
  • GUI graphical user interface
  • display processors may electronically display a map interface identifying relevant destinations, routine trips, or one or more travel metrics based on a specified starting location.
  • the user input 682 may be a mouse, keyboard, touchscreen, microphone, or any other type of input.
  • the user input may receive the user’s authorization to use the location sensor 692 to obtain location information for the travel metrics. For example, the user can select particular applications for which to allow location services, particular times during which location services can be enabled, or other permissions or limitations for the location services.
  • the location sensor 692 may be, for example, a global positioning system (“GPS”) sensor, wireless communications interface, etc.
  • GPS global positioning system
  • the location sensor 692 when enabled by the user, may provide a rough indication as to the location of the device.
  • the location sensors when authorized by the user, may provide location information indicating an originating location, terminating location, stops, and routes for possible carpools.
  • the location information may be stored locally on the device 602 or navigational system, such as part of an application or integrated into vehicle 612.
  • the location information may be shared to a remote location, such as a remote server 630 or storage system 640.
  • the location information may be used to identify originating locations, terminating locations, stops, and routes of possible carpools.
  • the devices 602 can be at various nodes of a network 620 and capable of directly and indirectly communicating with other nodes of network 620. Although three (3) computing devices are depicted in Figure 6A, it should be appreciated that a typical system can include one or more computing devices, with each computing device being at a different node of network 620.
  • the network 620 and intervening nodes described herein can be interconnected using various protocols and systems, such that the network can be part of the Internet, World Wide Web, specific intranets, wide area networks, or local networks.
  • the network 620 can utilize standard communications protocols, such as WiFi, Bluetooth, 4G, 5G, etc., that are proprietary to one or more companies.
  • system 600 may include one or more server computing devices 630 having a plurality of computing devices, e.g., a load balanced server farm, that exchange information with different nodes of a network for the purpose of receiving, processing and transmitting the data to and from other computing devices.
  • server computing devices 630 may be a web server that is capable of communicating with the one or more client computing devices 602 via the network 620.
  • server computing device 630 may use network 620 to transmit and present information to a user of one of the other computing devices 602 or a passenger of a vehicle.
  • vehicles 612 may be considered client computing devices.
  • Server computing device 630 may include one or more processors, memory, instructions, data, location sensors, etc. These components operate in the same or similar fashion as those described above with respect to computing devices 602.
  • each device 602 may be a personal computing device intended for use by a respective user 622, and have all of the components normally used in connection with a personal computing device including one or more processors (e.g., a central processing unit (CPU)), memory (e.g., RAM and internal hard drives) storing data and instructions, an output, such as a display (e.g., a monitor having a screen, a touch-screen, a projector, a television, or other device such as a smart watch display that is operable to display information), and user input devices (e.g., a mouse, keyboard, touchscreen or microphone).
  • the devices may also include a camera for recording video streams, speakers, a network interface device, and all of the components used for connecting these elements to one another.
  • Devices 602 may be capable of wirelessly exchanging or obtaining data over the network 620.
  • the client computing devices may each comprise a full-sized personal computing device, they may alternatively comprise mobile computing devices capable of wirelessly exchanging data with a server over a network such as the Internet.
  • devices 602 may be mobile phones or devices such as a wireless-enabled PDA, smartphones, a tablet PC, a wearable computing device (e.g., a smartwatch, AR/VR headset, smart helmet, etc.), or a netbook that is capable of obtaining information via the Internet or other networks.
  • User 622 may operate a respective vehicle 612.
  • the vehicle 612 may include a location sensor.
  • vehicle 612 may include an integrated navigation system.
  • the navigation system may be integrated into a user’s 622 respective device 602.
  • the device 602 or vehicle 612 may execute a mapping application that provides maps or directions, identifies a user’s location, etc.
  • Any use of location information or travel history of a user 622 is authorized by the respective user.
  • the user 622 may provide authorization to an application for determining carpoolability metrics and/or travel metrics by setting certain permissions for the application.
  • the authorization may be for the application to access one or more databases or sub-databases in the memory of the device, vehicle, remote server, etc.
  • the user may select specific sub-databases to which the application is granted access. For instance, the user may grant access to the location history database but not the calendar archive database.
  • Vehicles 612 may include a computing device (not shown).
  • the computing device may include one or more components similar to devices 602, such as one or more processors, memory, data, instructions, a display, a user input, etc.
  • vehicles 612 may include a perception system for detecting and performing analysis on objects external to the vehicle such as other vehicles, obstacles in the roadway, traffic signals, signs, trees, etc. Additionally or alternatively, the perception system may determine whether the vehicle is in motion or parked.
  • the perception system may include lasers, sonar, radar, one or more cameras, or any other detection devices which record data which may be processed by a computing device (not shown) within vehicles 612.
  • the car may include a laser mounted on the roof or other convenient locations as well as other sensors such as cameras, radars, sonars, and additional lasers (not shown).
  • Storage system 640 may store various types of information. For instance, the storage system 640 may store data or information related to a user’s location information, such as the user’s travel history, carpool routes, including bus and train routes, etc. In some examples, storage system 640 may store data or information related to originating locations of carpools, terminating locations of carpools, stops of carpools, or carpool for retrieval in response to a request to determine carpoolability metrics.
  • Storage system 640 may store map data.
  • This map data may include, for instance, originating locations of carpools, terminating location of carpools, stops of carpools, routes of carpools, locations of specialty lanes, such as carpool/HOV lanes, etc.
  • Map data may also include locations, road names, road configurations, etc.
  • storage system 640 may store data or information related to a user’s 622 location information after receiving authorization from the user 622.
  • the authorization may be, for example, provided by setting permissions for the system to access location information and travel history.
  • a user may be provided with controls allowing the user to make an election as to both if and when systems, programs, or features described herein may enable collection of location information, and if the user is sent content or communications from a server.
  • certain data may be treated in one or more ways before it is stored or used, so that personally identifiable information is removed. The user may have control over what information is collected about the user, how that information is used, and what information is provided to the user.
  • the user’s 622 location information or travel history may be used to identify, or determine, a user’s 622 originating location, terminating location, stops, and route of a carpool.
  • Figures 6A and 6B illustrate a single user 622 and their respective device(s) 602 and vehicle 612, it should be understood that there may be multiple users and their respective devices and vehicles.
  • the location information and travel history of each user may be used to determine a respective user’ s travel history.
  • Each user’s location information and travel history may be aggregated and used to illustrate carpoolability metrics for a given area, such as a neighborhood, town, city, county, state, etc.
  • Each respective user provides authorization for an application to access their location information and travel history.
  • the user may set permissions for the application to indicate what location information and travel history the application may access.
  • the location information may be stored locally on the user device.
  • the location information from the user device(s) and/or navigational applications may be shared with and, therefore, stored by one or more servers.
  • the location information may be captured and stored by navigational applications.
  • the location information and travel history may only be shared with and stored by servers after a user authorizes the sharing of location information and travel history.
  • Figure ? illustrates an example method for identifying a candidate geographic region for a business. The following operations do not have to be performed in the precise order described below. Rather, various operations can be handled in a different order or simultaneously, and operations may be added or omitted.
  • a first candidate geographic region for a potential physical location for the business may be identified.
  • a first metric for the first candidate geographic region may be computed.
  • Computing the first metric may comprise identifying one or more carpools for frequenters of the business.
  • the one or more carpools may include existing carpools originating in, terminating in, or traveling through the first candidate geographic region.
  • the frequenters of the business may be, for example, employees or visitors of the business.
  • seat availability may be determined. Seat availability may correspond to the number of frequenters that can be added to existing carpools.
  • the one or more first metrics may be determined based on the seat availability in the first candidate geographic region.
  • a second candidate geographic region for the potential physical location for the business may be identified.
  • a second metric for the second candidate geographic region may be computed.
  • Computing the second metric may comprise identifying one or more carpools for frequenters of the business.
  • the one or more carpools may include existing carpools originating in, terminating in, or traveling through the second candidate geographic region.
  • the first metric may be compared with the second metric.
  • reducing the consumption of resources may include reducing a number of vehicles traveling to the business.
  • reducing the number of vehicles traveling to the business may correspond to a decrease in a carbon footprint, a decrease in fossil fuel consumption, or a decrease in electricity usage.
  • reducing the consumption of resources comprises improving a travel metric for at least a subset of the frequenters.
  • the travel metric may include, for example, mileage, driving time, carbon footprint, driving expenses, etc.
  • seat availability may be determined.
  • the one or more second metrics may be determined based on the seat availability in the second candidate geographic region.
  • an indication of the first or second candidate geographic region may be provided for output.
  • the indicated first or second candidate geographic region may reduce the consumption of resources for a greater number of frequenters as compared to the other of the first or second candidate geographic region.
  • the resources consumed by the frequenters may be reduced as compared to each of the frequenters driving separately. For example, by using carpools, fewer vehicles may be traveling on the roads, which may lead to a reduction of fuel and carbon emissions for vehicles with internal combustion engines or a reduction of electricity for electric vehicles. In some examples, the reduction in resources consumed by the frequenters may correspond to an improved value of one of the submetrics used to determine the carpoolability metrics and/or a travel metric.
  • the system beneficially determines a candidate geographic region for a business to establish, relocate, or open another location.
  • the candidate geographic region objectively provides an improved value of one of the submetrics used to determine the carpoolability metric and/or travel metric.
  • the candidate geographic region objectively provides a reduction in vehicles traveling on the roads, fuel and/or electricity usage for the vehicles, carbon emissions, etc.
  • Comparing the carpoolability metrics for geographic regions and providing an indication of the geographic region that has an improved value of one or more of the submetrics used to determine the carpoolability metrics and/or one or more travel metrics may ensure computational and energy efficiency.
  • a user searching through information provided by various entities and manually aggregating the data is cumbersome, computationally intensive, and time consuming, by providing an indication of the geographic region corresponding to a greater reduction of resources consumed by the frequenters, an improved value of one or more of the submetrics used to determine carpoolability metric, or an improved value of one or more travel metrics, this may increase the efficiency of the system.

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Abstract

La technologie concerne de manière générale des systèmes et des procédés d'identification d'une région géographique candidate pour une entreprise sur la base de mesures de capacité de covoiturage. Les mesures de capacité de covoiturage pour une région géographique donnée peuvent être déterminées sur la base de covoiturages au départ de la zone géographique, à l'arrivée de celle-ci ou à travers celle-ci. Les covoiturages peuvent prendre n'importe quelle forme de déplacement partagé. Le nombre total de covoiturages existants, le nombre d'arrêts des covoiturages, le nombre de sièges disponibles dans les covoiturages, le nombre total de kilomètres de voies réservées, etc., peuvent être utilisés comme mesures secondaires lors de la détermination de la mesure de la capacité de covoiturage de la région géographique. Les mesures de capacité de covoiturage de régions géographiques peuvent être comparées pour déterminer la région géographique qui réduit la consommation de ressources pour des habitués de l'entreprise. La région géographique qui présente une plus forte réduction des ressources consommées peut être considérée comme région géographique candidate pour l'entreprise.
PCT/US2022/051166 2022-11-29 2022-11-29 Identification de régions candidates sur la base d'une commutabilité partagée WO2024118050A1 (fr)

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Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130046586A1 (en) * 2011-08-16 2013-02-21 Walk Score Management LLC System and method for assessing quality of transit networks at specified locations
EP2808832A1 (fr) * 2013-05-29 2014-12-03 Google, Inc. Notation de transport public itératif

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130046586A1 (en) * 2011-08-16 2013-02-21 Walk Score Management LLC System and method for assessing quality of transit networks at specified locations
EP2808832A1 (fr) * 2013-05-29 2014-12-03 Google, Inc. Notation de transport public itératif

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