US20120239289A1 - Transportation Information Systems and Methods Associated With Generating Multiple User Routes - Google Patents
Transportation Information Systems and Methods Associated With Generating Multiple User Routes Download PDFInfo
- Publication number
- US20120239289A1 US20120239289A1 US13/228,246 US201113228246A US2012239289A1 US 20120239289 A1 US20120239289 A1 US 20120239289A1 US 201113228246 A US201113228246 A US 201113228246A US 2012239289 A1 US2012239289 A1 US 2012239289A1
- Authority
- US
- United States
- Prior art keywords
- user
- scheduling information
- location
- data
- information
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000015556 catabolic process Effects 0.000 description 36
- 238000006731 degradation reaction Methods 0.000 description 36
- 238000010586 diagram Methods 0.000 description 20
- 230000006399 behavior Effects 0.000 description 7
- 230000008901 benefit Effects 0.000 description 6
- 230000001413 cellular effect Effects 0.000 description 4
- 230000009471 action Effects 0.000 description 3
- 230000001934 delay Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 230000002123 temporal effect Effects 0.000 description 2
- 230000006978 adaptation Effects 0.000 description 1
- 230000002776 aggregation Effects 0.000 description 1
- 238000004220 aggregation Methods 0.000 description 1
- 239000000872 buffer Substances 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000004590 computer program Methods 0.000 description 1
- 230000003111 delayed effect Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003203 everyday effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- -1 walking speeds Substances 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/123—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams
- G08G1/127—Traffic control systems for road vehicles indicating the position of vehicles, e.g. scheduled vehicles; Managing passenger vehicles circulating according to a fixed timetable, e.g. buses, trains, trams to a central station ; Indicators in a central station
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3423—Multimodal routing, i.e. combining two or more modes of transportation, where the modes can be any of, e.g. driving, walking, cycling, public transport
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/26—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 specially adapted for navigation in a road network
- G01C21/34—Route searching; Route guidance
- G01C21/3407—Route searching; Route guidance specially adapted for specific applications
- G01C21/3438—Rendez-vous, i.e. searching a destination where several users can meet, and the routes to this destination for these users; Ride sharing, i.e. searching a route such that at least two users can share a vehicle for at least part of the route
-
- 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
- G06Q10/02—Reservations, e.g. for tickets, services or events
- G06Q10/025—Coordination of plural reservations, e.g. plural trip segments, transportation combined with accommodation
-
- 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G06Q50/40—
Definitions
- This specification generally relates to transportation information and applications thereof.
- Transportation information can be used for planning trips.
- a user can refer to a published route schedule of a transportation system when determining which route to use. Determining which route to take, however, can be challenging for users of transportation systems, for example, when two users try to coordinate with each other to meet using a transportation system. Schedules of transportation systems are often inaccurate compared to actual transportation system performance. Furthermore, transportation systems can fail to alert the user to changes, interruptions, or other situations that affect, a planned trip.
- Embodiments of this description generally relate to transportation information, and applications thereof.
- Methods, systems, and techniques for providing transportation information are provided.
- one aspect of the subject matter described in this specification may be embodied in a method for providing transportation information.
- An exemplary method for providing transportation information includes the actions of receiving user data associated with public transportation usage.
- the exemplary method also includes receiving public transportation data
- the exemplary method further includes generating scheduling information based on the user data and public transportation data.
- Another exemplary method for providing transportation information includes generating first scheduling information for a first user based on first user data, public transportation data, a first starting location, and a first destination location.
- the exemplary method also includes determining whether a second user starting from a second starting location different from the first starting location would like to join the first user.
- the exemplary method further includes generating second scheduling information for the second user to meet the first user based on second user data, the public transportation data, the second starting location, real-time location information for the first user, and a second destination location.
- the exemplary method also includes generating an alert for the second user following the second scheduling information to depart from the second starting location at a specified time to meet the first user following the first scheduling information.
- Another exemplary method for providing transportation information includes receiving public transportation data including real-time vehicle location information and at least one of historical vehicle location information and scheduled vehicle location information.
- the exemplary method also includes generating a schedule degradation mode based on a deviation of real-time vehicle location information from at least one of historical vehicle location information and scheduled vehicle location information.
- the exemplary method also includes generating scheduling information for a user based on a deviation of real-time vehicle location information from at least one of historical vehicle location information and scheduled vehicle location information.
- the scheduling information includes an indication of the schedule degradation mode.
- the scheduling information can be changed substantially based on the schedule degradation mode.
- Another exemplary method for providing transportation information includes receiving user data associated with public transportation usage including at least one of user locations, user movements, user transportation queries, user routes, and user vehicles.
- the exemplary method also includes receiving public transportation data including routes available to a user.
- the exemplary method further includes generating a user profile fore the user based on the user data and the public transportation data.
- the user profile includes automatically generated route suggestions for the user.
- FIG. 1 is a diagram of an exemplary transportation information system, in accordance with an embodiment.
- FIG. 2 is a diagram of an exemplary transportation information system including a profile creator, in accordance with an embodiment.
- FIG. 3 is a diagram, of an exemplary transportation information system including a public transportation analyzer and a rider analyzer, in accordance with an embodiment.
- FIG. 4 is a diagram of an exemplary transportation information system including a routing engine and a degradation mode, in accordance with an embodiment.
- FIG. 5 is a diagram of an exemplary transportation information system including a rider analyzer, a routing engine, and updated scheduling information, in accordance with an embodiment.
- FIG. 6 is a diagram of an exemplary transportation information system including an alert generator and an alert, in accordance with an embodiment.
- FIG. 7 is a flowchart of a method for providing transportation information, in accordance with an embodiment.
- FIG. 8 is a flowchart of another method for providing transportation information, in accordance with an embodiment.
- FIG. 9 is a flowchart of another method for providing transportation information, in accordance with an embodiment.
- FIG. 10 is a flowchart of another method for providing transportation information, in accordance with an embodiment.
- FIG. 11 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- FIG. 12 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- FIG. 13 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- FIG. 14 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- Embodiments of this disclosure relate to transportation information systems and methods, and applications thereof. Users may need help navigating transportation systems.
- user data associated with public transportation usage is received.
- Public transportation data including real-time public transportation data is received.
- Scheduling information is generated based on the user data and real-time public transportation data.
- first scheduling information is generated for a first user based on first user data, public transportation data, a first starting location, and a first destination location of the first user.
- Second scheduling information is generated for the second user to meet the first user based on second user data, public transportation data, the second starting location, real-time location information for the first user, and a second destination location.
- an alert can be generated for the second user to depart from the second starting location at a specified time to meet the first user.
- references to “one embodiment”, “an embodiment”, “an example embodiment”, etc. indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
- FIG. 1 is a diagram of an exemplary transportation information system 100 , in accordance with an embodiment.
- Transportation information system 100 includes an analyzer 110 .
- Analyzer 110 includes a profile creator 112 , public transportation analyzer 114 , rider analyzer 116 , routing engine 118 , alert generator 120 , and report generator 122 .
- Analyzer 110 can receive user data 130 , public transportation data 140 , and other inputs.
- Analyzer 110 can provide user profile 150 , scheduling information 160 , degradation mode 170 , and other outputs.
- Report generator 122 can generate reports of the scheduling information.
- Analyzer 110 is in communication with network(s) 180 , which is in communication with computing device(s) 190 , third party service(s) 194 , mapping service(s) 198 , and other interfaces.
- Network(s) 180 can include the Internet and one or more networks including local area networks (LANs), wide area networks (WANs), and wireless networks.
- Computing device(s) 190 can include personal computers, mobile computers including cellular telephones, tablet computing devices, and other devices capable of exchanging information.
- Third party service(s) 194 can include developers and aggregators.
- Analyzer 110 can interface with various services, including but not limited to Google Goggles, Google Latitude, Google Calendar, Google Earth, Android, Google Mobile Maps, Google Voice Search, Google Search, Google Maps, and Google Translate.
- Analyzer 110 can also interface with various transit systems, including but not limited to bus systems, railway systems, subway systems, airline systems, boating systems, traffic infrastructure systems, and alert systems.
- Components of transportation information system 100 may be implemented as software, hardware, firmware, or any combination thereof.
- Components of transportation information system 100 may also be implemented as computer-readable code executed on one or more computing devices capable of carrying out the functionality described herein.
- a computing device can include, but is not limited to, a personal computer, mobile device such as a mobile phone, workstation, embedded system, game console, television, set-top box, or any other computing device.
- a computing device can include, but is not limited to, a device having a processor and memory for executing and storing instructions.
- Software may include one or more applications and an operating system.
- Hardware can include, but is not limited to, a processor, memory and graphical user interface display.
- the computing device may also have multiple processors and multiple shared or separate memory components.
- the computing device may be a clustered computing environment or server farm.
- any subset of the components shown in FIG. 1 may in fact be embodied as a single component.
- the functionalities of rider analyzer 116 and routing engine 118 may be combined in a single device or module.
- Other combinations of the functional components of FIG. 1 are also possible, as would be known to a person of skill in the art.
- analyzer 110 may have more or less than the components shown in FIG. 1 .
- FIG. 2 is a diagram of an exemplary transportation information system 200 including a profile creator 112 , in accordance with an embodiment.
- Profile creator 112 can receive user data 130 as input, and can provide user profile 150 as output.
- User data 130 can include user locations, user movements, user transportation queries, user routes, user vehicles, and other user data related to transportation. Times and localities for the user data can also be provided to profile creator 112 .
- User data 130 can also include user location data 210 .
- User location data 210 enables a user's location to be determined through various techniques.
- User location data 210 can include browser-based location information, mobile computing device location information, public transportation services location data, user check-in to public transportation vehicles (e.g., swiping an access card at a vehicle-mounted reader), user association with public transportation entry ports (e.g., swiping an access card at a station turnstile), user access to a routing search engine or public transportation information, and user-provided locations such as a home address or business address.
- public transportation vehicles e.g., swiping an access card at a vehicle-mounted reader
- public transportation entry ports e.g., swiping an access card at a station turnstile
- user access to a routing search engine or public transportation information e.g., swiping an access card at a station turnstile
- user-provided locations such as a home address or business address.
- User location data 210 and user data 130 can be used by profile creator 112 to create user profile 150 .
- User profile 150 can be created automatically based on user data 130 and user location data 210 .
- Profile creator 112 can collect known route segments the rider has taken, and build user profile 150 .
- profile creator 112 can collect known route segments a rider has taken from GPS tacks, vehicle/trip check-ins, timing of boarding and alighting from public transportation, and usage of other public transportation applications.
- a transportation information system can learn from user locations, movements, queries, preferred/most used routes, trips, vehicles, and other user data 130 , and can thereby provide users with improved transportation information.
- FIG. 3 is a diagram of an exemplary transportation information system 300 including public transportation analyzer 114 and rider analyzer 116 , in accordance with an embodiment.
- Public transportation analyzer 114 can receive public transportation data 140 as input, and provide degradation mode 170 as output.
- Rider analyzer 116 can receive, as input, public transportation data 140 , user data 130 , user profile 150 , and output from public transportation analyzer 114 .
- Rider analyzer 116 can provide, as output, updated user profile 310 and relevant public transportation route segments 312 .
- Relevant public transportation route segments 312 can be based on updated user profile 310 .
- Public transportation analyzer 114 can analyze historical, current (including real-time), scheduled, and other types of public transportation data 140 .
- public transportation data 140 includes real-time public transportation vehicle location information, public transportation scheduling information, historical public transportation vehicle location information, public transportation stations, public transportation lines, and public transportation available trips.
- Public transportation data 140 can include any relevant information that enables public transportation analyzer 114 to prepare an analysis.
- Public transportation systems can have a schedule which determines at what times public transportation vehicles pass certain stations or time points corresponding to the schedule. As long as the transit network operates according to the schedule, very precise plans for trip requests can be generated. Even if vehicles deviate slightly from the schedule, precise routing can provide useful information to users because the vehicles should deviate only slightly from the precise plans.
- a service provided by a transit network can become degraded even beyond slight deviations from the schedule.
- Degradation including even slight deviations, can be detected by public transportation analyzer 114 and indicated by degradation mode 170 .
- scheduling information is substantially changed based on degradation mode 170 .
- Degradation of public transportation systems can occur in many situations. For example, during, rush hour, buses may not keep up with their schedule because of general traffic or congestion. Buses serving the same line might overtake each other and affect the times at which they arrive, depart, and service each bus stop or reach a point in the schedule. Unpredictable changes that affect the transportation system can cause the operation of the transportation system to depart significantly from the schedule, so that the schedule can no longer be relied upon. Such unpredictable changes can include accidents, rerouting, cancellations, extra trips, dispatcher intervention, and other unpredictable changes. Furthermore, changes in one portion of the transportation system can affect other portions of the transportation system, sometimes in ways that are not immediately apparent to users or even operators.
- Degradation modes can be used to enable different handling by embodiments of a transportation information system.
- Degradation modes can apply to an entire public transportation system/transit network, or part of the public transportation system/transit network.
- a degradation mode can indicate that service is running according to schedule with high precision. Another degradation mode can indicate that service is not running according to schedule, with significant deviations. Yet another degradation mode can indicate that service is not running according to schedule at all, but an approximate frequency of vehicles is still maintained. An approximate frequency of vehicles may correspond to normal operating mode for some agencies. Yet another degradation mode can indicate that service is not running according to either schedule or frequencies (for example, no bus serving a station for 30 minutes where normally a bus serves that station every 10 minutes).
- various services can be provided depending on the degradation mode.
- the way routes are computed can be changed, e.g., the way that scheduling information is determined and provided. For example, when routes are computed according to a schedule and the next bus passes the first station in 10 minutes, that 10 minutes is used as a basis for starting the route.
- the route can be started from the current time, and vehicle frequency used as an expected waiting time.
- a transportation information system can change the way routes (including requested scheduling information 160 ) are displayed, corresponding to the degradation mode.
- routes can be displayed to indicate that timing is imprecise corresponding to the degradation mode, and that scheduling information 160 is computed based on approximate, and not precise, scheduling times.
- a transportation information system can compute and display confidence intervals in the computed timings associated with scheduling information 160 .
- users can be alerted in association with a degradation mode.
- a transit network may supply alerts for service disruptions, but such alerts may not enable a user to predict what affect the alert will have on a planned trip.
- a transportation information system can use such alerts to inform a user of an event, and can also derive and show an alert independently from the transit network alerts (separate from or in addition to showing routes in a different way).
- Alerts may be generated and shown in the following contexts: i) when the user views the map in public transport mode (or just zoomed in enough), ii) when the user views schedules of a station or a line, iii) when the user views a computed route, and iv) while the user is following a previously computed route. Additional techniques and combinations of generating and showing alerts are possible.
- public transportation analyzer 114 can compare real-time vehicle positions or arrival estimations with the schedule. In another embodiment, public transportation analyzer 114 can compare real-time vehicle positions or arrival estimations with historical data for a similar period. The historical data can be collected over time from a transit network if available, or can be collected over time using embodiments of the transportation information system. Such comparisons can enable embodiments to compute how unusual is the current situation, e.g., degradation mode 170 .
- Generating an alert can be dependent on schedule adherence. For example, for Zurich, where schedule adherence is high, alerts regarding degradation mode 170 can be generated when a train is over one minute late (and a severe alert if the train is over 10 minutes late). In contrast, for a bus system somewhere else where schedule adherence is not as high, the corresponding values for generating alerts may be 15 minutes or an, hour, adjustable depending on such factors as the schedule adherence, historical performance, and real-time data for the particular transit network.
- rider analyzer 116 can receive as input public transportation data 140 , user data 130 , user profile 150 , and output from public transportation analyzer 114 . Rider analyzer 116 can then analyze the inputs and generate an updated user profile 310 , including relevant public transportation route segments 312 .
- Temporal travel patterns of a user may include the user traveling at the same time of day.
- Locality travel patterns of a user may include the user traveling with the same service, though not necessarily the same trip every day.
- rider analyzer 116 can identify a cluster of route segments in a transit network that is relevant to a user, and generate an updated user profile 310 that assigns those route segments to updated user profile 310 .
- locations and times of day can be assigned to a user profile.
- a user's relevant route segments can be automatically detected based on the user's user profile 150 .
- Updated user profile 310 can be generated based on detecting features of the transit network local to the user.
- the local transit network can be segmented and clustered into used and unused services for that user.
- Clustering can be done locally (similar routes, as defined by vehicle type, route, etc., up to mild variations, including different times of day).
- Clustering can also be done temporally (services running along a similar route, or sharing similar start and end points, at similar times of the day over time).
- the route segment clusters can then be used to identify relevant public transportation route segments 312 and other information that may affect the user's trip.
- Relevant public transportation route segments 312 and other information can be provided to the user. For example, relevant public transportation route segments 312 may be displayed on a screen of a computing device for the user. Relevant public transportation route segments 312 and other information can be stored in updated user profile 310 .
- using updated user profile 310 can provide various applications.
- Personalized nearby public transportation information can be enabled for the user. For example, in one embodiment, nearby stations, lines, and trips can be ranked according to the user's profile.
- public transportation service alerts can be personalized to a user based on deduced commute routes, regardless of an exact time of travel.
- Alert severity can be customized based on an importance to the user. For example, a mild delay in a station outside of the user's area may still lead to severe delays on a service relevant to the user. Accordingly, the user is alerted even though it may not have been apparent to the user that the mild delay in a station outside of the user's area would have led to a delay that affected the user.
- routes that the user is not taking can be suggested to the user by analyzing that such routes fit the user's profile or provide benefits. Users may not always know all the transit systems around them or know the fastest route using a transit system. In one example, a suggested route may be faster than the user's currently chosen route. Other benefits may be based on other criteria, such as providing routes having fewer connections, using a rail transportation system instead of a bus, and so on.
- an alert is generated when a user is taking a vehicle that does not fit the user's profile, or is otherwise an unexpected selection for the user based on user profile 150 , updated user profile 310 , or both (e.g., going on a bus that differs from the user's usual commute at a time when the user is expected to take another action such as going home).
- a transit system can be personalized for a user by providing known trips for the user (analyzed from user profile 150 , updated user profile 310 , or both).
- a transportation, information system can enable the user to compare previously taken routes to newly suggested routes.
- a transportation information system can provide useful defaults for user routing queries.
- rider analyzer 116 may take note of queries entered by a user and a trip that the user ultimately decides to take. This data may be used to offer suggestions to other users when searching similar trips.
- User profile 150 , updated user profile 310 , or both can enable embodiments to find a reasonable set of from and to locations and relevant times of day for the user.
- user preferences for routing parameters can be learned.
- rider analyzer 116 can determine appropriate connection time buffers, walking speeds, vehicle type preferences, walking distance preferences, and other user preferences by automatic analysis of various data.
- user preferences can be manually configured.
- the use of a user's transportation information may be provided as an opt-in service where a user may indicate in advance his or her approval of use of the user's transportation information.
- FIG. 4 is a diagram of an exemplary transportation information system 400 including routing engine 118 and degradation mode 170 , in accordance with an embodiment.
- Routing engine 118 can receive, as input, user data 130 , public transportation data 140 , user profile 150 , and degradation mode 170 . Accordingly, routing engine 118 can provide scheduling information 160 as output, including an indication of degradation mode 170 .
- scheduling information 160 can include explicit mention of the degradation mode and the level of deviation from the schedule. Scheduling information 160 can also be presented in a way that visually represents the level of degradation or deviation from the schedule. For example, a circle centered on a destination can approximate a range of arrival times using a corresponding diameter, in contrast to a point. Routing engine 118 may display the generated scheduling information to a user (e.g., on the user's computing device). Based on degradation mode 170 , routing engine 118 may alter an appearance of scheduling information 160 .
- FIG. 5 is a diagram of an exemplary transportation information system 500 including rider analyzer 116 , routing engine 118 , and updated scheduling information 520 , in accordance with an embodiment.
- Rider analyzer 116 can receive, as input, user behavior 510 and scheduling information 160 . Rider analyzer 116 can detect discrepancies between routing suggestions, provided in scheduling information 160 , and routes users actually take, provided in user behavior 510 . Rider analyzer 116 can provide the analysis results to routing engine 118 . Routing engine 118 can use the output from rider analyzer 116 to generate updated scheduling information 520 .
- a transportation information system can adapt to user preferences, and provide popular routes that are more consistent with user behavior 510 .
- a transportation information system can provide an indication that scheduling information has been updated, e.g., when generating updated scheduling information 520 . The user can be asked to verify whether updated scheduling information 520 is desirable.
- FIG. 6 is a diagram of an exemplary transportation information system 600 including alert generator 120 and alert 610 , in accordance with an embodiment.
- Alert generator 120 can receive, as input, degradation mode 170 , user behavior 510 , user data 130 , public transportation data 140 , user profile 150 , scheduling information 160 , and vehicle identification 620 .
- Vehicle identification 620 can be determined using various techniques. For example, determining which vehicle a user (passenger of the identified vehicle) is on can involve matching the user's location with real-time data for the identified vehicle's location.
- the user's location can be provided by a Global Positioning System (GPS) feature on the user's portable computing device such as, for example, a smartphone. Other location methods are possible, including wireless signal triangulation.
- GPS Global Positioning System
- the identified vehicle location can be provided by, for example, the transit agencies.
- vehicle identification 620 corresponding to the user's location, can be provided to alert generator 120 .
- Alert generator 120 can generate alert 610 , which can be used in various applications.
- vehicle identification 620 can be provided to various other components of analyzer 110 , including rider analyzer 116 , routing engine 118 , and other components.
- alert 610 can be used to notify analyzer 110 to use a different method of determining the user's location.
- analyzer 110 can determine a user's location based on a position of the vehicle the user is in, according to vehicle identification 620 .
- Position data for the identified vehicle may be gathered using a GPS that functions in tunnels, odometer readings that give the distance the train has travelled, or other methods.
- a transit network may use transponders positioned on the tracks to identify train locations. Even during a detour, the system can determine that the vehicle will arrive at a specific station, information which can be used for locating the vehicle and user.
- Alert 610 can also be used to notify the user that a different method of location detection is being used for the user.
- a user's GPS can be compared with a vehicle's GPS to determine that the user is on a particular vehicle.
- the user can be “checked in” to that vehicle.
- the user may also be given the option of manually “checking in” to a vehicle.
- the user can send the vehicle information to other users who can be kept informed of the user's progress via that vehicle's progress.
- alert 610 can be used to provide various information to the user. In another embodiment, alert 610 can be used to provide various information to analyzer 110 . Alert 610 can warn the user that the vehicle the user is on is about to enter an area with no cellular signal or no GPS signal. This is useful, for example, if the user is on the phone during a telephone call or using data provided by the cellular signal or GPS signal. Alert 610 can notify the user that analyzer 110 may not be able to provide trip advice while the user is in the tunnel or otherwise without a data signal, GPS signal, or both.
- Alert 610 can be used to notify analyzer 110 , the user, or both when the vehicle the user is on is about to reach the user's stop. Alert 610 can be used to alert the user if the user is going to miss a connection on a planned trip.
- Alert 610 can be used to notify other people regarding the user's status. For example, a user's friend who is going to meet the user can be notified of the user's progress on a trip based on the predictions analyzer 110 has for the identified vehicle the user is traveling on.
- Alert 610 can provide basic information about the trip the user is currently on. For example, analyzer 110 can provide scheduling information 160 including a list of upcoming stations and estimated times, similar to that which is often displayed on trams. Alert 610 can provide notifications of this information to the user, e.g., on the user's own device such as a mobile computing device.
- Alert 610 can provide a warning of problems up ahead along the user's route, so that the user can reroute before getting stuck.
- FIG. 7 is a flowchart 700 of a method for providing transportation information, in accordance with an embodiment.
- user data associated with public transportation usage is received.
- public transportation data is received.
- scheduling information is generated based on the user data and the public transportation data.
- FIG. 8 is a flowchart 800 of a method for providing transportation information, in accordance with an embodiment.
- first scheduling information is generated for a first user.
- routing engine 118 may generate first scheduling information for a first user based on first user data, public transportation data, a first starting location, and a first destination location.
- routing engine 118 may determine that a second user starting from a second starting location different from the first starting location would like to join the first user.
- second scheduling information is generated for the second user.
- routing engine 118 may generate second scheduling information for a second user to meet the first user based on second user data, public transportation data, the second starting location, real-time location information for the first user, and a second destination location.
- a stage 835 it is determined whether it is time for the second user to depart. If it is not time for the second user to depart, the system waits at a stage 837 and process flow returns to stage 835 . If it is time for the second user to depart, at a stage 840 , an alert is generated for the second user to depart to join the first user. In one embodiment, alert generator 120 generates an alert for the second user to depart to join the first user. Alert generator 120 may generate an alert for the second user to depart from a second starting location at a specified time to meet the first user.
- FIG. 9 is a flowchart 900 of a method for providing transportation information, in accordance with an embodiment.
- public transportation data is received.
- the public transportation data may include scheduled vehicle location information and actual vehicle location information.
- scheduling information including an indication of the schedule degradation mode is generated for the user.
- FIG. 10 is a flowchart 1000 of a method for providing transportation information, in accordance with an embodiment.
- user data associated with public transportation usage is received.
- public transportation data including routes available to the user is received.
- a user profile including automatically generated route suggestions is generated.
- FIG. 11 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- Users A 1110 and B 1120 agree to meet at a destination 1150 , e.g., a restaurant, using a transit system.
- a 1110 plans his route to destination 1150 .
- As route from origin 1112 to destination 1150 includes portions 1114 and 1116 .
- a 1110 shares his itinerary with B 1120 .
- B chooses to “join” this trip.
- scheduling information and B's scheduling information can be generated based on different forms of travel used by A and B (e.g., their travel preferences).
- A begins the trip at origin 1112 , and once he boards the vehicle at origin 1112 , the actual times of the vehicles he will catch are calculated (e.g., based on best approximations of connection times, degradation modes, etc., as determined by analyzer 110 ).
- B 1120 is informed when to begin his trip so that he will meet with A 1110 at stop 1130 .
- B's route from origin 1122 to destination 1150 includes portions 1124 and 1126 .
- B's vehicle makes a stop at stop 1130 .
- a transportation information system instructs B 1120 such that B 1120 arrives at stop 1130 in time to catch the vehicle that A 1110 is using. Therefore, A 1110 and B 1120 meet on the vehicle, and travel together (for example, along the last leg 1140 of a journey). A 1110 and B 1120 proceed to destination 1150 together, and do not have to ride separately in portions 1116 and 1126 of the trip.
- a vehicle that A 1110 is riding on that travels along a path of As generated scheduling information is identified. The identified vehicle and path are included in B's generated scheduling information.
- a 1110 or B 1120 may experience delays or a deviation from the original scheduling information.
- As scheduling information is updated based on real-time transportation data of B 1120 .
- B's scheduling information is updated based on real-time transportation data of A 1110 . For example, if A 1110 is delayed and there are multiple stops along ifs path, B 1120 may decide to exit a transportation vehicle that B 1120 is riding on, take a coffee break at a particular stop for a time period, and take a different transportation vehicle at a later point in time to join A 1110 at stop 1130 .
- a 1110 is alerted when real-time transportation data of B 11120 deviates from the second scheduling information.
- B 1120 is alerted when real-time transportation data of A 1110 deviates from the first scheduling information.
- FIG. 12 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- a system can choose different routes, and even modify a passenger's route postfactum, in order to maximize a portion 1250 of the trip that users A 1210 and B 1220 spend together.
- B 1220 if traveling alone or taking a direct trip, would not typically choose to travel away from a destination 1260 .
- B 1220 might choose to go out of his way if that helped him meet A 1210 sooner and allowed A 1210 and B 1220 to spend more time together on the trip.
- A's scheduling information may be adjusted to increase a portion of the trip that A 1210 and B 1220 spend together.
- B's scheduling information may be adjusted to increase a portion of the trip that A 1210 and B 1220 spend together. For example, a distance of B's generated route that includes the path of A's generated route is longer than a distance of another route from B's starting location to B's destination location. In this embodiment, A 1210 and B 1220 spend more time together along the route.
- a 1210 departs from origin 1212 , proceeds along path 1214 to a stop 1230 , then along path 1216 to stop 1240 , and along path 1218 to stop 1260 .
- a 1210 shares his itinerary with B 1220 and B 1220 chooses to join A's trip.
- B 1220 has an option of traveling a more direct route from origin 1222 along path 1223 to stop 1240 .
- B 1220 chooses to spend more time with A 1210 during the trip.
- B 1220 can be instructed when to depart from origin 1222 , and the vehicle in which A 1210 is riding can be identified, so that B 1220 can find A 1210 .
- a 1210 and B 1220 travel together from stop 1230 to stop 1240 and on to destination 1260 .
- FIG. 13 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- Users A 1310 and B 1320 want to meet at a common location, timed to arrive approximately simultaneously at destination 1340 .
- a 1310 is departing from origin 1312
- B 1320 is departing from origin 1322 .
- the system can determine that As path will take more time, and generate scheduling instructions for A 1310 to depart before B 1320 departs.
- a 1310 travels along path 1314 to stop 1330 , then along path 1316 to destination 1340 .
- the system determines when B 1320 should depart from origin 1322 .
- B 1320 then departs and travels along path 1324 .
- B 1320 arrives at destination 1340 approximately at the same time as A 1310 , meeting A 1310 at destination 1340 .
- A's trip changes or is rerouted for some reason then the system can notify B 1320 , reroute A 1310 , reroute B 1320 , or a combination of these. For example, if A 1310 misses a connection, B 1320 is notified and can be rerouted to meet A 1310 . The system may determine that B 1320 should leave at a later time. Similarly, A 1310 can be notified of changes in B's trip. For example, A 1310 can be notified that B 1320 has chosen to join A's trip, or that B 1320 is expected to meet A 1310 at a certain point. If B's trip changes, A 1310 can be updated and decide whether to be rerouted.
- FIG. 14 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment.
- Users A 1410 and B 1420 agree to meet at a stop 1430 , e.g., a bus stop, using a transit system, and travel together for a duration of time along their respective routes.
- A's destination is different from B's destination.
- a 1410 has a destination 1452 and B 1420 has a destination 1454 .
- a 1410 plans his route to destination 1452 , staring at origin 1412 .
- A's route from origin 1412 to destination 1452 includes portions 1414 , 1416 , and 1456 .
- A's vehicle makes stops, including a stop 1430 .
- a 1410 shares his itinerary with B 1420 .
- B 1420 chooses to meet A 1410 along his trip.
- scheduling information is generated for B 1420 to meet A 1410 at stop 1430 and travel along a path 1440 together.
- B's route from origin 1422 to destination 1454 includes portions 1424 , 1426 , and 1458 .
- a 1410 and B 1420 can meet on a vehicle at stop 1430 , and travel together until a stop 1450 .
- a and B proceed to stop 1450 together, and do not have to ride separately in portions 1416 and 1426 of the trip.
- a 1410 and B 1420 can separate so that A can proceed to destination 1452 and B can proceed to destination 1454 .
- a 1410 remains in the vehicle and B 1420 departs from the vehicle to ride a different vehicle.
- B 1420 remains in the vehicle and A 1410 departs from the vehicle to ride a different vehicle.
- a 1410 and B 1420 depart from the vehicle to ride a different vehicle.
- Embodiments illustrated in FIGS. 11-14 can be used between multiple vehicle types, including between public transit and personal transportation. If A 1310 is meeting B 1320 simultaneously in FIG. 13 , the system can track when A 1310 gets on the train at origin 1312 , for example. The system will calculate when B 1320 should get in his car, for example, so that B 1320 arrives at destination 1340 at approximately the same time that A 1310 arrives at destination 1340 . This can be extended to any form of traveling such as walking, bicycling, car driving, bus systems, train systems, and any combination of these for routing or meeting en route.
- riders can be alerted as to the capacity of various vehicles.
- the system can notify a user that a bus or train car is full.
- the user can plan to catch the next bus or train car that is not as crowded.
- a transportation information system can determine such information based on information from a transit system, user behavior 510 , and other data that can identify passenger load in a vehicle.
- a transportation information system can notify users of various features of a transit network/system. For example, embodiments can determine that it is raining, and therefore can advise a user which stops have a shelter to avoid the rain. For example, the system can alert the user to get off one stop early, so that the user can wait under a shelter at the earlier stop.
- Embodiments can be used for real-time information in public transportation systems. Users, developers, aggregators, and others can use the information in various ways. Developers/a developer feed can query a subset of the data. An example query can be “arrivals at station X in the next 10 minutes.” Embodiments can provide information with little need to cross reference, and can synthesize many standards across a variety of transportation systems. A snapshot of all the data can be provided, e.g., for an aggregator/aggregator feed. The data can be provided in a consistent format. Data formats can be optimized for aggregation, including a reference to a static schedule and incremental updates.
- Real-time data can be useful for alerting users if a vehicle is late or otherwise deviating from a schedule, rerouting a nip, or knowing that an event affects a user's trip.
- a transportation information system can determine whether parts of a public transit system route lack cellular or GPS signals and offer a user the choice of choosing another route with more reliable wireless signals.
- Embodiments can determine signal dead-spots where there are no requests coming from mobile networks. In high-usage areas, such as major cities, dead-spots may correspond to areas with no signal and embodiments can build up highly localized coverage maps.
- information can be collected where wireless signals are available on public transit systems.
- Real-time location data for a user can be used to convert a statically planned trip (e.g., origin/path/destination) to a precise list of concrete vehicles, times, or both associated with the trip.
- a statically planned trip e.g., origin/path/destination
- Scheduled information can be matched with real-time data, and can provide updates in the form of time increments to a schedule on a per-trip basis.
- Real-time data can include service alerts, schedule updates, location information (e.g., users and transit systems), passenger loads, video camera feeds, user GPS information, and other data.
- Raw data can be made available to websites and other data distributors.
- Embodiments can provide integration for otherwise loosely connected internal systems at an agency, and compensate when the relation of actual traffic versus scheduled traffic degrades over time.
- Morning Commute Marcus lives near Altersheim, Zurich. Route to work: Bus 140 from Altersheim to Langnau then the S4 from Langnau to Zurich HB.
- Marcus gets up and receives an alert on his phone that the bus to the train station is cancelled. Since it is only a short walk to the train, he can just leave a bit earlier and still catch the train.
- Marcus's phone knows when his first meeting of the afternoon is and alerts him when he needs to take the train back to work. He doesn't waste time waiting at the stop and arrives on time.
- Marcus's phone After enjoying the concert they head back to Zurich. It starts raining, so Marcus's phone directs them to a bus stop with a shelter nearby. Both of them are tired after a long day and fall asleep on the train. Fortunately, Marcus's phone knows when they are about to reach the station and an alarm sounds to wake them up.
Abstract
Description
- The present application claims the benefit of U.S. Provisional Patent Application No. 61/381,361, filed on Sep. 9, 2010, entitled “Transportation Information Systems and Methods” by Gontmakher et al, which is incorporated herein by reference in its entirety.
- This specification generally relates to transportation information and applications thereof.
- Transportation information can be used for planning trips. For example, a user can refer to a published route schedule of a transportation system when determining which route to use. Determining which route to take, however, can be challenging for users of transportation systems, for example, when two users try to coordinate with each other to meet using a transportation system. Schedules of transportation systems are often inaccurate compared to actual transportation system performance. Furthermore, transportation systems can fail to alert the user to changes, interruptions, or other situations that affect, a planned trip.
- Embodiments of this description generally relate to transportation information, and applications thereof. Methods, systems, and techniques for providing transportation information are provided. In general, one aspect of the subject matter described in this specification may be embodied in a method for providing transportation information. An exemplary method for providing transportation information includes the actions of receiving user data associated with public transportation usage. The exemplary method also includes receiving public transportation data The exemplary method further includes generating scheduling information based on the user data and public transportation data.
- Another exemplary method for providing transportation information includes generating first scheduling information for a first user based on first user data, public transportation data, a first starting location, and a first destination location. The exemplary method also includes determining whether a second user starting from a second starting location different from the first starting location would like to join the first user. The exemplary method further includes generating second scheduling information for the second user to meet the first user based on second user data, the public transportation data, the second starting location, real-time location information for the first user, and a second destination location. The exemplary method also includes generating an alert for the second user following the second scheduling information to depart from the second starting location at a specified time to meet the first user following the first scheduling information.
- Another exemplary method for providing transportation information includes receiving public transportation data including real-time vehicle location information and at least one of historical vehicle location information and scheduled vehicle location information. The exemplary method also includes generating a schedule degradation mode based on a deviation of real-time vehicle location information from at least one of historical vehicle location information and scheduled vehicle location information. The exemplary method also includes generating scheduling information for a user based on a deviation of real-time vehicle location information from at least one of historical vehicle location information and scheduled vehicle location information. The scheduling information includes an indication of the schedule degradation mode. The scheduling information can be changed substantially based on the schedule degradation mode.
- Another exemplary method for providing transportation information includes receiving user data associated with public transportation usage including at least one of user locations, user movements, user transportation queries, user routes, and user vehicles. The exemplary method also includes receiving public transportation data including routes available to a user. The exemplary method further includes generating a user profile fore the user based on the user data and the public transportation data. The user profile includes automatically generated route suggestions for the user.
- Other embodiments of these aspects include corresponding systems, apparatuses, and computer program products configured to perform the actions of these methods, encoded on computer storage devices.
- Further embodiments, features, and advantages as well as the structure and operation of the various embodiments are described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers may indicate identical or functionally similar elements.
-
FIG. 1 is a diagram of an exemplary transportation information system, in accordance with an embodiment. -
FIG. 2 is a diagram of an exemplary transportation information system including a profile creator, in accordance with an embodiment. -
FIG. 3 is a diagram, of an exemplary transportation information system including a public transportation analyzer and a rider analyzer, in accordance with an embodiment. -
FIG. 4 is a diagram of an exemplary transportation information system including a routing engine and a degradation mode, in accordance with an embodiment. -
FIG. 5 is a diagram of an exemplary transportation information system including a rider analyzer, a routing engine, and updated scheduling information, in accordance with an embodiment. -
FIG. 6 is a diagram of an exemplary transportation information system including an alert generator and an alert, in accordance with an embodiment. -
FIG. 7 is a flowchart of a method for providing transportation information, in accordance with an embodiment. -
FIG. 8 is a flowchart of another method for providing transportation information, in accordance with an embodiment. -
FIG. 9 is a flowchart of another method for providing transportation information, in accordance with an embodiment. -
FIG. 10 is a flowchart of another method for providing transportation information, in accordance with an embodiment. -
FIG. 11 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. -
FIG. 12 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. -
FIG. 13 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. -
FIG. 14 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. - Embodiments are described with reference to the accompanying drawings. The drawing in which an element first appears is typically indicated by the leftmost digit or digits in the corresponding reference number. The drawings are not necessarily drawn to scale.
- I. Overview
- II. System Architecture
- III. User Profile
- IV. Degradation Modes
- V. Determining Relevant Routes for a User
- VI. Adapting to User Behavior
- VII. Alerts
- VIII. Exemplary Methods
- IX. Routing
- X. Additional Advantages Including Real-Time Applications
- XI. Further Examples
- XII. Conclusion
- Embodiments of this disclosure relate to transportation information systems and methods, and applications thereof. Users may need help navigating transportation systems. In one embodiment, user data associated with public transportation usage is received. Public transportation data including real-time public transportation data is received. Scheduling information is generated based on the user data and real-time public transportation data.
- Two users using a transportation system may coordinate with each other to meet. In one embodiment, first scheduling information is generated for a first user based on first user data, public transportation data, a first starting location, and a first destination location of the first user. A second user starting from a second starting location different from the first starting location would like to join the first user. Second scheduling information is generated for the second user to meet the first user based on second user data, public transportation data, the second starting location, real-time location information for the first user, and a second destination location. When it is time, an alert can be generated for the second user to depart from the second starting location at a specified time to meet the first user.
- In the detailed description that follows, references to “one embodiment”, “an embodiment”, “an example embodiment”, etc., indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to effect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described.
-
FIG. 1 is a diagram of an exemplarytransportation information system 100, in accordance with an embodiment.Transportation information system 100 includes ananalyzer 110.Analyzer 110 includes aprofile creator 112,public transportation analyzer 114,rider analyzer 116,routing engine 118,alert generator 120, andreport generator 122.Analyzer 110 can receiveuser data 130,public transportation data 140, and other inputs.Analyzer 110 can provideuser profile 150,scheduling information 160,degradation mode 170, and other outputs.Report generator 122 can generate reports of the scheduling information. -
Analyzer 110 is in communication with network(s) 180, which is in communication with computing device(s) 190, third party service(s) 194, mapping service(s) 198, and other interfaces. Network(s) 180 can include the Internet and one or more networks including local area networks (LANs), wide area networks (WANs), and wireless networks. Computing device(s) 190 can include personal computers, mobile computers including cellular telephones, tablet computing devices, and other devices capable of exchanging information. Third party service(s) 194 can include developers and aggregators.Analyzer 110 can interface with various services, including but not limited to Google Goggles, Google Latitude, Google Calendar, Google Earth, Android, Google Mobile Maps, Google Voice Search, Google Search, Google Maps, and Google Translate.Analyzer 110 can also interface with various transit systems, including but not limited to bus systems, railway systems, subway systems, airline systems, boating systems, traffic infrastructure systems, and alert systems. - Components of transportation information system 100 (e.g.,
profile creator 112,routing engine 118,alert generator 120, and report generator 122) may be implemented as software, hardware, firmware, or any combination thereof. Components oftransportation information system 100 may also be implemented as computer-readable code executed on one or more computing devices capable of carrying out the functionality described herein. Such a computing device can include, but is not limited to, a personal computer, mobile device such as a mobile phone, workstation, embedded system, game console, television, set-top box, or any other computing device. Further, a computing device can include, but is not limited to, a device having a processor and memory for executing and storing instructions. Software may include one or more applications and an operating system. Hardware can include, but is not limited to, a processor, memory and graphical user interface display. The computing device may also have multiple processors and multiple shared or separate memory components. For example, the computing device may be a clustered computing environment or server farm. - Note that in alternative embodiments, any subset of the components shown in
FIG. 1 may in fact be embodied as a single component. For example, the functionalities ofrider analyzer 116 androuting engine 118 may be combined in a single device or module. Other combinations of the functional components ofFIG. 1 are also possible, as would be known to a person of skill in the art. Further,analyzer 110 may have more or less than the components shown inFIG. 1 . -
FIG. 2 is a diagram of an exemplarytransportation information system 200 including aprofile creator 112, in accordance with an embodiment.Profile creator 112 can receiveuser data 130 as input, and can provideuser profile 150 as output.User data 130 can include user locations, user movements, user transportation queries, user routes, user vehicles, and other user data related to transportation. Times and localities for the user data can also be provided toprofile creator 112. -
User data 130 can also includeuser location data 210.User location data 210 enables a user's location to be determined through various techniques.User location data 210 can include browser-based location information, mobile computing device location information, public transportation services location data, user check-in to public transportation vehicles (e.g., swiping an access card at a vehicle-mounted reader), user association with public transportation entry ports (e.g., swiping an access card at a station turnstile), user access to a routing search engine or public transportation information, and user-provided locations such as a home address or business address. -
User location data 210 anduser data 130 can be used byprofile creator 112 to createuser profile 150.User profile 150 can be created automatically based onuser data 130 anduser location data 210.Profile creator 112 can collect known route segments the rider has taken, and builduser profile 150. For example,profile creator 112 can collect known route segments a rider has taken from GPS tacks, vehicle/trip check-ins, timing of boarding and alighting from public transportation, and usage of other public transportation applications. - In one embodiment, a transportation information system can learn from user locations, movements, queries, preferred/most used routes, trips, vehicles, and
other user data 130, and can thereby provide users with improved transportation information. -
FIG. 3 is a diagram of an exemplarytransportation information system 300 includingpublic transportation analyzer 114 andrider analyzer 116, in accordance with an embodiment.Public transportation analyzer 114 can receivepublic transportation data 140 as input, and providedegradation mode 170 as output.Rider analyzer 116 can receive, as input,public transportation data 140,user data 130,user profile 150, and output frompublic transportation analyzer 114.Rider analyzer 116 can provide, as output, updateduser profile 310 and relevant publictransportation route segments 312. Relevant publictransportation route segments 312 can be based on updateduser profile 310. -
Public transportation analyzer 114 can analyze historical, current (including real-time), scheduled, and other types ofpublic transportation data 140. In one example,public transportation data 140 includes real-time public transportation vehicle location information, public transportation scheduling information, historical public transportation vehicle location information, public transportation stations, public transportation lines, and public transportation available trips.Public transportation data 140 can include any relevant information that enablespublic transportation analyzer 114 to prepare an analysis. - Public transportation systems can have a schedule which determines at what times public transportation vehicles pass certain stations or time points corresponding to the schedule. As long as the transit network operates according to the schedule, very precise plans for trip requests can be generated. Even if vehicles deviate slightly from the schedule, precise routing can provide useful information to users because the vehicles should deviate only slightly from the precise plans.
- A service provided by a transit network can become degraded even beyond slight deviations from the schedule. Degradation, including even slight deviations, can be detected by
public transportation analyzer 114 and indicated bydegradation mode 170. In one embodiment, scheduling information is substantially changed based ondegradation mode 170. - Degradation of public transportation systems can occur in many situations. For example, during, rush hour, buses may not keep up with their schedule because of general traffic or congestion. Buses serving the same line might overtake each other and affect the times at which they arrive, depart, and service each bus stop or reach a point in the schedule. Unpredictable changes that affect the transportation system can cause the operation of the transportation system to depart significantly from the schedule, so that the schedule can no longer be relied upon. Such unpredictable changes can include accidents, rerouting, cancellations, extra trips, dispatcher intervention, and other unpredictable changes. Furthermore, changes in one portion of the transportation system can affect other portions of the transportation system, sometimes in ways that are not immediately apparent to users or even operators.
- Different degradation modes can be used to enable different handling by embodiments of a transportation information system. Degradation modes can apply to an entire public transportation system/transit network, or part of the public transportation system/transit network.
- A degradation mode can indicate that service is running according to schedule with high precision. Another degradation mode can indicate that service is not running according to schedule, with significant deviations. Yet another degradation mode can indicate that service is not running according to schedule at all, but an approximate frequency of vehicles is still maintained. An approximate frequency of vehicles may correspond to normal operating mode for some agencies. Yet another degradation mode can indicate that service is not running according to either schedule or frequencies (for example, no bus serving a station for 30 minutes where normally a bus serves that station every 10 minutes).
- In one embodiment, various services can be provided depending on the degradation mode. The way routes are computed can be changed, e.g., the way that scheduling information is determined and provided. For example, when routes are computed according to a schedule and the next bus passes the first station in 10 minutes, that 10 minutes is used as a basis for starting the route. In one embodiment if a transportation information system detects that the transit network is now operating in a degradation mode associated with frequency-only, the route can be started from the current time, and vehicle frequency used as an expected waiting time.
- In one embodiment, a transportation information system can change the way routes (including requested scheduling information 160) are displayed, corresponding to the degradation mode. In one example, a route can be displayed to indicate that timing is imprecise corresponding to the degradation mode, and that
scheduling information 160 is computed based on approximate, and not precise, scheduling times. In one embodiment, a transportation information system can compute and display confidence intervals in the computed timings associated withscheduling information 160. - In one embodiment, users can be alerted in association with a degradation mode. A transit network may supply alerts for service disruptions, but such alerts may not enable a user to predict what affect the alert will have on a planned trip. In one embodiment, a transportation information system can use such alerts to inform a user of an event, and can also derive and show an alert independently from the transit network alerts (separate from or in addition to showing routes in a different way). Alerts may be generated and shown in the following contexts: i) when the user views the map in public transport mode (or just zoomed in enough), ii) when the user views schedules of a station or a line, iii) when the user views a computed route, and iv) while the user is following a previously computed route. Additional techniques and combinations of generating and showing alerts are possible.
- Various techniques can be used to compute
degradation mode 170. In one embodiment,public transportation analyzer 114 can compare real-time vehicle positions or arrival estimations with the schedule. In another embodiment,public transportation analyzer 114 can compare real-time vehicle positions or arrival estimations with historical data for a similar period. The historical data can be collected over time from a transit network if available, or can be collected over time using embodiments of the transportation information system. Such comparisons can enable embodiments to compute how unusual is the current situation, e.g.,degradation mode 170. - Generating an alert can be dependent on schedule adherence. For example, for Zurich, where schedule adherence is high, alerts regarding
degradation mode 170 can be generated when a train is over one minute late (and a severe alert if the train is over 10 minutes late). In contrast, for a bus system somewhere else where schedule adherence is not as high, the corresponding values for generating alerts may be 15 minutes or an, hour, adjustable depending on such factors as the schedule adherence, historical performance, and real-time data for the particular transit network. - V. Determining Relevant Routes for a User
- Referring again to the embodiment illustrated in
FIG. 3 ,rider analyzer 116 can receive as inputpublic transportation data 140,user data 130,user profile 150, and output frompublic transportation analyzer 114.Rider analyzer 116 can then analyze the inputs and generate an updateduser profile 310, including relevant publictransportation route segments 312. - Users (e.g., public transportation riders) over time can develop some public transportation usage patterns that may be temporal or local. Temporal travel patterns of a user may include the user traveling at the same time of day. Locality travel patterns of a user may include the user traveling with the same service, though not necessarily the same trip every day. In one embodiment,
rider analyzer 116 can identify a cluster of route segments in a transit network that is relevant to a user, and generate an updateduser profile 310 that assigns those route segments to updateduser profile 310. In one example, locations and times of day can be assigned to a user profile. In one embodiment, a user's relevant route segments can be automatically detected based on the user'suser profile 150. - Updated
user profile 310 can be generated based on detecting features of the transit network local to the user. The local transit network can be segmented and clustered into used and unused services for that user. Clustering can be done locally (similar routes, as defined by vehicle type, route, etc., up to mild variations, including different times of day). Clustering can also be done temporally (services running along a similar route, or sharing similar start and end points, at similar times of the day over time). The route segment clusters can then be used to identify relevant publictransportation route segments 312 and other information that may affect the user's trip. Relevant publictransportation route segments 312 and other information can be provided to the user. For example, relevant publictransportation route segments 312 may be displayed on a screen of a computing device for the user. Relevant publictransportation route segments 312 and other information can be stored in updateduser profile 310. - In some embodiments, using updated
user profile 310 can provide various applications. Personalized nearby public transportation information can be enabled for the user. For example, in one embodiment, nearby stations, lines, and trips can be ranked according to the user's profile. - In some embodiments, public transportation service alerts can be personalized to a user based on deduced commute routes, regardless of an exact time of travel. Alert severity can be customized based on an importance to the user. For example, a mild delay in a station outside of the user's area may still lead to severe delays on a service relevant to the user. Accordingly, the user is alerted even though it may not have been apparent to the user that the mild delay in a station outside of the user's area would have led to a delay that affected the user.
- In one embodiment, routes that the user is not taking can be suggested to the user by analyzing that such routes fit the user's profile or provide benefits. Users may not always know all the transit systems around them or know the fastest route using a transit system. In one example, a suggested route may be faster than the user's currently chosen route. Other benefits may be based on other criteria, such as providing routes having fewer connections, using a rail transportation system instead of a bus, and so on.
- In one embodiment, an alert is generated when a user is taking a vehicle that does not fit the user's profile, or is otherwise an unexpected selection for the user based on
user profile 150, updateduser profile 310, or both (e.g., going on a bus that differs from the user's usual commute at a time when the user is expected to take another action such as going home). - In one embodiment, a transit system can be personalized for a user by providing known trips for the user (analyzed from
user profile 150, updateduser profile 310, or both). In another embodiment, a transportation, information system can enable the user to compare previously taken routes to newly suggested routes. - In one embodiment, a transportation information system can provide useful defaults for user routing queries. For example,
rider analyzer 116 may take note of queries entered by a user and a trip that the user ultimately decides to take. This data may be used to offer suggestions to other users when searching similar trips.User profile 150, updateduser profile 310, or both can enable embodiments to find a reasonable set of from and to locations and relevant times of day for the user. - In one embodiment, user preferences for routing parameters can be learned. In one example,
rider analyzer 116 can determine appropriate connection time buffers, walking speeds, vehicle type preferences, walking distance preferences, and other user preferences by automatic analysis of various data. In another example, user preferences can be manually configured. In some embodiments, the use of a user's transportation information may be provided as an opt-in service where a user may indicate in advance his or her approval of use of the user's transportation information. -
FIG. 4 is a diagram of an exemplarytransportation information system 400 includingrouting engine 118 anddegradation mode 170, in accordance with an embodiment. -
Routing engine 118 can receive, as input,user data 130,public transportation data 140,user profile 150, anddegradation mode 170. Accordingly,routing engine 118 can providescheduling information 160 as output, including an indication ofdegradation mode 170. For example, schedulinginformation 160 can include explicit mention of the degradation mode and the level of deviation from the schedule.Scheduling information 160 can also be presented in a way that visually represents the level of degradation or deviation from the schedule. For example, a circle centered on a destination can approximate a range of arrival times using a corresponding diameter, in contrast to a point.Routing engine 118 may display the generated scheduling information to a user (e.g., on the user's computing device). Based ondegradation mode 170,routing engine 118 may alter an appearance ofscheduling information 160. -
FIG. 5 is a diagram of an exemplarytransportation information system 500 includingrider analyzer 116,routing engine 118, and updatedscheduling information 520, in accordance with an embodiment.Rider analyzer 116 can receive, as input,user behavior 510 andscheduling information 160.Rider analyzer 116 can detect discrepancies between routing suggestions, provided inscheduling information 160, and routes users actually take, provided inuser behavior 510.Rider analyzer 116 can provide the analysis results torouting engine 118.Routing engine 118 can use the output fromrider analyzer 116 to generate updatedscheduling information 520. - In one embodiment, a transportation information system can adapt to user preferences, and provide popular routes that are more consistent with
user behavior 510. In another embodiment, a transportation information system can provide an indication that scheduling information has been updated, e.g., when generating updatedscheduling information 520. The user can be asked to verify whether updatedscheduling information 520 is desirable. -
FIG. 6 is a diagram of an exemplarytransportation information system 600 includingalert generator 120 and alert 610, in accordance with an embodiment.Alert generator 120 can receive, as input,degradation mode 170,user behavior 510,user data 130,public transportation data 140,user profile 150,scheduling information 160, andvehicle identification 620. -
Vehicle identification 620 can be determined using various techniques. For example, determining which vehicle a user (passenger of the identified vehicle) is on can involve matching the user's location with real-time data for the identified vehicle's location. The user's location can be provided by a Global Positioning System (GPS) feature on the user's portable computing device such as, for example, a smartphone. Other location methods are possible, including wireless signal triangulation. The identified vehicle location can be provided by, for example, the transit agencies. - In one embodiment,
vehicle identification 620, corresponding to the user's location, can be provided to alertgenerator 120.Alert generator 120 can generate alert 610, which can be used in various applications. Although not illustrated,vehicle identification 620 can be provided to various other components ofanalyzer 110, includingrider analyzer 116,routing engine 118, and other components. - In one example, when a train is about to enter a tunnel and the user will lose GPS location, alert 610 can be used to notify
analyzer 110 to use a different method of determining the user's location. In one embodiment,analyzer 110 can determine a user's location based on a position of the vehicle the user is in, according tovehicle identification 620. Position data for the identified vehicle may be gathered using a GPS that functions in tunnels, odometer readings that give the distance the train has travelled, or other methods. For example, a transit network may use transponders positioned on the tracks to identify train locations. Even during a detour, the system can determine that the vehicle will arrive at a specific station, information which can be used for locating the vehicle and user.Alert 610 can also be used to notify the user that a different method of location detection is being used for the user. A user's GPS can be compared with a vehicle's GPS to determine that the user is on a particular vehicle. The user can be “checked in” to that vehicle. The user may also be given the option of manually “checking in” to a vehicle. The user can send the vehicle information to other users who can be kept informed of the user's progress via that vehicle's progress. - In one embodiment, alert 610 can be used to provide various information to the user. In another embodiment, alert 610 can be used to provide various information to
analyzer 110.Alert 610 can warn the user that the vehicle the user is on is about to enter an area with no cellular signal or no GPS signal. This is useful, for example, if the user is on the phone during a telephone call or using data provided by the cellular signal or GPS signal.Alert 610 can notify the user that analyzer 110 may not be able to provide trip advice while the user is in the tunnel or otherwise without a data signal, GPS signal, or both. -
Alert 610 can be used to notifyanalyzer 110, the user, or both when the vehicle the user is on is about to reach the user's stop.Alert 610 can be used to alert the user if the user is going to miss a connection on a planned trip. -
Alert 610 can be used to notify other people regarding the user's status. For example, a user's friend who is going to meet the user can be notified of the user's progress on a trip based on the predictions analyzer 110 has for the identified vehicle the user is traveling on. -
Alert 610 can provide basic information about the trip the user is currently on. For example,analyzer 110 can providescheduling information 160 including a list of upcoming stations and estimated times, similar to that which is often displayed on trams.Alert 610 can provide notifications of this information to the user, e.g., on the user's own device such as a mobile computing device. -
Alert 610 can provide a warning of problems up ahead along the user's route, so that the user can reroute before getting stuck. -
FIG. 7 is aflowchart 700 of a method for providing transportation information, in accordance with an embodiment. At astage 710, user data associated with public transportation usage is received. At astage 720, public transportation data is received. At astage 730, scheduling information is generated based on the user data and the public transportation data. -
FIG. 8 is aflowchart 800 of a method for providing transportation information, in accordance with an embodiment. At astage 810, first scheduling information is generated for a first user. In one embodiment,routing engine 118 may generate first scheduling information for a first user based on first user data, public transportation data, a first starting location, and a first destination location. - At a
stage 820, it is determined that a second user would like to join the first user. In one embodiment,routing engine 118 may determine that a second user starting from a second starting location different from the first starting location would like to join the first user. - At a
stage 830, second scheduling information is generated for the second user. In one embodiment,routing engine 118 may generate second scheduling information for a second user to meet the first user based on second user data, public transportation data, the second starting location, real-time location information for the first user, and a second destination location. - At a
stage 835, it is determined whether it is time for the second user to depart. If it is not time for the second user to depart, the system waits at astage 837 and process flow returns to stage 835. If it is time for the second user to depart, at astage 840, an alert is generated for the second user to depart to join the first user. In one embodiment,alert generator 120 generates an alert for the second user to depart to join the first user.Alert generator 120 may generate an alert for the second user to depart from a second starting location at a specified time to meet the first user. -
FIG. 9 is aflowchart 900 of a method for providing transportation information, in accordance with an embodiment. At astage 910, public transportation data is received. The public transportation data may include scheduled vehicle location information and actual vehicle location information. At astage 915, it is determined whether scheduled vehicle location information deviates from actual vehicle location information. If the deviation does not exceed a threshold, at astage 917, scheduling information is generated for the user. If the deviation exceeds a threshold, at astage 920, a schedule degradation mode is generated. At astage 930, scheduling information including an indication of the schedule degradation mode is generated for the user. -
FIG. 10 is aflowchart 1000 of a method for providing transportation information, in accordance with an embodiment. At astage 1010, user data associated with public transportation usage is received. At astage 1020, public transportation data including routes available to the user is received. At astage 1030, a user profile including automatically generated route suggestions is generated. -
FIG. 11 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. Users A 1110 andB 1120 agree to meet at adestination 1150, e.g., a restaurant, using a transit system. A 1110 plans his route todestination 1150. As route fromorigin 1112 todestination 1150 includesportions - A 1110 shares his itinerary with
B 1120. B chooses to “join” this trip. As scheduling information and B's scheduling information can be generated based on different forms of travel used by A and B (e.g., their travel preferences). - A begins the trip at
origin 1112, and once he boards the vehicle atorigin 1112, the actual times of the vehicles he will catch are calculated (e.g., based on best approximations of connection times, degradation modes, etc., as determined by analyzer 110). -
B 1120 is informed when to begin his trip so that he will meet with A 1110 atstop 1130. B's route fromorigin 1122 todestination 1150 includesportions stop 1130. - In one embodiment, a transportation information system instructs
B 1120 such thatB 1120 arrives atstop 1130 in time to catch the vehicle that A 1110 is using. Therefore, A 1110 andB 1120 meet on the vehicle, and travel together (for example, along thelast leg 1140 of a journey). A 1110 andB 1120 proceed todestination 1150 together, and do not have to ride separately inportions - During travel, A 1110 or
B 1120 may experience delays or a deviation from the original scheduling information. In one embodiment, As scheduling information is updated based on real-time transportation data ofB 1120. In another embodiment, B's scheduling information is updated based on real-time transportation data of A 1110. For example, if A 1110 is delayed and there are multiple stops along ifs path,B 1120 may decide to exit a transportation vehicle thatB 1120 is riding on, take a coffee break at a particular stop for a time period, and take a different transportation vehicle at a later point in time to join A 1110 atstop 1130. - In one embodiment, A 1110 is alerted when real-time transportation data of B 11120 deviates from the second scheduling information. In another embodiment,
B 1120 is alerted when real-time transportation data of A 1110 deviates from the first scheduling information. -
FIG. 12 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. As illustrated, a system can choose different routes, and even modify a passenger's route postfactum, in order to maximize aportion 1250 of the trip that users A 1210 andB 1220 spend together. For example,B 1220, if traveling alone or taking a direct trip, would not typically choose to travel away from adestination 1260.B 1220, however, might choose to go out of his way if that helped him meet A 1210 sooner and allowed A 1210 andB 1220 to spend more time together on the trip. - In one embodiment, A's scheduling information may be adjusted to increase a portion of the trip that A 1210 and
B 1220 spend together. In another embodiment, B's scheduling information may be adjusted to increase a portion of the trip that A 1210 andB 1220 spend together. For example, a distance of B's generated route that includes the path of A's generated route is longer than a distance of another route from B's starting location to B's destination location. In this embodiment, A 1210 andB 1220 spend more time together along the route. - As illustrated, A 1210 departs from
origin 1212, proceeds alongpath 1214 to astop 1230, then alongpath 1216 to stop 1240, and alongpath 1218 to stop 1260. A 1210 shares his itinerary withB 1220 andB 1220 chooses to join A's trip. -
B 1220 has an option of traveling a more direct route fromorigin 1222 alongpath 1223 to stop 1240.B 1220, however, chooses to spend more time with A 1210 during the trip. In one embodiment, it is determined thatB 1220 can travel alongpath 1224 andintercept A 1210 by catching A's vehicle atstop 1230. In this embodiment,B 1220 can be instructed when to depart fromorigin 1222, and the vehicle in which A 1210 is riding can be identified, so thatB 1220 can find A 1210. - Accordingly, for the remainder of
trip 1250, A 1210 andB 1220 travel together fromstop 1230 to stop 1240 and on todestination 1260. This avoids A 1210 andB 1220 from having to travel separately alongpaths 1216/1226 and 1218/1228. -
FIG. 13 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. Users A 1310 andB 1320 want to meet at a common location, timed to arrive approximately simultaneously atdestination 1340. A 1310 is departing fromorigin 1312, andB 1320 is departing fromorigin 1322. - The system can determine that As path will take more time, and generate scheduling instructions for A 1310 to depart before
B 1320 departs. A 1310 travels alongpath 1314 to stop 1330, then alongpath 1316 todestination 1340. While A 1310 is traveling, the system determines whenB 1320 should depart fromorigin 1322.B 1320 then departs and travels alongpath 1324.B 1320 arrives atdestination 1340 approximately at the same time as A 1310, meeting A 1310 atdestination 1340. - If A's trip changes or is rerouted for some reason, then the system can notify
B 1320, reroute A 1310, rerouteB 1320, or a combination of these. For example, if A 1310 misses a connection,B 1320 is notified and can be rerouted to meet A 1310. The system may determine thatB 1320 should leave at a later time. Similarly, A 1310 can be notified of changes in B's trip. For example, A 1310 can be notified thatB 1320 has chosen to join A's trip, or thatB 1320 is expected to meet A 1310 at a certain point. If B's trip changes, A 1310 can be updated and decide whether to be rerouted. -
FIG. 14 is a diagram of an application of an exemplary transportation information system, in accordance with an embodiment. Users A 1410 andB 1420 agree to meet at astop 1430, e.g., a bus stop, using a transit system, and travel together for a duration of time along their respective routes. A's destination is different from B's destination. A 1410 has adestination 1452 andB 1420 has adestination 1454. A 1410 plans his route todestination 1452, staring atorigin 1412. A's route fromorigin 1412 todestination 1452 includesportions stop 1430. - A 1410 shares his itinerary with
B 1420.B 1420 chooses to meet A 1410 along his trip. In one embodiment, scheduling information is generated forB 1420 to meet A 1410 atstop 1430 and travel along apath 1440 together. B's route fromorigin 1422 todestination 1454 includesportions stop 1430. - A 1410 and
B 1420 can meet on a vehicle atstop 1430, and travel together until astop 1450. A and B proceed to stop 1450 together, and do not have to ride separately inportions stop 1450, A 1410 andB 1420 can separate so that A can proceed todestination 1452 and B can proceed todestination 1454. In one example, A 1410 remains in the vehicle andB 1420 departs from the vehicle to ride a different vehicle. In another example,B 1420 remains in the vehicle and A 1410 departs from the vehicle to ride a different vehicle. In another example, A 1410 andB 1420 depart from the vehicle to ride a different vehicle. - Embodiments illustrated in
FIGS. 11-14 can be used between multiple vehicle types, including between public transit and personal transportation. If A 1310 is meetingB 1320 simultaneously inFIG. 13 , the system can track when A 1310 gets on the train atorigin 1312, for example. The system will calculate whenB 1320 should get in his car, for example, so thatB 1320 arrives atdestination 1340 at approximately the same time that A 1310 arrives atdestination 1340. This can be extended to any form of traveling such as walking, bicycling, car driving, bus systems, train systems, and any combination of these for routing or meeting en route. - X. Additional Advantages Including Real-Time Applications
- In one embodiment, riders can be alerted as to the capacity of various vehicles. In one example, the system can notify a user that a bus or train car is full. In this example, the user can plan to catch the next bus or train car that is not as crowded. In one embodiment, a transportation information system can determine such information based on information from a transit system,
user behavior 510, and other data that can identify passenger load in a vehicle. - In one embodiment, a transportation information system can notify users of various features of a transit network/system. For example, embodiments can determine that it is raining, and therefore can advise a user which stops have a shelter to avoid the rain. For example, the system can alert the user to get off one stop early, so that the user can wait under a shelter at the earlier stop.
- Embodiments can be used for real-time information in public transportation systems. Users, developers, aggregators, and others can use the information in various ways. Developers/a developer feed can query a subset of the data. An example query can be “arrivals at station X in the next 10 minutes.” Embodiments can provide information with little need to cross reference, and can synthesize many standards across a variety of transportation systems. A snapshot of all the data can be provided, e.g., for an aggregator/aggregator feed. The data can be provided in a consistent format. Data formats can be optimized for aggregation, including a reference to a static schedule and incremental updates.
- Real-time data can be useful for alerting users if a vehicle is late or otherwise deviating from a schedule, rerouting a nip, or knowing that an event affects a user's trip. For example, embodiments of a transportation information system can determine whether parts of a public transit system route lack cellular or GPS signals and offer a user the choice of choosing another route with more reliable wireless signals. Embodiments can determine signal dead-spots where there are no requests coming from mobile networks. In high-usage areas, such as major cities, dead-spots may correspond to areas with no signal and embodiments can build up highly localized coverage maps. In one embodiment, information can be collected where wireless signals are available on public transit systems. Users can rely on the collected information and be able to select options including trip routing to maximize signal availability. For example, a user may be willing to pay a penalty in trip time in order to have a 30 signal available for the entire trip. Real-time location data for a user can be used to convert a statically planned trip (e.g., origin/path/destination) to a precise list of concrete vehicles, times, or both associated with the trip.
- Scheduled information can be matched with real-time data, and can provide updates in the form of time increments to a schedule on a per-trip basis. Real-time data can include service alerts, schedule updates, location information (e.g., users and transit systems), passenger loads, video camera feeds, user GPS information, and other data. Raw data can be made available to websites and other data distributors. Embodiments can provide integration for otherwise loosely connected internal systems at an agency, and compensate when the relation of actual traffic versus scheduled traffic degrades over time.
- The following table is an example of a first trip joining scenario:
-
Time Marcus's Trip Phil's Trip Any time Searches for a trip from A before trip to B and decides on a route using public transit Any time Sends itinerary to Phil Receives itinerary from at/before trip Marcus 11:57 Gets on Bus 94 from Phil's phone knows that Hallenbad Oerlikon. Marcus has started the trip and so calculates the actual trips Marcus will be on from the itinerary and the information we have on schedules and current time. 12:00 Arrives at Bahnhof Oerlikon 12:04 Phil is alerted that he should leave the office in 5 minutes in order to catch the same train as Marcus 12:07 Takes the S16 from Bahnhof Oerlikon towards Bahnhof Tiefenbrunnen. 12:09 Phil is alerted that he should leave the office now in order to catch the same train as Marcus. He leaves the office. 12:15 Passes through Zurich Gets on the S16 at Zurich Hauptbahnhof on the train. Huptbahnhof towards Meets Phil on the train. Bahnhof Tiefenbrunnen. Meets Marcus on the train. 12:20 Phil and Marcus arrive Phil and Marcus arrive together at Bahnhof together at Bahnhof Tiefenbrunnen. Tiefenbrunnen. - The following are examples illustrating trip joining, and other features:
- 1. Morning Commute: Marcus lives near Altersheim, Zurich. Route to work:
Bus 140 from Altersheim to Langnau then the S4 from Langnau to Zurich HB. - Marcus gets up and receives an alert on his phone that the bus to the train station is cancelled. Since it is only a short walk to the train, he can just leave a bit earlier and still catch the train.
- Once Marcus arrives at Langnau, he gets on the train. There has been an accident up ahead. Accordingly, he receives an alert that the train is not going to be able to reach Zurich HB. Rather than wait to get close to the destination and be stuck, his phone informs him to exit the train three stops early and take a tram instead.
- Marcus arrives at work on time, despite the cancellations and delays.
- 2. Lunch: Marcus's friend, Phil, calls him about a new restaurant and suggests they meet there for lunch. Phil sends his itinerary to Marcus and he agrees to join Phil on his journey to the restaurant.
- Phil lives in Oerlikon and takes a bus to reach his local train station. As soon as he starts his trip to the restaurant Marcus's phone keeps track of Phil's journey and informs him when to leave the office. Phil changes onto the S6 to reach the restaurant at Bahnhof Tiefenbrunnen. Marcus has live information on when the train will pass Zurich HB, near Marcus's work. Marcus is alerted when to start walking to the station and which train and carriage to take so that Marcus and Phil meet on the train. They arrive at the restaurant together.
- Marcus's phone knows when his first meeting of the afternoon is and alerts him when he needs to take the train back to work. He doesn't waste time waiting at the stop and arrives on time.
- 3. Evening: After work Marcus wants to meet his girlfriend at Zurich HB, ready to go for a concert in Winterthur. His phone warns him that the next train about to arrive is full of people, but there is another one in 10 minutes that should be quieter. Since they are not in a rush and would enjoy a more comfortable ride, they wait for the next train, where there are plenty of seats. Once they arrive in Winterthur, they take the bus to the concert. Since neither of them are familiar with the buses there, they panic and think they have taken the bus in the wrong direction, but fortunately Marcus can check his phone and determine which bus he is on from the location. Marcus can confirm they took the right one.
- After enjoying the concert they head back to Zurich. It starts raining, so Marcus's phone directs them to a bus stop with a shelter nearby. Both of them are tired after a long day and fall asleep on the train. Fortunately, Marcus's phone knows when they are about to reach the station and an alarm sounds to wake them up.
- The Summary and Abstract sections may set forth one or more but not all exemplary embodiments as contemplated by the inventors, and thus, are not intended to limit the present disclosure and the appended claims in any way.
- The present disclosure has been described above with the aid of functional building blocks illustrating the implementation of specified functions and relationships thereof. The boundaries of these functional building blocks have been arbitrarily defined herein for the convenience of the description. Alternate boundaries can be defined so long as the specified functions and relationships thereof are appropriately performed.
- The foregoing description of the specific embodiments will so fully reveal the general nature of the present disclosure that others can, by applying knowledge within the skill of the art, readily modify and/or adapt for various applications such specific embodiments, without undue experimentation, without departing from the general concept of the present disclosure. Therefore, such adaptations and modifications are intended to be within the meaning and range of equivalents of the disclosed embodiments, based on the teaching and guidance presented herein. It is to be understood that the phraseology or terminology herein is for the purpose of description and not of limitation, such that the terminology or phraseology of the present specification is to be interpreted by the skilled artisan in light of the teachings and guidance.
- The breadth and scope of the present disclosure should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
- The claims in the instant application are different than those of the parent application or other related applications. Arguments made in a related application should not be read into the instant application.
Claims (22)
Priority Applications (3)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US13/228,246 US20120239289A1 (en) | 2010-09-09 | 2011-09-08 | Transportation Information Systems and Methods Associated With Generating Multiple User Routes |
EP11824214.8A EP2614483A4 (en) | 2010-09-09 | 2011-09-09 | Transportation information systems and methods |
PCT/US2011/051097 WO2012034083A2 (en) | 2010-09-09 | 2011-09-09 | Transportation information systems and methods |
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US38136110P | 2010-09-09 | 2010-09-09 | |
US13/228,246 US20120239289A1 (en) | 2010-09-09 | 2011-09-08 | Transportation Information Systems and Methods Associated With Generating Multiple User Routes |
Publications (1)
Publication Number | Publication Date |
---|---|
US20120239289A1 true US20120239289A1 (en) | 2012-09-20 |
Family
ID=46796826
Family Applications (4)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/228,225 Active 2032-01-09 US8645050B2 (en) | 2010-09-09 | 2011-09-08 | Transportation information systems and methods associated with degradation modes |
US13/228,246 Abandoned US20120239289A1 (en) | 2010-09-09 | 2011-09-08 | Transportation Information Systems and Methods Associated With Generating Multiple User Routes |
US13/228,199 Abandoned US20120296885A1 (en) | 2010-09-09 | 2011-09-08 | Transportation Information Systems and Methods |
US14/145,370 Active US9552729B2 (en) | 2010-09-09 | 2013-12-31 | Transportation information systems and methods |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/228,225 Active 2032-01-09 US8645050B2 (en) | 2010-09-09 | 2011-09-08 | Transportation information systems and methods associated with degradation modes |
Family Applications After (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US13/228,199 Abandoned US20120296885A1 (en) | 2010-09-09 | 2011-09-08 | Transportation Information Systems and Methods |
US14/145,370 Active US9552729B2 (en) | 2010-09-09 | 2013-12-31 | Transportation information systems and methods |
Country Status (3)
Country | Link |
---|---|
US (4) | US8645050B2 (en) |
EP (1) | EP2614483A4 (en) |
WO (1) | WO2012034083A2 (en) |
Cited By (13)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2015095828A1 (en) * | 2013-12-20 | 2015-06-25 | Urban Engines, Inc. | Transportation system reconstruction |
US9389094B2 (en) * | 2014-09-05 | 2016-07-12 | Paypal, Inc. | Methods and systems for determining routing |
US20170163591A1 (en) * | 2015-12-04 | 2017-06-08 | International Business Machines Corporation | Live events attendance smart transportation and planning |
EP3036507B1 (en) * | 2013-08-19 | 2020-06-17 | TomTom Navigation B.V. | Methods and systems for obtaining a multi-modal route |
US10762462B1 (en) * | 2018-08-07 | 2020-09-01 | Amazon Technologies, Inc. | Sensor-based customer arrival detection |
US10769712B1 (en) * | 2018-07-16 | 2020-09-08 | Amazon Technologies, Inc. | ETA-based item pick-up and fulfillment alternatives |
US10921147B1 (en) | 2018-08-29 | 2021-02-16 | Amazon Technologies, Inc. | Customer and merchant location-based ETA determination |
US11200517B2 (en) | 2016-08-01 | 2021-12-14 | International Business Machines Corporation | Redistribution based on real time presence data |
US11466993B2 (en) * | 2014-05-06 | 2022-10-11 | Uber Technologies, Inc. | Systems and methods for travel planning that calls for at least one transportation vehicle unit |
US11551325B2 (en) | 2015-12-10 | 2023-01-10 | Uber Technologies, Inc. | Travel coordination system implementing pick-up location optimization |
US11582328B2 (en) | 2017-08-11 | 2023-02-14 | Uber Technologies, Inc. | Dynamic scheduling system for planned service requests |
US11669785B2 (en) | 2014-05-06 | 2023-06-06 | Uber Technologies, Inc. | System and methods for verifying that one or more directives that direct transport of a second end user does not conflict with one or more obligations to transport a first end user |
US11674810B2 (en) | 2017-11-05 | 2023-06-13 | Uber Technologies, Inc. | Network computer system to arrange pooled transport services |
Families Citing this family (53)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8645050B2 (en) * | 2010-09-09 | 2014-02-04 | Google Inc. | Transportation information systems and methods associated with degradation modes |
US8911507B1 (en) * | 2011-11-22 | 2014-12-16 | Symantec Corporation | Systems and methods for mitigating mobile device loss |
JP5590266B2 (en) * | 2012-03-08 | 2014-09-17 | オムロン株式会社 | Output device, output system, and program |
US9097535B2 (en) * | 2012-05-09 | 2015-08-04 | Google Inc. | Public transportation journey planning |
MX348162B (en) | 2012-09-07 | 2017-05-31 | Moovit App Global Ltd | Public transportation navigator. |
JP6043161B2 (en) * | 2012-11-13 | 2016-12-14 | 株式会社日立システムズ | Information transmission system, method, and program |
CA2833542C (en) | 2012-11-20 | 2020-06-30 | Accenture Global Services Limited | Situation-aware mobile travel advisory to public transport commuters |
US9286801B2 (en) | 2013-03-06 | 2016-03-15 | International Business Machines Corporation | Leveraging information for use in a traffic prediction scenario |
US9020754B2 (en) * | 2013-03-22 | 2015-04-28 | Here Global B.V. | Vehicle arrival prediction |
US9273970B2 (en) | 2013-05-14 | 2016-03-01 | Google Inc. | Systems and methods for generating a plurality of trip patterns |
US9217647B2 (en) | 2013-05-14 | 2015-12-22 | Google Inc. | Guidebook transit routing |
US8972190B1 (en) * | 2013-05-14 | 2015-03-03 | Google Inc. | Systems and methods for generating transit trips |
US20150046602A1 (en) * | 2013-08-11 | 2015-02-12 | Staccatotrip | Data synchronization systems and methods |
US20150066558A1 (en) * | 2013-08-29 | 2015-03-05 | Thales Canada Inc. | Context aware command and control system |
US9552560B1 (en) * | 2013-12-31 | 2017-01-24 | Google Inc. | Facilitating communication between event attendees based on event starting time |
WO2015162458A1 (en) | 2014-04-24 | 2015-10-29 | Singapore Telecommunications Limited | Knowledge model for personalization and location services |
CA2896404C (en) | 2014-07-08 | 2018-10-30 | The Toronto-Dominion Bank | Systems and methods for providing sensor-based location proximity detection and notification |
EP2975561B1 (en) * | 2014-07-14 | 2023-12-13 | Gerrit Böhm | Capacity prediction for public transport vehicles |
WO2016042357A1 (en) * | 2014-09-16 | 2016-03-24 | Singapore Telecommunications Limited | Predicting human movement behaviors using location services model |
US10572847B2 (en) * | 2014-10-10 | 2020-02-25 | Conduent Business Services, Llc | Dynamic space-time diagram for visualization of transportation schedule adherence |
US10620010B2 (en) * | 2015-02-05 | 2020-04-14 | Moovit App Global Ltd | Public and ordered transportation trip planning |
JP5831917B1 (en) * | 2015-05-01 | 2015-12-09 | コガソフトウェア株式会社 | Notification server, notification method, and notification program |
EP3091498A1 (en) | 2015-05-07 | 2016-11-09 | TrueMotion, Inc. | Motion detection system for transportation mode analysis |
US10158977B2 (en) | 2015-09-17 | 2018-12-18 | Truemotion, Inc. | Systems and methods for detecting and assessing distracted drivers |
CN108292308A (en) * | 2015-11-27 | 2018-07-17 | 宝马股份公司 | It is that user recommends vehicle/passenger's resource according to mobile custom |
CN105512750A (en) * | 2015-11-27 | 2016-04-20 | 清华大学 | Satellite-precipitation-data-based precipitation station network layout method and apparatus |
US10841852B2 (en) | 2015-12-09 | 2020-11-17 | DataSpark, PTE. LTD. | Transportation network monitoring using cellular radio metadata |
US11691565B2 (en) | 2016-01-22 | 2023-07-04 | Cambridge Mobile Telematics Inc. | Systems and methods for sensor-based detection, alerting and modification of driving behaviors |
US20170265040A1 (en) * | 2016-03-08 | 2017-09-14 | Google Inc. | Verification of pickup times in real-time ride-sharing feeds |
US10510006B2 (en) * | 2016-03-09 | 2019-12-17 | Uptake Technologies, Inc. | Handling of predictive models based on asset location |
US10176340B2 (en) | 2016-03-13 | 2019-01-08 | DataSpark, PTE. LTD. | Abstracted graphs from social relationship graph |
US11157520B2 (en) | 2016-03-28 | 2021-10-26 | DataSpark, Pte Ltd. | Uniqueness level for anonymized datasets |
US10337876B2 (en) | 2016-05-10 | 2019-07-02 | Microsoft Technology Licensing, Llc | Constrained-transportation directions |
US10386197B2 (en) | 2016-05-17 | 2019-08-20 | Microsoft Technology Licensing, Llc | Calculating an optimal route based on specified intermediate stops |
US11072339B2 (en) | 2016-06-06 | 2021-07-27 | Truemotion, Inc. | Systems and methods for scoring driving trips |
US11562300B2 (en) | 2016-06-10 | 2023-01-24 | Conduent Business Services, Llc | System and method for optimal automated booking of on-demand transportation in multi-modal journeys |
US10060752B2 (en) | 2016-06-23 | 2018-08-28 | Microsoft Technology Licensing, Llc | Detecting deviation from planned public transit route |
US20180122024A1 (en) * | 2016-11-01 | 2018-05-03 | Mastercard International Incorporated | Systems and Methods for Use in Providing Offers to Consumers Based on Transit Conditions |
US10147325B1 (en) | 2017-02-02 | 2018-12-04 | Wells Fargo Bank, N.A. | Customization of sharing of rides |
AU2017399008A1 (en) | 2017-02-17 | 2019-09-05 | Dataspark Pte, Ltd | Mobility gene for visit data |
US10873832B2 (en) | 2017-02-17 | 2020-12-22 | DataSpark, PTE. LTD. | Mobility gene for trajectory data |
US11418915B2 (en) | 2017-02-17 | 2022-08-16 | DataSpark, PTE. LTD. | Trajectory analysis with mode of transportation analysis |
US10546255B2 (en) * | 2017-05-05 | 2020-01-28 | Conduent Business Services, Llc | Efficient optimization of schedules in a public transportation system |
US10760916B2 (en) * | 2017-06-07 | 2020-09-01 | International Business Machines Corporation | Methods and systems for determining shared routes |
SG10201705159PA (en) * | 2017-06-21 | 2019-01-30 | Mastercard International Inc | Administration Of An Incentive Program Encouraging Public Transport Usage |
CN107424407A (en) * | 2017-08-21 | 2017-12-01 | 江苏萌小明智能科技有限公司 | A kind of vehicle dispatch system and vehicle scheduling scheme generation method |
WO2019203805A1 (en) * | 2018-04-17 | 2019-10-24 | Ford Global Technologies, Llc | Filtering for efficient routing data |
CN112005562B (en) * | 2018-04-23 | 2022-02-01 | 谷歌有限责任公司 | Method, computing system and computer readable medium for determining vehicle congestion using real-time location data |
US11593735B2 (en) | 2019-05-21 | 2023-02-28 | International Business Machines Corporation | Automated and efficient personal transportation vehicle sharing |
CN110750611A (en) * | 2019-10-16 | 2020-02-04 | 上海掌门科技有限公司 | Method and equipment for providing rain sheltering information |
US20210108934A1 (en) * | 2020-12-23 | 2021-04-15 | Deepak Dasalukunte | Collaborative multimodal trip planning |
CN113066304B (en) * | 2021-06-03 | 2021-09-28 | 云上(南昌)大数据运营有限公司 | Traffic capacity configuration system applying urban brain cloud platform |
CN113743541B (en) * | 2021-11-04 | 2022-02-08 | 华中科技大学 | Method for predicting residual life of marine power system bearing based on degradation mode |
Citations (31)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4360875A (en) * | 1981-02-23 | 1982-11-23 | Behnke Robert W | Automated, door-to-door, demand-responsive public transportation system |
US5559707A (en) * | 1994-06-24 | 1996-09-24 | Delorme Publishing Company | Computer aided routing system |
US6253148B1 (en) * | 1997-07-04 | 2001-06-26 | Jean-Claude Decaux | Information system for informing users of a public transport network about waiting times at stops in the network |
US20010056363A1 (en) * | 2000-06-26 | 2001-12-27 | Gantz Donald T. | System for providing ride matching services using e-mail and the internet |
US20020062192A1 (en) * | 2000-11-17 | 2002-05-23 | Koninklijke Philips Electronics N.V. | Method, and related system and apparatus, for providing travel-related information to a mobile communications device |
US6424910B1 (en) * | 2000-11-22 | 2002-07-23 | Navigation Technologies Corp. | Method and system for providing related navigation features for two or more end users |
US20030100993A1 (en) * | 2001-11-27 | 2003-05-29 | Kirshenbaum Evan R. | Automatic gathering and analysis of data on commute paths |
US20030109266A1 (en) * | 2000-02-09 | 2003-06-12 | Moshe Rafiah | Integrated journey planner |
US20030177020A1 (en) * | 2002-03-14 | 2003-09-18 | Fujitsu Limited | Method and apparatus for realizing sharing of taxi, and computer product |
US20040049424A1 (en) * | 2002-06-21 | 2004-03-11 | Murray Thomas A. | System and method for facilitating ridesharing |
US20050033614A1 (en) * | 2003-08-05 | 2005-02-10 | Sabre Inc. | System and method for coordinating travel itineraries |
US6975997B1 (en) * | 1999-07-07 | 2005-12-13 | Honda Giken Kogyo Kabushiki Kaisha | Method for efficient vehicle allocation in vehicle sharing system |
US7027995B2 (en) * | 2001-06-01 | 2006-04-11 | International Business Machines Corporation | Dynamic resource scheduling to optimize location of meeting participants |
US20060155460A1 (en) * | 2005-01-08 | 2006-07-13 | Stephen Raney | Method for GPS carpool rendezvous tracking and personal safety verification |
US7080019B1 (en) * | 2001-03-04 | 2006-07-18 | Ducktrip, Llc | Ride share contact system |
US7082364B2 (en) * | 2003-06-24 | 2006-07-25 | Bellsouth Intellectual Property Corporation | Methods, systems and computer program products for ride matching based on current location information |
US20060276960A1 (en) * | 2003-06-24 | 2006-12-07 | Maria Adamczyk | Methods, systems and computer program products for ride matching based on selection criteria and driver characteristic information |
US20070106468A1 (en) * | 2005-11-07 | 2007-05-10 | France Telecom | Product, service and activity based interactive trip mapping system, method, and computer program product |
US20080054072A1 (en) * | 2005-11-17 | 2008-03-06 | Lalitesh Katragadda | Vehicle information systems and methods |
US7353034B2 (en) * | 2005-04-04 | 2008-04-01 | X One, Inc. | Location sharing and tracking using mobile phones or other wireless devices |
US20080091342A1 (en) * | 2006-10-11 | 2008-04-17 | Jeffrey Assael | System and method for ride matching |
US20100121662A1 (en) * | 2003-06-26 | 2010-05-13 | Becker Ian S | System and Method of Booking Transportation |
US20100274569A1 (en) * | 2009-04-23 | 2010-10-28 | Douglas Reudink | Real-time location sharing |
US7856300B2 (en) * | 2006-11-21 | 2010-12-21 | Aisin Seiki Kabushiki Kaisha | Seat with side support control for vehicle responsive to distance and position in curve roads |
US8090707B1 (en) * | 2005-07-07 | 2012-01-03 | Rearden Commerce Inc. | Chance meeting addition to trip planner or meeting planner |
US8140256B1 (en) * | 2006-08-16 | 2012-03-20 | University Of South Florida | Dynamic ride matching system |
US8145417B1 (en) * | 2008-12-31 | 2012-03-27 | Cellco Partnership | Enabling a first mobile device to navigate to a location associated with a second mobile device |
US8150608B2 (en) * | 2006-09-22 | 2012-04-03 | Rockstar Bidco, LP | Method and apparatus for enabling commuter groups |
US8285570B2 (en) * | 2009-08-28 | 2012-10-09 | Rideamigos Corp. | Matching system for ride reservation platforms |
US20120290652A1 (en) * | 2011-05-13 | 2012-11-15 | Zeljko BOSKOVIC | Arrangement and method for transport sharing |
US20130041941A1 (en) * | 2010-04-09 | 2013-02-14 | Carnegie Mellon University | Crowd-Sourcing of Information for Shared Transportation Vehicles |
Family Cites Families (22)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5400020A (en) * | 1993-05-18 | 1995-03-21 | Global Research Systems, Inc. | Advance notification system and method |
US20020069017A1 (en) * | 1995-08-14 | 2002-06-06 | Schmier Kenneth J. | Public transit vehicle arrival information system |
US7983836B2 (en) * | 1997-10-22 | 2011-07-19 | Intelligent Technologies International, Inc. | Vehicle-traffic control device communication techniques |
US7119696B2 (en) * | 2001-11-19 | 2006-10-10 | Volvo Trucks North America, Inc. | System for ensuring driver competency |
WO2003069576A1 (en) * | 2002-02-14 | 2003-08-21 | Everyday Wireless Llc | Wireless moble vehicle real-time tracking and notification systems and methods related thereto |
US6845316B2 (en) * | 2002-10-14 | 2005-01-18 | Mytrafficnews.Com, Inc. | Distribution of traffic and transit information |
US20040107028A1 (en) * | 2002-12-03 | 2004-06-03 | Catalano Anthony B. | Override protocol system for affording vehicle safety and for preventing hijacking |
US7174153B2 (en) * | 2003-12-23 | 2007-02-06 | Gregory A Ehlers | System and method for providing information to an operator of an emergency response vehicle |
KR20050093210A (en) | 2004-03-18 | 2005-09-23 | 에스케이 텔레콤주식회사 | System for controlling personal schedule management service and method thereof |
KR100617808B1 (en) | 2005-02-22 | 2006-08-28 | 삼성전자주식회사 | System guiding information of public traffic and method thereof |
US8138907B2 (en) * | 2005-08-11 | 2012-03-20 | University Of South Florida | Travel assistant device |
US7920967B1 (en) * | 2005-09-08 | 2011-04-05 | TransLoc, Inc. | Methods and devices for providing route information |
US8229657B2 (en) * | 2006-06-08 | 2012-07-24 | Lg Electronics Inc. | Method and apparatus for providing and using public transportation information |
KR20090042573A (en) | 2007-10-26 | 2009-04-30 | (주)케이티에프테크놀로지스 | Traffic information notification terminal using location information and traffic information providing server and method thereof |
EP2065867B1 (en) * | 2007-11-15 | 2013-08-21 | Vodafone Holding GmbH | Method for providing transport time schedule information, mobile terminal and central processing unit |
EP2217880B1 (en) | 2007-11-24 | 2015-02-18 | Routerank Ltd | Optimized route planning |
US9159238B2 (en) | 2008-10-02 | 2015-10-13 | Microsoft Technology Licensing, LLP | Location-aware selection of public transportation |
US8566016B2 (en) * | 2010-05-13 | 2013-10-22 | Saab Sensis Corporation | Surface hold advisor using critical sections |
US20120023033A1 (en) * | 2010-07-21 | 2012-01-26 | Martin Tomasz | Transport information system |
US8645050B2 (en) * | 2010-09-09 | 2014-02-04 | Google Inc. | Transportation information systems and methods associated with degradation modes |
US8880490B2 (en) * | 2010-09-10 | 2014-11-04 | Google Inc. | Correlating transportation data |
US9267806B2 (en) * | 2011-08-29 | 2016-02-23 | Bayerische Motoren Werke Aktiengesellschaft | System and method for automatically receiving geo-relevant information in a vehicle |
-
2011
- 2011-09-08 US US13/228,225 patent/US8645050B2/en active Active
- 2011-09-08 US US13/228,246 patent/US20120239289A1/en not_active Abandoned
- 2011-09-08 US US13/228,199 patent/US20120296885A1/en not_active Abandoned
- 2011-09-09 WO PCT/US2011/051097 patent/WO2012034083A2/en active Application Filing
- 2011-09-09 EP EP11824214.8A patent/EP2614483A4/en not_active Withdrawn
-
2013
- 2013-12-31 US US14/145,370 patent/US9552729B2/en active Active
Patent Citations (33)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4360875A (en) * | 1981-02-23 | 1982-11-23 | Behnke Robert W | Automated, door-to-door, demand-responsive public transportation system |
US5559707A (en) * | 1994-06-24 | 1996-09-24 | Delorme Publishing Company | Computer aided routing system |
US6253148B1 (en) * | 1997-07-04 | 2001-06-26 | Jean-Claude Decaux | Information system for informing users of a public transport network about waiting times at stops in the network |
US6975997B1 (en) * | 1999-07-07 | 2005-12-13 | Honda Giken Kogyo Kabushiki Kaisha | Method for efficient vehicle allocation in vehicle sharing system |
US20030109266A1 (en) * | 2000-02-09 | 2003-06-12 | Moshe Rafiah | Integrated journey planner |
US20010056363A1 (en) * | 2000-06-26 | 2001-12-27 | Gantz Donald T. | System for providing ride matching services using e-mail and the internet |
US20020062192A1 (en) * | 2000-11-17 | 2002-05-23 | Koninklijke Philips Electronics N.V. | Method, and related system and apparatus, for providing travel-related information to a mobile communications device |
US6424910B1 (en) * | 2000-11-22 | 2002-07-23 | Navigation Technologies Corp. | Method and system for providing related navigation features for two or more end users |
US7080019B1 (en) * | 2001-03-04 | 2006-07-18 | Ducktrip, Llc | Ride share contact system |
US7027995B2 (en) * | 2001-06-01 | 2006-04-11 | International Business Machines Corporation | Dynamic resource scheduling to optimize location of meeting participants |
US20030100993A1 (en) * | 2001-11-27 | 2003-05-29 | Kirshenbaum Evan R. | Automatic gathering and analysis of data on commute paths |
US20030177020A1 (en) * | 2002-03-14 | 2003-09-18 | Fujitsu Limited | Method and apparatus for realizing sharing of taxi, and computer product |
US20040049424A1 (en) * | 2002-06-21 | 2004-03-11 | Murray Thomas A. | System and method for facilitating ridesharing |
US20060276960A1 (en) * | 2003-06-24 | 2006-12-07 | Maria Adamczyk | Methods, systems and computer program products for ride matching based on selection criteria and driver characteristic information |
US7082364B2 (en) * | 2003-06-24 | 2006-07-25 | Bellsouth Intellectual Property Corporation | Methods, systems and computer program products for ride matching based on current location information |
US20100121662A1 (en) * | 2003-06-26 | 2010-05-13 | Becker Ian S | System and Method of Booking Transportation |
US20050033614A1 (en) * | 2003-08-05 | 2005-02-10 | Sabre Inc. | System and method for coordinating travel itineraries |
US7136747B2 (en) * | 2005-01-08 | 2006-11-14 | Stephen Raney | Method for GPS carpool rendezvous tracking and personal safety verification |
US20060155460A1 (en) * | 2005-01-08 | 2006-07-13 | Stephen Raney | Method for GPS carpool rendezvous tracking and personal safety verification |
US7353034B2 (en) * | 2005-04-04 | 2008-04-01 | X One, Inc. | Location sharing and tracking using mobile phones or other wireless devices |
US8090707B1 (en) * | 2005-07-07 | 2012-01-03 | Rearden Commerce Inc. | Chance meeting addition to trip planner or meeting planner |
US20070106468A1 (en) * | 2005-11-07 | 2007-05-10 | France Telecom | Product, service and activity based interactive trip mapping system, method, and computer program product |
US20080054072A1 (en) * | 2005-11-17 | 2008-03-06 | Lalitesh Katragadda | Vehicle information systems and methods |
US8140256B1 (en) * | 2006-08-16 | 2012-03-20 | University Of South Florida | Dynamic ride matching system |
US8150608B2 (en) * | 2006-09-22 | 2012-04-03 | Rockstar Bidco, LP | Method and apparatus for enabling commuter groups |
US8340890B1 (en) * | 2006-09-22 | 2012-12-25 | Rockstar Bidco, LP | Method and apparatus for enabling commuter groups |
US20080091342A1 (en) * | 2006-10-11 | 2008-04-17 | Jeffrey Assael | System and method for ride matching |
US7856300B2 (en) * | 2006-11-21 | 2010-12-21 | Aisin Seiki Kabushiki Kaisha | Seat with side support control for vehicle responsive to distance and position in curve roads |
US8145417B1 (en) * | 2008-12-31 | 2012-03-27 | Cellco Partnership | Enabling a first mobile device to navigate to a location associated with a second mobile device |
US20100274569A1 (en) * | 2009-04-23 | 2010-10-28 | Douglas Reudink | Real-time location sharing |
US8285570B2 (en) * | 2009-08-28 | 2012-10-09 | Rideamigos Corp. | Matching system for ride reservation platforms |
US20130041941A1 (en) * | 2010-04-09 | 2013-02-14 | Carnegie Mellon University | Crowd-Sourcing of Information for Shared Transportation Vehicles |
US20120290652A1 (en) * | 2011-05-13 | 2012-11-15 | Zeljko BOSKOVIC | Arrangement and method for transport sharing |
Non-Patent Citations (3)
Title |
---|
Garcia, Ander, et al. "Personalized tourist route generation." Current Trends in Web Engineering. Springer Berlin Heidelberg, 2010. 486-497. * |
Gidofalvi, Gyözö, and Torben Bach Pedersen. "Cab-sharing: An effective, door-to-door, on-demand transportation service." Proceedings of the 6th European Congress on Intelligent Transport Systems and Services, 18-20 Jun, 2007, Aalborg, Denmark. ERTICO, 2007. * |
Gidófalvi, Gyözö, Gergely Herenyi, and Torben Bach Pedersen. "Instant Social Ride-Sharing." Proceedings of the Fifteenth World Congress on Intelligent Transport Systems, Nov 16-20, 2008, New York, NY, USA. Intelligent Transportation Society of America, 2008. * |
Cited By (17)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
EP3036507B1 (en) * | 2013-08-19 | 2020-06-17 | TomTom Navigation B.V. | Methods and systems for obtaining a multi-modal route |
US9915542B2 (en) | 2013-12-20 | 2018-03-13 | Google Llc | Transportation system reconstruction |
WO2015095828A1 (en) * | 2013-12-20 | 2015-06-25 | Urban Engines, Inc. | Transportation system reconstruction |
US11669785B2 (en) | 2014-05-06 | 2023-06-06 | Uber Technologies, Inc. | System and methods for verifying that one or more directives that direct transport of a second end user does not conflict with one or more obligations to transport a first end user |
US11466993B2 (en) * | 2014-05-06 | 2022-10-11 | Uber Technologies, Inc. | Systems and methods for travel planning that calls for at least one transportation vehicle unit |
US10788328B2 (en) | 2014-09-05 | 2020-09-29 | Paypal, Inc. | Methods and systems for determining routing |
US9389094B2 (en) * | 2014-09-05 | 2016-07-12 | Paypal, Inc. | Methods and systems for determining routing |
US9998420B2 (en) * | 2015-12-04 | 2018-06-12 | International Business Machines Corporation | Live events attendance smart transportation and planning |
US20170163591A1 (en) * | 2015-12-04 | 2017-06-08 | International Business Machines Corporation | Live events attendance smart transportation and planning |
US11551325B2 (en) | 2015-12-10 | 2023-01-10 | Uber Technologies, Inc. | Travel coordination system implementing pick-up location optimization |
US11200517B2 (en) | 2016-08-01 | 2021-12-14 | International Business Machines Corporation | Redistribution based on real time presence data |
US11582328B2 (en) | 2017-08-11 | 2023-02-14 | Uber Technologies, Inc. | Dynamic scheduling system for planned service requests |
US11924308B2 (en) | 2017-08-11 | 2024-03-05 | Uber Technologies, Inc. | Dynamic scheduling system for planned service requests |
US11674810B2 (en) | 2017-11-05 | 2023-06-13 | Uber Technologies, Inc. | Network computer system to arrange pooled transport services |
US10769712B1 (en) * | 2018-07-16 | 2020-09-08 | Amazon Technologies, Inc. | ETA-based item pick-up and fulfillment alternatives |
US10762462B1 (en) * | 2018-08-07 | 2020-09-01 | Amazon Technologies, Inc. | Sensor-based customer arrival detection |
US10921147B1 (en) | 2018-08-29 | 2021-02-16 | Amazon Technologies, Inc. | Customer and merchant location-based ETA determination |
Also Published As
Publication number | Publication date |
---|---|
US20140111358A1 (en) | 2014-04-24 |
WO2012034083A8 (en) | 2012-04-19 |
US20120296885A1 (en) | 2012-11-22 |
US9552729B2 (en) | 2017-01-24 |
WO2012034083A3 (en) | 2012-08-23 |
EP2614483A4 (en) | 2014-05-14 |
EP2614483A2 (en) | 2013-07-17 |
US8645050B2 (en) | 2014-02-04 |
WO2012034083A2 (en) | 2012-03-15 |
US20120232776A1 (en) | 2012-09-13 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US9552729B2 (en) | Transportation information systems and methods | |
US11908034B2 (en) | Computer system arranging transport services for users based on the estimated time of arrival information | |
US9373259B2 (en) | Situation-aware mobile travel advisory to public transport commuters | |
US11118924B2 (en) | Method and system for predicting traffic conditions | |
US9024752B2 (en) | Traveler hurry status monitor | |
US9602961B2 (en) | Monitoring method and system | |
US20180087911A1 (en) | Time regulated navigation of travel through an airport | |
JP6058139B2 (en) | Public transport navigator | |
US20140207375A1 (en) | Distribution of location and movement information of meeting participants | |
JP6140312B2 (en) | Optimal route transmission method including a plurality of waypoints and apparatus therefor | |
US9273970B2 (en) | Systems and methods for generating a plurality of trip patterns | |
JP2008102046A (en) | Navigation system, route search server, and terminal device | |
US20190303806A1 (en) | Boarding management system, boarding management method, and system | |
US9494431B2 (en) | Method for acquiring or providing update information for route to third party and apparatus for same | |
CA2864007C (en) | Traveler hurry status monitor | |
JP7075187B2 (en) | Information processing terminal, information processing method and program | |
JP2022105212A (en) | Information processing terminal, information processing method and program | |
JP2022139230A (en) | Information processing device | |
EP2648140A1 (en) | Traveler hurry status monitor |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: GOOGLE INC., CALIFORNIA Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:GONTMAKER, ALEX;BREWIN, FREDERICK PETER;BEN HAIM, NOAM;SIGNING DATES FROM 20110907 TO 20110928;REEL/FRAME:027211/0152 |
|
AS | Assignment |
Owner name: GOOGLE INC., CALIFORNIA Free format text: CORRECTIVE ASSIGNMENT TO CORRECT THE LAST NAME OF THE 1ST INVENTOR FROM GONTMAKER PREVIOUSLY RECORDED ON REEL 027211 FRAME 0152. ASSIGNOR(S) HEREBY CONFIRMS THE CORRECT NAME OF THE 1ST INVENTOR IS GONTMAKHER;ASSIGNORS:GONTMAKHER, ALEX;BREWIN, FREDERICK PETER;BEN HAIM, NOAM;SIGNING DATES FROM 20110907 TO 20110928;REEL/FRAME:027399/0368 |
|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |
|
AS | Assignment |
Owner name: GOOGLE LLC, CALIFORNIA Free format text: CHANGE OF NAME;ASSIGNOR:GOOGLE INC.;REEL/FRAME:044142/0357 Effective date: 20170929 |