GB2586929A - Sensor fusion for transit applications - Google Patents

Sensor fusion for transit applications Download PDF

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Publication number
GB2586929A
GB2586929A GB2016577.5A GB202016577A GB2586929A GB 2586929 A GB2586929 A GB 2586929A GB 202016577 A GB202016577 A GB 202016577A GB 2586929 A GB2586929 A GB 2586929A
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United Kingdom
Prior art keywords
transit
data
station
vehicle
specific
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.)
Withdrawn
Application number
GB2016577.5A
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GB202016577D0 (en
Inventor
Bergdale Micah
Donovan Edward
O'haire Michael
Ihm Nicholas
Smith Ross
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Bytemark Inc
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Bytemark Inc
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Publication date
Priority claimed from US15/927,305 external-priority patent/US20180211188A1/en
Application filed by Bytemark Inc filed Critical Bytemark Inc
Publication of GB202016577D0 publication Critical patent/GB202016577D0/en
Publication of GB2586929A publication Critical patent/GB2586929A/en
Withdrawn legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/02—Reservations, e.g. for tickets, services or events
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/63—Location-dependent; Proximity-dependent
    • 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
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/40—Business processes related to the transportation industry
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07B—TICKET-ISSUING APPARATUS; FARE-REGISTERING APPARATUS; FRANKING APPARATUS
    • G07B15/00—Arrangements or apparatus for collecting fares, tolls or entrance fees at one or more control points
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/06—Authentication
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/021—Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
    • 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
    • G06Q2240/00—Transportation facility access, e.g. fares, tolls or parking
    • G—PHYSICS
    • G07—CHECKING-DEVICES
    • G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
    • G07C9/00—Individual registration on entry or exit
    • G07C9/20—Individual registration on entry or exit involving the use of a pass
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W12/00—Security arrangements; Authentication; Protecting privacy or anonymity
    • H04W12/60—Context-dependent security
    • H04W12/63—Location-dependent; Proximity-dependent
    • H04W12/64—Location-dependent; Proximity-dependent using geofenced areas
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/80—Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication

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  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Computer Security & Cryptography (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Signal Processing (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Economics (AREA)
  • Human Resources & Organizations (AREA)
  • Marketing (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Strategic Management (AREA)
  • Quality & Reliability (AREA)
  • Operations Research (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Finance (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Devices For Checking Fares Or Tickets At Control Points (AREA)
  • Mobile Radio Communication Systems (AREA)

Abstract

A system and method in which various sensors collect and/or generate data that are analyzed to provide automated transit features. In the automatic capacity management feature, a transit operator is alerted of potential capacity issues in advance to enable the operator to handle the situation before a station or a vehicle reaches its capacity limit. The automatic trip planning feature allows a passenger to dynamically plan the fastest route to a destination according to real time data and historical data trends. The automatic fraud detection feature alerts a fare inspector to a ticket fraud or other fraudulent activity at a specific transit station or on a specific transit vehicle. The automatic vehicle routing feature dynamically routes autonomous transit vehicles to stations, notifies transit vehicle drivers to stop at a particular station, and/or notifies transit operators to route a vehicle to a particular station based on current and historical demand from passengers.

Claims (20)

WHAT IS CLAIMED IS:
1. A method in a control unit associated with a transit system, the method comprising: receiving sensor data from a plurality of sensors in the transit system, wherein the control unit is communicatively coupled with the sensors, and wherein each sensor-specific portion of the sensor data includes at least one of the following: a sensor-specific passenger data defining one or more attributes of a user availing a transit service in the transit system, a sensor-specific vehicle data defining one or more attributes of a transit vehicle associated with the transit service, and a sensor-specific station data defining one or more attributes of a transit station associated with the transit service; combining received sensor-specific passenger data to generate a system-specific passenger data, received sensor-specific vehicle data to generate a system-specific vehicle data, and received sensor-specific station data to generate a system-specific station data; analyzing the system-specific passenger data, the system-specific vehicle data, and the system-specific station data; and performing at least one of the following based on the analysis of the system-specific passenger data, the system-specific vehicle data, and the system-specific station data: facilitating management of passenger-handling capacity of at least one of the transit station and the transit vehicle, dynamically planning a trip for the user availing the transit service, facilitating detection of fraud for the transit service, and dynamically planning a route for the transit vehicle.
2. The method of claim 1 , wherein the plurality of sensors includes two or more of the following: a Global Positioning System (GPS) sensor; a Bluetooth Low Energy (BLE) beacon sensor; a positioning unit including a BLE receiver and a positioning engine for determining position of a mobile device carried by the user; an object detection camera; a fare payment monitor; and a location tracker on the transit vehicle.
3. The method of claim 1 , wherein the sensor-specific passenger data includes one or more of the following attributes: a unique ID assigned to the user; a geographical location of the user; an Estimated Time of Arrival (ETA) of the user at a first transit station for boarding the transit vehicle; a first identifier for the first transit station; a second identifier for a second transit station where the user is scheduled to disembark the transit vehicle; a first flag for indicating that the user is in proximity of the first transit station; a second flag for indicating that the user is inside the first transit station; and a third flag for indicating that the user is inside the transit vehicle.
4. The method of claim 1 , wherein the sensor-specific vehicle data includes one or more of the following attributes: a unique ID assigned to the transit vehicle; a first value indicating a maximum number of passengers the transit vehicle can carry; a second value indicating a number of passengers currently on the transit vehicle; identifiers for transit stations where the transit vehicle stops along the route; a transit station-specific Estimated Time of Arrival (ETA) of the transit vehicle for the transit stations along the route; a geographical location of the transit vehicle; and a flag for indicating that the transit vehicle is currently at full capacity.
5. The method of claim 1 , wherein the sensor-specific station data includes one or more of the following attributes: a unique ID assigned to the transit station; a first value indicating a maximum number of passengers that can be present at the transit station at a given time; a second value indicating a number of passengers currently present at the transit station; and a third value indicating a number of passengers on way to the transit station.
6. The method of claim 1 , wherein said combining includes: establishing a first plurality of data fields in a database, wherein each data field in the first plurality of data fields corresponds to a distinct attribute of the user; establishing a second plurality of data fields in the database, wherein each data field in the second plurality of data fields corresponds to a distinct attribute of the transit vehicle; establishing a third plurality of data fields in the database, wherein each data field in the third plurality of data fields corresponds to a distinct attribute of the transit station; populating a first data field in the first plurality of data fields with the sensor-specific passenger data corresponding to a user attribute associated with the first data field being populated; populating a second data field in the second plurality of data fields with the sensor- specific vehicle data corresponding to a transit vehicle attribute associated with the second data field being populated; and populating a third data field in the third plurality of data fields with the sensor-specific station data corresponding to a transit station attribute associated with the third data field being populated.
7. The method of claim 1 , wherein said analyzing includes performing the following data point determinations: using the system-specific passenger data to determine a first number of users approaching the transit station, a second number of users currently present at the transit station, a third number of users to be embarking the transit vehicle, a fourth number of users to be disembarking the transit vehicle, and an estimated time of arrival for each user approaching the transit station, using the system-specific vehicle data to determine a fifth number of users currently present inside the transit vehicle, an estimated time of arrival of the transit vehicle at the transit station, and passenger-handling capacity of the transit vehicle, and using the system-specific station data to determine a sixth number of users currently present at the transit station and passenger-handling capacity of the transit station; and wherein facilitating management of passenger-handling capacity includes performing at least one of the following based on the data point determinations: determining that the transit station is currently operating at capacity, predicting when the transit station will be operating at capacity, determining that the transit vehicle is currently operating at capacity, and predicting when the transit vehicle will be operating at capacity.
8. The method of claim 1 , wherein dynamically planning a trip includes performing at least one of the following: recommending a different transit vehicle to the user; recommending a different transit station to the user; and recommending a different transit service to the user.
9. The method of claim 1 , wherein said analyzing includes performing the following: determining a first number of users who have actually paid for the transit service, determining a second number of users who are present in an area of the transit station designated for users who have paid for the transit service, and determining a third number of users who are inside the transit vehicle; and wherein facilitating detection of fraud includes performing one of the following: comparing the first, the second, and the third numbers to indicate that a fare fraud is detected for the transit vehicle, and comparing the first, the second, and the third numbers to indicate that a fare fraud is detected at the transit station.
10. The method of claim 1 , wherein said analyzing includes performing the following data point determinations: using the system-specific passenger data to determine a first number of users approaching the transit station, a second number of users currently present at the transit station, a third number of users to be embarking the transit vehicle, and an estimated time of arrival for each user approaching the transit station, using the system-specific vehicle data to determine a fifth number of users currently present inside the transit vehicle, a current location of the transit vehicle, an estimated time of arrival of the transit vehicle at the transit station, and passenger-handling capacity of the transit vehicle, and using the system-specific station data to determine a sixth number of users currently present at the transit station and passenger-handling capacity of the transit station; and wherein dynamically planning a route includes performing at least one of the following based on the data point determinations: recommending a different transit station for the transit vehicle, recommending a different transit vehicle to be sent to the transit station, and recommending a modified time of arrival of the transit vehicle at the transit station.
11. A control unit associated with a transit system, wherein the control unit comprises: an interface unit operable to perform the following: receive sensor data from a plurality of sensors in the transit system, wherein the control unit is communicatively coupled with the sensors, and wherein each sensor- specific portion of the sensor data includes at least one of the following: a sensor-specific passenger data defining one or more attributes of a user availing a transit service in the transit system, a sensor-specific vehicle data defining one or more attributes of a transit vehicle associated with the transit service, and a sensor-specific station data defining one or more attributes of a transit station associated with the transit service; a memory for storing program instructions and the sensor data received by the interface unit; and a processor coupled to the interface unit and to the memory, wherein the processor is operable to execute the program instructions, which, when executed by the processor, cause the control unit to: combine received sensor-specific passenger data to generate a system- specific passenger data, received sensor-specific vehicle data to generate a system-specific vehicle data, and received sensor-specific station data to generate a system-specific station data, analyze the system-specific passenger data, the system-specific vehicle data, and the system-specific station data, and perform at least one of the following based on the analysis of the system- specific passenger data, the system-specific vehicle data, and the system-specific station data: facilitate management of passenger-handling capacity of at least one of the transit station and the transit vehicle, dynamically plan a trip for the user availing the transit service, facilitate detection of fraud for the transit service, and dynamically plan a route for the transit vehicle.
12. The control unit of claim 1 1 , wherein the program instructions, when executed by the processor, cause the control unit to carry out the following data point determinations: use the system-specific passenger data to determine a first number of users approaching the transit station, a second number of users currently present at the transit station, a third number of users to be embarking the transit vehicle, a fourth number of users to be disembarking the transit vehicle, and an estimated time of arrival for each user approaching the transit station; use the system-specific vehicle data to determine a fifth number of users currently present inside the transit vehicle, an estimated time of arrival of the transit vehicle at the transit station, and passenger-handling capacity of the transit vehicle; use the system-specific station data to determine a sixth number of users currently present at the transit station and passenger-handling capacity of the transit station; and perform at least one of the following based on the data point determinations to facilitate management of passenger-handling capacity: determine that the transit station is currently operating at capacity, predict when the transit station will be operating at capacity, determine that the transit vehicle is currently operating at capacity, and predict when the transit vehicle will be operating at capacity.
13. The control unit of claim 1 1 , wherein the program instructions, when executed by the processor, cause the control unit to perform at least one of the following to dynamically plan a trip for the user: recommend a different transit vehicle to the user; recommend a different transit station to the user; and recommend a different transit service to the user.
14. The control unit of claim 1 1 , wherein the program instructions, when executed by the processor, cause the control unit to: determine a first number of users who have actually paid for the transit service; determine a second number of users who are present in an area of the transit station designated for users who have paid for the transit service; determine a third number of users who are inside the transit vehicle; and perform one of the following to facilitate detection of fraud: compare the first, the second, and the third numbers to indicate that a fare fraud is detected for the transit vehicle, and compare the first, the second, and the third numbers to indicate that a fare fraud is detected at the transit station.
15. The control unit of claim 11 , wherein the program instructions, when executed by the processor, cause the control unit to carry out the following data point determinations: use the system-specific passenger data to determine a first number of users approaching the transit station, a second number of users currently present at the transit station, a third number of users to be embarking the transit vehicle, and an estimated time of arrival for each user approaching the transit station; use the system-specific vehicle data to determine a fifth number of users currently present inside the transit vehicle, a current location of the transit vehicle, an estimated time of arrival of the transit vehicle at the transit station, and passenger-handling capacity of the transit vehicle; use the system-specific station data to determine a sixth number of users currently present at the transit station and passenger-handling capacity of the transit station; and perform at least one of the following based on the data point determinations to dynamically plan a route for the transit vehicle: recommend a different transit station for the transit vehicle, recommend a different transit vehicle to be sent to the transit station, and recommend a modified time of arrival of the transit vehicle at the transit station.
16. The control unit of claim 11 , wherein the sensor-specific passenger data includes one or more of the following attributes: a unique ID assigned to the user; a geographical location of the user; an Estimated Time of Arrival (ETA) of the user at a first transit station for boarding the transit vehicle; a first identifier for the first transit station; a second identifier for a second transit station where the user is scheduled to disembark the transit vehicle; a first flag for indicating that the user is in proximity of the first transit station; a second flag for indicating that the user is inside the first transit station; and a third flag for indicating that the user is inside the transit vehicle.
17. The control unit of claim 11 , wherein the sensor-specific vehicle data includes one or more of the following attributes: a unique ID assigned to the transit vehicle; a first value indicating a maximum number of passengers the transit vehicle can carry; a second value indicating a number of passengers currently on the transit vehicle; identifiers for transit stations where the transit vehicle stops along the route; a transit station-specific Estimated Time of Arrival (ETA) of the transit vehicle for the transit stations along the route; a geographical location of the transit vehicle; and a flag for indicating that the transit vehicle is currently at full capacity.
18. The control unit of claim 11 , wherein the sensor-specific station data includes one or more of the following attributes: a unique ID assigned to the transit station; a first value indicating a maximum number of passengers that can be present at the transit station at a given time; a second value indicating a number of passengers currently present at the transit station; and a third value indicating a number of passengers on way to the transit station.
19. A transit system comprising: a plurality of sensors to provide sensor data; and a control unit that is communicatively coupled with the sensors and adapted to implement a method comprising: receiving the sensor data from the plurality of sensors, wherein each sensor- specific portion of the sensor data includes at least one of the following: a sensor-specific passenger data defining one or more attributes of a user availing a transit service in the transit system, a sensor-specific vehicle data defining one or more attributes of a transit vehicle associated with the transit service, and a sensor-specific station data defining one or more attributes of a transit station associated with the transit service; combining received sensor-specific passenger data to generate a system- specific passenger data, received sensor-specific vehicle data to generate a system-specific vehicle data, and received sensor-specific station data to generate a system-specific station data; analyzing the system-specific passenger data, the system-specific vehicle data, and the system-specific station data; and performing at least one of the following based on the analysis of the system- specific passenger data, the system-specific vehicle data, and the system-specific station data: facilitating management of passenger-handling capacity of at least one of the transit station and the transit vehicle, dynamically planning a trip for the user availing the transit service, facilitating detection of fraud for the transit service, and dynamically planning a route for the transit vehicle.
20. The system of claim 19, wherein the plurality of sensors includes two or more of the following: a Global Positioning System (GPS) sensor; a Bluetooth Low Energy (BLE) beacon sensor; a positioning unit including a BLE receiver and a positioning engine for determining position of a mobile device carried by the user; an object detection camera; a fare payment monitor; and a location tracker on the transit vehicle.
GB2016577.5A 2018-03-21 2018-10-22 Sensor fusion for transit applications Withdrawn GB2586929A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US15/927,305 US20180211188A1 (en) 2015-08-17 2018-03-21 Methods and systems for hands-free fare validation and gateless transit
PCT/US2018/056829 WO2019182646A1 (en) 2018-03-21 2018-10-22 Sensor fusion for transit applications

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GB202016577D0 GB202016577D0 (en) 2020-12-02
GB2586929A true GB2586929A (en) 2021-03-10

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GB2016588.2A Active GB2587509B (en) 2018-03-21 2018-05-08 Methods and systems for hands-free fare validation and gateless transit
GB2016577.5A Withdrawn GB2586929A (en) 2018-03-21 2018-10-22 Sensor fusion for transit applications

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CA (2) CA3094302A1 (en)
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CN111769885B (en) 2020-06-29 2022-02-11 北京小米移动软件有限公司 Ultrasonic data transmission method, device, system, terminal equipment and medium
CN112530154B (en) * 2020-11-13 2022-07-01 北京小米移动软件有限公司 Information transmission method, information transmission device, and electronic device
SI26249A (en) * 2021-09-07 2023-03-31 Margento R&D D.O.O Smart system for automatic validation and notification
CN115018511B (en) * 2022-03-04 2024-07-09 浪潮工业互联网股份有限公司 Anti-counterfeiting method, equipment and medium for agricultural machinery

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5797330A (en) * 1996-07-31 1998-08-25 Li; Zhengzhong Mass transit system
US20010037174A1 (en) * 2000-04-04 2001-11-01 Dickerson Stephen L. Communications and computing based urban transit system
RU94931U1 (en) * 2009-12-28 2010-06-10 Общество с ограниченной ответственностью Научно-Производственное Предприятие "Циркон Сервис" SYSTEM OF ACCOUNTING THE ACTUAL NUMBER OF PASSENGERS IN A PASSENGER CAR
US20120245769A1 (en) * 2009-12-03 2012-09-27 Creissels Technologies Aerial tramway with monitoring of the number of passengers allowable in the tram car
US20160055605A1 (en) * 2014-08-21 2016-02-25 Uber Technologies, Inc. Arranging a transport service for a user based on the estimated time of arrival of the user
US20180068315A1 (en) * 2011-03-11 2018-03-08 Bytemark, Inc. Short range wireless translation methods and systems for hands-free fare validation

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8457354B1 (en) * 2010-07-09 2013-06-04 Target Brands, Inc. Movement timestamping and analytics
US9408147B2 (en) * 2012-09-24 2016-08-02 Broadcom Corporation Enhanced rate physical layer for Bluetooth™ low energy
WO2016105322A1 (en) * 2014-12-25 2016-06-30 Echostar Ukraine, L.L.C. Simultaneously viewing multiple camera angles
CA2989051C (en) * 2015-08-17 2024-05-28 Bytemark, Inc. Short range wireless translation methods and systems for hands-free fare validation

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5797330A (en) * 1996-07-31 1998-08-25 Li; Zhengzhong Mass transit system
US20010037174A1 (en) * 2000-04-04 2001-11-01 Dickerson Stephen L. Communications and computing based urban transit system
US20120245769A1 (en) * 2009-12-03 2012-09-27 Creissels Technologies Aerial tramway with monitoring of the number of passengers allowable in the tram car
RU94931U1 (en) * 2009-12-28 2010-06-10 Общество с ограниченной ответственностью Научно-Производственное Предприятие "Циркон Сервис" SYSTEM OF ACCOUNTING THE ACTUAL NUMBER OF PASSENGERS IN A PASSENGER CAR
US20180068315A1 (en) * 2011-03-11 2018-03-08 Bytemark, Inc. Short range wireless translation methods and systems for hands-free fare validation
US20160055605A1 (en) * 2014-08-21 2016-02-25 Uber Technologies, Inc. Arranging a transport service for a user based on the estimated time of arrival of the user

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Publication number Publication date
AU2018414542A1 (en) 2020-10-08
AU2023204670A1 (en) 2023-08-03
GB2587509B (en) 2023-01-11
GB202016588D0 (en) 2020-12-02
AU2023204670B2 (en) 2024-08-15
AU2023203911A1 (en) 2023-07-13
GB2587509A (en) 2021-03-31
WO2019182646A1 (en) 2019-09-26
WO2019182625A1 (en) 2019-09-26
GB202016577D0 (en) 2020-12-02
AU2018414521A1 (en) 2020-10-08
CA3094302A1 (en) 2019-09-26
CA3105335A1 (en) 2019-09-26

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