The Garba Tulla HTSP Project: Increasing Contraceptive Uptake in Northern Kenya
Real-time data and smart phone technology increasing the uptake of public transport
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Transcript of Real-time data and smart phone technology increasing the uptake of public transport
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Real-time data & mobileIncreasing the uptake of public transport
Rupert HansonDeveloper, AppJourney@rpy
NSW Transport Infrastructure SummitAugust 2013
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Outline
•The case for real-time data
•How real-time data works
•Emergence and challenges
• Implications
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The case for real-time data
• Service reliability is difficult
• Agencies need to communicate with customers in a timely, relevant way
• Fulfil customer information needs
• Increase customer satisfaction
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Top 4 customer information needs
• Departure, arrival times
• Trackwork, station closures
• Delays, cancellations
• Wayfinding
Source: Stancombe Research & Planning, December 2011
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Customer information needs
“Obtaining train delay information is:
• Most difficult when you are on the train and before the journey
• Acceptable when you are at the station
• Not relevant when you arrive at the destination”
Source: Stancombe Research & Planning, December 2011
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Voice of the customer
“If the train is 15 minutes late, tell me it’s going to be 15
minutes late”
Source: Customer interviews conducted by PwC, October 2012
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Customer experience
• 80% of transit users indicated uncertainty as to the arrival time of their service caused frustration
• Transit users overestimate wait time by 24-30%
Source: A Stated Preference Analysis of Real-Time Public Transit Stop Information, Journal of Public Transportation, Vol. 12, No. 3, 2009
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Why open data?
• Technology landscape changing rapidly
• Public can contribute services that are cost/time prohibitive for public sector
• Developers want to innovate
• Ensure a single, quality source of truth
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How does real-time data work?
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How does real-time data work?
Collect data Publish feeds Real-time apps
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But where from?
• Scheduling systems
• Vehicle telemetry
• Operations staff
• Network infrastructure
Collect data Publish feeds Real-time apps
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Data feed types
• Schedules
• Vehicle positions
• Service alerts
• Trip updates
Collect data Publish feeds Real-time apps
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Data interchange formats
• GTFS
• GTFS-realtime
• TransXChange
• SIRI
• Proprietary APIs (NextBus, REST, SOAP)
Collect data Publish feeds Real-time apps
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Collect data Publish feeds Real-time apps
GTFS: Google Transit Feed Specification
• Schedules, shapes, fares
• CSV based flat files
• Low level, but easy to generate and consume
• Created by Google and TriMet in 2005
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Collect data Publish feeds Real-time apps
TransXChange
• Schedule data format
• XML based
• UK standard sponsored by Department of Transport since 2000
• Follows CEN Transmodel, interoperable with SIRI
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• GTFS smaller, works as relational data, contains shapes
• Volumes for schedule data in Sydney:
0
225
450
675
900
GTFS TransXChange
58MB105MB
883MB
439MB
TDX Sydney Buses Sydney Trains
Collect data Publish feeds Real-time apps
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Collect data Publish feeds Real-time apps
GTFS-realtime
• Vehicle position, delays and service alerts
• Protobuf binary format
• Provides complete snapshot of the network
• Introduced by Google in August 2011
header { gtfs_realtime_version: "1.0" incrementality: FULL_DATASET timestamp: 1375286551}entity { id: "75035903_20130701_11954" vehicle { trip { trip_id: "75035903_20130701_11954" } position { latitude: -33.651478 longitude: 151.3231 bearing: 16.0 speed: 34.4 } timestamp: 1375286537 vehicle { id: "75035903_20130701_11954" label: "1721" } }}
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Collect data Publish feeds Real-time apps
SIRI: Service Interface for Real-time Information
• Complex, broad ranging XML API
• European standard developed by France, Germany, Scandinavia, UK
• Covers schedule data, real-time position, delays, service alerts, performance metrics, managing connecting services
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Proprietary APIs
• Some agencies have rolled their own API
• NextBus commercial XML based system popular in US
• Proprietary implementations limit potential for innovation
Collect data Publish feeds Real-time apps
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Collect data Publish feeds Real-time apps
Sydney Trains
PTIPS
131500 TDX
TfNSW infrastructure Application servers
Real-time apps
GTFS
GTFS-RT
GTFS
GTFS-RT
GTFS
TransXCh
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Emergence of real-time data
Source: 131500.com.au, February 2001
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NSW: PTIPS
• Real-time bus tracking system
• Grants traffic signal priority
• Provides feedback to bus operators
• Project commenced 2004
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NSW: PTIPS
Vehicles send GPS position at waypoints
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NSW: TDX
• Transport Data Exchange
• Launched 2009
• Open access to schedule data, RMS traffic alerts
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NSW: real-time bus data
• 0488TXTBUS launched 2010
• Temporary access to real-time vehicle positions in March 2011 at apps4nsw competition
• App developer hothouse held October 2012
• GTFS-realtime feeds for vehicle position, delay forecasts generated from PTIPS
• Real-time apps launched December 2012
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NSW: real-time train data
• Developer hothouse in January 2013
• GTFS daily and long term schedule data
• GTFS-realtime vehicle position, service alert feeds
• Real-time apps launched April 2013
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NSW: real-time train data
• Signalling reports track circuit occupation
• Passenger information systems correlate to runs and GPS coordinates
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NSW: real-time train data
• Vehicle positions updated every 10 seconds
• RMC staff report alerts at network, route, trip and station levels
• Delay forecasting based on waypoints and dwell times
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NSW: The future
• More PTIPS enabled bus agencies
• More rail network coverage
• Real-time ferries
• Light rail data
• Accuracy improvements
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In Australia
Sydney GTFS, TransXChange, GTFS-realtime
Brisbane GTFS, real-time in development
Canberra GTFS, real-time in development
Perth GTFS
Adelaide GTFS Melbourne No data; proprietary tram API
Hobart No data
Darwin No data
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In Australia
0
10000
20000
30000
40000
Sydney Brisbane Perth Adelaide Canberra
Bus Train Ferry Light Rail
Services scheduled to operate Wednesday 7 August 2013 Source: TfNSW, TransLink, PTAWA, Adelaide Metro, ACTION GTFS data feeds
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Around the world
• 200+ US transit agencies publishing GTFS
• 330+ GTFS feeds globally
• GTFS-realtime in US, New Zealand, France
• NextBus API popular in US, Canada
• SIRI used in Norway, UK, Germany, Sweden
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Around the world
Sources: Various agencies, gtfs-data-exchange.com, code.google.com/p/googletransitdatafeed/wiki/PublicFeedsNonGTFS
GTFSTransXChange
Proprietary API
GTFS-realtimeNextBus
SIRI
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Challenges
• Data quality and service reliability
• Data longevity
• Integrating disparate systems
• Resistance to transparency
• Engagement with developers
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Implications
• Customer experience
• Increased transit ridership
• Multi-modal integration
• Reduced technology costs
• Analytics for agencies and customers
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Customer experience
• 92% of transit users somewhat more or much more satisfied
• 91% of users reported spending less time waiting
Source: Ferris, Watkins & Borning, 2010, ‘OneBusAway: results from providing real-time arrival information for public transit’, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’10, ACM, pp. 1807-1816
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Customer experience
• Real-time information reduced perceived wait time by 20-26%
• 46% of night time transit users felt safer knowing when the service will arrive
Source: A Stated Preference Analysis of Real-Time Public Transit Stop Information, Journal of Public Transportation, Vol. 12, No. 3, 2009
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Customer experience
• Milwaukee: complaints decreased 24%
• Denver: complaints decreased 26%
• Portland: complaints decreased 53% on one route
Source: Enhancing the Rider Experience: The Impact of Real-Time Information on Transit Ridership, 2005, National Center for Transit Research, Unviersity of South Florida
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Increased transit ridership
Source: Ferris, Watkins & Borning, 2010, ‘OneBusAway: results from providing real-time arrival information for public transit’, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’10, ACM, pp. 1807-1816
Trips per week taken by real-time transit users
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Increased transit ridership
• Finland: 25% of bus passengers reported increased use because of real-time data
• Liverpool: ridership increased 5-6% on lines with real-time data
• Belgium: ridership increased 6% on lines with real-time data
Source: Enhancing the Rider Experience: The Impact of Real-Time Information on Transit Ridership, 2005, National Center for Transit Research, Unviersity of South Florida
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Multi-modal integration
• Customers can make real-time multi-modal decisions
• Decentralised demand management following service interruptions
• Adjust planned connections on multi-stage journeys
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Multi-modal integration
• 78% customers more likely to walk to a different stop than previously
• Users with access to real-time data walk 6.9 more blocks per week
• In Seattle and San Francisco, 5-10% users changed modes as a result of real-time data
Sources: Enhancing the Rider Experience: The Impact of Real-Time Information on Transit Ridership, 2005, National Center for Transit Research, Unviersity of South Florida; Ferris, Watkins & Borning, 2010, ‘OneBusAway: results from providing real-time arrival information for public transit’, Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’10, ACM, pp. 1807-1816
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Reduced technology costs
• Decreased procurement requirements for customer facing applications
• Draw on developer community resources
• Focus on core business of service delivery
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Reduced technology costs
“We’re small and we can’t provide every customised solution people ask for... it’s like having an army of
developers available to us.”
-- Tim McHugh, CTO of Portland’s TriMet
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Analytics for agencies and customers
• Network coverage
• On-time running, service reliability
• Network bottlenecks
• Travel demand patterns
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Analytics
Network coverage
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Analytics
On-time running
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Analytics
Network bottlenecks
• Analyse vehicle movements, compare against scheduled timings
• Aggregate data over short and long term
• Determine congested paths within network
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Analytics
Travel demand patterns
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Real-time data & mobileIncreasing the uptake of public transport
Rupert HansonDeveloper, AppJourney@rpy
NSW Transport Infrastructure SummitAugust 2013