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Real-time data and smart phone technology increasing the uptake of public transport
 

Real-time data and smart phone technology increasing the uptake of public transport

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Rupert Hanson, Web/ IOS Developer, Triptastic delivered this presentation at the 2013 NSW State Transport Infrastructure Summit. ...

Rupert Hanson, Web/ IOS Developer, Triptastic delivered this presentation at the 2013 NSW State Transport Infrastructure Summit.
The State Transport Infrastructure Series of events represent the leading forums in Australia to assess the future plans for transport infrastructure development and financing across Australia. For more information, please visit www.statetransportevents.com.au

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    Real-time data and smart phone technology increasing the uptake of public transport Real-time data and smart phone technology increasing the uptake of public transport Presentation Transcript

    • Real-time data & mobile Increasing the uptake of public transport Rupert Hanson Developer, AppJourney @rpy NSW Transport Infrastructure Summit August 2013
    • Outline •The case for real-time data •How real-time data works •Emergence and challenges •Implications
    • 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
    • Top 4 customer information needs • Departure, arrival times • Trackwork, station closures • Delays, cancellations • Wayfinding Source: Stancombe Research & Planning, December 2011
    • 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
    • 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
    • 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
    • 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
    • How does real-time data work?
    • How does real-time data work? Collect data Publish feeds Real-time apps
    • But where from? • Scheduling systems • Vehicle telemetry • Operations staff • Network infrastructure Collect data Publish feeds Real-time apps
    • Data feed types • Schedules • Vehicle positions • Service alerts • Trip updates Collect data Publish feeds Real-time apps
    • Data interchange formats • GTFS • GTFS-realtime • TransXChange • SIRI • Proprietary APIs (NextBus, REST, SOAP) Collect data Publish feeds Real-time apps
    • 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
    • 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
    • • GTFS smaller, works as relational data, contains shapes • Volumes for schedule data in Sydney: 0 225 450 675 900 GTFS TransXChange 58MB 105MB 883MB 439MB TDX Sydney Buses Sydney Trains Collect data Publish feeds Real-time apps
    • 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" } } }
    • 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
    • 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
    • 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
    • Emergence of real-time data Source: 131500.com.au, February 2001
    • NSW: PTIPS • Real-time bus tracking system • Grants traffic signal priority • Provides feedback to bus operators • Project commenced 2004
    • NSW: PTIPS Vehicles send GPS position at waypoints
    • NSW: TDX • Transport Data Exchange • Launched 2009 • Open access to schedule data, RMS traffic alerts
    • 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
    • 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
    • NSW: real-time train data • Signalling reports track circuit occupation • Passenger information systems correlate to runs and GPS coordinates
    • 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
    • NSW: The future • More PTIPS enabled bus agencies • More rail network coverage • Real-time ferries • Light rail data • Accuracy improvements
    • 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
    • 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
    • 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
    • Around the world Sources: Various agencies, gtfs-data-exchange.com, code.google.com/p/googletransitdatafeed/wiki/PublicFeedsNonGTFS GTFS TransXChange Proprietary API GTFS-realtime NextBus SIRI
    • Challenges • Data quality and service reliability • Data longevity • Integrating disparate systems • Resistance to transparency • Engagement with developers
    • Implications • Customer experience • Increased transit ridership • Multi-modal integration • Reduced technology costs • Analytics for agencies and customers
    • 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
    • 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
    • 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
    • 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
    • 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
    • Multi-modal integration • Customers can make real- time multi-modal decisions • Decentralised demand management following service interruptions • Adjust planned connections on multi-stage journeys
    • 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
    • Reduced technology costs • Decreased procurement requirements for customer facing applications • Draw on developer community resources • Focus on core business of service delivery
    • 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
    • Analytics for agencies and customers • Network coverage • On-time running, service reliability • Network bottlenecks • Travel demand patterns
    • Analytics Network coverage
    • Analytics On-time running
    • Analytics Network bottlenecks • Analyse vehicle movements, compare against scheduled timings • Aggregate data over short and long term • Determine congested paths within network
    • Analytics Travel demand patterns
    • Real-time data & mobile Increasing the uptake of public transport Rupert Hanson Developer, AppJourney @rpy NSW Transport Infrastructure Summit August 2013