A short guest lecture in the UniMelb subject 'GEOM90008 Foundations of Spatial Information', https://handbook.unimelb.edu.au/view/2014/GEOM90008.

1. UnderstandingPublicTransportNetworksusing
FreeandOpenSourceSoftware
Patrick Sunter: PhD Candidate in Architecture Building and Planning, University of
Melbourne
Presentation 12 May in GEOM90008, Foundations of Spatial Information Subject
Acknowledgment: maps produced during this presentation have been part of
collaborative work with Beyond Zero Emissions (BZE).

2. Context of my PhD
 Interpretive Action-Research Paradigm
using:-
 Co-Development of Tools
 Participant Observation
 Interviews,
 Focus Groups,
 Artifact Analysis
PhD: Focus is on exploring Free & Open Source software as a potential
means of increasing civil society organisation’s ability to engage with
Metropolitan-scale transport planning and propose alternative futures
Partner Organisations:-
* Beyond Zero Emissions (BZE)
* Public Transport Users Association (PTUA)
Network image from HiTrans Best Practice Guide (Nielsen et
al, 2005). Photo credits: www.pt4me2.org.au, Wikimedia
commons user "voland b", Flickr user "avlxyz”. Travel time
map from www.mapumental.com.

3. Selecting Tools and Goals
 What sort of technical analysis and communication
one can perform is a function of not just goals but
available expertise, tools, and data.
 With both project partners, after design and tools
review we’ve focused on GIS-based analysis of public
transport network performance (next slide)
 Work with BZE in the context of a larger project that
included aspects of 4-step model etc.

4. Target Capability: Public
Transport Network Analysis
 “Travel Time Maps” (Isochrone
maps)
 Display either:-
 Locations reachable from a
given origin in a given time;
 ‘Catchment’ to reach a given
destination
 Generally involve A* network
calculation but can be
optimised.
 Good because they indicate
overall network quality,
including interchanges
Travel time map from www.mapumental.com.

5. Data: GTFS and OpenStreetMap
 GTFS = “General Transit Feed
Specification’
 developers.google.com/transit/
 Emerged in mid 2000s from Portland
TriMet and Google’s 20% time
 Plaintext format: Entire GTFS feed of
Portland is ~169 Mb
 Live feeds available from 376+ agencies,
see:- www.gtfs-data-exchange.com/
 Now available for all AU state capitals,
not yet Melbourne (though other data
released ~Mar 2014)
 Quite strong ecosystem of tools, apps to
process & work with this format
 (* re Territories, not sure about Darwin?)
Top diagram courtesy Martin Davis via
http://lin-ear-th-inking.blogspot.com.au/2011/09/data-model-diagrams-for-gtfs.html

6. OpenTripPlanner
 Open Source software that at core is a fast Journey Planner
(algorithms for time-dependent route-finding), collaboration
between Portland’s TriMet and several researchers, + OpenPlans
organisation
 Primarily Java-based, built on other standards and software such
as Tomcat (web services), Leaflet for web application.

7. Progress with OpenTripPlanner
 With a mixture of running existing Open Source tools –
especially OpenTripPlanner and Quantum GIS, and some
scripting and GIS work, we’ve developed useful visualisations.

8. OTP Post-Processed in QGIS

9. Extending Potential to ‘Before
and After’ Analysis
 Workflow:-
 Assembling original new routes and stops as
Shapefiles
 Running scripts (using PostGIS, GDAL) to convert
these routes to a ‘topological network’ of
segments, stops, with metadata like average
speed attached.
 Converting these topological files to network
formats needed, such as GTFS, or Netview scripts
 In OpenTripPlanner’s case, building a connected
‘graph’ of street network, timetables, transfer

10. Network Topology Screenshot
https://www.dropbox.com/s/
8ss39pxjswmd721/Screenshot
%202014-05-11%2016.41.18.png

11. before & after example maps
Left: calculated accessibility from Chadstone, PTV current.
Right: same location & time, but with revised bus network and ‘best case’ service (30km/h avg
speed, 5min headways, implies significant road prioritisation measures)

12. Futher Potential of this kind of GIS-
based network analysis
 Left: Differential impact to New York Transit network after Hurricane Sandy
 Right: Mode “Accessibility gap” in Washington D.C. between car and
public transport, plus employment
McGurrin, M. F. & Greczner, D. 2011,
'Performance Metrics: Calculating
Accessibility Using Open Source
Software and Open Data', 11-0230.
http://www.theatlanticcities.com/commute/2013/01/
best-maps-weve-seen-sandys-transit-outage-new-york/
4488/

13. References & Contacts
Hillsman, E. & Barbeau, S. 2011, 'Enabling Cost-Effective Multimodal Trip Planners
through Open Transit Data', National Center for Transit Research (University of
Southern Florida), Final Report, FDOT BDK85 TWO 977-20,
http://www.locationaware.usf.edu/ongoing-research/projects/open-transit-
data/.
McGurrin, M. F. & Greczner, D. 2011, 'Performance Metrics: Calculating
Accessibility Using Open Source Software and Open Data', 11-0230.
Contacts & Project Website:
 P.sunter@pgrad.unimelb.edu.au
 http://www.appropedia.org/OSSTIP