A Web-based Accessibility Toolkit for Transportation Planners Howard Slavin Andres Rabinowicz...
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Transcript of A Web-based Accessibility Toolkit for Transportation Planners Howard Slavin Andres Rabinowicz...
A Web-based Accessibility Toolkit for Transportation Planners
Howard SlavinAndres RabinowiczGiovanni Flammia
Caliper CorporationOctober 2013
Project Overview
• FHWA-sponsored project
• Competitive response to a Broad Agency Announcement (BAA) for projects that could be transformational for transportation planning
• The BAA primary goal was the development of tools and techniques that support state and local capacity building
• A secondary goal was to develop tools and techniques that support Tribal planning, public involvement, environmental justice, and visualization in planning
The Toolkit Approach
• Provide a free web-based tool that can be used by planners and citizens
• Deploy simple, but powerful analytical tools
• Exploit advances in GIS, web software, and data availability
• Focus on the ultimate goal of transportation initiatives
• Provide a rich and valid alternative to travel demand models
Accessibility Concept
• Conventionally traffic or mobility measures are used in place of accessibility measures, but “Accessibility is the ultimate goal of most transportation and so is the best approach to use” Todd Litman 2003
• Accessibility refers to the possibilities of traveling to destination opportunities and the level of service associated with a wide range of travel options
• Can be assessed for both person travel and freight movements and for all modes, not just vehicular modes
• Increasing travel options or their quality and performance increases accessibility
The 5-Cs of Effective Accessibility Measures
• As identified by Kevin Krizek and David Levinson
• Cumulative
• Comparable
• Clear
• Comprehensive
• Calculable
Accessibility Measures
• Develop easy to understand measures• Examples of used, but complex measures
– Gravity based (Hansen)
– Utility Based •
• Instead, we use time as the measure
The Concept is Old, Not New!
• Extensive literature extolling the virtues of the approach
• Numerous, but limited examples of U.S. application
• A key aspect of British planning where it is part of the fabric of “evidence-based” planning
• Can be used to examine all parts of a study region and to compare them and perform evaluation of plan components using consistent and low cost methods
Accessibility Measure Examples
• Travel time by mode
• Average travel time by mode
• Count of jobs, people within a travel time band
• Travel time savings with and without a project or improvement
Toolkit Transportation Modes
• Car
• Transit
• Bicycle
• Pedestrian
Data Requirements
Layers• Routable Street line
layers• Transit Route Systems• Demographic data
files• Employment Data• Landmark point
databases
Potential Data Sources• TIGER Streets and
Boundaries• GTFS Transit DATA• Census DATA• MPO Planning Model
Data• Local GIS data• User-supplied data• Further needs
Data Issues
• Routable streets not freely available • Planning model road networks are
available but generally insufficient in the level of detail and may be insufficient in many other ways
• Walk networks and bike networks are generally not prepared or prepared carefully by modelers
• Transit poses particular problems despite the availability of GTFS
Using GTFS to Measure Transit Accessibility
• Acronym for General Transit Feed Specification originally called the Google Transit Feed Specification
• Common format for transit schedules and related information
• Used by transit operators to submit data to Google
• A large number of transit agencies have public feeds
GTFS Pros
• The GTFS format and the GTFS data exchange have made transit data more widely available
• The GTFS format forces transit agencies to think about geographic locations by requiring a longitude and latitude for physical stops.
More GTFS Pros, But some Cons
• Makes transit data more widely available– GTFS data is available for 595 Agencies (May
2013)• Provides geographic coordinates for
transit stops• Route geography is often poor or missing• Does not include a street reference layer• To use one, conflation is required.
Comparison of Route Alignments and GTFS Shapes at Dupont Circle
Comparison of Route Alignments and GTFS shapes in Virginia
GTFS Conflation
• Requires a geographically accurate, routable street layer
• Even with good tools, some manual fix-up is probably inevitable
• Can be difficult even for experts
Examples of Conflated Transit Routes
Computational Approach
• TransCAD accessibility computation engine
• Custom web interface
• Generation of Comparative Maps and Reports
• Several technical challenges
Computational Elements
• Modal travel time skims between all intersections
• In our North Carolina example, there are 76,000 road nodes leading to 5 Billion path calculations.
• Contour generation for time bands
• Polygon overlay to obtain demographics
Network Bands Challenges
• Efficiency building band isochrones• Accuracy
– Account for major water bodies– Account for special links such as bridges,
tunnels and ferries– Account for sparse networks (national
parks, difficult topography) and out of analysis region areas
• Efficiency overlaying isochrones with demographic layers for data reporting
Starting Point: Band Area 6.9 sq. mi)
Without Exclusion Areas (5, 10, 15 min)
With Exclusion Areas
Area Difference
From (min) To (min) Area without Exclusion (sq. mi)
Area with Exclusion (sq. mi)
0 5 13.11 10.23
5 10 55.80 46.57
10 15 115.91 102.38
Bridges and Tunnels
Bridges and Tunnels
Treatment of Long Links
MapPoint 5 min Band
MapPoint 15 min Band
MapPoint Band vs. Path Inconsistency
Planning Networks vs. Accurate GIS
Planning Network Dense GIS Layer
Triangle NC Case Study
Base Scenario 2040
Links 92,174 93,708
Nodes 76,863 77,474
Routes 195 287
Stops 4,433 4,904
Transit Pathfinding Nuances
• “Best” transit paths include walking and possibly other modes
• In dense areas, there may be many alternative transit paths and these may overlap considerably
• Transit travelers preferences for routes vary with differing willingness to walk or wait or transfer
• Habitual users know about reliability, crowding, and other route choice factors
• Simple, schedule-based routing is not sufficient for measuring accessibility
• Our accessibility calculator can handle many route choice mechanisms
Transit Bands: Matrices
Data Requirements
• Road Layer (GIS, Transportation Model Networks)
• Transit Route Systems (Transportation Models, GTFS)
• Landmark database
• TAZ or similar polygon layer with demographic attributes to report
• Water areas and major exclusion areas
Process Description
Select a starting or Destination Point
Calculate Paths
Build Contours
Aggregate data by Time band
Report data
Functional Requirements: End User
Users
Compare
Travel Modes
Scenarios
Travel Times
Share
Download
Results
Functional Requirements: Administrator
Administrator
Add New Region
Add New Transportatio
n ScenarioNew or
Updated Demographi
c
New GIS Layers
Scale website
Application Architecture
Client Side API
• HTML single-page application – no plugins
• Javascript Library – Toolkit.app– Toolkit.Share– Toolkit.Gallery– Toolkit.Compare– Toolkit.Scenarios
•
Scenario Management
– Javascript, self documentedtoolkit.scenarios[“Base"] = {…overlay_fields: [["HHs", "Households"],
["TOT_POP", "Population"], ["TOT_EMP", "Jobs"]],
sizes: [5, 10, 15], min_fields: [["TIME", "Minutes"],
["LENGTH", "Miles"]], // List of available travel modes travel_modes: [["car", "Car"],
["walking", "Walking"], ["bike", "Bike"], ["bus", "Bus"]]
…}
– Hierarchy Structure (Project Scenario = Base Scenario + Differences) toolkit.scenarios[“Project"] = extend(toolkit.scenarios[“Base”], { min_fields: [ “TIME2040” …] })
Server Side
• Thin layer– ASP.NET Web Application
• Request broker, communicates with the GIS Web Server Farm
• Caches user request and responses • GIS Web Services from TransCAD for the
Web– Parallelisms via multiple instances of TransCAD– Each Instance highly multi-threaded– Drawing Engine– Geocoding, reverse geocoding– Accessibility calculator
Application Interface
Wake Memorial and Duke Hospital by Transit
Accessibility Demographic Measures
Comparison Side by Side (Transit vs Car)
Comparison Side by Side (car vs. transit)
Overlay Comparison
10 minute access band for a route
Quarter mile around all transit stops
Quarter mile transit stop accessibilityField Value (1/4
mile)Whole
RegionPercentage
Population 277,384 1,641,484 16%
Hispanic Origin 38,514 169,924 22%
White 129,845 1,000,210 13%
Black 88,460 370,809 24%
American Indian 1,294 8,984 14%
Asian 16,751 79,224 21%
Median Income 43,027 60,785
Avg. Per Capita Income 25,795 30,379
Median Family Income 59,037 73,080
Some Conclusions
• Very detailed data is needed for meaningful resolution
• A computationally intense process is therefore required
• Local data gathering and collection will typically be needed unless NAVTEQ® or alternative routable street database is available
• Unfortunately, a fair amount of work will be involved for any application
Possible Applications
• Travel Demand Model Support• Transit Planning• Bicycle and Pedestrian Planning• Smart Growth Analysis• Environmental Justice• Public Outreach• Performance Monitoring
Transit/Non-motorized Applications
• Market Analysis• Identification of Service Geography• Point to point level-of-service (LOS)
measures• Comparisons with auto LOS• User benefit mapping• Bike Lane/ sidewalk mapping• Non-motorized transit connectivity
EJ Applications
• Title VI Calculations• Identification of Under-served Transit
Markets• Distribution of Incremental User Benefits
by Income and Ethnicity
Software Availability
• The toolkit software is available now from Caliper
• One free copy is available to any U.S. State DOT, MPO, or public transit agency
• Data, data preparation, and implementation support are not included