Challenges in regional transportation coordination Regional GIS - - PDF document

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Center for Urban Transportation Research | University of South Florida

Development of a Regional Public Transportation GIS Architecture and Data Model with FDOT D7

Sean J. Barbeau, Richard Pascoe, Elba Lopez

Funded by the National Center for Transit Research and the Florida Department of Transportation

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Overview

• Challenges in regional transportation

coordination

• Regional GIS Architecture and Data Model
• Demo
• Next Steps

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I ntroduction

• Regional intermodal transportation

coordination is important

– Planning, construction, and operations of roads can affect transit, and vice versa

• Coordination can increase efficiency and cost‐

effectiveness for overlapping areas of service

– E.g., Construction can be coordinated for roads and transit stops

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Challenges

• Regional transportation coordination is

difficult

– Many jurisdictions with many points of contact – Constantly changing data – Data often stored in different formats – Various levels of technical expertise at different agencies – Time consuming to manually exchange/format/analyze data

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Regional GI S Architecture and Data Model Project

• Concept:

– Create a common data format for all transit agencies in a region (i.e., data model) – Create software to automatically retrieve transit data from regional agencies and import into FDOT District 7 geodatabase (i.e., GIS architecture)

• Benefits:

– Reduce data exchange/formatting efforts – Common web‐based view of intermodal data for all agencies

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Transit Data Update Strategy

• Leverage existing General Transit Feed

Specification (GTFS) data and process

– GTFS used for Google Transit, other apps

GTFS data consists of multiple text files GTFS data powers Google Transit and other apps

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Know n Florida agencies w ith GTFS data

• HART – Tampa
• PSTA – Clearwater/St. Pete
• SCAT ‐ Sarasota
• LeeTran – Lee County
• SCAT – Space Coast
• BCT – Broward
• MDT – Miami‐Dade
• Lynx – Orlando
• RTS – Gainesville
• Citrus Connection – Lakeland
• TriRail – Pompano Beach
• Estimated cost for putting data in GTFS format using consultant is

$200‐500 per route

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Adding new fields to GTFS data

• The project working group identified additional

data that would be useful beyond existing GTFS data fields

– Bus stop amenities – Further route classifications (e.g., local vs. express) – Performance stats (e.g., boardings, alightings per stop)

• Agencies add new fields to the GTFS route.txt and

stops.txt files. e.g., for stops.txt:

stop_id bike_rack sign park_and_ ride shelter trash_can restroom boardings alightings 1645 1 1 1 35.573205 17.61923

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Regional GI S Architecture

CUTR GTFS Data Sync Desktop Application

GTFS conversion to spatial data format

FDOT D7 Infastructure

Spatial Database Web Server

. . . . Transit Agency Web Servers

HART Server PSTA Server HTTP Request GTFS file Agency Data

Internet/Intranet Users

CUTR Regional Data Visualization Web Application

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Process per Agency Schedule Update

• 1. Transit agency (estimated 30 min to 3 hrs of work):

a) Adds extra fields to their GTFS data, and b) Uploads the google_transit.zip file to the agency’s website

• 2. FDOT D7 runs the GTFS Data Sync software:

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Regional Visualization W ebsite

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Regional Visualization W ebsite

• Additional details are available when zooming in

FDOT Work Program Data HART Data

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Regional Visualization W ebsite

• Clicking on a bus stop gives additional info in popup

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Regional Visualization W ebsite

• Clicking on a route gives additional info in popup

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Regional Visualization W ebsite

• Clicking on a FDOT D7 work program gives info from D7 database

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Regional Visualization W ebsite

• Can query data via toolbar – e.g., shows all stops with shelters

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Challenges

• Varying skills levels of data analysts at agencies

1. Highly skilled 2. Data analysis is secondary duty 3. Data analysis is outsourced

• In our pilot project, HART and PSTA were able to

provide full datasets (GTFS + extras)

– PCPT didn’t yet have a bus stop inventory or GTFS dataset

• Determining when to collect data is a challenge
• Potential lack of shape info in GTFS feed

– Not required per GTFS spec – Without shape info of bus path, “connect‐the‐dots” of bus stops is shown as route shape

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Next Steps

• Production deployment of tools at FDOT D7

– Integration of tools into FDOT D7 workflow

• FDOT D7 will coordinate with regional transit

agencies so the agency uploads their new data with every schedule change

• FDOT D7 investigating sharing website publicly so

agencies can also view the data

• Source code for project is open‐source, so any

agency or vendor can use/update it:

– https://github.com/CUTR‐at‐ USF/RegionalTransitArchitecture/wiki

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Questions?

Sean J. Barbeau, Ph.D.

Principal Mobile Software Architect for R&D Center for Urban Transportation Research University of South Florida barbeau@cutr.usf.edu

Richard Pascoe

GIS Project Manager Grimail Crawford Inc. rpascoe@gc‐inc.com

Elba Lopez

Public Transit/Intermodal Administrator FDOT District 7 Elba.lopez@dot.state.fl.us