Center for Urban Transportation Research | University of South Florida

TDM Technology Session

Sean J. Barbeau, Ph.D.Principal Mobile Software Architect for R&D

Center for Urban Transportation ResearchUniversity of South Florida

National Center for Transit Research

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Agenda

• OneBusAway – How does real-time information affect riders?– Slide credits to Dr. Kari Watkins, Georgia Tech

• USF Maps App – Multimodal campus-focused solution

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ONEBUSAWAY

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What is OneBusAway?

• What? Suite of tools that provides real-time bus/train tracking information– Open source software– API for developers– Free to riders

• Why? Make riding public transit easier by providing good information in usable formats– Research to evaluate the impacts

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Mobile Apps!

Android Windows PhoneiPhone

Support user location, route, stop contextual /personalized informationAll OPEN-SOURCE!

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OneBusAway Multi-region

• Created centralized server directory

• Modified apps to find cities using directory

• Add a new city by adding a record in the directory

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Seattle, WA: Original deployment

New York, NY: Adapted for the MTA (Bus Time)

Washington, DC: 2016

Atlanta, GA: 2013

Tampa, FL: 2013

York, ON: 2014

Rouge Valley, OR:

2015

Where is OneBusAway?

San Joaquin, CA: In testing

San Diego, CA: 2016

Lappeenranta, Finland:

In testing

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IMPACTS OF REAL-TIMEARRIVAL INFORMATION

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Impacts

• Riders are more satisfied• Riders feel safer• Riders wait less time

• Do they take more transit trips?

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Change in Satisfaction

“I no longer sit with pitted stomach wondering where is the bus. It's less stressful simply knowing it's nine minutes away, or whatever the case.”

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Perception of Safety

• Perception of Safety– 79% no change– 18% somewhat safer– 3% much safer

• Safety correlated with gender– χ2=19.458– p-value=0.001

Men

Women

0% 20% 40% 60% 80% 100%

Somewhat Less Safe No ChangeSomewhat More Safe Much Safer

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Wait Time

• Without real time, perceived wait > actual wait• With real time, perceived wait = actual wait• Value of real time >> more frequent service

Group Real Time Schedule Difference T-stat (p-value)

Mean Typical Wait 7.54 9.86 2.32 5.50 (0.00)

Aggravation Level 3.35 3.29 -0.05 -0.24 (0.81)

Actual Wait Time 9.23 11.21 1.98 2.17 (0.03)

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Ridership - TampaBefore-After Control Group Research Design

• Motivation: HART provided USF & Georgia Tech special access to real-time data

• Recruitment: HART website/email list (Incentive of 1 day bus pass)

• Measurement: Web-based surveys

• Group Assignment: Random number generator

• Treatment: OneBusAway

Limiting the Treatment: iPhone & Android Apps

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Tampa

• Significant improvements in the waiting experience– Decreases in self-reported usual wait times– Increases in satisfaction with wait times and reliability

• Little evidence supporting a change in transit trips– Approx. 1/3 of RTI users stated they ride the bus more frequently, perhaps because

of:• Affirmation bias of respondents• Scale of measurement (trips per week)

– Only riders within sphere of transit agency

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Ridership - New York City

#1. February 2011: Brooklyn

Pilot (B63)

#2. February 2012: Staten Island Launch

#3. November 2012: Bronx

Launch

#4. October 2013: Manhattan

Launch

#5. March 2014: Queens + Brooklyn

Launch

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Ridership - New York City

• Method• Comparison of multiple panel regression techniques in a well-suited natural experiment

• ConclusionsReal-time Information as a single variable• Average increase of ~115 rides per route per weekday (median of 1.6%), similar to previous

Chicago study

Real-time Information by route size• Average increase of ~338 rides per weekday on the largest quartile of routes (median of

2.3%)

• Limitations• Short Timescale• Aggregate Analysis

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Comparison of Key Findings

New York City Tampa Atlanta

Transit Agency

Methodology Natural experiment with panel regression

Behavioral experiment with a before-after control group design

Before-after analysis of transit trips

Key Finding

Average weekday route-level increase of ~115 rides

(median of 1.6%);

Average weekday increase of ~338 rides on the largest

routes (median of 2.3%)

Little evidence supporting a change in bus trips;

Significant improvements in the waiting experience, particularly wait

times

Little evidence supporting a change in bus/train trips;

Perceived improvements in wait times and overall

satisfaction with MARTA

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USF MAPS APP

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Background

• USF students have many travel options:– Drive– USF Bull Runner– Hillsborough Area Regional Transit– Bike– Share-A-Bull Bike share– Walk

• For those unfamiliar with campus (and even those that are), the best option for each trip isn’t obvious

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Background (Con’t)

• Transit and bike share modes also have a real-time component

• Knowing where USF buildings are, and how to get from A to B, is challenging– Requires translating 3 letter abbreviation into

building name and location• How can we make getting around USF campus

easier for students, staff, and visitors?

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USF Student Green Energy Fund (SGEF)

• Initially funded two student-driven projects:– Smart Parking– “Share-A-Bull” Bike share

• USF Maps App was created to share information on all modes with students/staff/visitors

• Funding from FDOT to supervise students

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USF Maps App

DesktopMobile

http://maps.usf.edu

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Find USF buildings by name, abbreviation

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Plan trips to/from building, real-time location

Buildings

Building locations

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Routes use actual USF walk/bike infrastructure

Distance/time summary Uses crosswalk

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Layer - Bike lanes at USF

Visible as a highlighted layer, in addition to being used for routing

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Layer - Share-A-Bull– Real-time info, booking links

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Share-A-Bull – trip plans consider real-time availability

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Layer - Real-time Bull Runner positions

Bus locations

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Layer – Bike repair stations

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Layer – Enterprise CarShare

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Layer – Parking Lots

USF Parking Permits Allowed

Tap to pay for pay-by-space

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Layer – Electric Car Charging

Tap to see real-time availability

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Layer – Blue Light Emergency Phones

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Accessible via MyUSF app

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Other features

• Walking paths that avoid stairs– Useful for those with limited mobility (e.g., in wheelchairs)

• Bike paths that prefer bike lanes• Transfer from Bull Runner to HART (and PSTA) buses– Students ride free on HART

• All open-source software– Based on OpenTripPlanner.org– Can continue to add new features

• Can deploy at multiple university sites– e.g., Different USF campuses, small communities

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Open data powers these apps

• OneBusAway– General Transit Feed Specification (GTFS)– GTFS-realtime

• USF Maps App– GTFS– GTFS-realtime– General Bikeshare Feed Specification (GBFS)– OpenStreetMap data

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Set up your own version!

• Requires some technical expertise– Experience in setting up servers (Tomcat) a plus– If you want to modify things, experience with

Java/Javascript is very useful

• Most IT departments should have the required skillset to get a demo up and running

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Set up your own OneBusAway!

• You’ll need:– GTFS data– If you want real-time, one of the following:• GTFS-realtime TripUpdates feed• SIRI• Other formats - http://bit.ly/OBARealtimeFormats

• Instructions - http://bit.ly/OBAQuickStart

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Set up your own USF Maps App!

• You’ll need:– GTFS data for planning transit trips– If you want real-time bus locations:

• GTFS-realtime VehiclePositions feed– If you want bikeshare locations/trip planning:

• GBFS data– Walking/bike paths:

• OpenStreetMap data– If you want Layers:

• OpenStreetMap data– Bike lanes, bike repair, parking lots, vehicle charging stations

• Car share – update an XML file• Emergency phone locations - a config file with locations

– Building abbreviations• Update an XML file with abbreviations/locations

– Instructions - http://bit.ly/USFMapsInstructions

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Thanks!

Sean J. Barbeau, Ph.D.barbeau@cutr.usf.edu813.974.7208

OneBusAway partners = Dr. Kari Watkins (GA Tech), Dr. Candace Brakewood (CCNY), Dr. Brian Ferris, Dr. Alan Borning (UW), Sound Transit, KC Metro, Pierce Transit, MTA NYC, HART, PSTA, MARTA, ARC, independent developers, many more…

OneBusAway funding = NSF, NCTR, US DOT, NCTSPM, CUTR, GVU Center, IPAT, and more…

Current USF Maps App Developers – Joseph Fields and JB Subils

USF Maps App funding partners - USF Student Green Energy fund and Florida Department of Transportation

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References• Ferris, Brian, Kari Watkins, and Alan Borning. “OneBusAway: Results from providing real-time arrival information for public transit.”

Proceedings of Association for Computing Machinery Conference on Human Factors in Computing Systems (CHI) 2010.

• Watkins, Kari, Brian Ferris, Alan Borning, G. Scott Rutherford and David Layton. “Where Is My Bus? Impact of mobile real-time information on the perceived and actual wait time of transit riders.” Transportation Research Part A, Vol. 45, No. 8, 2011.

• Gooze, Aaron, Kari Watkins and Alan Borning. “Benefits of Real-Time Transit Information and Impacts of Data Accuracy on Rider Experience”, Transportation Research Record #2351, 2013.

• Windmiller, Sarah, Todd Hennessy and Kari Watkins, “Accessibility of Communication Technology and the Rider Experience: Case Study of St. Louis Metro” Transportation Research Record #2415, 2014.

• Barbeau, Sean, Alan Borning and Kari Watkins, “OneBusAway Multi-region – Rapidly Expanding Mobile Transit Apps to New Cities” Journal of Public Transportation, Vol. 17, No. 4, 2014.

• Brakewood, Candace, Sean Barbeau and Kari Watkins, “An experiment validating the impacts of transit information on bus riders in Tampa, Florida”, Transportation Research Part A, Vol. 69, 2014

• Brakewood, Candace, Gregory Macfarlane, and Kari Watkins, “The Impact of Real-time Information on Bus Ridership in New York City”, Transportation Research Part C, Vol. 53, 2015.

• Berrebi, S., K. Watkins, and J. Laval, “A Real-Time Bus Dispatching Policy to Minimize Headway Variance”, Transportation Research Part B, Vol. 81, pp. 377-389, 2015.