2011 GIS in Transit - Cell Phones and GIS - Lessons Learned from Developing Transit Navigation Software

Patents Pending USF 2009
Sean J. Barbeau
Research Associate
Center for Urban Transportation Research (CUTR)
University of South Florida (USF)
Mark Sheppard
Travel Trainer
Hillsborough Area Regional Transit (HART)
1
Cell Phones and GIS:
Lessons Learned from Developing
Transit Navigation Software

Patents Pending USF 2009Patents Pending USF 2009
Overview
Role of travel training
Travel Assistance Device
Challenges and Solutions
Next steps
07/08/1311/17/2008
2

Project Partners
3
Sean Barbeau, Phil Winters, and Nevine Georggi,
CUTR, USF
Miguel Labrador and Rafael Perez, Computer
Science & Engineering, USF
Mark Sheppard, HART Travel Trainer
Gigi Gonzalez, Special Education Facilitator for
STAGES program at USF
Amy Datz, FDOT Project Manager
Harvey Berlin, TRB IDEA Project Manager
11/17/2008

Travel Training
4
. . . the Challenges . . . the Victories
11/17/2008

The Challenges . . .
5
Transportation is essential for independent living
Individuals with mental/cognitive disabilities
(14.2M Americans, 6.9% of pop.)¹ often have
problems with quick actions required by transit
Paratransit is expensive $27.90 per unlinked
passenger trip (bus) versus $3.20 per unlinked
passenger trip (demand responsive) and can be
restrictive to riders
Travel training helps reduce learning curve for fixed
route transit
1 - National Institute on Disability and Rehabilitation Research. “Survey of Income and Program Participation (SIPP)”, 1997.
11/17/2008

A Solution . . .TAD
6
Develop first navigation software for public
transportation using GPS-enabled mobile phones
 Alert user when to get off the bus with audio, visual, and
tactile prompts
 Target simplicity, with cognitively disabled in mind
11/17/2008

TAD Web Page – Create Trips
7
11/17/2008

 Transit Rider Selects Trip That Was Planned On Website
TAD Cell Phone Application

On Bus…
Then the user hears: “Get Ready!”

Then: “Pull the Cord Now!”

Field Tests
11
 Over 50 test runs in Tampa:
 Over 38 by testing team
 12 trips with riders with special needs
Overall, proof-of-concept was successful
Most consistent issue in tests:
 Error in bus stop locations
 Problems with close proximity of stops
11/17/2008
Alert
Timing
Number of
Occurrences
Ideal 39
Early 2
Late 6
None 4

12
Challenge: GPS is very dynamic…
11/17/2008

Challenge: Updating
Route Information
Google Transit provides
free trip planning tool to
agencies
Agency has incentive to
post schedule updates to
a webpage so Google can
update their system
TAD system can grab the
same updates and use
them!
This feature also allows
adding new agencies to
TAD with the click of a
button!
13
11/17/2008

Challenge: Bus Stop Accuracy
14
11/17/2008
• Errors in bus stop inventory location vs. true geographic location

Lessons Learned
15
First Bus Stop Detection algorithm, based on radius
surrounding final stop
11/17/2008
2nd
-to-last Stop Destination Stop
Alert Radius

Lessons Learned
16
To avoid delivering alert late, radius should be
increased
11/17/2008
2nd

Lessons Learned
17
With GPS, uncertainty of true position exists
11/17/2008
2nd
Uncertainty Radius
Possible True Position
Calculated Position

Lessons Learned
18
Problems arise when alert radius and uncertainty
overlap when bus stops are close
11/17/2008
2nd
-to-last Stop
Destination Stop

Lessons Learned
19
When alert radius is big, can cause unpredictable
results for certain route configurations
11/17/2008
2nd
-to-last StopDestination Stop
X
Early Alert

Lessons Learned
20
New Algorithm based on circles surorunding 2nd
-to-
last stop
11/17/2008
2nd
-to-last Stop
Destination Stop

Detects user passing 2nd
-to-last stop
Lessons Learned
21
11/17/2008
2nd
-to-last Stop
Destination Stop
Trigger Alert!

Lessons Learned
22
Create Bus Stop Management Tool
11/17/2008

Lessons Learned
23
Human Factors – Investigate Bluetooth Headset
 Privacy for Individual
 Easier to hear over noise on bus
11/17/2008

TAD with AVL
24
Ideas Deserving Exploratory Analysis (IDEA)
project to link TAD with AVL system
 Provides new services based on real-time bus location
11/17/2008

Next Steps
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Testing with HART in Tampa Bay area has
been successful
Expanding TAD deployment opportunities
with other transit agencies
11/17/2008

New TAD Partners
Partners will be asked to:
 Format their data into Google Transit format
(HASTUS and Trapeze both provide export tool)
 Test TAD by their travel trainer as part of daily trips
with trainees
 Correct errors in any bus stop locations through
TAD webpage
 Provide Feedback to TAD research team

New TAD Partners
CUTR will:
 Provide adequate TAD orientation/demo/training
sessions
 Help transit agency with TAD integration
 Monitor TAD and provide support during tests
 Resolve any TAD technical issues as they occur

SEAN BARBEAU
RESEARCH ASSOCIATE
(813) 974-7208
BARBEAU@CUTR.USF.EDU
MARK SHEPPARD
TRAVEL TRAINER
(813) 449-4545
SHEPPARDM@GOHART.ORG
28
Questions?
11/17/2008
Please contact Sean Barbeau if you’re interested
in TAD Deployment in your city!

2011 GIS in Transit - Cell Phones and GIS - Lessons Learned from Developing Transit Navigation Software

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