Center for Urban Transportation Research | University of South
Florida Technology Quick Check Sean J. Barbeau, Ph.D.
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2 Overview Mobile Tracking Technology Monitoring Carsharing
Behavior Using Mobile Tracking Technology Cost-Effective Multimodal
Trip Planners
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3 MOBILE TRACKING TECHNOLOGY The nuts and bolts
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4 Problem Past vehicle-based GPS tracking give low- resolution
view of daily travel behavior Are these GPS fixes:
Points-of-interest? Stops in traffic? Difficult to extract info:
Distance traveled Origin-Destination pairs Misses non-vehicle
trips
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5 Innovation Mobile phone apps can capture high- definition
view of travel behavior Much easier to determine: Path, distance
traveled Origin-Destination pairs Avg. speeds Can capture
transit/bike/walk trips Sprint CDMA EV-DO Rev. A network
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6 New Problem We can record GPS fixes as frequently as once per
second and send to our server However, frequent GPS fixes come at
great cost to: battery energy data transfer over network Both
battery life and cell network data transfer are very limited
resources
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7 Sprint CDMA EV-DO Rev. A network Sprint CDMA EV-DO Rev. A
network One-day Requirement
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8 Lets decrease the GPS recalculation rate when
stationary!
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9 What is Stationary? Detecting User Movement MovingStopped d
GPS noise causes uncertainty in states Many false transitions waste
battery energy 4 second GPS sampling 5 minute GPS sampling
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10 Auto-Sleep to Reduce Energy Consumption 4 second GPS
sampling 5 minute GPS sampling US Patent 8,036,679 October 11, 2011
Dynamically change the GPS sampling interval on the phone
MovingStopped
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11 Evaluation Summary of 30 tests Approx. 88% mean accuracy in
state tracking Avg. doubling of battery life (based on TRAC-IT
tests)
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12 Monitoring Carsharing Behavior Using Mobile Tracking
Technology
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13 Case Study - Carsharing Summary Provided flip-phones for
test and control subjects with TRAC-IT mobile app Carried phone for
all trips Passive data collection Varied hourly price in peak to
shift time of rentals Provided daily summary and map of trips via
email Collected data for two 3-week data collection periods Data
instantly transmitted to us This is my trip to campus, via the Bull
Runner, to pick up the WeCar. I then drove the WeCar to the CVS on
Fowler to pick up medication and then drove to the grocery store on
Bears Ave. After shopping, I dropped the groceries off at home and
then drove back to campus to return the WeCar. I then took the Bull
Runner back home.
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14 Measuring Spatial Patterns of Activity-Travel Trip Length
(miles)SDE (square miles) User TypeAverage Carsharing Trip Non
Carsharing Average Carsharing Trip Non-Carsharing Trip Carsharing
2.68.01.70.50.20.5 Non-Carsharing4.2- 7.8- ActivitiesMean Center
SDC Minor Axis Major Axis SDE Y X Y X
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15 Lessons Learned Pluses Providing phone: Reduced need to test
on multiple platforms Povided additional privacy protection
Continuous tracking while moving without running out of battery
energy Passive collection with free-text self-validation worked
well with extended period of data collection Phone instantly
provides data to identify problems quickly Virtually limitless
length of field deployment Minuses Need to carry a second
phone/charger Providing cell phones and data plans Data
post-processing More work needed to differentiate points of
interest from stuck in traffic when passively collecting data A
current research focus
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16 COST-EFFECTIVE MULTIMODAL TRIP PLANNERS Open source, open
data
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17 Mobility and Travel Choices Mobility and travel choices mean
multiple travel options for getting around Not being car-, bus-,
bike-, or walk- dependent Being able to mix and match modes to meet
needs
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18 Why multimodal trip planners? If you want to drive, the
question is How do I get there? Road networks are dense, connected,
complete Google, Mapquest, Yahoo can easily tell you For
bike/walk/bus, the question is Can I get there (by a safe route)?
Networks are sparse, incomplete, or both For bike/walk, path is
very important
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19 Free, open-source software opentripplanner.org Initial
development led by TriMet and OpenPlans Available for anyone to
download, deploy, and modify Companies such as Conveyal can provide
installation, customization, maintenance support
21 TriMet Portland, OR Primary motivation was to merge separate
transit and bike trip planners http://rtp.trimet.org/ Launched beta
version Oct. 2011 Switched to OTP Summer 2012
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22 Pune Bus Guide, India Production deployment of
OpenTripPlanner http://punebusguide.org/guide/ Translated to
Devanagari script, including right-to- left interface
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23 Businfo, Tel Aviv, Israel Production deployment of
OpenTripPlanner http://businfo.co.il/ Translated to Hebrew Also
uses right-to-left interface Funded by regional transportation
authority after reorganization of regional transit routes
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24 goEuropa, Poznan, Poland Production deployment of
OpenTripPlanner http://iplaner.pl/iPlaner2/ Translated to Polish
Customized website interface, uses OTP to calculate routes on
server
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25 Mobile OpenTripPlanner CUTR team is working on open-source
Android app Can interface with any OTP server iPhone app source
code also available from OpenPlans
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26 Why dont we just use Google Maps? At USF, Google Maps cant
find USF building names or abbreviations Google Maps gives walking
directions on Alumni Dr. (no sidewalks) and using a cross-street
(instead of the nearby crosswalk) Google Maps OpenTripPlanner 2011
Google Map data 2011 Google Data CC-By-SA OpenStreetMap
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27 Can Add New Transit Systems HART USF Bull Runner
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28 Bike Routing Options OTP bike routing supports mix of
multiple options: Time (fastest) Hills (flatest) Safety (dedicated
bike lanes) Still open research area
30 Route with no stairs Wheelchair-accessible routing
stairs
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31 Open Data Sources - Transit General Transit Feed
Specification (GTFS) Over 200 agencies in US have transit data in
GTFS, more than 447 world-wide See GTFS Data Exchange for list of
agencies with open GTFS data: http://www.gtfs-data-exchange.com/
Challenges: Not all agencies openly share their GTFS data See
City-Go-Round for list of closed transit agencies:
http://www.citygoround.org/ http://www.citygoround.org/ Some
agencies need help organizing data
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32 Road/Bike/Walk - OpenStreetMap.org Wikipedia for geographic
data Users contribute data under Creative Commons license Edit
online, tracing GPS or donated imagery, or via code Anyone can
download and use the data Challenge Coverage is still sparse in
some areas
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33 CONCLUSIONS The takeaways
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34 Conclusions Mobile phones are new multimodal survey tool,
can provide wealth of GPS and other data Battery life, data
processing still largest challenges OpenTripPlanner is
cost-effective, customizable multimodal trip planner
Pedestrian/bike data from OpenStreetMap may be sparse in some
communities
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35 Thanks! Sean J. Barbeau, Ph.D. [email protected]
813.974.7208 Principal Mobile Software Architect for R&D Center
for Urban Transportation Research University of South Florida