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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

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20 OpenTripPlanner = Multimodal USFs OTP Demo for Tampa, Fl - http://opentripplanner.usf.edu Example: Bike->Bus->Bike

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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

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29 Shortest Route (with stairs) Wheelchair-accessible routing stairs

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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. barbeau@cutr.usf.edu 813.974.7208 Principal Mobile Software Architect for R&D Center for Urban Transportation Research University of South Florida