1. MassTRAVEL Understand the past … Predict the future …

5. PROBLEM Traffic is highly unpredictable Current interfaces only show a snapshot of real-time data, with virtually no ability predict traffic conditions at different times.

6. This …

8. Is not especially useful.

9. This … Is not especially useful. (sorry, Google)

10. Objective Develop a method that will allow us to determine with levels of confidence historical travel times Represent these data visually and relate it to a map interface Integrate this visualization in to a web application

11. Our goal: User Experience: Allow travelers to choose less congested travel times or alternate travel modes, by doing so, reduce carbon emissions Technical: to create a database to analyze average travel times, the mean and percentiles by time 5-minute time segment

12. How we did it Collected RTTM bluetooth travel data Built a front-end to display an area map with levels of confidence for all historical data Let users refine date range by type of day (weekday, weekend, holiday, etc) and specify specific routes to identify travel times/areas most important to them

13. How we did it, ctd. Front end with JavaScript using the D3 and NVD3 Libraries and Google Maps API Translated the data to prepare it for analysis Analyzed carbon emission savings from reduced congestion Further work is required to fully analyze these data and fully build this system, but it is certainly feasible.

15. Next Steps for MassTRAVEL Create a framework which will allow us to integrate travel times from other modes (transit, bicycle) in to the interface. Create a routing mechanism to link together multiple segments and estimate travel times. Create a model which will compare real-time travel times with historic data and predict short- and medium-term traffic conditions

16. MassTRAVEL Questions? and answers