1. Yinhai Wang University of Washington and Harbin Institute of Technology Email: yinhai@uw.eduTel: 1-206-616-2696yinhai@uw.edu For OpenITS Symposium Oct. 26, 2014 Big Data to Big Discoveries and Big Decisions: Challenges, Opportunities, and Actions for Transportation Professionals

2. PacTrans STAR Lab Research on Big Data and E-Science Background 1 What causes congestion and how to mitigate it? How much fuel and time wasted? How much extra pollution caused by traffic jam? Image source: http://static.guim.co.uk/sys-images/Guardian/Pix/pictures/2009/6/18/1245347153341/Traffic-runs-slowly-as-he-001.jpghttp://static.guim.co.uk/sys-images/Guardian/Pix/pictures/2009/6/18/1245347153341/Traffic-runs-slowly-as-he-001.jpg

3. PacTrans STAR Lab Research on Big Data and E-Science Background 2 Picture source: http://en.wikipedia.org/wiki/I-35W_Mississippi_River_bridge How to monitor health condition of transportation infrastructure? Which infrastructure piece is the most critical for the roadway network?

4. PacTrans STAR Lab Research on Big Data and E-Science Other Sample Key Questions How to quantify the benefit from a transportation investment? How to measure vehicle miles of travel/vehicle hours of travel? Where to place electric vehicle charge stations? What is the impact of a road construction project on travel? How to estimate traffic emissions at a given location and time? What is the impact of toll on users of different income levels? Where do pedestrians go and how to improve their safety? Which route deserves top priority to build? How to improve transit services without adding new resources? How does congestion form up and how to mitigate it? How much does an incident cost and how to reduce the cost? Where do trucks go and how to guide them to the best routes? … 3

5. PacTrans STAR Lab Research on Big Data and E-Science Data Hurdles 4 To answer critical transportation questions and make informed decisions, we need

6. PacTrans STAR Lab Research on Big Data and E-Science Data Hurdles 5 Segmented by jurisdictions Lack of standardization

7. PacTrans STAR Lab Research on Big Data and E-Science Age of Big Data 6 Traffic Sensors Transportation Big Data!

8. PacTrans STAR Lab Research on Big Data and E-Science Age of Big Data 7 Image sources: http://connectedvehicle.challengepost.com/submissions/2912-dsrc-the-roadway-to-intelligent-transportation

9. PacTrans STAR Lab Research on Big Data and E-Science Opportunities with Big Data Potential for big discoveries Google’s H1N1 flu outbreak prediction in 2009 8 Image source: http://www.google.org/flutrends/us/#UShttp://www.google.org/flutrends/us/#US

10. PacTrans STAR Lab Research on Big Data and E-Science Opportunities with Big Data Rich data for big decisions Baidu’s 3.6 billion person trip prediction for China’s Spring Festival passenger travel 9 Image source: http://photocdn.sohu.com/20140127/Img394255787.jpghttp://photocdn.sohu.com/20140127/Img394255787.jpg

11. PacTrans STAR Lab Research on Big Data and E-Science Challenges to Transportation Professionals Transportation theory Mathematical equation driven Based on small and possibly biased samples Location specific Lack of field validation and application guidance Transportation professionals Mostly trained as civil engineers Weak in IT and database knowledge Typically make empirical decisions without sufficient data support Static and isolated system view Transportation infrastructure Instrumented to some extent, but no general guidance on using the sensor data Data are not efficiently shared 10

12. PacTrans STAR Lab Research on Big Data and E-Science Research Needs 11 Proposed actions to address the gaps: Actively pull what we need from the existing data resources Build our own stream of big data Design a standard mechanism for connecting transportation related datasets Develop e-science transportation methods to take advantage of the spatial and temporal datasets to support transportation analysis and decision making Build big data analytics tools to facilitate usage of big data Develop new courses in transportation curriculum to make our students ready for the big data era

13. PacTrans STAR Lab Research on Big Data and E-Science Research Needs 12 What is e-science?  Computationally intensive science that is carried out in highly distributed network environments  Application of computer technology to the undertaking of modern scientific investigation E-science of transportation:  Computationally intensive science for scientific investigations in transportation issues using immense data sets

14. PacTrans STAR Lab Research on Big Data and E-Science OpenITS Open Architecture Open Data Open Standard Open Results 13