InfoSphere Streams helps Stockholm build Traffic Information System

1. BLD-3661A InfoSphere Streams helps Stockholm build Traffic Information System Roger Rearrea@us.ibm.com Erling WeibustERLING@se.ibm.com Haris N. Koutsopouloshnk@infra.kth.se

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4. Agenda • The congestion challenge • Congestion control via time of day charging • Integration of multimodal traffic systems

5. Cities are now the center of urban activity In 2007, for the first time in history, the majority of the world’s population lived in cities – 3.3 billion. By 2050, city dwellers are expected to make up 70 percent of the Earth’s total population – 6.4 billion

6. Chronic traffic congestion creates significant impact to cities and citizens PRODUCTIVITY & QUALITY OF LIFE FUEL AND TIME COST Congestion cost Americans $87 Billion in 2007 - - an increase of 50% in the past decade Americans experienced travel delays of 4.2 Billion Hours in 2007 - - equivalent to a week of work per traveler ENVIRONMENTAL IMPACT ECONOMIC IMPACT Prior to the implementation of its congestion pricing program, London traffic and CO2 emissions were 20% higher Gross Regional Product is reduced by up to 10% as a result of transportation congestion

7. What is an Intelligent Transportation System (ITS)? “…..defined as the electronics, communications or information processing used singly or integrated toimprovethe efficiency or safety of surface transportation.”

8. Stockholm Congestion Tax Solution (Road User Charging) – The Background • A city of 14 town-sized islands • Too many cars, too few roads • Over 500,000 cars traveling into the city on weekdays • Population growth 20,000 per year • Average commute increasing 18% per year

9. Stockholm Congestion Tax – The Objectives • Reduce traffic by 10-15% on the main roads • Increase average speeds on streets and roads • Reduce emissions of hazardous pollutants and carbon dioxide • Inhabitants should feel that the city environment has Improved • More resources to public transport

10. Stockholm Congestion Tax Solution – The Framework • Charge for use of city center roads during peak business hours • 18 roadside control points deployed to identify and charge • Charge varied depending on time of day (i.e. higher during peak) • Transponder tags trigger automatic payment of road use fees • License plates photographed: • Identify vehicles without tags • Enforcement of non-payers • Drivers able to pay bills at local banks, over the Internet and at convenience stores

11. Stockholm Congestion Tax Solution – The Results • Traffic reduction of nearly 25% • 40,000 more transit passengers • Increased efficiency in the public bus transport operation • Taxi revenues increased 10-20% • Emission reduced by 40% in the City • City retailers not negatively affected

12. Stockholm Traffic Information v2.0 Current System: Elegant! Beneficial! Yet basically static Deliver travel information To influencebehavior in real time Travel to Arlanda Airport? 48 min by taxi, 37 min by train

13. ITS Opportunities and Challenges From data infrastructure to information infrastructure

14. KTH ITS Lab NexTMC3: Next Generation Traffic Management, Communications, and Control Center for Sustainable Urban Transport • Handle real time streaming data • Integrate data and models • Promote multimodal services • Provide a testing and demonstration ground • Provide a resource for researchers and professionals

15. KTH ITS Lab

16. Multimodal Data Streams GPS Cell-phones Public Transport Travel time data for fixed OD pairs Induction loop detector data Incidents Road closures (road work, etc) Pollution measurements Weather conditions (including road conditions) Real Time Traffic Monitoring & Information Control (Multimodal) Travel Planner Traffic Management for Sustainability and Efficiency Real Time Transformation Logic Real Time Geo Mapping Real Time Speed & Heading Estimation Real Time Aggregates & Statistics GPS Data Streams Storage adapters Interactive visualization Data Warehouse Web Server Offline statistical analysis Google Earth

17. Real Time Geo Mapping & Speed Estimation GPS probe Matching map artifact Estimated path Estimated speed & heading

18. Real Time Traffic Information

19. Status The lab started receiving data on 3rd December 2009 Total number of probes (Dec-April): ~ 40 million Number of unique vehicles reporting: 1486

20. Distribution of the time lag between measurement and receipt time

21. Probes by time of day

22. Spatial distribution of probes by time of day

23. Example: Trip Planning Travel time from Stockholm T-Centralen to Arlanda Airport 2 months of data (9th Dec 2009 - 10th Feb 2010)

24. Travel time 7.00 - 9.00 vs. 16.30 - 17.30

25. Example: Monitoring Data from February and March 2010

26. Monitoring: Impact of weather

27. Activities and Next Steps Addition of new data sources Validation of basic analytics Data collected from instrumented vehicle Speed and travel time estimation Data fusion for traffic estimation and prediction

28. Powered by InfoSphere Streams GPS Location mapping: 4 x86 blade servers 250,000 GPS probes per second Mapped to 630,000 road segments Streams delivers: Ability to fuse structured and unstructured data types Scalability for large urban transportation centers Intuitive programming model Real time delivery Powerful Analytics Millions of events per second Microsecond Latency Traditional / Non-traditional data sources

29. IBM InfoSphere Streams directions Front Office WebSphereBusinessEvents Tools Streams Studio enhancements Video/audio analytics Text/unstructured analytics Streams Processsing Language v2 Native XML support Runtime High Availability Security enhancements Unicode support Installation enhancements Adapters Cognos Now WebSphere MQ RSS feeds Mashup Hub WebSphere Business Events Oracle SQL Server Cognos InfoSphere Warehouse 8BI IBM MashupHub Millions of events per second Millisecond Latency Existing business information Data in motion All statements regarding IBM's plans, directions, and intent are subject to change or withdrawal without notice. Any reliance on these statements are at the relying party's sole risk and will not create any liability or obligation for IBM.

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