Los Angeles County Traffic Analysis

1. Los Angeles County Traffic Analysis Geog 176c - Project Proposal Project Advisor: Kirk Goldsberry Group Members: Tyler Brundage Cara Moore Art Eisberg David Fleishman AJ Block

2. Motivation • L.A. has some of the worst traffic in the world • People hate traffic • Traffic creates economic loss • Time matters!

3. Traffic “Traffic jams cost the average city $900,000,000 in lost work time and wasted fuel every year.” - USA Today August 2003

4. Traffic “‘In 2003, each driver in L.A. lost an average of 93 hours due to congestion.’” - (Schrank and Lomax, 2005). http://www.econ.ucsb.edu/graduate/PhDResearch/BKGasJun29.pdf

5. Motivation • Everyone has perceptions of L.A. traffic trends • Some are more accurate than others • Cab drivers likely to have accurate views of traffic trends • Out-of-towners not likely to have an accurate view of traffic trends • Bottom line: these cognitive maps are based on perceptions

6. Objectives • We wish to improve these perceptions using empirical data to create an atlas of L.A. traffic trends for the general public

7. Objectives • Bring relevance to the cognitive maps of L.A. traffic • Supplement human perceptions of traffic trends in L.A. with empirical data

8. Objectives • Use GIS to depict LA traffic trends • Highlight problem areas and time periods • Create a straightforward representation of traffic trends for the general public

9. Methods • Use statistical software to average traffic speeds for each day of the week at specified times over a three month period, which will then be used to calculate the Travel Time Index (TTI)

10. Travel Time Index • We will be using the metric know as the Travel Time Index (TTI) upon which to base our analysis • The TTI equals the free-flow traffic velocity divided by the mean measured traffic velocity

11. Travel Time Index • In layman’s terms, the TTI indicates how much longer a trip would take than in free-flow conditions • If TTI = 1, the trip would take the same amount of time as free flow traffic • If TTI = 2, the trip would take twice as long

12. Travel Time Index • The TTI in 2003 for Los Angeles was 1.75, the worst in the country!

13. Methods • Build a geodatabase containing the major highways of L.A. county • Simplify L.A. highways into a schematic map to create maps which can be easily understood by the general public • Create a relationship class linking the TTI to sensor locations

14. Methods • Decide on class breaks for the TTI to create thematic maps of traffic trends throughout the week • Create a geovisualization of traffic trends throughout the week depicting TTI taken at various sensors throughout L.A. county • Publish webpage for general public

15. Data Sources • Traffic data from freeway sensors provided by PeMS Data (Freeway Performance Measuring System) from the Cal Berkeley Department of Electrical Engineering and Computer Science. http://pems.eecs.berkeley.edu/

16. Anticipated Problems • Gaps in data • Large amount of data- Over 17,000 text files! • Abnormal travel days and accidents

17. Anticipated Problems • Technical difficulties • Finding a balance between simplifying highways for clarity and maintaining actual geography

18. Likely Results • An accurate depiction of average L.A. traffic trends throughout the week presented in an easily accessible system understood by a wide demographic population • Create an atlas of traffic trends for the general public to influence public perceptions of traffic trends

19. Likely Results • Depict the influence time has on traffic trends • Prove the importance of considering time in travel

20. Potential Results • Change the behavior of drivers • Create a model that will support arguments for improved public transportation in areas of high congestion

21. Potential Future Projects • Develop more in-depth analysis of the affects of time/day on travel time so services such as MapQuest can give more accurate time estimations • Use developed schematic map of L.A. county freeways to display traffic in real time.

22. Background Research Average L.A. Freeway Traffic Versus Time and Day of Week - Tom Chester, retired Astrophysicist, work from 1997 • The average L.A. traffic congestion pattern is almost like clockwork, following the same pattern day after day. • Even though the average L.A. traffic congestion pattern is quite repeatable, the actual current traffic on any individual freeway is much more variable. Quoted from http://home.znet.com/schester/calculations/traffic/la/index.html

23. Background Research Average L.A. Freeway Traffic Versus Time and Day of Week - Tom Chester, retired Astrophysicist, work from 1997 • 25-32% of all sensors in L.A. county indicate bad congestion during the morning rush hour and the afternoon rush hour from Tuesday through Friday! • 5-10% of all sensors indicate bad congestion at all times of all days, except Sundays and possibly between midnight and 6 a.m. • Fridays are by far the worst traffic day for the evening commute of the weekdays • Monday afternoon rush hour congestion is always the lowest of the week. Quoted from http://home.znet.com/schester/calculations/traffic/la/index.html

24. Background Research * Y-axis indicates the fraction of sensors indicating congestion From http://home.znet.com/schester/calculations/traffic/la/index.html

25. Background Research * Y-axis indicates the fraction of sensors indicating congestion From http://home.znet.com/schester/calculations/traffic/la/index.html

26. Traffic Texas Transportation Institute http://mobility.tamu.edu/ums/

27. Traffic Texas Transportation Institute http://mobility.tamu.edu/ums/

28. Traffic Texas Transportation Institute http://mobility.tamu.edu/ums/

29. Current Real-Time Traffic Maps

30. Current Real-Time Traffic Maps

31. Current Real-Time Traffic Maps