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).

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. Bring relevance to the cognitive maps of L.A. traffic
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.

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

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

24. Background Research
* Y-axis indicates the fraction of sensors indicating congestion
From

25. Background Research
* Y-axis indicates the fraction of sensors indicating congestion
From

26. Traffic
Texas Transportation Institute

27. Traffic
Texas Transportation Institute

28. Traffic
Texas Transportation Institute

29. Current Real-Time Traffic Maps

30. Current Real-Time Traffic Maps

31. Current Real-Time Traffic Maps