The Tragedy of the Commons in Traffic Routing and Congestion

1. Craig Haseler Computer Systems Lab TJHSST 2008-2009 The Tragedy of the Commons in Traffic Routing and Congestion

2. Abstract • Demonstrates the effectiveness of a traffic solution in which a central computer makes decisions rather than individual drivers. • Turning over control to a computer can have significant benefits to the system as a whole, even if it causes individuals to make a slight sacrifice. OR

3. Structure: Overview Traffic Sim Stores a grid of Remembers all the RoadSquares Routes Are lists of Knows its May have a Car

4. Structure: TrafficSim • Incorporates the GUI of the simulation window • Calculates and displays statistics • Keeps the other three classes organized • GUI consists of a grid of RoadSquares • JButtons and JSliders for various functions

5. Structure: RoadSquare RoadSquare Type (Road, house, grass, etc) List of users Capacity Car (or not)

6. Structure: Car, Route • Car: stores the optimal Route from its an accessible factory it randomly chooses. • Route: Calculates and stores that optimal route as a list of RoadSquares

7. A* Search • Based on the idea of looking at distance traveled so far plus the estimated distance remaining. • Best first search, designed to eliminate looking down needless paths, or traveling in the wrong direction

13. Brute Force Method • Instead of treating each car individually, I look at every single possible combination of routes • This is very inefficient, but can produce better results • This method can also allow me to optimize based on any criterion I want, including minimum and maximum travel times, average travel times, and standard deviation.

14. Here we see a sample traffic map, with 2 houses and a factory, and several routes to work.

15. There are many possible routes one car can take. We look at all of them.

16. There are many possible routes one car can take. We look at all of them.

17. There are many possible routes one car can take. We look at all of them.

18. There are many possible routes one car can take. We look at all of them.

19. But we not only look at the route of one car, but all cars in the system.

20. And all possible routes.

21. The system finds the minimum across all routes. In this case, it is looking at average time.

22. In this example, it is not noticeably different from the standard A* method.

23. But in more complex simulations, the difference in quality of the actual results can be significant.

24. Unfortunately, with current processor speeds, this takes a long time to run. There are a lot of routes.

25. In the long term, this is not a problem, as processor speeds are continually improving.

26. The computer hardware needed to run a full scale traffic controller on this level is not available today, but that does not mean this is not a useful idea. It will be there in 10 or 20 years, when a project of this scale might become possible.

27. Bibliography • Matti Pursula, “Simulation of Traffic Systems - An Overview”, Journal of Geographic Information and Decision Analysis 18 pp. 1-8, 1999. • Jin, Itmi, &Abdulrab, “A cooperative multi-agent system simulation model for urban traffic intelligent control” ,Proceedings of the 2007 summer computer simulation conference, 2007