Traffic Flow Simulation for Intelligent Transportation Systems

1. Project 9TrafficFlow Simulation Team 5

2. Contents • Introduction & Motivation • Environment Modeling (Roadways) • Simulation • Statistics • Visualization • Conclusion

3. Introduction • Real-time image processing and Robotics for automotive applications • Driver assistance using Intelligent feedback on traffic conditions, cross-roads accidents, etc. • Collision warning and avoidance system • Intelligent parking assistance

4. Environment Modeling- Roadways • Preparing the map The map is stored in a text file • It is represented by: • Lines • Curves

5. Representing lines • ( x1, y1, z1 ) -> ( x2, y2, z2 ) line 125 400 10 125 375 20

6. Representing curves • ( x, y, z, r, anglestart, anglestop, direction) arc 125 300 20 75 270 180 -1

7. Sampling • Sampling distance • Line • length of line • number of sampling points • allocating the points • Curve • angle • length of arc • number of sampling points • angle of sampling points • allocating the points

8. Simulation of Car Traffic Flow • Based on physics laws (kinematics) • The control parameters: • the number of cars • the size of the histogram interval (for generating statistics) • Equations • the velocity law: • the position law:

9. The parameters of the cars • Position on the road: index and lane • Current speed and cruising speed • Maximum acceleration • Maximum deceleration • Reaction time of the driver

10. How the simulation works • The time is divided into small intervals (~ 10ms) • In one time slice a car can only: • maintain speed • accelerate • decelerate

11. The algorithm • for each car • must decelerate ? • yes: decelerate ! • no: current speed < cruising speed & can accelerate ? • yes: accelerate ! • no: maintain speed.

12. When the car must decelerate ? • We search for the cars in front of the current car • When the cars in front of the current car are close together (20m), they block the road. • We assume that in the next time-slice the cars in front will maintain speed (a reasonable assumption) • After that, we check if we maintain the speed of the current car, the time distance between cars will be decreasedbelow the time_dist (a constant value).

13. The car can accelerate? • a car can accelerate when the time distance to the car in front is less than the time_distanceor when an overtake is performed (not yet implemented) • the maximum allowed acceleration is the greatest between the maximum possible acceleration of the car and the acceleration that will not lower the time distance under time_distance

14. Acceleration and Deceleration • We update the position and the velocity:

15. Utilization of road • Dividing the road to smaller intervals • Counting the number of cars on each interval -> histogram • Drawing a chartminimal, average, maximal utilization

16. Example

17. Example

18. 3D Visualization • Actually a 2.5D representation • It can be rotated and zoomed in and out • Still to do more !!

19. 3D example

20. 3D example

21. Thank you for your attention!