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Project 9 Traffic F low Simulation

Project 9 Traffic F low Simulation. Team 5. Content s. Introduction & Motivation Environment Modeling (Roadways) Simulation Statistics Visualization Conclusion. Introduction. Real-time image processing and Robotics for automotive applications

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Project 9 Traffic F low Simulation

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  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!

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