...
The algorithm requires the prediction of the time at which a car enters and exits the intersection. For this reason disturbances and the input signal is are assumed to be monotonic with respect to the position along the path. The main task tasks of this work is to are to:
- determine and limit the disturbances that make the prediction too much uncertain;
- identify a model of the system that is suitable for the long term prediction that the algorithm requires.
SUMMARY OF THE CURRENT STATUS
...
- Implemented a simulator in C for Linux. This is integrated with the code used on cars (ca2). It simulates the cars dynamics and the behavior of the Camera Positioning Systems (CPS). Besides being very useful to verify the system model, it makes easy to test changes to code and the controller before applying those changes to cars.
- Implemented a script to visually debug cars behavior. It works both with the simulator and test-bed experiments data.
- ca2: grouped utility functions in a separate folder that is shared with the simulator. This makes the code more modular.
- ca2: partially implemented a Kalman filter in the attempt to remove part of the measurement noise of cameras. The model must be refined for it to prove its real effectiveness.
- CPS: fixed a bug that affected the initial target dectection for cars that were not tracked by computer 0.
- CPS: now compute and send also the 2D speed of the cars. This is likely to be needed for the predictor in the future. See section #2D SPEED TESTING.
- CPS: implemented linear error correction for the computation of camera position. This visibly improves the path following of cars. See section #CAMERA MEASUREMENT ERROR CORRECTION.
...
CAMERA MEASUREMENT ERROR CORRECTION
Problem
The position of the car on the test-bed computed by the CPS is affected by a considerable error. I made some manual measurement of this error by finding the real position with the measuring tape and checking the computed position on the CPS and I found it to be be up to 25cm. Moreover, when the tracking of a car pass from a camera to another, the global coordinates "leap" because the position error in the transition point is different for the two cameras. From the experiments on the path fig8, this leap can be up to 35cm30cm. This negatively affects the ability of the car to accurately follow a path which is a crucial aspect in limiting disturbances.
I made some investigation on the trend of this error. The results are shown in error_trend.png. In the figure, "x_loc" indicate the x coordinate in pixels in the local coordinate system of the camera (i.e. the horizontal one), while "x_glob" is the x coordinate in cm in the global coordinate system. Remember that the axises of the local and the global coordinate systems are inverted. Data where gathered for two cameras.
...