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The goal of the project is to set up an experiment that proves the effectiveness of an algorithm for collision avoidance at intersections. Three cars run on a test-bed following three different paths that all intersect in a single point. Cars are controlled by an on-board computer. Cars positions are measured by six cameras on the ceiling. Cars speed can be measured by an encoder mounted on the rear axis.
The final experiment will have an autonomous vehicle and 2 human-driven ones. The experiment will last few minutes and it will be considered successful if they vehicles will never bump into each other, given few constraints on the path following performance (e.g. the distance of the vehicle from its path cannot be greater than 30cm) that will have to be satisfied by both the autonomous and the human-driven vehicles.
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 are assumed to be enters and exits the intersection. The algorithm is robust to noise, meaning that it takes into account the existence of disturbances that cannot be controlled, given that those disturbances are limited and monotonic with respect to the position along the path y. It is assumed that the input signal (i.e. the torque applied by the motor) is also monotonic with respect to y. The main tasks of this work are thus to:
- determine and limit the disturbances which make the prediction uncertain to a degree that make the experiment unfeasible;
- identify a model of the system that is suitable for the long term prediction that the algorithm requires.
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